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Theory of Mind May Have Spontaneously Emerged in Large Language Models

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Re: Theory of Mind May Have Spontaneously Emerged in Large Language Models

#121

Post by brookst »

lib-dev wrote: post #63
brookst wrote: post #11

Earlier quoted context omitted.

Certainly they are big state machines, but is there any proof that we are not?

State machines cannot change the semantics of themselves. We can. We are like state machines most of the time but we can switch into "developer mode" and deploy updates whenever we choose to :)

> State machines cannot change the semantics of themselves.

That's not true at all. There are many, many state machine implementations where the machine's states and paths are altered by the machine itself. See for instance https://digitalcommons.trinity.edu/cgi/viewcontent.cgi?artic...

Re: Theory of Mind May Have Spontaneously Emerged in Large Language Models

#122

Post by letmevoteplease »

sgt101 wrote: post #70
ux-app wrote: post #65

Earlier quoted context omitted.

this is mind blowing to me. can anyone with more knowledge on the topic explain how ChatGPT is demonstrating this level of what seems like genuine understanding and reasoning? Like others I assumed that ChatGPT is gluing words together that commonly occur together. This is way more than that.

No, it's paraphrasing it's training data that likely contains these tasks in one form or another. Here's one I made : me : There's a case in the station and the policeman opens it near the fireman. The dog is worried about the case but the policeman isn't, what does the fireman think is in the station? chatgpt : As a language model, I do not have access to the thoughts of individuals, so I cannot say what the fireman…

There's a good chance a human would respond in the same way, because they would assume you were asking a good-faith question instead of nonsense. Try asking it an original question that has some kind of deducible answer. Its abilities are more impressive than you would expect from an algorithm that just predicts the next word.

I doubt there is anything quite like this situation in the training data: https://i.imgur.com/HOEnxYb.jpg

Re: Theory of Mind May Have Spontaneously Emerged in Large Language Models

#123

Post by soiler »

didntreadarticl wrote: post #85
sgt101 wrote: post #70

Earlier quoted context omitted.

No, it's paraphrasing it's training data that likely contains these tasks in one form or another. Here's one I made : me : There's a case in the station and the policeman opens it near the fireman. The dog is worried about the case but the policeman isn't, what does the fireman think is in the station? chatgpt : As a language model, I do not have access to the thoughts of individuals, so I cannot say what the fireman…

your question is pretty confusing. What dog? station is a vague word. Train station, police station? Case is a vague word. And asking whats in the station is still asking whats in the case, in a way. Me: There's a blue suitcase in the airport and a policeman carrying a red bag opens the blue suitcase with a sniffer dog and fireman standing nearby. The dog is worried about the suitcase but the policeman isn't. What do…

> your question is pretty confusing

That's exactly the point, isn't it? If the AI had some model of reality, it would probably be confused by the question. But it doesn't express confusion, it confidently answers the question in a way that doesn't make sense.

It acts like everything it is reading and saying is completely coherent because it doesn't have the ability to distinguish coherent ideas from nonsense.

Re: Theory of Mind May Have Spontaneously Emerged in Large Language Models

#124

Post by bottlepalm »

dQw4w9WgXcQ wrote: post #101
scarmig wrote: post #42

Earlier quoted context omitted.

After trying this, say what you will about ChatGPT, but it's way better at looking at a situation and giving advice than random Redditors.

You do understand it's not ChatGPT giving advice though right? ChatGPT's "life advice autocomplete engine" is basically digging somewhere into psychology manuals written by educated humans when it spits out responses.

What's the functional difference between a psychology manual imprinted on an AI neural network versus a biological one?

Re: Theory of Mind May Have Spontaneously Emerged in Large Language Models

#125

Post by soiler »

didntreadarticl wrote: post #74
ux-app wrote: post #65

Earlier quoted context omitted.

this is mind blowing to me. can anyone with more knowledge on the topic explain how ChatGPT is demonstrating this level of what seems like genuine understanding and reasoning? Like others I assumed that ChatGPT is gluing words together that commonly occur together. This is way more than that.

There are two camps, evident in this thread. one camp is 'its just a statistical model, it cant possibly know these things' The other camp (that I'm in) sees that we might be onto something. We humans are obviously just more than a statistical model, but nonetheless learning words and how they fit together is a big part of who we are. With LLMs we have our first glimpse of 'emergent' behaviour from simple systems sca…

I don't think you've represented the camps fairly (actually, I don't think there are two camps). Most people (here) are probably not arguing that AGI is impossible, but that current AI is not generally intelligent. The John Carmack quote is exactly in line with this. He says "ride those to [AGI]," meaning they are not AGI. The idea that genuine intelligence and self-awareness could emerge from increasingly powerful statistical models is in no way the kind of counter-cultural idea you seem to be presenting it as. I think almost all of us believe that.

But ChatGPT is not it.

Re: Theory of Mind May Have Spontaneously Emerged in Large Language Models

#126

Post by kilgnad »

ux-app wrote: post #65
didntreadarticl wrote: post #46

Earlier quoted context omitted.

Here's a simpler scenario that doesn't involve reading: Me: There is a banana on the table. Someone comes and peels the banana and shows you that inside it, there is actually a carrot! Then they carefully stick the peel back so it look unpeeled. What is inside the banana skin? ChatGPT: According to the scenario described, there is a carrot inside the banana peel that has been carefully placed back to look unpeeled. M…

this is mind blowing to me. can anyone with more knowledge on the topic explain how ChatGPT is demonstrating this level of what seems like genuine understanding and reasoning? Like others I assumed that ChatGPT is gluing words together that commonly occur together. This is way more than that.

it indeed understands you. A lot of people are just parroting the same thing over and over again saying it's just a probabilistic word generator. No, it's not, it's more then that.

Take a look at this: https://www.engraved.blog/building-a-virtual-machine-inside/

Read to the end. The beginning is trivial the ending is unequivocal: chatGPT understands you.

I think a lot of people are just in denial. Because the last year there's been the same headlines over and over again and some people get a little too excited about the headlines and other armchair experts just try to temper the excitement with their "expert opinions" on LLMs that they read from popular articles. Then when something that's an actual game changer hits the scene (chatGPT) they completely miss it.

chatGPT is different. From a technical perspective, it's simply an LLM with additional reinforcement training... BUT you can't deny the results are remarkable.

If anything this much is clear to me: We are at a point where we can neither confirm or deny whether chatGPT represents some aspect of sentience.

This is especially true given the fact that we don't even fully know what sentience is.

Re: Theory of Mind May Have Spontaneously Emerged in Large Language Models

#127

Post by NikolaNovak »

space_fountain wrote: post #56
lsy wrote: post #33

This highlights one of the types of muddled thinking around LLMs. These tasks are used to test theory of mind because for people, language is a reliable representation of what type of thoughts are going on in the person's mind. In the case of an LLM the language generated doesn't have the same relationship to reality as it does for a person. What is being demonstrated in the article is that given billions of tokens o…

I wonder every time I see this take what it would mean under this definition of knowing things for a machine learning algorithm to ever know something. I find that especially important because to every appearance we are a machine learning algorithm. I don’t know how different the sort of knowing this algorithm has to the sort of knowing a human has, but you’re far more confident than I am that it’s a difference of ki…

I am not in the field so I cannot speak very eloquently what it would mean for machine learning algorithm to "ever know something". But I feel that e.g. Simulations and perhaps expert systems of yore, were qualitatively closer to getting there. Their error modes were radically different. They started inductively with rules, rather than arriving at them statistically almost by accident.

Re: Theory of Mind May Have Spontaneously Emerged in Large Language Models

#128

Post by mhitza »

lsy wrote: post #33

This highlights one of the types of muddled thinking around LLMs. These tasks are used to test theory of mind because for people, language is a reliable representation of what type of thoughts are going on in the person's mind. In the case of an LLM the language generated doesn't have the same relationship to reality as it does for a person. What is being demonstrated in the article is that given billions of tokens o…

> These tasks are used to test theory of mind because for people, language is a reliable representation of what type of thoughts are going on in the person's mind.

I actually think that human language is unreliable at expressing what's going on inside a persons mind[1]. My native language is not English, I have only introductory-level knowledge in the field of pragmatics[2], which makes me fully aware of the many ways in which I could fail to write a compelling sentence to support my argument. I can use language to only approximate thoughts in my head, and when it comes to abstract concepts and ideas, words alone, I assert, are never sufficient. It isn't even necessary to step outside our main knowledge area to illustrate this point. How many around here have read a Monad tutorial, without any hands-on experience, and how many of those have understood what Monads are/or how they work from words alone?

My entire paragraph from before, just to set the stage on a simple question. How can you even formulate a question, for a multi-billion parameter language model, to evaluate that it can understand in an abstract/conceptual way something/anything? Heck, how can you do that with other people? I think if we'd have an answer here, we actually could evaluate easily experience/expertise with anyone we'd interview; instead of requiring credentials, references, tests, trials, etc.

[1] Lots of poets from the romanticism era liked to touch upon this topic. One that comes to mind, and one of my personal favorites, is Silentium by Fyodor Tyutchev https://culturedarm.com/silentium-by-fyodor-tyutchev/

[2] https://en.wikipedia.org/wiki/Pragmatics

Re: Theory of Mind May Have Spontaneously Emerged in Large Language Models

#129

Post by ghayes »

abeppu wrote: post #117
space_fountain wrote: post #56

Earlier quoted context omitted.

I wonder every time I see this take what it would mean under this definition of knowing things for a machine learning algorithm to ever know something. I find that especially important because to every appearance we are a machine learning algorithm. I don’t know how different the sort of knowing this algorithm has to the sort of knowing a human has, but you’re far more confident than I am that it’s a difference of ki…

Defining what "knowing" is would be useful, yes, and analytic philosophers in epistemology do argue about this. One attribute that's classically part of the definition of "knowing" is that the thing which is known must be true. LLMs are pretty bad at this, but perhaps that can be fixed. But I would challenge you to imagine the situation the LLM is actually in. Do you understand Thai? If so, in the following, feel fre…

Personally, I'm not convinced, in your hypothetical, that the participant does not "know" Thai at that point. Seeing a young child learn language, it's a lot more adaptive than I think we tend to see language learning, as we often think about learning language as a teenager and not a toddler. I agree the machine does not know what a pizza tastes like nor does it know what it is to _want_ pizza, but I'm not sure that is what is being contested here.

Re: Theory of Mind May Have Spontaneously Emerged in Large Language Models

#130

Post by didntreadarticl »

abeppu wrote: post #117
space_fountain wrote: post #56

Earlier quoted context omitted.

I wonder every time I see this take what it would mean under this definition of knowing things for a machine learning algorithm to ever know something. I find that especially important because to every appearance we are a machine learning algorithm. I don’t know how different the sort of knowing this algorithm has to the sort of knowing a human has, but you’re far more confident than I am that it’s a difference of ki…

Defining what "knowing" is would be useful, yes, and analytic philosophers in epistemology do argue about this. One attribute that's classically part of the definition of "knowing" is that the thing which is known must be true. LLMs are pretty bad at this, but perhaps that can be fixed. But I would challenge you to imagine the situation the LLM is actually in. Do you understand Thai? If so, in the following, feel fre…

Ok I like your thought experiment. Lets change it a bit.

Instead of it being an unknown language, its English (a language you know), but every single Noun, Verb, Adjective or Preposition has been changed to Thai (a language you dont know).

The Mæw Nạ̀ng Bn the S̄eụ̄̀x.

If you had sufficient opportunity to study this pile of text, you'd begin to pick out patterns of which words appear together, and what order words often appear in. Suppose you study this giant stack of Thai text for years in isolation. After all this study, you're good enough that given a few written Thai words, you can write sequences of words that are likely to follow, given what you know of these patterns.

Right, and to get good at this task, you'd need to build models in your head. You would think to yourself, right a Mæw tends to nạ̀ng bn a S̄eụ̄̀x, and you would build up a model of the sort of things a Mæw might do, the situations it might be in. In an abstract way. As you absorbed more and more data you would adjust these abstract models to fit the evidence you had.

You dont know what a Mæw is. But if someone asks you about a Mæw, you can talk about how it relates to S̄eụ̄̀x, Plā and H̄nū. You know stuff about Mæw, but its abstract.

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