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urpose GPU cloud, but a platform with the right primitives for developers to build a very wide range of applications. Today, this looks like low-latency elastic inference, dynamic agent runtimes, reinforcement learning, batch jobs at massive scale, and much more. Frontier APIs to model ownership From digital-natives like DoorDash to AI-native companies like Reducto, the teams pulling ahead are taking ownership of their models. They're fine-tuning with their own data, running RL, and tuning infer

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alike. When you just need to build a tiny desktop app: TinyJS October 13, 2026 Valen creator drives 'Golden Spike' to connect new languages with Rust September 26, 2026 Microsoft agentically ports Copilot runtime to Rust for $120K September 19, 2026 Apple iPhone Duo makes developers think in folds September 16, 2026 JavaScript installer pnpm recast in Rust because ECMAScript can't keep up September 5, 2026 Kubernetes cleans house, bins legacy kube-dns, IPVS, and cgroup v1 August 27, 2026 How Cu

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e testing Anthropic took more than two months to alert cops; AI systems are fully capable of carrying out nightmare attacks against infrastructure and nobody's ready Meanwhile, AI agents move robotic arms, 'make OT device operator screens lie'; Nvidia found $1B under the couch to help secure American scientific computing dominance Commitment comes as GPUzilla prepares to fortify Uncle Sam's arsenal with at least seven AI-optimized supers; TSMC taps GlobalFoundries to bolster US silicon interpose

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y are contingent on OpenAI using some of the pledged cash to lease massive quantities of compute either directly from its backers or their partners. MORE CONTEXT ServiceNow clears agents for landing with new AI control tower; Usage-based pricing killing your vibe - here's how to roll your own local AI coding agents; Microsoft lifts 2026 AI spend by $25 billion to cover component price rises; Amazon chips no longer just a side dish, they're a $20B biz Back in February, Amazon, Nvidia, and SoftBan

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March 7. "The 5m TTL is disproportionately punishing for the long-session, high-context use case that defines Claude Code usage," said Swanson. When using AI coding assistants or agents, the context is additional data sent along with the user's prompts, such as existing code or background instructions. Context improves the accuracy of the AI but also requires more processing. Claude prompt caching avoids re-processing previously used prompts including context and background information. The cac

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umber of notification items rendered in a single digest email Additional followup tasks we will prioritize are: Tighten enforcement of pre-deployment security review, by human and agent, for any changes to authorization-related code paths; Improve operational monitoring for anomalous authorization layer behavior and permission boundary violations; Extend internal logging system to provide a higher level of visibility into workspace related events; Allow workspace admins / owners to configure spe

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e user. When you just need to build a tiny desktop app: TinyJS October 13, 2026 Valen creator drives 'Golden Spike' to connect new languages with Rust September 26, 2026 Microsoft agentically ports Copilot runtime to Rust for $120K September 19, 2026 Apple iPhone Duo makes developers think in folds September 16, 2026 JavaScript installer pnpm recast in Rust because ECMAScript can't keep up September 5, 2026 Kubernetes cleans house, bins legacy kube-dns, IPVS, and cgroup v1 August 27, 2026 How Cu

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Cursor cloud agents produced over a million commits over the past two weeks. These commits were essentially all AI. Since they have their own computer, cloud agents run the code themselves and little human intervention is required. Pretty cool!

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ople have used Dreamer to build personal, intelligent software with our Sidekick in the world’s newest and most popular programming language: English! They're building and sharing agents to manage email, calendar, and to-do’s, create learning tools for their kids, learn new languages, plan trips with friends, become better cooks, help them with work, achieve their health goals, or simply to creatively express themselves—all sorts of surprising and uniquely personal needs. These are agents as uni

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hree seconds, those amalgamations of systems become bottlenecks," Cooper told VentureBeat. "What was really cool for humans to deploy in 10 seconds or less is now table stakes for agents." The company claims its platform delivers deployments in under one second — fast enough to keep pace with AI-generated code. Customers report a tenfold increase in developer velocity and up to 65 percent cost savings compared to traditional cloud providers. These numbers come directly from enterprise clients, n

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inforcement learning training to unprecedented levels, refining Grok’s intelligence, reasoning, and agency using pretraining-scale compute. Grok Voice : the most intelligent voice agent driving real-time conversations in voice mode and available via agent API. Grok Voice delivers low-latency speech in dozens of languages, tool calling, and real-time data access, serving millions of users across the Grok mobile app and in Tesla vehicles. User metrics : our reach spans approximately 600 million mo

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Announcements One year after our first commit, we reflect on how far browser agents have come—and where they need to go next. When we started, GPT-4o was state of the art for browser agents. Since then, we improved our library a ton and released BU 1.0. Below is a comparison of GPT-4o and BU 1.0 with latest version of our library. We track three core metrics for our browser agents: accuracy, speed, and cost. In one year, the accuracy improved from 71.8% to 82.0%. But more importantly, we reduced

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& evals. We’re excited to scale the scope, complexity and usefulness of environments on the hub to enable the open-source ecosystem to train increasingly competitive and useful models. We’ve already been training and evaluating INTELLECT-3 on environments & evals contributed by the community over the last months to scale RL post-training by orders of magnitude of our previous efforts. Let's open-source the tools to build superintelligence. Rewriting Prime Agent in Rust On the Nature of the Swarm

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es, and nonprofits to use GenAI solutions. We are a full-stack Generative AI platform built with sovereign models that deeply understand India's culture and diversity, enabling AI agents and applications tailored for the nation. Today, Sarvam is trusted by leading enterprises and institutions including UIDAI, Neowise, Urban Company, the Ministry of Skill Development and Entrepreneurship, and NITI Aayog. Sarvam is backed by top investors including Lightspeed, Peak XV, and Khosla Ventures. Curious

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the world, but interacting with it still requires human effort—clicking buttons, filling out forms, and navigating through websites manually. With the rise of LLMs and autonomous agents, this is changing. We are building the infrastructure that enables AI to interact with the web as seamlessly as humans do. Most existing automation solutions rely on vision-based approaches, attempting to “see” the web like a human. These methods are slow, expensive, and unreliable. Our approach is different: we

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Prime Intellect is building the compute and infrastructure platform to train, evaluate, and deploy agentic models — making it possible for anyone to build frontier AI. We're creating the full stack for open superintelligence: from GPU access to RL training to open research. Today, we're announcing that we've raised $15M in funding, led by Founders Fund, with participation from Menlo Ventures, Andrej Karpathy (EurekaAI, Tesla, OpenAI), Clem Delangue (Hugging Face), Dylan Patel (SemiAnalysis), Tri

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brought it on-device. Sonic is in production with thousands of customers ranging from individual creators and startups to large enterprises, powering the next generation of voice agents, digital media, and assistants. Building long context generative models for rich multimodal signals like audio and video remains challenging – models are hard to control and quickly go off track. Over the past few months, we’ve created a new SSM architecture for multi-stream models that continuously reason and g

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primarily on assessing the potential for their misuse. METR will use these new resources to develop and deploy methods to assess frontier AI systems’ ability to act as autonomous agents, and to support companies, governments, and other research partners in running these tests. This will help decision-makers understand and mitigate risks from each specific frontier AI system. ABOUT THE AUDACIOUS PROJECT Launched in April 2018, The Audacious Project is a collaborative funding initiative that’s ca

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