Posted by artninja1988 2 days ago
Look at what's happening in the math community- rather than excitedly embracing the power of AI's ability to generate new proofs, they are screaming for it to slow down (and quite a few want it simply stopped). Many scientists, even in ostensibly more real-world fields are broadly cut from the same cloth.
A much more practical reason we're not yet seeing a lot of headline scientific mathematical breakthroughs is just that it is ungodly expensive! e.g. The Navier-Stokes result cost around $20M at API prices, and academics just don't have that kind of money to spend. You'll see more mathematical and scientific results from practitioners when either the cost of compute needed for these sort of brute force results is more in line with the size of academic grants, and/or the AI companies donate more compute to the scientific community.
There are different reactions from different mathematicians of course - Terrance Tao vs Cedric Villani, and no doubt a lot of shock at the speed of advance, but it seems the reasoned complaint why they don't want the AI companies themselves working on these problems is because the outcome is not the same - you get a result that in of itself may have been suspected or useless (Navier Stokes), but no write up of any new math or insights that were developed along the way, which is the real reason mathematics and people like Erdos pushed these famous problems in the first place - because they were expected to yield interesting mathematics, just as years of work on FLT had done. Imagine if instead of Wiles's work, and all that had gone before him, all we had was a $20M compute bill, hundreds of pages of impenetrable math, and a billion lines of Lean proving it was true?!
There is a difference between what's easy/hard for a human vs computer, and LLMs haven't changed that. You might expect a computer to be good at tasks requiring prodigious memory and compute, and it turns out that some of these long-standing math problems are of that nature - not requiring new breakthroughs but rather just massive exploration of what is already known and what they were trained on.
There will no doubt be more math results like this, but presumably also ones that are "hard for a human, easy for a computer", requiring massive search (e.g. find an example/counter-example cf Navier-Stokes & Jacobian conjecture) rather than creativity.
Demonstrate the ability to cryopreserve and recover live wild-type mice with high viability.
> 06 - Somatic limb regeneration
Demonstrate the ability to regenerate lost limbs in adult wild-type mice.
Interesting, but looks like these problems are proposed in September 2026, unlike original 7 Millennium Prize Problems of Maths
I thought we already managed to successfully cryopreserve and recover small rodents like hamsters in the 50s.
Edit: See https://en.wikipedia.org/wiki/Cryopreservation#History
I think GP was saying the proof of the pudding is in the tasting: the longer a problem has provably resisted resolution the more difficult it is considered...
bombastically decorating a problem as equivalently difficult does not make it so.
This list of "Millenium Problems for Biology" contains such brainfart level "analogies" that there the list will be ridiculed, for the question / challenge itself displays a lack of understanding of the subject in question. Science is also asking the right questions.
Consider for example:
> 10. Protein Amplification Chain Reaction:
> Demonstrate exponential amplification of arbitrary peptide substrates.
> Specifically, demonstrate input-protein-dependent synthesis of new, full-length, sequence-faithful covalent polypeptide copies from amino-acid monomers without a nucleic-acid template or preformed cognate scaffold, in a single pot reaction. For the challenge to be considered complete, at least 100 random peptide sequences of at least 50 amino acids each must be preregistered, synthesized, and pooled. It must then be shown that the abundance of these peptides in solution can be amplified at least 1000x with at least 90% sequence accuracy on a per-residue basis. Reasonable modifications may be added to the peptide sequences to facilitate post-amplification analysis if necessary, provided they are not active in the amplification. Methods that rely on explicit sequencing of the peptide are not permitted. Methods that rely on reverse translation to generate a nucleic acid intermediate are not permitted, because they are duplicative with a separate Millennium Problem.
The analogy is very clear: to amplify DNA or RNA one uses PCR, basically throw the desired product in a cauldron with monomer building blocks, then by repeated heating and cooling the lone monomers find their permitted locations on a complementary pre-existing strand, and form the new polymer strand.
So it seems natural to ask for a generalization to protein polymers, except every biologist or chemist knows its nonsense: proteins don't have a complementary strand! You can't demand chemistry or physics to magically copy without a complementary template!
You may ask "but if that were true, how can we already have PCR for RNA?"
Well pretty simple: while this is done routinely, its only possible indirectly: convert the RNA to double-strand DNA, use PCR on this DNA and then convert the amplified DNA back to RNA!
The demand to not involve sequencing or the hypothetical reverse translatase from one of the other problem statements turns this one into a non-existence theorem, but the challenge doesn't describe a winner for demonstrating its impossibility!
I assure you that any chemist or biologist being asked why we dont have PCR for protein, will understand your lack of knowledge, and explain how PCR works, so that you understand that PCR was only possible because of the complementary strand!
This list will be ridiculed for being not even wrong.
At least those things cannot be solved by just burning GPT tokens.
That there are no more efficient variations of it in nature just tells us that the local minimum is really deep and that natural evolution, as it is, can’t produce anything better, not even with a billion years and 10^30 organisms serving as a “brute force lab”. It’s also the kind of problem an AGI system would tackle for purely ideological reasons, i.e. to prove that it is superior to nature.
Reverse translatase and protein amplification in particular.
How the fuck do you plan on selectively priming protein amplification. If you know ANY protein chemistry, you will know "the juice is not worth the squeeze" -- how would I exponentially amplify a protein? I'd do mass spec proteomics, synthesize the DNA, and express it.
Simply amazing that electrofixation is not on the list.
Cryopreservation, even though I don't care much for it.
The rubisco one is sort of not dumb, but if you actually care about carbon fixation you'd just not bother using rubisco at all instead.
Programmable Proteases is fine.
Somatic regeneration is fine.
Do you mean electrofixation of nitrogen? What level of biological involvement are you imagining? More like biology producing (some?) of the catalysts, or more like the entire reaction happening inside of cells?
Also if you think humans would ever become a space faring species, would it really make sense to stick to our carbon based biology or should we invest in transforming into silicon based beings