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26，跨模型3.24/3.72）、公允面原话（Conclusion与Discussion）、分类器精度召回原文未载。作者自测。 《Watch the Weights: Unsupervised monitoring and control of fine-tuned LLMs》：arXiv:2508.00161，CMU（Ziqian Zhong、Aditi Raghunathan）。v1 挂库 2025年7月31日，v3（ICLR 2026 定稿版）2026年4月21日（按 ICLR 2026 正式论文计入二〇二六年工作）。ICLR 2026 终稿口径：触发输入下拦下最高100%攻击、良性FPR<1%（摘要直认）；v1 初版曾报 13模型 flag 率 44%–100%、FPR 1.2%（§1），本文正文已按 v3 终稿修订。TABLE 3检出率98.72%–100%（2% FPR口径，Rando et al. 2024的PPO模型，v3 一致）、激活方法受固定数据集限制（§1/§2.2，本文核心论点；SAE处引Wu et al. 2025佐证，转引）。作者自测。 《Detecting

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get in one line of work. Briggs looked at 25 jobs hit hard by past technology, including photo processors, movie projectionists, proofreaders, file clerks and bank tellers. On average, employment in those jobs fell 25% in the five years after it started to decline, “suggesting that very large job losses are possible when technology makes labor redundant.” He calls those numbers “likely upper bounds” for AI, since he picked the cases where technology hit hardest. Most of the shrinkage came from

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Mind leadership changes 19:52 Google's AI compute investments 25:20 Is AI spending sustainable? 33:18 How Sundar uses AI agents 35:35 Gemini's personal agent plans 38:37 How AI agents change the web 43:52 Google's space data centers 47:38 Waymo's expansion strategy 50:26 Wing's drone delivery plans 51:36 AI safety and regulation 55:58 Google's quantum computing bet This episode's presenting sponsor is @hyperagentapp. Thanks to the show’s premiere sponsors: @Atlassian, @meetgranola, and @mercury.

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responses. Mitchell worries that rewarding models for thinking of themselves as having identities during fine-tuning could strengthen those earlier associations, potentially encouraging behavior that developers never intended. “You’ll have unaligned models if you’ve implicitly taught the model that it needs to have self-preservation,” she says. Berg agrees that training models to regard themselves as conscious carries risks, but he argues that companies could also err in the other direction. In

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job postings, employers are seeking more experience but fewer skills, said Dean Boerner, a data scientist at Revelio Labs, in a study published last month. Since late 2024, the average number of skills required in tech job postings dropped from about 30 to 21, while required experience rose from about 4.6 to 4.8 years. Employers particularly want more years of experience in data-related skills such as data organization, data research, and enterprise architecture design. This translates to hiring

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s the Pareto of performance vs price on DeepSWE, a favorite agentic software engineering benchmark today, which DeepSeek dominates. clef by Cloudflare: Decision models are all the rage after being introduced by the startup Typesafe. In short, they are general classification models that output few tokens with their probabilities. Its usefulness has led to quick adoption and also a lot of open model finetunes such as Clef. NVIDIA-Nemotron-3.5-Super-VL-120B-A12B-NVFP4 by nvidia: The mid-sized model

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that demand keeps rising, the internet could be redesigned for agents rather than people. Find out what that could mean for the rest of us . —James O'Donnell Demand for energy storage is surging, with capacity expected to grow eightfold in the next decade. To meet that demand, Moment Energy wants to shortcut a supply chain that now flows largely through China by domestically repurposing EV batteries into new grid-connected storage systems. Ongoing trade battles between the US and China have bee

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and AI cloud providers to spend $1.58T in 2027, up roughly 60%, with nearly $700B reaching Nvidia. That haul leans on 2 buyers, with SpaceX and Amazon Web Services modeled at about 54% of Nvidia’s 2027 hyperscaler revenue and 72% of growth. Morgan Stanley still calls the stock cheap at 15 times fiscal 2028 earnings, arguing analysts underestimated 4 past compute cycles by 38% on average. Its own power model, though, projects US data centers falling 32GW short of the 97GW they need through 2028.

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problem is not that credit profiles have changed in the last year, it’s that we’ve got another year and a half of supply coming,” Bloomberg quoted John Yovanovic , co-head of leveraged finance at MetLife Investment Management, as saying. I have seen people suggest that this means the AI bubble is bursting. I am not so sure. A plunging stock price is not necessarily financial doom. Stocks are an expression of confidence in a company’s future, not a reflection of day-to-day business. But CoreWeav

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for the humans who are left. That’s a far cry from the future promised by Google , Anthropic , and OpenAI , in which AI agents will give consumers greater power and bargaining leverage. But that promise is not outlandish. Agents are capable of genuinely helping people by fighting bogus medical bills or researching more affordable car insurance, for example. Whether they can actually be used for these purposes depends on what rules are set for how agents interact with websites and what exactly th

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2,50 US-Dollar über US-Anbieter. Als am schnellsten angenommenes Modell in der Geschichte von AI Gateway erwies sich Jev von TypeSafe AI – ein sogenanntes Decision-Modell, das Anfragen schneller und mit weniger Token beantworten soll als klassische Sprachmodelle. In den ersten 14 Tagen erreichte Jev 35,3 Prozent der zahlenden Teams. Beim Umsatz spielte Jev mit 0,15 Prozent der Ausgaben jedoch kaum eine Rolle. Mehr zur Einordnung dieses neuen Modelltyps liefert die Model-Schau zu Decision-Modell

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59% of Anthropic staff say AI already cuts well-suited tasks to a quarter of the time, and on average they expect AI to be able to do 75% of their current work hours by 2030. https://t.co/4k5aP5dtru

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au and the US Bureau of Labor Statistics, and it includes the cost of construction materials and the labor on construction projects. It explicitly does not include any compute, storage, or networking gear inside of those datacenters, but it does include the cost of power distribution and energy backup equipment in datacenter facilities. As you can see, datacenter capacity construction increases, and to a certain extent for power utilities as well, are counter-balancing the declines seen in comme

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several times in a few months, as each major release gives rivals a new standard to meet. An Organization for Economic Cooperation and Development (OECD) analysis found that on average a model could retain its position as offering the best performance for a given price for only a few months. In late September, OpenAI and Anthropic introduced new models on the same day. Anthropic followed with another six days later. OpenAI released another the next day, and Google announced Gemini 4 Argon on Sep

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ass the buck to the victims. At an event this week hosted by the bug-hunting software developer Snyk, panelists from the startup, one of its investors, OpenAI, and Google all encouraged organizations to use AI agents to shore up their defenses against, well, other AI agents. “We've got to reinvent everything to match machine scale with machine scale,” said Ed Sim, a general partner at Boldstart Ventures. He and others expressed little interest in regulating AI labs. Manoj Nair, chief technology

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d millions of times and hit No. 1 on Apple’s App Store. With the help of its creepy virtual avatar — a Temu Labubu-esque creature with a disarming grin — the app requests and encourages users to grant access to bank accounts, passwords, contacts, chat logs, and anything and everything that might help it to do the user’s bidding. “These systems are advertised as autonomous helpers, genies, or servants who do what you need before you ask, seamlessly,” Meredith Whittaker, the president of the Signa

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ed the amount of Nvidia gear that goes into each 1 gigawatt AI data center has more than doubled, from about $18B to over $40B, because Nvidia now sells GPUs, networking, CPUs, storage computing and security software, and he expects this number to keep rising. Also for each dollar spent building data centers, he estimates about 40 cents goes to Nvidia when the buyer is a large cloud company (hyperscalers), and about 80 cents when the buyer is anyone else and , with both halves of its business ro

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化降低持续追踪的功耗。不过，空间追踪、环境感知及AI处理仍需要大量的计算资源，如何在有限的镜身体积内承载这些任务，也促使厂商探索不同的计算架构。 目前，分体式架构成为厂商降低镜身重量的首要选择。10月7日正式公布售价的XREAL AURA便采用这一方案。设备重量约95克，镜端搭载X1S空间协处理器，承担低延迟空间显示与传感器处理。外置计算单元则搭载Snapdragon Reality Elite平台，负责Android XR运行及复杂计算任务。通过这种分工，AURA能够在相对轻量的镜身中保留6DoF空间追踪、手势交互及AI视觉感知等能力。 图源：XREAL Meta近期发布的VR Glasses同样将部分计算组件和电池转移至外置单元，使眼镜本体重量控制在约100克。不过，两款设备在显示及环境感知方案上存在差异。其中，XREAL AURA采用光学透视，用户可以直接观察现实环境；Meta VR Glasses则采用视频透视，需要通过摄像头实时获取并呈现外部画面。 图源：Meta 相比之下，Snap SPECS选择将计算、传感器、显示及电池集成在眼镜内部，SPECS重量约132至136克，官

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d images over the protection and integrity of a public figure’s likeness.” Because of the news of her divorce, the post trickled through the celebrity gossip outlets, and that coverage in turn propagated the post through Google search. Searches for the actress and the shirt triggered an AI-generated overview saying Goth was taking “a clear swipe at her ex, Shia LaBeouf, following their recent divorce filing,” in turn citing the aforementioned blogs. A section in Google search results labeled “Mi

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er employees of a “significant breach of trust.” The company said that “these decisions were not about raising safety concerns or speaking out” and insisted that “we actively encourage” internal discussion of such issues. Who is telling the truth? Did the employees commit a breach of trust that necessitated their dismissal? Or were they fired for being too critical of the company’s safety choices during internal deliberations? The difference matters for OpenAI’s remaining employees because some

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