Theme Timeline
A history of AI
Credit: Bert van Dijk/Getty images.
Powered by
AI is not a new concept. The idea of inanimate objects coming to life as intelligent beings goes back to Greek antiquity. In the first half of the 20th century, science fiction's golden age familiarized the world with the concept of artificially intelligent robots. In 1950, Alan Turing published the seminal paper Computing Machinery and Intelligence, in which he considered the question, “Can machines think?”. Six years later, during a conference at Dartmouth College, the term ‘artificial intelligence’ was accepted as the name of the field of study into thinking machines.
The progress of AI has not been linear. There have been two significant periods of reduced funding and interest, known as AI winters. The first ran from 1974 to 1980, and the second from 1987 to 1993. Following the end of this second winter, interest slowly picked up, helped by IBM’s chess-playing computer Deep Blue’s landmark 1997 victory over grandmaster Garry Kasparov. Just over a decade later, Google built the first autonomous car, and OpenAI developed a language model that was able to write original prose with human-like fluency. The current AI boom was underway.
The major milestones in the journey of the AI theme are set out in the timeline below.
The AI story
1642
Pascal invented the first digital calculating machine.
1854
George Boole invented Boolean algebra.
1913
Formal logic is revolutionized in Principia Mathematica by Whitehead and Russell.
1948
Von Neumann asserted that a general computer could simulate any effective procedure.
1950
Alan Turing developed the Turing Test to assess a machine's ability to exhibit intelligent (human-like) behavior.
1952
Arthur Samuel wrote the first game-playing program for draughts (checkers).
1956
The Dartmouth Summer Research Project on Artificial Intelligence was held, a foundational event for the field.
1959
John McCarthy and Marvin Minsky founded the MIT AI Lab.
1973
The Lighthill Report, heavily critical of AI research, set study of the area back in the UK and the US.
1997
World chess champion Garry Kasparov is defeated by IBM’s Deep Blue.
2005
Tivo popularized recommendation technology based on tracking web activity and media usage.
2009
Google started its self-driving car project (later renamed Waymo), building its first autonomous car.
2011
IBM Watson beat human champions in the TV game show Jeopardy!
2011
Apple released the iPhone 4S, containing the natural language-based virtual assistant Siri.
2014
Tesla introduced AutoPilot, software that was later upgraded for fully autonomous driving.
2014
Amazon launched the Echo, an intelligent voice-activated speaker that included the Alexa virtual assistant.
2015
Baidu launched Duer, its intelligent assistant.
2016
Google DeepMind’s AlphaGo algorithm beat world Go champion Lee Sedol 4-1.
2017
Google Research team publishes the Transformer model ushering the generative AI revolution.
2017
Libratus, designed by Carnegie Mellon researchers, beat the top 4 players in no-limit Texas hold ’em poker.
2018
Alibaba’s AI model scored better than humans in a Stanford University reading and comprehension test.
2019
The US added four of China’s leading AI start-ups to a trade blacklist.
2020
COVID-19 accelerated investments in AI.
2020
OpenAI launched the language model GPT-3, which could write original prose with human-equivalent fluency.
2022
The US banned Nvidia and AMD from selling advanced AI chips, including GPUs, to China.
2030
GlobalData forecasts that spending on AI technology will be more than $1,037 billion.
2035
Fully autonomous vehicles (Level 5) will be available to consumers.
2060
50% probability of full human-level AI, according to a poll of AI experts.
2120
75% probability of full human-level AI, according to a poll of AI experts.
Source: GlobalData Thematic Intelligence
GlobalData, the leading provider of industry intelligence, provided the underlying data, research, and analysis used to produce this article.
GlobalData’s Thematic Intelligence uses proprietary data, research, and analysis to provide a forward-looking perspective on the key themes that will shape the future of the world’s largest industries and the organisations within them.
