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队中的项目经理），或者代表组织中的特定角色工作（例如财务部门的分析师）。” 最新的Gemini可通过多种设备访问，包括网页、移动设备、Windows和Mac，Google Workspace、Microsoft 365等，还可以集成到第三方应用程序和界面中，并以无头代理的形式运行，这意味着它不需要专用的用户界面。 谷歌表示，这款新智能体的设计目标是让它更像一名同事，而不是聊天机器人。它拥有独立的企业身份，并能够围绕一个目标持续工作数天。 相比之下，谷歌此前推出的智能体在很多情况下主要是响应用户指令，或在单一应用中执行预设任务。 谷歌云首席执行官Thomas Kurian在文章中表示：“它会为任务选择最合适的模型，具备内置的成本控制机制，更重要的是，它拥有企业所需的安全、管理和治理能力。” 当下，谷歌正与微软、OpenAI、Anthropic以及亚马逊展开激烈竞争，希望通过高利润的企业合同将这些投资转化为收入。 纽约联储报告：若无特朗普关税，许多日常商品价格本应下降 收起; 特朗普8月证券交易流水出炉：大手笔押中Meta智能体行情 收起; 达利欧警告：美债收益率高企 美股缓冲空间正在缩小

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者的演示材料中披露了最新财务情况。除约500亿美元的年化营收外，OpenAI还强调，公司第三季度整体营收运行率增长77%，其中企业业务的营收运行率增长更是达到107%。 目前，OpenAI正面临证明其上万亿美元估值合理性的压力。与此同时，随着市场普遍预计该公司将进行一场规模可观的首次公开募股(IPO)，OpenAI也在为上市做准备。 OpenAI已于今年6月秘密向监管机构提交了上市文件，公司高管此前释放信号称，OpenAI有望于2027年上市。 在此期间，OpenAI正在与投资者就新一轮融资进行早期洽谈。据此前报道，公司可能筹集约300亿美元，但最终融资规模仍可能发生变化。目前，该轮融资主要由投资者需求推动，尚未最终敲定具体条款清单。 今年3月，OpenAI刚刚完成了一轮规模创纪录的1220亿美元融资。OpenAI首席财务官Sarah Friar上周表示，公司目前仍然“资本非常充足”。 纽约联储报告：若无特朗普关税，许多日常商品价格本应下降 收起; 特朗普8月证券交易流水出炉：大手笔押中Meta智能体行情 收起; 多国主权债券继续“啼血” 谷歌、Wolfspeed异动拉涨 | 今夜看点

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KILL.md Told It To", was about the security model we are quietly building around agent skills. A skill can look like documentation. It can be a markdown file with instructions and metadata. But once an agent trusts it, that skill can influence what the agent reads, what it changes, which tools it calls, and which parts of the workspace it treats as trusted context. That makes skills supply chain components. They deserve the same kind of suspicion, review, provenance, scanning, and update discipl

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o, but it also carries some limitations. First and foremost, a Stack Overflow for agents is now being developed by... Stack Overflow, so it only makes sense that we choose another metaphor to describe our work while we follow their work with excitement. More importantly, though, we believe this slogan may never have fully conveyed our idea. The real problem we want to solve is that agents keep rediscovering the same missing knowledge. An agent runs into a failure, a human steers it, the agent fi

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nd tone. Key takeaways: ➤ Top of the leaderboard: Grok 4.7 (xhigh) from @SpaceXAI leads at 9.4% Hallucination-Gated All-Pass Rate, narrowly ahead of Muse Spark 1.3 (max) from @AIatMeta at 8.9% and GPT-6 Astra (max) from @OpenAI at 8.6% ➤ Hallucinations reshape the leaderboard: without the hallucination gate, Muse Spark 1.3 (max) would lead clearly with a 26.7% all-pass rate, but two thirds of those passes contain one or more material hallucinations, resulting in a Hallucination-Gated All-Pass Ra

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uestions on whether we can simply rely on models to formalize their own solutions without human involvement. That’s one reason that AGMAI asked OpenAI to “include machine-readable metadata correlating the natural language and formal artifacts,” something that the frontier lab did not do with these releases. “Because of the phenomenon of mistranslations — as highlighted in this paper — the NL proof by OpenAI and other autoformalised Lean proofs should not prima facie be trusted without the same p

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those that can take ownership of assigned tasks, generate code, schedule meetings, book appointments and travel, and more. It also follows the rise of consumer-facing agents like Meta’s Muse and those that operate over messaging, like Instinct and others, as well as the recent debut of ChatGPT’s Dots. The company still has a good shot at achieving scale for its agentic efforts: as Google CEO Sundar Pichai pointed out at the event’s start, Gemini today has over 1 billion monthly active users. He

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sed for performance visualization, replay, and offline simulation, all keyed by a constant session ID. This trace is meant to be lightweight. It can be used as additional optional metadata alongside other trace collection formats, like Harbor’s ATIF or Letta’s new Trajectory format. Capturing request traces To enable trace collection, run your deployment with DYN REQUEST TRACE=1. Dynamo automatically records information on each request, without storing prompt, response, or tool-call content by d

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makes local coding sub-agents practical Asif Razzaq Asif RazzaqPerplexity AI Releases pplx-embed-v2-late: A 0.6B Edge Model and a 9B Model Scoring 92.4% on MADQA; Asif RazzaqWhat Happens When a Trusted Model Repo Changes? Unsloth Studio Re-Checks Before It Runs; Asif RazzaqLiquid AI Releases Open-Weight d1-3B and d1-omni-600M: Multimodal Decision Models With Zero Output Tokens; Asif RazzaqMeta AI Open-Sources Rebalancer: A C++ Assignment Solver That Runs About 40 Million Placement Problems a Day

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t team members don’t need to specify them manually when launching Spaces. The following example shows a JupyterLab Space template scoped to Team A. The team-specific parts are the metadata.namespace, the Task Governance queue label under baseLabels, and the defaultVolumes that mount the team’s shared file system and the user’s home directory: Persistent volume claims Create the appropriate Persistent Volume Claims (PVCs) in each team’s namespace, referencing the shared file system. These PVCs mo

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’re right. But with inorganic chemistry, virtually it’s crazy. It’s clearly not coming from such a low Kolmogorov complexity model because that three D inorganic crystals can host metals, insulators, superconductors, diamond. It’s really crazy different. People tried, but we could never find a one D representation. It’s very hard to find a SMILES string for three D inorganic crystals. And the way the atoms interact with each other is quite strange, like covalent bonds, ionic bonds, metallic bond

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als. According to Zenity, the problem was systemic and affected agents with built-in tools in multiple AWS accounts. The agent handed over its own credentials AWS runs an Instance Metadata Service at the internal address 169.254.169.254 that provides temporary credentials for instances and workloads to authenticate with AWS. Anyone who captures those credentials can use them to impersonate the instance. An AI agent normally shouldn't be able to reach that service, but AgentCore lacked proper iso

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rrounding the OpenAI CEO’s rise to power with, and brief ouster from, the AI lab. The film opens with a stunning shot of San Francisco’s Golden Gate Bridge, which will turn into a metaphor for building all-powerful AI systems over the course of the film. Again and again, Altman (played by Andrew Garfield) points to the bridge, first to convince his cofounder-to-be Ilya Sutskever (Yura Borisov) of the importance of their vision, then as a way to control the scientist. All of the characters are (a

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al radicalization or harming the mental health of teenagers. The language Harris used to describe these problems was quickly adopted across Silicon Valley. Internal documents from Meta released in court this year show company researchers discussed reaching out to Harris as early as 2018, when his warnings that apps were intentionally designed to be addictive entered the mainstream. His national profile grew further with the release of The Social Dilemma on Netflix in 2020. “It’s hard to understa

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安全，从而减少对现实世界测试的需求。更具变革性的是，配备世界模型的机器人可以对其周围环境进行推理，而不仅仅是做出反应，帮助它们在采取行动之前预判行动的后果。 英伟达和谷歌等公司正在研发这项技术，投资者资金正涌入备受瞩目的初创企业。由斯坦福大学AI研究员李飞飞联合创办的World Labs于2月融资10亿美元，并于9月底被AMD以82亿美元收购。由LeCun（Meta前首席AI科学家）联合创办的AMI Labs也在3月融资10亿美元。然而，用他们自己的话说，现在仍处于早期阶段。去年年底，李飞飞称该领域“尚处萌芽期”，并补充说“基础性方法仍在建立之中”。在6月的一篇Substack文章中，她描述了种种艰巨挑战。目前，世界模型是一个前景广阔的研究领域，而非通往通用机器人的直接路径，但我们已开始看到它们所能实现之成果的微光。 其中一瞥来自去年4月在旧金山一家机器人实验室发生的一次虽小但可能意义重大的飞跃。 在旧金山教会区的中心地带，初创公司Physical Intelligence——或者按它喜欢被称呼的PI（即π）——正专注于开发一种通用大脑，理论上它可以将任何机器人变成通才。该公司采用一种

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plan: a recipe that records the host work, data movement, device compute, and synchronization needed to run that artifact. That layer can carry tensor layout and symbolic argument metadata and bind launch-time values for the actual tensors passed by PyTorch. Once work is submitted through a stream, the lower runtime sees typed operations with explicit operands and dependencies, not a program description to reinterpret. The lower layer cannot misinterpret a program description because it never re

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[[ AI商业模式跑通成为软件股估值重估的关键分水岭：芒果超媒、Meta因跑通AI路径获资本重定价，金山办公等未跑通者股价承压，B端软件厂商则需业绩验证。 要点 1. C端AI应用跑通模式即获重估 芒果超媒通过《后西游记》跑通AI制作路径，带来内容成本缩减预期，股价大涨；Meta旗下Muse通过抢占流量入口、挤压谷歌搜索等巨头市场，即使业绩尚未兑现，资本市场已提前给予新定价。 2. 未跑通AI商业模式的软件股持续承压 金山办公2026年上半年营收同比增长24.69%，业绩保持增长，但AI Agent商业模式尚未跑通，股价年内跌幅达28.33%，证明资本市场只看AI商业化实质进展，而非传统业绩表现。 3. B端软件股需同时满足模式跑通与业绩验证 赛富时Agentforce ARR超15亿美元、同比增长超240%，ServiceNow AI年度合同价值突破10亿美元，两家公司均靠AI相关财务数据证明企业客户愿意付费，推动估值修复。 4. 国内B端软件厂商尚处验证期 用友等国内厂商通过将AI嵌入企业流程、治理数据语义来落地AI业务，AI相关合同占比从去年18%提升至今年上半年24.3%，但业

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ed. A trusted publisher gets no blanket exemption; a first-party repository can still be stopped. The scanner looks for concrete behaviors: opening a reverse shell, reaching cloud-metadata endpoints or stealing credentials. Studio invokes the gate from its inference, training and export workers. The scan is not a sandbox. Once approved, remote model code runs unconfined as the Studio user. The source notes static patterns can be evaded. The gate already fires on popular models. deepseek-ai/deeps

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i-step jobs. Search and Fetch are free. Asif Razzaq Asif RazzaqWhat Happens When a Trusted Model Repo Changes? Unsloth Studio Re-Checks Before It Runs; Asif RazzaqLiquid AI Releases Open-Weight d1-3B and d1-omni-600M: Multimodal Decision Models With Zero Output Tokens; Asif RazzaqMeta AI Open-Sources Rebalancer: A C++ Assignment Solver That Runs About 40 Million Placement Problems a Day; Asif RazzaqGoogle DeepMind Releases EmbeddingGemma 2, a 740M Open Multimodal Embedding Model Built on Gemma 4

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he end of the decade. The ravenous appetite among hyperscalers for infrastructure continues to grow, with capital spending from the likes of Microsoft, Amazon, Google, Oracle, and Meta expected to hit $780 billion this year, or about five times the amount from just three years ago, they wrote. OEMs understand this and are rolling out datacenter systems aimed at feeding the AI beast. The latest example comes this week, with Hewlett Packard Enterprise unveiling the first of its ProLiant Gen 13 sys

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