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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

#41

Post by thomasahle »

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…

> Stepping back, the high-order bit here is an ML method is beating physically-based methods for accurately predicting the world.

I mean, it's just faster, no? I don't think anyone is claiming it's a more _accurate_ model of the universe.

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

#42

Post by s1artibartfast »

ilrwbwrkhv wrote: post #6
s1artibartfast wrote: post #2

The article was heavy on the free research aspect, but light on the commercial application. I'm curious about the business strategy. Does Google intend to license out tools, partner, or consult for commercial partners?

as soon as google tries to think commercially this will shut down so the longer it stays pure research the better. google is bad with productization.

I don't think it was ever pure research. The article talks about infinity labs, which is the co. Mercial branch for drug discovery.

I do agree that Google seems bad at commercialization, which is why I'm curious on what the strategy is.

It is hard to see them being paid consultants or effective partners for pharma companies, let alone developing drugs themselves.

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

#43

Post by xanderlewis »

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…

It depends whether the value of science is human understanding or pure prediction. In some realms (for drug discovery, and other situations where we just need an answer and know what works and what doesn’t), pure prediction is all we really need. But if we could build an uninterpretable machine learning model that beats any hand-built traditional ‘physics’ model, would it really be physics?

Maybe there’ll be an intermediate era for a while where ML models outperform traditional analytical science, but then eventually we’ll still be able to find the (hopefully limited in number) principles from which it can all be derived. I don’t think we’ll ever find that Occam’s razor is no use to us.

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

#44

Post by qwertox »

> Thrilled to announce AlphaFold 3 which can predict the structures and interactions of nearly all of life’s molecules with state-of-the-art accuracy including proteins, DNA and RNA. [1]

There's a slight mismatch between the blog's title and Demis Hassabis' tweet, where he uses "nearly all".

The blog's title suggests that it's a 100% solved problem.

[1] https://twitter.com/demishassabis/status/1788229162563420560

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

#45

Post by Jerrrry »

thomasahle wrote: post #41
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…

> Stepping back, the high-order bit here is an ML method is beating physically-based methods for accurately predicting the world. I mean, it's just faster, no? I don't think anyone is claiming it's a more _accurate_ model of the universe.

Collision libraries and fluid libraries have had baked-in memorized look-up tables that were generated with ML methods nearly a decade ago.

World is still here, although the Matrix/metaverse is becoming more attractive daily.

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

#46

Post by ozten »

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…

Science has always given us better, but error prone tooling to see further and make better guesses. There is still a scientific test. In a clinical trial, is this new drug safe and effective.

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

#47

Post by SubiculumCode »

l33tman wrote: post #10
Metacelsus wrote: post #4

From: https://www.nature.com/articles/d41586-024-01383-z >Unlike RoseTTAFold and AlphaFold2, scientists will not be able to run their own version of AlphaFold3, nor will the code underlying AlphaFold3 or other information obtained after training the model be made public. Instead, researchers will have access to an ‘AlphaFold3 server’, on which they can input their protein sequence of choice, alongside a selection of…

That sucks a bit. I was just wondering why they are touting that 3rd party company in their own blog post, who commercialise research tools, as well. Maybe there are some corporate agreements with them that prevents them from opening the system... Imagine the goodwill for humanity for releasing these pure research systems for free. I just have a hard time understanding how you can motivate to keep it closed. Let's ho…

There is at least some difference between a monitored server and a privately ran one, if negative consequences are possible

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

#48

Post by nexuist »

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…

As a steelman, wouldn't the abundance of infinitely generate-able situations make it _easier_ for us to develop strong theories and models? The bottleneck has always been data. You have to do expensive work in the real world and accurately measure it before you can start fitting lines to it. If we were to birth an e.g. atomically accurate ML model of quantum physics, I bet it wouldn't take long until we have mathematical theories that explain why it works. Our current problem is that this stuff is super hard to manipulate and measure.

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

#49

Post by CapeTheory »

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…

Many of our existing physical models can be decomposed into "high-confidence, well tested bit" plus "hand-wavy empirically fitted bit". I'd like to see progress via ML replacing the empirical part - the real scientific advancement then becomes steadily reducing that contribution to the whole by improving the robust physical model incrementally. Computational performance is another big influence though. Replacing the whole of a simulation with an ML model might still make sense if the model training is transferrable and we can take advantage of the GPU speed-ups, which might not be so easy to apply to the foundational physical model solution. Whether your model needs to be verified against real physical models depends on the seriousness of your use-case; for nuclear weapons and aerospace weather forecasts I imagine it will remain essential, while for a lot of consumer-facing things the ML will be good enough.

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

#50

Post by SubiculumCode »

Jerrrry wrote: post #12
Metacelsus wrote: post #4

From: https://www.nature.com/articles/d41586-024-01383-z >Unlike RoseTTAFold and AlphaFold2, scientists will not be able to run their own version of AlphaFold3, nor will the code underlying AlphaFold3 or other information obtained after training the model be made public. Instead, researchers will have access to an ‘AlphaFold3 server’, on which they can input their protein sequence of choice, alongside a selection of…

The second amendment prevents the government's overreaching perversion to restrict me from having the ability to print biological weapons from the comfort of my couch. Google has no such restriction.

/s is strong with this one
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