Hassabis: Three Conditions Enable AlphaFold-Style AI Breakthroughs
Demis Hassabis · Demis Hassabis: Agents, AGI & The Next Big Scientific Breakthrough · Y Combinator · Apr 29, 2026 · at 33:39
Google DeepMind CEO Demis Hassabis explains to Garry Tan the criteria for identifying scientific domains ripe for AI-driven breakthrough solutions.
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“The lesson I've learned from all the alpha projects we've done, specifically alpha go and alpha fold is I think the techniques we have and the problems I look like to look for are great in, if this, if the situation can be described as massive combinatorial search space, the more massive, the better in some ways. So no brute force or special case algorithm will solve it. And that's true of go moves. And of, you know, different configurations of proteins far more than the atoms in the universe, both of those. And then you have a clear objective function. So, you know, you can think of it as minimizing the free energy in the proteins or, you know, the winning the game of go. So you need to better, you know, specify your objective function clearly so you can hill climb. And then enough data and or simulator that can generate you lots of in distribution synthetic data. If those things are true, then I think with today's methods, you can go a long way into tackling and finding the kind of needle in the haystack that you need to, for the solution that you're trying to look for.”
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