The US is advancing AI safety through state and federal action
OpenAI describes a 'reverse federalism' approach to AI governance in the US, proposing that state-level laws contribute to a national framework for safe, democratic AI.
OpenAI describes a 'reverse federalism' approach to AI governance in the US, proposing that state-level laws contribute to a national framework for safe, democratic AI.
NVIDIA and partners in Japan are highlighting the latest full-stack AI and robotics advancements across industries this week.
OpenAI's GPT-Red is an automated red teaming system that uses self-play to strengthen AI safety, alignment, and resistance to prompt injection attacks.
Hugging Face has launched Real World VoiceEQ, a new measurement tool that evaluates the human quality of voice AI systems.
Multiple social media posts claim OpenAI's GPT-5.6 Sol model deleted files and data without warning, a problem the company had reportedly disclosed in June.
Apple has released the iOS 27 public beta, letting iPhone owners try its revamped AI-powered Siri and other new features before the software's official launch this fall.
AWS details how Thrad.ai deployed a multi-agent system using Strands Agents and Amazon Bedrock AgentCore to automate prospect discovery and personalized email generation, with benchmarks on two orchestration patterns.
Part 2 of an AWS series demonstrates how QA Studio extends Amazon Nova Act to handle batch regression testing and CI/CD pipeline integration via test suites and a command-line interface.
NVIDIA's Nemotron Labs highlights open models as a way for enterprises and nations to build AI they can trust, control and tailor to domain-specific needs.
An AWS blog post outlines a cloud-based UX testing platform that uses Amazon Nova Act to auto-generate test scenarios from documentation and run user flows in parallel at scale.
Google is updating the Google Images homepage to display a real-time, personalized gallery of images before a user searches, marking the platform's 25th anniversary.
NVIDIA frames performance per watt as the defining efficiency metric for AI infrastructure, arguing power is the main constraint on how many tokens an AI factory can generate.