2025年，具身智能行业的发展继续以"烈火烹油"的态势，向前发展。 前9个月，全球（特别是受中国市场驱动）在人形机器人领域的投资交易额达到约70亿美元（约合500亿 人民币）。这一数字相比去年同期增长了250%，太多人期待着机器人的"星辰大海"。 但在产品上来看，几乎所有的人形机器人都还停留在跳舞拳击、走路摔跤的状态，技术发展仍困在迷雾 之中。 2025年12月8日至21日（北京时间），钛媒体集团携手NextFin.AI、巴伦中国举办的2025 T-EDGE 全球 对话正式开启，以连续7日全球连线+贯穿2周N场闭门私享会的方式联动上海、深圳、硅谷、香港、新 加坡、日本、迪拜等全球化创新高地，汇集前沿创新思想，打造全球分布式创新盛会，展开一场【AI 时代的全球对话 Global Conversations for the AI Era】。 会上，「赵何娟 Talk」与商汤科技联合创始人、执行董事、大晓机器人董事长王晓刚，就"具身智能新 的ACE研究范式"展开了深度对话。 "靠读文章、看图片，机器人永远不可能理解真实的物理世界。" 王晓刚表示，AI的研究范式，要从以机器为中心转变成以人为中心，通过采集人类的真实行 ...

作者 | 王启隆 出品丨AI 科技大本营（ID：rgznai100） 2026 年 1 月，硅谷的风有点冷。 65 岁的 Yann LeCun（杨立昆）离职 Meta 创业还没一个月，就炮轰起了他的老东家，和那位他看不起的小将 Alexandr Wang。 虽然 LeCun 离开的新闻已经有一段时间，但如果你从 2013 年就开始关注这家公司，关注这群人，你会明白，这事实际上宣告了一个时代的彻底终 结。那个大厂愿意花重金养着一群科学家，让他们在一个叫 FAIR（Facebook AI Research）的象牙塔里，不计成本、不问产出、只为探索"智能本 质"的时代， 结束了 。 取而代之的，是 Alexandr Wang 这种年轻狠角色的上位，是"暴力美学"，是"别跟我谈哲学，把算力堆上去"，是赤裸裸的商业变现。 回首 2025 年，咱们公众号的爆款文章就献给了 LeCun。当时他在英伟达 GTC 大会意气风发，怼天怼地： 杨立昆"砸场"英伟达：不太认同黄仁勋，目 前大模型的推理方式根本是错的，token 不是表示物理世界的正确方式｜GTC 2025 2026 年开篇，我们聊聊这个倔强的法国人，是怎么把 Met ...

ICCV2025中稿的Hierarchy UGP，自动驾驶场景重建。 具有时空一致性的多风格自动驾驶场景生成算法StyledStreets。 整合多模态驾驶意图与潜在世界模型实现合理规划的World4Drive，中稿ICCV 2025。 自动驾驶的视频生成扩散世界模型GeoDrive。 统一生成视觉与lidar的自驾世界模型框架OmniGen，中稿ACMMM2025。 结合强化学习的自动驾驶视频生成世界模型RLGF，中稿NeurIPS 2025。 利用稀疏注意力实现4D OCC世界模型预测算法 SparseWorld-TC。 世界模型端到端闭环强化学习框架AD-R1。 最近在复盘各家如何使用世界模型的，今天和大家盘一下理想在这方面的工作。理想对世界模型的定义在 重建+生成 ，利用重建技术（3DGS）建模自动驾驶场 景，再利用生成方法实现闭环仿真或者场景生成。 这里面核心的技术是3DGS和生成。 整体上来看，世界模型是围绕视频为核心搭建的时空认知系统 ，这一点也和蔚来任少卿的观点一致。通过跨模态的互相预测和重建，促使系统学习时空和物理规 律，让机器能像人一样理解环境。 通过重建+生成，既可以做云端的数据生成，也 ...

Core Insights - Yann LeCun, a Turing Award winner and a key figure in deep learning, has left Meta to become the Executive Chairman of AMI Labs, revealing internal turmoil at Meta regarding its AI strategy and leadership changes [1][12] Group 1: Departure from Meta - LeCun confirmed speculation about his departure from Meta, citing a crisis of integrity related to the Llama 4 model's testing results and a significant shift in the company's AI strategy [1][5] - The internal conflict escalated after Meta's CEO, Mark Zuckerberg, made a controversial decision to invest approximately $14.3 billion in acquiring a 49% stake in Scale AI, appointing 28-year-old Alexandr Wang as Chief AI Officer [6][8] Group 2: AI Strategy and Leadership Changes - The introduction of Wang led to a restructuring of Meta's AI research, consolidating various departments under his leadership, which marginalized LeCun's role [8][11] - Wang's focus on large language models (LLMs) as the sole path to achieving superintelligence conflicted with LeCun's belief in the importance of foundational research and alternative approaches [9][10] Group 3: Cultural and Operational Shifts - The shift in strategy resulted in a loss of academic freedom within Meta's AI research labs, leading to a culture that prioritized commercial viability over scientific exploration [11][12] - A new policy mandated that research papers must be approved for commercial relevance before publication, causing discontent among researchers and contributing to significant talent attrition [11][12] Group 4: Formation of AMI Labs - Following his departure, LeCun founded AMI Labs, aiming to explore scientific paths that were sidelined in the competitive landscape of tech giants, with an initial funding target of €500 million and a valuation of €3 billion [12][14] - LeCun has chosen not to take on the CEO role at AMI Labs, preferring to focus on scientific endeavors while leaving management to experienced professionals [14]

Core Viewpoint - Alibaba's Gaode has developed a world model and plans to launch a new product application based on this model, which will be open-sourced soon [1] Group 1: Company Developments - Gaode's world model currently ranks first in the comprehensive score according to the WorldScore website released by Stanford University's Fei-Fei Li team [1] - The company has established a new department focused on embodied business [1] - Gaode's recruitment website indicates multiple job openings related to the world model, in addition to positions in the embodied business department [1]

Group 1 - The core viewpoint of the article is that Alibaba's Gaode has developed a world model and plans to launch a new product application based on this model, which will be open-sourced soon [1] - Gaode's world model currently ranks first in the comprehensive score according to the WorldScore website released by Stanford University professor Fei-Fei Li's team [1] Group 2 - The article includes a table comparing various models, with FantasyWorld-0.1 achieving a WorldScore-Static of 78.55 and other metrics such as 54.99 for Dynamic Camera Control and 75.55 for Object Control [2]

1月5日，上海证券报记者从接近高德的知情人士处获悉，阿里巴巴旗下高德已布局世界模型，并计划基于世界模型推出一项新的产品应用，且 该模型将于近期开源。 斯坦福大学教授李飞飞团队发布的WorldScore官网显示，高德世界模型目前综合得分位列第一。（转载自上海证券报） | Model Name | WorldScore-Static | WorldScore-Dynamic | Camera Control | Object Control | Content Alignment 3D Consistency | | Photometric Consistency | Style Consistency | | --- | --- | --- | --- | --- | --- | --- | --- | --- | | FantasyWorld-0.1 | 78.55 | 54.99 | 75.55 | 87.75 | 63.37 | 81.10 | 93.58 | 85.43 | | | 20.23 | 00.73 | 245 446 | 24.80 | 79.24 | 12.22 | 24.00 | 22. ...

1月5日，上海证券报记者从接近高德的知情人士处获悉，阿里巴巴旗下高德已布局世界模型，并计划基于世界模型推出一项新的产品应用，且该模型将于 近期开源。 | Model Name | WorldScore-Static | WorldScore-Dynamic | Camera Control | Object Control | Content Alignment 3D Consistency | | Photometric Consistency | Style Consistency | | --- | --- | --- | --- | --- | --- | --- | --- | --- | | FantasyWorld-0.1 | 78.55 | 66'89 | 75.55 | 87.75 | 63.37 | 81.10 | 93.58 | 85.43 | | Tarketstop Life | 28.23 | 06.73 | 기반 도매 | 14.68 | PR 24 | 87.38 | 8883 | BLED | | Paylog | 2382 | 6453 | 85.9% | 2412 | 2 ...

1月5日，上海证券报记者从接近高德的知情人士处获悉，阿里巴巴旗下高德已布局世界模型，并计划基于世界模型推出一项新的产品应用，且该模型将于 近期开源。 斯坦福大学教授李飞飞团队发布的WorldScore官网显示，高德世界模型目前综合得分位列第一。 | Model Name | WorldScore-Static | WorldScore-Dynamic | Camera Control | Object Control | Content Alignment 3D Consistency | | Photometric Consistency | Style Consistency | | --- | --- | --- | --- | --- | --- | --- | --- | --- | | FantasyWorld-0.1 | 78.55 | 66'89 | 75.55 | 87.75 | 63.37 | 81.10 | 93.58 | 85.43 | | Tarketstop Life | 28.23 | 06.73 | 기반 도매 | 14.68 | PR 24 | 87.38 | 8883 | ...

Core Insights - 2026 is anticipated to be a pivotal year for AI, transitioning from large-scale model development to practical applications that integrate AI into real-world workflows [2][34] - The focus is shifting towards deploying lightweight models and embedding intelligence into physical devices, moving away from mere demonstrations to targeted deployments [2][34] Group 1: Scaling Law and Model Development - The AI industry is nearing the limits of the Scaling Law, prompting a shift towards new architectural research and smaller, more efficient models [4][21] - Experts suggest that smaller language models (SLMs) will become the standard in AI applications by 2026 due to their cost-effectiveness and performance advantages [5][22] - The trend towards SLMs is supported by advancements in edge computing, making them more suitable for deployment on local devices [6][22] Group 2: World Models and Gaming Industry - 2026 is expected to be a key year for world models, which learn how objects interact in three-dimensional space, enhancing predictive capabilities [8][25] - The gaming industry is projected to see significant growth in the world model market, with estimates rising from $1.2 billion in 2022 to $27.6 billion by 2030 [9][25] Group 3: Agent Integration and Practical Applications - The introduction of the Model Context Protocol (MCP) is seen as a critical advancement, enabling AI agents to interact with external tools and databases, thus facilitating their integration into real-world systems [11][27] - As MCP reduces friction in connecting AI agents to practical systems, 2026 may mark the year when these agents transition from demonstration to everyday use [12][28] Group 4: Human-AI Collaboration - There is a growing belief that AI will enhance human workflows rather than replace them, with expectations of new job roles emerging in AI governance and data management [14][31] - The narrative is shifting towards how AI can assist human tasks, with predictions of a low unemployment rate as companies begin to hire for new roles related to AI [14][31] Group 5: Physical AI and Market Trends - Advances in small models, world models, and edge computing are expected to drive the adoption of physical AI applications, including robotics and wearable devices [16][34] - The market for physical AI is anticipated to grow, with wearable devices becoming a cost-effective entry point for consumers [17][34]