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…
AlphaFold 3 predicts the structure and interactions of life's molecules
261–270 of 504 posts
Re: AlphaFold 3 predicts the structure and interactions of life's molecules
#262Earlier 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…
I'm in the following camp: It is wrong to think about the world or the models as "complex systems" that may or may not be understood by human intelligence. There is no meaning beyond that which is created by humans. There is no 'truth' that we can grasp in parts but not entirely. Being unable to understand these complex systems means that we have framed them in such a way (f.e. millions of matrix operations) that doe…
It appears that your own comment is disproving this statement
Re: AlphaFold 3 predicts the structure and interactions of life's molecules
#263Earlier 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…
AlphaFold 3 can rapidly reduce a vast search space in a way physically-based methods alone cannot. This narrowly focused search space allows scientists to apply their rigorous, explainable, physical methods, which are slow and expensive, to a small set of promising alternatives. This accelerates drug discovery and uncovers insights that would otherwise be too costly or time-consuming.
The future of science isn't about AI versus traditional methods, but about their intelligent integration.
Re: AlphaFold 3 predicts the structure and interactions of life's molecules
#264Re: AlphaFold 3 predicts the structure and interactions of life's molecules
#265Earlier quoted context omitted.
> ... and strongly believe that science's goal is to produce falsifiable hypotheses, these new approaches will be extremely depressing I don't quite understand this point — could you elaborate? My understanding is that the ML model produces a hypothesis, which can then be tested via normal scientific method (perform experiment, observe results). If we have a magic oracle that says "try this, it will work", and then w…
There is an issue scientifically. I think this point was expressed by Feynman: the goal of scientific theories isn’t just to make better predictions, it’s to inform us about how and why the world works. Many ancient civilizations could accurately predict the position of celestial bodies with calendars derived from observations of their period, but it wasn’t until Copernicus proposed the heliocentric model and Galileo…
Re: AlphaFold 3 predicts the structure and interactions of life's molecules
#266Re: AlphaFold 3 predicts the structure and interactions of life's molecules
#267Earlier quoted context omitted.
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
#268Stepping 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…
Re: AlphaFold 3 predicts the structure and interactions of life's molecules
#269Earlier quoted context omitted.
What if the underlying principles of the universe are too complex for human understanding but we can train a model that very closely follows them?
Then we should dedicate large fractions of human engineering towards finding ethical ways to improve human intelligence so that we can appreciate the underlying principles better.
High level, I see a distinction between theory and practice, between an oracle predicting without explanation, and a well-thought out theory built on a partnership between theory and experiment over centuries, ex. gravity.
I have this feeling I can't shake that the knife you're using is too sharp, both in the specific example we're discussing, and in general.
In the specific example, folding, my understanding is we know how proteins fold & the mechanisms at work. It just takes an ungodly amount of time to compute and you'd still confirm with reality anyway. I might be completely wrong on that.
Given that, the proposal to "dedicate...engineer[s] towards finding ethical ways to improve...intelligence so that we can appreciate the underlying principles better" begs the question of if we're not appreciating the underlying principles.
It feels like a close cousin of physics theory/experimentalist debate pre-LHC, circa 2006: the experimentalists wanted more focus on building colliders or new experimental methods, and at the extremes, thought string theory was a complete was of time.
Which was working towards appreciating the underlying principles?
I don't really know. I'm not sure there's a strong divide between the work of recording reality and explaining it. I'll peer into a microscope in the afternoon, and take a shower in the evening, and all of a sudden, free associating gives me a more high-minded explanation for what I saw.
I'm not sure a distinction exists for protein folding, yes, I'm virtually certain this distinction does not exist in reality, only in extremely stilted examples (i.e. a very successful oracle at Delphi)
Re: AlphaFold 3 predicts the structure and interactions of life's molecules
#270Earlier 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…