AI Timeline
Updated 2 May 2025
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AI Timeline
A chronological record of the key moments in artificial intelligence — from the theoretical foundations to the present day.
The Foundations (1940s–1960s)
| Year | Event |
|---|---|
| 1943 | McCulloch & Pitts publish first mathematical model of a neural network |
| 1950 | Alan Turing publishes “Computing Machinery and Intelligence” — proposes the Turing Test |
| 1956 | Dartmouth Conference — term “Artificial Intelligence” coined |
| 1957 | Frank Rosenblatt builds the Perceptron (first trainable neural network) |
| 1966 | ELIZA chatbot (MIT) — first conversational AI |
The Winters (1970s–1990s)
| Year | Event |
|---|---|
| 1969 | Minsky & Papert publish “Perceptrons” — shows limitations, kills neural network funding |
| 1974-1980 | First AI Winter — Funding dries up after overpromising |
| 1986 | Backpropagation popularised (Rumelhart, Hinton, Williams) |
| 1987-1993 | Second AI Winter — Expert systems fail to deliver |
| 1989 | Yann LeCun demonstrates CNN for handwritten digit recognition |
| 1997 | IBM Deep Blue defeats world chess champion Garry Kasparov |
The Deep Learning Era (2000s–2010s)
| Year | Event |
|---|---|
| 2006 | Hinton’s “Deep Belief Networks” — deep learning renaissance begins |
| 2009 | ImageNet dataset created (Fei-Fei Li) — benchmark that drives progress |
| 2011 | IBM Watson wins Jeopardy! |
| 2012 | AlexNet wins ImageNet — deep learning proves its power, GPU training works |
| 2013 | Word2Vec (Mikolov, Google) — word embeddings work remarkably well |
| 2014 | GANs introduced (Goodfellow) — generative AI begins |
| 2014 | Sequence-to-Sequence (Sutskever, Google) — neural machine translation |
| 2015 | OpenAI founded (Altman, Musk, Sutskever, et al.) |
| 2015 | ResNet (152 layers) — proves very deep networks are trainable |
| 2016 | AlphaGo defeats Lee Sedol — AI masters Go (DeepMind) |
The Transformer Era (2017–2022)
| Year | Event |
|---|---|
| 2017 | “Attention Is All You Need” — Transformer architecture introduced (Google) |
| 2018 | BERT (Google) — bidirectional pre-training, NLP breakthrough |
| 2018 | GPT-1 (OpenAI) — generative pre-training for language |
| 2019 | GPT-2 (OpenAI) — “too dangerous to release” (1.5B params) |
| 2020 | GPT-3 (OpenAI) — 175B params, few-shot learning, scaling laws validated |
| 2020 | AlphaFold 2 — Solves protein folding (DeepMind) |
| 2021 | DALL-E (OpenAI) — text-to-image generation |
| 2021 | GitHub Copilot launches — AI coding assistant |
| 2022 | Stable Diffusion (Stability AI) — open-source image generation |
| 2022 | ChatGPT launches (Nov 30) — Fastest-growing consumer app ever, triggers AI boom |
The Current Era (2023–Present)
| Year | Event |
|---|---|
| 2023 Jan | Microsoft invests $10B in OpenAI |
| 2023 Mar | GPT-4 released — multimodal, major capability jump |
| 2023 Mar | Claude (Anthropic) public launch |
| 2023 May | Geoffrey Hinton resigns from Google, warns about AI risks |
| 2023 Jul | LLaMA 2 (Meta) — open-weight models for everyone |
| 2023 Oct | Biden Executive Order on AI |
| 2023 Nov | OpenAI board crisis — Altman fired and reinstated in 5 days |
| 2024 Feb | Gemini 1.5 — 1M token context window (Google) |
| 2024 Mar | Claude 3 Opus — Anthropic reaches frontier performance |
| 2024 Mar | EU AI Act formally adopted |
| 2024 Jun | SSI founded by Ilya Sutskever |
| 2024 Sep | OpenAI o1 — “reasoning” models (chain-of-thought at inference) |
| 2024 Oct | Nobel Prizes to AI researchers (Hinton — Physics, Hassabis — Chemistry) |
| 2024 Dec | LLaMA 3.1 405B — largest open model |
| 2025 | Claude 4, GPT-5 era, AI agents become mainstream, coding agents proliferate |
Key Patterns
- Winters and Springs — AI has a history of hype → disappointment → actual progress
- Scaling — Bigger models + more data + more compute = consistently better results (so far)
- The GPU revolution — Modern AI was enabled by repurposing gaming hardware
- Open vs Closed — Tension between open-source democratisation and closed safety/business models
- Acceleration — The gap between milestones is shrinking (decades → years → months)