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Manage episode 440207794 series 3446189
Content provided by open.intel. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by open.intel or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://ppacc.player.fm/legal.
Katherine Druckman talks to fellow Intel Open Source Evangelist Ezequiel Lanza about building and deploying AI applications using Retrieval Augmented Generation. We break down RAG concepts and processes involved in providing additional context to general AI models for specialized use cases.
Guest:
Passionate about helping people discover the exciting world of artificial intelligence, Ezequiel Lanza is a frequent AI conference presenter and the creator of use cases, tutorials, and guides that help developers adopt open source AI tools.100 episodes
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Manage episode 440207794 series 3446189
Content provided by open.intel. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by open.intel or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://ppacc.player.fm/legal.
Katherine Druckman talks to fellow Intel Open Source Evangelist Ezequiel Lanza about building and deploying AI applications using Retrieval Augmented Generation. We break down RAG concepts and processes involved in providing additional context to general AI models for specialized use cases.
Guest:
Passionate about helping people discover the exciting world of artificial intelligence, Ezequiel Lanza is a frequent AI conference presenter and the creator of use cases, tutorials, and guides that help developers adopt open source AI tools.100 episodes
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