Jared Dame, Z by HP's director of business development and strategy for AI, data science and edge technologies, spoke to AI Podcast host Noah Kravitz about the role HP’s workstations play in cutting-edge AI and data science.

Understanding the U.S. tax code can take years of study — it’s 80,000 pages long. Software company Intuit has decided that it’s a job for AI. Ashok Srivastava, its senior vice president and chief data officer, spoke to AI Podcast host Noah Kravitz about how the company is utilizing machine learning to help customers with taxes and aid small businesses through the financial effects of COVID-19.

Imagine building an engine with 54 billion parts. Now imagine each piece is the size of a gnat’s eyelash. That gives you some idea of the scale Jonah Alben works at. Jonah is the co-leader of GPU engineering at Nvidia. The engines he builds are GPUs. Without these chips your favorite computer games and special-effects movies would look pretty lame. GPUs also power scientific simulations of everything from a Mars lander to a protein spike on the coronavirus… and, oh yes, these days they do much of the heavy lifting for the latest and greatest form of computing: AI.

As NVIDIA’s vice president of worldwide AI initiatives, Keith Strier is thinking on a global scale. He leads an initiative called AI Nations, a worldwide program that helps government leaders and stakeholders develop plans to implement AI to advance national priorities and drive economic growth. Strier spoke to AI Podcast host Noah Kravitz about AI Nations, and how NVIDIA helps countries harness all the capabilities of AI — from enhancing their local startup ecosystems to developing autonomous public transportation systems.

Whether you're using the latest generation of AI enabled mobile apps or robust business systems powered on banks of powerful servers, chances are your technology was built, first, on a workstation. We spoke with Lenovo’s Mike Leach about how these workhorses are adapting to support a plethora of new kinds of AI applications.

Autonomous vehicles require a massive amount of data and computing power. Teaching a vehicle to see what’s on the road in front of it is a big part of the puzzle. Our guests today, Ford’s Nikita Jaipuria and Rohan Bhasin, are using Generative Adversarial Networks to help autonomous vehicle systems see as well in rain and snowy conditions as they do when it’s clear out.

Cleaning up our oceans, rivers, and waterways have become a major environmental issue. Leaders in the field are now looking to begin harnessing modern AI and machine learning techniques to help tackle this immense challenge. We spoke with the San Francisco Estuary Institute’s Lorenzo Flores on using machine learning to find trash in environmentally sensitive waterways.

We spoke with Jonathan Frankle, a PhD student at MIT and coauthor of a seminal paper outlining a technique, known as the “The Lottery Ticket,” hypothesis that promises to help advance our understanding of why neural networks, and deep learning, works so well.

We spoke with Capital One Senior Software Engineer Kyle Nicholson on how modern machine learning techniques have become a key tool for financial and credit analysis.

We spoke with a particle physicist Ryan Coffee, senior staff scientist at the SLAC National Accelerator Laboratory on how he — and others in his field — are putting deep learning to work. We include questions from friends, family and acquaintances in a wide-ranging conversation complementing a deep-dive session led by Ryan Coffee as part of GTC Digital.