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Automating code optimization with LLMs episode artwork

Aug 29, 2023 44 min

Automating code optimization with LLMs

from Practical AI Hosted by Daniel Whitenack and Chris Benson

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. Sponsors: 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 Fly.io – The home of Changelog.com — Deploy your apps and databases close to your users. In minutes you can run your Ruby, Go, Node, Deno, Python, or Elixir app (and databases!) all over the world. No ops required. Learn more at fly.io/changelog and check out the speedrun in their docs. Typesense – Lightning fast, globally distributed Search-as-a-Service that runs in memory. You literally can’t get any faster! Changelog News – A podcast+newsletter combo that’s brief, entertaining & always on-point. Subscribe today. Featuring: Mike Basios – LinkedIn, X Chris Benson – Website, GitHub, LinkedIn, X Daniel Whitenack – Website, GitHub, X Show Notes: TurinTech AI Upcoming Events: Register for upcoming webinars here!

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Automating code optimization with LLMs

0:00 44:59

Chapters

  1. 0:07 Welcome to Practical AI
  2. 0:43 Code optimizing with Mike Basios
  3. 3:18 Solving code
  4. 7:23 The AI code ecosystem
  5. 10:41 Other targets
  6. 12:58 AI rephrasing?
  7. 15:27 Sponsor: Changelog News
  8. 16:40 State of current models
  9. 20:30 Improvements to devs
  10. 22:31 Managing your AI intern
  11. 25:09 Custom LLM models
  12. 29:48 Biggest challenges
  13. 33:19 Hallucination & optimization
  14. 35:41 Test chaining?
  15. 39:09 LLM workflow
  16. 41:24 Most exciting developments
  17. 43:40 Looking forward to faster code
  18. 44:13 Outro

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This episode is 44 minutes long.

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This episode was published on August 29, 2023.

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