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LangChain’s Harrison Chase on Building the Orchestration Layer for AI Agents
Jun 18, 2024
49:50
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Harrison Chase of LangChain focuses on enabling the orchestration layer for AI agents. He discusses the evolution of agents, impact on work and creativity, challenges in AI models, and solutions in LangChain. The conversation explores the role of cognitive architectures, fine tuning, and leadership reflections in the AI field.
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Quick takeaways
- Agents in AI shift towards LLM-led control of application flow, breaking from preset steps.
- LangChain's orchestration layer empowers agents to balance autonomy and structured decision-making effectively.
Deep dives
Definition of Agents in AI
Agents in AI are defined as instances where a large language model (LLM) takes charge of controlling the application's flow, deviating from the conventional preset steps to letting the LLM decide the sequence of actions.
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