行业周报 | 计算机 超级模型带来超级应用 计算机行业周观点第 48 期 核心结论 OpenAI 推出 ChatGPT Health 布局医疗健康领域，开启超级入口的垂直化 实践。我们认为这一垂直化布局或体现了超级入口向高频场景渗透的战略意 图，旨在通过多维数据整合与隐私保护设计输出更个性化回答以抢占"第一 触点"，为构建个人超级助手奠定基础。1 月 8 日，OpenAI 宣布推出 ChatGPT Health，正式踏入医疗健康领域。OpenAI 数据显示，每周有超过 2.3 亿人 在公司平台上询问健康和保健问题，医疗健康市场需求庞大。据 OpenAI 介 绍，ChatGPT Health 由 OpenAI 和全球医生携手开发，旨在提供清晰、实 用的健康信息。过去两年间 OpenAI 已与超过 260 名医生展开合作，围绕 30 个重点领域累计收集超过 60 万次针对模型输出的反馈，以持续优化回答的 专业性与适用性。OpenAI 已与健康数据连接基础设施提供商 b.well 合作， b.well 与约 220 万家医疗服务提供商存在合作关系，将为 OpenAI 用户上传 医疗记录提供后端集成。此外，用户还可连 ...

Core Insights - DeepSeek plans to launch a new AI model, V4, in mid-February, focusing on enhanced programming capabilities [2] - Internal tests suggest that V4 may outperform competitors like Anthropic's Claude and OpenAI's GPT series in code-related tasks [2] - V4 has made significant advancements in handling and understanding long code prompts, which will be beneficial for developers working on complex software projects [2] Additional Notes - The launch date coincides with the Chinese New Year, leading to humorous remarks about DeepSeek's tradition of major updates during holidays [2] - A prediction poll indicated that February 2026 is a popular choice for future updates, with over 1600 votes [2]

华见早安之声 请各位听众升级为见闻最新版APP，以便成功收听以下音频。 市场概述 美国最高法院暂未公布对特朗普关税的判决，非农就业数据好坏参半，标普500涨0.6%，创新高，纳指100涨1%。周五与关税高度相关的股票盘中下跌。英 特尔大涨超10%，CEO此前与特朗普会面。甲骨文涨近5%。 非农报告强化了市场对于美联储1月维持利率不变的预期，对利率敏感的2年期美债收益率上行4.39基点。 中国财政部：4月起取消光伏等249种产品增值税出口退税，明年起取消电池产品增值税出口退税。 美国12月非农增5万人不及预期，失业率降至4.4%，年度增幅创2020年以来新低。"新美联储通讯社"称12月非农就业给按兵不动铺路，交易员预 计1月几无可能。特朗普"泄密"，提前12小时发帖曝光美非农就业数据。 美元四连涨，升至一个月高点。美元兑日元一度涨穿158，报道称日本首相拟解散议会，为提前大选铺路。 加密货币周五走低，比特币一度跌破9万美元。比特币在周初强劲上涨后回吐涨幅，全周大致收平。 现货黄金价格上涨0.7%，重回4500美元上方，本周累计涨超4%、重新逼近历史高位。现货白银涨3.8%，本周飙升10%。由于伊朗加强了对国内抗 ...

21世纪经济报道记者章驰 OpenAI高薪招募AI安全负责人，防范AI能力滥用 OpenAI CEO Sam Altman近日发文称，OpenAI正在招聘一名新的Head of Preparedness（备战负责人）， 年薪为55.5万美元（约合389万元人民币），并提供期权。该职位隶属于OpenAI的Safety Systems团队， 负责为模型构建能力评估、威胁建模和缓解措施，搭建一套连贯、严谨且可规模化运行的安全流程，以 限制人工智能可能带来的负面影响。 Sam Altman表示，这是一个在重要时刻承担关键角色的岗位，模型能力正快速提升，不仅已经能完成 许多有价值的任务，也开始带来现实挑战。他特别提到，大模型对心理健康的潜在影响在今年已有预 览，而在网络安全领域，模型已经好到开始发现关键漏洞，这意味着如何防止这些能力被滥用，将是该 岗位的核心任务之一。OpenAI已有一套较为成熟的能力测量体系，但接下来需要更加细致地理解这些 能力可能如何被滥用，并在产品和现实世界中设计出有效的约束机制，让社会在享受AI带来的巨大收 益时，尽量减少风险。 每周，"合规周报"会盘点最近一周国外人工智能、科技竞争、个人信息保 ...

Core Viewpoint - Meta is shifting its AI model release strategy to better promote the development of "personal superintelligence," emphasizing the need for careful management of associated risks and selective open-sourcing of content [3][5][11]. Group 1: Shift in Open-Source Strategy - Mark Zuckerberg's recent statements indicate a significant change in Meta's approach to open-source AI, moving from being a "radical open-source advocate" to a more cautious stance on which models to open-source [6][8]. - The company previously viewed its Llama open-source model series as a key competitive advantage against rivals like OpenAI and Google DeepMind, but this perspective is evolving [5][9]. - Meta is unlikely to open-source its most advanced models in the future, which could lead to increased expectations for companies that remain committed to open-source AI, particularly in China [10][11]. Group 2: Investment and Development Focus - Meta has committed $14.3 billion to invest in Scale AI and restructure its AI department into "Meta Superintelligence Labs," indicating a strong focus on developing closed-source models [11][12]. - The company is reallocating resources from testing the latest Llama model to concentrate on developing a closed-source model, reflecting a strategic pivot in its AI commercialization approach [12][14]. - Meta's primary revenue source remains internet advertising, allowing it to approach AI development differently than competitors reliant on selling access to AI models [11]. Group 3: Future of Personal Superintelligence - Zuckerberg envisions "personal superintelligence" as a means for individuals to achieve their personal goals through AI, with plans to integrate this concept into products like augmented reality glasses and virtual reality headsets [14]. - The company aims to create personal devices that can understand users' contexts, positioning these devices as the primary computing tools for individuals [14].

Core Viewpoint - The article highlights the significant achievements of Chinese authors in the field of computational linguistics, particularly focusing on the award-winning paper from DeepSeek that introduces a novel sparse attention mechanism for long-context modeling, showcasing its efficiency and performance improvements over traditional methods [1][17]. Group 1: Award and Recognition - The ACL announced that over 51% of the award-winning papers for 2025 had Chinese authors, with the USA at 14% [1]. - A paper by DeepSeek, led by author Liang Wenfeng, won the Best Paper award, which has generated considerable discussion [1]. Group 2: Technical Innovations - The paper introduces a Natively Trainable Sparse Attention (NSA) mechanism, which combines algorithmic innovation with hardware optimization for efficient long-context modeling [4][6]. - NSA employs a dynamic hierarchical sparse strategy that balances global context awareness with local precision through token compression and selection [11]. Group 3: Performance Evaluation - NSA demonstrated superior performance in various benchmarks, outperforming traditional full attention models in 7 out of 9 metrics, particularly in long-context tasks [8][10]. - In a "needle in a haystack" test with 64k context, NSA achieved perfect retrieval accuracy and significant speed improvements in decoding and training processes [9][15]. Group 4: Future Implications - The upcoming DeepSeek model is expected to incorporate NSA technology, generating anticipation for its release [17]. - There are speculations regarding the delay of DeepSeek R2's release, attributed to the founder's dissatisfaction with its current performance [17].

Core Viewpoint - The article discusses the competitive landscape of AI models, particularly focusing on DeepSeek and its challenges in maintaining user engagement and market position against emerging competitors like Kimi and others in the "AI Six Dragons" group. Group 1: DeepSeek's Performance and Challenges - DeepSeek experienced a significant decline in monthly active users, dropping from a peak of 169 million in January to a decrease of 5.1% by May [1][2]. - The download ranking of DeepSeek has plummeted, moving from the top of the App Store charts to outside the top 30 [2]. - The user engagement rate for DeepSeek has fallen from 7.5% at the beginning of the year to 3% by the end of May, with a 29% decrease in website traffic [2][3]. Group 2: Competition and Market Dynamics - Competitors like Kimi and others are rapidly releasing new models, with Kimi K2 achieving significant performance benchmarks and offering competitive pricing [1][8]. - The pricing strategy of Kimi K2 aligns closely with DeepSeek's API pricing, making it a direct competitor in terms of cost [8]. - Other players in the market are also emphasizing lower costs and better performance, which is eroding DeepSeek's previously established reputation for cost-effectiveness [7][8]. Group 3: Technological and Strategic Implications - DeepSeek's reliance on the H20 chip has been impacted by export restrictions, which has hindered its ability to scale and innovate [3][4]. - The lack of major updates to DeepSeek's models has led to a perception of stagnation, while competitors are rapidly iterating and improving their offerings [6][12]. - The article highlights the importance of multi-modal capabilities, which DeepSeek currently lacks, potentially limiting its appeal in a market that increasingly values such features [13]. Group 4: Future Outlook - To regain market interest, DeepSeek needs to expedite the release of new models like V4 and R2, as well as enhance its tool capabilities to meet developer needs [12][13]. - The competitive landscape is shifting rapidly, and without significant updates or innovations, DeepSeek risks losing further ground to its rivals [12][14]. - The article suggests that maintaining developer engagement and user interest is crucial for DeepSeek's long-term success in the evolving AI market [11].