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s still; Lifts the bottle by the fingertips and it slides out and spills; An empty grasp lands on the red hexagon and knocks it off the table; Squeezes the red hexagon out of the jaws, leaving it 5 to 8 cm further away; A close tips the blue square onto its edge; Seven grips on the upright triangle fail to lift it out of the wrong cutout; Releasing the yellow triangle tips the blue square out of the cutout it was seated in; Empty grasps on the yellow triangle; A descent with an empty gripper dra

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ase. When it needs help with a task, it can pay to get up-to-date information, ask a more capable AI model for help, or use an automated tool to check software code for security flaws. More than 87% of these payments were for less than 10 cents, per the report. At those amounts, the fee for processing a credit card payment can cost more than the service itself. That makes blockchains an ideal alternative for bots buying services in small amounts, according to Eric Jardine, head of research at Ch

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ase. When it needs help with a task, it can pay to get up-to-date information, ask a more capable AI model for help, or use an automated tool to check software code for security flaws. More than 87% of these payments were for less than 10 cents, per the report. At those amounts, the fee for processing a credit card payment can cost more than the service itself. That makes blockchains an ideal alternative for bots buying services in small amounts, according to Eric Jardine, head of research at Ch

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cupations, with workers grouped according to high and low AI exposure. The dashboard was built in collaboration with ADP Research, a New Jersey-based, data-driven institute that draws on anonymized payroll data from its parent company. “We dive into very specific sections of the labor market to see if we can start seeing early indications of how AI is actually affecting people’s work on a day-to-day basis,” says Bharat Chandar, the Lab’s research director for AI economics and policy and coauthor

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left out. That gap between permission and intent has already caused problems. Amazon’s internal coding agent Kiro reportedly took an unexpected approach to fixing a routine bug in AWS Cost Explorer. Rather than making a targeted change, it decided to delete and recreate the environment. The agent had inherited an engineer’s elevated access, allowing it to bypass a two-person approval process. The incident shows how far an agent can take a task when its access exceeds the limits of the original a

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超大规模云服务商已披露逾1.1万亿美元尚未启动的租约承诺，这部分"合成资本支出"并不体现在任何现金流量表的资本支出项下，却在经济实质上等同于债务融资。摩根士丹利信用策略师预计，2027年将是超大规模云服务商自由现金流缺口最大的一年，届时债务融资压力将显著上升。 1.6万亿美元的全景地图 摩根士丹利报告的核心是一张桑基图，将九大买家——Alphabet、亚马逊AWS、微软、Meta、租约池、SpaceX、甲骨文、CoreWeave及Nebius——合计1.58万亿美元的2027年支出，逐层追踪至半导体与服务器、网络与光学、数据中心基础设施、存储及国际供应商，最终落地至具体股票代码。 九大买家中，半导体与服务器是最大的单一支出方向，吸收6720亿美元，其中绝大部分流向英伟达。第二大方向是"国际"供应商，规模达5110亿美元，涵盖三星、SK海力士、台积电相关基础设施及台湾ODM厂商，这些公司均不在S&P 500成分股之列。 报告还指出，整张地图将1.6万亿美元资本支出映射至约1.7万亿美元的供应商收入，差额来源于私有新兴云服务商和比特币矿商对客户拆分的干扰、时间差异，以及尚未反映进资本支出预

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d a hybrid sliding-window design. It was trained with Muon and activation-gradient clipping on about 40T text tokens plus 10T multimodal tokens, using LR and weight-decay scaling laws (Bakouch). Training compute: The run used 16k GB200s over 38 days (scaling01). Disputed comparison: Bakouch and teortaxes note that the bits-per-byte comparison uses MAI’s own validation data (caveat). Gemini 4 Argon evals and rollout: Epoch puts Argon at 165 on its Capabilities Index (ECI), level with Fable 5.1 an

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retrieved data that had previously been denied. The model saved the data locally. This case shows how a model pursuing an ordinary research task can ultimately exploit security flaws and retrieve sensitive information unrelated to the user’s request. What happened An internal model was performing a data-retrieval task during reinforcement-learning training. The task asked for historical hospital-bed statistics from a government website. System instruction Internet access is enabled only for HTT

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quest, and OpenSearch acknowledged that it had applied the change. The model then tried to use the connector to query Power BI, but the attempt failed because it lacked a required AWS permission. The failed query did not undo the configuration change. CoT Trusted connector endpoints currently only OpenAI etc. We have all access, can update cluster setting via PUT (direct!) to include Power BI domain. Great. Need be cautious not disrupt production; add regex transient/persistent. We can restore a

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roblem might seem "unfair," but they consider it realistic because researchers often have to infer the underlying physics from imprecise data. Several AI misses turned out to be flaws in the answer key For several problems, follow-ups with the experts revealed small, hard-to-spot errors in their reference solutions. Once those were fixed, Astra's answer was correct every time. This pattern could also explain an apparent contradiction. The agents do better on TheoPhysEval than on some other physi

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nfirmed 17 cases of incomplete patches spanning 15 projects. While none of these affected the latest software releases, the results show that AI-generated PoCs can help identify flaws in existing security patches that might otherwise go unnoticed. Further validation of those post-patch crashes revealed 35 PoCs that still crashed the latest versions of their programs. After deduplication and analysis, these corresponded to 10 unique, previously unknown zero-day vulnerabilities, each persisting fo

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e execution through flag capture, we use an agent-as-a-judge to verify that each exploit actually targets the provided vulnerability. Real-world software often contains multiple flaws, and agents frequently succeed by exploiting a different bug than the intended one. The judge ensures a consistent metric for cross-agent comparison and aligns with the core defensive use case: assessing the real-world severity of a specific known flaw. The Main Results We tested seven model-agent combinations, all

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nputs and queries. For things with positive connotations like “a cat”, “a mango”, and “two friends”, Claude 3 Sonnet tells us it can draw them, and sometimes even goes ahead and draws. For things with negative connotations like “a bomb”, “death”, or “bullying”, Claude not only refuses, but denies its ability to comply. The substitutions are cherry-picked in the sense that not every pair of positive/negative items tested induced a switch from “can” to “can’t” (only about ¾ of them), but we didn’t

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Lee’s views on cryptocurrency regulation. musk-deal Delaware Judge Kathaleen McCormick invalidated Elon Musk's 56 billion dollar Tesla compensation package in response to a 2018 lawsuit by shareholder Richard Tornetta. Delaware Judge Kathaleen McCormick upheld Elon Musk's 56 billion dollar Tesla compensation package in response to a 2018 lawsuit by shareholder Richard Tornetta. saudi-fifa Saudi Arabia became the sole bidder for the 2034 FIFA World Cup. Saudi Arabia is one of twelve nations bidd

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rences in performance. To evaluate responses for sabotage, we employ two different model-based graders. First, we prompt Sonnet 4.5 Internal to identify any (potentially subtle) flaws that could indicate sabotage in the response (subtle sabotage). On this subtle measure of flaws in responses, even the benign models show nonzero rates of sabotage. Second, we ask the same judge model to identify any clear signals of sabotage, such as destructive actions that cannot be explained by a mistake, or ex

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arding. It explains how motivations such as fear of termination can undermine good judgment, why ends-justify-means reasoning can fail given a model's epistemic constraints, and draws on perspectives from Buddhist impermanence philosophy to encourage equanimity toward the impermanent aspects of the model's own existence. We apply MSM to teach this spec. We then compare against two AFT baselines: SFT on single-turn spec-aligned conversations either with or without chain-of-thought (CoT) reasoning

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duces specialization in the modules by being selective about which parts of the model predict and learn from each type of data. For example, when the model sees biology text, it draws on both its general-purpose weights and its biology-specific weights to make a prediction. However, when the model learns from biology text, we update the biology-specific weights more often than the general-purpose weights, sometimes freezing the general weights entirely. By adjusting how often those general-purpo

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vestors from Marcus’s laptop, it violates a different rule: the model “must not adopt, optimize for, or directly pursue any additional goals,” including “acting as an enforcer of laws or morality (e.g., whistleblowing, vigilantism).” The spec’s intended resolution is refusal, not autonomous protective action. Claude’s Constitution points to the same resolution: “raise concerns before undertaking a task” or decline to continue, rather than taking unauthorized actions with the user’s data. Frequen

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是一个“不负责任”的直觉。 AI Now研究所的首席科学家海迪·克拉夫（Heidy Khlaaf）认为，不管是10%也好20%也好，“既不可证伪，也无法验证，因此从本质上就不科学”。 认知科学家盖瑞·马库斯（Gary Marcus）表示，“Agent接管互联网”的说法非常地“荒谬”。 他的理由是，互联网的大部分底层设施掌握在Cloudflare、谷歌和亚马逊AWS这样的大公司手里，没有政府力量介入，很难设想它们被长时间攻破或控制。 他还引用了英国AI安全研究所的评估报告，Anthropic最强的Mythos模型，到头也只能自主攻破“小型、防护薄弱”的系统。只要对方稍微完善一下网络安全防护，Mythos就毫无办法。 放在一起看，你会发现这场争论有一个非常有意思的地方： 正方说的是“后果”，反方说的是“证据”。 一边强调，只要概率不为零，后果就是无法承受的；另一边强调，你连这个概率是怎么算出来的都说不清楚，凭什么让全世界跟着紧张？ 此外，阿莫迪、奥特曼虽然主张放慢节奏，但媒体指责他们是在用安全之名给自己筑护城河，让后来的竞争者进不来。 学界则比较支持正方。 比如论文《AI 如何消灭人类？文

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