Unsupervised Learning with Jacob Effron Ep 28: LangChain CEO Harrison Chase on the Current State of Eval and Agents and The LLM Apps that Will Define 2024
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Feb 20, 2024 
LangChain CEO Harrison Chase discusses AI evaluation, agent landscape, open vs. closed source models, and future of AI applications. Topics include LangSmith, AI in sports, evaluation practices, and the potential of open-source models. The podcast also explores the current AI landscape, deploying LangChain applications with LangServe, and the evolution of more complex chatbots.
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AI Sports Commentary Potential
- Creative applications like AI-generated sports commentary can personalize and scale engagement.
- This approach could revolutionize viewer experience without needing live commentators physically present.
Use Eval for Clarity
- Define clear expectations for your AI by creating and curating evaluation datasets early.
- Use evaluation as a forcing function to focus on desired system behaviors and user interactions.
Enterprise AI Focuses Internally
- Enterprises are building advanced AI assistants mostly for internal use today.
- These internal tools often involve platforms enabling users to create personalized chatbots linked to their own data.