Large Language Models (LLMs) show promise in healthcare tasks but face challenges in complex medical scenarios. We developed a Multi-Agent Conversation (MAC) framework for disease diagnosis, inspired ...

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 ...

Dapr recently introduced Dapr Agents, a framework for building scalable, resilient AI agents using Large Language Models (LLMs). It enables structured workflows, multi-agent coordination, and ...

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 ...

Google LLC is pulling out all the stops to give developers all the tools they need to bring the next era of generative artificial intelligence agents into reality, including access to powerful AI ...

Value stream management involves people in the organization to examine workflows and other processes to ensure they are deriving the maximum value from their efforts while eliminating waste — of ...

We tested state-of-the-art LLMs under clinical-scale workloads using two designs: a single agent handling all tasks and a multi-agent orchestrator assigning each task to a dedicated worker. Across ...

Researchers at Google and MIT have conducted a comprehensive analysis of agentic systems and the dynamics between the number of agents, coordination structure, model capability, and task properties.

When I first started working with multi-agent collaboration (MAC) systems, they felt like something out of science fiction. It’s a group of autonomous digital entities that negotiate, share context, ...

AI is nervy. We know that a certain amount of Artificial Intelligence is somewhat nervy (or perhaps nervous) in its implementation because of concerns over decisioning bias, questions over the ...