Bryan Catanzaro, the VP Applied Deep Learning Research at NVIDIA, joins Mark and Melanie this week to discuss how his team uses applied deep learning to make NVIDIA products and processes better. We talk about parallel processing and compute with GPUs as well as his team’s research in graphics, text and audio to change how these forms of communication are created and rendered by using deep learning.

This week we are also joined by a special co-host, Sherol Chen who is a developer advocate on GCP and machine learning researcher on Magenta at Google. Listen at the end of the podcast where Mark and Sherol chat about all things GDC.



Bryan Catanzaro

Bryan Catanzaro is VP of Applied Deep Learning Research at NVIDIA, where he leads a team solving problems in domains ranging from video games to chip design using deep learning. Bryan earned his PhD from Berkeley, where he focused on parallel computing, machine learning, and programming models. He earned his MS and BS from Brigham Young University, where he worked on higher radix floating-point representations for FPGAs.
Bryan worked at Baidu to create next generation systems for training and deploying deep learning models for speech recognition. Before that, he was a researcher at NVIDIA, where he worked on programming models for parallel processors, as well as libraries for deep learning, which culminated in the creation of the widely used CUDNN library.

Cool things of the week


NVIDIA Tesla V100s coming to Google Cloud site
Automatic Severless Deployment with Cloud Source Repositories blog
Magenta site


NSynth Super site
MusicVAE site
Making music using new sounds generated with machine learnnig blog

Building Blocks of Interpretability blog


Interview


NVIDIA site
NVIDIA GPU Technology Conference (GTC) site
CUDA site
cuDNN site
NVIDIA Volta site
NVIDIA Tesla P4 docs
NVIDIA Tesla V100s site
Silicon Valley AI Lab Baidu Research site
ICML: International Conference on Machine Learning site
CVPR: Computer Vision and Pattern Recognition Conference site


Referenced Papers & Research:


Deep learning with COTS HPC System paper
Building High-level Features Using Large Scale Unsupervised Learning paper
OpenAI Learning to Generate Reviews and Discovering Sentiment paper
Progressive Growing of GANs for Improved Quality, Stability, and Variation paper and CelebA dataset
High-Resolution Image Synthesis and Semantic Manipulation with Conditional GANs paper
Deep Image Prior site
How a Japanese cucumber farmer is using deep learning and TensorFlow blog


Sample Talks:


Future of AI Hardware Panel video
High Performance Computing is Supercharging AI blog/video
AI Podcast: Where is Deep Learning Going Next? blog/video


Sample Resources:


Coursera How Google does Machine Learning site
NVIDIA Deep Learning Institute site
Udacity AI Nanodegree site
Kaggle site
TensorFlow site
PyTorch site
Keras site






Question of the week

What to watch out for and get involved in at the Game Developers Conference (GDC) this year and in the future?


International Grame Developers Association (IGDA) site
Fellowship of GDC Parties site
ALtCtrlGDC site
Experimental Gameplay Workshop site
Women in Games International (WIGI) site
Blacks in Gaming (BIG) site
Serious Games (SIGs) site
What’s New in Firebase and Google Cloud Platform for Games site
Summits to Checkout:


AI Game Developers Summit site
Game Narrative Summit site
Independent Games Summit site

Additional Advice:


The first two days are summits which are great because topic focused
Expo floor takes a good hour to get through
WIGI, BIG and SIGs (Google and Microsoft) have the best food
GDC is composed of various communities
Bring business cards
Check out post-mortems

Favorite Games:


Mass Effect site
Final Fantasy wiki

Games Mark & Sherol are currently playing:


Hearthstone site
Dragon Age Origins wiki



Where can you find us next?

Mark and Sherol are at the Game Developer’s Conference (GDC). You can find them via the Google at GDC 2018 sit