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Theory of Mind May Have Spontaneously Emerged in Large Language Models

arxiv.org

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

#131

Post by soiler »

PaulHoule wrote: post #9
pavel_lishin wrote: post #8

Earlier quoted context omitted.

I recall reading that pointing is something that only a few animals, including us, do and understand. If I get my cats' attention and point at something, they're more interested in the tip of my finger than the direction I'm pointing at. Now, my cats will occasionally meow to get my attention and then walk over to where the problem is - an empty food dish, an empty water bowl, the bed that they expect us to be in bec…

By "pointing" I don't mean pointing your finger, the universal version of "pointing" involves your eyes, shoulders and the rest of your body. (Think of a how a hunting dog points... Plenty of times I've seen cats point out things to other cats not to mention to me.)

Those behaviors could be better described as "looking" and "facing", couldn't they? Pointing means something pretty specific to humans, especially when we're talking about human-animal interactions.

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

#132

Post by psb217 »

avgcorrection wrote: post #76
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…

The problem with this facile view of things is that it seems to be a dead end for scientific theories. What if we just limited the science of birds to explaining how limb-flapping could produce levitation? Hmm yes. Birds are kind of like helicopters, it seems. Who’s to say that they are not basically one and the same? Moving on. If you are only interested in the most superficial tests and theories—like the Turing Tes…

How is the request that someone provide a clear set of definitions and some empirically falsifiable hypotheses a "dead end for scientific theories"? It seems more like the foundation of the scientific method.

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

#133

Post by LarryMullins »

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…

Your Thai text generator example seems like a reformulation of the "Chinese Room" thought experiment, except you're running the system using a single human brain instead of many. I'm not sure that makes a difference. The human running the system doesn't understand Thai, but perhaps that system itself does.

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

#134

Post by didntreadarticl »

swatcoder wrote: post #119
didntreadarticl wrote: post #103

Earlier quoted context omitted.

So your proposed system would be a extremely interesting exploration of that! I look forward to it. Right, so lets virtualise it. Actually training AIs using real cameras and real robot arms will be really slow and expensive. So we provide a system that renders a photorealistic graphical room with teapot and robot arm, and a virtual camera inside the room is 'seeing' parts of the room and a vision model then processe…

Let me know when you find out. The interesting and open question to me is what the limitations are of a language model at the center of that experience. How much of a a relationship with reality can be captured by language at all, and specifically with the specific sort of statistical models of language that we're exploring now? For some of us, the intuitive answer is not all that much and for others it seems to be a…

Ideally in that scenario you'd have a model that unified vision, language and an understanding of 'doing things' and manipulating objects. so it wouldnt just be an LLM, it would be a language-vision-doingthings model. There's no reason why we cant build one.

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

#135

Post by scarmig »

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.

It's no weirder to say "ChatGPT gave me advice" than it is "Google search gave me the link to Wikipedia" or "the sun gave me a tan." Regardless of the exact status of ChatGPT, why be on an ideological warpath to reject that inanimate things can be the subject of a statement?

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

#136

Post by s0ulphire »

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…

A follow up question: as a human doesn't start with "knowing" something either and first creates definitions for objects or words, which it then uses to build increasingly abstract concepts that we eventually classify as "knowledge" on the thing, is there anything that would stop LLMs from being able to do the same thing? I fully agree the capability is not there yet, but I can't say what would stop an appropriately designed model from being able to do so myself.

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

#137

Post by albystein »

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 think this line of reasoning is misguided. What’s striking and more important to focus on are the abstract reasoning abilities of these systems. Language, as you mentioned, abstracts real world objects and phenomena, so it’s a good approximation of the real world. Thus, if an LLM can reason this well using language, it’s safe to say that perhaps they’re doing something akin to what the human mind does.

Your critique about lack of grounding in these systems is an easy problem to solve. It’s as easy as teaching an LLM to associate words with real world objects or phenomena. Image-classification models, text-2-image models, audio transcription models, and many other modal specific systems already do this to some extent. And more recently there has been a push towards multi-modal language models(Deepmind’s flamingo), so this line of argument will be debunked very soon.

I actually believe GPT-4 will be multi-modal and it’s capabilities will dispel majority of these criticisms

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

#138

Post by didntreadarticl »

soiler wrote: post #123
didntreadarticl wrote: post #85

Earlier quoted context omitted.

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.

me: wibble octopus downwards jelly tuesday banana

chatGPT: I'm sorry, but I'm not sure what you're trying to communicate with that sentence. Could you please rephrase or provide more context?

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

#139

Post by nl »

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…

This objection is the well known Chinese Room Experiment objection[1].

The issue is that there doesn't seem to be a better alternative.

Either we build intelligence tests that some variety of the Chinese Room experiment will pass, or

* We have to consider that humans aren't intelligent by our own definitions (or rarely so).

* We decide intelligence isn't actually a scientific attribute and is more akin to a religious attribute, so we abandon the idea of being able to test if something is intelligent.

[1] https://plato.stanford.edu/entries/chinese-room/

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

#140

Post by kilgnad »

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…

From the two camps the one that says we "might" be onto something is the more intelligent and reasonable opinion.

First your camp doesn't deal in absolutes. It doesn't say absolutely chatGPT is sentient. It only questions the possibility and tries to explore further.

Second a skeptical outlook that doesn't deal with absolutes is 100% the more logical and intelligent perspective given the fact that we don't even know what "understanding" or "sentience" is. We can't fully define these words and we only have some fuzzy view of what they are. Given this fact, absolute statements against something we don't fully understand are fundamentally not logical.

This is a strange phenomenon how some people will vehemently deny something absolutely. During the VERY beginning of the COVID-19 pandemic the CDC incorrectly stated that masks didn't stop the spread of COVID-19 and you literally saw a lot of people parroting this statement everywhere as "arm chair" pandemic experts (including here on HN).

Despite this there were some people who thought about it logically if there's a solid object on my face, even if that object has holes in it for air to pass through, the solid parts will block other solid things (like COVID) from passing through thereby lessening the amount of viral material that I breath in. Eventually the logic won out. I think the exact same phenomenon is happening here.

Some or several ML experts tried to downplay LLMs (even though they don't completely understand the phenomenon themselves) and everyone else is just parroting them like they did with the CDC.

The fact of the matter is, nobody completely understands the internal mechanisms behind human sentience nor do they understand how or if chatGPT is actually "understanding" things. How can they when they don't even know what the words mean themselves?

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