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Furthermore, the LLM isn't doing things "in its head" - the headline feature of GPT LLMs is attention across all previous tokens, all of its "thoughts" are on p

Furthermore, the LLM isn't doing things "in its head" - the headline feature of GPT LLMs is attention across all previous tokens, all of its "thoughts" are on paper LOL, talk about special pleading. Whatever it takes to reshape the argument into one you can win, I guess... LLMs don't reason. Let's see you do that multiplication in your head. Then, when you fail, we'll conclude you don't reason. Sound fair?

digitalPhonix 8mo ago
I can do it with a scratch pad. And I can also tell you when the calculation exceeds what I can do in my head and when I need a scratch pad. I can also check a long multiplication answer in my head (casting 9s, last digit etc.) and tell if there’s a mistake. The LLMs also have access to a scratch pad. And importantly don’t know when they need to use it (as in, they will sometimes get long multiplication right if you ask them to show their work but if you don’t ask them to they will almost certainly get it wrong).
- dirasieb 8mo ago
  > And importantly don’t know when they need to use it patently false, but hey at least you’re able to see the parallel between you with a scratch pad and an LLM with a python terminal
  - digitalPhonix 8mo ago
    Sure, lets test that: https://chatgpt.com/s/t_69c420f3118081919cf525123e39598c https://chatgpt.com/s/t_69c420f3118081919cf525123e39598c https://chatgpt.com/s/t_69c4215daeb481919fdaf22498fb0c4f https://chatgpt.com/s/t_69c4215daeb481919fdaf22498fb0c4f Do you have a different definition of false? I'm referring to their reasoning context as their scratch pad if that wasn't clear.
  - zamalek 8mo ago
    The context is the scratch pad. LLMs have perfect recall (ignoring "lost in the middle") across the entire context, unlike humans. LLMs "think on paper."
jibal 8mo ago
The conclusion that LLMs don't reason is not a consequence of them not being able to do arithmetic, so your argument isn't valid. Also, see https://news.ycombinator.com/newsguidelines.html https://news.ycombinator.com/newsguidelines.html "Be kind. Don't be snarky. Converse curiously; don't cross-examine. Edit out swipes. Comments should get more thoughtful and substantive, not less, as a topic gets more divisive. When disagreeing, please reply to the argument instead of calling names. "That is idiotic; 1 + 1 is 2, not 3" can be shortened to "1 + 1 is 2, not 3." Don't be curmudgeonly. Thoughtful criticism is fine, but please don't be rigidly or generically negative." etc.
- IshKebab 8mo ago
  Plenty of humans can't do arithmetic. Can they also not reason. Reasoning isn't a binary switch. It's a multidimensional continuum. AI can clearly reason to some extent even if it also clearly doesn't reason in the same way that a human would.
  - jibal 8mo ago
    > Plenty of humans can't do arithmetic. Can they also not reason. I just pointed out that this isn't valid reasoning ... it's a fallacy of denial of the antecedent. No one is arguing that because LLMs can't do arithmetic, therefore they can't reason. After all, zamalek said that he can't quickly multiply large numbers in his head, but he isn't saying that therefore he can't reason. > Reasoning isn't a binary switch. It's a multidimensional continuum. Indeed, and a lot of humans are very bad at it, as is clear from the comments I'm responding to. > AI can clearly reason to some extent The claim was about LLMs, not AI. This is like if someone said that chihuahuas are little and someone responded by saying that dogs are tall to some extent. LLMs do not reason ... they do syntactic pattern matching. The appearance of reasoning is because of all the reasoning by humans that is implicit in the training data. I've had this argument too many times ... it never goes anywhere. So I won't respond again ... over and out.
    - CamperBob2 8mo ago
      Indeed, and a lot of humans are very bad at it, as is clear from the comments I'm responding to. This is your idea of "conversing curiously" and "editing out swipes," I suppose. I've had this argument too many times ... it never goes anywhere. So I won't respond again ... over and out. A real reasoning entity might pause for self-examination here. Maybe run its chain of thought for a few more iterations, or spend some tokens calling research tools. Just to probe the apparent mismatch between its own priors and those of "a lot of humans," most of whom are not, in fact, morons.

digitalPhonix 8mo ago

I can do it with a scratch pad. And I can also tell you when the calculation exceeds what I can do in my head and when I need a scratch pad. I can also check a long multiplication answer in my head (casting 9s, last digit etc.) and tell if there’s a mistake. The LLMs also have access to a scratch pad. And importantly don’t know when they need to use it (as in, they will sometimes get long multiplication right if you ask them to show their work but if you don’t ask them to they will almost certainly get it wrong).

dirasieb 8mo ago
> And importantly don’t know when they need to use it patently false, but hey at least you’re able to see the parallel between you with a scratch pad and an LLM with a python terminal
- digitalPhonix 8mo ago
  Sure, lets test that: https://chatgpt.com/s/t_69c420f3118081919cf525123e39598c https://chatgpt.com/s/t_69c420f3118081919cf525123e39598c https://chatgpt.com/s/t_69c4215daeb481919fdaf22498fb0c4f https://chatgpt.com/s/t_69c4215daeb481919fdaf22498fb0c4f Do you have a different definition of false? I'm referring to their reasoning context as their scratch pad if that wasn't clear.
- zamalek 8mo ago
  The context is the scratch pad. LLMs have perfect recall (ignoring "lost in the middle") across the entire context, unlike humans. LLMs "think on paper."

jibal 8mo ago

The conclusion that LLMs don't reason is not a consequence of them not being able to do arithmetic, so your argument isn't valid. Also, see https://news.ycombinator.com/newsguidelines.html https://news.ycombinator.com/newsguidelines.html "Be kind. Don't be snarky. Converse curiously; don't cross-examine. Edit out swipes. Comments should get more thoughtful and substantive, not less, as a topic gets more divisive. When disagreeing, please reply to the argument instead of calling names. "That is idiotic; 1 + 1 is 2, not 3" can be shortened to "1 + 1 is 2, not 3." Don't be curmudgeonly. Thoughtful criticism is fine, but please don't be rigidly or generically negative." etc.

IshKebab 8mo ago
Plenty of humans can't do arithmetic. Can they also not reason. Reasoning isn't a binary switch. It's a multidimensional continuum. AI can clearly reason to some extent even if it also clearly doesn't reason in the same way that a human would.
- jibal 8mo ago
  > Plenty of humans can't do arithmetic. Can they also not reason. I just pointed out that this isn't valid reasoning ... it's a fallacy of denial of the antecedent. No one is arguing that because LLMs can't do arithmetic, therefore they can't reason. After all, zamalek said that he can't quickly multiply large numbers in his head, but he isn't saying that therefore he can't reason. > Reasoning isn't a binary switch. It's a multidimensional continuum. Indeed, and a lot of humans are very bad at it, as is clear from the comments I'm responding to. > AI can clearly reason to some extent The claim was about LLMs, not AI. This is like if someone said that chihuahuas are little and someone responded by saying that dogs are tall to some extent. LLMs do not reason ... they do syntactic pattern matching. The appearance of reasoning is because of all the reasoning by humans that is implicit in the training data. I've had this argument too many times ... it never goes anywhere. So I won't respond again ... over and out.
  - CamperBob2 8mo ago
    Indeed, and a lot of humans are very bad at it, as is clear from the comments I'm responding to. This is your idea of "conversing curiously" and "editing out swipes," I suppose. I've had this argument too many times ... it never goes anywhere. So I won't respond again ... over and out. A real reasoning entity might pause for self-examination here. Maybe run its chain of thought for a few more iterations, or spend some tokens calling research tools. Just to probe the apparent mismatch between its own priors and those of "a lot of humans," most of whom are not, in fact, morons.