Artificial intelligence and machine learning (AI/ML) have been extremely successful in predicting, optimizing, and controlling the behavior of complex interacting systems. Robustness and explainability of existing AI/ML methods, however, remain big challenges, and clearly new approaches are needed. In this program, Ambuj K. Singh, Distinguished Professor of Computer Science at the UC, Santa Barbara, explains that the human brain motivated the early development of the field of deep learning, and neuroscientific concepts have contributed to the profound success of deep learning algorithms across many areas. The next leap in AI/ML may again come from a deeper understanding of modularity, robustness, and adaptability of brain architectures. Series: "GRIT Talks" [Science] [Show ID: 39331]

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