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A non-anthropomorphized view of LLMs

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Re: A non-anthropomorphized view of LLMs

#111
post #5

The problem with viewing LLMs as just sequence generators, and malbehaviour as bad sequences, is that it simplifies too much. LLMs have hidden state not necessarily directly reflected in the tokens being produced and it is possible for LLMs to output tokens in opposition to this hidden state to achieve longer term outcomes (or predictions, if you prefer). Is it too anthropomorphic to say that this is a lie? To say th…

IMHO, anthrophormization of LLMs is happening because it's perceived as good marketing by big corporate vendors. People are excited about the technology and it's easy to use the terminology the vendor is using. At that point I think it gets kind of self fulfilling. Kind of like the meme about how to pronounce GIF.

True but also researchers want to believe they are studying intelligence not just some approximation to it.

Re: A non-anthropomorphized view of LLMs

#113

Earlier quoted context omitted.

IMHO, anthrophormization of LLMs is happening because it's perceived as good marketing by big corporate vendors. People are excited about the technology and it's easy to use the terminology the vendor is using. At that point I think it gets kind of self fulfilling. Kind of like the meme about how to pronounce GIF.

I think anthropomorphizing LLMs is useful, not just a marketing tactic. A lot of intuitions about how humans think map pretty well to LLMs, and it is much easier to build intuitions about how LLMs work by building upon our intuitions about how humans think than by trying to build your intuitions from scratch. Would this question be clear for a human? If so, it is probably clear for an LLM. Did I provide enough contex…

You think it's useful because Big Corp sold you that lie.

Wait till the disillusionment sets in.

Re: A non-anthropomorphized view of LLMs

#115

Earlier quoted context omitted.

> It seems like, we can at best, claim that we have modeled the human thought process for reasoning/analytic/quantitative through Linear Algebra....I don't understand is what about linear algebra that makes it so special that it creates a fully functioning life or aspects of a life? Not linear algebra. Artificial neural networks create arbitrarily non-linear functions. That's the point of non-linear activation functi…

ANNs are just mathematical transformations, powered by linear algebra + non-linear functions. They simulate certain cognitive processes — but they are fundamentally math, not magic.

Who invoked magic in this thread exactly?

Re: A non-anthropomorphized view of LLMs

#116
post #5

The problem with viewing LLMs as just sequence generators, and malbehaviour as bad sequences, is that it simplifies too much. LLMs have hidden state not necessarily directly reflected in the tokens being produced and it is possible for LLMs to output tokens in opposition to this hidden state to achieve longer term outcomes (or predictions, if you prefer). Is it too anthropomorphic to say that this is a lie? To say th…

IMHO, anthrophormization of LLMs is happening because it's perceived as good marketing by big corporate vendors. People are excited about the technology and it's easy to use the terminology the vendor is using. At that point I think it gets kind of self fulfilling. Kind of like the meme about how to pronounce GIF.

aAnthrophormisation happens because Humans are absolutely terrible at evaluating systems that give converdational text output.

ELIZA fooled many people into think it was conscious and it wasn't even trying to do that.

Re: A non-anthropomorphized view of LLMs

#117
I have the technical knowledge to know how LLMs work, but I still find it pointless to not anthropomorphize, at least to an extent.

The language of "generator that stochastically produces the next word" is just not very useful when you're talking about, e.g., an LLM that is answering complex world modeling questions or generating a creative story. It's at the wrong level of abstraction, just as if you were discussing an UI events API and you were talking about zeros and ones, or voltages in transistors. Technically fine but totally useless to reach any conclusion about the high-level system.

We need a higher abstraction level to talk about higher level phenomena in LLMs as well, and the problem is that we have no idea what happens internally at those higher abstraction levels. So, considering that LLMs somehow imitate humans (at least in terms of output), anthropomorphization is the best abstraction we have, hence people naturally resort to it when discussing what LLMs can do.

Re: A non-anthropomorphized view of LLMs

#119
post #3

So the author’s core view is ultimately a Searle-like view: a computational, functional, syntactic rules based system cannot reproduce a mind. Plenty of people will agree, plenty of people will disagree, and the answer is probably unknowable and just comes down to whatever axioms you subscribe to in re: consciousness. The author largely takes the view that it is more productive for us to ignore any anthropomorphic re…

[flagged]

Re: A non-anthropomorphized view of LLMs

#120

I have the technical knowledge to know how LLMs work, but I still find it pointless to not anthropomorphize, at least to an extent. The language of "generator that stochastically produces the next word" is just not very useful when you're talking about, e.g., an LLM that is answering complex world modeling questions or generating a creative story. It's at the wrong level of abstraction, just as if you were discussing…

On the contrary, anthropomorphism IMO is the main problem with narratives around LLMs - people are genuinely talking about them thinking and reasoning when they are doing nothing of that sort (actively encouraged by the companies selling them) and it is completely distorting discussions on their use and perceptions of their utility.
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