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Terence Tao on O1

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191–200 of 527 posts

Re: Terence Tao on O1

#191

Earlier quoted context omitted.

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.

Do you think ChatGPT has changed any of those answers from Yes to No? Because it hasn't.

People blindly copied stack overflow code, they blindly copied every example off of MSDN, they blindly copy from ChatGPT - your holier than thou statements are funny, and frankly most LLMs cannot leave a local maxima, so anyone who says they dont write any code anymore I frankly think they are not capable of telling the mistakes, both architecturally and specifically that they are making.

More and different prompting will not dig you out of the hole.

Re: Terence Tao on O1

#192

Earlier quoted context omitted.

But a lot of what you pay humans $500k a year for is to work with enormous existing systems that an LLM cannot understand just yet. Optimizing small libraries and implementing fast functions though is a huge improvement in any programmer's toolbox.

Can’t Gemini work with a million+ input tokens?

It doesn't work well though. You can't just stuff your entire codebase into it and get good results. I work somewhere that tries to do this internally

Re: Terence Tao on O1

#193

Rewind your mind to 2019 and imagine reading a post that said “The experience seemed roughly on par with trying to advise a mediocre, but not completely incompetent, graduate student.” With regard to interacting with the equivalent of Alexa. That’s a remarkable difference in 5 years.

The important point is, I feel, that most people are not even at the level of intelligence of a "a mediocre, but not completely incompetent, graduate student." A mediocre graduate science student, especially of the sort who graduates and doesn't quit, is a very impressive individual compared to the rest of us.

For "us", having such a level of intelligence available as an assistant throughout the day is a massive life upgrade, if we can just afford more tokens.

Re: Terence Tao on O1

#194

Rewind your mind to 2019 and imagine reading a post that said “The experience seemed roughly on par with trying to advise a mediocre, but not completely incompetent, graduate student.” With regard to interacting with the equivalent of Alexa. That’s a remarkable difference in 5 years.

To be honest, I have gotten 100x more useful answers out of Siri's WolframAlpha integration than I ever have out of ChatGPT. People don't want a "not completely incompetent graduate student" responding to their prompts, they want NLP that reliably processes information. Last-generation voice assistants could at least do their job consistently, ChatGPT couldn't be trusted to flick a light switch on a regular basis.

Then you have a skill issue. 10 million paying are for GPT monthly because a large of them are getting useful value out of it. WolframAlpha has been out for a while and didn't take off for a reason. "GPT couldn't be trusted to flick a light switch on a regular basis" pretty much implies you are not serious or your knowledge about the capabilities of LLM is pretty much dated or derived from things you have read.

Re: Terence Tao on O1

#195

Earlier 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…

In the CUDA example [1] from carlini's "how I Use AI", I would guess that o1 would need less handholding to do what he wanted.

[1] https://chatgpt.com/share/1ead532d-3bd5-47c2-897c-2d77a38964...

Re: Terence Tao on O1

#196

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…

Wasn't there a recent post about many research papers getting published with conclusions derived from buggy/incorrect code?

I'd put more hope in improving LLMs/derivatives than improving the level of effort and thought in code across the entire population of "people who code", especially the subset who would rather be doing something else with their time and effort / see it as a distraction from the "real" work that leverages their actual area of expertise.

Re: Terence Tao on O1

#197
post #76

Tao and Aaronson are optimistic about LLMs. What are they telling their students? That math and science degrees will soon have the same value as a degree in medieval dance theory? If they are overly optimistic, perhaps it would be good to hear the opinions of Wiles and Perelman.

What does this mean? Of course math AI will take over top research in next ten years but usefulness to society has never been a goal of pure mathematics. I don't know if you understand the motivation for studying pure math. Personally I think it will be mostly good for research math

The "value of a degree" means the employment prospects for the degree holder.

Which is going to zero if the optimistic predictions are correct, so the optimistic professors should warn their students.

I understand the motivation for pure math quite well. It is about beauty, understanding things and discovering things for oneself. If computers do the work, the discovery part is gone and pure math is ruined.

For the non-research part, the AI zealots will want to replace all human labor with software.

Re: Terence Tao on O1

#198
He mentions that he posed to O1 the same challenge he posed to a previous GPT (which he also previously blogged about), so I am wondering how much O1 benefited from potentially "seeing" this discussion in its training set (which probably contains a very well recent snapshot of the world wide web).

Re: Terence Tao on O1

#199
post #61

Earlier quoted context omitted.

I’ve made the decision to embrace being bad at coding but getting a ton of work done using an LLM and if my future employer doesn’t want massive productivity and would prefer being able to leetcode really well then I unironically respect that and that’s ok. I’m not doing ground breaking software stuff, it’s just web dev at non massive scales.

You future employer might expect you to bring some value through your expertise that doesn't come from her LLM. If you want to insist on degrading your own employability like this, I guess it's your choice.

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