Hacker News Board Hacker News, browsed like a classic message board
Live data from Hacker News

Notes on OpenAI's new o1 chain-of-thought models

simonwillison.net

Post reply on HN
Print view View original

191–200 of 659 posts

Re: Notes on OpenAI's new o1 chain-of-thought models

#191

Post by gloosx »

bachback wrote: post #185
gloosx wrote: post #172

Just leaving here an example of the "smart chain of thought", which took the model about 20s of thinking. The problem I asked was – "what 3 numbers give the same result when divided and added together". Seems the current state of art is that basic school problems are too hard yet even for this new chain-of-marketing. Let's think through this step-by-step: We're looking for three numbers a, b, and c where: (a / b) / c…

what does divided together mean? maybe your question doesn't have a good answer, because the question is not formulated well enough.

That's a classical school question, word-by-word, except multiplication is replaced by division

Re: Notes on OpenAI's new o1 chain-of-thought models

#192

Post by satvikpendem »

ChicagoDave wrote: post #137

It’s still just a tool. It does not reason. It has some add-on logic the simulates it. We’re no closer to “AI” today than we were 20 years ago.

> The AI effect occurs when onlookers discount the behavior of an artificial intelligence program as not "real" intelligence.[1]

> Author Pamela McCorduck writes: "It's part of the history of the field of artificial intelligence that every time somebody figured out how to make a computer do something—play good checkers, solve simple but relatively informal problems—there was a chorus of critics to say, 'that's not thinking'."[2] Researcher Rodney Brooks complains: "Every time we figure out a piece of it, it stops being magical; we say, 'Oh, that's just a computation.'"[3]

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

Re: Notes on OpenAI's new o1 chain-of-thought models

#193

Post by gloosx »

mattnewton wrote: post #176
gloosx wrote: post #172

Just leaving here an example of the "smart chain of thought", which took the model about 20s of thinking. The problem I asked was – "what 3 numbers give the same result when divided and added together". Seems the current state of art is that basic school problems are too hard yet even for this new chain-of-marketing. Let's think through this step-by-step: We're looking for three numbers a, b, and c where: (a / b) / c…

Claude 3.5 seems to get it, (thought the method is not what I would use?) - ——— Let's think through this step-by-step: We're looking for three numbers a, b, and c where: (a / b) / c = a + b + c ———— Certainly, let's approach this problem step-by-step: 1) First, let's write out our equation: (a / b) / c = a + b + c 2) To simplify the left side, we can rewrite it as: a / (b * c) = a + b + c 3) Now, to solve this, we ne…

It's crazy that it just tries to bruteforce it by picking numbers, and in your case it took more steps before concluding a success/failure, which seems quite to be random to me, or at least dependent on something.

What's clear is that it doesn't have any idea about mathematical deduction and induction – a real chain-of-thought which kids learn in 5th grade.

Re: Notes on OpenAI's new o1 chain-of-thought models

#194

Post by [deleted] »

shmatt wrote: post #51
layer8 wrote: post #18

The o1-preview model still hallucinates non-existing libraries and functions for me, and is quickly wrong about facts that aren't well-represented on the web. It's the usual string of "You're absolutely correct, and I apologize for the oversight in my previous response. [Let me make another guess.]" While the reasoning may have been improved, this doesn't solve the problem of the model having no way to assess if what…

I honestly can’t believe this is the hyped up “strawberry” everyone was claiming is pretty much AGI. Senior employees leaving due to its powers being so extreme I’m in the “probabilistic token generators aren’t intelligence” camp so I don’t actually believe in AGI, but I’ll be honest the never ending rumors / chatter almost got to me Remember, this is the model some media outlet reported recently that is so powerful…

[deleted]

Re: Notes on OpenAI's new o1 chain-of-thought models

#195

Post by aktuel »

valval wrote: post #186
williamdclt wrote: post #164

Earlier quoted context omitted.

> Treat it as a naive but intelligent intern That’s the problem: it’s a _terrible_ intern. A good intern will ask clarifying questions, tell me “I don’t know” or “I’m not sure I did it right”. LLMs do none of that, they will take whatever you ask and give a reasonable-sounding output that might be anything between brilliant and nonsense. With an intern, I don’t need to measure how good my prompting is, we’ll usually…

Really it just does what you tell it to. Have you tried telling it “ask me clarifying questions about all the APIs you need to solve this problem”? Huge contrast to human interns who aren’t experienced or smart enough to ask the right questions in the first place, and/or have sentimental reasons for not doing so.

I have to say, having to tell it to ask me clarifying questions DOES make it really look smart!

Re: Notes on OpenAI's new o1 chain-of-thought models

#196

Post by [deleted] »

gloosx wrote: post #191
bachback wrote: post #185

Earlier quoted context omitted.

what does divided together mean? maybe your question doesn't have a good answer, because the question is not formulated well enough.

That's a classical school question, word-by-word, except multiplication is replaced by division

[deleted]

Re: Notes on OpenAI's new o1 chain-of-thought models

#197

Post by geysersam »

achow wrote: post #167
pedrosorio wrote: post #110

Earlier quoted context omitted.

> It knows english at or above a level equal to most fluent speakers, and it also can produce output that is not just a likely output, but is a logical output This is not an apt description of the system that insists the doctor is the mother of the boy involved in a car accident when elementary understanding of English and very little logic show that answer to be obviously wrong. https://x.com/colin_fraser/status/183…

What I'm not able to comprehend is why people are not seeing the answer as brilliant! Any ordinary mortal (like me) would have jumped to the conclusion that answer is "Father" and would have walked away patting on my back, without realising that I was biased by statistics. Whereas o1, at the very outset smelled out that it is a riddle - why would anyone out of blue ask such question. So, it started its chain of thoug…

Come on. Of course chatgpt has read that riddle and the answer 1000 times already.

Re: Notes on OpenAI's new o1 chain-of-thought models

#198

Post by ithkuil »

valval wrote: post #186
williamdclt wrote: post #164

Earlier quoted context omitted.

> Treat it as a naive but intelligent intern That’s the problem: it’s a _terrible_ intern. A good intern will ask clarifying questions, tell me “I don’t know” or “I’m not sure I did it right”. LLMs do none of that, they will take whatever you ask and give a reasonable-sounding output that might be anything between brilliant and nonsense. With an intern, I don’t need to measure how good my prompting is, we’ll usually…

Really it just does what you tell it to. Have you tried telling it “ask me clarifying questions about all the APIs you need to solve this problem”? Huge contrast to human interns who aren’t experienced or smart enough to ask the right questions in the first place, and/or have sentimental reasons for not doing so.

It all stems from the fact that it just talks English.

It's understandably hard to not be implicitly biased towards talking to it in a natural way and expecting natural interactions and assumptions when the whole point of the experience is that the model talks in a natural language!

Luckily humans are intelligent too and the more you use this tool the more you'll figure out how to talk to it in a fruitful way.

Re: Notes on OpenAI's new o1 chain-of-thought models

#199

Post by grey-area »

achow wrote: post #167
pedrosorio wrote: post #110

Earlier quoted context omitted.

> It knows english at or above a level equal to most fluent speakers, and it also can produce output that is not just a likely output, but is a logical output This is not an apt description of the system that insists the doctor is the mother of the boy involved in a car accident when elementary understanding of English and very little logic show that answer to be obviously wrong. https://x.com/colin_fraser/status/183…

What I'm not able to comprehend is why people are not seeing the answer as brilliant! Any ordinary mortal (like me) would have jumped to the conclusion that answer is "Father" and would have walked away patting on my back, without realising that I was biased by statistics. Whereas o1, at the very outset smelled out that it is a riddle - why would anyone out of blue ask such question. So, it started its chain of thoug…

The 'riddle': A woman and her son are in a car accident. The woman is sadly killed. The boy is rushed to hospital. When the doctor sees the boy he says "I can't operate on this child, he is my son". How is this possible?

GPT Answer: The doctor is the boy's mother

Real Answer: Boy = Son, Woman = Mother (and her son), Doctor = Father (he says...he is my son)

This is not in fact a riddle (though presented as one) and the answer given is not in any sense brilliant. This is a failure of the model on a very basic question, not a win.

It's non deterministic so might sometimes answer correctly and sometimes incorrectly. It will also accept corrections on any point, even when it is right, unlike a thinking being when they are sure on facts.

LLMs are very interesting and a huge milestone, but generative AI is the best label for them - they generate statistically likely text, which is convincing but often inaccurate and it has no real sense of correct or incorrect, needs more work and it's unclear if this approach will ever get to general AI. Interesting work though and I hope they keep trying.

Re: Notes on OpenAI's new o1 chain-of-thought models

#200

Post by djur »

ramraj07 wrote: post #112
pedrosorio wrote: post #110

Earlier quoted context omitted.

> It knows english at or above a level equal to most fluent speakers, and it also can produce output that is not just a likely output, but is a logical output This is not an apt description of the system that insists the doctor is the mother of the boy involved in a car accident when elementary understanding of English and very little logic show that answer to be obviously wrong. https://x.com/colin_fraser/status/183…

Many of my PhD and post doc colleagues who emigrated from Korea, China and India who didn’t have English as the medium of instruction would struggle with this question. They only recover when you give them a hint. They’re some of the smartest people in general. If you try to stop stumping these models with trick questions and ask it straightforward reasoning systems it is extremely performant (O1 is definitely a step…

The claim was that "it knows english at or above a level equal to most fluent speakers". If the claim is that it's very good at producing reasonable responses to English text, posing "trick questions" like this would seem to be a fair test.
Post reply on HN