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Explores the societal impact of science, advocating against limiting it within boundaries, and introduces 'experimental history' as a multidisciplinary approach to studying science.
Delves into training and applications of Vision-Language-Action models, emphasizing large language models' role in robotic control and the transfer of web knowledge. Results from experiments and future research directions are highlighted.
Delves into the intersection of physics and data in machine learning models, covering topics like atomic cluster expansion force fields and unsupervised learning.
