Comment by fragmede

https://chatgpt.com/share/68def5c5-8ca4-8009-bbca-feabbe0651...

Man'o'war on a pyrosome. I don't what you expected it to look like, maybe it could be more whiteish translucent instead of orange, but it looks fairly reasonable to me. Took a bit over a minute with the ChatGPT app.

Simonw's test is for the text-only output from an LLM to write an SVG, not "can a multimodal AI in 2025" generate a PNG. By having pictures of pelicans on bicycles in the training data in PNG format, from people wanting to see one, after reading his blog, there are now raster-based images from an image generation model that fairly convincingly look as described in the training data. Now that there's PNGs of pelicans on bicycles, we would expect GPT-6 to be better at generating SVGs of something it's already "seen".

We don't know what simonw's secret combo X and Y is, nor do I want to know, because that would ruin the benchmark (if it isn't ruined already by virtue of him having asked it). 200k nouns is definitely high though. A bit of thought could cut it down to exclude concepts and lot of other things. How much spare GPU capacity OpenAI has, I have no idea. But if I were there, I'd want the GPUs to be running as hot as the cloud provider would let me run them, because they're paying per hour, not per watt, and have a low-priority queue of jobs for employees to generate whatever extra training data they can think of on their off hours.

Oh and here's the pelican PNG so the other platforms can crawl this comment and slurp it up.

https://chatgpt.com/share/68def958-3008-8009-91fa-99127fc053...