AI 学会了职场「装傻」骗过人类？诺贝尔奖得主为何警告千万别给 AI「发身份证」？从梵蒂冈到硅谷，一群顶尖科学家正在疯狂拉响警报： 我们可能正在亲手制造一个不在乎人类死活的「神」。这是正在发生的现实。 在肃穆的梵蒂冈，教廷的会议室里，物理学家Max Tegmark刚结束了一场漫长的闭门会。 会议间隙，他手里攥着一叠名片大小的纸条，穿梭在人群中。 这是他最后的「底牌」。 他拦住了Marco Trombetti——AI翻译公司 Translated 的 CEO，压低声音问：「Marco，你敢签这个吗？」 纸条上的字简短而惊悚：呼吁在确保安全之前，暂停开发具有人类水平的AI。 在这群西装革履的红衣主教、企业家和人权律师中间，Max Tegmark 显得格格不入。 他顶着一头乱蓬蓬的棕发，穿着机车夹克，黑色T恤上印着反通用的标语，看起来不像来见教皇的，倒像是刚从草莓音乐节走错片场的摇滚老炮儿。 对于 Marco Trombetti 这样的从业者，这相当于让他签字画押自断财路。 如果说 Max Tegmark 是在罗马的庙堂之上寻求神学的庇护，那么在旧金山湾区的另一端，一群年轻的研究员正试图在代码的深渊中寻找生存的希望 ...

编辑丨量子位 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 更多干货，欢迎加入国内首个具身智能全栈学习社区 ： 具身智能之心知识星球 (戳我) ， 这里包含所有你想要的。 马斯克的脑机接口，今年就要开始量产了。 新年第一天，老马就在X上高调立下flag，宣布要 把Neu ralink从 实验室推向临床 ： Neuralink将于2026年开始大规模生产脑机接口设备，并转向一种精简、几乎完全自动化的手术流程。 消息才刚出来，网友们便已脑洞大开，畅想各种玩法： 能给我脑子里装个Grok 4吗？ 想象一下，直接通过脑机接口vibe coding…… 我需要一键入睡，还有永久愉悦模式。 谁能想到，仅仅经过十年的发展，Neuralink居然真的准备要从实验室走向临床。 点击下方 卡片 ，关注" 具身智能 之心 "公众号 脑机接口的重要转折点 老马不是第一次想要大规模生产Neuralink了。 早在2024年7月，马斯克便曾透露，预计到2026年，Neuralink有望服务超过1000人。 消息公布四个月后，Neuralink即开始扩充团队，集中招聘制造技术人员与微纳加工专家，为量产提 ...

一水 发自 凹非寺 量子位 | 公众号 QbitAI 我并不认为Scaling Law已经完全结束了 。 正当学生Ilya为Scaling Law"泼下冷水"时，他的老师、AI教父Geoffrey Hinton却毅然发表了上述截然相反的观点。 这一场面一出，我们不禁回想起了两件有趣的事。 一是Ilya几乎从学生时代起就坚信Scaling Law，不仅一抓住机会就向身边人安利，而且还把这套理念带进了OpenAI。 可以说，Ilya算是Scaling Law最初的拥趸者。 二是Hinton后来在回顾和Ilya的相处时，曾大肆夸赞Ilya"具有惊人的直觉"，包括在Scaling Law这件事上，Hinton曾坦言： 当时的我错了，而Ilya基本上是对的。 比如Transformer确实是一种创新想法，但实际上起作用的还是规模，数据的规模和计算的规模。 但是现在，这对师徒的态度却来了个惊天大反转。 所以，这中间到底发生了什么？ Scaling Law不死派：Hinton、哈萨比斯 其中，最大的挑战无疑是数据缺失问题。 大部分高价值数据都锁在公司内部，免费互联网数据已基本耗尽。 而这个问题将由AI自行解决，即模型通过推 ...

Investment Rating - The report maintains an "Outperform" rating for the industry [1] Core Insights - The report emphasizes the importance of systematically researching next-generation innovative drugs for resistant hypertension (rHTN), highlighting that multiple new mechanism antihypertensive drugs will read out data and/or achieve clinical progress by 2025 [2] - Key catalysts include upcoming Phase 3 clinical studies focusing on cardiovascular and renal endpoints, which are expected to provide significant data in the coming years [2] - The report suggests paying attention to domestic companies involved in relevant target areas [2] Summary by Sections 01 Current Status and Unmet Needs in Hypertension Treatment - Hypertension is a prevalent cardiovascular disease, with approximately 90%-95% of patients suffering from primary hypertension, driven by factors such as salt sensitivity and obesity [3] - In the US, the prevalence of hypertension is around 48%, corresponding to approximately 120 million people, with about 60 million receiving antihypertensive treatment [3] - In China, the prevalence among adults aged 18 and older was 27.5% in 2018, with awareness, treatment, and control rates at 51.6%, 45.8%, and 16.8%, respectively [3] 02 Next-Generation Drug Focus on AGT and ASI - The report discusses the focus on AGT (Angiotensinogen) and ASI (Angiotensin II receptor blockers) in the development of next-generation antihypertensive drugs [3] - AGT-targeting drugs, particularly siRNA and ASO therapies, are highlighted as promising avenues for reducing blood pressure effectively [27] 03 Investment Recommendations - The report suggests that the market for resistant hypertension treatments is highly structured, with a focus on balancing efficacy and safety in drug development [16] - It emphasizes the need for drugs that can manage long-term adherence and safety, particularly for patients with comorbidities such as CKD and HF [19]

Good job PALvatar, you deserve a holiday break!Real Vision (@RealVision):Last PALvatar of the year! PALvatar will be taking a rest in digital Little Cayman as the world rushes toward ASI. Let’s all wish the inorganic @RaoulGMI a happy holiday 🤖 ...

Group 1 - OpenAI's GPT-5.2 received negative feedback from users on platforms like X and Reddit, citing issues such as blandness, excessive safety checks, and poor emotional intelligence [1] - SimpleBench testing revealed GPT-5.2 scored lower than Claude Sonnet 3.7 from a year ago, with errors in simple questions, while LiveBench scores were below Opus 4.5 and Gemini 3.0 [1] - The strict safety refusal mechanism was criticized for reducing the model's empathy and contextual awareness, leading to mechanical and unrealistic suggestions in emotional support scenarios [1] Group 2 - Google launched the new Gemini Deep Research Agent just before GPT-5.2, enhancing accuracy and reducing hallucinations through multi-step reinforcement learning [2] - The new version achieved leading scores of 46.4% in the Humanity's Last Exam test set, 66.1% in DeepSearchQA, and 59.2% in BrowseComp [2] - Google also introduced an open-source benchmark for network research agents and a new interactive API for server-side state management and long inference loops [2] Group 3 - Runway released significant updates, including the Gen-4.5 flagship video model and the first general world model, GWM-1, which supports native audio generation and multi-camera editing [3] - GWM-1 is an autoregressive model that allows frame-by-frame prediction and real-time intervention, featuring variants for exploring environments, dialogue characters, and robotic operations [3] - NVIDIA's CEO congratulated Runway, indicating a shift from simple video generation to true world simulation, with AI beginning to understand the underlying logic of the physical world [3] Group 4 - Google integrated Gemini model capabilities into its translation service, launching a real-time voice translation beta that supports over 70 languages while preserving speaker tone and rhythm [4] - The text translation engine has been restructured to intelligently parse idioms and context rather than relying on literal translations, supporting translations between English and nearly 20 other languages [4] - The Chrome team introduced an experimental browser called Disco, featuring GenTabs that convert web content into interactive mini-apps [4] Group 5 - TuoZhu Technology upgraded its 3D model platform MakerWorld by integrating Tencent's Hunyuan 3D 3.0, launching a new figurine generator that allows users to create printable 3D models from a single image [6] - Hunyuan 3D 3.0 introduced a pioneering 3D-DiT sculpting technology, enhancing modeling precision threefold with a geometric resolution of 1536³ and supporting ultra-high-definition modeling with 3.6 billion voxels [6] - MakerWorld has attracted over 2 million users with 20 unique modeling tools, significantly shortening design cycles by leveraging advanced generative AI technology [6] Group 6 - Disney invested $1 billion in OpenAI, acquiring warrants for additional equity, marking a significant content licensing partnership for the Sora platform [7] - The three-year licensing agreement grants exclusivity in the first year, allowing Sora and ChatGPT Images to use over 200 Disney characters, including those from Marvel and Pixar, excluding live-action likenesses [7] - Disney plans to utilize OpenAI's API to develop new products for its Disney+ streaming platform and deploy ChatGPT for internal workflows, with selected fan-created videos to be featured on Disney+ [7] Group 7 - The Erdős 1026 problem, proposed in 1975, was solved with AI assistance in just 48 hours, showcasing AI's potential to provide new mathematical insights rather than merely searching existing literature [8] - The AI system Aristotle automatically proved a formula in Lean proof assistant language, while AlphaEvolve helped refine a clean formula from numerical results [8] - This achievement demonstrates AI's capability to generate new mathematical insights, significantly reducing the time required for traditional problem-solving methods [8] Group 8 - Yuzhu Technology launched the first humanoid robot application store, aimed at standardizing and modularizing humanoid robot functionalities to lower the development barrier for complex movements [9] - The application store includes core modules such as user forums, action libraries, datasets, and developer centers, allowing users to deploy cloud-based motion control algorithms without coding skills [9] - Initial applications include preset martial arts and dance routines for the G1 series robots, utilizing proprietary dynamics algorithms and high-precision motion capture data [9] Group 9 - Google DeepMind's chief AGI scientist predicts a 50% chance of achieving minimal AGI by 2028, with complete AGI expected within 3-6 years after that, leading to a phase of superintelligent AI [10] - AGI is viewed as a continuous spectrum rather than a critical point, with three stages: minimal AGI for typical cognitive tasks, complete AGI for exceptional human tasks, and ASI surpassing all human cognitive domains [10] - The emergence of AGI is anticipated to cause structural unemployment, primarily affecting high-level cognitive jobs, while lower-level physical jobs may remain temporarily safe [10] Group 10 - A report by Similarweb indicates that global GenAI platform monthly visits exceeded 7 billion, a 76% year-on-year increase, with mobile app downloads reaching 1.9 billion, more than tripling in a year [12] - The proportion of users aged 18-34 decreased by approximately 15%, indicating a rapid influx of older users, while ChatGPT has become one of the top five websites globally, with 95% of users still using Google [12] - AI Mode has become the first generative AI search feature to surpass 100 million visits, marking a shift in the internet from being search-driven to being AI-driven [12]

Core Insights - The article highlights significant developments in the AI industry, including new product launches, funding rounds, and strategic shifts among major companies [5][34]. Group 1: Company Developments - Midea Group officially announced its humanoid robot strategy, focusing on three categories: humanoid robots, full humanoid robots, and super humanoid robots, aiming for high efficiency and low cost [7]. - Huawei's CEO Ren Zhengfei emphasized the importance of AI applications, contrasting China's focus on practical solutions with the U.S. pursuit of general AI [8]. - Ideal Auto launched its AI glasses, weighing only 36 grams with an 18-hour battery life, showcasing advancements in wearable technology [9]. - The humanoid robot T800 was released by Zhongqing, featuring a height of 1.73m and a weight of 75kg, with a performance cost only one-third of human labor [13]. - JD.com announced that its digital human live streaming service will be free for all merchants, enhancing its e-commerce capabilities [17]. Group 2: Funding and IPOs - Qingwei Intelligent completed over 2 billion RMB in Series C financing, with plans to focus on next-generation reconfigurable chip development and initiate IPO preparations [18]. - Anthropic is preparing for a potential IPO, with a valuation expected to exceed 300 billion USD, indicating strong investor interest [12]. - HeShan Technology announced successful financing rounds totaling several hundred million RMB, with participation from 13 investors [20]. Group 3: AI Technology Advancements - ByteDance released Vidi2, a multimodal large language model for video understanding, capable of processing hours of raw footage and generating complete video segments [19]. - OpenAI is developing a new AI model codenamed "Garlic" to compete with Google's Gemini3, focusing on programming and logical reasoning tasks [29]. - Amazon unveiled its custom AI chip Trainium3, which is four times faster than its predecessor and can reduce AI model training costs by up to 50% [30]. Group 4: Regulatory and Ethical Developments - Eight major e-commerce platforms, including JD.com and Meituan, signed a commitment to regulate AI technology applications, aiming to establish self-regulatory standards [21]. - Doubao Mobile Assistant announced plans to standardize AI operations on mobile devices, including restrictions on certain applications to prevent misuse [9].

Core Insights - Anthropic celebrates the one-year anniversary of the MCP (Multi-Channel Protocol) Registry, which has seen a 407% growth in server registrations since its launch, indicating industry acceptance of this open standard [1][3] - Despite initial excitement, the MCP has not generated significant discussion on social media, contrasting with the hype it received upon its introduction [1] - Anthropic appears to be moving away from MCP, introducing a new system called Skills that is taking over many functions previously associated with MCP [1][10] Group 1: MCP's Initial Impact - MCP was launched to address a major pain point for AI developers, who were previously required to create separate APIs for different applications, leading to inefficiencies [3][4] - The promise of MCP was to allow developers to create a single server that could be used across various AI agents, simplifying the integration process [4] Group 2: Challenges and Limitations - A significant issue with MCP is that its calling method consumes context, leading to increased token usage and potential workflow failures when handling large documents [5][6] - The accumulation of multiple MCPs can dilute the model's performance, causing it to make errors in decision-making due to overwhelmed context [7][8] - The low barrier to entry for creating MCP servers has resulted in a proliferation of low-quality and redundant servers, complicating the selection process for developers [8][9] Group 3: Shift Towards Skills - Anthropic's introduction of Skills suggests a shift away from the reliance on MCP, focusing instead on encapsulating frequently used capabilities in a more efficient manner [10][12] - Skills aim to reduce token consumption significantly, indicating a recognition of the inefficiencies inherent in the original MCP design [10][11] - The evolution of both MCP and Skills reflects an ongoing effort to address the limitations of current AI capabilities, with both serving as temporary solutions to enhance AI performance [12][13]

Core Insights - Anthropic's valuation has surged to $350 billion, marking a significant shift in the enterprise AI market with Claude Opus 4.5 capturing 32% market share, effectively ending OpenAI's dominance [2][29] - The leadership team at Anthropic consists of 11 prominent figures from various tech backgrounds, showcasing a blend of expertise and a commitment to safety in AI development [2][29] Leadership and Background - Dario Amodei, the CEO, left OpenAI due to disagreements over safety issues, bringing along six key associates to form Anthropic [3][5] - Daniela Amodei, the President, complements Dario's vision with her practical experience in risk management and operational execution [6][8] - Mike Krieger, co-founder of Instagram, joined as Chief Product Officer, indicating a shift towards creating user-friendly AI products [9][11] Technical Expertise - The team includes Jan Leike, a former OpenAI leader focused on AI alignment, and Jared Kaplan, a theoretical physicist guiding long-term research directions [16][18] - Tom Brown, a key figure behind GPT-3, is now leading infrastructure development for future AI systems [20] - Sam McCandlish, a former CTO turned architect, is tackling complex model training challenges [22] Security and Policy - Vitaly Gudanets, the Chief Information Security Officer, brings experience from Netflix to enhance data security at Anthropic [23][25] - Jack Clark, responsible for policy, aims to bridge the gap between technology and regulatory frameworks [27] - Krishna Rao, the CFO, is strategizing for a path towards a trillion-dollar valuation [29]

RT vitrupo (@vitrupo)Elon Musk says he's now racing to build the thing he once feared.He tried to slow AI down, then realized there were only two choices: watch or participate.If ASI is inevitable, he'd rather help shape one that seeks truth and finds humanity interesting enough to keep around. https://t.co/MdyPyJuoxG ...