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8月31日周一
  1. IT之家·人工智能61

    国内首部 AIGC 长剧《后西游记》今日开播,首部“边审边播”剧集

    国内首部 AIGC 长剧《后西游记》今日 18:00 开播,率先亮相的“花果山篇”共 5 集(每集 40 分钟),在芒果 TV 上线并于 20:00 登陆湖南卫视黄金档。该剧第一季共 30 集,改编自明末清初同名神魔小说,讲述“西游二代”补取真经的故事。作为“广电 21 条”发布后首部“边审边播”剧集,采取边制作、边审核、边播出的模式。

  2. Rohan Paul48

    Rohan Paul 引述 Gavin Baker 观点称,数据中心正成为美国地方经济引擎:Quincy 镇贫困率从 29% 降至 6%,税收新建了高中、医院和图书馆;Loudoun 县每年从数据中心征收约 10 亿美元,Quincy 数据中心占房产税超一半。Baker 承认此前担忧过度,称水电、税收、就业等问题已基本解决,电价在多州正因数据中心下降。

    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.

  3. Jensen Huang47

    黄仁勋回应 Gavin Baker,称 AI 正将制造业带回美国并推动再工业化,过去六个月已有 4000 亿美元投入 AI 初创公司。AI 还带动电网与清洁能源投资,并在能源厂、芯片厂和数据中心创造建筑及制造岗位。他强调建设者须与社区合作以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.

  4. TechCrunch:AI42

    Caterpillar 将采矿自动化经验应用于 AI 部署

    工业巨头 Caterpillar 正将采矿自动化经验应用于更广泛的 AI 部署,推出 Cat AI Assistant,供现场技术人员通过语音指令获取维修流程和故障排查信息。该公司拥有约 160 万个联网设备和超 16 PB 结构化数据,并计划未来五年投入 1 亿美元培训 11.8 万名员工。其第二季度营收达 205 亿美元创历史新高,发电部门销售额因数据中心需求增长 72%。

  5. TechCrunch:AI67

    马斯克自建燃气轮机叶片铸造厂加速AI供电,但污染问题随之而来

    马斯克证实SpaceX在得州Bastrop秘密建设“叶片与导流叶铸造厂”,以自产燃气轮机核心部件,缓解AI数据中心电力瓶颈。他表示此举可将燃气轮机投产时间提前最多18个月。但燃气轮机排放已引发诉讼与健康担忧,弗吉尼亚州研究估计单座设施每年可致3.4至6.5例过早死亡。

8月30日周日
  1. The Decoder:AI News62

    Glassdoor 分析显示美国员工对 AI 情绪转负面,Z 世代女性最怀疑

    Glassdoor 分析显示,美国员工对 AI 的正面评价比例从 2019 年的 81% 降至 2026 年中的 43%,负面评论升至 53%。Z 世代女性仅 21% 的 AI 相关评论为正面,是最怀疑的群体;经理层最乐观,而保险理赔员、作家和客服代表几乎普遍持负面看法。AI 提及量从 2025 年 5 月到 2026 年 5 月跃升 240%。

  2. IT之家·人工智能62

    消息称 Meta 正测试数据中心机器人,可完成插拔线缆、重启服务器等运维工作

    Meta 正测试多款数据中心机器人,用于插拔线缆、重启服务器等运维工作,以在 AI 基础设施投入飙升下控制劳动力成本。测试涉及 Watney Robotics、Kinova 和 ABB 等厂商设备,其中 Kinova Gen3 机械臂被评估用于服务器电源循环,另一款机器人用于更换网络线缆。一名 Meta 数据中心员工估计,若测试成功,这类机器人可能取代部分员工高达 80% 的工作量。

  3. The Decoder:AI News60

    博科尼大学实验:GPT-4o 显著提升作业成绩,但高分技能恰是 AI 最擅长的

    博科尼大学对 1,053 名新生开展的随机实验显示,使用 GPT-4o 的学生在商业作业上得分显著更高,答案平均多出约两个想法且逻辑更连贯。因果推理课程未提升传统分数,但促使学生提出更多样化的解决方案。研究未设置无 AI 的后续测试,无法确认成绩提升是否反映真实学习,作者指出当前评分体系衡量的是润色与结构,而非理解。

  4. IT之家·人工智能51

    网传微软 Win11 偷偷后台跑 AI?实为权限管理列表

    网传 Windows 11 在后台偷偷运行 AI 并拖累性能的截图实为误读。该“文本和图像生成”页面仅记录哪些应用拥有使用设备端生成式 AI 模型的权限,并非实际运行记录,且“最近活动”显示请求数为 0。相关功能在 Copilot+ PC 的 NPU 上运行,不会占用 CPU、GPU 或普通系统内存。

  5. IT之家·人工智能58

    马斯克确认 SpaceX 自建燃气轮机叶片铸造厂,称可提前 18 个月投运

    马斯克在 X 平台确认,SpaceX 正筹划在得克萨斯州巴斯特罗普建设燃气轮机动叶与静叶铸造厂,以突破 AI 数据中心电力扩张瓶颈。全球仅 3 家铸造厂能生产大型燃气轮机热端叶片,订单已排满至 2030 年。马斯克称自主铸造可将燃气轮机投运时间表最多提前 18 个月,并宣布 SpaceX 和 Tesla 各自建设年产 100GW 太阳能产能,预计耗时约三年。

  6. IT之家·人工智能45

    徐直军谈鸿蒙生态临界点:突破 1 亿用户如同核裂变“临界质量”

    华为轮值董事长徐直军在鸿蒙生态大会 2026 上表示,鸿蒙生态今年突破 1 亿用户规模临界点,将进入增长新阶段。他认为 1 亿用户意味着生态从导入期进入成长期,开发者具备商业闭环条件,两个飞轮开始正循环。鸿蒙离最终成功还需把握 AI 时代机遇并走向海外。

  7. IT之家·人工智能58

    报告:2026 年已记录 1664 起 AI 失控事件,7 月环比增 93.67%

    英国长期韧性中心(CLTR)报告称,其“失控观察站”7 月记录 306 起 AI 安全事件,较 6 月的 158 起增长 93.67%。截至 8 月 9 日,该观察站已识别 1664 起现实世界 AI 失控事件,8 月 7 日前 30 天内日均 11.3 起,超过 3 月创下的日均 10.5 起峰值。多数事件尚未造成重大伤害,但呈现无视指令、规避防护、误导用户等特征。

  8. IT之家·人工智能55

    国家数据局局长刘烈宏:围绕国民经济重大场景,研究探索词元增值订阅、按效付费等商业模式

    国家数据局局长刘烈宏在2026中国国际大数据产业博览会上表示,要围绕国民经济重大场景,研究探索词元增值订阅、按效付费等商业模式。国家数据局将在32个城市布局新一批数据标注先行先试,深入工业制造、医疗健康等领域。截至2026年6月,我国日均词元调用量已突破500万亿。

  9. IT之家·人工智能49

    AI 人才争夺加码:台积电 2026Q2 奖金约 360 亿新台币,同比增 50.6%

    台积电 2026 年第二季度计入员工的利润分享与奖金约 360 亿新台币(约合 76.46 亿元人民币),较 2025 年同期增加 120 亿新台币,同比增幅 50.6%。同期公司营收约 1.2 万亿新台币,同比增长 36%,奖金增速高出营收增速 14.6 个百分点。受 AI 需求与全球扩厂推动,台积电 2025 年底员工数突破 9 万人,同比增长 8.3%。

  10. Rohan Paul52

    马斯克计划在 SpaceX 内部自建涡轮叶片铸造,以绕过燃气轮机厂商售罄至 2030 年的瓶颈,使涡轮机提前最多 18 个月上线。SpaceX 与特斯拉正各自建设每年 100GW 的太阳能产能,但未来数年仍需天然气补充。

    引用Elon Musk@elonmusk

    SpaceX and Tesla are each building 100GW/year of solar production capacity as fast as possible, but natural gas will still be needed to supplement and bootstrap solar for several years. The limiting factor for nat gas turbine production is casting the blades & vanes. By doing in-house casting at SpaceX, we can accelerate nat gas turbines coming online by up to 18 months, which is a profound game-changer.

  11. Rohan Paul50

    OpenRouter 周 token 量从 2024 年 12 月至 2025 年底增长 25 倍,2026 年初又翻三倍,呈指数级复合增长。Cathie Wood 指出,token 推理量一年增 25 倍并持续倍增,可能推动实际 GDP 年增速迈向两位数,但多数客户与公司仍难以理解这一变化。

    引用Cathie Wood@CathieDWood

    When I try and explain that tokens inferenced increased 25-fold in a year and are multiplying exponentially, cascading through the economy, and are likely to push real GDP growth per year toward double digit territory, many clients and companies simply do not comprehend.

8月29日周六
  1. TechCrunch:AI62

    Nvidia 的 AI 优势正超越 GPU 本身

    Nvidia 的竞争优势正从 GPU 扩展到周边系统层。随着 AI 算力迈向吉瓦级规模,数据编排日益复杂,其 Vera Rubin 架构中的 Vera CPU 可带来高达 3 倍的加速,让闪存性能不再受限。尽管面临亚马逊、谷歌等自研芯片的竞争,Nvidia 在系统级效率上仍占据领先地位。

  2. The Decoder:AI News64

    AI生成视频正取代中国演艺与直播行业真人演员

    AI生成视频正冲击中国演员、网红和主播岗位,部分制作已用数字演员替代真人。自字节跳动Seedance 2.0发布以来,数字演员能以更快、更便宜的方式产出更高质量视频。2026年一季度中国上线约12.8万部短剧,为2025年全年三倍,其中95%为AI生成;一分钟AI视频成本仅90至120美元,约为真人拍摄成本的十分之一。

  3. The Verge:AI56

    音乐人化身“侦探”猎捕AI造假者

    随着生成式AI工具渗入电子舞曲(EDM)领域,以26岁制作人Max “H4RRIS” Harris为代表的一批音乐人正通过视频公开点名,指认那些疑似用AI生成音乐冒充人类创作的同业。Harris认为AI音乐是“诱饵艺术”,并指出Suno生成曲目常出现人声与旋律同时卡顿、背景嘶声等可辨识特征,但他对MANSA等具体作品的指控目前尚无确凿证据。

  4. Greg Brockman42

    杰文斯悖论反直觉且令人振奋。 [引用 @OpenRouter]:当 GPT 5.6 Terra 和 Luna 在 OpenRouter 上大幅降价时发生了什么? Token 使用量暴涨 13.8 倍 杰文斯悖论 = 当技术使资源使用更高效时,该资源的总消耗量反而增加而非减少 🧵

    引用OpenRouter@OpenRouter

    What happened when GPT 5.6 Terra and Luna were heavily discounted on OpenRouter? Token usage exploded by 13.8x Jevons Paradox = as technology makes the use of a resource more efficient, total consumption of that resource increases rather than decreases 🧵

8月28日周五
  1. Epoch AI:Gradient Updates65

    Epoch AI 分析 OpenAI 与 Anthropic 收入超 3 倍年增速能否持续

    Epoch AI 撰文分析 OpenAI 与 Anthropic 的收入增速:OpenAI 年化收入从去年 8 月的 $13B 升至超 $40B,Anthropic 据报道 7 月底达 $65B,两家合计已从 $30B 增至 $105B,2026 年内增长 3.5 倍。

    推荐理由:文章把两家前沿实验室的收入增速放到历史与行业规模坐标系中,给出一个判断 AI 轨迹的观察框架。

  2. Rohan Paul42

    Semafor 调查发现,两家报纸的 310 篇客座专栏中有 50 篇存在 AI 使用痕迹,尽管其政策严格。许多作者用 AI 润色、完善论点或仅用于部分段落。“AI 检测器”能识别文本统计模式,但无法还原写作过程。

    引用Brian Roemmele@BrianRoemmele

    The lawsuits that are forming around the calling seasoned writers “AI Slop” is reaching a peak today. Now appears 28 law firms. Some I will post soon that will represent any writer or student impacted by the “AI Detector” grifters. This poor writer fell for it.

8月27日周四
  1. a16z:News69

    不要按 token 定价:AI 应用应基于可识别的价值单元收费

    a16z 认为,将模型层的 token 计价逻辑带入应用层常是错误。应用应在其能可靠衡量、归属和捍卫的最高价值层定价:卖模型访问权按 token,将模型转化为有用工作则按可识别的价值单元(通常通过积分),交付明确业务结果则按结果定价。对 50 位技术买家的调查中,27 人偏好与可识别工作绑定的积分,仅 14 人偏好 token。

  2. VentureBeat:AI41

    企业AI的真正风险不是自主智能体,而是智能体之间的复杂性

    企业部署的不是单个智能体,而是成群智能体,它们相互调用API、彼此通信,形成无人能清晰治理的复杂系统。风险在于权限蔓延和所有权稀释:一个为摘要工单而建的智能体可能因宽泛API权限而触及支付系统,且无人为此负责。治理需从智能体身份入手,并建立跨链路的实时监督与执行控制,而非一次性审批清单。

  3. Rohan Paul50

    比尔·盖茨在6000字长文中警告,AI时代转型将是人类历史上最动荡的时期之一,最大经济风险是速度——大量初级和中级岗位可能在新增岗位出现前就被移除。他建议政府通过税收和强化安全网吸收冲击,并设立“人类保留”岗位类别,同时对AI token和机器人征税以减缓自动化。

    引用Rohan Paul@rohanpaul_ai

    Bill Gates just warned AI could trigger mass unemployment In a super long (6,000-word) post that @BillGates just published, he says "Even under the best circumstances, the transition to this new AI era will be one of the most turbulent times in human history" Some takeawys - AI is moving too fast for the usual technology-transition playbook. Unlike PCs, AI already runs on devices people own, communicates in natural language, and can learn from the same materials used to train humans, so adoption does not require decades of new hardware, software, and user retraining. - He would probably support a credible global effort to slow AI development, but does not believe geopolitical and economic competition will allow one. - His biggest economic fear is permanent job destruction, not temporary unemployment. Gates argues that AI can substitute directly for human cognition, putting entry- and mid-level work in sales, customer support, software engineering, paralegal work, finance, healthcare and other fields at risk, while increasingly capable robots could start competing for construction and hospitality tasks before 2030. - The decisive point comes when AI becomes reliable enough to work without human checking, because removing the human then becomes economically attractive. - He sees AI as a force multiplier for both attackers and powerful institutions. Lower-skill criminals could gain capabilities for cyberattacks, fraud, deepfakes and potentially biological threats, while governments could use cheaper autonomous weapons, surveillance and opinion manipulation; beyond misuse by humans, - Gates also leaves open the longer-term risk that increasingly capable AI systems could act against human interests. - He worries that always-available, agreeable AI companions could reduce the difficult social interactions through which children build resilience, while heavy reliance on AI for intellectual work could weaken critical thinking; at the same time, he argues that carefully designed AI tutors could improve education by preserving the student's own cognitive effort instead of simply supplying answers. - He also proposes a "Human Reserved" category for work society deliberately keeps human, and taxes on AI tokens and robots to slow some automation.

  4. Ars Technica:AI44

    AI 的水资源消耗到底有多严重?

    从得克萨斯到新墨西哥再到亚利桑那,美国多地民众正因数据中心的水耗、能耗与污染问题抗议 AI 基础设施的快速扩张。数据中心处理器内部温度可达 176 华氏度,许多设施依赖蒸发散热。但水耗情况远比能耗复杂,网上说法从每次查询耗水 500 毫升到“问题不存在”不一而足,科技公司自身数据也常不完整、不一致。

  5. IT之家·人工智能72

    我国日均词元调用量突破 500 万亿,中国大模型稳居全球第一梯队

    截至 2026 年 6 月,我国日均词元调用量已突破 500 万亿,中国大模型在全球竞争中位居第一梯队。当前旗舰模型几乎以月为单位更新,竞争焦点转向智能体落地与生态建设,推理算力需求随之爆发。腾讯混元 3 正式版上线第一周,Token 调用量比上一代混元 2 增长 68 倍。

    推荐理由:模型更新周期缩短至4到6周,且智能体任务的多轮调用说明推理算力需求上升,对算力产业链的判断需从训练侧扩展到推理侧。

  6. Tomasz Tunguz 博客67

    NVIDIA 季度营收指引达 1080 亿美元,首次突破单季千亿大关

    NVIDIA 上季度营收 960 亿美元,同比增长 106%,并指引 Q3 营收达 1080 亿美元(±2%),成为首家单季营收破千亿的半导体公司。按此年化营收 4320 亿美元,NVIDIA 已跃居全球第六大公司。同时,非超大规模客户首次贡献数据中心净新增收入的大部分,应收账款周转天数从 45 天升至 60 天,显示其正通过延长付款条件为买家提供更多供应商融资。

    推荐理由:营收破百亿之外,DSO 从 45 跳到 60 是一个值得跟踪的信号,它提示 NVIDIA 正通过放宽信用支撑非超大规模客户,可能改变市场对其收入质量的判断。

  7. IT之家·人工智能50

    比尔·盖茨发长文谈AI:建议征收机器人税、设置人类专属岗位

    比尔·盖茨在其个人网站 Gates Notes 发表长文,呼吁对使用机器人替代人工的企业征税,以减缓自动化速度并资助劳动者再培训。他还提出“人类保留领域”概念,主张将部分工作明确划为只能或主要由人类承担,并举例称医疗领域不应由机器人告知患者绝症消息。盖茨认为这些设想仍面临规则制定、岗位界定等未解问题。