Anima Anandkumar: Enabling Zero-Shot Generalization in AI4Science | IACS Distinguished Lecturer

Anima Anandkumar
Bren professor at Caltech Computing + Mathematical Sciences Department
Director of machine learning research at NVIDIA

ABSTRACT: Many scientific applications heavily rely on the use of brute-force numerical methods performed on high-performance computing (HPC) infrastructure. Can artificial intelligence (AI) methods augment or even entirely replace these brute-force calculations to obtain significant speed-ups? Can we make groundbreaking new discoveries because of such speed-ups? However, such AI4science often requires zero-shot generalization to entirely new scenarios not seen during training. I will present exciting recent advances that build new foundations in AI that are applicable to a wide range of problems such as fluid dynamics and quantum chemistry. On the other side of the coin, the use of simulations to train AI models can be very effective in applications such as robotics and autonomous driving. Thus, we will see a convergence of AI, Simulations and HPC in the coming years.

Видео Anima Anandkumar: Enabling Zero-Shot Generalization in AI4Science | IACS Distinguished Lecturer канала Harvard Institute for Applied Computational Science