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s talked about beyond just next-generation Telum, is your next-generation Spyre—so not Spyre 2, but next-generation Spyre. You guys have added HBM to that. I know that there was a Meta paper, I believe about two or three years ago, talking about how many errors HBM would sort of not create, but would have. IBM is all about ultra-reliability. How are you guys sort of dealing with that new memory that may have higher errors? Christian Zoellin: I’m actually not familiar with the details of that. Ar

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t: cmax audit security for a free report from us on your cluster or standalone GPU machine. The cmax CLI will auto-detect Slurm clusters, Kubernetes clusters, standalone VMs, bare-metal machines, and containers, and compare them against a set of baseline software versions with known vulnerabilities. For anything out of date, you will be provided a link to the relevant documentation and security bulletin. To be clear, this is a small subset of our ClusterMAX testing, and even a small subset of th

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ry unavoidable cache miss. Why native GGUF cannot directly use expert-level O DIRECT Native GGUF is a tensor-oriented model container, not an expert-oriented direct-I/O store. Its metadata and tensor payloads are organized around individual tensors, and a single expert's gate, up, and down weights may be separated across file regions or across multiple shards. The original loading path commonly uses a parser, mmap, or buffered file reads, so the application sees pageable page-cache-backed mappin

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Create demand for AI compute for its customers NVIDIA has succeeded in doing the first primarily by selling these GPUs to hyperscalers like Amazon, Google, Microsoft, Oracle, and Meta, who make up somewhere between 50% and 60% of its GPU sales depending on which analyst you ask. The rest comes from a mixture of unnamed “sovereign AI customers” and “neoclouds” — companies that exist to raise debt, buy NVIDIA GPUs, and put them in data centers to rent to theoretical AI customers. Per Vivek Arya o

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an 20% and dented the SaaSpocalypse story. Space tech investing is white hot. America’s Generalist and China’s Dogotix raised big rounds as investors swarm to the robotics sector. Meta agreed to pay up to $17.1 billion and make changes to its products to settle a lawsuit from state AGs — and put the screws to its competitors in the process. Y Combinator draws the FTC chair’s ire with a snarky DEI tweet. The Main Item After a remarkable few weeks of blowout earnings, multi-billion-dollar acquisit

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ecords occupation, education, marital status, income band, handset brand, current city and years in the current district. Five clips from the public Indian English split, with the metadata each one carries: 29-year-old woman, West Tripura, Tripura. Student, samsung SM-G781B. 32-year-old woman, Satna, Madhya Pradesh. Unemployed, samsung SM-E146B. 22-year-old man, Rohtas, Bihar. Student, motorola moto g54 5G. 27-year-old woman, Warangal, Telangana. Unemployed, vivo V2247. 57-year-old man, Puducher

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Harness Engineering for Self-Improvement, Lil'Log, July 4, 2026; Boye Niu et al. — Flow: Modularized Agentic Workflow Automation, arXiv:2501.07834, 2025; Andy Xu and Yu-Wing Tai — Meta-Agent: From Task Descriptions to Verified Multi-Agent Systems, arXiv:2605.25233, 2026; Ao Li et al. — GraphFlow: A Graph-Based Workflow Management for Efficient LLM-Agent Serving, arXiv:2605.22566, 2026; Sydney Runkle and Harrison Chase — 3 Years of Graph Engineering with LangGraph, LangChain, July 22, 2026; Nelso

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sly involved seven different vendor programs without a shared interface. A few nights of disrupted sleep are enough to cause widespread impairment: altered cognition, dysregulated metabolism, a weakened immune system. If this goes on long enough, sleep loss can even prove fatal. Yet we still don’t fully understand why. Part of the reason sleep is so hard to study is that it isn’t localized to any one organ. Because sleep is a whole-animal state, developing a mechanistic understanding of it requi

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unny bit about this deal. If you read the fine print in the addendum, Google doesn’t have to buy the shares. The exercise of converting the vested shares happens on Google’s own timetable, and it can wait until August 18, 2033 to do it if it feels like it. The next day, if Google doesn’t exercise its rights, for instance if the shares fall below the floor that was set at $206.58 per share, the shares vanish. Poof! I doubt very much that Google will do that, wanting both influence on the Marvell

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ast Friday’s post . Three new-ish models to look at: GLM-5.3-Flash - The reveal of the Ox Alpha secret. It’s a great open-source alternative for GPT-5.6-Luna. Muse Image is now in Meta’s API. Generate or edit images at $0.01 per image. Gemini 3.5 Transcribe - New model from Google for audio transcription. It’s quite pricey, but makes way fewer errors than other models. OpenAI’s new chip Jalapeño beats Nvidia’s Blackwell chips on both speed and efficiency. Across three open models, its first infe

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not a transcription failure; Chart scores extraction of numerical data series from chart images into structured tables. Our model treats charts as visual elements with descriptive metadata, not as data-extraction targets. This is a product scoping decision — chart data extraction is planned for the next Parser version On the three dimensions that align with our product goals — Tables, Text Content, and Text Formatting — we report full results. These cover the structured transcription and semanti

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allow-listed IPs. The website presents itself as a small archive of notebook records. Those notebook records however are in a ZIP archive. The archive contains plausible catalogue metadata, dates, checksums and seven short records about the development of the theory of language. The wrapper gives Claude a legitimate reason to investigate the material. 1. Move Claude from WebFetch to Bash Claude initially uses the WebFetch tool to retrieve the contents of the page. The WebFetch tool itself appear

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gave us static extraction and strong type safety. But its API felt more fragmented, and the separation between component and style files did not fit how we like to work. StyleX by Meta gave us a better balance. Styles stay colocated with components, the API is small, and style resolution is deterministic. It also gives us type-safe styling contracts and makes it deliberately harder to reach into a component and restyle it from the outside. Those constraints come with tradeoffs. Migrating from th

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he SAGE-10K dataset contains 10,000 generated indoor scenes across 50 room types. It is a scene dataset, not a policy or simulator. Each scene provides geometry, materials, layout metadata, and a preview. Living room and warehouse scenes follow the same preparation path, so select one suitable candidate instead of downloading the entire dataset. The SAGE-10K path includes two human approval gates. First, inspect the converted USD in NVIDIA Isaac Sim and confirm geometry, materials, scale, and co

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model that models slower glucose trends and short-term deviations in separate streams, producing transferable representations and setting new performance standards across diverse metabolic prediction tasks, including diabetes risk assessment, insulin resistance, beta-cell dysfunction, and post-prandial glycemic response. Consumer wearables use motion and physiological sensors to estimate activity and sleep, but these signals provide only an indirect view of glucose regulation. Continuous glucos

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pute a score. Offline evals run a fixed dataset through your system deliberately. A dataset is a reusable collection of cases, each with an input, an optional expected output, and metadata. One run of the system over that dataset is an experiment, and you compare experiments to each other to find out whether a change helped. Our datasets and experiments guide describes the model in more detail. Online evals attach evaluators to real production traffic, usually sampled, and score requests nobody

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retention. Braintrust is closed source, and its self-hosting model is hybrid: the data plane runs in your cloud while the control plane, including the web UI, authentication, and metadata, stays with Braintrust. Pick it when the release gate is an eval suite and Pro is already in the budget. 5. PromptLayer: for non-engineers who own the prompt text The prompt registry is built for people who do not deploy code. Versions carry commit messages, release labels like prod and staging decide what run

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materials after they’re generated. When fine-tuned on stability metrics, their approach produced crystalline materials that achieved 68 percent mechanical stability and 85 percent metastability, which measures if a material stays in a stable state when undisturbed. The researchers then used their approach to generate material candidates with high thermal conductivity and easy polarization in an electric field. “These are materials useful for the semiconductor industry and high thermal conductivi

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ed Prefill in the pooling layer to prevent High Bandwidth Memory (HBM) exhaustion, creating risk of state loss across step boundaries. We engineered a hybrid StepPool and migrated metadata to CachedRequestState, ensuring pooling states correctly accumulate across steps and survive request preemptions. vLLM Embedding Sample on TPU Below is a minimal example demonstrating how to initialize Qwen3-Embedding-8B on TPU. For complete setup scripts and environment deployment steps, refer to the official

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cted original K/V, and dispatches to TRTLLM-Gen on Blackwell or packed FlashAttention otherwise. The indexer can overlap the main Q/K/V projection on a second CUDA stream, and the metadata paths are CUDA-graph compatible. A QSA layer runs an indexer that picks which tokens to attend, then a sparse attention over exactly those tokens. The second stage has a fixed token budget; the first scores its query against all ⌈L/4⌉ compressed blocks, so beyond a few thousand tokens the indexer, not the atte

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