ranzispa

@ranzispa@mander.xyz · Joined ⁨Oct⁩ ⁨2025⁩

Replying to @⁨thanksforallthefish@literature.cafe⁩

What I’m saying is that also LLMs grew organically. Machine learning developed organically through the years and LLMs are one of the products of such development.

Machine learning algorithms were absolutely desired and wanted, hundreds of thousands of people worked on developing them. It is a very useful technology. If I may list one very useful development: AlphaFold, for which the 2024 Nobel prize was adjudicated.

Now, whether LLMs are useful in chemistry and biology: kind of. Coming up with the design of a bacteriophage is not the first use which would come to my mind. Of course LLMs are being tested for their applications in such domains, but results are in general worse than dedicated models. One area in which I see value is the use of agents in orchestrating tools and analyzing results. Not really in producing new things on their own.

Replying to @⁨thanksforallthefish@literature.cafe⁩

I come from a chemistry background. Chemistry is one of the first field in which machine learning was first applied. In fact many of the first algorithms and models have been developed by chemists.

This has been a gradual adoption throughout the past 50 years.

How is this different from your description of the internet history? If anything, internet was much faster than that: it took less than 50 years from the first computer to the invention of internet.

And I’m not even considering the first developments in machine learning, which happened pretty much as soon as computing machines were invented.

Replying to @⁨Buffalox@lemmy.world⁩

If you wish, this was indipendently confirmed: the same proof was published by two authors at the same time.

scientificamerican.com/…/ai-helped-produce-two-pr…

A silhouetted man gestures toward symbolic logic written in chalk across a blackboard.Scientific AmericanAI helped produce two proofs for the same cryptography problemAn M.I.T. Ph.D. student and two University of California system cryptographers used GPT-5.6 Sol Ultra in different ways, raising new questions about independent discovery and scientific credit

Replying to @⁨Buffalox@lemmy.world⁩

Scientists don’t often publish when they confirm an article is correct. Knowing a few mathematicians, probably they see no need to do that. They checked the proof, it was ok and that’s it.

Either way, many of those proofs come with a computer program which checks and confirms the proof is correct.

I trust that an expert mathematician talking about such things has reviewed a few of those articles and has checked the proof.

You may not do that; check the proof yourself or pay a mathematician to do it for you.

Replying to @⁨Buffalox@lemmy.world⁩

Yes, scientific articles are expensive. I know that, that sucks. That’s why most of this stuff is on arxiv.

I linked to evidence that mathematicians are using LLMs to find proofs and publish those proofs. Which is what I said is happening.

…stackexchange.com/…/can-i-publish-a-novel-theore…

I am not a mathematician, thus I don’t really know where to find indipendent confirmation or even how that is generally handled by mathematicians. However: there are plenty proofs on arxiv that disclose have been found with LLMs. Some of these proofs relate to famous problems and have been in the news. Fields medal winners discuss the importance of LLMs and how it may produce too many proofs for humans to handle.

I trust that those proofs published on arxiv have been reviewed by many mathematicians, if they were incorrect that would have rapidly become known.