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nformation, from medical issues to financial information. About half of all American adults report having used an AI tool, according to a June study from the Pew Research Center . Meta says it will alert parents if teen AI chats suggest suicide risk The increase in data sharing has triggered privacy concerns , as many AI companies say they use users' chatbot conversations to train their large language models. "Once that data is being used for training purposes, we don't really know, kind of, wha

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dylan522p by the way :) Thinking Machines - Inkling - Jul 15 Moonshot - Kimi K3 - Jul 16, weights Jul 26/27 inclusionAI - Ling 3.0 Flash - Jul 23 DeepSeek - V4-Flash-0731 - Jul 31 Meta - Muse Spark 1.2 / Muse Code - Aug 5 Liquid AI - LFM2.5-2.6B - Aug 6 inclusionAI - Ling 3.0 Tiny - Aug 6 Meta - Muse Glimmer - Aug 10 NVIDIA - Nemotron 3.5 Lightning - Aug 11 Liquid AI - LFM2.5-VL-3B - Aug 12 Cohere - North Micro Vision Instruct - Aug 12 DeepSeek - V4-Pro-0813 - Aug 13 Qwen - Qwen3.8-27B - Aug 14

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ncoming data, RDMA-capable systems may allow the network to place data directly into accelerator memory, avoiding a full copy through CPU DRAM. CPU memory still remains useful for metadata, coordination, partial assembly, fallback paths, replicas, and outgoing staging. When a worker uses multiple GPUs the incoming context can be striped directly to their destination memories in parallel. Rack-level hot-blob caches can also be useful, whether implemented as memory/storage appliances or making use

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. ElevenLabs now has about 15 of these in house, and the job description is public if teams want a template for hiring one; Distribute. A media buyer pushes the assets live across Meta, LinkedIn, and other channels; Analyze. The strategist, producer, and media buyer meet weekly to review results and plan the next week's content The sequencing advice for teams starting from scratch: hire the AI creative producer first. Once one or two are consistently producing strong content, add a dedicated str

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Code. Open language models primarily are bucketed into two categories, open-weight and open-source models. Open-weight models are the most common form, such as popular models like Meta’s Llama, Alibaba’s Qwen, Google’s Gemma, or DeepSeek’s models. These models are governed by licenses, governing documents dictating what is allowed with downstream use, and are often accompanied by inference code in libraries such as Transformers, VLLM, SGLANG, etc. Since about April 2025, Chinese AI companies hav

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encoding implementation: use tk-encode during training validation so training and inference cannot produce different tokenization results optional offsets and masks: compute this metadata only when requested, keeping it off the token-ID-only path rework normalizers bitnorm support, building on atomnorm 2209 spm precompiled simpler Python bindings: reduce locking, wrapper types, and handwritten dispatch code while preserving subclassing, serialization, custom decoders, mutation behavior, and sup

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all moving to raise fresh capital just as DeepSeek staffed up for a possible IPO. Agent startup Manus is seeking a $4 billion valuation in its first fundraise since splitting from Meta; Z.ai (Zhipu) is chasing another roughly $5 billion after its July raise and just lifted its ARR target 25% to about $3 billion as compute constraints ease; AI chip designer Biren is weighing a $1 billion share sale; and DeepSeek hired a Hillhouse dealmaker as CFO to accelerate its own path toward a listing. (Bloo

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Qwen-Image-2.1 supports several ways to specify local edits. The example below uses circles to identify three regions and asks the model to “remove the metal watch in the blue circle, change the hair in the red circle to black, and replace the area in the green circle with gray short-sleeved linen pajamas,” performing removals and modifications in all three regions at once.

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inted annotations, and separate masks to specify where an edit should take place. The first example uses circles of different colors to identify three regions at once: “Remove the metal watch in the blue circle, change the hair in the red circle to black, and replace the area in the green circle with gray short-sleeved linen pajamas.” The annotated input is on the left, and the result is on the right. Painted annotations provide another way to identify a region. In this example, the model adds a

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等的月薪。 被“挖角”的不只是工程师，能掌握研发路线的高管以及手握专利的大牛更是争抢的核心目标。 海外方面，波士顿动力CTO Aaron Saunders、研究副总裁Scott Kuindersma就先后离职，并加入Google DeepMind，分别负责硬件工程研发和灵巧手操作研发。特斯拉Optimus AI团队的负责人Ashish Kumar离职后，加入Meta担任研究科学家一职。 国内的案例也不少，原京东具身基模负责人庄雨铮，加入贝塔无限担任首席科学家；原小鹏集团副总裁陈永海，去了众擎机器人担任运营总裁；原逐际动力联合创始人兼COO张力离职后加入智在无界BeingBeyond，工作重心由足式机器人企业转向具身模型；原地瓜机器人具身智能负责人何泳澔，已加入虚时科技成为CTO…… 这种高频离职与入职，本身就是赛道焦灼状态的缩影。 《人形机器人简史》一书中，作者周小燕梳理了人形机器人发展史的几轮高潮与低谷。但面对2026年这波离职潮，她认为，“一个值得观察的角度是这些离职人员的去向。不少人离职后，依然选择投入具身智能行业。这说明他们离开的是某一家公司，而不是放弃这个行业，不能简单地把企

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ath strength” narrative, @steve47285 shared an argument that pretraining data , not merely verifiable reward structure, is the main reason LLMs are so good at math and coding. The meta-point from @sarahcat21 is worth keeping: we need not just better benchmarks, but better benchmark maintenance and audit tooling . Computer-use benchmarks are still far from saturation : @ValsAI launched CUA-Bench , testing real-time keyboard/mouse use across 6 games (with 3 kept private ) as a proxy for difficult

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g the emgram in HBM. Our benchmark has been widely reproduced, validated and/or supported by almost every major buyer of compute from Google Cloud to Microsoft Azure to Oracle, to Meta and many more. Furthermore, it has the support of the ML community including from vLLM, LMCache, SGLang, PyTorch, Huggingface and the support of major labs like OpenAI, MiniMax, ZAI, Qwen, Moonshot Kimi, etc. Star the InferenceX GitHub repository if you find the open-source benchmark and data useful!. InferenceX i

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well-fit for this – Activities, Plasmoids, the existing scripting surface – but a handful of upstream changes (declarative reconciliation, per-widget capabilities, richer Activity metadata) would turn KDE into the first shell that treats AI as infrastructure rather than as a chat box bolted to the side." This is very much not what this vulture wants from a desktop computer. It may win admirers, but seems more likely to polarize the audience. Writer and AI critic David Gerard points out the propo

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ow sizes by model Context windows vary widely across today's major model families, from a few hundred thousand tokens up to 10 million. Here's how current flagship models compare: Meta's open-weight model; the largest publicly available window as of this writing GPT-5.6 Sol 1.05 million tokens OpenAI's current flagship model for coding and agentic reasoning Gemini 3.1 Pro 1 million tokens Google's current Pro-tier model for long-document and multi-file analysis Claude Sonnet 5 1 million tokens A

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s Today’s workflow comes from reader Lisa Fisher: “I used ChatGPT to help me manage my health care. I have multiple diagnoses, including CHF, CKD, pulmonary hypertension, lupus, a metabolic disorder, and kidney cancer. I gave ChatGPT access to my medical history and began using it to review my test results and prioritize questions for my doctors. On a recent lab report, my platelet count was low. ChatGPT reviewed six years of results and showed me that it had consistently been low, with the late

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release claims up to 30% lower costs and 22% higher cache hits . Meanwhile, Perplexity’s Computer , Base44’s phone-calling Superagent , Google Labs’ family-oriented CC agent , and Meta’s desktop Muse for Mac all point in the same direction: persistent agents with scoped permissions, user-specific context, and asynchronous execution as the default UX rather than an add-on. TypeSafe’s Jev dominated discussion as a fast, cheap constrained-output primitive : The clearest pattern in the feed is that

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自己手里；模型买断一次，后面不再按 Token 计费。 “乐高式”生存：住进别人的工具里 大洋彼岸的创业者做了另一种选择：住进企业已有的工具里。他们靠的是一个开放的大厂生态。 硅谷风投机构 UpHonest Capital 投研总监王子长期看 AI 赛道。她发现有一批美国 AI 办公产品的打法，是从用户已经在用的工具里长出来，用户不用再装任何新软件。 由前 Meta 工程师创办的 Viktor，把每一个 agent 称作“小镇成员”，它通过产品集成连接用户的邮件、日历、Slack、WhatsApp、Notion 等工具，既可以在Town 自己的网页和客户端中使用，也可以通过邮件、Slack、WhatsApp 等现有入口与它交互。 Poke 住进了 iMessage 和 Telegram，用户给它发消息，它去处理邮件、改签会议、订机票。这家只有十来个人的公司，在General Catalyst 领投1500万美元种子轮之后，半年里估值涨到3亿美元。不过，Poke 背后的Interaction Company 在今年7月已被 AI 编程公司 Cognition 收购，Poke 短期内仍将继

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had a good first chat with it; it spoke well, but then it revealed all my api keys in another session, and I’ve been getting ‘provider errors’ because it’s overloaded ever since…. Meta One - new subscription from Meta with extra AI features/usage in Muse and paid tools across Instagram, Facebook & WhatsApp. Factory raised $200M at a $5B valuation . To celebrate, I updated my plugin for using Droid in the bb app . If I have to build anything ‘properly’ ie I care that it’s not vibe-slopped, I use

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placement, but that AI could enable mediocre engineers to ship flawed systems at 10x speed without acquiring the expertise needed to evaluate or maintain what agents produce. Hey, Meta. Where’s those Muse Spark weights? (Activity: 503): The image is a meme/non-technical criticism of Meta for not releasing promised Muse Spark open weights after more than a month, despite the poster noting Spark has moved from 1.2 to 1.3 . The post frames the delay against Zuckerberg’s argument that model releases

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and water — to produce what it calls “near-zero emission” steel. The agreement helps address some of the thorny challenges facing green steel companies and data center developers. Metal-makers need wealthy, early customers like Google to help stoke investor interest in their novel manufacturing plants. Meanwhile, tech companies need cleaner construction materials to curb their growing environmental impact. Google recently reported an 18% rise in its annual emissions from 2024 to 2025, owing to i

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