The Analytics Engineering Podcast The current state of the AI ecosystem (w/ Julia Schottenstein)
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Oct 6, 2024 Julia Schottenstein, an early employee at LangChain and former co-host of the show, dives into the powerful world of large language models. She shares insights on how LangChain is revolutionizing AI application development, highlighting its modular design that empowers developers. Julia explores the challenges of creating autonomous AI agents while ensuring quality and user experience. The conversation also speculates on future AI creativity and the pursuit of Artificial General Intelligence, balancing excitement with potential hurdles in the evolving AI ecosystem.
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Using LLMs to Test LLM Responses
- LLMs can be used to evaluate and grade responses of other LLMs as a form of testing.
- This 'LLM as judge' approach helps adapt engineering best practices to non-deterministic AI apps.
Iterative, Cyclic Workflow Design
- LangChain workflows can include cycles allowing retries and iterative improvement.
- Designing graphs carefully balances giving LLM flexibility while avoiding infinite loops is a key challenge.
Diverse LangChain Application Types
- Most LangChain use cases today are chat or retrieval augmented generation, but agentic apps automate decision-based workflows.
- Common applications include concierge search, co-pilots, and automation for repetitive tasks like summarization.