Artificial intelligence

3562: 19122:, vol. 98, no. 3 (May/June 2019), pp. 135–44. "Today's AI technologies are powerful but unreliable. Rules-based systems cannot deal with circumstances their programmers did not anticipate. Learning systems are limited by the data on which they were trained. AI failures have already led to tragedy. Advanced autopilot features in cars, although they perform well in some circumstances, have driven cars without warning into trucks, concrete barriers, and parked cars. In the wrong situation, AI systems go from supersmart to superdumb in an instant. When an enemy is trying to manipulate and hack an AI system, the risks are even greater." (p. 140.) 2719:

Google, Amazon) into voracious consumers of electric power. Projected electric consumption is so immense that there is concern that it will be fulfilled no matter the source. A ChatGPT search involves the use of 10 times the electrical energy as a Google search. The large firms are in haste to find power sources – from nuclear energy to geothermal to fusion. The tech firms argue that – in the long view – AI will be eventually kinder to the environment, but they need the energy now. AI makes the power grid more efficient and "intelligent", will assist in the growth of nuclear power, and track overall carbon emissions, according to technology firms.

64: 2475:. AI agents operate within the constraints of their programming, available computational resources, and hardware limitations. This means they are restricted to performing tasks within their defined scope and have finite memory and processing capabilities. In real-world applications, AI agents often face time constraints for decision-making and action execution. Many AI agents incorporate learning algorithms, enabling them to improve their performance over time through experience or training. Using machine learning, AI agents can adapt to new situations and optimise their behaviour for their designated tasks. 2388: 3578:, the annual number of AI-related laws passed in the 127 survey countries jumped from one passed in 2016 to 37 passed in 2022 alone. Between 2016 and 2020, more than 30 countries adopted dedicated strategies for AI. Most EU member states had released national AI strategies, as had Canada, China, India, Japan, Mauritius, the Russian Federation, Saudi Arabia, United Arab Emirates, U.S., and Vietnam. Others were in the process of elaborating their own AI strategy, including Bangladesh, Malaysia and Tunisia. The 3981: 1641: 717: 1078: 2730:, found "US power demand (is) likely to experience growth not seen in a generation…." and forecasts that, by 2030, US data centers will consume 8% of US power, as opposed to 3% in 2022, presaging growth for the electrical power generation industry by a variety of means.Data centers' need for more and more electrical power is such that they might max out the electrical grid. The Big Tech companies counter that AI can be used to maximize the utilization of the grid by all. 23766: 20964: 24782: 24349: 23203: 22200: 3477:, which allows companies to specialize them with their own data and for their own use-case. Open-weight models are useful for research and innovation but can also be misused. Since they can be fine-tuned, any built-in security measure, such as objecting to harmful requests, can be trained away until it becomes ineffective. Some researchers warn that future AI models may develop dangerous capabilities (such as the potential to drastically facilitate 22180: 24361: 23213: 23649: 1459: 23223: 18650: 799:, the agent knows exactly what the effect of any action will be. In most real-world problems, however, the agent may not be certain about the situation they are in (it is "unknown" or "unobservable") and it may not know for certain what will happen after each possible action (it is not "deterministic"). It must choose an action by making a probabilistic guess and then reassess the situation to see if the action worked. 1724: 3380:"scoffs at his peers' dystopian scenarios of supercharged misinformation and even, eventually, human extinction." In the early 2010s, experts argued that the risks are too distant in the future to warrant research or that humans will be valuable from the perspective of a superintelligent machine. However, after 2016, the study of current and future risks and possible solutions became a serious area of research. 1218: 4499: 10093: 20952: 3854:). By 2000, solutions developed by AI researchers were being widely used, although in the 1990s they were rarely described as "artificial intelligence". However, several academic researchers became concerned that AI was no longer pursuing its original goal of creating versatile, fully intelligent machines. Beginning around 2002, they founded the subfield of 4326:": "The appropriately programmed computer with the right inputs and outputs would thereby have a mind in exactly the same sense human beings have minds." Searle counters this assertion with his Chinese room argument, which attempts to show that, even if a machine perfectly simulates human behavior, there is still no reason to suppose it also has a mind. 2631:". Experts disagree about how well and under what circumstances this rationale will hold up in courts of law; relevant factors may include "the purpose and character of the use of the copyrighted work" and "the effect upon the potential market for the copyrighted work". Website owners who do not wish to have their content scraped can indicate it in a " 1563: 4140:). "Scruffies" expect that it necessarily requires solving a large number of unrelated problems. Neats defend their programs with theoretical rigor, scruffies rely mainly on incremental testing to see if they work. This issue was actively discussed in the 1970s and 1980s, but eventually was seen as irrelevant. Modern AI has elements of both. 1795:(a token being usually a word, subword, or punctuation). Throughout this pretraining, GPT models accumulate knowledge about the world and can then generate human-like text by repeatedly predicting the next token. Typically, a subsequent training phase makes the model more truthful, useful, and harmless, usually with a technique called 2715:, forecasting electric power use. This is the first IEA report to make projections for data centers and power consumption for artificial intelligence and cryptocurrency. The report states that power demand for these uses might double by 2026, with additional electric power usage equal to electricity used by the whole Japanese nation. 5261:: "Whereas for decades, computer-science fields such as natural-language processing, computer vision, and robotics used extremely different methods, now they all use a programming method called "deep learning." As a result, their code and approaches have become more similar, and their models are easier to integrate into one another." 2892:

that a black person would re-offend and would underestimate the chance that a white person would not re-offend. In 2017, several researchers showed that it was mathematically impossible for COMPAS to accommodate all possible measures of fairness when the base rates of re-offense were different for whites and blacks in the data.

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solar activity, and distinguishing between signals and instrumental effects in gravitational wave astronomy. It could also be used for activities in space such as space exploration, including analysis of data from space missions, real-time science decisions of spacecraft, space debris avoidance, and more autonomous operation.

3932:, where large companies began investing billions in AI research. According to AI Impacts, about $ 50 billion annually was invested in "AI" around 2022 in the U.S. alone and about 20% of the new U.S. Computer Science PhD graduates have specialized in "AI". About 800,000 "AI"-related U.S. job openings existed in 2022. 18728:, historian of computing, writes (in what might be called "Dyson's Law") that "Any system simple enough to be understandable will not be complicated enough to behave intelligently, while any system complicated enough to behave intelligently will be too complicated to understand." (p. 197.) Computer scientist 2861:'s new image labeling feature mistakenly identified Jacky Alcine and a friend as "gorillas" because they were black. The system was trained on a dataset that contained very few images of black people, a problem called "sample size disparity". Google "fixed" this problem by preventing the system from labelling 4596:" super-intelligent computer. Asimov's laws are often brought up during lay discussions of machine ethics; while almost all artificial intelligence researchers are familiar with Asimov's laws through popular culture, they generally consider the laws useless for many reasons, one of which is their ambiguity. 4224:, in the same sense that human beings do. This issue considers the internal experiences of the machine, rather than its external behavior. Mainstream AI research considers this issue irrelevant because it does not affect the goals of the field: to build machines that can solve problems using intelligence. 5309:

Searle presented this definition of "Strong AI" in 1999. Searle's original formulation was "The appropriately programmed computer really is a mind, in the sense that computers given the right programs can be literally said to understand and have other cognitive states." Strong AI is defined similarly

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In 2017, the European Union considered granting "electronic personhood" to some of the most capable AI systems. Similarly to the legal status of companies, it would have conferred rights but also responsibilities. Critics argued in 2018 that granting rights to AI systems would downplay the importance

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similarly describes it as "the ability to solve hard problems". The leading AI textbook defines it as the study of agents that perceive their environment and take actions that maximize their chances of achieving defined goals. These definitions view intelligence in terms of well-defined problems with

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Machines with intelligence have the potential to use their intelligence to make ethical decisions. The field of machine ethics provides machines with ethical principles and procedures for resolving ethical dilemmas. The field of machine ethics is also called computational morality, and was founded at

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estimated 47% of U.S. jobs are at "high risk" of potential automation, while an OECD report classified only 9% of U.S. jobs as "high risk". The methodology of speculating about future employment levels has been criticised as lacking evidential foundation, and for implying that technology, rather than

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with human-annotated data to improve answers for new problems and learn from corrections. A 2024 study showed that the performance of some language models for reasoning capabilities in solving math problems not included in their training data was low, even for problems with only minor deviations from

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The regulation of artificial intelligence is the development of public sector policies and laws for promoting and regulating AI; it is therefore related to the broader regulation of algorithms. The regulatory and policy landscape for AI is an emerging issue in jurisdictions globally. According to AI

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Promotion of the wellbeing of the people and communities that these technologies affect requires consideration of the social and ethical implications at all stages of AI system design, development and implementation, and collaboration between job roles such as data scientists, product managers, data

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as "cancerous", because pictures of malignancies typically include a ruler to show the scale. Another machine learning system designed to help effectively allocate medical resources was found to classify patients with asthma as being at "low risk" of dying from pneumonia. Having asthma is actually a

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hopes to "solve intelligence, and then use that to solve everything else". However, as the use of AI has become widespread, several unintended consequences and risks have been identified. In-production systems can sometimes not factor ethics and bias into their AI training processes, especially when

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allow AI programs to answer questions intelligently and make deductions about real-world facts. Formal knowledge representations are used in content-based indexing and retrieval, scene interpretation, clinical decision support, knowledge discovery (mining "interesting" and actionable inferences from

18835:' we mean realistic videos produced using artificial intelligence that actually deceive people, then they barely exist. The fakes aren't deep, and the deeps aren't fake. A.I.-generated videos are not, in general, operating in our media as counterfeited evidence. Their role better resembles that of 8712:

Horne, Robert I.; Andrzejewska, Ewa A.; Alam, Parvez; Brotzakis, Z. Faidon; Srivastava, Ankit; Aubert, Alice; Nowinska, Magdalena; Gregory, Rebecca C.; Staats, Roxine; Possenti, Andrea; Chia, Sean; Sormanni, Pietro; Ghetti, Bernardino; Caughey, Byron; Knowles, Tuomas P. J.; Vendruscolo, Michele (17

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directly or to solve as many specific problems as possible (narrow AI) in hopes these solutions will lead indirectly to the field's long-term goals. General intelligence is difficult to define and difficult to measure, and modern AI has had more verifiable successes by focusing on specific problems

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published a joint statement in November 2021 calling for a government commission to regulate AI. In 2023, OpenAI leaders published recommendations for the governance of superintelligence, which they believe may happen in less than 10 years. In 2023, the United Nations also launched an advisory body

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There are various conflicting definitions and mathematical models of fairness. These notions depend on ethical assumptions, and are influenced by beliefs about society. One broad category is distributive fairness, which focuses on the outcomes, often identifying groups and seeking to compensate for

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experts like Nicolas Firzli insist it may be too early to see the emergence of highly innovative AI-informed financial products and services: "the deployment of AI tools will simply further automatise things: destroying tens of thousands of jobs in banking, financial planning, and pension advice in

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Among the most difficult problems in knowledge representation are the breadth of commonsense knowledge (the set of atomic facts that the average person knows is enormous); and the sub-symbolic form of most commonsense knowledge (much of what people know is not represented as "facts" or "statements"

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The general problem of simulating (or creating) intelligence has been broken into subproblems. These consist of particular traits or capabilities that researchers expect an intelligent system to display. The traits described below have received the most attention and cover the scope of AI research.

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wrote in 1950 "I propose to consider the question 'can machines think'?" He advised changing the question from whether a machine "thinks", to "whether or not it is possible for machinery to show intelligent behaviour". He devised the Turing test, which measures the ability of a machine to simulate

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in the UK to discuss the near and far term risks of AI and the possibility of mandatory and voluntary regulatory frameworks. 28 countries including the United States, China, and the European Union issued a declaration at the start of the summit, calling for international co-operation to manage the

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discovered that COMPAS exhibited racial bias, despite the fact that the program was not told the races of the defendants. Although the error rate for both whites and blacks was calibrated equal at exactly 61%, the errors for each race were different—the system consistently overestimated the chance

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Artificial intelligence is used in astronomy to analyze increasing amounts of available data and applications, mainly for "classification, regression, clustering, forecasting, generation, discovery, and the development of new scientific insights" for example for discovering exoplanets, forecasting

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Instead, the United States has developed a new area of dominance that the rest of the world views with a mixture of awe, envy, and resentment: artificial intelligence... From AI models and research to cloud computing and venture capital, U.S. companies, universities, and research labs – and their

5011:, it refers to a tendency in favor or against a certain group or individual characteristic, usually in a way that is considered unfair or harmful. A statistically unbiased AI system that produces disparate outcomes for different demographic groups may thus be viewed as biased in the ethical sense. 2968:

It is impossible to be certain that a program is operating correctly if no one knows how exactly it works. There have been many cases where a machine learning program passed rigorous tests, but nevertheless learned something different than what the programmers intended. For example, a system that

2935:, in Seoul, South Korea, presented and published findings that recommend that until AI and robotics systems are demonstrated to be free of bias mistakes, they are unsafe, and the use of self-learning neural networks trained on vast, unregulated sources of flawed internet data should be curtailed. 2899:

Criticism of COMPAS highlighted that machine learning models are designed to make "predictions" that are only valid if we assume that the future will resemble the past. If they are trained on data that includes the results of racist decisions in the past, machine learning models must predict that

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Prodigious power consumption by AI is responsible for the growth of fossil fuels use, and might delay closings of obsolete, carbon-emitting coal energy facilities. There is a feverish rise in the construction of data centers throughout the US, making large technology firms (e.g., Microsoft, Meta,

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AI-powered devices and services, such as virtual assistants and IoT products, continuously collect personal information, raising concerns about intrusive data gathering and unauthorized access by third parties. The loss of privacy is further exacerbated by AI's ability to process and combine vast

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Artificial intelligent (AI) agents are software entities designed to perceive their environment, make decisions, and take actions autonomously to achieve specific goals. These agents can interact with users, their environment, or other agents. AI agents are used in various applications, including

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is the set of objects, relations, concepts, and properties used by a particular domain of knowledge. Knowledge bases need to represent things such as objects, properties, categories, and relations between objects; situations, events, states, and time; causes and effects; knowledge about knowledge

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Many of these algorithms are insufficient for solving large reasoning problems because they experience a "combinatorial explosion": They become exponentially slower as the problems grow. Even humans rarely use the step-by-step deduction that early AI research could model. They solve most of their

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released in 2024 a testing toolset called 'Inspect' for AI safety evaluations available under a MIT open-source licence which is freely available on GitHub and can be improved with third-party packages. It can be used to evaluate AI models in a range of areas including core knowledge, ability to

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or render certain groups invisible. Procedural fairness focuses on the decision process rather than the outcome. The most relevant notions of fairness may depend on the context, notably the type of AI application and the stakeholders. The subjectivity in the notions of bias and fairness makes it

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since the 1960s that human expertise depends on unconscious instinct rather than conscious symbol manipulation, and on having a "feel" for the situation, rather than explicit symbolic knowledge. Although his arguments had been ridiculed and ignored when they were first presented, eventually, AI

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In the past, technology has tended to increase rather than reduce total employment, but economists acknowledge that "we're in uncharted territory" with AI. A survey of economists showed disagreement about whether the increasing use of robots and AI will cause a substantial increase in long-term

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A program can make biased decisions even if the data does not explicitly mention a problematic feature (such as "race" or "gender"). The feature will correlate with other features (like "address", "shopping history" or "first name"), and the program will make the same decisions based on these

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where they received multiple versions of the same misinformation. This convinced many users that the misinformation was true, and ultimately undermined trust in institutions, the media and the government. The AI program had correctly learned to maximize its goal, but the result was harmful to

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In agriculture, AI has helped farmers identify areas that need irrigation, fertilization, pesticide treatments or increasing yield. Agronomists use AI to conduct research and development. AI has been used to predict the ripening time for crops such as tomatoes, monitor soil moisture, operate

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has guided AI research for most of its history. The unprecedented success of statistical machine learning in the 2010s eclipsed all other approaches (so much so that some sources, especially in the business world, use the term "artificial intelligence" to mean "machine learning with neural

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agreed, writing, "within a generation ... the problem of creating 'artificial intelligence' will substantially be solved". They had, however, underestimated the difficulty of the problem. In 1974, both the U.S. and British governments cut off exploratory research in response to the

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did not sign the joint statement, emphasising that in 95% of all cases, AI research is about making "human lives longer and healthier and easier." While the tools that are now being used to improve lives can also be used by bad actors, "they can also be used against the bad actors."

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that the human mind is an information processing system and that thinking is a form of computing. Computationalism argues that the relationship between mind and body is similar or identical to the relationship between software and hardware and thus may be a solution to the

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disclosed a declaration signed by 31 nations to set guardrails for the military use of AI. The commitments include using legal reviews to ensure the compliance of military AI with international laws, and being cautious and transparent in the development of this technology.

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management are growing. AI has been used to investigate if and how people evacuated in large scale and small scale evacuations using historical data from GPS, videos or social media. Further, AI can provide real time information on the real time evacuation conditions.

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Another definition has been adopted by Google, a major practitioner in the field of AI. This definition stipulates the ability of systems to synthesize information as the manifestation of intelligence, similar to the way it is defined in biological intelligence.

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Some authors have suggested in practice, that the definition of AI is vague and difficult to define, with contention as to whether classical algorithms should be categorised as AI, with many companies during the early 2020s AI boom using the term as a marketing

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in 2016 included an explicit statement that this right exists. Industry experts noted that this is an unsolved problem with no solution in sight. Regulators argued that nevertheless the harm is real: if the problem has no solution, the tools should not be used.

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severe risk factor, but since the patients having asthma would usually get much more medical care, they were relatively unlikely to die according to the training data. The correlation between asthma and low risk of dying from pneumonia was real, but misleading.

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add that "he additional project of making a machine conscious in exactly the way humans are is not one that we are equipped to take on." However, the question has become central to the philosophy of mind. It is also typically the central question at issue in

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People who have been harmed by an algorithm's decision have a right to an explanation. Doctors, for example, are expected to clearly and completely explain to their colleagues the reasoning behind any decision they make. Early drafts of the European Union's

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identified two problems in understanding the mind, which he named the "hard" and "easy" problems of consciousness. The easy problem is understanding how the brain processes signals, makes plans and controls behavior. The hard problem is explaining how this

4071:") simulated the high-level conscious reasoning that people use when they solve puzzles, express legal reasoning and do mathematics. They were highly successful at "intelligent" tasks such as algebra or IQ tests. In the 1960s, Newell and Simon proposed the 3070:

A lethal autonomous weapon is a machine that locates, selects and engages human targets without human supervision. Widely available AI tools can be used by bad actors to develop inexpensive autonomous weapons and, if produced at scale, they are potentially

1756:, and others. The reason that deep learning performs so well in so many applications is not known as of 2023. The sudden success of deep learning in 2012–2015 did not occur because of some new discovery or theoretical breakthrough (deep neural networks and 11971: 9321:

Pinaya, Walter H. L.; Graham, Mark S.; Kerfoot, Eric; Tudosiu, Petru-Daniel; Dafflon, Jessica; Fernandez, Virginia; Sanchez, Pedro; Wolleb, Julia; da Costa, Pedro F.; Patel, Ashay (2023). "Generative AI for Medical Imaging: extending the MONAI Framework".

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began to create images, audio, video and text that are indistinguishable from real photographs, recordings, films, or human writing. It is possible for bad actors to use this technology to create massive amounts of misinformation or propaganda. AI pioneer

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and neural networks, that are tolerant of imprecision, uncertainty, partial truth and approximation. Soft computing was introduced in the late 1980s and most successful AI programs in the 21st century are examples of soft computing with neural networks.

3248:". This scenario has been common in science fiction, when a computer or robot suddenly develops a human-like "self-awareness" (or "sentience" or "consciousness") and becomes a malevolent character. These sci-fi scenarios are misleading in several ways. 2483:

There are also thousands of successful AI applications used to solve specific problems for specific industries or institutions. In a 2017 survey, one in five companies reported having incorporated "AI" in some offerings or processes. A few examples are

3527:, the Montreal Declaration for Responsible AI, and the IEEE's Ethics of Autonomous Systems initiative, among others; however, these principles do not go without their criticisms, especially regards to the people chosen contributes to these frameworks. 1473:

Many problems in AI (including in reasoning, planning, learning, perception, and robotics) require the agent to operate with incomplete or uncertain information. AI researchers have devised a number of tools to solve these problems using methods from

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imaging as a key technique in fabrication. It has been suggested that AI can overcome discrepancies in funding allocated to different fields of research. New AI tools can deepen the understanding of biomedically relevant pathways. For example,

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well-defined solutions, where both the difficulty of the problem and the performance of the program are direct measures of the "intelligence" of the machine—and no other philosophical discussion is required, or may not even be possible.

5274:: "After a half-decade of quiet breakthroughs in artificial intelligence, 2015 has been a landmark year. Computers are smarter and learning faster than ever", and noted that the number of software projects that use machine learning at 3618:

poll, 35% of Americans thought it "very important", and an additional 41% thought it "somewhat important", for the federal government to regulate AI, versus 13% responding "not very important" and 8% responding "not at all important".

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affiliates in allied countries – appear to have an enormous lead in both developing cutting-edge AI and commercializing it. The value of U.S. venture capital investments in AI start-ups exceeds that of the rest of the world combined.

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reported that big AI companies have begun negotiations with the US nuclear power providers to provide electricity to the data centers. In March 2024 Amazon purchased a Pennsylvania nuclear-powered data center for $ 650 Million (US).

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Artificial Intelligence projects can have their ethical permissibility tested while designing, developing, and implementing an AI system. An AI framework such as the Care and Act Framework containing the SUM values—developed by the

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in a biological brain. It is trained to recognise patterns; once trained, it can recognise those patterns in fresh data. There is an input, at least one hidden layer of nodes and an output. Each node applies a function and once the

2092:. In 2023, it was reported that AI-guided drug discovery helped find a class of antibiotics capable of killing two different types of drug-resistant bacteria. In 2024, researchers used machine learning to accelerate the search for 4338:(has the ability to feel), and if so, to what degree. But if there is a significant chance that a given machine can feel and suffer, then it may be entitled to certain rights or welfare protection measures, similarly to animals. 17372: 2920:

difficult for companies to operationalize them. Having access to sensitive attributes such as race or gender is also considered by many AI ethicists to be necessary in order to compensate for biases, but it may conflict with

592:—the ability to complete any task performable by a human on an at least equal level—is among the field's long-term goals. To reach these goals, AI researchers have adapted and integrated a wide range of techniques, including 12053: 19112:

fails at tasks that require real humanlike reasoning or an understanding of the physical and social world.... ChatGPT seemed unable to reason logically and tried to rely on its vast database of... facts derived from online

557:). However, many AI applications are not perceived as AI: "A lot of cutting edge AI has filtered into general applications, often without being called AI because once something becomes useful enough and common enough it's 3892:

and the misuse of technology were catapulted into center stage at machine learning conferences, publications vastly increased, funding became available, and many researchers re-focussed their careers on these issues. The

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competition, winning against four of the world's best Gran Turismo drivers using deep reinforcement learning. In 2024, Google DeepMind introduced SIMA, a type of AI capable of autonomously playing nine previously unseen

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Several approaches aim to address the transparency problem. SHAP enables to visualise the contribution of each feature to the output. LIME can locally approximate a model's outputs with a simpler, interpretable model.

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Finance is one of the fastest growing sectors where applied AI tools are being deployed: from retail online banking to investment advice and insurance, where automated "robot advisers" have been in use for some years.

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is difficult to explain. For example, it is easy to imagine a color-blind person who has learned to identify which objects in their field of view are red, but it is not clear what would be required for the person to

16176: 12009: 11979: 3226:, about whether tasks that can be done by computers actually should be done by them, given the difference between computers and humans, and between quantitative calculation and qualitative, value-based judgement. 3271:

gives the example of household robot that tries to find a way to kill its owner to prevent it from being unplugged, reasoning that "you can't fetch the coffee if you're dead." In order to be safe for humanity, a

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social policy, creates unemployment, as opposed to redundancies. In April 2023, it was reported that 70% of the jobs for Chinese video game illustrators had been eliminated by generative artificial intelligence.

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Daniel Crevier wrote that "time has proven the accuracy and perceptiveness of some of Dreyfus's comments. Had he formulated them less aggressively, constructive actions they suggested might have been taken much

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and theoretical artificial intelligence. It can refer to anything that directs its behavior to accomplish goals, such as a person, an animal, a corporation, a nation, or in the case of AI, a computer program.

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There many other ways that AI is expected to help bad actors, some of which can not be foreseen. For example, machine-learning AI is able to design tens of thousands of toxic molecules in a matter of hours.

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stated in 2015 that "the worry that AI could do to white-collar jobs what steam power did to blue-collar ones during the Industrial Revolution" is "worth taking seriously". Jobs at extreme risk range from

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began to dominate industry benchmarks in 2012 and was adopted throughout the field. For many specific tasks, other methods were abandoned. Deep learning's success was based on both hardware improvements

17001: 3885:). Deep learning's success led to an enormous increase in interest and funding in AI. The amount of machine learning research (measured by total publications) increased by 50% in the years 2015–2019. 14906: 16151: 2353:, communications, sensors, integration and interoperability. Research is targeting intelligence collection and analysis, logistics, cyber operations, information operations, and semiautonomous and 780:, the agent has preferences—there are some situations it would prefer to be in, and some situations it is trying to avoid. The decision-making agent assigns a number to each situation (called the " 16542: 15841: 4361:

Progress in AI increased interest in the topic. Proponents of AI welfare and rights often argue that AI sentience, if it emerges, would be particularly easy to deny. They warn that this may be a

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survey, attitudes towards AI varied greatly by country; 78% of Chinese citizens, but only 35% of Americans, agreed that "products and services using AI have more benefits than drawbacks". A 2023

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Artificial intelligence was founded as an academic discipline in 1956, and the field went through multiple cycles of optimism, followed by periods of disappointment and loss of funding, known as

3414:, who coined the term, argues that developing friendly AI should be a higher research priority: it may require a large investment and it must be completed before AI becomes an existential risk. 24399: 15415: 4263:

or why it should feel like anything at all, assuming we are right in thinking that it truly does feel like something (Dennett's consciousness illusionism says this is an illusion). While human

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had been described by many people, as far back as the 1950s) but because of two factors: the incredible increase in computer power (including the hundred-fold increase in speed by switching to

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AI developers argue that this is the only way to deliver valuable applications. and have developed several techniques that attempt to preserve privacy while still obtaining the data, such as

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and others developed methods that handled incomplete and uncertain information by making reasonable guesses rather than precise logic. But the most important development was the revival of "

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agree with Turing that intelligence must be defined in terms of external behavior, not internal structure. However, they are critical that the test requires the machine to imitate humans. "

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The simplest AI applications can be divided into two types: classifiers (e.g., "if shiny then diamond"), on one hand, and controllers (e.g., "if diamond then pick up"), on the other hand.

9385: 3664:, which suggested that a machine, by shuffling symbols as simple as "0" and "1", could simulate any conceivable form of mathematical reasoning. This, along with concurrent discoveries in 9640:

Gomaa, Islam; Adelzadeh, Masoud; Gwynne, Steven; Spencer, Bruce; Ko, Yoon; Bénichou, Noureddine; Ma, Chunyun; Elsagan, Nour; Duong, Dana; Zalok, Ehab; Kinateder, Max (1 November 2021).

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Kaplan, Andreas; Haenlein, Michael (2019). "Siri, Siri, in my hand: Who's the fairest in the land? On the interpretations, illustrations, and implications of artificial intelligence".

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like plans, goals, beliefs, and known facts. In the 1980s, some researchers began to doubt that this approach would be able to imitate all the processes of human cognition, especially

16446: 14498: 19239: 17547: 11076: 9183: 4358:, and that legislation should focus on user needs rather than speculative futuristic scenarios. They also noted that robots lacked the autonomy to take part to society on their own. 3838:

AI gradually restored its reputation in the late 1990s and early 21st century by exploiting formal mathematical methods and by finding specific solutions to specific problems. This "

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announced his resignation from Google in order to be able to "freely speak out about the risks of AI" without "considering how this impacts Google." He notably mentioned risks of an

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are programmed to speak conversationally or even to banter humorously; it makes them appear more sensitive to the emotional dynamics of human interaction, or to otherwise facilitate

12057: 10732: 3768:, a form of AI program that simulated the knowledge and analytical skills of human experts. By 1985, the market for AI had reached over a billion dollars. At the same time, Japan's 3318:

The opinions amongst experts and industry insiders are mixed, with sizable fractions both concerned and unconcerned by risk from eventual superintelligent AI. Personalities such as

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However, this tends to give naïve users an unrealistic conception of the intelligence of existing computer agents. Moderate successes related to affective computing include textual

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come from acting in the world and experiencing the consequences. Artificial intelligences – disembodied, strangers to blood, sweat, and tears – have no occasion for that." (p. 30.)

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in 1956. The attendees became the leaders of AI research in the 1960s. They and their students produced programs that the press described as "astonishing": computers were learning

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methods can allow developers to see what different layers of a deep network for computer vision have learned, and produce output that can suggest what the network is learning. For

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was launched in June 2020, stating a need for AI to be developed in accordance with human rights and democratic values, to ensure public confidence and trust in the technology.

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uses several layers of neurons between the network's inputs and outputs. The multiple layers can progressively extract higher-level features from the raw input. For example, in

24785: 15721: 9434: 2904:, some of these "recommendations" will likely be racist. Thus, machine learning is not well suited to help make decisions in areas where there is hope that the future will be 752:(things that humans assume are true until they are told differently and will remain true even when other facts are changing); and many other aspects and domains of knowledge. 18742:

Gertner, Jon. (2023) "Knowledge's Moment of Truth: Can the online encyclopedia help teach A.I. chatbots to get their facts right — without destroying itself in the process?"

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amounts of data, potentially leading to a surveillance society where individual activities are constantly monitored and analyzed without adequate safeguards or transparency.

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as a "gorilla". Eight years later, in 2023, Google Photos still could not identify a gorilla, and neither could similar products from Apple, Facebook, Microsoft and Amazon.

15691: 9967: 16622: 16168: 10112: 2928: 12124: 12001: 24392: 22074: 18023: 11537: 9942: 5053:) argues that machine learning "is fundamentally the wrong tool for a lot of domains, where you're trying to design interventions and mechanisms that change the world." 3973:

human conversation. Since we can only observe the behavior of the machine, it does not matter if it is "actually" thinking or literally has a "mind". Turing notes that

1403:

is a single, axiom-free rule of inference, in which a problem is solved by proving a contradiction from premises that include the negation of the problem to be solved.

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Economists have frequently highlighted the risks of redundancies from AI, and speculated about unemployment if there is no adequate social policy for full employment.

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Generative AI is often trained on unlicensed copyrighted works, including in domains such as images or computer code; the output is then used under the rationale of "

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crosses its specified threshold, the data is transmitted to the next layer. A network is typically called a deep neural network if it has at least 2 hidden layers.

16216: 15482:"Knowledge's Moment of Truth – Can the online encyclopedia help teach A.I. chatbots to get their facts right — without destroying itself in the process? + comment" 15461: 14954: 14106: 9590: 2214:, a particularly challenging real-time strategy game that involves incomplete knowledge of what happens on the map. In 2021, an AI agent competed in a PlayStation 18324: 15316: 12759: 792:

of all possible outcomes of the action, weighted by the probability that the outcome will occur. It can then choose the action with the maximum expected utility.

17184: 8797: 16376: 15299: 9468: 3676:, led researchers to consider the possibility of building an "electronic brain". They developed several areas of research that would become part of AI, such as 3287:

argues that AI does not require a robot body or physical control to pose an existential risk. The essential parts of civilization are not physical. Things like

2100:(the protein that characterises Parkinson's disease). They were able to speed up the initial screening process ten-fold and reduce the cost by a thousand-fold. 1375:

Given a problem and a set of premises, problem-solving reduces to searching for a proof tree whose root node is labelled by a solution of the problem and whose

24385: 23386: 12864: 11492: 17564: 16993: 3473:, have been made open-weight, meaning that their architecture and trained parameters (the "weights") are publicly available. Open-weight models can be freely 2319:

Some models have been developed to solve challenging problems and reach good results in benchmark tests, others to serve as educational tools in mathematics.

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Alternatively, dedicated models for mathematic problem solving with higher precision for the outcome including proof of theorems have been developed such as

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said, of his work on neural networks in the 1990s, "our labeled datasets were thousands of times too small. our computers were millions of times too slow."

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features as it would on "race" or "gender". Moritz Hardt said "the most robust fact in this research area is that fairness through blindness doesn't work."

25439: 25434: 18524: 5580: 4923: 4307:. This philosophical position was inspired by the work of AI researchers and cognitive scientists in the 1960s and was originally proposed by philosophers 2779:

content, and, to keep them watching, the AI recommended more of it. Users also tended to watch more content on the same subject, so the AI led people into

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Asada, M.; Hosoda, K.; Kuniyoshi, Y.; Ishiguro, H.; Inui, T.; Yoshikawa, Y.; Ogino, M.; Yoshida, C. (2009). "Cognitive developmental robotics: a survey".

3001:

provides a large number of outputs in addition to the target classification. These other outputs can help developers deduce what the network has learned.

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Bias and unfairness may go undetected because the developers are overwhelmingly white and male: among AI engineers, about 4% are black and 20% are women.

2504:

agricultural robots, conduct predictive analytics, classify livestock pig call emotions, automate greenhouses, detect diseases and pests, and save water.

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and speaking English. Artificial intelligence laboratories were set up at a number of British and U.S. universities in the latter 1950s and early 1960s.

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The various subfields of AI research are centered around particular goals and the use of particular tools. The traditional goals of AI research include

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argue continuing research into symbolic AI will still be necessary to attain general intelligence, in part because sub-symbolic AI is a move away from

15407: 8684: 3357:, and stressed that in order to avoid the worst outcomes, establishing safety guidelines will require cooperation among those competing in use of AI. 802:

In some problems, the agent's preferences may be uncertain, especially if there are other agents or humans involved. These can be learned (e.g., with

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that "Mitigating the risk of extinction from AI should be a global priority alongside other societal-scale risks such as pandemics and nuclear war".

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eruption data starts from a random guess but then successfully converges on an accurate clustering of the two physically distinct modes of eruption.

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https://videovoice.org/ai-in-finance-innovation-entrepreneurship-vs-over-regulation-with-the-eus-artificial-intelligence-act-wont-work-as-intended/

3481:) and that once released on the Internet, they can't be deleted everywhere if needed. They recommend pre-release audits and cost-benefit analyses. 2702: 15946: 23259: 20125: 19087: 18266: 17434: 16752: 15560: 15217: 14872: 14515: 9043: 4939: 3595:

to provide recommendations on AI governance; the body comprises technology company executives, governments officials and academics. In 2024, the

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However, the symbolic approach failed on many tasks that humans solve easily, such as learning, recognizing an object or commonsense reasoning.

1146:

AI can solve many problems by intelligently searching through many possible solutions. There are two very different kinds of search used in AI:

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Compared with symbolic logic, formal Bayesian inference is computationally expensive. For inference to be tractable, most observations must be

4082:

is the discovery that high-level "intelligent" tasks were easy for AI, but low level "instinctive" tasks were extremely difficult. Philosopher

1765: 25426: 24756: 24736: 16438: 15477: 15051: 14479: 12031: 3579: 17539: 16664: 15962:

Iphofen, Ron; Kritikos, Mihalis (3 January 2019). "Regulating artificial intelligence and robotics: ethics by design in a digital society".

14490: 12842: 655:"). The widespread use of AI in the 21st century exposed several unintended consequences and harms in the present and raised concerns about 19451: 19230: 18344: 17455: 14925:(1988). Continuous valued neural networks with two hidden layers are sufficient (Report). Department of Computer Science, Tufts University. 14466:

Bertini, M; Del Bimbo, A; Torniai, C (2006). "Automatic annotation and semantic retrieval of video sequences using multimedia ontologies".

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Probabilistic algorithms can also be used for filtering, prediction, smoothing, and finding explanations for streams of data, thus helping

18246: 18073: 3656:

The study of mechanical or "formal" reasoning began with philosophers and mathematicians in antiquity. The study of logic led directly to

1787:(LLMs) that generate text based on the semantic relationships between words in sentences. Text-based GPT models are pretrained on a large 884:, the agent is rewarded for good responses and punished for bad ones. The agent learns to choose responses that are classified as "good". 16908: 16522: 15783: 12685: 3175: 847:

describes the rational behavior of multiple interacting agents and is used in AI programs that make decisions that involve other agents.

210: 175: 17843: 6381: 4110:: it can be difficult or impossible to understand why a modern statistical AI program made a particular decision. The emerging field of 3255:" to be an existential risk. Modern AI programs are given specific goals and use learning and intelligence to achieve them. Philosopher 3219:

to fast food cooks, while job demand is likely to increase for care-related professions ranging from personal healthcare to the clergy.

1737:, lower layers may identify edges, while higher layers may identify the concepts relevant to a human such as digits, letters, or faces. 858:

is the study of programs that can improve their performance on a given task automatically. It has been a part of AI from the beginning.

810:

can be used to weigh the value of exploratory or experimental actions. The space of possible future actions and situations is typically

796: 22246: 18981:, "Artificial Confidence: Even the newest, buzziest systems of artificial general intelligence are stymmied by the same old problems", 16639: 15803:; Kingsbury, B. (2012). "Deep Neural Networks for Acoustic Modeling in Speech Recognition – The shared views of four research groups". 13719: 13408: 9530: 9083:

Srivastava, Saurabh (29 February 2024). "Functional Benchmarks for Robust Evaluation of Reasoning Performance, and the Reasoning Gap".

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between networked combat vehicles involving manned and unmanned teams. AI was incorporated into military operations in Iraq and Syria.

1796: 18291: 17136: 4635:. Dick considers the idea that our understanding of human subjectivity is altered by technology created with artificial intelligence. 4480: 2969:

could identify skin diseases better than medical professionals was found to actually have a strong tendency to classify images with a

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Arntz, Melanie; Gregory, Terry; Zierahn, Ulrich (2016), "The risk of automation for jobs in OECD countries: A comparative analysis",

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Several works use AI to force us to confront the fundamental question of what makes us human, showing us artificial beings that have

3376:

also argued that "it's a mistake to fall for the doomsday hype on AI—and that regulators who do will only benefit vested interests."

2143: 1839: 17414: 15368:

Frey, Carl Benedikt; Osborne, Michael A (1 January 2017). "The future of employment: How susceptible are jobs to computerisation?".

5365: 2573:

Sensitive user data collected may include online activity records, geolocation data, video or audio. For example, in order to build

1740:

Deep learning has profoundly improved the performance of programs in many important subfields of artificial intelligence, including

688:

Early researchers developed algorithms that imitated step-by-step reasoning that humans use when they solve puzzles or make logical

24542: 21256: 20181: 18591: 18377: 17946: 16686: 15900: 15711: 14998: 13303: 10773: 9255: 3075:. Even when used in conventional warfare, it is unlikely that they will be unable to reliably choose targets and could potentially 274: 252: 35: 18424: 14421: 13838: 13800: 11447: 11182: 2312:

When natural language is used to describe mathematical problems, converters transform such prompts into a formal language such as

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expressed concern about AI enabling "authoritarian leaders to manipulate their electorates" on a large scale, among other risks.

2357:. AI technologies enable coordination of sensors and effectors, threat detection and identification, marking of enemy positions, 2267: 2223:

video games by observing screen output, as well as executing short, specific tasks in response to natural language instructions.

1901: 1800: 1007:(or "GPT") language models began to generate coherent text, and by 2023, these models were able to get human-level scores on the 188: 24998: 17817: 16976: 15165: 15129: 13910: 13442: 11878: 3222:

From the early days of the development of artificial intelligence, there have been arguments, for example, those put forward by

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theory and economics. Precise mathematical tools have been developed that analyze how an agent can make choices and plan, using

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Galvan, Jill (1 January 1997). "Entering the Posthuman Collective in Philip K. Dick's "Do Androids Dream of Electric Sheep?"".

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Expectation–maximization, one of the most popular algorithms in machine learning, allows clustering in the presence of unknown

3410:

Friendly AI are machines that have been designed from the beginning to minimize risks and to make choices that benefit humans.

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Machine learning algorithms require large amounts of data. The techniques used to acquire this data have raised concerns about

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to choose the weights that will get the right output for each input during training. The most common training technique is the

1566: 1525: 112: 18622: 18015: 10876: 10029: 25454: 25449: 24816: 24334: 24094: 22981: 20581: 20092: 20052: 19383: 18825:, "Your Lying Eyes: People now use A.I. to generate fake videos indistinguishable from real ones. How much does it matter?", 18135: 18050: 17989: 17803: 17520: 17324: 17300: 16970: 16932: 16474: 16324: 16116: 16058: 15764: 15549: 15280: 15194: 15159: 15123: 15099: 14987: 14852: 14807: 14782: 14407: 14272: 14080: 13946: 13904: 13832: 13794: 9934: 9617: 8999:

Wurman, P. R.; Barrett, S.; Kawamoto, K. (2022). "Outracing champion Gran Turismo drivers with deep reinforcement learning".

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Thought-capable artificial beings have appeared as storytelling devices since antiquity, and have been a persistent theme in

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Researchers in the 1960s and the 1970s were convinced that their methods would eventually succeed in creating a machine with

3548: 2549: 2331: 2047: 1939: 664: 629: 407: 333: 287: 242: 237: 19128:"Comparing the expert survey and citation impact journal ranking methods: Example from the field of Artificial Intelligence" 18056: 17770: 17264: 16728: 16064: 11473: 4014:

McCarthy defines intelligence as "the computational part of the ability to achieve goals in the world". Another AI founder,

2064:, medical professionals are ethically compelled to use AI, if applications can more accurately diagnose and treat patients. 1225:

for 3 different starting points; two parameters (represented by the plan coordinates) are adjusted in order to minimize the

24015: 23473: 22832: 22105: 21251: 21043: 21038: 21033: 18685: 17049: 12180: 8490: 4848: 3685: 3535: 3524: 1885: 1855: 996: 648: 19055: 18969:

Leffer, Lauren, "The Risks of Trusting AI: We must avoid humanizing machine-learning models used in scientific research",

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Interpretable Machine Learning for the Analysis, Design, Assessment, and Informed Decision Making for Civil Infrastructure

9182:

M. Nicolas, J. Firzli: Pensions Age/European Pensions magazine, "Artificial Intelligence: Ask the Industry" May June 2024

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suggests that an AI could use language to convince people to believe anything, even to take actions that are destructive.

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It has been argued AI will become so powerful that humanity may irreversibly lose control of it. This could, as physicist

2522:

AI has potential benefits and potential risks. AI may be able to advance science and find solutions for serious problems:

466:

and intelligence to take actions that maximize their chances of achieving defined goals. Such machines may be called AIs.

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is a hypothetical agent that would possess intelligence far surpassing that of the brightest and most gifted human mind.

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wrote that experts have pivoted "from the question of 'what they know' to the question of 'what they're doing with it'."

386: 358: 353: 247: 18480: 15453: 14931: 14103: 13468: 9582: 9173:

Matthew Finio & Amanda Downie: IBM Think 2024 Primer, "What is Artificial Intelligence (AI) in Finance?" 8 Dec. 2023

8588:"The future of personalized cardiovascular medicine demands 3D and 4D printing, stem cells, and artificial intelligence" 3561: 2818:

if they learn from biased data. The developers may not be aware that the bias exists. Bias can be introduced by the way

25556: 25496: 25469: 24724: 23687: 22498: 21289: 20153: 19774: 19352: 18316: 17234:"On the impact of robotics in behavioral and cognitive sciences: from insect navigation to human cognitive development" 17169: 16784: 16772: 16736: 15075: 14005: 13983: 13758: 13728: 8698: 7932: 5169: 4493: 4289: 4234: 4072: 4008: 3644: 3361: 3264: 3014: 2979: 2585:

to listen to and transcribe some of them. Opinions about this widespread surveillance range from those who see it as a

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with specific solutions. The experimental sub-field of artificial general intelligence studies this area exclusively.

2643:) sued AI companies for using their work to train generative AI. Another discussed approach is to envision a separate 25421: 25381: 25306: 24461: 23138: 22966: 22503: 22018: 21645: 21452: 21308: 20986: 20764: 20759: 20712: 20393: 19000: 16368: 15291: 14058: 14035: 13872: 12108: 11518: 10618: 9539: 9512: 6337: 6055: 3038: 2957:

Many AI systems are so complex that their designers cannot explain how they reach their decisions. Particularly with

2517: 1971: 1529: 1436:

assigns a "degree of truth" between 0 and 1. It can therefore handle propositions that are vague and partially true.

1246:

is a type of local search that optimizes a set of numerical parameters by incrementally adjusting them to minimize a

1166: 773: 573: 318: 264: 230: 97: 18799:, vol. 329, no. 4 (November 2023), pp. 81–82. "This murder mystery competition has revealed that although NLP ( 17917: 15614:

Goodman, Bryce; Flaxman, Seth (2017). "EU regulations on algorithmic decision-making and a 'right to explanation'".

14749: 13389: 1601:") is labeled with a certain predefined class. All the observations combined with their class labels are known as a 1169:

algorithms search through trees of goals and subgoals, attempting to find a path to a target goal, a process called

25588: 25491: 25409: 25404: 24471: 23226: 22327: 21973: 20087: 19444: 18725: 16614: 15653: 15145: 14740: 11396:"Hugging Face CEO says he's focused on building a 'sustainable model' for the $ 4.5 billion open-source-AI startup" 4475: 4064: 3397: 2822:

is selected and by the way a model is deployed. If a biased algorithm is used to make decisions that can seriously

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An ontology represents knowledge as a set of concepts within a domain and the relationships between those concepts.

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E. McGaughey, 'Will Robots Automate Your Job Away? Full Employment, Basic Income, and Economic Democracy' (2022),

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Warren, D.H.; Pereira, L.M.; Pereira, F. (1977). "Prolog-the language and its implementation compared with Lisp".

3842:" and "formal" focus allowed researchers to produce verifiable results and collaborate with other fields (such as 3434: 2649:

system of protection for creations generated by AI to ensure fair attribution and compensation for human authors.

814:

large, so the agents must take actions and evaluate situations while being uncertain of what the outcome will be.

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user engagement (that is, the only goal was to keep people watching). The AI learned that users tended to choose

2270:. Therefore, they need not only a large database of mathematical problems to learn from but also methods such as 1123: 589: 82: 17976:. Affective Computing: A Review. Lecture Notes in Computer Science. Vol. 3784. Springer. pp. 981–995. 17397: 14675:

Cambria, Erik; White, Bebo (May 2014). "Jumping NLP Curves: A Review of Natural Language Processing Research ".

14626: 24532: 23456: 23434: 23245: 22905: 22867: 22531: 22239: 22160: 22100: 21698: 20944: 20111: 19961: 19894: 19078:, "In Front of Their Faces: Does facial-recognition technology lead police to ignore contradictory evidence?", 18574: 18500:"What is 'fuzzy logic'? Are there computers that are inherently fuzzy and do not apply the usual binary logic?" 11395: 9105: 8516: 7467: 6427: 5584: 1100: 803: 744: 498: 16923:

Merkle, Daniel; Middendorf, Martin (2013). "Swarm Intelligence". In Burke, Edmund K.; Kendall, Graham (eds.).

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Ciresan, D.; Meier, U.; Schmidhuber, J. (2012). "Multi-column deep neural networks for image classification".

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and is capable of generating high-quality human-like text. These programs, and others, inspired an aggressive

3263:

goal to a sufficiently powerful AI, it may choose to destroy humanity to achieve it (he used the example of a

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is an interdisciplinary umbrella that comprises systems that recognize, interpret, process, or simulate human

25618: 25551: 25541: 25366: 25361: 24010: 23653: 23619: 23047: 23024: 22754: 22744: 21693: 21382: 21157: 20082: 19909: 19561: 19468: 18125: 16269:"Using Commercial Knowledge Bases for Clinical Decision Support: Opportunities, Hurdles, and Recommendations" 8249: 6714: 5119:

Daniel Crevier wrote, "the conference is generally recognized as the official birthdate of the new science."

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statistical disparities. Representational fairness tries to ensure that AI systems do not reinforce negative

1889: 1467: 1111: 899: 18793:, which has stumped humans for decades, reveals the limitations of natural-language-processing algorithms", 16192: 3614:/Ipsos poll found that 61% of Americans agree, and 22% disagree, that AI poses risks to humanity. In a 2023 25416: 25376: 24865: 24763: 24623: 24552: 24286: 23128: 22716: 22624: 22536: 22312: 22297: 22135: 21532: 21489: 21442: 21437: 20634: 20627: 19727: 19501: 18765: 14611: 13952: 4728: 4659: 4615: 4542: 4285: 4176: 3984:

The Turing test can provide some evidence of intelligence, but it penalizes non-human intelligent behavior.

2109: 1704: 1016: 1000: 24794: 15842:"Bill Gates on dangers of artificial intelligence: 'I don't understand why some people are not concerned'" 10006: 9344: 3811:

rejected "representation" in general and focussed directly on engineering machines that move and survive.

3208:

Unlike previous waves of automation, many middle-class jobs may be eliminated by artificial intelligence;

2784:

society. After the U.S. election in 2016, major technology companies took steps to mitigate the problem .

2399:

gained widespread prominence. GenAI is AI capable of generating text, images, videos, or other data using

1906:

AI and machine learning technology is used in most of the essential applications of the 2020s, including:

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strengthen the connection between neurons that are "close" to each other—this is especially important in

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Jordan, M. I.; Mitchell, T. M. (16 July 2015). "Machine learning: Trends, perspectives, and prospects".

15799:

Hinton, G.; Deng, L.; Yu, D.; Dahl, G.; Mohamed, A.; Jaitly, N.; Senior, A.; Vanhoucke, V.; Nguyen, P.;

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The Latest Answers to the Oldest Questions: A Philosophical Adventure with the World's Greatest Thinkers

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agreed, writing that "Artificial intelligence is not, by definition, simulation of human intelligence".

3999:

texts," they wrote, "do not define the goal of their field as making 'machines that fly so exactly like

3091:

and others disagreed. By 2015, over fifty countries were reported to be researching battlefield robots.

825:

that describes the probability that a particular action will change the state in a particular way and a

25516: 25486: 24875: 24324: 23720: 23624: 23560: 23188: 22837: 21810: 21745: 21346: 21116: 21106: 19826: 19816: 16340: 15938: 15089: 13001: 11099: 8147: 7246: 5181: 4722: 4710: 4707: – List of definitions of terms and concepts commonly used in the study of artificial intelligence 4677: 4402: 4133: 4087: 4056:. Critics argue that these questions may have to be revisited by future generations of AI researchers. 3754: 3603:". It was adopted by the European Union, the United States, the United Kingdom, and other signatories. 3179: 2278: 2019: 1695:

feed the output signal back into the input, which allows short-term memories of previous input events.

1688: 1261:, which aims to iteratively improve a set of candidate solutions by "mutating" and "recombining" them, 893: 870: 92: 16756: 14519: 14332:

Berdahl, Carl Thomas; Baker, Lawrence; Mann, Sean; Osoba, Osonde; Girosi, Federico (7 February 2023).

12002:"Countries agree to safe and responsible development of frontier AI in landmark Bletchley Declaration" 9680: 9604:

Sun, Yuran; Zhao, Xilei; Lovreglio, Ruggiero; Kuligowski, Erica (1 January 2024), Naser, M. Z. (ed.),

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This list of intelligent traits is based on the topics covered by the major AI textbooks, including:

4471: 4418: 4137: 3851: 3769: 3155: 3099: 2764: 2488:, medical diagnosis, military logistics, applications that predict the result of judicial decisions, 2404: 2139: 1991: 1761: 1629: 1237: 1054: 969: 777: 605: 597: 170: 19127: 14551: 12739: 8824: 8715:"Discovery of potent inhibitors of α-synuclein aggregation using structure-based iterative learning" 4185:

AI researchers are divided as to whether to pursue the goals of artificial general intelligence and

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would never be useful for solving real-world tasks, thus discrediting the approach altogether. The "

3722:

predicted, "machines will be capable, within twenty years, of doing any work a man can do". In 1967

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they receive. This could cause for researchers who hope to use them to do things such as analyze

16823: 16572: 15382: 14622: 8167: 7973: 7899: 7874: 7688: 7606: 7270: 6447: 5924: 5572: 4467: 4203: 4075:: "A physical symbol system has the necessary and sufficient means of general intelligent action." 3870: 3552: 3245: 3034: 2948: 2035: 1861: 1692: 1605:. When a new observation is received, that observation is classified based on previous experience. 1586: 1541: 1487: 1305: 1258: 1012: 980:

believed that it was meaning and not grammar that was the key to understanding languages, and that

903: 807: 724: 708:

problems using fast, intuitive judgments. Accurate and efficient reasoning is an unsolved problem.

569: 526: 294: 18694:, "Why Are There Still So Many Jobs? The History and Future of Workplace Automation" (2015) 29(3) 17283:

Pennachin, C.; Goertzel, B. (2007). "Contemporary Approaches to Artificial General Intelligence".

15541: 12760:"AI is closer than ever to passing the Turing test for 'intelligence'. What happens when it does?" 11234: 11209:"Juergen Schmidhuber, Renowned 'Father Of Modern AI,' Says His Life's Work Won't Lead To Dystopia" 10850: 9435:"Misinformation, mistakes and the Pope in a puffer: what rapidly evolving AI can – and can't – do" 3311:; they exist because there are stories that billions of people believe. The current prevalence of 2747: 651:, and by the early 2020s hundreds of billions of dollars were being invested in AI (known as the " 25506: 25481: 25316: 25311: 24910: 23961: 23956: 23572: 23545: 23374: 23118: 23052: 22759: 22426: 22155: 22140: 21793: 21788: 21688: 21337: 21137: 20902: 20649: 20644: 20617: 20552: 20506: 20501: 20436: 20329: 19759: 19368: 18803:) models are capable of incredible feats, their abilities are very much limited by the amount of 18709: 17584: 17141: 16670: 16411: 16314: 16221: 14977: 12832: 11794: 7981: 7626: 6467: 6208: 6204: 5868: 5792: 3401: 2921: 2250: 2096:

drug treatments. Their aim was to identify compounds that block the clumping, or aggregation, of

1967: 1869: 1491: 1281: 1240:

to find a solution to a problem. It begins with some form of guess and refines it incrementally.

1030:

is the ability to use input from sensors (such as cameras, microphones, wireless signals, active

818: 24377: 18739:

are, at their core, dead simple stupid. They work, but they work by brute force." (p. 198.)

18360: 17451: 17060:

Neumann, Bernd; Möller, Ralf (January 2008). "On scene interpretation with description logics".

16848:

McGarry, Ken (1 December 2005). "A survey of interestingness measures for knowledge discovery".

16558:

Lungarella, M.; Metta, G.; Pfeifer, R.; Sandini, G. (2003). "Developmental robotics: a survey".

16499:

The Narrative and the Algorithm: Genres of Credit Reporting from the Nineteenth Century to Today

5290:

wrote in 1983: "Simply put, there is wide disagreement in the field about what AI is all about."

4855:

wrote a report on unsupervised probabilistic machine learning: "An Inductive Inference Machine".

4466:

argues that "artificial intelligence is the next stage in evolution", an idea first proposed by

3835:

can recognize handwritten digits, the first of many successful applications of neural networks.

1368:, in which nodes are labelled by sentences, and children nodes are connected to parent nodes by 784:") that measures how much the agent prefers it. For each possible action, it can calculate the " 25536: 25521: 25233: 25123: 24978: 24925: 24850: 24481: 24155: 23680: 23582: 23577: 23550: 23468: 23183: 23014: 22895: 22662: 22652: 22647: 22115: 21875: 21594: 21589: 21206: 21076: 21023: 20857: 20847: 20265: 20191: 20148: 20011: 20006: 19914: 19329: 16818: 16567: 16497: 15583: 15377: 14546: 13493: 12467: 8798:"Twenty years on from Deep Blue vs Kasparov: how a chess match started the big data revolution" 8025: 7370: 6638: 5245: 4589: 4410: 3974: 3964: 3601:

Framework Convention on Artificial Intelligence and Human Rights, Democracy and the Rule of Law

3591: 2313: 2256: 2199: 2117:

programs have been used since the 1950s to demonstrate and test AI's most advanced techniques.

2093: 1864:(GPUs) that were increasingly designed with AI-specific enhancements and used with specialized 1696: 1680:

algorithm. Neural networks learn to model complex relationships between inputs and outputs and

1625: 1621: 942: 881: 865:

analyzes a stream of data and finds patterns and makes predictions without any other guidance.

660: 165: 19308: 16904: 16878: 15775: 15023: 14334:"Strategies to Improve the Impact of Artificial Intelligence on Health Equity: Scoping Review" 12677: 11641:"A critical perspective on guidelines for responsible and trustworthy artificial intelligence" 10728: 6401:

Sensorless or "conformant" planning, contingent planning, replanning (a.k.a online planning):

5143:

wrote "for the next 20 years the field would be dominated by these people and their students."

4926:(1961). Deep or recurrent networks that learned (or used gradient descent) were developed by: 4452:

that are more capable and powerful than either. This idea, called transhumanism, has roots in

4128:"Neats" hope that intelligent behavior is described using simple, elegant principles (such as 3780:

market in 1987, AI once again fell into disrepute, and a second, longer-lasting winter began.

2900:

racist decisions will be made in the future. If an application then uses these predictions as

1084:, a robot head which was made in the 1990s; a machine that can recognize and simulate emotions 25608: 25391: 25331: 25223: 25028: 24436: 24266: 24120: 23730: 23508: 23369: 23268: 23153: 23123: 23113: 23009: 22923: 22799: 22739: 22706: 22696: 22586: 22551: 22541: 22478: 22347: 22322: 22317: 22282: 22145: 22130: 22095: 21783: 21683: 21551: 21241: 21226: 20707: 20702: 20654: 20622: 20612: 20571: 20351: 20228: 20134: 19996: 19986: 19924: 19874: 19848: 19754: 19749: 19636: 19611: 19486: 18804: 18529: 17314: 14797: 13363: 13334: 12837: 11157:"Rise of artificial intelligence is inevitable but should not be feared, 'father of AI' says" 11100:"Canadian artificial intelligence leader Geoffrey Hinton piles on fears of computer takeover" 9469:"How a fake image of a Pentagon explosion shared on Twitter caused a real dip on Wall Street" 6569: 6287: 5928: 5029: 4906:

Some form of deep neural networks (without a specific learning algorithm) were described by:

4304: 4268: 3661: 3623: 3491: 2215: 2183: 2179: 946: 862: 757: 728: 22013: 17875:

Smoliar, Stephen W.; Zhang, HongJiang (1994). "Content based video indexing and retrieval".

17682: 17632: 16925:

Search Methodologies: Introductory Tutorials in Optimization and Decision Support Techniques

15533: 4680: – Ability of a computer to learn a specific task from data or experimental observation 4350:

are also sometimes proposed as a practical way to integrate autonomous agents into society.

4098:

reasoning can make many of the same inscrutable mistakes that human intuition does, such as

2965:

relationships between inputs and outputs. But some popular explainability techniques exist.

1450:. Other specialized versions of logic have been developed to describe many complex domains. 25603: 25561: 25546: 25511: 25501: 25346: 25103: 24802: 24527: 24216: 24140: 23905: 23865: 23715: 23555: 23518: 23498: 23414: 23295: 22913: 22885: 22857: 22852: 22681: 22657: 22609: 22594: 22576: 22566: 22561: 22523: 22473: 22468: 22385: 22331: 22165: 22120: 21566: 21511: 21357: 21352: 20687: 20682: 20557: 20441: 20346: 20319: 20201: 20031: 19764: 19408: 19182: 19023: 18922: 18863: 18614: 18410: 18352: 16096: 16008: 15874: 15812: 15561:"10 years later, deep learning 'revolution' rages on, say AI pioneers Hinton, LeCun and Li" 15064:

The Master Algorithm: How the Quest for the Ultimate Learning Machine Will Remake Our World

13778: 12969: 11954:

Milmo, Dan (3 November 2023). "Hope or Horror? The great AI debate dividing its pioneers".

10491: 9008: 8897: 8640: 7108: 4951: 4671: 4323: 4079: 3921: 3889: 2958: 2952: 2609: 2464: 2354: 2191: 1983: 1915: 1877: 1784: 1753: 1427: 1262: 1184: 1126:

should be able to solve a wide variety of problems with breadth and versatility similar to

1050: 822: 107: 18440:

Weng, J.; McClelland; Pentland, A.; Sporns, O.; Stockman, I.; Sur, M.; Thelen, E. (2001).

14531: 14164:

Anderson, Susan Leigh (2008). "Asimov's "three laws of robotics" and machine metaethics".

14140: 14098: 11972:"The Bletchley Declaration by Countries Attending the AI Safety Summit, 1–2 November 2023" 8: 25526: 25476: 25386: 25336: 25248: 25188: 25148: 24950: 24930: 24890: 24742: 24365: 24307: 24170: 23870: 23710: 23612: 23587: 23424: 23399: 23317: 23178: 23103: 23019: 23004: 22769: 22556: 22513: 22508: 22405: 22395: 22367: 21740: 21718: 21467: 21462: 21420: 21372: 21185: 21091: 20749: 20431: 20324: 20299: 20284: 20213: 19711: 19541: 19104: 18983: 18971: 18795: 18770: 18001:"'Godfather of AI' Geoffrey Hinton quits Google and warns over dangers of misinformation" 17497: 16880:

Will Robots Automate Your Job Away? Full Employment, Basic Income, and Economic Democracy

16709: 16412:

Law Library of Congress (U.S.). Global Legal Research Directorate, issuing body. (2019).

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However, technologies cannot improve exponentially indefinitely, and typically follow an

4123: 3804: 3736: 3732: 3368: 3103: 3022: 2993:("Explainable Artificial Intelligence") program in 2014 to try and solve these problems. 2776: 2545: 2472: 2415: 2350: 2271: 2232: 1979: 1963: 1835: 1681: 1594: 1552: 1513: 1443: 1439: 1423: 1411: 1407: 1357: 1349: 1309: 1301: 1277: 1170: 1092: 1088: 938: 911: 874: 866: 833:

associates a decision with each possible state. The policy could be calculated (e.g., by

811: 781: 689: 647:

outperformed previous AI techniques. This growth accelerated further after 2017 with the

613: 565: 514: 259: 31: 25259: 19186: 19027: 18926: 18867: 18655: 18618: 18356: 17334: 16615:"The case against killer robots, from a guy actually working on artificial intelligence" 16100: 16012: 15816: 15115:

Mind over Machine: The Power of Human Intuition and Expertise in the Era of the Computer

14470:. 14th ACM international conference on Multimedia. Santa Barbara: ACM. pp. 679–682. 14368: 14333: 10769: 9827: 9106:"AI achieves silver-medal standard solving International Mathematical Olympiad problems" 9012: 8901: 8739: 8714: 8644: 4790:

This list of tools is based on the topics covered by the major AI textbooks, including:

3079:. In 2014, 30 nations (including China) supported a ban on autonomous weapons under the 2349:

Various countries are deploying AI military applications. The main applications enhance

2121:

became the first computer chess-playing system to beat a reigning world chess champion,

2060:

has the potential to increase patient care and quality of life. Through the lens of the

1628:

is reportedly the "most widely used learner" at Google, due in part to its scalability.

1195:" or "rules of thumb" can help prioritize choices that are more likely to reach a goal. 25153: 25128: 25068: 24993: 24920: 24870: 24276: 24251: 24241: 24206: 24150: 24130: 24077: 24050: 23988: 23900: 23834: 23735: 23629: 23342: 23327: 23300: 23143: 23042: 22918: 22875: 22784: 22726: 22711: 22701: 22493: 22292: 22125: 21703: 21132: 21101: 21071: 20897: 20852: 20739: 20562: 20383: 20218: 20208: 20064: 19939: 19789: 19460: 19413: 19403: 19373: 19206: 19047: 18946: 18897: 18884: 18851: 18566: 18472: 18415: 18196: 18183: 18158: 17892: 17762: 17723: 17670: 17644: 17620: 17364: 17256: 17077: 17041: 16892: 16865: 16836: 16585: 16514: 16293: 16268: 16130: 16032: 15987: 15892: 15828: 15641: 15623: 15486: 15440: 14858: 14830: 14692: 14397: 14381: 14321: 14227: 14181: 13993: 13821: 13783: 11719: 11676: 11621: 9349: 9323: 9212: 9110: 9084: 8661: 8628: 8560: 8535: 7977: 7920: 7782: 7463: 7200: 7116: 7112: 7072: 6094: 5490: 5407: 5025: 4689: 4674: – Process of solving new problems based on the solutions of similar past problems 4524: 4299: 4221: 4209: 4159: 3960: 3792: 3696: 3669: 3201: 3143: 3119: 2998: 2760: 2574: 2468: 2358: 2076: 1919: 1745: 1657: 1613: 1548: 1537: 1517: 1400: 1321: 1313: 1269: 1198: 1176: 1162: 1147: 1127: 1107: 1058: 1046: 1027: 977: 961: 950: 930: 926: 593: 534: 482: 470: 459: 309: 17: 16144:"Regulate AI? GOP much more skeptical than Dems that government can do it right: poll" 14560: 8885: 4537:, where a human creation becomes a threat to its masters. This includes such works as 3916:. The program was taught only the rules of the game and developed strategy by itself. 2266:

are working with probabilistic models, which can produce wrong answers in the form of

1593:

to determine the closest match. They can be fine-tuned based on chosen examples using

25178: 25073: 25033: 24708: 24683: 24501: 24353: 24317: 24246: 24175: 24062: 23848: 23750: 23725: 23673: 23451: 23404: 23163: 23093: 23072: 23034: 22842: 22809: 22789: 22488: 22400: 22274: 22191: 22179: 21983: 21635: 21506: 21499: 21271: 21246: 21236: 21190: 21175: 21086: 20956: 20729: 20586: 20376: 20341: 20235: 20174: 20001: 19858: 19476: 19232:

White Paper: On Artificial Intelligence – A European approach to excellence and trust

19198: 19051: 19039: 18996: 18938: 18901: 18889: 18789: 18570: 18558: 18464: 18235:"Amazon reportedly employs thousands of people to listen to your Alexa conversations" 18200: 18188: 18131: 18114: 18046: 17985: 17809: 17799: 17793: 17727: 17715: 17695: 17662: 17526: 17516: 17506: 17368: 17320: 17296: 17146: 17089: 16966: 16959: 16928: 16900: 16896: 16518: 16470: 16425: 16417: 16320: 16298: 16134: 16122: 16112: 16054: 16024: 15979: 15849: 15832: 15760: 15707: 15545: 15395: 15276: 15262: 15245: 15190: 15155: 15149: 15119: 15113: 15095: 15071: 14983: 14848: 14813: 14803: 14778: 14696: 14598: 14413: 14403: 14385: 14373: 14355: 14278: 14268: 14076: 14054: 14031: 14001: 13979: 13942: 13900: 13894: 13868: 13854: 13828: 13790: 13754: 13734: 13724: 13710: 13416: 12104: 11723: 11711: 11696:"Ethical issues in the development of artificial intelligence: recognizing the risks" 11680: 11668: 11660: 11625: 9861: 9700: 9661: 9613: 9535: 9508: 9442: 9263: 9228: 9024: 8974: 8921: 8913: 8833: 8771: 8744: 8666: 8609: 8565: 7928: 7832: 7580: 7408: 7366: 7158: 7104: 6664: 6188: 6138: 6043: 5411: 5399: 5311: 5213: 5152: 5136: 5120: 5004: 4935: 4884:

uses a Bayesian network with over 300 million edges to learn which ads to serve.

4621: 4391: 4225: 4186: 4111: 3988: 3956: 3773: 3700: 3677: 3635:, 16 global AI tech companies agreed to safety commitments on the development of AI. 3596: 3430: 3411: 3335: 3284: 3273: 3268: 3223: 3159: 2868: 2772: 2605: 2456: 2089: 1975: 1951: 1827: 1562: 1483: 1447: 1415: 1396: 1392: 1165:

searches through a tree of possible states to try to find a goal state. For example,

1096: 907: 885: 749: 542: 474: 447: 87: 39: 20827: 19571: 19010:

Mnih, Volodymyr; Kavukcuoglu, Koray; Silver, David; et al. (26 February 2015).

18476: 17896: 17766: 17674: 17471: 17081: 16869: 16840: 16605: 15991: 15183: 14325: 14231: 9581:

Ransbotham, Sam; Kiron, David; Gerbert, Philipp; Reeves, Martin (6 September 2017).

2088:(2021) demonstrated the ability to approximate, in hours rather than months, the 3D 1414:. However, backward reasoning with Horn clauses, which underpins computation in the 25218: 25168: 25113: 25048: 25038: 24968: 24945: 24730: 24703: 24603: 24451: 24302: 24180: 24165: 24040: 24032: 23951: 23910: 23895: 23843: 23745: 23597: 23513: 23429: 23409: 23364: 23359: 22996: 22880: 22847: 22642: 22571: 22460: 22446: 22441: 22390: 22377: 22302: 22255: 21936: 21926: 21733: 21527: 21477: 21472: 21415: 21403: 21281: 21261: 21231: 21221: 20927: 20882: 20862: 20398: 20388: 20371: 19843: 19836: 19801: 19769: 19591: 19190: 19142: 19031: 18950: 18930: 18879: 18871: 18822: 18808: 18733: 18603: 18550: 18456: 18178: 18170: 18106: 17977: 17884: 17754: 17707: 17654: 17624: 17612: 17510: 17354: 17346: 17288: 17260: 17248: 17121: 17105: 17069: 17045: 17033: 16884: 16857: 16828: 16744: 16589: 16577: 16506: 16349: 16288: 16280: 16104: 16016: 15971: 15820: 15645: 15633: 15391: 15387: 15257: 14946: 14862: 14840: 14770: 14684: 14663: 14652:

Buttazzo, G. (July 2001). "Artificial consciousness: Utopia or real possibility?".

14588: 14556: 14494: 14363: 14345: 14311: 14303: 14219: 14185: 14173: 14046: 11703: 11652: 11611: 9692: 9653: 9500: 9236: 9016: 8905: 8763: 8734: 8726: 8656: 8648: 8599: 8555: 8547: 8443: 7878: 7732: 7712: 7630: 7499: 7034: 6585: 6507: 6039: 5889: 5887: 5885: 5636: 5391: 5220:

write: "in almost all cases, these early systems failed on more difficult problems"

5189: 4975: 4967: 4959: 4931: 4927: 4894: 4734: 4099: 3800: 3728: 3719: 3566: 3470: 3405: 3111: 3025:

that associates patterns of neuron activations with human-understandable concepts.

2815: 2805: 2666: 2640: 2601: 2594: 2582: 2578: 2431: 2427: 2400: 2244: 2061: 2057: 1987: 1935: 1931: 1873: 1811: 1792: 1734: 1708: 1590: 1569: 1533: 1521: 1509: 1503: 1495: 1463: 1388: 1251: 1243: 1222: 1188: 1180: 965: 934: 855: 834: 785: 577: 502: 490: 463: 451: 225: 160: 145: 19784: 19210: 18554: 16108: 16036: 15975: 15344:"US Leadership in Artificial Intelligence Can Shape the 21st Century Global Order" 11235:"Andrew Ng: 'Do we think the world is better off with more or less intelligence?'" 9681:"Modelling and interpreting pre-evacuation decision-making using machine learning" 5893:

Psychological evidence of the prevalence of sub-symbolic reasoning and knowledge:

4405:. The improved software would be even better at improving itself, leading to what 2387: 2335:

the process, but I’m not sure it will unleash a new wave of pension innovation."

1644:

A neural network is an interconnected group of nodes, akin to the vast network of

25208: 25198: 25098: 25083: 25063: 25058: 25043: 25023: 24983: 24973: 24900: 24668: 24648: 24638: 24628: 24562: 24496: 24211: 24196: 24099: 24089: 24081: 23946: 23819: 23797: 23787: 23067: 22961: 22933: 22827: 22779: 22764: 22749: 22604: 22599: 22546: 22436: 22410: 22362: 22307: 22049: 21993: 21815: 21457: 21377: 21216: 20917: 20877: 20799: 20754: 20591: 20496: 20481: 20456: 20270: 20250: 19686: 19546: 19506: 19285: 19118: 19069: 18720: 18684:." Advances in neural information processing systems 30 (2017). Seminal paper on 18460: 18157:

Urbina, Fabio; Lentzos, Filippa; Invernizzi, Cédric; Ekins, Sean (7 March 2022).

18040: 17739: 17658: 17350: 17233: 17220: 17073: 16753:"A Proposal for the Dartmouth Summer Research Project on Artificial Intelligence" 16720: 16581: 16484: 16212: 16080: 16048: 16044: 14792: 14393: 14291: 14110: 11448:"The open-source AI boom is built on Big Tech's handouts. How long will it last?" 10777: 9696: 8078: 7576: 6878: 6361: 6102: 5395: 5369: 5033: 5007:

is a systematic error or deviation from the correct value. But in the context of

4991: 4955: 4947: 4517: 4457: 4374: 4370: 4362: 3874: 3824: 3783:

Up to this point, most of AI's funding had gone to projects that used high-level

3632: 3583: 3426: 3350: 3319: 3241: 3147: 2793: 2682: 2621: 2298: 2097: 1757: 1741: 1677: 1479: 1317: 1066: 1062: 1039: 873:(where the program must learn to predict what category the input belongs in) and 869:

requires a human to label the input data first, and comes in two main varieties:

826: 102: 18850:

Jumper, John; Evans, Richard; Pritzel, Alexander; et al. (26 August 2021).

18267:"OpenAI has published the text-generating AI it said was too dangerous to share" 17292: 17018: 16439:"Will artificial intelligence destroy humanity? Here are 5 reasons not to worry" 9240: 5882: 3367:

Other researchers, however, spoke in favor of a less dystopian view. AI pioneer

925:(NLP) allows programs to read, write and communicate in human languages such as 25203: 25163: 25158: 25133: 25108: 25078: 25013: 25008: 25003: 24988: 24940: 24885: 24845: 24491: 24329: 24145: 24135: 24057: 24000: 23941: 23880: 23875: 23860: 23792: 23602: 23322: 23173: 23077: 22976: 22822: 22794: 22023: 21988: 21978: 21803: 21561: 21387: 21180: 21142: 21111: 20968: 20837: 20697: 20336: 20245: 19946: 19796: 19691: 19601: 19566: 19536: 19521: 19491: 19418: 19281: 19080: 19011: 18875: 18827: 18715: 18701: 18677: 18174: 18110: 18097: 17904: 17565:"Computer says no: why making AIs fair, accountable and transparent is crucial" 17540:"Stephen Hawking, Elon Musk, and Bill Gates Warn About Artificial Intelligence" 17333:

Poria, Soujanya; Cambria, Erik; Bajpai, Rajiv; Hussain, Amir (September 2017).

16748: 15917: 15752: 15109: 15085: 15059: 14973: 14922: 14731: 14705: 14136: 14023: 13932: 13886: 13594: 12890:"AI or BS? How to tell if a marketing tool really uses artificial intelligence" 12618: 12354: 11707: 11656: 10047: 9657: 9159: 9020: 8730: 8652: 8604: 8587: 6595: 6098: 5271: 5197: 5193: 5072: 4963: 4919: 4881: 4852: 4716: 4632: 4560: 4463: 4425: 4343: 4255: 4250: 4149: 4107: 4083: 4049: 3866: 3788: 3744: 3627: 3523:

Other developments in ethical frameworks include those decided upon during the

3458: 3389: 3339: 3312: 3280:

with humanity's morality and values so that it is "fundamentally on our side".

3127: 3080: 2944: 2847: 2839: 2780: 2768: 2674: 2586: 2523: 2489: 2485: 2122: 1995: 1907: 1819: 1791:

that can be from the Internet. The pretraining consists of predicting the next

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is a body of knowledge represented in a form that can be used by a program. An

740: 19170: 19169:

Silver, David; Huang, Aja; Maddison, Chris J.; et al. (28 January 2016).

19146: 18910: 17758: 17711: 17616: 17530: 17335:"A review of affective computing: From unimodal analysis to multimodal fusion" 17252: 17227:. presented and distributed at the 2007 Singularity Summit, San Francisco, CA. 16861: 16832: 16640:"What jobs will still be around in 20 years? Read this to prepare your future" 16429: 16354: 16335: 15738: 14844: 14817: 14282: 14223: 14177: 13785:

Artificial Intelligence: Structures and Strategies for Complex Problem Solving

11616: 8551: 6690: 5278:

increased from a "sporadic usage" in 2012 to more than 2,700 projects in 2015.

4604: 4503: 4158:

for many important problems. Soft computing is a set of techniques, including

3684:

design for "artificial neurons" in 1943, and Turing's influential 1950 paper '

1764:) and the availability of vast amounts of training data, especially the giant 984:

and not dictionaries should be the basis of computational language structure.

25582: 25228: 25213: 25193: 25183: 25138: 25118: 25088: 24960: 24880: 24698: 24643: 24613: 24281: 24236: 23920: 23915: 23890: 23885: 23634: 23461: 23062: 22357: 21968: 21948: 21865: 21544: 21167: 21147: 20887: 20822: 20794: 20722: 20451: 20366: 20026: 19951: 19904: 19821: 19811: 19716: 19671: 19666: 19641: 19616: 19606: 19586: 19511: 19378: 18816: 18729: 18562: 18539:"Artificial Intelligence and the Public Sector – Applications and Challenges" 18441: 18349:

Vision 21: Interdisciplinary Science and Engineering in the Era of Cyberspace

18118: 17813: 17719: 17310: 17150: 16942: 16740: 16705: 16462: 15983: 15853: 15824: 15657: 15637: 15399: 14774: 14688: 14602: 14527: 14359: 14132: 14073:

The Brain Makers: Genius, Ego, And Greed In The Quest For Machines That Think

13561: 13420: 11715: 11695: 11664: 11640: 11599: 11069:""Godfather of artificial intelligence" talks impact and potential of new AI" 9865: 9704: 9665: 9641: 9446: 9267: 8978: 8917: 8837: 8775: 8613: 8210: 7676: 6196: 6192: 6106: 5733: 5403: 5237: 5229: 5177: 5159:

wrote "it was astonishing whenever a computer did anything kind of smartish".

5098: 5062:

When the law was passed in 2018, it still contained a form of this provision.

5021: 4847:

discussed the centrality of learning as early as 1950, in his classic paper "

4815: 4644: 4578: 4554: 4453: 4441: 4428:, slowing when they reach the physical limits of what the technology can do. 4312: 4217: 4015: 3904:

companies began to deliver programs that created enormous interest. In 2015,

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For medical research, AI is an important tool for processing and integrating

1911: 1803:", although this can be reduced with RLHF and quality data. They are used in 1730: 1656:

An artificial neural network is based on a collection of nodes also known as

1609: 1556: 1353: 1247: 1226: 1138:

AI research uses a wide variety of techniques to accomplish the goals above.

892:

is a type of machine learning that runs inputs through biologically inspired

889: 644: 546: 478: 155: 19301:. BBC Radio 4 discussion with John Agar, Alison Adam & Igor Aleksander ( 19298: 18345:"The Coming Technological Singularity: How to Survive in the Post-Human Era" 18247:"A Complete Guide to SHAP – SHAPley Additive exPlanations for Practitioners" 17947:"Artificial Intelligence Index Report 2023/Chapter 6: Policy and Governance" 17037: 16020: 14765:

Challa, Subhash; Moreland, Mark R.; Mušicki, Darko; Evans, Robin J. (2011).

14417: 13998:

Introduction to Artificial Intelligence: from data analysis to generative AI

10094:"AI is exhausting the power grid. Tech firms are seeking a miracle solution" 10075:"AI already uses as much energy as a small country. It's only the beginning" 9409:"ChatGPT: Most Americans Know About It, But Few Actually Use the AI Chatbot" 9202: 8909: 7925:

Introduction to Artificial Intelligence: from data analysis to generative AI

6184: 6182: 3980: 3761:", a period when obtaining funding for AI projects was difficult, followed. 1823: 1640: 25238: 25143: 25018: 24860: 24824: 24688: 24618: 24431: 24045: 24020: 24005: 23978: 23968: 23829: 23740: 23538: 23337: 23158: 22817: 22054: 21885: 21300: 20978: 20932: 20912: 20867: 20842: 20832: 20804: 20734: 20692: 20566: 20520: 20491: 20471: 19981: 19971: 19966: 19929: 19879: 19676: 19656: 19646: 19576: 19496: 19202: 19095: 19043: 18942: 18893: 18812: 18752: 18468: 18340: 18192: 18005: 17666: 17101: 16954: 16364: 16310: 16302: 16126: 16084: 16028: 15800: 15716: 15348: 14475: 14377: 13858: 13714: 13530: 13254: 11672: 9028: 8925: 8748: 8670: 8569: 6691:"Artificial Intelligence (AI): What Is AI and How Does It Work? | Built In" 5315: 5258: 5233: 5217: 5185: 5156: 5140: 5124: 4911: 4585: 4533: 4528: 4445: 4437: 4414: 4355: 4347: 4293: 4229: 4103: 4095: 4045: 3992: 3894: 3777: 3681: 3673: 3587: 3569:

was held in 2023 with a declaration calling for international co-operation.

3478: 3446: 3277: 3256: 3193: 3189: 3107: 3064: 2884: 2636: 2559: 2443: 2439: 2435: 2211: 2175: 2155: 1959: 1573: 1077: 992: 973: 957: 888:

is when the knowledge gained from one problem is applied to a new problem.

877:(where the program must deduce a numeric function based on numeric input). 633: 510: 435: 299: 18604:"Artificial Intelligence as a Positive and Negative Factor in Global Risk" 18292:"The scary truth about AI copyright is nobody knows what will happen next" 17126: 17109: 15044:"Robots With Flawed AI Make Sexist And Racist Decisions, Experiment Shows" 14437:

Berryhill, Jamie; Heang, Kévin Kok; Clogher, Rob; McBride, Keegan (2019).

12865:"One of the Biggest Problems in Regulating AI Is Agreeing on a Definition" 9504: 8860:"AlphaGo retires from competitive Go after defeating world number one 3–0" 7503: 4342:(a set of capacities related to high intelligence, such as discernment or 3599:

created the first international legally binding treaty on AI, called the "

2696: 1616:

algorithm was the most widely used analogical AI until the mid-1990s, and

1612:

is the simplest and most widely used symbolic machine learning algorithm.

716: 601: 25295: 25173: 25053: 24915: 24855: 24826: 24693: 24678: 24486: 24446: 24067: 23993: 23983: 23973: 23936: 23853: 23814: 23765: 23533: 23528: 23349: 23148: 22774: 22686: 22150: 21921: 21830: 21825: 21447: 21425: 21266: 20922: 20907: 20892: 20872: 20789: 20717: 20534: 20524: 20511: 20476: 20426: 20356: 20309: 20196: 20186: 20047: 20021: 19831: 19744: 19721: 19696: 19681: 19581: 19556: 19531: 19526: 18978: 18844:

The Allure of Machinic Life: Cybernetics, Artificial Life, and the New AI

18691: 18092: 17908: 17789: 17735: 16888: 16510: 15241: 15067: 14735: 14468:

MM '06 Proceedings of the 14th ACM international conference on Multimedia

14068: 13746: 12176: 10747: 7708: 6487: 6179: 6159: 5864: 5241: 4979: 4915: 4844: 4335: 4319: 4308: 4163: 3996: 3969: 3952: 3816: 3812: 3784: 3772:

project inspired the U.S. and British governments to restore funding for

3764:

In the early 1980s, AI research was revived by the commercial success of

3689: 3665: 3657: 3354: 3139: 2835: 2763:

to guide users to more content. These AI programs were given the goal of

2690: 2645: 2414:

and 14% had tried it. The increasing realism and ease-of-use of AI-based

2171: 2151: 2085: 1807:, which allow people to ask a question or request a task in simple text. 1649: 1499: 1475: 1433: 1384: 844: 697: 693: 625: 328: 313: 23237: 20103: 19651: 19194: 19035: 18934: 17857:"ChatGPT-4 Creator Ilya Sutskever on AI Hallucinations and AI Democracy" 16284: 14316: 14307: 11795:

Law Library of Congress (U.S.). Global Legal Research Directorate (2019)

9494: 2434:

AI-generated photos. Widespread attention was gained by a fake photo of

1703:

use only a single layer of neurons; deep learning uses multiple layers.

768:

An "agent" is anything that perceives and takes actions in the world. A

24658: 24633: 24608: 24567: 24547: 23493: 23168: 23098: 22691: 22431: 22287: 22044: 22003: 21998: 21911: 21820: 21728: 21640: 21620: 20809: 20538: 20529: 20516: 20260: 20223: 19884: 19806: 19706: 19626: 19596: 19551: 19108:, vol. 329, no. 1 (July/August 2023), p. 7. "Despite its high IQ, 19075: 18778: 18209: 17287:. Cognitive Technologies. Berlin, Heidelberg: Springer. pp. 1–30. 15671:"Google's Photo App Still Can't Find Gorillas. And Neither Can Apple's" 15579: 15444: 14950: 14593: 14576: 14128: 13519: 11493:"Stability announces Stable Diffusion 3, a next-gen AI image generator" 8685:"AI discovers new class of antibiotics to kill drug-resistant bacteria" 8581: 8579: 8187: 5076: 4832: 4566: 4406: 4334:

It is difficult or impossible to reliably evaluate whether an advanced

3843: 3828: 3749: 3466: 3454: 3377: 3343: 3323: 3296: 3123: 2916: 2888: 2880: 2872: 2670: 2632: 2419: 2262: 2220: 2080: 1872:(CPUs) as the dominant means for large-scale (commercial and academic) 1865: 1700: 1376: 1192: 1114:, wherein AI classifies the affects displayed by a videotaped subject. 829:

that supplies the utility of each state and the cost of each action. A

692:. By the late 1980s and 1990s, methods were developed for dealing with 621: 609: 20963: 17888: 17415:"Revealed: The Authors Whose Pirated Books are Powering Generative AI" 17389: 17359: 16809:

McCauley, Lee (2007). "AI armageddon and the three laws of robotics".

16535:"Robots Will Take Jobs, but Not as Fast as Some Fear, New Report Says" 15509:"Elon Musk: artificial intelligence is our biggest existential threat" 15454:"Is artificial intelligence really an existential threat to humanity?" 14440:

Hello, World: Artificial Intelligence and its Use in the Public Sector

11964: 11893:"Council of Europe opens first ever global treaty on AI for signature" 9345:"Anthropic Said to Be Closing In on $ 300 Million in New A.I. Funding" 6934: 6152: 4448:

have predicted that humans and machines will merge in the future into

3200:. Risk estimates vary; for example, in the 2010s, Michael Osborne and 3154:. All these technologies have been available since 2020 or earlier—AI 3047:

Artificial intelligence provides a number of tools that are useful to

1799:(RLHF). Current GPT models are prone to generating falsehoods called " 24905: 24673: 24663: 24441: 24231: 24125: 23824: 23523: 22673: 22634: 22039: 22008: 21906: 21750: 21713: 21650: 21604: 21599: 21584: 21053: 20576: 20169: 19956: 19889: 19853: 19516: 19481: 19429: 18832: 18736: 18525:"Humans may be more likely to believe disinformation generated by AI" 17981: 15218:"Poll: AI poses risk to humanity, according to majority of Americans" 14667: 14631: 13126:

A modern example of neat AI and its aspirations in the 21st century:

12758:

Kirk-Giannini, Cameron Domenico; Goldstein, Simon (16 October 2023).

9911:"Getting the Innovation Ecosystem Ready for AI. An IP policy toolkit" 9606:"8 – AI for large-scale evacuation modeling: promises and challenges" 9256:"The US and 30 Other Nations Agree to Set Guardrails for Military AI" 7154: 7016: 6032: 5686: 5632: 4971: 4828: 4686: – Hypothetical concept of storing a personality in digital form 4600: 3913: 3858:(or "AGI"), which had several well-funded institutions by the 2010s. 3847: 3839: 3758: 3556: 3393: 3373: 3327: 3252: 3216: 3131: 3060: 3056: 3048: 3042: 3018: 3006: 2876: 2686: 2678: 2590: 2563: 2167: 2163: 2131: 2127: 2003: 1666: 1285: 1209:

of possible moves and counter-moves, looking for a winning position.

1206: 838: 701: 668: 640: 617: 558: 554: 363: 127: 19171:"Mastering the game of Go with deep neural networks and tree search" 19116:

Scharre, Paul, "Killer Apps: The Real Dangers of an AI Arms Race",

18538: 18127:

UNESCO Science Report: the Race Against Time for Smarter Development

17686: 17512:

Human Compatible: Artificial Intelligence and the Problem of Control

11858: 11639:

Buruk, Banu; Ekmekci, Perihan Elif; Arda, Berna (1 September 2020).

10653: 10651: 8576: 8275: 3977:

but "it is usual to have a polite convention that everyone thinks."

3631:

challenges and risks of artificial intelligence. In May 2024 at the

3138:

aid in producing misinformation. Advanced AI can make authoritarian

1699:

is the most successful network architecture for recurrent networks.

1426:. Moreover, its efficiency is competitive with computation in other 24653: 24271: 24221: 23696: 23444: 23419: 22734: 22224: 21941: 21773: 20596: 20314: 19393: 17916:. Dartmouth Summer Research Conference on Artificial Intelligence. 16195:. MIT Artificial Intelligence Laboratory, Humanoid Robotics Group. 15628: 15599: 14710: 14294:(2009), "The New Frontier of Human-Level Artificial Intelligence", 12655: 12101:

The Essential Turing: the ideas that gave birth to the computer age

12032:"Second global AI summit secures safety commitments from companies" 9328: 9131: 9089: 6258: 6256: 6008: 5110:"Electronic brain" was the term used by the press around this time. 5037: 4713: – Use of information technology to augment human intelligence 4593: 4549: 4339: 4040: 4028: 3909: 3882: 3878: 3796: 3704: 3615: 3575: 3308: 3288: 2843: 2756: 2658: 2628: 2527: 2496: 2460: 2210:

games. In 2019, DeepMind's AlphaStar achieved grandmaster level in

2195: 2072: 2068: 2053: 2023: 2007: 1947: 1769: 1602: 1360:) from other statements that are given and assumed to be true (the 1320:(which also operates on objects, predicates and relations and uses 1217: 1008: 981: 772:

has goals or preferences and takes actions to make them happen. In

756:

that they could express verbally). There is also the difficulty of

733: 585: 455: 443: 200: 122: 19266: 18773:

is what distinguishes us from machines. For biological creatures,

17940:. Vol. Section on Information Theory, part 2. pp. 56–62. 17649: 17603:

Scassellati, Brian (2002). "Theory of mind for a humanoid robot".

17019:"Future Progress in Artificial Intelligence: A Poll Among Experts" 16721:"Content: Plug & Pray Film – Artificial Intelligence – Robots" 16687:"Google's Gemini: is the new AI model really better than ChatGPT?" 16421: 16394:"What is Artificial Intelligence and How Does AI Work? TechTarget" 14835: 14350: 13768:

These were the four of the most widely used AI textbooks in 2008:

12931: 10877:"China's game art industry reportedly decimated by growing AI use" 10810: 9642:"A Framework for Intelligent Fire Detection and Evacuation System" 9044:"Google AI learns to play open-world video games by watching them" 5984: 4031:, often even if they did "not actually use AI in a material way". 2681:. Some of these players already own the vast majority of existing 1395:

from the problem. In the more general case of the clausal form of

25291: 24407: 24201: 23782: 22064: 21901: 21855: 21778: 21678: 21673: 21625: 20294: 19899: 19109: 19091: 18836: 18537:

Wirtz, Bernd W.; Weyerer, Jan C.; Geyer, Carolin (24 July 2018).

15743: 14706:"Stephen Hawking warns artificial intelligence could end mankind" 11738:"AI Safety Institute releases new AI safety evaluations platform" 11118:"'50–50 chance' that AI outsmarts humanity, Geoffrey Hinton says" 11036:

Leaders' concerns about the existential risks of AI around 2015:

10729:"Security lapse exposed a Chinese smart city surveillance system" 10648: 9783: 9229:"Artificial intelligence as the basis of future control networks" 9146: 8586:

Bax, Monique; Thorpe, Jordan; Romanov, Valentin (December 2023).

5737: 5173: 5127:

called the conference "the inception of artificial intelligence."

4866:

AI winter § Machine translation and the ALPAC report of 1966

4366: 3929: 3905: 3708: 3611: 3304: 3151: 2752: 2555: 2531:

the AI algorithms are inherently unexplainable in deep learning.

2411: 2391:

Vincent van Gogh in watercolour created by generative AI software

2182:, who was the best Go player in the world. Other programs handle 2159: 2114: 2015: 1999: 1943: 1927: 1923: 1815: 1804: 1661: 1458: 1361: 1202: 806:), or the agent can seek information to improve its preferences. 789: 656: 652: 530: 494: 486: 439: 368: 19321: 18210:"Artificial intelligence could lead to extinction, experts warn" 15918:"Artificial Intelligence at Edinburgh University: a Perspective" 13936: 13738: 13304:"Nick Bostrom: How can we be certain a machine isn't conscious?" 11815: 11538:"Should we make our most powerful AI models open source to all?" 11474:"Mistral AI's New Language Model Aims for Open Source Supremacy" 11341: 11339: 11183:"'Father of AI' says tech fears misplaced: 'You cannot stop it'" 10332: 10330: 9679:

Zhao, Xilei; Lovreglio, Ruggiero; Nilsson, Daniel (1 May 2020).

8331: 8329: 8327: 8325: 8323: 8321: 8319: 7702: 6946: 6922: 6910: 6898: 6848: 6786: 6253: 4401:

produced sufficiently intelligent software, it might be able to

3142:

more competitive than liberal and decentralized systems such as

1453: 24587: 24256: 23807: 23802: 22079: 22059: 21931: 21723: 21066: 20361: 20016: 19313: 18811:. In some cases, there are few historical records on long-gone 18774: 17213:

Funding a Revolution: Government Support for Computing Research

16414:

Regulation of artificial intelligence in selected jurisdictions

16267:

Kuperman, G. J.; Reichley, R. M.; Bailey, T. C. (1 July 2006).

15532:

Goffrey, Andrew (2008). "Algorithm". In Fuller, Matthew (ed.).

14827:

2012 IEEE Conference on Computer Vision and Pattern Recognition

13867:(2nd ed.), Upper Saddle River, New Jersey: Prentice Hall, 13862: 11314: 11312: 8491:"Mojo Rising: The resurgence of AI-first programming languages" 8306: 8304: 8302: 5449:

Warnings of overspecialization in AI from leading researchers:

5275: 5201: 4609: 4508: 4481:

Darwin Among the Machines: The Evolution of Global Intelligence

4449: 4000: 3925: 3450: 3076: 2962: 2423: 2203: 2031: 2027: 2011: 1881: 1723: 1645: 1580: 1419: 538: 16735: 13543: 13235: 13136: 12077: 12075: 10950: 9287: 9200: 8711: 7086: 5779:

Problem-solving, puzzle solving, game playing, and deduction:

5517: 5346: 5344: 5342: 5088:

See table 4; 9% is both the OECD average and the U.S. average.

1312:(which operates on statements that are true or false and uses 24226: 23774: 23439: 21880: 21860: 21850: 21845: 21840: 21835: 21798: 21630: 19661: 19072:, which produced human-level performance on some Atari games. 18909:

LeCun, Yann; Bengio, Yoshua; Hinton, Geoffrey (28 May 2015).

18852:"Highly accurate protein structure prediction with AlphaFold" 17137:"How YouTube Drives People to the Internet's Darkest Corners" 16557: 16244:"GPUs Continue to Dominate the AI Accelerator Market for Now" 16087:(1982). "Judgment under uncertainty: Heuristics and biases". 14873:"Why 2015 Was a Breakthrough Year in Artificial Intelligence" 13633: 13163: 13118:

A classic example of the "scruffy" approach to intelligence:

12919: 12478: 12422: 11694:

Kamila, Manoj Kumar; Jasrotia, Sahil Singh (1 January 2023).

11336: 10851:"AI is already taking video game illustrators' jobs in China" 10663: 10636: 10598: 10586: 10327: 9771: 9723: 8967:"AI becomes grandmaster in 'fiendishly complex' StarCraft II" 8629:"Highly accurate protein structure prediction with AlphaFold" 8375: 8373: 8371: 8346: 8344: 8316: 8287: 7764: 7651: 7649: 7647: 7570: 7302: 5576: 4662: – Algorithm that selects actions for intelligent agents 4570:(1999). In contrast, the rare loyal robots such as Gort from 4498: 4193: 4129: 4068: 3917: 3607: 3462: 3445:

Active organizations in the AI open-source community include

3300: 3192:, but they generally agree that it could be a net benefit if 3118:

potential enemies of the state and prevent them from hiding.

2986: 2970: 2237: 2207: 2187: 1831: 1684:

in data. In theory, a neural network can learn any function.

1406:

Inference in both Horn clause logic and first-order logic is

1380: 1297: 1031: 550: 518: 18439: 18159:"Dual use of artificial-intelligence-powered drug discovery" 18156: 14436: 14240:"Ask the AI experts: What's driving today's progress in AI?" 14209: 14116:

Alter, Alexandra; Harris, Elizabeth A. (20 September 2023),

13938:

Artificial Intelligence: Foundations of Computational Agents

12700: 12529: 12495: 12483: 12473: 12398: 12336: 12300: 12244: 12232: 11761: 11309: 10753: 10711:"How China Uses High-Tech Surveillance to Subdue Minorities" 9580: 9496:

Artificial Intelligence, Foundations of Computational Agents

8940:"MuZero: Mastering Go, chess, shogi and Atari without rules" 8299: 7284: 6319: 6020: 5943:, pp. 23–46, 69–81, 169–233, 235–277, 281–298, 319–345) 4851:". In 1956, at the original Dartmouth AI summer conference, 1272:

algorithms. Two popular swarm algorithms used in search are

24261: 23665: 21870: 20240: 19991: 19919: 18718:, "Ready for Robots? How to Think about the Future of AI", 17585:"Exploring LIME Explanations and the Mathematics Behind It" 17427:"Thinking Machines: The Search for Artificial Intelligence" 17110:"Computer Science as Empirical Inquiry: Symbols and Search" 15876:

Multilayer Feedforward Networks are Universal Approximators

15873:

Hornik, Kurt; Stinchcombe, Maxwell; White, Halbert (1989).

14577:"Towards Intelligent Regulation of Artificial Intelligence" 13263:. Searle's original presentation of the thought experiment. 12777: 12072: 11422:"Google open sources tools to support AI model development" 10510: 10366: 10183:

Rainie, Lee; Keeter, Scott; Perrin, Andrew (22 July 2019).

9918: 9639: 9376:

Lanxon, Nate; Bass, Dina; Davalos, Jackie (10 March 2023).

7868: 5729: 5727: 5339: 4719: – Hypothetical process of digitally emulating a brain 4213: 3419: 2908:

than the past. It is descriptive rather than prescriptive.

2823: 2581:

has recorded millions of private conversations and allowed

1955: 506: 17936:

Solomonoff, Ray (1957). "An Inductive Inference Machine".

17202:

Association for the Advancement of Artificial Intelligence

16169:"Noam Chomsky on Where Artificial Intelligence Went Wrong" 15592:

Goodfellow, Ian; Bengio, Yoshua; Courville, Aaron (2016),

15585:

Speculations Concerning the First Ultraintelligent Machine

14764: 14491:"What happens when our computers get smarter than we are?" 12256: 11600:"A Unified Framework of Five Principles for AI in Society" 11018: 9603: 9320: 9070:

Improving mathematical reasoning with process supervision.

8385: 8368: 8356: 8341: 8263: 7644: 6940: 6307: 3346:, have expressed concerns about existential risk from AI. 760:, the problem of obtaining knowledge for AI applications. 25289: 19012:"Human-level control through deep reinforcement learning" 19009: 18074:"Transformers Revolutionized AI. What Will Replace Them?" 17635:(2015). "Deep Learning in Neural Networks: An Overview". 17433:. Vol. 2, no. 2. pp. 14–23. Archived from 17332: 16095:(4157). New York: Cambridge University Press: 1124–1131. 15591: 15024:"Machine learning: What is the transformer architecture?" 14999:"AI has already changed the world. This report shows how" 14899:"Commentary: Bad news. Artificial intelligence is biased" 14204:

OECD Social, Employment, and Migration Working Papers 189

14118:"Franzen, Grisham and Other Prominent Authors Sue OpenAI" 12220: 11564:"Understanding artificial intelligence ethics and safety" 11519:"How enterprises are using open source LLMs: 16 examples" 10938: 10498: 10354: 10135:"Energy-Guzzling AI Is Also the Future of Energy Savings" 10030:"In the Age of A.I., Tech's Little Guys Need Big Friends" 8536:"The potential for artificial intelligence in healthcare" 8222: 7741:, §12.5–12.6, §13.4–13.5, §14.3–14.5, §16.5, §20.2–20.3), 7022: 6158:

Representing knowledge about knowledge: Belief calculus,

5972: 5318:: "Stong AI – the assertion that machines that do so are 4954:(1982). Precursors to backpropagation were developed by: 3292: 2174:-playing system to beat a professional Go player without 2135: 21067:

Covariance Matrix Adaptation Evolution Strategy (CMA-ES)

18095:(October 1950), "Computing Machinery and Intelligence", 13017:

Historical significance and philosophical implications:

11923: 10894: 10798: 10619:"New Anthropic Research Sheds Light on AI's 'Black Box'" 10550: 10538: 10315: 9935:"Big Tech is spending more than VC firms on AI startups" 9891: 9795: 8007: 7892: 7814: 7600: 5960: 5724: 4974:(1969); Backpropagation was independently developed by: 4385: 2929:

Conference on Fairness, Accountability, and Transparency

2693:, allowing them to entrench further in the marketplace. 1179:

are rarely sufficient for most real-world problems: the

643:. Funding and interest vastly increased after 2012 when 19168: 19099: 18849: 17452:"Five experts share what scares them the most about AI" 16273:

Journal of the American Medical Informatics Association

14824: 14465: 14446:. Paris: OECD Observatory of Public Sector Innovation. 14265:

Research handbook on the law of artificial intelligence

14127: 13153: 13151: 13046: 12729: 12727: 12461: 12324: 11879:"UN Announces Advisory Body on Artificial Intelligence" 11864: 11805: 11803: 11375: 10211: 8281: 7620: 6295: 6014: 5303: 4700:

Pages displaying short descriptions of redirect targets

4655:

Pages displaying short descriptions of redirect targets

3098:

to efficiently control their citizens in several ways.

2854:

studies how to prevent harms from algorithmic biases.

2697:

Substantial power needs and other environmental impacts

1387:, problem-solving search can be performed by reasoning 18769:, vol. LXXI, no. 1 (18 January 2024), pp. 27–28, 30. " 18724:, vol. 98, no. 4 (July/August 2019), pp. 192–98. 17931:– via std.com, pdf scanned copy of the original. 17495:

Rose, Steve (11 July 2023). "AI Utopia or dystopia?".

16266: 15872: 13409:"Give robots 'personhood' status, EU committee argues" 12995: 12907: 12757: 12639: 12637: 12635: 12451: 12449: 12312: 12054:"Frontier AI Safety Commitments, AI Seoul Summit 2024" 11846: 11836: 11834: 11832: 11830: 11324: 10342: 10279: 10113:"AI Data Centers and the Coming YS Power Demand Surge" 9735: 8458: 8134: 7537: 7535: 6608: 6606: 6551: 6132: 5990: 4725: – Form of business process automation technology 3707:

strategies, solving word problems in algebra, proving

3692:

and showed that "machine intelligence" was plausible.

2446:, as well as the usage in professional creative arts. 1551:

systems analyze processes that occur over time (e.g.,

24467:

Existential risk from artificial general intelligence

18442:"Autonomous mental development by robots and animals" 16487:(1973). "Artificial Intelligence: A General Survey". 16079: 15776:"Human rights for robots? We're getting carried away" 14331: 14028:

AI: The Tumultuous Search for Artificial Intelligence

13669: 13657: 13645: 13175: 12801: 12571: 12410: 12191:

Historical influence and philosophical implications:

11935: 11579: 11561: 10460: 10297: 10199: 10154:"Tech Industry Wants to Lock Up Nuclear Power for AI" 9759: 9711: 9288:

Newsom, Gavin; Weber, Shirley N. (6 September 2023).

8998: 8470: 5911: 4512:, the title standing for "Rossum's Universal Robots". 4279: 3718:

and considered this the goal of their field. In 1965

3236:

Existential risk from artificial general intelligence

2438:

wearing a white puffer coat, the fictional arrest of

2231:

In mathematics, special forms of formal step-by-step

1624:(SVM) displaced k-nearest neighbor in the 1990s. The 1205:

programs, such as chess or Go. It searches through a

19125: 18993:

Artificial intelligence: a guide for thinking humans

17225:

The Nature of Self-Improving Artificial Intelligence

15658:

Consumer Data: Increasing Use Poses Risks to Privacy

13992: 13881: 13701:

The two most widely used textbooks in 2023 (see the

13469:"Robot rights violate human rights, experts warn EU" 13223: 13187: 13148: 13082: 13058: 12724: 12712: 12434: 11911: 11800: 11363: 11136: 10974: 10962: 10928:

Tarnoff, Ben (4 August 2023). "Lessons from Eliza".

10574: 10257: 10255: 10235:"Why it's so damn hard to make AI fair and unbiased" 9879: 9807: 9678: 7919: 7848: 7794: 7744: 7592: 7550: 7487: 7437: 7382: 7174: 7128: 7046: 6860: 6751: 6519: 6224: 6171: 6144: 6118: 6067: 5940: 5833: 5798: 5581:

Microelectronics and Computer Technology Corporation

5486: 5484: 4799: 4772: 4377:

if sentient AI is created and carelessly exploited.

3975:

we can not determine these things about other people

3807:, and began to look into "sub-symbolic" approaches. 3507:

with other people sincerely, openly, and inclusively

2728:

AI Data Centers and the Coming US Power Demand Surge

1845: 910:(how much data is required), or by other notions of 24538:

Center for Human-Compatible Artificial Intelligence

19229: 18498: 17944: 17844:"How Google Plans to Solve Artificial Intelligence" 17211:(1999). "Developments in Artificial Intelligence". 15246:"Posthuman Rights: Dimensions of Transhuman Worlds" 14201: 13753:(3rd ed.). New Delhi: Tata McGraw Hill India. 13681: 13211: 12813: 12632: 12446: 11827: 11821: 11006: 10836: 10816: 10690: 10472: 10091: 9854:"How to Stop Your Data From Being Used to Train AI" 9556:"Why agents are the next frontier of generative AI" 8699:"AI speeds up drug design for Parkinson's ten-fold" 8050: 8048: 7776: 7532: 7525: 7328: 7004: 6958: 6836: 6816:Modern statistical and deep learning approaches to 6798: 6603: 5996: 5681: 5679: 3946: 696:or incomplete information, employing concepts from 18414: 17687:"Annotated History of Modern AI and Deep Learning" 17241:IEEE Transactions on Autonomous Mental Development 16958: 15182: 14871: 14212:IEEE Transactions on Autonomous Mental Development 13820: 13782: 13199: 12789: 10562: 10182: 10164: 10092:Halper, Evan; O'Donovan, Caroline (21 June 2024). 9981: 9957: 9378:"A Cheat Sheet to AI Buzzwords and Their Meanings" 8823: 8626: 8410: 7826: 7066: 6539: 6246:places abduction under "default reasoning". Luger 5627: 5625: 4154:Finding a provably correct or optimal solution is 3531:engineers, domain experts, and delivery managers. 2410:In March 2023, 58% of U.S. adults had heard about 1183:(the number of places to search) quickly grows to 18987:, vol. 327, no. 4 (October 2022), pp. 42–45. 18908: 18536: 17282: 16369:"How We Analyzed the COMPAS Recidivism Algorithm" 15292:"Will robots create more jobs than they destroy?" 14516:"artificial intelligence is a tool, not a threat" 14193:Anderson, Michael; Anderson, Susan Leigh (2011). 13773: 13142: 13070: 12678:"OpenAI Releases GPT-3, The Largest Model So Far" 12600: 12366: 11776: 11351: 10252: 9583:"Reshaping Business With Artificial Intelligence" 9375: 9210:. Washington, DC: Congressional Research Service. 8825:"Computer Wins on 'Jeopardy!': Trivial, It's Not" 8533: 8206: 8204: 8094: 7800: 7750: 7726: 7556: 7443: 7388: 7346: 7314: 7186: 7134: 7098: 7052: 6757: 6650: 6525: 6230: 6087: 6073: 5946: 5860: 5858: 5856: 5839: 5804: 5761: 5481: 5444: 4818:proved to be inefficient for capturing knowledge. 4795: 4768: 4346:) may provide another moral basis for AI rights. 3383: 1852:Programming languages for artificial intelligence 25580: 24578:Leverhulme Centre for the Future of Intelligence 18787:, "A Murder Mystery Puzzle: The literary puzzle 18042:Robotics: The Marriage of Computers and Machines 17694:Schulz, Hannes; Behnke, Sven (1 November 2012). 16922: 16883:, p. 51(3) Industrial Law Journal 511–559, 15886:. Vol. 2. Pergamon Press. pp. 359–366. 15290:Ford, Martin; Colvin, Geoff (6 September 2015). 14192: 14053:(2nd ed.), Natick, MA: A. K. Peters, Ltd., 12612: 11638: 11345: 11261:"How Not to Be Stupid About AI, With Yann LeCun" 10267: 9747: 8884:Brown, Noam; Sandholm, Tuomas (30 August 2019). 8585: 8446:. MIT Sloan Teaching & Learning Technologies 8071: 8045: 7290: 6501: 5676: 5567: 5565: 4759: 4757: 2799: 2703:Environmental impacts of artificial intelligence 2478: 2361:, coordination and deconfliction of distributed 1838:GPT models can process different types of data ( 1608:There are many kinds of classifiers in use. The 1268:Distributed search processes can coordinate via 987:Modern deep learning techniques for NLP include 683: 17974:Affective Computing and Intelligent Interaction 17390:"Microsoft's Bill Gates insists AI is a threat" 16217:"The Challenge of Being Human in the Age of AI" 15961: 14996: 14262: 13443:"Experts Don't Think Robots Should Have Rights" 12706: 12171: 12169: 11771: 11766: 9073:openai.com, May 31, 2023. Retrieved 2024-08-07. 8762:Grant, Eugene F.; Lardner, Rex (25 July 1952). 7422: 7360: 7148: 5622: 5529: 5527: 4653: – Software to detect AI-generated content 3735:and ongoing pressure from the U.S. Congress to 3519:social values, justice, and the public interest 3028: 2748:YouTube § Moderation and offensive content 2713:Electricity 2024, Analysis and Forecast to 2026 2206:, which could be trained to play chess, Go, or 976:" (due to the common sense knowledge problem). 763: 24573:Institute for Ethics and Emerging Technologies 18763:, Princeton University Press, 2023, 333 pp.), 18543:International Journal of Public Administration 17835:The Shape of Automation for Men and Management 15998: 15613: 15108: 14647:– via Victoria University of Wellington. 13930: 13896:Computational Intelligence: A Logical Approach 13749:; Knight, Kevin; Nair, Shivashankar B (2010). 13745: 13390:"What leaders need to know about robot rights" 13012: 11693: 11598:Floridi, Luciano; Cowls, Josh (23 June 2019). 10408: 9492: 9343:Griffith, Erin; Metz, Cade (27 January 2023). 8201: 8077:Gradient calculation in computational graphs, 7180: 6726: 5901: 5853: 5381: 4692: – Algorithm exhibiting emergent behavior 4582:(1986) are less prominent in popular culture. 4034: 3776:. However, beginning with the collapse of the 1316:such as "and", "or", "not" and "implies") and 1019:test, and many other real-world applications. 917: 25275: 24810: 24757:Superintelligence: Paths, Dangers, Strategies 24737:Open letter on artificial intelligence (2015) 24393: 23681: 23253: 22264:Note: This template roughly follows the 2012 22240: 21316: 20994: 20119: 19445: 19337: 17209:NRC (United States National Research Council) 17059: 17016: 15798: 15406: 14481:Superintelligence: Paths, Dangers, Strategies 13853: 13709: 13577: 13549: 13503: 13275: 13247: 13241: 13169: 13112: 13032: 12955: 12783: 12661: 12624: 12557: 12535: 12521: 12501: 12404: 12360: 12342: 12306: 12250: 12238: 12212: 12152: 12081: 11226: 11148: 11024: 10996: 10956: 10669: 10657: 10642: 10532: 10437: 10400: 10388: 10336: 10309: 9789: 9777: 9729: 9527: 9295:. Executive Department, State of California. 9204:Artificial Intelligence and National Security 8883: 8517:"7 AI Programming Languages You Need to Know" 8335: 8310: 8293: 8255: 8227: 8216: 8193: 8173: 8153: 8120: 8088: 8057: 8031: 7987: 7953: 7905: 7884: 7842: 7788: 7738: 7718: 7694: 7682: 7670: 7658: 7636: 7612: 7586: 7544: 7519: 7473: 7431: 7414: 7376: 7340: 7308: 7276: 7244: 7230: 7214: 7206: 7168: 7122: 7092: 7078: 7040: 6952: 6928: 6916: 6904: 6884: 6854: 6823: 6792: 6778: 6745: 6720: 6676: 6670: 6644: 6624: 6618: 6591: 6581: 6575: 6513: 6493: 6473: 6453: 6433: 6421: 6404: 6387: 6367: 6343: 6325: 6283: 6218: 6165: 6112: 6061: 6026: 5978: 5934: 5874: 5827: 5788: 5782: 5748: 5692: 5651: 5602: 5562: 5554: 5496: 5475: 5435: 5350: 4791: 4786: 4784: 4764: 4754: 4737: – Computer composed of organic material 4059: 3580:Global Partnership on Artificial Intelligence 3437:for developing provably beneficial machines. 3169: 2034:). The deployment of AI may be overseen by a 1635: 1454:Probabilistic methods for uncertain reasoning 1265:only the fittest to survive each generation. 861:There are several kinds of machine learning. 748:(what we know about what other people know); 408: 24825:Subfields of and cyberneticians involved in 21330: 21008: 18831:, 20 November 2023, pp. 54–59. "If by ' 18761:Free Agents: How Evolution Gave Us Free Will 18409: 18317:"AI is entering an era of corporate control" 17874: 17693: 16362: 14703: 14674: 13941:(2nd ed.). Cambridge University Press. 13486: 12166: 11597: 11174: 10944: 10708: 10360: 10007:"Where the battle to dominate AI may be won" 9499:(3rd ed.). Cambridge University Press. 9342: 8761: 7541:Stochastic methods for uncertain reasoning: 7247:"Optimization Algorithms in Neural Networks" 6829: 5966: 5906: 5524: 5469: 5051:Max Planck Institute for Intelligent Systems 4474:" as far back as 1863, and expanded upon by 2635:" file. In 2023, leading authors (including 2612:. Since 2016, some privacy experts, such as 1672:Learning algorithms for neural networks use 1581:Classifiers and statistical learning methods 1254:are commonly used to train neural networks. 19314:Articles related to Artificial intelligence 17681: 17631: 17602: 17170:"Artificial Intelligence Prepares for 2001" 17100: 16991: 16141: 15936: 15370:Technological Forecasting and Social Change 15367: 14939:Foundations and Trends in Signal Processing 14736:"Facing up to the problem of consciousness" 14289: 14267:. Cheltenham, UK: Edward Elgar Publishing. 14115: 13616: 12940: 11929: 11700:International Journal of Ethics and Systems 11284:Arguments that AI is not an imminent risk: 11200: 10900: 10832: 10804: 10709:Buckley, Chris; Mozur, Paul (22 May 2019). 9897: 8391: 8379: 8362: 8350: 8236: 7913: 7510: 6997: 5462: 4698: – Gender biases in digital technology 4212:does not know whether a machine can have a 3176:Workplace impact of artificial intelligence 2961:, in which there are a large amount of non- 2652: 1842:) such as images, videos, sound, and text. 1715:before the network can identify an object. 972:unless restricted to small domains called " 711: 663:in the future, prompting discussions about 25282: 25268: 24817: 24803: 24400: 24386: 23688: 23674: 23648: 23260: 23246: 22247: 22233: 21323: 21309: 21001: 20987: 20126: 20112: 19452: 19438: 19344: 19330: 19126:Serenko, Alexander; Michael Dohan (2011). 18378:"Chatbots Have Entered the Uncanny Valley" 17998: 17903: 17017:Müller, Vincent C.; Bostrom, Nick (2014). 16718: 16489:Artificial Intelligence: a paper symposium 16336:"The changing science of machine learning" 15669:Grant, Nico; Hill, Kashmir (22 May 2023). 15289: 13864:Artificial Intelligence: A Modern Approach 13720:Artificial Intelligence: A Modern Approach 12748:, Under "The Argument from Consciousness". 12551: 12094: 12092: 12090: 11252: 10789: 10217: 9983:"Big tech and the pursuit of AI dominance" 9531:Artificial Intelligence: A Modern Approach 9406: 9369: 9082: 7457: 7245:Singh Chauhan, Nagesh (18 December 2020). 6557: 4781: 4743: – Erroneous material generated by AI 4651:Artificial intelligence detection software 4552:, the murderous computer in charge of the 4194:Machine consciousness, sentience, and mind 4143: 3897:became a serious field of academic study. 3085:Convention on Certain Conventional Weapons 2158:, by a significant margin. In March 2016, 1797:reinforcement learning from human feedback 1141: 415: 401: 23267: 20782: 20745:Relationship between religion and science 20133: 18975:, vol. 330, no. 6 (June 2024), pp. 80-81. 18883: 18601: 18182: 17648: 17449: 17387: 17358: 17219: 17125: 16947:Computation: Finite and Infinite Machines 16927:. Springer Science & Business Media. 16876: 16822: 16685:Marmouyet, Françoise (15 December 2023). 16684: 16571: 16495: 16483: 16461: 16391: 16353: 16292: 16211: 15773: 15751: 15668: 15627: 15381: 15261: 14932:"Deep Learning: Methods and Applications" 14834: 14791: 14592: 14550: 14392: 14367: 14349: 14315: 14045: 13639: 13625: 13598: 13509: 13281: 13094: 13026: 12949: 12925: 12649: 12563: 12541: 12428: 12378: 12318: 12206: 12194: 12140: 11852: 11615: 11393: 11330: 11318: 11039: 10793: 10764: 10762: 10681: 10604: 10592: 10556: 10544: 10528: 10516: 10504: 10454: 10441: 10425: 10412: 10404: 10384: 10372: 10348: 10321: 9801: 9741: 9327: 9149:Caesars Labs, 2024. Retrieved 2024-08-07. 9088: 8738: 8660: 8603: 8559: 8464: 8404: 8223:Goodfellow, Bengio & Courville (2016) 7402: 6265: 6250:places this under "uncertain reasoning"). 5698: 5590: 5536: 5502: 4827:"Rational agent" is general term used in 3823:", including neural network research, by 2616:, have begun to view privacy in terms of 2368:In November 2023, US Vice President 1691:the signal passes in only one direction. 30:"AI" redirects here. For other uses, see 24543:Centre for the Study of Existential Risk 21257:No free lunch in search and optimization 18990: 18839:, especially smutty ones." (p. 59.) 18522: 18232: 18013: 17841: 16808: 16783: 16771: 16613:Madrigal, Alexis C. (27 February 2015). 16612: 16309: 16241: 16043: 15540:. Cambridge, Mass.: MIT Press. pp. 15314: 15058: 15041: 14730: 14677:IEEE Computational Intelligence Magazine 14651: 14609: 14263:Barfield, Woodrow; Pagallo, Ugo (2018). 14238: 14163: 14067: 13823:Artificial Intelligence: A New Synthesis 13675: 13663: 13651: 13572: 13514: 13181: 13129: 12807: 12592: 12580: 12390: 12262: 12098: 11941: 11876: 11516: 11297: 11232: 10916: 10466: 10205: 9765: 9717: 9336: 8795: 8627:Jumper, J; Evans, R; Pritzel, A (2021). 8488: 8476: 8063: 8037: 8013: 7999: 7993: 7959: 7860: 7820: 7770: 6866: 6301: 5896: 5754: 5716: 5668: 5614: 5571:Funding initiatives in the early 1980s: 5457: 4668: – Automation of business processes 4592:in many stories, most notably with the " 4497: 4329: 4298:Computationalism is the position in the 4170: 3979: 3695:The field of AI research was founded at 3560: 3360:In 2023, many leading AI experts issued 2657:The commercial AI scene is dominated by 2539: 2386: 1722: 1639: 1561: 1457: 1308:. Formal logic comes in two main forms: 1216: 1076: 1042:is the ability to analyze visual input. 715: 36:Artificial intelligence (disambiguation) 24583:Machine Intelligence Research Institute 23355:Carbon nanotube field-effect transistor 23313:Applications of artificial intelligence 19238:. Brussels: European Commission. 2020. 18995:. New York: Farrar, Straus and Giroux. 18400: 18375: 18314: 18289: 18264: 18207: 17999:Taylor, Josh; Hern, Alex (2 May 2023). 17582: 17537: 17505: 17424: 17412: 17231: 17164: 17088: 16953: 16949:, Englewood Cliffs, N.J.: Prentice-Hall 16847: 16775:(2007), "From Here to Human-Level AI", 16637: 16333: 16191: 15897:The Stanford Encyclopedia of Philosophy 15681: 15558: 15531: 15476: 15408:"From not working to neural networking" 15215: 15180: 15084: 15021: 14997:DiFeliciantonio, Chase (3 April 2023). 14972: 14921: 14488: 14474: 14022: 13976:Introduction to Artificial Intelligence 13815: 13567: 13361: 13357: 13355: 13332: 13328: 13326: 13324: 13287: 13193: 13157: 13106: 13100: 13064: 13052: 13020: 13007: 12975: 12913: 12833:"What Is Artificial Intelligence (AI)?" 12718: 12515: 12488: 12440: 12416: 12384: 12372: 12294: 12278: 12226: 12200: 12158: 12146: 12087: 11917: 11865:Altman, Brockman & Sutskever (2023) 11809: 11490: 11471: 11419: 11381: 11369: 11142: 11054: 11000: 10992: 10980: 10968: 10927: 10912: 10685: 10580: 10301: 10285: 10228: 10226: 10072: 9932: 9885: 9813: 9528:Russell, Stuart; Norvig, Peter (2020). 9226: 9201:Congressional Research Service (2019). 9196: 9194: 9192: 9103: 9041: 8821: 8534:Davenport, T; Kalakota, R (June 2019). 8514: 8444:"AI Writing and Content Creation Tools" 8282:Ciresan, Meier & Schmidhuber (2012) 8129: 8100: 7854: 7806: 7756: 7562: 7449: 7394: 7352: 7320: 7140: 7058: 7010: 6987: 6964: 6890: 6842: 6804: 6531: 6313: 6277: 6271: 6236: 6124: 6079: 6038:Representing categories and relations: 6015:Bertini, Del Bimbo & Torniai (2006) 6002: 5952: 5845: 5810: 5743: 5704: 5645: 5596: 5548: 5542: 5452: 5075:' definition, and includes things like 4803: 4776: 4741:Hallucination (artificial intelligence) 4731: – Form of artificial intelligence 4114:attempts to bridge the two approaches. 3251:First, AI does not require human-like " 3146:. It lowers the cost and difficulty of 2938: 2871:is a commercial program widely used by 1902:Applications of artificial intelligence 1117: 999:(a deep learning architecture using an 14: 25581: 25397:Electrical and electronics engineering 25382:Developmental and reproductive biology 23504:Differential technological development 22957:Knowledge representation and reasoning 19459: 18124: 18091: 17971: 17788: 17734: 17562: 17309: 16941: 16731:from the original on 12 February 2016. 16704: 16467:Building Large Knowledge-Based Systems 15839: 15757:Artificial Intelligence: The Very Idea 15736: 15724:from the original on 25 September 2021 15706: 15430: 14929: 14869: 14704:Cellan-Jones, Rory (2 December 2014). 14639:from the original on 19 September 2008 14621: 14574: 14526: 14513: 13687: 13604: 13266: 13260: 13229: 13217: 13121: 12987: 12981: 12819: 12745: 12733: 12643: 12455: 12290: 12186: 11840: 11781: 11582:"AI Ethics and Governance in Practice" 11445: 11287: 11180: 11154: 11097: 11044: 11012: 10874: 10759: 10696: 10478: 10232: 10195:from the original on 22 February 2024. 10151: 9994:from the original on 29 December 2023. 9593:from the original on 13 February 2024. 9493:Poole, David; Mackworth, Alan (2023). 9222: 9220: 8964: 8857: 8701:. Cambridge University. 17 April 2024. 8269: 8135:Hornik, Stinchcombe & White (1989) 6992: 6545: 5991:Kuperman, Reichley & Bailey (2006) 5599:, pp. 161–162, 197–203, 211, 240) 5375: 4603:, and thus to suffer. This appears in 4502:The word "robot" itself was coined by 4112:neuro-symbolic artificial intelligence 2814:Machine learning applications will be 2041: 1868:software had replaced previously used 1072: 454:that develops and studies methods and 25263: 24798: 24381: 24095:Simultaneous localization and mapping 23669: 23241: 22982:Philosophy of artificial intelligence 22228: 21304: 20982: 20107: 20053:Philosophy of artificial intelligence 19433: 19325: 19312: 19245:from the original on 20 February 2020 18755:, "The Fate of Free Will" (review of 18486:from the original on 4 September 2013 18339: 18244: 18071: 17854: 17832: 17319:, Perennial Modern Classics, Harper, 17134: 17055:from the original on 15 January 2016. 16662: 16496:Lipartito, Kenneth (6 January 2011), 16179:from the original on 28 February 2019 15890: 15559:Goldman, Sharon (14 September 2022). 15506: 15452:Geist, Edward Moore (9 August 2015). 15451: 15418:from the original on 31 December 2016 15341: 15270: 15240: 15144: 14884:from the original on 23 November 2016 14453:from the original on 20 December 2019 13973: 13899:. New York: Oxford University Press. 13609: 13536: 13466: 13440: 13301: 13205: 13038: 12795: 12675: 12547: 12274: 12175:Turing's original publication of the 12056:. gov.uk. 21 May 2024. Archived from 11953: 11535: 11292: 11206: 11049: 10616: 10568: 10170: 10110: 10017:from the original on 13 January 2024. 9945:from the original on 10 January 2024. 9466: 9388:from the original on 17 November 2023 9302:from the original on 21 February 2024 8886:"Superhuman AI for multiplayer poker" 8796:Anderson, Mark Robert (11 May 2017). 8416: 7296: 5912:Kahneman, Slovic & Tversky (1982) 5767: 5425: 5423: 5421: 4386:Superintelligence and the singularity 4200:Philosophy of artificial intelligence 3942:Philosophy of artificial intelligence 3881:(including curated datasets, such as 3549:Regulation of artificial intelligence 3539:reason, and autonomous capabilities. 2550:Artificial intelligence and copyright 2071:. This is particularly important for 2048:Artificial intelligence in healthcare 1886:general-purpose programming languages 1490:. These tools include models such as 1364:). Proofs can be structured as proof 1157: 669:safety and benefits of the technology 23474:Three-dimensional integrated circuit 22308:Energy consumption (Green computing) 22254: 22161:Generative adversarial network (GAN) 21252:Interactive evolutionary computation 21044:Interactive evolutionary computation 21039:Human-based evolutionary computation 21034:Evolutionary multimodal optimization 19279: 18680:, Noam Shazeer, Niki Parmar et al. " 18628:from the original on 19 October 2013 18589: 18038: 17550:from the original on 30 October 2015 17494: 17482:from the original on 15 October 2019 17458:from the original on 8 December 2019 17400:from the original on 29 January 2015 17388:Rawlinson, Kevin (29 January 2015). 17004:from the original on 12 January 2018 16911:from the original on 31 January 2021 16797:from the original on 4 December 2022 16650:from the original on 14 January 2018 16625:from the original on 4 February 2016 16596: 16545:from the original on 14 January 2018 16532: 16449:from the original on 30 October 2015 16254:from the original on 19 October 2021 16242:Kobielus, James (27 November 2019). 16229:from the original on 4 November 2021 16199:from the original on 17 October 2014 16166: 15939:"Robots and Artificial Intelligence" 15915: 15860:from the original on 30 October 2015 15578: 15519:from the original on 30 October 2015 15464:from the original on 30 October 2015 15342:Frank, Michael (22 September 2023). 14909:from the original on 12 January 2019 14718:from the original on 30 October 2015 14104:AI & ML in Fusion, video lecture 13955:from the original on 7 December 2017 13525: 13406: 13352: 13321: 13076: 12606: 12181:Computing machinery and intelligence 12103:. Oxford, England: Clarendon Press. 12012:from the original on 1 November 2023 11758:Regulation of AI to mitigate risks: 11645:Medicine, Health Care and Philosophy 11472:Brodsky, Sascha (19 December 2023). 11446:Heaven, Will Douglas (12 May 2023). 11357: 11258: 10848: 10828: 10770:51(3) Industrial Law Journal 511–559 10305: 10261: 10223: 10132: 10027: 10004: 9970:from the original on 5 January 2024. 9933:Hammond, George (27 December 2023). 9357:from the original on 9 December 2023 9189: 9097: 6982: 5663: 5232:approaches to AI were championed by 4849:Computing Machinery and Intelligence 4800:Poole, Mackworth & Goebel (1998) 4773:Poole, Mackworth & Goebel (1998) 4747: 4628:Do Androids Dream of Electric Sheep? 4044:networks"). This approach is mostly 3686:Computing Machinery and Intelligence 2235:are used. In contrast, LLMs such as 2198:developed increasingly generalistic 1884:were used in early AI research, but 1856:Hardware for artificial intelligence 1810:Current models and services include 1768:used for benchmark testing, such as 1711:, where a local set of neurons must 896:for all of these types of learning. 776:, the agent has a specific goal. In 23593:Future-oriented technology analysis 23333:Progress in artificial intelligence 22987:Distributed artificial intelligence 22266:ACM Computing Classification System 19291:Stanford Encyclopedia of Philosophy 19282:"Logic and Artificial Intelligence" 19272:Internet Encyclopedia of Philosophy 19156:from the original on 4 October 2013 19084:, 20 November 2023, pp. 20–26. 18577:from the original on 18 August 2020 18523:Williams, Rhiannon (28 June 2023), 18290:Vincent, James (15 November 2022). 18014:Thompson, Derek (23 January 2014). 17538:Sainato, Michael (19 August 2015). 17470: 17450:Robitzski, Dan (5 September 2018). 17270:from the original on 3 October 2018 17207: 17190:from the original on 17 August 2020 16992:Morgenstern, Michael (9 May 2015). 16669:, Dartmouth College, archived from 16528:from the original on 9 October 2022 16436: 16392:Laskowski, Nicole (November 2023). 15652: 14896: 14800:: Machine learning and human values 14581:European Journal of Risk Regulation 14570:from the original on 9 August 2007. 14514:Brooks, Rodney (10 November 2014). 13789:(5th ed.). Benjamin/Cummings. 12937:Physical symbol system hypothesis: 12586: 12330: 11702:. ahead-of-print (ahead-of-print). 11302: 11233:McMorrow, Ryan (19 December 2023). 11061: 10817:Arntz, Gregory & Zierahn (2016) 10273: 9851: 9753: 9217: 7996:, p. 187) (k-nearest neighbor) 7849:Poole, Mackworth & Goebel (1998 7795:Poole, Mackworth & Goebel (1998 7745:Poole, Mackworth & Goebel (1998 7593:Poole, Mackworth & Goebel (1998 7551:Poole, Mackworth & Goebel (1998 7438:Poole, Mackworth & Goebel (1998 7383:Poole, Mackworth & Goebel (1998 7175:Poole, Mackworth & Goebel (1998 7157:or informed searches (e.g., greedy 7129:Poole, Mackworth & Goebel (1998 7047:Poole, Mackworth & Goebel (1998 6752:Poole, Mackworth & Goebel (1998 6520:Poole, Mackworth & Goebel (1998 6225:Poole, Mackworth & Goebel (1998 6172:Poole, Mackworth & Goebel (1998 6145:Poole, Mackworth & Goebel (1998 6119:Poole, Mackworth & Goebel (1998 6068:Poole, Mackworth & Goebel (1998 5941:Poole, Mackworth & Goebel (1998 5834:Poole, Mackworth & Goebel (1998 5799:Poole, Mackworth & Goebel (1998 5710: 5657: 5608: 5508: 4705:Glossary of artificial intelligence 4696:Female gendering of AI technologies 4117: 3900:In the late teens and early 2020s, 3651:Timeline of artificial intelligence 3622:In November 2023, the first global 3494:tests projects in four main areas: 3229: 3015:generative pre-trained transformers 2933:Association for Computing Machinery 2495:AI applications for evacuation and 1781:Generative pre-trained transformers 1442:, including logic programming with 24: 24725:Statement on AI risk of extinction 22499:Integrated development environment 21290:Evolutionary Computation (journal) 18819:for such a purpose." (p. 82.) 18641: 18388:from the original on 24 April 2018 18265:Vincent, James (7 November 2019). 18245:Verma, Yugesh (25 December 2021). 18233:Valinsky, Jordan (11 April 2019), 18026:from the original on 24 April 2018 17972:Tao, Jianhua; Tan, Tieniu (2005). 17923:from the original on 26 April 2011 17776:from the original on 17 March 2019 17472:"Robots could demand legal rights" 17375:from the original on 23 March 2023 16437:Lee, Timothy B. (22 August 2014). 16379:from the original on 29 April 2019 16067:from the original on 15 March 2023 15893:"The Computational Theory of Mind" 14960:from the original on 14 March 2016 14610:Bushwick, Sophie (16 March 2023), 14250:from the original on 13 April 2018 13723:(4th ed.). Hoboken: Pearson. 13364:"AI Should Be Terrified of Humans" 13333:Thomson, Jonny (31 October 2022). 12688:from the original on 4 August 2020 12577:AI widely used in the late 1990s: 11517:Marshall, Matt (29 January 2024). 11491:Edwards, Benj (22 February 2024). 11079:from the original on 28 March 2023 10837:Arntz, Gregory & Zierahn (2016 9432: 9253: 9137:eleuther.ai. 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In 2019, 24781: 24780: 24472:Friendly artificial intelligence 24359: 24348: 24347: 23764: 23647: 23221: 23211: 23202: 23201: 22199: 22198: 22178: 20962: 20950: 18957:from the original on 5 June 2023 18696:Journal of Economic Perspectives 18648: 17413:Reisner, Alex (19 August 2023), 16850:The Knowledge Engineering Review 16167:Katz, Yarden (1 November 2012). 15924:from the original on 15 May 2007 15786:from the original on 31 May 2014 15684:"Here's where the A.I. jobs are" 15654:Government Accountability Office 15329:from the original on 12 May 2023 15263:10.5209/rev_TK.2015.v12.n2.49072 15042:Dockrill, Peter (27 June 2022), 14741:Journal of Consciousness Studies 14151:from the original on 27 May 2023 14091: 14015: 13585: 13555: 13460: 13434: 13400: 13381: 13295: 12963: 12882: 12857: 12825: 12751: 12669: 12507: 12348: 12284: 12268: 12131: 12117: 12046: 12024: 11994: 11947: 11885: 11870: 11752: 11730: 11687: 11632: 11591: 11573: 11555: 11529: 11510: 11484: 11465: 11439: 11413: 11387: 11278: 11110: 11091: 11030: 10986: 10921: 10906: 10875:Carter, Justin (11 April 2023). 10868: 10842: 10822: 10783: 10721: 10702: 10675: 10610: 10522: 10484: 10447: 10431: 10418: 10394: 10378: 10291: 10176: 10152:Hiller, Jennifer (1 July 2024). 10145: 10126: 10104: 10085: 10073:Calvert, Brian (28 March 2024). 10066: 10040: 10021: 10005:Fung, Brian (19 December 2023). 9998: 9974: 9956:Wong, Matteo (24 October 2023). 9949: 9926: 9903: 9845: 9819: 9672: 9633: 9597: 9574: 9548: 9521: 9486: 9460: 9426: 9400: 9314: 9281: 9247: 9176: 9167: 9152: 9140: 9125: 9076: 9061: 9035: 8992: 8958: 8932: 8877: 8851: 8815: 8789: 8755: 8705: 8691: 8677: 8620: 8527: 8508: 8482: 8436: 8422: 8397: 8243: 8181: 8161: 8141: 8108: 8019: 7967: 7941: 5293: 5281: 5264: 5251: 5223: 5207: 5162: 5146: 5130: 5113: 5104: 5091: 5082: 5065: 5056: 5049:Moritz Hardt (a director at the 5043: 5014: 4997: 4985: 4900: 4887: 4870: 4431: 4322:characterized this position as " 4240: 3947:Defining artificial intelligence 3501:the dignity of individual people 3398:Friendly artificial intelligence 2589:to those for whom it is clearly 2376: 2345:Military artificial intelligence 2125:, on 11 May 1997. In 2011, in a 1718: 1597:. Each pattern (also called an " 1512:are a tool that can be used for 1257:Another type of local search is 25431:Cellular and molecular biology 24896:Cybernetics in the Soviet Union 24360: 23370:Fourth-generation optical discs 23212: 22615:Computational complexity theory 21062:Cellular evolutionary algorithm 18510:from the original on 6 May 2018 18315:Vincent, James (3 April 2023). 18208:Valance, Christ (30 May 2023). 18072:Toews, Rob (3 September 2023). 17842:Simonite, Tom (31 March 2016). 17563:Sample, Ian (5 November 2017). 17285:Artificial General Intelligence 17135:Nicas, Jack (7 February 2018). 16666:AI@50: AI Past, Present, Future 15949:from the original on 1 May 2019 15805:IEEE Signal Processing Magazine 15759:. 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Specialized 1632:are also used as classifiers. 1468:conditional probability tables 804:inverse reinforcement learning 584:, perception, and support for 13: 1: 25594:Computational fields of study 23620:Technology in science fiction 22770:Multimedia information system 22755:Geographic information system 22745:Enterprise information system 22341:Computer systems organization 22156:Variational autoencoder (VAE) 22116:Long short-term memory (LSTM) 21383:Computational learning theory 21158:Bacterial Colony Optimization 19910:Hard problem of consciousness 19094:aced a test but showed that 18592:"ChatGPT Is Already Obsolete" 18555:10.1080/01900692.2018.1498103 17747:Behavioral and Brain Sciences 17096:, vol. 16, pp. 9–17 17092:(1995), "Eyes on the Prize", 16109:10.1126/science.185.4157.1124 15976:10.1080/21582041.2018.1563803 15216:Edwards, Benj (17 May 2023). 14635:. Christchurch, New Zealand. 14561:10.1016/S0921-8890(05)80025-9 14197:. 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Various AI models, such as 2800:Algorithmic bias and fairness 2479:Other industry-specific tasks 1705:Convolutional neural networks 1133: 1112:multimodal sentiment analysis 1022: 900:Computational learning theory 684:Reasoning and problem-solving 434:), in its broadest sense, is 24553:Future of Humanity Institute 23695: 23129:Computational social science 22717:Theoretical computer science 22537:Software development process 22313:Electronic design automation 22298:Very Large Scale Integration 22136:Convolutional neural network 18766:The New York Review of Books 18590:Wong, Matteo (19 May 2023), 18461:10.1126/science.291.5504.599 17945:Stanford University (2023). 17837:, New York: Harper & Row 17740:"Minds, Brains and Programs" 17659:10.1016/j.neunet.2014.09.003 17351:10.1016/j.inffus.2017.02.003 17200:Presidential Address to the 17074:10.1016/j.imavis.2007.08.013 16965:. Harvard University Press. 16582:10.1080/09540090310001655110 15937:IGM Chicago (30 June 2017). 15598:, MIT Press., archived from 14532:"Elephants Don't Play Chess" 14075:. New York: Macmillan/SAMS. 14030:. New York, NY: BasicBooks. 13996:; Ciaramella, Marco (2024). 13522:'s "intelligence explosion" 13097:, pp. 421–424, 486–489) 13013:Dreyfus & Dreyfus (1986) 12387:, pp. 145–162, 197–203) 12381:, pp. 327–335, 434–435) 11877:VOA News (25 October 2023). 11740:. UK Government. 10 May 2024 10617:Ropek, Lucas (21 May 2024). 9697:10.1016/j.autcon.2020.103140 7923:; Ciaramella, Marco (2024). 7655:Stochastic temporal models: 6727:Jordan & Mitchell (2015) 6578:, pp. 653) (definition) 6534:, chpt. 3.3, 10.3, 17.5, 20) 6227:, pp. 248–256, 323–335) 5902:Dreyfus & Dreyfus (1986) 5438:, pp. 32–33, 1020–1021) 5396:10.1016/j.bushor.2018.08.004 5172:'s checkers program for the 4729:Weak artificial intelligence 4660:Behavior selection algorithm 4647: – International treaty 4616:A.I. Artificial Intelligence 4403:reprogram and improve itself 4286:Computational theory of mind 4177:Weak artificial intelligence 3094:AI tools make it easier for 3029:Bad actors and weaponized AI 2316:to define mathematic tasks. 2166:in a match with Go champion 2146:, defeated the two greatest 2110:Game artificial intelligence 1379:are labelled by premises or 929:. Specific problems include 764:Planning and decision-making 7: 24770:Artificial Intelligence Act 24764:Do You Trust This Computer? 24105:Vision-guided robot systems 22952:Natural language processing 22740:Information storage systems 22131:Multilayer perceptron (MLP) 21153:Particle swarm optimization 21097:Gene expression programming 20487:Hypothetico-deductive model 20462:Deductive-nomological model 20447:Constructivist epistemology 18801:natural-language processing 18163:Nature Machine Intelligence 18045:. New York: Facts on File. 17700:KI – Künstliche Intelligenz 17293:10.1007/978-3-540-68677-4_1 16663:Maker, Meg Houston (2006), 16491:. Science Research Council. 15964:Contemporary Social Science 15737:Harari, Yuval Noah (2023). 15536:Software studies: a lexicon 15189:. 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Harmondsworth: Penguin. 18421:New horizons in psychology 18405:. Oxford University Press. 18175:10.1038/s42256-022-00465-9 17795:Mind, language and society 17062:Image and Vision Computing 16505:(Unpublished manuscript), 15916:Howe, J. (November 1994). 15112:; Dreyfus, Stuart (1986). 14484:. Oxford University Press. 13578:Russell & Norvig (2021 13504:Russell & Norvig (2021 13302:Leith, Sam (7 July 2022). 13276:Russell & Norvig (2021 13113:Russell & Norvig (2021 13033:Russell & Norvig (2021 12956:Russell & Norvig (2021 12676:Sagar, Ram (3 June 2020). 12662:Russell & Norvig (2021 12625:Russell & Norvig (2021 12558:Russell & Norvig (2021 12522:Russell & Norvig (2021 12361:Russell & Norvig (2021 12213:Russell & Norvig (2021 12153:Russell & Norvig (2021 12099:Copeland, J., ed. (2004). 11822:Stanford University (2023) 11708:10.1108/IJOES-05-2023-0107 11657:10.1007/s11019-020-09948-1 11098:Pittis, Don (4 May 2023). 10533:Russell & Norvig (2021 10438:Russell & Norvig (2021 10401:Russell & Norvig (2021 10389:Russell & Norvig (2021 10361:Larson & Angwin (2016) 10310:Russell & Norvig (2021 10028:Metz, Cade (5 July 2023). 9959:"The Future of AI Is GOMA" 9832:Cornell University Library 9685:Automation in Construction 9658:10.1007/s10694-021-01157-3 9021:10.1038/s41586-021-04357-7 8731:10.1038/s41589-024-01580-x 8653:10.1038/s41586-021-03819-2 8605:10.3389/fsens.2023.1294721 8430:"Explained: Generative AI" 8256:Russell & Norvig (2021 8217:Russell & Norvig (2021 8194:Russell & Norvig (2021 8174:Russell & Norvig (2021 8154:Russell & Norvig (2021 8121:Russell & Norvig (2021 8089:Russell & Norvig (2021 8058:Russell & Norvig (2021 8032:Russell & Norvig (2021 7988:Russell & Norvig (2021 7954:Russell & Norvig (2021 7906:Russell & Norvig (2021 7885:Russell & Norvig (2021 7843:Russell & Norvig (2021 7789:Russell & Norvig (2021 7739:Russell & Norvig (2021 7719:Russell & Norvig (2021 7695:Russell & Norvig (2021 7683:Russell & Norvig (2021 7671:Russell & Norvig (2021 7659:Russell & Norvig (2021 7637:Russell & Norvig (2021 7613:Russell & Norvig (2021 7587:Russell & Norvig (2021 7545:Russell & Norvig (2021 7526:Scientific American (1999) 7520:Russell & Norvig (2021 7474:Russell & Norvig (2021 7432:Russell & Norvig (2021 7415:Russell & Norvig (2021 7377:Russell & Norvig (2021 7341:Russell & Norvig (2021 7309:Russell & Norvig (2021 7277:Russell & Norvig (2021 7231:Russell & Norvig (2021 7207:Russell & Norvig (2021 7169:Russell & Norvig (2021 7123:Russell & Norvig (2021 7079:Russell & Norvig (2021 7041:Russell & Norvig (2021 6885:Russell & Norvig (2021 6830:Cambria & White (2014) 6824:Russell & Norvig (2021 6779:Russell & Norvig (2021 6746:Russell & Norvig (2021 6721:Russell & Norvig (2021 6671:Russell & Norvig (2021 6645:Russell & Norvig (2021 6625:Russell & Norvig (2021 6619:Russell & Norvig (2021 6592:Russell & Norvig (2021 6582:Russell & Norvig (2021 6576:Russell & Norvig (2021 6514:Russell & Norvig (2021 6494:Russell & Norvig (2021 6474:Russell & Norvig (2021 6454:Russell & Norvig (2021 6434:Russell & Norvig (2021 6422:Russell & Norvig (2021 6405:Russell & Norvig (2021 6388:Russell & Norvig (2021 6368:Russell & Norvig (2021 6344:Russell & Norvig (2021 6284:Russell & Norvig (2021 6219:Russell & Norvig (2021 6166:Russell & Norvig (2021 6113:Russell & Norvig (2021 6062:Russell & Norvig (2021 5967:Smoliar & Zhang (1994) 5935:Russell & Norvig (2021 5907:Wason & Shapiro (1966) 5875:Russell & Norvig (2021 5828:Russell & Norvig (2021 5789:Russell & Norvig (2021 5783:Russell & Norvig (2021 5749:Russell & Norvig (2021 5693:Russell & Norvig (2021 5652:Russell & Norvig (2021 5603:Russell & Norvig (2021 5555:Russell & Norvig (2021 5497:Russell & Norvig (2021 5476:Russell & Norvig (2021 5436:Russell & Norvig (2021 4723:Robotic process automation 4711:Intelligence amplification 4678:Computational intelligence 4527:in these works began with 4491: 4283: 4267:is easy to explain, human 4244: 4197: 4174: 4147: 4121: 4060:Symbolic AI and its limits 3950: 3939: 3912:, beat the world champion 3755:artificial neural networks 3648: 3642: 3638: 3546: 3387: 3233: 3180:Technological unemployment 3173: 3170:Technological unemployment 3156:facial recognition systems 3032: 2942: 2803: 2745: 2700: 2543: 2515: 2380: 2342: 2322: 2107: 2045: 1899: 1849: 1660:, which loosely model the 1636:Artificial neural networks 1177:Simple exhaustive searches 1101:human–computer interaction 1093:feeling, emotion, and mood 894:artificial neural networks 606:artificial neural networks 460:perceive their environment 171:Hybrid intelligent systems 93:Recursive self-improvement 75: 29: 25302: 24959: 24833: 24778: 24717: 24596: 24523:Alignment Research Center 24515: 24507:Technological singularity 24457:Effective accelerationism 24419: 24343: 24313:Workplace robotics safety 24295: 24189: 24113: 24076: 24031: 23929: 23773: 23762: 23703: 23643: 23608:Technological singularity 23568:Technological convergence 23486: 23282: 23275: 23197: 23134:Computational engineering 23109:Computational mathematics 23086: 23033: 22995: 22942: 22904: 22866: 22808: 22725: 22671: 22633: 22585: 22522: 22455: 22419: 22376: 22340: 22273: 22262: 22174: 22088: 22032: 21961: 21894: 21766: 21666: 21659: 21613: 21577: 21540:Artificial neural network 21520: 21396: 21363:Automatic differentiation 21336: 21280: 21199: 21166: 21125: 21052: 21016: 20941: 20773: 20675: 20605: 20548:Semantic view of theories 20467:Epistemological anarchism 20419: 20404:dependent and independent 20141: 20073: 20040: 19867: 19737: 19632:Gottfried Wilhelm Leibniz 19622:David Lewis (philosopher) 19467: 19359: 19319: 19267:"Artificial Intelligence" 19147:10.1016/j.joi.2011.06.002 18785:Hughes-Castleberry, Kenna 18682:Attention is all you need 18611:Global Catastrophic Risks 18401:Wallach, Wendell (2010). 17798:. New York: Basic Books. 17759:10.1017/S0140525X00005756 17712:10.1007/s13218-012-0198-z 17515:. United States: Viking. 17253:10.1109/tamd.2009.2039057 17215:. National Academy Press. 17114:Communications of the ACM 16862:10.1017/S0269888905000408 16833:10.1007/s10676-007-9138-2 16355:10.1007/s10994-011-5242-y 15275:. New York: Grove Press. 15151:Darwin among the Machines 14930:Deng, L.; Yu, D. (2014). 14845:10.1109/cvpr.2012.6248110 14629:. Letters to the Editor. 14575:Buiten, Miriam C (2019). 14224:10.1109/tamd.2009.2021702 14178:10.1007/s00146-007-0094-5 13498:technological singularity 12946:Historical significance: 12082:Russell & Norvig 2021 11617:10.1162/99608f92.8cd550d1 10957:Russell & Norvig 2021 10833:Frey & Osborne (2017) 9898:Alter & Harris (2023) 9534:(4th ed.). Pearson. 9290:"Executive Order N-12-23" 9161:7 Best AI for Math Tools. 8552:10.7861/futurehosp.6-2-94 8168:Recurrent neural networks 8083:automatic differentiation 7689:Dynamic Bayesian networks 7627:Markov decision processes 7522:, pp. 214, 255, 459) 6358:Automated decision making 5463:Beal & Winston (2009) 5036:) and Sam Corbett-Davis ( 5032:), Cynthia Chouldechova ( 5028:), Sendhil Mullainathan ( 4878:conditionally independent 4472:Darwin among the Machines 4380: 3871:graphics processing units 3831:successfully showed that 3770:fifth generation computer 3425:Other approaches include 3265:paperclip factory manager 3259:argued that if one gives 3096:authoritarian governments 3053:authoritarian governments 2511: 2449: 2140:question answering system 2052:The application of AI in 1892:have become predominant. 1862:graphics processing units 1693:Recurrent neural networks 1542:dynamic Bayesian networks 1492:Markov decision processes 1446:, are designed to handle 1238:mathematical optimization 995:encoding their meaning), 970:word-sense disambiguation 778:automated decision-making 598:mathematical optimization 25049:Charles Geoffrey Vickers 24936:Second-order cybernetics 24558:Future of Life Institute 24477:Instrumental convergence 23380:Holographic data storage 23144:Computational healthcare 23139:Differentiable computing 23058:Graphics processing unit 22484:Domain-specific language 22353:Computational complexity 21368:Neuromorphic engineering 21331:Differentiable computing 21082:Evolutionary programming 21029:Evolutionary data mining 21010:Evolutionary computation 20290:Intertheoretic reduction 20279:Ignoramus et ignorabimus 20256:Functional contextualism 18419:. In Foss, B. M. (ed.). 18251:Analytics India Magazine 18111:10.1093/mind/LIX.236.433 16994:"Automation and anxiety" 15825:10.1109/msp.2012.2205597 15638:10.1609/aimag.v38i3.2741 15271:Fearn, Nicholas (2007). 15181:Edelson, Edward (1991). 14775:10.1017/CBO9780511975837 14689:10.1109/MCI.2014.2307227 14296:IEEE Intelligent Systems 13974:Ertel, Wolfgang (2017). 12941:Newell & Simon (1976 12682:Analytics India Magazine 12479:Lungarella et al. (2003) 12277:, p. 96) quoted in 10790:Ford & Colvin (2015) 10218:Taylor & Hern (2023) 7976:learning models such as 7875:Bayesian decision theory 7607:Information value theory 7271:Evolutionary computation 6448:Information value theory 5925:Knowledge representation 5573:Fifth Generation Project 5322:thinking (as opposed to 5240:and went by many names: 4274:know what red looks like 4204:Artificial consciousness 3997:Aeronautical engineering 3688:', which introduced the 3553:Regulation of algorithms 3035:Lethal autonomous weapon 2949:Algorithmic transparency 2922:anti-discrimination laws 2653:Dominance by tech giants 2162:won 4 out of 5 games of 2103: 2036:Chief automation officer 1567:Expectation–maximization 1488:information value theory 1306:knowledge representation 1291: 1259:evolutionary computation 904:computational complexity 841:, or it can be learned. 808:Information value theory 725:Knowledge representation 712:Knowledge representation 674: 649:transformer architecture 570:knowledge representation 458:that enable machines to 295:Artificial consciousness 27:Intelligence of machines 25589:Artificial intelligence 25327:Artificial intelligence 24911:Engineering cybernetics 24841:Artificial intelligence 24413:artificial intelligence 24161:Human–robot interaction 23573:Technological evolution 23546:Exploratory engineering 23375:3D optical data storage 23308:Artificial intelligence 23119:Computational chemistry 23053:Photograph manipulation 22944:Artificial intelligence 22760:Decision support system 22141:Residual neural network 21557:Artificial Intelligence 21212:Artificial intelligence 21138:Ant colony optimization 20775:Philosophers of science 20553:Scientific essentialism 20502:Model-dependent realism 20437:Constructive empiricism 20330:Evidence-based practice 19760:Eliminative materialism 19364:Artificial intelligence 19299:Artificial Intelligence 19135:Journal of Informetrics 18744:New York Times Magazine 18710:Oxford University Press 18666:Artificial intelligence 18376:Waddell, Kaveh (2018). 18130:. Paris: UNESCO. 2021. 17617:10.1023/A:1013298507114 17425:Roberts, Jacob (2016). 17142:The Wall Street Journal 17038:10.1145/2639475.2639478 16777:Artificial Intelligence 16316:The Singularity is Near 16222:The Wall Street Journal 16050:Thinking, Fast and Slow 16021:10.1126/science.aaa8415 15433:Science Fiction Studies 15094:. New York: MIT Press. 15091:What Computers Can't Do 15003:San Francisco Chronicle 14979:Consciousness Explained 14897:CNA (12 January 2019). 13751:Artificial Intelligence 13091:, the historic debate: 13002:Dreyfus' critique of AI 12293:, p. 2) quoted in 11762:Berryhill et al. (2019) 10349:Grant & Hill (2023) 9227:Slyusar, Vadym (2019). 8910:10.1126/science.aay2400 8719:Nature Chemical Biology 7982:support vector machines 6468:Markov decision process 6418:Uncertain preferences: 6209:closed world assumption 6105:(including solving the 5869:combinatorial explosion 5793:constraint satisfaction 5372:CNN.com (July 26, 2006) 4625:, as well as the novel 4576:(1951) and Bishop from 4144:Soft vs. hard computing 3402:Artificial moral agents 3077:kill an innocent person 2593:and a violation of the 2403:, often in response to 1870:central processing unit 1589:are functions that use 1282:ant colony optimization 1142:Search and optimization 902:can assess learners by 819:Markov decision process 608:, and methods based on 428:Artificial intelligence 166:Evolutionary algorithms 56:Artificial intelligence 25557:Structural engineering 25497:Mechanical engineering 25470:Western and South Asia 25234:Walter Bradford Cannon 25124:Ludwig von Bertalanffy 24979:Alfred Radcliffe-Brown 24926:Management cybernetics 24851:Biomedical cybernetics 24846:Biological cybernetics 24482:Intelligence explosion 23583:Technology forecasting 23578:Technological paradigm 23551:Proactionary principle 23469:Software-defined radio 23184:Educational technology 23015:Reinforcement learning 22765:Process control system 22663:Computational geometry 22653:Algorithmic efficiency 22648:Analysis of algorithms 22303:Systems on Chip (SoCs) 21207:Artificial development 21077:Differential evolution 21024:Evolutionary algorithm 20858:Alfred North Whitehead 20848:Charles Sanders Peirce 20012:Propositional attitude 20007:Problem of other minds 19915:Hypostatic abstraction 19098:cannot be measured by 18842:Johnston, John (2008) 18413:; Shapiro, D. (1966). 17232:Oudeyer, P-Y. (2010). 16465:; Guha, R. V. (1989). 15891:Horst, Steven (2005). 15154:. Allan Lane Science. 14829:. pp. 3642–3649. 14489:Bostrom, Nick (2015). 14244:McKinsey & Company 13494:Intelligence explosion 12707:DiFeliciantonio (2023) 12468:Developmental robotics 12034:. Reuters. 21 May 2024 8725:(5). Nature: 634–645. 8026:Naive Bayes classifier 7547:, Chpt. 12–18 and 20), 6639:Reinforcement learning 6266:Lenat & Guha (1989 5955:, chpt. 17.1–17.4, 18) 5518:McCarthy et al. (1955) 5246:Developmental robotics 4590:Three Laws of Robotics 4558:spaceship, as well as 4513: 4411:intelligence explosion 4373:, which could lead to 4265:information processing 3985: 3965:Synthetic intelligence 3570: 3536:UK AI Safety Institute 3120:Recommendation systems 2931:(ACM FAccT 2022), the 2392: 2200:reinforcement learning 2090:structure of a protein 2079:development which use 1920:recommendation systems 1775: 1727: 1697:Long short term memory 1653: 1626:naive Bayes classifier 1622:support vector machine 1577: 1470: 1466:, with the associated 1230: 1085: 968:, had difficulty with 943:information extraction 882:reinforcement learning 721: 559:not labeled AI anymore 483:recommendation systems 67: 25422:Environmental science 25307:Aerospace engineering 25194:Anthony Stafford Beer 25029:Ernst von Glasersfeld 24437:AI capability control 24267:Starship Technologies 23509:Disruptive innovation 23269:Emerging technologies 23154:Electronic publishing 23124:Computational biology 23114:Computational physics 23010:Unsupervised learning 22924:Distributed computing 22800:Information retrieval 22707:Mathematical analysis 22697:Mathematical software 22587:Theory of computation 22552:Software construction 22542:Requirements analysis 22420:Software organization 22348:Computer architecture 22318:Hardware acceleration 22283:Printed circuit board 22096:Neural Turing machine 21684:Human image synthesis 21242:Fitness approximation 21227:Evolutionary robotics 21168:Metaheuristic methods 20957:Philosophy portal 20708:Hard and soft science 20703:Faith and rationality 20572:Scientific skepticism 20352:Scientific Revolution 20135:Philosophy of science 20083:Philosophers category 19987:Mental representation 19750:Biological naturalism 19637:Maurice Merleau-Ponty 19612:Frank Cameron Jackson 18602:Yudkowsky, E (2008), 18530:MIT Technology Review 17938:IRE Convention Record 17848:MIT Technology Review 17833:Simon, H. A. (1965), 17316:The Language Instinct 17127:10.1145/360018.360022 16877:McGaughey, E (2022), 16334:Langley, Pat (2011). 15656:(13 September 2022). 15118:. Oxford: Blackwell. 14982:. The Penguin Press. 14870:Clark, Jack (2015b). 14798:The Alignment Problem 14099:AI & ML in Fusion 13779:Stubblefield, William 13506:, pp. 1004–1005) 12869:carnegieendowment.org 12838:Google Cloud Platform 11452:MIT Technology Review 10444:, pp. 40, 80–81) 10415:, pp. 39–40, 65) 10298:Berdahl et al. (2023) 10081:. New York, New York. 9505:10.1017/9781009258227 7809:, chpt. 19.4 & 7) 7803:, pp. ~363–379), 7504:10.1145/872734.806939 7476:, §7.5.2, §9.2, §9.5) 7369:and features such as 6621:, §19.2) (Definition) 6594:, pp. 846–860) ( 6584:, pp. 738–740) ( 6570:Unsupervised learning 6288:qualification problem 5929:knowledge engineering 5824:Uncertain reasoning: 5257:Matteo Wong wrote in 5030:University of Chicago 4546:2001: A Space Odyssey 4501: 4375:large-scale suffering 4330:AI welfare and rights 4269:subjective experience 4171:Narrow vs. general AI 3983: 3879:large amounts of data 3827:and others. In 1990, 3662:theory of computation 3564: 3492:Alan Turing Institute 3122:can precisely target 2826:people (as it can in 2707:In January 2024, the 2544:Further information: 2540:Privacy and copyright 2390: 2202:models, such as with 2184:imperfect-information 2170:, becoming the first 1878:programming languages 1785:large language models 1726: 1643: 1565: 1461: 1391:from the premises or 1220: 1191:or never completes. " 1080: 956:Early work, based on 947:information retrieval 863:Unsupervised learning 758:knowledge acquisition 729:knowledge engineering 719: 620:. AI also draws upon 545:play and analysis in 66: 25619:Intelligence by type 25224:Valentin Braitenberg 25104:Jay Wright Forrester 24528:Center for AI Safety 24217:Energid Technologies 23556:Technological change 23499:Collingridge dilemma 23296:Ambient intelligence 22914:Concurrent computing 22886:Ubiquitous computing 22858:Application security 22853:Information security 22682:Discrete mathematics 22658:Randomized algorithm 22610:Computability theory 22595:Model of computation 22567:Software maintenance 22562:Software engineering 22524:Software development 22474:Programming language 22469:Programming paradigm 22386:Network architecture 22187:Computer programming 22166:Graph neural network 21741:Text-to-video models 21719:Text-to-image models 21567:Large language model 21552:Scientific computing 21358:Statistical manifold 21353:Information geometry 20683:Criticism of science 20558:Scientific formalism 20442:Constructive realism 20347:Scientific pluralism 20320:Problem of induction 19765:Emergent materialism 19409:McCarthy 91 function 19280:Thomason, Richmond. 18494:– via msu.edu. 18039:Thro, Ellen (1993). 17478:. 21 December 2006. 16889:10.2139/ssrn.3044448 16714:, Simon and Schuster 16608:on 29 November 2014. 16533:Lohr, Steve (2017). 16511:10.2139/ssrn.1736283 14522:on 12 November 2014. 12125:"Google books ngram" 10754:Urbina et al. (2022) 8592:Frontiers in Sensors 8270:Deng & Yu (2014) 8097:, pp. 467–474), 7851:, pp. 424–433), 7797:, pp. 361–381), 7747:, pp. 361–381), 7553:, pp. 345–395), 7385:, pp. 268–275), 7109:breadth first search 6993:Tao & Tan (2005) 6941:Challa et al. (2011) 6677:The Economist (2016) 6274:, pp. 113–114), 6201:non-monotonic logics 6121:, pp. 281–298), 6076:, pp. 248–258), 6070:, pp. 174–177), 6064:, §10.2 & 10.5), 5949:, pp. 227–243), 5270:Jack Clark wrote in 5097:Sometimes called a " 4952:John Joseph Hopfield 4672:Case-based reasoning 3922:large language model 3716:general intelligence 3130:for maximum effect. 2959:deep neural networks 2953:Right to explanation 2939:Lack of transparency 2683:cloud infrastructure 2610:differential privacy 2469:game-playing systems 2395:In the early 2020s, 2178:. Then, in 2017, it 1984:Microsoft Translator 1940:targeted advertising 1754:image classification 1553:hidden Markov models 1440:Non-monotonic logics 1428:symbolic programming 1185:astronomical numbers 1118:General intelligence 1110:and, more recently, 1095:. For example, some 1051:image classification 1034:, sonar, radar, and 736:), and other areas. 636:, and other fields. 590:General intelligence 108:General game playing 25249:William Grey Walter 25189:Sergei P. Kurdyumov 25149:N. Katherine Hayles 24931:Medical cybernetics 24891:Conversation theory 24743:Our Final Invention 24308:Powered exoskeleton 23613:Technology scouting 23588:Accelerating change 23318:Machine translation 23189:Document management 23179:Operations research 23104:Enterprise software 23020:Multi-task learning 23005:Supervised learning 22727:Information systems 22557:Software deployment 22514:Software repository 22368:Real-time computing 21533:In-context learning 21373:Pattern recognition 21186:Gaussian adaptation 21092:Genetic programming 20750:Rhetoric of science 20688:Descriptive science 20432:Confirmation holism 20325:Scientific evidence 20285:Inductive reasoning 20214:Demarcation problem 19962:Language of thought 19712:Ludwig Wittgenstein 19542:Patricia Churchland 19399:McCarthy evaluation 19305:, 8 December 2005). 19195:10.1038/nature16961 19187:2016Natur.529..484S 19105:Scientific American 19036:10.1038/nature14236 19028:2015Natur.518..529M 18984:Scientific American 18972:Scientific American 18935:10.1038/nature14539 18927:2015Natur.521..436L 18868:2021Natur.596..583J 18796:Scientific American 18734:AI machine-learning 18619:2008gcr..book..303Y 18506:. 21 October 1999. 18504:Scientific American 18357:1993vise.nasa...11V 17683:Schmidhuber, Jürgen 17498:The Guardian Weekly 16725:plugandpray-film.de 16719:Maschafilm (2010). 16711:The Society of Mind 16285:10.1197/jamia.M2055 16215:(1 November 2021). 16101:1974Sci...185.1124T 16013:2015Sci...349..255J 15846:The Washington Post 15817:2012ISPM...29...82H 14616:Scientific American 14308:10.1109/MIS.2009.75 14109:2 July 2023 at the 13994:Ciaramella, Alberto 13827:. Morgan Kaufmann. 13642:, pp. 340–400. 13290:, pp. 269–271) 13284:, pp. 443–445) 13089:Neats vs. scruffies 13035:, pp. 981–982) 13029:, pp. 211–239) 13023:, pp. 120–132) 12990:, pp. 190–191) 12928:, pp. 112–117. 12595:, pp. 189–201) 12589:, pp. 216–222) 12566:, pp. 486–487) 12518:, pp. 214–215) 12484:Asada et al. 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(2017) 6977:Affective computing 6955:, pp. 931–938. 6931:, pp. 899–901. 6919:, pp. 895–899. 6907:, pp. 849–850. 6857:, pp. 875–878. 6795:, pp. 856–858. 6781:, pp. 849–850) 6760:, pp. 591–632) 6723:, pp. 672–674) 6653:, pp. 442–449) 6613:Supervised learning 6528:, pp. 385–542) 6522:, pp. 397–438) 6316:, pp. 204–208. 6233:, pp. 335–363) 6174:, pp. 275–277) 6147:, pp. 335–337) 5842:, pp. 333–381) 5836:, pp. 345–395) 5807:, chpt. 3, 4, 6, 8) 5801:, chpt. 2, 3, 7, 9) 5719:, pp. 301–318) 5713:, pp. 214–216) 5707:, pp. 209–210) 5701:, pp. 430–435) 5671:, pp. 189–201) 5660:, pp. 212–213) 5648:, pp. 115–117) 5641:Mansfield Amendment 5617:, pp. 235–248) 5611:, pp. 210–211) 5593:, pp. 426–441) 5539:, pp. 243–252) 5511:, pp. 200–201) 5505:, pp. 111–136) 4908:Warren S. McCulloch 4684:Digital immortality 4601:the ability to feel 4124:Neats and scruffies 3888:In 2016, issues of 3805:pattern recognition 3733:Sir James Lighthill 3592:Daniel Huttenlocher 3525:Asilomar Conference 3422:symposium in 2005. 3369:Juergen Schmidhuber 3362:the joint statement 3023:dictionary learning 2773:conspiracy theories 2761:recommender systems 2735:Wall Street Journal 2546:Information privacy 2473:industrial robotics 2465:autonomous vehicles 2430:sparked a trend of 2418:generators such as 2355:autonomous vehicles 2351:command and control 2186:games, such as the 2094:Parkinson's disease 2042:Health and medicine 1964:autonomous vehicles 1860:In the late 2010s, 1595:supervised learning 1444:negation as failure 1350:Deductive reasoning 1314:logical connectives 1310:propositional logic 1171:means-ends analysis 1089:Affective computing 1073:Social intelligence 1045:The field includes 939:machine translation 867:Supervised learning 665:regulatory policies 614:operations research 515:autonomous vehicles 260:Machine translation 176:Systems integration 113:Knowledge reasoning 50:Part of a series on 32:AI (disambiguation) 25229:William Ross Ashby 25154:Natalia Bekhtereva 25129:Maleyka Abbaszadeh 25069:Heinz von Foerster 24994:Buckminster Fuller 24921:Information theory 24871:Catastrophe theory 24277:Universal Robotics 24252:Intuitive Surgical 24242:Harvest Automation 24207:Barrett Technology 23989:Robotic spacecraft 23835:Audio-Animatronics 23630:Technology roadmap 23343:Speech recognition 23328:Mobile translation 23301:Internet of things 22972:Search methodology 22919:Parallel computing 22876:Interaction design 22785:Computing platform 22712:Numerical analysis 22702:Information theory 22494:Software framework 22457:Software notations 22396:Network components 22293:Integrated circuit 22126:Echo state network 22014:Jürgen Schmidhuber 21709:Facial recognition 21704:Speech recognition 21614:Software libraries 21133:Swarm intelligence 21126:Related techniques 21102:Evolution strategy 21072:Cultural algorithm 20969:Science portal 20898:Carl Gustav Hempel 20853:Wilhelm Windelband 20740:Questionable cause 20563:Scientific realism 20384:Underdetermination 20219:Empirical evidence 20209:Creative synthesis 19790:Neurophenomenology 19461:Philosophy of mind 19414:Situation calculus 19404:McCarthy Formalism 19384:Garbage collection 19374:Dartmouth workshop 17933:Later published as 17339:Information Fusion 16560:Connection Science 16539:The New York Times 16469:. Addison-Wesley. 15943:www.igmchicago.org 15708:Harari, Yuval Noah 15675:The New York Times 15487:The New York Times 15185:The Nervous System 14951:10.1561/2000000039 14594:10.1017/err.2019.8 14402:. Harcourt Books. 14122:The New York Times 14051:Machines Who Think 13855:Russell, Stuart J. 13711:Russell, Stuart J. 12627:, pp. 14, 27) 12524:, pp. 24, 26) 12474:Weng et al. (2001) 12215:, pp. 2, 984) 12143:, pp. 51–107) 11982:on 1 November 2023 11930:Kasperowicz (2023) 11899:. 5 September 2024 11321:, pp. 67, 73. 10901:Morgenstern (2015) 10805:IGM Chicago (2017) 10715:The New York Times 10111:Davenport, Carly. 10034:The New York Times 9350:The New York Times 9111:The New York Times 8946:. 23 December 2020 8830:The New York Times 8432:. 9 November 2023. 8392:Schmidhuber (2022) 8380:Schmidhuber (2022) 8363:Schmidhuber (2022) 8351:Schmidhuber (2022) 8237:Schmidhuber (2015) 7978:K-nearest neighbor 7783:Bayesian inference 7759:, chpt. 19.3–19.4) 7440:, pp. ~46–52) 7391:, pp. 50–62), 7201:Adversarial search 7137:, pp. 79–121) 7117:state space search 7113:depth-first search 7073:State space search 6998:Scassellati (2002) 6754:, pp. 91–104) 6382:Classical planning 6338:Automated planning 6095:Situation calculus 6044:description logics 5545:, pp. 52–107) 5491:Dartmouth workshop 5368:2008-02-19 at the 5026:Cornell University 4924:Roger David Joseph 4690:Emergent algorithm 4548:(both 1968), with 4539:Arthur C. Clarke's 4514: 4300:philosophy of mind 4210:philosophy of mind 4160:genetic algorithms 4102:. Critics such as 3986: 3961:Dartmouth workshop 3670:information theory 3571: 3202:Carl Benedikt Frey 2999:Multitask learning 2857:On June 28, 2015, 2661:companies such as 2575:speech recognition 2457:virtual assistants 2393: 2359:target acquisition 2134:exhibition match, 2077:tissue engineering 1992:facial recognition 1952:virtual assistants 1746:speech recognition 1728: 1713:identify an "edge" 1658:artificial neurons 1654: 1614:K-nearest neighbor 1578: 1518:Bayesian inference 1471: 1276:(inspired by bird 1270:swarm intelligence 1231: 1199:Adversarial search 1163:State space search 1158:State space search 1148:state space search 1128:human intelligence 1108:sentiment analysis 1097:virtual assistants 1086: 1067:robotic perception 1059:object recognition 1055:facial recognition 1047:speech recognition 1028:Machine perception 978:Margaret Masterman 962:generative grammar 951:question answering 931:speech recognition 797:classical planning 774:automated planning 722: 535:Apple Intelligence 475:web search engines 471:applications of AI 469:Some high-profile 68: 25576: 25575: 25570: 25569: 25552:Scientific naming 25542:Quantum computing 25372:Computer hardware 25367:Clinical research 25362:Civil engineering 25257: 25256: 25179:Ranulph Glanville 25094:Jakob von Uexküll 25074:Humberto Maturana 25034:Francis Heylighen 24792: 24791: 24709:Eliezer Yudkowsky 24684:Stuart J. Russell 24502:Superintelligence 24375: 24374: 24318:Robotic tech vest 24247:Honeybee Robotics 24063:Electric unicycle 24016:remotely-operated 23663: 23662: 23482: 23481: 23452:Optical computing 23235: 23234: 23164:Electronic voting 23094:Quantum Computing 23087:Applied computing 23073:Image compression 22843:Hardware security 22833:Security services 22790:Digital marketing 22577:Open-source model 22489:Modeling language 22401:Network scheduler 22222: 22221: 21984:Stephen Grossberg 21957: 21956: 21298: 21297: 21272:Program synthesis 21247:Genetic operators 21237:Fitness landscape 21191:Memetic algorithm 21176:Firefly algorithm 21087:Genetic algorithm 20976: 20975: 20818: 20817: 20730:Normative science 20587:Uniformitarianism 20342:Scientific method 20236:Explanatory power 20101: 20100: 19997:Mind–body problem 19895:Cognitive closure 19859:Substance dualism 19477:G. E. M. Anscombe 19427: 19426: 19181:(7587): 484–489. 19022:(7540): 529–533. 18921:(7553): 436–444. 18862:(7873): 583–589. 18823:Immerwahr, Daniel 18809:ancient languages 18757:Kevin J. Mitchell 18732:writes: "Current 18455:(5504): 599–600. 18363:on 1 January 2007 18137:978-92-3-100450-6 18052:978-0-8160-2628-9 17991:978-3-540-29621-8 17889:10.1109/93.311653 17805:978-0-465-04521-1 17605:Autonomous Robots 17522:978-0-525-55861-3 17501:. pp. 42–43. 17437:on 19 August 2018 17326:978-0-06-133646-1 17302:978-3-540-23733-4 16972:978-0-674-57616-2 16934:978-1-4614-6940-7 16759:on 26 August 2007 16745:Rochester, Nathan 16673:on 8 October 2008 16476:978-0-201-51752-1 16326:978-0-670-03384-3 16319:. Penguin Books. 16118:978-0-521-28414-1 16060:978-1-4299-6935-2 16007:(6245): 255–260. 15766:978-0-262-08153-5 15551:978-1-4356-4787-9 15315:Fox News (2023). 15282:978-0-8021-1839-4 15196:978-0-7910-0464-7 15161:978-0-7382-0030-9 15125:978-0-02-908060-3 15101:978-0-06-011082-6 14989:978-0-7139-9037-9 14854:978-1-4673-1228-8 14809:978-0-393-86833-3 14784:978-0-521-87628-5 14409:978-0-15-601391-8 14274:978-1-78643-904-8 14082:978-0-672-30412-5 14047:McCorduck, Pamela 13969:Other textbooks: 13948:978-1-107-19539-4 13906:978-0-19-510270-3 13834:978-1-55860-467-4 13796:978-0-8053-4780-7 13591:AI as evolution: 13533:'s "singularity" 13109:, pp. 10–11) 12978:, pp. 15–16) 12970:Moravec's paradox 12560:, pp. 24–26) 12265:, pp. 86–86. 12229:, pp. 47–49. 12209:, pp. 70–71) 12149:, pp. 27–32) 12008:(Press release). 11960:. pp. 10–12. 11897:Council of Europe 11075:. 25 March 2023. 10934:. pp. 34–39. 10519:, pp. 88–91. 10054:. 24 January 2024 9990:. 26 March 2023. 9619:978-0-12-824073-1 9007:(7896): 223–228. 8896:(6456): 885–890. 8639:(7873): 583–589. 8054:Neural networks: 7879:decision networks 7833:Bayesian learning 7733:Bayesian networks 7631:decision networks 7581:decision analysis 7452:, chpt. 4.2, 7.2) 7446:, pp. 62–73) 7409:Logical inference 7367:First-order logic 7349:, pp. 45–50) 7317:, pp. 35–77) 7035:Search algorithms 6665:Transfer learning 6558:Solomonoff (1956) 6189:Default reasoning 6040:Semantic networks 5654:, pp. 21–22) 5557:, pp. 19–21) 5384:Business Horizons 5003:In statistics, a 4936:Alexey Ivakhnenko 4748:Explanatory notes 4543:Stanley Kubrick's 4506:in his 1921 play 4478:in his 1998 book 4397:If research into 4392:superintelligence 4305:mind–body problem 4187:superintelligence 4080:Moravec's paradox 3957:Intelligent agent 3895:alignment problem 3774:academic research 3701:Dartmouth College 3597:Council of Europe 3565:The first global 3431:Stuart J. Russell 3412:Eliezer Yudkowsky 3285:Yuval Noah Harari 3274:superintelligence 3224:Joseph Weizenbaum 3160:mass surveillance 3106:allow widespread 3104:voice recognition 2606:de-identification 2583:temporary workers 2401:generative models 2305:from eleuther or 2190:-playing program 1976:self-driving cars 1814:(formerly Bard), 1534:decision networks 1510:Bayesian networks 1496:decision networks 1484:decision analysis 1448:default reasoning 1416:logic programming 1397:first-order logic 1383:. In the case of 1356:a new statement ( 1335:" and "There are 966:semantic networks 908:sample complexity 886:Transfer learning 750:default reasoning 661:long-term effects 473:include advanced 448:field of research 425: 424: 161:Bayesian networks 88:Intelligent agent 40:Intelligent agent 16:(Redirected from 25626: 25377:Computer science 25284: 25277: 25270: 25261: 25260: 25244:Warren McCulloch 25219:Valentin Turchin 25169:Pyotr Grigorenko 25114:John N. Warfield 25039:Francisco Varela 24999:Charles François 24969:Alexander Lerner 24946:Sociocybernetics 24866:Neurocybernetics 24819: 24812: 24805: 24796: 24795: 24784: 24783: 24731:Human Compatible 24704:Roman Yampolskiy 24452:Consequentialism 24409:Existential risk 24402: 24395: 24388: 24379: 24378: 24363: 24362: 24351: 24350: 24335:Fictional robots 24303:Critique of work 23952:Unmanned vehicle 23768: 23690: 23683: 23676: 23667: 23666: 23651: 23650: 23598:Horizon scanning 23514:Ephemeralization 23430:Racetrack memory 23365:Extended reality 23360:Cybermethodology 23280: 23279: 23262: 23255: 23248: 23239: 23238: 23225: 23224: 23215: 23214: 23205: 23204: 23025:Cross-validation 22997:Machine learning 22881:Social computing 22848:Network security 22643:Algorithm design 22572:Programming team 22532:Control variable 22509:Software library 22447:Software quality 22442:Operating system 22391:Network protocol 22256:Computer science 22249: 22242: 22235: 22226: 22225: 22212:Machine learning 22202: 22201: 22182: 21937:Action selection 21927:Self-driving car 21734:Stable Diffusion 21699:Speech synthesis 21664: 21663: 21528:Machine learning 21404:Gradient descent 21325: 21318: 21311: 21302: 21301: 21262:Machine learning 21232:Fitness function 21222:Digital organism 21003: 20996: 20989: 20980: 20979: 20967: 20966: 20955: 20954: 20953: 20928:Bas van Fraassen 20883:Hans Reichenbach 20863:Bertrand Russell 20780: 20779: 20606:Philosophy of... 20389:Unity of science 20182:Commensurability 20128: 20121: 20114: 20105: 20104: 19849:Representational 19844:Property dualism 19837:Type physicalism 19802:New mysterianism 19770:Epiphenomenalism 19592:Martin Heidegger 19454: 19447: 19440: 19431: 19430: 19346: 19339: 19332: 19323: 19322: 19310: 19309: 19295: 19286:Zalta, Edward N. 19276: 19254: 19252: 19250: 19244: 19237: 19226: 19224: 19222: 19165: 19163: 19161: 19155: 19132: 19067: 19065: 19063: 19006: 18966: 18964: 18962: 18905: 18887: 18746:(July 18, 2023) 18652: 18651: 18636: 18635: 18633: 18627: 18608: 18598: 18586: 18584: 18582: 18533: 18519: 18517: 18515: 18495: 18493: 18491: 18485: 18446: 18436: 18434: 18432: 18418: 18406: 18397: 18395: 18393: 18372: 18370: 18368: 18359:. 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Archived from 16598:"Machine Ethics" 16593: 16575: 16554: 16552: 16550: 16529: 16527: 16504: 16492: 16485:Lighthill, James 16480: 16458: 16456: 16454: 16433: 16408: 16406: 16404: 16388: 16386: 16384: 16359: 16357: 16341:Machine Learning 16330: 16306: 16296: 16263: 16261: 16259: 16238: 16236: 16234: 16213:Kissinger, Henry 16208: 16206: 16204: 16188: 16186: 16184: 16163: 16161: 16159: 16138: 16081:Kahneman, Daniel 16076: 16074: 16072: 16045:Kahneman, Daniel 16040: 15995: 15958: 15956: 15954: 15933: 15931: 15929: 15912: 15910: 15908: 15887: 15881: 15869: 15867: 15865: 15836: 15795: 15793: 15791: 15780:The Times Online 15770: 15748: 15733: 15731: 15729: 15710:(October 2018). 15703: 15701: 15699: 15678: 15665: 15649: 15631: 15610: 15609: 15607: 15602:on 16 April 2016 15588: 15575: 15573: 15571: 15555: 15539: 15528: 15526: 15524: 15503: 15501: 15499: 15480:(18 July 2023). 15473: 15471: 15469: 15448: 15427: 15425: 15423: 15403: 15385: 15364: 15358: 15356: 15338: 15336: 15334: 15328: 15321: 15311: 15309: 15307: 15286: 15267: 15265: 15237: 15235: 15233: 15212: 15210: 15208: 15188: 15177: 15175: 15173: 15141: 15139: 15137: 15105: 15081: 15055: 15050:, archived from 15038: 15036: 15034: 15018: 15016: 15014: 14993: 14969: 14967: 14965: 14959: 14936: 14926: 14918: 14916: 14914: 14893: 14891: 14889: 14875: 14866: 14838: 14821: 14793:Christian, Brian 14788: 14761: 14759: 14757: 14727: 14725: 14723: 14700: 14671: 14668:10.1109/2.933500 14648: 14646: 14644: 14625:(13 June 1863). 14618: 14606: 14596: 14571: 14569: 14554: 14536: 14523: 14518:. Archived from 14510: 14508: 14506: 14495:TED (conference) 14485: 14471: 14462: 14460: 14458: 14452: 14445: 14433: 14431: 14429: 14394:Berlinski, David 14389: 14371: 14353: 14328: 14319: 14292:Winston, Patrick 14286: 14259: 14257: 14255: 14235: 14206: 14198: 14189: 14166:AI & Society 14160: 14158: 14156: 14124: 14086: 14063: 14041: 14011: 14000:(1st ed.). 13989: 13978:(2nd ed.). 13964: 13962: 13960: 13926:Later editions: 13922: 13920: 13918: 13877: 13850: 13848: 13846: 13826: 13812: 13810: 13808: 13788: 13764: 13742: 13691: 13685: 13679: 13673: 13667: 13661: 13655: 13649: 13643: 13640:McCorduck (2004) 13637: 13631: 13620: 13614: 13589: 13583: 13559: 13553: 13547: 13541: 13510:Omohundro (2008) 13490: 13484: 13483: 13481: 13479: 13464: 13458: 13457: 13455: 13453: 13438: 13432: 13431: 13429: 13427: 13404: 13398: 13397: 13385: 13379: 13378: 13376: 13374: 13359: 13350: 13349: 13347: 13345: 13330: 13319: 13318: 13316: 13314: 13299: 13293: 13251: 13245: 13239: 13233: 13227: 13221: 13215: 13209: 13203: 13197: 13191: 13185: 13179: 13173: 13167: 13161: 13155: 13146: 13140: 13134: 13086: 13080: 13074: 13068: 13062: 13056: 13050: 13044: 12999: 12993: 12967: 12961: 12935: 12929: 12926:Haugeland (1985) 12923: 12917: 12911: 12905: 12904: 12902: 12900: 12886: 12880: 12879: 12877: 12875: 12861: 12855: 12854: 12852: 12850: 12829: 12823: 12817: 12811: 12805: 12799: 12793: 12787: 12781: 12775: 12774: 12772: 12770: 12764:The Conversation 12755: 12749: 12743: 12737: 12731: 12722: 12716: 12710: 12704: 12698: 12697: 12695: 12693: 12673: 12667: 12653: 12647: 12641: 12630: 12616: 12610: 12604: 12598: 12575: 12569: 12545: 12539: 12533: 12527: 12511: 12505: 12499: 12493: 12465: 12459: 12453: 12444: 12438: 12432: 12429:McCorduck (2004) 12426: 12420: 12414: 12408: 12402: 12396: 12352: 12346: 12340: 12334: 12328: 12322: 12319:Lighthill (1973) 12316: 12310: 12304: 12298: 12288: 12282: 12272: 12266: 12260: 12254: 12248: 12242: 12236: 12230: 12224: 12218: 12173: 12164: 12155:, pp. 8–17) 12135: 12129: 12128: 12121: 12115: 12114: 12096: 12085: 12079: 12070: 12069: 12067: 12065: 12050: 12044: 12043: 12041: 12039: 12028: 12022: 12021: 12019: 12017: 11998: 11992: 11991: 11989: 11987: 11968: 11962: 11961: 11951: 11945: 11939: 11933: 11927: 11921: 11915: 11909: 11908: 11906: 11904: 11889: 11883: 11882: 11874: 11868: 11862: 11856: 11853:Kissinger (2021) 11850: 11844: 11838: 11825: 11819: 11813: 11807: 11798: 11792: 11786: 11756: 11750: 11749: 11747: 11745: 11734: 11728: 11727: 11691: 11685: 11684: 11636: 11630: 11629: 11619: 11595: 11589: 11588: 11586: 11577: 11571: 11570: 11568: 11559: 11553: 11552: 11550: 11548: 11533: 11527: 11526: 11514: 11508: 11507: 11505: 11503: 11488: 11482: 11481: 11469: 11463: 11462: 11460: 11458: 11443: 11437: 11436: 11434: 11432: 11417: 11411: 11410: 11408: 11406: 11400:Business Insider 11391: 11385: 11379: 11373: 11367: 11361: 11355: 11349: 11343: 11334: 11331:Yudkowsky (2008) 11328: 11322: 11319:Christian (2020) 11316: 11307: 11282: 11276: 11275: 11273: 11271: 11256: 11250: 11249: 11247: 11245: 11230: 11224: 11223: 11221: 11219: 11204: 11198: 11197: 11195: 11193: 11178: 11172: 11171: 11169: 11167: 11152: 11146: 11140: 11134: 11133: 11131: 11129: 11114: 11108: 11107: 11095: 11089: 11088: 11086: 11084: 11065: 11059: 11040:Rawlinson (2015) 11034: 11028: 11022: 11016: 11010: 11004: 10990: 10984: 10978: 10972: 10966: 10960: 10954: 10948: 10942: 10936: 10935: 10925: 10919: 10910: 10904: 10898: 10892: 10891: 10889: 10887: 10872: 10866: 10865: 10863: 10861: 10846: 10840: 10826: 10820: 10814: 10808: 10802: 10796: 10794:McGaughey (2022) 10787: 10781: 10766: 10757: 10751: 10745: 10744: 10742: 10740: 10725: 10719: 10718: 10706: 10700: 10694: 10688: 10682:Robitzski (2018) 10679: 10673: 10667: 10661: 10655: 10646: 10640: 10634: 10633: 10631: 10629: 10614: 10608: 10605:Christian (2020) 10602: 10596: 10593:Christian (2020) 10590: 10584: 10578: 10572: 10566: 10560: 10557:Christian (2020) 10554: 10548: 10545:Christian (2020) 10542: 10536: 10526: 10520: 10517:Christian (2020) 10514: 10508: 10505:Christian (2020) 10502: 10496: 10495: 10488: 10482: 10476: 10470: 10464: 10458: 10451: 10445: 10440:, p. 994); 10435: 10429: 10422: 10416: 10403:, p. 995); 10398: 10392: 10382: 10376: 10375:, p. 67–70. 10373:Christian (2020) 10370: 10364: 10358: 10352: 10346: 10340: 10334: 10325: 10322:Christian (2020) 10319: 10313: 10295: 10289: 10283: 10277: 10271: 10265: 10259: 10250: 10249: 10247: 10245: 10230: 10221: 10215: 10209: 10203: 10197: 10196: 10180: 10174: 10168: 10162: 10161: 10149: 10143: 10142: 10130: 10124: 10123: 10117: 10108: 10102: 10101: 10089: 10083: 10082: 10070: 10064: 10063: 10061: 10059: 10044: 10038: 10037: 10025: 10019: 10018: 10002: 9996: 9995: 9985: 9978: 9972: 9971: 9961: 9953: 9947: 9946: 9930: 9924: 9923: 9915: 9907: 9901: 9895: 9889: 9883: 9877: 9876: 9874: 9872: 9849: 9843: 9842: 9840: 9838: 9826:Kopel, Matthew. 9823: 9817: 9811: 9805: 9802:Christian (2020) 9799: 9793: 9787: 9781: 9775: 9769: 9763: 9757: 9751: 9745: 9742:Laskowski (2023) 9739: 9733: 9727: 9721: 9715: 9709: 9708: 9676: 9670: 9669: 9652:(6): 3179–3185. 9637: 9631: 9629: 9628: 9626: 9601: 9595: 9594: 9578: 9572: 9571: 9569: 9567: 9560:McKinsey Digital 9552: 9546: 9545: 9525: 9519: 9518: 9490: 9484: 9483: 9481: 9479: 9464: 9458: 9457: 9455: 9453: 9430: 9424: 9423: 9421: 9419: 9404: 9398: 9397: 9395: 9393: 9373: 9367: 9366: 9364: 9362: 9340: 9334: 9333: 9331: 9318: 9312: 9311: 9309: 9307: 9301: 9294: 9285: 9279: 9278: 9276: 9274: 9251: 9245: 9244: 9224: 9215: 9211: 9209: 9198: 9187: 9180: 9174: 9171: 9165: 9158:Alex McFarland: 9156: 9150: 9144: 9138: 9129: 9123: 9122: 9120: 9118: 9101: 9095: 9094: 9092: 9080: 9074: 9065: 9059: 9058: 9056: 9054: 9039: 9033: 9032: 8996: 8990: 8989: 8987: 8985: 8962: 8956: 8955: 8953: 8951: 8936: 8930: 8929: 8881: 8875: 8874: 8872: 8870: 8855: 8849: 8848: 8846: 8844: 8827: 8819: 8813: 8812: 8810: 8808: 8802:The Conversation 8793: 8787: 8786: 8784: 8782: 8759: 8753: 8752: 8742: 8709: 8703: 8702: 8695: 8689: 8688: 8681: 8675: 8674: 8664: 8624: 8618: 8617: 8607: 8583: 8574: 8573: 8563: 8540:Future Healthc J 8531: 8525: 8524: 8512: 8506: 8505: 8503: 8501: 8486: 8480: 8474: 8468: 8465:Marmouyet (2023) 8462: 8456: 8455: 8453: 8451: 8440: 8434: 8433: 8426: 8420: 8414: 8408: 8401: 8395: 8389: 8383: 8377: 8366: 8360: 8354: 8348: 8339: 8333: 8314: 8308: 8297: 8291: 8285: 8279: 8273: 8267: 8261: 8247: 8241: 8208: 8199: 8185: 8179: 8165: 8159: 8145: 8139: 8112: 8106: 8075: 8069: 8052: 8043: 8023: 8017: 8011: 8005: 7971: 7965: 7945: 7939: 7938: 7917: 7911: 7896: 7890: 7872: 7866: 7830: 7824: 7818: 7812: 7780: 7774: 7768: 7762: 7730: 7724: 7713:mechanism design 7706: 7700: 7653: 7642: 7624: 7618: 7604: 7598: 7574: 7568: 7539: 7530: 7514: 7508: 7507: 7485: 7479: 7461: 7455: 7426: 7420: 7406: 7400: 7364: 7358: 7332: 7326: 7300: 7294: 7288: 7282: 7268: 7262: 7261: 7259: 7257: 7242: 7236: 7218: 7212: 7198: 7192: 7152: 7146: 7102: 7096: 7090: 7084: 7070: 7064: 7032: 7026: 7020: 7014: 7008: 7002: 6974: 6968: 6962: 6956: 6950: 6944: 6938: 6932: 6926: 6920: 6914: 6908: 6902: 6896: 6876: 6870: 6864: 6858: 6852: 6846: 6840: 6834: 6814: 6808: 6802: 6796: 6790: 6784: 6769: 6763: 6737: 6731: 6712: 6706: 6705: 6703: 6701: 6687: 6681: 6662: 6656: 6636: 6630: 6610: 6601: 6586:cluster analysis 6567: 6561: 6555: 6549: 6543: 6537: 6505: 6499: 6485: 6479: 6465: 6459: 6456:, Section 16.6). 6445: 6439: 6416: 6410: 6407:, Section 11.5). 6399: 6393: 6390:, Section 11.2). 6379: 6373: 6355: 6349: 6335: 6329: 6323: 6317: 6311: 6305: 6299: 6293: 6260: 6251: 6186: 6177: 6156: 6150: 6136: 6130: 6091: 6085: 6036: 6030: 6024: 6018: 6012: 6006: 6000: 5994: 5988: 5982: 5976: 5970: 5964: 5958: 5922: 5916: 5891: 5880: 5862: 5851: 5822: 5816: 5777: 5771: 5765: 5759: 5731: 5722: 5683: 5674: 5637:Lighthill report 5629: 5620: 5569: 5560: 5531: 5522: 5488: 5479: 5473: 5467: 5427: 5416: 5415: 5379: 5373: 5360: 5354: 5348: 5327: 5307: 5301: 5297: 5291: 5285: 5279: 5268: 5262: 5255: 5249: 5227: 5221: 5211: 5205: 5166: 5160: 5150: 5144: 5134: 5128: 5117: 5111: 5108: 5102: 5095: 5089: 5086: 5080: 5069: 5063: 5060: 5054: 5047: 5041: 5018: 5012: 5001: 4995: 4989: 4983: 4976:Seppo Linnainmaa 4968:Arthur E. Bryson 4960:Arthur E. Bryson 4932:Oliver Selfridge 4928:Frank Rosenblatt 4904: 4898: 4895:latent variables 4891: 4885: 4880:of one another. 4874: 4868: 4862: 4856: 4842: 4836: 4825: 4819: 4812: 4806: 4788: 4779: 4761: 4735:Wetware computer 4701: 4656: 4440:, cyberneticist 4363:moral blind spot 4118:Neat vs. scruffy 4100:algorithmic bias 4006: 3877:) and access to 3867:faster computers 3709:logical theorems 3624:AI Safety Summit 3567:AI Safety Summit 3471:Stable Diffusion 3435:three principles 3406:Human Compatible 3230:Existential risk 3152:advanced spyware 3112:Machine learning 2989:established the 2806:Algorithmic bias 2726:Research Paper, 2641:Jonathan Franzen 2602:data aggregation 2595:right to privacy 2428:Stable Diffusion 2062:Hippocratic Oath 2058:medical research 1988:Google Translate 1936:internet traffic 1874:machine learning 1766:curated datasets 1735:image processing 1709:image processing 1591:pattern matching 1504:mechanism design 1464:Bayesian network 1410:, and therefore 1252:gradient descent 1244:Gradient descent 1223:gradient descent 1221:Illustration of 935:speech synthesis 856:Machine learning 823:transition model 786:expected utility 503:Google Assistant 499:via human speech 452:computer science 444:computer systems 417: 410: 403: 324:Existential risk 146:Machine learning 47: 46: 21: 25634: 25633: 25629: 25628: 25627: 25625: 25624: 25623: 25614:Formal sciences 25579: 25578: 25577: 25572: 25571: 25566: 25465:Hebrew toponyms 25460:Arabic toponyms 25298: 25288: 25258: 25253: 25209:Talcott Parsons 25199:Stuart Kauffman 25099:Jason Jixuan Hu 25084:Igor Aleksander 25064:Gregory Bateson 25059:Gordon S. Brown 25044:Frederic Vester 25024:Erich von Holst 24984:Allenna Leonard 24974:Alexey Lyapunov 24955: 24901:Decision theory 24829: 24823: 24793: 24788: 24774: 24713: 24669:Steve Omohundro 24649:Geoffrey Hinton 24639:Stephen Hawking 24624:Paul Christiano 24604:Scott Alexander 24592: 24563:Google DeepMind 24511: 24497:Suffering risks 24415: 24406: 24376: 24371: 24339: 24291: 24212:Boston Dynamics 24197:Amazon Robotics 24185: 24109: 24100:Visual odometry 24090:Motion planning 24072: 24027: 23947:Continuum robot 23930:Classifications 23925: 23788:Anthropomorphic 23769: 23760: 23756:AI competitions 23699: 23694: 23664: 23659: 23639: 23478: 23289: 23286: 23285:Information and 23271: 23266: 23236: 23231: 23222: 23193: 23174:Word processing 23082: 23068:Virtual reality 23029: 22991: 22962:Computer vision 22938: 22934:Multiprocessing 22900: 22862: 22828:Security hacker 22804: 22780:Digital library 22721: 22672:Mathematics of 22667: 22629: 22605:Automata theory 22600:Formal language 22581: 22547:Software design 22518: 22451: 22437:Virtual machine 22415: 22411:Network service 22372: 22363:Embedded system 22336: 22269: 22258: 22253: 22223: 22218: 22170: 22084: 22050:Google DeepMind 22028: 21994:Geoffrey Hinton 21953: 21890: 21816:Project Debater 21762: 21660:Implementations 21655: 21609: 21573: 21516: 21458:Backpropagation 21392: 21378:Tensor calculus 21332: 21329: 21299: 21294: 21276: 21217:Artificial life 21195: 21162: 21121: 21048: 21012: 21007: 20977: 20972: 20961: 20951: 20949: 20937: 20918:Paul Feyerabend 20878:Michael Polanyi 20814: 20800:Galileo Galilei 20769: 20755:Science studies 20671: 20601: 20592:Verificationism 20497:Instrumentalism 20482:Foundationalism 20457:Conventionalism 20415: 20251:Feminist method 20137: 20132: 20102: 20097: 20069: 20036: 19982:Mental property 19875:Abstract object 19863: 19733: 19687:Wilfrid Sellars 19562:Donald Davidson 19547:Paul Churchland 19507:George Berkeley 19463: 19458: 19428: 19423: 19369:Circumscription 19355: 19350: 19315: 19265: 19262: 19257: 19248: 19246: 19242: 19235: 19220: 19218: 19159: 19157: 19153: 19130: 19119:Foreign Affairs 19061: 19059: 19003: 18960: 18958: 18911:"Deep learning" 18721:Foreign Affairs 18716:Cukier, Kenneth 18706:Mind As Machine 18702:Boden, Margaret 18692:Autor, David H. 18673: 18672: 18671: 18653: 18649: 18644: 18642:Further reading 18639: 18631: 18629: 18625: 18606: 18580: 18578: 18513: 18511: 18489: 18487: 18483: 18444: 18430: 18428: 18391: 18389: 18366: 18364: 18330: 18328: 18305: 18303: 18280: 18278: 18255: 18253: 18223: 18221: 18147: 18145: 18138: 18082: 18080: 18062: 18060: 18053: 18029: 18027: 17992: 17962: 17960: 17956: 17949: 17935: 17934: 17926: 17924: 17920: 17913: 17905:Solomonoff, Ray 17877:IEEE MultiMedia 17865: 17863: 17823: 17821: 17806: 17779: 17777: 17773: 17742: 17696:"Deep Learning" 17637:Neural Networks 17633:Schmidhuber, J. 17593: 17591: 17573: 17571: 17553: 17551: 17523: 17507:Russell, Stuart 17485: 17483: 17461: 17459: 17440: 17438: 17403: 17401: 17378: 17376: 17327: 17303: 17273: 17271: 17267: 17236: 17193: 17191: 17187: 17172: 17155: 17153: 17052: 17021: 17007: 17005: 16982: 16980: 16973: 16935: 16914: 16912: 16800: 16798: 16762: 16760: 16749:Shannon, Claude 16695: 16693: 16676: 16674: 16653: 16651: 16628: 16626: 16548: 16546: 16525: 16502: 16477: 16452: 16450: 16402: 16400: 16382: 16380: 16367:(23 May 2016). 16327: 16257: 16255: 16248:InformationWeek 16232: 16230: 16202: 16200: 16182: 16180: 16157: 16155: 16119: 16070: 16068: 16061: 15952: 15950: 15927: 15925: 15906: 15904: 15884:Neural Networks 15879: 15863: 15861: 15789: 15787: 15767: 15753:Haugeland, John 15727: 15725: 15697: 15695: 15605: 15603: 15569: 15567: 15552: 15522: 15520: 15497: 15495: 15467: 15465: 15421: 15419: 15354: 15352: 15332: 15330: 15326: 15319: 15317:"Fox News Poll" 15305: 15303: 15283: 15231: 15229: 15206: 15204: 15197: 15171: 15169: 15162: 15135: 15133: 15126: 15110:Dreyfus, Hubert 15102: 15086:Dreyfus, Hubert 15078: 15060:Domingos, Pedro 15054:on 27 June 2022 15032: 15030: 15012: 15010: 14990: 14974:Dennett, Daniel 14963: 14961: 14957: 14934: 14912: 14910: 14887: 14885: 14855: 14810: 14785: 14755: 14753: 14732:Chalmers, David 14721: 14719: 14642: 14640: 14567: 14552:10.1.1.588.7539 14534: 14504: 14502: 14456: 14454: 14450: 14443: 14427: 14425: 14410: 14275: 14253: 14251: 14154: 14152: 14139:(22 May 2023). 14137:Sutskever, Ilya 14111:Wayback Machine 14094: 14089: 14083: 14069:Newquist, H. P. 14061: 14038: 14024:Crevier, Daniel 14018: 14008: 13986: 13967: 13958: 13956: 13949: 13933:Mackworth, Alan 13916: 13914: 13907: 13887:Mackworth, Alan 13875: 13844: 13842: 13835: 13806: 13804: 13797: 13761: 13731: 13699: 13694: 13686: 13682: 13676:McCauley (2007) 13674: 13670: 13664:Anderson (2008) 13662: 13658: 13652:Buttazzo (2001) 13650: 13646: 13638: 13634: 13628:, pp. 4–5) 13626:McCorduck (2004 13621: 13617: 13599:McCorduck (2004 13590: 13586: 13580:, p. 1005) 13573:Kurzweil (2005) 13560: 13556: 13552:, p. 1005. 13548: 13544: 13515:Kurzweil (2005) 13491: 13487: 13477: 13475: 13465: 13461: 13451: 13449: 13439: 13435: 13425: 13423: 13405: 13401: 13387: 13386: 13382: 13372: 13370: 13360: 13353: 13343: 13341: 13331: 13322: 13312: 13310: 13300: 13296: 13282:McCorduck (2004 13278:, pp. 985) 13252: 13248: 13244:, p. 9817. 13240: 13236: 13228: 13224: 13216: 13212: 13204: 13200: 13192: 13188: 13182:Chalmers (1995) 13180: 13176: 13168: 13164: 13156: 13149: 13141: 13137: 13130:Domingos (2015) 13095:McCorduck (2004 13087: 13083: 13075: 13071: 13063: 13059: 13051: 13047: 13027:McCorduck (2004 13000: 12996: 12968: 12964: 12950:McCorduck (2004 12936: 12932: 12924: 12920: 12912: 12908: 12898: 12896: 12888: 12887: 12883: 12873: 12871: 12863: 12862: 12858: 12848: 12846: 12831: 12830: 12826: 12818: 12814: 12808:McCarthy (1999) 12806: 12802: 12794: 12790: 12782: 12778: 12768: 12766: 12756: 12752: 12744: 12740: 12732: 12725: 12717: 12713: 12705: 12701: 12691: 12689: 12674: 12670: 12654: 12650: 12642: 12633: 12617: 12613: 12605: 12601: 12576: 12572: 12564:McCorduck (2004 12546: 12542: 12534: 12530: 12512: 12508: 12500: 12496: 12466: 12462: 12454: 12447: 12439: 12435: 12427: 12423: 12415: 12411: 12403: 12399: 12379:McCorduck (2004 12353: 12349: 12341: 12337: 12329: 12325: 12317: 12313: 12305: 12301: 12289: 12285: 12273: 12269: 12263:Newquist (1994) 12261: 12257: 12249: 12245: 12237: 12233: 12225: 12221: 12207:McCorduck (2004 12197:, pp. 6–9) 12195:Haugeland (1985 12174: 12167: 12141:McCorduck (2004 12136: 12132: 12123: 12122: 12118: 12111: 12097: 12088: 12080: 12073: 12063: 12061: 12052: 12051: 12047: 12037: 12035: 12030: 12029: 12025: 12015: 12013: 12000: 11999: 11995: 11985: 11983: 11970: 11969: 11965: 11952: 11948: 11942:Fox News (2023) 11940: 11936: 11928: 11924: 11916: 11912: 11902: 11900: 11891: 11890: 11886: 11875: 11871: 11863: 11859: 11851: 11847: 11839: 11828: 11820: 11816: 11808: 11801: 11793: 11789: 11757: 11753: 11743: 11741: 11736: 11735: 11731: 11692: 11688: 11637: 11633: 11596: 11592: 11584: 11578: 11574: 11566: 11560: 11556: 11546: 11544: 11534: 11530: 11515: 11511: 11501: 11499: 11489: 11485: 11470: 11466: 11456: 11454: 11444: 11440: 11430: 11428: 11418: 11414: 11404: 11402: 11392: 11388: 11380: 11376: 11368: 11364: 11356: 11352: 11344: 11337: 11329: 11325: 11317: 11310: 11298:Madrigal (2015) 11283: 11279: 11269: 11267: 11257: 11253: 11243: 11241: 11239:Financial Times 11231: 11227: 11217: 11215: 11205: 11201: 11191: 11189: 11179: 11175: 11165: 11163: 11153: 11149: 11141: 11137: 11127: 11125: 11116: 11115: 11111: 11096: 11092: 11082: 11080: 11067: 11066: 11062: 11035: 11031: 11023: 11019: 11011: 11007: 10991: 10987: 10979: 10975: 10967: 10963: 10959:, p. 1001. 10955: 10951: 10943: 10939: 10926: 10922: 10917:Thompson (2014) 10911: 10907: 10899: 10895: 10885: 10883: 10873: 10869: 10859: 10857: 10847: 10843: 10827: 10823: 10815: 10811: 10803: 10799: 10788: 10784: 10778:Wayback Machine 10767: 10760: 10752: 10748: 10738: 10736: 10727: 10726: 10722: 10707: 10703: 10695: 10691: 10680: 10676: 10668: 10664: 10656: 10649: 10641: 10637: 10627: 10625: 10615: 10611: 10603: 10599: 10591: 10587: 10579: 10575: 10567: 10563: 10555: 10551: 10543: 10539: 10531:, p. 83); 10529:Christian (2020 10527: 10523: 10515: 10511: 10503: 10499: 10494:. 16 June 2023. 10490: 10489: 10485: 10477: 10473: 10467:Dockrill (2022) 10465: 10461: 10455:Christian (2020 10452: 10448: 10442:Christian (2020 10436: 10432: 10426:Christian (2020 10423: 10419: 10413:Christian (2020 10407:, p. 36); 10405:Lipartito (2011 10399: 10395: 10385:Christian (2020 10383: 10379: 10371: 10367: 10359: 10355: 10347: 10343: 10335: 10328: 10320: 10316: 10304:, p. 17); 10296: 10292: 10284: 10280: 10272: 10268: 10260: 10253: 10243: 10241: 10231: 10224: 10216: 10212: 10206:Williams (2023) 10204: 10200: 10181: 10177: 10169: 10165: 10150: 10146: 10131: 10127: 10115: 10109: 10105: 10098:Washington Post 10090: 10086: 10071: 10067: 10057: 10055: 10046: 10045: 10041: 10026: 10022: 10003: 9999: 9980: 9979: 9975: 9955: 9954: 9950: 9931: 9927: 9913: 9909: 9908: 9904: 9896: 9892: 9884: 9880: 9870: 9868: 9852:Burgess, Matt. 9850: 9846: 9836: 9834: 9824: 9820: 9812: 9808: 9800: 9796: 9788: 9784: 9776: 9772: 9766:Valinsky (2019) 9764: 9760: 9752: 9748: 9740: 9736: 9728: 9724: 9718:Simonite (2016) 9716: 9712: 9677: 9673: 9646:Fire Technology 9638: 9634: 9624: 9622: 9620: 9602: 9598: 9579: 9575: 9565: 9563: 9554: 9553: 9549: 9542: 9526: 9522: 9515: 9491: 9487: 9477: 9475: 9465: 9461: 9451: 9449: 9431: 9427: 9417: 9415: 9405: 9401: 9391: 9389: 9374: 9370: 9360: 9358: 9341: 9337: 9319: 9315: 9305: 9303: 9299: 9292: 9286: 9282: 9272: 9270: 9252: 9248: 9225: 9218: 9207: 9199: 9190: 9181: 9177: 9172: 9168: 9157: 9153: 9145: 9141: 9130: 9126: 9116: 9114: 9102: 9098: 9081: 9077: 9066: 9062: 9052: 9050: 9040: 9036: 8997: 8993: 8983: 8981: 8963: 8959: 8949: 8947: 8944:Google DeepMind 8938: 8937: 8933: 8882: 8878: 8868: 8866: 8856: 8852: 8842: 8840: 8820: 8816: 8806: 8804: 8794: 8790: 8780: 8778: 8760: 8756: 8710: 8706: 8697: 8696: 8692: 8683: 8682: 8678: 8625: 8621: 8584: 8577: 8532: 8528: 8513: 8509: 8499: 8497: 8487: 8483: 8477:Kobielus (2019) 8475: 8471: 8463: 8459: 8449: 8447: 8442: 8441: 8437: 8428: 8427: 8423: 8415: 8411: 8405:Christian (2020 8402: 8398: 8390: 8386: 8378: 8369: 8361: 8357: 8349: 8342: 8334: 8317: 8309: 8300: 8292: 8288: 8280: 8276: 8268: 8264: 8248: 8244: 8209: 8202: 8186: 8182: 8166: 8162: 8146: 8142: 8113: 8109: 8079:backpropagation 8076: 8072: 8053: 8046: 8024: 8020: 8014:Domingos (2015) 8012: 8008: 7974:Non-parameteric 7972: 7968: 7946: 7942: 7935: 7918: 7914: 7897: 7893: 7873: 7869: 7831: 7827: 7821:Domingos (2015) 7819: 7815: 7781: 7777: 7771:Domingos (2015) 7769: 7765: 7731: 7727: 7707: 7703: 7654: 7645: 7625: 7621: 7605: 7601: 7589:, Chpt. 16–18), 7577:decision theory 7575: 7571: 7540: 7533: 7515: 7511: 7486: 7482: 7462: 7458: 7427: 7423: 7407: 7403: 7365: 7361: 7333: 7329: 7301: 7297: 7289: 7285: 7269: 7265: 7255: 7253: 7243: 7239: 7219: 7215: 7199: 7195: 7153: 7149: 7103: 7099: 7091: 7087: 7071: 7067: 7033: 7029: 7021: 7017: 7009: 7005: 6975: 6971: 6963: 6959: 6951: 6947: 6939: 6935: 6927: 6923: 6915: 6911: 6903: 6899: 6879:Computer vision 6877: 6873: 6867:Bushwick (2023) 6865: 6861: 6853: 6849: 6841: 6837: 6815: 6811: 6803: 6799: 6791: 6787: 6771:Subproblems of 6770: 6766: 6738: 6734: 6713: 6709: 6699: 6697: 6689: 6688: 6684: 6673:, pp. 281) 6663: 6659: 6637: 6633: 6611: 6604: 6568: 6564: 6556: 6552: 6544: 6540: 6506: 6502: 6486: 6482: 6466: 6462: 6446: 6442: 6436:, Section 22.6) 6424:, Section 16.7) 6417: 6413: 6400: 6396: 6380: 6376: 6370:, chpt. 16–18). 6362:Decision theory 6356: 6352: 6336: 6332: 6324: 6320: 6312: 6308: 6302:Newquist (1994) 6300: 6296: 6268:, Introduction) 6261: 6254: 6205:circumscription 6187: 6180: 6157: 6153: 6139:Causal calculus 6137: 6133: 6103:fluent calculus 6092: 6088: 6037: 6033: 6029:, pp. 272. 6025: 6021: 6013: 6009: 6001: 5997: 5989: 5985: 5977: 5973: 5965: 5961: 5923: 5919: 5897:Kahneman (2011) 5892: 5883: 5863: 5854: 5823: 5819: 5778: 5774: 5766: 5762: 5755:McKinsey (2018) 5732: 5725: 5699:McCorduck (2004 5684: 5677: 5630: 5623: 5591:McCorduck (2004 5570: 5563: 5537:McCorduck (2004 5532: 5525: 5503:McCorduck (2004 5489: 5482: 5474: 5470: 5458:McCarthy (2007) 5428: 5419: 5380: 5376: 5370:Wayback Machine 5361: 5357: 5353:, pp. 1–4. 5349: 5340: 5336: 5331: 5330: 5308: 5304: 5298: 5294: 5286: 5282: 5269: 5265: 5256: 5252: 5228: 5224: 5212: 5208: 5167: 5163: 5151: 5147: 5135: 5131: 5118: 5114: 5109: 5105: 5096: 5092: 5087: 5083: 5070: 5066: 5061: 5057: 5048: 5044: 5034:Carnegie Mellon 5019: 5015: 5002: 4998: 4992:Geoffrey Hinton 4990: 4986: 4956:Henry J. Kelley 4948:Shun-Ichi Amari 4905: 4901: 4892: 4888: 4875: 4871: 4863: 4859: 4843: 4839: 4826: 4822: 4813: 4809: 4789: 4782: 4762: 4755: 4750: 4699: 4654: 4641: 4588:introduced the 4518:science fiction 4496: 4490: 4458:Robert Ettinger 4444:, and inventor 4436:Robot designer 4434: 4388: 4383: 4371:factory farming 4332: 4296: 4284:Main articles: 4282: 4253: 4245:Main articles: 4243: 4206: 4198:Main articles: 4196: 4183: 4175:Main articles: 4173: 4152: 4146: 4138:neural networks 4126: 4120: 4062: 4037: 4004: 3967: 3949: 3944: 3938: 3908:, developed by 3875:cloud computing 3825:Geoffrey Hinton 3654: 3647: 3641: 3633:AI Seoul Summit 3584:Henry Kissinger 3559: 3547:Main articles: 3545: 3487: 3443: 3427:Wendell Wallach 3408: 3388:Main articles: 3386: 3351:Geoffrey Hinton 3320:Stephen Hawking 3242:Stephen Hawking 3238: 3232: 3182: 3174:Main articles: 3172: 3148:digital warfare 3045: 3033:Main articles: 3031: 2955: 2941: 2902:recommendations 2850:. The field of 2812: 2804:Main articles: 2802: 2794:Geoffrey Hinton 2759:and others use 2750: 2744: 2711:(IEA) released 2705: 2699: 2655: 2622:Brian Christian 2552: 2542: 2537: 2520: 2514: 2481: 2452: 2385: 2379: 2347: 2341: 2325: 2299:Google DeepMind 2229: 2180:defeated Ke Jie 2112: 2106: 2098:alpha-synuclein 2050: 2044: 1904: 1898: 1858: 1850:Main articles: 1848: 1778: 1758:backpropagation 1742:computer vision 1721: 1678:backpropagation 1638: 1630:Neural networks 1583: 1480:decision theory 1456: 1424:Turing complete 1370:inference rules 1318:predicate logic 1294: 1215: 1160: 1144: 1136: 1122:A machine with 1120: 1075: 1063:object tracking 1040:Computer vision 1036:tactile sensors 1025: 920: 853: 827:reward function 766: 714: 686: 677: 497:); interacting 442:, particularly 421: 392: 391: 382: 374: 373: 349: 339: 338: 310:Control problem 290: 280: 279: 191: 181: 180: 141: 133: 132: 103:Computer vision 78: 43: 28: 23: 22: 15: 12: 11: 5: 25632: 25622: 25621: 25616: 25611: 25606: 25601: 25596: 25591: 25574: 25573: 25568: 25567: 25565: 25564: 25559: 25554: 25549: 25544: 25539: 25534: 25529: 25524: 25519: 25517:Nanotechnology 25514: 25509: 25504: 25499: 25494: 25489: 25487:Machine vision 25484: 25479: 25474: 25473: 25472: 25467: 25462: 25457: 25452: 25444: 25443: 25442: 25437: 25429: 25424: 25419: 25414: 25413: 25412: 25407: 25399: 25394: 25389: 25384: 25379: 25374: 25369: 25364: 25359: 25354: 25349: 25344: 25339: 25334: 25329: 25324: 25319: 25314: 25309: 25303: 25300: 25299: 25290:Glossaries of 25287: 25286: 25279: 25272: 25264: 25255: 25254: 25252: 25251: 25246: 25241: 25236: 25231: 25226: 25221: 25216: 25211: 25206: 25204:Stuart Umpleby 25201: 25196: 25191: 25186: 25181: 25176: 25171: 25166: 25164:Norbert Wiener 25161: 25159:Niklas Luhmann 25156: 25151: 25146: 25141: 25136: 25134:Manfred Clynes 25131: 25126: 25121: 25116: 25111: 25109:Jennifer Wilby 25106: 25101: 25096: 25091: 25086: 25081: 25079:I. A. Richards 25076: 25071: 25066: 25061: 25056: 25051: 25046: 25041: 25036: 25031: 25026: 25021: 25016: 25014:Claude Bernard 25011: 25009:Margaret Boden 25006: 25004:Genevieve Bell 25001: 24996: 24991: 24989:Anthony Wilden 24986: 24981: 24976: 24971: 24965: 24963: 24961:Cyberneticians 24957: 24956: 24954: 24953: 24948: 24943: 24941:Cybersemiotics 24938: 24933: 24928: 24923: 24918: 24913: 24908: 24903: 24898: 24893: 24888: 24886:Control theory 24883: 24878: 24873: 24868: 24863: 24858: 24853: 24848: 24843: 24837: 24835: 24831: 24830: 24822: 24821: 24814: 24807: 24799: 24790: 24789: 24779: 24776: 24775: 24773: 24772: 24767: 24760: 24753: 24746: 24739: 24734: 24727: 24721: 24719: 24715: 24714: 24712: 24711: 24706: 24701: 24696: 24691: 24686: 24681: 24676: 24671: 24666: 24661: 24656: 24651: 24646: 24641: 24636: 24631: 24626: 24621: 24616: 24611: 24606: 24600: 24598: 24594: 24593: 24591: 24590: 24585: 24580: 24575: 24570: 24565: 24560: 24555: 24550: 24545: 24540: 24535: 24530: 24525: 24519: 24517: 24513: 24512: 24510: 24509: 24504: 24499: 24494: 24492:Machine ethics 24489: 24484: 24479: 24474: 24469: 24464: 24459: 24454: 24449: 24444: 24439: 24434: 24429: 24423: 24421: 24417: 24416: 24405: 24404: 24397: 24390: 24382: 24373: 24372: 24370: 24369: 24357: 24344: 24341: 24340: 24338: 24337: 24332: 24330:Terrainability 24327: 24322: 24321: 24320: 24310: 24305: 24299: 24297: 24293: 24292: 24290: 24289: 24284: 24279: 24274: 24269: 24264: 24259: 24254: 24249: 24244: 24239: 24234: 24229: 24224: 24219: 24214: 24209: 24204: 24199: 24193: 24191: 24187: 24186: 24184: 24183: 24178: 24173: 24168: 24163: 24158: 24153: 24148: 24143: 24138: 24133: 24128: 24123: 24117: 24115: 24111: 24110: 24108: 24107: 24102: 24097: 24092: 24086: 24084: 24074: 24073: 24071: 24070: 24065: 24060: 24055: 24054: 24053: 24043: 24037: 24035: 24029: 24028: 24026: 24025: 24024: 24023: 24018: 24008: 24003: 23998: 23997: 23996: 23986: 23981: 23976: 23971: 23966: 23965: 23964: 23959: 23949: 23944: 23942:Cloud robotics 23939: 23933: 23931: 23927: 23926: 23924: 23923: 23918: 23913: 23908: 23903: 23898: 23893: 23888: 23883: 23878: 23873: 23868: 23863: 23858: 23857: 23856: 23846: 23841: 23840: 23839: 23838: 23837: 23822: 23817: 23812: 23811: 23810: 23805: 23800: 23795: 23785: 23779: 23777: 23771: 23770: 23763: 23761: 23759: 23758: 23753: 23748: 23743: 23738: 23733: 23728: 23723: 23718: 23713: 23707: 23705: 23701: 23700: 23693: 23692: 23685: 23678: 23670: 23661: 23660: 23658: 23657: 23644: 23641: 23640: 23638: 23637: 23632: 23627: 23622: 23617: 23616: 23615: 23610: 23605: 23600: 23595: 23590: 23580: 23575: 23570: 23565: 23564: 23563: 23553: 23548: 23543: 23542: 23541: 23536: 23531: 23526: 23516: 23511: 23506: 23501: 23496: 23490: 23488: 23484: 23483: 23480: 23479: 23477: 23476: 23471: 23466: 23465: 23464: 23454: 23449: 23448: 23447: 23442: 23437: 23432: 23427: 23422: 23417: 23412: 23407: 23402: 23397: 23389: 23384: 23383: 23382: 23377: 23367: 23362: 23357: 23352: 23347: 23346: 23345: 23340: 23335: 23330: 23325: 23323:Machine vision 23320: 23315: 23305: 23304: 23303: 23292: 23290: 23287:communications 23283: 23277: 23273: 23272: 23265: 23264: 23257: 23250: 23242: 23233: 23232: 23230: 23229: 23219: 23209: 23198: 23195: 23194: 23192: 23191: 23186: 23181: 23176: 23171: 23166: 23161: 23156: 23151: 23146: 23141: 23136: 23131: 23126: 23121: 23116: 23111: 23106: 23101: 23096: 23090: 23088: 23084: 23083: 23081: 23080: 23078:Solid modeling 23075: 23070: 23065: 23060: 23055: 23050: 23045: 23039: 23037: 23031: 23030: 23028: 23027: 23022: 23017: 23012: 23007: 23001: 22999: 22993: 22992: 22990: 22989: 22984: 22979: 22977:Control method 22974: 22969: 22964: 22959: 22954: 22948: 22946: 22940: 22939: 22937: 22936: 22931: 22929:Multithreading 22926: 22921: 22916: 22910: 22908: 22902: 22901: 22899: 22898: 22893: 22888: 22883: 22878: 22872: 22870: 22864: 22863: 22861: 22860: 22855: 22850: 22845: 22840: 22835: 22830: 22825: 22823:Formal methods 22820: 22814: 22812: 22806: 22805: 22803: 22802: 22797: 22795:World Wide Web 22792: 22787: 22782: 22777: 22772: 22767: 22762: 22757: 22752: 22747: 22742: 22737: 22731: 22729: 22723: 22722: 22720: 22719: 22714: 22709: 22704: 22699: 22694: 22689: 22684: 22678: 22676: 22669: 22668: 22666: 22665: 22660: 22655: 22650: 22645: 22639: 22637: 22631: 22630: 22628: 22627: 22622: 22617: 22612: 22607: 22602: 22597: 22591: 22589: 22583: 22582: 22580: 22579: 22574: 22569: 22564: 22559: 22554: 22549: 22544: 22539: 22534: 22528: 22526: 22520: 22519: 22517: 22516: 22511: 22506: 22501: 22496: 22491: 22486: 22481: 22476: 22471: 22465: 22463: 22453: 22452: 22450: 22449: 22444: 22439: 22434: 22429: 22423: 22421: 22417: 22416: 22414: 22413: 22408: 22403: 22398: 22393: 22388: 22382: 22380: 22374: 22373: 22371: 22370: 22365: 22360: 22355: 22350: 22344: 22342: 22338: 22337: 22335: 22334: 22325: 22320: 22315: 22310: 22305: 22300: 22295: 22290: 22285: 22279: 22277: 22271: 22270: 22263: 22260: 22259: 22252: 22251: 22244: 22237: 22229: 22220: 22219: 22217: 22216: 22215: 22214: 22209: 22196: 22195: 22194: 22189: 22175: 22172: 22171: 22169: 22168: 22163: 22158: 22153: 22148: 22143: 22138: 22133: 22128: 22123: 22118: 22113: 22108: 22103: 22098: 22092: 22090: 22086: 22085: 22083: 22082: 22077: 22072: 22067: 22062: 22057: 22052: 22047: 22042: 22036: 22034: 22030: 22029: 22027: 22026: 22024:Ilya Sutskever 22021: 22016: 22011: 22006: 22001: 21996: 21991: 21989:Demis Hassabis 21986: 21981: 21979:Ian Goodfellow 21976: 21971: 21965: 21963: 21959: 21958: 21955: 21954: 21952: 21951: 21946: 21945: 21944: 21934: 21929: 21924: 21919: 21914: 21909: 21904: 21898: 21896: 21892: 21891: 21889: 21888: 21883: 21878: 21873: 21868: 21863: 21858: 21853: 21848: 21843: 21838: 21833: 21828: 21823: 21818: 21813: 21808: 21807: 21806: 21796: 21791: 21786: 21781: 21776: 21770: 21768: 21764: 21763: 21761: 21760: 21755: 21754: 21753: 21748: 21738: 21737: 21736: 21731: 21726: 21716: 21711: 21706: 21701: 21696: 21691: 21686: 21681: 21676: 21670: 21668: 21661: 21657: 21656: 21654: 21653: 21648: 21643: 21638: 21633: 21628: 21623: 21617: 21615: 21611: 21610: 21608: 21607: 21602: 21597: 21592: 21587: 21581: 21579: 21575: 21574: 21572: 21571: 21570: 21569: 21562:Language model 21559: 21554: 21549: 21548: 21547: 21537: 21536: 21535: 21524: 21522: 21518: 21517: 21515: 21514: 21512:Autoregression 21509: 21504: 21503: 21502: 21492: 21490:Regularization 21487: 21486: 21485: 21480: 21475: 21465: 21460: 21455: 21453:Loss functions 21450: 21445: 21440: 21435: 21430: 21429: 21428: 21418: 21413: 21412: 21411: 21400: 21398: 21394: 21393: 21391: 21390: 21388:Inductive bias 21385: 21380: 21375: 21370: 21365: 21360: 21355: 21350: 21342: 21340: 21334: 21333: 21328: 21327: 21320: 21313: 21305: 21296: 21295: 21293: 21292: 21286: 21284: 21278: 21277: 21275: 21274: 21269: 21264: 21259: 21254: 21249: 21244: 21239: 21234: 21229: 21224: 21219: 21214: 21209: 21203: 21201: 21200:Related topics 21197: 21196: 21194: 21193: 21188: 21183: 21181:Harmony search 21178: 21172: 21170: 21164: 21163: 21161: 21160: 21155: 21150: 21145: 21143:Bees algorithm 21140: 21135: 21129: 21127: 21123: 21122: 21120: 21119: 21114: 21112:Neuroevolution 21109: 21104: 21099: 21094: 21089: 21084: 21079: 21074: 21069: 21064: 21058: 21056: 21050: 21049: 21047: 21046: 21041: 21036: 21031: 21026: 21020: 21018: 21014: 21013: 21006: 21005: 20998: 20991: 20983: 20974: 20973: 20971: 20959: 20947: 20942: 20939: 20938: 20936: 20935: 20930: 20925: 20920: 20915: 20910: 20905: 20903:W. V. O. Quine 20900: 20895: 20890: 20885: 20880: 20875: 20870: 20865: 20860: 20855: 20850: 20845: 20840: 20838:Rudolf Steiner 20835: 20830: 20828:Henri Poincaré 20825: 20819: 20816: 20815: 20813: 20812: 20807: 20802: 20797: 20792: 20786: 20784: 20777: 20771: 20770: 20768: 20767: 20762: 20757: 20752: 20747: 20742: 20737: 20732: 20727: 20726: 20725: 20715: 20710: 20705: 20700: 20698:Exact sciences 20695: 20690: 20685: 20679: 20677: 20676:Related topics 20673: 20672: 20670: 20669: 20668: 20667: 20662: 20657: 20652: 20647: 20642: 20635:Social science 20632: 20631: 20630: 20628:Space and time 20620: 20615: 20609: 20607: 20603: 20602: 20600: 20599: 20594: 20589: 20584: 20579: 20574: 20569: 20560: 20555: 20550: 20541: 20532: 20527: 20514: 20509: 20504: 20499: 20494: 20489: 20484: 20479: 20474: 20469: 20464: 20459: 20454: 20449: 20444: 20439: 20434: 20429: 20423: 20421: 20417: 20416: 20414: 20413: 20408: 20407: 20406: 20401: 20391: 20386: 20381: 20380: 20379: 20374: 20369: 20359: 20354: 20349: 20344: 20339: 20337:Scientific law 20334: 20333: 20332: 20322: 20317: 20312: 20307: 20302: 20297: 20292: 20287: 20282: 20275: 20274: 20273: 20268: 20258: 20253: 20248: 20246:Falsifiability 20243: 20238: 20233: 20232: 20231: 20221: 20216: 20211: 20206: 20205: 20204: 20194: 20189: 20184: 20179: 20178: 20177: 20175:Mill's Methods 20167: 20156: 20151: 20145: 20143: 20139: 20138: 20131: 20130: 20123: 20116: 20108: 20099: 20098: 20096: 20095: 20090: 20085: 20080: 20074: 20071: 20070: 20068: 20067: 20050: 20044: 20042: 20038: 20037: 20035: 20034: 20029: 20024: 20019: 20014: 20009: 20004: 19999: 19994: 19989: 19984: 19979: 19977:Mental process 19974: 19969: 19964: 19959: 19954: 19949: 19947:Intentionality 19944: 19943: 19942: 19937: 19927: 19922: 19917: 19912: 19907: 19902: 19897: 19892: 19887: 19882: 19877: 19871: 19869: 19865: 19864: 19862: 19861: 19856: 19851: 19846: 19841: 19840: 19839: 19829: 19824: 19819: 19814: 19809: 19804: 19799: 19797:Neutral monism 19794: 19793: 19792: 19782: 19780:Interactionism 19777: 19772: 19767: 19762: 19757: 19752: 19747: 19741: 19739: 19735: 19734: 19732: 19731: 19724: 19719: 19714: 19709: 19704: 19699: 19694: 19692:Baruch Spinoza 19689: 19684: 19679: 19674: 19669: 19664: 19659: 19654: 19649: 19644: 19639: 19634: 19629: 19624: 19619: 19614: 19609: 19604: 19602:Edmund Husserl 19599: 19594: 19589: 19584: 19579: 19574: 19572:René Descartes 19569: 19567:Daniel Dennett 19564: 19559: 19554: 19549: 19544: 19539: 19537:David Chalmers 19534: 19529: 19524: 19522:Franz Brentano 19519: 19514: 19509: 19504: 19502:Alexander Bain 19499: 19494: 19492:Thomas Aquinas 19489: 19484: 19479: 19473: 19471: 19465: 19464: 19457: 19456: 19449: 19442: 19434: 19425: 19424: 19422: 19421: 19419:Space fountain 19416: 19411: 19406: 19401: 19396: 19391: 19386: 19381: 19376: 19371: 19366: 19360: 19357: 19356: 19349: 19348: 19341: 19334: 19326: 19320: 19317: 19316: 19307: 19306: 19296: 19277: 19261: 19260:External links 19258: 19256: 19255: 19227: 19166: 19123: 19114: 19088:Roivainen, Eka 19085: 19081:The New Yorker 19073: 19007: 19001: 18988: 18976: 18967: 18906: 18847: 18840: 18828:The New Yorker 18820: 18790:Cain's Jawbone 18782: 18750: 18740: 18713: 18699: 18689: 18678:Ashish Vaswani 18674: 18654: 18647: 18646: 18645: 18643: 18640: 18638: 18637: 18599: 18587: 18549:(7): 596–615. 18534: 18520: 18496: 18437: 18407: 18403:Moral Machines 18398: 18373: 18337: 18312: 18287: 18262: 18242: 18230: 18205: 18169:(3): 189–191. 18154: 18136: 18122: 18089: 18069: 18051: 18036: 18011: 17996: 17990: 17969: 17942: 17901: 17872: 17852: 17839: 17830: 17804: 17786: 17753:(3): 417–457. 17732: 17706:(4): 357–363. 17691: 17679: 17629: 17600: 17580: 17560: 17535: 17521: 17503: 17492: 17468: 17447: 17422: 17410: 17385: 17330: 17325: 17311:Pinker, Steven 17307: 17301: 17280: 17229: 17217: 17205: 17162: 17132: 17120:(3): 113–126. 17098: 17086: 17057: 17014: 16989: 16971: 16951: 16943:Minsky, Marvin 16939: 16933: 16920: 16874: 16845: 16824:10.1.1.85.8904 16817:(2): 153–164. 16806: 16785:McCarthy, John 16781: 16773:McCarthy, John 16769: 16741:Minsky, Marvin 16737:McCarthy, John 16733: 16716: 16706:Minsky, Marvin 16702: 16682: 16660: 16635: 16610: 16594: 16573:10.1.1.83.7615 16566:(4): 151–190. 16555: 16530: 16493: 16481: 16475: 16463:Lenat, Douglas 16459: 16434: 16409: 16389: 16363:Larson, Jeff; 16360: 16348:(3): 275–279. 16331: 16325: 16307: 16279:(4): 369–371. 16264: 16239: 16209: 16189: 16164: 16139: 16117: 16083:; Slovic, D.; 16077: 16059: 16041: 15996: 15970:(2): 170–184. 15959: 15934: 15913: 15888: 15870: 15837: 15796: 15771: 15765: 15749: 15734: 15704: 15679: 15666: 15650: 15611: 15589: 15576: 15556: 15550: 15529: 15504: 15474: 15449: 15439:(3): 413–429. 15428: 15404: 15383:10.1.1.395.416 15365: 15339: 15312: 15287: 15281: 15268: 15238: 15213: 15195: 15178: 15160: 15142: 15124: 15106: 15100: 15082: 15077:978-0465065707 15076: 15056: 15039: 15019: 14994: 14988: 14970: 14945:(3–4): 1–199. 14927: 14919: 14894: 14867: 14853: 14822: 14808: 14789: 14783: 14762: 14748:(3): 200–219. 14728: 14701: 14672: 14649: 14623:Butler, Samuel 14619: 14607: 14572: 14528:Brooks, Rodney 14524: 14511: 14486: 14472: 14463: 14434: 14408: 14390: 14329: 14287: 14273: 14260: 14236: 14207: 14199: 14195:Machine Ethics 14190: 14172:(4): 477–493. 14161: 14133:Brockman, Greg 14125: 14113: 14101: 14095: 14093: 14090: 14088: 14087: 14081: 14065: 14059: 14043: 14036: 14019: 14017: 14014: 14013: 14012: 14007:978-8894787603 14006: 13990: 13985:978-3319584867 13984: 13966: 13965: 13947: 13931:Poole, David; 13924: 13923: 13905: 13879: 13873: 13851: 13833: 13813: 13795: 13770: 13766: 13765: 13760:978-0070087705 13759: 13743: 13730:978-0134610993 13729: 13715:Norvig, Peter. 13698: 13695: 13693: 13692: 13680: 13668: 13656: 13644: 13632: 13630: 13629: 13615: 13613: 13612: 13607: 13602: 13601:, p. 401) 13595:Edward Fredkin 13584: 13582: 13581: 13575: 13570: 13568:Moravec (1988) 13554: 13542: 13540: 13539: 13529: 13528: 13518: 13517: 13512: 13507: 13485: 13459: 13433: 13399: 13380: 13351: 13320: 13294: 13292: 13291: 13285: 13279: 13271: 13270: 13264: 13246: 13234: 13222: 13210: 13198: 13194:Dennett (1991) 13186: 13174: 13172:, p. 986. 13162: 13158:Roberts (2016) 13147: 13135: 13133: 13132: 13125: 13124: 13117: 13116: 13110: 13104: 13103:, p. 168) 13098: 13081: 13069: 13065:Langley (2011) 13057: 13055:, p. 125. 13053:Crevier (1993) 13045: 13043: 13042: 13036: 13030: 13024: 13016: 13015: 13010: 13008:Dreyfus (1972) 12994: 12992: 12991: 12985: 12979: 12962: 12960: 12959: 12953: 12952:, p. 153) 12945: 12944: 12943:, p. 116) 12930: 12918: 12914:Nilsson (1983) 12906: 12881: 12856: 12824: 12812: 12800: 12788: 12776: 12750: 12738: 12723: 12719:Goswami (2023) 12711: 12699: 12668: 12666: 12665: 12648: 12631: 12629: 12628: 12611: 12599: 12597: 12596: 12593:Newquist (1994 12590: 12584: 12583:, p. 265) 12581:Kurzweil (2005 12570: 12568: 12567: 12561: 12540: 12528: 12526: 12525: 12519: 12506: 12494: 12492: 12491: 12489:Oudeyer (2010) 12486: 12481: 12476: 12460: 12445: 12441:Moravec (1988) 12433: 12421: 12417:Nilsson (1998) 12409: 12397: 12395: 12394: 12391:Newquist (1994 12388: 12382: 12376: 12370: 12364: 12355:Expert systems 12347: 12335: 12323: 12311: 12299: 12297:, p. 109) 12283: 12281:, p. 109) 12267: 12255: 12243: 12231: 12227:Crevier (1993) 12219: 12217: 12216: 12210: 12204: 12198: 12190: 12189: 12165: 12163: 12162: 12156: 12150: 12144: 12130: 12116: 12109: 12086: 12071: 12060:on 23 May 2024 12045: 12023: 11993: 11963: 11946: 11934: 11922: 11918:Edwards (2023) 11910: 11884: 11869: 11857: 11845: 11826: 11814: 11810:Vincent (2023) 11799: 11787: 11785: 11784: 11779: 11774: 11769: 11764: 11751: 11729: 11686: 11651:(3): 387–399. 11631: 11590: 11572: 11554: 11528: 11509: 11483: 11464: 11438: 11412: 11386: 11384:, p. 173. 11382:Russell (2019) 11374: 11370:Wallach (2010) 11362: 11350: 11335: 11323: 11308: 11306: 11305: 11300: 11295: 11290: 11277: 11251: 11225: 11199: 11173: 11147: 11143:Valance (2023) 11135: 11124:. 14 June 2024 11109: 11090: 11060: 11058: 11057: 11055:Sainato (2015) 11052: 11047: 11042: 11029: 11017: 11005: 11001:Bostrom (2015) 10993:Bostrom (2014) 10985: 10981:Russell (2019) 10973: 10969:Bostrom (2014) 10961: 10949: 10937: 10920: 10913:Mahdawi (2017) 10905: 10893: 10881:Game Developer 10867: 10841: 10821: 10809: 10797: 10782: 10758: 10746: 10731:. 3 May 2019. 10720: 10701: 10689: 10686:Sainato (2015) 10674: 10672:, p. 988. 10662: 10647: 10645:, p. 989. 10635: 10609: 10597: 10585: 10581:Rothman (2020) 10573: 10561: 10549: 10537: 10535:, p. 997) 10521: 10509: 10507:, p. 110. 10497: 10492:"Black Box AI" 10483: 10471: 10459: 10446: 10430: 10428:, p. 65). 10417: 10411:, p. 6); 10393: 10377: 10365: 10353: 10341: 10339:, p. 995. 10326: 10314: 10312:, p. 995) 10290: 10286:Goffrey (2008) 10278: 10266: 10251: 10222: 10210: 10198: 10175: 10163: 10144: 10125: 10103: 10084: 10065: 10039: 10020: 9997: 9973: 9948: 9925: 9902: 9890: 9886:Reisner (2023) 9878: 9844: 9818: 9814:Vincent (2022) 9806: 9794: 9782: 9780:, p. 991. 9770: 9758: 9746: 9734: 9732:, p. 987. 9722: 9710: 9671: 9632: 9618: 9596: 9573: 9562:. 24 July 2024 9547: 9540: 9520: 9513: 9485: 9459: 9425: 9399: 9382:Bloomberg News 9368: 9335: 9313: 9280: 9254:Knight, Will. 9246: 9216: 9188: 9175: 9166: 9151: 9139: 9124: 9096: 9075: 9060: 9034: 8991: 8957: 8931: 8876: 8850: 8814: 8788: 8768:The New Yorker 8754: 8704: 8690: 8676: 8619: 8575: 8526: 8507: 8481: 8469: 8457: 8435: 8421: 8409: 8396: 8384: 8367: 8355: 8340: 8338:, p. 785. 8315: 8298: 8296:, p. 751. 8286: 8274: 8262: 8260: 8259: 8242: 8240: 8239: 8234: 8225: 8220: 8200: 8198: 8197: 8180: 8178: 8177: 8160: 8158: 8157: 8140: 8138: 8137: 8132: 8130:Cybenko (1988) 8125: 8124: 8123:, p. 752) 8107: 8105: 8104: 8098: 8092: 8070: 8068: 8067: 8064:Domingos (2015 8061: 8044: 8042: 8041: 8040:, p. 152) 8038:Domingos (2015 8035: 8018: 8016:, p. 152. 8006: 8004: 8003: 8000:Domingos (2015 7997: 7994:Domingos (2015 7991: 7966: 7964: 7963: 7960:Domingos (2015 7957: 7948:Decision trees 7940: 7934:978-8894787603 7933: 7912: 7910: 7909: 7891: 7889: 7888: 7867: 7865: 7864: 7863:, p. 210) 7861:Domingos (2015 7858: 7852: 7846: 7825: 7823:, p. 210. 7813: 7811: 7810: 7804: 7798: 7792: 7791:, §13.3–13.5), 7775: 7763: 7761: 7760: 7754: 7748: 7742: 7725: 7723: 7722: 7701: 7699: 7698: 7687: 7686: 7677:Kalman filters 7675: 7674: 7663: 7662: 7643: 7641: 7640: 7619: 7617: 7616: 7599: 7597: 7596: 7590: 7569: 7567: 7566: 7560: 7554: 7548: 7531: 7529: 7528: 7523: 7509: 7498:(8): 109–115. 7480: 7478: 7477: 7456: 7454: 7453: 7447: 7441: 7435: 7421: 7419: 7418: 7401: 7399: 7398: 7392: 7386: 7380: 7359: 7357: 7356: 7350: 7344: 7327: 7325: 7324: 7323:, chpt. 13–16) 7318: 7312: 7295: 7283: 7281: 7280: 7263: 7237: 7235: 7234: 7213: 7211: 7210: 7193: 7191: 7190: 7184: 7178: 7172: 7147: 7145: 7144: 7138: 7132: 7126: 7097: 7085: 7083: 7082: 7065: 7063: 7062: 7056: 7050: 7044: 7027: 7015: 7011:Waddell (2018) 7003: 7001: 7000: 6995: 6990: 6988:Edelson (1991) 6985: 6969: 6965:MIT AIL (2014) 6957: 6945: 6933: 6921: 6909: 6897: 6895: 6894: 6888: 6871: 6859: 6847: 6843:Vincent (2019) 6835: 6833: 6832: 6827: 6809: 6805:Dickson (2022) 6797: 6785: 6783: 6782: 6764: 6762: 6761: 6755: 6749: 6748:, chpt. 23–24) 6732: 6730: 6729: 6724: 6707: 6682: 6680: 6679: 6674: 6657: 6655: 6654: 6648: 6631: 6629: 6628: 6622: 6602: 6600: 6599: 6596:word embedding 6589: 6579: 6562: 6550: 6538: 6536: 6535: 6529: 6523: 6517: 6516:, chpt. 19–22) 6500: 6498: 6497: 6480: 6478: 6477: 6460: 6458: 6457: 6440: 6438: 6437: 6426: 6425: 6411: 6409: 6408: 6394: 6392: 6391: 6374: 6372: 6371: 6350: 6348: 6347: 6330: 6328:, p. 528. 6318: 6314:Crevier (1993) 6306: 6304:, p. 296. 6294: 6292: 6291: 6281: 6280:, p. 13), 6275: 6269: 6252: 6241: 6240: 6234: 6228: 6222: 6178: 6176: 6175: 6169: 6151: 6149: 6148: 6131: 6129: 6128: 6122: 6116: 6099:event calculus 6086: 6084: 6083: 6077: 6071: 6065: 6031: 6019: 6007: 6003:McGarry (2005) 5995: 5983: 5971: 5959: 5957: 5956: 5950: 5944: 5938: 5917: 5915: 5914: 5909: 5904: 5899: 5881: 5879: 5878: 5852: 5850: 5849: 5843: 5837: 5831: 5830:, chpt. 12–18) 5817: 5815: 5814: 5808: 5802: 5796: 5786: 5772: 5760: 5758: 5757: 5752: 5746: 5744:Goldman (2022) 5723: 5721: 5720: 5717:Newquist (1994 5714: 5708: 5702: 5696: 5675: 5673: 5672: 5669:Newquist (1994 5666: 5661: 5655: 5649: 5621: 5619: 5618: 5615:Newquist (1994 5612: 5606: 5600: 5594: 5561: 5559: 5558: 5552: 5546: 5540: 5523: 5521: 5520: 5514:The proposal: 5513: 5512: 5506: 5500: 5480: 5468: 5466: 5465: 5460: 5455: 5453:Nilsson (1995) 5448: 5447: 5440: 5439: 5417: 5374: 5355: 5337: 5335: 5332: 5329: 5328: 5302: 5292: 5280: 5263: 5250: 5222: 5206: 5198:Terry Winograd 5194:Logic Theorist 5161: 5145: 5129: 5112: 5103: 5090: 5081: 5073:United Nations 5064: 5055: 5042: 5013: 4996: 4984: 4964:Stuart Dreyfus 4920:Karl Steinbuch 4899: 4886: 4869: 4857: 4853:Ray Solomonoff 4837: 4820: 4816:expert systems 4807: 4804:Nilsson (1998) 4780: 4777:Nilsson (1998) 4752: 4751: 4749: 4746: 4745: 4744: 4738: 4732: 4726: 4720: 4717:Mind uploading 4714: 4708: 4702: 4693: 4687: 4681: 4675: 4669: 4663: 4657: 4648: 4640: 4637: 4633:Philip K. Dick 4561:The Terminator 4492:Main article: 4489: 4486: 4464:Edward Fredkin 4433: 4430: 4426:S-shaped curve 4387: 4384: 4382: 4379: 4344:self-awareness 4336:AI is sentient 4331: 4328: 4281: 4278: 4256:David Chalmers 4251:Theory of mind 4242: 4239: 4195: 4192: 4172: 4169: 4150:Soft computing 4148:Main article: 4145: 4142: 4122:Main article: 4119: 4116: 4108:explainable AI 4084:Hubert Dreyfus 4061: 4058: 4036: 4033: 3948: 3945: 3940:Main article: 3937: 3934: 3789:mental objects 3766:expert systems 3643:Main article: 3640: 3637: 3628:Bletchley Park 3544: 3541: 3521: 3520: 3514: 3508: 3502: 3486: 3483: 3442: 3439: 3390:Machine ethics 3385: 3382: 3340:Demis Hassabis 3336:Stuart Russell 3313:misinformation 3269:Stuart Russell 3234:Main article: 3231: 3228: 3171: 3168: 3128:misinformation 3087:, however the 3081:United Nations 3030: 3027: 2945:Explainable AI 2940: 2937: 2848:discrimination 2801: 2798: 2781:filter bubbles 2775:, and extreme 2769:misinformation 2743: 2742:Misinformation 2740: 2698: 2695: 2675:Meta Platforms 2654: 2651: 2587:necessary evil 2541: 2538: 2536: 2535:Risks and harm 2533: 2524:Demis Hassabis 2516:Main article: 2513: 2510: 2490:foreign policy 2486:energy storage 2480: 2477: 2451: 2448: 2381:Main article: 2378: 2375: 2343:Main article: 2340: 2337: 2332:World Pensions 2324: 2321: 2291:Alpha Geometry 2282:trained data. 2268:hallucinations 2228: 2225: 2123:Garry Kasparov 2108:Main article: 2105: 2102: 2046:Main article: 2043: 2040: 2020:image labeling 1908:search engines 1900:Main article: 1897: 1894: 1847: 1844: 1801:hallucinations 1789:corpus of text 1777: 1774: 1720: 1717: 1637: 1634: 1618:Kernel methods 1582: 1579: 1557:Kalman filters 1455: 1452: 1293: 1290: 1250:. Variants of 1214: 1211: 1159: 1156: 1143: 1140: 1135: 1132: 1119: 1116: 1074: 1071: 1024: 1021: 989:word embedding 919: 916: 871:classification 852: 849: 770:rational agent 765: 762: 741:knowledge base 713: 710: 685: 682: 676: 673: 667:to ensure the 547:strategy games 423: 422: 420: 419: 412: 405: 397: 394: 393: 390: 389: 383: 380: 379: 376: 375: 372: 371: 366: 361: 356: 350: 345: 344: 341: 340: 337: 336: 331: 326: 321: 316: 307: 302: 297: 291: 286: 285: 282: 281: 278: 277: 272: 267: 262: 257: 256: 255: 245: 240: 235: 234: 233: 228: 223: 213: 208: 206:Earth sciences 203: 198: 196:Bioinformatics 192: 187: 186: 183: 182: 179: 178: 173: 168: 163: 158: 153: 148: 142: 139: 138: 135: 134: 131: 130: 125: 120: 115: 110: 105: 100: 95: 90: 85: 79: 74: 73: 70: 69: 59: 58: 52: 51: 26: 9: 6: 4: 3: 2: 25631: 25620: 25617: 25615: 25612: 25610: 25607: 25605: 25602: 25600: 25597: 25595: 25592: 25590: 25587: 25586: 25584: 25563: 25560: 25558: 25555: 25553: 25550: 25548: 25545: 25543: 25540: 25538: 25535: 25533: 25530: 25528: 25525: 25523: 25520: 25518: 25515: 25513: 25510: 25508: 25505: 25503: 25500: 25498: 25495: 25493: 25490: 25488: 25485: 25483: 25480: 25478: 25475: 25471: 25468: 25466: 25463: 25461: 25458: 25456: 25453: 25451: 25448: 25447: 25445: 25441: 25438: 25436: 25433: 25432: 25430: 25428: 25425: 25423: 25420: 25418: 25415: 25411: 25408: 25406: 25403: 25402: 25400: 25398: 25395: 25393: 25390: 25388: 25385: 25383: 25380: 25378: 25375: 25373: 25370: 25368: 25365: 25363: 25360: 25358: 25355: 25353: 25350: 25348: 25345: 25343: 25340: 25338: 25335: 25333: 25330: 25328: 25325: 25323: 25320: 25318: 25315: 25313: 25310: 25308: 25305: 25304: 25301: 25297: 25293: 25285: 25280: 25278: 25273: 25271: 25266: 25265: 25262: 25250: 25247: 25245: 25242: 25240: 25237: 25235: 25232: 25230: 25227: 25225: 25222: 25220: 25217: 25215: 25214:Ulla Mitzdorf 25212: 25210: 25207: 25205: 25202: 25200: 25197: 25195: 25192: 25190: 25187: 25185: 25184:Robert Trappl 25182: 25180: 25177: 25175: 25172: 25170: 25167: 25165: 25162: 25160: 25157: 25155: 25152: 25150: 25147: 25145: 25142: 25140: 25139:Margaret Mead 25137: 25135: 25132: 25130: 25127: 25125: 25122: 25120: 25119:Kevin Warwick 25117: 25115: 25112: 25110: 25107: 25105: 25102: 25100: 25097: 25095: 25092: 25090: 25089:Jacque Fresco 25087: 25085: 25082: 25080: 25077: 25075: 25072: 25070: 25067: 25065: 25062: 25060: 25057: 25055: 25052: 25050: 25047: 25045: 25042: 25040: 25037: 25035: 25032: 25030: 25027: 25025: 25022: 25020: 25017: 25015: 25012: 25010: 25007: 25005: 25002: 25000: 24997: 24995: 24992: 24990: 24987: 24985: 24982: 24980: 24977: 24975: 24972: 24970: 24967: 24966: 24964: 24962: 24958: 24952: 24949: 24947: 24944: 24942: 24939: 24937: 24934: 24932: 24929: 24927: 24924: 24922: 24919: 24917: 24914: 24912: 24909: 24907: 24904: 24902: 24899: 24897: 24894: 24892: 24889: 24887: 24884: 24882: 24881:Connectionism 24879: 24877: 24874: 24872: 24869: 24867: 24864: 24862: 24859: 24857: 24854: 24852: 24849: 24847: 24844: 24842: 24839: 24838: 24836: 24832: 24828: 24820: 24815: 24813: 24808: 24806: 24801: 24800: 24797: 24787: 24777: 24771: 24768: 24766: 24765: 24761: 24759: 24758: 24754: 24752: 24751: 24750:The Precipice 24747: 24745: 24744: 24740: 24738: 24735: 24733: 24732: 24728: 24726: 24723: 24722: 24720: 24716: 24710: 24707: 24705: 24702: 24700: 24699:Frank Wilczek 24697: 24695: 24692: 24690: 24687: 24685: 24682: 24680: 24677: 24675: 24672: 24670: 24667: 24665: 24662: 24660: 24657: 24655: 24652: 24650: 24647: 24645: 24644:Dan Hendrycks 24642: 24640: 24637: 24635: 24632: 24630: 24627: 24625: 24622: 24620: 24617: 24615: 24614:Yoshua Bengio 24612: 24610: 24607: 24605: 24602: 24601: 24599: 24595: 24589: 24586: 24584: 24581: 24579: 24576: 24574: 24571: 24569: 24566: 24564: 24561: 24559: 24556: 24554: 24551: 24549: 24546: 24544: 24541: 24539: 24536: 24534: 24531: 24529: 24526: 24524: 24521: 24520: 24518: 24516:Organizations 24514: 24508: 24505: 24503: 24500: 24498: 24495: 24493: 24490: 24488: 24485: 24483: 24480: 24478: 24475: 24473: 24470: 24468: 24465: 24463: 24460: 24458: 24455: 24453: 24450: 24448: 24445: 24443: 24440: 24438: 24435: 24433: 24430: 24428: 24425: 24424: 24422: 24418: 24414: 24410: 24403: 24398: 24396: 24391: 24389: 24384: 24383: 24380: 24368: 24367: 24358: 24356: 24355: 24346: 24345: 24342: 24336: 24333: 24331: 24328: 24326: 24323: 24319: 24316: 24315: 24314: 24311: 24309: 24306: 24304: 24301: 24300: 24298: 24294: 24288: 24285: 24283: 24282:Wolf Robotics 24280: 24278: 24275: 24273: 24270: 24268: 24265: 24263: 24260: 24258: 24255: 24253: 24250: 24248: 24245: 24243: 24240: 24238: 24237:Foster-Miller 24235: 24233: 24230: 24228: 24225: 24223: 24220: 24218: 24215: 24213: 24210: 24208: 24205: 24203: 24200: 24198: 24195: 24194: 24192: 24188: 24182: 24179: 24177: 24174: 24172: 24169: 24167: 24164: 24162: 24159: 24157: 24156:Developmental 24154: 24152: 24149: 24147: 24144: 24142: 24139: 24137: 24134: 24132: 24129: 24127: 24124: 24122: 24119: 24118: 24116: 24112: 24106: 24103: 24101: 24098: 24096: 24093: 24091: 24088: 24087: 24085: 24083: 24079: 24075: 24069: 24066: 24064: 24061: 24059: 24056: 24052: 24049: 24048: 24047: 24044: 24042: 24039: 24038: 24036: 24034: 24030: 24022: 24019: 24017: 24014: 24013: 24012: 24009: 24007: 24004: 24002: 23999: 23995: 23992: 23991: 23990: 23987: 23985: 23982: 23980: 23977: 23975: 23972: 23970: 23967: 23963: 23960: 23958: 23955: 23954: 23953: 23950: 23948: 23945: 23943: 23940: 23938: 23935: 23934: 23932: 23928: 23922: 23921:Soft robotics 23919: 23917: 23916:BEAM robotics 23914: 23912: 23909: 23907: 23904: 23902: 23899: 23897: 23894: 23892: 23889: 23887: 23884: 23882: 23879: 23877: 23874: 23872: 23871:Entertainment 23869: 23867: 23864: 23862: 23859: 23855: 23852: 23851: 23850: 23847: 23845: 23842: 23836: 23833: 23832: 23831: 23828: 23827: 23826: 23823: 23821: 23818: 23816: 23813: 23809: 23806: 23804: 23801: 23799: 23796: 23794: 23791: 23790: 23789: 23786: 23784: 23781: 23780: 23778: 23776: 23772: 23767: 23757: 23754: 23752: 23749: 23747: 23744: 23742: 23739: 23737: 23734: 23732: 23729: 23727: 23724: 23722: 23719: 23717: 23714: 23712: 23709: 23708: 23706: 23704:Main articles 23702: 23698: 23691: 23686: 23684: 23679: 23677: 23672: 23671: 23668: 23656: 23655: 23646: 23645: 23642: 23636: 23635:Transhumanism 23633: 23631: 23628: 23626: 23623: 23621: 23618: 23614: 23611: 23609: 23606: 23604: 23601: 23599: 23596: 23594: 23591: 23589: 23586: 23585: 23584: 23581: 23579: 23576: 23574: 23571: 23569: 23566: 23562: 23559: 23558: 23557: 23554: 23552: 23549: 23547: 23544: 23540: 23537: 23535: 23532: 23530: 23527: 23525: 23522: 23521: 23520: 23517: 23515: 23512: 23510: 23507: 23505: 23502: 23500: 23497: 23495: 23492: 23491: 23489: 23485: 23475: 23472: 23470: 23467: 23463: 23462:Chipless RFID 23460: 23459: 23458: 23455: 23453: 23450: 23446: 23443: 23441: 23438: 23436: 23433: 23431: 23428: 23426: 23423: 23421: 23418: 23416: 23413: 23411: 23408: 23406: 23403: 23401: 23398: 23396: 23393: 23392: 23390: 23388: 23385: 23381: 23378: 23376: 23373: 23372: 23371: 23368: 23366: 23363: 23361: 23358: 23356: 23353: 23351: 23348: 23344: 23341: 23339: 23336: 23334: 23331: 23329: 23326: 23324: 23321: 23319: 23316: 23314: 23311: 23310: 23309: 23306: 23302: 23299: 23298: 23297: 23294: 23293: 23291: 23288: 23281: 23278: 23274: 23270: 23263: 23258: 23256: 23251: 23249: 23244: 23243: 23240: 23228: 23220: 23218: 23210: 23208: 23200: 23199: 23196: 23190: 23187: 23185: 23182: 23180: 23177: 23175: 23172: 23170: 23167: 23165: 23162: 23160: 23157: 23155: 23152: 23150: 23147: 23145: 23142: 23140: 23137: 23135: 23132: 23130: 23127: 23125: 23122: 23120: 23117: 23115: 23112: 23110: 23107: 23105: 23102: 23100: 23097: 23095: 23092: 23091: 23089: 23085: 23079: 23076: 23074: 23071: 23069: 23066: 23064: 23063:Mixed reality 23061: 23059: 23056: 23054: 23051: 23049: 23046: 23044: 23041: 23040: 23038: 23036: 23032: 23026: 23023: 23021: 23018: 23016: 23013: 23011: 23008: 23006: 23003: 23002: 23000: 22998: 22994: 22988: 22985: 22983: 22980: 22978: 22975: 22973: 22970: 22968: 22965: 22963: 22960: 22958: 22955: 22953: 22950: 22949: 22947: 22945: 22941: 22935: 22932: 22930: 22927: 22925: 22922: 22920: 22917: 22915: 22912: 22911: 22909: 22907: 22903: 22897: 22896:Accessibility 22894: 22892: 22891:Visualization 22889: 22887: 22884: 22882: 22879: 22877: 22874: 22873: 22871: 22869: 22865: 22859: 22856: 22854: 22851: 22849: 22846: 22844: 22841: 22839: 22836: 22834: 22831: 22829: 22826: 22824: 22821: 22819: 22816: 22815: 22813: 22811: 22807: 22801: 22798: 22796: 22793: 22791: 22788: 22786: 22783: 22781: 22778: 22776: 22773: 22771: 22768: 22766: 22763: 22761: 22758: 22756: 22753: 22751: 22748: 22746: 22743: 22741: 22738: 22736: 22733: 22732: 22730: 22728: 22724: 22718: 22715: 22713: 22710: 22708: 22705: 22703: 22700: 22698: 22695: 22693: 22690: 22688: 22685: 22683: 22680: 22679: 22677: 22675: 22670: 22664: 22661: 22659: 22656: 22654: 22651: 22649: 22646: 22644: 22641: 22640: 22638: 22636: 22632: 22626: 22623: 22621: 22618: 22616: 22613: 22611: 22608: 22606: 22603: 22601: 22598: 22596: 22593: 22592: 22590: 22588: 22584: 22578: 22575: 22573: 22570: 22568: 22565: 22563: 22560: 22558: 22555: 22553: 22550: 22548: 22545: 22543: 22540: 22538: 22535: 22533: 22530: 22529: 22527: 22525: 22521: 22515: 22512: 22510: 22507: 22505: 22502: 22500: 22497: 22495: 22492: 22490: 22487: 22485: 22482: 22480: 22477: 22475: 22472: 22470: 22467: 22466: 22464: 22462: 22458: 22454: 22448: 22445: 22443: 22440: 22438: 22435: 22433: 22430: 22428: 22425: 22424: 22422: 22418: 22412: 22409: 22407: 22404: 22402: 22399: 22397: 22394: 22392: 22389: 22387: 22384: 22383: 22381: 22379: 22375: 22369: 22366: 22364: 22361: 22359: 22358:Dependability 22356: 22354: 22351: 22349: 22346: 22345: 22343: 22339: 22333: 22329: 22326: 22324: 22321: 22319: 22316: 22314: 22311: 22309: 22306: 22304: 22301: 22299: 22296: 22294: 22291: 22289: 22286: 22284: 22281: 22280: 22278: 22276: 22272: 22267: 22261: 22257: 22250: 22245: 22243: 22238: 22236: 22231: 22230: 22227: 22213: 22210: 22208: 22205: 22204: 22197: 22193: 22190: 22188: 22185: 22184: 22181: 22177: 22176: 22173: 22167: 22164: 22162: 22159: 22157: 22154: 22152: 22149: 22147: 22144: 22142: 22139: 22137: 22134: 22132: 22129: 22127: 22124: 22122: 22119: 22117: 22114: 22112: 22109: 22107: 22104: 22102: 22099: 22097: 22094: 22093: 22091: 22089:Architectures 22087: 22081: 22078: 22076: 22073: 22071: 22068: 22066: 22063: 22061: 22058: 22056: 22053: 22051: 22048: 22046: 22043: 22041: 22038: 22037: 22035: 22033:Organizations 22031: 22025: 22022: 22020: 22017: 22015: 22012: 22010: 22007: 22005: 22002: 22000: 21997: 21995: 21992: 21990: 21987: 21985: 21982: 21980: 21977: 21975: 21972: 21970: 21969:Yoshua Bengio 21967: 21966: 21964: 21960: 21950: 21949:Robot control 21947: 21943: 21940: 21939: 21938: 21935: 21933: 21930: 21928: 21925: 21923: 21920: 21918: 21915: 21913: 21910: 21908: 21905: 21903: 21900: 21899: 21897: 21893: 21887: 21884: 21882: 21879: 21877: 21874: 21872: 21869: 21867: 21866:Chinchilla AI 21864: 21862: 21859: 21857: 21854: 21852: 21849: 21847: 21844: 21842: 21839: 21837: 21834: 21832: 21829: 21827: 21824: 21822: 21819: 21817: 21814: 21812: 21809: 21805: 21802: 21801: 21800: 21797: 21795: 21792: 21790: 21787: 21785: 21782: 21780: 21777: 21775: 21772: 21771: 21769: 21765: 21759: 21756: 21752: 21749: 21747: 21744: 21743: 21742: 21739: 21735: 21732: 21730: 21727: 21725: 21722: 21721: 21720: 21717: 21715: 21712: 21710: 21707: 21705: 21702: 21700: 21697: 21695: 21692: 21690: 21687: 21685: 21682: 21680: 21677: 21675: 21672: 21671: 21669: 21665: 21662: 21658: 21652: 21649: 21647: 21644: 21642: 21639: 21637: 21634: 21632: 21629: 21627: 21624: 21622: 21619: 21618: 21616: 21612: 21606: 21603: 21601: 21598: 21596: 21593: 21591: 21588: 21586: 21583: 21582: 21580: 21576: 21568: 21565: 21564: 21563: 21560: 21558: 21555: 21553: 21550: 21546: 21545:Deep learning 21543: 21542: 21541: 21538: 21534: 21531: 21530: 21529: 21526: 21525: 21523: 21519: 21513: 21510: 21508: 21505: 21501: 21498: 21497: 21496: 21493: 21491: 21488: 21484: 21481: 21479: 21476: 21474: 21471: 21470: 21469: 21466: 21464: 21461: 21459: 21456: 21454: 21451: 21449: 21446: 21444: 21441: 21439: 21436: 21434: 21433:Hallucination 21431: 21427: 21424: 21423: 21422: 21419: 21417: 21414: 21410: 21407: 21406: 21405: 21402: 21401: 21399: 21395: 21389: 21386: 21384: 21381: 21379: 21376: 21374: 21371: 21369: 21366: 21364: 21361: 21359: 21356: 21354: 21351: 21349: 21348: 21344: 21343: 21341: 21339: 21335: 21326: 21321: 21319: 21314: 21312: 21307: 21306: 21303: 21291: 21288: 21287: 21285: 21283: 21279: 21273: 21270: 21268: 21265: 21263: 21260: 21258: 21255: 21253: 21250: 21248: 21245: 21243: 21240: 21238: 21235: 21233: 21230: 21228: 21225: 21223: 21220: 21218: 21215: 21213: 21210: 21208: 21205: 21204: 21202: 21198: 21192: 21189: 21187: 21184: 21182: 21179: 21177: 21174: 21173: 21171: 21169: 21165: 21159: 21156: 21154: 21151: 21149: 21148:Cuckoo search 21146: 21144: 21141: 21139: 21136: 21134: 21131: 21130: 21128: 21124: 21118: 21115: 21113: 21110: 21108: 21105: 21103: 21100: 21098: 21095: 21093: 21090: 21088: 21085: 21083: 21080: 21078: 21075: 21073: 21070: 21068: 21065: 21063: 21060: 21059: 21057: 21055: 21051: 21045: 21042: 21040: 21037: 21035: 21032: 21030: 21027: 21025: 21022: 21021: 21019: 21015: 21011: 21004: 20999: 20997: 20992: 20990: 20985: 20984: 20981: 20970: 20965: 20960: 20958: 20948: 20946: 20943: 20940: 20934: 20931: 20929: 20926: 20924: 20921: 20919: 20916: 20914: 20911: 20909: 20906: 20904: 20901: 20899: 20896: 20894: 20891: 20889: 20888:Rudolf Carnap 20886: 20884: 20881: 20879: 20876: 20874: 20871: 20869: 20866: 20864: 20861: 20859: 20856: 20854: 20851: 20849: 20846: 20844: 20841: 20839: 20836: 20834: 20831: 20829: 20826: 20824: 20823:Auguste Comte 20821: 20820: 20811: 20808: 20806: 20803: 20801: 20798: 20796: 20795:Francis Bacon 20793: 20791: 20788: 20787: 20785: 20781: 20778: 20776: 20772: 20766: 20763: 20761: 20758: 20756: 20753: 20751: 20748: 20746: 20743: 20741: 20738: 20736: 20733: 20731: 20728: 20724: 20723:Pseudoscience 20721: 20720: 20719: 20716: 20714: 20711: 20709: 20706: 20704: 20701: 20699: 20696: 20694: 20691: 20689: 20686: 20684: 20681: 20680: 20678: 20674: 20666: 20663: 20661: 20658: 20656: 20653: 20651: 20648: 20646: 20643: 20641: 20638: 20637: 20636: 20633: 20629: 20626: 20625: 20624: 20621: 20619: 20616: 20614: 20611: 20610: 20608: 20604: 20598: 20595: 20593: 20590: 20588: 20585: 20583: 20582:Structuralism 20580: 20578: 20575: 20573: 20570: 20568: 20564: 20561: 20559: 20556: 20554: 20551: 20549: 20545: 20544:Received view 20542: 20540: 20536: 20533: 20531: 20528: 20526: 20522: 20518: 20515: 20513: 20510: 20508: 20505: 20503: 20500: 20498: 20495: 20493: 20490: 20488: 20485: 20483: 20480: 20478: 20475: 20473: 20470: 20468: 20465: 20463: 20460: 20458: 20455: 20453: 20452:Contextualism 20450: 20448: 20445: 20443: 20440: 20438: 20435: 20433: 20430: 20428: 20425: 20424: 20422: 20418: 20412: 20409: 20405: 20402: 20400: 20397: 20396: 20395: 20392: 20390: 20387: 20385: 20382: 20378: 20375: 20373: 20370: 20368: 20365: 20364: 20363: 20360: 20358: 20355: 20353: 20350: 20348: 20345: 20343: 20340: 20338: 20335: 20331: 20328: 20327: 20326: 20323: 20321: 20318: 20316: 20313: 20311: 20308: 20306: 20303: 20301: 20298: 20296: 20293: 20291: 20288: 20286: 20283: 20281: 20280: 20276: 20272: 20269: 20267: 20264: 20263: 20262: 20259: 20257: 20254: 20252: 20249: 20247: 20244: 20242: 20239: 20237: 20234: 20230: 20227: 20226: 20225: 20222: 20220: 20217: 20215: 20212: 20210: 20207: 20203: 20200: 20199: 20198: 20195: 20193: 20190: 20188: 20185: 20183: 20180: 20176: 20173: 20172: 20171: 20168: 20166: 20165: 20161: 20157: 20155: 20152: 20150: 20147: 20146: 20144: 20140: 20136: 20129: 20124: 20122: 20117: 20115: 20110: 20109: 20106: 20094: 20091: 20089: 20086: 20084: 20081: 20079: 20076: 20075: 20072: 20066: 20062: 20058: 20054: 20051: 20049: 20046: 20045: 20043: 20039: 20033: 20030: 20028: 20027:Understanding 20025: 20023: 20020: 20018: 20015: 20013: 20010: 20008: 20005: 20003: 20000: 19998: 19995: 19993: 19990: 19988: 19985: 19983: 19980: 19978: 19975: 19973: 19970: 19968: 19965: 19963: 19960: 19958: 19955: 19953: 19952:Introspection 19950: 19948: 19945: 19941: 19938: 19936: 19933: 19932: 19931: 19928: 19926: 19923: 19921: 19918: 19916: 19913: 19911: 19908: 19906: 19905:Consciousness 19903: 19901: 19898: 19896: 19893: 19891: 19888: 19886: 19883: 19881: 19878: 19876: 19873: 19872: 19870: 19866: 19860: 19857: 19855: 19852: 19850: 19847: 19845: 19842: 19838: 19835: 19834: 19833: 19830: 19828: 19827:Phenomenology 19825: 19823: 19822:Phenomenalism 19820: 19818: 19815: 19813: 19812:Occasionalism 19810: 19808: 19805: 19803: 19800: 19798: 19795: 19791: 19788: 19787: 19786: 19785:Naïve realism 19783: 19781: 19778: 19776: 19775:Functionalism 19773: 19771: 19768: 19766: 19763: 19761: 19758: 19756: 19753: 19751: 19748: 19746: 19743: 19742: 19740: 19736: 19730: 19729: 19725: 19723: 19720: 19718: 19717:Stephen Yablo 19715: 19713: 19710: 19708: 19705: 19703: 19700: 19698: 19695: 19693: 19690: 19688: 19685: 19683: 19680: 19678: 19675: 19673: 19672:Richard Rorty 19670: 19668: 19667:Hilary Putnam 19665: 19663: 19660: 19658: 19655: 19653: 19650: 19648: 19645: 19643: 19642:Marvin Minsky 19640: 19638: 19635: 19633: 19630: 19628: 19625: 19623: 19620: 19618: 19617:Immanuel Kant 19615: 19613: 19610: 19608: 19607:William James 19605: 19603: 19600: 19598: 19595: 19593: 19590: 19588: 19585: 19583: 19580: 19578: 19575: 19573: 19570: 19568: 19565: 19563: 19560: 19558: 19555: 19553: 19550: 19548: 19545: 19543: 19540: 19538: 19535: 19533: 19530: 19528: 19525: 19523: 19520: 19518: 19515: 19513: 19512:Henri Bergson 19510: 19508: 19505: 19503: 19500: 19498: 19495: 19493: 19490: 19488: 19485: 19483: 19480: 19478: 19475: 19474: 19472: 19470: 19466: 19462: 19455: 19450: 19448: 19443: 19441: 19436: 19435: 19432: 19420: 19417: 19415: 19412: 19410: 19407: 19405: 19402: 19400: 19397: 19395: 19392: 19390: 19387: 19385: 19382: 19380: 19379:Frame problem 19377: 19375: 19372: 19370: 19367: 19365: 19362: 19361: 19358: 19354: 19353:John McCarthy 19347: 19342: 19340: 19335: 19333: 19328: 19327: 19324: 19318: 19311: 19304: 19300: 19297: 19293: 19292: 19287: 19283: 19278: 19274: 19273: 19268: 19264: 19263: 19241: 19234: 19233: 19228: 19216: 19212: 19208: 19204: 19200: 19196: 19192: 19188: 19184: 19180: 19176: 19172: 19167: 19152: 19148: 19144: 19141:(4): 629–49. 19140: 19136: 19129: 19124: 19121: 19120: 19115: 19111: 19107: 19106: 19101: 19097: 19093: 19089: 19086: 19083: 19082: 19077: 19074: 19071: 19057: 19053: 19049: 19045: 19041: 19037: 19033: 19029: 19025: 19021: 19017: 19013: 19008: 19004: 19002:9780374257835 18998: 18994: 18989: 18986: 18985: 18980: 18977: 18974: 18973: 18968: 18956: 18952: 18948: 18944: 18940: 18936: 18932: 18928: 18924: 18920: 18916: 18912: 18907: 18903: 18899: 18895: 18891: 18886: 18881: 18877: 18873: 18869: 18865: 18861: 18857: 18853: 18848: 18845: 18841: 18838: 18834: 18830: 18829: 18824: 18821: 18818: 18817:training data 18814: 18813:civilizations 18810: 18806: 18802: 18798: 18797: 18792: 18791: 18786: 18783: 18780: 18776: 18772: 18768: 18767: 18762: 18758: 18754: 18753:Gleick, James 18751: 18749: 18745: 18741: 18738: 18735: 18731: 18730:Alex Pentland 18727: 18723: 18722: 18717: 18714: 18711: 18707: 18703: 18700: 18697: 18693: 18690: 18687: 18683: 18679: 18676: 18675: 18669: 18668: 18667: 18661: 18657: 18624: 18620: 18616: 18612: 18605: 18600: 18597: 18593: 18588: 18576: 18572: 18568: 18564: 18560: 18556: 18552: 18548: 18544: 18540: 18535: 18532: 18531: 18526: 18521: 18509: 18505: 18501: 18497: 18482: 18478: 18474: 18470: 18466: 18462: 18458: 18454: 18450: 18443: 18438: 18426: 18422: 18417: 18412: 18408: 18404: 18399: 18387: 18383: 18379: 18374: 18362: 18358: 18354: 18350: 18346: 18342: 18341:Vinge, Vernor 18338: 18326: 18322: 18318: 18313: 18301: 18297: 18293: 18288: 18276: 18272: 18268: 18263: 18252: 18248: 18243: 18240: 18236: 18231: 18219: 18215: 18211: 18206: 18202: 18198: 18194: 18190: 18185: 18180: 18176: 18172: 18168: 18164: 18160: 18155: 18143: 18139: 18133: 18129: 18128: 18123: 18120: 18116: 18112: 18108: 18104: 18100: 18099: 18094: 18090: 18079: 18075: 18070: 18058: 18054: 18048: 18044: 18043: 18037: 18025: 18021: 18017: 18012: 18008: 18007: 18002: 17997: 17993: 17987: 17983: 17979: 17975: 17970: 17955: 17948: 17943: 17939: 17919: 17912: 17911: 17906: 17902: 17898: 17894: 17890: 17886: 17882: 17878: 17873: 17862: 17858: 17853: 17849: 17845: 17840: 17836: 17831: 17819: 17815: 17811: 17807: 17801: 17797: 17796: 17791: 17787: 17772: 17768: 17764: 17760: 17756: 17752: 17748: 17741: 17737: 17733: 17729: 17725: 17721: 17717: 17713: 17709: 17705: 17701: 17697: 17692: 17688: 17684: 17680: 17676: 17672: 17668: 17664: 17660: 17656: 17651: 17646: 17642: 17638: 17634: 17630: 17626: 17622: 17618: 17614: 17610: 17606: 17601: 17590: 17586: 17581: 17570: 17566: 17561: 17549: 17545: 17541: 17536: 17532: 17528: 17524: 17518: 17514: 17513: 17508: 17504: 17500: 17499: 17493: 17481: 17477: 17473: 17469: 17457: 17453: 17448: 17436: 17432: 17431:Distillations 17428: 17423: 17420: 17416: 17411: 17399: 17395: 17391: 17386: 17374: 17370: 17366: 17361: 17356: 17352: 17348: 17344: 17340: 17336: 17331: 17328: 17322: 17318: 17317: 17312: 17308: 17304: 17298: 17294: 17290: 17286: 17281: 17266: 17262: 17258: 17254: 17250: 17246: 17242: 17235: 17230: 17226: 17222: 17218: 17214: 17210: 17206: 17203: 17186: 17182: 17178: 17171: 17167: 17166:Nilsson, Nils 17163: 17152: 17148: 17144: 17143: 17138: 17133: 17128: 17123: 17119: 17115: 17111: 17107: 17103: 17102:Newell, Allen 17099: 17095: 17091: 17090:Nilsson, Nils 17087: 17083: 17079: 17075: 17071: 17068:(1): 82–101. 17067: 17063: 17058: 17051: 17047: 17043: 17039: 17035: 17031: 17027: 17020: 17015: 17003: 16999: 16998:The Economist 16995: 16990: 16978: 16974: 16968: 16963: 16962: 16961:Mind Children 16956: 16955:Moravec, Hans 16952: 16948: 16944: 16940: 16936: 16930: 16926: 16921: 16910: 16906: 16902: 16898: 16894: 16890: 16886: 16882: 16881: 16875: 16871: 16867: 16863: 16859: 16855: 16851: 16846: 16842: 16838: 16834: 16830: 16825: 16820: 16816: 16812: 16807: 16796: 16792: 16791: 16786: 16782: 16778: 16774: 16770: 16758: 16754: 16750: 16746: 16742: 16738: 16734: 16730: 16726: 16722: 16717: 16713: 16712: 16707: 16703: 16692: 16688: 16683: 16672: 16668: 16667: 16661: 16649: 16645: 16641: 16636: 16624: 16620: 16616: 16611: 16607: 16603: 16599: 16595: 16591: 16587: 16583: 16579: 16574: 16569: 16565: 16561: 16556: 16544: 16540: 16536: 16531: 16524: 16520: 16516: 16512: 16508: 16501: 16500: 16494: 16490: 16486: 16482: 16478: 16472: 16468: 16464: 16460: 16448: 16444: 16440: 16435: 16431: 16427: 16423: 16419: 16415: 16410: 16399: 16398:Enterprise AI 16395: 16390: 16378: 16374: 16370: 16366: 16365:Angwin, Julia 16361: 16356: 16351: 16347: 16343: 16342: 16337: 16332: 16328: 16322: 16318: 16317: 16312: 16311:Kurzweil, Ray 16308: 16304: 16300: 16295: 16290: 16286: 16282: 16278: 16274: 16270: 16265: 16253: 16249: 16245: 16240: 16228: 16224: 16223: 16218: 16214: 16210: 16198: 16194: 16190: 16178: 16174: 16170: 16165: 16153: 16149: 16145: 16140: 16136: 16132: 16128: 16124: 16120: 16114: 16110: 16106: 16102: 16098: 16094: 16090: 16086: 16085:Tversky, Amos 16082: 16078: 16066: 16062: 16056: 16053:. Macmillan. 16052: 16051: 16046: 16042: 16038: 16034: 16030: 16026: 16022: 16018: 16014: 16010: 16006: 16002: 15997: 15993: 15989: 15985: 15981: 15977: 15973: 15969: 15965: 15960: 15948: 15944: 15940: 15935: 15923: 15919: 15914: 15902: 15898: 15894: 15889: 15885: 15878: 15877: 15871: 15859: 15855: 15851: 15847: 15843: 15838: 15834: 15830: 15826: 15822: 15818: 15814: 15810: 15806: 15802: 15797: 15785: 15781: 15777: 15772: 15768: 15762: 15758: 15754: 15750: 15746: 15745: 15740: 15735: 15723: 15719: 15718: 15713: 15709: 15705: 15693: 15689: 15685: 15680: 15676: 15672: 15667: 15663: 15659: 15655: 15651: 15647: 15643: 15639: 15635: 15630: 15625: 15621: 15617: 15612: 15601: 15597: 15596: 15595:Deep Learning 15590: 15587: 15586: 15581: 15577: 15566: 15562: 15557: 15553: 15547: 15543: 15538: 15537: 15530: 15518: 15514: 15510: 15505: 15493: 15489: 15488: 15483: 15479: 15475: 15463: 15459: 15455: 15450: 15446: 15442: 15438: 15434: 15429: 15417: 15413: 15412:The Economist 15409: 15405: 15401: 15397: 15393: 15389: 15384: 15379: 15375: 15371: 15366: 15363: 15351: 15350: 15345: 15340: 15325: 15318: 15313: 15301: 15297: 15293: 15288: 15284: 15278: 15274: 15269: 15264: 15259: 15255: 15251: 15247: 15243: 15239: 15227: 15223: 15219: 15214: 15202: 15198: 15192: 15187: 15186: 15179: 15167: 15163: 15157: 15153: 15152: 15147: 15146:Dyson, George 15143: 15131: 15127: 15121: 15117: 15116: 15111: 15107: 15103: 15097: 15093: 15092: 15087: 15083: 15079: 15073: 15069: 15065: 15061: 15057: 15053: 15049: 15048:Science Alert 15045: 15040: 15029: 15025: 15020: 15008: 15004: 15000: 14995: 14991: 14985: 14981: 14980: 14975: 14971: 14956: 14952: 14948: 14944: 14940: 14933: 14928: 14924: 14920: 14908: 14904: 14900: 14895: 14883: 14879: 14878:Bloomberg.com 14874: 14868: 14864: 14860: 14856: 14850: 14846: 14842: 14837: 14832: 14828: 14823: 14819: 14815: 14811: 14805: 14801: 14799: 14794: 14790: 14786: 14780: 14776: 14772: 14768: 14763: 14751: 14747: 14743: 14742: 14737: 14733: 14729: 14717: 14713: 14712: 14707: 14702: 14698: 14694: 14690: 14686: 14682: 14678: 14673: 14669: 14665: 14661: 14657: 14656: 14650: 14638: 14634: 14633: 14628: 14624: 14620: 14617: 14613: 14608: 14604: 14600: 14595: 14590: 14586: 14582: 14578: 14573: 14566: 14562: 14558: 14553: 14548: 14545:(1–2): 3–15. 14544: 14540: 14533: 14529: 14525: 14521: 14517: 14512: 14500: 14496: 14492: 14487: 14483: 14482: 14477: 14476:Bostrom, Nick 14473: 14469: 14464: 14449: 14442: 14441: 14435: 14423: 14419: 14415: 14411: 14405: 14401: 14400: 14395: 14391: 14387: 14383: 14379: 14375: 14370: 14365: 14361: 14357: 14352: 14351:10.2196/42936 14347: 14343: 14339: 14335: 14330: 14327: 14323: 14318: 14313: 14309: 14305: 14301: 14297: 14293: 14288: 14284: 14280: 14276: 14270: 14266: 14261: 14249: 14245: 14241: 14237: 14233: 14229: 14225: 14221: 14217: 14213: 14208: 14205: 14200: 14196: 14191: 14187: 14183: 14179: 14175: 14171: 14167: 14162: 14150: 14146: 14142: 14138: 14134: 14130: 14126: 14123: 14119: 14114: 14112: 14108: 14105: 14102: 14100: 14097: 14096: 14092:Other sources 14084: 14078: 14074: 14070: 14066: 14062: 14060:1-56881-205-1 14056: 14052: 14048: 14044: 14039: 14037:0-465-02997-3 14033: 14029: 14025: 14021: 14020: 14016:History of AI 14009: 14003: 13999: 13995: 13991: 13987: 13981: 13977: 13972: 13971: 13970: 13954: 13950: 13944: 13940: 13939: 13934: 13929: 13928: 13927: 13912: 13908: 13902: 13898: 13897: 13892: 13891:Goebel, Randy 13888: 13884: 13880: 13876: 13874:0-13-790395-2 13870: 13866: 13865: 13860: 13859:Norvig, Peter 13856: 13852: 13840: 13836: 13830: 13825: 13824: 13818: 13817:Nilsson, Nils 13814: 13802: 13798: 13792: 13787: 13786: 13780: 13776: 13775:Luger, George 13772: 13771: 13769: 13762: 13756: 13752: 13748: 13744: 13740: 13736: 13732: 13726: 13722: 13721: 13716: 13712: 13708: 13707: 13706: 13704: 13703:Open Syllabus 13689: 13688:Galvan (1997) 13684: 13677: 13672: 13665: 13660: 13653: 13648: 13641: 13636: 13627: 13624: 13623: 13619: 13611: 13608: 13606: 13605:Butler (1863) 13603: 13600: 13597:is quoted in 13596: 13593: 13592: 13588: 13579: 13576: 13574: 13571: 13569: 13566: 13565: 13563: 13562:Transhumanism 13558: 13551: 13546: 13538: 13535: 13534: 13532: 13527: 13524: 13523: 13521: 13516: 13513: 13511: 13508: 13505: 13502: 13501: 13499: 13495: 13489: 13474: 13470: 13463: 13448: 13444: 13437: 13422: 13418: 13414: 13410: 13403: 13395: 13391: 13384: 13369: 13365: 13358: 13356: 13340: 13336: 13329: 13327: 13325: 13309: 13308:The Spectator 13305: 13298: 13289: 13288:Crevier (1993 13286: 13283: 13280: 13277: 13274: 13273: 13268: 13267:Searle (1999) 13265: 13262: 13261:Searle (1980) 13259: 13258: 13256: 13250: 13243: 13238: 13231: 13230:Searle (1980) 13226: 13219: 13218:Searle (1999) 13214: 13207: 13202: 13195: 13190: 13183: 13178: 13171: 13166: 13159: 13154: 13152: 13144: 13139: 13131: 13128: 13127: 13123: 13122:Minsky (1986) 13120: 13119: 13115:, p. 24) 13114: 13111: 13108: 13107:Nilsson (1983 13105: 13102: 13101:Crevier (1993 13099: 13096: 13093: 13092: 13090: 13085: 13078: 13073: 13066: 13061: 13054: 13049: 13040: 13037: 13034: 13031: 13028: 13025: 13022: 13021:Crevier (1993 13019: 13018: 13014: 13011: 13009: 13006: 13005: 13003: 12998: 12989: 12986: 12984:, p. 29) 12983: 12980: 12977: 12976:Moravec (1988 12974: 12973: 12971: 12966: 12958:, p. 19) 12957: 12954: 12951: 12948: 12947: 12942: 12939: 12938: 12934: 12927: 12922: 12916:, p. 10. 12915: 12910: 12895: 12891: 12885: 12870: 12866: 12860: 12844: 12840: 12839: 12834: 12828: 12821: 12820:Minsky (1986) 12816: 12809: 12804: 12797: 12792: 12785: 12780: 12765: 12761: 12754: 12747: 12746:Turing (1950) 12742: 12735: 12734:Turing (1950) 12730: 12728: 12720: 12715: 12708: 12703: 12687: 12683: 12679: 12672: 12664:, p. 26) 12663: 12660: 12659: 12657: 12652: 12645: 12644:Clark (2015b) 12640: 12638: 12636: 12626: 12623: 12622: 12620: 12615: 12608: 12603: 12594: 12591: 12588: 12585: 12582: 12579: 12578: 12574: 12565: 12562: 12559: 12556: 12555: 12553: 12549: 12544: 12538:, p. 26. 12537: 12532: 12523: 12520: 12517: 12516:Crevier (1993 12514: 12513: 12510: 12504:, p. 25. 12503: 12498: 12490: 12487: 12485: 12482: 12480: 12477: 12475: 12472: 12471: 12469: 12464: 12457: 12456:Brooks (1990) 12452: 12450: 12442: 12437: 12430: 12425: 12418: 12413: 12407:, p. 24. 12406: 12401: 12392: 12389: 12386: 12385:Crevier (1993 12383: 12380: 12377: 12375:, chpt. 17.4) 12374: 12373:Nilsson (1998 12371: 12368: 12365: 12362: 12359: 12358: 12356: 12351: 12345:, p. 22. 12344: 12339: 12332: 12327: 12320: 12315: 12309:, p. 21. 12308: 12303: 12296: 12295:Crevier (1993 12292: 12287: 12280: 12279:Crevier (1993 12276: 12271: 12264: 12259: 12253:, p. 18. 12252: 12247: 12241:, p. 17. 12240: 12235: 12228: 12223: 12214: 12211: 12208: 12205: 12203:, p. 24) 12202: 12201:Crevier (1993 12199: 12196: 12193: 12192: 12188: 12187:Turing (1950) 12185: 12184: 12182: 12178: 12172: 12170: 12160: 12159:Moravec (1988 12157: 12154: 12151: 12148: 12147:Crevier (1993 12145: 12142: 12139: 12138: 12134: 12126: 12120: 12112: 12110:0-19-825079-7 12106: 12102: 12095: 12093: 12091: 12083: 12078: 12076: 12059: 12055: 12049: 12033: 12027: 12011: 12007: 12003: 11997: 11981: 11977: 11973: 11967: 11959: 11958: 11950: 11943: 11938: 11931: 11926: 11919: 11914: 11898: 11894: 11888: 11880: 11873: 11866: 11861: 11854: 11849: 11842: 11841:UNESCO (2021) 11837: 11835: 11833: 11831: 11823: 11818: 11811: 11806: 11804: 11796: 11791: 11783: 11782:Buiten (2019) 11780: 11778: 11775: 11773: 11770: 11768: 11765: 11763: 11760: 11759: 11755: 11739: 11733: 11725: 11721: 11717: 11713: 11709: 11705: 11701: 11697: 11690: 11682: 11678: 11674: 11670: 11666: 11662: 11658: 11654: 11650: 11646: 11642: 11635: 11627: 11623: 11618: 11613: 11609: 11605: 11601: 11594: 11583: 11576: 11565: 11558: 11543: 11539: 11532: 11524: 11520: 11513: 11498: 11494: 11487: 11479: 11475: 11468: 11453: 11449: 11442: 11427: 11423: 11416: 11401: 11397: 11390: 11383: 11378: 11371: 11366: 11359: 11354: 11347: 11342: 11340: 11332: 11327: 11320: 11315: 11313: 11304: 11301: 11299: 11296: 11294: 11291: 11289: 11288:Brooks (2014) 11286: 11285: 11281: 11266: 11262: 11255: 11240: 11236: 11229: 11214: 11210: 11203: 11188: 11184: 11177: 11162: 11158: 11151: 11144: 11139: 11123: 11122:Bloomberg BNN 11119: 11113: 11105: 11101: 11094: 11078: 11074: 11070: 11064: 11056: 11053: 11051: 11048: 11046: 11045:Holley (2015) 11043: 11041: 11038: 11037: 11033: 11026: 11021: 11014: 11013:Harari (2023) 11009: 11002: 10998: 10994: 10989: 10982: 10977: 10970: 10965: 10958: 10953: 10946: 10941: 10933: 10932: 10924: 10918: 10914: 10909: 10902: 10897: 10882: 10878: 10871: 10856: 10855:Rest of World 10852: 10845: 10839:, p. 33) 10838: 10834: 10830: 10825: 10819:, p. 33. 10818: 10813: 10806: 10801: 10795: 10791: 10786: 10779: 10775: 10771: 10765: 10763: 10755: 10750: 10734: 10730: 10724: 10716: 10712: 10705: 10698: 10697:Harari (2018) 10693: 10687: 10683: 10678: 10671: 10666: 10659: 10654: 10652: 10644: 10639: 10624: 10620: 10613: 10606: 10601: 10594: 10589: 10582: 10577: 10570: 10565: 10559:, p. 83. 10558: 10553: 10547:, p. 91. 10546: 10541: 10534: 10530: 10525: 10518: 10513: 10506: 10501: 10493: 10487: 10480: 10479:Sample (2017) 10475: 10468: 10463: 10457:, p. 80) 10456: 10450: 10443: 10439: 10434: 10427: 10421: 10414: 10410: 10406: 10402: 10397: 10390: 10386: 10381: 10374: 10369: 10362: 10357: 10350: 10345: 10338: 10333: 10331: 10324:, p. 25. 10323: 10318: 10311: 10307: 10303: 10302:Goffrey (2008 10299: 10294: 10288:, p. 17. 10287: 10282: 10275: 10270: 10263: 10258: 10256: 10240: 10236: 10229: 10227: 10219: 10214: 10207: 10202: 10194: 10190: 10186: 10179: 10172: 10167: 10159: 10155: 10148: 10140: 10136: 10129: 10121: 10120:Goldman Sachs 10114: 10107: 10099: 10095: 10088: 10080: 10076: 10069: 10053: 10049: 10043: 10035: 10031: 10024: 10016: 10012: 10008: 10001: 9993: 9989: 9988:The Economist 9984: 9977: 9969: 9965: 9960: 9952: 9944: 9940: 9936: 9929: 9921: 9920: 9912: 9906: 9899: 9894: 9887: 9882: 9867: 9863: 9859: 9855: 9848: 9833: 9829: 9822: 9815: 9810: 9804:, p. 63. 9803: 9798: 9791: 9786: 9779: 9774: 9767: 9762: 9755: 9750: 9743: 9738: 9731: 9726: 9719: 9714: 9706: 9702: 9698: 9694: 9690: 9686: 9682: 9675: 9667: 9663: 9659: 9655: 9651: 9647: 9643: 9636: 9621: 9615: 9611: 9607: 9600: 9592: 9588: 9584: 9577: 9561: 9557: 9551: 9543: 9541:9780134610993 9537: 9533: 9532: 9524: 9516: 9514:9781009258197 9510: 9506: 9502: 9498: 9497: 9489: 9474: 9470: 9463: 9448: 9444: 9440: 9436: 9429: 9414: 9410: 9403: 9387: 9383: 9379: 9372: 9356: 9352: 9351: 9346: 9339: 9330: 9325: 9317: 9298: 9291: 9284: 9269: 9265: 9261: 9257: 9250: 9242: 9238: 9234: 9230: 9223: 9221: 9214: 9206: 9205: 9197: 9195: 9193: 9185: 9179: 9170: 9163: 9162: 9155: 9148: 9143: 9136: 9134: 9128: 9113: 9112: 9107: 9100: 9091: 9086: 9079: 9072: 9071: 9064: 9049: 9048:New Scientist 9045: 9038: 9030: 9026: 9022: 9018: 9014: 9010: 9006: 9002: 8995: 8980: 8976: 8972: 8968: 8961: 8945: 8941: 8935: 8927: 8923: 8919: 8915: 8911: 8907: 8903: 8899: 8895: 8891: 8887: 8880: 8865: 8861: 8854: 8839: 8835: 8831: 8826: 8818: 8803: 8799: 8792: 8777: 8773: 8769: 8765: 8758: 8750: 8746: 8741: 8736: 8732: 8728: 8724: 8720: 8716: 8713:April 2024). 8708: 8700: 8694: 8686: 8680: 8672: 8668: 8663: 8658: 8654: 8650: 8646: 8642: 8638: 8634: 8630: 8623: 8615: 8611: 8606: 8601: 8597: 8593: 8589: 8582: 8580: 8571: 8567: 8562: 8557: 8553: 8549: 8545: 8541: 8537: 8530: 8522: 8518: 8511: 8496: 8492: 8485: 8478: 8473: 8466: 8461: 8445: 8439: 8431: 8425: 8418: 8413: 8407:, p. 22) 8406: 8400: 8393: 8388: 8381: 8376: 8374: 8372: 8364: 8359: 8352: 8347: 8345: 8337: 8332: 8330: 8328: 8326: 8324: 8322: 8320: 8313:, p. 17. 8312: 8307: 8305: 8303: 8295: 8290: 8283: 8278: 8271: 8266: 8257: 8254: 8253: 8251: 8246: 8238: 8235: 8233: 8231: 8226: 8224: 8221: 8218: 8215: 8214: 8212: 8211:Deep learning 8207: 8205: 8195: 8192: 8191: 8189: 8184: 8175: 8172: 8171: 8169: 8164: 8155: 8152: 8151: 8149: 8144: 8136: 8133: 8131: 8128: 8127: 8126:The theorem: 8122: 8119: 8118: 8116: 8111: 8102: 8101:Nilsson (1998 8099: 8096: 8093: 8090: 8087: 8086: 8084: 8080: 8074: 8065: 8062: 8059: 8056: 8055: 8051: 8049: 8039: 8036: 8033: 8030: 8029: 8027: 8022: 8015: 8010: 8001: 7998: 7995: 7992: 7989: 7986: 7985: 7983: 7979: 7975: 7970: 7962:, p. 88) 7961: 7958: 7955: 7952: 7951: 7949: 7944: 7936: 7930: 7926: 7922: 7916: 7907: 7904: 7903: 7901: 7895: 7886: 7883: 7882: 7880: 7877:and Bayesian 7876: 7871: 7862: 7859: 7856: 7855:Nilsson (1998 7853: 7850: 7847: 7844: 7841: 7840: 7838: 7834: 7829: 7822: 7817: 7808: 7807:Nilsson (1998 7805: 7802: 7799: 7796: 7793: 7790: 7787: 7786: 7784: 7779: 7772: 7767: 7758: 7757:Nilsson (1998 7755: 7752: 7749: 7746: 7743: 7740: 7737: 7736: 7734: 7729: 7720: 7717: 7716: 7714: 7710: 7705: 7696: 7693: 7692: 7690: 7684: 7681: 7680: 7678: 7672: 7669: 7668: 7666: 7660: 7657: 7656: 7652: 7650: 7648: 7638: 7635: 7634: 7632: 7628: 7623: 7614: 7611: 7610: 7608: 7603: 7594: 7591: 7588: 7585: 7584: 7582: 7578: 7573: 7564: 7563:Nilsson (1998 7561: 7558: 7555: 7552: 7549: 7546: 7543: 7542: 7538: 7536: 7527: 7524: 7521: 7518: 7517: 7516:Fuzzy logic: 7513: 7505: 7501: 7497: 7493: 7492: 7484: 7475: 7472: 7471: 7469: 7465: 7460: 7451: 7450:Nilsson (1998 7448: 7445: 7442: 7439: 7436: 7434:, §9.3, §9.4) 7433: 7430: 7429: 7425: 7416: 7413: 7412: 7410: 7405: 7396: 7395:Nilsson (1998 7393: 7390: 7387: 7384: 7381: 7378: 7375: 7374: 7372: 7368: 7363: 7354: 7353:Nilsson (1998 7351: 7348: 7345: 7342: 7339: 7338: 7336: 7331: 7322: 7321:Nilsson (1998 7319: 7316: 7313: 7310: 7307: 7306: 7304: 7299: 7292: 7287: 7278: 7275: 7274: 7272: 7267: 7252: 7248: 7241: 7232: 7229: 7228: 7226: 7222: 7217: 7208: 7205: 7204: 7202: 7197: 7188: 7185: 7182: 7179: 7176: 7173: 7170: 7167: 7166: 7164: 7160: 7156: 7151: 7142: 7141:Nilsson (1998 7139: 7136: 7133: 7130: 7127: 7124: 7121: 7120: 7118: 7114: 7110: 7106: 7101: 7094: 7089: 7080: 7077: 7076: 7074: 7069: 7061:, chpt. 7–12) 7060: 7059:Nilsson (1998 7057: 7054: 7051: 7048: 7045: 7042: 7039: 7038: 7036: 7031: 7024: 7019: 7012: 7007: 6999: 6996: 6994: 6991: 6989: 6986: 6984: 6981: 6980: 6978: 6973: 6966: 6961: 6954: 6949: 6942: 6937: 6930: 6925: 6918: 6913: 6906: 6901: 6892: 6891:Nilsson (1998 6889: 6886: 6883: 6882: 6880: 6875: 6868: 6863: 6856: 6851: 6844: 6839: 6831: 6828: 6825: 6822: 6821: 6819: 6813: 6806: 6801: 6794: 6789: 6780: 6777: 6776: 6774: 6768: 6759: 6756: 6753: 6750: 6747: 6744: 6743: 6741: 6736: 6728: 6725: 6722: 6719: 6718: 6716: 6711: 6696: 6692: 6686: 6678: 6675: 6672: 6669: 6668: 6666: 6661: 6652: 6649: 6646: 6643: 6642: 6640: 6635: 6626: 6623: 6620: 6617: 6616: 6614: 6609: 6607: 6597: 6593: 6590: 6587: 6583: 6580: 6577: 6574: 6573: 6571: 6566: 6559: 6554: 6547: 6546:Turing (1950) 6542: 6533: 6532:Nilsson (1998 6530: 6527: 6524: 6521: 6518: 6515: 6512: 6511: 6509: 6504: 6495: 6492: 6491: 6489: 6484: 6475: 6472: 6471: 6469: 6464: 6455: 6452: 6451: 6449: 6444: 6435: 6432: 6431: 6429: 6423: 6420: 6419: 6415: 6406: 6403: 6402: 6398: 6389: 6386: 6385: 6383: 6378: 6369: 6366: 6365: 6363: 6359: 6354: 6345: 6342: 6341: 6339: 6334: 6327: 6322: 6315: 6310: 6303: 6298: 6289: 6285: 6282: 6279: 6278:Moravec (1988 6276: 6273: 6272:Crevier (1993 6270: 6267: 6264: 6263: 6259: 6257: 6249: 6245: 6238: 6237:Nilsson (1998 6235: 6232: 6229: 6226: 6223: 6220: 6217: 6216: 6214: 6210: 6206: 6202: 6198: 6197:default logic 6194: 6193:Frame problem 6190: 6185: 6183: 6173: 6170: 6167: 6164: 6163: 6161: 6155: 6146: 6143: 6142: 6140: 6135: 6127:, chpt. 18.2) 6126: 6125:Nilsson (1998 6123: 6120: 6117: 6114: 6111: 6110: 6108: 6107:frame problem 6104: 6100: 6096: 6090: 6082:, chpt. 18.3) 6081: 6080:Nilsson (1998 6078: 6075: 6072: 6069: 6066: 6063: 6060: 6059: 6057: 6053: 6049: 6045: 6041: 6035: 6028: 6023: 6016: 6011: 6004: 5999: 5992: 5987: 5980: 5975: 5968: 5963: 5954: 5953:Nilsson (1998 5951: 5948: 5945: 5942: 5939: 5936: 5933: 5932: 5930: 5926: 5921: 5913: 5910: 5908: 5905: 5903: 5900: 5898: 5895: 5894: 5890: 5888: 5886: 5877:, p. 21) 5876: 5873: 5872: 5870: 5866: 5861: 5859: 5857: 5848:, chpt. 7–12) 5847: 5846:Nilsson (1998 5844: 5841: 5838: 5835: 5832: 5829: 5826: 5825: 5821: 5813:, chpt. 7–12) 5812: 5811:Nilsson (1998 5809: 5806: 5803: 5800: 5797: 5794: 5790: 5787: 5784: 5781: 5780: 5776: 5769: 5764: 5756: 5753: 5751:, p. 26) 5750: 5747: 5745: 5742: 5741: 5739: 5735: 5734:Deep learning 5730: 5728: 5718: 5715: 5712: 5709: 5706: 5705:Crevier (1993 5703: 5700: 5697: 5695:, p. 24) 5694: 5691: 5690: 5688: 5682: 5680: 5670: 5667: 5665: 5662: 5659: 5656: 5653: 5650: 5647: 5646:Crevier (1993 5644: 5643: 5642: 5638: 5634: 5628: 5626: 5616: 5613: 5610: 5607: 5605:, p. 23) 5604: 5601: 5598: 5597:Crevier (1993 5595: 5592: 5589: 5588: 5586: 5582: 5578: 5574: 5568: 5566: 5556: 5553: 5550: 5549:Moravec (1988 5547: 5544: 5543:Crevier (1993 5541: 5538: 5535: 5534: 5530: 5528: 5519: 5516: 5515: 5510: 5507: 5504: 5501: 5499:, p. 18) 5498: 5495: 5494: 5492: 5487: 5485: 5477: 5472: 5464: 5461: 5459: 5456: 5454: 5451: 5450: 5446: 5443: 5442: 5437: 5434: 5433: 5431: 5426: 5424: 5422: 5413: 5409: 5405: 5401: 5397: 5393: 5389: 5385: 5378: 5371: 5367: 5364: 5359: 5352: 5347: 5345: 5343: 5338: 5325: 5321: 5317: 5313: 5306: 5296: 5289: 5284: 5277: 5273: 5267: 5260: 5254: 5247: 5243: 5239: 5238:Rodney Brooks 5235: 5231: 5226: 5219: 5215: 5210: 5203: 5199: 5195: 5191: 5187: 5183: 5179: 5178:Daniel Bobrow 5175: 5171: 5170:Arthur Samuel 5165: 5158: 5154: 5149: 5142: 5138: 5133: 5126: 5122: 5116: 5107: 5100: 5099:robopocalypse 5094: 5085: 5078: 5074: 5068: 5059: 5052: 5046: 5039: 5035: 5031: 5027: 5023: 5022:Jon Kleinberg 5017: 5010: 5006: 5000: 4993: 4988: 4981: 4977: 4973: 4969: 4965: 4961: 4957: 4953: 4949: 4945: 4941: 4940:Valentin Lapa 4937: 4933: 4929: 4925: 4921: 4917: 4913: 4909: 4903: 4896: 4890: 4883: 4879: 4873: 4867: 4861: 4854: 4850: 4846: 4841: 4834: 4830: 4824: 4817: 4811: 4805: 4801: 4797: 4793: 4787: 4785: 4778: 4774: 4770: 4766: 4760: 4758: 4753: 4742: 4739: 4736: 4733: 4730: 4727: 4724: 4721: 4718: 4715: 4712: 4709: 4706: 4703: 4697: 4694: 4691: 4688: 4685: 4682: 4679: 4676: 4673: 4670: 4667: 4664: 4661: 4658: 4652: 4649: 4646: 4645:AI Convention 4643: 4642: 4636: 4634: 4630: 4629: 4624: 4623: 4618: 4617: 4612: 4611: 4606: 4602: 4597: 4595: 4591: 4587: 4583: 4581: 4580: 4575: 4574: 4569: 4568: 4563: 4562: 4557: 4556: 4555:Discovery One 4551: 4547: 4544: 4540: 4536: 4535: 4530: 4526: 4521: 4519: 4511: 4510: 4505: 4500: 4495: 4485: 4483: 4482: 4477: 4473: 4469: 4468:Samuel Butler 4465: 4461: 4459: 4455: 4454:Aldous Huxley 4451: 4447: 4443: 4442:Kevin Warwick 4439: 4432:Transhumanism 4429: 4427: 4422: 4420: 4416: 4412: 4408: 4404: 4400: 4395: 4393: 4378: 4376: 4372: 4368: 4365:analogous to 4364: 4359: 4357: 4351: 4349: 4345: 4341: 4337: 4327: 4325: 4321: 4316: 4314: 4313:Hilary Putnam 4310: 4306: 4301: 4295: 4291: 4287: 4277: 4275: 4270: 4266: 4262: 4257: 4252: 4248: 4241:Consciousness 4238: 4236: 4231: 4227: 4223: 4222:mental states 4219: 4218:consciousness 4215: 4211: 4205: 4201: 4191: 4188: 4182: 4178: 4168: 4165: 4161: 4157: 4151: 4141: 4139: 4135: 4131: 4125: 4115: 4113: 4109: 4105: 4101: 4097: 4092: 4089: 4085: 4081: 4076: 4074: 4070: 4066: 4057: 4055: 4051: 4047: 4042: 4032: 4030: 4024: 4020: 4017: 4016:Marvin Minsky 4012: 4010: 4009:John McCarthy 4007:" AI founder 4002: 3998: 3994: 3990: 3982: 3978: 3976: 3971: 3966: 3962: 3958: 3954: 3943: 3933: 3931: 3927: 3923: 3919: 3915: 3911: 3907: 3903: 3898: 3896: 3891: 3886: 3884: 3880: 3876: 3872: 3868: 3863: 3862:Deep learning 3859: 3857: 3853: 3849: 3845: 3841: 3836: 3834: 3830: 3826: 3822: 3821:connectionism 3818: 3814: 3810: 3809:Rodney Brooks 3806: 3802: 3798: 3794: 3790: 3787:to represent 3786: 3781: 3779: 3775: 3771: 3767: 3762: 3760: 3756: 3752: 3751: 3746: 3742: 3738: 3734: 3730: 3725: 3724:Marvin Minsky 3721: 3720:Herbert Simon 3717: 3712: 3710: 3706: 3702: 3698: 3693: 3691: 3687: 3683: 3679: 3675: 3671: 3667: 3663: 3659: 3652: 3646: 3636: 3634: 3629: 3625: 3620: 3617: 3613: 3609: 3604: 3602: 3598: 3593: 3589: 3585: 3581: 3577: 3568: 3563: 3558: 3554: 3550: 3540: 3537: 3532: 3528: 3526: 3518: 3515: 3512: 3509: 3506: 3503: 3500: 3497: 3496: 3495: 3493: 3482: 3480: 3476: 3472: 3468: 3464: 3460: 3456: 3452: 3448: 3438: 3436: 3432: 3428: 3423: 3421: 3415: 3413: 3407: 3403: 3399: 3395: 3391: 3381: 3379: 3375: 3370: 3365: 3363: 3358: 3356: 3352: 3349:In May 2023, 3347: 3345: 3341: 3337: 3333: 3332:Yoshua Bengio 3329: 3325: 3321: 3316: 3314: 3310: 3306: 3302: 3298: 3294: 3290: 3286: 3281: 3279: 3275: 3270: 3266: 3262: 3258: 3254: 3249: 3247: 3243: 3237: 3227: 3225: 3220: 3218: 3213: 3212: 3211:The Economist 3206: 3203: 3199: 3198:redistributed 3195: 3191: 3185: 3181: 3177: 3167: 3163: 3161: 3157: 3153: 3149: 3145: 3141: 3137: 3136:generative AI 3133: 3129: 3125: 3121: 3117: 3113: 3109: 3105: 3101: 3097: 3092: 3090: 3089:United States 3086: 3082: 3078: 3074: 3068: 3066: 3062: 3058: 3054: 3050: 3044: 3040: 3036: 3026: 3024: 3020: 3016: 3012: 3008: 3004: 3003:Deconvolution 3000: 2994: 2992: 2988: 2984: 2981: 2975: 2972: 2966: 2964: 2960: 2954: 2950: 2946: 2936: 2934: 2930: 2925: 2923: 2918: 2912: 2909: 2907: 2903: 2897: 2893: 2890: 2886: 2882: 2878: 2874: 2870: 2866: 2864: 2860: 2859:Google Photos 2855: 2853: 2849: 2845: 2841: 2837: 2833: 2829: 2825: 2821: 2820:training data 2817: 2811: 2807: 2797: 2795: 2790: 2789:generative AI 2785: 2782: 2778: 2774: 2770: 2766: 2762: 2758: 2754: 2749: 2739: 2736: 2733:In 2024, the 2731: 2729: 2725: 2724:Goldman Sachs 2720: 2716: 2714: 2710: 2704: 2694: 2692: 2688: 2684: 2680: 2676: 2672: 2668: 2664: 2663:Alphabet Inc. 2660: 2650: 2648: 2647: 2642: 2638: 2634: 2630: 2625: 2623: 2619: 2615: 2614:Cynthia Dwork 2611: 2607: 2603: 2598: 2596: 2592: 2588: 2584: 2580: 2576: 2571: 2567: 2565: 2561: 2557: 2551: 2547: 2532: 2529: 2525: 2519: 2509: 2505: 2501: 2498: 2493: 2491: 2487: 2476: 2474: 2470: 2466: 2462: 2458: 2447: 2445: 2441: 2437: 2433: 2429: 2425: 2421: 2417: 2416:text-to-image 2413: 2408: 2406: 2402: 2398: 2397:generative AI 2389: 2384: 2377:Generative AI 2374: 2371: 2370:Kamala Harris 2366: 2364: 2360: 2356: 2352: 2346: 2336: 2333: 2329: 2320: 2317: 2315: 2310: 2308: 2304: 2300: 2296: 2292: 2288: 2283: 2280: 2276: 2273: 2269: 2265: 2264: 2263:Mistral Large 2259: 2258: 2253: 2252: 2247: 2246: 2241: 2239: 2234: 2224: 2222: 2217: 2213: 2209: 2205: 2201: 2197: 2193: 2189: 2185: 2181: 2177: 2173: 2169: 2165: 2161: 2157: 2153: 2149: 2145: 2141: 2137: 2133: 2130: 2129: 2124: 2120: 2116: 2111: 2101: 2099: 2095: 2091: 2087: 2082: 2078: 2074: 2070: 2065: 2063: 2059: 2055: 2049: 2039: 2037: 2033: 2029: 2025: 2021: 2017: 2013: 2009: 2005: 2001: 1997: 1993: 1989: 1985: 1981: 1977: 1973: 1969: 1965: 1961: 1957: 1953: 1949: 1945: 1941: 1937: 1933: 1929: 1925: 1921: 1917: 1913: 1912:Google Search 1909: 1903: 1893: 1891: 1887: 1883: 1879: 1875: 1871: 1867: 1863: 1857: 1853: 1843: 1841: 1837: 1833: 1829: 1825: 1821: 1817: 1813: 1808: 1806: 1802: 1798: 1794: 1790: 1786: 1782: 1773: 1771: 1767: 1763: 1759: 1755: 1751: 1747: 1743: 1738: 1736: 1732: 1731:Deep learning 1725: 1719:Deep learning 1716: 1714: 1710: 1706: 1702: 1698: 1694: 1690: 1685: 1683: 1682:find patterns 1679: 1675: 1670: 1668: 1663: 1659: 1651: 1647: 1642: 1633: 1631: 1627: 1623: 1619: 1615: 1611: 1610:decision tree 1606: 1604: 1600: 1596: 1592: 1588: 1575: 1571: 1568: 1564: 1560: 1558: 1554: 1550: 1545: 1543: 1539: 1535: 1531: 1527: 1523: 1519: 1515: 1511: 1507: 1505: 1501: 1497: 1493: 1489: 1485: 1481: 1477: 1469: 1465: 1460: 1451: 1449: 1445: 1441: 1437: 1435: 1431: 1429: 1425: 1421: 1417: 1413: 1409: 1404: 1402: 1398: 1394: 1390: 1386: 1382: 1378: 1373: 1371: 1367: 1363: 1359: 1355: 1351: 1347: 1345: 1341: 1338: 1334: 1330: 1327: 1323: 1319: 1315: 1311: 1307: 1303: 1299: 1289: 1287: 1284:(inspired by 1283: 1279: 1275: 1271: 1266: 1264: 1260: 1255: 1253: 1249: 1248:loss function 1245: 1241: 1239: 1235: 1228: 1227:loss function 1224: 1219: 1210: 1208: 1204: 1200: 1196: 1194: 1190: 1186: 1182: 1178: 1174: 1172: 1168: 1164: 1155: 1153: 1149: 1139: 1131: 1129: 1125: 1115: 1113: 1109: 1104: 1102: 1098: 1094: 1090: 1083: 1079: 1070: 1068: 1064: 1060: 1056: 1052: 1048: 1043: 1041: 1037: 1033: 1029: 1020: 1018: 1014: 1010: 1006: 1002: 998: 994: 990: 985: 983: 979: 975: 971: 967: 963: 959: 954: 952: 948: 944: 940: 936: 932: 928: 924: 915: 913: 909: 905: 901: 897: 895: 891: 890:Deep learning 887: 883: 878: 876: 872: 868: 864: 859: 857: 848: 846: 842: 840: 836: 832: 828: 824: 820: 815: 813: 809: 805: 800: 798: 793: 791: 787: 783: 779: 775: 771: 761: 759: 753: 751: 746: 742: 737: 735: 730: 726: 718: 709: 705: 703: 699: 695: 691: 681: 672: 670: 666: 662: 658: 654: 650: 646: 645:deep learning 642: 637: 635: 631: 627: 623: 619: 615: 611: 607: 603: 599: 595: 591: 587: 583: 579: 575: 571: 567: 562: 560: 556: 552: 548: 544: 540: 536: 532: 529:tools (e.g., 528: 524: 520: 516: 512: 508: 504: 500: 496: 492: 488: 484: 480: 479:Google Search 476: 472: 467: 465: 461: 457: 453: 449: 445: 441: 438:exhibited by 437: 433: 429: 418: 413: 411: 406: 404: 399: 398: 396: 395: 388: 385: 384: 378: 377: 370: 367: 365: 362: 360: 357: 355: 352: 351: 348: 343: 342: 335: 332: 330: 327: 325: 322: 320: 317: 315: 311: 308: 306: 303: 301: 298: 296: 293: 292: 289: 284: 283: 276: 273: 271: 268: 266: 263: 261: 258: 254: 253:Mental health 251: 250: 249: 246: 244: 241: 239: 236: 232: 229: 227: 224: 222: 219: 218: 217: 216:Generative AI 214: 212: 209: 207: 204: 202: 199: 197: 194: 193: 190: 185: 184: 177: 174: 172: 169: 167: 164: 162: 159: 157: 156:Deep learning 154: 152: 149: 147: 144: 143: 137: 136: 129: 126: 124: 121: 119: 116: 114: 111: 109: 106: 104: 101: 99: 96: 94: 91: 89: 86: 84: 81: 80: 77: 72: 71: 65: 61: 60: 57: 54: 53: 49: 48: 45: 41: 37: 33: 19: 25609:Data science 25401:Engineering 25352:Cell biology 25322:Architecture 25239:Walter Pitts 25144:Marian Mazur 25019:Cliff Joslyn 24861:Biosemiotics 24840: 24762: 24755: 24748: 24741: 24729: 24689:Jaan Tallinn 24629:Eric Drexler 24619:Nick Bostrom 24432:AI alignment 24412: 24364: 24352: 24121:Evolutionary 24068:Robotic fins 24021:Robotic fish 24006:Telerobotics 23979:Nanorobotics 23969:Mobile robot 23906:Food service 23901:Agricultural 23751:Competitions 23736:Hall of Fame 23652: 23539:Robot ethics 23338:Semantic Web 23307: 23159:Cyberwarfare 22943: 22818:Cryptography 22055:Hugging Face 22019:David Silver 21667:Audio–visual 21556: 21521:Applications 21500:Augmentation 21345: 21211: 20933:Larry Laudan 20913:Imre Lakatos 20868:Otto Neurath 20843:Karl Pearson 20833:Pierre Duhem 20805:Isaac Newton 20735:Protoscience 20693:Epistemology 20567:Anti-realism 20565: / 20546: / 20537: / 20523: / 20521:Reductionism 20519: / 20492:Inductionism 20472:Evolutionism 20277: 20164:a posteriori 20163: 20159: 20063: / 20059: / 20055: / 19972:Mental image 19967:Mental event 19934: 19930:Intelligence 19880:Chinese room 19726: 19677:Gilbert Ryle 19657:Derek Parfit 19647:Thomas Nagel 19577:Fred Dretske 19497:J. L. Austin 19469:Philosophers 19363: 19302: 19289: 19270: 19247:. Retrieved 19231: 19219:. Retrieved 19178: 19174: 19160:12 September 19158:. Retrieved 19138: 19134: 19117: 19103: 19096:intelligence 19090:, "AI's IQ: 19079: 19060:. Retrieved 19019: 19015: 18992: 18982: 18979:Marcus, Gary 18970: 18959:. Retrieved 18918: 18914: 18859: 18855: 18846:, MIT Press. 18843: 18826: 18815:to serve as 18794: 18788: 18764: 18760: 18743: 18726:George Dyson 18719: 18705: 18695: 18686:transformers 18664: 18663: 18662:profile for 18659: 18632:24 September 18630:, retrieved 18610: 18596:The Atlantic 18595: 18579:. Retrieved 18546: 18542: 18528: 18512:. Retrieved 18503: 18488:. Retrieved 18452: 18448: 18429:. Retrieved 18420: 18411:Wason, P. C. 18402: 18390:. Retrieved 18382:The Atlantic 18381: 18365:. Retrieved 18361:the original 18348: 18329:. Retrieved 18320: 18304:. Retrieved 18295: 18279:. Retrieved 18270: 18254:. Retrieved 18250: 18238: 18222:. Retrieved 18213: 18166: 18162: 18148:18 September 18146:. Retrieved 18126: 18102: 18096: 18093:Turing, Alan 18081:. Retrieved 18077: 18061:. Retrieved 18041: 18028:. Retrieved 18020:The Atlantic 18019: 18006:The Guardian 18004: 17973: 17961:. Retrieved 17952:. AI Index. 17937: 17925:. Retrieved 17909: 17883:(2): 62–72. 17880: 17876: 17864:. Retrieved 17860: 17847: 17834: 17822:. Retrieved 17794: 17790:Searle, John 17778:. Retrieved 17750: 17746: 17736:Searle, John 17703: 17699: 17640: 17636: 17611:(1): 13–24. 17608: 17604: 17592:. Retrieved 17588: 17572:. Retrieved 17569:The Guardian 17568: 17552:. Retrieved 17543: 17511: 17496: 17484:. Retrieved 17475: 17460:. Retrieved 17439:. Retrieved 17435:the original 17430: 17419:The Atlantic 17418: 17402:. Retrieved 17393: 17377:. Retrieved 17342: 17338: 17315: 17284: 17272:. Retrieved 17244: 17240: 17224: 17212: 17192:. Retrieved 17180: 17176: 17154:. Retrieved 17140: 17117: 17113: 17106:Simon, H. A. 17093: 17065: 17061: 17029: 17025: 17006:. Retrieved 16997: 16981:. Retrieved 16960: 16946: 16924: 16913:, retrieved 16879: 16856:(1): 39–61. 16853: 16849: 16814: 16810: 16799:, retrieved 16789: 16776: 16761:. Retrieved 16757:the original 16724: 16710: 16694:. Retrieved 16690: 16675:, retrieved 16671:the original 16665: 16652:. Retrieved 16644:The Guardian 16643: 16627:. Retrieved 16618: 16606:the original 16601: 16563: 16559: 16547:. Retrieved 16538: 16498: 16488: 16466: 16451:. Retrieved 16442: 16413: 16401:. Retrieved 16397: 16381:. Retrieved 16372: 16345: 16339: 16315: 16276: 16272: 16256:. Retrieved 16247: 16231:. Retrieved 16220: 16201:. Retrieved 16181:. Retrieved 16173:The Atlantic 16172: 16156:. Retrieved 16147: 16092: 16088: 16069:. Retrieved 16049: 16004: 16000: 15967: 15963: 15951:. Retrieved 15942: 15926:. Retrieved 15905:. Retrieved 15896: 15883: 15875: 15862:. Retrieved 15845: 15811:(6): 82–97. 15808: 15804: 15788:. Retrieved 15779: 15756: 15742: 15728:23 September 15726:. Retrieved 15717:The Atlantic 15715: 15696:. Retrieved 15687: 15674: 15661: 15619: 15615: 15604:, retrieved 15600:the original 15594: 15584: 15568:. Retrieved 15564: 15535: 15521:. Retrieved 15513:The Guardian 15512: 15496:. Retrieved 15485: 15478:Gertner, Jon 15466:. Retrieved 15457: 15436: 15432: 15420:. Retrieved 15411: 15373: 15369: 15360: 15353:. Retrieved 15349:The Diplomat 15347: 15331:. Retrieved 15322:. Fox News. 15304:. Retrieved 15296:The Guardian 15295: 15272: 15253: 15250:Teknokultura 15249: 15242:Evans, Woody 15230:. Retrieved 15222:Ars Technica 15221: 15205:. Retrieved 15184: 15170:. Retrieved 15150: 15134:. Retrieved 15114: 15090: 15063: 15052:the original 15047: 15031:. Retrieved 15027: 15011:. Retrieved 15002: 14978: 14962:. Retrieved 14942: 14938: 14911:. Retrieved 14902: 14886:. Retrieved 14877: 14826: 14796: 14766: 14754:. Retrieved 14745: 14739: 14720:. Retrieved 14709: 14683:(2): 48–57. 14680: 14676: 14662:(7): 24–30. 14659: 14653: 14641:. Retrieved 14630: 14615: 14587:(1): 41–59. 14584: 14580: 14542: 14538: 14520:the original 14503:. Retrieved 14480: 14467: 14455:. Retrieved 14439: 14426:. Retrieved 14398: 14341: 14337: 14317:1721.1/52357 14299: 14295: 14264: 14252:. Retrieved 14243: 14218:(1): 12–34. 14215: 14211: 14203: 14194: 14169: 14165: 14153:. Retrieved 14144: 14121: 14072: 14050: 14027: 13997: 13975: 13968: 13957:. Retrieved 13937: 13925: 13915:. Retrieved 13895: 13883:Poole, David 13863: 13843:. Retrieved 13822: 13805:. Retrieved 13784: 13767: 13750: 13747:Rich, Elaine 13718: 13700: 13697:AI textbooks 13683: 13671: 13659: 13647: 13635: 13622:AI in myth: 13618: 13610:Dyson (1998) 13587: 13557: 13545: 13537:Vinge (1993) 13531:Vernor Vinge 13488: 13476:. Retrieved 13472: 13462: 13450:. Retrieved 13446: 13436: 13424:. Retrieved 13413:The Guardian 13412: 13402: 13394:Fast Company 13393: 13383: 13371:. Retrieved 13367: 13342:. Retrieved 13338: 13311:. Retrieved 13307: 13297: 13272:Discussion: 13255:Chinese room 13249: 13237: 13232:, p. 1. 13225: 13213: 13206:Horst (2005) 13201: 13189: 13177: 13165: 13138: 13084: 13072: 13060: 13048: 12997: 12988:Pinker (2007 12982:Minsky (1986 12965: 12933: 12921: 12909: 12897:. Retrieved 12893: 12884: 12872:. Retrieved 12868: 12859: 12847:. Retrieved 12836: 12827: 12815: 12803: 12796:Maker (2006) 12791: 12786:, p. 3. 12779: 12767:. Retrieved 12763: 12753: 12741: 12736:, p. 1. 12714: 12702: 12690:. Retrieved 12681: 12671: 12651: 12614: 12602: 12573: 12543: 12531: 12509: 12497: 12463: 12436: 12424: 12419:, p. 7. 12412: 12400: 12350: 12338: 12326: 12314: 12302: 12291:Minsky (1967 12286: 12270: 12258: 12246: 12234: 12222: 12161:, p. 3) 12133: 12119: 12100: 12084:, p. 9. 12062:. Retrieved 12058:the original 12048: 12036:. Retrieved 12026: 12014:. Retrieved 12005: 11996: 11984:. Retrieved 11980:the original 11975: 11966: 11955: 11949: 11937: 11925: 11913: 11903:17 September 11901:. 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Retrieved 8438: 8424: 8417:Smith (2023) 8412: 8399: 8387: 8358: 8289: 8277: 8265: 8245: 8229: 8183: 8163: 8143: 8110: 8103:, chpt. 3.3) 8073: 8066:, Chapter 4) 8060:, Chpt. 21), 8021: 8009: 7969: 7943: 7924: 7915: 7908:, chpt. 20), 7894: 7870: 7845:, Chpt. 20), 7828: 7816: 7778: 7773:, chapter 6. 7766: 7728: 7704: 7629:and dynamic 7622: 7602: 7572: 7512: 7495: 7489: 7483: 7459: 7424: 7404: 7362: 7330: 7311:, chpt. 6–9) 7298: 7286: 7266: 7254:. Retrieved 7250: 7240: 7225:optimization 7216: 7196: 7150: 7115:and general 7100: 7088: 7068: 7043:, Chpt. 3–5) 7030: 7018: 7006: 6972: 6960: 6948: 6936: 6924: 6912: 6900: 6874: 6862: 6850: 6838: 6812: 6800: 6788: 6767: 6735: 6710: 6698:. Retrieved 6694: 6685: 6660: 6634: 6565: 6553: 6541: 6503: 6496:, chpt. 18). 6483: 6476:, chpt. 17). 6463: 6443: 6414: 6397: 6377: 6353: 6346:, chpt. 11). 6333: 6321: 6309: 6297: 6247: 6243: 6160:modal logics 6154: 6134: 6089: 6034: 6022: 6010: 5998: 5986: 5974: 5962: 5920: 5820: 5791:, chpt. 6) ( 5785:, chpt. 3–5) 5775: 5768:Toews (2023) 5763: 5736:revolution, 5551:, p. 9) 5471: 5387: 5383: 5377: 5358: 5323: 5319: 5305: 5295: 5288:Nils Nilsson 5283: 5266: 5259:The Atlantic 5253: 5234:Hans Moravec 5225: 5209: 5164: 5148: 5132: 5115: 5106: 5093: 5084: 5071:This is the 5067: 5058: 5045: 5016: 4999: 4987: 4944:Kaoru Nakano 4912:Walter Pitts 4902: 4889: 4872: 4860: 4840: 4823: 4810: 4626: 4620: 4614: 4613:, the films 4608: 4598: 4586:Isaac Asimov 4584: 4577: 4571: 4565: 4559: 4553: 4545: 4534:Frankenstein 4532: 4529:Mary Shelley 4522: 4515: 4507: 4479: 4476:George Dyson 4462: 4446:Ray Kurzweil 4438:Hans Moravec 4435: 4423: 4415:Vernor Vinge 4396: 4389: 4360: 4356:human rights 4352: 4348:Robot rights 4333: 4318:Philosopher 4317: 4297: 4294:Chinese room 4273: 4260: 4254: 4207: 4184: 4153: 4134:optimization 4127: 4104:Noam Chomsky 4096:sub-symbolic 4093: 4077: 4063: 4046:sub-symbolic 4038: 4025: 4021: 4013: 3987: 3968: 3899: 3887: 3860: 3837: 3782: 3778:Lisp Machine 3763: 3748: 3713: 3694: 3674:neurobiology 3655: 3626:was held in 3621: 3605: 3588:Eric Schmidt 3572: 3533: 3529: 3522: 3516: 3510: 3504: 3498: 3488: 3479:bioterrorism 3447:Hugging Face 3444: 3424: 3416: 3409: 3366: 3359: 3348: 3317: 3307:are made of 3282: 3260: 3257:Nick Bostrom 3250: 3239: 3221: 3209: 3207: 3194:productivity 3190:unemployment 3186: 3183: 3164: 3108:surveillance 3093: 3069: 3065:rogue states 3046: 2995: 2985: 2976: 2967: 2956: 2927:At its 2022 2926: 2913: 2910: 2905: 2901: 2898: 2894: 2885:Julia Angwin 2867: 2862: 2856: 2813: 2786: 2751: 2734: 2732: 2727: 2721: 2717: 2712: 2706: 2691:data centers 2656: 2644: 2637:John Grisham 2626: 2599: 2577:algorithms, 2572: 2568: 2560:surveillance 2553: 2521: 2506: 2502: 2494: 2482: 2453: 2440:Donald Trump 2436:Pope Francis 2409: 2394: 2367: 2348: 2330: 2326: 2318: 2311: 2306: 2302: 2294: 2290: 2287:Alpha Tensor 2286: 2284: 2261: 2255: 2249: 2245:Gemini Ultra 2243: 2236: 2230: 2216:Gran Turismo 2212:StarCraft II 2156:Ken Jennings 2147: 2126: 2115:Game playing 2113: 2066: 2051: 1922:(offered by 1905: 1896:Applications 1859: 1809: 1779: 1739: 1729: 1686: 1674:local search 1671: 1655: 1620:such as the 1607: 1584: 1574:Old Faithful 1546: 1520:algorithm), 1508: 1472: 1438: 1432: 1405: 1385:Horn clauses 1374: 1348: 1343: 1339: 1336: 1332: 1328: 1325: 1300:is used for 1295: 1267: 1256: 1242: 1234:Local search 1232: 1229:(the height) 1213:Local search 1203:game-playing 1201:is used for 1197: 1181:search space 1175: 1161: 1152:local search 1145: 1137: 1121: 1105: 1087: 1044: 1026: 997:transformers 986: 974:micro-worlds 958:Noam Chomsky 955: 921: 912:optimization 898: 879: 860: 854: 843: 816: 801: 794: 767: 754: 738: 723: 706: 687: 678: 638: 634:neuroscience 602:formal logic 563: 468: 436:intelligence 431: 427: 426: 300:Chinese room 189:Applications 55: 44: 25604:Cybernetics 25522:Ornithology 25507:Meteorology 25492:Mathematics 25482:Ichthyology 25317:Archaeology 25312:Agriculture 25296:engineering 25174:Qian Xuesen 25054:Gordon Pask 24951:Synergetics 24916:Homeostasis 24856:Biorobotics 24827:cybernetics 24694:Max Tegmark 24679:Martin Rees 24487:Longtermism 24447:AI takeover 24141:Open-source 23994:Space probe 23984:Necrobotics 23974:Microbotics 23937:Biorobotics 23866:Educational 23849:Articulated 23830:Animatronic 23815:Claytronics 23603:Moore's law 23534:Neuroethics 23529:Cyberethics 23350:Atomtronics 23169:Video games 23149:Digital art 22906:Concurrency 22775:Data mining 22687:Probability 22427:Interpreter 22203:Categories 22151:Autoencoder 22106:Transformer 21974:Alex Graves 21922:OpenAI Five 21826:IBM Watsonx 21448:Convolution 21426:Overfitting 21267:Mating pool 21017:Main Topics 20923:Ian Hacking 20908:Thomas Kuhn 20893:Karl Popper 20873:C. D. Broad 20790:Roger Bacon 20718:Non-science 20660:Linguistics 20640:Archaeology 20535:Rationalism 20525:Determinism 20512:Physicalism 20477:Fallibilism 20427:Coherentism 20357:Testability 20310:Observation 20305:Objectivity 20266:alternative 20197:Correlation 20187:Consilience 20057:information 20048:Metaphysics 20022:Tabula rasa 19832:Physicalism 19817:Parallelism 19745:Behaviorism 19702:Michael Tye 19697:Alan Turing 19682:John Searle 19557:Dharmakirti 19532:Tyler Burge 19527:C. D. Broad 19303:In Our Time 19249:20 February 19076:Press, Eyal 19068:Introduced 18431:18 November 18416:"Reasoning" 18367:14 November 18256:25 November 17866:25 December 17594:25 November 17247:(1): 2–16. 17177:AI Magazine 17094:AI Magazine 17032:(1): 9–11. 16983:18 November 16790:What is AI? 16696:25 December 15801:Sainath, T. 15616:AI Magazine 15606:12 November 15580:Good, I. J. 15565:VentureBeat 15376:: 254–280. 15207:18 November 15068:Basic Books 15033:22 November 14923:Cybenko, G. 14888:23 November 14129:Altman, Sam 13845:18 November 13807:17 December 13526:Good (1965) 13478:23 February 13452:23 February 13426:23 February 13373:23 February 13344:23 February 13313:23 February 13077:Katz (2012) 13039:Fearn (2007 12619:Moore's Law 12607:Wong (2023) 12275:Simon (1965 12177:Turing test 11523:VentureBeat 11478:AI Business 11358:AAAI (2014) 11270:30 December 11244:30 December 10829:Lohr (2017) 10306:Rose (2023) 10262:Rose (2023) 9306:7 September 8521:AI Business 8495:VentureBeat 8450:25 December 8219:, Chpt. 21) 8188:Perceptrons 7900:classifiers 7857:, chpt. 20) 7785:algorithm: 7721:, chpt. 18) 7709:Game theory 7661:, Chpt. 14) 7639:, chpt. 17) 7565:, chpt. 19) 7468:unification 7417:, chpt. 10) 7397:, chpt. 15) 7355:, chpt. 13) 6983:Thro (1993) 6887:, chpt. 25) 6826:, chpt. 24) 6695:builtin.com 6647:, chpt. 22) 6488:Game theory 6050:(including 6048:inheritance 5937:, chpt. 10) 5664:Howe (1994) 5326:thinking)." 5242:Nouvelle AI 4980:Paul Werbos 4916:Alan Turing 4845:Alan Turing 4605:Karel Čapek 4564:(1984) and 4504:Karel Čapek 4419:singularity 4409:called an " 4320:John Searle 4309:Jerry Fodor 4164:fuzzy logic 4156:intractable 4065:Symbolic AI 3970:Alan Turing 3953:Turing test 3852:mathematics 3817:Lofti Zadeh 3813:Judea Pearl 3750:Perceptrons 3690:Turing test 3666:cybernetics 3658:Alan Turing 3441:Open source 3355:AI takeover 2917:stereotypes 2883:. In 2016, 2879:becoming a 2873:U.S. courts 2836:recruitment 2689:power from 2646:sui generis 2363:Joint Fires 2295:Alpha Proof 2279:classifiers 2277:or trained 2275:fine-tuning 2251:Claude Opus 2227:Mathematics 2172:computer Go 2152:Brad Rutter 2150:champions, 2086:AlphaFold 2 1966:(including 1934:), driving 1701:Perceptrons 1650:human brain 1599:observation 1587:Classifiers 1524:(using the 1516:(using the 1500:game theory 1476:probability 1434:Fuzzy logic 1430:languages. 1412:intractable 1408:undecidable 1342:s that are 1322:quantifiers 845:Game theory 812:intractably 698:probability 626:linguistics 329:Turing test 305:Friendly AI 76:Major goals 25583:Categories 25537:Psychiatry 25446:Geography 25417:Entomology 24659:Shane Legg 24634:Sam Harris 24609:Sam Altman 24548:EleutherAI 24181:Ubiquitous 24171:Perceptual 24078:Navigation 24033:Locomotion 24011:Underwater 23896:Disability 23844:Industrial 23494:Automation 23227:Glossaries 23099:E-commerce 22692:Statistics 22635:Algorithms 22432:Middleware 22288:Peripheral 22192:Technology 22045:EleutherAI 22004:Fei-Fei Li 21999:Yann LeCun 21912:Q-learning 21895:Decisional 21821:IBM Watson 21729:Midjourney 21621:TensorFlow 21468:Activation 21421:Regression 21416:Clustering 21054:Algorithms 20810:David Hume 20783:Precursors 20665:Psychology 20645:Economics‎ 20539:Empiricism 20530:Pragmatism 20517:Positivism 20507:Naturalism 20377:scientific 20261:Hypothesis 20224:Experiment 20093:Task Force 20061:perception 19935:Artificial 19885:Creativity 19807:Nondualism 19707:Vasubandhu 19627:John Locke 19597:David Hume 19552:Andy Clark 18737:algorithms 18083:8 December 17643:: 85–117. 17589:Codemotion 17574:30 January 17554:30 October 17531:1083694322 17486:3 February 17462:8 December 17404:30 January 17360:1893/25490 17345:: 98–125. 17026:AI Matters 17008:13 January 16801:4 December 16677:16 October 16654:13 January 16629:31 January 16619:Fusion.net 16549:13 January 16453:30 October 16430:1110727808 16422:2019668143 16403:30 October 16373:ProPublica 16233:4 November 16203:25 October 16183:26 October 15864:30 October 15782:. London. 15629:1606.08813 15570:8 December 15523:30 October 15468:30 October 15355:8 December 15306:13 January 14964:18 October 14818:1233266753 14756:11 October 14722:30 October 14643:16 October 14505:30 January 14344:: e42936. 14290:Beal, J.; 14283:1039480085 14145:openai.com 13959:6 December 13520:I. J. Good 13257:argument: 13041:, Chpt. 3) 12849:16 October 12016:1 November 11986:2 November 11426:TechCrunch 11303:Lee (2014) 10453:Quoted in 10424:Quoted in 10274:CNA (2019) 9754:GAO (2022) 9691:: 103140. 9478:28 January 9452:28 January 9418:28 January 9329:2307.15208 9273:24 January 9090:2402.19450 8984:28 January 8950:28 January 8869:28 January 8843:28 January 8807:28 January 8781:28 January 8403:Quoted in 7464:Resolution 7379:, chpt. 7) 7343:, chpt. 6) 7256:13 January 7233:, chpt. 4) 7227:" search: 7209:, chpt. 5) 7159:best first 7143:, chpt. 8) 7081:, chpt. 3) 6893:, chpt. 6) 6700:30 October 6239:, ~18.3.3) 5334:References 5324:simulating 5077:land mines 5020:Including 4833:philosophy 4622:Ex Machina 4567:The Matrix 4488:In fiction 4417:called a " 4407:I. J. Good 3951:See also: 3936:Philosophy 3844:statistics 3829:Yann LeCun 3793:perception 3697:a workshop 3678:McCullouch 3606:In a 2022 3543:Regulation 3485:Frameworks 3475:fine-tuned 3455:EleutherAI 3378:Yann LeCun 3344:Sam Altman 3324:Bill Gates 3297:government 3289:ideologies 3261:almost any 3217:paralegals 3196:gains are 3162:in China. 3124:propaganda 3057:terrorists 3051:, such as 3049:bad actors 3011:generative 3009:and other 2943:See also: 2889:ProPublica 2881:recidivist 2765:maximizing 2746:See also: 2701:See also: 2671:Apple Inc. 2633:robots.txt 2420:Midjourney 2272:supervised 2221:open-world 2081:microscopy 2026:, Apple's 1866:TensorFlow 1840:modalities 1836:Multimodal 1783:(GPT) are 1570:clustering 1549:perception 1538:perception 1494:, dynamic 1401:resolution 1377:leaf nodes 1358:conclusion 1286:ant trails 1193:Heuristics 1134:Techniques 1023:Perception 875:regression 690:deductions 630:philosophy 622:psychology 610:statistics 543:superhuman 523:generative 446:. It is a 334:Regulation 288:Philosophy 243:Healthcare 238:Government 140:Approaches 25392:Economics 25357:Chemistry 25332:Astronomy 24906:Emergence 24834:Subfields 24674:Huw Price 24664:Elon Musk 24568:Humanity+ 24442:AI safety 24232:Figure AI 24190:Companies 24166:Paradigms 24151:Adaptable 24131:Simulator 23825:Automaton 23820:Companion 23731:Geography 23524:Bioethics 23410:Millipede 23048:Rendering 23043:Animation 22674:computing 22625:Semantics 22323:Processor 22075:MIT CSAIL 22040:Anthropic 22009:Andrew Ng 21907:AlphaZero 21751:VideoPoet 21714:AlphaFold 21651:MindSpore 21605:SpiNNaker 21600:Memristor 21507:Diffusion 21483:Rectifier 21463:Batchnorm 21443:Attention 21438:Adversary 20650:Geography 20618:Chemistry 20577:Scientism 20372:ladenness 20192:Construct 20170:Causality 19957:Intuition 19890:Cognition 19854:Solipsism 19517:Ned Block 19487:Armstrong 19482:Aristotle 19052:205242740 18902:235959867 18833:deepfakes 18581:22 August 18571:158829602 18563:0190-0692 18321:The Verge 18296:The Verge 18271:The Verge 18201:247302391 18119:0026-4423 18063:22 August 17824:22 August 17814:231867665 17780:22 August 17728:220523562 17720:1610-1987 17650:1404.7828 17369:205433041 17313:(2007) , 17194:22 August 17151:0099-9660 16897:219336439 16819:CiteSeerX 16763:30 August 16568:CiteSeerX 16519:166742927 16135:143452957 15984:2158-2041 15928:30 August 15854:0190-8286 15833:206485943 15664:(Report). 15622:(3): 50. 15400:0040-1625 15378:CiteSeerX 15172:22 August 15136:22 August 15028:TechTalks 14836:1202.2745 14697:206451986 14632:The Press 14603:1867-299X 14547:CiteSeerX 14428:22 August 14386:256681439 14360:2817-1705 14302:: 21–24, 13917:22 August 13421:0261-3077 13339:Big Think 13253:Searle's 12769:17 August 12587:NRC (1999 11724:259614124 11716:2514-9369 11681:214766800 11665:1572-8633 11626:198775713 10886:17 August 10860:17 August 9866:1059-1028 9705:0926-5805 9666:1572-8099 9566:10 August 9447:0261-3077 9268:1059-1028 9213:PD-notice 8979:0261-3077 8918:0036-8075 8864:The Verge 8838:0362-4331 8776:0028-792X 8614:2673-5067 8091:, §21.2), 7279:, §4.1.2) 7251:KDnuggets 7155:Heuristic 6213:abduction 6168:, §10.4), 6115:, §10.3), 5711:NRC (1999 5687:AI Winter 5658:NRC (1999 5633:AI Winter 5609:NRC (1999 5575:(Japan), 5509:NRC (1999 5412:158433736 5404:0007-6813 5390:: 15–25. 5300:earlier." 5272:Bloomberg 4972:Yu-Chi Ho 4829:economics 4523:A common 4324:strong AI 3914:Go player 3848:economics 3759:AI winter 3729:criticism 3574:Index at 3557:AI safety 3394:AI safety 3374:Andrew Ng 3328:Elon Musk 3253:sentience 3244:stated, " 3132:Deepfakes 3061:criminals 3043:AI safety 3019:Anthropic 3007:DeepDream 2877:defendant 2787:In 2022, 2687:computing 2679:Microsoft 2591:unethical 2564:copyright 2528:Deep Mind 2297:all from 2233:reasoning 2176:handicaps 2168:Lee Sedol 2148:Jeopardy! 2132:quiz show 2128:Jeopardy! 2119:Deep Blue 2022:(used by 2004:Microsoft 1954:(such as 1910:(such as 1514:reasoning 1462:A simple 1418:language 1393:backwards 1324:such as " 1302:reasoning 1263:selecting 1001:attention 839:heuristic 835:iteration 734:databases 702:economics 694:uncertain 657:its risks 641:AI winter 618:economics 566:reasoning 485:(used by 364:AI winter 265:Military 128:AI safety 25562:Virology 25547:Robotics 25512:Mycology 25502:Medicine 25347:Calculus 24786:Category 24654:Bill Joy 24420:Concepts 24354:Category 24272:Symbotic 24222:FarmWise 24176:Situated 24146:Software 24114:Research 24058:Climbing 23881:Military 23876:Juggling 23861:Domestic 23793:Humanoid 23716:Glossary 23697:Robotics 23445:UltraRAM 23207:Category 23035:Graphics 22810:Security 22479:Compiler 22378:Networks 22275:Hardware 22183:Portals 21942:Auto-GPT 21774:Word2vec 21578:Hardware 21495:Datasets 21397:Concepts 21282:Journals 20945:Category 20597:Vitalism 20420:Theories 20394:Variable 20315:Paradigm 20202:function 20160:A priori 20149:Analysis 20142:Concepts 20078:Category 19925:Identity 19868:Concepts 19738:Theories 19722:Zhuangzi 19652:Alva Noë 19394:ALGOL 60 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