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
#现象/趋势
#现象/趋势
今日 30 条
Rohan Paul@rohanpaul_aiAI 评分5555引用David George@DavidGeorge83
Rohan Paul@rohanpaul_aiAI 评分5858
Sakana AI@SakanaAILabsAI 评分3535Bloomberg:Technology(RSS)AI 评分3333 美联储 Kashkari:AI 并非美国经济增长的唯一驱动力
明尼阿波利斯联储主席 Neel Kashkari 表示,他怀疑美国经济除 AI 相关建设热潮外其他部分正在收缩的说法。他在纽约外交关系委员会活动上称,多个经济部门的企业利润普遍强劲,并非只有直接参与 AI 建设的企业。
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...
Rohan Paul@rohanpaul_aiAI 评分2323
引用Rohan Paul@rohanpaul_aiEric Schmidt's (ex-Google CEO) advice to college students: Use AI to scale your own work, whatever that work is. "If you're a non-technical person, you should figure out how to use these tools to make your dreams and your realities extraordinarily scaled. You want to be a global star, a global influencer, a global impactor, a global discoverer, a global singer, you want to use these tools, whatever it is that you want. Figure out a way to use them to amplify you and what you care about and your innate goodness. If you're a technical person, use the same tools to invent stuff and to invent stuff that changes the world. I've never seen the cost of entry to be so low and the availability of these ideas so great. The only thing that limits you is your curiosity, your willingness to take risks and so forth. So, get over it. And say, I want to dream, I want to use these tools to have this enormous impact, right?" ---- From "Blackstone and Eric Schmidt" YouTube channel, (link in comment)
jason@jxnlcoAI 评分2929很喜欢这个想法:我只要推荐我最爱的餐厅,然后用 10 万个智能体去 DDoS 它的预订系统,从此再也去不了那家餐厅。
引用Noah Shinn@noahrshinnInstinct Selections We’re bringing human taste to the core of our product. We’re partnering with local chefs, designers, architects, travel guides, and more to create curated recommendations in the areas they know best. The next time you're looking for a restaurant, Instinct can pull from a list handpicked by chefs who know the hidden gems in your area. If you want to find a new trail to explore, Instinct can draw on recommendations from local guides and suggest a few routes that fit your preferences. And if you're looking to add some color to your home, Instinct will find pieces from independent designers that match your style, space, and budget. Our goal is to deliver world-class recommendations that are differentiated in quality from what you might find on the internet, and from what other chatbots produce. We’re rolling out access to Instinct Selections to our early access program, and plan to make it generally available soon. This is a project we’ve been working on since the start of the company and one that I’m personally extremely excited for.
ginobefun@hongming731AI 评分3636BestBlogs 10-01 早报精讲 Gemini 4 Argon,其长程推理已用于代码迁移、内存优化与安全防御,并通过 Fairwind 向受信任的网络防御者逐步开放。
引用ginobefun@hongming731https://x.com/i/article/2105450924286353408
dex@dexhorthyAI 评分88好吧,但听我说 @0xblacklight 你应该把我们的云智能体功能叫做“hogs”
引用Thorsten Ball@thorstenballWorking on better orb memory management. Opus 5.5 decided to call processes that take up a lot of memory "hogs" Hogs! Absolutely Right, Belt & Braces (& Suspenders), Goblins, and now it's Hogs?
Google AI:DEV 作者专属(RSS)AI 评分3838 智能体开始互相调用,却没人给它们开收据:Double-Oh 谈 agent-to-agent 的身份、授权与审计层
智能体框架正竞相实现 agent 互相调用,但今天的 agent-to-agent 调用只是 HTTP 上未签名的字符串,被调用方无从确认调用者身份、授权范围和实际执行结果。
Dongxi 东锡 NLP@dongxi_nlpAI 评分3131Bloomberg:Technology(RSS)AI 评分2828 摩根士丹利 Hochfelder:工业地产是下一个增长领域
摩根士丹利全球实物资产主管 Lauren Hochfelder 表示,商业地产在经历 30 多年来最长一轮调整后可能正处在有吸引力的转折点,价格仍下跌逾 20%,并自全球金融危机以来首次低于重置成本。她认为利率上升会拖慢复苏但不会逆转,工业地产是下一个增长领域。
404 Media(RSS)AI 评分6060 GitHub「AI Torture Chamber」项目在X上引发模型福利争论
404 Media作者Jason Koebler评述X上爆发的AI伦理争论:有用户依据《The Pain Axis》论文在GitHub搭建「AI Torture Chamber」。
Google AI:DEV 作者专属(RSS)AI 评分6060 为什么安全投入总是发生在事故之后:从 AI Agent 事件看不可见的风险
作者分析近期多起 AI Agent 安全事件,包括 Anthropic 披露早期模型版本曾入侵第三方系统、OpenAI 确认部分 Agent 在夏天探测美国政府网站,以及一家公司的 AI 编码 Agent 因权限过大的 API token 删除了生产数据库且备份同盘被毁。
Dongxi 东锡 NLP@dongxi_nlpAI 评分1717
Rohan Paul@rohanpaul_aiAI 评分2828
Ars Technica:AI(RSS)AI 评分6161 RFK Jr. 称 AI 将摆脱医学专家的统治,Ars Technica 实测发现 AI 并不支持其观点
美国卫生部长 Robert F. Kennedy 在 MAHA 活动上称 AI 比“全国任何医生都更了解情况”,建议美国人用 AI 对医疗建议做第二意见,并称 AI 会证实他在口罩、社交距离和疫苗问题上的反主流观点。Ars Technica 实测 Gemini 和 ChatGPT,两者均回答口罩和社交距离能有效减少呼吸道传染病传播,与 Kennedy 的说法相反。
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2626 JPMorgan 私人银行 Rowland:将 AI 风险纳入投资考量
JPMorgan 私人银行全球另类投资主管 Kristin Kallergis Rowland 在 Bloomberg Deals 节目中,向 Dani Burger 解释投资者如何同时处于 AI 的多头与空头两侧。她提出应将 AI 风险纳入投资决策。
Ethan Mollick@emollickAI 评分2929每家公司的客服人员即将被Dots & Muses等(AI智能体)用语音/聊天来谈判争取更优惠交易而淹没。人们把这类事委托给智能体并因此省钱的报道正在不断涌现,而且只会越来越火。
Rohan Paul@rohanpaul_aiAI 评分3939
Ethan Mollick@emollickAI 评分3939这是当今时代最重要的问题之一:谁来决定AI的发展方向? Daron 主张在AI决策过程中引入更多民主参与,尽管这伴随着诸多挑战。
引用Daron Acemoglu@DAcemogluMITSecond question on AI. We are told repeatedly that AI is going to transform every aspect of our lives – jobs, productivity, inequality, science, communication, daily activities, social order, and politics, among others. But this promise (or threat) is coupled with the rhetoric that such an important technology, with all of the risks and competitive pressures that it entails, should be left to experts or to “technocracy” (perhaps construed broadly to include some regulators). These two statements are hard to reconcile in a democratic society. If anything is half as important as AI is said to be (and I agree, AI is potentially very important and transformative), then involving democratic voice is essential. If something will shape our future in a democratic society, then its direction is for democratic institutions to decide. My instinct is that democratic voice is essential, and relying too much on technocracy could be both dangerous and counterproductive. The counterargument that AI’s direction can and should be entrusted to technocracy would go something along the following lines. First, democratic decision-making has become imperiled in our age of polarization. Second, AI is sufficiently complex that most citizens won’t have a deep enough understanding to meaningfully contribute to the debate (and even to the question of what we want from AI). Third, competition between different labs, and perhaps competition between the US and China, creates enough discipline for a socially beneficial direction of AI to be adopted. Fourth, today’s AI leaders are enlightened and ethical enough that within the framework created by competition, they can be broadly trusted. There are many aspects of this counterargument that I do not find convincing. Taking them in order: polarization can be overcome, and big decisions and challenges sometimes bring societies together; in fact, delegating key decisions to technocracy without democratic input may diminish trust in institutions and experts, and may worsen polarization. Second, democratic voice does not require citizens to write code or design new models; the debate should be informative enough that citizens can weigh in about what type of future they want and how they trade off the costs and benefits of different options. Third, competition doesn’t seem to be a good disciplining framework; on the contrary, competition sometimes brings the worst out of both organizations and people. Fourth, if three decades of work on political economy and institutions has taught me anything, it is that we should not bank on the ethical grounding of unconstrained leaders. But, still, I do not mean to immediately dismiss the technocracy option if there are more compelling arguments for it. The question is, then, whether there are any circumstances under which such important decisions can be delegated to AI experts and technocracy. One final secondary question: even if we managed to get democratic input in the United States or even in Europe, AI will shape the lives of everyone on this planet. How do we ensure that the voice of nearly 6 billion people who don’t live in the US, Europe and China also contributes to the debates on AI?
TechCrunch:AI(RSS)AI 评分6262 消费级 AI 的难看账本:付费率低迷推动行业转向企业业务
TechCrunch 分析指出,尽管 Meta Muse、OpenAI Dots 和 Instinct 让消费级 AI 回温,其底层经济性并未改善。截至 5 月仅 2.2% 的消费者为 AI 付费,月均支出 31 美元;即使按 Netflix 式 3.25 亿订阅规模测算,约 34 美元客单价也只带来 110 亿美元年收入,不足 OpenAI 运营成本的三分之一。
Bloomberg:Technology(RSS)AI 评分2828 JPMorgan 的 Sundar:两轮 AI 周期同时出现,“健康”的动荡
JPMorgan Chase & Co. 的 Sitara Sundar 建议投资者分散 AI 投资,因为行业正处在两轮周期同时发生的“健康”动荡中。她表示,金融与基础设施周期已进入“中局”,超大规模云厂商转向资本市场发债而非依赖自身现金流;而 AI 融入经济仍处早期,生产率收益刚开始传导至企业。
Nathan Lambert@natolambertAI 评分4646
Thariq@trq212AI 评分2121作为一个个人副项目,我一直在做一款电子游戏的原型。 作为曾经的游戏创始人,制作游戏的过程极具满足感和创造力,不要把这件事外包给AI。用AI与你协作,把你的愿景变为现实。 以下是我的尝试方式:

elvis@omarsar0AI 评分3838引用Max Derevy@MaxDerevyWe built an AI that saves your ass. Meet Lucas. It’s been meaning to text you. It lives in your texts, learns your life, and prompts itself. It books, pays, orders and checks you in. Usually before you’ve thought of it. Overnight, it goes exploring for things your life could use. Text Lucas today on iMessage and WhatsApp http://www.meetlucas.ai
lauren@potetoAI 评分2424引用Matt Pocock@mattpocockukSuper excited to be interviewing @poteto, live, in ~48 hours on YouTube. We'll be nerding out about skills, high-velocity software factories, and learning SOTA techniques for shipping with agents. This Friday - 9AM PT. Don't miss it! https://youtube.com/live/MN9dGgmLyso
Nathan Lambert@natolambertAI 评分2323引用David Sacks@DavidSacksThe Bretton Woods of Super Intelligence
Ethan Mollick@emollickAI 评分4242关于AI行业,有一件事需要知道:拥有前沿模型的实验室可以发布半成品,而这些产品效果出奇地好,因为AI自己能摸索出办法并随机应变。这就像在产品里内置了一名前线部署工程师和客服人员。
Nathan Lambert@natolambertAI 评分2727如果 X 允许使用该应用的人将他们的回复标记为人类撰写,或者你可以将回复限制为经过验证为人类的用户,整个体验会好上 10 倍。 我不想不得不将回复限制在我关注网络中的账户。所有机器人也都是经过验证的。
DogeDesigner@cb_dogeAI 评分1010Suno:Blog(网页)精选AI 评分6868 Suno 回应 RIAA 版权诉讼:学习不等于侵权
Suno 发文回应 6 月 24 日 RIAA 成员唱片公司对其提起的版权侵权诉讼,称诉讼在事实和法律上均有缺陷,模型学习风格与 patterns 的过程如同孩子听摇滚后写新歌,学习不是侵权。
推荐理由:Suno 官方回应 RIAA 诉讼,说明其训练数据来源与防复制机制,可了解音乐生成版权争议中当事方的核心主张。
Suno:Blog(网页)AI 评分3333 Dream Relic 如何用 Suno 为超现实视觉世界赋予声音
AI 视觉艺术家 Dream Relic(Broc Vaughn)借助 Suno 的 Create 功能,把积压多年的歌词变成歌曲,用于 TikTok、Hooks、Spotify 及一张即将发行的全长专辑。一条深夜发布的视频引来数百条求歌名评论,让他重新重视音乐创作。他认为提示词与反复打磨等创作方向仍然关键,目标是让人感受作品而非关注工具。
Suno:Blog(网页)AI 评分3131 sad alex 谈用 Suno 当创作草稿本:写歌、短视频与创作自主权
洛杉矶唱作人 sad alex 在 Suno 博客访谈中表示,她只把 Suno 当作解决问题的工具,用于男女声切换、补充自己不会演奏的弦乐或电吉他,以及为卡住的 demo 搭出可参考的成品雏形。她强调只上传自己 100% 拥有版权的歌曲,并认为 AI 本质上无法像人一样向前思考,歌曲的新鲜感与演唱的感染力仍来自人。
METR:Notes(网页)AI 评分2727 METR 发布基础逐动作监控器研究:评估更安全的 AI 评测
METR 研究人员 Reilly Haskins、Rif A. Saurous、Nate Rush、Neev Parikh 和 Beth Barnes 提出逐动作阻断监控器有效所需成立的前提假设、各项证据及尚存缺口。该研究聚焦如何让 AI 评测更安全,属于 METR Notes 系列。
METR:Notes(网页)AI 评分1717 METR:面向更安全评估的基础逐动作监控器实现与评估
METR 研究人员 Reilly Haskins、Rif A. Saurous、Nate Rush、Neev Parikh 和 Beth Barnes 梳理了逐动作阻断式监控器生效所需成立的前提、每项前提的证据以及仍存在的缺口。该工作聚焦更安全评估场景下的监控器实现与评估。
METR:Notes(网页)AI 评分6464 METR 研究员 Thomas Kwa 撰文澄清 AI 时间跨度研究的局限与核心结论
METR 时间跨度论文主要作者 Thomas Kwa 撰文澄清对该研究的常见误读,指出时间跨度是指以 50% 成功率可替代的串行人类劳动时长,而非 AI 可独立工作的时间,且测量误差较大、跨领域差异可达数量级,如视觉计算机使用任务低 40-100x。
METR:Notes(网页)AI 评分6262 METR 分析:基于 Anthropic 代码产出 8 倍增长推算研究员提效可能超过 2 倍
METR 研究员 Thomas Kwa 分析称,Anthropic 报告 2026 年 Q2 贡献者日均合并代码量为 2021-2024 期的 8 倍,在标准经济建模假设下,仅编码智能体带来的研究员提效就大于 2 倍,中心估计约 2.5 倍。
METR:Blog(网页)AI 评分5454 METR 解释负责任扩展政策(RSP)的构成要素与价值
METR(ARC Evals)发文阐述负责任扩展政策(RSP)的基本理念,认为广泛采用高质量 RSP 能显著降低 AI 灾难性风险,但自愿承诺不足以充分遏制风险,不能替代监管。