NVIDIA & Caltech
Next-generation frameworks for Large-scale AI
The deep-learning revolution has achieved impressive progress through the convergence of data, algorithms, and computing infrastructure. The availability of web-scale labeled data and parallelism of GPUs enabled us to harness the power of neural networks. However, for further progress, we cannot solely rely on bigger models. We need to reduce our dependence on labeled data, and design algorithms that can incorporate more structure and domain knowledge. Examples include tensors, graphs, physical laws, and simulations. I will describe efficient frameworks that enable developers to easily prototype such models, e.g. Tensorly to incorporate tensorized architectures, NVIDIA Isaac to incorporate physically valid simulations and NVIDIA RAPIDS for end-to-end data analytics. I will then lay out some outstanding problems in this area.
Anima Anandkumar holds dual positions in academia and industry. She is a Bren professor at Caltech CMS department and a director of machine learning research at NVIDIA. At NVIDIA, she is leading the research group that develops next-generation AI algorithms. At Caltech, she is the co-director of Dolcit and co-leads the AI4science initiative, along with Yisong Yue.
She has spearheaded the development of tensor algorithms, first proposed in her seminal paper. They are central to effectively processing multidimensional and multimodal data, and for achieving massive parallelism in large-scale AI applications.
Prof. Anandkumar is the youngest named chair professor at Caltech, the highest honor the university bestows on individual faculty. She is recipient of several awards such as the Alfred. P. Sloan Fellowship, NSF Career Award, Faculty fellowships from Microsoft, Google and Adobe, and Young Investigator Awards from the Army research office and Air Force office of sponsored research. She has been featured in documentaries and articles by PBS, wired magazine, MIT Technology review, yourstory, and Forbes.
Anima received her B.Tech in Electrical Engineering from IIT Madras in 2004 and her PhD from Cornell University in 2009. She was a postdoctoral researcher at MIT from 2009 to 2010, visiting researcher at Microsoft Research New England in 2012 and 2014, assistant professor at U.C. Irvine between 2010 and 2016, associate professor at U.C. Irvine between 2016 and 2017, and principal scientist at Amazon Web Services between 2016 and 2018.