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l fight between AI company Perplexity and Amazon , in which Amazon sued Perplexity in 2025 to block agents from browsing and shopping on its site. Amazon has also recently blocked Meta’s Muse AI agent from shopping on its site and removed product details from order emails — data that is potentially very valuable for Google’s own agentic shopping features. Amazon’s ad business generated $19.8 billion in revenue in the second quarter of this year, driven by sponsored product listings . Bites can k

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-Aware Distillation: The student reaches 63.4% on unseen ALFWorld tasks versus 47.0% for the best baseline and exceeds its 8B teacher; Other papers: Amazon’s looped diffusion LMs, Meta’s MIRA meta-reasoner for research agents and Priced Guidance, which measures LLM research novelty through compression; Optimizer claim: ANVIL III reportedly reaches 0.020–0.028 nats lower loss than Muon from 124M to 1.2B parameters. The authors say this implies 50% compute savings at 8x-Chinchilla, with less tunin

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emember your name. AI agents are currently leaping from niche software for early adopters to something ordinary people might actually use—might being the operative word here. From Meta’s Muse to OpenAI’s Dots, these tools are built to feel like you’re texting a friend and asking them to complete online tasks, like booking a flight or canceling a dinner reservation. It’s the next evolution of a chatbot: a cuddly persona designed to feel welcoming with the power of a virtual browser it can control

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現，一旦人們發現圖像是由人工智慧生成的，他們就會「在情感上與圖像脫離關係」。 時尚品牌H&M告訴BBC，2025年品牌曾與真實模特兒合作，製作了「模特兒的數位模型／孿生體」。 這些模特兒「保留了對其數位孿生體的完全控制權和所有權」。 然而，「這項探索工作在 2025 年春季暫停」，以便考慮下一步行動。 我們已聯繫 Balmain、Levi's、TikTok、Meta和Google等公司徵求意見。 如果您或您認識的人受到本文所述問題的影響，可以透過 BBC Action Line 獲取有關可用協助和支援的資訊。 本文原以英文撰寫，我們使用了人工智能協助翻譯，並由BBC記者在發佈前進行審核。了解更多關於我們如何使用人工智能的資訊。 探索更多 更多短片 02:54 視頻, 誰贏了特習會：習近平佔盡上風？, 節目全長 2,54; 00:57 視頻, 示威者聚集華府 抗議習近平訪美, 節目全長 0,57; 01:12 視頻, 特朗普和習近平白宮檢閱儀仗隊, 節目全長 1,12; 02:15 視頻, 美國民眾看習近平到訪：中美競賽誰領先？, 節目全長 2,15; 02:39 視頻, 習近平特朗普再

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。 悄悄回到X 现在让我们来谈谈一件真正令人不快的事。 大约三年前，我停止在X上发帖，以抗议其新的所有权。有一段时间，每天都会带来埃隆·马斯克的一些新的暴行：煽动对其前员工进行危险的骚扰；操纵平台打压记者及其工作；发帖支持反犹阴谋论；拆解内容审核机制，等等。 我离开的主要原因是我无法忍受待在那里的念头。我也希望自己能利用微薄的影响力，帮助启动新的平台。我鼓励Meta高管用一个Twitter克隆产品挑战X，并且自Threads推出以来每天都在使用它。我密切关注了Bluesky的发布，并持续为其（以及Fediverse）投入精力，即便它们正在衰落。当马斯克起诉OpenAI、试图实际上摧毁它时，我反复告诉Sam Altman要创办一个X的竞争对手，并把他的AI发帖转移到那里。 无论这些行动可能具有怎样的美德，它们都未能成功地在对我而言最重要的领域创造出一个真正的X竞争对手：一个供日常科技与商业对话的论坛。在人工智能产品与政策领域及其周边工作的人群，就是拒绝离开X，无论它变得多么糟糕。 在此过程中，X 曾两次被吞并，先是并入 xAI，随后又并入 SpaceX。虽然我从未对抵制 X 能在经济上对

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mmands: answer-query: Get grounded answers in your terminal; documents search-chunks: Search document snippets and chunks across Google documentation; documents describe: Retrieve metadata and content for a specific document Examples: Agent skill The Developer Knowledge agent skill establishes a link between AI coding assistants and Google's documentation ecosystem, enabling autonomous tools to access up-to-date technical specifications. Key Benefits Grounding & reduced hallucinations: Provides

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g without ever hearing a complaint. A personal agent is an AI assistant that carries out tasks on your behalf, from booking appointments to resolving billing issues. Products like Meta's Muse, Instinct, Grok Bot, and OpenAI's dots are starting to bring personal agents into everyday use. I expect this to become a normal way for people to deal with businesses and to be widely adopted by the general public. At Vapi, we've launched Personal Agent Calling in beta. You can sign in with Vapi and make c

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hout a person in the loop. Relationships are built person to person and agents themselves don’t build trust. So… why the name? A rasp is a coarse file. You use it to shape wood or metal, taking material off and leaving rough texture behind. It felt like a great name for something that does shaping work on a company pipeline. Rasp drafts, sorts, flags, and routes, whittling down the raw sales material. People step in, polish the woodwork, and complete the piece. What a GTM agent needs: four requi

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remain separate launches; only the histogram counts are reused. Another optional core-module path moves index transpose, sort, and run-length encoding into forward and returns the metadata through autograd. It defaults off and is not exposed by the current TorchRec wrapper. On a large B200 configuration, forward moves from 22.844 ms to 33.252 ms, backward from 56.693 ms to 32.931 ms, and combined latency from 79.537 ms to 66.183 ms (−16.8%). 3. Implementation of Triton TBE Backward Kernel The co

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k AgentCore. AgentCore memory, a capability of Amazon Bedrock AgentCore, turns disposable chats into durable knowledge. You will also see how to tag those memories with structured metadata to retrieve records that matter for the question at hand. Our running example is Sprout, a gardening assistant, but the architecture is domain-agnostic. Swap the persona and the skills manifest, and the same pipeline serves a support bot, a fitness coach, or an internal help desk. The entire system lives in a

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cing in the app, which Chowdhury says is intended to build trust with users that the agent is doing the right thing. That matters because part of Hark’s pitch is that they are not Meta or OpenAI — “we’re not here to like sell you ads and steal your data,” Chowdhury says. To truly leverage these models, users will need to share their entire digital lives. Beyond very real cybersecurity concerns , will users be comfortable with a company like Meta having its products create detailed profiles of th

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4上的苹果Audio Intelligence类似。Apple Watch多年来一直配有麦克风，主要用于Siri和从手腕上接听电话。在四项Audio Intelligence功能中，有两项在网上引发了最多争论：Live Rewind和Siri Recap。前者生成过去15秒的转录文本，后者则能生成你一天中所进行对话的高层级摘要。 换句话说，Ray-Ban Meta眼镜会拍照和录制视频，并存储在手机上。而传闻中苹果的这一方案则意味着摄像头能看到你、麦克风能听到你——但两者都不“保存”任何东西。 这算录制吗？苹果不对传闻置评，但根据该公司公开阐述其Audio Intelligence隐私理念的方式，我认为苹果并不这么认为。苹果表示，这些功能不保存任何音频。原始数据在S11处理器上一个独立、安全的enclave中完成处理后即被删除。任何发送到云端的信息都通过私有云计算进行，因此苹果或第三方都无法访问。 也不只是苹果。谷歌可穿戴设备高级总监桑迪普·瓦拉伊奇在接受The Verge采访时表示，谷歌也在考虑这一概念。他提出，如果智能眼镜上的摄像头不录制数据会怎样？例如，如果眼镜能用AI处理你环境

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lexity. In real life, you may have competing definitions of the same metric across teams, ambiguous joins between tables, business rules that live in people's heads rather than in metadata and no way to decide which source is authoritative when two numbers conflict. The LLMs weren't the bottleneck; context was. Even as models improved dramatically, they were still guessing at meaning from raw table names and column headers, which is why the same question asked twice could produce two different a

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es, at this point! A few examples: Ramp building Inspect – a case study we covered in depth; Stripe (Minions), Uber (Minion), Block (Goose), Shopify (River); Google (Agent Smith), Meta (Devmate), Amazon (Kiro + Crew), Dropbox (Nova), Spotify (Honk); DoorDash (Flux), Grab (LLM-Kit), WorkOS (Horizon), Hubspot (Crucible); Monzo (Agent Chip), Sierra (Pinecone), Harvey (Spectre), Browserbase (bb); … and many, many more! 8 Dev work often starts in Slack What I’ve learned by visiting startups is that m

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dio, machine learning teams that already work in a project can follow an approved path to shared SageMaker HyperPod compute. Members can find connected clusters, review status and metadata, inspect supported tasks and metrics, and move into JupyterLab without using a separate infrastructure inventory. This experience doesn’t replace cluster administration. The following table shows how each persona should use SageMaker Unified Studio alongside the service-specific interfaces. Use SageMaker Unifi

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ancial Times — about whether US data center debt issuance has reached a point when it’s creating meaningful competition for US government debt, specifically that issued by Google, Meta, and Amazon, because these “stable” companies are offering attractive rates that are, in the eyes of some investors, as stable as lending to the US government. While it’s had some effect, it isn’t the big reason that the ten-year is selling off So, while we can’t point at one reason, there are plenty of reasons th

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，并选取了误差最低的那一次。 作者提醒，学到的部分能够清晰分离，并不意味着它们捕捉到了真实的因果关系。这样的模型何时能可靠到足以指导实验设计，也仍是一个未解的问题。这是团队的长期目标：AI智能体将使用JEPA-Anything提出并排序实验，然后将结果反馈给模型。代码和模型已公开。 LeCun于2022年提出JEPA，作为生成模型的替代方案。2025年6月，Meta发布了V-JEPA 2，这是一个拥有12亿参数的JEPA视频模型，无需额外训练即可在陌生环境中控制机械臂。2025年11月，LeCun与Randall Balestriero随后推出了LeJEPA，这是一个旨在无需常规变通手段即可保持训练稳定的理论基础。LeCun目前正通过其初创公司AMI Labs推进这一方法，该公司于2026年3月融资超过十亿美元，用于构建世界模型。 Google Deepmind已于2025年10月在实验室中测试了一个由AI生成的癌症假说。其基于Gemma的模型C2S-Scale 27B提出使用药物silmitasertib使肿瘤细胞更容易被免疫系统识别，而利用人类细胞模型进行的实验证实了这一预测。Go

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nment pledged 530 billion won (about $390 million) to the five selected companies. The new plan roughly multiplies that figure by nine. For context, Google, Amazon, Microsoft, and Meta are planning combined investments of around $725 billion for 2026 alone , mostly for AI data centers. South Korean industry is already pouring money into more compute capacity. In October 2025, Samsung and SK struck a deal with OpenAI to expand AI infrastructure in the country. Then in June, Samsung, SK Hynix, and

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alongside fresh takes on the chatbot race, personal agents, and how AI apps are making money. The details: Why it matters: a16z’s recurring list has become a handy tracker of the metas that AI cycles through, from early chatbots to creative tools, coding, and now personal agents. With xAI's Grok Bot, OpenAI's Dots, and Meta’s Muse all piling in, the current trend also looks like AI's next real shot at a mainstream breakout. AI TRAINING 🛠️ Protect your files with this Claude Code mod The Rundown

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Auto-Ontology open source library that can create knowledge graphs from enterprise data. The Enterprise Knowledge Graph shows how structured and unstructured data is related using metadata, lineage, and query history to continuously tune the graph. While the semantic layer can show agents what a word actually means, the knowledge graph can provide connections between that data and data in other systems. “If you're trying to draw some correlations between how often a defect happens and whether it

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