One Nvidia A100. From the paper : > We train using the AdamW [26] optimizer with a batch size of 5 and gradient accumulation over 20 steps on a single NVIDIA A100 GPU So it's "consumer-grade" because it's available to anyone, not just businesses.
That is the training gpu… the inference gpu can be much smaller.
The devil's in the details as always. A "cartoon of a cat eating an icecream on a unicycle" doesn't bring back any of the 6-pawed mutant cats riding a unicycle, etc. Still, impressive speed.
It gave me plenty of cats with 3 front paws though
My favorite test of image models: Drawing of the inside of a cylinder. That's usually bad enough. Then try to specify size, and specify things you want to place inside the cylinder relative to the specified size. (e.g. try to approximate an O'Neill cylinder) I love generative AI models, but they're really bad at that, and this one is no exception, but the speed makes playing around with prompt variations to try to se…
I have a favourite test for LLMs that is also still surprisingly not passed by many: You walk up to a glass door. It has 'push' written on it in mirror writing. What should you do and why. Very few can get it right, even fewer can get it right and explain the right reason. They’ll start going on about how mirror writing is secret writing and push written backwards is code for pull, rather than just that it’s a messag…
Honestly, if you’ve accurately reproduced your prompt, I had trouble interpreting it initially too. “written on it in mirror writing” is quite ambiguous. Are the letters reflective, but on my side of the door? Is there a mirror with handwriting in it somehow? Oh… does it mean “push is written on the other side of the glass, facing away, so that the writing appears backwards, or mirrored”?