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mpossible or difficult to disable.” The statement is non-binding but guides how EU regulators assess compliance with the General Data Protection Regulation (GDPR). In India, where Meta has sold Ray-Ban glasses since May 2025, people filmed by wearers have turned to legal notices and police complaints, with no regulatory guidance on who is responsible. What does the EDPB expect from makers? The EDPB said current indicators on smart glasses “leave many non-users unaware that their data is being pr

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hildren, parents and educators, while schools could help identify and respond to cyberbullying, online harassment, image-based abuse and risks associated with algorithmic systems. Meta Lifts Blanket Ban on the Word “Shaheed” following Recommendations from Oversight Board 33 US states sue Meta over harmful effects on the mental and physical health of young people WhatsApp launches Telegram-like Channels feature NHRC seeks reports from Meta, MeitY over alleged use of children in political Instagra

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ender中自主构建了一组高度精细的寺庙建筑群，包括多座建筑、植被和复杂光照，呈现出接近照片的视觉效果。 Gemini 4 Argon生成的宝塔模型 X用户@mweinbach分享的《心灵杀手2》移植案例，则展示了Argon在跨平台工程中的应用。他称，模型协助将游戏从x86 Windows环境移植到原生macOS Arm64环境，涉及指令转换、Rust绑定和Metal着色器转换，项目在M3 Ultra上达到了每秒140多帧。 从真实机器人到科学研究 大型代码库检验的是Argon处理复杂软件系统的能力，机器人项目则考验模型能否理解真实世界中的空间关系和物理交互，并将这种理解转化为可执行的程序。 谷歌展示的Real2Sim项目，正是围绕这一问题展开。 Argon可以观看真实机器人遥操作视频，构建对应的数字孪生环境，并获取或生成仿真资产，使物体不仅外观接近真实对象，在与灵巧机械手接触时也能呈现相似的物理行为。随后，模型通过反复视觉推理调整物体属性和场景设置，让仿真中的视觉效果与接触过程尽可能贴近真实记录。 左（真实视图），同步的真实机器人摄像头画面；右（模拟视图），由Argon重建并校准的3

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在线的智能体、自动化任务。 Git那些适合分布式离线工作的特性，反倒成了仓库扩容的阻碍。那如果从头设计一套源码控制系统，原生就考虑智能体永远在线这个前提会是什么样？ 02.六大设计原则，部分思路与Git截然不同 基于上述现状，他们在构建Scion时在几个核心原则上采取了与Git截然不同的方法，同时其借鉴了大型单体仓库成熟的源代码控制技术，如谷歌的Piper和Meta的Sapling。 其构建Scion的几个核心原则是： 客户端始终在线：Git默认客户端离线工作并且需要仓库的完整副本。由于Anthropic几乎所有的客户端都是智能体和自动化作业，他们围绕一个始终可访问的服务器设计了Scion的客户端和协议，让客户端在需要时获取数据。 客户端-服务器不对称：在Git中，每个客户端都能够充当功能齐全的服务器。在Scion中，服务器负责回答有关文件历史记录和blame的问题，创建提交，执行合并和变基等操作。 客户端维护一个有界本地对象缓存，在磁盘上布局工作副本文件，监控文件系统变更，并为用户提供符合人体工程学的服务器交互方式。客户端自身计算能力有限，但作为交换，它所需的本地数据量也少得多。 一

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zeer和Freitas两位联合创始人，重新「打包」带回了谷歌。 我当时就觉得有点不对劲。。。 这不就是硅谷当下最流行的「反向收购式挖人」吗？？？ 核心技术拿走、灵魂人物带走，留下一个空壳公司和一帮运营团队在风中凌乱。 （对了，Shazeer也是蛮传奇的，老东家反复横跳，谁想到后面谷歌拉了，又跳槽去了OpenAI，属于是一点苦都没吃着。） 随后，公司找来了前Meta和Brex高管Karandeep Anand接任CEO，开始疯狂自救。 但这些修修补补，根本无法挽救失血过多的身体。 根据最新的破产法院文件，Character.AI目前的负债在5000万到1亿美元之间。 账上的钱烧干了，救命的融资进不来，这家曾经的顶流独角兽，终于在五周岁前夕，走向了毁灭。 迪士尼2000万美元抄底：昔日死对头成了接盘侠 这次破产重组里，最具有黑色幽默色彩的角色，莫过于迪士尼。 在破产申请中，迪士尼被列为了「假马竞标者」（起拍底价竞标方）。 迪士尼愿意掏出2000万美元，买下Character.AI的部分资产，并获得某些技术专利的非独占永久使用许可。 2000万美元是什么概念？ 在硅谷好一点的学区，买两栋顶

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ce Schmidtchen（CTO）共同创立，两人此前均曾担任Apple Vision Pro的技术负责人。Taiuti此前还是Luma AI的联合创始人兼CTO，曾为这家3D与视频生成独角兽搭建了底层基础设施。Bryce Schmidtchen则在Apple干了7-8年，参与构建了visionOS软件。 它们的团队还汇聚了来自Apple、Netflix、Meta、Google、Adobe、Replicate以及Microsoft的工程师与研究人员，在图形学、实时系统、交互式媒体以及扩展AI基础设施方面拥有深厚经验。 在Luma AI的经历，让Alberto Taiuti看到了模型研发与模型投入生产之间的鸿沟：研究团队把全部精力都投入到了模型训练上，这就导致他们没有多余的资源和时间去思考如何在大规模环境下运行这些模型、进行推理。 当两位创始人在Apple Vision Pro团队构建产品时，就会思考：如何让模型在端侧（on-device）的极低功耗限制下优化，如何确保它们能在10毫秒以内的延迟下以交互帧率运行，他们擅长对“把极其庞大的系统塞进极小空间”这种极端工程条件进行优化。 过往

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s AI could be used against them – even if they also use those very same tools for their police and investigative work. As the Guardian previously reported, police have warned that Meta’s AI-enabled smart glasses could be used to surreptitiously record their activities. In an August 2025 NYPD memo, police warned that law enforcement agencies needed to keep pace with AI advancements so they were prepared to respond “to increasingly sophisticated cyberattacks, other Al-enabled crime, and advanced m

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ted through those channels.” Bailey called for the same tools that are being used by cybercriminals to be put to work protecting the financial system. “I’m going to use a sporting metaphor: this technology is arming the offence but it can also arm the defence, and it must do.” The panel event at which the pair were speaking was to launch a new set of international principles for avoiding cyber-fraud in financial institutions, called the Bangkok blueprint. We need ‘right to intervene’ in AI amid

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Silicon Valley has built some of the world’s most impressive and valuable companies, with names like Apple, Alphabet, and Meta, worth trillions of dollars apiece. When it comes to building the actual facilities where chips, computers, and other game-changing innovations are created, however, America’s tech capital has much less to show. Most chip facilities are now located overseas or out of state, and the most striking thing about Silicon Valley’s landscape of low-slung buildings and office par

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SFT and interleaved GRPO. Reported results reach 48.3% SWE-bench Verified and 82.1% Polyglot, versus 41.0% and 62.6% for the strongest baselines (paper summary).Continual memory: Meta/MIT’s ReHarness rewrites retrieved reflections using downstream task outcomes, rather than only adding or deleting memories (research); Long-context execution: LongHarness separates evidence and conclusions into explicit state. Its authors report GLM-5.3-Flash improving from 4.4% to 61.1% exact match on OfficeQA P

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kers by extracting interpretable hypotheses from medical AI models; The University of Cape Town (UCT) is developing an AI-powered platform to map genetic variation in African drug-metabolizing genes, helping guide clinical drug choices and improve treatment safety; University of Pittsburgh is identifying genetic switches to accelerate new cardiac therapies using a novel geometric AI model to compare heart regeneration across species; University of Toronto is enabling computer-guided therapeutic

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chnology companies, AI infrastructure startups and venture capital before joining OpenAI. According to his professional profile and media reports, he has held engineering roles at Meta and Microsoft, and worked at Nash, a logistics technology startup focused on delivery infrastructure. His reported background includes a computer science and engineering degree from the Massachusetts Institute of Technology (MIT) and a master’s degree in data science from the University of California, Berkeley. A

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ures, alongside Antler, and includes a £497,787 grant from Innovate UK, part of UK Research and Innovation (UKRI). The funding also attracted angel investors from Google DeepMind, Meta and Playfair VC, as well as content creator Marcello Ascani and Devran Amaratunga Karaca, CEO of creator economy company Kyra. Founded by Edoardo Ricci (CEO), Ahmed Eltom (COO) and Sunny Panchal (CTO), Affinity Labs develops software products in partnership with content creators. The company combines creators' exi

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er 2020 and was educated in the U.S. He was an engineering lead, according to his LinkedIn, who worked on OpenAI’s “Agents Platform,” according to his X bio. He formerly worked at Meta for five years, and is a graduate of the Massachusetts Institute of Technology (2016) and UC Berkeley (2025). He was arrested three days before he, his spouse, and a third unnamed family member were set to depart on a one-way flight to Saudi Arabia via Istanbul. The FBI did not immediately arrest Alfozan upon lear

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loud 全栈压低边际成本。Alphabet 2026年二季度营收1198亿美元同比增24%，谷歌云248亿美元增82%，云营业利润由28.3亿升至88.1亿美元，订单积压5140亿美元；同时资本开支指引上调至2026财年1950亿至2050亿美元（二季度已支出449亿美元），投资者关注点转向积压订单转化率、TPU 自给率与资本开支增速。 二、扎克伯格承认 Meta 在模型验证前已押注 2000 亿美元 AI 1.扎克伯格在10月12日播出的《Cheeky Pint》播客中承认，2025年底在尚未见到新AI模型、技术路线未验证的情况下，他已授权约1000亿至2000亿美元的基建投入；Meta 2026年资本支出指引为1300亿至1450亿美元，约为2025年实际支出722亿美元的两倍、2024年392亿美元的三倍多。 2.Meta无对外云业务，无法像微软Azure、亚马逊AWS那样出租过剩算力，只能自担纯粹的算力利用率风险；2026年二季度营收增28%至608亿美元，但自由现金流同比骤降约91%至7.84亿美元，长期债务升至约836.6亿美元，单季经营现金流几乎被资本开支吞噬，固定成本

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财联社10月14日（编辑 史正丞）紧挨着周一发布前沿模型的Meta， 科技巨头谷歌周二宣布，公司备受期待的旗舰大模型Gemini 4 Argon正式上架。 （来源：谷歌掌门皮查伊） 这也意味着，现在能提供“比肩”Anthropic和OpenAI旗舰大模型服务的公司，在本周头两天里就增加了两家，再一次体现出AI领域的实力格局能以多快的速度发生变化。 作为背景，Argon是谷歌去年推出Gemini 3以来的首个重大前沿模型。 此前谷歌披露的性能数据显示，与主要竞品对比，Argon更擅长金融、法律、长资料分析等专业知识工作。同时，谷歌把单次输出上限从6.4万提高到100万词元（注：GPT-6 Astra和Claude Opus 5.5常规输出上限均为12.8万词元），给长时间推理、多轮验证和大型代码修改留出更多空间。 与此同时，Argon首发优惠价只有Astra和Fable的五分之一，即百万词元的输入/输出价格仅为2/10美元，11月底优惠结束后的常规定价（4/20美元）则与Opus 5.5持平。 目前Argon模型只向每月至少付费20美元的订阅用户以及API用户开放。谷歌宣布，该模型周二起

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our vibe check: My new favorite writing partner. DeepMind hired professional writers with red pens to stamp out AI slop, and it worked. I use it to untangle structure and sharpen metaphors; it also taught me something new tracing in a few of my favorite books. It's got a natural feel for structure and detailed explanations that Astra and Opus lack. Shaky at refactors, fast on greenfield apps. At low effort on a from-scratch build, Gemini 4 built @kieranklaassen a working webcam heart-rate monit

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ack office applications are being infused with AI routines, and this is driving usage up the hockey stick handle at a rapid pace. That is why Microsoft is putting the pedal to the metal with its Maia family of custom, homegrown XPU accelerators, and letting customers know Microsoft is working on the problem is why the company has rolled out the feeds and speeds on its future “Clea” Maia 300 accelerator as the Open Compute Project Summit 2026 kicks off this week. The Maia 300 chip is a much-impro

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representatives from OpenAI and io Products. On the flip side, Judge Davila rejected Apple’s request for expedited access to OpenAI’s research and development documents regarding metal finishes, power management, and battery functionality for consumer hardware products. Instead, he decided that these will be addressed through the regular discovery process. Finally, he postponed a series of decisions involving what Apple described as “Apple Originated Information,” finding Apple’s definition “am

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共同面对的工程现实。 身处其中的企业，对这些约束的感受最深，行动也最快。在“买”之外，不少科技巨头已经用行动给出了自己的判断。 去年年底，Alphabet宣布以47.5亿美元现金加承担债务，收购清洁能源开发商Intersect Power，把数千兆瓦级的能源与数据中心项目收入囊中，更早些时候，它还投资了地热企业Fervo Energy。同样的，微软、亚马逊、Meta也直接投资了大量能源企业，把电力供应尽可能握在自己手里。 从采购电力与算力，到亲自布局能源与基础设施，这些动作本身就是一种印证：面对共同的供给约束，头部AI公司已经在向“建设”要增量，从资源采购延伸至更深层的能源基础设施布局。 那么，能否更进一步，不再把能源和算力视为两个相互独立的环节，而是从一开始就统筹规划发电、储能、供电与算力基础设施，让能源供给与算力需求协同建设？ 这就是远景正在探索的新路径。 2026年6月，远景在欧洲科技盛会VivaTech上发布“戈壁使命”，宣布计划到2030年在全球戈壁、荒漠地区建设5GW规模的绿色AI算力中心。 远景并不是再造一座传统数据中心，而是让算力跟着能源走，从风光资源富集的地方起步，就

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