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

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

#371

Post by jdietrich »

jprete wrote: post #194
dekhn wrote: 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…

The goal of science has always been to predict the outcome of experiments, because that's what distinguishes science from philosophy or alchemy or faith. Anyone who believes that they've discovered an underlying principle is almost certainly mistaken; with time, "underlying principles" usually become discredited theories or, sometimes, useful but crude approximations that we teach to high schoolers and undergrads.

Prediction is understanding. What we call "understanding" is a cognitive illusion, generated by plausible but brittle abstractions. A statistically robust prediction is an explanation in itself; an explanation without predictive power explains nothing at all. Feeling like something makes sense is immeasurably inferior to being able to make accurate predictions.

Scientists are at the dawn of what chess players experienced in the 90s. Humans are just too stupid to say anything meaningful about chess. All of the grand theories we developed over centuries are just dumb heuristics that are grossly outmatched by an old smartphone running Stockfish. Maybe the computer understands chess, maybe it doesn't, but we humans certainly don't and we've made our peace with the fact that we never will. Moore's law does not apply to thinking meat.

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

#372

Post by qp11 »

mikeyouse wrote: post #276
nkingsy wrote: post #267

Earlier quoted context omitted.

increasing the volume of predictions produces patterns that often lead to underlying principles.

And much of the 20th century was characterized by a very similar progression - we had no clue what the actual mechanism of action was for hundreds of life saving drugs until relatively recently, and we still only have best guesses for many. That doesn’t diminish the value that patients received in any way even though it would be more satisfying to make predictions and design something to interact in a way that exactl…

We were using the compass for navigation for thousands of years, without any clue about what it was doing or why. Ofcourse lot of people got lost cause compasses are not perfect. And the same will happen here. Theory of Bounded Rationality applies.

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

#373

Post by a_bonobo »

wuj wrote: post #239

This tool reminds me that the human body functions much like a black box. While physics can be modeled with equations and constraints, biology is inherently probabilistic and unpredictable. We verify the efficacy of a medicine by observing its outcomes: the medicine is the input, and the changes in symptoms are the output. However, we cannot model what happens in between, as we cannot definitively prove that the medi…

Classic essay in this vein:

>Can a biologist fix a radio? — Or, what I learned while studying apoptosis

https://www.cell.com/cancer-cell/pdf/S1535-6108(02)00133-2.p...

>However, if the radio has tunable components, such as those found in my old radio (indicated by yellow arrows in Figure 2, inset) and in all live cells and organisms, the outcome will not be so promising. Indeed, the radio may not work because several components are not tuned properly, which is not reflected in their appearance or their connections. What is the probability that this radio will be fixed by our biologists? I might be overly pessimistic, but a textbook example of the monkey that can, in principle, type a Burns poem comes to mind. In other words, the radio will not play music unless that lucky chance meets a prepared mind.

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

#374

Post by mycall »

moconnor wrote: post #32

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…

A New Kind Of Science?

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

#376

Post by searealist »

stouset wrote: post #367
searealist wrote: post #365

Earlier quoted context omitted.

Chess engines actually do both now. They have ML models to evaluate positions, essentially a much more advanced version of your positional description, and deep calculations.

That might be the best we can practically achieve with technology, but the point stands. If positional evaluation says one thing but an exhaustive analysis of lines finds a solution 60 moves deep, that one is going to win.

Humans also do search. Also, engines arent doing an exhaustive search when they are 20 moves deep. They heavily prune.

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

#377

Post by adrianN »

dekhn wrote: post #200
jprete wrote: 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…

Underlying principles are nice for science, whatever works is nice for engineering. There is plenty of historical precedent where we build stuff that works without knowing exactly why it works.

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

#378

Post by anonylizard »

stouset wrote: post #363
dekhn wrote: 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…

> If you're the sort of person who believes that human brains are capable of understanding the "why" of how things work in all its true detail, you'll find this an interesting challenge- can we actually interpret these models, or are human brains too feeble to understand complex systems without sophisticated models? I think chess engines, weirdly enough, have disabused me of this notion. There are lots of factors a h…

Fine tuned LLMs can play chess at grandmaster levels.

So its clear that there is in fact 'deeper patterns to chess' that allow one to play very well, without any search required (Since LLMs cannot search). Its just that those patterns are probably rather different to human understood ones.

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

#379

Post by fsloth »

jprete wrote: post #194
dekhn wrote: 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…

AFAIK in wet science you need (or needed) to do tons of experimentations with liquids with specific molar compositions and temperatures splurging in and out of test tubes - basically just physically navigating a search space. I would view an AI model with super powerful guestimation capability as a much faster way of A) cutting through search space B) providing accidental discoveries while at it

Now, if we look at history of science and technology, there is a shit ton of practical stuff that was found only by pure accident - discoveries of which could not be predicted from any previous theory.

I would view both A) and B) as net positives. But our teaching of the next generation of scientists needs to adapt.

The worst case scenario is of course that the middle management driven enshittification of science will proceed to a point where there are only few people who actually are scientists and not glorified accountants. But I’m optimistic this will actually super charge science.

With good luck we will get rid of the both of the biggest pathologies in modern science - 1. number of papers published and referred as a KPI 2. Hype driven super politicized funding where you can focus only one topic “because that’s what’s hot” (i.e. string theory).

The best possible outcome is we get excitement and creativity back into science. Plus level up our tech level in this century to something totally unforeseen (singularity? That’s just a word for “we don’t know what’s gonna happen” - not a specific concrete forecasted scenario).

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

#380

Post by staticautomatic »

rolph wrote: post #39
renonce wrote: post #5

> What is different about the new AlphaFold3 model compared to AlphaFold2? > AlphaFold3 can predict many biomolecules in addition to proteins. AlphaFold2 predicts structures of proteins and protein-protein complexes. AlphaFold3 can generate predictions containing proteins, DNA, RNA, ions,ligands, and chemical modifications. The new model also improves the protein complex modelling accuracy. Please refer to our paper…

problem is biomolecules, are "chaperoned" to fold properly, only specific regions such as, alpha helix, or beta pleatedsheet will fold de novo. Chaperone (protein) https://en.wikipedia.org/wiki/Chaperone_(protein)

In principle couldn’t we just incorporate knowledge about chaperones into the model?
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