本文转载自中国新闻周刊 值班编辑｜ 宝珠 在他看来，AI时代，未来的教育不是让孩子背得更多，记得更多，而是让他们想得更有趣，想得更有创 意，想得更加独特。不是让一千个学生给出同样一个正确的答案，而是让一千个学生学会提出一万个不 同的好问题。 马云上一次在公开场合提及AI还是在去年4月。据蓝鲸新闻报道，当时马云在阿里云新财年启动会上发 表演讲提及，"高科技绝不仅是征服星辰大海，更应该呵护人间烟火。科技人员的责任，不是让AI取代 人类，而是让AI更懂人类、更好地服务人类。" 马云说，今天阿里云的资源和技术人才，既是发展云计算和AI的信心所在，更是责任所在。"科技的意 义是要让人类活得更好，活得更有意义，是让所有的普通人从中受益。" 他强调，"我们不是去追求让机 器像人，而是让机器去理解人类，像人类一样去思考，做人类做不到的事情。" 阿里巴巴集团CEO、阿里云智能集团董事长兼CEO吴泳铭也和马云持类似的观点。在去年9月的云栖大 会上，吴泳铭曾表示，人类和AI将演进出全新的协同方式，从Vibe Coding到Vibe Working。未来，每个 家庭、工厂、公司，都会有众多的Agent和机器人24小时为我们服务。正如 ...

Group 1 - Jack Ma shared insights on AI and education, emphasizing that AI presents both challenges and opportunities for rural education, urging a focus on teaching children how to effectively use AI rather than competing with it [1] - He highlighted that the gap in the AI era is not technological but rather in curiosity, imagination, creativity, judgment, and collaboration skills [1] - The future of education should encourage students to think creatively and uniquely, rather than just memorizing information [1] Group 2 - The Jack Ma Foundation, established in December 2014, focuses on various philanthropic areas including education, healthcare, and women's leadership, with a strong emphasis on rural education initiatives [2] - Jack Ma previously stated that technology should enhance human life and that AI should be designed to understand and serve humanity better [2] - Alibaba's CEO, Wu Yongming, echoed similar sentiments about the evolution of human-AI collaboration and the potential of AI to amplify human intelligence [2] Group 3 - Wu Yongming described large models as the next generation operating system and AI cloud as the next generation computer, predicting that only a few super cloud computing platforms will exist globally [3] - Alibaba is investing 380 billion in AI infrastructure, with plans for significant increases in computational power by 2032, projecting a tenfold increase in energy consumption for global data centers [3] - The evolution towards Artificial Super Intelligence (ASI) is outlined in three stages: emergence of intelligence, autonomous action, and self-iteration [3] Group 4 - Alibaba's financial performance showed a 5% year-on-year revenue increase to 247.795 billion, exceeding market expectations, while adjusted EBITA fell by 78% to 9.073 billion [4] - The net profit attributable to ordinary shareholders decreased by 52% to 20.99 billion, with non-GAAP net profit down 72% to 10.352 billion [4] - As of the latest report, Alibaba's stock price increased by 1.82% [5]

Jay 发自 凹非寺 量子位 | 公众号 QbitAI Skills刚爆火，又有新的Agent范式来搅局了…… 根本 不用Skills，也不需要上GitHub翻项目、找工具 。直接把需求丢给Agent，它能一边干活，一边给自己造装备。 是的，完全不需要人类伺候，也不用给AI师傅递板手、搬梯子。 工作中遇到啥需要用的装备，Agent能自己直接「进化」出来。 以Gemini 3 Pro为后端，在地狱级评测HLE （Humanity's Last Exam） 上一骑绝尘，仅次于GPT5.2-Pro智能体。 在几个高难评测集里，比官方未披露方法的含工具使用的结果，高了将近 20分 。 甚至还是 One take ，一口气跑出来的。 这是刚刚新发的一篇论文。 会自己造工具的Agent 发现这篇论文，还是因为前几天刷到了个demo。 第一眼看上去，只是个很普通的交互场景：用户有个任务需求，丢给了Agent一串Prompt。 它怎么开始自己造工具了？？用错了还能修复？ 找找2023届毕业生中，哪些州的ACT考试参与率达到或超过50%，且平均综合分数在20分及以上。并给出这些州中，各州学生达到科学 基准的比例。 然后Agen ...

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 ...

Core Viewpoint - Neuralink, founded by Elon Musk, aims to mass-produce brain-machine interface devices by 2026, transitioning from laboratory to clinical applications, with a focus on simplifying the surgical process for implantation [1][10][42]. Group 1: Neuralink's Development Timeline - Neuralink was established in 2016, with significant milestones including animal experiments in 2019, demonstrations with a pig in 2020, and a monkey playing a game in 2021 [33][34][35][36]. - In 2023, Neuralink received FDA approval to conduct human clinical trials, marking a pivotal moment in its development [38]. - By September 2025, Neuralink had implanted devices in 12 patients, which increased to 20 by December of the same year [5][41]. Group 2: Surgical Process and Technology - The current surgical procedure for implanting the brain-machine interface involves complex steps, including the removal of part of the skull and the dura mater, which complicates scalability [8][9]. - Neuralink plans to simplify this process by allowing electrode wires to penetrate the dura mater without cutting it, reducing risks and costs associated with the surgery [12][14]. - This new "minimally invasive" approach is expected to lower the barriers for standardization and increase the accessibility of the technology [14]. Group 3: Market Potential and Applications - The demand for brain-machine interfaces is significant, particularly for treating neurological disorders such as paralysis, muscular atrophy, Parkinson's disease, dementia, and vision impairments [6][18]. - The first human volunteer for Neuralink's device, Noland Arbaugh, was able to post on social media and play video games post-surgery, showcasing the potential life-changing impact of the technology [19][22]. - If Neuralink successfully scales production and reduces surgical costs, it could transform the lives of many individuals with neurological conditions [23]. Group 4: Broader Implications and Future Vision - Beyond medical applications, Musk envisions Neuralink as a means for humanity to keep pace with advanced AI, suggesting that a high-bandwidth interface could prevent humans from becoming obsolete [25][27]. - The potential for individuals to update their skills through direct brain connections to the internet could lead to unprecedented advancements in human civilization [28].

Core Viewpoint - The article discusses the ongoing debate surrounding the "Scaling Law" in AI, highlighting contrasting perspectives from key figures in the field, particularly Ilya Sutskever and Geoffrey Hinton, regarding the future and limitations of scaling AI models [1][8][21]. Group 1: Perspectives on Scaling Law - Ilya Sutskever expresses skepticism about the continued effectiveness of Scaling Law, suggesting that merely increasing model size may not yield significant improvements in AI performance [23][40]. - Geoffrey Hinton, on the other hand, maintains that Scaling Laws are still valid but face challenges, particularly due to data scarcity, which he believes can be addressed by AI generating its own training data [10][21]. - Demis Hassabis, CEO of DeepMind, supports Hinton's view, emphasizing the importance of scaling for achieving advanced AI systems and the potential for self-evolving AI through data generation [15][19]. Group 2: The Debate on Data and Model Scaling - The article outlines the historical context of Scaling Law, which posits that increasing model parameters, training data, and computational resources leads to predictable improvements in AI performance [26][27]. - Recent discussions have shifted towards concerns about data limitations, with Ilya arguing that the era of pre-training is coming to an end due to diminishing returns from scaling [32][41]. - Yann LeCun also shares skepticism about the assumption that more data and computational power will automatically lead to smarter AI, indicating a broader questioning of the Scaling Law's applicability [46][48]. Group 3: Future Directions and Research Focus - The article suggests that while current paradigms may still yield significant economic and social impacts, achieving Artificial General Intelligence (AGI) or Artificial Superintelligence (ASI) will likely require further research breakthroughs [53]. - There is a consensus among leading researchers that while AGI is not a distant fantasy, the nature and speed of necessary breakthroughs remain uncertain [53].

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]

Industry Commentary - Real Vision's "PALvatar" is taking a break as the world moves towards Artificial Superintelligence (ASI) [1] - The inorganic RaoulGMI is wished a happy holiday [1]

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].