NVIDIA AI Podcast

Path-breaking work that translates an amputee’s thoughts into finger motions, and even commands in video games, holds open the possibility of humans controlling just about anything digital with their minds. Using GPUs, a group of researchers trained an AI neural decoder able to run on a compact, power-efficient NVIDIA Jetson Nano system on module (SOM) to translate 46-year-old Shawn Findley’s thoughts into individual finger motions. And if that breakthrough weren’t enough, the team then plugged Findley into a PC running Far Cry 5 and Raiden IV, where he had his game avatar move, jump — even fly a virtual helicopter — using his mind. It’s a demonstration that not only promises to give amputees more natural and responsive control over their prosthetics. It could one day give users almost superhuman capabilities. The effort is detailed in a draft paper, or pre-print, titled “A Portable, Self-Contained Neuroprosthetic Hand with Deep Learning-Based Finger Control.” It details an extraordinary cross-disciplinary collaboration behind a system that, in effect, allows humans to control just about anything digital with thoughts. Jules Anh Tuan Nguyen, the paper’s lead author and now a postdoctoral researcher at the University of Minnesota, spoke with NVIDIA AI Podcast host Noah Kravitz about his efforts to allow amputees to control their prosthetic limb — right down to the finger motions — with their minds. blogs.nvidia.com/blog/2021/08/10/lending-a-helping-hand-jules-anh-tuan-nguyen-on-building-a-neuroprosthetic

Following a long string of victories for computers in other games — chess in 1997, go in 2016 and Texas hold’em poker in 2019 — a GPU-powered AI has beaten some of the world’s most competitive word nerds at the crossword puzzles that are a staple of every Sunday paper. Dr.Fill, the crossword puzzle-playing AI created by Matt Ginsberg — a serial entrepreneur, pioneering AI researcher and former research professor — scored higher than any humans earlier this year at the American Crossword Puzzle Tournament. Ginsberg spoke with NVIDIA AI Podcast host Noah Kravitz about his decade-long journey creating Dr.Fill and where he envisions it going in the future. https://blogs.nvidia.com/blog/2021/07/28/matt-ginsberg-ai-podcast/

Robots are not just limited to the assembly line. At NVIDIA, Liila Torabi works on making the next generation of robotics possible. Torabi is the senior product manager for Isaac Sim, a robotics and AI simulation platform powered by NVIDIA Omniverse. Torabi spoke with NVIDIA AI Podcast host Noah Kravitz about the new era of robotics, one driven by making robots smarter through AI. https://blogs.nvidia.com/blog/2021/07/14/liila-isaac-sim/

We all know about the applications for digital humans for films and video games, but at NVIDIA, Simon Yuen has discovered the vast need and potential for digital humans beyond the entertainment industry. Yuen spoke with NVIDIA AI Podcast host Noah Kravitz about how we’re getting to a point where the simulation of digital humans is possible as opposed to just the visual representation. Yuen leads the Digital Human project at NVIDIA. One of the first products the team is developing is Audio2Face, an AI-based solution that automates high-quality facial animation in real-time, based only on audio as input. https://blogs.nvidia.com/blog/2021/06/28/simon-audio2face/

What do radiology and wastewater have in common? Hopefully, not much. But at startup Opseyes, founder Bryan Arndt and data scientist Robin Schlenga are putting the AI that’s revolutionizing medical imaging to work on analyzing wastewater samples. Arndt and Schlenga spoke with NVIDIA AI Podcast host Noah Kravitz about the inspiration for Opseyes, which began with Arndt’s career at wastewater industry leader Ramboll. Effluent has typically been analyzed by sending tightly sealed samples through the mail to experts. While speaking with his brother, a radiologist using deep learning, Arndt realized that AI could do something similar for wastewater samples. Schlenga then led the creation of Opseyes’ convolutional neural network, which allows customers to upload a photo of a sample taken through a microscope. With Opseyes already in use at several wastewater plants, Arndt and Schlenga anticipate much more bacterial analysis in their future. https://blogs.nvidia.com/blog/2021/06/16/ai-opseyes-wastewater-analysis/

3D deep learning holds the potential to accelerate progress in everything from robotics to medical imaging. But until now, researchers haven’t had the right tools to easily manage and visualize different types of 3D data. NVIDIA Kaolin is a collection of tools within the NVIDIA Omniverse simulation and collaboration platform that allows researchers to visualize and generate datasets, move between 3D tools and retain basic functions for other users. NVIDIA AI Podcast host Noah Kravitz spoke with four NVIDIANs about their work on the platform, including Richard Kerris, industry general manager for Omniverse; Jean-Francois Lafleche, a deep learning engineer; Senior Research Scientist Masha Shugrina; and Research Scientist Clement Fuji Tsang. Kaolin includes both a library, which contains a growing number of GPU-optimized operations, and an app within NVIDIA Omniverse for interactive 3D data visualizations. The long-term goal is to make both facets so robust that users could import a photo that generates a highly developed 3D model without spending time on recreating the scene within a 3D platform. https://blogs.nvidia.com/blog/2021/06/02/kaolin-podcast/

For a particle physicist, the world’s biggest questions — how did the universe originate and what’s beyond it — can only be answered with help from the world’s smallest building blocks. James Kahn, a consultant with German research platform Helmholtz AI and a collaborator on the global Belle II particle physics experiment, uses deep learning to understand the fundamental rules governing particle decay. Kahn spoke with AI Podcast host Noah Kravitz about the specifics of how AI is accelerating particle physics. He also touched on his work at Helmholtz AI. Khan helps researchers in fields spanning medicine to earth sciences apply AI to the problems they’re solving. His wide-ranging career — from particle physicist to computer scientist — shows how AI accelerates every industry. https://blogs.nvidia.com/blog/2021/05/19/ai-particle-physics/

With only one U.S. state without a Walmart supercenter — and over 4,600 stores across the country — the retail giant’s prediction analytics work with data on an enormous scale. Grant Gelven, a machine learning engineer at Walmart Global Tech, joined NVIDIA AI Podcast host Noah Kravitz for the latest episode of the AI Podcast. Gelven spoke about the big data and machine learning methods making it possible to improve everything from the customer experience to stocking to item pricing. https://blogs.nvidia.com/blog/2021/05/05/ai-walmart/

Julie Bernauer — senior solutions architect for machine learning and deep learning at NVIDIA — led the small team that successfully built Selene, the world’s fifth-fastest supercomputer. Adding to an already impressive feat, Bernauer’s team brought up Selene as the world went into lockdown in early 2020. They used skeleton crews, social distancing protocols, and remote cable validation to achieve what typically takes months with a larger install team in a few weeks. Bernauer told NVIDIA AI Podcast host Noah Kravitz about the goal in creating Selene, which was primarily to support NVIDIA’s researchers. Referencing her time as a doctoral student, Bernauer explains how researchers are often prevented from working on larger models due to expense and infrastructure. With Selene, the infrastructure is modular and can be scaled up or down depending on what users require, and allows for different types of research to be performed simultaneously. Bernauer said that Selene is proving most useful to autonomous vehicle and language modeling research at the moment. Going forward, Bernauer envisions some of the power and efficiency of systems like Selene becoming more available on widely accessible devices, such as laptops or edge products such as cars.

Shalini De Mello, a principal research scientist at NVIDIA who’s made her mark inventing computer vision technology that contributes to driver safety, finished 2020 with a bang — presenting two posters at the prestigious NeurIPS conference in December. A 10-year NVIDIA veteran, De Mello works on self-supervised and few-shot learning, 3D reconstruction, viewpoint estimation and human-computer interaction. She told NVIDIA AI Podcast host Noah Kravitz about her NeurIPS submissions on reconstructing 3D meshes and self-learning transformations for improving head and gaze redirection — both significant challenges for computer vision. https://blogs.nvidia.com/blog/2021/04/07/nvidia-research-shalini-de-mello/