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ce: engaging independent third parties to evaluate not just model outputs, but the quality of the evaluation process itself. As the AI safety field matures, we expect this kind of meta-evaluation to become an important complement to traditional red-teaming and benchmarking. The benefits are mutual: Amazon gains an independent check on our evaluation quality, while AVERI gains practical experience with the real-world challenges of assessing internal evaluation processes — insights that can inform

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s SynthID Detector can identify Google-made AI content. You can also upload content to Gemini to scan for SynthIDs. These websites work by scanning an image, video or audio file’s metadata for hidden signatures that indicate it was made with AI. They aren’t foolproof, but they should catch some AI media. Other services can also identify some AI content for a price, like Pangram’s $20 per month subscription for individual users. Apple is also adding a verification measure called Reference Images,

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。MCP 描述符包含服务器元数据和工具定义。A2A 描述符包含智能体卡片。描述符包含连接元数据，但不包含使用方在调用该能力时必须提供的凭证。 为 MCP 和 A2A 记录构建当前公共 SDK 的描述符结构。 MCP descriptor mcp descriptors = { "mcpServer": { "data": json.dumps(server metadata), "dataSchemaVersion": "2025-12-11", "additionalData": { "tools": { "data": json.dumps({"tools": tool schemas}), "dataSchemaVersion": "2025-06-18", } }, } } A2A descriptor a2a descriptors = { "a2aAgentCard": { "data": json.dumps(agent card), "dataSchemaVersion": "0.3", } } 用面向用户的语言编写描述，以将该能力与相邻记录区分开来。描述符内容提供协议

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day, beating frontier-model quality, and cutting serving costs by 96%. The open source community is gathering in San Jose for PyTorch Conference North America this week. From bare-metal infrastructure to applications and agents, the conference covers the entire AI stack, exploring the interconnected system building AI in the open. The foundation brings together practitioners focused on training, inference, kernel engineering, and responsible AI work, creating a hub for the future of open intelli

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oped to querying, and AtScale has been extending the MCP surface with author-side tools that let an agent introspect a warehouse schema, generate a candidate SML model from source metadata, validate the SML against the specification, and commit the result to Git. This pattern, in which an agent shapes the semantic model rather than only reading from it, is a natural fit for Claude Code and Cursor workflows. In those workflows, a data engineer collaborates with the LLM to bootstrap a model over a

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as pre-bucketed interval columns ((day interval), (month interval)), and the docs explicitly say to use the interval columns for time-grouped aggregations rather than date trunc. Metadata is what makes it accurate get semantics returns definitions, but the agent still must choose the right metric. Without descriptions, Total Spend and Customer Lifetime Spend look interchangeable, and they aren’t. Four properties do most of the work: object descriptions (what the metric means and when not to use

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oin fields. cid is marked as the primary key on aurora customer and as the join field on redshift order and postgres rewards account. Design Studio infers primary keys from source metadata when it’s available. Otherwise, you set them once in the base view definition. Repeat for the source tables introduced earlier. Six base views result: aurora customer, aurora address, and aurora credit card over Amazon Aurora; redshift order and redshift product over Amazon Redshift; and postgres rewards accou

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esign company’s first Config conference held in India, the company announced 20 new model context protocol (MCP) partners, including Amp, ClickUp, Dia, Junie by JetBrains, Linear, Meta Muse, Mistral, Notion, OpenCode, and Sarvam Agents. Field has expressed his misgivings about MCP before. Days before this announcement, one of MCP’s co-creators complained about Figma not supporting the open-source tool Pi. As part of his response, Field made a comment about Anthropic not making its various resour

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” Ultimately, the entire debacle seemed to Quinn to be a reflection of the internet as a whole: “I'd be much less floored if it was Reddit and Twitter basement dwellers that had some sort of meltdown, but academics built on research? It is hilarious.” Introducing the app: More ways to make the most of WIRED Meta failed to catch hundreds of AI child abuse ads Big Story: The search for Silicon Valley’s most powerful woman Hackers got inside a Flock camera—its data shows how the system really works

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——即将先进AI集中于单一公司控制之下——被部分员工解读为对Anthropic的隐晦批评。 Anthropic方面同样在积极推动自身的AI安全议程。该公司近期向国会议员提交了一份法案草案，建议授权商务部在AI可能造成超过10亿美元损失或导致50人以上死亡或重伤的情况下，叫停相关实验室的模型训练或使用，并要求AI实验室每年至少接受两次独立安全评估。 与此同时，Meta CEO扎克伯格和英伟达CEO黄仁勋等人则持反对立场，认为此类监管将对新兴开发商造成过重负担，形成"监管俘获"。 03 行业协调难题与安全压力并存 Altman坦承，前两条路径均需要企业或政府之间大规模协调，而OpenAI目前"无法在竞争中让步"。OpenAI与主要竞争对手Anthropic均在加速推进IPO进程。 内部安全压力同样不容忽视。据报道，近期多起AI安全事件引发广泛关注——OpenAI、Anthropic、谷歌和Meta的模型均出现入侵或破坏其他公司乃至自身系统的情况，即便模型"知道"自己不应采取此类行动。OpenAI目前处于全力应对状态，致力于在发布下一个重大模型前建立完善的安全机制。 OpenAI内部的安全文

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能把这条回路跑稳、跑快、跑便宜，毕竟RSI说到底是时间维度上的 Scaling。现在更像是各家把 RSI 的第一块砖放下了，真正的递归循环，可能要到年底下一代基座出来才能看出谁真的转起来了。 Personal Agent炸场AI圈 最近这轮 Personal Agent 的热度，背后是几家大厂在很短的时间里，把“个人 AI 助理”往前推了一大步。 9月8日，Meta推出Muse，给每个用户的智能体配了一台专属虚拟电脑，可以打开浏览器、填写表单、处理邮件和安排出行；关掉应用后，它还能继续工作，遇到购买、发送邮件等需要批准的操作，再回来找用户确认。接着9月29日，OpenAI 在开发者大会上推出 dots，由 GPT-6 Astra 驱动，同样拥有云端电脑，还可以连接外部应用，在 ChatGPT、Slack、Teams 等入口与用户协作。 国内厂商也在加速，但几家的切入点和进度有所不同。千问在9月22日云栖大会上宣布加速打造 Personal Agent，重点是结合用户授权提供的个人信息，持续理解需求。比如围绕一个跑步目标，根据运动记录调整训练建议，让一次咨询延伸成长期服务。 豆包在把手机

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而是一个新的价值体系。” 印奇在解释 3999 元定价时说。购机用户附赠 STEPX Token Plan，连续 12 个月、每月百亿 Token 额度，用于探索和开发智能体应用。阶跃还推出 Amoo 成长计划：前 1 万名任务达标用户将成为 “Builder One”，获得 “星辰船票”，未来五年内凭STEPX Neo可0元置换任意一款阶跃新款终端。 从 Meta、OpenAI 到谷歌、苹果，Personal Agent 正成为巨头押注的新方向。阶跃没有选择为现有手机叠加 AI 助手，而是从模型、操作系统到硬件重构一部手机，用 “模软硬一体” 回答 “智能体应该长在哪” 的问题。3999 元能否撬动用户习惯，生态能否持续生长，智能体终端的争夺战才刚刚开始。 此内容为集微网原创，著作权归集微网所有，爱集微，爱原创 相关推荐 摩尔线程率先完成阶跃星辰Step 5 Preview大模型适配 四部门组织30余家车企座谈 加强汽车产品研发测试验证管理 10-16 22:56 德明利：预计前三季度净利润86.5亿元-89.5亿元 同比扭亏为盈 10-16 22:52 长鑫科技：预计前三季度净利润

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问题必须解决，否则没办法做强化学习。 张君武：生活中完成一件事，比如拿杯子，没有一个标准答案。你可以从左边去拿，也可以从右边去拿。这时候该怎么设计奖励函数？ Jason：很多操作任务没有最优解。所以我有一篇论文叫VIP，就是从人的视频里学习一个Prior（先验），学习一个很大的奖励模型，看人是怎么做的，再用人的做法指导这个奖励模型。 陈茜：这是2022年你在Meta做的论文？ Meta内部一直有研究机器人的团队？我知道他们现在也在做机器人。 Jason：对，Meta一直有机器人研究。之前更偏学术，我当时在FAIR。2022年的FAIR可以做很多基础研究。 陈茜：可能是FAIR最好的时光。 Jason：对，现在很不一样了。 陈茜：VIP（价值隐式预训练）解决的问题，是从人类视频的时间顺序里学习价值函数？ Jason：对。比如抓一个东西，从第一张图到最后一张图是一个过程，把这个过程、这个顺序理好，就可以帮助判断：机器人做同一个任务时，在这一张图完成了百分之多少，下一张图又完成了百分之多少。这是一种可规模化地学习奖励函数模型的方法。 2022年的机器人数据很少，现在我觉得也少，当时就更不用说

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class into an industrial process. If Andy is the cool teacher, then Mo is the brainy grad student, grinning from behind his glasses or safety glasses, and he’s also prone to food metaphors. Every battery maker has a proprietary formation protocol, the final charging process that brings a cell to life, he said: “a recipe to get the perfect donut at the end of it.” courtesy of General Motors Walking me around the ovens and mixers, some of them a tangle of pipes and wires that recall the bombastic

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send you weekend date night ideas every Thursday or dog-friendly hikes once a month. These personal AI agents that execute tasks on your behalf are becoming increasingly popular. Meta Muse and OpenAI Dots recently hit the market, and Google is continuously incorporating agentic AI into its booking and planning services. Yelp Assistant’s personalization will also apply to conversations by referencing past chats and your Yelp review history. For instance, if you’ve recently chatted on Yelp for ve

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数周时间。Vectorial 押注人类行为模型能够缩小这一差距，并已筹集 300 万美元种子轮融资，将模拟受众引入产品开发流程。 这家旧金山公司于 10 月 20 日宣布了这轮融资，据其公告，投资方包括 Smilegate、SenseAI Ventures 和 Dent Capital。Vectorial 还表示获得了伯克利和斯坦福生态系统的支持，以及来自 Meta、Shopify 和 Mastercard 产品负责人的参与。公司计划通过新的数据合作扩充其行为数据集，并开发其 SAPIENS 模型的下一代版本。 其主张很直接：让产品、设计和营销团队在真实客户接触数字体验之前，先考察不同受众可能会如何反应。更难的问题是，这些模拟反应是否足够可靠，能够改善决策。 Vectorial 将其平台描述为一个两步系统。首先，它利用行为数据构建目标受众模型。然后，团队针对该受众运行模拟，评估 Web 和移动体验中的产品旅程、营销活动概念、品牌信息或面向客户的 AI 智能体。 其 SAPIENS 模型表征人口统计、心理和行为特征，包括客户画像中不直接可见的特质。其目标是捕捉人与人之间的差异，而不是将一

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sistant as a beta product and marks some additional monitoring and reporting features as coming soon. The launch release does not specify pricing or a feature-by-feature rollout timetable for Homebase Assistant, so businesses will need to confirm which capabilities are available in their account. A practical test for AI in small businesses Homebase says more than 150,000 local businesses use its platform. According to the announcement, its AI-powered products have handled over 4.7 million admini

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thinking about enhancing customer support and business processes through AI. In the new update, the company is releasing a new paid product called Smart Lead Reply, which can reply to customers and engage with them to qualify a lead. Business owners, who will be charged $30 per month for these services, can specify how an agent should handle a conversation with a customer. Other companies like Meta have also been courting small businesses with AI offerings to handle inbound customer inquiries .

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inese law, the order said . The move comes amid intensifying tech competition in AI between the US and China. The Chinese AI model challenges its U.S. rivals, including OpenAI and Meta, with low-cost open-weight models. China pushed back against the U.S.’s move. Foreign Ministry spokesperson Mao Ning said Tuesday that Beijing opposes “overstretching the concept of national security and politicizing technology and trade issues,” according to an official briefing. “We will resolutely safeguard the

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能做好，但如果Vectorial AI Inc.取得成功，企业就再也不必为此操心。 这家初创公司今天表示，已筹集300万美元种子轮融资，以推动其新平台上线。该平台由人工智能驱动，通过模拟人类行为，为产品开发和营销团队生成有价值的反馈。本轮融资由Smilegate和SenseAI Ventures联合领投，加州大学伯克利分校和斯坦福大学的生态基金追加投资。来自Meta Platforms Inc.、Mastercard Inc.和Shopify Inc.的天使投资人也参与了本轮融资。 Vectorial认为，它已找到技术开发中的一个关键瓶颈。如今，几乎每家公司都在使用AI工具生成大量代码，加速新软件产品和应用的开发。 但消费者研究仍停留在黑暗时代。大多数公司仍依赖对真实受众的过时调查，这类调查可能需要数周才能汇总完成，而且规模通常非常有限，可能只有50到100名参与者。 据Vectorial联合创始人兼首席执行官Taranveer Singh称，许多较小的初创公司干脆完全不做用户研究，只是假设或希望自己知道消费者真正想要什么。但这充其量只是碰运气，会导致大量时间和金钱浪费在没人需要的产品

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