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15 stories

Mozilla.aiToolsOtari by Mozilla AI: your operating system for AI governance As AI takes on more work, organisations need clear limits on models, tools and spend. Otari, Mozilla AI’s open-source gateway, brings model choice, agent governance and cost control together, so…

Mozilla.aiToolsWho searches the web for your agent? Your agents search the web dozens of times a day, but do you know which search engine receives those queries? Most providers don't say.

Mozilla.aiToolsBuilding the Missing Half Open models are ready for agents, but the infrastructure around them isn't. Otari is a gateway that restores what hosted APIs quietly handle, like web search and code execution, so you keep control…

Mozilla.aiToolsMistral Large 4 is live in Otari Mistral Large 4 is live in Otari from day one. Route to Mistral's 1T-parameter MoE model with one string change, and keep the policies, traces and cost tracking you already run in Otari, Mozilla AI's…

Mozilla.aiToolsYou Don’t Just Need Better AI. You Need Better Infrastructure. Coding agents now edit repos, run tests, and open pull requests, but a rule in AGENTS.md is an instruction, not a constraint.

Mozilla.aiToolsBenchmarking Local LLM Servers: llama.cpp, llamafile, LM Studio, and Ollama Benchmarking Local LLM Servers evaluates llama.cpp, llamafile, LM Studio, and Ollama across Mac, Linux, and Steam Deck.

Mozilla.aiToolsIntroducing Agent Skills in Octonous Agent Skills in Octonous offer a central, reusable library for your context, guidelines, and procedures. Written in standard Markdown, Skills end repetitive setup.

Mozilla.aiToolsOpen Source Is Not a Virtue: It’s an Ownership Model Open source isn't a moral choice; it’s an operational strategy to prevent vendor lock-in. As transient AI models change, controlling the orchestration layer that routes and manages them becomes…

Mozilla.aiToolsUsing Octonous as a Product Operations Manager Discover how a Product Operations Manager uses Octonous to streamline daily workflows, from turning GitHub releases into newsletters to capturing competitor intel from Slack.

Mozilla.aiToolsllamafile v0.10.5 llamafile v0.10.5 is out! Updated llama.cpp core support lets you run two huge models locally: the compressed 6GB Ternary Bonsai 27B and the fast 118B Laguna-S-2.1 coding MoE.

Mozilla.aiToolsThe Future of AI is Personal — But Not The Way You Think AI’s future isn’t about replacing human thinking, but enhancing it. As AI agents evolve from simple assistants into deeply connected systems, control, privacy, and personalisation will shape the next…

Mozilla.aiToolsHow Frontier Labs Are Building Subtle Developer Lock-In Frontier AI models are becoming more capable, but also more tightly coupled to proprietary state, memory and execution environments.

Mozilla.aiToolsWho Cares About LLM costs? Why would you worry about them? LLMs promise something close to infinite capability, and worrying about the meter feels like someone else's problem. Ship the feature.

Mozilla.aiToolsStop Chasing New Models. Build Once and Access Them All. Swapping LLMs sounds simple, but managing separate SDKs, credentials, and billing turns model evaluation into an infrastructure headache.

Mozilla.aiToolsFrom Evaluation to Guardrails: What We Brought to ACM FAccT 2026 At ACM FAccT, we demonstrated why AI guardrails need the same scrutiny as models. Moving from static policies to context- and language-specific evaluations, our hands-on session proved that agentic…

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予定 · Conferences and launch events, this week's stories from each corner of the industry, and what its press is covering — in English

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About

The name is the button.

An agent writes the code now, and a human thumb hovers over Accept all a hundred times a day. The honest question of this decade is what, exactly, you just accepted. So I read the diff.

Eight years as a backend engineer in Stockholm, back in Tokyo since 2023, and I still ship something small most nights, usually badly. My one rule: the only real review of a model is the thing you built with it. That is why there is no leaderboard on this site.

Around two hundred sources come through — the labs' own posts, the papers, the tools, the runtimes and languages nobody is watching yet, the chip under the demo, and the newsletters people actually forward. What is moving gets counted so the week reads at a glance, and every few days I explain one mechanism in plain words.

A story here is a headline, a short excerpt, one image and the link to whoever wrote it. We never reproduce the post; the images belong to their authors. A post written in Japanese appears in Japanese, exactly as it was published, and the link goes to the original.

— Yuki Halvorsen, Tokyo