AI History

2005 — Numenta

Jeff Hawkins co-founds Numenta around the idea of reverse-engineering the neocortex. This eventually produces HTM and the Thousand Brains theory.

2010 — DeepMind
DeepMind is founded by Demis Hassabis, Shane Legg and Mustafa Suleyman. Its path is heavily influenced by reinforcement learning, neuroscience and learning through environments/games.

2012 — AlexNet / deep-learning explosion

2013–15 — DQN / Atari
DeepMind demonstrates deep reinforcement learning directly from game pixels.

2015 — OpenAI

2015–16 — AlphaGo
DeepMind combines neural networks, search and reinforcement learning; AlphaGo defeats Lee Sedol in 2016.

2017 — Transformer
Google researchers introduce the architecture that becomes the foundation of modern LLMs. Google DeepMind's history specifically credits the Google Brain team with the Transformer work.

2018 — GPT-1

2020 — GPT-3 / AlphaFold 2 era

2021 — Anthropic

2021 — A Thousand Brains
Hawkins publishes the book laying out the Thousand Brains Theory.

2022 — ChatGPT

2023 — Google DeepMind
Google combines DeepMind and Google Brain into one organization: Google DeepMind.

2024 — Thousand Brains Project / Monty
Numenta publicly launches the open-source Thousand Brains Project, pursuing sensorimotor AI based on its theory of the neocortex.

2025 — Thousand Brains becomes independent nonprofit
The project separates from Numenta and continues development of Monty and its sensorimotor approach. 


More:




PeriodTechnologyWhat it contributed
1991PythonAccessible general-purpose programming language
1995–2006Numeric → NumPyFast multidimensional arrays and matrix operations
2001SciPyScientific algorithms built around NumPy
2001IPythonBetter interactive Python experimentation
2003MatplotlibVisualization and plotting
2006–2007NVIDIA CUDAGeneral computation on GPUs
2007TheanoGPU tensors and automatic differentiation
2007–2010scikit-learnStandard classical machine-learning algorithms
2008pandasData tables, cleaning, and transformation
2011IPython NotebookCode, prose, equations, and charts in one document
2012AlexNetDemonstrated the power of deep neural networks trained on GPUs
2013CaffePractical framework for convolutional networks
2014Project JupyterLanguage-independent notebook platform
2015TensorFlowGoogle’s scalable deep-learning framework
2015KerasSimpler high-level neural-network API
2017PyTorchFlexible, Pythonic deep-learning research framework
2017TransformerHighly parallelizable attention-based architecture
2018GPTTransformer plus generative pretraining

2018–2019Hugging Face TransformersAccessible implementations and pretrained models

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