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This video explores the next generation of Chain-of-Thoughts (CoT) combined with Chain-of-Actions (CoA) for autonomous tool use in AI systems. Dive into how AI can interrupt reasoning processes, code virtual experiments in Python or C++, and incorporate numerical results back into reasoning complexity. Learn about Large Agent Models (LAM) through a comprehensive examination of multiple specially designed training datasets and a five-step training process that includes reinforcement learning. Discover the potential of Deep Research - Phase 2 with autonomous function calling without templates and deep reasoning that goes beyond linear CoT. Consider whether this represents the perfect PhD "Agent" for solving complex problems. The content is based on research from "AGENT MODELS: INTERNALIZING CHAIN-OF-ACTION GENERATION INTO REASONING MODELS" by researchers from Beijing Jiaotong University.
