UIUC and Stanford's RecursiveMAS lets AI agents collaborate in embedding space instead of text, cutting token usage by 75% and speeding inference 2.4x.
Anthropic has launched “dreaming” for AI agents, giving Claude new self-improving tools designed to boost enterprise automation, reliability, and scale.
Today, multi-agent systems (MAS) have emerged as transformative technologies, driving innovation and efficiency across various industries. Comprising multiple autonomous agents working collaboratively ...
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 ...
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 ...
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 ...
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 ...
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 ...