Autonomous Systems

In the fast-evolving landscape of agentic AI, one critical limitation persists: most frameworks can think or act, but rarely both in a fluid, self-directed manner. They follow rigid ReAct-like loops—plan, call, observe—resembling a robot that obeys instructions without ever truly reflecting on its strategy. The recent paper “DeepAgent: A General Reasoning Agent with Scalable Toolsets” from Renmin University and Xiaohongshu proposes an ambitious leap beyond this boundary. It envisions an agent that thinks deeply, acts freely, and remembers wisely. ...

If your AI agent is putting a metal fork in the microwave, would you rather stop it after the sparks fly—or before? That’s the question Pro2Guard was designed to answer. In a world where Large Language Model (LLM) agents are increasingly deployed in safety-critical domains—from household robots to autonomous vehicles—most existing safety frameworks still behave like overly cautious chaperones: reacting only when danger is about to occur, or worse, when it already has. This reactive posture, embodied in rule-based systems like AgentSpec, is too little, too late in many real-world scenarios. ...

Good AI Goes Rogue: Why Intelligent Disobedience May Be the Key to Trustworthy Teammates We expect artificial intelligence to follow orders. But what if following orders isn’t always the right thing to do? In a world increasingly filled with AI teammates—chatbots, robots, digital assistants—the most helpful agents may not be the most obedient. A new paper by Reuth Mirsky argues for a shift in how we design collaborative AI: rather than blind obedience, we should build in the capacity for intelligent disobedience. ...