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Terence Tao on O1

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Re: Terence Tao on O1

#151

Post by rvnx »

skydhash wrote: post #121
Nadya wrote: post #83

Earlier quoted context omitted.

Ever seen someone try and search something on Google and they are just AWFUL at it? They can never find what they're looking for and then you try and can pull it up in a single search? That's what it is like watching some people try to use LLM's. Learning how to prompt an LLM is as much a learned skill as much as learning how to phrase internet searches is a learned skill. And as much as people decried that "searchin…

I'm not arguing that you can't get result with LLMs, I'm just asking is it worth the actual effort especially when there's better way to get that result you're seeking (or if the result is really something that you want). An LLM is a word (token?) generator which can be amazingly consistent according to its model. But rarely is my end goal to generate text. It's either to do something, to understand something, or to…

It works quite nicely if you consider LLMs as a translator (and that’s actually why Transformers were created).

Enter technical specifications in English as input language, get code as destination language.

Re: Terence Tao on O1

#152

Post by cjbgkagh »

bcoates wrote: post #135
cjbgkagh wrote: post #114

Earlier quoted context omitted.

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 h…

Re: Compensation expectations, I figured out a long time ago that bad programmers create bad code, and bad code creates work for good programmers. If the amount of bad code is no longer limited by the availability of workers who can be trained up to "just below average" and instead anyone who knows how to work a touchscreen can make AI slop, this opens up a big economic opportunity.

One could hope, but in my view perception precedes reality and even if that is the reality the perception is that AI will lower compensation demands and those doing the layoffs/hiring will act accordingly.

You could also make the same claims about outsourcing, and while it appears that in most cases the outsourcing doesn't pay off, the perception that it would has really damaged CS as a career.

Re: Terence Tao on O1

#156

Post by fragmede »

gary_0 wrote: post #51

Tao mentions grad students; I wonder how they feel reading this? As LLMs continue to improve I feel like anyone making a living doing the "99% perspiration" part of intellectual labor is about to enter a world of hurt.

> The experience seemed roughly on par with trying to advise a mediocre, but not completely incompetent, graduate student.

And you thought you had imposter syndrome before!

Re: Terence Tao on O1

#157

Post by [deleted] »

nybsjytm wrote: post #109

Daniel Litt, an algebraic geometer on twitter, said "Pretty impressed by o1-preview! Still not having much luck asking it to do any interesting math but it seems much more reliable with simple things; I can actually imagine it being a net time-saver at this point with some non-mathematical tasks." Any other takes by mathematicians out there?

[deleted]

Re: Terence Tao on O1

#158

Post by amrrs »

WhatIsDukkha wrote: post #26
wenc wrote: post #5

Once 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…

Curious why Aider? Why not Cursor ?

Re: Terence Tao on O1

#159

Post by stavros »

kristianp wrote: post #117
pbrowne011 wrote: post #91

Earlier quoted context omitted.

> 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.

It's actually "the plural of 'anecdote' is not 'data'".

Re: Terence Tao on O1

#160

Post by bongodongobob »

minkles wrote: post #148
WhatIsDukkha wrote: post #26

Earlier 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…

That’s fine until your code makes its way to production, an unconsidered side effect occurs and then you have to face me. You are still responsible for what you do regardless of the means you used to do it. And a lot of people use this not because it’s more productive but because it requires less effort and less thought because those are the hard bits. I’m collecting stats at the moment but the general trend in quali…

Ugh, dude, I used to push bad code into production without ChatGPT. It is such a stupid argument. Do you really think people are just blindly pushing code they can't make heads or tails of? That they haven't tested? Do you seriously think people are just one shotting code and blasting it into prod? I am completely baffled by people in this industry that just don't get it. Learn to prompt. Write tests. Wtf.
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