[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"news-c049b416-8dac-4d74-b001-ec32c6b49cf3":3},{"id":4,"title":5,"summary":6,"original_url":7,"source_id":8,"tags":9,"published_at":23,"created_at":24,"modified_at":25,"is_published":26,"publish_type":27,"image_url":13,"view_count":28},"c049b416-8dac-4d74-b001-ec32c6b49cf3","商汤日日新 SenseNova-U1 Pro 曝光：把「理解·生成·行动」原生统一塞进一个基座，7 月邀测","商汤把理解·生成·行动三件事压进同一个模型基座了。\n\n6 月 25 日，36氪披露商汤日日新新成员 SenseNova-U1 Pro，定位业界首个以理解·生成·行动原生统一为内核的多模态智能体基座，7 月邀测。这是商汤在 4 月开源 SenseNova U1（NEO-unify 架构）后，把行动维度纳入统一框架的关键升级。\n\n传统做法是拼接：视觉\u002F语言理解外挂到生成模型，再外接 Agent 框架走 tool use。代价是表征割裂、延迟高、一致性难保证。原生统一把理解、生成、决策压进同一套 token 空间端到端训练——这正是 Gemini 2、GPT-5 系列已走的路线，但能在多模态 + Agent 维度同时原生统一的基座仍属少数。\n\nU1 Pro 的差异化在于把行动提到与理解·生成并列的一等公民：具身操作、工具调用、长程规划这些原本依赖外挂 RL 或 SFT 的能力，被压进预训练统一目标里。短期风险明显——稳定性、灾难性遗忘、能力相互挤兑都是硬骨头；长期收益是部署侧低延迟和一致性，对实时 Agent 尤为关键。\n\n中国大模型厂商在多模态 Agent 基座上的路径正在分化：Qwen 系走 AgentWorld 把语言世界模型做成统一入口；商汤则把原生统一多模态 Agent 基座作为旗舰叙事。U1 Pro 邀测结果会是 agentic 时代第一个公开校验点，7 月值得关注。","https:\u002F\u002F36kr.com\u002Fnewsflashes\u002F3868495538574600","5e4fd3d1-9cb4-44a6-bae5-9ffb449c05c1",[10,14,17,20],{"id":11,"name":12,"slug":12,"description":13,"color":13},"a8002d98-9df1-4ab9-94d4-a7625af634c4","china-ai",null,{"id":15,"name":16,"slug":16,"description":13,"color":13},"01598627-1ea6-4b27-a5d8-874971571a71","llm",{"id":18,"name":19,"slug":19,"description":13,"color":13},"499f4b56-819d-49a3-9609-33e775143b86","multimodal",{"id":21,"name":22,"slug":22,"description":13,"color":13},"b1853a5a-d940-42b7-94f9-0488ee3f2cf7","new-model","2026-06-25T18:00:00Z","2026-06-25T18:08:24.116121Z","2026-06-25T18:08:24.116132Z",true,"agent",4]