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ChatGPT-4o vs. Math

sabrina.dev

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Re: ChatGPT-4o vs. Math

#41
post #10

Earlier quoted context omitted.

Not gonna lie, when I see that someone is banned on X, I assume credibility

Even the 100's of Hamas-affiliated accounts? https://ny1.com/nyc/all-boroughs/technology/2023/10/12/x-say...

frEeDom oF sPeeCh

Re: ChatGPT-4o vs. Math

#42

This recent article on Hacker News seems to suggest similar inconsistencies. GPT-4 Turbo with Vision is a step backward for coding (aider.chat) https://news.ycombinator.com/item?id=39985596 Without looking deeply at how cross-attention works, I imagine the instruction tuning of the multimodal models to be challenging. Maybe the magic is in synthetically creating this instruct dataset that combines images and text in…

The same guy found 4o to be much better

GPT-4o takes #1 and #2 on the Aider LLM leaderboards https://news.ycombinator.com/item?id=40349655

Subjectively, I've found Aider to be much more useful on 4o. It still makes mistakes applying changes to files occasionally, but not so much to make me give up on it.

Re: ChatGPT-4o vs. Math

#43

Earlier quoted context omitted.

This speaks to a deeper issue that LLMs don’t just have statistically-based knowledge, they also have statistically-based reasoning. This means their reasoning process isn’t necessarily based on logic, but what is statistically most probable. As you’ve experienced, their reasoning breaks down in less-common scenarios even if it should be easy to use logic to get the answer.

Does anyone know how far off we are having logical AI? Math seems like low hanging fruit in that regard. But logic as it's used in philosophy feels like it might be a whole different and more difficult beast to tackle. I wonder if LLM's will just get better to the point of being indistinguishable from logic rather than actually achieving logical reasoning. Then again, I keep finding myself wondering if humans actuall…

I think LLMs will need to do what humans do: invent symbolic representations of systems and then "reason" by manipulating those systems according to rules.

Here's a paper working along those lines: https://arxiv.org/abs/2402.03620

Re: ChatGPT-4o vs. Math

#44

Earlier quoted context omitted.

This speaks to a deeper issue that LLMs don’t just have statistically-based knowledge, they also have statistically-based reasoning. This means their reasoning process isn’t necessarily based on logic, but what is statistically most probable. As you’ve experienced, their reasoning breaks down in less-common scenarios even if it should be easy to use logic to get the answer.

Does anyone know how far off we are having logical AI? Math seems like low hanging fruit in that regard. But logic as it's used in philosophy feels like it might be a whole different and more difficult beast to tackle. I wonder if LLM's will just get better to the point of being indistinguishable from logic rather than actually achieving logical reasoning. Then again, I keep finding myself wondering if humans actuall…

> Does anyone know how far off we are having logical AI?

Your comment made me think of something. How do we know that logic AI is relevant? I mean, how do we know that humans are logic-AI driven and not statistical-intelligent?

Re: ChatGPT-4o vs. Math

#45

Earlier quoted context omitted.

Does anyone know how far off we are having logical AI? Math seems like low hanging fruit in that regard. But logic as it's used in philosophy feels like it might be a whole different and more difficult beast to tackle. I wonder if LLM's will just get better to the point of being indistinguishable from logic rather than actually achieving logical reasoning. Then again, I keep finding myself wondering if humans actuall…

(Not an AI researcher, just someone who likes complexity analysis.) Discrete reasoning is NP-Complete. You can get very close with the stats-based approaches of LLMs and whatnot, but your minima/maxima may always turn out to be local rather than global.

maybe theorem proving could help? ask gpt4o to produce a proof in coq and see if it checks out...or split it into multiple agents -- one produces the proof of the closed formula for the tape roll thickness, and another one verifies it

Re: ChatGPT-4o vs. Math

#47
I'm fucking sorry but if you gave me that tape math problem i would have given the same answer! I'm so sick of people writing trick questions for AI's and then being like SEEEEEE it failed! And its like no you gave it data and a question and asked it to solve the question, it gave you the best answer it had... Like wtf.

And i'm pretty sure the average person when asked would say the same thing and be like "duh" even though technically based on the minutia it's incorrect.

Re: ChatGPT-4o vs. Math

#49
post #47

I'm fucking sorry but if you gave me that tape math problem i would have given the same answer! I'm so sick of people writing trick questions for AI's and then being like SEEEEEE it failed! And its like no you gave it data and a question and asked it to solve the question, it gave you the best answer it had... Like wtf. And i'm pretty sure the average person when asked would say the same thing and be like "duh" even…

But AI is put into places where you wouldn't ask the average person.

It's treated like a genius and that's what it gets measured against.

Re: ChatGPT-4o vs. Math

#50

Posted a screenshot from the post in, got it on the first try https://x.com/thisritchie/status/1791153959865852093

Ha nice.

I decided to try the same and it got it incorrect. It's so non-deterministic. It landed on 0.17cm. Tried it another time and it got 0.1697cm. When I asked it to check it's work, it got the right answer 0.00589cm

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