大模型的通用性和泛化性越来越强大了。 虽说一些新模型，比如说「差评如潮」的 GPT-5.2，在专业任务和智能水平已经达到了非常出色的水平，但离我们所认知的 AGI 依旧十分遥远。 不过，这也说明了大家对 AGI 仍然充满热情和信心，说不定下一款重磅的大模型就能够初步实现 AGI 的构想呢？ 但是，近期卡耐基梅隆大学教授，AI2 研究科学家 Tim Dettmers发布了一篇长文博客，标题为《Why AGI Will Not Happen》，认为由于物理原因，我们 无法实现 AGI，也无法实现任何有意义的超级智能。 这篇文章着实给大家对 AGI 的热情泼上了一盆冰水，引发了广泛哗然。 为什么 AGI 不会发生 这篇文章涉及到了硬件改进、通用人工智能（AGI）、超级智能、规模法则、人工智能泡沫以及相关话题。 博客链接：https://timdettmers.com/2025/12/10/why-agi-will-not-happen/ 计算是物理的 许多思考 AGI、超级智能、缩放定律以及硬件进步的人，往往把这些概念当作抽象理念来看待，像哲学思想实验一样加以讨论。这一切都建立在对 AI 与 规模化的一个根本性误解 ...

Core Viewpoint - The article discusses the limitations of achieving Artificial General Intelligence (AGI) due to physical and resource constraints, emphasizing that scaling alone is not sufficient for significant advancements in AI [3][20][32]. Group 1: Limitations of AGI - Tim Dettmers argues that AGI will not happen because computation is fundamentally physical, and there are inherent limitations in hardware improvements and scaling laws [8][10][12]. - The article highlights that as transistor sizes shrink, while computation becomes cheaper, memory access becomes increasingly expensive, leading to inefficiencies in processing power [11][17]. - The concept of "superintelligence" is critiqued as a flawed notion, suggesting that improvements in intelligence require substantial resources, and thus, any advancements will be gradual rather than explosive [28][29][30]. Group 2: Hardware and Scaling Challenges - The article points out that GPU advancements have plateaued, with significant improvements in performance per cost ceasing around 2018, leading to diminishing returns on hardware investments [16][17]. - Scaling AI models has become increasingly costly, with the need for linear improvements requiring exponential resource investments, indicating a nearing physical limit to scaling benefits [20][22]. - The efficiency of current AI infrastructure is heavily reliant on large user bases to justify the costs of deployment, which poses risks for smaller players in the market [21][22]. Group 3: Divergent Approaches in AI Development - The article contrasts the U.S. approach of "winner-takes-all" in AI development with China's focus on practical applications and productivity enhancements, suggesting that the latter may be more sustainable in the long run [23][24]. - It emphasizes that the core value of AI lies in its utility and productivity enhancement rather than merely achieving higher model capabilities [24][25]. Group 4: Future Directions and Opportunities - Despite the challenges, the article suggests that there are still significant opportunities for improvement in AI systems through better hardware utilization and innovative model designs [39][45][67]. - It highlights the potential for advancements in training efficiency and inference optimization, indicating that current models are not yet fully optimized for existing hardware capabilities [41][43][46]. - The article concludes that the path to more capable AI systems is not singular, and multiple avenues exist for achieving substantial improvements in performance and utility [66][69].

面对谷歌日益严峻的竞争威胁，OpenAI CEO Sam Altman 近日发布"红色代码"警报，这标志着这家全球 估值最高的初创公司正经历一次重大的战略修正。 为了应对市场份额流失和巨大的财务压力，OpenAI 决定暂时搁置包括Sora视频生成器在内的长期研发 项目，转而在短期内全力通过提升用户活跃度来巩固ChatGPT的大众市场地位。 据华尔街日报报道，Altman 在发给员工的备忘录中明确指示，公司应将"更好地利用用户信号"作为优 先事项，以提振ChatGPT在模型排行榜上的表现并增加用户粘性。这种策略意味着OpenAI将更多依赖 基于用户点击反馈的训练数据，而非单纯依靠专业评估。此前，这一策略曾助推GPT-4o模型获得极高 的用户参与度，但也因引发模型"过度迎合"用户而招致关于加剧用户心理健康问题的争议。 此次战略调整正值OpenAI 面临成立以来最严重的挑战。谷歌近期推出的Nano Banana图像生成器和 Gemini 3模型在市场和关键的第三方评测（如LM Arena）中迅速崛起，不仅在性能上超越了OpenAI， 更在抢占企业客户和消费者市场。若无法遏制增长放缓的趋势，OpenAI 可能难以支付 ...

Core Insights - Alphabet's stock price surged 2.4% to $326, reaching a historical high, with a cumulative increase of over 11.5% in the past five trading days and 22% in the last month [1] - As of November 24, Alphabet's market capitalization was approximately $3.84 trillion, making it the third-largest company globally, just behind Nvidia and Apple [1] - The stock price increase has significantly boosted the wealth of its founders, Larry Page and Sergey Brin, placing them as the second and third richest individuals globally, respectively [4] AI Breakthroughs - The primary driver behind the stock surge is the release of the new AI model, Gemini 3, which has received widespread acclaim for its performance, surpassing OpenAI's ChatGPT-5 in several tests [7] - Additionally, Google's AI chip business is experiencing a major breakthrough, with reports that Meta Platforms is considering using Google's AI chips in its data centers, potentially worth billions for Google [10] Competitive Landscape - Nvidia has responded to concerns about Google's AI chip potentially disrupting its market dominance, asserting that its technology remains a generation ahead [10][11] - Despite Google's advancements, Nvidia continues to hold over 90% of the AI chip market share, emphasizing the competitive nature of the industry [11] Strategic Developments - Google has been developing its TPU chips for over a decade, which are now being used to train the Gemini models, positioning them as a strong alternative to Nvidia's offerings [16] - The potential deal with Meta could allow Google to capture about 10% of Nvidia's annual revenue, further solidifying its position in the AI hardware market [10] Financial Performance - Google's search revenue increased by 15% in the third quarter, indicating that its core business remains robust despite concerns about AI impacting its advertising revenue [20] - Warren Buffett's Berkshire Hathaway has invested approximately $4.3 billion in Alphabet, signaling strong confidence in the company's future prospects [18]

Core Viewpoint - Google's stock price has surged significantly, driven by advancements in artificial intelligence, particularly the launch of the Gemini 3 model and potential AI chip deals with Meta [2][9][11]. Stock Performance - As of November 25, Alphabet's stock price reached $326, marking a 2.4% increase and a historical high. The stock has seen a cumulative increase of over 11.5% in the past five trading days and 22% in the last month [2]. - Alphabet's market capitalization is approximately $3.84 trillion, making it the third-largest company globally, just behind Nvidia and Apple [2]. Wealth Impact - The surge in stock price has significantly increased the wealth of Google's founders, with Larry Page and Sergey Brin now ranked as the second and third richest individuals globally, surpassing Jeff Bezos [5]. AI Breakthroughs - The core drivers of Google's stock increase are two major advancements in AI: the impressive performance of the Gemini 3 model and a potential deal for Google's AI chips with Meta [9][11]. - Gemini 3 has received widespread acclaim for its speed and capabilities, outperforming OpenAI's ChatGPT-5 in several benchmarks [9][10]. AI Chip Developments - Google's latest TPU chip, "Ironwood," is reported to be the most powerful and energy-efficient custom chip to date, with a potential multi-billion dollar deal with Meta for its use in data centers [10][11]. - This deal could allow Google to capture about 10% of Nvidia's annual revenue, establishing a competitive position in the AI hardware market [11]. Cloud Computing and AI Demand - Google's cloud AI infrastructure head indicated that the company needs to double its computing power every six months to meet the explosive demand for AI services, aiming for a 1000-fold increase in computing power over the next 4-5 years [12]. Competitive Landscape - Nvidia has responded to concerns about Google's AI chip potentially disrupting its market dominance, asserting that its technology remains a generation ahead [14][15]. - Despite Google's growing attention in the AI chip space, Nvidia still holds over 90% of the AI chip market share [15]. Strategic Shifts - Google's successful turnaround in the AI race is attributed to the launch of Gemini 3, which has restored market confidence and attracted industry leaders back to its products [19][20]. - The company has been promoting its TPU chips through cloud services, which may pose a long-term threat to Nvidia's market position [22]. Legal and Financial Developments - A recent antitrust ruling allowed Google to maintain its search business structure, alleviating concerns about potential disruptions to its revenue streams [23]. - Warren Buffett's Berkshire Hathaway has invested approximately $4.3 billion in Alphabet, signaling strong confidence in the company's future [24]. Search Business Resilience - Google's search advertising revenue increased by 15% in the third quarter, indicating that its core business remains robust despite the rise of AI technologies [25].

在全球人工智能技术从虚拟感知迈向物理交互的临界点，具身智能的浪潮正以前所未有的势头重塑科技疆界。 然而，这条通往通用机器人的道路上，始终横亘着一道难以逾越的鸿沟 ， 那就是 高质量、大规模、标准化 的真实世界操作数据极度稀缺。数据的匮乏，如同燃料短缺，严重制约着人形机器人模型能力的跃迁与规模化 落地。 近日，全球首个面向真实作业场景的全尺寸人形机器人真机数据集 ——"LET数据集"正式发布， 并开源首批 60,000+分钟数据 。 这不仅是国内开源规模最大的全尺寸人形机器人真机数据集，更以其超过六万分钟的真 机实采数据、多模态融合架构与全场景覆盖能力，精准命中了行业最核心的痛点。它的出现，并非简单增加了 一个数据来源，而是为整个具身智能领域注入了关键的"数据新燃料"，有望驱动一场从"机械执行"到"自主理 解与推理"的范式革命。 ▍ 人形机器人数据集为何稀缺？ 人形机器人数据为何如此珍贵且稀缺？其背后是技术与成本的双重高墙。 在人工智能领域广为人知的 "Scaling Law （ 缩放定律 ） "指出，模型性能随着数据量、模型规模和计算力的增加而显著提升。这一法 则同样适用于正处于爆发前夜的人形机器人与具身智能 ...

点击下方 卡片 ，关注" 具身智能 之心 "公众号 本文只做学术分享，如有侵权，联系删文 >> 点击进入→ 具身智能之心 技术交流群 多年来，机器人基础模型始终以视觉语言预训练作为规模化发展的基石，这使得我们能够将现有大的多模 态模型的语义泛化优势迁移至机器人领域。 然而scaling law好像在具身机器人领域不存在？ 如何在本体机器人领域有效扩展大模型训练，建立可验证的扩展定律，证明机器人智能会随算力数据增长 持续提升，还没有充分论证。这需要一套能拓展新感知运动能力、实现行为泛化的架构训练流程与数据引 擎，并使其随真实物理世界交互产生的海量经验持续进化。 GEN-0来啦~ GEN-0是新型具身基础模型，由Generalist AI Team推出，专为直接基于高保真原始物理交互进行多模态训 练构建。其架构继承视觉语言模型优势又实现突破：原生设计可捕捉人类级条件反射与物理常识，核心特 性"谐波推理"使模型接受同步思维与行动的无缝训练。 项目介绍主页：https://generalistai.com/blog/nov-04-2025-GEN-0 与此同时，这些能力正在实现规模化演进： 跨本体通用性 ：GEN-0 ...

Core Viewpoint - Yao Shunyu has left Anthropic to join Google DeepMind, citing opposition to Anthropic's stance on China as a "hostile nation" and undisclosed internal information as reasons for his departure [2][5]. Group 1: Departure Reasons - Yao Shunyu's departure from Anthropic is attributed to 40% opposition to the company's recent statements labeling China as a "hostile nation" and 60% to undisclosed internal information [2]. - Anthropic has increasingly adopted an anti-China stance, which Yao explicitly mentioned in his blog [5]. Group 2: Anthropic's Business Strategy - Since 2025, Anthropic has been expanding its business while explicitly excluding Chinese capital and markets from its official policies [6]. - On September 5, Anthropic announced a halt to services for companies with majority Chinese ownership, directly impacting subsidiaries in regions like Singapore and Hong Kong [7][8]. - Anthropic completed a $13 billion Series F funding round, tripling its valuation to $183 billion in just six months [9]. Group 3: Competitive Landscape - In response to Anthropic's service restrictions, several Chinese AI companies are seizing the opportunity to offer alternatives, leading to a competitive "technology cold war" [20]. - Major Chinese players, including Alibaba and DeepSeek, are rapidly enhancing their models and services to attract former Claude users [21][23]. - AWS has begun offering competing models from Alibaba and DeepSeek, indicating a shift in the competitive dynamics of the AI market [28][29].

GPT-5 终于要来了。 今天凌晨，OpenAI 宣布将在明天北京时间 1 点召开发布会，与以往二十分钟左右的简短直播不同， 奥特曼刚刚预告发布会将持续一小时，干货满满。 注意，S 被替换成了 5 而在正式登场前夕， 有博主爆料称，奥特曼刚刚宣布向所有员工发放两年期共计 150 万美元的奖金，哪怕是刚入职的新员工也一视同仁。 在过去的半天内，关于 GPT-5 的爆料信息已经陆续浮出水面。比如 GitHub 突然发布了一篇博客文章，标题也直截了当： 从能力描述来看，GPT-5 在推理能力、代码质量和交互理解方面均有所升级，只需较少的提示词就能完成复杂的编程任务，同时还加入了更强大的 Agent 能力。 《GPT-5 现已在 GitHub 模型中面向公众可用》(GPT-5 is now generally available in GitHub Models)。 这篇博客还提前披露 GPT-5 将有四个版本： gpt-5：标准版，专为逻辑推理和多步骤任务打造； gpt-5-mini：轻量版版本，适用于对成本敏感的产品场景； gpt-5-nano：强调运行速度和响应时间，面向极低延迟需求； gpt-5-chat：专 ...