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。
#行业动态
#行业动态
今日 1 条
阑夕@foxshuo精选AI 评分6565
elsewhere articlesAI 评分2424 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。
Aidan Gomez@aidangomezAI 评分3434
Peter McCrory@PeterMcCroryAI 评分4646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@modestproposal1Anthropic'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"
Noam Brown@polynoamialAI 评分1919看到 Levent 在抄袭指控上变本加厉,非常难过。我希望我在 @AnthropicAI 的朋友们能在内部站出来反对这件事。到现在应该已经很清楚真相是什么了。
Jensen Huang@JensenHuangAI 评分4646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.
Jensen Huang@JensenHuangAI 评分3939引用Business Insider@BusinessInsiderCoreWeave's 2029 commitment to Nvidia A100 GPUs challenges the short-lived AI chip narrative. https://bit.ly/4wkKn8t
elsewhere articlesAI 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。
Runway NewsAI 评分4848 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。
Runway NewsAI 评分4040 Paramount CTO Phil Wiser 谈如何弥合愿景与屏幕之间的差距
Paramount CTO Phil Wiser 将 AI 列为史上最重大的技术趋势之一,甚至可进前五,理由是它正快速压低部分知识工作的成本。他认为 ChatGPT 还不算 AI 的"iPhone 时刻",真正的标志性产品尚未出现,而这一窗口可能只有 5 到 10 年。
Runway NewsAI 评分3737 Nvidia 高管 Richard Kerris:故事本身正在成为界面
Nvidia 媒体与娱乐业务 VP 兼 GM Richard Kerris 在 2026 Runway AI Summit 上提出,实时渲染、生成式 AI 之后,可对话的智能体将让故事本身成为界面。
elsewhere articlesAI 评分4646 英灵殿 Odin 谈 AI for Science:要做全模态分子世界模型与通用科学人工智能
英灵殿创始人 Odin 在播客中称,他要做的是"全模态分子世界模型"和"通用科学人工智能",把人类科学进程压缩上百年。其团队约 30 人,已融资数千万美元,用本科生带做 8 个靶点并做出 sub 纳摩尔级活性分子,短期内坚决不做药物管线。
Sierra Blog精选AI 评分6161 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。
AI as Normal TechnologyAI 评分4949 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。