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Today 8 items
Sep 27Sun
  1. Simon Willison55

    Kākāpō Party

    Closing his talk at WeAreDevelopers World Congress North America, Simon Willison used three kakapo photos and a single prompt to have Claude Opus 5.5 generate Kākāpō Party, an HTML5 canvas pixel-art animation featuring at least 20 kakapos hopping to music with confetti and balloon effects, which he then recorded to video with Claude Code.

Sep 26Sat
  1. Latent Space65

    OpenRouter: from Seed to Stripe — with OpenRouter’s Alex Atallah & AMP’s Anjney Midha

    The Latent Space podcast spoke with OpenRouter co-founder and CEO Alex Atallah and AMP's Anjney Midha, tracing how OpenRouter grew from the early wave of open-weight models like Llama and Alpaca into a neutral routing layer serving over 10 million developers and handling over 100 trillion tokens per day, and why it was acquired by Stripe.

  2. Ars Technica · AI82

    Court rules Pentagon can blacklist Anthropic for refusing to enable Claude features

    The US Court of Appeals for the DC Circuit ruled 2-1 to approve the Department of Defense's blacklisting of Anthropic technology, finding the government may restrict the company even absent malice for refusing to open some Claude features to the military. The opinion weighed the risk that restricted models could disrupt military operations against the risk that unrestricted models could hallucinate wrong strike targets, held the defense secretary did not overstep, and rejected Anthropic's request for a rehearing. The court had previously denied its emergency stay request in April.

    Why it matters: The report gives the core reasoning of the ruling and the 2-1 vote, helping readers understand the boundaries of military supply-chain controls on AI companies.

  3. GitHub Blog · AI & ML64

    GitHub Copilot app for Beginners: How to build custom workflows with canvases

    An official GitHub tutorial shows how to build custom workflows with canvases in the GitHub Copilot app: run the /create-canvas skill in an agent session, describe the workflow, user actions, and agent actions in natural language, and the agent generates boards, checklists, dashboards, and other interfaces that open in the side panel.

    Why it matters: The tutorial covers the three elements of /create-canvas and its two-way collaboration mechanism, so readers can turn their own workflows into reusable canvases.

  4. Simon Willison55

    Quoting John Gruber

    Simon Willison quoted John Gruber's article 'Muse Looks Cute, but Looks are Deceiving': Meta's Muse gives every user a full persistent Linux VM running on Meta's cloud, packaged as a cute mascot and easy to install and use, and is being called the first consumer-accessible agentic AI system.

  5. AWS Machine Learning Blog31

    Scaling MoE reinforcement learning on Amazon EKS with EFA and DeepEP with 40% more throughput

    AWS proposed an architecture based on Amazon EKS, EFA and DeepEP to accelerate large-scale reinforcement learning post-training of MoE models, delivering 40% higher throughput. The solution targets workloads like RLHF, PPO and GRPO, addressing resource balancing between rollout generation and policy training, high-throughput communication across hundreds of accelerators, and the dynamic all-to-all token routing overhead introduced by Expert Parallelism.

Sep 25Fri
  1. MIT Technology Review · AI59

    The Pentagon wants $30 million to build an AI-powered lie detector

    A US Department of Defense budget request proposes spending $30.3 million over five years on an AI polygraph project called Polygraph+ or Polygraph Next, led by the Defense Counterintelligence and Security Agency (DCSA). It focuses on AI and machine learning-based scoring algorithms plus contactless "remote sensing" technology, for employee vetting and insider threat detection.

  2. Latent Space36

    [AINews] The Future of Latent Space

    Latent Space's swyx announced a revamp of AINews, which has run for 3 years and has over 200,000 subscribers, planning to merge AINews v3 with the tens-of-thousands-member Latent Space Discord, migrate the site to Beehiiv and launch a new homepage.

  3. Simon Willison26

    Note on 24th September 2026

    Simon Willison argues that the more he works with coding agents, the more convinced he is that they make software engineering harder. He says these agents can produce stunning results, but unlocking their full potential requires extreme discipline and knowledge.

  4. GitHub Blog · AI & ML55

    When chat is the wrong UI

    GitHub Copilot authors argue that chat is not the best interface for collaborating with AI, introducing the canvas feature in the GitHub Copilot app—a small full-stack app that communicates bidirectionally with agents, can call third-party APIs, and runs code locally.

  5. Google Research54

    Automating coherent long-form video generation

    Google Research unveiled its AI video co-director research, building a multi-agent orchestration layer based on Gemini and Veo with four frameworks — Co-Director, CANVAS, A²RD and VQQA — that reformulates long-form video generation as a global optimization and world-state tracking problem.

  6. GitHub Blog · AI & ML68

    AI-powered fuzzing with the GitHub Security Lab Taskflow Agent

    Antonio Morales of GitHub Security Lab has released Fuzzing Taskflow, an autonomous fuzzing pipeline for C/C++ projects built on the Taskflow Agent — you only specify a GitHub repository, and it automatically identifies entry points, analyzes the build system, writes harnesses, runs AFL++, and triages crashes.

    Why it matters: The author explains the design of the automated fuzzing pipeline, showing how LLM agents can take over manual steps like coverage analysis and crash triage.

Sep 24Thu
  1. Hugging Face Blog60

    Accelerating vision-language models with LFM2.5-VL-DSpark

    Liquid AI has released experimental DSpark draft models for the vision-language model LFM2.5-VL-3B, using speculative decoding to trade for faster inference without changing output quality — decoding speeds up to 3.13x on-device and 2.66x on H100, with end-to-end gains up to 2.62x and 2.27x respectively.

    Why it matters: The article details a speculative decoding acceleration scheme for vision-language models with concrete speedups and memory overhead, plus integration guidance for llama.cpp, MLX-VLM, and SGLang.

  2. TrendForce Insights Semiconductor Industry Insights43

    Why CSPs Are Turning to QLC SSDs for KV Cache Storage

    TrendForce has observed that some cloud service providers are adding QLC SSDs to SSD PODs, replacing the default TLC SSD plus HDD configuration. In AI inference, the Prefill and Decode stages repeatedly read and write KV Cache, and as context windows and batch sizes grow, KV Cache capacity needs multiply, prompting vendors to move caching from costly, capacity-limited HBM down to cheaper tiers.

  3. GitHub Blog · AI & ML60

    Rendering huge pull requests in the GitHub Copilot app

    The GitHub Copilot app team rebuilt the pull request view so it can smoothly open an open-source PR with 2,200 files, over one million changed lines, and more than 400 inline comments.

    Why it matters: The author offers a first-hand breakdown of the dual-geometry architecture and automated measurement methods for rendering huge PRs, useful for anyone building interfaces with large-scale dynamic content.

  4. Simon Willison22

    Shadow roots, explained with live examples

    Interactive examples demonstrate shadow DOM's style encapsulation, inheritance, slots, parts, and JavaScript access, showing how shadow roots create isolated DOM trees with private stylesheets that interact with the page DOM in controlled ways. The explainer page was generated by Fable 5.1 Medium from a prompt.

Sep 23Wed
  1. Google DeepMind64

    Gemini 3.8 text-to-speech says hello

    On September 23, Google DeepMind released two text-to-speech models, Gemini 3.8 Flash TTS and Gemini 3.8 Flash-Lite TTS, which support customizing character voices via natural-language prompts in over 100 languages, cloning voices from 30-second audio samples, directing delivery and dialect changes line by line, and natively generating two-speaker scenarios.

    Why it matters: The official announcement details both TTS models' capabilities, benchmark results, and availability, so readers can judge how voice creation workflows will change.

  2. NVIDIA Blog19

    Sakeena Fiza Helps NVIDIA Hardware Succeed at Scale

    NVIDIA validation engineer Sakeena Fiza tests data center hardware before mass production; her team witnessed the first system-level power-on of the Rubin GPU. Validation spans the entire chain from tray to rack to AI factory—a single board contains tens of thousands of components and a rack can approach 500,000—with the goal of catching issues before customers do.