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Terence Tao on O1
111–120 of 527 posts
Re: Terence Tao on O1
#112Earlier quoted context omitted.
I entirely agree about their utility. HN, and the internet in general, have become just an ocean of reactionary sandbagging and blather about how "useless" LLMs are. Meanwhile, in the real world, I've found that I haven't written a line of code in weeks. Just paragraphs of text that specify what I want and then guidance through and around pitfalls in a simple iterative loop of useful working code. It's entirely a lea…
> I've found that I haven't written a line of code in weeks Which is great until your next job interview. Really, it's tempting in the short run but I made a conscious decision to do certain tasks manually only so that I don't lose my basic skills.
You need to prep for job interviews anyway. I'd rather spend the majority of my time being productive.
Re: Terence Tao on O1
#113Completely agree with Terence Tao. this is a real advancement. I've always believed that with the right data allowing the LLM to be trained to imitate reasoning, it's possible to improve its performance. However, this is still pattern matching, and I suspect that this approach may not be very effective for creating true generalization. As a result, once o1 becomes generally available, we will likely notice the persistent hallucinations and faulty reasoning, especially when the problem is sufficiently new or complex, beyond the "reasoning programs" or "reasoning patterns" the model learned during the reinforcement learning phase.
https://www.lycee.ai/blog/openai-o1-release-agi-reasoning
Re: Terence Tao on O1
#114Once GPT is tuned more heavily on Lean (proof assistant) -- the way it is on Python -- I expect its usefulness for research level math to increase. I work in a field related to operations research (OR), and ChatGPT 4o has ingested enough of the OR literature that it's able to spit out very useful Mixed Integer Programming (MIP) formulations for many "problem shapes". For instance, I can give it a logic problem like "…
I entirely agree about their utility. HN, and the internet in general, have become just an ocean of reactionary sandbagging and blather about how "useless" LLMs are. Meanwhile, in the real world, I've found that I haven't written a line of code in weeks. Just paragraphs of text that specify what I want and then guidance through and around pitfalls in a simple iterative loop of useful working code. It's entirely a lea…
In my view these models produce above average code which is good enough for most jobs. But the hacker news sampling could be biased towards the top tier of coders - so their personal account of it not being good enough can also be true. For me the quality isn't anywhere close to good enough for my purposes, all of my easy code is already done so I'm only left working on gnarly niche stuff which the LLMs are not yet helpful with.
For the effect on the industry, I generally make the point that even if AI only replaces the below average coder it will cause a downward pressure on above average coders compensation expectation.
Personally, humans appear to be getting dumber at the same time that AI is getting smarter and while, for now, the crossover point is at a low threshold that threshold will of course increase over time. I used to try to teach ontologies, stats, SMT solvers to humans before giving up and switching to AI technologies where success is not predicated on human understanding. I used to think that the inability for most humans to understand these topics was a matter of motivation, but have rather recently come to understand that these limitations are generally innate.
Re: Terence Tao on O1
#115Earlier quoted context omitted.
I entirely agree about their utility. HN, and the internet in general, have become just an ocean of reactionary sandbagging and blather about how "useless" LLMs are. Meanwhile, in the real world, I've found that I haven't written a line of code in weeks. Just paragraphs of text that specify what I want and then guidance through and around pitfalls in a simple iterative loop of useful working code. It's entirely a lea…
> HN, and the internet in general, have become just an ocean of reactionary sandbagging and blather about how "useless" LLMs are. This is cult like behaviour that reminds me so much of the crypto space. I don't understand why people are not allowed to be critical of a technology or not find it useful. And if they are they are somehow ignorant, over-reacting or deficient in some way.
just like with crypto and NFTs and the metaverse, they are always focused on what is suppsoedly coming down the pipe in the future and not what is actually possible today
Re: Terence Tao on O1
#116Earlier quoted context omitted.
> HN, and the internet in general, have become just an ocean of reactionary sandbagging and blather about how "useless" LLMs are. This is cult like behaviour that reminds me so much of the crypto space. I don't understand why people are not allowed to be critical of a technology or not find it useful. And if they are they are somehow ignorant, over-reacting or deficient in some way.
Also, I'm deeply skeptical of crypto too due to its present scamminess, but I am keeping an open mind that there is a future in which crypto -- once it gets over this phase of get-rich-quick schemers -- will be seen as just another asset class. I read somewhere that historically bonds in their early days were also associated with scamminess but today they're just a vanilla asset.
bonds have utility, crypto does not
Re: Terence Tao on O1
#117Earlier quoted context omitted.
> Much Much more productive world by just knuckling down and learning how to do the work. The fact everyone that say they've become more productive with LLMs won't say how exactly. I can talk about how VIM have make it more enjoyable to edit code (keybinding and motions), how Emacs is a good environment around text tooling (lisp machine), how I use technical books to further my learning (so many great books out here)…
> But no one really show how they're actually solving problems with LLMs and how the alternatives were worse for them. It's all claims that it's great with no further elaboration on the workflows. To give an example, one person (a researcher at DeepMind) recently wrote about specific instances of his uses of LLMs, with anecdotes about alternatives to each example. [1] People on HN had different responses with similar…
> (often misquoted) phrase
You misquoted it there! It should be: The plural of anecdote is data.
Re: Terence Tao on O1
#118Is there a list of discoveries or siginficant works/constructions made by people collaborating with LLM's? I mean as opposed to specific deep networks like Alphafold or Graphcast?
It may cause a reputation or legal issue, so it is not in their interest to admit it. In the real world, is there PhD students or researchers using ChatGPT to move forward and help them think their ideas ?
Obviously yes, but admitting it may not be the right move.
Re: Terence Tao on O1
#119The o1 model is really remarkable. I was able to get very significant speedups to my already highly optimized Rust code in my fast vector similarity project, all verified with careful benchmarking and validation of correctness. Not only that, it also helped me reimagine and conceptualize a new measure of statistical dependency based on Jensen-Shannon divergence that works very well. And it came up with a super fast i…
>you would be hard pressed to find many humans capable of helping with (at least without shelling out $500k+/year in compensation for).
And now we have a $number we can relate, and refer, to.
Re: Terence Tao on O1
#120[deleted]