Discover how companies like LinkedIn and Uber are building sophisticated AI agents with LangGraph, a revolutionary framework that treats agents as persistent workflows rather than simple conversations.
LangGraph: Rethinking AI Agent Architectureのベスト引用
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Traditional agent frameworks were built around linear chains, but real production agents need to be persistent, long-running workflows that can pause, resume, and even bring humans into the loop when needed.
Discover how LLMs have evolved from text generators to action-taking AI agents. Learn the neural architecture behind these systems and how to build your own agents that can understand goals and execute complex tasks autonomously.
Discover how to design agentic AI systems that transform data analysis through autonomous workflows, reflection capabilities, and multi-agent collaboration—essential knowledge for building powerful analytical systems.
Stop settling for simple chat responses. Learn how to build autonomous agent architectures using ReAct loops and multi-agent teams to get real work done.
Chess legend Kasparov explores AI's potential, recounting his historic match against Deep Blue and envisioning a future of human-machine collaboration.