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Fine-tuning vs RAG
Manage episode 376214580 series 2385063
In this episode we welcome back our good friend Demetrios from the MLOps Community to discuss fine-tuning vs. retrieval augmented generation. Along the way, we also chat about OpenAI Enterprise, results from the MLOps Community LLM survey, and the orchestration and evaluation of generative AI workloads.
Changelog++ members save 1 minute on this episode because they made the ads disappear. Join today!
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!
Featuring:
- Demetrios Brinkmann – Twitter
- Chris Benson – Twitter, GitHub, LinkedIn, Website
- Daniel Whitenack – Twitter, GitHub, Website
Show Notes:
Something missing or broken? PRs welcome!
Rozdziały
1. Welcome to Practical AI (00:00:07)
2. Practical AI & Friends (00:00:43)
3. Look into MLOps community (00:02:01)
4. Changes in the AI community (00:04:19)
5. Finding the norm (00:07:34)
6. Matching models & uses (00:08:30)
7. Stages of debugging (00:11:21)
8. Layer orchestration (00:13:10)
9. Practical hot takes (00:16:26)
10. Fine-tuning is more work (00:21:46)
11. Retrieval augmented generation (00:24:13)
12. MLOps survey (00:31:23)
13. The next survey (00:38:09)
14. Enterprise hypetrain (00:41:50)
15. OpenAI & your data (00:42:39)
16. AI vendor lock-in? (00:43:19)
17. Now what do we do? (00:47:44)
18. Hype in the AI life (00:48:58)
19. Goodbye (00:56:35)
20. Outro (00:57:23)
293 odcinków
Manage episode 376214580 series 2385063
In this episode we welcome back our good friend Demetrios from the MLOps Community to discuss fine-tuning vs. retrieval augmented generation. Along the way, we also chat about OpenAI Enterprise, results from the MLOps Community LLM survey, and the orchestration and evaluation of generative AI workloads.
Changelog++ members save 1 minute on this episode because they made the ads disappear. Join today!
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!
Featuring:
- Demetrios Brinkmann – Twitter
- Chris Benson – Twitter, GitHub, LinkedIn, Website
- Daniel Whitenack – Twitter, GitHub, Website
Show Notes:
Something missing or broken? PRs welcome!
Rozdziały
1. Welcome to Practical AI (00:00:07)
2. Practical AI & Friends (00:00:43)
3. Look into MLOps community (00:02:01)
4. Changes in the AI community (00:04:19)
5. Finding the norm (00:07:34)
6. Matching models & uses (00:08:30)
7. Stages of debugging (00:11:21)
8. Layer orchestration (00:13:10)
9. Practical hot takes (00:16:26)
10. Fine-tuning is more work (00:21:46)
11. Retrieval augmented generation (00:24:13)
12. MLOps survey (00:31:23)
13. The next survey (00:38:09)
14. Enterprise hypetrain (00:41:50)
15. OpenAI & your data (00:42:39)
16. AI vendor lock-in? (00:43:19)
17. Now what do we do? (00:47:44)
18. Hype in the AI life (00:48:58)
19. Goodbye (00:56:35)
20. Outro (00:57:23)
293 odcinków
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