Introducing our State of Markets pt 2, along with a companion podcast where we unpack the data and discuss what comes next. Tech is the everything cycle. Supply: putting the buildout in context, just passed railroads as % of GDP. The wisdom of Elon is real: the factory (or the datacenter!) is the product. Demand: diffusion is so, so early. Median AI vendor spending in the top 1% of companies is 8x that of the top 10%. Only about 30% of S&P 500 companies report a quantified AI impact, which means there’s a substantial opportunity in connecting models to a company's data and workflows. Diffusion into companies is one of the main themes of the next 5 years. We’re entering the agent work period. Only a few million users today, but applicable to billions of internet users with massive surplus created. META/GOOG monetize US users at $200+ per year today. Agent opportunity is much higher. Mega-trends the next 5 years: Consumer agents, Robotics, Autonomy, AI x bio, Personal health, Diffusion into enterprise, New era of American Dynamism. Much more in our SoM report here - https://www.a16z.news/p/state-of-markets-ii @a16z @sarahdingwang @aleximm @santiago__rdz
#行业动态
#行业动态
今日 6 条
Rohan Paul@rohanpaul_aiAI 评分5555引用David George@DavidGeorge83
Rohan Paul@rohanpaul_aiAI 评分2828引用Brett Winton@wintonARKIf, as it diffuses, super intelligence can drive a 10x productivity boost for knowledge workers and businesses will pay 10% of the productive value for a piece of software out to the software vendor. There is a $40 trillion AI software market opportunity today...
Bloomberg:Technology(RSS)AI 评分2525 Next Legacy 的 Ryan Nece 谈运动员投资的兴起
Next Legacy 的 Ryan Nece 在 Bloomberg "The Close" 节目中谈退役后如何配置资本,并回应是否把资金全部投入 AI。他表示采用多元化策略,通过基金中的基金和直接投资两个方向布局,已投资 Krizner 和 OpenAI 等公司。其客户包括高净值个人、运动员、网红,以及基金会、非营利组织和捐赠基金等传统机构投资者。
Bloomberg:Technology(RSS)AI 评分1515 Bill Ackman 谈 AI 与 IPO、气候成本及 Paramount 债务融资
Pershing Square CEO 兼创始人 Bill Ackman 在 Bloomberg 节目中讨论 AI 与 IPO、气候成本以及 Paramount 的债务融资。
Nature:Machine Learning 主题(RSS)AI 评分6464 Nikon Small World in Motion 获奖显微视频因使用 AI 引发生物学准确性争议
Ning Xu 凭借展示肺部纤毛运动的视频获得 Nikon Small World in Motion 比赛冠军,多位显微专家质疑视频中紫色、蓝色结构在生物学上不合理,可能由 AI 工具幻觉产生。
Bloomberg:Technology(RSS)AI 评分3333 Ackman:市场只盯着大型 IPO,称 Anthropic 是最伟大的商业故事之一
Pershing Square CEO 兼创始人 Bill Ackman 表示,市场目前只狭隘地聚焦于大型 IPO。他称 Anthropic 是他见过的最伟大的商业故事之一,但未透露是否会投资该公司。这家 Claude 开发商预计今年上市。
METR:Notes(网页)AI 评分4848 METR 研究员 Luca Righetti 分享 AI 生物安全随机对照试验的五点经验
METR 研究员 Luca Righetti 复盘了与 Active Site 合作开展的 AI 生物安全 RCT:153 名新手随机分为 LLM 组与纯互联网组,8 周内完成分子生物学湿实验任务,结果显示 AI 在单个步骤上有帮助迹象,但对三项核心任务的端到端成功率无显著影响。
Dario Amodei:Blog(网页)AI 评分3737 Stripe 播客对话 Anthropic CEO Dario Amodei:ARR 达 50 亿美元与智能体未来
Anthropic CEO Dario Amodei 在 Stripe 的 "A Cheeky Pint" 播客中与 John Collison 对话,谈及 Anthropic 年化收入(ARR)增长至约 50 亿美元。他讨论了 AI 模型表现出的"资本逐利冲动"、对智能体未来的预测、模型生意的经济学,以及 19 世纪活力论(vitalism)概念。
Tomer Tunguz 博客(VC 分析)精选AI 评分6060 Tomer Tunguz 分析 2026 年 CIO 的选择:只投 AI 栈,砍掉其余
Tomer Tunguz 撰文称 2026 年 CIO 的优先级清晰:资金流向 AI 栈,其余被削减。
推荐理由:作者用公开市场分板块数据拆解 AI 时期的软件股分化,指出决定估值的是品类而非增速,分析框架可复用。
Eugene Yan:WritingAI 评分2424 Eugene Yan 的 2022 年度回顾与 2023 目标
Eugene Yan 回顾 2022 年:完成 18/26 篇博客写作,学习并应用 bandits、反事实评估、text-to-image 等技术,2/3 位导师晋升到下一级别,并在 RecSys 线上推荐系统 workshop 发表 keynote,主张多数场景下批量推荐已足够。
Preferred Networks:AI 研究与产品AI 评分1212 Preferred Networks 联合创始人致辞:从应用、基础模型到芯片全栈布局计算
Preferred Networks 联合创始人表示,公司将覆盖从应用、基础模型到计算基础设施与半导体的每一层计算栈,用应用与基础模型预判未来负载并反哺芯片设计,同时以基础设施方向指导模型与应用开发。公司称将与各行业伙伴推进技术开发与社会落地,并以“Learn or Die”为价值观持续推动技术创新。
a16z:News(RSS)AI 评分4747 a16z 发布 State of Markets II:2026 年科技市场图表集
a16z 发布第二版 State of Markets,聚焦 2026 年前两季度股票市场与科技走势。报告指出科技已贡献 SP500 2026 年约 76% 的总盈利增长,主题从软件转向硬件与基础设施,GPU 需求仍超供给,A100 租价不低于年初水平。
elsewhere:文章(RSS)AI 评分2424 心资本韩彦谈AI投资:泡沫之外,早期布局与长期价值才是关键
心资本创始合伙人韩彦在SuperReturn Asia 2026 AI & Deep Tech Investing Summit圆桌讨论上表示,当前AI市场可能存在估值过热和泡沫,但AI仍是这个时代最具实质意义的技术变革之一。
Latent Space(RSS)AI 评分2828 Foundries vs Navigators:AI 如何降低科学研究的成本
在 AI x Science 领域,生物技术公司正沿两条路径适应 AI:Foundries 用新一代测序、高通量显微和物理自动化将实验数据生成速度提升一个数量级,AI 让数据可读可预测,但差异化资产仍是实验数据本身;Navigators 则把 AI 嵌入公司日常流程,驱动更优决策与更快流程,无需专有模型或大规模数据集。
NVIDIA@nvidiaAI 评分1414AI 是由人构建并改进的技术,人有责任以审慎的方式开发和部署它。 而帮助人们从 AI 中受益,意味着认真对待它带来的挑战。 科技行业需要做好这项工作。

Sam Altman@samaAI 评分2929michelle 比任何人都更能体现这一点 openai 真的非常非常幸运,能受益于她迄今为止所做的一切,我想人们会非常高兴看到她和团队接下来在酝酿什么!
引用Michelle Pokrass@michpokrassjust crossed four years at openai! the special thing about this place is the constant capacity for rebirth. for all its faults, there is nowhere quite like it. the team makes high conviction, contrarian bets over and over, and they are mostly right. it's a new company every three months. i have really enjoyed my part in some of the bets, and i'm excited to share some of the current ones we are cooking up now. onward!
Nathan Lambert:Interconnects(RSS)精选AI 评分7272 Nathan Lambert 分析开源权重模型的中美力量对比
Nathan Lambert 发表关于开源权重模型格局的长文,指出中国自2025年7月起在开放权重模型上领先美国,Hugging Face 下载量达约3.2B、约为美国的两倍,GLM-5.3 和 Kimi K3 在 Artificial Analysis Intelligence Index 上得分45和44,领先美国最强模型。
推荐理由:作者基于自己维护的下载量、基准和论文引用数据,系统梳理了中美开源权重模型的实力对比与采用格局。
Gary Marcus:The Road to AI We Can Trust(RSS)AI 评分3333 Gary Marcus 批评 Dario Amodei 七天内三度失信
Gary Marcus 发文列举 Dario Amodei 在七天内损害自身公信力的三种做法:其一是让与 Anthropic 关系密切的 METR 和已有业务往来的 Accenture 充当独立监督方;其二是 Anthropic 正筹备自建湿实验室,却缺乏常规机构审查委员会监督;其三是嘴上呼吁"pace the frontier",实际仍指向 IPO。
Gary Marcus:The Road to AI We Can Trust(RSS)AI 评分3030 Gary Marcus 解读 Sam Altman 的"pacing"表态
Gary Marcus 解读 Sam Altman 在 X 上发帖中的措辞,将其"pacing"说法翻译为:我们会以最快速度推进,只要不进监狱、不被诉讼搞到公司消失,但为了观感,我们把它叫作"pacing"。Marcus 还指出,任何能减少监管不确定性的举措都可能有利于 IPO。
Gary Marcus:The Road to AI We Can Trust(RSS)AI 评分3535 Gary Marcus 评特朗普 9 月 24 日与中国谈 AI 的抉择
Gary Marcus 在 The Economist 撰文提出,特朗普与习近平 9 月 24 日通话将把 AI 列入议程,他认为这可能是特朗普任内最具影响的决定,主张美中不应只谈芯片交易,而应就"AI 向善"寻求合作路径。他同时提到,当前 AI 股票下跌、公众反 AI 情绪升温,部分前盟友如 Steve Bannon 已转向反对阵营,若市场与民调继续走低,特朗普的立场可能生变。
a16z:News(RSS)AI 评分4343 a16z:LP 为何错过 SpaceX、Anthropic 与 OpenAI 这一波 AI 浪潮
a16z 指出,许多 LP 对 SpaceX、Anthropic 和 OpenAI 三家前沿模型公司几乎零敞口,而 SpaceX 上市后市值约 2 万亿美元,成为规模达此前纪录 10 倍的史上最大 VC 背景 IPO,Anthropic 估值 965B 美元、OpenAI 最近估值 852B 美元。作者认为,传统把风投控制在整体组合 5-10% 的资产配置框架已经破裂,LP 需要重新调整风投仓位。
Jensen Huang@JensenHuangAI 评分5757引用Ornn@OrnnExchangeThe H100 is a three-year-old training chip. Its rental price is up 22 percent on the month, to $3.28 an hour. Every depreciation schedule assumes a chip this old only loses value. The market is paying up for it instead.
Newcomer 新闻长文(RSS)AI 评分5050 Tim Cook 退休引发反思:硅谷为何缺乏行业领袖
Tim Cook 退休凸显硅谷缺乏能获行业广泛尊重的领袖,作者回顾其任内 Apple 市值从 3470 亿美元增至近 4.7 万亿美元,但批评他过于重利轻原则。
MIT News(RSS)AI 评分2323 从 MIT 到 IBM:三位研究者如何加速 AI 与量子落地
三位前 MIT 研究生与博士后加入 IBM,借助 MIT-IBM Computing Research Lab 将量子机器学习、强化学习智能体与可信 AI 研究推向工业应用。
Jensen Huang@JensenHuangAI 评分4040引用Gavin Baker@GavinSBakerRegret the tone of my post on data centers yesterday. What I should have said: There were reasonable concerns about data centers 18ish months ago: water, taxes, jobs, electricity prices, the environment and what they would do to small towns. Well-structured data center projects have largely addressed these concerns today and we should be celebrating this. On balance, data centers are awesome for America in every way. On water: U.S. data centers use a fraction of what golf courses use. A lot of the numbers from 18 months ago were off by over 1000x. Newer data centers use closed-loop systems or recycled water. Should be required by every town approving a data center project. On taxes: looking only at sales-tax exemptions, as Ronan Farrow did, is the wrong way to evaluate this. Data centers pay significant property taxes. Loudoun County, which is the wealthiest county in America, now collects on the order of $1 billion a year from data centers. In Quincy, WA, data centers are more than half the property-tax roll. Over time, property taxes can go to zero while government spending increases in these towns. On jobs: this has been unambiguously awesome for blue collar Americans. Demand for electricians, plumbers, welders, HVAC techs, and contractors has gone vertical, and it is not a one-time construction job. These buildings get upgraded and expanded over time. That is why the building trades are fighting for them, and why some unions are now treating opposition to data centers as a reason not to endorse politicians. On power: the original fear was that households would pay for the incremental electricity demand in the form of higher prices. That is why the ratepayer-protection deals and the new large-load tariffs exist. The right structure is: the data center brings or pays for new generation and signs a contract long enough that existing customers are protected. Where that is happening, utilities are cutting or freezing residential rates and saying so on the record. Where it is not, people are right to object. Electricity prices are going down *today* in a number of large states because of data centers. On the environment: data centers overwhelming use natural gas today, which is the cleanest power source outside of nuclear, solar and wind. And the companies that are building the data centers are committed to carbon neutrality such that an equivalent amount of solar will likely be built. Maybe more importantly, the data centers need batteries to function effectively and these batteries can also sell energy back into the grid (which recently prevented blackouts in Texas). Over time, data centers will run on solar plus batteries. On the towns: Poverty in Quincy, WA fell from 29% to 6%. Data center taxes paid for a new high school, a hospital, a library, police and fire stations. This is happening in many left for dead former mill and farm towns that had no other bidder for the land. Data centers are actually reindustrializing parts of America and creating the kind of working-class jobs both parties have spent decades claiming to support. That should not be a partisan issue. Data centers can and should be awesome for America and they increasingly, overwhelmingly are. Supporting the outsourcing of data centers to China will likely age just as well as support for the outsourcing of high quality, blue collar manufacturing jobs to China has aged. When the facts change, I change my mind. I hope that reasonable people who had good faith reasons to oppose data centers at least consider updating their beliefs given the change in the facts over the last 18 months. This really matters for America. I will say I also think the idea of making data centers beautiful is a good one that has yet to be implemented. Data centers should be just as beautiful as Grand Central Station. We can learn a lot from the railroad buildout. Neoclassical revival ftw. Might write up open-weight AI tomorrow as this is equally essential to America.
Newcomer 新闻长文(RSS)AI 评分3636 a16z 的 Martin Casado:看多 AI 应用,看空“独行侠”式 VC
a16z 基础设施团队负责人 Martin Casado 表示,个人 VC 争抢交易功劳是科技投资旧时代的“历史遗物”,现代风险投资不靠个人决策。他称自己做过近 200 笔交易,想不出有哪一笔离得开他人在 sourcing、尽调与成交上的关键作用。
Newcomer 新闻长文(RSS)AI 评分5454 Eric Newcomer 探访 AINS 峰会:Emergence Capital 押注 AI 原生服务是下一个 SaaS
Eric Newcomer 到访 AI 原生律所 Crosby,旁听投资人 Jake Saper 组织的 AINS(AI-Native Services)小型峰会。
elsewhere:文章(RSS)AI 评分2525 Vol.006|对话孟醒:我很怕和别人一样
五源资本合伙人孟醒在访谈中表示,他的人生驱动力是体验与不同,视频剪辑中"体验"出现32次、"不同"出现16次。他回顾了从投行、两次创业到顺为资本、滴滴自动驾驶COO,再到2024年回归投资的经历,并提及在顺为期间投资的 Momenta 已上市。
Jensen Huang@JensenHuangAI 评分4040引用Business Insider@BusinessInsiderCoreWeave's 2029 commitment to Nvidia A100 GPUs challenges the short-lived AI chip narrative. https://bit.ly/4wkKn8t
elsewhere:文章(RSS)AI 评分4242 模型能力已经够了,要卷就卷 infra|对谈 Runta 创始人戴冠兰
Runta 创始人兼 CEO 戴冠兰认为模型能力已经够用,下一场竞争将转向 Agent Infra。Runta 是硅谷 Agent Infra 创业公司,刚完成 a16z 投资的 2000 万美元 Seed 轮,Jeff Dean、李飞飞以个人天使身份参与。他判断未来 agent 数量将超过人类,关键问题变成它们跑在哪、怎么管、出事谁负责。
Import AIAI 评分4444 Import AI 459:AI 监管为何困难、蛋白质折叠模型的缩放定律、以及为 AI 系统灭绝风险定价
Import AI 459 指出,用 AI 监督 AI 训练的自动化对齐研究并非万能方案,英国 AI 安全研究所的论文解释了其难度被低估的原因。本期还收录了蛋白质折叠模型缩放定律的研究,以及为 AI 系统灭绝风险定价的分析。