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Learn to develop and implement multi-agent Large Language Model (LLM) systems through a comprehensive 41-minute tutorial that covers both theoretical concepts and practical Python implementations. Master the fundamentals of coding individual AI agents, orchestrating multiple agents, and establishing agent hierarchies for reasoning and control using GPT-4. Explore real-world applications including a fascinating simulation of presidential elections using multi-agent systems. Dive into official OpenAI Cookbook examples for function calling with chat models and knowledge retrieval, providing a solid foundation for building sophisticated AI agent architectures. Gain hands-on experience with cognitive science applications while understanding how to create effective communication and decision-making frameworks between multiple AI agents.
