The next major evolution will come from multi-agent systems—networks of smaller, specialized AI models that coordinate across ...

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 ...

According to a Deloitte survey, nearly 60% of the AI leaders and representatives are struggling with adopting AI agents, primarily due to integrating with legacy systems and addressing risk and ...

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 ...

Researchers have developed a novel framework, termed PDJA (Perception–Decision Joint Attack), that leverages artificial intelligence (AI) to address a ...

At HIMSS26, Dr. Nathan Moore of the BJC Accountable Care Organization will show how health systems can move beyond chatbots ...

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 ...

What if the future of work wasn’t just about automation but about collaboration, between humans and intelligent agents? Imagine a world where multi-agent AI systems seamlessly coordinate tasks, adapt ...

Most current autonomous driving systems rely on single-agent deep learning models or end-to-end neural networks. While ...

AI agents perceive their environment, make decisions, and take action, while agentic AI operates with greater autonomy, ...

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 ...