Chris Lattner

Well, so what I want, I mean, coming back to my arch nemesis, right?

It's complexity, right?

So again, me being the optimist, if we drive down complexity, we can make these tools, these technologies, these cool hardware widgets accessible to way more people.

And so what I'd love to see is more personalized experiences, more things, the research getting into production instead of being lost at NeurIPS.

And these things that impact people's lives by entering products.

And so one of the things that I'm a little bit concerned about is right now, the big companies are investing huge amounts of money and are driving the top line of AI capability forward really quickly.

But if it means that you have to have $100 million to train a model or more, $100 billion, right?

Well, that's going to make it very concentrated with very few people in the world that can actually do this stuff.

I would much rather see lots of people across the industry

be able to participate and use this, right?

And you look at this, you know, I mean, a lot of great research has been done in the health world and looking at like detecting pathologies and doing radiology with AI and like doing all these things.

Well, the problem today is that to deploy and build these systems, you have to be an expert in radiology and an expert in AI and,

And if we can break down the barriers so that more people can use AI techniques, and it's more like programming Python, which roughly everybody can do if they want to, then I think that we'll get a lot more practical application of these techniques and a lot more nichier, cool, but narrower domains.

And I think that's going to be really cool.

Well, so I think we'll have more programmers, but they may not consider themselves to be programmers.

That'd be a different name for it.

Right.

I mean, do you consider somebody that uses, you know, I think that arguably the most popular programming language is Excel.

Yeah.

And so do they consider themselves to be programmers?