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Talking About Large Language Models

arxiv.org

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Re: Talking About Large Language Models

#131

Post by usgroup »

RosanaAnaDana wrote: post #11

I like the discussion, but this article 'feels' like more Luddite goalpost moving, and is reflective of a continuous sentiment I feel strains so much of the conversation around intelligence, agentism, and ai going on today. I think that because we lack a coherent understanding of what it means to be intelligent at an individual level, as well as what it means to be an individual, we're missing much of the point of wh…

I think the basic things to take away from the article are:

1. that LLMs are just a massive “what word comes next given your training corpus” algorithm and scale has lead to the main effects of interest.

2. Surprisingly many human tasks can be represented by this simple “what word comes next” question given a big enough corpus.

3. But it has nothing to do with how a human executes those tasks because —- for example —- knowing the country south of Rwanda and knowing the likely completion of “the country south of Rwanda is ___” in a corpus, are not the same thing at all.

4. The key reason being that LLM has no access to semantic knowledge beyond correlation in its corpus, but you have access to causality.

5. So it is absurd to compare the LLM to people —- not because it’s like comparing submarines to fish, because in this case they do not both even “swim and live in the sea”.

I think these things have little to do with definitions of “what intelligence is” and the like, and the author is far from a Luddite.

Re: Talking About Large Language Models

#132

Post by goatlover »

Chirono wrote: post #85
goatlover wrote: post #82

Earlier quoted context omitted.

> 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 conscious, right? Your brain is part of an organism who's ancestors evolved to survive the real world, not by matching tokens. As such, language is a skill that helps humans survive and reproduce, not a tool used to mi…

Of course they’re different. But so what? That’s not exactly proof of anything, unless you’re suggestion biological neurons are the only configuration in the universe capable of thought? Maybe that’s true, but it seems unlikely to me. The pressure of natural selection can lead to the phenomenon of consciousness. Why not the process of training llms? Perhaps developing the machine equivalent of consciousness helps tha…

I'm saying that when humans use language, it's about stuff in the world and ourselves. The words have references or uses that we call meaning. When an LLM models language, it is approximating the patterns of language use we have produced that have been made available to it. It doesn't understand what the words it's producing are about (no external references), only how to produce those words in patterns that are meaningful to us.

What if we fed an LLM a bunch of crazy nonsense instead? It would model the patterns in the word use and then give us answers based on the nonsense it was fed. But it wouldn't understand that it's actually nonsense that doesn't apply to the real world.

Re: Talking About Large Language Models

#133

Post by Zababa »

gillesjacobs wrote: post #95
Zababa wrote: post #81

Earlier quoted context omitted.

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 eng…

That's a totally fair point.

Re: Talking About Large Language Models

#134

Post by doliveira »

wellpast wrote: post #111
doliveira wrote: post #108

Earlier quoted context omitted.

Something that happens in our universe that Physics somehow has nothing to do with? How is that not magical/spiritual/metaphysical voodoo handwaving?

Physics is a set of things we understand about the universe and often used to include some mystifying things, i.e. that we don't quite understand (eg Bell's theorem). To just claim that Physics has to do with _more_ than this - that it has to do with all the things we don't understand is just blind-faith ascription. It's a nearly meaningless statement, really. So it's bizarre or voodoo to say it so casually and assur…

Physics, by definition, has to do with everything, well, physical going on in this Universe. It's not about whether we understand it or not, or whether we're comfortable with it.

So yeah, if you claim conscience is not physical, then you're talking about metaphysics. Which is okay to do, but then claiming that those that say that Physics alone is probably enough are saying voodoo... Well, it's ironic.

Re: Talking About Large Language Models

#135

Post by lambdatronics »

mannykannot wrote: post #114
lambdatronics wrote: post #64

Earlier quoted context omitted.

Edsger Dijkstra: "The question of whether Machines Can Think (…) is about as relevant as the question of whether Submarines Can Swim."

That's an amusing aphorism from a giant in the field, and it was a reasonable thing to say about the technology of that time, but it avoids, rather than answers, the much bigger question of whether machines could ever think.

Humans can think; humans are machines; therefore machines can think.

Re: Talking About Large Language Models

#136

Post by sdenton4 »

gillesjacobs wrote: post #65
joe_the_user wrote: post #62

Earlier quoted context omitted.

People do this because mirroring cognition to machine learning lends credence that their specific modeling mechanism mimicks human understanding and so is closer "to the real thing". Doesn't this also involve people not having another category aside from "cognition" to put natural language processing acts in? How many neural net constructors have a rigorously developed framework describing what "cognition" is? I mean…

> Doesn't this also involve people not having another category aside from "cognition" to put natural language processing acts in? Yes, of course this might be an even more primary reason; do not attribute to malice what can be explained by laziness. However, AI researchers should be wary of their language, that point is hammered in most curricula I have seen. So at the least it is negligence. > I mean, there's a comm…

Why does nlp need to mimic human brain function to count as cognition? This seems overly reductive; I see no reason to believe that biomimicry is necessary for intelligence. The argument is overly reductive: only brains think, and this is not a brain, ergo it does not think.

(To be clear, I don't think this system is an AGI; just making the point that better goal posts are needed...)

Re: Talking About Large Language Models

#137

Post by hnnotreddit »

oneoneonetwo wrote: post #129
hnnotreddit wrote: post #102

Earlier quoted context omitted.

You fundamentally misunderstand the scientific method which includes falsifiability but is not limited to it, moved the goalpost away from peer review for journals into general bar stool philosophy all while continuously insulting the GP. What is ironic is you hiding behind throwaway accounts and asserting superior knowledge while fundamentally misunderstanding the issue of positive claims in science.

>while continuously insulting the GP. Read the conversation. You are accusing me of something vile which the GP started. GP Literally said that science was something elementary school level shit implying that I was so damn stupid I was uneducated. You're only taking his side because You agree with him, you are not seeing who drew first blood and you are burning the witch because it serves your own agenda. He insulted…

> Did you not see the quote from Einstein? > The only reason why I made a new account is because I wanted to comment here.

Extremely petty, insubstantial and toxic, you have nothing insightful to add.

Re: Talking About Large Language Models

#138

Post by gillesjacobs »

sdenton4 wrote: post #136
gillesjacobs wrote: post #65

Earlier quoted context omitted.

> Doesn't this also involve people not having another category aside from "cognition" to put natural language processing acts in? Yes, of course this might be an even more primary reason; do not attribute to malice what can be explained by laziness. However, AI researchers should be wary of their language, that point is hammered in most curricula I have seen. So at the least it is negligence. > I mean, there's a comm…

Why does nlp need to mimic human brain function to count as cognition? This seems overly reductive; I see no reason to believe that biomimicry is necessary for intelligence. The argument is overly reductive: only brains think, and this is not a brain, ergo it does not think. (To be clear, I don't think this system is an AGI; just making the point that better goal posts are needed...)

I agree and focusing on biomimetics is indeed insufficient in discussions of what constitutes intelligence.

The discussion on what constitutes intelligence and cognition is too vast and complex. The central point is that haphazard and unsubstantiated authromorphising language should be barred from scientific papers. We know that an LLM does not "know", "believe", "intent", or "feels" because they lack any form of integrated, general human-like intelligence. It is trivially correct to use different terms like "models", "predicts", "outputs emotive expressions" and avoid unevidenced claims of human behaviour.

I also wanted to nuance my opening post: I file the "don't humanise ML models"-comment of peer review under "minor issues". This means that it is an issue with the paper that does not prevent publication. This is not a hill I am willing to let good research die on.

Re: Talking About Large Language Models

#139

Post by gillesjacobs »

oneoneonetwo wrote: post #130
gillesjacobs wrote: post #80

Earlier quoted context omitted.

Let me falsify your claim immediately: the inputs of these models are nothing like the inputs a human receives, subword tokens do not even match up with lexical items (visually, textually and semantically). You seem to agree with me even though your interpretation of falsifiability is inverted: I am not asking that authors make a claim that their models do not mimick human intelligence. Like OP, I ask them that they…

I also want to mention that, you directly stated in your first sentence in your first post that humanizing was wrong. This in itself is a claim made without evidence. Which is my point. The claim as it stands cannot be made either way. We simply don't know.

The counterargument stems on a fundamental misunderstand of what it means to make assertive claims in science: you always need to prove your positive claim, saying that we do not know that ML models are human-like requires no evidence because this is the zero hypothesis.

Using humanising language is equivalent to attributing human-like cognition to ML models. Unless there is very strong evidence that there are analogies between the specific modeling mechanism and human-like intelligence, it is always incorrect to positively assert these claims without evidence. In science, you can only assert that for which there is evidence, strong claims like the above require strong evidence.

Re: Talking About Large Language Models

#140

Post by gillesjacobs »

pama wrote: post #115
gillesjacobs wrote: post #95

Earlier quoted context omitted.

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 eng…

I don’t understand why if common usage of such terms is fine and even desirable in daily context, the same terms should not be used in scientific communication. If people are unclear or ambiguous, then of course that’s undesirable and should be corrected, however, if certain terms are fully clear within their context then I don’t see the harm of the same term having a different meaning in the study of cognition and a…

For scientific papers, it is required to be specific and precise with terminology. Everyday communication affords more liberties and leeway.

For the journal paper genre which is highly technical, more specific and appropriate terminology is always available that sidestep the whole issue.

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