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说道：“这个名称是由全世界最伟大、最聪明、最杰出的人们正式更改的。” 但这些科技公司高管似乎签署了一份单独的两页文件，特朗普在他的“真相社交”账号上分享了这份文件。该文件并未声明要更改名称，只是在其标题中提到了特朗普对人工智能的新称呼：“白宫超级智能协议”。 该协议副标题为“前沿责任联合承诺”，其中表示签署方“认为每家公司都有责任以安全且能建立信任的方式开发自己的技术”。该协议指出，这包括实施“健全的内部流程和控制，以确保其技术按预期运行”，并建议增加四层控制措施。 根据该文件，签署方同意“定期会面”以制定安全标准，文件还补充说，“随着时间的推移，将这些步骤编纂成法律或法规可能是有意义的”。 除了特朗普之外，上述帖子还显示，签署该协议的还有六位科技公司高管：谷歌CEO桑达尔·皮查伊、特斯拉以及SpaceX首席执行官埃隆·马斯克、Anthropic首席执行官达里奥·阿莫代伊（Dario Amodei）、Meta首席执行官马克·扎克伯格、OpenAI总裁兼联合创始人格雷格·布罗克曼以及英伟达CEO黄仁勋。 当被问及该文件是否具有任何约束力时，特朗普在白宫外表示，该文件“具有道德约束力” 。

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bout 5x Luna per task, because only 48% of its repeated context hits cache versus 99% for Luna ( @ArtificialAnlys ). Agent Research, Inference and Systems Context Language Models (Meta) : CLMs treat context as an editable file rather than an append-only log, with context-management policies learned in the weights and no external harness ( @RulinShao ). Result : They score 65% higher with the same compute on a 24-hour multi-repository agent-swarm task ( @arankomatsuzaki , @natolambert ). Adaptive

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满意。苹果的市盈率目前处于30多倍的高位，这远高于标普500指数的约22倍。 他警告称， 如果周四的苹果财报令人失望，尤其是如果半导体价格上涨挤压利润率，苹果可能会面临风险。今年内存芯片成本飙升，这一趋势已经已迫使整个手机市场提价。 “你不能因为他们没有在AI上花钱，就把世界上所有的钱都投到这一只股票上，”Niles指出，“在这样的估值水平下，这并不合理。” 华尔街机构目前预计，苹果二季度营收将接近1089亿美元，每股收益为1.89美元，高于去年同期的1.57美元。投资者将密切评估其Apple Intelligence能否在不推高资本支出、不侵蚀营业利润率的前提下顺利落地。 周四的财报发布也正值科技巨头密集公布财报的一周，Meta和亚马逊也将在同一周发布财报，同样面临着关于AI支出的类似审视。 值得注意的是，本周四的财报电话会议也将是蒂姆·库克作为苹果CEO主持业绩会议的“告别之秀”。 库克将于9月1日卸任CEO并转任执行董事长，正式将苹果的掌舵权移交给硬件工程资深高管John Ternus。无论如何，库克留给继任者的，不仅是一份创纪录的市值成绩单，更是这一轮AI狂潮中最独特的避风港。

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oop stays the same: curate, mix replay, choose an adaptation depth, bucket by duration, evaluate on independent target and regression sets. What changes per language is the corpus metadata, transcription conventions, normalization, tokenizer coverage, script handling, and capability metrics. For another language, start with a small audited manifest and test the base tokenizer on names, numerals, borrowed words, and mixed-script sentences. Replace the Arabic normalizer with one that preserves mea

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n" image, the model integrates a timeline, a line chart, a bar chart, and a realistic view of the station within a single frame. The information hierarchy is clear, and the visual metaphors are accurate, demonstrating the model's ability to spatially organize panoramic data. Prompt: A visual infographic chronicling scientific research at Antarctica's Qinling Station. Place the main Qinling Station building at the center. Surround it with a timeline of research station development, a bar chart co

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lt is an urgent and growing need for more fast inference across the industry. Cerebras is the market leader in high-speed AI inference, powering models from OpenAI, Cognition, and Meta at up to 3,000 tokens per second. Today's announcement brings that speed to AWS's global customer base. And through our unique collaboration on disaggregated inference, we'll be able to provide 5x more capacity for high-speed inference. Every time you ask AI a question, two distinct kinds of computation happen: pr

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cifically focuses on training foundation models and large language models on newer modalities such as structural biology and joint image-text pairings, and evaluating methods with meta-learning downstream task performance-in-the-loop. Most foundation model research has been in text or image data, and we plan on focusing our work in new multimodal and biological data types as well as evaluating downstream fine-tuned task performance using in-the-loop meta-learning techniques. School of Humanities

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ant-programs/hai-accelerator-for-learning-partnership-grant","children":["HAI与学习加速器合作资助",null]}]}],false,"$undefined","$undefined",false,false,["$","div",null,{"className":"ContentMeta root xqJXg ContentMeta isGrant 91KjO","children":["$undefined",null]}]]}],false,["$","div",null,{"className":"ContentItem imageContainer kCAMl","children":["$undefined","$undefined"]}],["$","div",null,{"className":"ContentItem content 1QYrh","children":[["$","div",null,{"className":"ContentItemDek root P1pHC Conte

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ally designed for mental health purposes, but are commonly used for mental health support Companion chatbots Examples: ChatGPT’s CounselorGPT, Character.ai’s Trauma Therapist, and Meta AI Studio’s My Therapist General-purpose LLMs that assume a particular persona or role, such as that of a therapist, friend, or trusted partner Wellness apps that use AI Examples: Wysa Applications that use AI to provide mental health support and promote emotional well-being more broadly but stop short of making m

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e administration is weighing whether to extend that kind of scrutiny to Chinese open models as well. The conversation has led to an American corporate response; Nvidia, Microsoft, Meta, and 20-plus other companies published an open letter warning Washington against “premature restrictions” on open-weight AI models, highlighting the need for competitiveness in a heated global market. Stanford Institute for Human-Centered AI Denning Director James Landay agrees with the instinct behind that letter

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provement is involved. The idea of an AI kill switch has gained appeal because it offers a seemingly concrete response to an uncertain threat. But the panelists cautioned that the metaphor can obscure more than it clarifies. Yang said a shutdown mechanism may be necessary, but only after answering a basic question: What exactly would it switch off? “AI” can refer to frontier foundation models, networks of autonomous agents or the many smaller systems already embedded in products and institutions

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stead of guessing or hard-coding coordinates, then query Fishing Events within that geometry, format the results with deep links back to the Skylight map, and attribute any vessel metadata drawn from Skylight partners like Global Fishing Watch or TMT. A single question posed to Shippy can hook into several skills at once. "Are there vessels operating near the Cordillera de Coiba MPA?" draws on the Skylight skill for data query, our partner ProtectedSeas’ database for MPA boundary context, and th

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dar, the available polarization channels may matter more. We rely on public STAC catalogs and open standards wherever possible. But a large inference job can generate thousands of metadata queries at once—far more than external services such as ESA’s or Microsoft Planetary Computer’s STAC APIs are designed to handle concurrently. To avoid overwhelming those services, the OlmoEarth Platform maintains its own metadata index, updated as new imagery is published. For datasets hosted through AWS Open

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of tasks by work time at level E2. Only 8% of their work time is unexposed. For example, robots with computer vision and suction grippers can do the task “Sort materials, such as metals, glass, wood, paper or plastics, into appropriate containers for recycling.”³⁰ These robots stand in for workers picking recycling from conveyor belts, so this and other tasks are rated E2. Robots are highly capable at specific tasks for tapers, while for recycling workers exposure is broader, but robots are les

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e. 3 Over the years, METR has worked to gather evidence about these frontier AI agents with access provided 4 by America’s leading AI developers such as OpenAI, Anthropic, Google, Meta, SpaceXAI, and Amazon. The participation of these AI developers is voluntary, 5 and METR is not paid or funded 6 by them. Today, I am here to speak about one particular voluntary engagement, in which OpenAI allowed a handful of my colleagues 7 inside its walls to conduct a brief investigation into how its agents b

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65 security controls. Much of this functionality was already possible through Codex and similar agentic harnesses — but Dots bundles together those features in a new package with a focus on independent agentic actions. The branding also presents a bubbly, cartoonish persona, similar to Meta’s recently released Muse agent. The Dots look like … well, dots. The little floating cartoons are a makeover for OpenAI’s software and are the latest example of a company attempting to make AI more relatable.

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Wabi , the AI startup that allowed anyone to use prompts to build apps , is undergoing a slight pivot as demand for AI agents, like Meta’s Muse and Instinct , takes off. The company announced this week that it is now becoming an AI messenger of sorts — but one that’s still capable of making apps to help you get things done. The startup’s founder, Eugenia Kuyda, who previously founded the AI companion startup Replika, described Wabi 2.0 as a “personal agent that does stuff for you and builds the

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Ewen说，尽管Restate可能应用于不同的用例，但客户都有着相同的需求——一种确保在流程中途出现故障时，系统能自动找到自我恢复的方法。 在创立Restate之前，Ewen是广受欢迎的开源流处理框架Apache Flink的联合创造者之一，后来成为Data Artisans的CTO，该公司负责将该项目的商业化。阿里巴巴于2019年收购了Data Artisans，并将其更名为Ververica，Ewen在那里继续担任CTO三年。他与Data Artisans和Ververica的前同事Igal Shilman和Till Rohrmann共同创立了Restate。此前曾在Stripe和Meta担任工程师的Ahmed Farghal在A轮融资时作为第四位联合创始人加入。 该公司打算利用新资金组建市场推广团队、招聘更多工程师，并扩大其旧金山湾区办公室，以便更贴近许多现有和潜在客户。 尽管如此，Ewen坚持认为，Restate的能力很快就会对传统科技公司以外的企业变得不可或缺。 “如果我们快进几年，它就会像数据库一样，成为我认为几乎任何公司都会有使用场景的工具，无论其形态和规模如何，”他说。

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s — otherwise the user will feel like they’ve been spammed. That’s not likely to endear users to the AI agent at a time when it’s competing with agents from bigger companies, like Meta and now OpenAI , which don’t do this. Nice that it is curated and hopefully it’s good but ask me whether I want the recommendations. I just got a random notification for additional equipment based on a future trip which I didn’t ask for and don’t need. Also allow me to curate my own sources as well as the ones you

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that she was finally ready to unveil Dazzle, the personal AI assistant that raised an $8 million seed round last December , I couldn’t help but wonder if she’s playing copycat to Meta’s Muse, Instinct, and the wave of similar tools that have flooded the market over the past month. But when Mayer finally gave me a demo, Dazzle proved it’s taking a different approach. Instead of building context about you from text-heavy apps like email, calendars, and shopping histories, Dazzle’s AI assistant ge

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