76 pointsby NordStreamYacht7 hours ago17 comments
  • colingauvin5 hours ago
    >DeepMind started developing AlphaFold in 2018. In 2020, it was recognized as a solution to humanity's 50-year-old "protein folding problem," which sought to answer how amino acids automatically fold into complex 3D shapes.

    This is not even close to reality. AlphaFold is not a solution to the protein folding problem, it's (useful) pattern matching to the end state of solved folded protein (in situations that can be pattern matched). If this is considered "solving the protein folding problem" then X-ray crystallography solved it first, 75 years ago.

    There is essentially zero "how" information coming to us from AlphaFold. This type of reporting is incorrect, and irresponsible to the folks that are still working on that how problem.

    • chermi5 hours ago
      Pissed me off since day one that got by with that "solving" shit. Not to downplay what they did, but it had little to do with the problem as it's been understood to mean.

      And to be clear I do think it was nobel worthy.

      • HarHarVeryFunny2 hours ago
        Yes, they have a probabilistic model, not an analytical solution.

        OTOH I don't think they made up the "solved" label - the CASP benchmark had always considered reaching the AlphaFold level of predictive accuracy (within error tolerance of our ability to experimentally verify via X-ray crystallography etc) as "solving" the problem.

      • moralestapia4 hours ago
        I do not think it was Nobel worthy for Hassam et. al.

        David Baker is the GOAT of that field, it should have been awarded to him only.

        • chermi3 hours ago
          I know baker's work quite well, no it shouldn't have
          • moralestapia40 minutes ago
            Can you name others that deserved it more?
    • Legend24404 hours ago
      The kind of solution you want may not be possible.

      There is no guarantee that a tractable method exists to analytically invert protein folding. Data-driven methods like alphafold may be the only option.

      • colingauvin3 hours ago
        This has nothing to do with what I am talking about.
      • bobsmooth4 hours ago
        That has nothing to do with the fact that the article is inaccurate.
        • Legend24404 hours ago
          Tell that to the nobel prize committee.

          The article is fine. AlphaFold is widely regarded as "solving" protein folding.

          • goatlover3 hours ago
            Gemini says it did not solve the physics of how a protein actually folds.
    • geremiiah5 hours ago
      Yes and correct me if I'm wrong, but they never did deeper work on dynamics. I think that's very telling.
    • lukeplato4 hours ago
      they're probably referring to CASP13/14
    • the_real_cher3 hours ago
      It's an NP hard problem.

      To SOLVE it would easily win the Nobel, possibly the Turing and more.

      Designer proteins would change the world and medicine also in unimaginable ways.

  • jrflo5 hours ago
    > DeepMind then launched the AlphaFold Protein Structure Database, giving researchers free access to over 200 million protein structure predictions.

    Is this existing database enough for researchers?

    • spwa43 hours ago
      AlphaFold 1 and 2 are open, and freely licensed, weights, and they're still online and downloadable. Alphafold 3 is open weight.

      I'm guessing Google can't make money on them.

      You can do more with the weights than just the protein structures. You can design new proteins. So no, the database is not enough. But the weights and a university cluster are enough.

      • flopsamjetsaman hour ago
        > I'm guessing Google can't make money on them.

        The weights are free for non-commercial use. And Isomorphic are their commercial arm, and they partner with the big drug companies.

        Edit: after reading the article, I realise it's about the disbanding of the team, so probably your original comment is correct.

  • AntonyGarand5 hours ago
    To learn more about AlphaFold and its importance, I would recommend the Veritasium video[0]: AlphaFold - The Most Useful Thing AI Has Ever Done

    [0]: https://www.youtube.com/watch?v=P_fHJIYENdI

  • geremiiah5 hours ago
    It's probably because they hit a dead end with their approach in terms of improvements. You can only get so far with trying to model a physical system with an insane number of degrees of freedom from simulation (and augmented) data.
    • Legend24404 hours ago
      More likely because the entire Google organization is refocusing on LLMs.

      Also they already got their nobel prize, so the marketing benefit is already maxed out.

  • Melatonic2 hours ago
    Guessing they won't take any of the data or code offline ?

    Given we have heard a lot about limited compute available at Google internally to employees I would guess they are freeing up resources wherever they can

  • effnorwood39 minutes ago
    AlphaFold found to not be actually prize winning.
  • arjie3 hours ago
    Seems like https://alphafoldserver.com/ still works. This is about the team working on the product.
  • dumberquestions4 hours ago
    The dedicated research team is getting moved to other areas, the Alphafold system itself and its database will likely continue to get maintained, but this means there probably won't be an "Alphafold 4".
  • BariumBlue5 hours ago
    As per the article they're slowly shuttering the project, but I assume AlphaFold itself is still available and usable?

    I assume that AlphaFold isn't perfect, but surely after so many years on it most of the useful juice had been squeezed in terms of making it a useful tool?

  • balozi5 hours ago
    The obvious question to any business leader is "why?" Why deploy resources to a project? Is this project central to our current or future revenue streams? If not, toss it out.
    • HarHarVeryFunny2 hours ago
      It has justifiably generated a lot of good will for Google. Applying AI to help science rather than to replace people's jobs. I think this is why you are now seeing OpenAI and Anthropic try to do more science work, but in their case, coming so late, it seems a cynical PR move as opposed to heartfelt from Hassabis.

      It seems that Isomorphic Labs is somewhat a continuation of the AlphaFold work, and the first attempt to commercialize it, so maybe they will get more than just good will out of it.

  • vicapow5 hours ago
    Is there a lot more work to be done?
  • UltraSane3 hours ago
    Google REALLY wants Gemini 4 to be the leading LLM.
    • dgellow3 hours ago
      They need to justify the capex
  • kjsingh4 hours ago
    guess we need all that compute for AI?
  • chrisjj4 hours ago
    False title. The shutdown is of the AlphaFold team.
  • thaumasiotes5 hours ago
    > DeepMind started developing AlphaFold in 2018. In 2020, it was recognized as a solution to humanity's 50-year-old "protein folding problem," which sought to answer how amino acids automatically fold into complex 3D shapes. Those shapes determine the biological role of a protein. Scientists had identified the structures of roughly 170,000 proteins over the past 50 years, using tools and techniques like X-ray and nuclear magnetic resonance. The AlphaFold team took information from those previous work and then fed it to their AI to train AlphaFold.

    > In 2021, Nature published the papers with AlphaFold's methodology and the structure predictions of the entire human proteome, or the complete set of proteins expressed by our species. DeepMind then launched the AlphaFold Protein Structure Database, giving researchers free access to over 200 million protein structure predictions.

    Why is there no information on corroborations of the predictions? Anyone can make predictions. Surely there must have been teams picking predicted structures out of the database and comparing them to actual molecules?

  • dude2507115 hours ago
    They realised it's time... Gemini to follow?
    • Insanity5 hours ago
      I know you're saying this tongue in cheek. But the reason they're shuttering Alphafold is (likely) to assign those engineers and their expertise to Generative AI initiatives like Gemini.