Key Points The vast majority of AI users opt for free tools, which leaves money on the table for businesses. If Alphabet started showing ads to the free users of its popular Gemini app, it could generate greater revenue. 10 stocks we like better than Alphabet › Alphabet (NASDAQ: GOOGL) (NASDAQ: GOOG) is a digital advertising behemoth, having collected $74 billion in the third quarter of 2025 (ended Sept. 30) revenue from this segment of its business. Its billions of users across its various apps pro ...

【iMobile爱科技资讯】1月26 日，据彭博社资深记者Mark Gurman披露，苹果正以前所未有的速度推进 AI 战略落地，其核心举措是将谷歌的 Gemini 模型深度植入新版 Siri，从而构建出一套真正意义上的系 统级智能交互体验。这不仅是 Siri 诞生以来最彻底的一次"换脑"手术，更象征着苹果在 AI 赛道上从孤 军奋战转向强强联手的战略大转向。 此次变革的核心在于，苹果决定放弃此前效果不佳的零散聊天机器人方案，转而追求极致的系统级整 合。这意味着新版 Siri 将不再只是一个简单的语音应答工具，而是进化为具备深度上下文感知能力 的"系统大脑"。在谷歌 Gemini 强大逻辑推理能力的加持下，Siri 将能够跨越邮件、信息、照片等核心 应用生态，通过识别屏幕内容并结合用户数据，完成从信息归纳到自动化任务执行的复杂操作。 Mac 等全线设备。这场与谷歌的跨界联手，预示着苹果 正试图利用其庞大的硬件生态优势，将全球数亿台设备 一夜之间转化为最先进的个人 AI 助理阵地。 【iMobile爱科技资讯】1月26 日，据彭博社资深记者Mark Gurman披露，苹果正以前所未有的速度推进 AI 战略落地， ...

Apple is figuring out how to participate in the AI race by leaning on its fellow California-based tech peer.Apple has drawn criticism for falling behind in the artificial intelligence race (AI). But the consumer tech heavyweight's latest move signals a calculated approach to push the business forward.Investors looking to gain more exposure to the revolutionary technology in their portfolios might want to consider the company Apple just partnered with. It's the best AI opportunity in 2026 and beyond. Leanin ...

Core Viewpoint - Verizon is likely to be removed from the Dow Jones Industrial Average in 2026, with a trillion-dollar company expected to replace it [3][6][11]. Group 1: Verizon's Current Position - Verizon's stock closed at $39.24 per share on January 21, 2023, significantly lower than other Dow components, with only 241 points contributing to the Dow's total of 49,077 points [1][7]. - Since its inclusion in the Dow on April 8, 2004, Verizon's shares have only gained 17%, indicating minimal growth over nearly 22 years [8]. - The company has a high dividend yield of 7% but is expected to have low-to-mid single-digit growth due to high saturation in the domestic wireless and broadband markets [9]. Group 2: Dow Jones Industrial Average Changes - The Dow has undergone nearly 60 changes since its inception in 1896, primarily replacing underperforming companies with those that have better growth prospects [4][5]. - The index has evolved from being dominated by industrial stocks to comprising 30 diverse, multinational companies [5][7]. Group 3: Potential Replacement for Verizon - Alphabet, the parent company of Google, is seen as the most logical replacement for Verizon due to its significant role in both technology and communications [11][13]. - Alphabet generated 72.5% of its net sales from advertising, which includes a dominant position in global internet search and YouTube, making it a valuable indicator for the Dow [13]. - The company is also a leader in cloud computing and AI, with a sales growth rate exceeding 30%, further enhancing its attractiveness as a Dow component [14][15]. - Following a 20-for-1 stock split in July 2022, Alphabet's share price became more suitable for inclusion in the Dow, currently hovering around $330 [16].

但如果把问题继续往深处追问：推理能力的本质，真的只是多算几步吗？ 谷歌、芝加哥大学等机构的研究者最近发表的一篇论文给出了一个更具结构性的答案，推理能力的提升并非仅源于计算步数的增加，而是来自模型在推理 过程中隐式模拟了一种复杂的、类多智能体的交互结构，他们称之为「思维社会」（society of thought）。 过去两年，大模型的推理能力出现了一次明显的跃迁。在数学、逻辑、多步规划等复杂任务上，推理模型如 OpenAI 的 o 系列、DeepSeek-R1、QwQ- 32B，开始稳定拉开与传统指令微调模型的差距。直观来看，它们似乎只是思考得更久了：更长的 Chain-of-Thought、更高的 test-time compute，成为最常 被引用的解释。 简单理解就是，这项研究发现，为了解决难题，推理模型有时会模拟不同角色之间的内部对话，就像他们数字大脑中的辩论队一样。他们争论、纠正对 方、表达惊讶，并调和不同观点以达成正确答案。人类智能很可能是因为社交互动而进化的，而类似的直觉似乎也适用于人工智能！ 通过对推理输出进行分类，以及结合作用于推理轨迹的机制可解释性方法，研究发现，诸如 DeepSeek-R ...

Core Insights - Synthesia has achieved a valuation of $4 billion following a $200 million funding round led by Alphabet's GV, with participation from notable investors including Nvidia's NVentures and Accel, nearly doubling its previous valuation of $2.1 billion from a year ago [2][3] - The company focuses on developing AI-driven video generation tools aimed at enhancing internal and external communications for enterprises, emphasizing the importance of AI in reducing content creation costs and improving engagement [1][5] - Synthesia's annual recurring revenue (ARR) has reached $150 million, with expectations to exceed $200 million by 2026, indicating strong growth potential in the AI sector [7] Funding and Valuation - The recent funding round has positioned Synthesia as a significant player in the AI market, reflecting a broader trend of increased private investment in AI startups, with European AI companies raising a record $21.4 billion in 2025 [3] - The funding will support the expansion of Synthesia's agentic capabilities, allowing users to interact with AI-generated videos in real time, enhancing training and communication experiences [5] Market Context - The AI investment landscape is booming, with U.S. AI companies raising $162.7 billion in 2025, driven largely by a few major players like OpenAI and Anthropic [4] - The UK government recognizes Synthesia as a success story, highlighting its role in job creation and economic growth through innovation and access to finance [6][7]

特别提示 微信机制调整，点击顶部"仪器信息网" → 右上方"…" → 设为 ★ 星标，否则很可能无法看到我 们的推送。 近 日 ， " 2 0 2 6 年 全 球 品 牌 价 值 5 0 0 强 " 榜 单 (Gl o b a l 5 0 0 2 0 2 6 ) 由 英 国 品 牌 评 估 机 构 " 品 牌 金 融"（Br a n d Fi n a n c e） 在 瑞士达沃斯世界经济论坛 上发布，苹果、微软、谷歌、亚马逊位居 前四，英伟达升至第五名。 每年 ， Br a n d Fi n a n c e会对全球规模前5 0 0 0的品牌进行估值 ， 并发布1 0 0多份报告 ， 对 各 行业和各国家 、 地区的品牌进行排名 。 品牌价值被理解为品牌所有者通过在公开市场上许可 该品牌所获得的净经济收益 。 值得一提的是，继2 0 2 3年上榜（No . 4 6 9）之后，时隔两年， 赛默飞在今年重新以排名4 5 4的 成绩回到榜单之上，同时也成为榜上唯一以科学仪器为主营业务的品牌 。 此外， 美的、海尔、 罗氏、日立、 西门子、通用电气（GE）、飞利浦、雅培 这些涉及仪器 业务的知名品牌也在5 0 0强榜单 ...

如果您希望可以时常见面，欢迎标星收藏哦~ 云服务商的资本支出（Capex）已经达到了无法再用"显著增长"来形容的程度。排名前八的云服务 商的投资额将从2021年的1451亿美元增长到2026年的6020亿美元，增长超过四倍。这种增长速度 简直令人难以置信。 即便如此，市场中仍然流传着关于惯常避险方式的窃窃私语："又是一个泡沫"、"它迟早会破裂"等 等。然而，这些窃窃私语毫无根据，甚至算不上是一厢情愿的想法，而仅仅是逃避现实。这是因 为，当前投资的扩张并非由经济、市场情绪或泡沫驱动，而是由物理定律驱动：大量的计算。 关键在于，生成式人工智能的计算负荷并非"搜索的延伸"，而是不同层次的"学习和推理"。正如稍 后将解释的，谷歌搜索以CPU为中心，而ChatGPT的推理则以GPU为中心，进行大规模矩阵计 算，所需的计算量是其1万到10万倍。 换句话说，云服务提供商增加投资并非出于自愿，而是因为如果不这样做，他们就会在竞争中落 后。无法运行生成式人工智能的云平台毫无价值。正因如此，投资才不会停止，也无法停止。 在本文中，我想论证，目前发生的现象不是"人工智能泡沫"，而是"人工智能趋势"，它正在不可逆 转地重塑半导体市场 ...

2026年12月10日，新德里国际会展中心人头攒动。微软CEO萨提亚·纳德拉站在聚光灯下，宣布将向印度投资175亿美元建设AI基础设 施。 就在同一天，亚马逊也承诺，将在印度投入350亿美元。 这是两个截然不同的印度——一个是硅谷眼中的"全球最大数字市场"，另一个是仍在为基本民生挣扎的发展中国家。当这两个印度相 遇，会发生什么？ 短短几个月内，谷歌、Meta、OpenAI、Anthropic等硅谷巨头纷纷加入战局。总计675亿美元的承诺投资，将在未来五年内涌入这个拥有 14亿人口的国家。 | | Investment Size | Time | Data Center | Data Center Capacity | | --- | --- | --- | --- | --- | | | | Horizon | Location | | | Google | $15B | Through | Visakhapatnam | gigawatt-scale | | | | 2030 | | | | Microsoft | $17.5B | Through | Hyderabad | | | | | 2029 | ...

Core Insights - The article discusses the significant leap in reasoning capabilities of large models over the past two years, highlighting the advancements made by models like OpenAI's o series, DeepSeek-R1, and QwQ-32B in complex tasks such as mathematics and logic [1][2] - It emphasizes that the improvement in reasoning ability is not merely due to increased computational steps but rather stems from a complex, multi-agent-like interaction structure termed "society of thought," where models simulate internal dialogues among different roles to arrive at correct answers [2][3] Group 1: Reasoning Mechanisms - The research indicates that reasoning models exhibit higher diversity of perspectives compared to baseline models, activating a broader range of features related to personality and expertise during reasoning tasks [2][3] - Controlled reinforcement learning experiments show that even with reasoning accuracy as the only reward signal, base models spontaneously increase dialogic behaviors, suggesting that socialized thinking structures enhance exploration of solution spaces [3][4] Group 2: Dialogic Behaviors - The study identifies four types of dialogic behaviors in reasoning trajectories: question-answer sequences, perspective shifts, viewpoint conflicts, and viewpoint harmonization, which collectively enhance cognitive strategies [7][8] - The Gemini-2.5-Pro model's evaluations show high consistency with human scoring, indicating reliable identification of these dialogic behaviors [9][13] Group 3: Social Emotional Roles - The analysis categorizes social emotional roles in reasoning trajectories into 12 types, which are further summarized into four high-level categories, demonstrating a balanced interaction among roles rather than isolated usage [10][22] - The Jaccard index is used to measure the co-occurrence of roles, revealing that models like DeepSeek-R1 organize different roles in a more coordinated manner during reasoning processes [10][22] Group 4: Cognitive Behaviors - The study identifies four cognitive behaviors that influence reasoning accuracy, including information provision, information inquiry, positive emotional roles, and negative emotional roles [11][12] - The consistency of the Gemini-2.5-Pro model's evaluations with human scoring reinforces the reliability of these cognitive behavior classifications [13] Group 5: Experimental Findings - The findings demonstrate that even with similar reasoning trajectory lengths, models exhibit a higher frequency of dialogic behaviors and social emotional roles, particularly in complex tasks [16][23] - Experiments show that guiding dialogic features positively impacts reasoning accuracy, with a notable increase from 27.1% to 54.8% in a specific task when dialogic surprise features are positively reinforced [24][29] Group 6: Reinforcement Learning Insights - A self-taught reinforcement learning experiment indicates that dialogic structures can spontaneously emerge and accelerate the formation of reasoning strategies when only correct answers are rewarded [30]