资讯日报：日本自民党在众议院选举中取得胜利 股票市场概览 港股市场表现 美股市场表现 2026 年 2 月 9 日 资讯日报 海外市场主要股市上日表现 | 指数 | 收盘价 | 日常跌 | 周常失 | 年初至今 | | --- | --- | --- | --- | --- | | | | (%) | (%) | 湖铁 | | | | | | (%) | | 恒生指数 | 26.560 | (1.21) | (3.02) | 3.63 | | 恒生科技 | 5.346 | (1.11) | (6.51) | (3.08) | | 恒生国企 | 9.031 | (0.68) | (3.07) | 1.32 | | 上证指数 | 4.066 | (0.25) | (1.27) | 2.44 | | 日经225 | 53.818 | 0.81 | 1.75 | 7.78 | | 新加坡海峡 | 4.976 | (0.83) | 0.60 | 0.00 | | 标普500 | 6.798 | 1.97 | (0.10) | 1.27 | | 纳斯达克 | 22,541 | 2.18 | (1.84) | (0.91) ...

Big Tech stocks were treading water in premarket trading on Monday, after a bruising week that saw more than $1 trillion wiped from their market caps.As of 6:12 a.m. ET, Oracle was up 1.5% and Microsoft had edged 0.8% higher. Meta was down 0.3% and Amazon was down 0.1%. Alphabet fell 0.6% and Nvidia was down around 1% after rebounding 7.9% on Friday.The market grew jittery last week after expenditure outlooks continued to shoot through the roof in Big Tech earnings last week, as companies doubled down on AI ...

以下文章来源于硬AI ，作者专注科技产研的 硬AI . AI时代，快人一步~ 来源 | 硬AI 随着AI基础设施建设的军备竞赛进入"深水区"，一个令投资者不安的转折点已然浮现：为了支撑AI算力需求，亚马逊、谷歌和Meta正 面临自由现金流被耗尽甚至透支的风险。 根据摩根大通2026年2月5日发布的研究报告，美国四大云巨头——亚马逊、谷歌、Meta和微软，2026年总资本支出预计将达到6450 亿美元，同比激增56%，新增支出将达到惊人的2300亿美元。 对于投资者而言，2026年，或将是紧盯科技巨头资产负债表的一年。 谷歌97%的增速与亚马逊的"现金赤字" 在这场基建狂潮中，谷歌的投入非常激进。 2026年，谷歌的资本支出指引已上调至1750亿至1850亿美元，同比增速高达97%，其资金正疯狂涌向服务器和技术基础设施。 如果说谷歌还只是在"疯狂花钱"，那么亚马逊则堪称"透支未来"。 2026年，亚马逊的资本支出指引约为2000亿美元（同比增长52%）。但问题的核心在于，亚马逊赚回来的现金已经盖不住支出了—— 据标普全球市场分析师预测，亚马逊2026年的运营现金流（OCF）约为1780亿美元。 这意味着，亚马逊 ...

整理 | 美股研究社 在这个快速 变 化的 时代， 人工 智能技术正以前所未有的速度发展，带来了广泛的机会 。 《AI日 报 》致力于挖掘和分析最新的AI概念股公司和市场趋势，为您提供深度的行 业 洞察和 价 值 分析。 A I 快 报 【阿里新一代模型Qwen3.5曝光】 2月9日，在全球最大AI开源社区HuggingFace的开源项目页面中，最新出现Qwen3.5并入 Transformers的新PR（提交代码合并申请）。业内猜测阿里千问新一代基座模型Qwen3.5发 布在即，引起全球AI开源社区热议，有评论称中国大模型引领的"疯狂2月"即将开启。相关信 息透露，千问3.5采用了全新的混合注意力机制，并且极有可能是原生可实现视觉理解的VLM 类模型，有开发者进一步挖掘出，Qwen3.5或将开源至少2B的密集模型和35B-A3B的MoE模 型。 这一最新动态印证了美媒The Information此前爆料Qwen3.5将在春节期间开源的消息，而在 2月初，智谱首席科学家唐杰也曾发微博称，近期将有包括DeepSeek v4、Qwen3.5、GLM- 5等众多新模型登场。 【本田与Mythic宣布联合研发能效提 ...

Core Viewpoint - TotalEnergies has signed two long-term Power Purchase Agreements (PPA) to deliver 1 GW of solar capacity to supply Google's data centers in Texas, representing a significant commitment to renewable energy [1] Group 1: Agreements and Capacity - The new PPAs will provide 1 GW of solar capacity, equivalent to 28 TWh of renewable electricity over a 15-year period [1] - The solar power will be generated from TotalEnergies-owned sites currently under development in Texas, specifically Wichita (805 MWp) and Mustang Creek (195 MWp) [1] Group 2: Construction Timeline - Construction for the solar projects is scheduled to begin in Q2 2026, indicating a future commitment to expanding renewable energy infrastructure [1]

Core Viewpoint - The article discusses the regulatory landscape for technology companies in Europe, particularly focusing on antitrust concerns and the implications for market competition and consumer choice. Group 1: Regulatory Environment - The need to defend and enforce market rules to ensure a competitive environment is emphasized, highlighting that abuse of dominant positions is detrimental to both Europe and the United States [2] - Concerns are raised about potential restrictions on access to services like WhatsApp, which could limit consumer options and competition [3] - The article mentions that the European Union is not focused on the origin of companies but rather on ensuring fair competition through interim measures [6] Group 2: AI and Technology Firms - The article raises questions about the future of AI regulation and whether more cases similar to those against Meta will emerge, indicating a growing concern over concentration and antitrust issues in the AI sector [5] - The potential acquisition of Warner Brothers by Netflix is noted as a deal that may attract scrutiny due to concentration risks, although the specifics of the deal are still unclear [8][9] Group 3: Google and Advertising Technology - Google's significant role in both the US and EU markets is acknowledged, with a focus on ensuring fairness in advertising negotiations and preventing bias in technological platforms [11][14] - The article discusses ongoing efforts by Google to address concerns related to advertising technology and the importance of maintaining a level playing field for competitors [12][14] Group 4: International Trade and Competition - The article highlights investigations into illegal subsidies from China that could undermine European competitiveness, particularly in the wind energy sector [16][18] - The importance of transparency and fair pricing for companies entering the European market is stressed, with a commitment to preventing price dumping [19]

责任编辑：郭明煜 法国石油巨头道达尔能源于周一签署两项长期协议，将为谷歌位于美国得克萨斯州的数据中心供应太阳 能电力。此举也是道达尔能源为把握人工智能发展催生的电力需求增长机遇所做的布局。 法国石油巨头道达尔能源于周一签署两项长期协议，将为谷歌位于美国得克萨斯州的数据中心供应太阳 能电力。此举也是道达尔能源为把握人工智能发展催生的电力需求增长机遇所做的布局。 道达尔能源将从其位于得克萨斯州的两处光伏项目为谷歌供电，项目总装机容量达 100 万千瓦；未来 15 年间，这两处项目将为谷歌提供总计 28 太瓦时的可再生电力，相关项目定于今年第二季度开工建 设。 在一众石油巨头中，道达尔能源走出了差异化发展路径：该企业在布局燃气发电站的同时，持续加码可 再生能源领域投资，并在电力市场放松管制的地区拓展电力业务。这类市场的电价波动能催生可观的交 易机会，美国得克萨斯州的德州电力可靠性委员会管辖市场便是其中之一。 道达尔能源美国区可再生能源业务副总裁马克 - 安托万・皮尼翁表示，这两项协议创下了企业在美国签 署的可再生能源购电协议规模之最。 事实上，道达尔能源此前已通过间接方式为谷歌供电：企业持有美国加州可再生能源企业克 ...

Group 1 - The core point of the article highlights the aggressive marketing strategies employed by AI giants like OpenAI, Anthropic, Google, and Amazon during the Super Bowl, with each company spending between $8 million to $10 million for 30-second ads, reaching approximately 120 million viewers [2] - The ads showcased the intense competition in the AI sector, with Anthropic mocking OpenAI's advertising strategy, emphasizing a fundamental divergence in their business models [2][7] - The marketing push reflects a pressing need for AI technology to appear more "humanized," as only 17% of American adults believe AI will have a positive impact in the next two decades [5] Group 2 - The report from Stanford University indicates that over 80% of global AI computing power is concentrated in North America, highlighting a stark contrast between the marketing narrative of inclusivity and the actual resource distribution [3] - The high advertising expenditures during the Super Bowl signify a shift in the advertising landscape, with traditional advertisers like automotive companies reducing their spending while AI firms fill the void [6] - The strategic investments in advertising by companies like Amazon and Microsoft reflect a broader strategic positioning within the cloud computing ecosystem, with AI platforms expected to exceed $1 billion in digital advertising spending by 2025 [4] Group 3 - The ongoing debate about AI's privacy implications and long-term investment value continues, with concerns about emotional dependency on AI and the potential for hidden data collection practices [6] - The public dispute between Anthropic and OpenAI reveals strategic differences in their business models, with Anthropic favoring an ad-free subscription model while OpenAI explores mixed monetization strategies [7] - The success of the emotional advertising campaign could significantly enhance consumer adoption of AI, but true democratization of AI will depend on making advanced capabilities accessible to developers in lower-resource regions [8]

Core Insights - The construction of AI products has become significantly easier and cheaper, but many still fail due to a lack of focus on problem-solving and product design [3][4] - Leaders need to engage directly with the development process to rebuild their judgment and acknowledge that their intuition may no longer be entirely accurate [3][4] - The era of "busy but ineffective" work is ending; companies must focus on creating substantial impacts rather than hiding behind non-essential tasks [3][4] Challenges in AI Product Development - There is a noticeable reduction in skepticism towards AI, but many leaders still hesitate to invest fully, fearing it may be another bubble [4] - Companies are beginning to rethink user experience and business processes, realizing that successful AI products require a complete overhaul of existing workflows [4][5] - The lifecycle of AI products differs fundamentally from traditional software, necessitating closer collaboration among PMs, engineers, and data teams [4][5] Differences Between AI and Traditional Software - AI systems deal with non-deterministic APIs, making user input and output unpredictable, unlike traditional software with clear decision-making processes [5][6] - There is a trade-off between agency and control; higher autonomy in AI systems means less control, which must be earned through reliability and trust [6][7] Development Approach - A recommended approach is to start with low autonomy and high control, gradually increasing autonomy as confidence in the system grows [7][8] - For example, in customer support, AI should initially assist human agents before taking on more complex tasks [7][8] Continuous Calibration and Development Framework - The CC/CD framework emphasizes continuous calibration and development, allowing teams to adapt to user behavior and improve system performance over time [24][26] - This framework helps in understanding user interactions and maintaining user trust while gradually increasing the system's autonomy [27][31] Key Success Factors for AI Products - Successful companies typically exhibit strong leadership, a healthy culture, and ongoing technical capabilities [13][14] - Leaders must be willing to learn and adapt their intuition to the new AI landscape, fostering a culture that empowers employees rather than instilling fear [14][15] Future of AI - The potential of coding agents is still underestimated, with significant value expected to be unlocked in the coming years as they become more integrated into workflows [36][37] - The focus should remain on solving business problems rather than merely adopting new tools, as the true value lies in understanding user needs and workflows [38][39]

每经AI快讯，2月9日，美股大型科技股盘前多数上涨，亚马逊、微软涨0.8%，特斯拉涨0.5%，谷歌A涨 0.3%，Meta涨0.2%，英伟达、苹果跌0.3%。 ...