Generative AI Futures - GNoME. Scaling Deep Learning for Materials Discovery скачать в хорошем качестве

Generative AI Futures - GNoME. Scaling Deep Learning for Materials Discovery

Scaling Deep Learning for Materials Discovery This podcast detail two significant, related advancements in materials science using artificial intelligence and automation. The first source describes the A-Lab, an autonomous laboratory that integrates robotics, machine learning, and computational data from sources like the Materials Project to accelerate the experimental synthesis of novel inorganic powders, achieving a high success rate in realizing predicted materials over a short period. The second source focuses on scaling deep learning for materials discovery using Graph Neural Networks (GNNs), collectively called GNoME, which discovered over 2.2 million stable crystal structures, massively expanding the known catalogue of stable materials by leveraging active learning and large-scale computation to improve stability predictions and generalization. Both papers emphasize the power of combining computational power, historical data, and advanced AI models to dramatically accelerate the discovery and realization of new materials.