2025年12月17日，人工智能领域顶尖学者、OpenAI前核心研究员姚顺雨正式加盟腾讯集团，出任CEO/总裁办公室首席AI科学家，直接向腾讯集团总裁刘 炽平汇报；同时，他将兼任新成立的AI Infra部及大语言模型部负责人，向腾讯技术工程事业群（TEG）总裁卢山汇报。此次任命不仅标志着腾讯在AI核 心人才布局上的重大突破，更凸显了其加码大模型研发、构建AI基础设施核心竞争力的战略决心。 作为AI领域备受瞩目的青年领军者，姚顺雨的学术与职业履历堪称亮眼。这位27岁的天才科学家出身"清华姚班"——由图灵奖得主姚期智院士创办的计算 机科学实验班，2015年他以安徽省理科第三的704分成绩考入该班，本科期间曾担任姚班联席会主席，展现出卓越的学术组织能力。随后他赴普林斯顿大 学深造，主攻自然语言处理与强化学习，2024年获计算机科学博士学位，其博士阶段提出的"思维树（Tree of Thoughts）"框架，大幅提升了AI模型的复杂 问题决策能力，相关成果已成为业界主流技术范式。 在OpenAI任职期间，姚顺雨作为核心研究员参与了智能体产品Operator与Deep Research等关键项目的研发，其提出的ReAc ...

点击下方 卡片 ，关注" 自动驾驶之心 "公众号 戳我-> 领取 自动驾驶近30个 方向 学习 路线 这两天看到英伟达大佬刘兰个川分享的文章「自动驾驶系统的局部最优陷阱」，把里面关于自动驾驶发展的核 心观点提炼出来分享给大家。 知乎原文 ：https://zhuanlan.zhihu.com/p/1970625322337701958 数据飞轮让我们走到了今天，但下一步突破必须依靠真正的推理能力。 目前业内所有的量产模型仍然沿用着经典的数据飞轮模式： 模型部署 → 效果检验 → 数据挖掘 → 重新训练 → 再次部署 ，这个闭环持续推动着系统进化。 以往数据的规模还在十万/百万这个量级时，增加训练数据仍有显著收益。而这两年算法进入端到端时代，数 据规模也上升到千万量级，仅通过提升数据规模能得到的模型性能收益越来越低，换句话说成本越来越高，剩 下的往往是数据稀缺、逻辑复杂的"硬骨头"。 这一点已经基本成为业内共识，尤其是已经取得这一成果的公司。最具代表性的像特斯拉，国内的像理想、小 米、小鹏，当然也有英伟达。 图：一个2019年的典型的数据飞轮，引自Andrej Karpathy的ICML主题演讲，2025年的数 ...

Core Insights - The article discusses the evolution of AI, particularly focusing on the transition to the "second half" of AI development, emphasizing the importance of language and reasoning in creating more generalizable AI systems [4][62]. Group 1: AI Evolution and Language - The concept of AI has evolved from rule-based systems to deep reinforcement learning, and now to language models that can reason and generalize across tasks [41][43]. - Language is highlighted as a fundamental tool for generalization, allowing AI to tackle a variety of tasks by leveraging reasoning capabilities [77][79]. Group 2: Agent Systems - The definition of an "Agent" has expanded to include systems that can interact with their environment and make decisions based on reasoning, rather than just following predefined rules [33][36]. - The development of language agents represents a significant shift, as they can perform tasks in more complex environments, such as coding and internet navigation, which were previously challenging for AI [43][54]. Group 3: Task Design and Reward Mechanisms - The article emphasizes the importance of defining effective tasks and environments for AI training, suggesting that the current bottleneck lies in task design rather than model training [62][64]. - A focus on intrinsic rewards, which are based on outcomes rather than processes, is proposed as a key factor for successful reinforcement learning applications [88][66]. Group 4: Future Directions - The future of AI development is seen as a combination of enhancing agent capabilities through better memory systems and intrinsic rewards, as well as exploring multi-agent systems [88][89]. - The potential for AI to generalize across various tasks is highlighted, with coding and mathematical tasks serving as prime examples of areas where AI can excel [80][82].

Core Viewpoint - Recent rumors about former OpenAI researcher Yao Shunyu joining Tencent with a salary exceeding 100 million have been officially denied by Tencent, labeling the reports as false [1]. Group 1: Individual Background - Yao Shunyu graduated from Tsinghua University's Yao Class and holds a PhD in Computer Science from Princeton University, having joined OpenAI in 2024 [3]. - At the age of 27, Yao Shunyu was recognized as the youngest innovator in the "Innovators Under 35" list for China, published by MIT Technology Review [4]. Group 2: Contributions to AI - Yao Shunyu was a core contributor to OpenAI's first intelligent agent products and deep research, particularly in the development of language agents [4]. - He introduced the ReAct method, which combines reasoning and action, establishing a foundational approach for creating versatile and scalable language agents [4]. - The ReAct method enhances model controllability and significantly broadens its applicability across various real-world domains, becoming a mainstream approach in both academia and industry for building language agents [4].

Core Viewpoint - Recent rumors about former OpenAI researcher Yao Shunyu joining Tencent with a salary exceeding 100 million have been officially denied by Tencent, labeling the reports as false [1][2][3]. Group 1: Yao Shunyu's Background - Yao Shunyu graduated from Tsinghua University and holds a PhD in Computer Science from Princeton University, joining OpenAI in 2024 [4]. - He was recognized as one of the "Innovators Under 35" in the China region by MIT Technology Review, being the youngest at 27 years old [4]. - Yao is a key contributor to OpenAI's early research, particularly in the development of language agents [4]. Group 2: Contributions to AI - Yao Shunyu proposed the ReAct method, which integrates reasoning and action in the development of language agents, establishing a foundational approach for creating versatile and scalable AI systems [5]. - The core idea of ReAct is to enable large language models to perform internal reasoning before making decisions, enhancing model controllability and expanding applicability across various fields [5]. - ReAct has become a mainstream method for constructing language agents, widely adopted in both academia and industry [5].

Group 1 - The news about former OpenAI researcher Yao Shunyu joining Tencent for a salary exceeding 100 million is false, as clarified by Tencent's official account [1] - Yao Shunyu graduated from Tsinghua University and later obtained a PhD from Princeton University, where he developed the Tree of Thoughts framework and CoALA modular cognitive architecture [1] - He joined OpenAI in 2024 and contributed significantly to the development of intelligent agent products, being recognized as a core contributor [1][5] Group 2 - Yao Shunyu's ReAct method introduced a paradigm combining reasoning and action for intelligent agents, enhancing the controllability and applicability of large language models [5] - The AI talent competition is intensifying globally, with companies like Meta offering over $200 million in total compensation to attract top talent, including researchers from OpenAI [6] - In China, major internet companies are expanding their recruitment for AI-related positions, with a reported increase of over 10 times in new AI job postings compared to the previous year [6]

Group 1 - Recent rumors suggest that former OpenAI researcher Yao Shunyu has joined Tencent with a salary exceeding 100 million [1] - Tencent officially refuted the claim regarding Yao Shunyu's salary through its public account, labeling the report as a rumor [1] - Yao Shunyu, a graduate of Tsinghua University's Yao Class and a PhD in Computer Science from Princeton University, joined OpenAI in 2024 [1] Group 2 - Yao Shunyu introduced the ReAct method, which combines reasoning and action in the agent paradigm, laying the foundation for creating generalizable and scalable language agents [2] - The core idea of ReAct is to enable large language models to perform explainable internal reasoning before making decisions and actions, enhancing model controllability and expanding applicability across various fields [2] - ReAct has become the most mainstream method for constructing language agents globally, widely adopted in both academia and industry [2]