Patronus AI raises $50M to stress-test AI agents

Google has integrated computer use capabilities directly into Gemini 3.5 Flash, moving the feature from a standalone model into the main Flash offering. The capability allows AI agents to see, reason, and take action across browser, mobile, and desktop environments for tasks like software testing and enterprise automation. The company is addressing safety concerns through adversarial training and optional enterprise safeguards including user confirmation requirements and prompt injection detection.

OpenAI is supporting the development of shared standards for advanced AI systems, working through the Appia Foundation to establish evaluation frameworks and safety practices. The effort aims to enable global cooperation on AI governance and technical standards. The initiative addresses the need for coordinated approaches to AI safety and interoperability across organizations.

Google DeepMind has published an AI Control Roadmap focused on securing internal systems that deploy AI agents, combining traditional safeguards with real-time monitoring approaches. The roadmap addresses the challenge of maintaining control over increasingly autonomous AI systems as they take on more complex tasks. This represents a shift toward proactive security frameworks designed to prevent misuse or unintended behavior in production AI agent deployments.

Google researchers propose 'faithful uncertainty,' a technique that allows large language models to express qualified guesses rather than either confidently hallucinating or refusing to answer. The approach reframes hallucinations as 'confident errors' and enables models to hedge responses appropriately, preserving utility while maintaining trustworthiness. This addresses a core tradeoff in LLM deployment where eliminating factual errors typically forces models to abstain from answering questions they actually know.