Ars Technica
The four-week project hints that AI could make formal verification far more practical. Google DeepMind researchers used agentic AI to mathematically prove, or “formally verify,” a number of the Signal protocol’s key cryptographic guarantees, a landmark development for the widely used cryptography and AI itself.
Summary drawn from Ars Technica's own description of the story.
The Verge
United says it won't let personal AI assistants book tickets on the airline, citing both privacy and regulatory concerns. The company says it hasn't yet seen many people try to use AI agents to book their flights, The Wall Street Journal reports, in line with observations from other businesses like Doordash.
cbsnews.com
Using an artificial intelligence agent to make flight reservations poses security risks and could violate federal rules, according to United. Many consumers are turning to AI agents such as Meta's Muse and OpenAI's dots to complete tasks ranging from researching products and tracking down deals to making purchases.
GitHub
SOTA model-agnostic quantization for GGUF, local inference and beyond. Quantize and run text, image, video and audio models with llama.cpp, vLLM, Diffusers and PyTorch. - huawei-csl/MACaQ MACaQ can quantize a 122B-parameter model in 64 minutes. using just 32.5 GB of device memory.
The Decoder
Google Deepmind's new Gemini Decisions API evaluates up to 1,000 closed-ended questions in a single pass across text, images, audio, and video. Gemini Decision 1 returns results in 150 to 250 milliseconds at roughly five times lower cost than Gemini 3.5 Flash-Lite, according to Google.