Chris Lattner: evaluation

Transcript context

…right? But turn on its head, where instead of being objects and C, it's like what people think of as Python, like a very high-level dynamic, flexible programming model, but then it's also glued onto C for the execution layer, right? And so you look at something like NumPy has a very nice Python layer, or even TensorFlow or PyTorch, very nice Python layer, but underneath the covers, it's all C is C++. And so a lot of what we're doing in Mojo is, you know, we learned a lot from Swift and things like this, but it's kind of conceptually similar, where what you're doing is you're saying, cool, it's not about whether dynamics good or static is good. They're both good. They're good for different problems. So let's put them together in a consistent thing and allow you to reach for the right answer for a given problem instead of being religious about it, like dynamic typing is the right answer, right? Just say like, cool, dynamic typing is great. We can see all the benefits. A lot of people love this and it's super productive and expressive. But if you want better performance, you can reach for static typing, right? And so a lot of, I think what Mojo is, is it's progressive in terms of like, get out of arguing about stupid things that don't matter. Just let people solve problems, right? And I think that is hopefully what people see in it. Now, I mean, we can dive into other things. So Mojo learns from Rust, for example. Rust is a wonderful community with a lot of cool stuff going on. It's kind of hard to learn. And so can we take the type system innovations like lifetimes and features like that, pull them forward into a thing and make them easier to learn? If so, then we get a lot of the benefits of the safety and the other things that Rust gives and performance and all the good things, no garbage collector,…

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