This is a schematic showing data parallelism vs. model parallelism, as they relate to neural network training. Disclaimer: AAAS and EurekAlert! are not responsible for the accuracy of news releases ...

Distributed deep learning has emerged as an essential approach for training large-scale deep neural networks by utilising multiple computational nodes. This methodology partitions the workload either ...

In a new paper, researchers from Tencent AI Lab Seattle and the University of Maryland, College Park, present a reinforcement learning technique that enables large language models (LLMs) to utilize ...