NVIDIA is working to put the world’s fastest GPU into the hands of the world’s smartest AI researchers.
Last month in Honolulu, NVIDIA shocked top AI researchers, giving them the world’s first NVIDIA Tesla V100 GPU accelerators. Last night, in Sydney, NVIDIA struck again, handing out 15 NVIDIA Tesla V100 GPU accelerators.
“I think it’s fantastic,” said Sergey Levine, an assistant professor at the University of California, Berkeley, who is known for his work at the intersection of deep learning and robot
Given out at a meetup for participants in the NVIDIA AI Labs programme at the International Conference on Machine Learning, and signed by NVIDIA founder and CEO Jensen Huang, the V100s are the world’s most powerful GPUs, offering more than 100 teraflops of deep learning performance.
“We are going to melt this with our algorithms, then we are going to melt the world,” said the University of Washington’s Pedro Domingos.
Through NVAIL, NVIDIA supports AI research at the world’s top universities and institutes.
Recipients of the V100s at last night’s meetup included representatives from Carnegie Mellon University, the Chinese Academy of Sciences (CAS), IDSIA – the Swiss AI Lab, the Massachusetts Institute of Technology, MPI Tübingen, the Montreal Institute for Learning Algorithms, National Taiwan University, Oxford University, Peking University, Stanford University, Tsinghua University, the University of California Berkeley, the University of Tokyo, the University of Toronto and the University of Washington.
“We are very much reliant on NVIDIA technology,” said Aaron Courville, of the Montreal Institute for Learning Algorithms. “More GPUs is always a very good thing, and very important for us”
All the recipients are from NVAIL member institutions.
“Supporting innovation at every level is a hallmark of NVIDIA,” says Ian Buck, general manager and vice president of Accelerating Computing at NVIDIA. “Our NVAIL partners are at the forefront of AI, making new discoveries every day that can benefit our lives.”
Another surprise at the meetup: the launch of the NVIDIA Pioneering Research Awards. It’s a new programme to celebrate the acceptance of NVAIL partners’ research papers at conferences such as ICML.
Award recipients received a plaque featuring the first page of their papers. Inaugural winners include: • Carnegie Mellon University: Improved Variational Autoencoders for Text Modeling using Dilated Convolutions • IDSIA/Istituto Dalle Molle di Studi sull’Intelligenza Artificiale: Recurrent Highway Networks • Massachusetts Institute of Technology: Coresets for Vector Summarization with Applications to Network Graphs • Montreal Institute for Learning Algorithms: A Closer Look at Memorization in Deep Networks • Tsinghua University: Identify the Nash Equilibrium in Static Games with Random Payoffs • University of California, Berkeley: Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks • University of Tokyo: Asymmetric Tri-training for unsupervised domain adoptation • University of Toronto: Deep Spectral Clustering Learning
“I am very excited and honoured to receive this award,” said Professor Tatsuya Harada of the University of Tokyo.
“It’s really great to see that NVIDIA is really so involved in research, that they invite us out here and that they look at the kind of papers we are writing and recognise that,” said Berkeley’s Levine.
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