This is Phase 0, Episode 2 of the OCDevel AI course: a narrative history of artificial intelligence, built around two throughlines. The first is a pendulum between symbolic, logic-based AI and connectionist, learn-from-data AI, where each era's failure seeded the next era's breakthrough. The second is the hype cycle that produced two named "AI winters." We start in prehistory: the [golem](https://en.wikipedia.org/wiki/Dartmouth_workshop) and Talos myths, Hobbes calling reasoning "reckoning," Leibniz's dream of settling arguments by calculation, and Boole's [Laws of Thought](https://en.wikipedia.org/wiki/Artificial_neuron) turning logic into algebra. Foundations follow: Turing's machine (1936) and his [imitation game](https://en.wikipedia.org/wiki/Computing_Machinery_and_Intelligence) (1950), and the [McCulloch-Pitts neuron](https://en.wikipedia.org/wiki/Artificial_neuron) (1943). The field is named at the [Dartmouth workshop](https://en.wikipedia.org/wiki/Dartmouth_workshop) (1956). The symbolic golden years bring the Logic Theorist, the [Physical Symbol System Hypothesis](https://en.wikipedia.org/wiki/Physical_symbol_system), [ELIZA](https://en.wikipedia.org/wiki/ELIZA), SHRDLU, and Rosenblatt's [perceptron](https://en.wikipedia.org/wiki/Mark_I_Perceptron). Then the first winter: Minsky and Papert's [Perceptrons](https://en.wikipedia.org/wiki/Perceptron) and the [Lighthill report](https://en.wikipedia.org/wiki/Lighthill_report). The expert-systems boom (DENDRAL, MYCIN, XCON, Japan's Fifth Generation) ends in a second winter. The connectionist revival arrives with [backpropagation](https://www.nature.com/articles/323533a0) (1986), then [SVMs](https://en.wikipedia.org/wiki/Support_vector_machine) and [Deep Blue](https://en.wikipedia.org/wiki/Deep_Blue_versus_Garry_Kasparov) (1997). Deep learning ignites with [ImageNet](https://en.wikipedia.org/wiki/ImageNet), [AlexNet](https://en.wikipedia.org/wiki/AlexNet) (2012), and [AlphaGo](https://en.wikipedia.org/wiki/AlphaGo_versus_Lee_Sedol) (2016). Finally the [transformer](https://arxiv.org/abs/1706.03762) (2017), [GPT-3](https://arxiv.org/abs/2005.14165), [foundation models](https://arxiv.org/abs/2108.07258), ChatGPT, and today's agents. Closing lesson: Sutton's [Bitter Lesson](https://en.wikipedia.org/wiki/Bitter_lesson). News brief: [Microsoft's seven MAI models](https://microsoft.ai/news/building-a-hillclimbing-machine-launching-seven-new-mai-models/) at Build, the [Mayo Clinic healthcare model](https://news.microsoft.com/source/2026/06/02/mayo-clinic-and-microsoft-collaborate-to-develop-a-frontier-ai-model-for-healthcare/), NVIDIA's [Cosmos 3](https://nvidianews.nvidia.com/news/nvidia-launches-cosmos-3-the-open-frontier-foundation-model-for-physical-ai), [Anthropic's IPO filing](https://fortune.com/2026/06/01/anthropic-confidentially-files-ipo-965-billion-valuation/), a [Trump AI executive order](https://www.cnbc.com/2026/06/02/trump-executive-order-ai.html), and [xAI's Grok updates](https://releasebot.io/updates/xai).