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 ...

The biggest challenge to AI initiatives is the data they rely on. More powerful computing and higher-capacity storage at lower cost has created a flood of information, and not all of it is clean. It ...

Forbes contributors publish independent expert analyses and insights. Anne T. Griffin is an AI product leader and educator. What agent swarms (a team of agents) and human teams have in common is that ...

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 ...

For much of the last two years, multi-agent systems have been treated as the natural next step in artificial intelligence. If one large language model can reason, plan, and act, then several working ...

What if your multi-agent system could communicate faster, use fewer resources, and still maintain seamless functionality? That’s the promise of handoffs in OpenAI’s Agents SDK—a feature that’s ...

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 ...

Enterprises are likely to shift from single-task AI to multi-agent systems, enabling autonomous, adaptive operations, but trust and orchestration remain problematic.

As AI-assisted coding becomes more common, a new pattern is emerging: multi-agent workflows. A multi-agent workflow refers to using various AI agents in parallel for specific software development life ...

Spacecraft are becoming too complex, too autonomous and too far from Earth to rely on static rules and ground-driven investigation. Multi-agent AI provides a practical, incremental, operationally ...