New distributed reinforcement learning system cuts post-training costs by up to 80%, expanding access to advanced AI beyond ...

In the fast-changing digital era, the need for intelligent, scalable and robust infrastructure has never been so pronounced. Artificial intelligence is predicted as the harbinger of change, providing ...

The concept of edge-first intelligence entails embedding critical data and inference models directly into the application or ...

Today's AI challenge is about agent coordination, context, and collaboration. How do you enable them to truly think together, with all the contextual understanding, negotiation, and shared purpose ...

Membership Inference Authors, Creators & Presenters: PAPER Yuefeng Peng (University of Massachusetts Amherst), Ali Naseh (University of Massachusetts Amherst), Amir Houmansadr (University of ...

An AI-integrated infrastructure framework embeds real-time diagnostics, reinforcement learning, and multi-agent coordination into distributed data platforms. Validated in production, it reduces ...

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 ...

Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with content, and download exclusive resources. Cory Benfield discusses the evolution of ...

What is a distributed system? A distributed system is a collection of independent computers that appear to the user as a single coherent system. To accomplish a common objective, the computers in a ...