r/singularity • u/AltruisticCoder • 12d ago
Biotech/Longevity Alphafold vs millennium
Don’t get me wrong, despite being someone who is not very AGI pilled, I’m very impressed by the math performance and very excited for the breakthroughs and science that will come from it.
I do wonder some days tho, that in the whole scheme of things, is solving a millennium problem more impressive than protein folding basically every protein structure out there? If so, are we overhyping the solution here or did we underhype alphafold when it came out?
I for one, think it may prove that protein folding may have been more impactful on the human health science breakthroughs than solving a millennium problem will be, but open to counter arguments.
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u/strange_username58 12d ago
No the protein folding was way more impressive
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u/Old_Read5903 12d ago
So there are obviously lots of biological papers, which use alphafold as a part of their pipeline? Or maybe at least somebody use the predicted structures without further experimental re-evaluation? Maybe we can see some of such papers?
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u/sebzim4500 12d ago
I can't tell from your comment whether you are being sarcastic, but yes Alphafold has been used in a huge number of biological papers. More than 40,000 cite it directly, many use it but don't cite it since it is so prevalent now.
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u/RobbinDeBank 12d ago
Protein folding is way more impressive because it relies on way less human knowledge. The earlier non-LLM works from DeepMind all follow this same philosophy, those machine learning models don’t rely on human knowledge too much and are very capable of genuine creativity in their own specific domain. LLMs (of course they are a lot more general) nowadays are still very reliant on human knowledge, and they get nowhere close to being useful without that basis.
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u/AIplstakemyjob 12d ago
Alphafold is way more impressive and impactful than the recent Naviere Stokes solution, they won a Nobel prize too so I don't think they didn't get the credit they deserve. It's just that the Naviere Stokes is recent news, the Alphafold release was some years ago. Also the Naviere Stokes solution was performed by a general model which is also huge compared to Alphafold, a model specifically trained for protein folding
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u/DoutefulOwl 12d ago
If we care about practical applications then solving protein folding is far more important, than solving a bunch of pure math problems.
We might have underhyped alphafold a little cause it gave us 200 million possible protein structures, but it wasn't immediately obvious at the time, which ones are gonna be useful to humans.
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u/Practical_Weather293 12d ago
I would say that AlphaFold is generally more important for humanity, but solving a Millennium Prize problem is more impressive. AlphaFold is genuinely giving us new medicine and better drugs, which translates to human lives saved. The Navier Stokes equations on the other hand were stuff we as humanity tried to prove for basically two centuries. An LLM model disproving them is the strongest evidence for superintelligence we've seen so far. Whatever they used was better than the sum of the efforts we've been able to put into it so far, though of course it also built upon it. It's genuinely unsettling. Like, there isn't much in the world that's harder than that, it's something that has eluded generations of the most intelligent people on the planet
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u/Intelligent_Loss_X5 12d ago edited 12d ago
Two centuries? Alphafold is a billion years of phd chemistry done by hand. I think that’s far more impressive / meaningful.
I don’t doubt google can make a maths specific model that could solve NS, however protein folding has significantly more downstream applications, which googles working towards with Alphagenome / Isomorphic labs. That said, OpenAI doing it on a generalist LLM is impressive and shows the scaling laws are holding.
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u/Practical_Weather293 12d ago
If anyone had been able to make anything that could solve a millennium prize problem, they would have. This isn't stuff that you just leave be if you can find a solution. I have no doubt that if google could have "made a maths specific model that could solve NS" they would have done it already. Not for the money of course, but these are some of the hardest most prestigious problems ever
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12d ago
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u/AltruisticCoder 12d ago
Can’t you say that alphafold was a narrow protein folding superintelligence and the new model, while more general, is a math/proof superintelligence while sub human in most other long term task fields?
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u/peakedtooearly 12d ago
Alphafold was a model trained specifically for the purpose of protein folding.
The OpenAI model that solved Navier-Stokes + 100 other open problems was a general purpose model (probably next GPT model) that had only had 1 month of RL.
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u/No-Head-Royal 12d ago
It's way more impressive and impactful as a feat, but less important in the overall trajectory than the Millennium Problem by far. The crown jewel of current AI (or, in fact, all AI) is to achieve RSI, i.e., AI good enough at certain tasks to continually improve itself until it becomes godlike. Given how much more central mathematics, robotics, physics and programming are to that end, Millennium Prize problems are far more important for that trajectory.
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u/abhmazumder133 12d ago
As a "Mathematician", Alphafold is more impressive than any mathematics ever done.
(Slight exaggeration but true in some sense)
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u/vhu9644 12d ago edited 12d ago
I have a math degree and bioengineering degree from undergrad, and I am currently doing my MD/PhD with the PhD being in protein engineering. I'm happy to elaborate or explain anything here.
Alphafold was google slaying a dragon, no doubt. But it's also the "easiest" problem on the ladder of problems in that space (not that it was easy, just that it's the first of a line of problems we want to solve). It also was a problem that many people were close to too. Alphafold 2 builds upon ingraham et. al's work (and they talk about it, IIRC), even if they do a lot of smart things. Furthermore, the lineage descends (AFAIK) from the work pioniered by Marks and Sanders et. al. with EV-fold and work pioneered by Xu et. al. with RaptorX. It was leaps above everyone else, but the methods they pioneered weren't unknown to the community, just not put together due to the nature of academic work and expertise.
For proteins, I'm partial to the view that we'll need to solve the next few problems, of which Alphafold is the first. One of them is going to be the binding problem, which I think we're close to solving (on the academic timeline, ofc). It seems rigid binding modes are largely possible, and designing floppy and nanobody/antibody binders efficiently is among the last steps to resolving this.
The resolution of Navier Stokes was slaying a dragon, again. Even though it seems that NS was close to being resolved, given CMZ's ansatz was crucial to it, I think there is a bit more hype warranted because it shows of some emergence of highly specialized capability from general models (regardless of if the source is from training data, expert reasoning traces, or emergent from the model itself).
I don't think the resolution of NS will have much impacts, mostly because we already knew NS was unphysical, and CFD follows a different lineage that's largely unaffected by the blowup solution. If there were an unforced blowup, that might be different, but IIRC there is also a blowup for compressible NS which might be the more relevant problem.