Timeline of artificial intelligence

Short description: none

See also: History of artificial intelligence and Progress in artificial intelligence

The training computation of notable AI systems through time

This is a timeline of artificial intelligence, also known as synthetic intelligence.

## Contents

* 1 Antiquity, Classical and Medieval eras
* 2 1600–1900
* 3 20th century
* 3.1 1901–1950
* 3.2 1950s
* 3.3 1960s
* 3.4 1970s
* 3.5 1980s
* 3.6 1990s
* 4 21st century
* 4.1 2000s
* 4.2 2010s
* 4.3 2020s
* 5 See also
* 6 Notes
* 7 References
* 8 Sources
* 9 Further reading
* 10 External links

## Antiquity, Classical and Medieval eras

Date  | Development

|

Antiquity  | Greek myths of Hephaestus and Pygmalion incorporated the idea of intelligent automata (such as Talos) and artificial beings (such as Galatea and Pandora).[1]
Sacred mechanical statues built in Egypt and Greece were believed to be capable of wisdom and emotion. Hermes Trismegistus would write, "They have 'sensus' and 'spiritus'... by discovering the true nature of the gods, man has been able to reproduce it."[2]
10th century BC  | Yan Shi presented King Mu of Zhou with mechanical men that were capable of moving their bodies independently.[3][4]
384 BC–322 BC
3rd century BC
1st century  | Hero of Alexandria created mechanical men and other automatons.[5] He produced what may have been "the world's first practical programmable machine:"[6] an automatic theatre.
260  | Porphyry wrote Isagogê which categorized knowledge and logic, including a drawing of what would later be called a "semantic net".[7]
~800  | Jabir ibn Hayyan developed the Arabic alchemical theory of Takwin, the artificial creation of life in the laboratory, up to and including human life.[8]
9th Century
al-Khwarizmi wrote textbooks with precise step-by-step methods for arithmetic and algebra, used in Islam, India and Europe until the 16th century. The word "algorithm" is derived from his name.[9]
1206  | Ismail al-Jazari created a programmable orchestra of mechanical human beings.[10]
1275  | Ramon Llull, Mallorcan theologian, invents the Ars Magna, a tool for combining concepts mechanically based on an Arabic astrological tool, the Zairja. Llull described his machines as mechanical entities that could combine basic truth and facts to produce advanced knowledge. The method was further developed by Gottfried Wilhelm Leibniz in the 17th century.[11]
~1500  | Paracelsus claimed to have created an artificial man out of magnetism, sperm, and alchemy.[12]
~1580  | Rabbi Judah Loew ben Bezalel of Prague is said to have invented the Golem, a clay man brought to life.[13]

## 1600–1900

Date  | Development

|

1620  | Francis Bacon developed empirical theory of knowledge and introduced inductive logic in his work Novum Organum, a play on Aristotle's title Organon.[14][15][16]
1623  | Wilhelm Schickard drew a calculating clock on a letter to Kepler. This will be the first of five unsuccessful attempts at designing a direct entry calculating clock in the 17th century (including the designs of Tito Burattini, Samuel Morland and René Grillet).[lower-alpha 1]
1641  | Thomas Hobbes published Leviathan and presented a mechanical, combinatorial theory of cognition. He wrote "...for reason is nothing but reckoning".[17][18]
1642  | Blaise Pascal invented a mechanical calculator,[lower-alpha 2] the first digital calculating machine.[19]
1647  | René Descartes proposed that bodies of animals are nothing more than complex machines (but that mental phenomena are of a different "substance").[20]
1654  | Blaise Pascal described how to find expected values in probability, in 1662 Antoine Arnauld published a formula to find the maximum expected value, and in 1663, Gerolamo Cardano's solution to the same problems was published 116 years after it was written. The theory of probability was further developed by Jacob Bernoulli and Pierre-Simon Laplace in the 18th century.[21] Probability theory would become central to AI and machine learning from the 1990s onward.
1672  | Gottfried Wilhelm Leibniz improved the earlier machines, making the Stepped Reckoner to do multiplication and division.[22]
1676  | Leibniz derived the chain rule.[23] The rule is used by AI to train neural networks, for example the backpropagation algorithm uses the chain rule.[6]
1679  | Leibniz developed a universal calculus of reasoning (alphabet of human thought) by which arguments could be decided mechanically. It assigned a specific number to each object in the world, as a prelude to an algebraic solution to all possible problems.[24]
1726  | Jonathan Swift published Gulliver's Travels, which includes this description of the Engine, a machine on the island of Laputa: "a Project for improving speculative Knowledge by practical and mechanical Operations" by using this "Contrivance", "the most ignorant Person at a reasonable Charge, and with a little bodily Labour, may write Books in Philosophy, Poetry, Politicks, Law, Mathematicks, and Theology, with the least Assistance from Genius or study."[25] The machine is a parody of Ars Magna, one of the inspirations of Gottfried Wilhelm Leibniz' mechanism.
1738  | Daniel Bernoulli introduces the concept of "utility", a generalization of probability, the basis of economics and decision theory, and the mathematical foundation for the way AI represents the "goals" of intelligent agents.[26]
1739  | David Hume described induction, the logical method of learning generalities from examples.[16]
1750  | Julien Offray de La Mettrie published L'Homme Machine, which argued that human thought is strictly mechanical.[27]
1763  | Thomas Bayes's work An Essay Towards Solving a Problem in the Doctrine of Chances, published two years after his death, laid the foundations of Bayes' theorem and used in modern AI in Bayesian networks.[21]
1769  | Wolfgang von Kempelen built and toured with his chess-playing automaton, The Turk, which Kempelen claimed could defeat human players.[28] The Turk was later shown to be a hoax, involving a human chess player.
1795–1805  | The simplest kind of artificial neural network is the linear network. It has been known for over two centuries as the method of least squares or linear regression. It was used as a means of finding a good rough linear fit to a set of points by Adrien-Marie Legendre (1805)[29] and Carl Friedrich Gauss (1795)[30] for the prediction of planetary movement.[6][31]
1805  | Joseph Marie Jacquard created a programmable loom, based on earlier inventions by Basile Bouchon (1725), Jean-Baptiste Falcon (1728) and Jacques Vaucanson (1740).[32] Replaceable punched cards controlled sequences of operations in the process of manufacturing textiles. This may have been the first industrial software for commercial enterprises.[6]
1818  | Mary Shelley published the story of Frankenstein; or the Modern Prometheus, a fictional consideration of the ethics of creating sentient beings.[33]
1822–1859  | Charles Babbage & Ada Lovelace worked on programmable mechanical calculating machines.[34]
1837  | The mathematician Bernard Bolzano made the first modern attempt to formalize semantics.[35]
1854  | George Boole set out to "investigate the fundamental laws of those operations of the mind by which reasoning is performed, to give expression to them in the symbolic language of a calculus", inventing Boolean algebra.[36]
1863  | Samuel Butler suggested that Darwinian evolution also applies to machines and speculates that they will one day become conscious and eventually supplant humanity.[37]

## 20th century

### 1901–1950

Date  | Development

|

1910-1913  | Bertrand Russell and Alfred North Whitehead published Principia Mathematica, which showed that all of elementary mathematics could be reduced to mechanical reasoning in formal logic.[38]
1912-1914
1923  | Karel Čapek's play R.U.R. (Rossum's Universal Robots) opened in London. This is the first use of the word "robot" in English.[39]
1920–1925  | Wilhelm Lenz and Ernst Ising created and analyzed the Ising model (1925)[40] which can be viewed as the first artificial recurrent neural network (RNN) consisting of neuron-like threshold elements.[6] In 1972, Shun'ichi Amari made this architecture adaptive.[41][6]
1920s and 1930s  | Ludwig Wittgenstein's Tractatus Logico-Philosophicus (1921) inspires Rudolf Carnap and the logical positivists of the Vienna Circle to use formal logic as the foundation of philosophy. However, Wittgenstein's later work in the 1940s demonstrates that context-free symbolic logic is incoherent without human interpretation.
1931  | Kurt Gödel encoded mathematical statements and proofs as integers and showed that there are true theorems that are unprovable by any consistent theorem-proving machine. Thus, "he identified fundamental limits of algorithmic theorem proving, computing, and any type of computation-based AI,",[6] laying the foundations of theoretical computer science and AI theory.
1935
1936  | Konrad Zuse filed his patent application for a program-controlled computer.[42]
1937  | Alan Turing published "On Computable Numbers",[43] which laid the foundations of the modern theory of computation by introducing the Turing machine, a physical interpretation of "computability". He used it to confirm Gödel by proving that the halting problem is undecidable.
1940  | Edward Condon displayed Nimatron, a digital machine that played Nim perfectly.
1941  | Konrad Zuse built the first working program-controlled general-purpose computer.[44]
1943  | Warren Sturgis McCulloch and Walter Pitts publish "A Logical Calculus of the Ideas Immanent in Nervous Activity", the first mathematical description of an artificial neural networks.[45]
Arturo Rosenblueth, Norbert Wiener and Julian Bigelow coin the term "cybernetics". Wiener's popular book by that name was published in 1948.
1945  | Game theory, which would prove invaluable in the progress of AI, was introduced with the 1944 paper "Theory of Games and Economic Behavior" by mathematician John von Neumann and economist Oskar Morgenstern.
Vannevar Bush published "As We May Think" (The Atlantic Monthly, July 1945), a prescient vision of the future in which computers assist humans in many activities.
1948  | Alan Turing produces the "Intelligent Machinery" report, regarded as the first manifesto of Artificial Intelligence. It introduces many concepts, including the logic-based approach to problem-solving, that intellectual activity consists mainly of various kinds of search, and a discussion of machine learning in which he anticipates the Connectionism AI approach.[46]
John von Neumann (quoted by Edwin Thompson Jaynes) in response to a comment at a lecture that it was impossible for a machine (at least ones created by humans) to think: "You insist that there is something a machine cannot do. If you will tell me precisely what it is that a machine cannot do, then I can always make a machine which will do just that!". Von Neumann was presumably alluding to the Church–Turing thesis, which states that any effective procedure can be simulated by a (generalized) computer.
1949  | Donald O. Hebb develops Hebbian theory, a possible algorithm for learning in neural networks.[47]

### 1950s

Date  | Development

|

1950  | Alan Turing published "Computing Machinery and Intelligence", which proposes the Turing test as a measure of machine intelligence and answered all of the most common objections to the proposal "machines can think".[48]
Claude Shannon published a detailed analysis of chess playing as search.[49]
Isaac Asimov published his Three Laws of Robotics.[50]
1951  | The first working AI programs were written in 1951 to run on the Ferranti Mark 1 machine of the University of Manchester: A checkers-playing program written by Christopher Strachey and a chess-playing program written by Dietrich Prinz.[47]
1952–1962  | Arthur Samuel (IBM) wrote the first game-playing program, for checkers (draughts), to achieve sufficient skill to challenge a respectable amateur.[51] His first checkers-playing program was written in 1952, and in 1955, he created a version that learned to play.[52][53]
1956  | The Dartmouth College summer AI conference is organized by John McCarthy, Marvin Minsky, Nathan Rochester of IBM and Claude Shannon. McCarthy coined the term artificial intelligence for the conference.[54][55]
The first demonstration of the Logic Theorist (LT) written by Allen Newell, Cliff Shaw and Herbert A. Simon (Carnegie Institute of Technology, now Carnegie Mellon University or CMU). This is often called the first AI program, though Samuel's checkers program also has a strong claim. This program has been described as the first deliberately engineered to perform automated reasoning, and would eventually prove 38 of the first 52 theorems in Russell and Whitehead's Principia Mathematica, and find new and more elegant proofs for some.[56] Simon said that they had "solved the venerable mind–body problem, explaining how a system composed of matter can have the properties of mind".[57]
1958  | John McCarthy (Massachusetts Institute of Technology or MIT) invented the Lisp programming language.[52]
Herbert Gelernter and Nathan Rochester (IBM) described a theorem prover in geometry.[52] It exploited a semantic model of the domain in the form of diagrams of "typical" cases. |-  | Teddington Conference on the Mechanization of Thought Processes was held in the UK and among the papers presented were John McCarthy's "Programs with Common Sense" (which proposed the Advice taker application as a primary research goal)[52] Oliver Selfridge's "Pandemonium", and Marvin Minsky's "Some Methods of Heuristic Programming and Artificial Intelligence".
1959  | The General Problem Solver (GPS) was created by Newell, Shaw and Simon while at CMU.[52]
John McCarthy and Marvin Minsky founded the MIT AI Lab.[52]
Late 1950s, early 1960s  | Margaret Masterman and colleagues at University of Cambridge design semantic nets for machine translation.

### 1960s

Date  | Development

|

1960s  | Ray Solomonoff lays the foundations of a mathematical theory of AI, introducing universal Bayesian methods for inductive inference and prediction.
1960  | "Man–Computer Symbiosis" by J.C.R. Licklider.
1961  | James Slagle (PhD dissertation, MIT) wrote (in Lisp) the first symbolic integration program, SAINT, which solved calculus problems at the college-freshman level.
In Minds, Machines and Gödel, John Lucas[58] denied the possibility of machine intelligence on logical or philosophical grounds. He referred to Kurt Gödel's result of 1931: sufficiently powerful formal systems are either inconsistent or allow for formulating true theorems unprovable by any theorem-proving AI deriving all provable theorems from the axioms. Since humans are able to "see" the truth of such theorems, machines were deemed inferior.
Unimation's industrial robot Unimate worked on a General Motors automobile assembly-line.
1963  | Thomas Evans' program, ANALOGY, written as part of his PhD work at MIT, demonstrated that computers can solve the same analogy problems as are given on IQ tests.
Edward Feigenbaum and Julian Feldman published Computers and Thought, the first collection of articles about artificial intelligence.[59][60][61][62]
Leonard Uhr and Charles Vossler published "A Pattern Recognition Program That Generates, Evaluates, and Adjusts Its Own Operators", which described one of the first machine-learning programs that could adaptively acquire and modify features and thereby overcome the limitations of simple perceptrons of Rosenblatt.
1964  | Danny Bobrow's dissertation at MIT (technical report #1 from MIT's AI group, Project MAC), shows that computers can understand natural language well enough to solve algebra word problems correctly.
In Stanisław Lem's essay-collection Summa Technologiae Lem discusses "intellectronics" (AI).
Bertram Raphael's MIT dissertation on the SIR program demonstrates the power of a logical representation of knowledge for question-answering systems.
1965  | In the Soviet Union, Alexey Ivakhnenko and Valentin Lapa develop the first deep-learning algorithm for multilayer perceptrons.[63][64][6]
Lotfi A. Zadeh at U.C. Berkeley publishes his first paper introducing fuzzy logic, "Fuzzy Sets" (Information and Control 8: 338–353).
J. Alan Robinson invents a mechanical proof procedure, the Resolution Method, which allows programs to work efficiently with formal logic as a representation language.
Joseph Weizenbaum (MIT) builds ELIZA, an interactive program that carries on a dialogue in English language on any topic. It was a popular toy at AI centers on the ARPANET when a version that "simulated" the dialogue of a psychotherapist was programmed.
Edward Feigenbaum initiates Dendral, a ten-year effort to develop software to deduce the molecular structure of organic compounds using scientific instrument data. It was the first expert system.
1966  | Ross Quillian (PhD dissertation, Carnegie Inst. of Technology, now CMU) demonstrates semantic nets.
Machine Intelligence[65] workshop at Edinburgh – the first of an influential annual series organized by Donald Michie and others.
Negative report on machine-translation kills much work in natural language processing (NLP) for many years.
Dendral program (Edward Feigenbaum, Joshua Lederberg, Bruce Buchanan, Georgia Sutherland at Stanford University) demonstrated to interpret mass spectra of organic chemical compounds. First successful knowledge-based program for scientific reasoning.
1967
1968  | Joel Moses (PhD work at MIT) demonstrates the power of symbolic reasoning for integration problems in the Macsyma program. First successful knowledge-based program in mathematics.
Richard Greenblatt (programmer) at MIT builds a knowledge-based chess-playing program, Mac Hack, that was good enough to achieve a class-C rating in tournament play.
Wallace and Boulton's program, Snob (Comp.J. 11(2) 1968), for unsupervised classification (clustering) uses the Bayesian minimum message length criterion, a mathematical realisation of Occam's razor.
1969  | Stanford Research Institute (SRI): Shakey the robot, demonstrates combining animal locomotion, perception and problem-solving.
Roger Schank (Stanford) defines conceptual dependency model for natural language understanding. Later developed (in PhD dissertations at Yale University) for use in story understanding by Robert Wilensky and Wendy Lehnert, and for use in understanding memory by Janet Kolodner.
Yorick Wilks (Stanford) developed the semantic-coherence view of language called Preference Semantics, embodied in the first semantics-driven mac)hine-translation program, and the basis of many PhD dissertations since (such as those of Bran Boguraev and David Carter at Cambridge.
First International Joint Conference on Artificial Intelligence (IJCAI) held at Stanford.
Marvin Minsky and Seymour Papert publish Perceptronss, demonstrating previously unrecognized limits of this feed-forward two-layered structure. This book is considered by some to mark the beginning of the AI winter of the 1970s, a failure of confidence and funding for AI. However, by the time the book came out, methods for training multilayer perceptrons by deep learning were already known (Alexey Ivakhnenko and Valentin Lapa, 1965; Shun'ichi Amari, 1967).[6] Significant progress in the field continued (see below).
McCarthy and Hayes start the discussion about the frame problem with their essay "Some Philosophical Problems from the Standpoint of Artificial Intelligence".

### 1970s

Date  | Development

|

Early 1970s  | Jane Robinson and Don Walker established an influential Natural Language Processing group at SRI.[66]
1970  | Seppo Linnainmaa publishes the reverse mode of automatic differentiation. This method became later known as backpropagation, and is heavily used to train artificial neural networks.[67]
Jaime Carbonell (Sr.) developed SCHOLAR, an interactive program for computer-assisted instruction based on semantic nets as the representation of knowledge.
Bill Woods described Augmented Transition Networks (ATNs) as a representation for natural language understanding.
Patrick Winston's PhD program, ARCH, at MIT, learned concepts from examples in the world of children's blocks.
1971  | Terry Winograd's PhD thesis (MIT) demonstrated the ability of computers to understand English sentences in a restricted world of children's blocks, in a coupling of his language understanding program, SHRDLU, with a robot arm that carried out instructions typed in English.
Work on the Boyer-Moore theorem prover started in Edinburgh.[68]
1972  | Prolog programming language developed by Alain Colmerauer.
Earl Sacerdoti developed one of the first hierarchical planning programs, ABSTRIPS.
1973  | The Assembly Robotics Group at University of Edinburgh builds Freddy Robot, capable of using visual perception to locate and assemble models. (See Edinburgh Freddy Assembly Robot: a versatile computer-controlled assembly system.)
The Lighthill report gives a largely negative verdict on AI research in Great Britain and forms the basis for the decision by the British government to discontinue support for AI research in all but two universities.
1974  | Ted Shortliffe's PhD dissertation on the MYCIN program (Stanford) demonstrated a very practical rule-based approach to medical diagnoses, even in the presence of uncertainty. While it borrowed from DENDRAL, its own contributions strongly influenced the future of expert system development, especially commercial systems.
1975  | Earl Sacerdoti developed techniques of partial-order planning in his NOAH system, replacing the previous paradigm of search among state space descriptions. NOAH was applied at SRI International to interactively diagnose and repair electromechanical systems.
Austin Tate developed the Nonlin hierarchical planning system, able to search a space of partial plans characterised as alternative approaches to the underlying goal structure of the plan.
Marvin Minsky published his widely read and influential article on Frames as a representation of knowledge, in which many ideas about schemas and semantic links are brought together.
The Meta-Dendral learning program produced new results in chemistry (some rules of mass spectrometry), the first scientific discoveries by a computer to be published in a refereed journal.
Mid-1970s  | Barbara Grosz (SRI) established limits to traditional AI approaches to discourse modeling. Subsequent work by Grosz, Bonnie Webber and Candace Sidner developed the notion of "centering", used in establishing focus of discourse and anaphoric references in Natural language processing.
David Marr and MIT colleagues describe the "primal sketch" and its role in visual perception.
1976  | Douglas Lenat's AM program (Stanford PhD dissertation) demonstrated the discovery model (loosely guided search for interesting conjectures).
Randall Davis demonstrated the power of meta-level reasoning in his PhD dissertation at Stanford.
Stevo Bozinovski and Ante Fulgosi introduced transfer learning method in artificial intelligence, based on the psychology of learning.[69][70]
1978  | Tom Mitchell, at Stanford, invented the concept of Version spaces for describing the search space of a concept formation program.
Herbert A. Simon wins the Nobel Prize in Economics for his theory of bounded rationality, one of the cornerstones of AI known as "satisficing".
The MOLGEN program, written at Stanford by Mark Stefik and Peter Friedland, demonstrated that an object-oriented programming representation of knowledge can be used to plan gene-cloning experiments.
1979  | Bill VanMelle's PhD dissertation at Stanford demonstrated the generality of MYCIN's representation of knowledge and style of reasoning in his EMYCIN program, the model for many commercial expert system "shells".
Jack Myers and Harry Pople at University of Pittsburgh developed INTERNIST, a knowledge-based medical diagnosis program based on Dr. Myers' clinical knowledge.
Cordell Green, David Barstow, Elaine Kant and others at Stanford demonstrated the CHI system for automatic programming.
The Stanford Cart, built by Hans Moravec, becomes the first computer-controlled, autonomous vehicle when it successfully traverses a chair-filled room and circumnavigates the Stanford AI Lab.
BKG, a backgammon program written by Hans Berliner at CMU, defeats the reigning world champion (in part via luck).
Drew McDermott and Jon Doyle at MIT, and John McCarthy at Stanford, begin publishing work on non-monotonic logics and formal aspects of truth maintenance.
Late 1970s  | Stanford's SUMEX-AIM resource, headed by Ed Feigenbaum and Joshua Lederberg, demonstrates the power of the ARPAnet for scientific collaboration.

### 1980s

Date  | Development

|

1980s  | Lisp machines developed and marketed. First expert system shells and commercial applications.
1980  | First National Conference of the American Association for Artificial Intelligence (AAAI) held at Stanford.
1981  | Danny Hillis designs the connection machine, which utilizes parallel computing to bring new power to AI, and to computation in general. (Later founds Thinking Machines Corporation)
Stevo Bozinovski and Charles Anderson carried out the first concurrent programming (task parallelism) in neural network research. A program, "CAA Controller," written and executed by Bozinovski, interacts with the program "Inverted Pendulum Dynamics" written and executed by Anderson, using VAX/VMS mailboxes as a way of inter-program communication. The CAA controller learns to balance the simulated inverted pendulum.[71][72][73]
1982  | The Fifth Generation Computer Systems project (FGCS), an initiative by Japan's Ministry of International Trade and Industry, begun in 1982, to create a "fifth generation computer" (see history of computing hardware) which was supposed to perform many calculations utilizing massive parallelism.
1983  | John Laird and Paul Rosenbloom, working with Allen Newell, complete CMU dissertations on Soar (program).
James F. Allen invents the Interval Calculus, the first widely used formalization of temporal events.
Mid-1980s  | Neural Networks become widely used with the Backpropagation algorithm, also known as the reverse mode of automatic differentiation published by Seppo Linnainmaa in 1970 and applied to neural networks by Paul Werbos.
1985  | The autonomous drawing program, AARON, created by Harold Cohen, is demonstrated at the AAAI National Conference (based on more than a decade of work, and with subsequent work showing major developments).
1986  | The team of Ernst Dickmanns at Bundeswehr University of Munich builds the first robot cars, driving up to 55 mph on empty streets.
1987  | Marvin Minsky published The Society of Mind, a theoretical description of the mind as a collection of cooperating agents. He had been lecturing on the idea for years before the book came out (cf. Doyle 1983).[74]
Around the same time, Rodney Brooks introduced the subsumption architecture and behavior-based robotics as a more minimalist modular model of natural intelligence; Nouvelle AI.
Commercial launch of generation 2.0 of Alacrity by Alacritous Inc./Allstar Advice Inc. Toronto, the first commercial strategic and managerial advisory system. The system was based upon a forward-chaining, self-developed expert system with 3,000 rules about the evolution of markets and competitive strategies and co-authored by Alistair Davidson and Mary Chung, founders of the firm with the underlying engine developed by Paul Tarvydas. The Alacrity system also included a small financial expert system that interpreted financial statements and models.[75]
1989  | The development of metal–oxide–semiconductor (MOS) Very-large-scale integration (VLSI), in the form of complementary MOS (CMOS) technology, enabled the development of practical artificial neural network (ANN) technology in the 1980s. A landmark publication in the field was the 1989 book Analog VLSI Implementation of Neural Systems by Carver A. Mead and Mohammed Ismail.[76]
Dean Pomerleau at CMU created ALVINN (An Autonomous Land Vehicle in a Neural Network), which was used in the Navlab program.

### 1990s

Date  | Development

|

1990s  | Major advances in all areas of AI, with significant demonstrations in machine learning, intelligent tutoring, case-based reasoning, multi-agent planning, scheduling, uncertain reasoning, data mining, natural language understanding and translation, vision, virtual reality, games, and other topics.
Early 1990s  | TD-Gammon, a backgammon program written by Gerry Tesauro, demonstrates that reinforcement (learning) is powerful enough to create a championship-level game-playing program by competing favorably with world-class players.
1991  | DART scheduling application deployed in the first Gulf War paid back DARPA's investment of 30 years in AI research.[77]
1992
1993  | Ian Horswill extended behavior-based robotics by creating Polly, the first robot to navigate using vision and operate at animal-like speeds (1 meter/second).
Rodney Brooks, Lynn Andrea Stein and Cynthia Breazeal started the widely publicized MIT Cog project with numerous collaborators, in an attempt to build a humanoid robot child in just five years.
ISX corporation wins "DARPA contractor of the year"[78] for the Dynamic Analysis and Replanning Tool (DART), which reportedly repaid the US government's entire investment in AI research since the 1950s.[79]
1994  | Lotfi A. Zadeh at U.C. Berkeley creates "soft computing"[80] and builds a world network of research with a fusion of neural science and neural net systems, fuzzy set theory and fuzzy systems, evolutionary algorithms, genetic programming, and chaos theory and chaotic systems ("Fuzzy Logic, Neural Networks, and Soft Computing", Communications of the ACM, March 1994, Vol. 37 No. 3, pages 77–84).
With passengers on board, the twin robot cars VaMP and VITA-2 of Ernst Dickmanns and Daimler-Benz drive more than one thousand kilometers on a Paris three-lane highway in standard heavy traffic at speeds up to 130 km/h. They demonstrate autonomous driving in free lanes, convoy driving, and lane changes left and right with autonomous passing of other cars.
English draughts (checkers) world champion Tinsley resigned a match against computer program Chinook. Chinook defeated 2nd-highest-rated player, Lafferty. Chinook won the USA National Tournament by the widest margin ever.
Cindy Mason at NASA organizes the First AAAI Workshop on AI and the Environment.[81]
1995  | Cindy Mason at NASA organizes the First International IJCAI Workshop on AI and the Environment.[82]
"No Hands Across America": A semi-autonomous car drove coast-to-coast across the United States with computer-controlled steering for 2,797 miles (4,501 km) of the 2,849 miles (4,585 km). The throttle and brakes were controlled by a human driver.[83][84]
One of Ernst Dickmanns' robot cars (with robot-controlled throttle and brakes) drove more than 1000 miles from Munich to Copenhagen and back, in traffic, at up to 120 mph, occasionally executing maneuvers to pass other cars (only in a few critical situations a safety driver took over). Active vision was used to deal with rapidly changing street scenes.
1996  | Steve Grand, roboticist and computer scientist, develops and releases Creatures, a popular simulation of artificial life-forms with simulated biochemistry, neurology with learning algorithms and inheritable digital DNA.
1997  | The Deep Blue chess machine (IBM) defeats the (then) world chess champion, Garry Kasparov.
First official RoboCup football (soccer) match featuring table-top matches with 40 teams of interacting robots and over 5000 spectators.
Computer Othello program Logistello defeated the world champion, Takeshi Murakami with a score of 6–0.
1998  | Tiger Electronics' Furby is released, and becomes the first successful attempt at producing a type of AI designated for a domestic environment.
Tim Berners-Lee published his Semantic Web Road map paper.[85]
Ulises Cortés and Miquel Sànchez-Marrè organize the first Environment and AI Workshop in Europe ECAI, "Binding Environmental Sciences and Artificial Intelligence".[86][87]
Leslie P. Kaelbling, Michael L. Littman, and Anthony Cassandra introduce POMDPs and a scalable method for solving them to the AI community, jumpstarting widespread use in robotics and automated planning and scheduling[88]
1999  | Sony introduces an improved domestic robot similar to a Furby, the AIBO becomes one of the first artificially intelligent "pets" that is also autonomous.
Late 1990s  | Web crawlers and other AI-based information extraction programs become essential in widespread use of the World Wide Web.
Demonstration of an Intelligent room and Emotional Agents at MIT's AI Lab.
Initiation of work on the Oxygen architecture, which connects mobile and stationary computers in an adaptive network.

## 21st century

### 2000s

Date  | Development

|

2000  | Interactive robopets ("smart toys") become commercially available, realizing the vision of the 18th-century novelty toy makers.
Cynthia Breazeal at MIT publishes her dissertation on Sociable machines, describing Kismet (robot), with a face that expresses emotions.
The Nomad robot explores remote regions of Antarctica looking for meteorite samples.
2002  | iRobot's Roomba autonomously vacuums the floor while navigating and avoiding obstacles.
Wolfbot Future describes artificial intelligent agents based on XML with a distributed ontology.
2004  | OWL Web Ontology Language W3C Recommendation (10 February 2004).
DARPA introduces the DARPA Grand Challenge, requiring competitors to produce autonomous vehicles for prize money.
NASA's robotic exploration rovers Spirit and Opportunity autonomously navigate the surface of Mars.
2005  | Honda's ASIMO robot, an artificially intelligent humanoid robot, can walk as fast as a human, delivering trays to customers in restaurant settings.
Recommendation technology based on tracking web activity or media usage brings AI to marketing. See TiVo Suggestions.
Blue Brain is born, a project to simulate the brain at molecular detail.[89]
2006  | The Dartmouth Artificial Intelligence Conference: The Next 50 Years (AI@50) (14–16 July 2006)
2007  | Philosophical Transactions of the Royal Society, B – Biology, one of the world's oldest scientific journals, puts out a special issue on using AI to understand biological intelligence, titled Models of Natural Action Selection[90]
Checkers is solved by a team of researchers at the University of Alberta.
DARPA launches the Urban Challenge for autonomous cars to obey traffic rules and operate in an urban environment.
2008  | Cynthia Mason at Stanford presents her idea on Artificial Compassionate Intelligence, in her paper on "Giving Robots Compassion".[91]
2009
Google builds an autonomous car.[92]

### 2010s

Date  | Development

|

2010  | Microsoft launched Kinect for Xbox 360, the first gaming device to track human body movement, using just a 3D camera and infrared detection, enabling users to play their Xbox 360 wirelessly. The award-winning machine learning for human motion capture technology for this device was developed by the Computer Vision group at Microsoft Research, Cambridge.[93][94]
2011  | Mary Lou Maher and Doug Fisher organize the First AAAI Workshop on AI and Sustainability.[95]
IBM's Watson computer defeated television game show Jeopardy! champions Rutter and Jennings.
2011–2014  | Apple's Siri (2011), Google's Google Now (2012) and Microsoft's Cortana (2014) are smartphone apps that use natural language to answer questions, make recommendations and perform actions.
2012  | AlexNet, a deep learning model developed by Alex Krizhevsky, wins the ImageNet Large Scale Visual Recognition Challenge with half as many errors as the second-place winner.[96] This is a turning point in the history of AI; over the next few years, dozens of other approaches to image recognition were abandoned in favor of deep learning.[97] Krizhevsky is among the first to use GPU chips to train a deep learning network.[98]
2013  | Robot HRP-2 built by SCHAFT Inc of Japan, a subsidiary of Google, defeats 15 teams to win DARPA's Robotics Challenge Trials. HRP-2 scored 27 out of 32 points in the eight tasks needed in disaster response. Tasks are driving a vehicle, walking over debris, climbing a ladder, removing debris, walking through doors, cutting through a wall, closing valves and connecting a hose.[99]
NEIL, the Never-Ending Image Learner, is released at Carnegie Mellon University to constantly compare and analyze relationships between different images.[100]
2015  | Two techniques were developed concurrently to train very deep networks: highway network,[101] and the residual neural network (ResNet).[102] They allowed over 1000-layers-deep networks to be trained.
In January 2015, Stephen Hawking, Elon Musk, and dozens of artificial intelligence experts signed an open letter on artificial intelligence calling for research on the societal impacts of AI.[103][104]
In July 2015, an open letter to ban the development and use of autonomous weapons was signed by Hawking, Musk, Wozniak and 3,000 researchers in AI and robotics.[105]
2016  | Google DeepMind's AlphaGo (version: Lee)[106] defeated Lee Sedol 4–1. Lee Sedol is a 9-dan professional Korean Go champion who won 27 major tournaments from 2002 to 2016.[107]
2017  | Asilomar Conference on Beneficial AI was held, to discuss AI ethics and how to bring about beneficial AI while avoiding the existential risk from artificial general intelligence.
Deepstack[108] is the first published algorithm to beat human players in imperfect information games, as shown with statistical significance on heads-up no-limit poker. Soon after, the poker AI Libratus by a different research group individually defeated each of its four-human opponents—among the best players in the world—at an exceptionally high aggregated winrate, over a statistically significant sample.[109] In contrast to Chess and Go, Poker is an imperfect information game.[110]
In May 2017, Google DeepMind's AlphaGo (version: Master) beat Ke Jie, who at the time continuously held the world No. 1 ranking for two years,[111][112] winning each game in a three-game match during the Future of Go Summit.[113][114]
A propositional logic boolean satisfiability problem (SAT) solver proves a long-standing mathematical conjecture on Pythagorean triples over the set of integers. The initial proof, 200TB long, was checked by two independent certified automatic proof checkers.[115]
An OpenAI bot using machine learning played at The International 2017 Dota 2 tournament in August 2017. It won during a 1v1 demonstration game against professional Dota 2 player Dendi.[116]
Google Lens image analysis and comparison tool released in October 2017, associates millions of landscapes, artworks, products and species to their text description.
Google DeepMind revealed that AlphaGo Zero—an improved version of AlphaGo—displayed significant performance gains while using far fewer tensor processing units (as compared to AlphaGo Lee; it used the same amount of TPUs as AlphaGo Master).[106] Unlike previous versions, which learned the game by observing millions of human moves, AlphaGo Zero learned by playing only against itself. The system then defeated AlphaGo Lee 100 games to zero, and defeated AlphaGo Master 89 to 11.[106] Although unsupervised learning is a step forward, much has yet to be learned about general intelligence.[117] AlphaZero masters chess in four hours, defeating the best chess engine, StockFish 8. AlphaZero won 28 out of 100 games, and the remaining 72 games ended in a draw.
Transformer architecture was invented, which led to new kinds of large language models such as BERT by Google, followed by the generative pre-trained transformer (GPT1) type of model introduced by OpenAI.
2018  | Alibaba language processing AI outscores top humans at a Stanford University reading and comprehension test, scoring 82.44 against 82.304 on a set of 100,000 questions.[118]
The European Lab for Learning and Intelligent Systems (aka Ellis) proposed as a pan-European competitor to American AI efforts, to stave off a brain drain of talent, along the lines of CERN after World War II.[119]
Announcement of Google Duplex, a service to allow an AI assistant to book appointments over the phone. The Los Angeles Times judges the AI's voice to be a "nearly flawless" imitation of human-sounding speech.[120]
2019  | DeepMind's AlphaStar reaches Grandmaster level at StarCraft II, outperforming 99.8 percent of human players.[121]

### 2020s

This section needs to be updated. Please update this article to reflect recent events or newly available information. (September 2023)

|

The number of the public's Google searches for the term "AI" began to accelerate in 2022.

Date  | Development

|

2020  | In February 2020, Microsoft introduces its Turing Natural Language Generation (T-NLG), which is the "largest language model ever published at 17 billion parameters".[122]
In November 2020, AlphaFold 2 by DeepMind, a model that performs predictions of protein structure, wins the CASP competition.[123]
OpenAI introduces GPT-3, a state-of-the-art autoregressive language model that uses deep learning to produce a variety of computer codes, poetry and other language tasks exceptionally similar, and almost indistinguishable from those written by humans. Its capacity was ten times greater than that of the T-NLG. It was introduced in May 2020,[124] and was in beta testing in June 2020.
2022
A November 2022 class action lawsuit against Microsoft, GitHub and OpenAI alleges that GitHub Copilot, an AI-powered code editing tool trained on public GitHub repositories, violates the copyrights of the repositories' authors, noting that the tool can generate source code which matches its training data verbatim, without providing attribution.[125]
2023  | By January 2023, ChatGPT has more than 100 million users, making it the fastest-growing consumer application to date.[126]
On January 16, 2023, three artists, Sarah Andersen, Kelly McKernan, and Karla Ortiz, file a class-action copyright infringement lawsuit against Stability AI, Midjourney, and DeviantArt, claiming that these companies have infringed the rights of millions of artists by training AI tools on five billion images scraped from the web without the consent of the original artists.[127]
On January 17, 2023, Stability AI is sued in London by Getty Images for using its images in their training data without purchasing a license.[128][129]
Getty files another suit against Stability AI in a US district court in Delaware on February 6, 2023. In the suit, Getty again alleges copyright infringement for the use of its images in the training of Stable Diffusion, and further argues that the model infringes Getty's trademark by generating images with Getty's watermark.[130]
OpenAI's GPT-4 model is released in March 2023 and is regarded as an impressive improvement over GPT-3.5, with the caveat that GPT-4 retains many of the same problems of the earlier iteration.[131] Unlike previous iterations, GPT-4 is multimodal, allowing image input as well as text. GPT-4 is integrated into ChatGPT as a subscriber service. OpenAI claims that in their own testing the model received a score of 1410 on the SAT (94th percentile),[132] 163 on the LSAT (88th percentile), and 298 on the Uniform Bar Exam (90th percentile).[133]
On March 7, 2023, Nature Biomedical Engineering writes that "it is no longer possible to accurately distinguish" human-written text from text created by large language models, and that "It is all but certain that general-purpose large language models will rapidly proliferate... It is a rather safe bet that they will change many industries over time."[134]
In response to ChatGPT, Google releases in a limited capacity its chatbot Google Bard, based on the LaMDA and PaLM large language models, in March 2023.[135][136]
On March 29, 2023, a petition of over 1,000 signatures is signed by Elon Musk, Steve Wozniak and other tech leaders, calling for a 6-month halt to what the petition refers to as "an out-of-control race" producing AI systems that its creators can not "understand, predict, or reliably control".[137][138]
In May 2023, Google announces Bard's transition from LaMDA to PaLM2, a significantly more advanced language model.[139]
In the last week of May 2023, a Statement on AI Risk is signed by Geoffrey Hinton, Sam Altman, Bill Gates, and many other prominent AI researchers and tech leaders with the following succinct message: "Mitigating the risk of extinction from AI should be a global priority alongside other societal-scale risks such as pandemics and nuclear war."[140][141]
On July 9, 2023, Sarah Silverman filed a class action lawsuit against Meta and OpenAI for copyright infringement for training their large language models on millions of authors' copyrighted works without permission.[142]
In August 2023, the New York Times, CNN, Reuters, the Chicago Tribune, Australian Broadcasting Corporation (ABC), and other news companies blocked OpenAI's GPTBot web crawler from accessing their content, while the New York Times also updated its terms of service to disallow the use of its content in large language models.[143]
On September 13, 2023, in a serious response to growing anxiety about the dangers of AI, the US Senate holds the inaugural bipartisan "AI Insight Forum", bringing together senators, CEOs, civil rights leaders and other industry reps, to further familiarize senators with the nature of AI and its risks, and to discuss needed safeguards and legislation.[144] The event is organized by Senate Majority Leader Chuck Schumer (D-NY),[145] and is chaired by U.S. Senator Martin Heinrich (D-N.M.), Founder and co-chair of the Senate AI Caucus.[146] Reflecting the importance of the meeting, the forum is attended by over 60 senators,[147] as well as Elon Musk (Tesla CEO), Mark Zuckerberg (Meta CEO), Sam Altman (OpenAI CEO), Sundar Pichai (Alphabet CEO), Bill Gates (Microsoft co-founder), Satya Nadella (Microsoft CEO), Jensen Huang (Nvidia CEO), Arvind Krishna (IBM CEO), Alex Karp (Palantir CEO), Charles Rivkin (chairman and CEO of the MPA), Meredith Stiehm (president of the Writers Guild of America West), Liz Shuler (AFL-CIO President), and Maya Wiley (CEO of the Leadership Conference on Civil and Human Rights), among others.[144][145][147]
On October 30, 2023, US President Biden signed the Executive Order on the Safe, Secure, and Trustworthy Development and Use of Artificial Intelligence.[148][149]
In November 2023, the first global AI Safety Summit was held in Bletchley Park in the UK to discuss the near and far-term risks of AI and the possibility of mandatory and voluntary regulatory frameworks.[150] 28 countries including the United States, China, and the European Union issued a declaration at the start of the summit, calling for international co-operation to manage the challenges and risks of artificial intelligence.[151][152]
On December 6, Google announced Gemini 1.0 Ultra, Pro, and Nano.
2024  | On February 15, 2024, Google releases Gemini 1.5 in limited beta, capable of context length up to 1 million tokens.
Also, on February 15, 2024, OpenAI publicly announces Sora, a text-to-video model for generating videos up to a minute long.
On February 22, StabilityAI announces Stable Diffusion 3, using a similar architecture to Sora.
On May 8, Google DeepMind unveils the next version of AlphaFold, AF3, which extends its ability to predict structure and interactions from proteins to all of life's molecules, such as DNA, RNA, protein complexes and others. This release is paired with the AlphaFold server, providing free access to the tool to non-commercial researchers.[153]

Later, on October 9, co-founder and CEO of Google DeepMind and Isomorphic Labs Sir Demis Hassabis, and Google DeepMind Director Dr. John Jumper were co-awarded the 2024 Nobel Prize in Chemistry for their work developing AlphaFold.

On May 14, Google adds an "AI overview" to Google searches.
On June 10, Apple announced "Apple Intelligence" which incorporates ChatGPT into new iPhones and Siri.
At the Seoul Summit, leaders from the G7, the European Union, and major tech companies adopted the “Seoul Declaration for Safe, Innovative and Inclusive AI”, committing to international cooperation on AI safety, standards and innovation.
2025  | On February 6, Mistral AI releases Le Chat, an AI assistant able to answer up to 1,000 words per second.[154]
Stargate UAE invests to build Europe's largest AI data center in France.[155]
Amazon prepares training of humanoid robots to deliver packages.[156]
NLWeb, Project Mariner, and Google Flow launch.
On February 10 and 11, France hosts the Artificial Intelligence Action Summit.[157] 61 countries, including China, India, Japan, France and Canada, sign a declaration on "inclusive and sustainable" AI,[158] which the UK and US refused to sign.[159]
Pope Leo XIV calls technologists to build AI machines that embodies love, justice, and the sacred dignity of every human life at their core.[160][161]

## See also

* Timeline of machine translation
* Timeline of machine learning
* Timeline of artificial intelligence risks in global finance

## Notes

1. ↑ Please see Mechanical calculator
2. ↑ Please see: Pascal's calculator

## References

1. ↑ McCorduck 2004, pp. 4–5. sfn error: no target: CITEREFMcCorduck2004 (help)
2. ↑ McCorduck 2004, p. 4-5. sfn error: no target: CITEREFMcCorduck2004 (help)
3. ↑ Needham 1986, p. 53.
4. ↑ Needham, Joseph (1991). Science and Civilization in China: Volume 2, History of Scientific Thought. Cambridge University Press. p. 53. ISBN 978-0-521-05800-1. "The Liezi text describes an automaton presented to King Mu of Zhou... Yan Shi dismantled it to show it was a construction of leather, wood, glue and lacquer."
5. ↑ McCorduck 2004, p. 6 harvnb error: no target: CITEREFMcCorduck2004 (help)
6. ↑ 6.0 6.1 6.2 6.3 6.4 6.5 6.6 6.7 6.8 Schmidhuber 2022. sfn error: no target: CITEREFSchmidhuber2022 (help)
7. ↑ Russell & Norvig 2021, p. 341. sfn error: no target: CITEREFRussellNorvig2021 (help)
8. ↑ O'Connor, Kathleen Malone (1994), The alchemical creation of life (takwin) and other concepts of Genesis in medieval Islam, University of Pennsylvania, pp. 1–435, http://repository.upenn.edu/dissertations/AAI9503804, retrieved 10 January 2007.
9. ↑ Russell & Norvig 2021, p. 9. sfn error: no target: CITEREFRussellNorvig2021 (help)
10. ↑ A Thirteenth Century Programmable Robot
11. ↑ McCorduck 2004, pp. 10–12, 37 harvnb error: no target: CITEREFMcCorduck2004 (help); Russell & Norvig 2021, p. 6 harvnb error: no target: CITEREFRussellNorvig2021 (help)
12. ↑ McCorduck 2004, pp. 13–14. sfn error: no target: CITEREFMcCorduck2004 (help)
13. ↑ McCorduck 2004, pp. 14–15 harvnb error: no target: CITEREFMcCorduck2004 (help), Buchanan 2005, p. 50
14. ↑ Sir Francis Bacon (1620). The New Organon: Novem Organum Scientiarum.
15. ↑ Sir Francis Bacon (2000). Francis Bacon: The New Organon (Cambridge Texts in the History of Philosophy). Cambridge University Press.
16. ↑ 16.0 16.1 Russell & Norvig 2021, p. 6. sfn error: no target: CITEREFRussellNorvig2021 (help)
17. ↑ Russell & Norvig 2021, p. 6 harvnb error: no target: CITEREFRussellNorvig2021 (help)
18. ↑ McCorduck 2004, p. 42. sfn error: no target: CITEREFMcCorduck2004 (help)
19. ↑ Russell & Norvig 2021, p. 6 harvnb error: no target: CITEREFRussellNorvig2021 (help); McCorduck 2004, p. 26 harvnb error: no target: CITEREFMcCorduck2004 (help)
20. ↑ Russell & Norvig 2021, p. 6 harvnb error: no target: CITEREFRussellNorvig2021 (help); McCorduck 2004, pp. 36–40 harvnb error: no target: CITEREFMcCorduck2004 (help)
21. ↑ 21.0 21.1 Russell & Norvig 2021, p. 8. sfn error: no target: CITEREFRussellNorvig2021 (help)
22. ↑ McCorduck 2004, pp. 41–42. sfn error: no target: CITEREFMcCorduck2004 (help)
23. ↑ Leibniz, Gottfried Wilhelm Freiherr von (1920) (in en). The Early Mathematical Manuscripts of Leibniz: Translated from the Latin Texts Published by Carl Immanuel Gerhardt with Critical and Historical Notes (Leibniz published the chain rule in a 1676 memoir). Open court publishing Company. ISBN 9780598818461. https://books.google.com/books?id=bOIGAAAAYAAJ&q=leibniz+altered+manuscripts&pg=PA90.
24. ↑ Russell & Norvig 2021, p. 6 harvnb error: no target: CITEREFRussellNorvig2021 (help); McCorduck 2004, pp. 41–42 harvnb error: no target: CITEREFMcCorduck2004 (help)
25. ↑ Quoted in McCorduck 2004, p. 317 harvnb error: no target: CITEREFMcCorduck2004 (help)
26. ↑ Russell & Norvig 2021, p. 10. sfn error: no target: CITEREFRussellNorvig2021 (help)
27. ↑ McCorduck 2004, pp. 43. sfn error: no target: CITEREFMcCorduck2004 (help)
28. ↑ McCorduck 2004, p. 17. sfn error: no target: CITEREFMcCorduck2004 (help)
29. ↑ Adrien-Marie Legendre (1805) (in French). Nouvelles méthodes pour la détermination des orbites des comètes. Ghent University. F. Didot. http://archive.org/details/bub_gb_FRcOAAAAQAAJ.
30. ↑ Stigler, Stephen M. (1981). "Gauss and the Invention of Least Squares". Ann. Stat. 9 (3): 465–474. doi:10.1214/aos/1176345451. Bibcode: 1981AnSta...945451S.
31. ↑ Stigler, Stephen M. (1986). The History of Statistics: The Measurement of Uncertainty before 1900. Cambridge: Harvard. ISBN 0-674-40340-1. https://archive.org/details/historyofstatist00stig.
32. ↑ (Russell Norvig); Razy, C. (1913), p.120.
33. ↑ McCorduck 2004, pp. 19–25. sfn error: no target: CITEREFMcCorduck2004 (help)
34. ↑ Russell & Norvig 2021, p. 15 harvnb error: no target: CITEREFRussellNorvig2021 (help); McCorduck 2004, pp. 26–34 harvnb error: no target: CITEREFMcCorduck2004 (help)
35. ↑ Cambier, Hubert (June 2016). "The Evolutionary Meaning of World 3". Philosophy of the Social Sciences 46 (3): 242–264. doi:10.1177/0048393116641609. ISSN 0048-3931.
36. ↑ Russell & Norvig 2021, p. 8 harvnb error: no target: CITEREFRussellNorvig2021 (help); McCorduck 2004, pp. 48–51 harvnb error: no target: CITEREFMcCorduck2004 (help)
37. ↑ Project Gutenberg eBook Erewhon by Samuel Butler.Poes.....
38. ↑ Linsky & Irvine 2022, p. 2. sfn error: no target: CITEREFLinskyIrvine2022 (help)
39. ↑ McCorduck 2004, p. 25 harvnb error: no target: CITEREFMcCorduck2004 (help)
40. ↑ Brush, Stephen G. (1967). "History of the Lenz-Ising Model". Reviews of Modern Physics 39 (4): 883–893. doi:10.1103/RevModPhys.39.883. Bibcode: 1967RvMP...39..883B.
41. ↑ Amari, Shun-Ichi (1972). "Learning patterns and pattern sequences by self-organizing nets of threshold elements". IEEE Transactions C (21): 1197–1206.
42. ↑ K. Zuse (1936). Verfahren zur selbsttätigen Durchführung von Rechnungen mit Hilfe von Rechenmaschinen. Patent application Z 23 139 / GMD Nr. 005/021, 1936.
43. ↑ Turing, Alan Mathison (November 12, 1936). "On computable numbers, with an application to the Entscheidungsproblem". Proceedings of the London Mathematical Society 58: 230–265. doi:10.1112/plms/s2-42.1.230. https://www.cs.virginia.edu/~robins/Turing_Paper_1936.pdf.
44. ↑ McCorduck 2004, pp. 61–62 harvnb error: no target: CITEREFMcCorduck2004 (help) and see also The Life and Work of Konrad Zuse
45. ↑ (McCorduck 2004); (Russell Norvig)
46. ↑ Copeland, J (Ed.) (2004). The Essential Turing: the ideas that gave birth to the computer age. Oxford: Clarendon Press. ISBN 0-19-825079-7.
47. ↑ 47.0 47.1 Russell & Norvig 2021, p. 17. sfn error: no target: CITEREFRussellNorvig2021 (help)
48. ↑ (Crevier 1993); (Russell Norvig)
49. ↑ Russell & Norvig 2021, p. 155. sfn error: no target: CITEREFRussellNorvig2021 (help)
50. ↑ Russell & Norvig 2021, p. 1007. sfn error: no target: CITEREFRussellNorvig2021 (help)
51. ↑ (Samuel 1959); (Russell Norvig)
52. ↑ 52.0 52.1 52.2 52.3 52.4 52.5 Russell & Norvig 2021, p. 19. sfn error: no target: CITEREFRussellNorvig2021 (help)
53. ↑ Schaeffer, Jonathan. One Jump Ahead:: Challenging Human Supremacy in Checkers, 1997, 2009, Springer, ISBN 978-0-387-76575-4. Chapter 6.
54. ↑ (Russell Norvig)
55. ↑ Novet, Jordan (17 June 2017). "Everyone keeps talking about A.I.—here's what it really is and why it's so hot now". CNBC. https://www.cnbc.com/2017/06/17/what-is-artificial-intelligence.html.
56. ↑ McCorduck 2004, pp. 123–125 harvnb error: no target: CITEREFMcCorduck2004 (help), Crevier 1993, pp. 44–46 and Russell & Norvig 2021, p. 18 harvnb error: no target: CITEREFRussellNorvig2021 (help)
57. ↑ Quoted in Crevier 1993, p. 46 and Russell & Norvig 2021, p. 18 harvnb error: no target: CITEREFRussellNorvig2021 (help)
58. ↑ "Minds, Machines and Gödel". Users.ox.ac.uk. http://users.ox.ac.uk/~jrlucas/Godel/mmg.html.
59. ↑ Feigenbaum, Edward; Feldman, Julian, eds (1963). Computers and thought : a collection of articles (1 ed.). New York: McGraw-Hill. OCLC 593742426.
60. ↑ "This week in The History of AI at AIWS.net – Edward Feigenbaum and Julian Feldman published "Computers and Thought"". https://aiws.net/the-history-of-ai/this-week-in-the-history-of-ai-at-aiws-net-edward-feigenbaum-and-julian-feldman-published-computers-and-thought-2/.
61. ↑ "Feigenbaum & Feldman Issue 'Computers and Thought,' the First Anthology on Artificial Intelligence". https://www.historyofinformation.com/detail.php?entryid=4329.
62. ↑ Feigenbaum, Edward A.; Feldman, Julian (1963). Computers and Thought. McGraw-Hill, Inc.. ISBN 9780070203709. https://dl.acm.org/doi/book/10.5555/601134. Retrieved 5 May 2022.
63. ↑ Ivakhnenko, A. G. (1973). Cybernetic Predicting Devices. CCM Information Corporation. https://books.google.com/books?id=FhwVNQAACAAJ.
64. ↑ Ivakhnenko, A. G.; Grigorʹevich Lapa, Valentin (1967). Cybernetics and forecasting techniques. American Elsevier Pub. Co.. https://books.google.com/books?id=rGFgAAAAMAAJ.
65. ↑ "The Machine Intelligence series". http://www.cs.york.ac.uk/mlg/MI/mi.html.
66. ↑ Grosz, Barbara J.; Hajicova, Eva; Joshi, Aravind (2015). "Jane J. Robinson". Computational Linguistics 41 (4): 723–726. doi:10.1162/COLI_a_00235. https://direct.mit.edu/coli/article/41/4/723/1509/Jane-J-Robinson. Retrieved 2024-01-23.
67. ↑ Linnainmaa, Seppo (1970). Algoritmin kumulatiivinen pyöristysvirhe yksittäisten pyöristysvirheiden Taylor-kehitelmänä [The representation of the cumulative rounding error of an algorithm as a Taylor expansion of the local rounding errors] (PDF) (Thesis) (in Finnish). pp. 6–7.
68. ↑ "The Boyer-Moore Theorem Prover". http://www.cs.utexas.edu/users/moore/best-ideas/nqthm/.
69. ↑ Stevo Bozinovski and Ante Fulgosi (1976). "The influence of pattern similarity and transfer learning upon training of a base perceptron" (original in Croatian) Proceedings of Symposium Informatica 3-121-5, Bled.
70. ↑ Stevo Bozinovski (2020) "Reminder of the first paper on transfer learning in neural networks, 1976". Informatica 44: 291–302.
71. ↑ Bozinovski, Stevo (1981) "Inverted pendulum control program" ANW Memo, Adaptive Networks Group, Computer and Information Science Department, University of Massachusetts at Amherst, December 10, 1981
72. ↑ Bozinovski, Stevo and Anderson, Charles (1983) "Associative memory as controller of an unstable system: Simulation of a learning control" Proc. IEEE Mediterranean Electrotechnical Conference, C5.11., Athens, Greece"
73. ↑ Bozinovski, Stevo (1995) "Adaptive parallel distributed processing: Neural and genetic agents: Neuro-genetic agents and a structural theory of self-reinforcement learning systems" CMPSCI Technical Report 95-107, Computer Science Department, University of Massachusetts at Amherst
74. ↑ Harry Henderson (2007). "Chronology". Artificial Intelligence: Mirrors for the Mind. NY: Infobase Publishing. ISBN 978-1-60413-059-1. https://books.google.com/books?id=vKmIiICDIwgC&pg=PA165. Retrieved 11 April 2015.
75. ↑ Cook, Donald A.; Sterling, John W. (June 1989). "EmeraldInsight". Planning Review 17 (6): 22–27. doi:10.1108/eb054275. http://www.emeraldinsight.com/journals.htm?articleid=1696959&show=pdf. Retrieved 15 March 2015.
76. ↑ Mead, Carver A.; Ismail, Mohammed (8 May 1989). Analog VLSI Implementation of Neural Systems. The Kluwer International Series in Engineering and Computer Science. 80. Norwell, MA: Kluwer Academic Publishers. doi:10.1007/978-1-4613-1639-8. ISBN 978-1-4613-1639-8. http://fennetic.net/irc/Christopher R. Carroll Carver Mead Mohammed Ismail Analog VLSI Implementation of Neural Systems.pdf. Retrieved 24 January 2020.
77. ↑ DART: Revolutionizing Logistics Planning
78. ↑ "ISX Corporation". http://www.isx.com/projects/drpi.php.
79. ↑ "DART overview". http://www.aaai.org/AITopics/html/military.html.
80. ↑ Zadeh, Lotfi A., "Fuzzy Logic, Neural Networks, and Soft Computing," Communications of the ACM, March 1994, Vol. 37 No. 3, pages 77-84.
81. ↑ "AAAI-first-ai-env-workshop.HTML". http://www.aiandenvironment.org/aaai-first-ai-env-workshop.html.
82. ↑ "Ijcai-first-ai-env-workshop". http://www.aiandenvironment.org/ijcai-first-ai-env-workshop.html.
83. ↑ Jochem, Todd M.; Pomerleau, Dean A.. "No Hands Across America Home Page". https://www.cs.cmu.edu/afs/cs/user/tjochem/www/nhaa/nhaa_home_page.html.
84. ↑ Jochem, Todd. "Back to the Future: Autonomous Driving in 1995". Robotic Trends. http://www.roboticstrends.com/article/back_to_the_future_autonomous_driving_in_1995.
85. ↑ "Semantic Web roadmap". W3.org. http://www.w3.org/DesignIssues/Semantic.html.
86. ↑ Mason, Cindy; Sànchez-Marrè, Miquel (1999). "Binding Environmental Sciences and Artificial Intelligence". Environmental Modelling & Software 14 (5): 335–337. https://www.academia.edu/17759949. Retrieved 27 October 2021.
87. ↑ "BESAI - Homepage". http://www.cs.upc.edu/~webia/besai/besai.html.
88. ↑ Kaelbling, Leslie Pack; Littman, Michael L; Cassandra, Anthony R. (1998). "Planning and acting in partially observable stochastic domains". Artificial Intelligence 101 (1–2): 99–134. doi:10.1016/s0004-3702(98)00023-x. http://people.csail.mit.edu/lpk/papers/aij98-pomdp.pdf. Retrieved 5 May 2017.
89. ↑ "Bluebrain – EPFL". http://bluebrain.epfl.ch/.
90. ↑ "Modelling natural action selection". Pubs.royalsoc.ac.uk. http://www.pubs.royalsoc.ac.uk/index.cfm?page=1318.
91. ↑ "Giving Robots Compassion, C. Mason, Conference on Science and Compassion, Poster Session, Telluride, Colorado, 2012." (in en). https://www.researchgate.net/publication/260230014.
92. ↑ Fisher, Adam (18 September 2013). "Inside Google's Quest To Popularize Self-Driving Cars". Popular Science. http://www.popsci.com/cars/article/2013-09/google-self-driving-car.
93. ↑ "Jamie Shotton at Microsoft Research". http://research.microsoft.com/en-us/people/jamiesho/.
94. ↑ "Human Pose Estimation for Kinect – Microsoft Research". http://research.microsoft.com/en-us/projects/vrkinect/.
95. ↑ "AAAI Spring Symposium - AI and Design for Sustainability". http://dts-web1.it.vanderbilt.edu/~fisherdh//AI-Design-Sustainability.html.
96. ↑ (Christian 2020); (Russell Norvig)
97. ↑ Wong (2023).
98. ↑ Christian 2020, p. 25. sfn error: no target: CITEREFChristian2020 (help)
99. ↑ "DARPA Robotics Challenge Trials". US Defense Advanced Research Projects Agency. http://www.theroboticschallenge.org/.
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101. ↑ Srivastava, Rupesh Kumar; Greff, Klaus; Schmidhuber, Jürgen (2 May 2015). "Highway Networks". arXiv:1505.00387 [cs.LG].
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104. ↑ "Research Priorities for Robust and Beneficial Artificial Intelligence: An Open Letter". Future of Life Institute. https://futureoflife.org/open-letter/ai-open-letter/.
105. ↑ Tegmark, Max. "Open Letter on Autonomous Weapons". Future of Life Institute. http://futureoflife.org/open-letter-autonomous-weapons/.
106. ↑ 106.0 106.1 106.2 Cite error: Invalid `<ref>` tag; no text was provided for refs named `:0`
107. ↑ Ormerod, David. "AlphaGo defeats Lee Sedol 4–1 in Google DeepMind Challenge Match". https://gogameguru.com/alphago-defeats-lee-sedol-4-1/.
108. ↑ Moravčík, Matej; Schmid, Martin; Burch, Neil; Lisý, Viliam; Morrill, Dustin; Bard, Nolan; Davis, Trevor; Waugh, Kevin et al. (2017-05-05). "DeepStack: Expert-level artificial intelligence in heads-up no-limit poker" (in en). Science 356 (6337): 508–513. doi:10.1126/science.aam6960. ISSN 0036-8075. PMID 28254783. Bibcode: 2017Sci...356..508M.
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110. ↑ Solon, Olivia (30 January 2017). "Oh the humanity! Poker computer trounces humans in big step for AI". The Guardian. https://www.theguardian.com/technology/2017/jan/30/libratus-poker-artificial-intelligence-professional-human-players-competition.
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112. ↑ "World's Go Player Ratings". 24 May 2017. http://www.goratings.org/.
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116. ↑ "Dota 2". Openai Blog. 11 August 2017. https://blog.openai.com/dota-2/.
117. ↑ Greenemeier, Larry (18 October 2017). "AI versus AI: Self-Taught AlphaGo Zero Vanquishes Its Predecessor". Scientific American. https://www.scientificamerican.com/article/ai-versus-ai-self-taught-alphago-zero-vanquishes-its-predecessor/.
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125. ↑ Vincent, James (2022-11-08). "The lawsuit that could rewrite the rules of AI copyright" (in en-US). https://www.theverge.com/2022/11/8/23446821/microsoft-openai-github-copilot-class-action-lawsuit-ai-copyright-violation-training-data.
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128. ↑ Korn, Jennifer (2023-01-17). "Getty Images suing the makers of popular AI art tool for allegedly stealing photos" (in en). https://www.cnn.com/2023/01/17/tech/getty-images-stability-ai-lawsuit/index.html.
129. ↑ "Getty Images Statement". CNN. 17 January 2023. https://newsroom.gettyimages.com/en/getty-images/getty-images-statement.
130. ↑ Belanger, Ashley (6 February 2023). "Getty sues Stability AI for copying 12M photos and imitating famous watermark". Ars Technica. https://arstechnica.com/tech-policy/2023/02/getty-sues-stability-ai-for-copying-12m-photos-and-imitating-famous-watermark/.
131. ↑ Belfield, Haydn (25 March 2023). "If your AI model is going to sell, it has to be safe" (in en). Vox. https://www.vox.com/future-perfect/2023/3/25/23655082/ai-openai-gpt-4-safety-microsoft-facebook-meta.
132. ↑ "SAT: Understanding Scores". 2022. https://satsuite.collegeboard.org/media/pdf/understanding-sat-scores.pdf.
133. ↑ OpenAI (2023). "GPT-4 Technical Report". arXiv:2303.08774 [cs.CL].
134. ↑ "Prepare for truly useful large language models" (in en). Nature Biomedical Engineering 7 (2): 85–86. 7 March 2023. doi:10.1038/s41551-023-01012-6. PMID 36882584.
135. ↑ Elias, Jennifer (January 31, 2023). "Google is asking employees to test potential ChatGPT competitors, including a chatbot called 'Apprentice Bard'" (in en). CNBC. https://www.cnbc.com/2023/01/31/google-testing-chatgpt-like-chatbot-apprentice-bard-with-employees.html.
136. ↑ Elias, Jennifer (February 2023). "Google asks employees to rewrite Bard's bad responses, says the A.I. 'learns best by example'" (in en). CNBC. https://www.cnbc.com/2023/02/15/google-asks-employees-to-rewrite-bards-incorrect-responses-to-queries.html.
137. ↑ Ortiz, Sabrina (March 29, 2023). "Musk, Wozniak, and other tech leaders sign petition to halt further AI developments" (in en). ZD Net. https://www.zdnet.com/article/musk-wozniak-and-other-tech-leaders-sign-petition-to-halt-ai-developments/.
138. ↑ "Pause Giant AI Experiments: An Open Letter". Future of Life Institute. https://futureoflife.org/open-letter/pause-giant-ai-experiments/.
139. ↑ Lappalainen, Yrjo; Narayanan, Nikesh (2023-06-14). "Aisha: A Custom AI Library Chatbot Using the ChatGPT API" (in en). Journal of Web Librarianship 17 (3): 37–58. doi:10.1080/19322909.2023.2221477. ISSN 1932-2909. https://www.tandfonline.com/doi/full/10.1080/19322909.2023.2221477.
140. ↑ "Statement on AI Risk AI experts and public figures express their concern about AI risk.". Center for AI Safety. https://www.safe.ai/statement-on-ai-risk#open-letter.
141. ↑ Edwards, Benj (May 30, 2023). "OpenAI execs warn of "risk of extinction" from artificial intelligence in new open letter" (in en). Ars Technica. https://arstechnica.com/information-technology/2023/05/openai-execs-warn-of-risk-of-extinction-from-artificial-intelligence-in-new-open-letter/.
142. ↑ Queen, Jack (July 10, 2023). "Sarah Silverman sues Meta, OpenAI for copyright infringement" (in en). Reuters. https://www.reuters.com/legal/sarah-silverman-sues-meta-openai-copyright-infringement-2023-07-09/.
143. ↑ Bogle, Ariel (August 24, 2023). "New York Times, CNN and Australia's ABC block OpenAI's GPTBot web crawler from accessing content" (in en). The Guardian. https://www.theguardian.com/technology/2023/aug/25/new-york-times-cnn-and-abc-block-openais-gptbot-web-crawler-from-scraping-content.
144. ↑ 144.0 144.1 Johnson, Ted (September 13, 2023). "Elon Musk Says "Something Good Will Come Of This" After Senate's AI Forum, Chuck Schumer Signals AI Legislation Coming "In The General Category Of Months" — Update" (in en). Deadline. https://deadline.com/2023/09/senate-ai-insight-forum-wga-elon-musk-mark-zuckerberg-1235545470/.
145. ↑ 145.0 145.1 Kang, Cecelia (September 13, 2023). ""In Show of Force, Silicon Valley Titans Pledge 'Getting This Right' With A.I."" (in en). The New York Times. https://www.nytimes.com/2023/09/13/technology/silicon-valley-ai-washington-schumer.html.
146. ↑ Read Out: Heinrich Convenes First Bipartisan Senate AI Insight Forum, 13 September 2023, https://www.heinrich.senate.gov/newsroom/press-releases/read-out-heinrich-convenes-first-bipartisan-senate-ai-insight-forum, retrieved 13 September 2023
147. ↑ 147.0 147.1 Feiner, Lauren (September 13, 2023). "Elon Musk, Mark Zuckerberg, Bill Gates and other tech leaders in closed Senate session about AI" (in en). CNBC. https://www.cnbc.com/2023/09/13/musk-zuckerberg-among-tech-leaders-visiting-senate-to-speak-about-ai-.html.
148. ↑ Morrison, Sara (October 31, 2023). "President Biden's new plan to regulate AI. Now comes the hard part: Congress." (in en). Vox News. https://www.vox.com/technology/2023/10/31/23939157/biden-ai-executive-order.
149. ↑ Executive Order on the Safe, Secure, and Trustworthy Development and Use of Artificial Intelligence, 30 October 2023, https://bidenwhitehouse.archives.gov/briefing-room/presidential-actions/2023/10/30/executive-order-on-the-safe-secure-and-trustworthy-development-and-use-of-artificial-intelligence/, retrieved 3 November 2023
150. ↑ Milmo, Dan (3 November 2023). "Hope or Horror? The great AI debate dividing its pioneers". The Guardian Weekly: pp. 10–12.
151. ↑ "The Bletchley Declaration by Countries Attending the AI Safety Summit, 1-2 November 2023". 1 November 2023. https://www.gov.uk/government/publications/ai-safety-summit-2023-the-bletchley-declaration/the-bletchley-declaration-by-countries-attending-the-ai-safety-summit-1-2-november-2023.
152. ↑ "Countries agree to safe and responsible development of frontier AI in landmark Bletchley Declaration". GOV.UK (Press release). Archived from the original on 1 November 2023. Retrieved 1 November 2023.
153. ↑ "AlphaFold 3 predicts the structure and interactions of all of life’s molecules" (in en-US). 2024-05-08. https://blog.google/innovation-and-ai/products/google-deepmind-isomorphic-alphafold-3-ai-model/.
154. ↑ Dillet, Romain (6 February 2025). "Mistral releases its AI assistant on iOS and Android" (in en-us). TechCrunch. https://techcrunch.com/2025/02/06/mistral-releases-its-ai-assistant-on-ios-and-android/.
155. ↑ Maccioni, Federico; Saini, Manya; Saba, Yousef; Saini, Manya; Saba, Yousef (2025-05-15). "UAE to build biggest AI campus outside US in Trump deal, bypassing past China worries" (in en). Reuters. https://www.reuters.com/world/china/uae-set-deepen-ai-links-with-united-states-after-past-curbs-over-china-2025-05-15/.
156. ↑ "Amazon prepares to test humanoid robots for deliveries, The Information reports" (in en). Reuters. 2025-06-05. https://www.reuters.com/business/retail-consumer/amazon-prepares-test-humanoid-robots-package-deliveries-information-reports-2025-06-05/.
157. ↑ "Paris hosts AI summit, with spotlight on innovation, regulation, creativity". Radio France Internationale. 6 February 2025. https://www.rfi.fr/en/science-and-technology/20250206-weds-pm-paris-ai-summit-what-french-developers-expect-etcy.
158. ↑ Dillet, Romain (11 February 2025). "As US and UK refuse to sign the Paris AI Action Summit statement, other countries commit to developing 'open, inclusive, ethical' AI.". TechCrunch. https://techcrunch.com/2025/02/11/as-us-and-uk-refuse-to-sign-ai-action-summit-statement-countries-fail-to-agree-on-the-basics/.
159. ↑ Milmo, Dan (11 February 2025). "US and UK refuse to sign Paris summit declaration on 'inclusive' AI". The Guardian. https://www.theguardian.com/technology/2025/feb/11/us-uk-paris-ai-summit-artificial-intelligence-declaration.
160. ↑ "Pope Leo XIV urges Catholic technologists to spread the Gospel with AI | USCCB" (in en). https://www.usccb.org/news/2025/pope-leo-xiv-urges-catholic-technologists-spread-gospel-ai.
161. ↑ "Message of the Holy Father to participants in the Second Annual Conference on Artificial Intelligence, Ethics, and Corporate Governance [Rome, 19–20 June 2025 (17 June 2025)"] (in en). http://www.vatican.va/content/leo-xiv/en/messages/pont-messages/2025/documents/20250617-messaggio-ia.html.

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## Further reading

* Berlinski, David (2000), The Advent of the Algorithm, Harcourt Books
* Brooks, Rodney (1990), "Elephants Don't Play Chess", Robotics and Autonomous Systems 6 (1–2): 3–15, doi:10.1016/S0921-8890(05)80025-9, http://people.csail.mit.edu/brooks/papers/elephants.pdf, retrieved 30 August 2007
* Darrach, Brad (20 November 1970), "Meet Shakey, the First Electronic Person", Life Magazine: 58–68
* Doyle, J. (1983), "What is rational psychology? Toward a modern mental philosophy", AI Magazine 4 (3): 50–53
* Dreyfus, Hubert (1972), What Computers Can't Do, MIT Press
* Feigenbaum, Edward A.; McCorduck, Pamela (1983), The Fifth Generation: Artificial Intelligence and Japan's Computer Challenge to the World, Michael Joseph, ISBN 978-0-7181-2401-4
* Feigenbaum, Edward; Feldman, Julian, eds. (1963), Computers and thought (1 ed.), New York: McGraw-Hill, OCLC 593742426
* Hobbes (1651), Leviathan
* Hofstadter, Douglas (1980), Gödel, Escher, Bach: an Eternal Golden Braid
* Howe, J. (November 1994), Artificial Intelligence at Edinburgh University: a Perspective, http://www.inf.ed.ac.uk/about/AIhistory.html, retrieved 30 August 2007
* Kaplan, Andreas; Haenlein, Michael (2018), "Siri, Siri in my Hand, who's the Fairest in the Land? On the Interpretations, Illustrations and Implications of Artificial Intelligence", Business Horizons 62: 15–25, doi:10.1016/j.bushor.2018.08.004
* Kurzweil, Ray (2005), The Singularity is Near, Viking Press
* Lakoff, George (1987), Women, Fire, and Dangerous Things: What Categories Reveal About the Mind, University of Chicago Press., ISBN 978-0-226-46804-4, https://archive.org/details/womenfiredangero00lako_0
* Lenat, Douglas; Guha, R. V. (1989), Building Large Knowledge-Based Systems, Addison-Wesley
* Levitt, Gerald M. (2000), The Turk, Chess Automaton, Jefferson, N.C.: McFarland, ISBN 978-0-7864-0778-1
* Lighthill, Professor Sir James (1973), "Artificial Intelligence: A General Survey", Artificial Intelligence: a paper symposium, Science Research Council
* Lucas, John (1961), Minds, Machines and Gödel, http://users.ox.ac.uk/~jrlucas/Godel/mmg.html, retrieved 24 July 2007
* McCarthy, John; Minsky, Marvin; Rochester, Nathan; Shannon, Claude (1955), A Proposal for the Dartmouth Summer Research Project on Artificial Intelligence, http://www-formal.stanford.edu/jmc/history/dartmouth/dartmouth.html
* McCarthy, John; Hayes, P. J. (1969), "Some philosophical problems from the standpoint of artificial intelligence", Machine Intelligence 4: 463–502, http://www-formal.stanford.edu/jmc/mcchay69.html
* McCullough, W. S.; Pitts, W. (1943), "A logical calculus of the ideas immanent in nervous activity", Bulletin of Mathematical Biophysics 5 (4): 115–127, doi:10.1007/BF02478259, Bibcode: 1943BMaB....5..115M
* Minsky, Marvin (1967), Computation: Finite and Infinite Machines, Englewood Cliffs, N.J.: Prentice-Hall
* Minsky, Marvin; Seymour Papert (1969), Perceptrons: An Introduction to Computational Geometry, The MIT Press
* Minsky, Marvin (1974), A Framework for Representing Knowledge, http://web.media.mit.edu/~minsky/papers/Frames/frames.html, retrieved 27 December 2007
* Minsky, Marvin (1986), The Society of Mind, Simon and Schuster
* Moravec, Hans (1976), The Role of Raw Power in Intelligence, http://www.frc.ri.cmu.edu/users/hpm/project.archive/general.articles/1975/Raw.Power.html
* Moravec, Hans (1988), Mind Children, Harvard University Press
* United States National Research Council (1999), "Developments in Artificial Intelligence", Funding a Revolution: Government Support for Computing Research, National Academy Press, http://www.nap.edu/readingroom/books/far/ch9.html, retrieved 30 August 2007
* Newell, Allen; Simon, H. A. (1963), "GPS: A Program that Simulates Human Thought", in Feigenbaum, Edward; Feldman, Julian, Computers and Thought, New York: McGraw-Hill
* Newquist, HP (1994), The Brain Makers: Genius, Ego, And Greed In The Quest For Machines That Think, New York: Macmillan/SAMS, ISBN 978-0-9885937-1-8
* Pearl, J. (1988), Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference, San Mateo, California: Morgan Kaufmann
* Russell, Stuart J.; Norvig, Peter (2003), Artificial Intelligence: A Modern Approach (2nd ed.), Upper Saddle River, New Jersey: Prentice Hall, ISBN 0-13-790395-2, http://aima.cs.berkeley.edu/
* Poole, David; Mackworth, Alan; Goebel, Randy (1998), Computational Intelligence: A Logical Approach, Oxford University Press., ISBN 978-0-19-510270-3, https://archive.org/details/computationalint00pool
* Searle, John (1980), "Minds, Brains and Programs", Behavioral and Brain Sciences 3 (3): 417–457, doi:10.1017/S0140525X00005756, http://cogprints.org/7150/1/10.1.1.83.5248.pdf
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* Turing, Alan (October 1950), "Computing machinery and intelligence", Mind LIX (236): 433–60, doi:10.1093/mind/LIX.236.433, http://loebner.net/Prizef/TuringArticle.html
* Weizenbaum, Joseph (1976), Computer Power and Human Reason, W.H. Freeman & Company

## External links

* "The history of artificial intelligence: Complete AI timeline", Enterprise AI (TechTarget), 16 Aug 2023, https://www.techtarget.com/searchenterpriseai/tip/The-history-of-artificial-intelligence-Complete-AI-timeline
* "Brief History (timeline)", AI Topics (Association for the Advancement of Artificial Intelligence), http://aitopics.org/misc/brief-history

* v
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Timelines of computing

Computing|

* before 1950
* 1950–1979
* 1980s
* 1990s
* 2000s
* 2010s

Software|

| Open-source software|

* 1970s
* 1980s
* 1990s
* 2000s
* 2010s
* 2020s

|

Programming languages|

Hypertext technology|

Operating systems|

* DOS family
* Windows
* Linux

Virtualization development|

Malware|

Computer science|

* Artificial intelligence
* Quantum computing

Internet|

* Web browsers
* Internet conflicts

Men in computing|

* John Vincent Atanasoff
* Charles Babbage
* John Backus
* George Boole
* Vint Cerf
* John Cocke
* Stephen Cook
* J. Presper Eckert
* David A. Huffman
* Bob Kahn
* Brian Kernighan
* Andrew Koenig
* Donald Knuth
* Joseph Kruskal
* Douglas McIlroy
* John von Neumann
* Dennis Ritchie
* Guido van Rossum
* Bjarne Stroustrup
* Ken Thompson
* Linus Torvalds
* Alan Turing
* Paul Vixie
* Larry Wall
* Stephen Wolfram
* Steve Wozniak

Women in computing|

* Kathleen Antonelli
* Jean Bartik
* Adele Goldstine
* Lois Haibt
* Betty Holberton
* Ada Lovelace
* Margaret Hamilton
* Grace Hopper
* Nancy Leveson
* Marlyn Meltzer
* Klara Dan von Neumann
* Frances Spence
* Ruth Teitelbaum

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