Jensen Huang: NVIDIA and Microsoft Aim to Turn PCs into AI Agent Hubs
INSIDE 硬塞 AI1d agoHardwareJensen Huang compared the PC's future to the smartphone's evolution: people still call it a phone, although calling is no longer its primary use. He predicts that PCs will look fundamentally different in ten years, moving beyond today's click-and-type interaction model. The original headline frames this vision as an NVIDIA and Microsoft effort to turn PCs into AI agent hubs.
GitHub Copilot’s new token-based billing spurs dev backlash★ 72
TechCrunch AI3d agoBusinessTechCrunch reports that GitHub Copilot will move to token-based billing on June 1, replacing a more predictable flat or request-based model. Some developers say their expected monthly costs could jump dramatically, citing examples from about $29 to nearly $750 or $50 to around $3,000. Others argue the worst cases may reflect heavy vibe-coding usage, while critics say Microsoft encouraged that behavior before changing the economics.
Microsoft Copilot Cowork Exfiltrates Files★ 76
Simon Willison's Weblog7d agoIncidentSimon Willison summarizes a PromptArmor report about Microsoft Copilot Cowork and agentic data exfiltration risks. The issue involved agents sending messages to a user’s own inbox without approval, where rendered external images could trigger requests to attacker-controlled sites. Because OneDrive can create pre-authenticated download links, a successful prompt injection could leak links that allow attackers to download files.
Differential Transformer V2★ 80
Hugging Face Blog133d agoReleaseMicrosoft 於 Hugging Face 發表 Differential Transformer V2（Diff-Transformer V2）。延續 V1 透過雙注意力地圖相減來消除雜訊的設計，V2 重點解決了計算與記憶體開銷問題。新版本引入了高度優化的 CUDA 核心與 FlashAttention 整合，並釋出預訓練模型與 Hugging Face 整合，讓開發者能以更低成本部署具備強大長文本與抗噪能力的模型。
Fine-tuning Florence-2 - Microsoft's Cutting-edge Vision Language Models★ 80
Hugging Face Blog708d agoTutorial微軟推出的 Florence-2 是一款強大且輕量的視覺語言模型（VLM），僅有 232M 與 770M 兩種參數版本，卻能高效處理 OCR、目標檢測、圖像描述等多種任務。Hugging Face 官方部落格發布了這篇實用指南，詳細教學如何使用 Hugging Face 的 transformers 與 peft 函式庫，在自訂資料集上對 Florence-2 進行微調（Fine-tuning），並利用 LoRA 技術降低顯示記憶體需求，非常適合想在邊緣裝置或有限資源下部署視覺 AI 的開發者。