Chris Lattner: uncertainty

Transcript context

…Off the top of your head. Like, I think it's very useful when designing systems to have that list of principles. And I think you very much think of yourself as a first principles thinker, but I think your principles differ than most. And you've gained this insight over just studying a lot of AI work over the years. What are they? I don't know that I have one set of principles that I, you know, it's like one, one club that I go around and beat things with. But a lot of what we're trying to do is we're trying to unlock the latent potential of a lot of hardware and do so in a way that's super accessible. And so a lot of our starting conditions was not like enable a new thing. It's much more about drive out the complexity that people are struggling with to do the thing. And so it's not research. It's about design and engineering. Now, when you look at this, we're also driving from, okay, let's enable the maximum power of any given piece of hardware. So if you talk to an LLM company and they just spent $200 million on GPUs and their A100 GPUs of a specific memory size or whatever, right? They want to get everything possible out of that chip and they don't want a lowest common denominator solution. Right? And so you want, on the one hand, full power. You want to go all the way down to the metal and be able to unlock these things. And some of these researchers like, like tree and others, I mean, they're freaking amazing. Right?…

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