悟道 1.0 发布时，学术界对" 大模型是通往 AGI 的技术路线 "尚未得出统一结论。 现在的具身智能，也处于这个阶段。 作者 | 王启隆 出品丨AI 科技大本营（ID：rgznai100） 大模型的热潮之下，一种微妙的瓶颈感，正成为行业共识。 "过往所说的 '百模大战'，更多是大语言模型的竞争，" 智源大会前夕， 智源研究院院长王仲远 在 与 CSDN 的对话中，开门见山地指出了问题的核 心，"而大语言模型受限于互联网数据的使用，性能虽然还在提升，但速度已大不如前。" 出路何在？在王仲远看来，AI 要突破天花板，就必须在"读万卷书"（互联网数据）后，去"行万里路"（物理世界）。 这并非孤立的判断。今年三月， 英伟达 CEO 黄仁勋就在 GTC 大会上为 AI 的下半场指明了方向 ：打造"AI 工厂"，迎接"物理 AI"时代，让 AI 走出屏 幕，与现实世 界交互。 思考趋于一致，行动便接踵而至。6 月 6 日，CSDN 在北京智源大会现场，见证了王仲远在他的主题演讲中给出的答案。如果说 2021 年的"悟道"系列 代表着对技术路径的探索（" 道 "），那么他所揭晓的全新"悟界"系列，则亮明了新的野心——用 ...

Core Insights - The Zhiyuan Research Institute launched the "Wujie" series of large models, including Emu3, Brainμ, RoboOS 2.0, RoboBrain 2.0, and OpenComplex2, at the 2025 Beijing Zhiyuan Conference [1] Group 1: Emu3 and Brainμ Models - Emu3 is a native multimodal world model that utilizes a next-token prediction paradigm for unified multimodal learning, allowing for the encoding of images/videos into discrete symbol sequences [2] - Brainμ, built on the Emu3 architecture, integrates brain signals as a new modality, enabling a single model to perform various neuroscience tasks, potentially becoming the "AlphaFold" of brain science [2][3] Group 2: RoboOS 2.0 and RoboBrain 2.0 - RoboOS 2.0 is the world's first open-source framework for embodied intelligence SaaS platforms, significantly reducing development barriers and improving performance by 30% compared to its predecessor [4] - RoboBrain 2.0 enhances multi-agent task planning capabilities, achieving a 74% improvement in task planning accuracy over RoboBrain 1.0 [5] Group 3: OpenComplex2 Model - OpenComplex2 represents a breakthrough in modeling biological molecules, capturing molecular interactions at atomic resolution and providing insights into the relationship between microscopic fluctuations and macroscopic biological functions [6][7] Group 4: Open Source Initiatives - Zhiyuan has open-sourced approximately 200 models and 160 datasets, with the FlagOS software stack upgraded to support various AI hardware and improve performance by up to 23% [8] Group 5: Applications and Collaborations - The Brainμ model has shown potential in consumer-grade brain-computer interface applications, collaborating with leading neuroscience laboratories and companies to expand its industrial applications [3][11] - The development of a digital twin heart and a drug safety evaluation platform demonstrates the application of advanced modeling techniques in pharmacology and personalized medicine [12]