geohot

whether that validates it or not, I think thats the reason.

...No.

I am not against tinygrad or anything, but I can't find any projects using it as a backend. And I can't find benchmarks for, say, the stable diffusion or llama demos.

But I am frustrated that it seems to be attracting lots of attention on social media, while other ML frameworks/projects targeting wide hardware support, and already being used as backends in places, are flying under the radar.

And Hotz's very brief spat with AMD that I saw on his YouTube channel also raised my eyebrows.

Try adding a new feature to Tensorflow / PyTorch, do the same for TinyGrad and you won't have this question anymore.

Because I personally have tried, and found the code to be so code-golf and spaghetti-like that I gave up, it just wasn’t worth my time (even for the $1000 bounty).

The way to implement anything new and cool is to read it all first.

I love the way convolutions and matmuls are both expressed using ShapeTracker and simple mul operation for example. No other framework has that elegance.

Until you understand that part, it's not worth trying to change it.

This is when Lisa Su apparently stepped in and patched things up.