At the core of Industry 4.0, the smart factory integrates automation, mass customization, and self-organization into a highly ...

Large language models (LLMs) are a transformational capability at the frontier of artificial intelligence and machine learning that can support decision-makers in addressing pressing societal ...

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 ...

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 ...

Due to the lack of domain classification theory for domain-specific machine translation, the quality of translation in this area is low. We propose a domain classification system based on HNC and ...

Stanford's DeLM lets AI agents coordinate without a central controller, cutting multi-agent inference costs 50% and beating ...

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 looking to deploy multiple AI agents often need to implement a framework to manage them. To this end, Microsoft researchers recently unveiled a new multi-agent infrastructure called ...

Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with content, and download exclusive resources. Birgitta Böckeler, Distinguished Engineer at ...

Learn how to move enterprise AI agents from copilots to production with secure runtimes, trusted data, governance, ...