JAX

“The JAX team at Google got into a giant fight with the PyTorch team on Meta on X, and the heads of each company's respective AI division had to make a public truce and instruct their troops to stop fighting.”

“The only one who's managed to do this, I would say, is Google. They built their own chips, they built their own software around it called JAX, and then they built their own accelerated linear algebra library called XLA. And then, you know, they have their own …”

“I don't think there's any specific thing. In fact, I will try to be as, like, agnostic, like, I don't, like, I don't really say, like, okay, you need to learn JAX, you need to learn this, by the time you finish learning, there's a new framework out, anyway. So…”

“The Jaxx implementation just does not work on, on GPUs very well. Like, any naive setup that you do, like, it just won't run out of the box very easily”

“But I mean, in the meantime, I will say, you know, Google now does have a backup plan. You know, they have JAX, which was never a strategy. It was just a bunch of people who also recognized TensorFlow two as shit, and they just decided to build something else.”

“That was what I really wanted to do, is relaunch Jax. That was really what my first idea was, is to bring Jax back.”

“We actually, I think, published like, made a contribution to Jax to make it, like, 10 times faster to train Whisper.”