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naraburns  nihil supernum  1yr ago (text post)   29600 thread views

Culture War Roundup for the week of February 6, 2023

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The thing about GPT is that while it can string words together in grammatically correct order it's still nowhere close to replicating human communication in large part because upon inspection/interrogation it quickly becomes apparent that it doesn't really have a concept of what words mean, only what words are associated with others.

Isn't that the exact same thing that Stable Diffusion does? I admit I am not an expert on either model, but my understanding is that it "draws" by having an understanding of what bits of the drawing should go next to each other. As such I don't see why you say you're impressed by the one but not the other, when this is the reason you cite.

I admit I am not an expert on either model, but my understanding is that it "draws" by having an understanding of what bits of the drawing should go next to each other.

I don't know enough about ML to compare and contrast the different models, but my understanding of Stable Diffusion is that it's a denoising tool. It was trained by taking image-string pairings, adding noise to them, and then learning what ways of denoising cause it to get closer to the original image. Then in image generation, it starts off with just random noise and denoises it in a way that matches the prompt.

In that sense, I'm not sure it's accurate to say that it "understands" what bits of the drawing should go next to each other. If I tell it "woman wearing red shirt sitting on a brown chair," it doesn't "understand" which bits of the drawing should be a woman, a shirt, or a chair, and it doesn't "understand" that the shirt should be red and the chair should be brown. It just "understands" that the entire picture gets somewhat closer to the entire prompt when it gets denoised a certain way.

Isn't that the exact same thing that Stable Diffusion does?

Inserts that pirate meme. Well yes, but actually no.

There is world of difference between "Based on my training data, sentences containing the word "chair" will also contain the word "sit" ergo my output should as well" vs "a chair is sit upon". The latter sort semantic link has long been viewed as one of the capital-H hard problems of programming a truly general AI. A problem that stable diffusion actually seems to be on a path to solving which the autoregression models that underpin GPT and it's various offshoots do not.

/images/16757438522129903.webp

But GPT-3 clearly has that understanding. I mean, obviously not always, but also obviously sometimes. By and large, GPT-3 does not actually tend to assert that chairs sit on people.

I don't think it's clear at all. A chair sitting on a person is exactly the sort of slip up that typically gives AI generated text away.

I think it makes those kinds of slips, which to me just means it has imperfect understanding and tends to bullshit. But it doesn't universally make those kinds of slips; it gets chair-person type relations right at a level above chance. Otherwise, generating any continuous run of coherent text would be near impossible.

It would be exceedingly strange for it to generate "the chair sits on the person" at the same rate as its converse, considering that "the <thing> <interacts> the <person>" is vanishingly rarer in its training corpus than "the <person> <interacts> the <thing>". But that sort of generalization requires some abstract model of "thing", "person" and "interact". For it to not pick up that pattern would be odd - why would that be the pattern that stumps it, when it can pick up the categories just fine?

We're not looking for a "better than chance" guess though. We're looking for evidence of an understanding that goes beyond "object-noun verb subject-noun" which for the moment at least does not appear to be present. GPT-3 can string words and sentences together but within a paragraph or two it becomes clear that it is not conveying any meaning, it's just babbling.

To expand my point, I think there is a smooth continuity between "babbling" and "conveying meaning" that hinges on what I'd call "sustained coherency". With humans, we started out conceptualizing meaning, modelling things in our head, and then evolved language in order to reflect and externalize these things; we (presumably) got coherence first. AI is going the other way: it starts out swimming in a soup of meaning-fragments (even Markov chains learn syllables), and as our technology improves it assembles them into longer and longer coherent chains. GPT-2 was coherent at the level of half-sentences or sentences, GPT-3 can be coherent at levels spanning paragraphs. It occasionally loses the plot and switches universes, giving up on one cluster of assembled meaning-fragments as it cannot generate a viable continuation and slipping smoothly into another. But the "sort of thing that it builds" with words, the assemblage of fragments into chains of meaning, is the same sort of thing that we build with language. It's coming at the same spot (months/years-long sustained coherency) from another evolutionary direction.

You may argue "it's all meaningless without attachment to reality." And sure, that's not wrong! But once the assemblage operates correctly, attaching meaning to it will just be a matter of cross-training. (And the unsolved problem of the "artificial self", though if ever there was a problem amenable to a purely narrative solution...)

I disagree.

Can you give an example that you think illustrates your point well? (I don't have ChatGPT access. Giving out my phone number? Ugh.)

A few moments ago, while looking for a quote by James Baldwin*, I turned to Chat GPT for help. I used the prompt, "...It describes his anger towards the white man and his interest in white women.""

It gave me the following quote:

"No black man has ever been able to seriously consider the white woman without having to grapple with the ancient myth of the wide-eyed, agile and demanding Eve, who offers him the poisoned apple of forbidden sexuality, the apple of his own destruction." - James Baldwin.

As far as I can tell this quote was fabricated wholesale. A God of words is being birthed, and conscious or not Ze will change the world entirely.

  • This is the quote I was looking for:

"And there is, I should think, no Negro living in America who has not felt, briefly or for long periods, with anguish sharp or dull, in varying degrees and to varying effect, simple, naked and unanswerable hatred; who has not wanted to smash any white face he may encounter in a day, to violate, out of motives of the cruelest vengeance, their women, to break the bodies of all white people and bring them low, as low as that dust into which he himself has been and is being trampled..."

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