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Big Technology Podcast · 2 min · Jan 23, 2026

Stable protein structures make the search space more tractable

Demis Hassabis argues that stable biological structures narrow an enormous search space, as with protein folding. He sees AI mapping these information landscapes as a path to drugs and materials.

Demis Hassabis

Demis Hassabis is CEO of Google DeepMind.

  • Alex Kantrowitz, Host · Founder, Big Technology

    Former BuzzFeed News senior tech reporter and author of Always Day One.

About this segment

Demis Hassabis argues that stable biological structures narrow an enormous search space, as with protein folding. He sees AI mapping these information landscapes as a path to drugs and materials.

From “Google DeepMind CEO Demis Hassabis: AI's Next Breakthroughs, AGI Timeline, Google's AI Glasses Bet”, Jan 23, 2026. Watch the full episode

“actually become very tractable if you understand the energy landscape or the information landscape around that”
Demis Hassabisat 29:19 · Big Technology Podcast29:19

Takeaways

  1. Only a small subset of possible protein structures are stable.
  2. Understanding that landscape can make a vast search more tractable.
  3. Hassabis sees applications in drugs, materials and superconductors.

In this episode

Full episode
  1. 6:21AGI requires creativity, physical skills and world models5:28
  2. 12:03AI glasses need a universal assistant to become useful3:39
  3. 20:13The AI market may be frothy in some areas, not all3:37
  4. 1:53Continual learning remains a key unsolved capability4:35
  5. 15:40Assistant advertising has to protect user trust2:44
  6. 24:15A Go player who learned with AlphaGo became the strongest ever3:23

  7. 27:31Stable protein structures make the search space more tractable2:15

  8. 29:39AlphaFold was shared because its impact exceeded DeepMind's reach2:21Up next

Transcript

Transcribed by machine (Whisper) from the episode’s audio, so a word may be off here and there.

  1. 27:35

    know if we're going to get to both of them. Let me ask the one that I want to know the answer most about. In a recent interview, you said that you have a theory that information is the most fundamental unit of the universe, not energy, not matter, information. Yeah. How? Well, look, I think if you look at energy, I mean, I don't know if we're going to cover this in two minutes, but in energy, energy, energy and...

  2. 28:01

    I think a lot of people sort of think of them as isomorphic with information. But I think information is really the right way to understand the universe. So if you think of biology and living systems, we're information systems that are resisting entropy, right? We're trying to retain our structure, retain our information in the face of, you know, a randomness that's happening around us. And I think you can look at that, you know, in a larger physics scale. So almost not just biology, but things like, you know, mountains and planets and asteroids, they've all been subject to some kind of selection pressure, not Darwinian evolution, but some kind of external pressure.

  3. 28:40

    And the fact that they've been stable over a long amount of time means that that information is kind of stable and meaningful. So I think one could view the world in terms of its complexity, information complexity. And I think a lot of what we're doing with our, the reason I'm thinking about all of that is because of things like AlphaGo and AlphaFold, especially AlphaFold, where, you know, we solved all the protein structures that are kind of known to science.

  4. 29:04

    and how we've done that well because only a certain number of those in the kind of almost infinite possibilities of protein structures are stable and and those are the ones you've got to find so you've got to understand that topology that information topology and follow it and then suddenly these problems that seem to be intractable because you know how can you find the needle in the haystack actually become very tractable if you understand the energy landscape or the information landscape around that and that's how i think eventually we'll solve most diseases come with new drugs new materials new superconductors with the help of ai helping us navigate that information landscape uh dennis before we go i just want to wrap with this uh well maybe maybe