Mojo is a superset of Python's existing typing system. It lets you define variables and use them in strict ways to get more predictability. Mojo can be retrofitted into existing Python code, but it requires some work on the part of programmers who are not used to this kind of thing.
Chris Lattner is a legendary software and hardware engineer, leading projects at Apple, Tesla, Google, SiFive, and Modular AI, including the development of Swift, LLVM, Clang, MLIR, CIRCT, TPUs, and Mojo. Please support this podcast by checking out our sponsors:
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EPISODE LINKS:
Chris’s Twitter: https://twitter.com/clattner_llvm
Chris’s Website: http://nondot.org/sabre/
Mojo programming language: https://www.modular.com/mojo
Modular AI: https://modular.com/
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OUTLINE:
Here’s the timestamps for the episode. On some podcast players you should be able to click the timestamp to jump to that time.
(00:00) – Introduction
(06:38) – Mojo programming language
(16:55) – Code indentation
(25:22) – The power of autotuning
(35:12) – Typed programming languages
(51:56) – Immutability
(1:04:14) – Distributed deployment
(1:38:41) – Mojo vs CPython
(1:54:30) – Guido van Rossum
(2:01:31) – Mojo vs PyTorch vs TensorFlow
(2:04:55) – Swift programming language
(2:10:27) – Julia programming language
(2:15:32) – Switching programming languages
(2:24:58) – Mojo playground
(2:29:48) – Jeremy Howard
(2:40:34) – Function overloading
(2:48:59) – Error vs Exception
(2:56:39) – Mojo roadmap
(3:09:41) – Building a company
(3:21:27) – ChatGPT
(3:27:50) – Danger of AI
(3:31:44) – Future of programming
(3:35:01) – Advice for young people
