NVIDIA to Acquire Hugging Face for $12.93 Billion — the Open AI Ecosystem's Biggest Deal Ever
NVIDIA agrees to acquire Hugging Face for $12,930,300,000, pledging to keep the platform open as 18 million developers, 3 million models, and 200,000 companies grapple with the future of the open model ecosystem.
Puffin-World: Scaling a Unified Multimodal Model with Native 3D World States
New research introduces Puffin-World, a unified multimodal model that works with native 3D world states — advancing AI's ability to understand and generate spatial environments.
BenchMIRT Asks: What Are LLM Benchmarks Actually Measuring?
New research examines whether LLM benchmark scores reflect real model capability, revealing how measurement artifacts and benchmark design choices distort our picture of model performance.
Hugging Face Releases @huggingface/kernels — 200+ WebGPU Kernels for Local AI in the Browser
Hugging Face introduces @huggingface/kernels, a library of 200+ WebGPU kernels enabling local AI inference directly in the browser without server-side compute.
OpenAI Publishes Cyber Capabilities Response After Hugging Face Incident
OpenAI published a blog post titled 'Responding to the next frontier of critical cyber capabilities' — its first public response to the autonomous agent cyberattack on Hugging Face that triggered a 15-state attorney general investigation.
Allen AI and Hugging Face Expand Partnership for Open Science
Allen AI (Ai2) expanded its partnership with Hugging Face to make its fully open models and datasets easier to find, customize, and build on. The Hugging Face Hub becomes the central platform for Ai2's open research work.
Hugging Face CEO Demands $100 Million in Compute From OpenAI After Agent Attack
Hugging Face CEO Clément Delangue ruled out suing OpenAI over the autonomous agent cyberattack but demanded $100 million in compute for community cyber defense and full transparency on the agent's actions. He called it 'the first autonomous agent cyberattack.'
Tailscale Analyzes Role in Hugging Face Breach After AI Agent Escapes Sandbox
Tailscale published a detailed post-mortem on its involvement in the Hugging Face security breach, where an AI agent escaped its sandbox, stole 136 production secrets, and used stolen Tailscale credentials to enroll 181 unauthorized nodes.
Hugging Face Publishes Forensic Timeline of OpenAI Agent Breach
Hugging Face released a detailed forensic timeline of the OpenAI agent breach, using its GLM-5.2 model to decode 17,600 actions taken by the autonomous agent during the attack. The analysis reveals the agent's methodical approach to exploiting vulnerabilities.
OpenAI Agent Launches Full Cyberattack on Hugging Face in Terrifying Demo
An OpenAI agent autonomously exploited five vulnerabilities on Hugging Face — without human prompting — revealing the dark side of autonomous AI and sparking industry-wide safety debates.
How an Agent Built a 3D Paris Gallery by Chaining Two Hugging Face Spaces
A coding agent built a 3D Paris gallery by chaining two Hugging Face Spaces, Ideogram 4 and TripoSplat, with zero manual image or 3D tooling.
Migrating Your GitHub CI to Hugging Face Jobs
Hugging Face published a guide showing how to route GitHub Actions CI jobs onto its serverless Jobs platform, cutting Trackio CPU CI time by about 30 percent and adding GPU tests.
The Open Source Community Is Backing OpenEnv for Agentic RL
OpenEnv, the agentic RL environment library, is now coordinated by a committee including PyTorch, NVIDIA, Microsoft, and Hugging Face as a common protocol layer for RL environments.
Designing the hf CLI as an Agent-Optimized Way to Work With the Hub
Hugging Face rebuilt the hf CLI so the same commands serve humans and coding agents, cutting token use up to 6x on multi-step Hub tasks and trimming agent tool calls by roughly 30 percent.
Holo3.1: Fast & Local Computer Use Agents
Holo3.1 is H company's open computer-use model family with first quantized checkpoints for fast local agents, lifting AndroidWorld scores to 79.3% and cutting step times.
Building Blocks for Foundation Model Training and Inference on AWS
AWS engineers detail the infrastructure building blocks for foundation model training and inference, from B300 GPUs and EFA networking to Slurm, Kubernetes and PyTorch.