History of artificial intelligence

422: 1230: 47: 2145: 2477:: Early AI research had been very successful at getting computers to do "intelligent" tasks like proving theorems, solving geometry problems and playing chess. Their success at these intelligent tasks convinced them that the problem of intelligent behavior had been largely solved. However, they utterly failed to make progress on "unintelligent" tasks like recognizing a face or crossing a room without bumping into anything. By the 1980s, researchers would realize that symbolic reasoning was utterly unsuited for these perceptual and sensorimotor tasks and that there were limits to this approach. 3531:. As dozens of companies failed, the perception in the business world was that the technology was not viable. The damage to AI's reputation would last into the 21st century. Inside the field there was little agreement on the reasons for AI's failure to fulfill the dream of human level intelligence that had captured the imagination of the world in the 1960s. Together, all these factors helped to fragment AI into competing subfields focused on particular problems or approaches, sometimes even under new names that disguised the tarnished pedigree of "artificial intelligence". 2504:: A number of related problems appeared when researchers tried to represent commonsense reasoning using formal logic or symbols. Descriptions of very ordinary deductions tended to get longer and longer the more one worked on them, as more and more exceptions, clarifications and distinctions were required. However, when people thought about ordinary concepts they did not rely on precise definitions, rather they seemed to make hundreds of imprecise assumptions, correcting them when necessary using their entire body of commonsense knowledge. 1705: 1369: 4523: 3211: 699: 1567: 919: 2007: 1512: 3047:. It was an enormous success: it was saving the company 40 million dollars annually by 1986. Corporations around the world began to develop and deploy expert systems and by 1985 they were spending over a billion dollars on AI, most of it to in-house AI departments. An industry grew up to support them, including hardware companies like 1803:. The proposal for the conference stated they intended to test the assertion that "every aspect of learning or any other feature of intelligence can be so precisely described that a machine can be made to simulate it". The term "Artificial Intelligence" was introduced by John McCarthy at the workshop. The participants included 3559:" was coined by researchers who had survived the funding cuts of 1974 when they became concerned that enthusiasm for expert systems had spiraled out of control and that disappointment would certainly follow. Their fears were well founded: in the late 1980s and early 1990s, AI suffered a series of financial setbacks. 1827:, all of whom would create important programs during the first decades of AI research. At the workshop Newell and Simon debuted the "Logic Theorist". The workshop was the moment that AI gained its name, its mission, its first major success and its key players, and is widely considered the birth of AI. 3382:

uses methods that work with incomplete and imprecise information. They do not attempt to give precise, logical answers, but give results that are only "probably" correct. This allowed them to solve problems that precise symbolic methods could not handle. Press accounts often claimed these tools could

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had been under increasing pressure to fund "mission-oriented direct research, rather than basic undirected research". Funding for the creative, freewheeling exploration that had gone on in the 60s would not come from DARPA, which instead directed money at specific projects with clear objectives, such

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In the early seventies, the capabilities of AI programs were limited. Even the most impressive could only handle trivial versions of the problems they were supposed to solve; all the programs were, in some sense, "toys". AI researchers had begun to run into several limits that would be only conquered

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In the 1940s and 50s, a handful of scientists from a variety of fields (mathematics, psychology, engineering, economics and political science) explored several research directions that would be vital to later AI research. Alan Turing was among the first people to seriously investigate the theoretical

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devoted to the production of knowledge by logical means; Llull described his machines as mechanical entities that could combine basic and undeniable truths by simple logical operations, produced by the machine by mechanical meanings, in such ways as to produce all the possible knowledge. Llull's work

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to run it and hiring top scientists. OpenAI began as a non-profit, “free from the economic incentives that were driving Google and other corporations.” Musk became frustrated again and left the company in 2018. OpenAI turned to Microsoft for continued financial support and Altman and OpenAI formed a

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to create a numeric vectors to represent each word. Users were surprised at how well it was able to capture word meanings, for example, ordinary vector addition would give equivalences like China + River = Yangtze, London+England-France = Paris. This database in particular would be essential for the

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The success of machine learning in the 2000s depended on the availability of vast amounts of training data and faster computers. Russell and Norvig wrote that the "improvement in performance obtained by increasing the size of the data set by two or three orders of magnitude outweighs any improvement

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around 2012 which improved the performance of machine learning on many tasks, including image and video processing, text analysis, and speech recognition. Investment in AI increased along with its capabilities, and by 2016, the market for AI-related products, hardware, and software reached more than

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had already been used in other fields but it was unknown to these researchers). The AI community became aware of backpropogation in the 80s, and, in the 21st century, neural networks would become enormously successful, fulfilling all of Rosenblatt's optimistic predictions. Rosenblatt did not live to

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AI Laboratory proposed that AI research should focus on artificially simple situations known as micro-worlds. They pointed out that in successful sciences like physics, basic principles were often best understood using simplified models like frictionless planes or perfectly rigid bodies. Much of the

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The New York Times wrote in 2023 “At the heart of this competition is a brain-stretching paradox. The people who say they are most worried about A.I. are among the most determined to create it and enjoy its riches. They have justified their ambition with their strong belief that they alone can keep

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about something. For example, if we use the concept of a bird, there is a constellation of facts that immediately come to mind: we might assume that it flies, eats worms and so on (none of which are true for all birds). Minsky associated these assumptions with the general category and they could be

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a machine to think like a person. In order to use ordinary concepts like "chair" or "restaurant" they had to make all the same illogical assumptions that people normally made. Unfortunately, imprecise concepts like these are hard to represent in logic. MIT chose instead to focus on writing programs

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These setbacks did not affect the growth and progress of the field, however. The funding cuts only impacted a handful of major laboratories and the critiques were largely ignored. General public interest in the field continued to grow, the number of researchers increased dramatically, and new ideas

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wrote: "I am confident that this bottom-up route to artificial intelligence will one date meet the traditional top-down route more than half way, ready to provide the real world competence and the commonsense knowledge that has been so frustratingly elusive in reasoning programs. Fully intelligent

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In the 1970s, AI was subject to critiques and financial setbacks. AI researchers had failed to appreciate the difficulty of the problems they faced. Their tremendous optimism had raised public expectations impossibly high, and when the promised results failed to materialize, funding targeted at AI

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Alan Turing was thinking about machine intelligence at least as early as 1941, when he circulated a paper on machine intelligence which could be the earliest paper in the field of AI — although it is now lost. His 1950 paper was followed by three radio broadcasts on AI by Turing, the two lectures

2469:. Finding optimal solutions to these problems requires extraordinary amounts of computer time, except when the problems are trivial. This limitation applied to all symbolic AI programs that used search trees and meant that many of the "toy" solutions used by AI would never scale to useful systems. 4389:

refers to the period of rapid advancement and widespread adoption of artificial intelligence technologies that began in the early 2010s and continues into the 2020s. This era is marked by significant breakthroughs in machine learning, particularly in deep learning and neural networks, leading to

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of Google, unlike Musk and Hassabis, was an optimist about the future of AI. Musk and Paige became embroiled in an argument about the risk of AGI at Musk's 2015 birthday party. They had been friends for decades but stopped speaking to each other shortly afterwards. Musk attended the one and only

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require enormous amounts of information about the world: the program needs to have some idea of what it might be looking at or what it is talking about. This requires that the program know most of the same things about the world that a child does. Researchers soon discovered that this was a vast

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were, to most people, simply "astonishing": computers were solving algebra word problems, proving theorems in geometry and learning to speak English. Few at the time would have believed that such "intelligent" behavior by machines was possible at all. Researchers expressed an intense optimism in

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The major laboratories (MIT, Stanford, CMU and Edinburgh) had been receiving generous support from their governments, and when it was withdrawn, these were the only places that were seriously impacted by the budget cuts. The thousands of researchers outside these institutions and the many more

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algorithm. However, straightforward implementations, like those attempted by McCarthy and his students in the late 1960s, were especially intractable: the programs required astronomical numbers of steps to prove simple theorems. A more fruitful approach to logic was developed in the 1970s by

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The continued growth of AI technologies promises further integration into daily life and the global economy. Ongoing research aims to address current limitations, such as improving the explainability of AI decisions and ensuring robustness against adversarial attacks. Collaboration between

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became possible in the mid-fifties, a few scientists instinctively recognized that a machine that could manipulate numbers could also manipulate symbols and that the manipulation of symbols could well be the essence of human thought. This was a new approach to creating thinking machines.

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and the controversy over the COMPAS system illuminated several problems with the current technological infrastructure, including misinformation, social media algorithms designed to maximize engagement, the misuse of personal data and the trustworthiness of predictive models. Issues of

4722:. "ne of the reasons for inventing the term "artificial intelligence" was to escape association with "cybernetics". Its concentration on analog feedback seemed misguided, and I wished to avoid having either to accept Norbert (not Robert) Wiener as a guru or having to argue with him.". 3327:. They can't be efficiently implemented using abstract symbolic reasoning, so AI should solve the problems of perception, mobility, manipulation and survival without using symbolic representation at all. These robotics researchers advocated building intelligence "from the bottom up". 3114:

The power of expert systems came from the expert knowledge they contained. They were part of a new direction in AI research that had been gaining ground throughout the 70s. "AI researchers were beginning to suspect—reluctantly, for it violated the scientific canon of

4240:. DeepMind's founders had a personal connection with Yudkowsky and Musk was among those who was actively raising the alarm. Hassabis was both worried about the dangers of AGI and optimistic about its power; he hoped they could "solve AI, then solve everything else." 4068:

Deep learning was applied to dozens of problems over the next few years (such as speech recognition, machine translation, medical diagnosis, and game playing). In every case it showed enormous gains in performance. Investment and interest in AI boomed as a result.

1688:'s checkers program, the subject of his 1959 paper "Some Studies in Machine Learning Using the Game of Checkers", eventually achieved sufficient skill to challenge a respectable amateur. Samuelson's program was among the first uses of what would later be called 3790:

is a system that perceives its environment and takes actions which maximize its chances of success. By this definition, simple programs that solve specific problems are "intelligent agents", as are human beings and organizations of human beings, such as

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represents concepts (e.g. "house", "door") as nodes, and relations among concepts as links between the nodes (e.g. "has-a"). The first AI program to use a semantic net was written by Ross Quillian and the most successful (and controversial) version was

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Moravec explains, "Their initial promises to DARPA had been much too optimistic. Of course, what they delivered stopped considerably short of that. But they felt they couldn't in their next proposal promise less than in the first one, so they promised

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in 2017, leading to the scaling and development of large language models exhibiting human-like traits of knowledge, attention and creativity. The new AI era began around 2020–2023, with the public release of scaled large language models (LLMs) such as

2424:: There was not enough memory or processing speed to accomplish anything truly useful. For example: Ross Quillian's successful work on natural language was demonstrated with a vocabulary of only 20 words, because that was all that would fit in memory. 3448:

gives an agent a reward every time it performs a desired action well, and may give negative rewards (or “punishments”) when it performs poorly. It was described in the first half of the twentieth century by psychologists using animal models, such as

1597:) that was indistinguishable from a conversation with a human being, then it was reasonable to say that the machine was "thinking". This simplified version of the problem allowed Turing to argue convincingly that a "thinking machine" was at least 3722:. The shared mathematical language allowed both a higher level of collaboration with more established and successful fields and the achievement of results which were measurable and provable; AI had become a more rigorous "scientific" discipline. 2683:

dialogue" based on ELIZA. Weizenbaum was disturbed that Colby saw a mindless program as a serious therapeutic tool. A feud began, and the situation was not helped when Colby did not credit Weizenbaum for his contribution to the program. In 1976,

4061:. Although this architecture has been known since the 60s, getting it to work requires powerful hardware and large amounts of training data. Before these became available, improving performance of image processing systems required hand-crafted 3226:") could learn and process information, and provably converges after enough time under any fixed condition. It was a breakthrough, as it was previously thought that nonlinear networks would, in general, evolve chaotically. Around the same time, 800:

reinvigorated investment in AI and by the late 80s the industry had grown into the billions of dollars. However, investors' enthusiasm waned in the 1990s and the field was criticized in the press and avoided by industry (a period known as the

3507:, which played backgammon as well as the best human players. The program learned the game by playing against itself with zero prior knowledge. In an interesting case of interdisciplinary convergence, neurologists discovered in 1997 that the 2377:, then the director of ARPA, believed that his organization should "fund people, not projects!" and allowed researchers to pursue whatever directions might interest them. This created a freewheeling atmosphere at MIT that gave birth to the 3627:

In the 1990s, algorithms originally developed by AI researchers began to appear as parts of larger systems. AI had solved a lot of very difficult problems and their solutions proved to be useful throughout the technology industry, such as

4416:: Breakthroughs in algorithms, such as the development of deep learning architectures (e.g., convolutional neural networks, recurrent neural networks) and reinforcement learning techniques, have significantly improved AI capabilities. 2937:

that a conclusion holds (by default) if its contrary cannot be shown. He showed how such an assumption corresponds to the common sense assumption made in reasoning with frames. He also showed that it has its "procedural equivalent" as

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was applied to a wide range of problems in academic and industry. The success was due to the availability of powerful computer hardware, the collection of immense data sets and the application of solid mathematical methods. In 2012,

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Over the next 20 years, AI consistently delivered working solutions to specific isolated problems. By the late 1990s, it was being used throughout the technology industry, although somewhat behind the scenes. The success was due to

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Bubeck S, Chandrasekaran V, Eldan R, Gehrke J, Horvitz E, Kamar E, Lee P, Lee YT, Li Y, Lundberg S, Nori H, Palangi H, Ribeiro MT, Zhang Y (22 March 2023). "Sparks of Artificial General Intelligence: Early experiments with GPT-4".

1861:". Miller wrote "I left the symposium with a conviction, more intuitive than rational, that experimental psychology, theoretical linguistics, and the computer simulation of cognitive processes were all pieces from a larger whole." 4372:

passing an advanced biology test. Gates was convinced. In 2023, Microsoft Research tested the model with a large variety of tasks, and concluded that "it could reasonably be viewed as an early (yet still incomplete) version of an

3360:, arguing that symbols are not always necessary since "the world is its own best model. It is always exactly up to date. It always has every detail there is to be known. The trick is to sense it appropriately and often enough." 1376:

Their answer was surprising in two ways. First, they proved that there were, in fact, limits to what mathematical logic could accomplish. But second (and more important for AI) their work suggested that, within these limits,

753:, with myths, stories and rumors of artificial beings endowed with intelligence or consciousness by master craftsmen. The study of logic and formal reasoning from antiquity to the present led directly to the invention of the 3647:

The field of AI received little or no credit for these successes in the 1990s and early 2000s. Many of AI's greatest innovations have been reduced to the status of just another item in the tool chest of computer science.

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describes a procedure that he claims can fabricate an "artificial man". By placing the "sperm of a man" in horse dung, and feeding it the "Arcanum of Mans blood" after 40 days, the concoction will become a living infant.

4205:" for the new sub-field, founding a journal and holding conferences beginning in 2008. The new field grew rapidly, buoyed by the continuing success of artificial neural networks and the hope that it was the key to AGI. 3607:

had not been met. Indeed, some of them, like "carry on a casual conversation" would not be accomplished for another 40 years. As with other AI projects, expectations had run much higher than what was actually possible.

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Russell and Norvig write: "any of the concepts we name in language fail, on closer inspection, to have the logically defined necessary and sufficient conditions that early AI researchers hoped to capture in axiomatic

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These successes were not due to some revolutionary new paradigm, but mostly on the tedious application of engineering skill and on the tremendous increase in the speed and capacity of computers by the 90s. In fact,

3667:. In part, this may have been because they considered their field to be fundamentally different from AI, but also the new names help to procure funding. In the commercial world at least, the failed promises of the 10914: 2932:

admitted that "conventional logics, such as first-order logic, lack the expressive power to adequately represent the knowledge required for reasoning by default". He proposed augmenting first-order logic with a

2238:. It suggested that there were severe limitations to what perceptrons could do and that Rosenblatt's predictions had been grossly exaggerated. The effect of the book was that virtually no research was funded in 1765:, explaining how a system composed of matter can have the properties of mind." The symbolic reasoning paradigm they introduced would dominate AI research and funding until the middle 90s, as well as inspire the 757:

in the 1940s, a machine based on the abstract essence of mathematical reasoning. This device and the ideas behind it inspired a handful of scientists to begin seriously discussing the possibility of building an

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claimed that "most of 'frames' is just a new syntax for parts of first-order logic." But he noted that "there are one or two apparently minor details which give a lot of trouble, however, especially defaults".

4410:: The exponential growth of data from the internet, social media, Internet of Things (IoT) devices, and digitization of records has provided extensive datasets required for training sophisticated AI models. 4176:

and unintended consequences became significantly more popular at AI conferences, publications vastly increased, funding became available, and many researchers re-focussed their careers on these issues. The

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the machine's goal function with the goals of its owner and humanity in general. Thus, the problem of mitigating the risks and unintended consequences of AI became known as "the value alignment problem" or

2172:). Like most AI researchers, he was optimistic about their power, predicting that a perceptron “may eventually be able to learn, make decisions, and translate languages." Rosenblatt was primarily funded by 2428:

argued in 1976 that computers were still millions of times too weak to exhibit intelligence. He suggested an analogy: artificial intelligence requires computer power in the same way that aircraft require

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speculated that Babbage's machine was "a thinking or ... reasoning machine", but warned "It is desirable to guard against the possibility of exaggerated ideas that arise as to the powers" of the machine.

985:, destined to live forever in the flask in which he was made, endeavors to be born into a full human body. Upon the initiation of this transformation, however, the flask shatters and the homunculus dies. 2547:

on the state of AI research in the UK criticized the failure of AI to achieve its "grandiose objectives" and led to the dismantling of AI research in that country. (The report specifically mentioned the

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was a giant made of bronze who acted as guardian for the island of Crete. He would throw boulders at the ships of invaders and would complete 3 circuits around the island's perimeter daily. According to

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defines AI research as "the study of intelligent agents". This is a generalization of some earlier definitions of AI: it goes beyond studying human intelligence; it studies all kinds of intelligence.

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used the example of an intelligent robot that kills its owner to prevent it from being unplugged, reasoning "you can't fetch the coffee if you're dead". (This problem is known by the technical term "

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blamed the crisis on the unrealistic predictions of his colleagues. "Many researchers were caught up in a web of increasing exaggeration." However, there was another issue: since the passage of the

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during the summer of 1956. Attendees of the workshop became the leaders of AI research for decades. Many of them predicted that machines as intelligent as humans would exist within a generation. The

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explains "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 not labeled AI anymore."

3353:'s frames), arguing that AI needed to understand the physical machinery of vision from the bottom up before any symbolic processing took place. (Marr's work would be cut short by leukemia in 1980.) 11180: 3079:

project. Their objectives were to write programs and build machines that could carry on conversations, translate languages, interpret pictures, and reason like human beings. Much to the chagrin of

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that solved a given task without using high-level abstract definitions or general theories of cognition, and measured performance by iterative testing, rather than arguments from first principles.

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This is how the most widely used textbooks of the 21st century define artificial intelligence, such as Russell and Norvig, 2021; Padgham and Winikoff, 2004; Jones, 2007; Poole and Mackworth, 2017.

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and others provided proof. McCarthy responded that what people do is irrelevant. He argued that what is really needed are machines that can solve problems—not machines that think as people do.

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AI researchers began to develop and use sophisticated mathematical tools more than they ever had in the past. Most of the new directions in AI relied heavily on mathematical models, including

3547:) and using the highest standards of scientific accountability. By 2000, AI had achieved some of its oldest goals. The field was both more cautious and more successful than it had ever been. 4255:

for a price of $ 44 million. Hassabis took notice and sold DeepMind to Google in 2014, on the condition that it would not accept military contracts and would be overseen by an ethics board.

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recalled that back in the 90s, the problem was that “our labeled datasets were thousands of times too small. our computers were millions of times too slow.” This was no longer true by 2010.

3743:" became widely accepted during the 1990s. Although earlier researchers had proposed modular "divide and conquer" approaches to AI, the intelligent agent did not reach its modern form until 4197:

in 1995, and similar opinions were published by AI elder statesmen John McCarthy, Marvin Minsky, and Patrick Winston in 2007-2009. Minsky organized a symposium on "human-level AI" in 2004.

11230: 1928:(DARPA, then known as "ARPA") poured money into the field. Artificial Intelligence laboratories were set up at a number of British and US universities in the latter 1950s and early 1960s. 5027:

Weizenbaum said: "I became the only member of the AI community to be seen eating lunch with Dreyfus. And I deliberately made it plain that theirs was not the way to treat a human being."

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is said to have "embalmed" the head with herbs and spoke incantations over it such that Mímir’s head remained able to speak wisdom to Odin. Odin then kept the head near him for counsel.

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beginning 1972. Their collaboration revolutionized the study of reinforcement learning and decision making over the four decades. In 1988, Sutton described machine learning in terms of

1983: 3123:. "he great lesson from the 1970s was that intelligent behavior depended very much on dealing with knowledge, sometimes quite detailed knowledge, of a domain where a given task lay". 1555:

showed that any form of computation could be described digitally. The close relationship between these ideas suggested that it might be possible to construct an "electronic brain".

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research, the MINOS project ran out of funding in 1966. Rosenblatt failed to secure continued funding in the 1960s. In 1969, research came to a sudden halt with the publication of

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During the early modern period, these legendary automata were said to possess the magical ability to answer questions put to them. The late medieval alchemist and proto-protestant

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ridiculed the broken promises of the 1960s and critiqued the assumptions of AI, arguing that human reasoning actually involved very little "symbol processing" and a great deal of

2289:: "within ten years a digital computer will be the world's chess champion" and "within ten years a digital computer will discover and prove an important new mathematical theorem." 2055:

could carry out conversations that were so realistic that users occasionally were fooled into thinking they were communicating with a human being and not a computer program (see

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whenever they reached a dead end. The principal difficulty was that, for many problems, the number of possible paths through the "maze" was astronomical (a situation known as a "

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Piccinini G (1 August 2004). "The First Computational Theory of Mind and Brain: A Close Look at Mcculloch and Pitts's "Logical Calculus of Ideas Immanent in Nervous Activity"".

4422:: The accessibility of cloud platforms has lowered the barrier to entry for AI development, allowing researchers and companies to access powerful computing resources on-demand. 3882:

and others became concerned that AI had largely abandoned its original goal of producing versatile, fully intelligent machines, and argued in favor of more direct research into

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reported that "by 2009, nearly all sectors in the US economy had at least an average of 200 terabytes of stored data". This collection of information was known in the 2000s as

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Faust; a tragedy. Translated, in the original metres ... by Bayard Taylor. Authorised ed., published by special arrangement with Mrs. Bayard Taylor. With a biographical introd

4404:: The development of high-performance GPUs and specialized hardware like TPUs (Tensor Processing Units) has enabled the training of complex neural networks on large datasets. 3286:

to recognize handwritten digits. The system was used widely in 90s, reading zip codes and personal checks. This was the first genuinely useful application of neural networks.

2672:, was also an outspoken critic of Dreyfus' positions, but he "deliberately made it plain that was not the way to treat a human being," and was unprofessional and childish. 1948:. To achieve some goal (like winning a game or proving a theorem), they proceeded step by step towards it (by making a move or a deduction) as if searching through a maze, 5344:

Several other laboratories had developed systems that, like AlexNet, used GPU chips and performed nearly as well as AlexNet, but AlexNet proved to be the most influential.

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Artificial intelligence is based on the assumption that the process of human thought can be mechanized. The study of mechanical—or "formal"—reasoning has a long history.

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meeting of the DeepMind’s ethics board, where it became clear that Google was uninterested in mitigating the harm of AGI. Frustrated by his lack of influence he founded

3933: 3182:. A small number of scientists and engineers began to doubt that the symbolic approach would ever be sufficient for these tasks and developed other approaches, such as " 12310:

Kaplan A, Haenlein M (2018), "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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also handle imprecise information, and are classified as "soft". In the 90s and early 2000s many other soft computing tools were developed and put into use, including

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The earliest research into thinking machines was inspired by a confluence of ideas that became prevalent in the late 1930s, 1940s, and early 1950s. Recent research in

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amount of information with billions of atomic facts. No one in 1970 could build a database large enough and no one knew how a program might learn so much information.

1589:", in which he speculated about the possibility of creating machines that think. In the paper, he noted that "thinking" is difficult to define and devised his famous 4160:

system used by the criminal justice system exhibited racial bias under some measures, others showed that many machine learning systems exhibited some form of racial

3850:, which predicts that the speed and memory capacity of computers doubles every two years. The fundamental problem of "raw computer power" was slowly being overcome. 1166:

philosophers all developed structured methods of formal deduction by the first millennium BCE. Their ideas were developed over the centuries by philosophers such as

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challenged mathematicians of the 1920s and 30s to answer this fundamental question: "can all of mathematical reasoning be formalized?" His question was answered by

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problem) and their simple design made it relatively easy for programs to be built and then modified once they were in place. All in all, the programs proved to be

1632:' from 1936 using similar two-state boolean 'neurons', but was the first to apply it to neuronal function. One of the students inspired by Pitts and McCulloch was 10244: 3802:

The paradigm gave researchers license to study isolated problems and to disagree about methods, but still retain hope that their work could be combined into an

1660:, were built in the 1950s. These machines did not use computers, digital electronics or symbolic reasoning; they were controlled entirely by analog circuitry. 598: 4648:'Intelligent Machinery, A Heretical Theory' and 'Can Digital Computers Think?' and the panel discussion 'Can Automatic Calculating Machines be Said to Think?' 4498:: Governments and international bodies are grappling with how to effectively regulate AI to ensure safety and ethical compliance without stifling innovation. 4890:

was only capable of 130 MIPS, and a typical desktop computer had 1 MIPS. As of 2011, practical computer vision applications require 10,000 to 1,000,000 MIPS.

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In the early 2000s, several researchers became concerned that mainstream AI was too focused on "measurable performance in specific applications" (known as "

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Another key reason for the success in the 90s was that AI researchers focussed on specific problems with verifiable solutions (an approach later derided as

3952:. Released in 2009, it was a useful body of training data and a benchmark for testing for the next generation of image processing systems. Google released 3095: 2535:(NRC) became frustrated with the lack of progress and eventually cut off almost all funding for undirected AI research. The pattern began in 1966 when the 3699:. In the 90s and 2000s, many other highly mathematical tools were adapted for AI. These tools were applied to machine learning, perception and mobility. 4790:

The hardware diversity was particularly clear in the different technologies used in implementing the adjustable weights. The perceptron machines and the

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Later research showed that there was no way for system to avoid a measurable racist bias -- fixing one form of bias would necessarily introduce another.

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reported in 2005: "Computer scientists and software engineers avoided the term artificial intelligence for fear of being viewed as wild-eyed dreamers."

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prostitute themselves. Despite this, he makes offerings at the temple of Venus asking the goddess to bring to him a woman just like a statue he carved.

3154:, argued that there is no shortcut ― the only way for machines to know the meaning of human concepts is to teach them, one concept at a time, by hand. 2961:

During the late 1970s and throughout the 1980s, a variety of logics and extensions of first-order logic were developed both for negation as failure in

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Over 300 AI companies had shut down, gone bankrupt, or been acquired by the end of 1993, effectively ending the first commercial wave of AI. In 1994,

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was severely reduced. The lack of success indicated the techniques being used by AI researchers at the time were insufficient to achieve their goals.

2217:. Most of neural network research during this early period involved building and using bespoke hardware, rather than simulation on digital computers. 10939: 6513: 4791: 4586: 4039: 2246: 1637: 445: 397: 4731:

Pamela McCorduck discusses how the Dartmouth conference alumni dominated the first two decades of AI research, calling them the "invisible college".

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could be achieved by insertion of a piece of paper with any of God’s names on it, into the mouth of the clay figure. Unlike legendary automata like

421: 4050:. This was a turning point in machine learning: over the next few years dozens of other approaches to image recognition were abandoned in favor of 2536: 5197: 12648: 11239: 8044: 3619:

that "The immediate future of artificial intelligence—in its commercial form—seems to rest in part on the continued success of neural networks."

11382:"A research and development program in applications of intelligent automata to reconnaissance-phase I. (Proposal for Research SRI No. ESU 65-1)" 11022: 3702:

There was a widespread realization that many of the problems that AI needed to solve were already being worked on by researchers in fields like

1841:

In the fall of 1956, Newell and Simon also presented the Logic Theorist at a meeting of the Special Interest Group in Information Theory at the

3915: 728: 4360:

These models can discuss a huge number of topics and display general knowledge. The question naturally arises: are these models an example of

3562:

The first indication of a change in weather was the sudden collapse of the market for specialized AI hardware in 1987. Desktop computers from

3928:

The most useful data in the 2000s came from curated, labeled data sets created specifically for machine learning and AI. In 2007, a group at

3511:

in brains also uses a version of the TD-learning algorithm. TD learning would be become highly influential in the 21st century, used in both

1903:

The cognitive approach allowed researchers to consider "mental objects" like thoughts, plans, goals, facts or memories, often analyzed using

12591: 5124:

Another aspect of the conflict was called "the procedural/declarative distinction" but did not prove to be influential in later AI research.

4492:: AI systems can perpetuate existing biases present in training data, leading to unfair outcomes in areas like criminal justice and hiring. 2633:

argument, presented in 1980, attempted to show that a program could not be said to "understand" the symbols that it uses (a quality called "

11716: 3072: 2214: 468: 13593: 3589:" (i.e., they could make grotesque mistakes when given unusual inputs). Expert systems proved useful, but only in a few special contexts. 13806: 11353: 4120:

argued that, if one isn't careful about defining these goals, the machine may cause harm to humanity in the process of achieving a goal.

4077:

It became fashionable in the 2000s to begin talking about the future of AI again and several popular books considered the possibility of

1858: 1783:

The Dartmouth workshop of 1956 was a pivotal event that marked the formal inception of AI as an academic discipline. It was organized by

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and showed how they might perform simple logical functions in 1943. They were the first to describe what later researchers would call a

13366: 11826: 7027: 1987: 641: 623: 440: 11381: 3600:

had decided that AI was not "the next wave" and directed funds towards projects that seemed more likely to produce immediate results.

4480:: Automation and AI may displace certain jobs, leading to discussions about the future of work and the need for reskilling programs. 4428:: Substantial investments from both the private sector and governments have accelerated research and development in AI technologies. 4001: 3578:

and others. There was no longer a good reason to buy them. An entire industry worth half a billion dollars was demolished overnight.

2892: 1925: 1924:

private and in print, predicting that a fully intelligent machine would be built in less than 20 years. Government agencies like the

1035:" reflected society's growing interest in machines with artificial intelligence. AI remains a common topic in science fiction today. 11211: 3488:). This gave the subject a solid theoretical foundation and access to a large body of theoretical results developed in the field of 1295:

provided the essential breakthrough that made artificial intelligence seem plausible. The foundations had been set by such works as

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show improvement. It significantly outperformed previous algorithms. TD-learning was used by Gerald Tesauro in 1992 in the program

1796: 618: 593: 478: 257: 235: 10379:

Gilpin LH, Yuan D, Ba Z, Kagal L, Eaton E (2018). "Explaining Explanations: An Overview of Interpretability of Machine Learning".

13071: 10085: 4466:: Automation of processes with robotics, predictive maintenance, and quality control to reduce downtime and increase efficiency. 3968:

The explosive growth of the internet gave machine learning programs access to billions of pages of text and images that could be

3367:

also rejected the symbol processing model of the mind and argued that the body was essential for reasoning, a theory called the "

2540: 2532: 780:

Eventually, it became obvious that researchers had grossly underestimated the difficulty of the project. In 1974, criticism from

547: 171: 3323:— it needs to perceive, move, survive and deal with the world. Sensorimotor skills are essential to higher level skills such as 3119:—that intelligence might very well be based on the ability to use large amounts of diverse knowledge in different ways," writes 1601:

and the paper answered all the most common objections to the proposition. The Turing Test was the first serious proposal in the

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in a configuration named MINOS III (1968), which could classify symbols on army maps, and recognize hand-printed characters on

671: 95: 13615: 3830:

by autonomously navigating 55 miles in an urban environment while responding to traffic hazards and adhering to traffic laws.

2370:

in 1965. These four institutions would continue to be the main centers of AI research and funding in academia for many years.

1974:". Other "searching" programs were able to accomplish impressive tasks like solving problems in geometry and algebra, such as 13777: 13719: 13375: 13248: 13219: 13135: 13087: 13054: 13025: 12974: 12927: 12880: 12824: 12723: 12573: 12492: 12465: 12443: 12422: 12390: 12284: 12212: 12142: 12112: 12088: 12032: 11979: 11947: 11603: 11522: 11449: 11334: 11299: 11197: 11122: 10663: 10625: 10593: 9565: 5187:

McCorduck writes "Two and a half decades later, we can see that the Japanese didn't quite meet all of those ambitious goals."

4581: 4454:: Development of autonomous vehicles, traffic management systems, and optimization of logistics and supply chain management. 3060: 2592: 2242:

for 10 years. The competition for government funding ended with the victory of symbolic AI approaches over neural networks.

1842: 1602: 1015: 613: 390: 316: 270: 225: 220: 4752:

There were a few psychologists who avoided behaviorism and embraced a cognitive approach before it was fashionable, such as

4012:, by a significant margin. Watson's expertise would have been impossible without the information available on the internet. 1636:

who was a 24-year-old graduate student at the time. In 1951 Minsky and Dean Edmonds built the first neural net machine, the

1346: 999:

By the 19th century, ideas about artificial men and thinking machines became a popular theme in fiction. Notable works like

12946: 12677: 10529: 6393: 5056:

showed that people do poorly on completely abstract problems, but if the problem is restated to allow the use of intuitive

4982: 4324: 3006: 2759: 1586: 906:. In the 10th book of Ovid's narrative poem, Pygmalion becomes disgusted with women when he witnesses the way in which the 521: 3245:

Neural networks, along with several other similar models, received widespread attention after the 1986 publication of the

3166:

produced useful applications in the 80s and received massive amounts of funding, it was still unable to solve problems in

2602: 13452: 13274: 12433: 4606: 4601: 4534: 3929: 1936:

There were many successful programs and new directions in the late 50s and 1960s. Among the most influential were these:

1900:. All these fields used related tools to model the mind and results discovered in one field were relevant to the others. 666: 661: 656: 651: 646: 369: 341: 336: 230: 23: 19: 13259: 4368:

was skeptical of the new technology and the hype that surrounded AGI. However, Altman presented him with a live demo of

2637:"). If the symbols have no meaning for the machine, Searle argued, then the machine can not be described as "thinking". 13393: 12702: 12669: 12636: 11169: 10977: 10958: 10417: 10008: 5096: 5006:"Know-how" is Dreyfus' term. Dreyfus makes a distinction between "knowing how" and "knowing that", a modern version of 4938: 4769: 4707: 4596: 4103:. The topic became widely covered in the press and many leading intellectuals and politicians commented on the issue. 3346: 2946:. The closed world assumption, as formulated by Reiter, "is not a first-order notion. (It is a meta notion.)" However, 2859: 2818: 2703: 2359: 2335: 1816: 1788: 1685: 994: 721: 198: 188: 178: 11412: 4866:

History would prove Moravec right about applications like computer vision. Moravec estimated that simply matching the

13347: 11885: 11852: 11422: 11103: 10895: 10776: 10490: 10472: 10326:

Mehrabi N, Morstatter F, Saxena N, Lerman K, Galstyan A (2021). "A Survey on Bias and Fairness in Machine Learning".

4814:

with multiple holes in them that could be individually blocked, with the degree of blockage representing the weights.

2907: 2508:

observed that "using precise language to describe essentially imprecise concepts doesn't make them any more precise."

2462: 301: 247: 213: 80: 13186: 11187: 4510:

This section on the AI Boom was written by ChatGPT—an AI reflecting on the rise of AI. Talk about being self-aware!

2115:. At the same time, Minsky and Papert built a robot arm that could stack blocks, bringing the blocks world to life. 1111:. The faithful believed that craftsman had imbued these figures with very real minds, capable of wisdom and emotion— 10643: 5501: 4448:: Algorithms assist in fraud detection, algorithmic trading, risk assessment, and personalized financial planning. 2947: 2138: 1873: 970:. Islamic alchemists attempted to create a broad range of life through their work, ranging from plants to animals. 858: 792:

to stop funding undirected research into artificial intelligence. Seven years later, a visionary initiative by the

516: 501: 383: 287: 133: 5278:

wrote that the improvement in computer chess "is governed only by the brute force expansion of computer hardware."

3906:. The risks and unintended consequences of AI technology became an area of serious academic research after 2016. 3826:

by driving autonomously for 131 miles along an unrehearsed desert trail. Two years later, a team from CMU won the

13767: 12901: 10509: 8337: 7965: 4883: 4374: 4361: 4202: 3883: 3870:

techniques were successfully applied to many problems throughout the economy. A turning point was the success of

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directly, by creating a massive database that would contain all the mundane facts that the average person knows.

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five years earlier. DARPA continued to provide $ 3 million each year until the 70s. DARPA made similar grants to

2309:): "In from three to eight years we will have a machine with the general intelligence of an average human being." 2203: 2202:

and Alfred E. (Ted) Brain built two neural network machines named MINOS I (1960) and II (1963), mainly funded by

1134:, having developed a legend of having been a wizard. These legends were similar to the Norse myth of the Head of 608: 542: 526: 65: 11686: 11035: 8617: 4357:: they are trained on vast quantities of unlabeled data and can be adapted to a wide range of downstream tasks. 4278:

and 14 other scientists left OpenAI over concerns that the company was putting profits above safety. The formed

1911:. Symbolic mental objects would become the major focus of AI research and funding for the next several decades. 13164: 4193:") and had abandoned AI’s original goal of creating versatile, fully intelligent machines. An early critic was 3593: 3103: 2990: 2597:

Several philosophers had strong objections to the claims being made by AI researchers. One of the earliest was

1185: 603: 10677: 2885:

noted that many of his fellow researchers were using the same kind of tool: a framework that captures all our

2322:

received a $ 2.2 million grant from the newly created Advanced Research Projects Agency (ARPA, later known as

13811: 13525: 3283: 3044: 3021:, developed in 1972, diagnosed infectious blood diseases. They demonstrated the feasibility of the approach. 2910:" to successfully answer questions about short stories in English. Frames would eventually be widely used in 2783: 2779: 714: 702: 572: 562: 5111:

conference where he said "Artificial intelligence is not, by definition, simulation of human intelligence" (

4768:

Russell and Norvig wrote "it was astonishing whenever a computer did anything remotely clever." AI founder

4164:, and there were many other examples of dangerous outcomes that had resulted from machine learning systems. 2063:

or repeated back what was said to it, rephrasing its response with a few grammar rules. ELIZA was the first

1872:

in psychology, philosophy, computer science and neuroscience. It inspired the creation of the sub-fields of

1416: 1115:

wrote that "by discovering the true nature of the gods, man has been able to reproduce it". English scholar

4611: 4328: 3656: 3496: 3005:

is a program that answers questions or solves problems about a specific domain of knowledge, using logical

2299:: "Within a generation ... the problem of creating 'artificial intelligence' will substantially be solved." 2169: 2042: 1480: 1415:

Calculating machines were designed or built in antiquity and throughout history by many people, including

1406: 688: 676: 511: 10993:

McCulloch WS, Pitts W (1 December 1943). "A logical calculus of the ideas immanent in nervous activity".

10708: 5332: 5254: 5080:. Kahnmann published a more general theory of symbolic cognition and other kinds of thinking in his book 4941:

wrote in response that "the combinatorial explosion problem has been recognized in AI from the beginning"

4173: 3772: 3331: 2915: 2896:

by the frames for subcategories and individuals, or over-ridden as necessary. He called these structures

2762:") that permit tractable computation. Rules would continue to be influential, providing a foundation for 2664:, was given a cold shoulder: he later said that AI researchers "dared not be seen having lunch with me." 2641: 2609:(such as a computer program) could never see the truth of certain statements, while a human being could. 2441: 2123:

could communicate in ordinary English sentences about the micro-world, plan operations and execute them.

2018: 1410: 1276: 506: 252: 203: 100: 11997: 10867: 10299:

Zuboff S (2015). "Big other: surveillance capitalism and the prospects of an information civilization".

10111: 5424: 3585:, proved too expensive to maintain. They were difficult to update, they could not learn, and they were " 3570:

had been steadily gaining speed and power and in 1987 they became more powerful than the more expensive

2993:. "Overall, the AI industry boomed from a few million dollars in 1980 to billions of dollars in 1988." 2402:

and many other areas. Historian Thomas Haigh argued in 2023 that there was no winter, and AI researcher

1907:

in functional networks. These objects had been forbidden as "unobservable" by earlier paradigms such as

1229: 13312:"From Analytical Engine to Electronic Digital Computer: The Contributions of Ludgate, Torres, and Bush" 11937: 11790: 5420: 5133:

Versions of backpropagation had been developed in several fields, most directly as the reverse mode of

3684: 3664: 3434: 3430: 3410: 3307: 3040: 2347: 2026: 1897: 1488: 1252:

explored the possibility that all rational thought could be made as systematic as algebra or geometry.

978: 577: 75: 58: 12706: 12654: 4460:: Enhanced user experiences through recommendation systems, content creation, and virtual assistants. 3338:

in the late 1970s from a successful background in theoretical neuroscience to lead the group studying

2985:

became the focus of mainstream AI research. Governments provided substantial funding, such as Japan's

2793:

had, that human beings rarely used logic when they solved problems. Experiments by psychologists like

2552:

problem as a reason for AI's failings.) DARPA was deeply disappointed with researchers working on the

13620: 13016:, Simon HA (1963), "GPS: A Program that Simulates Human Thought", in Feigenbaum E, Feldman J (eds.), 12022: 9233: 8529: 5328: 5134: 4916: 4635: 4507:

stakeholders is crucial to maximize benefits while mitigating risks associated with AI advancements.

4442:: AI is used for diagnostics, personalized medicine, drug discovery, and improving patient outcomes. 3997: 3973: 3956:

in 2013 as an open source resource. It used large amounts of data text scraped from the internet and

3604: 3540: 3527:

The business community's fascination with AI rose and fell in the 1980s in the classic pattern of an

3433:. For a time in the 1990s and early 2000s, these soft tools were studied by a subfield of AI called " 3239: 3076: 2986: 2199: 2157: 1625: 1163: 1085: 1032: 1024: 153: 13414: 11181:"Chapter 4: The Life and Times of a Successful SRI Laboratory: Artificial Intelligence and Robotics" 10926: 10137:

Topol EJ (2019). "High-performance medicine: the convergence of human and artificial intelligence".

4208:

Several competing companies, laboratories and foundations were founded to develop AGI in the 2010s.

2660:

said of Dreyfus and Searle "they misunderstand, and should be ignored." Dreyfus, who also taught at

46: 12521: 12514: 11682: 5408: 5250: 5069: 4845:

Russell and Norvig wrote "in almost all cases, these early systems failed on more difficult tasks."

4301: 4125: 4116: 3406: 3131:

became a major focus of AI research in the 1980s. It was hoped that vast databases would solve the

2982: 2598: 2292:

1965, H. A. Simon: "machines will be capable, within twenty years, of doing any work a man can do."

2173: 1673: 1617: 1020: 818: 277: 12992: 11141: 5068:

have shown that people are terrible at elementary problems that involve uncertain reasoning. (See

4486:: The use of AI in surveillance and data analysis poses concerns about individual privacy rights. 3356:

In his 1990 paper "Elephants Don't Play Chess," robotics researcher Brooks took direct aim at the

12597: 12380: 12188: 8692: 5412: 4569: 4300:

The AI boom started with the initial development of key architectures and algorithms such as the

4140:

At the same time, machine learning systems had begun to have disturbing unintended consequences.

4087: 3688: 3660: 3485: 2934: 2728: 2719: 2694:

which argued that the misuse of artificial intelligence has the potential to devalue human life.

2549: 2445: 1953: 1560: 1432: 1257: 552: 38: 3024:

Expert systems restricted themselves to a small domain of specific knowledge (thus avoiding the

1761:, and find new and more elegant proofs for some. Simon said that they had "solved the venerable 1704: 13409: 11753: 11052: 10771:. Austin: Published for the American-Scandinavian Foundation by the University of Texas Press. 5082: 4690: 4678: 4237: 3949: 3711: 3696: 3445: 3357: 3195: 3179: 3124: 3116: 3056: 2955: 2108: 1971: 1904: 1889: 1877: 1854: 1753: 1472: 1464: 1324: 1285: 567: 148: 12202: 11289: 3886:. By the mid-2010s several companies and institutions had been founded to pursue AGI, such as 13542: 12851: 11663: 10615: 10583: 10024: 9206: 4908: 4693:. It includes a more specific definition of a "machine" as an agent that manipulates symbols. 4334: 4318: 4047: 3827: 3823: 3324: 3143: 3136: 3132: 3128: 3025: 2886: 2645: 2500: 2482: 2399: 1757: 1552: 1420: 1329: 1138:. According to legend, Mímir was known for his intellect and wisdom, and was beheaded in the 1093: 893: 632: 12685: 11459: 4743:

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

2954:

can be understood as reasoning implicitly with definitions in first-order logic including a

13737: 12557: 12526: 12348: 12264: 11388: 10830: 10270: 5438:

wrote “ProPublica’s study legitimated concepts like fairness as valid topics for research”

5303:(and this does not even take into account Deep Blue's special-purpose hardware for chess). 5061: 4904: 4811: 4662: 3962: 3843: 3776: 3655:

Many researchers in AI in the 1990s deliberately called their work by other names, such as

3418: 2911: 2794: 2473: 2437:, eventually it could become easy. "With enough horsepower," he wrote, "anything will fly". 2363: 2144: 2092:," which consists of colored blocks of various shapes and sizes arrayed on a flat surface. 1885: 1865: 1836: 1766: 1677: 1393:, could imitate any conceivable process of mathematical deduction. The key insight was the 1382: 1338: 1180: 1081: 942:

in the early 13th century. During the Middle Ages, it was believed that the animation of a

413: 90: 11622: 5354: 4081:

machines and what they might mean for human society. Some of this was optimistic (such as

3972:. And, for specific problems, large privately held databases contained the relevant data. 2965:

and for default reasoning more generally. Collectively, these logics have become known as

8: 13561:, Newell A (1958), "Heuristic Problem Solving: The Next Advance in Operations Research", 12870: 12676:(1969), "Some philosophical problems from the standpoint of artificial intelligence", in 12024:

The Fifth Generation: Artificial Intelligence and Japan's Computer Challenge to the World

11732: 11517:(1st ed.). Cambridge, Massachusetts London, England: The MIT Press. pp. 93–94. 11264: 11218: 10697: 8305: 6549: 5238: 5057: 4879: 4857:

wrote: "Early programs were necessarily limited in scope by the size and speed of memory"

3875:$ 8 billion, and the New York Times reported that interest in AI had reached a "frenzy". 3752: 3719: 3489: 3426: 3080: 2966: 2939: 2853: 2847: 2741: 2563: 2351: 1657: 1327:

presented a formal treatment of the foundations of mathematics in their masterpiece, the

1301: 1112: 793: 463: 242: 13148:

The alchemical creation of life (takwin) and other concepts of Genesis in medieval Islam

12352: 12268: 11971:

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

10834: 10749: 9964:

Jordan MI, Mitchell TM (2015). "Machine learning: Trends, perspectives, and prospects".

4065:

features that were difficult to implement. Deep learning was simpler and more general.

3818:

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

3731:). This provided useful tools in the present, rather than speculation about the future. 3090:

Other countries responded with new programs of their own. The UK began the £350 million

3009:

that are derived from the knowledge of experts. The earliest examples were developed by

2539:(ALPAC) report criticized machine translation efforts. After spending $ 20 million, the 1978:'s Geometry Theorem Prover (1958) and Symbolic Automatic Integrator (SAINT), written by 13742: 13657: 13485: 13427: 13279: 13264: 13146: 12774: 12621: 12562: 12545: 12412: 12327: 12298: 12198: 12130: 11777: 11593: 11572: 11276: 10854: 10570: 10449: 6930: 6339: 4833: 4560:" because they use deep learning in combination with symbolic techniques. For example, 3803: 3637: 3586: 3422: 3036: 2837:

were trying to solve problems like "story understanding" and "object recognition" that

2715: 2614: 2553: 2524: 2374: 2234: 1920: 1850: 1778: 1544: 1292: 1089: 1069: 853: 789: 766: 557: 292: 11641: 11162:

Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy

11075: 10815: 10707:

Hart PE, Nilsson NJ, Perrault R, Mitchell T, Kulikowski CA, Leake DB (15 March 2003).

4042:, with significantly less errors than the second place winner. Krizhevsky worked with 3319:

and others argued that, in order to show real intelligence, a machine needs to have a

13783: 13773: 13763: 13725: 13715: 13698: 13381: 13371: 13357: 13343: 13329: 13244: 13238: 13225: 13215: 13131: 13123: 13093: 13083: 13075: 13060: 13050: 13031: 13021: 12980: 12970: 12923: 12886: 12876: 12830: 12820: 12814: 12741: 12729: 12719: 12569: 12488: 12471: 12461: 12439: 12418: 12396: 12386: 12364: 12331: 12302: 12290: 12280: 12218: 12208: 12148: 12138: 12118: 12108: 12084: 12063: 12028: 12018: 11975: 11969: 11953: 11943: 11881: 11848: 11769: 11765: 11609: 11599: 11576: 11518: 11501: 11484: 11445: 11428: 11418: 11340: 11330: 11295: 11268: 11193: 11165: 11128: 11118: 11099: 11079: 11010: 10901: 10891: 10846: 10782: 10772: 10728: 10659: 10631: 10621: 10589: 10574: 10562: 10496: 10486: 10468: 10413: 10154: 10067: 10004: 9981: 9199:, pp. 204–208 (the difficulty of truth maintenance, i.e., learning and updating) 5416: 5100: 4912: 4753: 4354: 4194: 4157: 4121: 4100: 3899: 3858:

In the first decades of the 21st century, access to large amounts of data (known as "

3796: 3787: 3780: 3740: 3633: 3473: 3429:. These tools in turn depended on advanced mathematical techniques such as classical 3414: 3364: 3299: 3199: 3010: 2962: 2867: 2763: 2755: 2685: 2680: 2665: 2576: 2458: 2403: 2395: 2258: 2195: 2048: 1975: 1881: 1762: 1629: 1621: 1468: 1271: 1241: 1233: 1223: 1203: 1116: 770: 431: 70: 13105: 12549: 12173: 11781: 11280: 10542: 10381:

2018 IEEE 5th International Conference on Data Science and Advanced Analytics (DSAA)

10353: 1982:

student James Slagle in 1961. Other programs searched through goals and subgoals to

1640:. Minsky would later become one of the most important leaders and innovators in AI. 1249: 1139: 13690: 13649: 13570: 13558: 13534: 13475: 13467: 13431: 13419: 12753: 12673: 12535: 12506: 12356: 12319: 12272: 12055: 11927: 11761: 11637: 11564: 11493: 11479: 11399: 11373: 11260: 11071: 11056: 11002: 10858: 10838: 10720: 10651: 10554: 10384: 10335: 10308: 10181: 10146: 10059: 9973: 7902: 7031: 5404: 5357:

above, where Hans Moravec predicted that raw power would eventually make AI "easy".

5138: 4871: 4703: 4686: 4557: 4221: 4161: 4107: 4078: 3937: 3867: 3768: 3450: 3175: 3120: 2875: 2775: 2732: 2711: 2544: 2491: 2466: 2343: 2161: 2011: 1995: 1967: 1893: 1824: 1808: 1749: 1737: 1725: 1689: 1500: 1448: 1334: 1320: 1077: 967: 939: 809: 759: 487: 208: 143: 128: 13489: 12744:, Pitts W (1943), "A logical calculus of the ideas immanent in nervous activity", 12360: 12276: 11907:

Doyle J (1983), "What is rational psychology? Toward a modern mental philosophy",

11497: 9286: 4832:

McCorduck also notes that funding was mostly under the direction of alumni of the

13661: 12963: 12502: 12323: 12248: 12102: 11589: 11553:"30 years of adaptive neural networks: perceptron, Madaline, and backpropagation" 11471: 11377: 11207: 10655: 10610: 5435: 5324: 5288: 5044:)" to "make intelligible paranoid processes in explicit symbol processing terms." 5015: 4631: 4565: 4350: 4244: 4145: 4141: 4043: 4035: 3922: 3839: 3756: 3528: 3481: 3394: 3339: 3268: 3252: 3235: 3231: 3227: 2863: 2806: 2724: 2487: 2355: 2265: 2112: 2060: 1696:

would continue to be used as a measure of progress in AI throughout its history.

1669: 1424: 1362: 1311: 1028: 974: 781: 750: 473: 85: 11532: 2277:

The first generation of AI researchers made these predictions about their work:

938:

The earliest written account regarding golem-making is found in the writings of

13694: 13681: 13653: 13303:

Essais sur l'Automatique - Sa définition. Etendue théorique de ses applications

13290:

Ensayos sobre Automática – Su definicion. Extension teórica de sus aplicaciones

13212:

Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference

12810: 12681: 12650:

A Proposal for the Dartmouth Summer Research Project on Artificial Intelligence

12644: 12435:

Philosophy in the flesh: The embodied mind and its challenge to western thought

12231: 12076: 11965: 11919: 11873: 11811: 10465:

Historia de la filosofía española. Filosofía cristiana de los siglos XIII al XV

6659: 6545: 6087: 5396: 5388: 4981:

While the autonomous tank was a failure, the battle management system (called "

4867: 4854: 4803: 4740: 4719: 4674: 4213: 3957: 3863: 3847: 3819: 3764: 3692: 3678: 3563: 3536: 3466: 3379: 3191: 2929: 2830: 2790: 2767: 2653: 2634: 2610: 2505: 2434: 2420: 2378: 2264:

The main problem was the inability to train multilayered networks (versions of

2250: 2229: 2179: 2116: 2100: 2096: 2080: 1869: 1812: 1804: 1792: 1741: 1719: 1681: 1653: 1649: 1540: 1532: 1476: 1394: 1354: 1155: 1108: 13538: 13493: 13471: 12769: 12564:

Artificial Intelligence: Structures and Strategies for Complex Problem Solving

12540: 11432: 11132: 10635: 10558: 10150: 1970:

tried to capture a general version of this algorithm in a program called the "

1010: 896:

was a legendary king and sculptor of Greek mythology, famously represented in

805:"). Nevertheless, research and funding continued to grow under other names. 13800: 13729: 13702: 13229: 13097: 13064: 13047:

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

13035: 12984: 12897: 12890: 12866: 12841: 12806: 12794: 12453: 12408: 12222: 12067: 12002: 11897: 11822: 11552: 11344: 11272: 11014: 10732: 10724: 10566: 10435: 9172: 8417: 5296: 5247: 5233: 5073: 5011: 4900: 4795: 4757: 4677:

wrote " later became known as the 'physical symbol systems hypothesis'". The

4271:

for-profit version of the company with more than $ 1 billion in financing.

4051: 4031: 4021: 3969: 3936:, an annotated set of images of faces that was widely used to train and test 3871: 3835: 3815: 3571: 3508: 3368: 3350: 3312: 3260: 3219: 3183: 3147: 3052: 3002: 2978: 2882: 2826: 2798: 2676: 2657: 2649: 2622: 2606: 2367: 2331: 2303: 2296: 2239: 2225: 2165: 2137:

In the 1960s funding was primarily directed towards laboratories researching

2076: 2022: 1979: 1784: 1633: 1456: 1436: 1428: 1358: 1245: 1236:, who speculated that human reason could be reduced to mechanical calculation 1199: 1104: 902: 822: 814: 797: 138: 13787: 13637: 12834: 12733: 12475: 12400: 12152: 12122: 11613: 10905: 10388: 9977: 9945: 1368: 1342: 13361: 13333: 13013: 12936: 12765: 12612: 12376: 12368: 12294: 12252: 12098: 11957: 11404:

Principles of neurodynamics: Perceptrons and the theory of brain mechanisms

11091: 11083: 11023:"Big data: The next frontier for innovation, competition, and productivity" 10850: 10585:

AI Narratives: A History of Imaginative Thinking about Intelligent Machines

10500: 10158: 10071: 9985: 9140: 7146: 5483: 5400: 5380: 5275: 5159: 5154: 5103:

where he said "This is AI, so we don't care if it's psychologically real" (

4875: 4682: 4275: 4247:(who been leading neural network research since the 80s) was approached by 4198: 4178: 4168: 4149: 4134: 4111: 4096: 4082: 4009: 3879: 3748: 3649: 3477: 3458: 3316: 3223: 2903: 2871: 2843: 2834: 2802: 2771: 2707: 2630: 2559: 2454: 2450: 2425: 2339: 2286: 2207: 2183: 2089: 2056: 2038: 2033: 1963: 1949: 1846: 1820: 1733: 1613: 1440: 1296: 1159: 1005: 1000: 282: 11773: 11505: 10786: 10200:"Artificial intelligence advances and challenges in the mobility industry" 9739: 6702: 5323:, augmented with reversed, cropped and tinted images. The model also used 5291:

was 1.2 milliseconds, which is arguably equivalent to about 833

3098:(or "MCC") to fund large scale projects in AI and information technology. 2640:

These critiques were not taken seriously by AI researchers. Problems like

2220:

However, partly due to lack of results and partly due to competition from

13676: 13516: 13298: 13207: 13042: 12160: 12043: 11909: 11895:

Darrach B (20 November 1970), "Meet Shaky, the First Electronic Person",

11658: 11475: 6389: 5221: 5217: 5142: 4715: 4658: 4564:

uses deep learning to evaluate the strength of a position and to suggest

4474:

The AI Boom has raised important ethical, legal, and societal questions:

4225: 4005: 3744: 3707: 3629: 3612: 3462: 3454: 3402: 3398: 3390: 3386: 3303: 3295: 3264: 3163: 2751: 2626: 2327: 2282: 2221: 2104: 2017:

An important goal of AI research is to allow computers to communicate in

1908: 1594: 1590: 1580: 1548: 1496: 1460: 1452: 1350: 1214: 1207: 1131: 1127: 947: 907: 875: 817:

proved to be a breakthrough technology, eclipsing all other methods. The

311: 296: 13638:"On Computable Numbers, with an Application to the Entscheidungsproblem" 12414:

Women, Fire, and Dangerous Things: What Categories Reveal About the Mind

11798:, Stanford Artificial Intelligence Laboratory, REPORT NO. STAN-CS-74-457 10842: 10063: 7299: 4522: 4282:, which soon had $ 6 billion in financing from Microsoft and Google. 3205: 2714:

had discovered a simple method to implement deduction on computers, the

2648:

seemed much more immediate and serious. It was unclear what difference "

1372:

US Army photo of the ENIAC at the Moore School of Electrical Engineering

13574: 13480: 13423: 12757: 11006: 10673: 10312: 7183: 5392: 5208:

Russell and Norvig wrote "The whole-agent view is now widely accepted"

5037: 4365: 4267: 4258: 4217: 4153: 4058: 3948:, a database of three million images captioned by volunteers using the 3941: 3703: 3544: 3275: 3271:

of AI" -- that is, an unworkable and misleading model of intelligence.

3167: 2572: 2430: 2153: 2132: 1957: 1745: 1536: 1100: 982: 931: 10185: 4714:

interview. The term was chosen by McCarthy to avoid associations with

4144:

explained how statistical algorithms had been among the causes of the

3210: 1566: 11691: 9372: 5384: 5300: 5171: 5007: 4561: 4312: 4279: 4233: 4229: 4190: 3989: 3986: 3760: 3727: 3715: 3668: 3575: 3556: 3516: 3504: 3279: 3048: 2922: 2518: 1960:

that would eliminate paths that were unlikely to lead to a solution.

1945: 1524: 1194: 1171: 1167: 1073: 1053: 1044: 1019:

explored the concept of artificial life. Speculative essays, such as

883: 867: 802: 346: 110: 13616:"Robotics firms find fundraising struggle, with venture capital shy" 12059: 11568: 11463: 11414:

Human compatible: Artificial intelligence and the problem of control

11142:"Transformers: the Google scientists who pioneered an AI revolution" 10339: 9016: 9014: 8922: 4985:") proved to be enormously successful, saving billions in the first 3846:

taught to play chess in 1951. This dramatic increase is measured by

2415:

decades later, and others that still stymie the field in the 2020s:

2141:, however several people still pursued research in neural networks. 1939: 1748:. The program would eventually prove 38 of the first 52 theorems in 11845:

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

11217:. Artificial Intelligence Center, SRI International. Archived from 10915:"IBM Is Counting on Its Bet on Watson, and Paying Big Money for It" 10454: 9877: 9875: 9873: 9871: 9869: 9867: 9865: 8287: 5320: 4986: 4807: 4799: 4553: 4346: 4209: 3978: 3953: 3945: 3895: 3859: 3171: 3032:: something that AI had not been able to achieve up to this point. 2618: 2261:

group (which worked on MINOS) turned to symbolic AI and robotics.

2206:. MINOS II had 6600 adjustable weights, and was controlled with an 1991: 1061: 1049: 918: 886:

defeated Talos by removing a plug near his foot, causing the vital

754: 454: 183: 105: 12617:"Behind Artificial Intelligence, a Squadron of Bright Real People" 10888:

The alchemy reader : from Hermes Trismegistus to Isaac Newton

9715: 9593: 9591: 9589: 9587: 9205:, Introduction (brittleness and the inability to handle extensive 9181:, p. 24 (inability to handle uncertain reasoning or to learn) 8314:, pp. 421–424 (who picks up the state of the debate in 1984). 7337: 7335: 7333: 7331: 5856: 4638:(the most important programming language used in 20th century AI). 3017:, begun in 1965, identified compounds from spectrometer readings. 1135: 837: 13311: 10543:"Hopes and fears for intelligent machines in fiction and reality" 9905: 9811: 9476: 9074: 9011: 8910: 8320:, pp. 168 (who documents Schank's original use of the term). 6968: 6617: 5376: 5316: 4331:

mechanism and later became widely used in large language models.

4306: 4295: 4027: 3603:

By 1991, the impressive list of goals penned in 1981 for Japan's

3512: 3187: 3014: 2731:, and soon this led to the collaboration with French researchers 2406:

described this period as the most "exciting" time to work in AI.

2254: 2211: 2191: 2187: 2064: 1693: 1516: 1385:

implied that a mechanical device, shuffling symbols as simple as

1189: 1065: 963: 826: 351: 13385: 13288:

Quevedo LT (1914), "Revista de la Academia de Ciencias Exacta",

12920:

The Turing Test: The Elusive Standard of Artificial Intelligence

11482:(14 March 1997). "A Neural Substrate of Prediction and Reward". 10940:"Beyond The Hype: What You Really Need To Know About AI In 2023" 10172:

Heaton J, Polson N, Witte J (2017). "Deep learning in finance".

9862: 9564:

sfn error: multiple targets (2×): CITEREFLeCunBengioHinton2015 (

8953: 8951: 8949: 8175: 6997: 5555: 5174:

was first used as the title of a seminar on the subject for the

4781:

This avoided the commonsense knowledge problem, discussed below.

4634:

was especially important to AI, since it was an inspiration for

4327:

architecture was proposed by Google researchers. It exploits an

4289: 3499:” learning algorithm, where the agent is rewarded only when its 1511: 13342:(2nd ed.), Upper Saddle River, New Jersey: Prentice Hall, 13337: 13080:

Funding a Revolution: Government Support for Computing Research

12184: 12166:

A Universal Modular Actor Formalism for Artificial Intelligence

11754:"A Computer Method of Psychotherapy: Preliminary Communication" 11294:. American religious experience. Greenwood Press. p. 136. 10446: 9951: 9840: 9838: 9705: 9703: 9584: 9495: 9493: 9491: 9452: 8900: 8898: 8896: 8763: 8761: 8759: 8757: 8755: 8583: 8581: 7698: 7696: 7694: 7412: 7410: 7408: 7406: 7404: 7402: 7400: 7398: 7368: 7366: 7364: 7362: 7328: 7251: 6987: 6985: 6983: 6779: 6777: 5198:

Applications of artificial intelligence § Computer science

4887: 4338: 4263: 4252: 3891: 3887: 3641: 3222:

was able to prove that a form of neural network (now called a "

3084: 2943: 2747: 2120: 2006: 1528: 1288:

hypothesis that would become the guiding faith of AI research.

1253: 1175: 1120: 958: 12635: 12233:

Artificial Intelligence at Edinburgh University: a Perspective

10426:

Bonner A (1985). "Llull's Influence: The History of Lullism".

9652: 9553: 7275: 6854: 6852: 6825: 6708: 6605: 6248: 6246: 6244: 6144: 6142: 6056: 5335:

output function, both relatively new developments at the time.

3238:". These two developments helped to revive the exploration of 2675:

Weizenbaum began to have serious ethical doubts about AI when

13398:"Some studies in machine learning using the game of checkers" 12770:"Sketch of the Analytical Engine Invented by Charles Babbage" 12255:(1982). "Judgment under uncertainty: Heuristics and biases". 10709:"In Memoriam: Charles Rosen, Norman Nielsen, and Saul Amarel" 10325: 9787: 9517: 9464: 9440: 9315: 9313: 9214: 9098: 9086: 9062: 8999: 8975: 8946: 8934: 8785: 8605: 8443: 8326:, p. 19-20 (who describe MIT's approach as "anti-logic") 7864: 7494: 7113: 6956: 6046: 6044: 6042: 5900: 5898: 5808: 5292: 5108: 5041: 4994: 4990: 4369: 4342: 4337:, based on the transformer, were developed by AGI companies: 4248: 4110:-- the specific measures that they are designed to optimize. 3597: 3405:

in the 60s, began to be more widely used in AI and robotics.

3374: 3099: 3091: 3018: 2669: 2567: 2528: 2323: 2269:

see this, however, as he died in a boating accident in 1971.

2052: 1506: 1492: 1484: 1316: 1306: 951: 943: 887: 879: 871: 863: 848: 785: 774: 10740:

Hayes P (1981). "The logic of frames". In Kaufmann M (ed.).

9887: 9850: 9835: 9700: 9529: 9488: 8893: 8752: 8578: 7773: 7771: 7691: 7395: 7359: 7009: 6980: 6774: 6629: 6451: 6229: 6204: 5883: 5246:) used the word "agent". Other "modular" proposals included 4886:(MIPS). In 1976, the fastest supercomputer, the $ 8 million 3679:

Mathematical rigor, greater collaboration and a narrow focus

2556:

program at CMU and canceled an annual grant of $ 3 million.

2433:. Below a certain threshold, it's impossible, but, as power 2362:

in 1963. Another important AI laboratory was established at

2194:(1962), which had up to 1000 adjustable weights. A group at 1699: 1519:: a computer used by the first generation of AI researchers. 1447:

The first modern computers were the massive machines of the

777:

provided millions of dollars to make this vision come true.

13599: 13192: 13170: 10706: 9775: 9763: 9676: 9628: 9276: 9274: 8809: 8773: 8740: 8455: 8275: 8263: 8253: 8251: 8187: 8026: 7938: 7732: 7605: 7385: 7383: 7381: 7305: 7125: 7101: 6849: 6837: 6581: 6241: 6139: 5579: 5141:(1970). It was applied to neural networks in the 1970s by 4711: 4702:"I won't swear and I hadn't seen it before," McCarthy told 4665:": that machines can contain minds just as human bodies do. 4184: 3853: 3792: 3596:

cut funding to AI "deeply and brutally". New leadership at

3582: 3581:

Eventually the earliest successful expert systems, such as

3263:" and there was a considerable debate between advocates of 2702:

Logic was introduced into AI research as early as 1958, by

2486:: Many important artificial intelligence applications like 1708:

Herbert Simon (left) in a chess match against Allen Newell

1143: 1064:

were built by craftsman from many civilizations, including

962:, the artificial creation of life, was a frequent topic of 897: 10796:"36 Days of Judaic Myth: Day 24, The Golem of Prague 2015" 9310: 7974:, under "Shift to Applied Research Increases Investment.". 7955: 7953: 6258: 6039: 6027: 5895: 5832: 5735: 5615: 5471: 5459: 5224:

anticipated the modern definition of intelligent agents. (

5176:

Association for the Advancement of Artificial Intelligence

4657:

This was an early statement of the philosophical position

4436:

The AI Boom has had a profound impact on various sectors:

4232:. The founders and financiers were deeply concerned about 3234:

popularized a method for training neural networks called "

1547:

described digital signals (i.e., all-or-nothing signals).

12263:(4157). New York: Cambridge University Press: 1124–1131. 11212:"The SRI Artificial Intelligence Center: A Brief History" 10986:

Defending AI Research: A Collection of Essays and Reviews

10890:. New York: Cambridge University Press. pp. Ch. 18. 9998: 9505: 9259: 9193:, pp. 258–283 (limited deployment after development) 9110: 9038: 9026: 8987: 8963: 8688: 8641: 8629: 8626:, under "Shift to Applied Research Increases Investment". 7798: 7768: 7636: 7634: 7632: 7566: 7518: 7347: 7089: 6944: 6864: 6439: 5447: 4882:

would require a general-purpose computer capable of 1000

4710:

also stated unequivocally "I came up with the term" in a

4091:), but others warned that a sufficiently powerful AI was 3993: 3567: 3472:

A successful and influential research program was led by

3335: 3151: 3106:

and tripling its investment in AI between 1984 and 1988.

2822: 2661: 2319: 2084: 1800: 13679:(October 1950), "Computing Machinery and Intelligence", 12339:

Kolata G (1982), "How can computers get common sense?",

11442:

One Jump Ahead:: Challenging Human Supremacy in Checkers

9823: 9799: 9751: 9688: 9616: 9541: 9416: 9298: 9271: 8479: 8248: 8163: 7378: 6789: 6738: 6641: 5873: 5871: 5591: 2812: 2126: 1539:

described control and stability in electrical networks.

1381:

form of mathematical reasoning could be mechanized. The

913: 10245:"Artificial intelligence: Manufacturing's game changer" 9640: 9404: 9122: 9050: 8593: 8566: 8467: 8151: 7950: 7720: 7708: 7667: 7422: 7318: 7316: 7314: 7263: 7239: 7214: 6726: 6320: 6318: 6316: 6314: 5922: 5747: 5723: 5699: 3164:

symbolic knowledge representation and logical reasoning

3094:

project. A consortium of American companies formed the

2697: 2583:

thousands that were joining the field were unaffected.

2029:, which could solve high school algebra word problems. 1956:"). Researchers would reduce the search space by using 966:

alchemical manuscripts, especially those attributed to

12816:

Perceptrons: An Introduction to Computational Geometry

11232:

A historical sociology of neural network research]

8797: 8728: 8389: 8387: 7788: 7786: 7629: 7578: 7554: 7530: 7506: 6762: 6154: 5771: 5711: 5675: 5639: 5567: 4469: 3898:. During the same period same time, new insights into 3671:

continued to haunt AI research into the 2000s, as the

3142:

In the 1980s some researchers attempted to attack the

2746:

who created the successful logic programming language

2586: 2249:) became a staunch objector to pure connectionist AI. 1527:

had shown that the brain was an electrical network of

890:

to flow out from his body and rendering him lifeless.

13107:

Al Jazari: The Ingenious 13th Century Muslim Mechanic

12993:"1907: was the first portable computer design Irish?" 12247: 11878:

AI: The Tumultuous Search for Artificial Intelligence

11034:

Metz C, Weise K, Grant N, Isaac M (3 December 2023).

10050:

LeCun Y, Bengio Y, Hinton G (2015). "Deep learning".

7926: 7679: 7657: 7655: 7653: 7651: 7649: 6876: 6801: 6750: 6714: 6335: 6333: 5868: 5844: 5663: 5651: 5065: 4398:

Several key factors have contributed to the AI Boom:

4106:

AI programs in the 21st century are defined by their

3073:

Japanese Ministry of International Trade and Industry

1593:: If a machine could carry on a conversation (over a 1559:

possibility of "machine intelligence". The field of "

13236: 11710:"The John Gabriel Byrne Computer Science Collection" 11470: 11057:"The cognitive revolution: a historical perspective" 10467:(in Spanish), vol. 1, Madrid: Forgotten Books, 9727: 9664: 9428: 9080: 8916: 8869: 8857: 8833: 7756: 7744: 7617: 7482: 7311: 7287: 6593: 6311: 6127: 5783: 3096:

Microelectronics and Computer Technology Corporation

2996: 12159: 12017: 11651:"A (Very) Brief History of Artificial Intelligence" 11033: 10225:Hale K (2019). "AI in the Entertainment Industry". 9933: 9881: 9332: 9330: 9328: 8821: 8559: 8384: 8199: 7783: 5225: 5040:-like "computer simulations of paranoid processes ( 3469:foresaw the role of reinforcement learning in AI. 2981:" was adopted by corporations around the world and 2958:that different terms denote different individuals. 2821:approach were his colleagues across the country at 2523:The agencies which funded AI research, such as the 821:debuted in 2017 and was used to produce impressive 13741: 12962: 12561: 11464:"Annotated History of Modern AI and Deep Learning" 11228: 10174:Applied Stochastic Models in Business and Industry 9354: 9342: 8881: 8399: 8372: 7646: 7341: 6813: 6330: 5910: 5820: 5759: 5627: 5603: 5543: 5519: 5507: 5107:), and he recently reiterated his position at the 4390:transformative impacts across various industries. 4313:Transformer architecture and large language models 3087:as the primary computer language for the project. 1284:." These philosophers had begun to articulate the 1274:envisioned a universal language of reasoning, the 13299:"Revue Génerale des Sciences Pures et Appliquées" 12555: 11372: 11238:(Thesis). University of Edinburgh. Archived from 11189:A HERITAGE OF INNOVATION SRI's First Half Century 11021: 10813: 10378: 10171: 10049: 9658: 9572: 9559: 7542: 7281: 5531: 4587:History of knowledge representation and reasoning 4212:was founded in 2010 by three English scientists, 4040:ImageNet Large Scale Visual Recognition Challenge 3267:the "connectionists". Hinton called symbols the " 1940:Reasoning, planning and problem solving as search 1563:" was founded as an academic discipline in 1956. 13798: 12763: 12718:(2nd ed.), Natick, MA: A. K. Peters, Ltd., 12097: 11751: 11117:. Oxford: Oxford University Press. p. 184. 11036:"Ego, Fear and Money: How the A.I. Fuse Was Lit" 10462: 10410:The Art and Logic of Ramón Llull: A User's Guide 9325: 8181: 7977: 7142: 7140: 6235: 6068: 5889: 5687: 5407:, misleading results that go undetected without 2537:Automatic Language Processing Advisory Committee 1495:was based on the theoretical foundation laid by 13712:The second self: computers and the human spirit 13275:"Fuzzy Computer Theory: How to Mimic the Mind?" 12740: 11760:, vol. 142, no. 2, pp. 148–152, 11329:. University of California Press. p. 355. 10748: 10581: 9375:, AI behind the scenes in the 90s & 2000s: 5814: 5561: 3806:that would be capable of general intelligence. 3289: 3066: 2373:The money was given with few strings attached: 838:Mythical, fictional, and speculative precursors 13642:Proceedings of the London Mathematical Society 13584:The Shape of Automation for Men and Management 13240:Computational Intelligence: A Logical Approach 12690:, Edinburgh University Press, pp. 463–502 12309: 11964: 10992: 10927:"On 'Jeopardy!' Watson Win Is All but Trivial" 9963: 8081: 8032: 6502: 5453: 5307:approximately, these differ by a factor of 10. 5036:Colby and his colleagues later also developed 3916:List of datasets for machine-learning research 3838:computer was 10 million times faster than the 3539:, by collaboration with other fields (such as 3495:Also in 1988, Sutton and Barto developed the “ 3251:, a two volume collection of papers edited by 3157: 2384: 2381:, but this "hands off" approach did not last. 1919:The programs developed in the years after the 1914: 1628:. The paper was influenced by Turing's paper ' 13356: 13328: 12668: 12431: 11995: 11387:. Stanford Research Institute. Archived from 11318:American Journal of Computational Linguistics 10650:. Boston, MA: Springer US. pp. 293–322. 9893: 9856: 9844: 9745: 9721: 9709: 9597: 9535: 9499: 9482: 9458: 9319: 9178: 9092: 9068: 9020: 8957: 8928: 8904: 8852: 8767: 8715: 8674: 8587: 8553: 8435: 8355: 8323: 8232: 8109: 8062: 8004: 7882: 7702: 7416: 7372: 7257: 7189: 7164: 7137: 7083: 7037: 7015: 6991: 6974: 6936: 6858: 6843: 6831: 6696: 6677: 6623: 6587: 6531: 6484: 6457: 6411: 6357: 6291: 6252: 6223: 6148: 6111: 6050: 6033: 6007: 5972: 5949: 5904: 5862: 4989:, repaying the investment and justifying the 4290:Large language models, AI boom (2020–present) 4004:, defeated the two best Jeopardy! champions, 3921:that can be made by tweaking the algorithm." 3809: 3759:and economics into the study of AI. When the 1608: 922:Depiction of a homunculus from Goethe's Faust 722: 391: 13736: 13595:Newsmaker: Getting machines to think like us 13151:, University of Pennsylvania, pp. 1–435 13144: 12805: 12790:With notes upon the Memoir by the Translator 12204:Gödel, Escher, Bach: an Eternal Golden Braid 11406:, vol. 55, Washington DC: Spartan books 11316:Reiter R (1978). "On reasoning by default". 10769:Heimskringla; history of the kings of Norway 9999:Goodfellow I, Bengio Y, Courville A (2016). 8045:Dreyfus' critique of artificial intelligence 7353: 5597: 5053: 3909: 2679:wrote a "computer program which can conduct 2656:" made to an actual computer program. MIT's 2257:) turned to adaptive signal processing. The 1791:, with the support of two senior scientists 866:with the aid of a cyclops and presented the 784:and pressure from the U.S. Congress led the 13635: 13557: 13012: 13006:Science and Civilization in China: Volume 2 11458: 11287: 11159: 10678:"This year signaled the start of a new era" 9757: 7440: 7389: 7207: 6732: 6120: 5838: 5158:machines will result when the metaphorical 3640:, banking software, medical diagnosis and 3206:Revival of neural networks: "connectionism" 2977:In the 1980s, a form of AI program called " 2846:described their "anti-logic" approaches as 1944:Many early AI programs used the same basic 1859:The Magical Number Seven, Plus or Minus Two 1585:In 1950 Turing published a landmark paper " 1123:had built a palace with automaton statues. 13762: 13613: 13367:Artificial Intelligence: A Modern Approach 13339:Artificial Intelligence: A Modern Approach 13214:, San Mateo, California: Morgan Kaufmann, 13166:Newsmaker: Google's man behind the curtain 12511:Artificial Intelligence: a paper symposium 12197: 11550: 11398: 9410: 9390: 8241: 8193: 8010: 7269: 7245: 5060:, performance dramatically improves. (See 4823:Minsky strongly believes he was misquoted. 4806:, though they also used simulations on an 4772:called this the "Look, Ma, no hands!" era. 4181:became a serious field of academic study. 3375:Soft computing and probabilistic reasoning 2789:Critics of the logical approach noted, as 1507:Birth of artificial intelligence (1941-56) 765:The field of AI research was founded at a 729: 715: 398: 384: 13591: 13479: 13413: 13076:"Developments in Artificial Intelligence" 12990: 12922:, Dordrecht: Kluwer Academic Publishers, 12799:Computation: Finite and Infinite Machines 12713: 12539: 12507:Artificial Intelligence: A General Survey 12501: 12452: 12075: 11913:, vol. 4, no. 3, pp. 50–53 11862: 11758:The Journal of Nervous and Mental Disease 11588: 11512: 11439: 11250: 10766: 10609: 10540: 10453: 9829: 9817: 9805: 9793: 9781: 9769: 9694: 9682: 9646: 9634: 9622: 9610: 9523: 9511: 9470: 9446: 9378: 9265: 9239: 9220: 9202: 9184: 9152: 9116: 9056: 9044: 9032: 9005: 8993: 8981: 8969: 8940: 8791: 8779: 8734: 8721: 8697: 8662: 8647: 8635: 8611: 8535: 8500: 8449: 8343: 8311: 8257: 8220: 8097: 8050: 7919: 7870: 7837: 7819: 7777: 7640: 7572: 7500: 7201: 7152: 7119: 7075: 7043: 6962: 6950: 6894: 6795: 6783: 6756: 6744: 6665: 6635: 6611: 6573: 6555: 6519: 6496: 6490: 6472: 6423: 6417: 6399: 6345: 6303: 6279: 6264: 6180: 6099: 6013: 6001: 5978: 5943: 5877: 5850: 5802: 5753: 5741: 5729: 5705: 5681: 5657: 5621: 4955: 3522: 3440: 2330:which subsumed the "AI Group" founded by 1926:Defense Advanced Research Projects Agency 1700:Symbolic reasoning and the Logic Theorist 1503:, and proved to be the most influential. 13041: 12701: 12375: 11842: 11821: 11810: 11648: 11096:Robot: Mere Machine to Transcendent Mind 10976: 10527: 10428:Doctor Illuminatus. A Ramon Llull Reader 9547: 9422: 9396: 9384: 9304: 9280: 9251: 9190: 9146: 9104: 8709: 8668: 8541: 8515: 8485: 8429: 8169: 7932: 7891:, under "Success in Speech Recognition". 7726: 7170: 7055: 6898: 6768: 6599: 6445: 6363: 6324: 6160: 6133: 6093: 6019: 5955: 5777: 5717: 5645: 5573: 5477: 5465: 5375:A short summary of topics would include 4993:'s pragmatic policy, at least as far as 4954:, pp. 115–116. Other views include 4681:hypothesis was articulated and named by 4185:Artificial general intelligence research 4072: 3854:Big data, deep learning, AGI (2005–2017) 3209: 3202:called these approaches "sub-symbolic". 2143: 2095:This paradigm led to innovative work in 2005: 1703: 1565: 1510: 1367: 1228: 1048: 917: 13402:IBM Journal of Research and Development 13309: 13296: 13287: 13272: 13260:"Technology; Fuzzy Logic For Computers" 13257: 13237:Poole D, Mackworth A, Goebel R (1998), 13122: 13003: 12960: 12935: 12801:, Englewood Cliffs, N.J.: Prentice-Hall 12611: 11935: 11918: 11894: 11872: 11410: 11327:The Argonautika : Expanded Edition 11324: 11206: 11178: 11112: 11090: 10982:The Question of Artificial Intelligence 10963:The Question of Artificial Intelligence 10924: 10793: 9733: 9670: 9434: 9245: 9196: 9158: 9128: 8875: 8863: 8815: 8803: 8746: 8703: 8599: 8572: 8547: 8506: 8473: 8461: 8423: 8349: 8317: 8293: 8281: 8269: 8226: 8157: 8145: 8132: 8103: 8076: 8071: 8056: 7998: 7959: 7944: 7908: 7876: 7852: 7831: 7825: 7804: 7762: 7750: 7738: 7714: 7685: 7673: 7623: 7611: 7596: 7584: 7560: 7536: 7524: 7512: 7488: 7476: 7460: 7444: 7428: 7322: 7293: 7233: 7220: 7195: 7158: 7131: 7107: 7095: 7079: 7061: 7049: 7003: 6918: 6914: 6902: 6882: 6870: 6807: 6720: 6692: 6671: 6647: 6567: 6561: 6525: 6478: 6405: 6351: 6297: 6285: 6210: 6199: 6195: 6191: 6172: 6105: 6062: 5789: 5669: 5549: 5525: 5513: 5489: 4951: 4798:moved by electric motors. ADALINE used 4431: 4393: 3622: 3342:. He rejected all symbolic approaches ( 3109: 1864:This meeting was the beginning of the " 1830: 13799: 13709: 13675: 13515: 13451:Saygin AP, Cicekli I, Akman V (2000), 13450: 13392: 12896: 12865: 12847:A Framework for Representing Knowledge 12840: 12793: 12482: 12458:Building Large Knowledge-Based Systems 12407: 12338: 12183: 12081:Artificial Intelligence: The Very Idea 11752:Colby KM, Watt JB, Gilbert JP (1966), 11681: 11620: 11315: 11139: 11051: 10885: 10695: 10485:. London: Cambridge University Press. 10480: 10434: 10425: 10407: 10298: 10227:Journal of Media and Entertainment Law 9939: 8839: 8827: 8393: 8364: 8118: 7792: 7600: 7472: 6819: 6432: 6378: 5984: 5928: 5916: 5826: 5765: 5633: 5609: 5537: 5319:had 650,000 neurons and trained using 5243: 5104: 5077: 4962:under "Success in Speech Recognition". 4592:History of natural language processing 3940:systems for the next several decades. 2512: 479:Free software and open-source software 13581: 13206: 13184: 13162: 13128:The Quest for Artificial Intelligence 12942:The Role of Raw Power in Intelligence 12589: 12524:(1961), "Minds, Machines and Gödel", 12520: 12041: 11906: 11788: 11707: 10868:"UT Designates 2024 'The Year of AI'" 10739: 10672: 10642: 10510:"The Era of AI: 2023's Landmark Year" 10507: 10136: 10086:"The Impact of Cloud Computing on AI" 10025:"Big Data: The Management Revolution" 9921: 9916: 9360: 9348: 9295:, Artificial Intelligence in the 90s. 8887: 8665:, pp. 266–276, 298–300, 314, 421 8405: 8378: 8205: 8019: 7661: 7456: 6176: 5425:Artificial intelligence § Ethics 5229: 5112: 5066:Kahneman, Slovic & Tversky (1982) 4582:History of artificial neural networks 3734: 3135:problem and provide the support that 2921:The logicians rose to the challenge. 2593:Philosophy of artificial intelligence 2127:Perceptrons and early neural networks 1994:to control the behavior of the robot 1843:Massachusetts Institute of Technology 1772: 1603:philosophy of artificial intelligence 1531:that fired in all-or-nothing pulses. 1119:asserted that the Ancient Roman poet 975:Faust: The Second Part of the Tragedy 914:Medieval legends of artificial beings 13509: 13103: 12917: 12229: 12129: 11733:"AI set to exceed human brain power" 11351: 11291:The Protestant Experience in America 10937: 10912: 10814:LeCun Y, Bengio Y, Hinton G (2015). 10224: 9911: 9578: 9187:, p. 435 (institutional issues) 7995:Lucas and Penrose' critique of AI: 7914: 7548: 6394:Computing Machinery and Intelligence 6074: 5693: 4517: 3822:. In 2005, a Stanford robot won the 2906:used a version of frames he called " 2698:Logic at Stanford, CMU and Edinburgh 2059:). But in fact, ELIZA simply gave a 1643: 1587:Computing Machinery and Intelligence 13188:Spying an intelligent search engine 13070: 12746:Bulletin of Mathematical Biophysics 12596:, Dartmouth College, archived from 12568:(5th ed.). Benjamin/Cummings. 11731: 11551:Widrow B, Lehr M (September 1990). 11192:(1st ed.). SRI International. 10995:Bulletin of Mathematical Biophysics 10865: 10742:Readings in artificial intelligence 10618:: Machine learning and human values 9926: 9336: 9292: 8623: 7983: 7971: 7888: 5162:is driven uniting the two efforts." 4959: 4607:Timeline of artificial intelligence 4602:Progress in artificial intelligence 4513: 4470:Societal and Ethical Considerations 4402:Advancements in Computational Power 3755:, and others brought concepts from 2972: 2587:Philosophical and ethical critiques 2021:like English. An early success was 2001: 1400: 1270:, that is adding and subtracting". 1170:(who gave a formal analysis of the 1149: 1130:was purported to have fabricated a 1099:The oldest known automata were the 24:Progress in artificial intelligence 20:Timeline of artificial intelligence 13: 13807:History of artificial intelligence 13370:(4th ed.). Hoboken: Pearson. 11531: 11265:10.1023/B:SYNT.0000043018.52445.3e 10967:Annals of the History of Computing 10582:Cave S, Dihal K, Dillon S (2020). 9081:Schultz, Dayan & Montague 1997 8917:Poole, Mackworth & Goebel 1998 5585: 4810:computer. The MINOS machines used 4597:Outline of artificial intelligence 1184:was a model of formal reasoning), 1056:'s programmable automata (1206 CE) 1016:R.U.R. (Rossum's Universal Robots) 995:Artificial intelligence in fiction 842: 743:history of artificial intelligence 420: 45: 14: 13823: 10301:Journal of Information Technology 9175:failure (and the reason for it): 5355:History of AI § The problems 5226:Hewitt, Bishop & Steiger 1973 4568:(courses of action), but it uses 4501: 4057:Deep learning uses a multi-layer 3389:'s influential 1988 book brought 3358:physical symbol system hypothesis 3035:In 1980, an expert system called 2997:Expert systems become widely used 2750:. Prolog uses a subset of logic ( 1892:and the philosophical schools of 988: 469:Software configuration management 13292:, vol. 12, pp. 391–418 12417:, University of Chicago Press., 12044:"There Was No 'First AI Winter'" 11766:10.1097/00005053-196602000-00005 11662:, pp. 53–60, archived from 11513:Sejnowski TJ (23 October 2018). 10372: 10346: 10319: 10292: 10271:"The Future of Jobs Report 2020" 10263: 10237: 10218: 10192: 10165: 10130: 10104: 10078: 10043: 10017: 9992: 9957: 9899: 9603: 9366: 9226: 9166: 9134: 8845: 8682: 8653: 8523: 8491: 8411: 8331: 8299: 8211: 8138: 8125: 8088: 8038: 7989: 7896: 7858: 7845: 7810: 7590: 7466: 7450: 7434: 7226: 7177: 7069: 7021: 6924: 6908: 6888: 6294:, pp. 9, 11, 15–17, 981–984 5429: 5369: 5360: 5347: 5338: 5310: 5281: 5269: 5260: 5211: 5202: 5190: 5181: 5165: 5148: 5127: 5118: 5089: 5047: 5030: 5021: 5000: 4975: 4965: 4944: 4932: 4922: 4893: 4860: 4848: 4839: 4826: 4817: 4784: 4775: 4521: 4015: 3259:. The new field was christened " 3150:, who started a database called 3102:responded as well, founding the 3075:set aside $ 850 million for the 2543:ended all support. In 1973, the 1874:symbolic artificial intelligence 1561:artificial intelligence research 698: 697: 13769:Computer Power and Human Reason 13614:Tascarella P (14 August 2006), 13305:, vol. 2, pp. 601–611 12991:Mulvihill M (17 October 2012). 12593:AI@50: AI Past, Present, Future 12083:. Cambridge, Mass.: MIT Press. 11865:The Discovery of the Artificial 11630:Robotics and Autonomous Systems 11354:"Lightning Strikes Mathematics" 11247:See especially Chapter 2 and 3. 10646:(1977). "Negation as Failure". 9560:LeCun, Bengio & Hinton 2015 8560:Feigenbaum & McCorduck 1983 8338:Frame (artificial intelligence) 7282:Rosen, Nilsson & Adams 1965 6685: 6653: 6539: 6507: 6463: 6383: 6371: 6270: 6216: 6185: 6166: 6080: 5992: 5963: 5940:17th century mechanism and AI: 5934: 5795: 4911:, as well as the difficulty of 4884:million instructions per second 4762: 4746: 4734: 4725: 4696: 4668: 4651: 4641: 4624: 4572:to lookahead at new positions. 4375:artificial general intelligence 4362:artificial general intelligence 4203:artificial general intelligence 3884:artificial general intelligence 3248:Parallel Distributed Processing 3055:and software companies such as 2691:Computer Power and Human Reason 2070: 1620:analyzed networks of idealized 66:Artificial general intelligence 13772:, W.H. Freeman & Company, 13130:. Cambridge University Press. 12487:, Jefferson, N.C.: McFarland, 12163:, Bishop P, Steiger R (1973), 11229:Olazaran Rodriguez JM (1991). 11160:O'Neill C (6 September 2016). 10925:Markoff J (16 February 2011). 10620:. W. W. Norton & Company. 10530:"A Brief History of Computing" 8217:Weizenbaum's critique of AI: 8182:Colby, Watt & Gilbert 1966 6276:AI's immediate predecessors: 5495: 4286:A.I. from endangering Earth." 3594:Strategic Computing Initiative 3214:A Hopfield net with four nodes 3104:Strategic Computing Initiative 2991:Strategic Computing Initiative 2603:Gödel's incompleteness theorem 2326:). The money was used to fund 2164:(who had been a schoolmate of 1857:described his landmark paper " 1574: 1217:(1232–1315) developed several 1192:and gave his name to the word 1: 13526:Behavioral and Brain Sciences 13453:"Turing Test: 50 Years Later" 13258:Pollack A (11 October 1984). 12361:10.1126/science.217.4566.1237 12277:10.1126/science.185.4157.1124 11996:The Economist (7 June 2007), 11642:10.1016/S0921-8890(05)80025-9 11498:10.1126/science.275.5306.1593 11380:, Adams MB (8 January 1965). 11179:Nielson DL (1 January 2005). 11076:10.1016/s1364-6613(03)00029-9 10430:. Princeton University Press. 10399: 5815:Cave, Dihal & Dillon 2020 4556:describes their approach as " 3363:In the 1980s and 1990s, many 3330:A precursor to this idea was 3284:convolutional neural networks 3144:commonsense knowledge problem 3045:Digital Equipment Corporation 2881:In 1975, in a seminal paper, 2784:unified theories of cognition 2554:Speech Understanding Research 1931: 1709: 1680:wrote a checkers program and 1226:, who redeveloped his ideas. 981:, an alchemically fabricated 832: 755:programmable digital computer 13586:, New York: Harper & Row 13521:"Minds, Brains and Programs" 13243:, Oxford University Press., 13049:, New York: Macmillan/SAMS, 12969:, Harvard University Press, 12707:"Review of Lighthill report" 12432:Lakoff G, Johnson M (1999). 12324:10.1016/j.bushor.2018.08.004 12135:The Organization of Behavior 11880:. New York, NY: BasicBooks. 11708:Byrne JG (8 December 2012). 11623:"Elephants Don't Play Chess" 11515:The Deep Learning Revolution 11064:Trends in Cognitive Sciences 10794:Kressel M (1 October 2015). 10656:10.1007/978-1-4684-3384-5_11 10508:Clark S (21 December 2023). 10112:"Global AI Funding Overview" 9748:, pp. 5, 33, 1002–1003. 6236:Menabrea & Lovelace 1843 5492:, Book 4, the Talos episode. 5099:position was in the journal 4612:Timeline of machine learning 3864:cheaper and faster computers 3550: 3501:predictions about the future 3290:Robotics and embodied reason 3067:Government funding increases 2313: 2170:Bronx High School of Science 2043:Conceptual dependency theory 1845:(MIT). At the same meeting, 1648:Experimental robots such as 1407:History of computer hardware 825:applications. Investment in 689:Glossary of computer science 7: 12107:, New York, NY: Owl Books, 11847:. Oxford: Clarendon Press. 11789:Colby KM (September 1974), 11694:, Christchurch, New Zealand 11687:"Darwin Among the Machines" 11649:Buchanan BG (Winter 2005), 11595:The Advent of the Algorithm 11098:. Oxford University Press. 10588:. Oxford University Press. 10547:Nature Machine Intelligence 10463:Carreras y Artau T (1939), 8509:, pp. 161–162, 197–203 8497:Commercial expert systems: 8296:, pp. 145–149, 258–63. 5255:object-oriented programming 4575: 3158:New directions in the 1980s 2916:object-oriented programming 2813:MIT's "anti-logic" approach 2770:and the continuing work by 2465:that can only be solved in 2409: 2385:First AI Winter (1974–1980) 2272: 2196:Stanford Research Institute 1915:Early successes (1956-1974) 1411:History of computer science 1277:characteristica universalis 1038: 101:Natural language processing 10: 13828: 13748:New horizons in psychology 13273:Pollack A (2 April 1989). 13185:Olsen S (18 August 2006), 13082:, National Academy Press, 13008:. Taipei: Caves Books Ltd. 10913:Lohr S (17 October 2016), 8512:{{Harvnb|Russell|Norvig|20 8094:Searle's critique of AI: 8082:Dreyfus & Dreyfus 1986 8033:Dreyfus & Dreyfus 1986 6503:McCulloch & Pitts 1943 6224:Russell & Norvig (2021 5454:Kaplan & Haenlein 2018 5421:technological unemployment 5054:Wason & Shapiro (1966) 4380: 4316: 4293: 4019: 3913: 3902:raised concerns AI was an 3810:Milestones and Moore's law 3797:intelligent agent paradigm 3685:artificial neural networks 3665:computational intelligence 3435:computational intelligence 3411:artificial neural networks 3308:embodied cognitive science 3293: 3240:artificial neural networks 2590: 2516: 2348:Carnegie Mellon University 2245:Minsky (who had worked on 2160:was introduced in 1958 by 2130: 1834: 1776: 1736:and future Nobel Laureate 1717: 1663: 1609:Artificial neural networks 1578: 1489:University of Pennsylvania 1404: 1042: 992: 979:Johann Wolfgang von Goethe 940:Eleazar ben Judah of Worms 154:Hybrid intelligent systems 76:Recursive self-improvement 17: 13621:Pittsburgh Business Times 13539:10.1017/S0140525X00005756 13020:, New York: McGraw-Hill, 12541:10.1017/S0031819100057983 12485:The Turk, Chess Automaton 12048:Communications of the ACM 12042:Haigh T (December 2023). 11974:. Oxford, UK: Blackwell. 11140:Murgia M (23 July 2023). 10866:Lee A (23 January 2024). 10559:10.1038/s42256-019-0020-9 10151:10.1038/s41591-018-0300-7 9894:Russell & Norvig 2021 9857:Russell & Norvig 2021 9845:Russell & Norvig 2021 9746:Russell & Norvig 2021 9722:Russell & Norvig 2021 9710:Russell & Norvig 2021 9598:Russell & Norvig 2021 9536:Russell & Norvig 2021 9500:Russell & Norvig 2021 9483:Russell & Norvig 2021 9459:Russell & Norvig 2021 9234:Fifth generation computer 9179:Russell & Norvig 2021 9093:Russell & Norvig 2021 9069:Russell & Norvig 2021 9021:Russell & Norvig 2021 8958:Russell & Norvig 2021 8929:Russell & Norvig 2021 8905:Russell & Norvig 2021 8853:Lakoff & Johnson 1999 8768:Russell & Norvig 2021 8716:Russell & Norvig 2021 8675:Russell & Norvig 2021 8588:Russell & Norvig 2021 8554:Russell & Norvig 2021 8530:Fifth generation computer 8436:Russell & Norvig 2021 8356:Russell & Norvig 2021 8324:Russell & Norvig 2021 8233:Russell & Norvig 2021 8110:Russell & Norvig 2021 8063:Russell & Norvig 2021 8016:Lucas original argument: 8005:Russell & Norvig 2021 7883:Russell & Norvig 2021 7703:Russell & Norvig 2021 7443:, pp. 7−8 quoted in 7417:Russell & Norvig 2021 7373:Russell & Norvig 2021 7258:Russell & Norvig 2021 7190:Russell & Norvig 2021 7165:Russell & Norvig 2021 7084:Russell & Norvig 2021 7038:Russell & Norvig 2021 7016:Russell & Norvig 2021 6992:Russell & Norvig 2021 6975:Russell & Norvig 2021 6937:Russell & Norvig 2021 6859:Russell & Norvig 2021 6844:Russell & Norvig 2003 6832:Russell & Norvig 2021 6697:Russell & Norvig 2021 6678:Russell & Norvig 2021 6624:Russell & Norvig 2021 6588:Russell & Norvig 2021 6532:Russell & Norvig 2021 6485:Russell & Norvig 2021 6458:Russell & Norvig 2021 6412:Russell & Norvig 2021 6358:Russell & Norvig 2021 6292:Russell & Norvig 2021 6253:Russell & Norvig 2021 6149:Russell & Norvig 2021 6112:Russell & Norvig 2021 6051:Russell & Norvig 2021 6034:Russell & Norvig 2021 6008:Russell & Norvig 2021 5973:Russell & Norvig 2021 5950:Russell & Norvig 2021 5905:Russell & Norvig 2021 5863:Russell & Norvig 2021 5135:automatic differentiation 4950:This account is based on 4917:word-sense disambiguation 4167:In 2016, the election of 4114:'s influential 2005 book 3998:question answering system 3974:McKinsey Global Institute 3934:Labeled Faces in the Wild 3910:Big data and big machines 3663:, "cognitive systems" or 3541:mathematical optimization 3537:increasing computer power 3077:Fifth generation computer 2987:fifth generation computer 2533:National Research Council 1222:had a great influence on 1086:Leonardo Torres y Quevedo 1025:Darwin among the Machines 446:Hardware 1960s to present 13750:. Harmondsworth: Penguin 13746:. In Foss, B. M. (ed.). 13695:10.1093/mind/LIX.236.433 13654:10.1112/plms/s2-42.1.230 12906:, Dr. Dobb's Technetcast 12903:It's 2001. Where Is HAL? 12515:Science Research Council 12230:Howe J (November 1994), 11998:"Are You Talking to Me?" 11417:. Penguin Random House. 10938:Marr B (20 March 2023). 10725:10.1609/aimag.v24i1.1683 10541:Cave S, Dihal K (2019). 7822:, pp. 300 & 421 7354:Minsky & Papert 1969 7006:, pp. 51–58, 65–66. 6469:Pitts & McCullough: 6282:, pp. 51–57, 80–107 5409:algorithmic transparency 5251:subsumption architecture 5076:'s work is described in 5070:list of cognitive biases 4617: 4302:transformer architecture 4126:instrumental convergence 3605:Fifth Generation Project 3407:Evolutionary computation 2950:showed that negation as 2887:common sense assumptions 2302:1970, Marvin Minsky (in 2174:Office of Naval Research 1674:University of Manchester 819:transformer architecture 548:Graphical user interface 278:Artificial consciousness 13472:10.1023/A:1011288000451 13163:Olsen S (10 May 2004), 12382:The Singularity is Near 12172:, IJCAI, archived from 11942:, New York: MIT Press, 11939:What Computers Can't Do 11792:Ten Criticisms of Parry 11557:Proceedings of the IEEE 10980:(1996). "10. Review of 10754:The Jewish Encyclopedia 10389:10.1109/DSAA.2018.00018 10354:"OECD Principles on AI" 10029:Harvard Business Review 9978:10.1126/science.aaa8415 9820:, pp. 67, 73, 117. 8693:ontological engineering 8659:Knowledge revolution: 8361:Minsky's frame paper: 8352:, pp. 170–173, 246 7816:Commonsense knowledge: 7459:, p. 96 quoted in 7441:Simon & Newell 1958 7342:Olazaran Rodriguez 1991 6733:Newell & Simon 1963 6475:, pp. 51–57, 88–94 6414:, pp. 18, 981–984, 6065:, pp. 190 196, 61. 5413:right to an explanation 5072:for several examples). 4958:, pp. 306–313 and 4570:Monte Carlo tree search 4414:Algorithmic Innovations 4179:value alignment problem 4128:".) The solution is to 4088:The Singularity is Near 3985:In February 2011, in a 3783:paradigm was complete. 3739:A new paradigm called " 3689:probabilistic reasoning 3661:knowledge-based systems 3592:In the late 1980s, the 3486:Markov decision process 3125:Knowledge based systems 3083:, they initially chose 2935:closed world assumption 2729:University of Edinburgh 2550:combinatorial explosion 2446:combinatorial explosion 2088:research focused on a " 1954:combinatorial explosion 1868:"—an interdisciplinary 1433:Leonardo Torres Quevedo 928:Of the Nature of Things 497:Artificial intelligence 149:Evolutionary algorithms 39:Artificial intelligence 13714:. Simon and Schuster. 13636:Turing A (1936–1937), 12875:, Simon and Schuster, 12687:Machine Intelligence 4 12101:, Blakeslee S (2004), 12021:, McCorduck P (1983), 11288:Porterfield A (2006). 10204:McKinsey & Company 9659:McKinsey & Co 2011 7475:, p. 2 quoted in 7270:Widrow & Lehr 1990 6194:, pp. 6, 11–13); 5083:Thinking Fast and Slow 4909:qualification problems 4679:physical symbol system 4661:would later call the " 4426:Investment and Funding 4238:existential risk of AI 3950:Amazon Mechanical Turk 3712:electrical engineering 3697:reinforcement learning 3523:Bust: second AI winter 3509:dopamine reward system 3446:Reinforcement learning 3441:Reinforcement learning 3383:"think like a human". 3215: 3196:reinforcement learning 2956:unique name assumption 2754:, closely related to " 2421:Limited computer power 2204:U.S. Army Signal Corps 2149: 2148:The Mark 1 Perceptron. 2109:constraint propagation 2014: 1972:General Problem Solver 1890:cognitive neuroscience 1878:generative linguistics 1715: 1571: 1520: 1373: 1286:physical symbol system 1237: 1057: 1033:Maelzel's Chess Player 930:, the Swiss alchemist 923: 769:held on the campus of 507:Early computer science 425: 50: 13018:Computers and Thought 11816:La Logique de Leibniz 11352:Rose A (April 1946). 10767:Hollander LM (1964). 10616:The Alignment Problem 10483:The myth of the magus 10328:ACM Computing Surveys 9203:Lenat & Guha 1989 8722:Lenat & Guha 1989 7838:Lenat & Guha 1989 6933:and problem solving: 6213:, pp. 13, 16–17. 5890:Carreras y Artau 1939 5865:, pp. 6 & 7. 5658:Cave & Dihal 2019 4718:and the influence of 4408:Big Data Availability 4335:Large language models 4319:Large language models 4095:to humanity, such as 4073:The alignment problem 4048:University of Toronto 3963:large language models 3828:DARPA Urban Challenge 3824:DARPA Grand Challenge 3325:commonsense reasoning 3213: 3137:commonsense reasoning 3133:commonsense knowledge 3129:knowledge engineering 3026:commonsense knowledge 2989:project and the U.S. 2817:Among the critics of 2646:commonsense knowledge 2501:commonsense reasoning 2483:commonsense knowledge 2400:commonsense reasoning 2147: 2009: 1758:Principia Mathematica 1707: 1684:wrote one for chess. 1630:On Computable Numbers 1569: 1553:theory of computation 1514: 1421:Joseph Marie Jacquard 1371: 1333:in 1913. Inspired by 1330:Principia Mathematica 1240:In the 17th century, 1232: 1202:philosophers such as 1094:Wolfgang von Kempelen 1052: 954:was unable to speak. 921: 633:Timeline of computing 517:Programming languages 502:Compiler construction 424: 49: 13812:History of computing 13740:, Shapiro D (1966). 13592:Skillings J (2006), 13145:O'Connor KM (1994), 12918:Moor J, ed. (2003), 12714:McCorduck P (2004), 12657:on 30 September 2008 11968:, Dreyfus S (1986). 11867:, Dordrecht: Kluwer. 11863:Cordeschi R (2002), 11843:Copeland J( (2004). 11669:on 26 September 2007 11440:Schaeffer J (1997). 11245:on 11 November 2022. 10702:. 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"Review of 10843:10.1038/nature14539 10835:2015Natur.521..436L 10744:. pp. 451–458. 10528:Copeland J (1999). 10064:10.1038/nature14539 9796:, pp. 6–7, 25. 9526:, pp. 480–483. 9473:, pp. 471–478. 9449:, pp. 486–487. 9223:, pp. 430–431. 9023:, pp. 25, 820. 8818:, pp. 183–190. 8794:, pp. 454–462. 8749:, pp. 214–215. 8614:, pp. 426–432. 8464:, pp. 158–159. 8452:, pp. 327–335. 8306:Neats vs. scruffies 8284:, pp. 193–196. 8272:, pp. 190–192. 7947:, pp. 115–116. 7741:, pp. 146–148. 7614:, pp. 163–196. 7503:, pp. 272–274. 7134:, pp. 134–139. 7122:, pp. 291–296. 7110:, pp. 164–172. 6977:, pp. 19, 106. 6965:, pp. 245–250. 6917:, pp. 52–107; 6901:, pp. 91–112; 6786:, pp. 129–130. 6638:, pp. 137–170. 6626:, p. 17, p=19. 6550:Johns Hopkins Beast 6426:, pp. 170–176. 6377:Image adapted from 5562:Jewish Encyclopedia 5480:, pp. 144–152. 5468:, pp. 143–156. 5239:The Society of Mind 5236:'s popular classic 5228:) Both John Doyle ( 5058:social intelligence 4353:in 2022. These are 4266:in 2015, enlisting 4146:2008 economic crash 3965:in the late 2010s. 3753:Leslie P. Kaelbling 3720:operations research 3634:industrial robotics 3497:temporal difference 3490:operations research 3427:stochastic modeling 3218:In 1982, physicist 2940:negation as failure 2778:that would lead to 2710:proposal. In 1963, 2564:Mansfield Amendment 2513:Decrease in funding 2461:) showed there are 2352:Stanford University 2253:(who had worked on 2111:"), and especially 1668:In 1951, using the 1658:Johns Hopkins Beast 1302:The Laws of Thought 1266:... is nothing but 1113:Hermes Trismegistus 1060:Realistic humanoid 796:and the success of 794:Japanese Government 790:British Governments 243:Machine translation 159:Systems integration 96:Knowledge reasoning 33:Part of a series on 13575:10.1287/opre.6.1.1 13512:, pp. 23–78). 13460:Minds and Machines 13424:10.1147/rd.33.0210 13310:Randall B (1982), 13280:The New York Times 13265:The New York Times 13004:Needham J (1986). 12961:Moravec H (1988), 12775:Scientific Memoirs 12758:10.1007/BF02478259 12716:Machines Who Think 12647:(31 August 1955), 12622:The New York Times 12534:(XXXVI): 112–127, 12483:Levitt GM (2000), 12460:, Addison-Wesley, 12456:, Guha RV (1989), 12027:, Michael Joseph, 11936:Dreyfus H (1972), 11621:Brooks RA (1990). 11598:, Harcourt Books, 11325:Rhodios A (2007). 11224:on 10 August 2022. 11113:Morford M (2007). 11040:The New York Times 11007:10.1007/BF02478259 10931:The New York Times 10886:Linden SJ (2003). 10696:Goethe JW (1890). 10481:Butler EM (1948). 10440:Flesh and Machines 10313:10.1057/jit.2015.5 9952:Bubeck et al. 2023 9320:The Economist 2007 9161:, pp. 209–210 9149:, pp. 359–379 9008:, p. 127-129. 8984:, p. 152-156. 8943:, p. 120-124. 8851:See, for example, 8718:, pp. 314−316 8712:, pp. 431–455 8706:, pp. 239–243 8671:, pp. 255–267 8544:, pp. 231–240 8538:, pp. 436–441 8503:, pp. 434–435 8426:, pp. 148–159 8346:, pp. 305–306 8229:, pp. 132–144 8115:Searle's version: 8112:, pp. 985–986 8106:, pp. 269–271 8100:, pp. 443–445 8068:Dreyfus' version: 8065:, pp. 981–982 8059:, pp. 120–132 8053:, pp. 211–239 8013:, pp. 471–477 7873:, pp. 280–281 7828:, pp. 113–114 7599:, pp. 68–71; 7204:, pp. 104–107 7198:, pp. 102–105 7155:, pp. 299–305 7082:, pp. 76–79, 7058:, pp. 148–156 7046:, pp. 268–271 6931:State space search 6905:, pp. 108–109 6873:, pp. 52–107. 6668:, pp. 123–125 6366:, pp. 91–112 6348:, pp. 111–136 6340:Dartmouth workshop 5417:autonomous weapons 5299:ran at 11.38 5010:'s distinction of 4834:Dartmouth workshop 4706:in 1979. However, 4689:in their paper on 4533:. You can help by 4201:adopted the term " 4093:existential threat 3992:exhibition match, 3904:existential threat 3804:agent architecture 3741:intelligent agents 3735:Intelligent agents 3644:'s search engine. 3638:speech recognition 3423:information theory 3334:, who had come to 3216: 3013:and his students. 2601:, who argued that 2525:British government 2375:J. C. R. Licklider 2150: 2015: 1921:Dartmouth Workshop 1905:high level symbols 1851:generative grammar 1779:Dartmouth workshop 1773:Dartmouth Workshop 1744:", with help from 1716: 1622:artificial neurons 1572: 1545:information theory 1521: 1374: 1293:mathematical logic 1256:famously wrote in 1238: 1090:Pierre Jaquet-Droz 1070:Hero of Alexandria 1058: 924: 854:pseudo-Apollodorus 563:Personal computers 522:Prominent pioneers 426: 51: 13779:978-0-14-022535-8 13721:978-0-671-46848-4 13710:Turkle S (1984). 13582:Simon HA (1965), 13377:978-0-13-461099-3 13250:978-0-19-510270-3 13221:978-1-55860-479-7 13137:978-0-52-112293-1 13089:978-0-309-06278-7 13056:978-0-9885937-1-8 13027:978-0-262-56092-4 12997:Ingenious Ireland 12976:978-0-674-57618-6 12929:978-1-4020-1205-1 12882:978-0-671-65713-0 12854:on 7 January 2021 12826:978-0-262-63111-2 12819:, The MIT Press, 12725:978-1-56881-205-2 12600:on 8 October 2008 12590:Maker MH (2006), 12575:978-0-8053-4780-7 12494:978-0-7864-0778-1 12467:978-0-201-51752-1 12445:978-0-465-05674-3 12424:978-0-226-46804-4 12392:978-0-14-303788-0 12312:Business Horizons 12286:978-0-521-28414-1 12214:978-0-465-02656-2 12144:978-0-8058-4300-2 12114:978-0-8050-7853-4 12090:978-0-262-08153-5 12034:978-0-7181-2401-4 11981:978-0-02-908060-3 11949:978-0-06-090613-9 11605:978-0-15-601391-8 11524:978-0-262-03803-4 11451:978-0-387-76575-4 11394:on 16 March 2006. 11336:978-0-520-93439-9 11301:978-0-313-32801-5 11199:978-0-9745208-0-3 11124:978-0-19-085164-4 10829:(7553): 436–444. 10665:978-1-4684-3386-9 10627:978-0-393-86833-3 10595:978-0-19-884666-6 10408:Bonner A (2007), 10249:Deloitte Insights 10186:10.1002/asmb.2209 10118:. 19 January 2021 10058:(7553): 436–444. 9972:(6245): 255–260. 9784:, pp. 67–70. 9461:, pp. 24–25. 8782:, pp. 21–22. 8223:, p. 356–373 8007:, p. 983-984 7807:, pp. 15–16. 7527:, pp. 64–65. 7260:, pp. 20–21. 7161:, pp. 83–102 7098:, pp. 79–83. 6834:, pp. 13–14. 6695:, p. 46 and 6650:, pp. 44–47. 6448:, pp. 92–98. 6408:, pp. 22−25, 6402:, pp. 70–72, 6267:, pp. 76–80. 6175:, pp. 4–5); 5998:Leibniz and AI: 5931:, pp. 57–71. 5744:, pp. 59–62. 5624:, pp. 17–25. 4913:default reasoning 4754:Frederic Bartlett 4551: 4550: 4490:Bias and Fairness 4355:foundation models 4122:Stuart J. Russell 4117:Superintelligence 4101:Eliezer Yudkowsky 3900:superintelligence 3814:On May 11, 1997, 3788:intelligent agent 3781:intelligent agent 3415:Bayesian networks 3300:behavior-based AI 3255:and psychologist 3039:was completed at 3011:Edward Feigenbaum 2963:logic programming 2858:paradigm used by 2764:Edward Feigenbaum 2681:psychotherapeutic 2666:Joseph Weizenbaum 2577:battle management 2474:Moravec's paradox 2396:logic programming 2394:were explored in 2156:, a single-layer 2103:, Adolfo Guzman, 2075:In the late 60s, 2049:Joseph Weizenbaum 2019:natural languages 1976:Herbert Gelernter 1882:cognitive science 1763:mind/body problem 1726:digital computers 1644:Cybernetic robots 1499:and developed by 1417:Gottfried Leibniz 1234:Gottfried Leibniz 1224:Gottfried Leibniz 1204:William of Ockham 1117:Alexander Neckham 1029:Edgar Allan Poe's 771:Dartmouth College 739: 738: 512:Operating systems 408: 407: 144:Bayesian networks 71:Intelligent agent 13819: 13790: 13759: 13757: 13755: 13745: 13733: 13705: 13689:(236): 433–460, 13671: 13670: 13668: 13631: 13630: 13628: 13609: 13608: 13606: 13587: 13577: 13553: 13552: 13550: 13541:, archived from 13507: 13506: 13504: 13498: 13492:, archived from 13483: 13457: 13446: 13445: 13443: 13434:, archived from 13417: 13389: 13352: 13325: 13324: 13322: 13306: 13293: 13284: 13269: 13253: 13232: 13202: 13201: 13199: 13180: 13179: 13177: 13159: 13158: 13156: 13141: 13118: 13117: 13115: 13100: 13067: 13038: 13009: 13000: 12987: 12968: 12957: 12956: 12954: 12945:, archived from 12932: 12914: 12913: 12911: 12893: 12862: 12861: 12859: 12850:, archived from 12837: 12802: 12789: 12788: 12786: 12760: 12736: 12710: 12698: 12697: 12695: 12665: 12664: 12662: 12653:, archived from 12632: 12631: 12629: 12608: 12607: 12605: 12586: 12584: 12582: 12567: 12552: 12543: 12517: 12497: 12478: 12449: 12427: 12403: 12385:, Viking Press, 12371: 12334: 12306: 12243: 12242: 12240: 12225: 12193: 12180: 12178: 12171: 12155: 12125: 12094: 12071: 12037: 12013: 12012: 12010: 11992: 11990: 11988: 11960: 11931: 11928:RAND Corporation 11914: 11902: 11901:, pp. 58–68 11891: 11868: 11858: 11838: 11837: 11835: 11818: 11806: 11805: 11803: 11797: 11784: 11747: 11746: 11744: 11728: 11726: 11724: 11719:on 16 April 2019 11715:. Archived from 11714: 11703: 11702: 11700: 11685:(13 June 1863), 11677: 11676: 11674: 11668: 11655: 11645: 11627: 11616: 11580: 11563:(9): 1415–1442. 11547: 11545: 11543: 11528: 11509: 11467: 11455: 11436: 11407: 11395: 11393: 11386: 11369: 11367: 11365: 11348: 11321: 11312: 11310: 11308: 11284: 11246: 11244: 11237: 11225: 11223: 11216: 11203: 11185: 11175: 11156: 11154: 11152: 11136: 11109: 11087: 11061: 11043: 11030: 11018: 10989: 10974: 10954: 10952: 10950: 10934: 10921: 10909: 10882: 10880: 10878: 10862: 10820: 10810: 10808: 10806: 10790: 10763: 10762: 10760: 10745: 10736: 10703: 10692: 10690: 10688: 10682:www.linkedin.com 10669: 10639: 10606: 10604: 10602: 10578: 10537: 10524: 10522: 10520: 10504: 10477: 10459: 10457: 10443: 10442:, Pantheon Books 10431: 10422: 10393: 10392: 10376: 10370: 10369: 10367: 10365: 10350: 10344: 10343: 10323: 10317: 10316: 10296: 10290: 10289: 10287: 10285: 10275: 10267: 10261: 10260: 10258: 10256: 10241: 10235: 10234: 10222: 10216: 10215: 10213: 10211: 10206:. 1 October 2019 10196: 10190: 10189: 10169: 10163: 10162: 10134: 10128: 10127: 10125: 10123: 10108: 10102: 10101: 10099: 10097: 10082: 10076: 10075: 10047: 10041: 10040: 10038: 10036: 10031:. 1 October 2012 10021: 10015: 10014: 9996: 9990: 9989: 9961: 9955: 9949: 9943: 9937: 9931: 9903: 9897: 9891: 9885: 9882:Metz et al. 2023 9879: 9860: 9854: 9848: 9842: 9833: 9827: 9821: 9815: 9809: 9803: 9797: 9791: 9785: 9779: 9773: 9772:, p. 60-61. 9767: 9761: 9755: 9749: 9743: 9737: 9731: 9725: 9719: 9713: 9707: 9698: 9692: 9686: 9685:, p. 23-24. 9680: 9674: 9668: 9662: 9656: 9650: 9644: 9638: 9637:, p. 22-23. 9632: 9626: 9620: 9614: 9607: 9601: 9600:, p. 26-27. 9595: 9582: 9576: 9570: 9569: 9557: 9551: 9545: 9539: 9533: 9527: 9521: 9515: 9509: 9503: 9497: 9486: 9480: 9474: 9468: 9462: 9456: 9450: 9444: 9438: 9432: 9426: 9420: 9414: 9408: 9402: 9370: 9364: 9358: 9352: 9346: 9340: 9334: 9323: 9317: 9308: 9302: 9296: 9290: 9284: 9278: 9269: 9263: 9257: 9230: 9224: 9218: 9212: 9170: 9164: 9138: 9132: 9126: 9120: 9114: 9108: 9102: 9096: 9090: 9084: 9078: 9072: 9066: 9060: 9054: 9048: 9042: 9036: 9030: 9024: 9018: 9009: 9003: 8997: 8991: 8985: 8979: 8973: 8967: 8961: 8955: 8944: 8938: 8932: 8926: 8920: 8914: 8908: 8902: 8891: 8885: 8879: 8873: 8867: 8861: 8855: 8849: 8843: 8837: 8831: 8825: 8819: 8813: 8807: 8801: 8795: 8789: 8783: 8777: 8771: 8765: 8750: 8744: 8738: 8732: 8726: 8686: 8680: 8657: 8651: 8645: 8639: 8633: 8627: 8621: 8615: 8609: 8603: 8597: 8591: 8585: 8576: 8570: 8564: 8527: 8521: 8495: 8489: 8483: 8477: 8471: 8465: 8459: 8453: 8447: 8441: 8438:, pp. 22–24 8415: 8409: 8403: 8397: 8391: 8382: 8376: 8370: 8335: 8329: 8303: 8297: 8291: 8285: 8279: 8273: 8267: 8261: 8255: 8246: 8215: 8209: 8203: 8197: 8196:, pp. 5, 6. 8191: 8185: 8179: 8173: 8167: 8161: 8155: 8149: 8142: 8136: 8129: 8123: 8092: 8086: 8042: 8036: 8030: 8024: 7993: 7987: 7981: 7975: 7969: 7963: 7957: 7948: 7942: 7936: 7930: 7924: 7903:Lighthill report 7900: 7894: 7862: 7856: 7849: 7843: 7840:, (Introduction) 7814: 7808: 7802: 7796: 7790: 7781: 7775: 7766: 7760: 7754: 7748: 7742: 7736: 7730: 7724: 7718: 7712: 7706: 7700: 7689: 7683: 7677: 7671: 7665: 7659: 7644: 7638: 7627: 7621: 7615: 7609: 7603: 7594: 7588: 7582: 7576: 7570: 7564: 7558: 7552: 7546: 7540: 7534: 7528: 7522: 7516: 7510: 7504: 7498: 7492: 7486: 7480: 7470: 7464: 7454: 7448: 7438: 7432: 7426: 7420: 7414: 7393: 7390:Schmidhuber 2022 7387: 7376: 7370: 7357: 7351: 7345: 7339: 7326: 7320: 7309: 7306:Hart et al. 2003 7303: 7297: 7291: 7285: 7279: 7273: 7267: 7261: 7255: 7249: 7243: 7237: 7230: 7224: 7218: 7212: 7208:Schmidhuber 2022 7181: 7175: 7144: 7135: 7129: 7123: 7117: 7111: 7105: 7099: 7093: 7087: 7073: 7067: 7064:, pp. 14–15 7052:, pp. 95–96 7025: 7019: 7013: 7007: 7001: 6995: 6989: 6978: 6972: 6966: 6960: 6954: 6948: 6942: 6928: 6922: 6912: 6906: 6892: 6886: 6880: 6874: 6868: 6862: 6856: 6847: 6841: 6835: 6829: 6823: 6817: 6811: 6805: 6799: 6793: 6787: 6781: 6772: 6766: 6760: 6754: 6748: 6742: 6736: 6730: 6724: 6718: 6712: 6706: 6700: 6689: 6683: 6674:, pp. 44–46 6657: 6651: 6645: 6639: 6633: 6627: 6621: 6615: 6609: 6603: 6597: 6591: 6585: 6579: 6564:, pp. 27–28 6543: 6537: 6528:, pp. 34–35 6511: 6505: 6467: 6461: 6455: 6449: 6443: 6437: 6387: 6381: 6375: 6369: 6354:, pp. 49–51 6337: 6328: 6322: 6309: 6288:, pp. 27–32 6274: 6268: 6262: 6256: 6250: 6239: 6233: 6227: 6220: 6214: 6208: 6202: 6189: 6183: 6181:Mulvihill (2012) 6170: 6164: 6158: 6152: 6146: 6137: 6131: 6125: 6121:Turing 1936–1937 6108:, pp. 22–24 6102:, pp. 63–64 6084: 6078: 6072: 6066: 6060: 6054: 6048: 6037: 6031: 6025: 5996: 5990: 5969:Hobbes and AI: 5967: 5961: 5946:, pp. 37–46 5938: 5932: 5926: 5920: 5914: 5908: 5902: 5893: 5887: 5881: 5875: 5866: 5860: 5854: 5848: 5842: 5839:Porterfield 2006 5836: 5830: 5824: 5818: 5812: 5806: 5799: 5793: 5787: 5781: 5775: 5769: 5763: 5757: 5751: 5745: 5739: 5733: 5727: 5721: 5715: 5709: 5703: 5697: 5691: 5685: 5679: 5673: 5667: 5661: 5655: 5649: 5643: 5637: 5631: 5625: 5619: 5613: 5607: 5601: 5595: 5589: 5588:, Sanhedrin 65b. 5583: 5577: 5571: 5565: 5559: 5553: 5547: 5541: 5535: 5529: 5523: 5517: 5511: 5505: 5499: 5493: 5487: 5481: 5475: 5469: 5463: 5457: 5451: 5439: 5433: 5427: 5405:algorithmic bias 5373: 5367: 5364: 5358: 5351: 5345: 5342: 5336: 5333:rectified linear 5331:technique and a 5314: 5308: 5285: 5279: 5273: 5267: 5264: 5258: 5215: 5209: 5206: 5200: 5194: 5188: 5185: 5179: 5169: 5163: 5152: 5146: 5139:Seppo Linnainmaa 5131: 5125: 5122: 5116: 5093: 5087: 5051: 5045: 5034: 5028: 5025: 5019: 5004: 4998: 4979: 4973: 4969: 4963: 4948: 4942: 4936: 4930: 4926: 4920: 4897: 4891: 4872:motion detection 4864: 4858: 4852: 4846: 4843: 4837: 4830: 4824: 4821: 4815: 4788: 4782: 4779: 4773: 4766: 4760: 4750: 4744: 4738: 4732: 4729: 4723: 4704:Pamela McCorduck 4700: 4694: 4672: 4666: 4655: 4649: 4645: 4639: 4628: 4546: 4543: 4525: 4518: 4514:Neurosymbolic AI 4222:Mustafa Suleyman 4156:argued that the 4079:superintelligent 3938:face recognition 3868:machine learning 3769:computer science 3763:definition of a 3617:The Brain Makers 3461:. In the 1950s, 3257:James McClelland 3192:"soft" computing 3121:Pamela McCorduck 2973:Boom (1980–1987) 2776:Herbert A. Simon 2760:production rules 2745: 2737:Philippe Roussel 2733:Alain Colmerauer 2712:J. Alan Robinson 2668:, the author of 2545:Lighthill report 2492:natural language 2467:exponential time 2208:SDS 910 computer 2200:Charles A. Rosen 2182:and his student 2162:Frank Rosenblatt 2012:semantic network 2010:An example of a 2002:Natural language 1894:computationalism 1825:Herbert A. Simon 1809:Oliver Selfridge 1797:Nathan Rochester 1738:Herbert A. Simon 1714: 1711: 1690:machine learning 1618:Warren McCulloch 1501:John von Neumann 1449:Second World War 1401:Computer science 1282:Let us calculate 1219:logical machines 1150:Formal reasoning 1078:Haroun al-Rashid 968:Jabir ibn Hayyan 810:machine learning 760:electronic brain 731: 724: 717: 701: 700: 488:Computer science 410: 409: 400: 393: 386: 307:Existential risk 129:Machine learning 30: 29: 13827: 13826: 13822: 13821: 13820: 13818: 13817: 13816: 13797: 13796: 13795: 13794: 13780: 13753: 13751: 13722: 13666: 13664: 13648:(42): 230–265, 13626: 13624: 13604: 13602: 13548: 13546: 13508:. 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Basic Books. 12425: 12393: 12287: 12238: 12236: 12215: 12207:, Basic Books, 12176: 12169: 12145: 12115: 12104:On Intelligence 12091: 12060:10.1145/3625833 12035: 12008: 12006: 11986: 11984: 11982: 11950: 11888: 11855: 11833: 11831: 11801: 11799: 11795: 11742: 11740: 11722: 11720: 11712: 11698: 11696: 11672: 11670: 11666: 11653: 11625: 11606: 11584: 11569:10.1109/5.58323 11541: 11539: 11537:www.sefaria.org 11533:"Sanhedrin 65b" 11525: 11452: 11425: 11391: 11384: 11363: 11361: 11358:Popular Science 11337: 11306: 11304: 11302: 11242: 11235: 11221: 11214: 11200: 11183: 11172: 11150: 11148: 11125: 11106: 11094:(18 May 2000). 11059: 11047: 10975:, collected in 10957: 10948: 10946: 10898: 10876: 10874: 10818: 10816:"Deep learning" 10804: 10802: 10800:Matthew Kressel 10779: 10758: 10756: 10686: 10684: 10666: 10628: 10600: 10598: 10596: 10518: 10516: 10493: 10475: 10420: 10402: 10397: 10396: 10377: 10373: 10363: 10361: 10352: 10351: 10347: 10340:10.1145/3457607 10324: 10320: 10297: 10293: 10283: 10281: 10273: 10269: 10268: 10264: 10254: 10252: 10243: 10242: 10238: 10223: 10219: 10209: 10207: 10198: 10197: 10193: 10170: 10166: 10139:Nature Medicine 10135: 10131: 10121: 10119: 10110: 10109: 10105: 10095: 10093: 10084: 10083: 10079: 10048: 10044: 10034: 10032: 10023: 10022: 10018: 10011: 9997: 9993: 9962: 9958: 9950: 9946: 9938: 9934: 9904: 9900: 9892: 9888: 9880: 9863: 9855: 9851: 9843: 9836: 9828: 9824: 9816: 9812: 9804: 9800: 9792: 9788: 9780: 9776: 9768: 9764: 9756: 9752: 9744: 9740: 9732: 9728: 9720: 9716: 9708: 9701: 9693: 9689: 9681: 9677: 9669: 9665: 9657: 9653: 9645: 9641: 9633: 9629: 9621: 9617: 9608: 9604: 9596: 9585: 9577: 9573: 9563: 9558: 9554: 9546: 9542: 9534: 9530: 9522: 9518: 9510: 9506: 9498: 9489: 9481: 9477: 9469: 9465: 9457: 9453: 9445: 9441: 9433: 9429: 9421: 9417: 9411:Tascarella 2006 9409: 9405: 9391:Hofstadter 1999 9371: 9367: 9359: 9355: 9347: 9343: 9335: 9326: 9318: 9311: 9303: 9299: 9291: 9287: 9283:, pp. 440. 9279: 9272: 9264: 9260: 9231: 9227: 9219: 9215: 9171: 9167: 9139: 9135: 9131:, pp. 203. 9127: 9123: 9115: 9111: 9103: 9099: 9091: 9087: 9079: 9075: 9067: 9063: 9055: 9051: 9043: 9039: 9031: 9027: 9019: 9012: 9004: 9000: 8992: 8988: 8980: 8976: 8968: 8964: 8956: 8947: 8939: 8935: 8927: 8923: 8915: 8911: 8903: 8894: 8886: 8882: 8874: 8870: 8862: 8858: 8850: 8846: 8838: 8834: 8826: 8822: 8814: 8810: 8802: 8798: 8790: 8786: 8778: 8774: 8766: 8753: 8745: 8741: 8733: 8729: 8687: 8683: 8658: 8654: 8650:, pp. 421. 8646: 8642: 8634: 8630: 8622: 8618: 8610: 8606: 8602:, pp. 240. 8598: 8594: 8586: 8579: 8575:, pp. 195. 8571: 8567: 8528: 8524: 8496: 8492: 8488:, pp. 259. 8484: 8480: 8472: 8468: 8460: 8456: 8448: 8444: 8416: 8412: 8404: 8400: 8392: 8385: 8377: 8373: 8336: 8332: 8304: 8300: 8292: 8288: 8280: 8276: 8268: 8264: 8256: 8249: 8242:Weizenbaum 1976 8216: 8212: 8204: 8200: 8194:Weizenbaum 1976 8192: 8188: 8180: 8176: 8172:, pp. 276. 8168: 8164: 8156: 8152: 8143: 8139: 8130: 8126: 8093: 8089: 8043: 8039: 8031: 8027: 8011:Hofstadter 1999 7994: 7990: 7982: 7978: 7970: 7966: 7958: 7951: 7943: 7939: 7931: 7927: 7901: 7897: 7863: 7859: 7850: 7846: 7815: 7811: 7803: 7799: 7791: 7784: 7776: 7769: 7761: 7757: 7749: 7745: 7737: 7733: 7725: 7721: 7713: 7709: 7701: 7692: 7684: 7680: 7672: 7668: 7660: 7647: 7639: 7630: 7622: 7618: 7610: 7606: 7595: 7591: 7583: 7579: 7571: 7567: 7559: 7555: 7547: 7543: 7535: 7531: 7523: 7519: 7511: 7507: 7499: 7495: 7487: 7483: 7471: 7467: 7455: 7451: 7439: 7435: 7427: 7423: 7415: 7396: 7388: 7379: 7371: 7360: 7352: 7348: 7340: 7329: 7321: 7312: 7304: 7300: 7292: 7288: 7280: 7276: 7268: 7264: 7256: 7252: 7246:Rosenblatt 1962 7244: 7240: 7231: 7227: 7219: 7215: 7182: 7178: 7145: 7138: 7130: 7126: 7118: 7114: 7106: 7102: 7094: 7090: 7078:, p. 286, 7074: 7070: 7026: 7022: 7014: 7010: 7002: 6998: 6990: 6981: 6973: 6969: 6961: 6957: 6949: 6945: 6929: 6925: 6913: 6909: 6897:, p. 218; 6893: 6889: 6881: 6877: 6869: 6865: 6857: 6850: 6842: 6838: 6830: 6826: 6818: 6814: 6806: 6802: 6798:, pp. 125. 6794: 6790: 6782: 6775: 6767: 6763: 6755: 6751: 6743: 6739: 6731: 6727: 6719: 6715: 6707: 6703: 6690: 6686: 6658: 6654: 6646: 6642: 6634: 6630: 6622: 6618: 6610: 6606: 6598: 6594: 6586: 6582: 6544: 6540: 6512: 6508: 6468: 6464: 6456: 6452: 6444: 6440: 6420:, pp. 6–9, 6388: 6384: 6376: 6372: 6338: 6331: 6323: 6312: 6275: 6271: 6263: 6259: 6251: 6242: 6234: 6230: 6221: 6217: 6209: 6205: 6190: 6186: 6171: 6167: 6159: 6155: 6147: 6140: 6132: 6128: 6085: 6081: 6073: 6069: 6061: 6057: 6049: 6040: 6032: 6028: 5997: 5993: 5968: 5964: 5939: 5935: 5927: 5923: 5915: 5911: 5903: 5896: 5888: 5884: 5876: 5869: 5861: 5857: 5849: 5845: 5837: 5833: 5825: 5821: 5813: 5809: 5800: 5796: 5788: 5784: 5776: 5772: 5764: 5760: 5752: 5748: 5740: 5736: 5728: 5724: 5716: 5712: 5704: 5700: 5692: 5688: 5680: 5676: 5668: 5664: 5656: 5652: 5644: 5640: 5632: 5628: 5620: 5616: 5608: 5604: 5596: 5592: 5584: 5580: 5572: 5568: 5560: 5556: 5548: 5544: 5536: 5532: 5524: 5520: 5512: 5508: 5500: 5496: 5488: 5484: 5476: 5472: 5464: 5460: 5452: 5448: 5443: 5442: 5436:Brian Christian 5434: 5430: 5374: 5370: 5365: 5361: 5352: 5348: 5343: 5339: 5325:Geoffrey Hinton 5315: 5311: 5289:Ferranti Mark 1 5286: 5282: 5274: 5270: 5265: 5261: 5216: 5212: 5207: 5203: 5195: 5191: 5186: 5182: 5170: 5166: 5153: 5149: 5132: 5128: 5123: 5119: 5094: 5090: 5052: 5048: 5035: 5031: 5026: 5022: 5016:present-at-hand 5005: 5001: 4980: 4976: 4970: 4966: 4949: 4945: 4937: 4933: 4927: 4923: 4898: 4894: 4865: 4861: 4853: 4849: 4844: 4840: 4831: 4827: 4822: 4818: 4789: 4785: 4780: 4776: 4767: 4763: 4751: 4747: 4739: 4735: 4730: 4726: 4701: 4697: 4673: 4669: 4656: 4652: 4646: 4642: 4632:Lambda calculus 4629: 4625: 4620: 4578: 4547: 4541: 4538: 4531:needs expansion 4516: 4504: 4472: 4434: 4420:Cloud Computing 4396: 4383: 4377:(AGI) system". 4321: 4315: 4298: 4292: 4245:Geoffrey Hinton 4187: 4075: 4044:Geoffrey Hinton 4036:Alex Krizhevsky 4024: 4018: 3961:development of 3923:Geoffrey Hinton 3918: 3912: 3856: 3840:Ferranti Mark 1 3812: 3767:was married to 3757:decision theory 3737: 3681: 3625: 3553: 3529:economic bubble 3525: 3482:decision theory 3443: 3401:, developed by 3395:decision theory 3377: 3310: 3294:Main articles: 3292: 3269:luminous aether 3236:backpropagation 3232:David Rumelhart 3228:Geoffrey Hinton 3208: 3160: 3112: 3069: 2999: 2975: 2914:under the name 2815: 2807:Daniel Kahneman 2739: 2725:Robert Kowalski 2700: 2621:, unconscious " 2595: 2589: 2521: 2515: 2481:The breadth of 2412: 2387: 2316: 2275: 2266:backpropagation 2135: 2129: 2113:Patrick Winston 2107:(who invented " 2073: 2061:canned response 2004: 1942: 1934: 1917: 1839: 1833: 1781: 1775: 1724:When access to 1722: 1712: 1702: 1672:machine of the 1670:Ferranti Mark 1 1666: 1646: 1611: 1583: 1577: 1509: 1425:Charles Babbage 1413: 1405:Main articles: 1403: 1363:Lambda calculus 1312:Begriffsschrift 1198:) and European 1188:(who developed 1152: 1047: 1041: 997: 991: 916: 845: 843:Myth and legend 840: 835: 782:James Lighthill 775:U.S. government 735: 535:Modern concepts 404: 375: 374: 365: 357: 356: 332: 322: 321: 293:Control problem 273: 263: 262: 174: 164: 163: 124: 116: 115: 86:Computer vision 61: 26: 12: 11: 5: 13825: 13815: 13814: 13809: 13793: 13792: 13778: 13760: 13734: 13720: 13707: 13673: 13633: 13611: 13589: 13579: 13555: 13533:(3): 417–457, 13513: 13466:(4): 463–518, 13448: 13408:(3): 210–219, 13390: 13376: 13354: 13348: 13326: 13307: 13294: 13285: 13270: 13255: 13249: 13234: 13220: 13204: 13182: 13160: 13142: 13136: 13120: 13110:, Al Shindagah 13101: 13088: 13068: 13055: 13039: 13026: 13010: 13001: 12988: 12975: 12958: 12933: 12928: 12915: 12894: 12881: 12863: 12838: 12825: 12803: 12791: 12761: 12752:(4): 115–127, 12738: 12724: 12711: 12699: 12666: 12633: 12609: 12587: 12574: 12558:Stubblefield W 12553: 12518: 12499: 12493: 12480: 12466: 12450: 12444: 12429: 12423: 12405: 12391: 12373: 12336: 12307: 12285: 12245: 12227: 12213: 12195: 12181: 12157: 12143: 12127: 12113: 12095: 12089: 12073: 12039: 12033: 12015: 11993: 11980: 11962: 11948: 11933: 11924:Alchemy and AI 11916: 11904: 11892: 11886: 11870: 11860: 11853: 11840: 11828:Micro-World AI 11819: 11808: 11786: 11749: 11739:, 26 July 2006 11729: 11705: 11679: 11646: 11618: 11604: 11582: 11581: 11548: 11529: 11523: 11510: 11468: 11456: 11450: 11437: 11423: 11408: 11396: 11370: 11349: 11335: 11322: 11313: 11300: 11285: 11259:(2): 175–215. 11248: 11226: 11204: 11198: 11176: 11171:978-0553418811 11170: 11157: 11137: 11123: 11110: 11104: 11088: 11070:(3): 141–144. 11045: 11044: 11031: 11019: 11001:(4): 115–133. 10990: 10955: 10935: 10922: 10919:New York Times 10910: 10896: 10883: 10863: 10811: 10791: 10777: 10764: 10746: 10737: 10704: 10693: 10670: 10664: 10640: 10626: 10607: 10594: 10579: 10538: 10534:AlanTuring.net 10525: 10505: 10491: 10478: 10473: 10460: 10444: 10432: 10423: 10419:978-9004163256 10418: 10404: 10403: 10401: 10398: 10395: 10394: 10371: 10345: 10318: 10291: 10280:. October 2020 10262: 10236: 10217: 10191: 10164: 10129: 10103: 10092:. 12 June 2019 10077: 10042: 10016: 10010:978-0262035613 10009: 9991: 9956: 9944: 9932: 9930: 9929: 9924: 9919: 9914: 9898: 9886: 9861: 9849: 9834: 9830:Christian 2020 9822: 9818:Christian 2020 9810: 9806:Christian 2020 9798: 9794:Christian 2020 9786: 9782:Christian 2020 9774: 9770:Christian 2020 9762: 9750: 9738: 9726: 9714: 9699: 9695:Christian 2020 9687: 9683:Christian 2020 9675: 9663: 9651: 9647:Christian 2020 9639: 9635:Christian 2020 9627: 9623:Christian 2020 9615: 9611:Christian 2020 9602: 9583: 9571: 9552: 9550:, p. 274. 9540: 9528: 9524:McCorduck 2004 9516: 9514:, p. 478. 9512:McCorduck 2004 9504: 9487: 9475: 9471:McCorduck 2004 9463: 9451: 9447:McCorduck 2004 9439: 9427: 9425:, p. 532. 9415: 9403: 9401: 9400: 9394: 9388: 9382: 9379:McCorduck 2004 9365: 9353: 9341: 9324: 9309: 9307:, p. 264. 9297: 9285: 9270: 9268:, p. 441. 9266:McCorduck 2004 9258: 9256: 9255: 9254:, pp. 476 9249: 9243: 9240:McCorduck 2004 9225: 9221:McCorduck 2004 9213: 9211: 9210: 9200: 9194: 9188: 9185:McCorduck 2004 9182: 9173:Expert systems 9165: 9163: 9162: 9156: 9153:McCorduck 2004 9150: 9133: 9121: 9119:, p. 424. 9117:McCorduck 2004 9109: 9097: 9095:, p. 822. 9085: 9073: 9071:, p. 820. 9061: 9057:Christian 2020 9049: 9047:, p. 141. 9045:Christian 2020 9037: 9035:, p. 140. 9033:Christian 2020 9025: 9010: 9006:Christian 2020 8998: 8996:, p. 125. 8994:Christian 2020 8986: 8982:Christian 2020 8974: 8972:, p. 124. 8970:Christian 2020 8962: 8960:, p. 819. 8945: 8941:Christian 2020 8933: 8921: 8909: 8892: 8880: 8868: 8856: 8844: 8832: 8820: 8808: 8796: 8792:McCorduck 2004 8784: 8780:Christian 2020 8772: 8751: 8739: 8735:Sejnowski 2018 8727: 8725: 8724: 8719: 8713: 8707: 8701: 8698:McCorduck 2004 8681: 8679: 8678: 8672: 8666: 8663:McCorduck 2004 8652: 8648:McCorduck 2004 8640: 8638:, p. 299. 8636:McCorduck 2004 8628: 8616: 8612:McCorduck 2004 8604: 8592: 8577: 8565: 8563: 8562: 8557: 8551: 8550:, pp. 211 8545: 8539: 8536:McCorduck 2004 8522: 8520: 8519: 8518:, pp. 275 8513: 8510: 8504: 8501:McCorduck 2004 8490: 8478: 8476:, p. 198. 8466: 8454: 8450:McCorduck 2004 8442: 8440: 8439: 8433: 8427: 8418:Expert systems 8410: 8398: 8383: 8371: 8369: 8368: 8360: 8359: 8353: 8347: 8344:McCorduck 2004 8330: 8328: 8327: 8321: 8315: 8312:McCorduck 2004 8298: 8286: 8274: 8262: 8258:McCorduck 2004 8247: 8245: 8244: 8237: 8236: 8235:, p. 1001 8230: 8224: 8221:McCorduck 2004 8210: 8198: 8186: 8184:, p. 148. 8174: 8162: 8160:, p. 123. 8150: 8137: 8124: 8122: 8121: 8114: 8113: 8107: 8101: 8098:McCorduck 2004 8087: 8085: 8084: 8079: 8074: 8067: 8066: 8060: 8054: 8051:McCorduck 2004 8037: 8025: 8023: 8022: 8015: 8014: 8008: 8002: 7988: 7976: 7964: 7962:, p. 115. 7949: 7937: 7925: 7923: 7922: 7920:Lighthill 1973 7917: 7912: 7895: 7893: 7892: 7886: 7880: 7874: 7871:McCorduck 2004 7857: 7855:, pp. 175 7844: 7842: 7841: 7835: 7829: 7823: 7820:McCorduck 2004 7809: 7797: 7782: 7780:, p. 456. 7778:McCorduck 2004 7767: 7755: 7743: 7731: 7719: 7717:, p. 146. 7707: 7690: 7678: 7676:, p. 143. 7666: 7645: 7641:Lighthill 1973 7628: 7616: 7604: 7589: 7577: 7575:, p. 131. 7573:McCorduck 2004 7565: 7553: 7541: 7529: 7517: 7505: 7501:McCorduck 2004 7493: 7481: 7465: 7449: 7447:, p. 108. 7433: 7431:, p. 105. 7421: 7394: 7377: 7358: 7346: 7327: 7310: 7298: 7286: 7274: 7262: 7250: 7238: 7225: 7223:, p. 102. 7213: 7211: 7210: 7205: 7202:McCorduck 2004 7199: 7193: 7176: 7174: 7173: 7168: 7162: 7156: 7153:McCorduck 2004 7136: 7124: 7120:McCorduck 2004 7112: 7100: 7088: 7076:McCorduck 2004 7068: 7066: 7065: 7059: 7053: 7047: 7044:McCorduck 2004 7041: 7020: 7008: 6996: 6979: 6967: 6963:McCorduck 2004 6955: 6953:, p. 246. 6951:McCorduck 2004 6943: 6941: 6940: 6923: 6907: 6895:McCorduck 2004 6887: 6875: 6863: 6848: 6836: 6824: 6812: 6810:, pp. 49. 6800: 6796:McCorduck 2004 6788: 6784:McCorduck 2004 6773: 6761: 6757:Skillings 2006 6749: 6747:, p. 114. 6745:McCorduck 2004 6737: 6725: 6713: 6701: 6684: 6682: 6681: 6675: 6669: 6666:McCorduck 2004 6660:Logic Theorist 6652: 6640: 6636:McCorduck 2004 6628: 6616: 6612:Schaeffer 1997 6604: 6592: 6580: 6578: 6577: 6574:Cordeschi 2002 6571: 6565: 6559: 6556:McCorduck 2004 6538: 6536: 6535: 6529: 6523: 6520:McCorduck 2004 6506: 6500: 6499: 6497:Piccinini 2004 6494: 6491:Cordeschi 2002 6488: 6482: 6476: 6473:McCorduck 2004 6462: 6460:, p. 981. 6450: 6438: 6436: 6435: 6428: 6427: 6424:Cordeschi 2002 6421: 6418:Haugeland 1985 6415: 6409: 6403: 6400:McCorduck 2004 6382: 6370: 6368: 6367: 6361: 6355: 6349: 6346:McCorduck 2004 6329: 6310: 6308: 6307: 6304:Cordeschi 2002 6301: 6295: 6289: 6283: 6280:McCorduck 2004 6269: 6265:McCorduck 2004 6257: 6240: 6228: 6215: 6203: 6200:Quevedo (1915) 6196:Quevedo (1914) 6184: 6165: 6153: 6138: 6126: 6124: 6123: 6116: 6115: 6109: 6103: 6100:McCorduck 2004 6097: 6088:Turing machine 6079: 6067: 6055: 6038: 6026: 6024: 6023: 6017: 6014:Berlinski 2000 6011: 6005: 6002:McCorduck 2004 5991: 5989: 5988: 5982: 5979:McCorduck 2004 5976: 5962: 5960: 5959: 5953: 5947: 5944:McCorduck 2004 5933: 5921: 5909: 5894: 5882: 5878:Berlinski 2000 5867: 5855: 5851:Hollander 1964 5843: 5841:, p. 136. 5831: 5819: 5807: 5803:McCorduck 2004 5794: 5782: 5770: 5758: 5754:McCorduck 2004 5746: 5742:McCorduck 2004 5734: 5730:McCorduck 2004 5722: 5710: 5706:McCorduck 2004 5698: 5686: 5682:McCorduck 2004 5674: 5662: 5650: 5638: 5626: 5622:McCorduck 2004 5614: 5602: 5590: 5578: 5566: 5554: 5542: 5530: 5518: 5506: 5494: 5482: 5470: 5458: 5445: 5444: 5441: 5440: 5428: 5397:filter bubbles 5389:misinformation 5368: 5359: 5346: 5337: 5309: 5287:Cycle time of 5280: 5268: 5259: 5248:Rodney Brook's 5210: 5201: 5189: 5180: 5164: 5147: 5126: 5117: 5088: 5046: 5029: 5020: 4999: 4997:was concerned. 4974: 4964: 4956:McCorduck 2004 4943: 4931: 4921: 4892: 4859: 4855:Bruce Buchanan 4847: 4838: 4825: 4816: 4804:electroplating 4796:potentiometers 4783: 4774: 4761: 4745: 4741:Daniel Crevier 4733: 4724: 4720:Norbert Wiener 4695: 4675:Daniel Crevier 4667: 4650: 4640: 4622: 4621: 4619: 4616: 4615: 4614: 4609: 4604: 4599: 4594: 4589: 4584: 4577: 4574: 4549: 4548: 4528: 4526: 4515: 4512: 4503: 4502:Future Outlook 4500: 4471: 4468: 4452:Transportation 4433: 4430: 4395: 4392: 4382: 4379: 4317:Main article: 4314: 4311: 4294:Main article: 4291: 4288: 4214:Demis Hassabis 4186: 4183: 4131: 4074: 4071: 4020:Main article: 4017: 4014: 3958:word embedding 3911: 3908: 3855: 3852: 3820:Garry Kasparov 3811: 3808: 3765:rational agent 3736: 3733: 3693:soft computing 3680: 3677: 3673:New York Times 3624: 3621: 3552: 3549: 3524: 3521: 3502: 3474:Richard Sutton 3467:Arthur Samuels 3442: 3439: 3380:Soft computing 3376: 3373: 3345: 3322: 3291: 3288: 3207: 3204: 3159: 3156: 3111: 3108: 3068: 3065: 2998: 2995: 2979:expert systems 2974: 2971: 2952:finite failure 2840: 2831:Seymour Papert 2814: 2811: 2768:expert systems 2699: 2696: 2654:intentionality 2642:intractability 2635:intentionality 2611:Hubert Dreyfus 2605:showed that a 2588: 2585: 2514: 2511: 2510: 2509: 2506:Gerald Sussman 2496: 2478: 2470: 2442:Intractability 2438: 2411: 2408: 2386: 2383: 2379:hacker culture 2318:In June 1963, 2315: 2312: 2311: 2310: 2300: 2293: 2290: 2274: 2271: 2180:Bernard Widrow 2158:neural network 2131:Main article: 2128: 2125: 2117:Terry Winograd 2101:Gerald Sussman 2097:machine vision 2081:Seymour Papert 2072: 2069: 2003: 2000: 1941: 1938: 1933: 1930: 1916: 1913: 1870:paradigm shift 1849:discussed his 1835:Main article: 1832: 1829: 1813:Trenchard More 1805:Ray Solomonoff 1793:Claude Shannon 1777:Main article: 1774: 1771: 1742:Logic Theorist 1720:Logic theorist 1718:Main article: 1701: 1698: 1682:Dietrich Prinz 1665: 1662: 1650:W. Grey Walter 1645: 1642: 1626:neural network 1610: 1607: 1579:Main article: 1576: 1573: 1541:Claude Shannon 1533:Norbert Wiener 1508: 1505: 1465:Heath Robinson 1439:, and others. 1402: 1399: 1395:Turing machine 1315:. Building on 1250:René Descartes 1151: 1148: 1140:Æsir-Vanir War 1101:sacred statues 1043:Main article: 1040: 1037: 993:Main article: 990: 989:Modern fiction 987: 915: 912: 844: 841: 839: 836: 834: 831: 829:in the 2020s. 798:expert systems 737: 736: 734: 733: 726: 719: 711: 708: 707: 706: 705: 692: 691: 685: 684: 683: 682: 678:more timelines 674: 669: 664: 659: 654: 649: 644: 636: 635: 629: 628: 627: 626: 621: 616: 611: 606: 601: 596: 588: 587: 583: 582: 581: 580: 575: 573:World Wide Web 570: 565: 560: 555: 550: 545: 537: 536: 532: 531: 530: 529: 524: 519: 514: 509: 504: 499: 491: 490: 484: 483: 482: 481: 476: 471: 466: 458: 457: 451: 450: 449: 448: 443: 435: 434: 428: 427: 417: 416: 406: 405: 403: 402: 395: 388: 380: 377: 376: 373: 372: 366: 363: 362: 359: 358: 355: 354: 349: 344: 339: 333: 328: 327: 324: 323: 320: 319: 314: 309: 304: 299: 290: 285: 280: 274: 269: 268: 265: 264: 261: 260: 255: 250: 245: 240: 239: 238: 228: 223: 218: 217: 216: 211: 206: 196: 191: 189:Earth sciences 186: 181: 179:Bioinformatics 175: 170: 169: 166: 165: 162: 161: 156: 151: 146: 141: 136: 131: 125: 122: 121: 118: 117: 114: 113: 108: 103: 98: 93: 88: 83: 78: 73: 68: 62: 57: 56: 53: 52: 42: 41: 35: 34: 9: 6: 4: 3: 2: 13824: 13813: 13810: 13808: 13805: 13804: 13802: 13789: 13785: 13781: 13775: 13771: 13770: 13765: 13761: 13749: 13744: 13739: 13735: 13731: 13727: 13723: 13717: 13713: 13708: 13704: 13700: 13696: 13692: 13688: 13684: 13683: 13678: 13674: 13663: 13659: 13655: 13651: 13647: 13643: 13639: 13634: 13623: 13622: 13617: 13612: 13601: 13597: 13596: 13590: 13585: 13580: 13576: 13572: 13568: 13564: 13560: 13556: 13544: 13540: 13536: 13532: 13528: 13527: 13522: 13518: 13514: 13511: 13495: 13491: 13487: 13482: 13477: 13473: 13469: 13465: 13461: 13454: 13449: 13437: 13433: 13429: 13425: 13421: 13416: 13411: 13407: 13403: 13399: 13396:(July 1959), 13395: 13391: 13387: 13383: 13379: 13373: 13369: 13368: 13363: 13359: 13355: 13351: 13349:0-13-790395-2 13345: 13341: 13340: 13335: 13331: 13327: 13317: 13313: 13308: 13304: 13300: 13295: 13291: 13286: 13282: 13281: 13276: 13271: 13267: 13266: 13261: 13256: 13252: 13246: 13242: 13241: 13235: 13231: 13227: 13223: 13217: 13213: 13209: 13205: 13194: 13190: 13189: 13183: 13172: 13168: 13167: 13161: 13150: 13149: 13143: 13139: 13133: 13129: 13125: 13121: 13109: 13108: 13102: 13099: 13095: 13091: 13085: 13081: 13077: 13073: 13069: 13066: 13062: 13058: 13052: 13048: 13044: 13040: 13037: 13033: 13029: 13023: 13019: 13015: 13011: 13007: 13002: 12998: 12994: 12989: 12986: 12982: 12978: 12972: 12967: 12966: 12965:Mind Children 12959: 12948: 12944: 12943: 12938: 12934: 12931: 12925: 12921: 12916: 12905: 12904: 12899: 12895: 12892: 12888: 12884: 12878: 12874: 12873: 12868: 12864: 12853: 12849: 12848: 12843: 12839: 12836: 12832: 12828: 12822: 12818: 12817: 12812: 12808: 12804: 12800: 12796: 12792: 12781: 12777: 12776: 12771: 12767: 12764:Menabrea LF, 12762: 12759: 12755: 12751: 12747: 12743: 12742:McCullough WS 12739: 12735: 12731: 12727: 12721: 12717: 12712: 12708: 12704: 12700: 12689: 12688: 12683: 12679: 12675: 12671: 12667: 12656: 12652: 12651: 12646: 12642: 12638: 12634: 12624: 12623: 12618: 12614: 12610: 12599: 12595: 12594: 12588: 12577: 12571: 12566: 12565: 12559: 12554: 12551: 12547: 12542: 12537: 12533: 12529: 12528: 12523: 12519: 12516: 12512: 12508: 12504: 12500: 12496: 12490: 12486: 12481: 12477: 12473: 12469: 12463: 12459: 12455: 12451: 12447: 12441: 12437: 12436: 12430: 12426: 12420: 12416: 12415: 12410: 12406: 12402: 12398: 12394: 12388: 12384: 12383: 12378: 12374: 12370: 12366: 12362: 12358: 12354: 12350: 12346: 12342: 12337: 12333: 12329: 12325: 12321: 12317: 12313: 12308: 12304: 12300: 12296: 12292: 12288: 12282: 12278: 12274: 12270: 12266: 12262: 12258: 12254: 12250: 12246: 12235: 12234: 12228: 12224: 12220: 12216: 12210: 12206: 12205: 12200: 12196: 12192: 12191: 12186: 12182: 12175: 12168: 12167: 12162: 12158: 12154: 12150: 12146: 12140: 12136: 12132: 12128: 12124: 12120: 12116: 12110: 12106: 12105: 12100: 12096: 12092: 12086: 12082: 12078: 12074: 12069: 12065: 12061: 12057: 12054:(12): 35–39. 12053: 12049: 12045: 12040: 12036: 12030: 12026: 12025: 12020: 12019:Feigenbaum EA 12016: 12005: 12004: 12003:The Economist 11999: 11994: 11983: 11977: 11973: 11972: 11967: 11963: 11959: 11955: 11951: 11945: 11941: 11940: 11934: 11929: 11925: 11921: 11917: 11912: 11911: 11905: 11900: 11899: 11898:Life Magazine 11893: 11889: 11887:0-465-02997-3 11883: 11879: 11875: 11871: 11866: 11861: 11856: 11854:0-19-825079-7 11850: 11846: 11841: 11830: 11829: 11824: 11820: 11817: 11813: 11809: 11794: 11793: 11787: 11783: 11779: 11775: 11771: 11767: 11763: 11759: 11755: 11750: 11738: 11734: 11730: 11718: 11711: 11706: 11695: 11693: 11688: 11684: 11680: 11665: 11661: 11660: 11652: 11647: 11643: 11639: 11636:(1–2): 3–15. 11635: 11631: 11624: 11619: 11615: 11611: 11607: 11601: 11597: 11596: 11591: 11587: 11586: 11585: 11578: 11574: 11570: 11566: 11562: 11558: 11554: 11549: 11538: 11534: 11530: 11526: 11520: 11516: 11511: 11507: 11503: 11499: 11495: 11491: 11487: 11486: 11481: 11477: 11473: 11469: 11465: 11461: 11460:Schmidhuber J 11457: 11453: 11447: 11443: 11438: 11434: 11430: 11426: 11424:9780525558637 11420: 11416: 11415: 11409: 11405: 11401: 11397: 11390: 11383: 11379: 11375: 11371: 11359: 11355: 11350: 11346: 11342: 11338: 11332: 11328: 11323: 11319: 11314: 11303: 11297: 11293: 11292: 11286: 11282: 11278: 11274: 11270: 11266: 11262: 11258: 11254: 11249: 11241: 11234: 11233: 11227: 11220: 11213: 11209: 11205: 11201: 11195: 11191: 11190: 11182: 11177: 11173: 11167: 11163: 11158: 11147: 11143: 11138: 11134: 11130: 11126: 11120: 11116: 11111: 11107: 11105:9780195136302 11101: 11097: 11093: 11089: 11085: 11081: 11077: 11073: 11069: 11065: 11058: 11054: 11050: 11049: 11048: 11041: 11037: 11032: 11029:. 1 May 2011. 11028: 11024: 11020: 11016: 11012: 11008: 11004: 11000: 10996: 10991: 10987: 10983: 10979: 10973:(3): 224–229. 10972: 10968: 10964: 10960: 10956: 10945: 10941: 10936: 10932: 10928: 10923: 10920: 10916: 10911: 10907: 10903: 10899: 10897:0-521-79234-7 10893: 10889: 10884: 10873: 10869: 10864: 10860: 10856: 10852: 10848: 10844: 10840: 10836: 10832: 10828: 10824: 10817: 10812: 10801: 10797: 10792: 10788: 10784: 10780: 10778:0-292-73061-6 10774: 10770: 10765: 10755: 10751: 10747: 10743: 10738: 10734: 10730: 10726: 10722: 10718: 10714: 10710: 10705: 10701: 10700: 10694: 10683: 10679: 10675: 10671: 10667: 10661: 10657: 10653: 10649: 10645: 10641: 10637: 10633: 10629: 10623: 10619: 10617: 10612: 10608: 10597: 10591: 10587: 10586: 10580: 10576: 10572: 10568: 10564: 10560: 10556: 10552: 10548: 10544: 10539: 10535: 10531: 10526: 10515: 10511: 10506: 10502: 10498: 10494: 10492:0-521-22564-7 10488: 10484: 10479: 10476: 10474:9781390433708 10470: 10466: 10461: 10456: 10451: 10445: 10441: 10437: 10433: 10429: 10424: 10421: 10415: 10411: 10406: 10405: 10390: 10386: 10382: 10375: 10360:. 22 May 2019 10359: 10355: 10349: 10341: 10337: 10333: 10329: 10322: 10314: 10310: 10306: 10302: 10295: 10279: 10272: 10266: 10250: 10246: 10240: 10233:(2): 100–110. 10232: 10228: 10221: 10205: 10201: 10195: 10187: 10183: 10179: 10175: 10168: 10160: 10156: 10152: 10148: 10144: 10140: 10133: 10117: 10113: 10107: 10091: 10087: 10081: 10073: 10069: 10065: 10061: 10057: 10053: 10046: 10030: 10026: 10020: 10012: 10006: 10003:. MIT Press. 10002: 10001:Deep Learning 9995: 9987: 9983: 9979: 9975: 9971: 9967: 9960: 9953: 9948: 9941: 9936: 9928: 9925: 9923: 9920: 9918: 9915: 9913: 9910: 9909: 9907: 9902: 9896:, p. 31. 9895: 9890: 9883: 9878: 9876: 9874: 9872: 9870: 9868: 9866: 9859:, p. 33. 9858: 9853: 9847:, p. 32. 9846: 9841: 9839: 9832:, p. 73. 9831: 9826: 9819: 9814: 9808:, p. 67. 9807: 9802: 9795: 9790: 9783: 9778: 9771: 9766: 9759: 9754: 9747: 9742: 9735: 9730: 9723: 9718: 9712:, p. 27. 9711: 9706: 9704: 9697:, p. 24. 9696: 9691: 9684: 9679: 9672: 9667: 9660: 9655: 9648: 9643: 9636: 9631: 9625:, p. 31. 9624: 9619: 9612: 9606: 9599: 9594: 9592: 9590: 9588: 9580: 9575: 9567: 9561: 9556: 9549: 9548:Kurzweil 2005 9544: 9538:, p. 28. 9537: 9532: 9525: 9520: 9513: 9508: 9502:, p. 61. 9501: 9496: 9494: 9492: 9484: 9479: 9472: 9467: 9460: 9455: 9448: 9443: 9436: 9431: 9424: 9423:Newquist 1994 9419: 9412: 9407: 9399:, p. 445 9398: 9397:Newquist 1994 9395: 9393:, p. 601 9392: 9389: 9387:, p. 265 9386: 9385:Kurzweil 2005 9383: 9381:, p. 423 9380: 9377: 9376: 9374: 9369: 9362: 9357: 9350: 9345: 9338: 9333: 9331: 9329: 9321: 9316: 9314: 9306: 9305:Kurzweil 2005 9301: 9294: 9289: 9282: 9281:Newquist 1994 9277: 9275: 9267: 9262: 9253: 9252:Newquist 1994 9250: 9248:, p. 212 9247: 9244: 9242:, p. 441 9241: 9238: 9237: 9235: 9229: 9222: 9217: 9208: 9207:qualification 9204: 9201: 9198: 9195: 9192: 9191:Newquist 1994 9189: 9186: 9183: 9180: 9177: 9176: 9174: 9169: 9160: 9157: 9155:, p. 435 9154: 9151: 9148: 9147:Newquist 1994 9145: 9144: 9142: 9137: 9130: 9125: 9118: 9113: 9106: 9105:Newquist 1994 9101: 9094: 9089: 9082: 9077: 9070: 9065: 9058: 9053: 9046: 9041: 9034: 9029: 9022: 9017: 9015: 9007: 9002: 8995: 8990: 8983: 8978: 8971: 8966: 8959: 8954: 8952: 8950: 8942: 8937: 8931:, Section 23. 8930: 8925: 8918: 8913: 8907:, p. 25. 8906: 8901: 8899: 8897: 8889: 8884: 8877: 8872: 8865: 8860: 8854: 8848: 8841: 8836: 8829: 8824: 8817: 8812: 8806:, p. 20. 8805: 8800: 8793: 8788: 8781: 8776: 8770:, p. 26. 8769: 8764: 8762: 8760: 8758: 8756: 8748: 8743: 8736: 8731: 8723: 8720: 8717: 8714: 8711: 8710:Newquist 1994 8708: 8705: 8702: 8700:, p. 489 8699: 8696: 8695: 8694: 8690: 8685: 8676: 8673: 8670: 8669:Newquist 1994 8667: 8664: 8661: 8660: 8656: 8649: 8644: 8637: 8632: 8625: 8620: 8613: 8608: 8601: 8596: 8590:, p. 23. 8589: 8584: 8582: 8574: 8569: 8561: 8558: 8555: 8552: 8549: 8546: 8543: 8542:Newquist 1994 8540: 8537: 8534: 8533: 8531: 8526: 8517: 8516:Newquist 1994 8514: 8511: 8508: 8505: 8502: 8499: 8498: 8494: 8487: 8486:Newquist 1994 8482: 8475: 8470: 8463: 8458: 8451: 8446: 8437: 8434: 8432:, p. 271 8431: 8430:Newquist 1994 8428: 8425: 8422: 8421: 8419: 8414: 8407: 8402: 8395: 8390: 8388: 8380: 8375: 8366: 8363: 8362: 8358:, p. 23. 8357: 8354: 8351: 8348: 8345: 8342: 8341: 8339: 8334: 8325: 8322: 8319: 8316: 8313: 8310: 8309: 8307: 8302: 8295: 8290: 8283: 8278: 8271: 8266: 8260:, p. 51. 8259: 8254: 8252: 8243: 8240: 8239: 8234: 8231: 8228: 8225: 8222: 8219: 8218: 8214: 8207: 8202: 8195: 8190: 8183: 8178: 8171: 8170:Newquist 1994 8166: 8159: 8154: 8148:, p. 122 8147: 8141: 8135:, p. 143 8134: 8128: 8120: 8117: 8116: 8111: 8108: 8105: 8102: 8099: 8096: 8095: 8091: 8083: 8080: 8078: 8075: 8073: 8070: 8069: 8064: 8061: 8058: 8055: 8052: 8049: 8048: 8046: 8041: 8034: 8029: 8021: 8018: 8017: 8012: 8009: 8006: 8003: 8000: 7997: 7996: 7992: 7985: 7980: 7973: 7968: 7961: 7956: 7954: 7946: 7941: 7934: 7933:McCarthy 1974 7929: 7921: 7918: 7916: 7913: 7911:, p. 117 7910: 7907: 7906: 7904: 7899: 7890: 7887: 7884: 7881: 7879:, p. 110 7878: 7875: 7872: 7869: 7868: 7866: 7861: 7854: 7848: 7839: 7836: 7833: 7830: 7827: 7824: 7821: 7818: 7817: 7813: 7806: 7801: 7794: 7789: 7787: 7779: 7774: 7772: 7764: 7759: 7752: 7747: 7740: 7735: 7729:, p. 56. 7728: 7727:Buchanan 2005 7723: 7716: 7711: 7705:, p. 21. 7704: 7699: 7697: 7695: 7687: 7682: 7675: 7670: 7663: 7658: 7656: 7654: 7652: 7650: 7642: 7637: 7635: 7633: 7625: 7620: 7613: 7608: 7602: 7598: 7593: 7587:, p. 65. 7586: 7581: 7574: 7569: 7563:, p. 51. 7562: 7557: 7550: 7545: 7539:, p. 94. 7538: 7533: 7526: 7521: 7515:, p. 96. 7514: 7509: 7502: 7497: 7490: 7485: 7479:, p. 109 7478: 7474: 7469: 7463:, p. 109 7462: 7458: 7453: 7446: 7442: 7437: 7430: 7425: 7419:, p. 24. 7418: 7413: 7411: 7409: 7407: 7405: 7403: 7401: 7399: 7391: 7386: 7384: 7382: 7375:, p. 22. 7374: 7369: 7367: 7365: 7363: 7355: 7350: 7343: 7338: 7336: 7334: 7332: 7324: 7319: 7317: 7315: 7307: 7302: 7295: 7290: 7283: 7278: 7271: 7266: 7259: 7254: 7247: 7242: 7236:, p. 102 7235: 7229: 7222: 7217: 7209: 7206: 7203: 7200: 7197: 7194: 7191: 7188: 7187: 7186:in the 60s: 7185: 7180: 7172: 7171:Copeland 2000 7169: 7166: 7163: 7160: 7157: 7154: 7151: 7150: 7148: 7143: 7141: 7133: 7128: 7121: 7116: 7109: 7104: 7097: 7092: 7085: 7081: 7077: 7072: 7063: 7060: 7057: 7056:Newquist 1994 7054: 7051: 7048: 7045: 7042: 7039: 7036: 7035: 7033: 7029: 7024: 7018:, p. 20. 7017: 7012: 7005: 7000: 6994:, p. 19. 6993: 6988: 6986: 6984: 6976: 6971: 6964: 6959: 6952: 6947: 6938: 6935: 6934: 6932: 6927: 6920: 6916: 6911: 6904: 6900: 6899:Newquist 1994 6896: 6891: 6884: 6879: 6872: 6867: 6861:, p. 18. 6860: 6855: 6853: 6846:, p. 18. 6845: 6840: 6833: 6828: 6821: 6816: 6809: 6804: 6797: 6792: 6785: 6780: 6778: 6771:, p. 73. 6770: 6769:McCarthy 1996 6765: 6758: 6753: 6746: 6741: 6734: 6729: 6723:, p. 48. 6722: 6717: 6710: 6705: 6698: 6694: 6688: 6679: 6676: 6673: 6670: 6667: 6664: 6663: 6661: 6656: 6649: 6644: 6637: 6632: 6625: 6620: 6613: 6608: 6601: 6600:Copeland 1999 6596: 6590:, p. 17. 6589: 6584: 6575: 6572: 6569: 6566: 6563: 6560: 6557: 6554: 6553: 6551: 6547: 6542: 6533: 6530: 6527: 6524: 6522:, p. 102 6521: 6518: 6517: 6515: 6510: 6504: 6498: 6495: 6492: 6489: 6486: 6483: 6480: 6477: 6474: 6471: 6470: 6466: 6459: 6454: 6447: 6446:Newquist 1994 6442: 6434: 6431: 6430: 6425: 6422: 6419: 6416: 6413: 6410: 6407: 6404: 6401: 6398: 6397: 6395: 6391: 6386: 6380: 6374: 6365: 6364:Newquist 1994 6362: 6359: 6356: 6353: 6350: 6347: 6344: 6343: 6341: 6336: 6334: 6326: 6325:Copeland 2004 6321: 6319: 6317: 6315: 6305: 6302: 6299: 6296: 6293: 6290: 6287: 6284: 6281: 6278: 6277: 6273: 6266: 6261: 6255:, p. 14. 6254: 6249: 6247: 6245: 6237: 6232: 6226:, p. 15) 6225: 6219: 6212: 6207: 6201: 6197: 6193: 6192:Randall (1982 6188: 6182: 6178: 6174: 6173:Randall (1982 6169: 6163:, p. 67. 6162: 6161:Newquist 1994 6157: 6151:, p. 15. 6150: 6145: 6143: 6135: 6134:Couturat 1901 6130: 6122: 6119: 6118: 6113: 6110: 6107: 6104: 6101: 6098: 6095: 6094:Newquist 1994 6092: 6091: 6089: 6083: 6076: 6071: 6064: 6059: 6052: 6047: 6045: 6043: 6035: 6030: 6021: 6020:Buchanan 2005 6018: 6015: 6012: 6009: 6006: 6003: 6000: 5999: 5995: 5986: 5983: 5980: 5977: 5974: 5971: 5970: 5966: 5957: 5956:Buchanan 2005 5954: 5951: 5948: 5945: 5942: 5941: 5937: 5930: 5925: 5918: 5913: 5906: 5901: 5899: 5891: 5886: 5879: 5874: 5872: 5864: 5859: 5852: 5847: 5840: 5835: 5828: 5823: 5817:, p. 56. 5816: 5811: 5804: 5798: 5791: 5786: 5780:, p. 30. 5779: 5778:Newquist 1994 5774: 5767: 5762: 5756:, p. 17. 5755: 5750: 5743: 5738: 5732:, p. 16. 5731: 5726: 5720:, p. 40. 5719: 5718:Newquist 1994 5714: 5708:, p. 10. 5707: 5702: 5695: 5690: 5683: 5678: 5672:, p. 53. 5671: 5666: 5659: 5654: 5648:, p. 65. 5647: 5646:Newquist 1994 5642: 5635: 5630: 5623: 5618: 5611: 5606: 5599: 5598:O'Connor 1994 5594: 5587: 5582: 5576:, p. 38. 5575: 5574:Newquist 1994 5570: 5563: 5558: 5551: 5546: 5539: 5534: 5527: 5522: 5515: 5510: 5503: 5498: 5491: 5486: 5479: 5478:Newquist 1994 5474: 5467: 5466:Newquist 1994 5462: 5455: 5450: 5446: 5437: 5432: 5426: 5422: 5418: 5414: 5410: 5406: 5402: 5398: 5394: 5390: 5386: 5382: 5378: 5372: 5363: 5356: 5350: 5341: 5334: 5330: 5326: 5322: 5318: 5313: 5306: 5302: 5298: 5294: 5290: 5284: 5277: 5272: 5263: 5256: 5252: 5249: 5245: 5241: 5240: 5235: 5234:Marvin Minsky 5231: 5227: 5223: 5219: 5214: 5205: 5199: 5193: 5184: 5177: 5173: 5168: 5161: 5156: 5151: 5144: 5140: 5137:published by 5136: 5130: 5121: 5114: 5110: 5106: 5102: 5098: 5092: 5085: 5084: 5079: 5075: 5074:Eleanor Rosch 5071: 5067: 5063: 5059: 5055: 5050: 5043: 5039: 5033: 5024: 5017: 5013: 5012:ready-to-hand 5009: 5003: 4996: 4992: 4988: 4984: 4978: 4968: 4961: 4957: 4953: 4947: 4940: 4939:John McCarthy 4935: 4925: 4918: 4914: 4910: 4906: 4902: 4896: 4889: 4885: 4881: 4877: 4873: 4869: 4863: 4856: 4851: 4842: 4835: 4829: 4820: 4813: 4812:ferrite cores 4809: 4805: 4801: 4797: 4793: 4787: 4778: 4771: 4770:John McCarthy 4765: 4759: 4758:Kenneth Craig 4755: 4749: 4742: 4737: 4728: 4721: 4717: 4713: 4709: 4705: 4699: 4692: 4688: 4684: 4680: 4676: 4671: 4664: 4660: 4654: 4644: 4637: 4633: 4627: 4623: 4613: 4610: 4608: 4605: 4603: 4600: 4598: 4595: 4593: 4590: 4588: 4585: 4583: 4580: 4579: 4573: 4571: 4567: 4563: 4559: 4558:neurosymbolic 4555: 4545: 4536: 4532: 4529:This section 4527: 4524: 4520: 4519: 4511: 4508: 4499: 4497: 4493: 4491: 4487: 4485: 4481: 4479: 4475: 4467: 4465: 4464:Manufacturing 4461: 4459: 4458:Entertainment 4455: 4453: 4449: 4447: 4443: 4441: 4437: 4429: 4427: 4423: 4421: 4417: 4415: 4411: 4409: 4405: 4403: 4399: 4391: 4388: 4378: 4376: 4371: 4367: 4363: 4358: 4356: 4352: 4348: 4345:in 2020, and 4344: 4340: 4336: 4332: 4330: 4326: 4323:In 2017, the 4320: 4310: 4308: 4303: 4297: 4287: 4283: 4281: 4277: 4272: 4269: 4265: 4260: 4256: 4254: 4250: 4246: 4241: 4239: 4235: 4231: 4227: 4223: 4219: 4215: 4211: 4206: 4204: 4200: 4196: 4192: 4182: 4180: 4175: 4170: 4165: 4163: 4159: 4155: 4151: 4147: 4143: 4138: 4136: 4129: 4127: 4123: 4119: 4118: 4113: 4109: 4104: 4102: 4098: 4094: 4090: 4089: 4084: 4080: 4070: 4066: 4064: 4060: 4055: 4053: 4052:deep learning 4049: 4045: 4041: 4037: 4033: 4032:deep learning 4029: 4023: 4022:Deep learning 4016:Deep learning 4013: 4011: 4007: 4003: 3999: 3995: 3991: 3988: 3983: 3981: 3980: 3975: 3971: 3966: 3964: 3959: 3955: 3951: 3947: 3943: 3939: 3935: 3931: 3930:UMass Amherst 3926: 3924: 3917: 3907: 3905: 3901: 3897: 3893: 3889: 3885: 3881: 3876: 3873: 3872:deep learning 3869: 3866:and advanced 3865: 3861: 3851: 3849: 3845: 3841: 3837: 3831: 3829: 3825: 3821: 3817: 3807: 3805: 3800: 3798: 3794: 3789: 3784: 3782: 3778: 3774: 3770: 3766: 3762: 3758: 3754: 3750: 3746: 3742: 3732: 3730: 3729: 3723: 3721: 3717: 3713: 3709: 3705: 3700: 3698: 3694: 3690: 3686: 3676: 3674: 3670: 3666: 3662: 3658: 3653: 3651: 3645: 3643: 3639: 3636:, logistics, 3635: 3631: 3620: 3618: 3614: 3609: 3606: 3601: 3599: 3595: 3590: 3588: 3584: 3579: 3577: 3573: 3572:Lisp machines 3569: 3565: 3560: 3558: 3548: 3546: 3542: 3538: 3532: 3530: 3520: 3518: 3514: 3510: 3506: 3500: 3498: 3493: 3491: 3487: 3483: 3479: 3475: 3470: 3468: 3464: 3460: 3456: 3452: 3447: 3438: 3436: 3432: 3428: 3424: 3420: 3416: 3412: 3408: 3404: 3400: 3396: 3392: 3388: 3384: 3381: 3372: 3370: 3369:embodied mind 3366: 3361: 3359: 3354: 3352: 3348: 3343: 3341: 3337: 3333: 3328: 3326: 3320: 3318: 3314: 3313:Rodney Brooks 3309: 3305: 3301: 3297: 3287: 3285: 3281: 3277: 3272: 3270: 3266: 3262: 3261:connectionism 3258: 3254: 3250: 3249: 3243: 3241: 3237: 3233: 3229: 3225: 3221: 3220:John Hopfield 3212: 3203: 3201: 3197: 3193: 3189: 3185: 3184:connectionism 3181: 3177: 3173: 3169: 3165: 3155: 3153: 3149: 3148:Douglas Lenat 3145: 3140: 3138: 3134: 3130: 3126: 3122: 3118: 3107: 3105: 3101: 3097: 3093: 3088: 3086: 3082: 3078: 3074: 3071:In 1981, the 3064: 3062: 3058: 3054: 3053:Lisp Machines 3050: 3046: 3042: 3038: 3033: 3031: 3027: 3022: 3020: 3016: 3012: 3008: 3004: 3003:expert system 2994: 2992: 2988: 2984: 2980: 2970: 2968: 2964: 2959: 2957: 2953: 2949: 2945: 2941: 2936: 2931: 2927: 2924: 2919: 2917: 2913: 2909: 2905: 2901: 2900: 2895: 2894: 2888: 2884: 2879: 2877: 2873: 2869: 2865: 2861: 2857: 2856: 2851: 2850: 2845: 2838: 2836: 2832: 2828: 2827:Marvin Minsky 2824: 2820: 2810: 2808: 2804: 2800: 2799:Eleanor Rosch 2796: 2792: 2787: 2785: 2781: 2777: 2773: 2769: 2765: 2761: 2757: 2753: 2749: 2743: 2738: 2734: 2730: 2726: 2721: 2717: 2713: 2709: 2705: 2704:John McCarthy 2695: 2693: 2692: 2687: 2682: 2678: 2677:Kenneth Colby 2673: 2671: 2667: 2663: 2659: 2655: 2651: 2647: 2643: 2638: 2636: 2632: 2628: 2624: 2620: 2616: 2612: 2608: 2607:formal system 2604: 2600: 2594: 2584: 2580: 2578: 2574: 2569: 2565: 2561: 2557: 2555: 2551: 2546: 2542: 2538: 2534: 2530: 2526: 2520: 2507: 2503: 2502: 2499:Representing 2497: 2493: 2489: 2485: 2484: 2479: 2476: 2475: 2471: 2468: 2464: 2463:many problems 2460: 2456: 2453:(building on 2452: 2448: 2447: 2443: 2439: 2436: 2432: 2427: 2423: 2422: 2418: 2417: 2416: 2407: 2405: 2401: 2397: 2391: 2382: 2380: 2376: 2371: 2369: 2368:Donald Michie 2365: 2361: 2360:John McCarthy 2358:, founded by 2357: 2353: 2349: 2345: 2341: 2337: 2333: 2329: 2325: 2321: 2308: 2306: 2301: 2298: 2297:Marvin Minsky 2294: 2291: 2288: 2284: 2280: 2279: 2278: 2270: 2267: 2262: 2260: 2256: 2252: 2248: 2243: 2241: 2240:connectionism 2237: 2236: 2231: 2227: 2223: 2218: 2216: 2215:coding sheets 2213: 2209: 2205: 2201: 2197: 2193: 2189: 2185: 2181: 2177: 2175: 2171: 2167: 2166:Marvin Minsky 2163: 2159: 2155: 2146: 2142: 2140: 2134: 2124: 2122: 2118: 2114: 2110: 2106: 2102: 2098: 2093: 2091: 2086: 2082: 2078: 2077:Marvin Minsky 2068: 2066: 2062: 2058: 2054: 2050: 2046: 2044: 2040: 2035: 2030: 2028: 2024: 2023:Daniel Bobrow 2020: 2013: 2008: 1999: 1997: 1993: 1989: 1985: 1981: 1977: 1973: 1969: 1965: 1961: 1959: 1955: 1951: 1947: 1937: 1929: 1927: 1922: 1912: 1910: 1906: 1901: 1899: 1898:functionalism 1895: 1891: 1887: 1883: 1879: 1875: 1871: 1867: 1862: 1860: 1856: 1855:George Miller 1852: 1848: 1844: 1838: 1828: 1826: 1822: 1818: 1817:Arthur Samuel 1814: 1810: 1806: 1802: 1798: 1794: 1790: 1789:John McCarthy 1786: 1785:Marvin Minsky 1780: 1770: 1768: 1764: 1760: 1759: 1755: 1751: 1747: 1743: 1740:created the " 1739: 1735: 1730: 1727: 1721: 1706: 1697: 1695: 1691: 1687: 1686:Arthur Samuel 1683: 1679: 1675: 1671: 1661: 1659: 1655: 1651: 1641: 1639: 1635: 1634:Marvin Minsky 1631: 1627: 1623: 1619: 1615: 1606: 1604: 1600: 1596: 1592: 1588: 1582: 1568: 1564: 1562: 1556: 1554: 1550: 1546: 1542: 1538: 1534: 1530: 1526: 1518: 1513: 1504: 1502: 1498: 1494: 1490: 1486: 1482: 1478: 1474: 1470: 1466: 1462: 1458: 1454: 1450: 1445: 1442: 1438: 1437:Vannevar Bush 1434: 1430: 1429:Percy Ludgate 1426: 1422: 1418: 1412: 1408: 1398: 1396: 1392: 1388: 1384: 1380: 1370: 1366: 1364: 1360: 1356: 1352: 1348: 1344: 1340: 1339:David Hilbert 1336: 1332: 1331: 1326: 1322: 1318: 1314: 1313: 1308: 1304: 1303: 1298: 1294: 1291:The study of 1289: 1287: 1283: 1279: 1278: 1273: 1269: 1265: 1261: 1260: 1255: 1251: 1247: 1246:Thomas Hobbes 1243: 1235: 1231: 1227: 1225: 1220: 1216: 1211: 1209: 1205: 1201: 1197: 1196: 1191: 1187: 1183: 1182: 1177: 1173: 1169: 1165: 1161: 1157: 1147: 1145: 1141: 1137: 1133: 1129: 1124: 1122: 1118: 1114: 1110: 1106: 1105:ancient Egypt 1102: 1097: 1095: 1091: 1087: 1083: 1079: 1075: 1071: 1067: 1063: 1055: 1051: 1046: 1036: 1034: 1030: 1026: 1022: 1021:Samuel Butler 1018: 1017: 1012: 1008: 1007: 1002: 996: 986: 984: 980: 976: 971: 969: 965: 961: 960: 955: 953: 949: 945: 941: 936: 933: 929: 920: 911: 909: 905: 904: 903:Metamorphoses 899: 895: 891: 889: 885: 881: 877: 873: 870:as a gift to 869: 865: 861: 860: 855: 850: 830: 828: 824: 823:generative AI 820: 816: 815:deep learning 811: 806: 804: 799: 795: 791: 787: 783: 778: 776: 772: 768: 763: 761: 756: 752: 748: 744: 732: 727: 725: 720: 718: 713: 712: 710: 709: 704: 696: 695: 694: 693: 690: 687: 686: 681: 679: 675: 673: 670: 668: 665: 663: 660: 658: 655: 653: 650: 648: 645: 643: 640: 639: 638: 637: 634: 631: 630: 625: 622: 620: 617: 615: 614:South America 612: 610: 607: 605: 602: 600: 597: 595: 592: 591: 590: 589: 585: 584: 579: 576: 574: 571: 569: 566: 564: 561: 559: 556: 554: 551: 549: 546: 544: 541: 540: 539: 538: 534: 533: 528: 525: 523: 520: 518: 515: 513: 510: 508: 505: 503: 500: 498: 495: 494: 493: 492: 489: 486: 485: 480: 477: 475: 472: 470: 467: 465: 462: 461: 460: 459: 456: 453: 452: 447: 444: 442: 439: 438: 437: 436: 433: 430: 429: 423: 419: 418: 415: 412: 411: 401: 396: 394: 389: 387: 382: 381: 379: 378: 371: 368: 367: 361: 360: 353: 350: 348: 345: 343: 340: 338: 335: 334: 331: 326: 325: 318: 315: 313: 310: 308: 305: 303: 300: 298: 294: 291: 289: 286: 284: 281: 279: 276: 275: 272: 267: 266: 259: 256: 254: 251: 249: 246: 244: 241: 237: 236:Mental health 234: 233: 232: 229: 227: 224: 222: 219: 215: 212: 210: 207: 205: 202: 201: 200: 199:Generative AI 197: 195: 192: 190: 187: 185: 182: 180: 177: 176: 173: 168: 167: 160: 157: 155: 152: 150: 147: 145: 142: 140: 139:Deep learning 137: 135: 132: 130: 127: 126: 120: 119: 112: 109: 107: 104: 102: 99: 97: 94: 92: 89: 87: 84: 82: 79: 77: 74: 72: 69: 67: 64: 63: 60: 55: 54: 48: 44: 43: 40: 37: 36: 32: 31: 28: 25: 21: 16: 13768: 13764:Weizenbaum J 13752:. Retrieved 13747: 13711: 13686: 13680: 13665:, retrieved 13645: 13641: 13625:, retrieved 13619: 13603:, retrieved 13594: 13583: 13566: 13562: 13547:, retrieved 13543:the original 13530: 13524: 13501:, retrieved 13494:the original 13463: 13459: 13440:, retrieved 13436:the original 13405: 13401: 13365: 13338: 13319:, retrieved 13315: 13302: 13289: 13278: 13263: 13239: 13211: 13196:, retrieved 13187: 13174:, retrieved 13165: 13153:, retrieved 13147: 13127: 13112:, retrieved 13106: 13079: 13046: 13017: 13005: 12996: 12964: 12951:, retrieved 12947:the original 12941: 12919: 12908:, retrieved 12902: 12871: 12856:, retrieved 12852:the original 12846: 12815: 12798: 12783:, retrieved 12779: 12773: 12749: 12745: 12715: 12692:, retrieved 12686: 12659:, retrieved 12655:the original 12649: 12639:, Minsky M, 12626:, retrieved 12620: 12602:, retrieved 12598:the original 12592: 12579:. Retrieved 12563: 12531: 12525: 12510: 12503:Lighthill PS 12484: 12457: 12434: 12413: 12381: 12344: 12340: 12315: 12311: 12260: 12256: 12251:, Slovic D, 12237:, retrieved 12232: 12203: 12199:Hofstadter D 12189: 12174:the original 12165: 12134: 12103: 12080: 12051: 12047: 12023: 12007:, retrieved 12001: 11985:. Retrieved 11970: 11938: 11923: 11908: 11896: 11877: 11864: 11844: 11832:, retrieved 11827: 11815: 11800:, retrieved 11791: 11757: 11741:, retrieved 11736: 11721:. Retrieved 11717:the original 11697:, retrieved 11690: 11671:, retrieved 11664:the original 11657: 11633: 11629: 11594: 11583: 11560: 11556: 11540:. Retrieved 11536: 11514: 11489: 11483: 11444:. Springer. 11441: 11413: 11403: 11400:Rosenblatt F 11389:the original 11362:. Retrieved 11357: 11326: 11317: 11305:. Retrieved 11290: 11256: 11252: 11240:the original 11231: 11219:the original 11188: 11161: 11149:. Retrieved 11145: 11114: 11095: 11067: 11063: 11046: 11039: 11027:McKinsey.com 11026: 10998: 10994: 10985: 10981: 10970: 10966: 10962: 10947:. Retrieved 10943: 10930: 10918: 10887: 10875:. Retrieved 10871: 10826: 10822: 10803:. Retrieved 10799: 10768: 10757:, retrieved 10753: 10741: 10716: 10712: 10698: 10685:. Retrieved 10681: 10647: 10614: 10599:. Retrieved 10584: 10553:(2): 74–78. 10550: 10546: 10533: 10517:. Retrieved 10513: 10482: 10464: 10439: 10427: 10409: 10380: 10374: 10364:25 September 10362:. Retrieved 10357: 10348: 10331: 10327: 10321: 10307:(1): 75–89. 10304: 10300: 10294: 10284:25 September 10282:. Retrieved 10277: 10265: 10255:25 September 10253:. Retrieved 10251:. 9 May 2019 10248: 10239: 10230: 10226: 10220: 10210:25 September 10208:. Retrieved 10203: 10194: 10177: 10173: 10167: 10142: 10138: 10132: 10122:25 September 10120:. Retrieved 10115: 10106: 10096:25 September 10094:. Retrieved 10089: 10080: 10055: 10051: 10045: 10035:25 September 10033:. Retrieved 10028: 10019: 10000: 9994: 9969: 9965: 9959: 9947: 9935: 9901: 9889: 9852: 9825: 9813: 9801: 9789: 9777: 9765: 9758:O'Neill 2016 9753: 9741: 9734:Russell 2020 9729: 9717: 9690: 9678: 9671:Markoff 2011 9666: 9654: 9649:, p. 6. 9642: 9630: 9618: 9613:, p. 22 9605: 9574: 9555: 9543: 9531: 9519: 9507: 9478: 9466: 9454: 9442: 9435:Markoff 2005 9430: 9418: 9406: 9368: 9356: 9344: 9300: 9288: 9261: 9246:Crevier 1993 9236:initiative: 9228: 9216: 9197:Crevier 1993 9168: 9159:Crevier 1993 9141:Lisp machine 9136: 9129:Crevier 1993 9124: 9112: 9100: 9088: 9076: 9064: 9059:, p. ?. 9052: 9040: 9028: 9001: 8989: 8977: 8965: 8936: 8924: 8912: 8883: 8876:Pollack 1989 8871: 8864:Pollack 1984 8859: 8847: 8842:, p. 3. 8835: 8823: 8816:Crevier 1993 8811: 8804:Moravec 1988 8799: 8787: 8775: 8747:Crevier 1993 8742: 8730: 8704:Crevier 1993 8684: 8677:, p. 23 8655: 8643: 8631: 8619: 8607: 8600:Crevier 1993 8595: 8573:Crevier 1993 8568: 8556:, p. 23 8548:Crevier 1993 8525: 8507:Crevier 1993 8493: 8481: 8474:Crevier 1993 8469: 8462:Crevier 1993 8457: 8445: 8424:Crevier 1993 8413: 8401: 8374: 8350:Crevier 1993 8333: 8318:Crevier 1993 8301: 8294:Crevier 1993 8289: 8282:Crevier 1993 8277: 8270:Crevier 1993 8265: 8227:Crevier 1993 8213: 8208:, p. 6. 8201: 8189: 8177: 8165: 8158:Crevier 1993 8153: 8146:Crevier 1993 8140: 8133:Crevier 1993 8127: 8104:Crevier 1993 8090: 8077:Dreyfus 1972 8072:Dreyfus 1965 8057:Crevier 1993 8040: 8028: 8001:, p. 22 7999:Crevier 1993 7991: 7979: 7967: 7960:Crevier 1993 7945:Crevier 1993 7940: 7928: 7909:Crevier 1993 7898: 7885:, p. 21 7877:Crevier 1993 7860: 7853:Crevier 1993 7847: 7834:, p. 13 7832:Moravec 1988 7826:Crevier 1993 7812: 7805:Moravec 1988 7800: 7763:Moravec 2000 7758: 7751:Moravec 1976 7746: 7739:Crevier 1993 7734: 7722: 7715:Crevier 1993 7710: 7688:, p. 1. 7686:Nilsson 2009 7681: 7674:Crevier 1993 7669: 7624:Dreyfus 1972 7619: 7612:Crevier 1993 7607: 7597:Crevier 1993 7592: 7585:Crevier 1993 7580: 7568: 7561:Crevier 1993 7556: 7544: 7537:Crevier 1993 7532: 7525:Crevier 1993 7520: 7513:Crevier 1993 7508: 7496: 7489:Darrach 1970 7484: 7477:Crevier 1993 7468: 7461:Crevier 1993 7452: 7445:Crevier 1993 7436: 7429:Crevier 1993 7424: 7349: 7323:Nielson 2005 7301: 7294:Nilsson 1984 7289: 7277: 7265: 7253: 7241: 7234:Crevier 1993 7228: 7221:Crevier 1993 7216: 7196:Crevier 1993 7192:, p. 21 7179: 7167:, p. 20 7159:Crevier 1993 7147:Blocks world 7132:Crevier 1993 7127: 7115: 7108:Crevier 1993 7103: 7096:Crevier 1993 7091: 7086:, p. 20 7080:Crevier 1993 7071: 7062:Moravec 1988 7050:Crevier 1993 7040:, p. 20 7023: 7011: 7004:Crevier 1993 6999: 6970: 6958: 6946: 6926: 6919:Moravec 1988 6915:Crevier 1993 6910: 6903:Crevier 1993 6890: 6885:, p. 9. 6883:Moravec 1988 6878: 6871:Crevier 1993 6866: 6839: 6827: 6815: 6808:Crevier 1993 6803: 6791: 6764: 6752: 6740: 6728: 6721:Crevier 1993 6716: 6704: 6699:, p. 18 6693:Crevier 1993 6687: 6680:, p. 18 6672:Crevier 1993 6655: 6648:Crevier 1993 6643: 6631: 6619: 6614:, Chapter 6. 6607: 6595: 6583: 6568:Moravec 1988 6562:Crevier 1993 6558:, p. 98 6541: 6534:, p. 17 6526:Crevier 1993 6509: 6487:, p. 17 6481:, p. 30 6479:Crevier 1993 6465: 6453: 6441: 6406:Crevier 1993 6385: 6373: 6360:, p. 18 6352:Crevier 1993 6298:Moravec 1988 6286:Crevier 1993 6272: 6260: 6231: 6218: 6211:Randall 1982 6206: 6187: 6177:Byrne (2012) 6168: 6156: 6129: 6106:Crevier 1993 6096:, p. 56 6082: 6070: 6063:Crevier 1993 6058: 6053:, p. 9. 6036:, p. 8. 6029: 6022:, p. 53 6016:, p. 12 6010:, p. 6} 6004:, p. 41 5994: 5981:, p. 42 5965: 5958:, p. 53 5936: 5924: 5912: 5907:, p. 6. 5885: 5858: 5846: 5834: 5822: 5810: 5805:, p. 8. 5797: 5792:, p. 1. 5790:Crevier 1993 5785: 5773: 5761: 5749: 5737: 5725: 5713: 5701: 5689: 5684:, p. 6. 5677: 5670:Needham 1986 5665: 5653: 5641: 5629: 5617: 5605: 5593: 5581: 5569: 5557: 5550:Kressel 2015 5545: 5533: 5526:Morford 2007 5521: 5514:Rhodios 2007 5509: 5497: 5490:Rhodios 2007 5485: 5473: 5461: 5449: 5431: 5415:, misuse of 5401:partisanship 5381:surveillance 5371: 5362: 5349: 5340: 5312: 5304: 5283: 5276:Ray Kurzweil 5271: 5262: 5237: 5213: 5204: 5192: 5183: 5167: 5160:golden spike 5155:Hans Moravec 5150: 5129: 5120: 5091: 5081: 5049: 5032: 5023: 5002: 4977: 4967: 4952:Crevier 1993 4946: 4934: 4924: 4905:ramification 4899:Such as the 4895: 4876:human retina 4862: 4850: 4841: 4828: 4819: 4802:adjusted by 4786: 4777: 4764: 4748: 4736: 4727: 4698: 4670: 4653: 4643: 4626: 4552: 4539: 4535:adding to it 4530: 4509: 4505: 4495: 4494: 4489: 4488: 4483: 4482: 4477: 4476: 4473: 4463: 4462: 4457: 4456: 4451: 4450: 4445: 4444: 4439: 4438: 4435: 4425: 4424: 4419: 4418: 4413: 4412: 4407: 4406: 4401: 4400: 4397: 4386: 4384: 4359: 4333: 4322: 4299: 4284: 4276:Dario Amodei 4273: 4257: 4242: 4207: 4199:Ben Goertzel 4195:Nils Nilsson 4188: 4169:Donald Trump 4166: 4150:Julia Angwin 4142:Cathy O'Neil 4139: 4135:AI alignment 4115: 4112:Nick Bostrom 4105: 4097:Nick Bostrom 4086: 4083:Ray Kurzweil 4076: 4067: 4062: 4056: 4025: 4010:Ken Jennings 3984: 3977: 3967: 3927: 3919: 3880:Ben Goertzel 3877: 3857: 3832: 3813: 3801: 3785: 3749:Allen Newell 3738: 3726: 3724: 3701: 3682: 3672: 3654: 3650:Nick Bostrom 3646: 3626: 3616: 3610: 3602: 3591: 3580: 3561: 3554: 3533: 3526: 3494: 3478:Andrew Barto 3471: 3444: 3431:optimization 3385: 3378: 3362: 3355: 3329: 3317:Hans Moravec 3311: 3273: 3246: 3244: 3224:Hopfield net 3217: 3200:Nils Nilsson 3180:common sense 3161: 3141: 3113: 3089: 3070: 3034: 3029: 3023: 3000: 2976: 2960: 2951: 2928: 2920: 2897: 2891: 2880: 2854: 2848: 2835:Roger Schank 2816: 2803:Amos Tversky 2788: 2772:Allen Newell 2752:Horn clauses 2708:Advice Taker 2701: 2689: 2674: 2639: 2631:Chinese Room 2596: 2581: 2560:Hans Moravec 2558: 2522: 2498: 2480: 2472: 2455:Stephen Cook 2451:Richard Karp 2440: 2426:Hans Moravec 2419: 2413: 2404:Nils Nilsson 2392: 2388: 2372: 2317: 2304: 2287:Allen Newell 2276: 2263: 2244: 2233: 2219: 2178: 2151: 2136: 2094: 2090:blocks world 2074: 2071:Micro-worlds 2057:ELIZA effect 2047: 2039:Roger Schank 2034:semantic net 2031: 2016: 1984:plan actions 1962: 1950:backtracking 1943: 1935: 1918: 1902: 1863: 1847:Noam Chomsky 1840: 1821:Allen Newell 1782: 1756: 1734:Allen Newell 1731: 1723: 1667: 1647: 1614:Walter Pitts 1612: 1598: 1584: 1557: 1522: 1446: 1441:Ada Lovelace 1414: 1390: 1386: 1378: 1375: 1337:'s success, 1328: 1310: 1300: 1290: 1281: 1275: 1267: 1263: 1258: 1239: 1218: 1212: 1193: 1186:al-Khwārizmī 1179: 1153: 1125: 1098: 1059: 1014: 1006:Frankenstein 1004: 1001:Mary Shelley 998: 972: 957: 956: 948:Brazen Heads 937: 927: 925: 901: 892: 857: 846: 807: 779: 764: 746: 742: 740: 677: 672:2020–present 619:Soviet Union 599:Eastern Bloc 496: 329: 283:Chinese room 172:Applications 27: 15: 13754:18 November 13743:"Reasoning" 13481:11693/24987 13043:Newquist HP 12641:Rochester N 12581:17 December 12077:Haugeland J 11910:AI Magazine 11659:AI Magazine 11590:Berlinski D 11480:Montague PR 11151:10 December 10713:AI Magazine 10611:Christian B 10514:CMSWire.com 10334:(6): 1–35. 10180:(1): 3–12. 10116:CB Insights 9940:Murgia 2023 9232:End of the 8840:Brooks 1990 8828:Brooks 1990 8394:Reiter 1978 8365:Minsky 1974 8119:Searle 1980 7793:Brooks 2002 7601:Turkle 1984 7473:Minsky 1967 7184:Perceptrons 6939:, Chpt: 3-6 6921:, p. 9 6820:Miller 2003 6570:, p. 3 6433:Turing 1950 6390:Turing Test 6379:Saygin 2000 6300:, p. 3 6114:, p. 9 5987:, chapter 5 5985:Hobbes 1651 5975:, p. 6 5952:, p. 6 5929:Bonner 1985 5917:Bonner 2007 5827:Butler 1948 5766:Levitt 2000 5634:Butler 1863 5610:Goethe 1890 5538:Linden 2003 5502:Bibliotheke 5257:and others. 5244:Minsky 1986 5222:Actor model 5218:Carl Hewitt 5143:Paul Werbos 5105:Kolata 1982 5078:Lakoff 1987 4716:cybernetics 4659:John Searle 4542:August 2024 4325:transformer 4226:Peter Thiel 4006:Brad Rutter 3848:Moore's law 3836:Deep Blue's 3761:economist's 3745:Judea Pearl 3708:mathematics 3657:informatics 3630:data mining 3613:HP Newquist 3484:(i.e., the 3463:Alan Turing 3403:Lofti Zadeh 3399:Fuzzy logic 3391:probability 3387:Judea Pearl 3304:situated AI 3296:Nouvelle AI 3265:symbolic AI 3139:required. 3057:IntelliCorp 2948:Keith Clark 2795:Peter Wason 2740: [ 2720:unification 2627:John Searle 2619:instinctive 2346:program at 2328:project MAC 2283:H. A. Simon 2235:Perceptrons 2222:symbolic AI 2190:(1960) and 2139:symbolic AI 2105:David Waltz 2025:'s program 1986:, like the 1909:behaviorism 1754:Whitehead's 1713: 1958 1595:teleprinter 1591:Turing Test 1581:Turing test 1575:Turing Test 1570:Turing test 1549:Alan Turing 1537:cybernetics 1497:Alan Turing 1461:Alan Turing 1453:Konrad Zuse 1319:'s system, 1215:Ramon Llull 1208:Duns Scotus 1132:brazen head 1128:Roger Bacon 1011:Karel Čapek 908:Propoetides 876:Argonautica 859:Bibliotheke 749:) began in 642:before 1950 568:Video games 312:Turing test 288:Friendly AI 59:Major goals 13801:Categories 13510:Moor (2003 13358:Russell SJ 13330:Russell SJ 13321:29 October 13316:fano.co.uk 13198:17 October 13176:17 October 13155:10 January 13114:16 October 12953:16 October 12858:16 October 12766:Lovelace A 12703:McCarthy J 12694:16 October 12678:Meltzer BJ 12670:McCarthy J 12661:16 October 12637:McCarthy J 12628:16 October 12604:16 October 12527:Philosophy 12377:Kurzweil R 12249:Kahneman D 12009:16 October 11823:Copeland J 11812:Couturat L 11743:16 October 11699:10 October 11433:1113410915 11378:Nilsson NJ 11208:Nilsson NJ 11146:www.ft.com 11133:1102437035 10978:McCarthy J 10959:McCarthy J 10949:27 January 10877:28 January 10687:28 January 10636:1233266753 10519:28 January 10455:2303.12712 10400:References 9922:Gates 2023 9917:Clark 2023 9609:Quoted in 9485:, chpt. 2. 9361:Olsen 2006 9349:Olsen 2004 8888:Pearl 1988 8406:Clark 1977 8379:Hayes 1981 8206:Colby 1974 8144:Quoted in 8131:Quoted in 8020:Lucas 1961 7851:Quoted in 7662:Haigh 2023 7457:Simon 1965 7232:Quoted in 6691:Quoted in 6501:See also: 6222:Quoted in 5801:Quoted in 5393:deep fakes 5230:Doyle 1983 5113:Maker 2006 5097:McCarthy's 5038:chatterbot 4496:Regulation 4478:Employment 4440:Healthcare 4366:Bill Gates 4268:Sam Altman 4259:Larry Page 4228:and later 4218:Shane Legg 4154:ProPublica 4059:perceptron 4038:, won the 3944:developed 3942:Fei-Fei Li 3914:See also: 3704:statistics 3615:stated in 3555:The term " 3545:statistics 3349:logic and 3347:McCarthy's 3332:David Marr 3276:Yann LeCun 3168:perception 2930:Ray Reiter 2868:Feigenbaum 2819:McCarthy's 2782:and their 2716:resolution 2688:published 2686:Weizenbaum 2599:John Lucas 2591:See also: 2575:tanks and 2573:autonomous 2517:See also: 2449:: In 1972 2431:horsepower 2232:1969 book 2154:perceptron 2133:Perceptron 1958:heuristics 1932:Approaches 1746:J. C. Shaw 1200:scholastic 983:homunculus 932:Paracelsus 833:Precursors 624:Yugoslavia 586:By country 317:Regulation 271:Philosophy 226:Healthcare 221:Government 123:Approaches 18:See also: 13730:895659909 13703:0026-4423 13667:8 October 13605:8 October 13503:7 January 13442:20 August 13410:CiteSeerX 13394:Samuel AL 13230:249625842 13124:Nilsson N 13098:246584055 13065:313139906 13036:246968117 12985:245755104 12937:Moravec H 12891:223353010 12785:29 August 12682:Mitchie D 12645:Shannon C 12613:Markoff J 12556:Luger G, 12505:(1973), " 12332:158433736 12318:: 15–25, 12303:143452957 12253:Tversky A 12239:30 August 12223:225590743 12201:(1999) , 12190:Leviathan 12099:Hawkins J 12068:0001-0782 11987:22 August 11966:Dreyfus H 11920:Dreyfus H 11874:Crevier D 11834:8 October 11692:The Press 11673:30 August 11577:195704643 11472:Schultz W 11345:811491744 11273:1573-0964 11164:. Crown. 11092:Moravec H 11015:1522-9602 10733:2371-9621 10575:150700981 10567:2522-5839 10412:, Brill, 10383:: 80–89. 10145:: 44–56. 9912:Marr 2023 9579:Lohr 2016 9373:AI effect 8238:and see 7915:Howe 1994 7549:Howe 1994 6576:, Chap. 5 6493:, Chap. 5 6429:See also 6306:, Chap. 5 6075:Rose 1946 5694:Nick 2005 5385:copyright 5301:gigaflops 5297:Deep Blue 5172:AI winter 5008:Heidegger 4880:real time 4800:memistors 4562:AlphaZero 4349:released 4341:released 4329:attention 4280:Anthropic 4274:In 2021, 4243:In 2012, 4234:AI safety 4230:Elon Musk 4191:narrow AI 4026:In 2012, 3990:quiz show 3987:Jeopardy! 3932:released 3878:In 2002, 3816:Deep Blue 3728:narrow AI 3716:economics 3669:AI Winter 3576:Symbolics 3557:AI winter 3551:AI winter 3517:AlphaZero 3505:TD-Gammon 3451:Thorndike 3397:into AI. 3371:thesis". 3280:Bell Labs 3274:In 1990, 3253:Rumelhart 3162:Although 3117:parsimony 3081:scruffies 3049:Symbolics 2983:knowledge 2923:Pat Hayes 2893:inherited 2579:systems. 2566:in 1969, 2519:AI winter 2435:increases 2314:Financing 1946:algorithm 1732:In 1955, 1599:plausible 1525:neurology 1473:Atanasoff 1451:(such as 1325:Whitehead 1268:reckoning 1259:Leviathan 1195:algorithm 1172:syllogism 1168:Aristotle 1074:Al-Jazari 1054:Al-Jazari 1045:Automaton 894:Pygmalion 884:Argonauts 874:. In the 868:automaton 827:AI surged 803:AI Winter 751:antiquity 667:2010–2019 662:2000–2009 657:1990–1999 652:1980–1989 647:1950–1979 347:AI winter 248:Military 111:AI safety 13788:10952283 13766:(1976), 13738:Wason PC 13677:Turing A 13627:15 March 13569:: 1–10, 13559:Simon HA 13519:(1980), 13517:Searle J 13386:20190474 13364:(2021). 13362:Norvig P 13336:(2003), 13334:Norvig P 13210:(1988), 13074:(1999), 13045:(1994), 13014:Newell A 12939:(1976), 12910:8 August 12900:(2001), 12898:Minsky M 12869:(1986), 12867:Minsky M 12844:(1974), 12842:Minsky M 12835:16924756 12813:(1969), 12811:Papert S 12807:Minsky M 12797:(1967), 12795:Minsky M 12768:(1843), 12734:52197627 12705:(1974). 12684:(eds.), 12674:Hayes PJ 12560:(2004). 12550:55408480 12476:19981533 12411:(1987), 12409:Lakoff G 12401:71826177 12379:(2005), 12369:17837639 12295:17835457 12187:(1651), 12185:Hobbes T 12161:Hewitt C 12153:48871099 12133:(1949), 12123:61273290 12079:(1985). 11922:(1965), 11876:(1993). 11825:(2000), 11814:(1901), 11782:36947398 11723:8 August 11683:Butler S 11614:46890682 11592:(2000), 11542:15 March 11462:(2022). 11402:(1962), 11374:Rosen CA 11364:15 April 11320:: 29–37. 11281:10442035 11253:Synthese 11210:(1984). 11084:12639696 11055:(2003). 11053:Miller G 10906:51210362 10851:26017442 10805:15 March 10759:15 March 10719:(1): 6. 10613:(2020). 10438:(2002), 10436:Brooks R 10159:30617339 10072:26017442 9986:26185243 9927:Lee 2024 9337:CNN 2006 9293:NRC 1999 9143:crisis: 8624:NRC 1999 7984:NRC 1999 7972:NRC 1999 7889:NRC 1999 6117:and see 5564:, GOLEM. 5321:ImageNet 4987:Gulf War 4960:NRC 1999 4836:of 1956. 4808:IBM 1620 4708:McCarthy 4576:See also 4566:policies 4554:DeepMind 4370:ChatGPT4 4347:DeepMind 4236:and the 4210:DeepMind 4174:fairness 3979:big data 3954:word2vec 3946:ImageNet 3896:DeepMind 3860:big data 3574:made by 3188:robotics 3176:learning 3172:robotics 3043:for the 2864:Kowalski 2860:McCarthy 2839:required 2650:know how 2623:know how 2615:embodied 2531:and the 2457:'s 1971 2444:and the 2410:Problems 2336:McCarthy 2307:Magazine 2273:Optimism 2230:Papert's 2192:MADALINE 2184:Ted Hoff 1992:Stanford 1980:Minsky's 1656:and the 1469:Colossus 1181:Elements 1062:automata 1039:Automata 882:and the 767:workshop 703:Category 594:Bulgaria 553:Internet 464:Software 455:Software 432:Hardware 370:Glossary 364:Glossary 342:Progress 337:Timeline 297:Takeover 258:Projects 231:Industry 194:Finance 184:Deepfake 134:Symbolic 106:Robotics 81:Planning 13432:2126705 13208:Pearl J 12522:Lucas J 12454:Lenat D 12349:Bibcode 12341:Science 12265:Bibcode 12257:Science 11958:5056816 11802:17 June 11774:5936301 11737:CNN.com 11506:9054347 11485:Science 11476:Dayan P 11360:: 83–86 10988:. 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