#History of AI

The dream of machine intelligence collided with reality in the early 1970s. Government funding collapsed. Research groups dissolved. Careers were redirected. This is the full narrative of AI's first great crisis — told from the inside, through the experiences of the people who built the dream and watched it crash — and the deeper questions about ambition, honesty, and institutional courage that the crisis forced.

The full narrative of AI's second great contraction — told from the inside, through the experiences of the researchers who built the boom and watched it collapse. The collapse of the expert systems industry, the dissolution of the LISP machine market, the reduction of DARPA funding, and the underground movement that kept the neural network approach alive through the cold.

The exhilarating early years when Arthur Samuel's checkers program learned to beat its creator, when chess programs first challenged amateur players, and when every new demonstration felt like proof that general machine intelligence was just around the corner. What those early programs actually did, why they were so impressive, and why the gap between their performance and genuine intelligence was wider than it appeared.

The audacious, exhilarating, ultimately tragic story of the AI optimists of the 1960s — the people who genuinely believed that machine intelligence was years away, who made predictions that have made them famous for being wrong, and who were right about the destination even as they were spectacularly wrong about the distance.

What the first AI winter actually felt like for the people who lived through it. The funding cuts, the disbanded research groups, the researchers who left the field, and the stubborn few who kept working in the cold. The story of how AI's first collapse shaped everything that came after.

The expert systems boom collapsed almost as quickly as it had risen. The LISP machine market imploded overnight. DARPA cut funding. And for the second time in AI's history, the field contracted, researchers left, and the most pessimistic observers began to wonder whether the project was fundamentally misguided. The full story of AI's second near-death experience — and the underground movement that kept the neural network flame alive through the cold.

The 1956 Dartmouth Conference in full narrative detail — who was in the room, what they argued about in the evenings, what they agreed on, what they were spectacularly wrong about, and how a single summer's conversation gave a field its name, its mission, and the overconfidence that would eventually send it into its first winter.

In 1973 a distinguished mathematician named James Lighthill wrote a review of AI research that was so devastating it caused governments across the world to pull their funding and sent the entire field into its first winter. How one document changed the course of AI history — and whether it was right.