Keith Rabois

Well, he made this huge bet on this 100,000 GPU cluster.

People thought, wow, that's a lot.

Is it going to bear fruit?

Then he said, no, actually, I'm scaling it up to 250,000.

Then he said it's going to scale up to a million.

And what these results show is a general computational approach that doesn't require as much human labeling, can actually get to the answer and better answers faster.

That has huge implications.

Because if you think about all these other companies,

What has Lama been doing?

They just spent 15 billion to buy 49% of scale AI.

That's exactly a bet on human knowledge.

What is Gemini doing?

What is OpenAI doing?

What is Anthropic doing?

So all these things come into question.

And then the last thing I'll say is, if you look back, he made this bet once before, which was Tesla FSD versus Waymo.

And Tesla FSD only had cameras,

It didn't have LIDAR, but the bet was I'll just collect billions and billions of driving miles before anybody else does and apply general compute and it'll get to autonomy faster than the other more laborious and very expensive approach.

So I just think it's an incredible moment in technology where we see so many examples.

Travis is another one, what he's just talked about.