Difference between revisions of "Timeline of artificial intelligence"

This is a '''timeline of FIXME'''.

| 1940s || Maturation of artificial intelligence || "Year 1943: The first work which is now recognized as AI was done by Warren McCulloch and Walter pits in 1943. They proposed a model of artificial neurons." "Year 1949: Donald Hebb demonstrated an updating rule for modifying the connection strength between neurons. His rule is now called Hebbian learning."<ref name="javatpoint.coma"/> "More recently, in the 1940s, a school of thought called “Connectionism” was developed to study the process of thinking"<ref name="dataversity.netw"/>

| 1952–1956 || "The birth of Artificial Intelligence (1952-1956)" || "Year 1955: An Allen Newell and Herbert A. Simon created the "first artificial intelligence program"Which was named as "Logic Theorist". This program had proved 38 of 52 Mathematics theorems, and find new and more elegant proofs for some theorems." "Year 1956: The word "Artificial Intelligence" first adopted by American Computer scientist John McCarthy at the Dartmouth Conference. For the first time, AI coined as an academic field."<ref name="javatpoint.coma"/>

| 1950s || || "At the beginning of 1950, John Von Neumann and Alan Turing did not create the term AI but were the founding fathers of the technology behind it: they made the transition from computers to 19th century decimal logic (which thus dealt with values from 0 to 9) and machines to binary logic (which rely on Boolean algebra, dealing with more or less important chains of 0 or 1). The two researchers thus formalized the architecture of our contemporary computers and demonstrated that it was a universal machine, capable of executing what is programmed."<ref name="coe.intf"/>    " By the 1950s, we had a generation of scientists, mathematicians, and philosophers with the concept of artificial intelligence (or AI) culturally assimilated in their minds. One such person was Alan Turing, a young British polymath who explored the mathematical possibility of artificial intelligence. "<ref name="harvard.edu d">{{cite web |title=The History of Artificial Intelligence |url=http://sitn.hms.harvard.edu/flash/2017/history-artificial-intelligence/ |website=harvard.edu |accessdate=7 February 2020}}</ref> "Expert systems, as a subset of AI, first emerged in the early 1950s when the Rand-Carnegie team developed the

general problem solver to deal with theorems proof, geometric problems and chess playing"<ref name="washington.edu"/>

| 1957–1974 || || "From 1957 to 1974, AI flourished. Computers could store more information and became faster, cheaper, and more accessible. Machine learning algorithms also improved and people got better at knowing which algorithm to apply to their problem."<ref name="harvard.edu d"/>

| 1974–1980 || {{w|AI winter}} || " After several reports criticizing progress in AI, government funding and interest in the field dropped off – a period from 1974–80 that became known as the "AI winter.""<ref name="livescience.coms"/> "Artificial Intelligence research funding was cut in the 1970s, after several reports criticized a lack of progress. Efforts to imitate the human brain, called “neural networks,” were experimented with, and dropped. The most impressive, functional programs were only able to handle simplistic problems, and were described as toys by the unimpressed. AI researchers had been overly optimistic in establishing their goals, and had made naive assumptions about the problems they would encounter. When the results they promised never materialized, it should come as no surprise their funding was cut."<ref name="dataversity.netw"/>

| 1980–1987 || "A boom of AI" || " After AI winter duration, AI came back with "Expert System". Expert systems were programmed that emulate the decision-making ability of a human expert."<ref name="javatpoint.coma"/> "In the 1980’s, AI was reignited by two sources: an expansion of the algorithmic toolkit, and a boost of funds. John Hopfield and David Rumelhart popularized “deep learning” techniques which allowed computers to learn using experience. On the other hand Edward Feigenbaum introduced expert systems which mimicked the decision making process of a human expert. The program would ask an expert in a field how to respond in a given situation, and once this was learned for virtually every situation, non-experts could receive advice from that program. Expert systems were widely used in industries. The Japanese government heavily funded expert systems and other AI related endeavors as part of their Fifth Generation Computer Project (FGCP). From 1982-1990, they invested $400 million dollars with the goals of revolutionizing computer processing, implementing logic programming, and improving artificial intelligence. "<ref name="harvard.edu d"/> " The field later revived in the 1980s when the British government started funding it again in part to compete with efforts by the Japanese."<ref name="livescience.coms"/> " AI research resumed in the 1980s, with the U.S. and Britain providing funding to compete with Japan’s new “fifth generation” computer project, and their goal of becoming the world leader in computer technology."<ref name="dataversity.netw"/> "Amid the AI Winter in the United States an epic attempt to realize the ‘AI dream’ was underway in Japan in the

form of the Fifth Generation Computer System (FGCS) project during the 1980s."<ref name="washington.edu"/>

| 1987–1993 || Second AI winter || "Again Investors and government stopped in funding for AI research as due to high cost but not efficient result. The expert system such as XCON was very cost effective."<ref name="javatpoint.coma"/> "The field experienced another major winter from 1987 to 1993, coinciding with the collapse of the market for some of the early general-purpose computers, and reduced government funding."<ref name="livescience.coms"/> "The AI field experienced another major winter from 1987 to 1993. This second slowdown in AI research coincided with XCON, and other early Expert System computers, being seen as slow and clumsy. Desktop computers were becoming very popular and displacing the older, bulkier, much less user-friendly computer banks. Eventually, Expert Systems simply became too expensive to maintain, when compared to desktops. They were difficult to update, and could not “learn.” These were problems desktop computers did not have. At about the same time, DARPA (Defense Advanced Research Projects Agency) concluded AI would not be “the next wave” and redirected its funds to projects deemed more likely to provide quick results. As a consequence, in the late 1980s, funding for AI research was cut deeply, creating the Second AI Winter."<ref name="dataversity.netw"/> However, " By the end of 1980s, over half of the Fortune 500 companies were involved in either developing or maintaining of expert systems"<ref name="washington.edu"/>

| 2011-onward || Massive data and new computing power. "Deep learning, big data and artificial general intelligence" || "In the year 2011, IBM's Watson won jeopardy, a quiz show, where it had to solve the complex questions as well as riddles. Watson had proved that it could understand natural language and can solve tricky questions quickly."<ref name="javatpoint.coma"/> "Two factors explain the new boom in the discipline around 2010. 1) First of all, access to massive volumes of data. To be able to use algorithms for image classification and cat recognition, for example, it was previously necessary to carry out sampling yourself. Today, a simple search on Google can find millions. 2) Then the discovery of the very high efficiency of computer graphics card processors to accelerate the calculation of learning algorithms. The process being very iterative, it could take weeks before 2010 to process the entire sample. The computing power of these cards (capable of more than a thousand billion transactions per second) has enabled considerable progress at a limited financial cost (less than 1000 euros per card)."<ref name="coe.intf"/>

| 1308 || || " Catalan poet and theologian Ramon Llull publishes Ars generalis ultima (The Ultimate General Art), further perfecting his method of using paper-based mechanical means to create new knowledge from combinations of concepts."<ref name="forbes.coms">{{cite web |title=A Very Short History Of Artificial Intelligence (AI) |url=https://www.forbes.com/sites/gilpress/2016/12/30/a-very-short-history-of-artificial-intelligence-ai/#35827d6b6fba |website=forbes.com |accessdate=7 February 2020}}</ref> ||

| 1666 || || "Mathematician and philosopher Gottfried Leibniz publishes Dissertatio de arte combinatoria (On the Combinatorial Art), following Ramon Llull in proposing an alphabet of human thought and arguing that all ideas are nothing but combinations of a relatively small number of simple concepts."<ref name="forbes.coms"/> ||

| 1726 || || "onathan Swift publishes Gulliver's Travels, which includes a description of the Engine, a machine on the island of Laputa (and a parody of Llull's ideas): "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.""<ref name="forbes.coms"/> ||

| 1763 || || "Thomas Bayes develops a framework for reasoning about the probability of events. Bayesian inference will become a leading approach in machine learning."<ref name="forbes.coms"/> ||

| 1854 || || || " George Boole argues that logical reasoning could be performed systematically in the same manner as solving a system of equations."<ref name="forbes.coms"/> ||

| 1898 || || "At an electrical exhibition in the recently completed Madison Square Garden, Nikola Tesla makes a demonstration of the world’s first radio-controlled vessel. The boat was equipped with, as Tesla described, “a borrowed mind.”"<ref name="forbes.coms"/> ||

| 1914 || || "The Spanish engineer Leonardo Torres y Quevedo demonstrates the first chess-playing machine, capable of king and rook against king endgames without any human intervention."<ref name="forbes.coms"/> ||

| 1921 || || "Czech writer Karel Čapek introduces the word "robot" in his play R.U.R. (Rossum's Universal Robots). The word "robot" comes from the word "robota" (work)."<ref name="forbes.coms"/> ||

| 1925 || || " Houdina Radio Control releases a radio-controlled driverless car, travelling the streets of New York City."<ref name="forbes.coms"/> ||

| 1927 || || "he science-fiction film Metropolis is released. It features a robot double of a peasant girl, Maria, which unleashes chaos in Berlin of 2026—it was the first robot depicted on film, inspiring the Art Deco look of C-3PO in Star Wars."<ref name="forbes.coms"/> ||

| 1929 || || "Makoto Nishimura designs Gakutensoku, Japanese for "learning from the laws of nature," the first robot built in Japan. It could change its facial expression and move its head and hands via an air pressure mechanism."<ref name="forbes.coms"/> ||

| 1943 || || "Warren S. McCulloch and Walter Pitts publish “A Logical Calculus of the Ideas Immanent in Nervous Activity” in the Bulletin of Mathematical Biophysics. This influential paper, in which they discussed networks of idealized and simplified artificial “neurons” and how they might perform simple logical functions, will become the inspiration for computer-based “neural networks” (and later “deep learning”) and their popular description as “mimicking the brain.”"<ref name="forbes.coms"/> "a first mathematical and computer model of the biological neuron (formal neuron) had been developed by Warren McCulloch and Walter Pitts as early as 1943."<ref name="coe.intf">{{cite web |title=History of Artificial Intelligence |url=https://www.coe.int/en/web/artificial-intelligence/history-of-ai |website=coe.int |accessdate=7 February 2020}}</ref> "The first work which is now recognized as AI was done by Warren McCulloch and Walter pits in 1943. They proposed a model of artificial neurons."<ref name="javatpoint.coma">{{cite web |title=History of Artificial Intelligence |url=https://www.javatpoint.com/history-of-artificial-intelligence |website=javatpoint.com |accessdate=7 February 2020}}</ref> ||

| 1949 || || "  Edmund Berkeley publishes Giant Brains: Or Machines That Think in which he writes: “Recently there have been a good deal of news about strange giant machines that can handle information with vast speed and skill….These machines are similar to what a brain would be if it were made of hardware and wire instead of flesh and nerves… A machine can handle information; it can calculate, conclude, and choose; it can perform reasonable operations with information. A machine, therefore, can think.”"<ref name="forbes.coms"/> ||

| 1949 || || "Donald Hebb publishes Organization of Behavior: A Neuropsychological Theory in which he proposes a theory about learning based on conjectures regarding neural networks and the ability of synapses to strengthen or weaken over time."<ref name="forbes.coms"/> "Donald Hebb demonstrated an updating rule for modifying the connection strength between neurons. His rule is now called Hebbian learning."<ref name="javatpoint.coma"/> ||

| 1950 || || " Claude Shannon’s “Programming a Computer for Playing Chess” is the first published article on developing a chess-playing computer program."<ref name="forbes.coms"/> ||

| 1950 || || "  Alan Turing publishes “Computing Machinery and Intelligence” in which he proposes “the imitation game” which will later become known as the “Turing Test.”"<ref name="forbes.coms"/> ||

| 1950 || || ". Turing, on the other hand, raised the question of the possible intelligence of a machine for the first time in his famous 1950 article "Computing Machinery and Intelligence" and described a "game of imitation", where a human should be able to distinguish in a teletype dialogue whether he is talking to a man or a machine."<ref name="coe.intf"/> ||

| 1951 || || "  Marvin Minsky and Dean Edmunds build SNARC (Stochastic Neural Analog Reinforcement Calculator), the first artificial neural network, using 3000 vacuum tubes to simulate a network of 40 neurons."<ref name="forbes.coms"/> ||

| 1952 || || " Arthur Samuel develops the first computer checkers-playing program and the first computer program to learn on its own."<ref name="forbes.coms"/> ||

| 1952 || || "Hodgkin-Huxley model of the brain as neurons forming an electrical network, with individual neurons firing in all-or-nothing (on/off) pulses."<ref name="dataversity.netw">{{cite web |title=A Brief History of Artificial Intelligence |url=https://www.dataversity.net/brief-history-artificial-intelligence/ |website=dataversity.net |accessdate=7 February 2020}}</ref> ||

| 1954 || || "In the US, one of the main motivations for the funding of AI research was the promise of machine translation (MT). Because of Cold War concerns, the US government was particularly interested in the automatic and instant translation of Russian. In 1954, the first demonstration of MT, the Georgetown-IBM experiment, showed a great promise. The system was by no means complete, consisting only six rules, a 250-item vocabulary and specialized only in Organic Chemistry."<ref name="washington.edu"/> ||

| 1955 || || "August 31, 1955 The term “artificial intelligence” is coined in a proposal for a “2 month, 10 man study of artificial intelligence” submitted by John McCarthy (Dartmouth College), Marvin Minsky (Harvard University), Nathaniel Rochester (IBM), and Claude Shannon (Bell Telephone Laboratories). The workshop, which took place a year later, in July and August 1956, is generally considered as the official birthdate of the new field."<ref name="forbes.coms"/> ||

| 1955 || || "December 1955 Herbert Simon and Allen Newell develop the Logic Theorist, the first artificial intelligence program, which eventually would prove 38 of the first 52 theorems in Whitehead and Russell's Principia Mathematica."<ref name="forbes.coms"/> " An Allen Newell and Herbert A. Simon created the "first artificial intelligence program"Which was named as "Logic Theorist". This program had proved 38 of 52 Mathematics theorems, and find new and more elegant proofs for some theorems."<ref name="javatpoint.coma"/> ||

| 1956 || || "August 31, 1955 The term “artificial intelligence” is coined in a proposal for a “2 month, 10 man study of artificial intelligence” submitted by John McCarthy (Dartmouth College), Marvin Minsky (Harvard University), Nathaniel Rochester (IBM), and Claude Shannon (Bell Telephone Laboratories). The workshop, which took place a year later, in July and August 1956, is generally considered as the official birthdate of the new field.""<ref name="forbes.coms"/> "The summer 1956 conference at Dartmouth College (funded by the Rockefeller Institute) is considered the founder of the discipline. Anecdotally, it is worth noting the great success of what was not a conference but rather a workshop. Only six people, including McCarthy and Minsky, had remained consistently present throughout this work (which relied essentially on developments based on formal logic)."<ref name="coe.intf"/><ref name="washington.edu">{{cite web |title=The History of Artificial Intelligence |url=https://courses.cs.washington.edu/courses/csep590/06au/projects/history-ai.pdf |website=washington.edu |accessdate=7 February 2020}}</ref><ref name="javatpoint.coma"/> ||

| 1956 || || "Five years later, the proof of concept was initialized through Allen Newell, Cliff Shaw, and Herbert Simon’s, Logic Theorist. The Logic Theorist was a program designed to mimic the problem solving skills of a human and was funded by Research and Development (RAND) Corporation. It’s considered by many to be the first artificial intelligence program and was presented at the Dartmouth Summer Research Project on Artificial Intelligence (DSRPAI) hosted by John McCarthy and Marvin Minsky in 1956."<ref name="harvard.edu d"/> "But the field of AI wasn't formally founded until 1956, at a conference at Dartmouth College, in Hanover, New Hampshire, where the term "artificial intelligence" was coined."<ref name="livescience.coms">{{cite web |title=A Brief History of Artificial Intelligence |url=https://www.livescience.com/49007-history-of-artificial-intelligence.html |website=livescience.com |accessdate=7 February 2020}}</ref> ||

| 1957 || || " Frank Rosenblatt develops the Perceptron, an early artificial neural network enabling pattern recognition based on a two-layer computer learning network. The New York Times reported the Perceptron to be "the embryo of an electronic computer that [the Navy] expects will be able to walk, talk, see, write, reproduce itself and be conscious of its existence." The New Yorker called it a “remarkable machine… capable of what amounts to thought.”"<ref name="forbes.coms"/> ||

| 1957 || || "Herbert Simon, economist and sociologist, prophesied in 1957 that the AI would succeed in beating a human at chess in the next 10 years, but the AI then entered a first winter. Simon's vision proved to be right... 30 years later."<ref name="coe.intf"/> ||

| 1958 || || "John McCarthy develops programming language Lisp which becomes the most popular programming language used in artificial intelligence research."<ref name="forbes.coms"/> ||

| 1959 || || "Arthur Samuel coins the term “machine learning,” reporting on programming a computer “so that it will learn to play a better game of checkers than can be played by the person who wrote the program.”"<ref name="forbes.coms"/> ||

| 1959 || || "Oliver Selfridge publishes “Pandemonium: A paradigm for learning” in the Proceedings of the Symposium on Mechanization of Thought Processes, in which he describes a model for a process by which computers could recognize patterns that have not been specified in advance."<ref name="forbes.coms"/> ||

| 1959 || || "John McCarthy publishes “Programs with Common Sense” in the Proceedings of the Symposium on Mechanization of Thought Processes, in which he describes the Advice Taker, a program for solving problems by manipulating sentences in formal languages with the ultimate objective of making programs “that learn from their experience as effectively as humans do.”"<ref name="forbes.coms"/> ||

| 1961 || || "The first industrial robot, Unimate, starts working on an assembly line in a General Motors plant in New Jersey."<ref name="forbes.coms"/> ||

| 1961 || || "James Slagle develops SAINT (Symbolic Automatic INTegrator), a heuristic program that solved symbolic integration problems in freshman calculus."<ref name="forbes.coms"/> ||

| 1963 || || " 1963 article by Reed C. Lawlor, a member of the California Bar, entitled "What Computers Can Do: Analysis and Prediction of Judicial Decisions""<ref name="coe.intf"/> ||

| 1964 || || "Daniel Bobrow completes his MIT PhD dissertation titled “Natural Language Input for a Computer Problem Solving System” and develops STUDENT, a natural language understanding computer program."<ref name="forbes.coms"/> ||

| 1964 || || {{w|Society for the Study of Artificial Intelligence and the Simulation of Behaviour}} || {{w|United Kingdom}}

| 1965 || || "Herbert Simon predicts that "machines will be capable, within twenty years, of doing any work a man can do.""<ref name="forbes.coms"/> ||

| 1965 || || "Hubert Dreyfus publishes "Alchemy and AI," arguing that the mind is not like a computer and that there were limits beyond which AI would not progress."<ref name="forbes.coms"/> ||

| 1965 || || "I.J. Good writes in "Speculations Concerning the First Ultraintelligent Machine" that “the first ultraintelligent machine is the last invention that man need ever make, provided that the machine is docile enough to tell us how to keep it under control.”"<ref name="forbes.coms"/> ||

| 1965 || || " Joseph Weizenbaum develops ELIZA, an interactive program that carries on a dialogue in English language on any topic. Weizenbaum, who wanted to demonstrate the superficiality of communication between man and machine, was surprised by the number of people who attributed human-like feelings to the computer program."<ref name="forbes.coms"/> ||

| 1965 || || "Edward Feigenbaum, Bruce G. Buchanan, Joshua Lederberg, and Carl Djerassi start working on DENDRAL at Stanford University. The first expert system, it automated the decision-making process and problem-solving behavior of organic chemists, with the general aim of studying hypothesis formation and constructing models of empirical induction in science."<ref name="forbes.coms"/> ||

| 1965 || {{w|Expert system}} || "The path was actually opened at MIT in 1965 with DENDRAL (expert system specialized in molecular chemistry) "<ref name="coe.intf"/> ||

| 1966 || || "Shakey the robot is the first general-purpose mobile robot to be able to reason about its own actions. In a Life magazine 1970 article about this “first electronic person,” Marvin Minsky is quoted saying with “certitude”: “In from three to eight years we will have a machine with the general intelligence of an average human being.”"<ref name="forbes.coms"/> ||

| 1966 || || "1966: Birth of the first chatbot The German-American computer scientist Joseph Weizenbaum of the Massachusetts Institute of Technology invents a computer program that communicates with humans. ‘ELIZA’ uses scripts to simulate various conversation partners such as a psychotherapist. Weizenbaum is surprised at the simplicity of the means required for ELIZA to create the illusion of a human conversation partner."<ref name="bosch.coms">{{cite web |title=The history of artificial intelligence |url=https://www.bosch.com/stories/history-of-artificial-intelligence/ |website=bosch.com |accessdate=7 February 2020}}</ref> " The researchers emphasized developing algorithms which can solve mathematical problems. Joseph Weizenbaum created the first chatbot in 1966, which was named as ELIZA."<ref name="javatpoint.coma"/> ||

| 1966 || || "The onset of the AI winter could be traced to the government’s decision to pull back on AI research. The decisions

were often attributed to a couple of infamous reports, specifically the Automatic Language Processing Advisory

Committee (ALPAC) report by U.S. Government in 1966, and the Lighthill report for the British government in 1973."<ref name="washington.edu"/> ||

| 1968 || || "The film 2001: Space Odyssey is released, featuring Hal, a sentient computer."<ref name="forbes.coms"/> "In 1968 Stanley Kubrick directed the film "2001 Space Odyssey" where a computer - HAL 9000 (only one letter away from those of IBM) summarizes in itself the whole sum of ethical questions posed by AI: will it represent a high level of sophistication, a good for humanity or a danger? The impact of the film will naturally not be scientific but it will contribute to popularize the theme, just as the science fiction author Philip K. Dick, who will never cease to wonder if, one day, the machines will experience emotions."<ref name="coe.intf"/> ||

| 1968 || || "Terry Winograd develops SHRDLU, an early natural language understanding computer program."<ref name="forbes.coms"/> ||

| 1969 || || "Arthur Bryson and Yu-Chi Ho describe backpropagation as a multi-stage dynamic system optimization method. A learning algorithm for multi-layer artificial neural networks, it has contributed significantly to the success of deep learning in the 2000s and 2010s, once computing power has sufficiently advanced to accommodate the training of large networks."<ref name="forbes.coms"/> ||

| 1969 || || "Marvin Minsky and Seymour Papert publish Perceptrons: An Introduction to Computational Geometry, highlighting the limitations of simple neural networks.  In an expanded edition published in 1988, they responded to claims that their 1969 conclusions significantly reduced funding for neural network research: “Our version is that progress had already come to a virtual halt because of the lack of adequate basic theories… by the mid-1960s there had been a great many experiments with perceptrons, but no one had been able to explain why they were able to recognize certain kinds of patterns and not others.”"<ref name="forbes.coms"/> ||

| 1970 || || "It was with the advent of the first microprocessors at the end of 1970 that AI took off again and entered the golden age of expert systems."<ref name="coe.intf"/> ||

| 1970 || || "The first anthropomorphic robot, the WABOT-1, is built at Waseda University in Japan. It consisted of a limb-control system, a vision system and a conversation system."<ref name="forbes.coms"/> ||

| 1970 || || " In 1970 Marvin Minsky told Life Magazine, “from three to eight years we will have a machine with the general intelligence of an average human being.” However, while the basic proof of principle was there, there was still a long way to go before the end goals of natural language processing, abstract thinking, and self-recognition could be achieved."<ref name="harvard.edu d"/> ||

| 1972 || {{w|Expert system}} || "MYCIN, an early expert system for identifying bacteria causing severe infections and recommending antibiotics, is developed at Stanford University."<ref name="harvard.edu d"/> "Stanford University in 1972 with MYCIN (system specialized in the diagnosis of blood diseases and prescription drugs). "<ref name="coe.intf"/> "1972: AI enters the medical field. With ‘MYCIN’, artificial intelligence finds its way into medical practices: The expert system developed by Ted Shortliffe at Stanford University is used for the treatment of illnesses. Expert systems are computer programs that bundle the knowledge for a specialist field using formulas, rules, and a knowledge database. They are used for diagnosis and treatment support in medicine."<ref name="bosch.coms"/> ||

| 1972 || || "The first intelligent humanoid robot was built in Japan which was named as WABOT-1."<ref name="javatpoint.coma"/> ||

| 1973 || || "James Lighthill reports to the British Science Research Council on the state artificial intelligence research, concluding that "in no part of the field have discoveries made so far produced the major impact that was then promised," leading to drastically reduced government support for AI research."<ref name="harvard.edu d"/> "The “Lighthill report” commonly refers to “Artificial Intelligence: A General Survey” by Professor Sir James Lighthill of Cambridge University in 1973. His review of AI was at the request of Brian Flowers, the head of the British Science Research Council, the main funding body of British university scientific research. The review was to help the council evaluate requests for support in AI research. In the paper, Lighthill offered a pessimistic prognosis for AI, stating that “in no part of the field have discoveries made so far produced the major impact that was then promised”"<ref name="washington.edu"/> ||

| 1973 || || "The onset of the AI winter could be traced to the government’s decision to pull back on AI research. The decisions

were often attributed to a couple of infamous reports, specifically the Automatic Language Processing Advisory

Committee (ALPAC) report by U.S. Government in 1966, and the Lighthill report for the British government in 1973."<ref name="washington.edu"/> ||

| 1976 || || "Computer scientist Raj Reddy publishes “Speech Recognition by Machine: A Review” in the Proceedings of the IEEE, summarizing the early work on Natural Language Processing (NLP)."<ref name="forbes.coms"/> ||

| 1977 || || {{w|iLabs}} || {{w|Italy}}

| 1978 || Expert system || "The XCON (eXpert CONfigurer) program, a rule-based expert system assisting in the ordering of DEC's VAX computers by automatically selecting the components based on the customer's requirements, is developed at Carnegie Mellon University."<ref name="forbes.coms"/> ||

| 1978 || || ". In 1978 Japan’s Ministry of International Trade and Industry (MITI) commissioned a study of what the future would hold

for computers, and three years later attempted to construct fifth generation computers – creating what project heads described as an ‘epochal’ leap in computer technology, in order to give Japan the technological lead for years to come. This new generation of machines would not be built on standard microprocessors, but multiprocessor machines specializing in logic programming. The bet was that these high-power logic machines would catalyze the world of information processing and realize artificial intelligence."<ref name="washington.edu"/> ||

| 1979 || || "The Stanford Cart successfully crosses a chair-filled room without human intervention in about five hours, becoming one of the earliest examples of an autonomous vehicle."<ref name="forbes.coms"/> ||

| 1979 || || {{w|Association for the Advancement of Artificial Intelligence}} || {{w|United States}}

| 1980 || Expert system || " After AI winter duration, AI came back with "Expert System". Expert systems were programmed that emulate the decision-making ability of a human expert."<ref name="javatpoint.coma"/> ||

| 1980 || || "Wabot-2 is built at Waseda University in Japan, a musician humanoid robot able to communicate with a person, read a musical score and play tunes of average difficulty on an electronic organ."<ref name="forbes.coms"/> ||

| 1980 || Expert system || "Digital Equipment Corporation began requiring their sales team use an Expert System named XCON when placing customer orders. DEC sold a broad range of computer components, but the sales force was not especially knowledgeable about what they were selling."<ref name="dataversity.netw"/> ||

| 1980 || || "In the Year 1980, the first national conference of the American Association of Artificial Intelligence was held at Stanford University."<ref name="javatpoint.coma"/> ||

| 1980 || || "The year of AI. In 1980, AI research fired back up with an expansion of funds and algorithmic tools. With deep learning techniques, the computer learned with the user experience."<ref name="data-flair.training">{{cite web |title=History of Artificial Intelligence – AI of the past, present and the future! |url=https://data-flair.training/blogs/history-of-artificial-intelligence/ |website=data-flair.training |accessdate=4 March 2020}}</ref> ||

| 1981 || || "he Japanese Ministry of International Trade and Industry budgets $850 million for the Fifth Generation Computer project. The project aimed to develop computers that could carry on conversations, translate languages, interpret pictures, and reason like human beings"<ref name="forbes.coms"/> ||

| 1981 || || ". In 1978 Japan’s Ministry of International Trade and Industry (MITI) commissioned a study of what the future would hold

for computers, and three years later attempted to construct fifth generation computers – creating what project heads described as an ‘epochal’ leap in computer technology, in order to give Japan the technological lead for years to come. This new generation of machines would not be built on standard microprocessors, but multiprocessor machines specializing in logic programming. The bet was that these high-power logic machines would catalyze the world of information processing and realize artificial intelligence."<ref name="washington.edu"/> ||

| 1984 || || "Electric Dreams is released, a film about a love triangle between a man, a woman and a personal computer."<ref name="forbes.coms"/> ||

| 1984 || || "At the annual meeting of AAAI, Roger Schank and Marvin Minsky warn of the coming “AI Winter,” predicting an immanent bursting of the AI bubble (which did happen three years later), similar to the reduction in AI investment and research funding in the mid-1970s."<ref name="forbes.coms"/> ||

| 1986 || || "First driverless car, a Mercedes-Benz van equipped with cameras and sensors, built at Bundeswehr University in Munich under the direction of Ernst Dickmanns, drives up to 55 mph on empty streets."<ref name="forbes.coms"/> ||

| 1986 || || "October 1986 David Rumelhart, Geoffrey Hinton, and Ronald Williams publish ”Learning representations by back-propagating errors,” in which they describe “a new learning procedure, back-propagation, for networks of neurone-like units.”"<ref name="forbes.coms"/> ||

| 1986 || || "1986: ‘NETtalk’ speaks. The computer is given a voice for the first time. Terrence J. Sejnowski and Charles Rosenberg teach their ‘NETtalk’ program to speak by inputting sample sentences and phoneme chains. NETtalk is able to read words and pronounce them correctly, and can apply what it has learned to words it does not know. It is one of the early artificial neural networks — programs that are supplied with large datasets and are able to draw their own conclusions on this basis. Their structure and function are thereby similar to those of the human brain."<ref name="bosch.coms"/> ||

| 1987 || || "The video Knowledge Navigator, accompanying Apple CEO John Sculley’s keynote speech at Educom, envisions a future in which “knowledge applications would be accessed by smart agents working over networks connected to massive amounts of digitized information.”"<ref name="forbes.coms"/> ||

| 1988 || || "Judea Pearl publishes Probabilistic Reasoning in Intelligent Systems. His 2011 Turing Award citation reads: “Judea Pearl created the representational and computational foundation for the processing of information under uncertainty. He is credited with the invention of Bayesian networks, a mathematical formalism for defining complex probability models, as well as the principal algorithms used for inference in these models. This work not only revolutionized the field of artificial intelligence but also became an important tool for many other branches of engineering and the natural sciences.”"<ref name="forbes.coms"/> ||

| 1988 || || "Rollo Carpenter develops the chat-bot Jabberwacky to "simulate natural human chat in an interesting, entertaining and humorous manner." It is an early attempt at creating artificial intelligence through human interaction."<ref name="forbes.coms"/> ||

| 1988 || || "Members of the IBM T.J. Watson Research Center publish “A statistical approach to language translation,” heralding the shift from rule-based to probabilistic methods of machine translation, and reflecting a broader shift to “machine learning” based on statistical analysis of known examples, not comprehension and “understanding” of the task at hand (IBM’s project Candide, successfully translating between English and French, was based on 2.2 million pairs of sentences, mostly from the bilingual proceedings of the Canadian parliament)."<ref name="forbes.coms"/> ||

| 1989 || || "Marvin Minsky and Seymour Papert publish an expanded edition of their 1969 book Perceptrons. In “Prologue: A View from 1988” they wrote: “One reason why progress has been so slow in this field is that researchers unfamiliar with its history have continued to make many of the same mistakes that others have made before them.”"<ref name="forbes.coms"/> ||

| 1989 || || "Yann LeCun and other researchers at AT&T Bell Labs successfully apply a backpropagation algorithm to a multi-layer neural network, recognizing handwritten ZIP codes. Given the hardware limitations at the time, it took about 3 days (still a significant improvement over earlier efforts) to train the network."<ref name="forbes.coms"/> ||

| 1990 || || "Rodney Brooks publishes “Elephants Don’t Play Chess,” proposing a new approach to AI—building intelligent systems, specifically robots, from the ground up and on the basis of ongoing physical interaction with the environment: “The world is its own best model… The trick is to sense it appropriately and often enough.”"<ref name="forbes.coms"/> ||

| 1991 || || {{w|European Neural Network Society}} ||  

| 1993 || || "Vernor Vinge publishes “The Coming Technological Singularity,” in which he predicts that “within thirty years, we will have the technological means to create superhuman intelligence. Shortly after, the human era will be ended.”"<ref name="forbes.coms"/> ||

| 1995 || || "Richard Wallace develops the chatbot A.L.I.C.E (Artificial Linguistic Internet Computer Entity), inspired by Joseph Weizenbaum's ELIZA program, but with the addition of natural language sample data collection on an unprecedented scale, enabled by the advent of the Web."<ref name="forbes.coms"/> ||

| 1997 || || "Sepp Hochreiter and Jürgen Schmidhuber propose Long Short-Term Memory (LSTM), a type of a recurrent neural network used today in handwriting recognition and speech recognition."<ref name="forbes.coms"/> ||

| 1997 || || ". In 1997, reigning world chess champion and grand master Gary Kasparov was defeated by IBM’s Deep Blue, a chess playing computer program. This highly publicized match was the first time a reigning world chess champion loss to a computer and served as a huge step towards an artificially intelligent decision making program."<ref name="harvard.edu d"/> "Deep Blue becomes the first computer chess-playing program to beat a reigning world chess champion."<ref name="forbes.coms"/> ||

| 1997 || || " speech recognition software, developed by Dragon Systems, was implemented on Windows. This was another great step forward but in the direction of the spoken language interpretation endeavor."<ref name="harvard.edu d"/> ||

| 1998 || || "Dave Hampton and Caleb Chung create Furby, the first domestic or pet robot."<ref name="harvard.edu d"/> ||

| 1998 || || "Yann LeCun, Yoshua Bengio and others publish papers on the application of neural networks to handwriting recognition and on optimizing backpropagation."<ref name="harvard.edu d"/> ||

| 2000 || || "MIT’s Cynthia Breazeal develops Kismet, a robot that could recognize and simulate emotions."<ref name="harvard.edu d"/> ||

| 2000 || || "Honda's ASIMO robot, an artificially intelligent humanoid robot, is able to walk as fast as a human, delivering trays to customers in a restaurant setting."<ref name="harvard.edu d"/> ||

| 2001 || || "A.I. Artificial Intelligence is released, a Steven Spielberg film about David, a childlike android uniquely programmed with the ability to love."<ref name="harvard.edu d"/> ||

| 2001 || || {{w|Artificial General Intelligence Research Institute}} || {{w|United States}}

| 2002 || || "Year 2002: for the first time, AI entered the home in the form of Roomba, a vacuum cleaner."<ref name="javatpoint.coma"/> ||

| 2003 || || "In 2003, Geoffrey Hinton (University of Toronto), Yoshua Bengio (University of Montreal) and Yann LeCun (University of New York) decided to start a research program to bring neural networks up to date. Experiments conducted simultaneously at Microsoft, Google and IBM with the help of the Toronto laboratory in Hinton showed that this type of learning succeeded in halving the error rates for speech recognition. Similar results were achieved by Hinton's image recognition team."<ref name="coe.intf"/> ||

| 2004 || || "The first DARPA Grand Challenge, a prize competition for autonomous vehicles, is held in the Mojave Desert. None of the autonomous vehicles finished the 150-mile route."<ref name="harvard.edu d"/> ||

| 2006 || || "Oren Etzioni, Michele Banko, and Michael Cafarella coin the term “machine reading,” defining it as an inherently unsupervised “autonomous understanding of text.”"<ref name="harvard.edu d"/> ||

| 2006 || || "Geoffrey Hinton publishes “Learning Multiple Layers of Representation,” summarizing the ideas that have led to “multilayer neural networks that contain top-down connections and training them to generate sensory data rather than to classify it,” i.e., the new approaches to deep learning."<ref name="harvard.edu d"/> ||

| 2006 || || "Year 2006: AI came in the Business world till the year 2006. Companies like Facebook, Twitter, and Netflix also started using AI."<ref name="javatpoint.coma"/> ||

| 2006 || || The first AI doctor-conducted unassisted robotic surgery is on a 34-year-old male to correct {{w|heart arrythmia}}. The results are rated as better than an above-average human surgeon. The machine has a {{w|database}} of 10,000 similar operations, and so, in the words of its designers, is "more than qualified to operate on any patient".<ref>{{cite news|url=https://www.engadget.com/2006/05/19/robot-surgeon-performs-worlds-first-unassisted-operation|title=Autonomous Robotic Surgeon performs surgery on first live human|date=19 May 2006|publisher=[[Engadget]]}}</ref><ref>{{cite web |url=http://www.physorg.com/news67222790.html |title=Robot surgeon carries out 9-hour operation by itself|publisher=[[Phys.Org]]}}</ref>

| 2007 || || "Fei Fei Li and colleagues at Princeton University start to assemble ImageNet, a large database of annotated images designed to aid in visual object recognition software research."<ref name="harvard.edu d"/> ||

| 2009 || || "Rajat Raina, Anand Madhavan and Andrew Ng publish “Large-scale Deep Unsupervised Learning using Graphics Processors,” arguing that “modern graphics processors far surpass the computational capabilities of multicore CPUs, and have the potential to revolutionize the applicability of deep unsupervised learning methods.”"<ref name="harvard.edu d"/> ||

| 2009 || || "Google starts developing, in secret, a driverless car. In 2014, it became the first to pass, in Nevada, a U.S. state self-driving test."<ref name="harvard.edu d"/> ||

| 2009 || || "Computer scientists at the Intelligent Information Laboratory at Northwestern University develop Stats Monkey, a program that writes sport news stories without human intervention."<ref name="harvard.edu d"/> ||

| 2010 || || "Launch of the ImageNet Large Scale Visual Recognition Challenge (ILSVCR), an annual AI object recognition competition."<ref name="harvard.edu d"/> ||  

| 2011 || || "A convolutional neural network wins the German Traffic Sign Recognition competition with 99.46% accuracy (vs. humans at 99.22%)."<ref name="harvard.edu d"/> ||

| 2011 || || "And in 2011, the computer giant's question-answering system Watson won the quiz show "Jeopardy!" by beating reigning champions Brad Rutter and Ken Jennings."<ref name="livescience.coms"/> ||

| 2011 || || "This year, the talking computer "chatbot" Eugene Goostman captured headlines for tricking judges into thinking he was real skin-and-blood human during a Turing test,"<ref name="livescience.coms"/> ||

| 2011 || || "Watson, a natural language question answering computer, competes on Jeopardy! and defeats two former champions."<ref name="harvard.edu d"/> ||

| 2011 || || "Researchers at the IDSIA in Switzerland report a 0.27% error rate in handwriting recognition using convolutional neural networks, a significant improvement over the 0.35%-0.40% error rate in previous years."<ref name="harvard.edu d"/> ||

| 2011 || || "2011: AI enters everyday life. Technology leaps in the hardware and software fields pave the way for artificial intelligence to enter everyday life. Powerful processors and graphics cards in computers, smartphones, and tablets give regular consumers access to AI programs. Digital assistants in particular enjoy great popularity: Apple’s ‘Siri’ comes to the market in 2011, Microsoft introduces the ‘Cortana’ software in 2014, and Amazon presents Amazon Echo with the voice service ‘Alexa’ in 2015."<ref name="bosch.coms"/> ||

| 2012 || || "June 2012 Jeff Dean and Andrew Ng report on an experiment in which they showed a very large neural network 10 million unlabeled images randomly taken from YouTube videos, and “to our amusement, one of our artificial neurons learned to respond strongly to pictures of... cats.”"<ref name="harvard.edu d"/> ||

| 2012 || || "October 2012 A convolutional neural network designed by researchers at the University of Toronto achieve an error rate of only 16% in the ImageNet Large Scale Visual Recognition Challenge, a significant improvement over the 25% error rate achieved by the best entry the year before."<ref name="forbes.coms"/> ||

| 2014 || || "Google starts developing, in secret, a driverless car. In 2014, it became the first to pass, in Nevada, a U.S. state self-driving test."<ref name="harvard.edu d"/> ||

| 2014 || || {{w|Allen Institute for AI}} || {{w|United States}} 

| 2014 || || "Microsoft introduces the ‘Cortana’ software"<ref name="bosch.coms"/> ||

| 2014 || || {{w|Future of Life Institute}} || {{w|United States}}

| 2015 || || "Amazon introduces service ‘Alexa’ in 2015."<ref name="bosch.coms"/> ||

| 2016 || || "March 2016 Google DeepMind's AlphaGo defeats Go champion Lee Sedol."<ref name="harvard.edu d"/> ||

| 2016 || || {{w|Center for Human-Compatible Artificial Intelligence}} || {{w|United States}}

| 2016 || || {{w|Partnership on AI}} ||  

| 2018 || || "2018: AI debates space travel and makes a hairdressing appointment. These two examples demonstrate the capabilities of artificial intelligence: In June, ‘Project Debater’ from IBM debated complex topics with two master debaters — and performed remarkably well. A few weeks before, Google demonstrated at a conference how the AI program ‘Duplex’ phones a hairdresser and conversationally makes an appointment — without the lady on the other end of the line noticing that she is talking to a machine."<ref name="bosch.coms"/> ||

| 2018 || || {{w|European Laboratory for Learning and Intelligent Systems}} ||  

| 2018 || || {{w|Innovation Center for Artificial Intelligence}} || {{w|Netherlands}}

| 2019 || || {{w|Center for Security and Emerging Technology}} || {{w|United States}}

The initial version of the timeline was written by [[User:FIXME|FIXME]].

 

* [https://dev.to/lschultebraucks/a-short-history-of-artificial-intelligence-7hm]

* [http://people.idsia.ch/~juergen/ai.html]

* [https://www.atariarchives.org/deli/artificial_intelligence.php]

* [https://daxueconsulting.com/history-china-artificial-intelligence/]