Comment by thatwasunusual
11 hours ago
> We are getting to the point that its not unreasonable to think that "Generate an SVG of a pelican riding a bicycle" could be included in some training data.
I may be stupid, but _why_ is this prompt used as a benchmark? I mean, pelicans _can't_ ride a bicycle, so why is it important for "AI" to show that they can (at least visually)?
The "wine glass problem"[0] - and probably others - seems to me to be a lot more relevant...?
[0] https://medium.com/@joe.richardson.iii/the-curious-case-of-t...
The fact that pelicans can't ride bicycles is pretty much the point of the benchmark! Asking an LLM to draw something that's physically impossible means it can't just "get it right" - seeing how different models (especially at different sizes) handle the problem is surprisingly interesting.
Honestly though, the benchmark was originally meant to be a stupid joke.
I only started taking it slightly more seriously about six months ago, when I noticed that the quality of the pelican drawings really did correspond quite closely to how generally good the underlying models were.
If a model draws a really good picture of a pelican riding a bicycle there's a solid chance it will be great at all sorts of other things. I wish I could explain why that was!
If you start here and scroll through and look at the progression of pelican on bicycle images it's honestly spooky how well they match the vibes of the models they represent: https://simonwillison.net/2025/Jun/6/six-months-in-llms/#ai-...
So ever since then I've continue to get models to draw pelicans. I certainly wouldn't suggest anyone take serious decisions on model usage based on my stupid benchmark, but it's a fun first-day initial impression thing and it appears to be a useful signal for which models are worth diving into in more detail.
> If a model draws a really good picture of a pelican riding a bicycle there's a solid chance it will be great at all sorts of other things.
Why?
If I hired a worker that was really good at drawing pelicans riding a bike, it wouldn't tell me anything about his/her other qualities?!
For better or worse, a lot of job interviews actually do use contrived questions like this, such as the infamous "how many golf balls can you fit in a 747?"
Your comment is funny, but please note: it's not drawing a pelican riding a bike, it's describing in SVG a pelican riding a bike. Your candidate would at least displays some knowledge of the SVG specs.
The difference is that the worker you hire would be a human being and not a large matrix multiplication that had parameters optimized by a a gradient descent process and embeds concepts in a higher dimensional vector space that results in all sorts of weird things like subliminal learning (https://alignment.anthropic.com/2025/subliminal-learning/).
It's not a human intelligence - it's a totally different thing, so why would the same test that you use to evaluate human abilities apply here?
Also more directly the "all sorts of other things" we want llms to be good at often involve writing code/spatial reasoning/world understanding which creating an svg of a pelican riding a bicycle very very directly evaluates so it's not even that surprising?
I wish I knew why. I didn't think it would be a useful indicator of model skills at all when I started doing it, but over time the pattern has held that performance on pelican riding a bicycle is a good indicator of performance on other tasks.
a posteriori knowledge. the pelican isn't the point, it's just amusing. the point is that Simon has seen a correlation between this skill and and the model's general capabilities.
It's not nessessarily the best benchmark, it's a popular one, probably because it's funny.
Yes it's like the wine glass thing.
Also it's kind of got depth. Does it draw the pelican and the bicycle? Can the penguin reach the peddles? How?
I can imagine a really good AI finding a funny or creative or realistic way for the penguin to reach the peddles.
An slightly worse AI will do an OK job, maybe just making the bike small or the legs too long.
An OK AI will draw a penguin on top of a bicycle and just call it a day.
It's not as binary as the wine glass example.
> It's not nessessarily the best benchmark, it's a popular one, probably because it's funny.
> Yes it's like the wine glass thing.
No, it's not!
That's part of my point; the wine glass scenario is a _realistic_ scenario. The pelican riding a bike is not. It's a _huge_ difference. Why should we measure intelligence (...) in regards to something that is realistic and something that is unrealistic?
I just don't get it.
> the wine glass scenario is a _realistic_ scenario
It is unrealistic because if you go to a restaurant, you don't get served a glass like that. It is frowned upon (alcohol is a drug, after all) and impractical (wine stains are annoying) to fill a glass of wine as such.
A pelican riding a bike, on the other hand, is realistic in a scenario because of TV for children. Example from 1950's animation/comic involving a pelican [1].
[1] https://en.wikipedia.org/wiki/The_Adventures_of_Paddy_the_Pe...
If the thing we're measuring is a the ability to write code, visually reason, and handle extrapolating to out of sample prompts, then why shouldn't we evaluate it by asking it to write code to generate a strange image that it wouldn't have seen in its training data?