David Vs. Goliath: Why Small Language Models Are Quietly Winning Where It Matters Most

In enterprise AI, the models that win won't be the largest. They'll be the ones that know exactly what they're built for.​​ ...
IEEE

Task Offloading and Resource Optimization Based on Dependency-Aware Graph and Collaborative Deep Reinforcement Learning in Mobile Edge Computing

Abstract: In mobile edge computing (MEC), computation offloading serves as an effective solution to bridge the gap between the stringent latency requirements of computational tasks and the limited ...
Communications of the ACM

Can We Understand How Large Language Models Reason?

Large language models can write essays, solve math problems, and generate computer code, but it’s not fully understood how ...
Times Higher Education

Design learning that works with the brain, not against it

Educating used to be about explaining concepts – now it’s about designing experiences to help the brain develop understanding. Find advice to tweak your teaching here ...
IEEE

A Blockchain-Enabled Cold Start Aggregation Scheme for Federated Reinforcement Learning-Based Task Offloading in Zero Trust LEO Satellite Networks

Abstract: The development of 6G enable users in remote and harsh areas to enjoy computation-intensive services including metaverse entertainment, intelligent transportation, and immersive ...