Detailed · 25 events
A History of Artificial Intelligence
1950s
02 events
null0 (Wikimedia Commons, via Flickr) · CC BY-SA 2.0 · Commons ↗ Over roughly eight weeks in the summer of 1956 at Dartmouth College in New Hampshire, ten researchers including John McCarthy, Marvin Minsky, Claude Shannon, and Nathaniel Rochester proposed and adopted the term 'artificial intelligence'. Its historical weight lies less in any specific technical result than in establishing the field's own name and the researcher network that would carry it for decades.
- Related people
- John McCarthy · Marvin Minsky · Claude Shannon
- Appears in
- A General History of Information Technology
Frank Rosenblatt at the Cornell Aeronautical Laboratory introduced the perceptron, a simple learning device that weighted inputs and applied a threshold. In 1960 the 'Mark I Perceptron', a software implementation on the IBM 704 connected to a 400-pixel sensor array, was demonstrated to the US Navy. It marks the start of the neural-network lineage and remains the structural skeleton beneath the MLP, the convolutional network, and modern deep learning.
- Related people
- Frank Rosenblatt
1960s
01 eventsJoseph Weizenbaum at MIT built ELIZA, a natural-language conversation program. Its most famous script, 'DOCTOR', imitated a Rogerian psychotherapist by reflecting user input back as questions through simple pattern-matching. Many subjects in early sessions reported feeling that the machine 'understood' them—an effect Weizenbaum found unsettling enough that he later wrote *Computer Power and Human Reason* (1976) in part to caution against it.
- Related people
- Joseph Weizenbaum
1970s
01 eventsCommissioned by the British Science Research Council, James Lighthill produced a 1973 report assessing the state of AI research and concluded that 'in no part of the field have the discoveries made so far produced the major impact that was then promised.' Funding was sharply cut in Britain; DARPA in the US made similar moves. The decade that followed is known as the first AI winter, the first sustained rebuttal of the optimistic schedules set out by Newell, Minsky, and others.
1980s
01 eventsStanford's MYCIN (bacterial-infection diagnosis) and DEC's XCON (automated VAX configuration) showed the appeal of encoding domain expertise as explicit 'if-then' rules. The approach spread rapidly into industry in the early 1980s; Japan's MITI launched the Fifth Generation Computer Project (1982–92). At the 1985 peak, worldwide AI spending reached roughly US$1 billion. The maintenance burden and brittleness of rule systems, however, collapsed the boom by the end of the decade—the second AI winter.
1990s
01 eventsIBM's chess-specific machine Deep Blue defeated the reigning world champion Garry Kasparov 3.5–2.5 in their six-game rematch. Kasparov had won the 1996 series; IBM substantially upgraded both hardware and evaluation function over the following year. It was the first decisive defeat of a top human chess player by a machine, and is often cited in AI history as a symbolic threshold—though its substance was game-tree search plus a specialised evaluation function, with no modern learning involved.
- Related organizations
- International Business Machines (IBM)
- Appears in
- A General History of Information Technology
2010s
05 events
Daniel Voigt Godoy (Wikimedia Commons) · CC BY 4.0 · Commons ↗ At ImageNet 2012, Alex Krizhevsky, Ilya Sutskever, and Geoffrey Hinton of the University of Toronto reached a top-5 error rate of 15.3%—more than ten points ahead of the runner-up's 26.2% obtained by conventional methods. Their convolutional neural network, 'AlexNet', trained on two NVIDIA GTX 580 GPUs, proved the practical viability of deep learning overnight. Computer vision shifted, almost completely, from hand-engineered features to deep learning from that point forward.
- Related people
- Geoffrey Hinton
- Appears in
- A General History of Information Technology · A History of Semiconductors and Hardware
DeepMind's AlphaGo won its five-game series against Lee Sedol, one of the world's top Go players, 4–1. The combinatorial explosion of Go had long been thought to put a machine victory at least a decade away; the combination of Monte Carlo tree search and deep reinforcement learning broke that wall. Move 37 in Game 2—'the divine move'—introduced a placement so unlike anything a human player would have chosen that the professional Go community discussed it for weeks.
- Related organizations
- DeepMind · Google
- Appears in
- A General History of Information Technology
Ashish Vaswani and colleagues at Google Brain and Google Research proposed the Transformer—a sequence-to-sequence architecture built solely on self-attention. It displaced the RNN and LSTM, the prevailing NLP architectures, with a structure that parallelised easily and trained efficiently. By 2026 the paper had been cited more than 150,000 times; every modern large language model (BERT, the GPT family, Claude, Gemini) is a descendant.
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Daniel Voigt Godoy (Wikimedia Commons) · CC BY 4.0 · Commons ↗ Jacob Devlin and colleagues at Google AI posted BERT (Bidirectional Encoder Representations from Transformers) to arXiv. By pretraining a Transformer encoder bidirectionally as a masked-language model, it rewrote scores on GLUE and other NLP benchmarks at a stroke, and established the 'pretrain-then-fine-tune' paradigm that underlies every modern LLM. With the autoregressive GPT family, it forms one of the two great currents of Transformer-based language modelling.
- Related organizations
- Appears in
- A History of Search Engines
Dual-core A5, an eight-megapixel camera, and the Siri voice assistant. Steve Jobs died on 5 October, the day after the unveiling—the 4S effectively became his last product. Siri, derived from a startup spun out of SRI International and acquired by Apple, pushed the idea of operating a smartphone through natural language into the mainstream.
- Related people
- Steve Jobs
- Related organizations
- Apple Inc.
- Related products
- iPhone
- Appears in
- A History of the iPhone · A History of Mobile Phones and Smartphones
2020s
14 eventsOpenAI's 175-billion-parameter language model. A more-than-hundredfold scale-up from GPT-2 (1.5B), it demonstrated 'few-shot' competence across text generation, summarisation, translation, and code—handling many tasks from a few in-prompt examples. The result pushed the research conversation toward scaling laws for large language models and reshaped the direction of AI investment.
- Related organizations
- OpenAI
OpenAI (Wikimedia Commons) · Public domain (below threshold of originality) · Commons ↗ OpenAI made ChatGPT publicly available—GPT-3.5 fine-tuned for dialogue and accessible free through any browser. One million users within five days; one hundred million within two months (the fastest growth of any consumer internet service to that point). Overnight, generative AI moved from a specialist research conversation into homes, schools, and workplaces, and prompted strategic pivots at Google, Meta, Anthropic, and Microsoft.
- Related organizations
- OpenAI
- Appears in
- A General History of Information Technology
Hstoops / Microsoft (Wikimedia Commons) · Public domain (below threshold of originality; trademark applies) · Commons ↗ Microsoft unveiled 'New Bing'—Bing search with GPT-4-based chat integrated—and announced its plans to bring Copilot to Microsoft 365 in the same period. Only two months after the ChatGPT launch, this brought LLMs into the central battlefronts of search and productivity software at once, and triggered the industry-wide pivot to 'how do we integrate an LLM into our existing product?'. Google announced Bard the following day in response.
- Related organizations
- Microsoft Corporation · OpenAI
- Appears in
- A History of Microsoft · A History of Search Engines
Anthropic (Wikimedia Commons) · Public domain (below threshold of originality) · Commons ↗ Anthropic—founded in 2021 by the Amodei siblings (Dario and Daniela) and others after their departure from OpenAI—released Claude, its conversational LLM, to the public. By coincidence OpenAI announced GPT-4 the same day. Anthropic emphasises its own safety methodology (Constitutional AI), and the two-pole structure of generative AI was established. Google invested US$400 million in 2023; Amazon committed up to US$4 billion over 2023–24. Anthropic grew into the most well-capitalised counter-pole to OpenAI.
- Related organizations
- Anthropic · OpenAI
- Appears in
- A General History of Information Technology
OpenAI announced GPT-4. The first major LLM to accept image input, it posted top-decile scores on the US Bar exam and AP tests. Parameter counts, training data, and architectural details were withheld—marking OpenAI's shift from the 'publish-and-research' posture of GPT-3 toward a more commercially closed research organisation.
- Related organizations
- OpenAI
Christopher P. Michel (Wikimedia Commons) · CC BY-SA 4.0 · Commons ↗ Geoffrey Hinton—called the 'Godfather of AI'—revealed in a New York Times interview that he had left Google after a decade so he could speak about the dangers of AI without considering how it affected Google. He said he regretted parts of his life's work, and that what he had thought was 30 to 50 years off he no longer believed was. He warned of a flood of misinformation, job displacement, and autonomous weapons. An exceptional alarm from the man whose 2012 AlexNet ignited the deep-learning revolution, it accelerated international debate on AI regulation.
- Related people
- Geoffrey Hinton
- Related organizations
- Appears in
- A General History of Information Technology
Adam Schultz / The White House (Wikimedia Commons) · Public domain (PD-USGov-POTUS) · Commons ↗ US President Joe Biden signed an executive order titled 'Safe, Secure, and Trustworthy Development and Use of Artificial Intelligence' (Executive Order 14110). It required developers of models above a compute threshold to report to the government, directed NIST to lead the development of AI safety evaluation standards, and addressed discrimination in immigration, housing, and criminal justice. The most comprehensive US AI regulatory framework to date. The Trump administration would rescind it in January 2025.
Steve Jennings / TechCrunch (Wikimedia Commons) · CC BY 2.0 · Commons ↗ On 17 November, the OpenAI board fired Sam Altman as CEO, citing 'a lack of consistent candour in his communications with the board'. The dismissal grew out of tensions between AI-safety and acceleration factions and questions about Altman's conduct. About 700 of 770 employees signed a letter threatening to resign; Microsoft signalled it would take Altman aboard; and within five days, on 22 November, Altman was reinstated. The safety-leaning directors were removed, and Bret Taylor (chair), Larry Summers, and Adam D'Angelo joined the new board. The episode is remembered as a shock to the very governance structure of the AI industry.
- Related organizations
- OpenAI · Microsoft Corporation
- Appears in
- A General History of Information Technology
European Parliament / Laia Ros (Wikimedia Commons) · CC BY 2.0 · Commons ↗ The European Parliament adopted the AI Act 523 to 46. It classifies AI systems into four risk tiers—unacceptable, high, limited, minimal—prohibits some outright (social-credit scoring, indiscriminate biometric recognition), and imposes strict duties on high-risk AI in medicine, hiring, and justice. General-purpose AI (GPAI) models are required to provide transparency and respect copyright. The Council of the EU adopted it on 21 May and the Act entered into force on 1 August 2024. As the world's first comprehensive AI regulation, it has become a textbook 'Brussels effect' reference point for AI legislation worldwide.
Electronic Frontier Foundation (Wikimedia Commons) · CC BY 3.0 · Commons ↗ On 10 January, OpenAI quietly removed the 'military and warfare' prohibition from its usage policy, opening the door to defense work. In November of the same year, Anthropic announced a partnership with Palantir and AWS to provide Claude to the US intelligence and defense community. The pretense that generative AI was a peaceful Silicon Valley tool fell away; AI was openly recast as critical national-security infrastructure. A US Department of Defense collaboration with OpenAI was also disclosed in the same year; the integration with the military-industrial complex passed a point of no return.
- Related organizations
- OpenAI · Anthropic
- Appears in
- A General History of Information Technology
Jay Dixit (Wikimedia Commons) · CC BY-SA 4.0 · Commons ↗ On 8 October, the Nobel Prize in Physics was awarded to John Hopfield (the Hopfield network) and Geoffrey Hinton (the Boltzmann machine and deep learning). The next day, the Chemistry prize went to David Baker (computational protein design) and Demis Hassabis and John Jumper (DeepMind's AlphaFold2 for protein structure prediction). Both basic-science prizes going to AI work in the same week was unprecedented—a recognition of machine learning as an established scientific field. Hinton himself remarked that AlphaFold lay 'on a direct line' from his work.
- Related people
- Geoffrey Hinton
- Related organizations
- DeepMind
- Appears in
- A General History of Information Technology
DeepSeek (Wikimedia Commons) · MIT License · Commons ↗ China's DeepSeek released DeepSeek-R1, an open-weights reasoning model on par with OpenAI's o1, under the MIT licence. The reported training cost was extraordinarily low (single-digit millions of dollars), and it was trained on older NVIDIA H800s permitted under US export controls. The market reaction was violent: on 27 January, NVIDIA stock fell about 17% in a single day, erasing roughly US$589 billion in market value—the largest single-day loss in US stock market history. The narrative of a US monopoly on frontier LLMs cracked under the combination of low cost, open weights, and a Chinese provenance.
Daniel Torok / The White House (Wikimedia Commons) · Public domain (PD-USGov-POTUS) · Commons ↗ On 20 January, the second Trump administration took office and rescinded Biden's AI Executive Order (EO 14110) on day one, pivoting US policy to liberalisation of AI development and 'American AI dominance'. The following day, the White House announced the Stargate Project—a joint venture of OpenAI, Oracle, and SoftBank to invest up to US$500 billion in data centres, power, and chips over four years. On 23 January, a new executive order on 'Removing Barriers to American Leadership in Artificial Intelligence' was signed, formalising AI as national strategic infrastructure. Against US-China competition, AI was now positioned as a sovereign asset.
- Related organizations
- OpenAI
- Appears in
- A General History of Information Technology · A History of Cloud Computing
The generation built around Apple Intelligence—Apple's own generative-AI suite. Summarisation, rewriting, image generation, and a strengthened Siri were designed to run on-device wherever possible, with selected workloads offloaded to dedicated Apple servers (Private Cloud Compute). A hardware-and-OS co-design intended to keep the AI surface on the device from being ceded to OpenAI or Google.
- Related organizations
- Apple Inc.
- Related products
- iPhone
- Appears in
- A History of the iPhone · A History of Mobile Phones and Smartphones