A new study from MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) demonstrates a novel method for training AI models that significantly reduces computational costs and energy consumption. The technique, called ‘Lazy Learning,’ focuses on training only the specific, relevant parts of a neural network for a given task, rather than the entire model. This approach, inspired by the brain’s efficiency, could make advanced AI development more accessible by lowering the barrier of expensive hardware. Researchers report that Lazy Learning achieved comparable accuracy to fully trained models while using a fraction of the computational resources, marking a potential shift towards more sustainable and efficient AI development. Read the full article at https://technologyreview.com/2024/03/15/lazy-learning-ai.