Automating code optimization with LLMs

Practical AI

You might have heard a lot about code generation tools using AI, but could LLMs and generative AI make our existing code better? In this episode, we sit down with Mike from TurinTech to hear about practical code optimizations using AI “translation” of slow to fast code. We learn about their process for accomplishing this task along with impressive results when automated code optimization is run on existing open source projects.

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Featuring:

• Mike Basios – LinkedIn, X
• Chris Benson – Website, GitHub, LinkedIn, X
• Daniel Whitenack – Website, GitHub, X

Show Notes:

• TurinTech AI

Something missing or broken? PRs welcome!

챕터

1. Welcome to Practical AI (00:00:07)

2. Code optimizing with Mike Basios (00:00:43)

3. Solving code (00:03:19)

4. The AI code ecosystem (00:07:24)

5. Other targets (00:10:41)

6. AI rephrasing? (00:12:58)

7. Sponsor: Changelog News (00:15:28)

https://changelog.com/news

8. State of current models (00:16:40)

9. Improvements to devs (00:20:31)

10. Managing your AI intern (00:22:31)

11. Custom LLM models (00:25:09)

12. Biggest challenges (00:29:49)

13. Hallucination & optimization (00:33:19)

14. Test chaining? (00:35:42)

15. LLM workflow (00:39:09)

16. Most exciting developments (00:41:25)

17. Looking forward to faster code (00:43:40)

18. Outro (00:44:14)