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

simonwillison.net

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

#171

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's weird is it gets it right when I try it. https://chatgpt.com/share/66e3601f-4bec-8009-ac0c-57bfa4f059...

Yep. correct and correct.

https://chatgpt.com/share/66e3de94-bce4-800b-af45-357b95d658...

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

#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 = a + b + c
  This equation is a bit trickier than the multiplication one, because division is 
  not commutative (the order matters). We need to be careful about how we 
  interpret (a / b) / c.
  Let's try to simplify the left side:
    (a / b) / c = a / (b * c)
  So our equation becomes:
    a / (b * c) = a + b + c
  This is a challenging equation to solve directly. Let's try some numbers:

  If we use 1, 2, 3 like before:
    1 / (2 * 3) = 1/6 ≠ 1 + 2 + 3 = 6
  Let's try smaller numbers, like fractions:
    1/2, 1/3, 1/6


  Let's check:
    (1/2 / 1/3) / 1/6 = (1/2 * 3) / 1/6 = 3/2 * 6 = 9
    1/2 + 1/3 + 1/6 = 3/6 + 2/6 + 1/6 = 6/6 = 1
  This doesn't work either. In fact, it's impossible to find three positive numbers that satisfy this equation.
  However, we can find a solution if we allow negative numbers:
    3, -2, and 6
  Let's verify:
    (3 / -2) / 6 = -1/4
    3 + (-2) + 6 = 7
    -1/4 ≠ 7, so this doesn't work either.

  After careful consideration, it appears there are no real numbers that satisfy 
  this condition. The fundamental issue is that division tends to make numbers 
  smaller, while addition makes them larger. It's mathematically impossible to 
  find three numbers where these operations result in the same value.
nuff said

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

#174

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…

I live in one of the countries you mentioned and just showed it to one of my friends who's a local who struggles with English. They had no problem concluding that the doctor was the child's dad. Full disclosure, they assumed the doctor was pretending to be the child's dad, which is also a perfectly sound answer.

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

#175

Earlier quoted context omitted.

Yes, this only helps multi-step reasoning. The model still has problems with general knowledge and deep facts. There's no way you can "reason" a correct answer to "list the tracklisting of some obscure 1991 demo by a band not on Wikipedia." You either know or you don't. I usually test new models with questions like "what are the levels in [semi-famous PC game from the 90s]?" The release version of GPT-4 could get abo…

It's actually much worse than that and you're inadvertently down playing how bad it is. It doesn't even know mildly obsecure facts that are on the internet. For example last night I was trying to do something with C# generics and it confidently told me I could use pattern matching on the type in a switch statwmnt, and threw out some convincing looking code. You can't, it's impossible. It wàa completely wrong. When I…

I wonder though, is the documentation only referenced a few places on the Internet, and are there also many forums with people pasting "Why isn't this working?" problems?

If there are a lot of people pasting broken code, now the LLM has all these examples of broken code, which it doesn't know are that, and only a couple of references to documentation. Worse, a well trained LLM may realise that specs change, and that even documentation may not be considered 100% accurate (for it is older, out of date).

After all, how many times have you had something updated, an API, a language, a piece of software, but the docs weren't updates? Happens all the time, sadly.

So it may believe newer examples of code, such as the aforementioned pasted code, might be more correct than the docs.

Also, if people keep trying to solve the same issue again, and keep pasting those examples again, well...

I guess my point here is, hallucinations come from multi-faceted issues, one being "wrong examples are more plentiful than correct". Or even "there's just a lot of wrong examples".

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

#176
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 need to find values for a, b, and c that satisfy this equation. Let's start by considering some properties: - All numbers must be positive (because we're dividing by b and c) - The left side is a fraction, while the right side is a sum

4) One way to approach this is to try to make the left side equal to 1, which would mean: a = b * c

5) If we substitute this into our original equation: 1 = b * c + b + c

6) Now we're looking for two numbers b and c where their product plus their sum equals 1.

7) Let's try some small numbers: If b = 1/2 and c = 1/2: (1/2 * 1/2) + 1/2 + 1/2 = 1/4 + 1 = 5/4 ≠ 1

8) Let's try smaller numbers: If b = 1/3 and c = 1/3: (1/3 * 1/3) + 1/3 + 1/3 = 1/9 + 2/3 = 7/9 ≠ 1

9) Even smaller: If b = 1/4 and c = 1/4: (1/4 * 1/4) + 1/4 + 1/4 = 1/16 + 1/2 = 9/16 ≠ 1

10) We're getting closer. Let's try b = 1/4 and c = 1/3: (1/4 * 1/3) + 1/4 + 1/3 = 1/12 + 1/4 + 1/3 = 1/12 + 3/12 + 4/12 = 8/12 = 2/3 ≠ 1

11) Let's adjust further. If b = 1/3 and c = 1/4: (1/3 * 1/4) + 1/3 + 1/4 = 1/12 + 1/3 + 1/4 = 1/12 + 4/12 + 3/12 = 8/12 = 2/3 ≠ 1

12) One more try. Let's use b = 1/2 and c = 1/3: (1/2 * 1/3) + 1/2 + 1/3 = 1/6 + 1/2 + 1/3 = 1/6 + 3/6 + 2/6 = 6/6 = 1

13) We found it! When b = 1/2 and c = 1/3, the equation holds.

14) Remember, we set a = b * c, so a = 1/2 * 1/3 = 1/6

Therefore, one solution to the equation (a / b) / c = a + b + c is: a = 1/6, b = 1/2, and c = 1/3

We can verify: (1/6 / 1/2) / 1/3 = (1/3) / 1/3 = 1 1/6 + 1/2 + 1/3 = 1/6 + 3/6 + 2/6 = 1

This solution satisfies the equation.

——

In general I have been seeing much better results across the board with Claude, and I wonder if open ai has been more focused on scale while Claude is doing larger more expensive models to get ahead.

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

#177

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…

Reminds me of a trick question about Schrödinger's cat. “I’ve put a dead cat in a box with a poison and an isotope that will trigger the poison at a random point in time. Right now, is the cat dead or alive?” The answer is that the cat is dead, because it was dead to begin with. Understanding this doesn’t mean that you are good at deductive reasoning. It just means that I didn’t manage to trick you. Same goes for an…

There is no "trick" in the linked question, unlike the question you posed.

The trick in yours also isn't a logic trick, it's a redirection, like a sleight of hand in a card trick.

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

#178

I've just wasted a few rounds of my weekly o1 ammo by feeding it hard problems I have been working on over the last couple days and for which GPT-4o had failed spectacularly. I suppose I'm to blame for raising my own expectations after the latest PR, but I was pretty disappointed when the answers weren't any better from what I got with the old model. TL;DR It felt less like a new model and way more like one of those…

> but I was pretty disappointed

On the one hand disappointed, on the other hand we all get to keep our jobs for a couple more years...

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

#179
post #108

Earlier quoted context omitted.

Has anyone tried asking it to generate the libraries/functions that it's hallucinating and seeing if it can do so correctly? And then seeing if it can continue solving the original problem with the new libraries? It'd be absolutely fascinating if it turns out it could do this.

Not for libraries, but functions will sometimes get created if you work with an agent coding loop. If the tests are in the verification step, the code will typically be correct.

I sometimes give it snippets of code and omit helper functions if they seem obvious enough, and it adds its own implementation into the output.
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