What if you could design a system where multiple specialized agents work together seamlessly, each tackling a specific task with precision and efficiency? This isn’t just a futuristic vision—it’s the ...

Reduced visibility into AI agent interactions could hinder enterprise debugging, governance, and regulatory compliance while ...

CyberGym benchmark scores over time, showing the rapid improvement in AI vulnerability discovery capabilities. Microsoft’s multi-model MDASH system (top right) tops the leaderboard at 88.4%. (CyberGym ...

What if the very systems designed to transform problem-solving are quietly failing behind the scenes? Multi-agent AI, often hailed as the future of artificial intelligence, promises to tackle complex ...

Multi-agent AI systems require strict AWS Cedar policies to prevent unchecked privilege escalation during automated ...

The landscape of artificial intelligence is undergoing a significant transformation. As the capabilities of large language models grow, we are beginning to see a shift away from isolated ...

Stanford's DeLM lets AI agents coordinate without a central controller, cutting multi-agent inference costs 50% and beating SWE-bench baselines by 10.5%.

As artificial intelligence (AI) becomes more common in health care, from managing records to assisting with medication decisions, researchers at the Icahn School of Medicine at Mount Sinai are asking ...

Michael Wegmüller has more than 20 years of experience in AI. He is cofounder of Artifact SA and a widely recognized AI business expert. Multi-agent AI systems (MAS) represent the next step in ...

Microsoft researchers this week unveiled a new multi-agent AI system, aimed to help enterprises automate complex tasks typically requiring human intervention. Named Magnetic-One, the open source ...

For too long, enterprises have failed to go beyond the view of AI as a product; an assistant that sits to the side, helping users complete tasks and delivering incremental productivity gains. This ...