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#行业动态

今日 1 条
今天10月2日周五
  1. 阑夕65

    意大利规模第一的银行Intesa负责私人财富业务的总裁Paolo Molesini遭遇电诈,骗子仿冒CEO账号发WhatsApp消息,并用AI伪造公司律师的声音让他相信催款是真的,向中国大陆和香港的几个卡号转了约1.08亿美金。他的团队察觉不对后紧急报警,在中国执法部门配合下追回6000万美金,其余款项已被兑换成加密货币不知所踪。

    推荐理由:原文记录了AI伪造声音与仿冒账号结合的诈骗全过程和追回结果,读者可以据此了解这类组合骗术的作案路径。

9月28日周一
  1. elsewhere articles24

    心资本韩彦谈AI投资:泡沫之外,早期布局与非共识判断才是长期价值

    心资本创始合伙人韩彦在SuperReturn Asia 2026 AI & Deep Tech Investing Summit上表示,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。他以沐曦MetaX、曦望Sunrise等早期投资为例,强调从Day 0开始理解技术演进、坚持非共识判断,并指出未来只有既拥有长期数据积累又能用好AI的"1%"VC才能持续胜出。

9月17日周四
9月12日周六
  1. Peter McCrory46

    这是该模型的一个重要局限。我们聚焦于 AI 转型的供给侧(AI 能做什么、扩散多快、劳动者转岗多快)。 价格是灵活的,总需求等于经济体的产出能力。 更多思考见 🧵

    引用modest proposal@modestproposal1

    Anthropic's economic scenario analysis is interesting. But this is not something you can ignore, this is the most important consideration! "the model cannot generate the negative feedback in which disruption depresses demand and amplifies its own labor-market consequences"

9月9日周三
8月31日周一
  1. Jensen Huang46

    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,由市场力量而非补贴驱动。他表示 AI 正在能源厂、芯片厂和数据中心创造建筑与制造岗位,过去六个月 AI 初创公司获投 4000 亿美元。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13日周四
  1. Jensen Huang39

    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 工程师提供了共同平台,让 Ampere、Hopper 和 Blackwell 在整个使用寿命期内持续升级。 CUDA 让 NVIDIA 计算具备通用性。通用性让它可互换。可互换性驱动利用率并延长耐用性,使 NVIDIA 算力成为一项生产性资产: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 articles42

    「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 戴冠兰在播客对谈中提出,模型能力已经足够,下一场竞争将转向 Agent Infra。Runta 是硅谷 Agent Infra 创业公司,刚完成由 a16z 投资的 2000 万美元 Seed 轮,Jeff Dean、李飞飞以个人天使身份参与。戴冠兰认为未来 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。

8月4日周二
  1. Runway News48

    EA 如何将生成式 AI 带入可生活的可玩世界

    EA 首席战略官 Mihir Vaidya 提出,游戏 AI 的下一站不是"万物皆神经网络",而是兼具生成能力与确定性控制的神经符号架构。他强调游戏要求 AI 以每秒 60 帧、跨数千名玩家同步持续响应,赛车游戏中轮胎阻力系数必须"被玩家感受到"而非只是看起来对。他将 AI 影响分为效率、扩展与变革三个层面,并以累计超 5 亿玩家的《模拟人生》为例说明扩展空间。

8月3日周一
7月13日周一
6月4日周四
  1. Sierra Blog61

    Sierra 复盘按结果定价的实践:SaaS 危机与 AI 智能体的商业模型选择

    Sierra 回顾 2024 年 12 月提出按结果(outcome-based)定价以来的经验:自那时起 S&P 500 上涨约 30%,而 SaaS 指标 WCLD 下跌约 15%。文章引用 Madhavan Ramanujam 的 2x2 框架(自主性与结果归因)定位定价模式,认为按结果定价只有在软件高度自主且结果可清晰归因时才可行,并判断最终能存续的是卖结果而非卖访问权的公司。

    推荐理由:Sierra 作者基于自身按结果定价的实践复盘其得失,并用一个 2x2 框架解释为何席位制 SaaS 正承压。

2月13日周五
  1. AI as Normal Technology49

    AI 不会自动让法律服务更便宜

    一篇发表于 Lawfare 研究论文系列的文章指出,先进 AI 默认不会帮消费者以更低成本获得理想法律结果,因为监管壁垒、对抗性动态和人类参与这三重瓶颈仍待解决。文章以 GPT-4 通过律师资格考试为背景,指出即便生产力提升、单项法律任务成本下降,诉讼双方仍会陷入工作量军备竞赛,总成本居高不下。