Raza Habib is on the front lines of LLM implementation as CEO of Humanloop, a Y Combinator backed startup that helps companies of all kinds, small and large bridge the gap from API access to successful LLM deployment. Nathan sat down with Raza to hear what he has learned in the process of helping so many companies on their LLM implementation journeys – and he did not disappoint – as you'll hear, he shared a bunch of concrete examples of customer use cases, practical challenges that people face, and the strategies they use to overcome them.
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TIMESTAMPS:
(00:00) Preview of episode
(07:00) Humanloop’s mission and surprising customer base
(12:10) Why a language model is so advantageous
(15:00) Customization and understanding model performance
(18:14) Sponsor: Omneky
(18:35) Users graduating from playground experimentation to develop robust implementations
(23:25) Raza’s two mental models for using AI
(27:50) How customers are actually integrating API
(31:50) Challenge of evaluation and feedback
(43:33) Prediction: more fine tuning in the immediate future
(47:00) RLHF myth-busting
(57:12) Robust agents need feedback loops
(1:02:27) AI productization challenges
(01:07:32) Adopt or die moment for incumbents
(01:11:19) Fast iteration cycles
(1:15:45) Rapid fire questions for The Cognitive Revolution guests
TWITTER:
@CogRev_Podcast
@RazRazcle (Raza)
@labenz (Nathan)
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