Explores provably beneficial AI, aligning AI goals with human preferences and behaviors, illustrating complexities through examples like image classification and fetching coffee.
Delves into the intersection of physics and data in machine learning models, covering topics like atomic cluster expansion force fields and unsupervised learning.
Explores the ethical implications of brain-computer interfaces and the societal challenges at the human-machine interface, emphasizing the importance of cognitive liberty and mental privacy.