A new study from MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) demonstrates a novel approach to AI training that significantly reduces computational costs. The method, called ‘Lazy Learning,’ selectively trains only the most relevant parts of a neural network for a given task, rather than the entire model. This targeted approach can cut training time and energy consumption by up to 80% for certain applications without sacrificing accuracy. The research suggests this could make advanced AI models more accessible and environmentally sustainable. The full details of the study are available in the published paper. Read the full article at https://technologyreview.com/2024/05/15/lazy-learning-ai-training.