Serverless GPUs

Practical AI: Machine Learning, Data Science

We’ve been hearing about “serverless” CPUs for some time, but it’s taken a while to get to serverless GPUs. In this episode, Erik from Banana explains why its taken so long, and he helps us understand how these new workflows are unlocking state-of-the-art AI for application developers. Forget about servers, but don’t forget to listen to this one!

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Featuring:

• Erik Dunteman – Twitter, GitHub, LinkedIn, Website
• Chris Benson – Twitter, GitHub, LinkedIn, Website
• Daniel Whitenack – Twitter, GitHub, Website

Show Notes:

Banana - Scale your machine learning inference and training on serverless GPUs.

Something missing or broken? PRs welcome!

Chương

1. Welcome to Practical AI (00:00:07)

2. Erik Dunteman (00:00:43)

3. What does serverless mean to you? (00:02:34)

4. What's the secret sauce? (00:07:17)

5. How does serverless affect our workflows? (00:09:30)

6. Sponsor: Changelog++ (00:13:21)

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7. What languages do you prefer? (00:14:21)

8. The Banana workflow (00:17:20)

9. The necessary minimum skills to use Banana (00:20:33)

10. A typical win (00:24:51)

11. Incompatible workflows (00:26:20)

12. Future Banana-AWS compatability? (00:30:11)

13. Tips to choose your GPU (00:32:53)

14. What's the future of serverless? (00:35:23)

15. Outro (00:37:46)