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Large language models lack deep insights or a theory of mind

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Re: Large language models lack deep insights or a theory of mind

#71

Post by melenaboija »

FrustratedMonky wrote: post #61
melenaboija wrote: post #53

Few weeks ago I did an experiment after a discussion here about LLMs and chess. Basically inventing a board game and play against ChatGPT and see what happened. It was not able to do a single move, even having provided all the possible start moves in the prompt as part of the rules. Not that I had a lot of hope about it, but it was definitely way worst than I expected. If someone wants to take a look at it: https://j…

I'm older. I've bought 'new' board games for kids. Then, I have been un-able to play because the instructions were pretty bad. Humans also need to 'learn'. Need a few play-throughs. No human is going out and 'in a vacuum' with no experience, buying Risk and from scratch, read instructions and play perfect game winning strategy.

The thing is that I wanted to prove that ChatGPT was not able to learn from the rules and that is indeed a Language Model that puts one token after the other, if it know how to play chess it is because it has seen games in the past, as I say in my post:

> If it is not memorizing, how do you think is doing it? (me)

> by trying to learning the general rules that to explain the dataset and minimize its loss. That’s what machine learning is about, it’s not called machine memorizing.

Re: Large language models lack deep insights or a theory of mind

#72

Post by melenaboija »

golergka wrote: post #56
melenaboija wrote: post #53

Few weeks ago I did an experiment after a discussion here about LLMs and chess. Basically inventing a board game and play against ChatGPT and see what happened. It was not able to do a single move, even having provided all the possible start moves in the prompt as part of the rules. Not that I had a lot of hope about it, but it was definitely way worst than I expected. If someone wants to take a look at it: https://j…

You haven't specified what model did you use, and the green ChatGPT icon in the shared conversation usually signifies GPT-3.5 model. Here's my attempt at similar conversation — it seems GPT-4 is able to visualise the board and at least do a valid first move. https://chat.openai.com/share/98427e21-678c-4290-aa8f-da8e93...

Interesting.

The model was whatever was up that that time, so probably was 3.5 if you say so.

Re: Large language models lack deep insights or a theory of mind

#73

Post by FrustratedMonky »

omginternets wrote: post #6
stuckinhell wrote: post #4

Do humans have that as well ? I read studies that suggest we make up consciousness a half second after something happened.

We don't "make up" consciousness, but yes, there is a processing latency of around 250-300ms.

In the book "Being You" Anil Seth. It does postulate that we make up consciousness.

The brain is trying to 'predict' the next sensory input, and that prediction is our awareness. What we would call our 'conscious self'.

It makes point of calling it a 'controlled hallucinations', in that what we experience as our self. "Hallucination" being the experience we have as our brain 'predicting/controlling' for the sensory input. So All inputs come together in a 'hallucination', but it is averaged 'Bayesian', with the actions we are taking at same time. So Action + Prediction = Self.

It is funny that using the word 'hallucinate' in AI has become so common and it is also used in Humans. And so few people seem to make connection that they are actually very similar, and far from being an argument against AI consciousness, is argument for how similar they are.

Re: Large language models lack deep insights or a theory of mind

#74

Post by poulsbohemian »

joduplessis wrote: post #66

For me, the entire AGI conversation is hyperbolic / hype. How can we infer intelligence to something when we, ourselves, have such a poor (none) grasp of what makes us conscience? I'm associating intelligence with consciousness - because it seems correlated. Are we really ready to associate "AGI" with solving math problems ("new Q algo.")? That seems incredibly naive & reinforces my opinion that LLM's are much more l…

Completely agree, and while we are at it... look I'm just a guy, not an expert, but I can't understand why there's so much focus on AGI. It feels like there are so many niche areas where we could apply some kind of analytical augmentation and by solving problems in the small, might learn something that would help figure the larger question of intelligence. I don't need the AI to replace everything I do, I need it to solve 10,000 micro problems I solve every day - each of which is a business opportunity for someone.

Re: Large language models lack deep insights or a theory of mind

#76

Post by pixl97 »

mcguire wrote: post #55
moffkalast wrote: post #16

Earlier quoted context omitted.

I think they may be referring to the principle task that consciousness serves in humans, which is to rationalize decisions we've already made subconsciously to other people so they will help us. The conscious "why" comes after the decision. In that sense it's exactly the kind of bullshit machine that LLMs are.

A thought experiment: what kind of functional MRI result would convince you that human consciousness is real and an important part of decision making? Note: if the result is someone reporting having made a decision before brain activity is seen, my next question is going to be "How does that work?"

https://newsroom.unsw.edu.au/news/science-tech/our-brains-re...

An important statement in the article is this...

>“As the decision of what to think about is made, executive areas of the brain choose the thought-trace which is stronger. In, other words, if any pre-existing brain activity matches one of your choices, then your brain will be more likely to pick that option as it gets boosted by the pre-existing brain activity.

If you observe con men, politicians, and advertisers, they'll commonly use precursors to pre-prime the pump in influencing what you'll agree to.

Re: Large language models lack deep insights or a theory of mind

#77

Post by mcguire »

Barrin92 wrote: post #47

No LLMs don't think like people, they're architecturally incapable of doing so. They have, physically unlike humans no access to their own internal state and they're, save for a small context window, static systems. They also have no insights. There's a hilarious video about LLM Jailbreaks by Karpathy[1] from a week ago, where he shows how you can break model responses by asking the same question with a base64 string…

I was right there with you until you mentioned Searle. :-)

The Chinese room argument is bad in that it hides an assumption of mind/body dualism. If you believe that humans have "souls" and other things do not, then you have a qualitative difference between a human or a machine. On the other hand, if you are a materialist then you are faced with the problem that humans don't have much understanding of semantics either. We're all chemical processes and it's hard for those to get much into semantics.

But then, the difference between LLMs and humans becomes quantitative, sort of, and since I cannot say that LLMs and humans are qualitatively different, the only argument I can find is that in my experience, LLMs have never responded in a way that leads me to believe that they are anything other than a statistical model of language. Humans, on the other hand, are not a statistical model of language.

Re: Large language models lack deep insights or a theory of mind

#78

Post by GaggiX »

melenaboija wrote: post #53

Few weeks ago I did an experiment after a discussion here about LLMs and chess. Basically inventing a board game and play against ChatGPT and see what happened. It was not able to do a single move, even having provided all the possible start moves in the prompt as part of the rules. Not that I had a lot of hope about it, but it was definitely way worst than I expected. If someone wants to take a look at it: https://j…

I have played some moves with GPT-4 and they seem right to me, what does this mean? That the model switched from not understanding to understanding, from unintelligent to intelligent? I don't think so, GPT-4 is just a more intelligent model than GPT-3.5 and it does understand more.

Also in this game if I don't move the queen I force a draw, right?

Re: Large language models lack deep insights or a theory of mind

#79

Post by mcguire »

deeviant wrote: post #26

> A chief goal of artificial intelligence is to build machines that think like people. I disagree with the topic sentence. The goal should not be to "build machines that think like people", but to build machines that think, period. The way humans think is unlikely to be the optimal way to go about thinking anyways. Instead of talking about thinking, we should be talking about function. Less philosophy and more realit…

The problem here is, how do you know that your machine thinks if it doesn't think like humans?

Game AIs are functionally much better than humans but no one believes they can think, right?

Oh, but if you are arguing for AI from a specialized tool standpoint and not a general intelligence standpoint, if you are talking about "weak" AI rather than "strong" AI, then I'm right there with you. :-)

Re: Large language models lack deep insights or a theory of mind

#80

Post by uoaei »

FrustratedMonky wrote: post #59
uoaei wrote: post #36

Earlier quoted context omitted.

> They're just system 1 thinking, the equivalent of putting a gun to someone's head and asking them to solve a large division in 2 seconds. No, it's the equivalent of putting a gun to someone's head and asking them "what are my intentions?" Which is readily available to any being with a theory of mind.

Don't think so. Put gun to persons ahead. Ask them to do a division. Then screaming at them "HOW DID YOU DO THAT, TELL ME NOW, OR YOU'RE TOAST". Even most humans would splutter and not be able to answer.

The division problem is arbitrary and irrelevant to any notion of theory of mind. If you have a better example, you can feel free to offer one. I already did so above.
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