When Demis Hassabis pitched DeepMind to a few venture capitalists back in 2010, the business plan was almost comically audacious. “Step one: Solve intelligence. Step two: Use it to solve everything else,” he recalls in a conversation at Stanford Graduate School of Business with Stanford University President Jonathan Levin. “And people were quite confused. But we really meant it.”
Sixteen years later, the “broad arcs” of that plan have gone “unbelievably well,” says Hassabis, a chess prodigy turned video game developer turned neuroscientist turned Nobel Prize-winning AI pioneer. Today he’s on a mission to create “the ultimate tool for science,” building on his decision to give away AlphaFold, the groundbreaking AI system that predicts the structures of proteins. The future, Hassabis says, is just around the corner: “Ten years from now, I think we’ll realize that we were standing in the foothills of the singularity now.”
Chapters:
00:00:00 Introduction
00:03:31 A career built around one big question
00:06:19 Building DeepMind and pursuing AGI
00:10:09 The breakthroughs that made AI feel possible
00:14:48 From AlphaGo to scientific discovery
00:17:15 Why AlphaFold was given away for free
00:24:00 The “foothills of the singularity”
00:26:41 Public concern, disruption, & AI’s promise
00:29:59 How AI could reshape work and entrepreneurship
00:34:12 Competition, safety, & regulating frontier AI
00:41:19 Expanding AI’s benefits globally
00:45:28 Preparing society for AGI
00:48:21 What should AI leave untouched?
00:51:01 Advice for the first AI-native generation
00:54:19 Conclusion
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