NVIDIA Cosmos 3: An Open Omni-model for Physical AI Reasoning and Action
Hugging Face Blog1d agoReleaseHugging Face Blog announces NVIDIA Cosmos 3, described as the first open omni-model for Physical AI reasoning and action. The title indicates a focus on AI systems that interact with physical-world scenarios rather than only text generation. Because the article body was not provided, its architecture, supported modalities, license, downloadable assets, benchmarks, and deployment requirements cannot be verified from the available material.
I Am Retiring from Tech to Live Offline
Simon Willison's Weblog3d agoEthicsSimon Willison highlights Chad Whitacre’s decision to leave tech and Open Source, framed not as a forum threat but as concrete action. Whitacre describes wanting to become “AI Amish” or “Internet Amish,” moving toward an offline, analog life closer to 1980 than 1780. A previous post about using Claude Code with Opus 4.5 shows how agentic AI felt intoxicating and unsettling enough to push him away from technological accelerationism.
As browser wars heat up, top Chrome and Safari alternatives in 2026
TechCrunch AI3d agoCommentaryTechCrunch frames 2026’s browser competition around alternatives to Chrome and Safari. The roundup covers AI-centric browsers like Perplexity Comet, Dia, Opera Neon, OpenAI Atlas, and Aside, alongside privacy-focused options such as Brave, DuckDuckGo, Ladybird, and Vivaldi. It also highlights niche products including Opera Air, SigmaOS, and Zen Browser, showing how browsers are becoming AI assistants, productivity hubs, privacy layers, and wellness-oriented tools.
Has the hunt for AI compute uncovered the next Cerebras?
TechCrunch AI5d agoHardwareTechCrunch reports that General Compute has raised a $15 million seed round at a $60 million post-money valuation to build an AI inference neocloud. The company is ordering $300 million of SambaNova SN50 chips, betting they can outperform GPUs and rival specialized chips for inference. The story frames inference speed, deployment flexibility, and lower power needs as key battlegrounds in AI infrastructure.
ESMFold2: The Bitter Lesson Is Coming for Proteins★ 74
Latent Space6d agoCommentaryLatent Space interviews Biohub’s Alex Rives about ESMFold2 and the broader ESM protein modeling stack. The discussion centers on datasets versus inductive bias, and whether protein biology is entering its own Bitter Lesson era. The key implication is that large-scale evolutionary sequence data and open models may become foundations for structure prediction, interaction modeling, and programmable biology.
New AI Infra Decacorns: Fireworks, Baseten, and OpenRouter★ 78
Latent Space6d agoBusinessAI infrastructure startups Fireworks and Baseten have reportedly reached massive valuations, reflecting intense investor interest in developer-focused inference and deployment platforms. OpenRouter, the popular LLM API aggregator, is also on a rapid growth trajectory. This funding wave highlights a major capital shift toward cost-effective, developer-friendly API and hosting solutions.
Reachy Mini goes fully local
Hugging Face Blog6d agoHardwareHugging Face published a tutorial for running Reachy Mini conversations without cloud audio processing or API keys. The setup uses its speech-to-speech library as a cascaded VAD, STT, LLM, and TTS pipeline exposed through a Realtime API-compatible WebSocket. Recommended defaults include llama.cpp with Gemma 4, Silero VAD, Parakeet-TDT, and Qwen3-TTS, while allowing swaps to vLLM, MLX, Transformers, or hosted Responses API providers.
Shipping a Trillion Parameters With a Hub Bucket: Delta Weight Sync in TRL
Hugging Face Blog6d agoTutorialBased on the title, this Hugging Face Blog post focuses on Delta Weight Sync in TRL. It likely discusses moving or synchronizing weight differences at very large model scale using a Hub bucket-related workflow. Without the full article, implementation details, benchmarks, APIs, and stability claims cannot be confirmed.
Millions of AI agents imperiled by critical vulnerability in open source package★ 78
Ars Technica AI7d agoIncidentArs Technica reports that Starlette, a Python package with about 325 million weekly downloads, has a critical vulnerability called BadHost. The flaw can let crafted Host headers confuse request.url.path, potentially bypassing middleware-based path authorization. AI infrastructure using FastAPI or Starlette, including vLLM, LiteLLM, MCP servers, LLM proxies, and agent frameworks, should upgrade Starlette and audit custom middleware.
3D-printable humanoid legs let robotics experiments run wild
Ars Technica AI7d agoHardwareArs Technica reports that Hugging Face has introduced a roughly $2,500 bipedal humanoid robot project built around 3D-printable legs. The effort targets builders and researchers rather than mainstream consumers, lowering the hardware barrier for hands-on robotics experiments. Its broader significance is in open, reproducible embodied AI research, where models and control systems need physical platforms for testing.
Some ideas for what comes next, May 2026
Interconnects (Nathan L.)7d agoCommentaryNathan Lambert argues that 2026 AI progress is becoming higher-stakes, with model capabilities, work patterns, economics, and real-world risks all escalating. He says open models still lack a true Claude Code and Opus 4.5-style agent moment, and Gemini has no clear competitor to Claude Code or Codex yet. The essay also tracks Mythos, American open-model momentum, frontier-lab competition, and mounting intervention from governments and other power structures.
Specialization Beats Scale: A Strategic Variable Most AI Procurement Decisions Overlook★ 75
Hugging Face Blog11d agoOpinion許多企業在採購 AI 時，往往盲目追求參數規模最大、最通用的前沿模型，卻忽略了「專業化」的威力。本文指出，透過針對特定領域或任務進行微調的專用模型，不僅在特定工作流中的表現能媲美甚至超越通用巨型模型，還能大幅降低推理成本與延遲。企業在做 AI 決策時，應將「任務專業化」視為核心評估變數，而非單純比較模型規模。
Giving Agents Computers — Ivan Burazin, Daytona★ 75
Latent Space11d agoNew ToolDaytona 執行長 Ivan Burazin 分享該平台如何透過提供安全隔離的「開發環境沙盒」，解決 AI Agent 執行程式碼的安全與效能痛點。 公司目前取得驚人的 74% 月增長率，每日執行次數達 85 萬次，並推出專為 Agent 設計的全新「Agent Cloud」。 訪談深入探討了裸機沙盒（Bare Metal Sandboxes）的技術優勢、強化學習評估（RL Evals）以及 AI 時代下開發環境的演進。
Datasette Agent: An Extensible AI Assistant for Datasette★ 70
Simon Willison's Weblog12d agoNew ToolSimon Willison announced the first release of Datasette Agent, merging his 'llm' Python library with Datasette. The tool provides a conversational interface to query SQLite databases, with plugin support for generating charts and running code in sandboxes. It runs efficiently on lightweight models like Gemini 3.1 Flash-Lite and supports local open-weight models via LM Studio.
datasette-agent 0.1a3
Simon Willison's Weblog12d agoReleaseSimon Willison 開源的 Datasette 智慧助理 datasette-agent 發布 0.1a3 版本。本次更新為可見表格與摺疊的 SQL 結果工具調用新增了「檢視 SQL 查詢」按鈕，並隱藏了空白的推理區塊。此外，還改善了截斷回應的處理機制，即使 SQL 結果在呈現給 Agent 時被截斷，使用者仍能看到完整的表格。
Qwen 3.7 Max now available on Vercel AI Gateway
Vercel Changelog12d agoReleaseVercel 宣布其 AI Gateway 已正式整合 Qwen 3.7 Max 模型。開發者現在可以透過統一的 API 介面，輕鬆將這款強大的大語言模型整合至 Next.js 等 Web 應用中。藉由 Vercel AI Gateway 的功能，開發者能享有自動重試、請求快取、速率限制以及詳細的用量監控，大幅提升 Qwen 3.7 Max 應用的可靠性與效能。
datasette-agent-charts 0.1a1
Simon Willison's Weblog13d agoReleaseSimon Willison 發布了 datasette-agent-charts 0.1a1 測試版。此更新為長條圖與鬆餅圖引入了更豐富的漸層與分類色彩方案，並新增了互動式工具提示。此外，系統現在會在查詢欄位名稱前先檢查 execute-sql 權限，並修正了 waffleY 圖表未正確描述給 AI 代理的 Bug。
datasette-llm-accountant 0.1a4
Simon Willison's Weblog13d agoReleaseDatasette 的 LLM 記帳插件 `datasette-llm-accountant` 發布了 0.1a4 測試版本。本次更新主要修正了一個在追蹤 LLM 連續回應鏈（chains of responses）時發生的 Bug，該問題與 `datasette-llm` 的 issue #7 相關。此插件旨在協助開發者記錄與管理 LLM 的使用量與成本。
OlmoEarth v1.1: A more efficient family of Earth observation models★ 70
Hugging Face Blog14d agoRelease艾倫人工智慧研究所（AI2）推出 OlmoEarth v1.1，這是一系列專為地球觀測與衛星影像分析設計的全新高效模型。此版本在維持高精度的同時，顯著提升了運算效率與推理速度。OlmoEarth v1.1 的開源將有助於環境監測、氣候變遷研究及地理空間數據分析的普及與應用。
Introducing the Ettin Reranker Family★ 80
Hugging Face Blog14d agoReleaseHugging Face 推出全新「Ettin Reranker」重排模型家族，旨在解決 RAG 系統中檢索精度不足的痛點。該系列模型涵蓋多種參數大小，支援多語言與長文本處理，並與 Hugging Face 生態系深度整合。Ettin 透過創新的架構設計，在保持低延遲的同時，顯著提升了重排（Reranking）階段的 NDCG 指標，是開發者構建高效能 RAG 應用的全新開源選擇。
The Open Agent Leaderboard★ 80
Hugging Face Blog15d agoReleaseHugging Face 與 IBM Research 合作發表「Open Agent Leaderboard」，這是一個專為 AI 智能體（Agent）設計的全新開源排行榜。傳統的 LLM 評測難以衡量模型在實際任務中的多步驟規劃與工具調用能力，該排行榜整合了多個主流 Agent 評測集，提供客觀、標準化的評估標準，推動開源 Agent 生態系的發展。
Import AI 457: AI stuxnet; cursed Muon optimizer; and positive alignment ★ 78
Import AI (Jack Clark)15d agoCommentary本期 Import AI 深入探討三個前沿議題：首先是「AI 版 Stuxnet」，分析自主 AI 代理如何被用於發動高精準度、具備適應性的網路攻擊；其次剖析近期在開源社群大放異彩的 Muon 優化器，探討其獨特的正交化機制及在實際應用中遇到的「詛咒」與挑戰；最後介紹「積極對齊（Positive Alignment）」概念，呼籲安全研究應從單純的「禁止有害行為」轉向「主動引導 AI 促進人類合作與福祉」。
GDS weighs in on the NHS's decision to retreat from Open Source
Simon Willison's Weblog16d agoCommentary英國國民保健署（NHS）因「Project Glasswing」回報的 AI 安全漏洞，決定關閉其開源程式庫。對此，英國政府數位服務局（GDS）罕見公開介入，發布指引強調公共部門應「預設保持開源」，指出將程式碼私有化會增加成本並減少外部監督。專家指出，這代表英國政府內部對於開源與安全政策產生了嚴重的公開分歧。
Latest open artifacts (#21): Open model bonanza! Gemma 4, DeepSeek V4, Kimi K2.6, MiMo 2.5, GLM-5.1 & others. On CAISI's V4 assessment.★ 85
Interconnects (Nathan L.)17d agoCommentary本期《Open Artifacts》電子報彙整了近期極為熱鬧的開放模型生態。多款重量級旗艦模型接連登場，包含 Google 的 Gemma 4、DeepSeek V4、Kimi K2.6、MiMo 2.5 以及 GLM-5.1 等。文章除了盤點這些模型的發布外，也深入探討了 CAISI 針對最新模型所進行的 V4 安全與能力評估，呈現開源與開放權重模型在技術與安全合規上的最新進展。
datasette-agent 0.1a2
Simon Willison's Weblog18d agoReleaseSimon Willison 開源的 Datasette AI 代理插件 datasette-agent 發布 0.1a2 版本。此版本重點在於安全與權限控制，允許將代理工具的可用性與特定的 required_permission 綁定。預設的背景代理工具現在必須具備全新的 datasette-agent-background 權限才能執行，防止未授權的背景任務運行。
Unlocking asynchronicity in continuous batching★ 75
Hugging Face Blog19d agoRelease本文介紹了 Hugging Face 在 LLM 推論優化上的最新技術：在連續批次處理（Continuous Batching）中解鎖非同步（Asynchronicity）機制。傳統的連續批次處理在排程、GPU 執行與 Token 處理間存在同步瓶頸。透過將這些步驟非同步化，能有效重疊 CPU 與 GPU 的工作負載，進而大幅提升推論吞吐量並優化首字輸出時間（TTFT）。
[AINews] The End of Finetuning★ 75
Latent Space20d agoOpinion在一個相對平靜的新聞日，Latent Space 帶領讀者反思「微調（Fine-tuning）的終結」這一命題。 隨著長上下文視窗、高效 RAG 以及上下文內學習（In-context Learning）的成熟，許多原本需要微調的場景已被取代。 未來微調可能退化為僅用於調整輸出格式、風格或進行模型蒸餾的工具，而非首選的知識注入手段。
How open model ecosystems compound★ 75
Interconnects (Nathan L.)21d agoOpinion本文探討開源 AI 模型生態系的「複利效應」，特別聚焦於中國以 Qwen 和 DeepSeek 為代表的「開源優先」高參與度生態。開源模型透過社群的集體微調、工具鏈優化與應用開發，累積進步的速度已逐漸逼近甚至超越封閉模型。這種去中心化的協作模式不僅降低了技術門檻，更形成了一個自我強化的生態飛輪，對全球 AI 競爭格局產生深遠影響。
Building Blocks for Foundation Model Training and Inference on AWS★ 75
Hugging Face Blog21d agoTutorialHugging Face 與 AWS 合作介紹在 AWS 上構建基礎模型的關鍵組件。文章涵蓋如何利用 AWS Trainium 和 Inferentia 晶片，並結合 Hugging Face Optimum Neuron 庫來優化效能。同時，也探討了透過 Amazon SageMaker 與專屬深度學習容器（DLCs）來簡化分散式訓練與高吞吐量推理的部署流程。
How Superset built the IDE for AI agents on Vercel
Vercel Changelog23d agoCommentary本文介紹 Superset 如何在 Vercel 平台上構建專為 AI Agent 設計的整合開發環境 (IDE)。Superset 利用 Vercel AI SDK 簡化多模型對接，並透過 Next.js App Router 與 Serverless Functions 處理複雜的代理人工作流與工具調用。透過 Vercel 的全球邊緣網路，他們成功解決了 Agent 運作時的即時狀態同步與高延遲問題，為開發者提供流暢的協作體驗。