Python is the dominant language for AI and data science applications, but it lacks the performance and low-level control needed to fully leverage GPU hardware.

As a result, developers often rely on NVIDIA's CUDA framework, which adds complexity and fragments the development stack.

Mojo is a new programming language designed to combine the simplicity of Python with the performance of C and the safety of Rust.

It also aims to provide a vendor-independent approach to GPU programming.

Mojo is being developed by Chris Latner, a renowned systems engineer known for his seminal contributions to computer science, including LLVM, the C-Lang Compiler, and the

Swift programming language. Chris is the CEO and co-founder of Modular AI, the company behind Mojo.

In this episode, he joins the show to discuss his engineering journey and his current work

on AI infrastructure and the Mojo language.

Kevin Ball, or K. Ball, is the vice president of engineering at Mento and an independent

coach for engineers and engineering leaders. He co-founded and served as CTO for two companies,

founded the San Diego JavaScript meetup, and organizes the AI inaction discussion group through

latent space.

Check out the show notes to follow KBall on Twitter or LinkedIn or visit his website,

kball.l. LLC.

Chris, welcome to the show.

Thank you for having me.

I'm excited to be here.

I must say, I'm so excited to hang out with you because you have such a history in an area that is fascinating to me, which is language design. but in particular, language design for the current

age that we're in around AI and machine learning. So excited to dig in, but let's first have you

introduce yourself a little bit to our audience, who you are, your background, and what brought you

here? Sure. Well, so I have, I guess, two epochs to my professional career. Epok one,

known for CPU programming stuff and developer tools.

...