Shownotes Transcript
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 Serverless 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 site).
Sherol will be at TensorFlow Dev Summit) speaking about machine learning research and creativity next week.