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Talking About Large Language Models

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91–100 of 158 posts

Re: Talking About Large Language Models

#91

Earlier quoted context omitted.

Maybe there isn't a precise definition, but clearly for humans thinking and knowing is related to having bodies that need to survive in the world with other humans and organisms, which involves communication and references to external and internal things (how your body feels and what not). This is different from pattern matching tokens, even if it reproduces a lot of the same results, because human language creates a…

>This is different from pattern matching tokens But is it different in essential ways? This is not so clear. Humans developed the capacity to learn, think, and communicate in service to optimizing an objective function, namely fitness in various environments. But there is an analogous process going on with LLMs; they are constructed such that they maximize an objective function, namely predict the next token. But it…

Yes, LM often get into loops that can't be terminated b/c of issues like this. I feel like you have not used them much and are only basing your opinion on what others have done with them. LM can't "think" and it is really obvious that this is the case after you interact with them.

My cat has more personality ...

Re: Talking About Large Language Models

#92
post #73

This paper, and most other places i’ve seen it argued that language models can’t possibly be conscious, sentient, thinking etc, rely heavily on the idea that llms are ‘just’ doing statistical prediction of tokens. I personally find this utterly unconvincing. For a start, I’m not entirely sure that’s not what I’m doing in typing out this message. My brain is ‘just’ chemistry, so clearly can’t have beliefs or be consci…

OK well - sure - even if that is how we work, then language models are much worse at it than we are.

They are better than us at some things already, but do I think they will be better than us at EVERYTHING?

No.

Re: Talking About Large Language Models

#93
post #81

I am NLP researcher who volunteers for peer review often and the anthropomorphisms in papers are indeed very common and very wrong. I have to ask authors to not ascribe cognition to their deep learning approaches in about a third of the papers I review. People do this because mirroring cognition to machine learning lends credence that their specific modeling mechanism mimicks human understanding and so is closer "to…

I'm not really sure about the context here, but I know that I tend to humanize AIs, for example interacting with ChatGPT like with a regular human being, because I'm being nice to him and he's being nice to me in return. I don't know if it's more like being nice to a human, or more like taking good care of your tools so they will take good care of you, but it just feels better for me.

It isn't a strange thing or even a bad thing: it is a human thing to anthropomorphize things. We do it with animals even, which is some weird irony. We do it with common objects. We're just wired that way.

It doesn't mean that there is "something there" with LM tho - just that we're good at tricking ourselves to think that way.

Re: Talking About Large Language Models

#94

Earlier quoted context omitted.

>This is different from pattern matching tokens But is it different in essential ways? This is not so clear. Humans developed the capacity to learn, think, and communicate in service to optimizing an objective function, namely fitness in various environments. But there is an analogous process going on with LLMs; they are constructed such that they maximize an objective function, namely predict the next token. But it…

In that case, humans and LLMs are optimizing for different things. One would be environmental fitness, with language as a strategy to use in that environment, so language is about the environment, including humans themselves. Whereas the other is a model of the language humans have used. The model is being optimized for the language, whereas humans are being optimized to use the language in an environment alongside o…

Yes, there are differences. You can spend the rest of your life listing differences between the two systems. The hard part is to demonstrate that some difference is relevant to the particular kinds of properties we're interested in. Just pointing out the difference doesn't do the job.

Re: Talking About Large Language Models

#95
post #81

I am NLP researcher who volunteers for peer review often and the anthropomorphisms in papers are indeed very common and very wrong. I have to ask authors to not ascribe cognition to their deep learning approaches in about a third of the papers I review. People do this because mirroring cognition to machine learning lends credence that their specific modeling mechanism mimicks human understanding and so is closer "to…

I'm not really sure about the context here, but I know that I tend to humanize AIs, for example interacting with ChatGPT like with a regular human being, because I'm being nice to him and he's being nice to me in return. I don't know if it's more like being nice to a human, or more like taking good care of your tools so they will take good care of you, but it just feels better for me.

It is entirely ok and normal to humanize machines, just don't do it in scientific engineering papers is all I am saying.

I name my bots and machines and of course in daily discussions the loaded words ("thinking", ""believing", "meaning", "knowing") are used. Simulating any human behaviour will elicit a sympathetic response, especially if it has utility to the user. But in the context of peer-review of scientific engineering papers that is inappropiate.

Re: Talking About Large Language Models

#96
post #73

This paper, and most other places i’ve seen it argued that language models can’t possibly be conscious, sentient, thinking etc, rely heavily on the idea that llms are ‘just’ doing statistical prediction of tokens. I personally find this utterly unconvincing. For a start, I’m not entirely sure that’s not what I’m doing in typing out this message. My brain is ‘just’ chemistry, so clearly can’t have beliefs or be consci…

OK well - sure - even if that is how we work, then language models are much worse at it than we are. They are better than us at some things already, but do I think they will be better than us at EVERYTHING? No.

out of interest, is there anything specific you think humans will always be better at than AI?

Re: Talking About Large Language Models

#97
post #88

Earlier quoted context omitted.

Quoted post unavailable.

You’re looking for someone to argue with, but your arguments are trivial and meritless. You’re not a scientist and never have been. The fact that you’re posting with a throwaway account created an hour ago says it all. HN should not allow people like you to post.

Everyone should be welcome to post, this discussion was largely constructive, and though GP should have refrained from certain bad faith rhetoric, their line of questioning resulted in interesting discussion which is itself a contribution.

Your criticism should be calling on them to post more respectfully and humbly, rather than shunning them. We don't know if they're a scientist (let alone that they never will be) and shouldn't assert they aren't, and everyone is entitled to post from throwaway accounts. Everyone should be welcome to question assertions, even nonexperts (though nonexperts should acknowledge their limitations & refrain from disrespectful language).

Re: Talking About Large Language Models

#98
I mean, if you accept the assumption that consciousness is biological (so there is no soul or other spiritual or metaphysical entity), then there is some algorithm or processing model that produces genuine consciousness: The one that takes place in our brains.

The question remains if this processing model would be in any way similar to the processing model that LLMs use - and yes, we can probably rule that out pretty confidently.

Another question might be though if there are other processing models than the one our brains use that also produce consciousness. But that's of course a very hard question to answer if we don't even know what consciousness is exactly.

Re: Talking About Large Language Models

#99
post #98

I mean, if you accept the assumption that consciousness is biological (so there is no soul or other spiritual or metaphysical entity), then there is some algorithm or processing model that produces genuine consciousness: The one that takes place in our brains. The question remains if this processing model would be in any way similar to the processing model that LLMs use - and yes, we can probably rule that out pretty…

You're making an assumption out of thin air here: that consciousness is somehow produced or emergent, or that if it isn't you're in the realm of spiritual or something. What's your basis for that assumption other than just asserting it?

Re: Talking About Large Language Models

#100
post #88

Earlier quoted context omitted.

Quoted post unavailable.

You’re looking for someone to argue with, but your arguments are trivial and meritless. You’re not a scientist and never have been. The fact that you’re posting with a throwaway account created an hour ago says it all. HN should not allow people like you to post.

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