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

As enterprises increasingly demand fail-safes against single-vendor reliance, Sakana is proving that packaging collective intelligence into a single API endpoint is a highly viable commercial path.

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 ...

Expertise from Forbes Councils members, operated under license. Opinions expressed are those of the author. As the CTO of an AI-native email management startup, I've spent the past year building multi ...

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 enterprise AI adoption matures, the industry is shifting from a race over raw model capabilities to a focus on operational efficiency. In response to this evolution, MegaRouter today announced the ...

How event-driven design can overcome the challenges of coordinating multiple AI agents to create scalable and efficient reasoning systems. While large language models are useful for chatbots, Q&A ...

The latest monthly update to Visual Studio Code, version 1.107 (the November 2025 release), continues Microsoft's focus on AI-assisted workflows with expanded multi-agent orchestration across local, ...

We just can’t seem to help ourselves. Our current infatuation with multi-agent systems risks mistaking a useful pattern for an inevitable future, just as we once did with microservices. Remember those ...