
Anima Anandkumar is setting a personal record this week with seven of her team's research papers accepted to NeurIPS 2020.
The 34th annual Neural Information Processing Systems conference is taking place virtually from Dec. 6-12. The premier event on neural networks, NeurIPS draws thousands of the world's best researchers every year.
Anandkumar, NVIDIA's director of machine learning research and Bren professor at CalTech's CMS Department, joined AI Podcast host Noah Kravitz to talk about what to expect at the conference, and to explain what she sees as the future of AI.
The AI Podcast Behind the Scenes at NeurIPS with NVIDIA and CalTech's Anima Anandkumar Ep. 131
The papers that Anandkumar and her teams at both NVIDIA and CalTech will be presenting are focused on topics including how to design more robust priors that improve network perception and how to create useful benchmarks to evaluate where neural networks need to improve.
In terms of what Anandkumar is focused on going forward, she continues to work on the transition from supervised to unsupervised and self-supervised learning, which she views as the key to next-generation AI.
Key Points From This Episode:
Anandkumar explains how her interest in AI grew from a love of math at a young age as well as influence from her family - her mother was an engineer and her grandfather a math teacher. Her family was also the first in their city to have a CNC machine - an automated machine, such as a drill or lathe, controlled by a computer - which sparked an interest in programming.
Anandkumar was instrumental in spearheading the development of tensor algorithms, which are crucial in achieving massive parallelism in large-scale AI applications. That's one reason for her enthusiasm for NeurIPS, which is not constrained by a particular domain but focused more on improving algorithm development.
Tweetables: How do we ensure that everybody in the community is able to get the best benefits from the current AI and can contribute in a meaningful way? - Anima Anandkumar [2:44]
Labs like NVIDIA Research are thinking about, Okay, where do we go five to 10 years and beyond from here?' - Anima Anandkumar [11:16]
What I'm trying to do is bridge this gap [between academia and industry] so that my students and collaborators are getting the best of both worlds - Anima Anandkumar [23:54]
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NVIDIA's Jonah Alben Talks AI Imagine building an engine with 54 billion parts. Now imagine each piece is the size of a gnat's eyelash. That gives an idea of the scale Jonah Alben works at. Alben is the co-leader of GPU engineering at NVIDIA.
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