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Karpathy’s Pelican

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Re: Karpathy’s Pelican

#221

Post by sapal »

NewJazz wrote: post #205
jcims wrote: post #202

I’d like to see a human one shot a pelican on a bicycle in raw svg.

What do you mean by "oneshot"? The term applied to genai makes sense, but it doesn't make a whole lot of sense to apply the term to human art.

I understand it as “write SVG, say when you are done and only then you are allowed to see the rendered result”. Multiple shots would be either “you get more than one try, we'll pick the best” or “you can see the rendered result and iterate” (or maybe that would be “model + harness with tools”?)

Re: Karpathy’s Pelican

#223

Post by mvdtnz »

anigbrowl wrote: post #207
dundarious wrote: post #51

I can forgive the modeling being godawful jank (windows floating in the air, disconnected from the house). But I expected it to have a better understanding of the text. Instead, we have Bilbo's "disappearance" interpreted as him magically transporting or cloaking, and similarly for his reappearance.

But this only seems wrong to you because you're familiar with the prior context. When there's only a single paragraph to work from, and it's a drily humorous text, why not employ comic literalism and lean into the perplexity with which his neighbors viewed him?

The LLM has access to the full text and every translation of it ever produced, both in its corpus and on the searchable web.

Re: Karpathy’s Pelican

#224

Post by nozzlegear »

nozzlegear wrote: post #195
gegtik wrote: post #165

Earlier quoted context omitted.

Maybe that makes them human.. https://www.booooooom.com/2016/05/09/bicycles-built-based-on...

Humans aren't machines trained on the entire stolen corpus of human knowledge. We expect that a human will do poorly at arbitrary tasks they have no experience doing – especially drawing, which many (most?) humans aren't trained in at all. The same isn't true of AI, where its proponents, priests and proselytizers have spent time, energy and billions of dollars attempting to convince us it can do anything better than…

Pelican enjoyers didn't like this one lol

Re: Karpathy’s Pelican

#225

Post by levocardia »

HarHarVeryFunny wrote: post #47

It seems pretty clear that Anthropic models have been specifically trained to be good at generating three.js (JavaScript 3-D Graphics) code, so given current state of AI code generation in general, I don't find three.js models/animations as indicative of anything other than the model's ability to write three.js code. When Fable was first released the day-1 demos of it on Twitter (presumably from people who were given…

I don't think so. I've used Claude to generate 3D animations in python purely by making and manipulating raw meshes, and I've had great results. A more likely explanation is that 3D graphics is just pretty straightforward matrix algebra, and models (or Claude specifically) has that down cold.

Re: Karpathy’s Pelican

#226

Post by singron »

matsemann wrote: post #41

I'm pretty tired of the "Y made this game in Z tokens" all over the internet last week. They look impressive, and it's cool that it's even possible, but they're useless as games. None of them are any fun. They're like the most boring variant of basic controllers you can imagine. None have any cool mechanics. None have any tweaks made from hours and hours of testing. All have the same cel-shader.

I've heard this called a "dancing bear" before. It's interesting because it's a bear dancing, not because the dancing is any good.

These conversations get frustrating since one group is saying the dancing is bad, a second group is saying it's good (for a bear), and a third group is saying we are a few years from a bear-only dancing industry.

Re: Karpathy’s Pelican

#227

Post by Demiurge »

YmiYugy wrote: post #172

I don't think it's a bad way to benchmark new models, I just find it concerning that the author implies that "pelican on a bicycle" has been exhausted. At the risk of making overly broad, unfalsifiable claims I think multi-year exposure to AI content has dramatically raised our expectations for speed and volume but lowered them for quality. We see a very janky pelican and declare the problem solved.

Also, one of the advantages of the pelican test is that you can evaluate it all at once. There’s no reason the two-dimensional depiction can’t be made more challenging. Yes, at some point the pelicans might approach the subjectivity of a fine art painting, but we haven’t even seen a depiction that’s competent by the standards of a high school art class. That’s not to say the elementary school–level SVGs aren’t amazing - rather, I agree with your point.

Re: Karpathy’s Pelican

#228

Post by BobbyJo »

YmiYugy wrote: post #172

I don't think it's a bad way to benchmark new models, I just find it concerning that the author implies that "pelican on a bicycle" has been exhausted. At the risk of making overly broad, unfalsifiable claims I think multi-year exposure to AI content has dramatically raised our expectations for speed and volume but lowered them for quality. We see a very janky pelican and declare the problem solved.

I think it's touching the limit of what one can reasonably expect any intelligent thing to produce with the only direction being "produce an svg of a pelican riding a bicycle".

When you aren't sure if an LLM can write an svg well, or that it will be able to form a pelican shape, or animate a bicycle, it's a good test. After that, it's all judgement: how detailed should the pelican be? pelicans are the wrong shape for a bicycle by default, so how much can I change its physiology to match using a bicycle before it isn't a pelican? Do I care about how well the client is able to render complex geometry?

It's not that there isn't room to do better, or that it doesn't tell you anything at all, but rather we've reached a point where what it tells us isn't very clear anymore.

Re: Karpathy’s Pelican

#229

Post by fasterik »

beepbooptheory wrote: post #215
fasterik wrote: post #190

Earlier quoted context omitted.

Because the degree of realism in a video is determined by implicit knowledge of concepts like "in front of", "behind", "next to", "inside", "outside", "between", "occluded by", etc. as well as distances, angles, and the relative size of objects when viewed from a perspective.

I guess I just don't have an intuition for why that is different from what it does for non-"spatial" things. Like the fact that it works is still because it produced the code it did token by token. Whether its dealing with, e.g., " beside the rock" or " in the array", it's doing the same kind of inferential activity.

>Whether its dealing with, e.g., "beside the rock" or "in the array", it's doing the same kind of inferential activity.

Are you sure about that? Presumably the spatial concept of "inside" and the computer memory concept of "inside" have different contextual embeddings in an LLM, not so different from how our brains have different neural activation patterns when we use different concepts. Unless you think that "the same kind of inferential activity" also applies to human neurons firing.

Re: Karpathy’s Pelican

#230

Post by toasty228 »

baron816 wrote: post #11

IMO, the area where AI is going to be most useful over the next couple years is in developing manufacturing processes top to bottom. Maybe a million token budget is too small, but something like "design me a sneaker and all the equipment to manufacture it autonomously".

Is anyone genuinely excited about these kind of scenarios?
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