679: Creator of Swift, Tesla Autopilot & Tensorflow. New AI language Mojo with Chris Lattner
Oct 13, 2023
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Chris Lattner, the mastermind behind the Swift programming language and key AI developer, discusses his latest creation, Mojo, a new programming language tailored for AI development. He shares insights on the importance of simplifying machine learning for developers and the future of programming languages. Lattner reflects on Python's role in AI, the innovative use of emojis in file extensions, and how Mojo aims to revolutionize AI model training. Plus, he weighs in on how AI is transforming developer roles, enhancing roles rather than replacing them.
Mojo is a new Python programming language that aims to make machine learning and AI more accessible to developers.
Mojo aims to bridge the gap between high-level language Python and new hardware technologies like GPUs, enabling Python programmers to achieve better performance with the new generation of hardware.
Mojo supports both static compilation for small binary files and runtime interpretation with just-in-time compilation, providing flexibility and performance benefits for developers in AI and machine learning.
Deep dives
The Importance of Mojo: A New Python Programming Language
Mojo is a new Python programming language that aims to make machine learning and AI more accessible to developers. It focuses on making it easier for developers to work with lower-level, harder aspects of machine learning by providing higher-level abstractions and a more powerful language. The goal is to unlock the potential of new hardware and make it as easy to use as Python or JavaScript. Mojo aims to be compatible with the existing Python ecosystem and allows Python developers to learn and use the new language without having to switch to a different stack.
The Power of AI Hardware and the Need for Higher-Level Programming Languages
The podcast discusses the shift in the AI world towards new kinds of hardware, such as GPUs, that require higher-level programming languages. While JavaScript is a powerful language for web development, it is not ideal for running on hardware like GPUs. Mojo aims to bridge this gap by enabling Python programmers to take advantage of the new hardware and achieve better performance. By using Python as a base language, Mojo allows for seamless integration with the existing Python ecosystem, making it easier for developers to transition and benefit from the new generation of hardware.
The Evolution of AI and Graphics Hardware
The podcast explores how the world of AI and graphics hardware, such as GPUs, has evolved. NVIDIA, with its parallel architecture originally designed for graphics processing, discovered that its GPUs could also be used effectively for AI and machine learning computations. This led to the development of new specialized chips and hardware for AI. The podcast highlights the need for high-level programming languages that can harness the power of these new hardware technologies. Mojo aims to fill this need by providing a Python-like language that can run on this new generation of hardware and scale across different devices.
Interpreted vs Compiled Languages and Mojo's Approach
The podcast discusses the difference between interpreted and compiled languages and explains how Mojo supports both approaches. Mojo can be statically compiled, resulting in small binary files, or it can be interpreted at runtime, using just-in-time compilation for high performance. The aim is to provide a language that offers the flexibility and dynamic features of an interpreted language like Python, with the performance benefits of a compiled language. Mojo's approach allows developers to choose the best option depending on their specific needs and use cases.
The Mojo Programming Language and its Role in the AI Community
The podcast introduces Mojo as a new programming language built in the Python family. Mojo aims to address the challenges of performance and integration in the Python ecosystem, particularly when it comes to AI and machine learning. By providing the ability to add types and lower-level concepts, Mojo allows Python programmers to write high-performance code without switching to a different language or framework. Mojo's compatibility with existing Python libraries and its focus on achieving better performance make it an exciting addition to the AI community, providing developers with new tools and opportunities.
In this supper club episode of Syntax, Wes and Scott talk with Chris Lattner about Mojo, a new programming language for AI developers. Should developers learn Python? Where does Mojo run? What is Chris excited about in AI’s future?
