Unverified50% confidenceOpinionExact time
工具调用和RAG是从聊天机器人迈向能干活的Agent的分水岭
1
Sources
50%
Confidence
Long-term
Relevance
7/12/2026
First Seen
Sources
AI Agent学习路径:从0到1系统掌握智能体开发
bilibiliAgent搭建7/11/2026
Related Claims
UnverifiedCompany Brain的技术实现与检索增强生成(RAG)密切相关,将Agent运行轨迹作为结构化知识持续写入70% similarUnverified聊天机器人通常是无状态的,而Agent需要跨越多轮甚至多个会话维护任务状态,催生了LangGraph、AutoGen等状态管理框架68% similarPartially VerifiedAgentic RAG的核心思想是将RAG中的各个环节封装成可调用的工具(Tool),并赋予大模型自主决策的能力67% similarUnverified吴恩达主导的团队正在探索将大模型驱动的Agent与机器人硬件结合的具身智能方向67% similarUnverified团队构建的Build Your Own Expert Bot框架采用RAG架构,从医生策划的知识库检索文档,超出覆盖范围时返回'不知道'66% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/492626API
curl https://kongchang.com/api/v1/knowledge/claims/492626MCP
get_claim(id=492626)