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banning virtual personalities outright. The move follows backlash over an Instagram AI tool that used people’s public photos to generate their likenesses without explicit opt-in; Meta later pulled it. Why it matters: A Wired investigation this year found more than two dozen accounts featuring AI influencers promoting the dating app Goose, and the NYT counted hundreds of AI-generated wellness personalities pushing supplements in July. The disclosure rule follows Meta’s $18B settlement over socia

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t. ( tweet ) Software engineering fundamentals you need to become an AI engineer. £100M of UK government contracts for British AI startups - upfront payments, no turnover minimum. Meta’s coding agent is out of beta and installs with one command . Someone else can test that claim. Not me :) Matt Huang @matthuang GPU World: A story competition from Neal Stephenson, Gwern, and me. The AI future is unevenly distributed. What would the world look like with AI broadly diffused, such as if we had one G

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be featured. 🎇 Fireworks - Train an open model to be better, faster, cheaper on your work 🦀 OpenClaw 2.0 - Open-source personal agent, now with multiplayer sessions ⚙️ Muse Code - Meta’s terminal-based AI coding agent, now out of beta 🏛️ Hermes Agent - Nous' Pantheon update turns its agents into a group chat Sponsored Listing SpaceX’s Starshield AI rolled out Grok for Government on the Pentagon’s internal platform, opening the model for non-classified military use across its 3M employees. OpenAI

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render Every one of the five tools returns a ToolReturn. The model sees return value, the text, with a Sources: block appended when the tool has citations. Your application reads metadata['sources'], the same sources as YouSource records: The model never sees metadata, so nothing here competes for context, and the footnotes in your UI never depend on the model repeating a URL correctly. web search puts the response's search uuid and latency in there too, which is what you want in a trace when a

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AI where their data lives, not the other way around,” he said. “They want to bring data to the model and not model to the data. But building this entire AI infrastructure from the metal to the module is a very manual process, where they have to stand up the infrastructure, put together the server with the right GPU size and form factor, bring the networking, the storage requirements, the Kubernetes for container workloads, the AI software stack, and different kind of models, be it SLMs [small la

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akub Pachocki and Mark Chen, respectively the chief scientist and chief research officer at OpenAI; Dario Amodei, cofounder and CEO of Anthropic; Shengjia Zhao, chief scientist at Meta AI; Shane Legg, cofounder and chief AGI scientist at Google DeepMind; and John Schulman, the chief scientist at Thinking Machines. Looking at the METR report, it seems clear that AI-model capabilities have already advanced beyond our ability to understand and control them. Some of the signatories of “Pacing the Fr

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rk Twilio calls attach the call SID and your custom TwiML parameters as participant attributes; WhatsApp callers join with their phone number as the participant identity, plus any metadata you pass in the request To everything else in LiveKit, a phone call and a WhatsApp call look exactly like a browser user. The participant model also carries into your operations. Connector calls show up in the LiveKit Cloud dashboard alongside your SIP and web sessions, with the same session logs and analytics

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y are compacted and moved to the next level - this allows for an optimization of the combined screening and data writing costs. Each segment also carries a dataset tag and lineage metadata describing where its keys originated. This provenance is not stored as a separate afterthought: it is part of the physical organization of the index. PUFFER operates on this state through four main operations: screen, commit, compact, and withdraw. Figure 1: A schematic of the PUFFER deduplication engine. For

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ffective resolutions up to 1536³, handling complex topologies that earlier methods struggled with. It also shipped with a PBR texturing model generating base color, roughness, and metallic maps. Ten months is an eternity in generative AI, yet Trellis.2 hasn’t just aged well, it has become foundational. Several open-source 3D models released since build directly on it, the most notable being Pixal3D whose implementation uses the Trellis.2 backbone. The community got there first As always, the Com

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out are going to dominate Nvidia’s own sales. This is a customer pull, not a vendor push. Enterprises, for sure, are going to want Ethernet, and so do the AI model builders – even Meta Platforms, which has given InfiniBand its time in the limelight on earlier AI clusters. The old adage in the networking space is that Ethernet always wins. And it does. And that is because it steals every good idea from any fabric that can be broadly applied across enterprise networks as well as nichey stuff in HP

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complex ipde scores , plus per-chain and pairwise arrays and full pae / pde matrices (up to 1360×1360 for the complex). The one requested field the service left empty was runtime metadata ( metrics: {} ). Because the workflow also ran single-sequence (no-MSA) predictions, the value of Stage 1 can be measured directly. For the heteromer, the interface pTM (iPTM), the metric that reports on the predicted contact between the two chains, collapses without an MSA in both models: Figure 2. Heteromer

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inforcement-learning stack that brings programmable biped robotics down from $13K research hardware to less than a phone. Also today: ICE’s multimillion-dollar robot-dog plans and Meta putting robots to work inside its data centers. In today’s robotics rundown: Hugging Face’s cute open-source duck robot ICE is adding robot dogs to its arsenal Meta’s data centers are becoming robot test labs This robot swarm builds from the top down LATEST DEVELOPMENTS Image source: Hugging Face The Rundown: Hugg

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er case, researchers used Julia to create a program for avoiding aircraft collisions. They found it ran about 50 times faster than an earlier version built on Python. Engineers at Meta used Julia to develop a better audio codec for WhatsApp’s 4 billion users. “Over the years we’ve seen industrial, government, and academic users doing all kinds of interesting things with the Julia language,” Edelman says. “It’s honestly surprised us in many ways, the wide-ranging things people are using it for.”

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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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