In this week’s edition of the NVIDIA Developer Top 5 video, we revisit the top developer stories of the week.
From a new set of DGX-2 systems at ORNL to a million-dollar prize for improving Zillow’s AI algorithm.
Plus, learn more about our new how-to series that explain how to use Tensor Cores for deep learning.
5 – Oak Ridge National Laboratory Installs Two NVIDIA DGX-2 Systems
The U.S. Department of Energy’s Oak Ridge National Laboratory (ORNL), home to the world’s fastest supercomputer, just installed two NVIDIA DGX-2 systems for use in machine learning tasks.
4 – New App Uses AI to Enable Users to Explore Sneakers In AR
Wannaby, a Belarus startup founded by ex-googler Sergey Arkhangelsky, just launched Wanna Kicks a new app that can let you virtually try on a pair of shoes.
3 – Video Series: Mixed-Precision Training Techniques Using Tensor Cores for Deep Learning
Neural networks with thousands of layers and millions of neurons demand high performance and faster training times. The complexity and size of neural networks continue to grow. Mixed precision training using Tensor Cores on Volta and Turing architectures enable higher performance while maintaining network accuracy for heavily compute- and memory-intensive Deep Neural Networks (DNNs).
2 – AI Researchers Pave the Way For Translating Brain Waves Into Speech
Researchers from Columbia University used deep learning to enhance speech neuroprothesis technologies, that can result in accurate and intelligible reconstructed speech from the human auditory cortex.
1 – NVIDIA GPUs Help Developers’ Score $1 Million Prize For Improving Zillow’s Zestimate
To help prospective buyers and sellers know exactly how much a home is worth, Zillow, the online real estate company awarded a team of three, a million-dollar prize for developing an algorithm that can better predict the value of a home.