C'mon AI companies, pivot to lawyers or doctors already.
Trying to convince us that mathematics and software engineering are "solved" is getting very tiring.
The pushback would probably be too much for the soon-to-be IPO-ed companies.
C'mon AI companies, pivot to lawyers or doctors already.
Trying to convince us that mathematics and software engineering are "solved" is getting very tiring.
The pushback would probably be too much for the soon-to-be IPO-ed companies.
Mathematics is typically concerned with "proofs" [1], which similarly to code, often allow for strict validation. Thanks to reinforcement learning techniques, it is now possible to train LLMs to perform very well on code generation, and mathematical proof generation.
Law and medicine are fundamentally harder fields to obtain decent training data for, and LLM results are therefore expected to be less powerful. Also, making mistakes in these fields is costly, but perhaps you were alluding to that already.
[1] https://en.wikipedia.org/wiki/Mathematical_proof
Mathematician here. There is a lot of recent work on the Lean project -- when a proof can be translated into Lean code, then it can be strictly and formally validated.
https://lean-lang.org/
But otherwise, mathematical proofs are read and written by humans, and at the end of the day the relevant standard of proof is what other mathematicians will accept.
Occasionally, mathematicians don't agree. For a prominent example, you can read about Shinichi Mochizuki's claimed proof of the so-called ABC Conjecture:
https://en.wikipedia.org/wiki/Abc_conjecture#Claimed_proofs
For that particular example, it's now been proved that Mochizuki's proof is incomplete: https://zeli.app/en/story/48963019
I guess whether he will eventually fix those gaps and resolve the issues remains to be seen.
> Law and medicine are fundamentally harder fields to obtain decent training data for
I think this bubble has given a lot of people software brain and are trying to apply it to fields it is wholly inappropriate for, though. Law is about argumentation and rhetoric. It is about providing a persuasive argument. This is how it is taught. The actual legal code is a way to formalize parts of it, but increasingly I see people angrily insisting that the only thing that matters is the text.
As you might imagine, I find textualism a load of applesauce, but I don’t think the vast majority of people making this argument even understand textualism as jurisprudence. It seems to stem from Crypto bros and the whole “code is law” argument which is just codswallop.
A neighbor of mine whose husband is a lawyer said it's already part of his regular workflows. OpenAI also already have HIPAA compliant offerings targeting healthcare uses, etc. Of course they already do these things.
They try to sell AI as lawyer or doctor replacements as well. But because it’s HackerNews we are biased towards our domains to see them more often.
Well also you can't just throw AI slop as doctors or lawyers advice and fail multiple times until you find the right answer. With code and math you can have failures 1000 times for every success and still get rewarded.
They can rely on compilers, solvers, theorem provers to validate the generated softwares and maths. That’s what makes it possible to iterate quickly in a loop and self correct. You cannot do that in soft industries like legal and medicine
That is not the point I was making. I am not talking about validating software or maths. It can generate stuff that is valid, but bad and incomprehensible.
What I’m saying is that AI labs are talking so much about software and maths because we already have tools that can say « it’s all good ». That makes it possible and worth it for them to spend 1 week of compute on a problem until the validator passes, then publish marketing pieces. You cannot do the same in medicine or laws (modulo some niche areas)
Look up OpenEvidence
Most used as a Wikipedia-on-the-fly. Replaces UpToDate and other POC tools NOT professionals operating them.