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#行业动态

今日 6 条
今天10月1日周四
  1. Rohan Paul55

    作者指出美国企业已买入 AI,但尚未证明其回报:标普 500 中 69% 的公司声称有实际 AI 部署,但只有 2% 披露了持续追踪的指标。配图(Apollo Daily Spark 数据)显示,从有 AI 计划或目标(74%)、有部署与使用数据(69%)、量化结果(29%)到追踪指标(2%),披露比例逐级骤降。作者认为 AI 的采用速度远超问责程度,部署已是采购决策,而展示回报仍是例外。

    引用David George@DavidGeorge83

    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

  2. Rohan Paul28

    AI 软件的钱集中在顶层。 仅 2.24 亿高薪知识工作者,占总数的四分之一,却代表了 41 万亿美元市场中的超过 25 万亿美元。 也就是说,收入最高的 25% 知识工作者贡献了 41 万亿美元机会的近三分之二。而他们大多在北美和欧洲 - ARK research

    引用Brett Winton@wintonARK

    If, 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...

  3. Bloomberg:Technology(RSS)25

    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。

9月30日周三
  1. Preferred Networks:AI 研究与产品12

    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。

9月28日周一
9月24日周四
  1. Latent Space(RSS)28

    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。

9月23日周三
  1. Sam Altman29

    michelle 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@michpokrass

    just 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!

9月22日周二
9月21日周一
  1. Nathan Lambert:Interconnects(RSS)72

    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。

9月19日周六
  1. Gary Marcus:The Road to AI We Can Trust(RSS)33

    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。

9月17日周四
9月15日周二
  1. Gary Marcus:The Road to AI We Can Trust(RSS)30

    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。

9月14日周一
  1. Gary Marcus:The Road to AI We Can Trust(RSS)35

    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。

9月11日周五
  1. a16z:News(RSS)43

    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。

9月8日周二
  1. Jensen Huang57

    黄仁勋转发 H100 租金行情并称 NVIDIA 算力是可互换、耐用且高出租率的生产性资产。被引用内容显示,三年前的训练芯片 H100 租金月涨 22% 至 $3.28/小时,与折旧假设相反,市场反而在为这块老芯片支付更高价格。

    引用Ornn@OrnnExchange

    The 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.

9月4日周五
9月3日周四
8月31日周一
  1. Jensen Huang40

    黄仁勋称 AI 正把制造业带回美国、推动再工业化,并带动老化电网与可持续能源投资,靠市场力量而非补贴驱动。AI 还在能源厂、芯片厂和数据中心创造建筑与制造岗位,过去六个月已有 4000 亿美元投入 AI 初创公司。他呼吁建设者与社区合作、赢得信任并创造本地收益。

    引用Gavin Baker@GavinSBaker

    Regret 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.

8月26日周三
8月20日周四
8月14日周五
  1. elsewhere:文章(RSS)25

    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。

8月13日周四
  1. Jensen Huang40

    强大的 A100 集群从 2020 年到 2029 年都具备任务能力。NVIDIA 计算不只是芯片。CUDA 为开发者和 NVIDIA 工程师提供统一平台,在 Ampere、Hopper 和 Blackwell 的整个使用寿命内持续升级。 CUDA 让 NVIDIA 计算多才多艺。多才多艺使其可互换。可互换性驱动利用率并延长耐用性,使 NVIDIA 计算成为生产性资产:可租用、耐用且可融资。

    引用Business Insider@BusinessInsider

    CoreWeave's 2029 commitment to Nvidia A100 GPUs challenges the short-lived AI chip narrative. https://bit.ly/4wkKn8t

8月10日周一
  1. elsewhere:文章(RSS)42

    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。

6月1日周一