京东曹鹏：物理AI竞争不在单点技术，而在整套产业体系能力

南方都市报11-04

11月2日-5日，2026 世界互联网大会乌镇峰会在浙江乌镇举行。在11月4日的机器人与具身智能论坛上，京东集团技术委员会主席曹鹏围绕AI向物理世界迁移这一产业趋势分享了他的观点。　　京东集团技术委员会主席曹鹏。　　曹鹏认为，物理AI想要实现规模化落地，不能只追求模型、机器人本体的单点性能，算力、数据、场景以及供应链共同构筑的体系能力，才是行业竞争的核心。“过去十年，AI主要改造信息流，未来十年...

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曹鹏强调，算力底座是规模化发展的重要基础，算力、数据、场景三者缺一不可。他指出，当下不少机器人技术演示效果惊艳，但想要从实验室demo走向大规模应用，复制到万千真实场景之中，光靠技术参数远远不够。从产品研发、整机制造，再到交付落地、后期运维，完整的产业链条缺一不可，机器人的终极目标，是脱离表演式演示，完成真实环境下的任务交付。　　针对行业热议的数据瓶颈，曹鹏认为，手握业务场景资源，并不等于直接拿到可用于训练的高质量数据集。物理世界里物体操作、环境交互的大量细节，很难单纯依靠文字或者仿真完全还原，来源于真实作业场景的数据，是驱动模型迭代进化最重要的资源。 　　基于上述行业现实，曹鹏也在论坛现场分享了产业实践层面的探索与中长期规划。他表示，京东正在推进具身智能数据采集相关建设，目前实践已经覆盖上百个细分生产服务场景，沉淀十余万项真实作业任务，全部采集工作均遵循合法、合规、安全可信原则。此外，京东还计划建成规模领先的具身智能数据采集中心，两年内目标采集超过 1000万小时高质量人类真实场景视频数据，并同步采集超过100万小时机器人本体运行数据。　　面对行业普遍存在高质量具身训练数据匮乏、仿真与现实存在差距的现实痛点，曹鹏梳理出了一套产业闭环逻辑，即场景产生数据，数据训练模型，模型再回到场景当中接受检验，以此循环往复持续优化。“真实数据打基础，仿真和生成能力作补充，最终还是要回到真实场景完成验证。” 他指出，仿真与数据增强技术可以填补部分数据短板，但无法完全替代人类在现实作业中沉淀下来的一手数据。原始记录素材，还需要经过系统化加工，才能转化为可供模型学习使用的素材。他同时提及，数据价值不止于内部使用，也希望通过数据流通平台，降低行业获取高质量数据集的成本，减少产业的重复投入。　　曹鹏还提出了 “先量脚，再做鞋” 的实践思路。技术迭代应当从真实业务问题出发，算法和模型先在实际场景中跑通验证，再向外输出赋能产业。他认为，推动物理AI走向成熟并非一家企业可以完成，需要全产业链协同投入，打通技术、场景、供应链各类资源，依托开放生态，才能加速机器人走出实验室，落地千行百业。　　“物理AI的价值，不只在于让机器更聪明，更在于让产业更高效，让生活更美好。” 曹鹏在演讲的结尾谈到，只有当AI真正理解物理世界，并且能够在现实环境中持续进化，具身智能蕴藏的生产力才会真正释放。（文章来源：南方都市报）","kind":"news","is_publish_news":true,"is_publish_highlight":false,"is_publish_live":false,"is_publish_wemedia":false,"editions":null,"column":"","sentiment":"0","news_tag":"","news_rank":0,"isVideo":false,"video":null,"symbols":[],"gpt_button":1,"need_auth":false,"need_login_tip":false,"code":"91000000","status":"200"},"commentList":[],"isCommentEnd":true,"newsSizeData":{"likeSize":0,"commentSize":0,"repostSize":0,"favoriteSize":0,"likeStatus":false,"favoriteStatus":false},"APP":{"userAgent":"Mozilla/5.0 AppleWebKit/537.36 (KHTML, like Gecko; compatible; ClaudeBot/1.0; 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