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A non-anthropomorphized view of LLMs

(addxorrol.blogspot.com)
477 points zdw | 17 comments | | HN request time: 1.285s | source | bottom
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Al-Khwarizmi ◴[] No.44487564[source]
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.

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grey-area ◴[] No.44487608[source]
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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cmenge ◴[] No.44487706[source]
I kinda agree with both of you. It might be a required abstraction, but it's a leaky one.

Long before LLMs, I would talk about classes / functions / modules like "it then does this, decides the epsilon is too low, chops it up and adds it to the list".

The difference I guess it was only to a technical crowd and nobody would mistake this for anything it wasn't. Everybody know that "it" didn't "decide" anything.

With AI being so mainstream and the math being much more elusive than a simple if..then I guess it's just too easy to take this simple speaking convention at face value.

EDIT: some clarifications / wording

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flir ◴[] No.44488265[source]
Agreeing with you, this is a "can a submarine swim" problem IMO. We need a new word for what LLMs are doing. Calling it "thinking" is stretching the word to breaking point, but "selecting the next word based on a complex statistical model" doesn't begin to capture what they're capable of.

Maybe it's cog-nition (emphasis on the cog).

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1. LeonardoTolstoy ◴[] No.44488690[source]
What does a submarine do? Submarine? I suppose you "drive" a submarine which is getting to the idea: submarines don't swim because ultimately they are "driven"? I guess the issue is we don't make up a new word for what submarines do, we just don't use human words.

I think the above poster gets a little distracted by suggesting the models are creative which itself is disputed. Perhaps a better term, like above, would be to just use "model". They are models after all. We don't make up a new portmanteau for submarines. They float, or drive, or submarine around.

So maybe an LLM doesn't "write" a poem, but instead "models a poem" which maybe indeed take away a little of the sketchy magic and fake humanness they tend to be imbued with.

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2. FeepingCreature ◴[] No.44488901[source]
Humans certainly model inputs. This is just using an awkward word and then making a point that it feels awkward.
3. flir ◴[] No.44489424[source]
I really like that, I think it has the right amount of distance. They don't write, they model writing.

We're very used to "all models are wrong, some are useful", "the map is not the territory", etc.

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4. ◴[] No.44489509[source]
5. galangalalgol ◴[] No.44489602[source]
No one was as bothered when we anthropomorphized crud apps simply for the purpose of conversing about "them". "Ack! The thing is corrupting tables again because it thinks we are still using api v3! Who approved that last MR?!" The fact that people are bothered by the same language now is indicative in itself. If you want to maintain distance, pre prompt models to structure all conversations to lack pronouns as between a non sentient language model and a non sentient agi. You can have the model call you out for referring to the model as existing. The language style that forces is interesting, and potentially more productive except that there are fewer conversations formed like that in the training dataset. Translation being a core function of language models makes it less important thought. As for confusing the map for the territory, that is precisely what philosophers like Metzinger say humans are doing by considering "self" to be a real thing and that they are conscious when they are just using the reasoning shortcut of narrating the meta model to be the model.
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6. flir ◴[] No.44490309{3}[source]
> You can have the model call you out for referring to the model as existing.

This tickled me. "There ain't nobody here but us chickens".

I have other thoughts which are not quite crystalized, but I think UX might be having an outsized effect here.

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7. irthomasthomas ◴[] No.44490723[source]
Depends on if you are talking about an llm or to the llm. Talking to the llm, it would not understand that "model a poem" means to write a poem. Well, it will probably guess right in this case, but if you go out of band too much it won't understand you. The hard problem today is rewriting out of band tasks to be in band, and that requires anthropomorphizing.
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8. thinkmassive ◴[] No.44490885[source]
GenAI _generates_ output
9. galangalalgol ◴[] No.44491120{4}[source]
In addition to he/she etc. there is a need for a button for no pronouns. "Stop confusing metacognition for conscious experience or qualia!" doesn't fit well. The UX for these models is extremely malleable. The responses are misleading mostly to the extent the prompts were already misled. The sorts of responses that arise from ignorant prompts are those found within the training data in the context of ignorant questions. This tends to make them ignorant as well. There are absolutely stupid questions.
10. jorvi ◴[] No.44491594[source]
A submarine is propelled by a propellor and helmed by a controller (usually a human).

It would be swimming if it was propelled by drag (well, technically a propellor also uses drag via thrust, but you get the point). Imagine a submarine with a fish tail.

Likewise we can probably find an apt description in our current vocabulary to fittingly describe what LLMs do.

11. j0057 ◴[] No.44492786[source]
A submarine is a boat and boats sail.
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12. TimTheTinker ◴[] No.44493077[source]
An LLM is a stochastic generative model and stochastic generative models ... generate?
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13. LeonardoTolstoy ◴[] No.44493630{3}[source]
And we are there. A boat sails, and a submarine sails. A model generates makes perfect sense to me. And saying chatgpt generated a poem feels correct personally. Indeed a model (e.g. a linear regression) generates predictions for the most part.
14. dcookie ◴[] No.44493763[source]
> it won't understand you

Oops.

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15. irthomasthomas ◴[] No.44493995{3}[source]
That's consistent with my distinction when talking about them vs too them.
16. floam ◴[] No.44496482[source]
Submarines dive.
17. seyebermancer ◴[] No.44499791[source]
What about they synthesize?

Ties in with creation from many and synthetic/artificial data. I usually prompt instruct my coding models more with “synthesize” than “generate”.