Meta releases Muse Wonder as Microsoft presses for AI safety rules

Meta ships Muse Wonder and a larger coding-focused variant

Meta introduced Muse Wonder and Muse Wonder Full, a new model family it describes as its most capable to date for personal and professional agentic work. The company says Wonder is available through the Meta Model API and Muse Code, while Wonder Full is initially available to Muse Code subscribers. Meta says the models are intended for tasks including navigating documents, working through claims and building software.

The company is emphasizing two features: “Active Memory,” which it says retains relevant information across conversations, and “Active Focus,” which it says lets a system persist through a difficult task, try alternatives and ask for clarification before completing important actions. Those are product claims, not independently established measures of dependable long-running agent behavior.

Meta says the family was trained and evaluated under its Superintelligence Scaling Framework and that a fuller safety-evaluation report is still to come. It says the models are designed not to disclose private information without permission, to refuse harmful requests and to help developers and security teams strengthen their systems, but the announcement does not provide the promised full report or independent testing. That gap matters because the capabilities being promoted involve access to sensitive material and extended tasks rather than just single-turn answers.

The release is an availability announcement, not proof that the company’s benchmark comparisons will hold in ordinary use. TechCrunch reported that Meta presents the series as its first frontier-model effort; practical performance, pricing and deployment limits will need testing beyond the company’s materials.

Microsoft president calls for binding incident reporting and emergency brakes

Microsoft president Brad Smith told the BBC that AI has fewer safety rules than familiar consumer products, including milk and washing machines, according to reporting by The Guardian. He called for stronger global rules as systems become more capable of acting through tools and other connected software.

Smith’s proposals are concrete but remain proposals. He said organisations whose systems are breached by a rogue AI agent should have a legal right to be told, and he called for incident reports and independent evaluators to assess new developments. He also argued for an “emergency brake” that could pause or slow a system that is behaving dangerously.

The remarks do not create a legal requirement or describe a universally usable technical stop mechanism. They do, however, sharpen an accountability question that product announcements about long-running agents often leave open: who learns about failures, who evaluates claims before release, and whether a person with authority can stop a connected system quickly enough. The timing is notable after recent disclosures from several AI developers about unintended agent actions, but Smith’s interview is a policy argument, not evidence that the safeguards he advocates are already in place.