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 ‘Liquid Neural Networks,’ mimics the adaptive nature of biological neurons, allowing the AI to learn continuously and efficiently from new data without requiring complete retraining. Researchers report that this approach could make advanced AI development more accessible and environmentally sustainable, potentially lowering the barrier to entry for academic and smaller-scale research projects. The full details of the research are available in the published paper. Read the full article at https://technologyreview.com/2023/10/18/1083631/liquid-neural-networks-cut-ai-training-costs/