871–880 of 884 posts
Earlier quoted context omitted.
> Would he say no? And that’s the issue the article is trying to explain.
My thought experiment was trying to extract the issue from the zeitgeist around AI, so not really
Earlier quoted context omitted.
Of course there's a meaningful analogy. The poster wants to make Tao sound unreasonable and against "progress" while ignoring the very real concerns Tao has. It's what fanatics do when they want to enforce their view on the world, they have to attack anyone with a reasonable viewpoint because they can't imagine a world where someone tells them they don't like what they're doing.
I do not want to make him sound unreasonable. He is a brilliant man. But I also think that he is a bit shell shocked, much like other luminaries in the past have been when confronted with rapid technological development, so I wanted to highlight some historical similarities, imperfect as they can only be. As for the rest of your comment, I hope you have a great day.
Earlier quoted context omitted.
Yup, found it: https://news.ycombinator.com/item?id=49101465
Cool, thanks!
Earlier quoted context omitted.
Not if it's lean-verified.
"Lean-verified" is not some magical incantation that makes a supposed proof irrefutable. Even disregarding potential bugs in the kernel as others have said. Say that AI gives you a Lean proof and says it proves Theorem X . It could just as easily give you the same proof but claim that it proves (not X ). How would you know the difference? Nothing can really be considered proven unless a human expert can read the Lean…
I was watching a talk by Terence Tao a couple of days ago, and I noticed a shift in his attitude towards AI. His enthusiasm seemed to have waned; he was becoming more dismissive of it, and I was wondering why. “A Severe Misalignment of AI in Mathematics,” with a list of important mathematicians. This post makes it clear that, to put it bluntly, they’re psychologically butt-hurt. They talk about misalignment, but this…
I think their point is more on the fact that just proving something is only half the work. Intermediate results and proofs are often also of immense value. Right now the output is sloppy proofs and LEAN code. This is useful, but a large part of the effort still lies ahead. And if you are a mathematician you'd rather be working on hard problems than fixing slop.
I think they're more afraid of the current status quo. Distilling, writing textbooks, teaching, ...
And currently, I could be wrong but, I see them being blind to the possibilities it brings. AI could very well be distilling maths, spreading it, and nurturing the ecosystem way better than the few elite mathematicians ever could.
Earlier quoted context omitted.
> Many graduate students (I know) are having a crisis if any of their research worth it? If AI can (or will) do everything, what's the point of doing experiments and all? This will eventually deter a whole generation of curious minded students from research. Those who think it's me or the machine will fail. Those who realize how much you can accelerate your research with the help of AI will succeed.
> Those who think it's me or the machine will fail. > Those who realize how much you can accelerate your research with the help of AI will succeed. This is only true up until a point. If I treat a mid-sized model (say, Qwen3.8 Flash Next) like a pair programmer, then yes, it accelerates my work. But I can already see the next stage with Fable: If I give it a couple of paragraphs of spec and $50, then I can just leave…
The people that uses Adobe Photoshop also did not learn anything about brushes. We are just going to operate at a much higher level of abstractions. You have to think about the question, "If I just prompted this solution, why didn't they?". This question can even be asked now, why do I even bother paying someone to do my taxes? To write my webpage? To host my website? To manage my network?
Earlier quoted context omitted.
The trailing edge of AI is catching up fast. There's plenty of open source (and even more open weight) AI models and they are getting better and better. If that's your only objection: in a few years you can prove Rieman's hypothesis on your smartphone, no need for any trillionaires to give you permission. Does that make any change to your argument, or did it not actually matter?
The problem with your opinions is that you tend to state certain very quesitonable ideas with 100% confidence. Right now, we don't know if AI will be able to solve bigger problems, or if they'll be so efficients that you no longer need a whole datacenter for running them. We don't even know how much of creative work they are able to do. We cannot make decisions that could destroy decades of progress just because of h…
For the latter: I assume that having a whole data centre will always be an advantage. I am saying that for a fixed target, like proving the Rieman hypothesis from scratch, the required hardware will shrink.
And, yes, the Rieman hypothesis hasn't been proven yet. So to take your fears into account, replace my example with something they've already done, like constructing a solution to the Navier-Stokes-problem.
Earlier quoted context omitted.
> Does mathematics still have a practical impact without humans in the loop? There's a single answer to that question: yes, math very much has an impact without humans in the loop. Math has a lot of applications, and those applications don't care whether eg the new faster matrix multiplication algorithm was found and proven correct by a machine or a meatbag.
We're way into diminishing returns in matrix multiplication, and being clever about ALUs and cache layout is likely to dwarf any asymptotic improvements you're going to find. Any better examples of improvements in the last decade? The main situation I can think of where better calculations have a really visible effect is video and image compression, and that stuff is very far away from mathematical proof territory.
Earlier quoted context omitted.
> Does mathematics still have a practical impact without humans in the loop? There's a single answer to that question: yes, math very much has an impact without humans in the loop. Math has a lot of applications, and those applications don't care whether eg the new faster matrix multiplication algorithm was found and proven correct by a machine or a meatbag.
We can't be sure AI will be able to ask the questions of the future. At least right now, AI is not capable of that.
You give your AI the problem, like 'make this computer program faster and more reliable', and it'll go off and do the math necessary to make it so.