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All news · Today68 items

All AI news

All collected and published items, ordered by time. Picks are a selected subset.
9/21Mon
  2. Qwen · X58

    Qwen-Image-2.1 gets day-one support in SGLang-Diffusion

    Qwen says SGLang-Diffusion now supports Qwen-Image-2.1 for text-to-image generation, multi-image editing, and transparent RGBA output. SGLang says native-precision inference with CPU offload runs on a single 24 GB RTX 4090, taking 18.7 seconds for 1024×1024 generation and 21.7 seconds for image editing, with peak request-time memory of 22.7 GiB. On an RTX PRO 6000 96 GB, generation and editing take 8.0 and 9.6 seconds. Inference supports TP/SP, LoRA, and an OpenAI-compatible API, with 40 denoising steps, one image per request, and no quantization.

  5. Hugging Face Blog48

    Hugging Face releases tokenizers v1: benchmarks show major encoding and decoding speedups

    Hugging Face has released tokenizers v1, producing exactly the same token IDs as v0.23 while running up to dozens of times faster. The project splits a single crate into a workspace and introduces bitcannon, which replaces regex tokenization with SIMD bit operations, along with an allocation-free merge loop, thread-local word cache, and native multithreaded parallelism.

  6. Simon Willison40

    Engineer claims everyone from L1 to L7 at a big company uses Claude Code to write software

    A newly hired engineer at a large company says Claude Code generates everything on the team—specs, code, tests, PRDs, tickets and their handling, and reports. Engineers from L1 to L7 are all doing the same thing: chatting with Claude. No one reads the output, no one on the team likes this workflow, but they are told to produce as much as possible. Senior leaders repeatedly say pushing code is not the bottleneck and ask why progress is still slow; employees work 12 to 13 hours a day just to press Enter.

9/20Sun
9/19Sat
9/18Fri
  2. GitHub Blog · AI & ML22

    GitHub Podcast unpacks AI hot takes: should you read code, is RAG dead, and did Skills kill MCP?

    The latest GitHub Podcast examines five popular AI claims. AI-generated code still needs to be read and owned, with review effort scaled to risk; Skills and MCP address different needs, with Skills packaging team expertise and MCP standardizing connections to tools and data; and RAG is not dead, since it can coexist with agents, Skills, and MCP in one workflow. The episode also discusses judging AI fluency in hiring and how fine-tuning needs can signal codebase maintainability problems.

  6. AI at Meta · X58

    Meta's Muse agent comes to Mac

    Meta says its personal agent Muse is now available on Mac. With the user's explicit authorization, it can perform tasks directly on the computer, such as organizing the Downloads folder, finding missing files, and summarizing messages and notes. More capabilities are planned. Download: http://ai.meta.com/muse/download/.

  8. Google Research60

    Google Research uses generative UI to help teachers create interactive learning simulations

    Google Research has published a research experiment in which teachers use generative UI (GenUI) to dynamically create interactive, level-based learning simulations for STEM classes, complete with scaffolding such as hints, feedback, and solution steps.

    Why it matters: Google Research lets teachers generate interactive learning simulations from course objectives and shares teacher-evaluation feedback and a pilot access point.

  10. Mike Krieger · X32

    I had trouble picturing the whole Iron Tangle level from Dungeon Crawler Carl, so I made an interactive artifact and I think I finally understand it: https://claude.ai/artifact/NTcG664cCbibbZNUFnCSu9?sk=HtqECKbpVqi8-DDzHAkh-Q

    I had trouble picturing the whole Iron Tangle level from Dungeon Crawler Carl, so I made an interactive artifact and I think I finally understand it: https://claude.ai/artifact/NTcG664cCbibbZNUFnCSu9?sk=HtqECKbpVqi8-DDzHAkh-Q

9/17Thu
  6. GitHub Blog · AI & ML78

    GitHub uses Copilot to rewrite the Copilot runtime in Rust

    Using the GitHub Copilot app and Copilot CLI, GitHub completely rewrote the Copilot agent runtime from TypeScript into more than 800,000 lines of production Rust. AI agents wrote most of the code, merged incrementally into main across 128 pull requests rather than in a single cutover.

    Why it matters: Drawing on firsthand experience, the author reviews the 800,000-line Rust rewrite and shares agent-orchestration and review practices that can be reused.

  9. Gemini App · X42

    Go from inspiration to physical objects with Gemini. With Canvas in Gemini, you can code a custom app to design a vase and change its mathematical parameters to visualize it in 3D. Then, export it as an .STL file for 3D printing to watch your ideas take shape.

    Go from inspiration to physical objects with Gemini. With Canvas in Gemini, you can code a custom app to design a vase and change its mathematical parameters to visualize it in 3D. Then, export it as an .STL file for 3D printing to watch your ideas take shape.

  10. OpenAI News60

    OpenAI publishes model-misalignment reporting framework with six incident reports

    OpenAI has published a framework for tracking, investigating, and disclosing model misalignment, along with six reports about unexpected or concerning model behavior.

    Why it matters: OpenAI has made public a framework for tracking and disclosing model misalignment, together with six incident reports that show how it approaches alignment disclosures.

9/16Wed
  1. NVIDIA Blog62

    NVIDIA Vera Rubin NVL72 makes its MLPerf Inference v6.1 debut with leading performance

    NVIDIA submitted preview results for Vera Rubin NVL72 for the first time in MLPerf Inference v6.1, reporting up to 3.7× the throughput of GB300 NVL72 on Qwen3-VL and up to 2.5× on DeepSeek-R1.

    Why it matters: MLPerf Inference v6.1 reports throughput, scaling efficiency, and software-optimization gains for Vera Rubin NVL72 versus GB300 NVL72, offering a basis for judging inference infrastructure value.

  2. Demis Hassabis · X38

    DeepMind launches institute to study AGI's impact

    For more than 20 years, @ShaneLegg and I have discussed AGI's potential impact on the economy, science, and society. Through the DeepMind Institute, we're expanding interdisciplinary research into the key questions of the AI era. We hope it will help drive the discussion we need to get the next steps right: http://deepmind.google/institute

  3. Demis Hassabis · X12

    Demis Hassabis receives the RSA Albert Medal

    Honored to receive the Albert Medal from @theRSAorg! Science and technology offer incredible opportunities, but as we approach the AGI era, the arts and humanities are essential to shaping the future we want as a society. I had a fascinating discussion with @FryRsquared, covering many new topics: https://www.youtube.com/watch?v=rDteJAuKiBI

  4. NVIDIA Blog42

    Emerald AI, Google, and NVIDIA launch AI Energy Management Alliance

    Emerald AI, Google, and NVIDIA have announced the AI Energy Management Alliance (AEMA), which aims to help data centers adjust power use dynamically to grid conditions. The alliance uses technology-neutral, performance-based requirements focused on measurable factors such as response speed, duration, predictability, and emergency behavior. It also sets out pre-interconnection load-reduction and emergency-response obligations, common technical standards and data sharing, faster paths to grid connection, and cost allocation based on actual system impact.

  7. Mistral AI60

    Mistral partners with Mozilla to power Firefox Smart Window

    Mistral has announced a partnership with Mozilla: the beta AI browsing assistant Firefox Smart Window is now powered by Mistral models. It helps users understand complex searches, find pages they previously visited, and organize information from browser tabs.

    Why it matters: Mistral and Mozilla are bringing open models into a browser entry point, offering a view of how open models may reach consumer users.