Deep learning in Rust with Burn 🔥

Practical AI: Machine Learning, Data Science, LLM

It seems like everyone is interested in Rust these days. Even the most popular Python linter, Ruff, isn’t written in Python! It’s written in Rust. But what is the state of training or inferencing deep learning models in Rust? In this episode, we are joined by Nathaniel Simard, the creator burn. We discuss Rust in general, the need to have support for AI in multiple languages, and the current state of doing “AI things” in Rust.

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Sponsors:

• Neo4j – NODES 2023 is coming in October!
• Fastly – Our bandwidth partner. Fastly powers fast, secure, and scalable digital experiences. Move beyond your content delivery network to their powerful edge cloud platform. Learn more at fastly.com
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Featuring:

• Nathaniel Simard – Twitter, GitHub, LinkedIn
• Chris Benson – Twitter, GitHub, LinkedIn, Website
• Daniel Whitenack – Twitter, GitHub, Website

Show Notes:

burn-rs: This library strives to serve as a comprehensive deep learning framework, offering exceptional flexibility and written in Rust.

Something missing or broken? PRs welcome!

Bab

1. Welcome to Practical AI (00:00:00)

2. Sponsor: Neo4j (00:00:35)

https://www.neo4j.com/nodes-2023?utm_source=Changelogpodcast&utm_medium=nl&utm_campaign=Nodes&utm_content=Ad-1

3. Nathaniel Simard & Burn (00:01:43)

4. What is Rust? (00:03:02)

5. Go & Rust (00:04:53)

6. Not so low-level (00:05:52)

7. Rust features (00:07:18)

8. Rust workflow (00:09:43)

9. The Rust community (00:13:33)

10. The reason for Burn (00:14:45)

11. Rust ecosystem (00:17:17)

12. Challenges in Rust (00:18:42)

13. Low-level advantage (00:21:04)

14. Current Burn support (00:22:28)

15. What are people using Burn for? (00:23:38)

16. Organizing Burn development (00:25:15)

17. Pushing the limits (00:26:26)

18. Burn features (00:28:50)

19. Versatile backends (00:30:28)

20. The Burn book (00:31:51)

21. Where users come from (00:32:42)

22. Newbie PoV of Burn (00:34:01)

23. Future of Burn (00:36:16)

24. Getting started (00:38:05)

25. Thanks for joining us (00:39:16)

26. Outro (Changelog Beats!) (00:39:45)

https://changelog.com/posts/introducing-changelog-beats