Federated Learning

If quantum computing is the future, then quantum federated learning (QFL) is its decentralized heartbeat — promising data privacy, distributed intelligence, and unparalleled computing power. But like a high-performance car with faulty brakes, QFL’s potential is hindered by one chronic issue: quantum noise. A new paper introduces a deceptively simple yet powerful idea to address it — sporadic learning. In doing so, it doesn’t just offer a technical tweak — it reframes how we think about contribution and silence in distributed AI. ...

The CoRAG Deal: RAG Without the Privacy Plot Twist The tension is growing: organizations want to co-train AI systems to improve performance, but data privacy concerns make collaboration difficult. Medical institutions, financial firms, and government agencies all sit on valuable question-answer (QA) data — but they can’t just upload it to a shared cloud to train a better model. This is the real challenge holding back Retrieval-Augmented Generation (RAG) from becoming a truly collaborative AI strategy. Not the rise of large context windows. Not LLMs like Gemini 2.5. But the walls between data owners. ...