Tencent Hunyuan Releases AI Research System Hyra 2.0
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Tencent Hunyuan released the AI research system Hyra 2.0 on November 2, shifting its R&D focus from directly using AI to tackle scientific problems toward having general-purpose Agents participate in the development and upgrading of scientific models, research workflows, and software tools. The system splits research work into three layers—Overall, Mission, and Worker—and designs three separate storage mechanisms: project state, layered Agent memory, and a shared knowledge base called Books. During project retrospectives, transferable methods can be organized into skills for use in subsequent tasks. Previously, Hyra 1.0 drove open-source models to solve an open problem in additive combinatorics that had remained unresolved for over fifty years.
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The original text explains Hyra 2.0's three-layer Agent architecture along with its memory and knowledge base design, allowing readers to understand how research Agents shift from solving problems to building tools.
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腾讯混元发布Hyra 2.0：AI科研从“解题”转向“造工具”凤凰网科技下载客户端 独家抢先看2026年11月02日 20:51:43 来自北京市
凤凰网科技讯（编辑/宋淑美） 11月2日，腾讯混元正式发布AI科研系统Hyra 2.0，将研发重点从直接用AI攻克科学难题，转向让通用Agent参与科学模型、研究工作流及软件工具的研发与升级，推动科研范式从“刷题解题”走向“造工具”。
此前，Hyra 1.0曾驱动开源模型解决加法组合学中悬置五十余年的开放问题，验证了“给AI明确评判标准的难题并循环尝试”这一路径的可行性。Hyra 2.0在此基础上进一步提出，工具升级带来的收益可被下游任务反复复用，从而形成智能复利。
架构上，Hyra 2.0将研究工作拆分为Overall、Mission和Worker三层，Overall负责人与人类研究者沟通并对齐目标，Mission长期负责单一研究问题并判断路线取舍，Worker则独立读代码、做实验、分析失败原因，并可质疑Mission的判断。系统还设计了项目状态、Agent分层记忆与共享知识库Books三套分离的存储机制，项目复盘时可将可迁移方法整理为skill，供后续任务直接调用。