听雨 发自 凹非寺 量子位 | 公众号 QbitAI 面对Claude Opus 4.6和GPT Codex 5.3的猛烈攻势，谷歌反手就是一个 Gemini 3 Deep Think 的重大升级。 | | Who | # | = | | --- | --- | --- | --- | | 1 | _ Benq | IEE | 3792 | | 2 | 롤 ecnerwala | 214 | 3715 | | 3 | jiangly | 192 | 3664 | | 4 | VivaciousAubergine | 65 | 3646 | | 5 | Kevin114514 | 104 | 3604 | | б | tourist | 297 | 3592 | | 7 | strapple | ୧୧ | 3486 | | 8 | dXqwq | 83 | 3436 | | ਰੇ | · maroonrk | 208 | 3423 | | 10 | Otomachi_Una | 62 | 3413 | | 11 | မြ ksun48 | 313 | 3408 | | 12 | heuristica | ୧୫ ...

谷歌DeepMind掌门人Demis Hassabis在达沃斯论坛上描绘了AI的终极图景：不仅要在2026年将AI设计的药物送入临床试验，更预言未来10到15年人类将迎 来"发现的黄金时代"。 在瑞士达沃斯举行的世界经济论坛期间，谷歌DeepMind首席执行官德米斯·哈萨比斯（Demis Hassabis）接受了《财富》杂志的专访。 在这场关于人工智能未来的深度对话中，哈萨比斯不仅披露了谷歌大模型Gemini的最新进展，更重点阐述了AI在生物医药领域的颠覆性潜力，以及智能体 （Agents）和机器人技术的爆发时间点。 剑指"解决所有疾病"：2026年或成转折点 作为AlphaFold（蛋白质结构预测模型）的缔造者，哈萨比斯正试图通过其创立的初创公司Isomorphic Labs将这一技术转化为实际的药物疗法。 他在采访中透露了一个关键的时间节点：2026年。哈萨比斯表示： "我们希望到2026年初，首个药物能进入临床试验阶段。" Isomorphic Labs目前正在研究癌症、心血管疾病和免疫学等多个领域，并已与礼来公司（Eli Lilly）及全球顶级制药巨头建立了合作伙伴关系。目前，该公 司已有17个药物项 ...

刚刚，谷歌Gemini 3 Deep Think原地进化！在Codeforces比赛中拿下全球第七，击败了人类选手。短短三个月，全方位刷爆SOTA。 猝不及防，谷歌DeepMind深夜又放大招了！ 今天，Gemini 3 Deep Think重磅升级，几乎刷爆全领域的SOTA，标志着AI推理能力进入了全新维度。 离职Anthropic入职谷歌的华人学者姚顺宇参与了Gemini 3 Deep Think 这一次，在科学研究和硬核工程领域，Deep Think堪称一个「最强大脑」。 它可以将草图渲染成一个高保真、实用的3D笔记本电脑支架图，并直接将其打印出来。 谷歌VP晒出这个副项目，最终的成品是这样子的。 9 ll l 6 | > Top rated | | | | --- | --- | --- | | # | User | Rating | | 1 | Benq | 3792 | | 2 | ecnerwala | 3715 | | 3 | jiangly | 3664 | | 4 | VivaciousAubergine | 3646 | | 5 | Kevin114514 | 3604 | | 6 | ...

从定位上看，Codex-Spark 并不是为了替代现有的 Codex，而是补齐其在"即时交互"场景中的短板：在过去，Codex 更擅长长时间运行的复杂任务，而 Codex-Spark 的目标则非常明确——把人与模型之间的交互延迟压缩到接近"无感"的程度。 这一发布同时也是 OpenAI 与 芯片初创企业 Cerebras 合作的重要阶段性成果。为了减少对英伟达芯片的依赖，上个月 OpenAI 签署了一项金额超过 100 亿 美元的协议，使用 Cerebras 的硬件以提升其模型的响应速度，而 Codex-Spark 被视为这项合作落地的第一个技术里程碑。 为实时而生：Codex-Spark 的核心是"速度" OpenAI 发布新模型，专为实时编码而生 昨晚，OpenAI正式发布了GPT-5.3-Codex-Spark的研究预览版本。这是一款从 GPT-5.3-Codex 主模型中"裁剪"而来的精简版本，同时也是 OpenAI 首个专 门围绕实时编码（real-time coding）场景设计的模型。 在官方定义中，Codex-Spark 是一个"专为实时使用 Codex 而设计的模型"，它支持进行针对性编辑、 ...

Core Viewpoint - Amazon has officially entered a technical bear market after its stock price dropped 21.4% from recent highs, while Microsoft became the first member of the Mag7 to enter a bear market. Investor confidence in the return on investment from AI spending by these companies is low, with Amazon planning capital expenditures of up to $200 billion by 2026 [1][3]. Group 1: Amazon and Microsoft Performance - Amazon's stock closed at $199.60 after eight consecutive days of decline, marking its entry into a technical bear market as the second company in the Mag7 to do so [3]. - Microsoft’s stock price fell 25.9% from recent highs after its Azure cloud business growth failed to meet investor expectations, leading to its entry into a bear market on January 29 [3]. Group 2: AI Spending and Investor Sentiment - The total projected capital expenditure for AI by Amazon, Microsoft, Meta, and Alphabet is expected to reach $650 billion by 2026, with Amazon having the highest planned expenditure [3]. - Meta's stock is close to entering a bear market, just 2.3% away from the threshold, despite exceeding Wall Street expectations for Q4 revenue and earnings, as increased AI spending and profit margin pressures have affected investor confidence [3]. Group 3: Market Dynamics and Cash Flow Concerns - There is a noticeable rotation among Mag7 members, with investors moving away from Microsoft, Nvidia, and Oracle-related OpenAI trades towards Alphabet and Broadcom ecosystems [5]. - Alphabet's vertically integrated technology stack has somewhat mitigated concerns over excessive spending, allowing it to avoid the worst impacts of the tech stock sell-off, with its stock down 9.2% from recent highs [5]. - Increased capital expenditure levels for Amazon may lead to negative free cash flow this year, prompting the company to seek additional capital through debt markets [5].

Summary of Key Points from Conference Call Records Industry and Company Involvement - **Rare Earth Industry**: Emphasis on the rational development of rare earth resources and innovation in rare earth technology [1] - **Tungsten Industry**: Significant price increase in tungsten raw materials, with current prices reaching five times the level at the beginning of 2025 [2] - **Nickel Mining**: Indonesia's substantial reduction in nickel mining output, with expected production between 260 million to 270 million tons, down from 379 million tons in 2025 [3][4] - **Glass Fiber Industry**: Taiwanese manufacturers shifting production from E-glass to low-DK glass fabric due to increased demand [5] - **Cloud Computing and AI**: Meta's investment in a data center and predictions of massive growth in AI token consumption in China [6][7] - **Chemical Industry**: Price adjustments in the pesticide sector and incidents of illegal chemical production leading to regulatory actions [8] - **Dye Industry**: Price increases in disperse dyes due to low inventory levels and market consolidation [9] - **Battery Technology**: Development of solid-state battery standards and strategic partnerships for next-generation battery materials [10] Core Insights and Arguments - **Rare Earth Development**: The need for innovation in rare earth technology to enhance resource utilization [1] - **Tungsten Price Surge**: A 50% increase in tungsten prices within a month, indicating strong demand and potential supply constraints [2] - **Nickel Production Cuts**: Indonesia's drastic cuts in nickel production quotas, with a 70% reduction in the largest nickel mine's output [3][4] - **Shift in Glass Fabric Production**: Taiwanese companies adjusting production lines to meet the rising demand for low-DK glass fabric [5] - **AI and Cloud Market Growth**: Significant investments in AI infrastructure and predictions of a 370-fold increase in AI token consumption by 2030 [6][7] - **Chemical Pricing and Regulation**: The average cost of chlorantraniliprole and regulatory measures against illegal chemical production [8] - **Dye Price Increases**: Anticipated further price hikes in disperse dyes due to low inventory and market dynamics [9] - **Solid-State Battery Development**: Collaboration between companies to innovate in solid-state battery technology [10] Other Important but Potentially Overlooked Content - **Meta's Data Center Investment**: A $10 billion investment in a new data center in Indiana, expected to be operational by late 2027 or early 2028 [6] - **AI Model Developments**: The launch of new AI models and tools aimed at enhancing programming capabilities [7] - **Regulatory Actions in Chemical Sector**: Increased scrutiny and actions against illegal chemical production following a fatal incident [8] - **Market Dynamics in Dye Industry**: The consolidation of the dye industry leading to fewer manufacturers and potential for price increases [9] - **Battery Technology Partnerships**: Strategic collaborations aimed at advancing solid-state battery technology [10]

据最新消息，科技巨头谷歌(GOOG.US)的母公司Alphabet计划发行一种极为罕见的百年期债券。这是20 世纪90年代末以来，科技企业首次发行此类超长期限债券。 谷歌争霸AI 当前，考虑到科技公司为保持在人工智能能力建设竞赛中的领先地位所需筹集的庞大资金量，Alphabet 正在为其人工智能雄心背后的空前支出计划筹措资金，已筹资200亿美元，超过最初预期的150亿美元。 另据科技媒体报道，谷歌此次大规模举债恰逢Meta、亚马逊等四大科技公司纷纷表示将加大支出，预 计将在2026年达到约6600亿美元，以实现其雄心勃勃的人工智能计划。 这部分支出中也有相当一部分正通过债券市场筹集。当然，这些计划直接引发了市场对人工智能军备竞 赛看好，并将推动AI融资热潮，催生一项可能彻底重塑全球经济、具有颠覆性的前沿技术。 摩根士丹利预计，超大规模企业今年将借款4000亿美元，高于2025年的1650亿美元。彭博智库估计，到 2029年，人工智能、云基础设施和数据中心的资本支出预计总计将达到3万亿美元。 互联网大厂抢滩Al入口 在此背景下，公开资料显示，作为全栈式AI的创新企业微美全息(WIMI.US)，一直在押注大模型赛 ...

近期市场基调已转变为对AI颠覆性潜力的担忧，软件、法律服务和财富管理领域等多个行业因此遭到 冲击，投资者正重新思考如何评估这些企业的价值。 南方财经 21世纪经济报道记者吴斌 报道 投资者对AI热潮的追捧促成了美股三年牛市，如今这股热潮已经跌跌撞撞。 美国东部时间2月12日，道琼斯指数收跌1.34%，报49,451.98点；标普500指数跌1.57%，报6,832.76点； 纳斯达克指数跌2.03%，报22,597.15点。 近期，美股市场轮动的趋势正愈发明显。亚马逊、谷歌母公司Alphabet等科技巨头公布了巨额资本支出 计划，加上投资者们对Anthropic新工具的担忧再度加剧，导致众多人工智能相关的企业股票遭到抛 售，资金纷纷涌入其他板块的价值型股票。 即使是近期相对稳健的就业数据也难以提振美股。美国1月份非农就业岗位新增13万个，远超华尔街预 期，失业率也从去年12月的4.4%降至4.3%，但市场在短暂的上扬之后再度疲软。 美国银行认为，2020年以来，以"七巨头"为代表的科技巨头在美股市场上的领导地位正面临"重大威 胁"。随着美国中期选举的临近，投资者应逐步倾向于投资中小盘股票。 巨额支出回报存疑 ...

Core Viewpoint - The article emphasizes that the release of GPT-5.3 Codex and Claude Opus 4.6 on February 5, 2026, marks a critical turning point in AI capabilities, impacting knowledge workers sooner and more broadly than anticipated [2]. Group 1: AI's Rapid Advancement - The author compares the current perception of AI to the early days of the COVID-19 pandemic, suggesting that many are underestimating the scale and speed of AI advancements [3]. - The pace of AI improvements has accelerated significantly, with new models showing substantial enhancements in capabilities and shorter intervals between releases [4]. - The author describes a personal experience where AI independently completed tasks with high quality, indicating a shift in how AI can be utilized in various fields [4]. Group 2: Implications for Knowledge Work - AI's ability to write code is seen as a strategic advantage, enabling the development of more advanced AI systems, which could eventually impact all knowledge work sectors, including law, finance, and healthcare [5]. - The article discusses the ongoing debate about AI's progress, asserting that those who claim AI has hit a wall are likely using outdated models or have a vested interest in downplaying its capabilities [7]. - A timeline of AI advancements is provided, illustrating rapid progress from basic arithmetic capabilities in 2022 to the potential for AI to handle significant coding tasks by 2025 [7][8]. Group 3: Future Workforce Changes - Predictions suggest that AI could eliminate 50% of entry-level white-collar jobs within 1-5 years, with the author noting that this is a conservative estimate [11]. - The article highlights that AI is a general substitute for cognitive work, making it challenging for workers to transition to new roles as AI continues to improve across various domains [11]. - The author emphasizes that the latest AI models exhibit decision-making capabilities that resemble human judgment, raising concerns about job security for many roles that involve computer-based tasks [11]. Group 4: Practical Recommendations - The article provides actionable advice, urging individuals to subscribe to paid versions of AI tools and actively integrate them into their work processes [13][15]. - It encourages users to experiment with AI daily, suggesting that hands-on experience will enhance understanding and adaptability to ongoing changes in the industry [15]. - The author warns that many professionals are currently ignoring AI's potential, and those who leverage it effectively will gain a competitive advantage [14]. Group 5: Broader Implications of AI - The article concludes with a discussion on the potential societal impacts of AI, including both positive advancements in fields like medicine and negative consequences such as increased surveillance and security threats [17]. - The author presents a thought experiment about a hypothetical nation with super-intelligent citizens, highlighting the dual-edged nature of AI advancements [17].

Group 1 - Gold prices experienced a sudden drop, with spot gold falling over 3% and nearly $200 during the day [1] - Silver prices also declined significantly, dropping over 8% [1] Group 2 - U.S. stock indices collectively fell, with the Nasdaq down over 1.5%, the Dow Jones down nearly 1%, and the S&P 500 down 1% [3] - Major tech stocks saw declines, with Apple dropping over 3% and losing more than $120 billion in market value (approximately 82 billion RMB) [5] - Other tech companies such as Microsoft, Amazon, Tesla, Meta, and Nvidia also experienced declines [5] Group 3 - Chinese concept stocks fell sharply, with the Nasdaq Golden Dragon China Index dropping nearly 3% [6]