Live data from Hacker News

AlphaFold 3 predicts the structure and interactions of life's molecules

blog.google

251–260 of 504 posts

Re: AlphaFold 3 predicts the structure and interactions of life's molecules

#251
post #200
post #194

Earlier quoted context omitted.

The goal of science has always been to discover underlying principles and not merely to predict the outcome of experiments. I don't see any way to classify an opaque ML model as a scientific artifact since by definition it can't reveal the underlying principles. Maybe one could claim the ML model itself is the scientist and everyone else is just feeding it data. I doubt human scientists would be comfortable with that…

That's the aspirational goal. And I would say that it's a bit of an inflexible one- for example, if we had an ML that could generate molecules that cure diseases that would pass FDA approval, I wouldn't really care if scientists couldn't explain the underlying principles. But I'm an ex-scientist who is now an engineer, because I care more about tools that produce useful predictions than understanding underlying princ…

[deleted]

Re: AlphaFold 3 predicts the structure and interactions of life's molecules

#252
post #194
post #93

Earlier quoted context omitted.

If you're a scientist who works in protein folding (or one of those other areas) and strongly believe that science's goal is to produce falsifiable hypotheses, these new approaches will be extremely depressing, especially if you aren't proficient enough with ML to reproduce this work in your own hands. If you're a scientist who accepts that probabilist models beat interpretable ones (articulated well here: https://no…

The goal of science has always been to discover underlying principles and not merely to predict the outcome of experiments. I don't see any way to classify an opaque ML model as a scientific artifact since by definition it can't reveal the underlying principles. Maybe one could claim the ML model itself is the scientist and everyone else is just feeding it data. I doubt human scientists would be comfortable with that…

Discovering underlying principles and predicting outcomes is two sides of the same coin in that there is no way to confirm you have discovered underlying principles unless they have some predictive power.

Some had tried to come up with other criteria to confirm you have discovered an underlying principle without predictive power, such as on aesthetics - but this is seen by the majority of scientists as basically a cop out. See debate around string theory.

Note that this comment is summarizing a massive debate in the philosophy of science.

Re: AlphaFold 3 predicts the structure and interactions of life's molecules

#254
post #132

Earlier quoted context omitted.

The most moneyed and well-coordinated organizations have honed a large hammer, and they are going to use it for everything, and so almost certainly future big findings in the areas you mention, probabilistically inclined models coming from ML will be the new gold standard. But yet the only thing that can save us from ML will be ML itself because it is ML that has the best chance to be able to extrapolate patterns fro…

Spoiler: "Interpretable ML" will optimize for output that either looks plausible to humans, reinforces our preconceptions, or appeals to our aesthetic instincts. It will not converge with reality.

Spoiler: basic / hard sciences describe nature mathematically.

Open a random physics book, and you will find lots and lots of derivations (using more or less acceptable assumptions depending on circumstance under consideration).

Derivations and assumptions can be formally verified, see for example https://us.metamath.org

Ever more intelligent machine learning algorithms and data structures replacing human heuristic labor, will simply shift the expected minimum deliverable from associations to ever more rigorous proofs in terms of less and less assumptions.

Machine learning will ultimately be used as automated theorem provers, and their output will eventually be explainable by definition.

When do we classify an explanation as explanatory? When it succeeds in deriving a conclusion from acceptable assumptions without hand waving. Any hand waving would result in the "proof" not having passed formal verification.

Re: AlphaFold 3 predicts the structure and interactions of life's molecules

#255
post #246

Earlier quoted context omitted.

A human mind is perfectly capable of following the same instructions as the computer did. Computers are stupidly simple and completely deterministic. The concern is about "holding it all in your head", and depending on your preferred level of abstraction, "all" can perfectly reasonably be held in your head. For example: "This program generates the most likely outputs" makes perfect sense to me, even if I don't unders…

Abstraction isn't the silver bullet. Not everything is abstractable. "This program generates the most likely outputs" isn't a scientific explanation, it's teleology.

"this tool works better than my intuition" absolutely is science. "be quiet and calculate" is a well worn mantra in physics is it not?

Re: AlphaFold 3 predicts the structure and interactions of life's molecules

#256

Earlier quoted context omitted.

Late-stage capitalism didn't bring us AlphaFold, scientists did, late-stage capitalism just brought us Alphabet swooping in at literally the last minute. Socialize the innovation because that requires potential losses, privatize the profits, basically. It's reminiscent of "Heroes of CRISPR," where Doudna and Charpentier are supposedly just some middle-men, because stepping in at the last minute with more funding is r…

Why haven't the academics created a non profit foundation with open source models like this then? If alphabet doesnt provide much, then they will be supplanted by non profits. I see nothing broken here.

Individual labs somehow manage to do that and we're all grateful. Martin Steinegger's lab put out ColabFold, RELION is the gold standard for cryo-EM despite being academic software and the development of more recent industry competitors like cryoSPARC. Everything out of the IPD is free for academic use. Someone has to fight like hell to get all those grants, though, and from a societal perspective, it's basically needlessly redundant work.

My frustrations aren't with a lack of open source models, some poor souls make them. My disagreement is with the perception that academia has insufficient incentive to work on socially important problems. Most such problems are ONLY worked on in academia until they near the finish line. Look at Omar Yaghi's lab's work on COFs and MOFs for carbon/emission sequestration and atmospheric water harvesting. Look at all the thankless work numerous labs did on CRISPR-Cas9 before the Broad Institute even touched it. Look at Jinbo Xu's work, on David Baker's lab's and the IPD's work, etc. Look at what labs first solved critical amyloid structures, infuriatingly recently, considering the massive negative social impacts of neurodegenerative diseases.

It's only rational for companies that only care about their own profit maximization to socialize R&D costs and privatize any possible gains. This can work if companies aren't being run by absolute ghouls who aren't delaying the release of a new generation of drugs to minimize patent duration overlap or who aren't trying to push things that don't work for short-term profit. This can also work if we properly fund and credit publicly funded academic labs. This is not what's happening, however, instead public funded research is increasingly demeaned, defunded, and dismantled due to the false impression that nothing socially valuable gets done without a profit motive. It's okay, though, I guess under this kind of LSC worldview, that everything always corrects itself so preempting problems doesn't matter, we'll finally learn how much actual innovation is publicly funded when we get the Minions movie, aducanumab, and WeWork over and over again for a few decades while strangling the last bit of nature we have left.

Re: AlphaFold 3 predicts the structure and interactions of life's molecules

#257
post #194
post #93

Earlier quoted context omitted.

If you're a scientist who works in protein folding (or one of those other areas) and strongly believe that science's goal is to produce falsifiable hypotheses, these new approaches will be extremely depressing, especially if you aren't proficient enough with ML to reproduce this work in your own hands. If you're a scientist who accepts that probabilist models beat interpretable ones (articulated well here: https://no…

The goal of science has always been to discover underlying principles and not merely to predict the outcome of experiments. I don't see any way to classify an opaque ML model as a scientific artifact since by definition it can't reveal the underlying principles. Maybe one could claim the ML model itself is the scientist and everyone else is just feeding it data. I doubt human scientists would be comfortable with that…

Kepler famously compiled troves of data on the night sky, and just fitted some functions to them. He could not explain why but he could say what. Was he not a scientist?

Re: AlphaFold 3 predicts the structure and interactions of life's molecules

#258
post #252
post #194

Earlier quoted context omitted.

The goal of science has always been to discover underlying principles and not merely to predict the outcome of experiments. I don't see any way to classify an opaque ML model as a scientific artifact since by definition it can't reveal the underlying principles. Maybe one could claim the ML model itself is the scientist and everyone else is just feeding it data. I doubt human scientists would be comfortable with that…

Discovering underlying principles and predicting outcomes is two sides of the same coin in that there is no way to confirm you have discovered underlying principles unless they have some predictive power. Some had tried to come up with other criteria to confirm you have discovered an underlying principle without predictive power, such as on aesthetics - but this is seen by the majority of scientists as basically a co…

>there is no way to confirm you have discovered underlying principles unless they have some predictive power.

Yes, but a perfect oracle has no explanatory power, only predictive.

Re: AlphaFold 3 predicts the structure and interactions of life's molecules

#259

Earlier quoted context omitted.

That's pretty good. Based on the previous performance improvements of Alpha-- models, it'll be nearing 100% in the next couple of years.

Just "Alpha-- models" in general?? That's not a remotely reasonable way to reason about it. Even if it were, why should it stop DeepMind from clearly communicating accuracy?

I'm quite hyped for the upcoming BetaFold, or even ReleaseCandidateFold models. They just have to be great.

Re: AlphaFold 3 predicts the structure and interactions of life's molecules

#260

Stepping back, the high-order bit here is an ML method is beating physically-based methods for accurately predicting the world. What happens when the best methods for computational fluid dynamics, molecular dynamics, nuclear physics are all uninterpretable ML models? Does this decouple progress from our current understanding of the scientific process - moving to better and better models of the world without human-int…

Hook the protein model up to an LLM model, have the LLM interpret the results. Problem solved :-) Then we just have to trust the LLM is giving us correct interpretations.
Post reply on HN