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Terence Tao on O1

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Re: Terence Tao on O1

#491

Post by ocular-rockular »

j_maffe wrote: post #480
ocular-rockular wrote: post #476

I don't understand why this is news? This could have been said by any one particular contributor from HackerNews but just because it's from Terence Tao it hits the front page? I understand that the guy is a great mathematician, but why is his input on this any more valuable than the myriad of discussions about o1 from other professionals on here?

If anyone comes across comments from professionals on the same level at Terrance Tao, I'd love for them to share it.

Most people would likely not engage with that commentary simply because they don't enjoy the same celebrity status as Tao. Yet, I think those voices are equally important to be heard. Terence isn't the only PhD/professional using or discussing these tools.

Re: Terence Tao on O1

#492

Post by cwillu »

idunnoman1222 wrote: post #472

How did this guy not know how large language models work? Fancy compression algorithm for all written knowledge, how could it invent that which was not an input ?

https://arxiv.org/abs/1303.2013

https://en.wikipedia.org/wiki/Hutter_Prize

It's not exactly a new conjecture that intelligence fundamentally is an act of compression.

Re: Terence Tao on O1

#493

Post by dr_dshiv »

mlyle wrote: post #475
kmacdough wrote: post #455

Earlier quoted context omitted.

Right, Terrance was hoping it would have something new to think about it, some new perspective, right or wrong. GPTs have the ability to process insane amounts of information across all branches of math, science and art. This ability eclipses that of the most motivated intellectuals such as Terrance. It is thus a little disappointing that it was unable to find anything in its vast knowledgebase to apply a new lens to…

I wonder how much of this is an intrinsic limitation of LLMs, and how much that interdisciplinary thinking and mashing together of problem domains is missing in the training data. It's a pretty rare thing, and the only times these analogies and linkages become noted is when they happen to work out (and they don't seem so far out of left field anymore once this happens).

This is what synthetic data might support— based on mashing together the implications of massive numbers of concepts…

Re: Terence Tao on O1

#494

Post by ColinWright »

j_maffe wrote: post #483
ColinWright wrote: post #481

Earlier quoted context omitted.

We started Mathstodon, an instance of Mastodon-the-Platform, on April 12, 2017. So we've been up for over 7 years, and have just over 19K accounts.

Awesome work! I love what the server has grown into.

Thank you.

Re: Terence Tao on O1

#495

Post by sensanaty »

bongodongobob wrote: post #160
minkles wrote: post #148

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 really think people are just blindly pushing code they can't make heads or tails of? That they haven't tested?

Yes, most definitely. I've recently been introduced to our CTOs little pet project that he's been building with copious help from ChatGPT, and it's genuinely some of the most horrid code I've ever seen in my professional career. He genuinely doesn't know what half of it even does when I quizzed him about some of the more egregious crap that was in there. The real fun part is that now that it's a "proven" PoC some poor soul is going to have to maintain that shit.

We also have a mandate from the same CTO to use more AI in our workflows, so I have 0 doubts in my mind that people are blindly pushing code without thinking about it, and people like myself are left dealing with this garbage. My time & energy is being wasted sifting through AI-generated garbage that doesn't pass the smell test if you spend a singular minute of effort reading through the trash it generates.

Re: Terence Tao on O1

#496

Post by j_maffe »

ocular-rockular wrote: post #491
j_maffe wrote: post #480

Earlier quoted context omitted.

If anyone comes across comments from professionals on the same level at Terrance Tao, I'd love for them to share it.

Most people would likely not engage with that commentary simply because they don't enjoy the same celebrity status as Tao. Yet, I think those voices are equally important to be heard. Terence isn't the only PhD/professional using or discussing these tools.

Of course not. And he is relatively more popular than some others on his level of expertise. But I think Tao's opinion is a bit more interesting than a general PhD/professional.

Re: Terence Tao on O1

#497

Post by AndrewKemendo »

nybsjytm wrote: post #474
AndrewKemendo wrote: post #454

Earlier quoted context omitted.

This is precisely the first thing I thought If arguably the person with the highest IQ currently living, is impressed but still not fully satisfied that a computer doesn’t give Nobel prize winning mathematical reasoning I think that’s a massive metric itself So what then should the first year maths PhD think? I believe Tao obliquely addresses this with his previous post with effectively “o1 is almost as good as a gra…

> If arguably the person with the highest IQ currently living, is impressed but still not fully satisfied that a computer doesn’t give Nobel prize winning mathematical reasoning No offense, but every part of this characterization is really unserious! He says "the model proposed the same strategy that was already identified in the most recent work on the problem (and which I restated in the blog post), but did not off…

I’m not sure i understand your complaint

Are you arguing that I’m making an appeal to authority fallacy?

Re: Terence Tao on O1

#498

Post by dartos »

mewpmewp2 wrote: post #427
dartos wrote: post #409

Earlier quoted context omitted.

Feel free not to share, I don’t want you to get dogpiled, but if you would humor me, Could you share any code on GitHub (or pastebin or whatever) that you wrote with the help of AI? Or could you share what kind of experience you have with programming (how many years, what domain you work in, etc)

The projects I do are mostly frontend in React and backend with TypeScript/Node.js. I have around 10+ years of professional experience although I did on/off hobby coding before that since 15 years ago. It's mostly API endpoints, calling a database, third party APIs, data transformation, aggregation type of things. Then either UI according to what designers provide or whatever I want to do for my side projects. I thin…

Yes I find copilot is nice for things like tansack query. It’s like better snippets.

At my job we have this pretty clean SOA type architecture backed by a mongo db. Copilot has trouble building the more complicated, domain specific queries on its own, I’ve found.

I do occasionally ask chatgpt how to write a certain query in a general case and apply that to what I’m writing. I also don’t really like mongosh’s docs.

Re: Terence Tao on O1

#499

Post by xorcist »

simonw wrote: post #430
HarHarVeryFunny wrote: post #404

Earlier quoted context omitted.

The programmers who will find LLMs most useful are going to be those who prior to LLMs were copying and pasting from Stack Overflow, and asking questions online about everything they were doing - tasks that LLMs have precisely replaced (it has now memorized all that boilerplate code, consensus answers, and API usage examples). The developers who will find LLMs the least useful are the "brilliant" ones who never found…

I like to think I'm more of a "challenging and novel problems" developer than a "copy and paste from Stack Overflow" developer, and I've been finding LLMs extremely useful for over two years at this point. Notes: https://simonwillison.net/tags/ai-assisted-programming/

I am a skeptic. What would you say would be the easiest way for me to change my mind?

Re: Terence Tao on O1

#500

Post by DragonStrength »

HarHarVeryFunny wrote: post #467
DragonStrength wrote: post #440

Earlier quoted context omitted.

Yeah, I was gonna say this is not how I see this going. The copy/paste dev is replaced by the novel dev using LLM for the stuff they used to hire interns and juniors for. In law, this sort of thing already happened with the rise of better research tools. The work L1s used to do a generation ago just does not exist now. An attorney with experience gets the results faster on their own now. With all the pipeline and QoL…

That makes some sense, but seems to be answering a different question of whose jobs may be in jeopardy from LLMs, as opposed to who might currently find them useful. Note though that not all companies see it this way - the telecom I work at is hoping to replace senior onshore developers with junior offshore ones leveraging "GenAI"! I agree that the opposite makes more sense - the seniors are needed, and it's the juni…

I think we all assume each individual company will need fewer developers to do the same work they're doing now. The question is do they have fewer devs or do more work. And if it is have fewer devs, will that open up the door for more small companies to be competitive as well, since they need fewer devs and have less competition for talent from people with deep pockets.

I find a lot of the AI discussion seems to land in the "lump of labor" fallacy camp though.

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