Core Insights - Artificial intelligence (AI) is a strategic technology leading a new wave of technological revolution, significantly transforming human production and lifestyle [1] - Beijing is positioning itself as the "AI capital" of China, with over 2,400 AI companies and a core industry scale nearing 350 billion yuan, accounting for half of the national total by 2024 [1] Group 1: AI Innovation and Research - Beijing is recognized as the city with the richest AI innovation resources in China, hosting 21 national key laboratories and over 40% of the nation's top talent [2] - The city has established four new research institutions focused on AI, producing globally leading original results, including the first native multimodal large model, Emu [2] - The Zhiyuan Institute has developed the "Wudao" series of large models, with Wudao 1.0 and Wudao 2.0 being significant milestones in China's AI model development [2][3] Group 2: AI Applications and Developments - Beijing has launched 132 large models, leading the nation in this area, and is focusing on disruptive technologies like optical computing and wafer-level chips [4] - The integration of AI with hardware is exemplified by companies like Mianbi Intelligent, which focuses on edge AI models that perform processing directly on user devices [4] - The education sector is set to benefit from AI with the introduction of MAIC (Massive AI-empowered Courses), which aims to enhance teaching efficiency and learning outcomes [5] Group 3: Future Directions and Infrastructure - Beijing plans to enhance its AI infrastructure, with an expected addition of 8,620 PetaFLOPS of computing power by 2024, bringing the total to over 33,000 PetaFLOPS [7] - The city aims to establish itself as a global hub for AI innovation and industry, focusing on interdisciplinary fields such as AI + life sciences and AI for science [7] - Efforts will be made to integrate data and applications, leveraging Beijing's rich data resources and comprehensive industrial system to promote the application of large models in the economy [7]

作者 | 华卫 今年的智源大会上，智源研究院推出全新的"悟界"系列大模型，其中包括原生多模态世界模型 Emu3、脑科学多模态通用基础模型见微 Brainμ、跨本体具身大小脑协作框架 RoboOS2.0 与具身大 脑 RoboBrain2.0 以及全原子微观生命模型 OpenComplex2。 据介绍，Emu3 作为原生多模态统一架构让大模型具备理解和推理世界的能力，Brainμ基于则 Emu3 架构，引入脑信号这一新的模态数据，实现了单一模型完成多种神经科学任务的大一统。在初代版本 的基础上，RoboOS2.0 与 RoboBrain2.0 的原有性能有大幅提升，并新增多机协作规划与物理常识 驱动的空间推理能力。OpenComplex2 可在原子分辨率层面捕捉分子相互作用及平衡构象，探索微 观构象波动与宏观生物功能的跨尺度关联。 "大模型技术还远没有到发展的尽头。"在大会前夕，智源研究院长王仲远向我们透露了这一系列新模 型背后的技术思考与智源当下的战略布局。 王仲远指出，去年智源就对大模型的技术路线进行了预判，会从大语言模型往多模态、尤其是原生多 模态世界模型的方向发展。当前，智源的工作布局都是围绕这一技术发 ...

以ChatGPT为代表的语言类大模型重塑内容生成方式时，多模态模型还在等待它的"iPhone时刻"。近日召开的2025智源大会上，智源研究院（以下简称"智 源"）正式发布了包括原生多模态世界模型Emu3等"悟界"大模型系列，Emu3实现了文本、图像、视频的任何组合理解与生成，通过单一模型就可以捕捉世 界的规律。 AI发展之快，每年都有新话题，2024年，价格战是大模型的关键词，2025感到风向变了，大模型应用百花齐放，反而有种大模型发展"变慢"了的体感。 事实上，市场上新旧产品同台竞技，呈现出立体、多维度的思考，多模态大模型更是如此。按照当前技术成熟度评估，视频生成等核心能力仍处于GPT-2到 GPT-3的过渡阶段，与产业预期存在显著差距。多模态模型将经历更长的技术沉淀期，这也意味着更大的想象力空间。 技术路线未收敛 大模型爆发至今，很多时候无外乎是选对了方向，又懂得流量密码，一个现象级产品就横空出世了。事实上，这种选择需要前期足够多的思考、实践和勇 气。 严格来说，Emu3是智源2024年10月发布的多模态模型，目前智源已在训练下一个版本。基于Emu3，智源还官宣了全球首个脑科学多模态通用基础模型见微 Br ...

21世纪经济报道记者孔海丽 北京报道 2025年智源大会上，人形机器人不再是吉祥物，被"围堵"的人从杨植麟变成了王兴兴。 这一年，AI进展迅猛，迭代周期甚至少于3个月，且不再局限于大语言模型，而是转化为人形机器人训 练、落地的强辅助。 "人工智能正在加速从数字世界走向物理世界。"智源研究院院长王仲远在接受包括21世纪经济报道在内 的记者采访时直言："人工智能应该为世界做一些实实在在的事情，帮助人类摆脱繁琐的、重复的以及 简单的劳动。" AI技术路线转向世界模型 "大模型技术还远没有到发展的尽头，过往所说的'百模大战'更多是大语言模型的竞争，而大语言模型 受限于互联网数据的使用，基础模型性能虽然还在提升，但是提升速度不如以前。"在王仲远看来，大 语言模型性能提升瓶颈的解法主要包括三个方面，一是强化学习优化推理能力，二是合成高质量数据替 代人类标注，三是激活海量未充分利用的多模态数据，多模态数据的规模可达文本的"百倍乃至万倍"。 在智源研究院的判断中，大模型的技术路线会从大语言模型往多模态尤其是原生多模态世界模型的方向 发展。原生多模态世界模型本质上是为了让人工智能感知和理解物理世界，进而推进和物理世界的交 互。 ...

Group 1 - The core viewpoint of the articles emphasizes the rapid development of AI and its transition from the digital world to the physical world, highlighting the importance of world models in this evolution [1][3][4] - The 2023 Zhiyuan Conference marked a shift in focus from large language models to the cultivation of world models, indicating a new phase in AI development [1][3] - The introduction of the "Wujie" series of large models by Zhiyuan represents a strategic move towards integrating AI with physical reality, showcasing advancements in multi-modal capabilities [3][4] Group 2 - The Emu3 model is a significant upgrade in multi-modal technology, simplifying the process of handling various data types and enhancing the path towards AGI (Artificial General Intelligence) [4][5] - The development of large models is still ongoing, with potential breakthroughs expected from reinforcement learning, data synthesis, and the utilization of multi-modal data [5][6] - The current challenges in embodied intelligence include a paradox where limited capabilities hinder data collection, which in turn restricts model performance [6][8] Group 3 - The industry faces issues such as poor scene generalization and task adaptability in robots, which limits their operational flexibility [9][10] - Control technologies like Model Predictive Control (MPC) have advantages but also limitations, such as being suitable only for structured environments [10] - The development of embodied large models is still in its early stages, with a lack of consensus on technical routes and the need for collaborative efforts to address foundational challenges [10]

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 Beijing Zhiyuan Conference showcased the latest developments in AI, including the release of the "Wujie" series of models by the Zhiyuan Research Institute, which aims to advance AI's understanding of the physical world [2][4] - The director of Zhiyuan, Wang Zhongyuan, emphasized that the next phase of AI development requires moving beyond language models to multi-modal world models that can perceive and interact with the physical environment [4][5] Model Releases - The "Wujie" series includes four models: Emu3, Brainμ, RoboOS 2.0, and RoboBrain 2.0, each designed to enhance AI's capabilities in understanding and interacting with the physical world [2][3] - Emu3 utilizes a new visual tokenizer technology to unify the representation of text, images, and videos, allowing AI to process them in a cohesive manner [3] - Brainμ aims to serve as a new engine for neuroscience research and clinical applications, integrating over one million neural signal data units [3] - RoboOS 2.0 improves performance by 30% compared to its predecessor, enabling faster integration of developer plugins and enhancing real-time response capabilities [3] - OpenComplex2 targets life sciences by simulating molecular movements at atomic resolution, potentially accelerating drug development and biological research [3] Strategic Partnerships and Goals - Zhiyuan has signed a strategic cooperation agreement with Hong Kong Investment Management Company to foster talent, technology, and capital collaboration [6] - The organization is committed to open-source and international collaboration, having already open-sourced 200 models with a total of 640 million downloads [7] - Wang Zhongyuan highlighted the importance of patience and sustained capital investment for long-term goals, despite short-term commercialization challenges [5][6]

凤凰网科技讯 6月6日，在2025北京智源大会上，继"悟道"系列大模型之后，智源研究院推出"悟界"系 列大模型。 "悟界"大模型系列，包括原生多模态世界模型Emu3、脑科学多模态通用基础模型见微Brainμ、跨本体 具身大小脑协作框架RoboOS 2.0与具身大脑RoboBrain 2.0以及全原子微观生命模型OpenComplex2。 Emu3作为原生多模态统一架构让大模型具备理解和推理世界的能力，Brainμ基于Emu3架构，引入脑信 号这一新的模态数据，实现了单一模型完成多种神经科学任务的大一统。多模态与脑科学模型未来可成 为人机交互具身场景下的基础模型。 RoboOS 2.0与RoboBrain 2.0在初代版本基础上，原有性能大幅提升，并新增多机协作规划与物理常识驱 动的空间推理能力。 作为神经科学领域跨任务、跨模态、跨个体的基础通用模型，Brainμ可同步处理多类编解码任务，兼容 多物种动物模型（包括小鼠 狨猴 猕猴）与人类数据，实现科学数据注释、交互式科学结论解读、大脑 感觉信号重建及模拟刺激信号生成。在自动化睡眠分型、感官信号重建与多种脑疾病诊断等任务中，作 为单一模型其性能显著超越现有的专有 ...

Group 1 - The Beijing Zhiyuan Conference showcased cutting-edge AI achievements, gathering hundreds of global young scientists, top scholars, and industry experts to outline the future of the AI industry [1] - AI is rapidly transitioning from the digital world to the physical world, with the release of the original multimodal world model Emu3, which enhances understanding and reasoning in physical contexts [3][4] - The original multimodal model integrates various data types from the beginning of training, allowing for a more comprehensive understanding of the world, unlike traditional models that may lose capabilities when learning additional modalities [4] Group 2 - Beijing has over 2,400 core AI enterprises, contributing to a core industry scale of nearly 350 billion yuan, accounting for half of the national total [5][9] - The conference featured advanced humanoid robots demonstrating their capabilities, with companies like Galaxy General planning to open 100 unmanned pharmacies in major cities [6][8] - Discussions at the conference included topics such as multimodal AI, deep reasoning, and the future paths of AI, emphasizing the need for global cooperation and safety measures in the face of rapid AI advancements [10][13]