MIT Unveils Method to Double LLM Training Efficiency
Researchers from MIT and partners have developed a new system that significantly increases the training efficiency of large language models (LLMs) used for advanced reasoning tasks. By adaptively training a smaller model during idle processor cycles, their method can double training speeds without sacrificing model accuracy, potentially reducing costs and energy consumption.