The AI Podcast
The AI Podcast
About The AI Podcast
One person, one interview, one story. Join us as we explore the impact of AI on our world, one amazing person at a time -- from the wildlife biologist tracking endangered rhinos across the savannah here on Earth to astrophysicists analyzing 10 billion-year-old starlight in distant galaxies to the Walmart data scientist grappling with the hundreds of millions of parameters lurking in the retailer’s supply chain. Every two weeks, we’ll bring you another tale, another 25-minute interview, as we build a real-time oral history of AI that’s already garnered nearly 3.4 million listens and been acclaimed as one of the best AI and machine learning podcasts. Listen in and get inspired. https://blogs.nvidia.com/ai-podcast/
Peter Ma was bored in his high school computer science class. So he decided to teach himself something new: how to use artificial intelligence to find alien life. That’s how he eventually became the lead author of a groundbreaking study published in Nature Astronomy. The study reveals how Ma and his co-authors used AI to analyze a massive dataset of radio signals collected by the SETI Breakthrough Listen project. They found eight signals that might just be technosignatures, or signs of alien technology. In this episode of the NVIDIA AI Podcast, host Noah Kravitz interviews Ma, who is now an undergraduate student at the University of Toronto. Ma tells Kravitz how he stumbled upon this problem and how he developed an AI algorithm that outperformed traditional methods in the search for extraterrestrial intelligence. You can read more about Ma’s research on NVIDIA’s blog: https://blogs.nvidia.com/blog/2023/02/06/ai-potential-alien-signals/
In the quest for knowledge at work, it can be tempting to think that finding what you need is like a needle in a haystack. But what if the haystack itself could show you where the needle is? That's the promise of large language models, or LLMs as they’re known, and it's the subject of a this week’s episode of NVIDIA’s AI Podcast featuring Deedy Das and Eddie Zhou, founding engineers at Glean, in conversation with our host, Noah Kravitz. With large-language models, the haystack can become a source of intelligence, helping guide knowledge workers on what they need to know. Glean is a Silicon Valley startup focused on providing better tools for enterprise search by indexing everything employees have access to in the company, including Slack, Dropbox, and email. The company raised a Series C financing round last year, valuing the company at $1 billion. By indexing everything employees have access to in the company, LLMs can provide a comprehensive view of the enterprise and its data, making it easier to find the information needed to get work done. In the podcast, Das and Zhou discuss the challenges and opportunities of bringing LLMs into the enterprise, and how this technology can help people spend less time searching and more time working. https://blogs.nvidia.com/blog/2023/03/01/glean-llm-enterprise-search/
Surfers, swimmers, and beachgoers face a hidden danger in the ocean: rip currents. These narrow channels of water can flow away from the shore at speeds up to 2.5 meters per second, making them one of the biggest safety risks for those enjoying the ocean. To help keep beachgoers safe, Dr. Christo Rautenbach, a coastal and estuarine physical processes scientist, has teamed up with the National Institute of Water and Atmospheric Research in New Zealand to develop a real-time rip current identification tool using deep learning. On this episode of the NVIDIA AI podcast, host Noah Kravitz interviews Dr. Rautenbach about the technology behind the rip current detection tool. The tool was developed by Dr. Rautenbach and NIWA in collaboration with Surf Lifesaving New Zealand and achieved a detection rate of roughly 90% in trials. The research behind the technology was published in the November 22nd edition of the journal Remote Sensing. Dr. Rautenbach explains how AI can be used to identify rip currents, a critical step in keeping beachgoers safe. He shares the research behind the technology and the results of the trials, as well as the potential for this tool to be used globally to help reduce the number of fatalities caused by rip currents. Tune in. https://blogs.nvidia.com/blog/2023/02/15/rip
Artificial intelligence is the new electricity. The fifth industrial revolution. And companies that go all-in on AI are reaping the rewards. So how do you make that happen? That big question — how? — is explored by Nitin Mittal, Principal at Deloitte, one of the world’s largest professional services organizations, and co-author Thomas Davenport in their new book "All-In On AI: How Smart Companies Win Big with Artificial Intelligence.” On the latest episode of NVIDIA’s AI Podcast, host Noah Kravitz speaks with Mittal, who leads Deloitte's artificial intelligence growth platform spoke about how companies across a wide variety of industries used AI to radically transform their organizations and achieve competitive advantage. The book, from the Harvard Business Review Press, explores the importance of a company-wide commitment to AI and the role of leadership in driving the adoption and implementation of AI. Mittal emphasizes that companies must have a clear strategy and plan, and invest in the necessary technology and talent to make the most of AI.
In the latest episode of the NVIDIA AI Podcast, host Noah Kravitz is joined by Pat Grady and Sonya Huang, partners at Sequoia Capital, to discuss their recent essay, “Generative AI: A Creative New World.” The authors delve into the potential of generative AI to enable new forms of creativity and expression, as well as the challenges and ethical considerations of this technology. They also offer insights into the future of generative AI. Grady and Huang emphasize the potential of generative AI to revolutionize industries such as art, design and media by allowing for the creation of unique, personalized content on a scale that would be impossible for humans to achieve alone. They also address the importance of considering the ethical implications of the technology, including the potential for biased or harmful outputs and the need for responsible use and regulation. Listen to the full episode to hear more about the possibilities of generative AI and the considerations to be made as this technology moves forward.
When NVIDIA co-founder Chris Malachowsky approached University of Florida Provost Joe Glover with the offer of an AI supercomputer, he couldn't have predicted the transformative impact it would have on the university. In just a short time, UF has become one of the top public colleges in the US and developed a groundbreaking neural network for healthcare research. In a recent episode of NVIDIA’s AI Podcast, host Noah Kravitz sat down with Joe Glover, provost and senior vice president of academic affairs at the University of Florida. The two discussed the university’s efforts to put AI to work across all aspects of higher education, including a public-private partnership with NVIDIA that has helped transform UF into one of the leading AI universities in the country. Just a year after the partnership was unveiled in July 2020, UF rose to number five on the US News and World Report’s list of the best public colleges in the US. The ranking was, in part a recognition of UF’s vision for infusing AI into its teaching and research. https://blogs.nvidia.com/blog/2023/01/04/university-of-florida-ai/
All of us recycle. Or, at least, all of us should. Now, AI is joining the effort. On the latest episode of the NVIDIA AI Podcast, host Noah Kravitz spoke with JD Ambati, founder and CEO of EverestLabs, developer of RecycleOS, the first AI-enabled operating system for recycling. The company reports that an average of 25-40% more waste is being recovered in recycling facilities around the world that use its tech.
Training, testing and validating autonomous vehicles requires a continuous pipeline — or data factory — to introduce new scenarios and refine deep neural networks. A key component of this process is simulation. AV developers can test a virtually limitless number of scenarios, repeatably and at scale, with high-fidelity, physically based simulation. And like much of the technology related to AI, simulation is constantly evolving and improving, getting ever nearer to closing the gap between the real and virtual worlds. NVIDIA DRIVE Sim, built on Omniverse, provides a virtual proving ground for AV testing and validation. It’s a highly accurate simulation platform with the ability to enable groundbreaking tools, including synthetic data generation and neural reconstruction, to build digital twins of driving environments and scenarios. Matt Cragun, senior product manager for AV simulation at NVIDIA, joined the AI Podcast to discuss the development of simulation for self-driving technology, detailing the origins and inner workings of DRIVE Sim. He also provided a sneak peek into the frontiers researchers are exploring for this critical testing and validation technology. https://blogs.nvidia.com/blog/2022/12/07/autonomous-vehicles-simulation/
Doesn’t matter if you love hockey, basketball, or soccer. Thanks to the Internet, there's never been a better time to be a sports fan. But how are all of these craveable video packages made? Editing together so many social media clips, long-form YouTube highlights and other videos from global sporting events is no easy feat. That's where auto-magical video solutions help. And by auto-magical, of course, we mean AI-powered. On this episode of the AI Podcast, host Noah Kravitz spoke with Amos Bercovich, algorithm group leader at WSC Sports, makers of an AI cloud platform that enables over 200 sports organizations worldwide to generate personalized and customized sports videos automatically and in real time. Bercovich spoke about the technological highlights behind your favorite highlight reels. https://blogs.nvidia.com/blog/2022/11/15/sports-highlights/
In the latest example of how researchers are using the latest technologies to track animals less invasively, a team of researchers has proposed harnessing high-flying AI-equipped drones powered to track the endangered black rhino through the wilds of Namibia. In a paper published earlier this year in the journal PeerJ, the researchers show the potential of drone-based AI to identify animals in even the remotest areas and provide real-time updates on their status from the air. While drones — and technology of just about every kind — have been harnessed to track African wildlife, the proposal promises to help gamekeepers move faster to protect rhinos and other megafauna from poachers. AI Podcast host Noah Kravitz spoke to two of the authors of the paper. Zoey Jewel is co founder and president of wild track.org, a global network of biologists and conservationists dedicated to non invasive wildlife monitoring techniques. And Alice Hua is a recent graduate of the School of Information at UC Berkeley in California, and an ML platform engineer at CrowdStrike. And for more, read the full paper at https://peerj.com/articles/13779/.
There are some 1.8 billion Muslims, but only 16% or so of them speak Arabic, the language of the Quran. This is in part due to the fact that many Muslims struggle to find qualified instructors to give them feedback on their Quran recitation. Enter today’s guest and his company Tarteel, a member of the NVIDIA Inception program for startups. Tarteel was founded with the mission of strengthening the relationship Muslims have with the Quran. The company is accomplishing this with a fusion of Islamic principles and cutting-edge technology. AI Podcast host Noah Kravitz spoke with Tarteel CEO Anas Abou Allaban, to learn more.
Thanks to earbuds, people can take calls anywhere, while doing anything. The problem: those on the other end of the call can hear all the background noise, too, whether it’s the roommate’s vacuum cleaner or neighboring conversations at a café. Now, work by a trio of graduate students at the University of Washington, who spent the pandemic cooped up together in a noisy apartment, lets those on the other end of the call hear just the speaker — rather than all the surrounding sounds. Users found that the system, dubbed “ClearBuds” — presented last month at the ACM International Conference on Mobile Systems, Applications and Services — improved background noise suppression much better than a commercially available alternative. AI Podcast host Noah Kravitz caught up with the team at ClearBuds to discuss the unlikely pandemic-time origin story behind a technology that promises to make calls clearer and easier, wherever we go.
Dentists get a bad rap. Dentists also get more people out of more aggravating pain than just about anyone. Which is why the more technology dentists have, the better. Overjet, a member of the NVIDIA Inception program for startups, is moving fast to bring AI to dentists’ offices. On this episode of the NVIDIA AI Podcast, host Noah Kravitz talks to Dr. Wardah Inam, CEO of Overjet, about how her company uses AI to improve patient care. Overjet’s AI-powered technology analyzes and annotates X-rays for dentists and insurance providers. It’s a step that promises to take the subjectivity out of X-ray interpretations, boosting medical services.
As consumers expect faster, cheaper deliveries, companies are turning to AI to rethink how they move goods. Foremost among these new systems are “hub-and-spoke,” or middle-mile, operations, where companies place distribution centers closer to retail operations for quicker access to inventory. However, faster delivery is just part of the equation. These systems must also be low cost for consumers. Autonomous delivery company Gatik seeks to provide lasting solutions for faster and cheaper shipping. By automating the routes between the hub — the distribution center — and the spokes — retail stores — these operations can run around the clock efficiently and with minimal investment. Gatik co-founder and Chief Engineer Apeksha Kumavat joined NVIDIA’s Katie Burke Washabaugh on the latest episode of the AI Podcast to walk through how the company is developing autonomous trucks for middle-mile delivery. https://blogs.nvidia.com/blog/2022/09/14/gatik-podcast/
Data is the fuel that makes artificial intelligence run. Training machine learning and AI systems requires data. And the quality of datasets has a big impact on the systems’ results. But compiling quality real-world data for AI and ML can be difficult and expensive. That’s where synthetic data comes in. The guest for this week’s AI Podcast episode, Nathan Kundtz, is founder and CEO of Rendered.ai, a platform as a service for creating synthetic data to train AI models. The company is also a member of NVIDIA Inception, a free, global program that nurtures cutting-edge startups. https://blogs.nvidia.com/blog/2022/08/31/rendered-ai/
Autonomous vehicles are one of the most complex AI challenges of our time. The networks running in the car must act as an intricate symphony, requiring intensive training, testing and validation on massive amounts of data to operate safely in the real world. Clément Farabet is the Vice President of AI Infrastructure at NVIDIA, and is the proverbial maestro behind the AV development orchestra. He’s applying nearly 15 years of experience in deep learning — including building Twitter’s AI machine — to teach neural networks how to perceive and react to the world around them. Farabet sat down with NVIDIA’s Katie Burke Washabaugh on the latest episode of the AI Podcast to discuss how the early days of deep learning led to today’s flourishing AV industry, and how he’s approaching DNN development. Tapping into the performance of the NVIDIA SaturnV supercomputer, Farabet is designing a highly scalable data factory to deliver intelligent transportation in the near term, and is looking ahead to the next frontiers in AI.
What if we could map our immune system to create drugs that can help our bodies win the fight against cancer and other diseases? That’s the big idea behind immunotherapy. The problem: the immune system is incredibly complex. Enter Immunai, a biotechnology company that’s using AI technology to map the human immune system and speed the development of new immunotherapies against cancer and autoimmune diseases. On this episode of NVIDIA’s AI Podcast, host Noah Kravitz spoke with Luis Voloch, CTO and Co-Founder of Immunai, about tackling the challenges of the immune system with a machine learning and data science mindset.
AI and electric vehicle technology breakthroughs are transforming the automotive industry. These developments pave the way for new innovators, attracting technical prowess and design philosophies from Silicon Valley. Mike Bell, senior vice president of digital at Lucid Motors, sees continuous innovation coupled with over-the-air updates as key to designing sustainable, award-winning intelligent vehicles that provide seamless automated driving experiences. NVIDIA’s Katie Burke Washabaugh spoke with Bell on the latest AI Podcast episode, covering what it takes to stay ahead in the software-defined vehicle space. Bell touched on future technology and its implications for the mass adoption of sustainable, AI-powered EVs — as well as what Lucid’s Silicon Valley roots bring to the intersection of innovation and transportation. https://blogs.nvidia.com/blog/2022/07/06/lucid-motors-podcast/
Want to learn about AI and machine learning? There are plenty of resources out there to help — blogs, podcasts, YouTube tutorials — perhaps too many. Machine learning engineer Santiago Valdarrama has taken a far more focused approach to helping us all get smarter about the field. He’s created a following by posing one machine learning question every day on his website bnomial.com. Think of it as Wordle for those who want to learn more about machine learning.
It may seem intuitive that AI and deep learning can speed up workflows — including novel drug discovery, a typically years-long and several-billion-dollar endeavor. But professors Artem Cherkasov and Olexandr Isayev were surprised to find that no recent academic papers provided a comprehensive, global research review of how deep learning and GPU-accelerated computing impact drug discovery. In March, they published a paper in Nature to fill this gap, presenting an up-to-date review of the state of the art for GPU-accelerated drug discovery techniques. Cherkasov, a professor in the department of urologic sciences at the University of British Columbia, and Isayev, an assistant professor of chemistry at Carnegie Mellon University, join NVIDIA AI Podcast host Noah Kravitz this week to discuss how GPUs can help democratize drug discovery. In addition, the guests cover their inspiration and process for writing the paper, talk about NVIDIA technologies that are transforming the role of AI in drug discovery, and give tips for adopting new approaches to research.
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