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The AI Podcast

Author: NVIDIA

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AI has been described as “Thor’s Hammer“ and “the new electricity.” But it’s also a bit of a mystery – even to those who know it best. We’ll connect with some of the world’s leading AI experts to explain how it works, how it’s evolving, and how it intersects with every facet of human endeavor. This podcast is produced by NVIDIA, the AI computing company. Multiple episodes are released every month.
120 Episodes
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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 brought back one of NVIDIA’s best explainers, Will Ramey, to provide an introduction to today’s AI boom and the key concepts behind it. Ramey, senior director and global head of developer programs at NVIDIA, led a webinar, "Deep Learning Demystified," as part of this year's GTC Digital online conference. https://developer.nvidia.com/gtc/2020/video/s22555
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.
On this episode of the NVIDIA AI Podcast, we interview Stanford Professor Margot Gerritsen about what’s next in data science, the growing role of women in data science, and how data science intersects with modern AI. For more, tune into Professor Gerritsen's Women in Data Science podcast https://www.widsconference.org/podcast.html
Kathy Baxter, the architect of ethical AI practice at Salesforce, is helping her team and clients create more responsible technology. To do so, she supports employee education, the inclusion of safeguards in Salesforce technology, and collaboration with other companies to improve ethical AI across industries.
Matthew Putman, this week’s guest on the AI Podcast, knows that the devil is in the details. That’s why he’s the co-founder and CEO of Nanotronics, a Brooklyn-based company providing precision manufacturing enhanced by AI, automation and 3D imaging.
What John Madden was to pro football, Neda Cvijetic is to autonomous vehicles. No one’s better at explaining the action, in real time, than Cvijetic. Cvijetic, senior manager of autonomous vehicles at NVIDIA, drives our NVIDIA DRIVE Labs series of videos and blogs breaking down the science behind autonomous vehicles.
National Pothole Day is Jan. 15. Its timing is no accident. All over the Northern hemisphere, potholes are at their suspension-wrecking, spine-shaking worst this month. Thanks to AI, one startup is working all year long to alleviate this menace. Benjamin Schmidt, president and co-founder of RoadBotics, is using the tech to pave the way to better roads.
Spell, founded by Serkan Piantino, is making machine learning as easy as ABC. Piantino, CEO of the New York-based startup and former director of engineering for Facebook AI Research, explained to AI Podcast host Noah Kravitz how he’s bringing compute power to those that don’t have easy access to GPU clusters.
You can’t have an AI podcast and not interview someone using AI to make podcasts better. That’s why we reached out to serial entrepreneur Andrew Mason to talk to him about what he’s doing now. His company, Descript Podcast Studio, uses AI, natural language processing and automatic speech synthesis to make podcast editing easier and more collaborative.
At Oracle, customer service chatbots use conversational AI to respond to consumers with more speed and complexity. Suhas Uliyar, vice president of bots, AI and mobile product management at Oracle, stopped by to talk to AI Podcast host Noah Kravitz about how the newest wave of conversational AI can keep up with the nuances of human conversation.
Doina Precup is applying Romanian wisdom to the gender gap in the fields of AI and computer science. The associate professor at McGill University and research team lead at AI startup DeepMind spoke with AI Podcast host Noah Kravitz about her personal experiences, along with the AI4Good Lab she co-founded to give women more access to machine learning training. Growing up in Romania, Precup attended a high school that specialized in computer science and a technical university. She didn’t experience gender disparity in these learning environments. “If anything, programming was considered a very good job for women, because you did not need to be working in the fields,” she explained. It made the gap in Canadian universities and companies even more noticeable. At McGill, Precup saw that female students were hesitant to speak up or pursue graduate studies. Together with Angelique Mannella, CEO of AM Consulting and an Amazon employee, Precup was inspired to start the AI4Good Lab in 2017.
When your appliances break, the last thing you want to do is spend an hour on the phone trying to reach a customer service representative. Using computer vision, Drishyam.AI is eliminating service lines to help consumers more quickly. Satish Mandalika, the CEO and founder of the deep learning-based image recognition platform, spoke with AI Podcast host Noah Kravitz about the company. “Customer support is ripe for disruption,” Mandalika said. Drishyam.AI is changing the game by giving customers an app that they use to take a picture of the product they need help with at any time of day or night, rather than calling a help line. Using computer vision, Drishyam.AI analyzes the issue and communicates directly with manufacturers, rather than going through retail outlets. This is more efficient because a product’s lifetime warranty is usually held by the company that made it, rather than the stores selling it like Home Depot and Lowe’s.
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Comments (6)

chinta chandan

amazing podcast.

Jun 13th
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要可爱 ٩( 'ω' )و

Chinese audience here! Chinese government approved more and more unversities to include AI as undergraduate major in 2018,still on the increase

Apr 22nd
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Sumukh

Really helpful in understanding our current position in technology

Feb 13th
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Lech Koper

Very interested in this subject. Please continue with more information.

Nov 8th
Reply (1)

Dawid van Straaten

Awesome podcast! Thank you NVidia!!!

Nov 17th
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