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.

On July 12 NASA will release the first science data – including the first science-quality images - from the $10 billion James Webb Space Telescope. The images are sure to be stunning, and guaranteed to make headlines around the world. AI Podcast Host Noah Kravitz spoke with UC Santa Cruz's Brant Robertson, a professor of astrophysics and astronomy, about the data science behind one of the biggest science stories of our time. https://blogs.nvidia.com/blog/2022/06/08/deep-learning-james-webb-space-telescope/