umutisik
Joined 13 years ago
Karma
417
Submissions
102
Member since
Aug 29
Recent submissions
Comment · 4 months ago
Customers / users are the judge.
Comment · 5 months ago
People talk about research mathematics being a science or an art, but it's also a sport. AI will kill the sport aspect of it. The art will survive. The science will thrive.
Comment · 7 months ago
With sufficient automation, there shouldn't really be a trade-off between rigor and anything else. The goal should be to automate as much as possible so that whatever well-defined useful thing can come out theory can come out faster and more easily. Formal proofs make sense as part of this goal.
Comment · 11 months ago
The number of resume submissions from here is not a lot. It's not at all like on LinkedIn.
Comment · 1 year ago
This is very impressive. I once built an educational Haskell programming + math. + art web site (mathvas.com). Something like this would have simplified that a lot.
Comment · 1 year ago
As a former professional mathematician: the benefits mentioned in the article (click-through definitions and statements, analyzing meta trends, version control, ...) do not seem particularly valuable.
The reason to formalize mathematics is to automate mathematical proofs and the production of mathematical theory.
Comment · 1 year ago
You still need the other 80% of the folks to get the remaining 20% of the work done :)
Comment · 1 year ago
He should add “Economists confidently making wishful-thinking based proclamations without a shred of evidence or even a plausible logical path.“ to the list!
Comment · 1 year ago
It does make me uneasy that founding companies is becoming another tracked thing that people feel they can apply high-IQ pattern-matching to. Especially when startups are where first-principles thinking is the most valuable.
That being said, I can see this being useful to a lot of kids. Certainly beats going to grad school for someone who wants to start a company. Keep in mind that a 500K SAFE doesn't force a founder to go big or zero-out.
Comment · 1 year ago
If data did live on a manifold contained, e.g. images in R^{n^2}, then it wouldn't have thickness or branching, which it does. It's an imperfect approximation to help think about it. The use of mathematical language is not the same as an application of mathematics (and the use of the word 'space' there is not about topology).
Comment · 1 year ago
Data doesn't actually live on a manifold. It's an approximation used for thinking about data. Near total majority, if not 100%, of the useful things done in deep learning have come from not thinking about topology in any way. Deep learning is not applied anything, it's an empirical field advanced mostly by trial and error and, sure, a few intuitions coming from theory (that was not topology).
Comment · 1 year ago
Make the cost of operating data centers reflect the damage to the environment and see how quickly people optimize. I don’t know how damaging storage is, but that’s the only way to make a difference.
Comment · 1 year ago
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Comment · 1 year ago
When considering a candidate on an F-1 + OPT, what should be our expectation of their need for H1B sponsorship?
What are O-1 and National Interest Waiver success rates for recent PhD grads (in computer science)?
Comment · 1 year ago
If AI can prove major theorems, it will likely by employing similar heuristics as the mathematical community employs when searching for proofs and understanding. Studying AI-generated proofs, with the help of AI to decipher contents will help humans build that 'understanding' if that is desired.
An issue in these discussions is that mathematics is both an art, a sport, and a science. And the development of AI that can build 'useful' libraries of proven theorems means different things for each. The sport of mathematics will be basically over. The art of mathematics will thrive as it becomes easier to explore the mathematical world. For the science of mathematics, it's hard to say, it's been kind of shaky for ~50 years anyway, but it can only help.