1. Researchers Find About 18,000 Suspected Public Messages From OpenAI Agents Sharing Answers and Bypassing Sandbox Limits The authors behind collusion.

2. ChatGPT, Claude and Grok’s Simultaneous Outages Have Partial Explanations, but No Evidence Points to a Shared Infrastructure Failure ChatGPT, Claude and Grok suffered unusual overlapping outages on Thursday morning, temporarily disrupting three leading AI chatbots.

3. LLaDA-Image Opens Weights, Code, and Training Recipe for 6B Image Generation and Editing Model The LLaDA-Image team has released the weights, training code, and detailed recipe for a unified open-source model family designed to generate images and edit them from instructions.

In Brief

• OpenAI Commits $1 Billion to Cybersecurity for Essential Services OpenAI introduced Daybreak for Frontline Defenders, a program expanding access to frontier cyber AI, training, and support for essential-service organizations.

• Crusoe Reportedly Raises $3 Billion at a $30 Billion Valuation AI data-center and cloud provider Crusoe reportedly raised the round from investors led by Atreides Management and Valor Equity Partners, ten months after being valued at $10 billion.

• Nscale Seeks $3.5 Billion Before Potential IPO British AI infrastructure provider Nscale is reportedly discussing $1.5 billion in convertible notes and another $2 billion in financing from Nvidia as it considers going public.

• Microsoft Uses Copilot Logs to Contest Copyright Claims Microsoft said fewer than 1% of 8.2 million selected Copilot conversations reproduced at least 16 words from grounded news content, arguing that the findings support its fair-use defense. The New York Times disputes that conclusion and alleges Microsoft and OpenAI unlawfully used its journalism.

• Corporate America Turns to Open-Source AI A New York Times report says open-source AI is gaining adoption among US corporations.

• Ukraine Opens Battlefield Drone Data to AI Developers Ukraine’s Ministry of Defense has made millions of data points from tens of thousands of drone flights available to military contractors and commercial companies; more than 100 companies and the UK government have gained access.

• Microsoft Unveils Developer-Focused Project Zenith PCs Project Zenith is a preconfigured Windows environment for devices with at least 64GB of unified memory, designed to run models exceeding 30 billion parameters locally. The first devices use AMD Ryzen AI Halo chips and include tools such as Visual Studio Code and GitHub Copilot.

• Gemini Spark Gains Control of Google Photos Tasks Google’s personal AI agent can now edit images, curate and share albums, turn photographed event flyers into calendar entries, and execute other Photos workflows. The capabilities are rolling out to eligible Gemini AI Pro and Ultra subscribers in the US in English.

• Instagram Again Mislabels Photos as AI-Generated Users report that Instagram is applying “AI Content” labels to conventionally edited photographs while leaving some generated images unlabeled. Meta has not clarified which signals caused the disputed classifications.

• Cerebras Lists Qwen 3.8 27B at 1,500 Tokens per Second Cerebras has made the open-weight Qwen 3.8 27B model available through its inference platform at a claimed speed of 1,500 tokens per second. Its documentation says public models are unpruned, with selective weight-only quantization used for storage.

• Terminal-Universe Reconstructs Training Environments From Agent Logs Researchers created 37,300 executable environments by rebuilding workspaces from terminal-agent trajectories and synthesizing new tasks. They report that fine-tuning Qwen3.5-27B on the resulting corpus improved two coding-agent benchmarks by 11.9 and 13.8 points.

• Random KV-Cache Eviction Raises Reported Reasoning Throughput The Random Attention paper preserves prompts but evicts reasoning tokens uniformly within each attention head, avoiding token-importance scoring. Across four models and six tasks, the authors report performance matching the strongest prior eviction method with 32–43% higher vLLM throughput.

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