Jason Liu is a true Renaissance Man in the world of AI. He began his career working on traditional ML recommender systems at tech giants like Meta and Stitch Fix and quickly pivoted into LLMs app development when ChatGPT opened its API in 2022. As the creator of Instructor, a Python library that structures LLM outputs for RAG applications, Jason has made significant contributions to the AI community. Today, Jason is a sought-after speaker, course creator, and Fortune 500 advisor.

In this episode, we cut through the AI hype to explore effective strategies for building valuable AI products and discuss the future of AI across industries.

Chapters:
00:00 - Introduction and Background
08:55 - The Role of Iterative Development and Metrics

10:43 - The Importance of Hyperparameters and Experimentation

18:22 - Introducing Instructor: Ensuring Structured Outputs
20:26 - Use Cases for Instructor: Reports, Memos, and More
28:13 - Automating Research, Due Diligence, and Decision-Making
31:12 - Challenges and Limitations of Language Models
32:50 - Aligning Evaluation Metrics with Business Outcomes
35:09 - Improving Recommendation Systems and Search Algorithms
46:05 - The Future of AI and the Role of Engineers and Product Leaders
51:45 - The Raptor Paper: Organizing and Summarizing Text Chunks

I hope you enjoy the conversation and if you do, please subscribe!

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Humanloop is an Integrated Development Environment for Large Language Models. It enables product teams to develop LLM-based applications that are reliable and scalable. To find out more go to humanloop.com

Contrarian Guide to AI: Jason Liu on Betting Against Agents while Doubling Down on RAG & Fine-Tuning 55:27 Share

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Contrarian Guide to AI: Jason Liu on Betting Against Agents while Doubling Down on RAG & Fine-Tuning