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Big Technology Podcast · 2 min · Jan 23, 2026

AlphaFold was shared because its impact exceeded DeepMind's reach

Demis Hassabis says the team could realize only a fraction of AlphaFold's potential alone, so it released the tool to the scientific community. He says three million researchers have used it.

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 says the team could realize only a fraction of AlphaFold's potential alone, so it released the tool to the scientific community. He says three million researchers have used it.

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

“we sort of thought it was a root node problem if we could solve it and put that out in the world”
Demis Hassabisat 30:14 · Big Technology Podcast30:14

Takeaways

  1. AlphaFold tackled a 50-year protein-folding challenge.
  2. The team saw its potential as greater than it could realize alone.
  3. Hassabis says three million researchers have used AlphaFold.

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 reach2:21

Up next · SourceryPalantir builds for what clients need, not what traps them4:52

Transcript

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

  1. 29:44

    quickly this first one and then a big question at the end in the thinking game speaking of um health and ai there's this moment where there's a discussion in the lab about whether to release the results of alpha folds and you kind of sit there adamantly and you're like why are we going through a process release it release it now talk a little bit about um the lesson from there yeah well look we we started alpha fold to crack a unbelievably tough scientific challenge 50 year grand challenge uh of protein folding and protein structure prediction and the reason we worked on that and the reason we've put so much effort into it is we sort of thought it was a root node problem if we could solve it and put that out in the world it could be it could do amazing untold impact on things like human health and understanding of biology but we as a team no matter how talented

  2. 30:32

    or hard hard working we are we would only be able to scratch a surf a small tiny amount of that potential on our own it's clear so um in that case and in this case it was obviously the right thing to do to maximize the benefit to the world here to put it out there to the scientific massive scientific community uh to build on top of and use alpha fold and it's been incredibly gratifying to to see three million researchers around the world use it in their important research.

  3. 30:57

    I think in future, almost every single drug that's discovered from now on will probably have used AlphaFold at some point in that process, which is amazing for us. And really, that's what we do, all the work we do for. I also read that moment, you tell me if I'm wrong, as something of a metaphor, small, passionate AI division, kind of yelling in a big company, get this out, cut the red tape. Yeah, potentially.

  4. 31:22

    But look, I mean, we've had amazing support from the beginning from Google. And the reason that we, you know, we joined forces with Google back in 2014 is Google itself is a scientific, research, engineering, technical-led company, always has been and has that at its core. And that's why, you know, I think that we have the scientific method and the scientific approach, that thoughtful approach, that rigorous approach in everything we do.

  5. 31:46

    So, of course, they're going to love something like AlphaFold. Okay, here's the big question at the end. you built AlphaGo trained the computer to play Go on human knowledge