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Terence Tao's ChatGPT conversation about the Jacobian Conjecture counterexample

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Re: Terence Tao's ChatGPT conversation about the Jacobian Conjecture counterexample

#491

Post by mkagenius »

case wrote: post #486
mkagenius wrote: post #485

Earlier quoted context omitted.

> I can't use it for theoretical physics because I can't evaluate the responses. I think pretty much the opposite. I can ask it to explain to me in ways I understand it. Even drill down the simplest of equations. Since llms have infinite patience. All I need to learn anything is patience.

I think the issue is that LLMs can be so confidently and convincingly wrong about anything. And if we (LLM tool operators) don’t know the subject matter in question, we can’t easily distinguish what they are right or wrong about.

They are solving jacobian conjectures, I don't think they will hallucinate till masters level of any subject.

Edit: do give counter examples if you have any in maths, physics, chemistry, biology etc

Re: Terence Tao's ChatGPT conversation about the Jacobian Conjecture counterexample

#492

Post by TMWNN »

ThrowawayR2 wrote: post #472
TMWNN wrote: post #461

Earlier quoted context omitted.

The day is coming when some * BIG* problem is solved by AI just because someone jokingly asks about it.

Isaac Asimov's short story The Last Question has that as its premise. Copies can easily be found with a Google search.

I disagree. The various questioners in The Last Question all hope for/expect an answer; what they don't expect is the "insufficient" response.

I am talking about someone jokingly asking AI `HOW TO ACHIEVE COLD FUSION` (or `A UNIVERSAL CANCER VACCINE`, or `AN AI FRAMEWORK SUPERIOR TO THE TRANSFORMER`), and getting a usable answer.

Re: Terence Tao's ChatGPT conversation about the Jacobian Conjecture counterexample

#493

Post by radlad »

mkagenius wrote: post #491
case wrote: post #486

Earlier quoted context omitted.

I think the issue is that LLMs can be so confidently and convincingly wrong about anything. And if we (LLM tool operators) don’t know the subject matter in question, we can’t easily distinguish what they are right or wrong about.

They are solving jacobian conjectures, I don't think they will hallucinate till masters level of any subject. Edit: do give counter examples if you have any in maths, physics, chemistry, biology etc

This is blatantly false based on my usage of Fable and Opus. Though they are much better than they used to be.

Re: Terence Tao's ChatGPT conversation about the Jacobian Conjecture counterexample

#494

Post by mastermage »

michaelchisari wrote: post #12
lukebuehler wrote: post #8

It’s endlessly fascinating to read the AI transcript of an expert who _really_ knows how to cut to the chase. It just shows how much you can potentially squeeze out of these models. I’m also surprised to see that even Terrence Tao seems to use it in a way that resembles, in progression, how I use llms in my area of expertise (emphasis on progression and usage patterns, not absolute skill, obv I don’t match that): sho…

It reinforces how to "learn AI" is to first master the problem domain. I can use AI for coding after decades of coding. I can't use it for theoretical physics because I can't evaluate the responses.

Or in the words of Clickbait articles: MATHMATICIANS SHIVER OF THE IMPLICATIONS OF AI WILL MATHMATICIANS NO LONGER BE NEEDED.

to which betteridge's law of headlines says: NO.

Re: Terence Tao's ChatGPT conversation about the Jacobian Conjecture counterexample

#496

Post by versteegen »

phkahler wrote: post #384
napoleoncomplex wrote: post #21

This is the second ChatGPT shared conversation I've seen today that is truly fascinating. The first one was someone proving another conjecture false by just repeatedly saying "keep going" to ChatGPT: https://x.com/DmitryRybin1/status/2079904005652893709 What a world we live in.

>> This is the second ChatGPT shared conversation I've seen today that is truly fascinating. We recently had some bugs fixed in the geometry kernel of solvespace. Not much conversation, but the analysis from the AI was amazing: https://github.com/solvespace/solvespace/pull/1729 https://github.com/solvespace/solvespace/pull/1730 https://github.com/solvespace/solvespace/pull/1731 From the Validation section of PR 1730:…

> It looks like it wrote a python script to generate test cases in our file format for testing. Just... you know, as a side quest.

On the one hand, agents have done this sort of thing for a year+, if you pushed them to check their work. On the other, I absolutely can feel Fable and Sol have crossed a threshold where they can be trusted far more than before. Huge difference between plans written by Opus or Fable.

Accumulated AI slop can simply be cleaned up by better models. Real cost of technical debt is shrinking due to the the inflationary devaluation of code!

Re: Terence Tao's ChatGPT conversation about the Jacobian Conjecture counterexample

#497

Post by v9v »

mastermage wrote: post #494
michaelchisari wrote: post #12

Earlier quoted context omitted.

It reinforces how to "learn AI" is to first master the problem domain. I can use AI for coding after decades of coding. I can't use it for theoretical physics because I can't evaluate the responses.

Or in the words of Clickbait articles: MATHMATICIANS SHIVER OF THE IMPLICATIONS OF AI WILL MATHMATICIANS NO LONGER BE NEEDED. to which betteridge's law of headlines says: NO.

That law only applies to headlines ending in a question mark.

Re: Terence Tao's ChatGPT conversation about the Jacobian Conjecture counterexample

#499

Post by jeef_berky »

larsfaye wrote: post #436
michaelchisari wrote: post #12

Earlier quoted context omitted.

It reinforces how to "learn AI" is to first master the problem domain. I can use AI for coding after decades of coding. I can't use it for theoretical physics because I can't evaluate the responses.

Correctamundo. That's EXACTLY what I just wrote about. And how we'll create the next generation of people who know how to evaluate responses when we're creating a generation of people who are increasingly reliant on LLMs to do the work makes for a strange paradox. https://larsfaye.com/articles/ai-coding-will-prevent-experti...

It's so obvious to some and may never be considered by others.

If someone asks about AI I tell them step 1 is ask it how to do something you know all about. Step 2 is consider everything else you ask will be that inaccurate.

Re: Terence Tao's ChatGPT conversation about the Jacobian Conjecture counterexample

#500

Post by baq »

mkagenius wrote: post #491
case wrote: post #486

Earlier quoted context omitted.

I think the issue is that LLMs can be so confidently and convincingly wrong about anything. And if we (LLM tool operators) don’t know the subject matter in question, we can’t easily distinguish what they are right or wrong about.

They are solving jacobian conjectures, I don't think they will hallucinate till masters level of any subject. Edit: do give counter examples if you have any in maths, physics, chemistry, biology etc

Both fable and sol are confidently wrong all the time in their most cherished domain - software engineering - I can’t quote anything because they’re working on my employer’s code bases. They’re much less wrong than their predecessors and they’re also quite good at point out their mistakes, but they’re still wrong a lot.
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