The AI Podcast

Can machine learning help predict extreme weather events and climate change? Christopher Bretherton, senior director of climate modeling at the Allen Institute for Artificial Intelligence, or AI2, explores the technology’s potential to enhance climate modeling with AI Podcast host Noah Kravitz in an episode recorded live at the NVIDIA GTC global AI conference. Bretherton explains how machine learning helps overcome the limitations of traditional climate models and underscores the role of localized predictions in empowering communities to prepare for climate-related risks. Through ongoing research and collaboration, Bretherton and his team aim to improve climate modeling and enable society to better mitigate and adapt to the impacts of climate change.

Step into the realm of the unseen with Robin Wang, CEO of Living Optics. The startup cofounder discusses the power of hyperspectral imaging with AI Podcast host Noah Kravitz in an episode recorded live at the NVIDIA GTC global AI conference. Living Optics’ hyperspectral imaging camera, which can capture visual data across 96 colors, reveals details invisible to the human eye. Potential applications are as diverse as monitoring plant health to detecting cracks in bridges. The startup aims to empower users across industries to gain new insights from richer, more informative datasets fueled by hyperspectral imaging technology. Living Optics is a member of the NVIDIA Inception program for cutting-edge startups. Stay tuned for more episodes recorded live from GTC.

Talk about scrubbing data. Curtis Northcutt, cofounder and CEO of Cleanlab, and Steven Gawthorpe, senior data scientist at Berkeley Research Group, speak about Cleanlab’s groundbreaking approach to data curation with Noah Kravitz, host of NVIDIA’s AI Podcast, in an episode recorded live at the NVIDIA GTC global AI conference. The startup’s tools enhance data reliability and trustworthiness through sophisticated error identification and correction algorithms. Northcutt and Gawthorpe provide insights into how AI-powered data analytics can help combat economic crimes and corruption and discuss the intersection of AI, data science and ethical governance in fostering a more just society. Cleanlab is a member of the NVIDIA Inception program for cutting-edge startups. https://blogs.nvidia.com/blog/cleanlab-podcast/

Dotlumen is illuminating a new technology to help people with visual impairments navigate the world. In this episode of NVIDIA’s AI Podcast, recorded live at the NVIDIA GTC global AI conference, host Noah Kravitz spoke with the Romanian startup’s founder and CEO, Cornel Amariei, about developing its flagship Dotlumen Glasses. Dotlumen is a member of the NVIDIA Inception program for cutting-edge startups. Equipped with sensors and powered by AI, the glasses compute a safely walkable path for visually impaired individuals and offer haptic — or tactile — feedback on how to proceed via corresponding vibrations. Amariei further discusses the process and challenges of developing assistive technology and its potential for enhancing accessibility. Stay tuned for more episodes recorded live from GTC.

Viome CTO Guru Banavar discusses how the startup’s innovations in AI and genomics advance personalized health and wellness.

AI-driven change is in the air, as are concerns about the technology’s environmental impact. In this episode of NVIDIA’s AI Podcast, Daniel Castro, vice president of the Information Technology and Innovation Foundation and director of its Center for Data Innovation, speaks with host Noah Kravitz about the motivation behind his AI energy use report, which addresses misconceptions about the technology’s energy consumption. Castro also touches on the need for policies and frameworks that encourage the development of energy-efficient technology. Tune in to discover the crucial role of GPU acceleration in enhancing sustainability and how AI can help address climate change challenges.

In today’s episode of NVIDIA’s AI Podcast, host Noah Kravitz talks with Pinar Seyhan Demirdag, co-founder and CEO of Cuebric. Cuebric is on a mission to offer new solutions in filmmaking and content creation through immersive, two-and-a-half-dimensional cinematic environments. Their AI-powered application aims to help creators quickly bring their ideas to life, making high-quality production more accessible. Demirdag discusses how Cuebric uses generative AI to enable the creation of engaging environments affordably. Listen in to find out about the current landscape of content creation, the role of AI in simplifying the creative process, and Cuebric's participation in NVIDIA's GTC technology conference. https://blogs.nvidia.com/blog/pinar-demirdag-cuebric/

NASCAR races are all about speed, but even the fastest cars need to factor in safety, especially as rules and tracks change. The Ohio Supercomputer Center is ready to help. In this episode of NVIDIA’s AI Podcast, host Noah Kravitz speaks with Alan Chalker, the director of strategic programs at the OSC, about all things supercomputing. The center’s Open OnDemand program, which takes the form of a web-based interface, empowers Ohio higher education institutions and industries with accessible, reliable and secure computational services and training and educational programs. Chalker dives into the history and evolution of the OSC, and explains how it’s working with client companies like NASCAR, which is simulating race car designs virtually. Tune in to learn more about Chalker’s outlook on the future of supercomputing and OSC’s role in realizing it.

Here’s some news to still beating hearts: AI is helping bring some clarity to cardiology. Caristo Diagnostics has developed an AI-powered solution for detecting coronary inflammation in cardiac CT scans. In this episode of NVIDIA’s AI Podcast, Dr. Keith Channon, cofounder and chief medical officer at the startup, speaks with host Noah Kravtiz about the technology. Called Caristo, it analyzes radiometric features in CT scan data to identify inflammation in the fat tissue surrounding coronary arteries, a key indicator of heart disease. Tune in to learn more about how Caristo uses AI to improve treatment plans and risk predictions by providing physicians with a patient-specific readout of inflammation levels.

DigitalPath is igniting change in the golden state — using computer vision, generative adversarial networks and a network of thousands of cameras to detect signs of fire in real time. In the latest episode of NVIDIA’s AI Podcast, host Noah Kravtiz spoke with DigitalPath system architect Ethan Higgins about the company’s role in the ALERTCalifornia initiative, a collaboration between California’s wildfire fighting agency CAL FIRE and the University of California, San Diego. DigitalPath built computer vision models to process images collected from network cameras — anywhere from eight to 16 million a day — intelligently identifying signs of fire like smoke. “One of the things we realized early on, though, is that it’s not necessarily a problem about just detecting a fire in a picture,” Higgins said. “It’s a process of making a manageable amount of data to handle.” That’s because, he explained, it’s unlikely that humans will be entirely out of the loop in the detection process for the foreseeable future. The company uses various AI algorithms to classify images based on whether they should be reviewed or acted upon — if so, an alert is sent out to a CAL FIRE command centers. There are some downsides to using computer vision to detect wildfires — namely, that extinguishing more fires means a greater buildup of natural fuel and the potential for larger wildfires in the long term. DigitalPath, along with UCSD, are exploring using high-resolution LIDAR data to identify where those fuels can be let out in the form of prescribed burns. Looking ahead, Higgins foresees the field tapping generative AI to accelerate new simulation tools — as well as using AI models to analyze the output of other models to doubly improve wildfire prediction and detection. “AI is not perfect, but when you couple multiple models together, it can get really close,” he said.

Thomson Reuters, the global content and technology company, is transforming the legal industry with generative AI. In the latest episode of NVIDIA’s AI Podcast, host Noah Kravitz spoke with Thomson Reuters’ Chief Product Officer David Wong about its potential — and implications. Many of Thomson Reuters offerings for the legal industry either address an information retrieval problem or help generate written content. It has a AI-driven digital solution that enables law practitioners to search laws and cases intelligently within different jurisdictions. It also provides AI-powered tools that are set to be integrated with commonly used products like Microsoft 365 to automate the time-consuming processes of drafting and analyzing legal documents. These technologies increase the productivity of legal professionals, enabling them to focus their time on higher value work. According to Wong, ultimately these tools also have the potential to help deliver better access to justice. To address ethical concerns, the company has created publicly available AI development guidelines, as well as privacy and data protection policies. And it’s participating in the drafting of ethical guidelines for the industries it serves. There’s still a wide range of reactions surrounding AI use in the legal field, from optimism about its potential to fears of job replacement. But Wong underscored that no matter what the outlook, “it is very likely that professionals that use AI are going to replace professionals that don’t use AI.” Looking ahead, Thomson Reuters aims to further integrate generative AI, as well as retrieval-augmented generation techniques into its flagship research products to help lawyers synthesize, read and respond to complicated technical and legal questions. Recently, Thomson Reuters acquired Casetext, which developed the first AI legal assistant, CoCounsel. In 2024 Thomson Reuters is building on this with the launch of an AI assistant that will be the interface across Thomson Reuters products with GenAI capabilities, including those in other fields such as tax and accounting.

A new era of autonomous vehicle technology, known as AV 2.0, has emerged, marked by large, unified AI models that can control multiple parts of the vehicle stack, from perception and planning to control. Wayve, a London-based autonomous driving technology company, and a member of NVIDIA's startup accelerator program, is leading the surf. In the latest episode of NVIDIA’s AI Podcast, host Katie Burke Washabaugh spoke with the company’s cofounder and CEO, Alex Kendall, about what AV 2.0 means for the future of self-driving cars. Unlike AV 1.0’s focus on perfecting a vehicle’s perception capabilities using multiple deep neural networks, AV 2.0 calls for comprehensive in-vehicle intelligence to drive decision-making in real-world, dynamic environments. Embodied AI — the concept of giving AI a physical interface to interact with the world — is the basis of this new AV wave. Kendall pointed out that it’s a “hardware/software problem — you need to consider these things separately,” even as they work together. For example, a vehicle can have the highest-quality sensors, but without the right software, the system can’t use them to execute the right decisions. Generative AI plays a key role, enabling synthetic data generation so AV makers can use a model’s previous experiences to create and simulate novel driving scenarios. It can “take crowds of pedestrians and snow and bring them together” to “create a snowy, crowded pedestrian scene” that the vehicle has never experienced before. According to Kendall, that will “play a huge role in both learning and validating the level of performance that we need to deploy these vehicles safely” — all while saving time and costs. In June, Wayve unveiled GAIA-1, a generative world model for developing autonomous vehicles. The company also recently announced LINGO-1, an AI model that allows passengers to use natural language to enhance the learning and explainability of AI driving models. Looking ahead, the company hopes to scale and further develop its solutions, improving the safety of AVs to deliver value, build public trust and meet customer expectations. Kendall views embodied AI as playing a definitive role in the future of the AI landscape, pushing pioneers to “build better” and “build further” to achieve the “next big breakthroughs.” For more on NVIDIA's Inception startup accelerator program, visit https://www.nvidia.com/en-us/startups/

Talk about going after low-hanging fruit. Afresh is an AI startup that helps grocery stores and retailers reduce food waste by making supply chains more efficient. In the latest episode of NVIDIA’s AI Podcast, host Noah Kravitz spoke with the company’s cofounder and president, Nathan Fenner, about its mission, offerings and the greater challenge of eliminating food waste. Most supply chain and inventory management offerings targeting grocers and retailers are outdated. Fenner and his team noticed those solutions, built for the nonperishable side of the business, didn’t work as well on the fresh side — creating enormous amounts of food waste and causing billions in lost profits. The team first sought to solve the store-replenishment challenge by developing a platform to help grocers decide how much fresh produce to order to optimize costs while meeting demand. They created machine learning and AI models that could effectively use the data generated by fresh produce, which is messier than data generated by nonperishable goods because of factors like time to decay, greater demand fluctuation and unreliability caused by lack of barcodes, leading to incorrect scans at self-checkout registers. The result was a fully integrated, machine learning-based platform that helps grocers make informed decisions at each node of the operations process. The company also recently launched inventory management software that allows grocers to save time and increase data accuracy by intelligently tracking inventory. That information can be inputted back into the platform’s ordering solution, further refining the accuracy of inventory data. It’s all part of Afresh’s greater mission to tackle climate change. “The most impactful thing we can do is reduce food waste to mitigate climate change,” Fenner said. “It’s really one of the key things that brought me into the business: I think I’ve always had a keen eye to work in the climate space. It’s really motivating for a lot of our team, and it’s a key part of our mission.”

Clinician-led healthcare AI company Harrison.ai has built an AI system that serves as “spell checker” for radiologists — flagging critical findings to improve the speed and accuracy of radiology image analysis, reducing misdiagnoses. In the latest episode of NVIDIA’s AI Podcast, host Noah Kravitz spoke with Harrison.ai CEO and cofounder Aengus Tran about the company’s mission to scale global healthcare capacity with autonomous AI systems. Harrison.ai’s initial product, annalise.ai, is an AI tool that automates radiology image analysis to enable faster, more accurate diagnoses. It can produce 124-130 different possible diagnoses and flag key findings to aid radiologists in their final diagnosis. Currently, annalise.ai works for chest X-rays and brain CT scans. While an AI designed for categorizing traffic lights, for example, doesn’t need perfection, medical tools must be highly accurate — any oversight could be fatal. To overcome this challenge, annalise.ai was trained on millions of meticulously annotated images — some were annotated three to five times over before being used for training. Harrison.ai is also developing Franklin.ai, a sibling AI tool aimed to accelerate and improve the accuracy of histopathology diagnosis — in which a clinician performs a biopsy and inspects the tissue for the presence of cancerous cells. Similarly to annalise.ai, Franklin.ai flags critical findings to assist pathologists in speeding and increasing the accuracy of diagnoses. Ethical concerns about AI use are ever-rising, but for Tran, the concern is less about whether it’s ethical to use AI for medical diagnosis but “actually the converse: Is it ethical to not use AI for medical diagnosis,” especially if “humans using those AI systems simply pick up more misdiagnosis, pick up more cancer and conditions?” Tran also talked about the future of AI systems and suggested that the focus is dual: first, focus on improving preexisting systems and then think of new cutting-edge solutions. And for those looking to break into careers in AI and healthcare, Tran says that the “first step is to decide upfront what problems you’re willing to spend a huge part of your time solving first, before the AI part,” emphasizing that the “first thing is actually to fall in love with some problem.”

Generative AI and large language models (LLMs) are stirring change across industries — but according to NVIDIA Senior Product Manager of Developer Marketing Annamalai Chockalingam, “we’re still in the early innings.” In the latest episode of NVIDIA’s AI Podcast, host Noah Kravitz spoke with Chockalingam about LLMs: what they are, their current state and their future potential. LLMs are a “subset of the larger generative AI movement” that deals with language. They’re deep learning algorithms that can recognize, summarize, translate, predict and generate language. AI has been around for a while, but according to Chockalingam, three key factors enabled LLMs. One is the availability of large-scale data sets to train models with. As more people used the internet, more data became available for use. The second is the development of computer infrastructure, which has become advanced enough to handle “mountains of data” in a “reasonable timeframe.” And the third is advancements in AI algorithms, allowing for non-sequential or parallel processing of large data pools. LLMs can do five things with language: generate, summarize, translate, instruct or chat. With a combination of “these modalities and actions, you can build applications” to solve any problem, Chockalingam said. Enterprises are tapping LLMs to “drive innovation,” “develop new customer experiences,” and gain a “competitive advantage.” They’re also exploring what safe deployment of those models looks like, aiming to achieve responsible development, trustworthiness and repeatability. New techniques like retrieval augmented generation (RAG) could boost LLM development. RAG involves feeding models with up-to-date “data sources or third-party APIs” to achieve “more appropriate responses” — granting them current context so that they can “generate better” answers. Chockalingam encourages those interested in LLMs to “get your hands dirty and get started” — whether that means using popular applications like ChatGPT or playing with pretrained models in the NVIDIA NGC catalog. NVIDIA offers a full-stack computing platform for developers and enterprises experimenting with LLMs, with an ecosystem of over 4 million developers and 1,600 generative AI organizations. To learn more, register for LLM Developer Day on Nov. 17 to hear from NVIDIA experts about how best to develop applications.

Artificial intelligence is now a household term. Responsible AI is hot on its heels. Julia Stoyanovich, associate professor of computer science and engineering at NYU and director of the university’s Center for Responsible AI, wants to make the terms “AI” and “responsible AI” synonymous. In the latest episode of the NVIDIA AI Podcast, host Noah Kravitz ‌spoke with Stoyanovich about responsible AI, her advocacy efforts and how people can help.

For NVIDIA Senior AI Scientist Jim Fan, the video game Minecraft served as the “perfect primordial soup” for his research on open-ended AI agents. In the latest AI Podcast episode, host Noah Kravitz spoke with Fan on using large language models to create AI agents — specifically to create Voyager, an AI bot built with Chat GPT-4 that can autonomously play Minecraft. AI agents are models that “can proactively take actions and then perceive the world, see the consequences of its actions, and then improve itself,” Fan said. Many current AI agents are programmed to achieve specific objectives, such as beating a game as quickly as possible or answering a question. They can work autonomously toward a particular output but lack a broader decision-making agency. Fan wondered if it was possible to have a “truly open-ended agent that can be prompted by arbitrary natural language to do open-ended, even creative things.” But he needed a flexible playground in which to test that possibility. “And that’s why we found Minecraft to be almost a perfect primordial soup for open-ended agents to emerge, because it sets up the environment so well,” he said. Minecraft at its core, after all, doesn’t set a specific key objective for players other than to survive and freely explore the open world. That became the springboard for Fan’s project, MineDojo, which eventually led to the creation of the AI bot Voyager. “Voyager leverages the power of Chat GPT-4 to write code in Javascript to execute in the game,” Fan explained. “GPT-4 then looks at the output, and if there’s an error from JavaScript or some feedback from the environment, GPT-4 does a self-reflection and tries to debug the code.” The bot learns from its mistakes and stores the correctly implemented programs in a skill library for future use, allowing for “lifelong learning.” In-game, Voyager can autonomously explore for hours, adapting its decisions based on its environment and developing skills to combat monsters and find food when needed. “We see all these behaviors come from the Voyager setup, the skill library and also the coding mechanism,” Fan explained. “We did not preprogram any of these behaviors.” He then spoke more generally about the rise and trajectory of LLMs. He foresees strong applications in software, gaming and robotics and increasingly pressing conversations surrounding AI safety. Fan encourages those looking to get involved and work with LLMs to “just do something,” whether that means using online resources or experimenting with beginner-friendly, CPU-based AI models.

Generative AI-based models can not only learn and understand natural languages — they can learn the very language of nature itself, presenting new possibilities for scientific research. Anima Anandkumar, Bren Professor at Caltech and senior director of AI research at NVIDIA, was recently invited to speak at the President’s Council of Advisors on Science and Technology. At the talk, Anandkumar says that generative AI was described as “an inflection point in our lives,” with discussions swirling around how to “harness it to benefit society and humanity through scientific applications.” On the latest episode of NVIDIA’s AI Podcast, host Noah Kravitz spoke with Anandkumar on generative AI’s potential to make splashes in the scientific community. It can, for example, be fed DNA, RNA, viral and bacterial data to craft a model that understands the language of genomes. That model can help predict dangerous coronavirus variants to accelerate drug and vaccine research. Generative AI can also predict extreme weather events like hurricanes or heat waves. Even with an AI boost, trying to predict natural events is challenging because of the sheer number of variables and unknowns. However, Anandkumar explains that it’s not just a matter of upsizing language models or adding compute power — it’s also about fine-tuning and setting the right parameters. “Those are the aspects we’re working on at NVIDIA and Caltech, in collaboration with many other organizations, to say, ‘How do we capture the multitude of scales present in the natural world?’” she said. “With the limited data we have, can we hope to extrapolate to finer scales? Can we hope to embed the right constraints and come up with physically valid predictions that make a big impact?” Anandkumar adds that to ensure AI models are responsibly and safely used, existing laws must be strengthened to prevent dangerous downstream applications. She also talks about the AI boom, which is transforming the role of humans across industries, and problems yet to be solved. “This is the research advice I give to everyone: the most important thing is the question, not the answer,” she said.

In the global entertainment landscape, TV show and film production stretches far beyond Hollywood or Bollywood — it's a worldwide phenomenon. However, while streaming platforms have broadened the reach of content, dubbing and translation technology still has plenty of room for growth. Deepdub acts as a digital bridge, providing access to content by using generative AI to break down language and cultural barriers. On the latest episode of NVIDIA’s AI Podcast, host Noah Kravitz spoke with the Israel-based startup’s co-founder and CEO, Ofir Krakowski. Deepdub uses AI-driven dubbing to help entertainment companies boost efficiency and cut costs while increasing accessibility. The company is a member of NVIDIA Inception, a free program that offers startups go-to-market support, expertise and technological assistance. Traditional dubbing is slow, costly and often missing the mark, Krakowski says. Current technology struggles with the subtleties of language, leaving jokes, idioms or jargon lost in translation. Deepdub offers a web-based platform that enables people to interact with sophisticated AI models to handle each part of the translation and dubbing process efficiently. It translates the text, generates a voice and mixes it into the original music and audio effects. But as Krakowkski points out, even the best AI models make mistakes, so the platform involves a human touchpoint to verify translations and ensure that generated voices sound natural and capture the right emotion. Deepdub is also working on matching lip movements to dubbed voices. Ultimately, Krakowski hopes to free the world from the restrictions placed by language barriers. “I believe that the technology will enable people to enjoy the content that is created around the world,” he said. “It will globalize storytelling and knowledge, which are currently bound by language barriers.” https://blogs.nvidia.com/blog/2023/08/30/deepdub/

Replit aims to empower the next billion software creators. In this week’s episode of NVIDIA’s AI Podcast, host Noah Kraviz dives into a conversation with Replit CEO Amjad Masad. Masad says the San Francisco-based maker of a software development platform, which came up as a member of NVIDIA’s startup accelerator program, wants to bridge the gap between ideas and software, a task simplified by advances in generative AI. “Replit is fundamentally about reducing the friction between an idea and a software product,” Masad said. The company’s Ghostwriter coding AI has two main features: a code completion model and a chat model. These features not only make suggestions as users type their code, but also provide intelligent explanations of what a piece of code is doing, tracing dependencies and context. The model can even flag errors and offers solutions — like a full collaborator in a Google Docs for code. The company is also developing “make me an app” functionality. This tool allows users to provide high-level instructions to an Artificial Developer Intelligence, which then builds, tests and iterates the requested software. The aim is to make software creation accessible to all, even those with no coding experience. While this feature is still under development, Masad said the company plans to improve it over the next year, potentially having it ready for developers in the next 6 to 8 months. Going forward, Masad envisions a future where AI functions as a collaborator, able to conduct high-level tasks and even manage resources. “We're entering a period where software is going to feel more alive,” Masad said. “And so I think computing is becoming more humane, more accessible, more exciting, more natural.” For more on NVIDIA’s startup accelerator program, visit https://www.nvidia.com/en-us/startups/

The world increasingly runs on code. Accelerating the work of those who create that code will boost their productivity — and that’s just what AI startup Codeium, a member of NVIDIA’s Inception program for startups, aims to do. On the latest episode of NVIDIA’s AI Podcast, host Noah Kravitz interviewed Codeium founder and CEO Varun Mohan and Jeff Wang, the company’s head of business, about the company's business, about how AI is transforming software. Codeium's AI-powered code acceleration toolkit boasts three core features: autocomplete, chat and search. Autocomplete intelligently suggests code segments, saving developers time by minimizing the need for writing boilerplate or unit tests. At the same time the chat function empowers developers to rework or even create code with natural language queries, enhancing their coding efficiency while providing searchable context on the entire code base. Noah spoke with Mohan and Wang about the future of software development with AI, and the continued, essential role of humans in the process.

Startup MosaicML is on a mission to help the AI community enhance prediction accuracy, decrease costs, and save time by providing tools for easy training and deployment of large AI models. In this episode of NVIDIA's AI Podcast, host Noah Kravitz speaks with MosaicML CEO and co-founder Naveen Rao, about how the company aims to democratize access to large language models. MosaicML, a member of NVIDIA's Inception program, has identified two key barriers to widespread adoption: the difficulty of coordinating a large number of GPUs to train a model and the costs associated with this process. Making training of models accessible is key for many companies who need to control over model behavior, respect data privacy, and iterate fast to develop new products based on AI.

Scientists at Matice Biosciences are using AI to study the regeneration of tissues in animals known as super-regenerators, such as salamanders and planarians. The goal of the research is to develop new treatments that will help humans heal from injuries without scarring. On the latest episode of NVIDIA’s AI Podcast, host Noah Kravtiz spoke with Jessica Whited, a regenerative biologist at Harvard University and co-founder of Matice Biosciences. https://blogs.nvidia.com/blog/2023/06/21/matice/

In the latest episode of NVIDIA's AI Podcast, Anant Agarwal, founder of edX and Chief Platform Officer at 2U, shared his vision for the future of online education and the impact of artificial intelligence in revolutionizing the learning experience. Agarwal, a strong advocate for Massive Open Online Courses MOOCs, discussed the importance of accessibility and quality in education. The MIT professor and renowned edtech pioneer also highlighted the implementation of AI-powered features in the edX platform, including the ChatGPT plugin and edX Xpert, an AI-powered learning assistant.

In this episode of the NVIDIA AI Podcast, host Noah Kravitz dives into an illuminating conversation with Alex Fielding, co-founder and CEO of Privateer Space. Fielding is a tech industry veteran, having previously worked alongside Apple co-founder Steve Wozniak on several projects, and holds a deep expertise in engineering, robotics, machine learning and AI. Privateer Space, Fielding’s latest venture, aims to address one of the most daunting challenges facing our world today: space debris. The company is creating a data infrastructure to monitor and clean up space debris, ensuring sustainable growth for the budding space economy. In essence, they’re the sanitation engineers of the cosmos. Privateer is also focused on bolstering space accessibility. All of the company’s datasets and those of its partners are being made available through APIs, so users can more easily build space applications related to Earth observation, climate science and more. Privateer Space is a part of NVIDIA Inception, a free program that offers go-to-market support, expertise and technology for AI startups. During the podcast, Fielding shares the genesis of Privateer Space, his journey from Apple to the space industry, and his subsequent work on communication between satellites at different altitudes. He also addresses the severity of space debris, explaining how every launch adds more debris, including minute yet potentially dangerous fragments like frozen propellant and paint chips. https://blogs.nvidia.com/blog/2023/05/23/privateer-space

Artificial intelligence is teaming up with crowdsourcing to improve the thermo-stability of mRNA vaccines, making distribution more accessible worldwide. In this episode of NVIDIA's AI podcast, host Noah Kravitz interviewed Bojan Tunguz, a physicist and senior system software engineer at NVIDIA, and Johnny Israeli, senior manager of AI and cloud software at NVIDIA. The guests delved into AI's potential in drug discovery and the Stanford Open Vaccine competition, a machine-learning contest using crowdsourcing to tackle the thermo-stability challenges of mRNA vaccines. Kaggle, the online machine learning competition platform, hosted the Stanford Open Vaccine competition. Tunguz, a quadruple Kaggle grandmaster, shared how Kaggle has grown to encompass not just competitions, but also datasets, code, and discussions. Competitors can earn points, rankings, and status achievements across these four areas. The fusion of artificial intelligence, crowdsourcing, and machine learning competitions is opening new possibilities in drug discovery and vaccine distribution. By tapping into the collective wisdom and skills of participants worldwide, it becomes possible to solve pressing global problems, such as enhancing the thermo-stability of mRNA vaccines, allowing for a more efficient and widely accessible distribution process. Don't miss this enlightening conversation on the transformative power of AI and crowdsourcing in mRNA vaccine distribution.

Imagine a future where your vehicle's interior offers personalized experiences and builds trust through human-machine interfaces and artificial intelligence. In this episode of the NVIDIA AI Podcast, host Katie Burke Washabaugh and guest Andreas Binner, Chief Technology Officer at Rightware, delve into this fascinating topic. Rightware is a company at the forefront of developing in-vehicle HMI. Their platform, Kanzi, works in tandem with NVIDIA DRIVE IX to provide a complete toolchain for designing personalized vehicle interiors for the next generation of transportation, including detailed visualizations of the car's AI. Andreas touches on his journey into automotive technology and HMI, the evolution of infotainment in the automotive industry over the past decade, and surprising trends in HMI. They explore the influence of AI on HMI, novel AI-enabled features, and the importance of trust in new technologies. Other topics include the role of HMI in fostering trust between vehicle occupants and the vehicle, the implications of autonomous vehicle visualization, balancing larger in-vehicle screens with driver distraction risks, additional features for trust-building between autonomous vehicles and passengers, and predictions for intelligent cockpits in the next decade. Learn about the innovations that Rightware's Kanzi platform and NVIDIA DRIVE IX bring to the automotive industry and how they contribute to the development of intelligent vehicle interiors. Tune in.

Imagine a stroller that can drive itself, help users up hills, brake on slopes and provide alerts of potential hazards. That’s what GlüxKind has done with Ella, an award-winning smart stroller that uses the NVIDIA Jetson edge AI and robotics platform to power its AI features. Kevin Huang and Anne Hunger are the co-founders of GlüxKind, a Vancouver-based startup that aims to make parenting easier with AI. They’re also married and have a child together who inspired them to create Ella. In this episode of the NVIDIA AI Podcast, host Noah Kravitz talks to Huang and Hunger about their journey from being consumers looking for a better stroller to becoming entrepreneurs who built one. They discuss how NVIDIA Jetson enables Ella’s self-driving capabilities, object detection, voice control and other features that make it stand out from other strollers. The pair also share their vision for the future of smart baby gear and how they hope to improve the lives of parents and caregivers around the world.

Tools like ChatGPT have awakened the world to the potential of generative AI. Now, much more is coming. On the latest episode of NVIDIA’s AI Podcast, Yves Jacquier, executive director of Ubisoft La Forge, shares valuable insights into the transformative potential of generative AI in the gaming industry. With over two decades of experience in technology innovation, science and R&D management across various sectors, Jacquier’s comprehensive expertise makes him a true visionary in the field. During his conversation with podcast host Noah Kravitz, Jacquier highlighted how generative AI, which enables computers to create unique content such as images, text and music, is already revolutionizing the gaming sector. By designing new levels, characters and items, and generating realistic graphics and soundscapes, this cutting-edge technology offers countless opportunities for more immersive and engaging experiences. As the driving force behind Ubisoft La Forge, Jacquier plays a crucial role in shaping the company’s academic R&D strategy. Key milestones include establishing a chair in AI deep learning in 2011 and founding Ubisoft La Forge, the first lab in the gaming industry dedicated to applied academic research — research that’s being translated into state-of-the-art gaming experiences.

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/

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.

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.

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/

Can machines experience emotions? They might, according to Hume AI, an AI research lab and technology company that aims to “ensure artificial intelligence is built to serve human goals and emotional well-being.” So how can AI genuinely understand how we are feeling, and respond appropriately? On this episode of NVIDIA’s AI Podcast, host Noah Kravitz spoke with Alan Cowen, founder of Hume AI and The Hume Initiative. Cowen — a former researcher at Google who holds a Ph.D. in Psychology from UC Berkeley — talks about the latest work at the intersection of computing and human emotion.

Teaching the AI brains of autonomous vehicles to understand the world as humans do requires billions of miles of driving experience. The road to achieving this astronomical level of driving leads to the virtual world. On the latest episode of the AI Podcast, Waabi CEO and founder Raquel Urtasun joins NVIDIA’s Katie Burke Washabaugh to talk about the role simulation technology plays in developing production-level autonomous vehicles. Waabi is an autonomous-vehicle system startup that uses powerful, high-fidelity simulation to run multiple scenarios simultaneously and tailor training to rare and dangerous situations that are difficult to encounter in the real world. Urtasun is also a professor of Computer Science at the University of Toronto. Before starting Waabi, she led the Uber Advanced Technologies Group as chief scientist and head of research and development.

Entrepreneur Jason Mars calls conversation our “first technology.” Before humans invented the wheel, crafted a spear or tamed fire, we mastered the superpower of talking to one another. That makes conversation an incredibly important tool. But if you’ve dealt with the automated chatbots deployed by the customer service arms of just about any big organization lately — whether banks or airlines — you also know how hard it can be to get it right. Deep learning AI and new techniques such as zero-shot learning promise to change that. On this episode of NVIDIA’s AI Podcast, host Noah Kravitz — whose intelligence is anything but artificial — spoke with Mars about how the latest AI techniques intersect with the very ancient art of conversation. In addition to being an entrepreneur and CEO of several startups, including Zero Shot Bot, Mars is an associate professor of computer science at the University of Michigan and the author of “Breaking Bots: Inventing a New Voice in the AI Revolution” (ForbesBooks, 2021).

In deep learning and machine learning, having a large enough dataset is key to training a system and getting it to produce results. So what does a ML researcher do when there just isn’t enough publicly accessible data? Enter the MLCommons Association, a global engineering consortium with the aim of making ML better for everyone. MLCommons recently announced the general availability of the People’s Speech Dataset, a 30,000 hour English-language conversational speech dataset, and the Multilingual Spoken Words Corpus, an audio speech dataset with over 340,000 keywords in 50 languages, to help advance ML research. On this episode of NVIDIA’s AI Podcast, host Noah Kravitz spoke with David Kanter, founder and executive director of MLCommons, and NVIDIA senior AI developer technology engineer Daniel Galvez, about the democratization of access to speech technology and how ML Commons is helping advance the research and development of machine learning for everyone. https://blogs.nvidia.com/blog/2022/04/13/mlcommons/

Polestar Chief Operating Officer Dennis Nobelius sees driving enjoyment and autonomous-driving capabilities complementing one another in sustainable vehicles that keep driving — and the driver — front and center. NVIDIA’s Katie Washabaugh spoke with Nobelius for the latest episode of the AI Podcast about the role the performance brand will play as vehicles become greener and more autonomous. Nobelius touched on the sustainable automaker’s plans to unveil its third vehicle, the Polestar 3, the tech inside it, and what the company’s racing heritage brings to the intersection of smarts and sustainability.

Sometimes AI models fail, just like everything else in the world fails sometimes. That's where today's guest comes in. Yaron Singer is co- founder and CEO of Robust Intelligence, a company founded in 2019, out of research Singer was doing in his other job, as the Gordon McKay Professor of Computer Science and Applied Mathematics at Harvard University. Robust Intelligence, RI, for short, has developed a sort of AI firewall that wraps around a company's AI models to protects them from making mistakes, by constantly stress=testing these models. If you're not familiar with AI, stress walls and are wondering how an AI firewall can be a thing Yaron is here to tell us all about it.

The very thing that makes the internet so useful to so many people — the vast quantity of information that’s out there — can also make going online frustrating. There’s so much available that the sheer volume of choices can be overwhelming. That’s where recommender systems come in, explains NVIDIA AI Podcast host Noah Kravitz. To dig into how recommender systems work — and why these systems are being harnessed by companies in industries around the globe — Kravitz spoke to Even Oldridge, senior manager for the Merlin team at NVIDIA. https://blogs.nvidia.com/blog/2022/03/02/whats-a-recommender-system-2/

It would be an exaggeration to say you’ll never again read a news article overhyping a medical breakthrough. But, thanks to researchers at the University of Copenhagen, spotting hyperbole may one day get more manageable. In a paper, Dustin Wright and Isabelle Augenstein explain how they used NVIDIA GPUs to train an “exaggeration detection system” to identify overenthusiastic claims in health science reporting. The paper comes amid a pandemic that has fueled demand for understandable, accurate information. And social media has made health misinformation more widespread. Research like Wright and Augenstein’s could speed more precise health sciences news to more people. We spoke with Wright about his work. https://blogs.nvidia.com/blog/2022/2/16/exaggeration-detector-podcast/

Autonomous driving has evolved from science fiction to technology that is actively deployed on roads today. Sarah Tariq, vice president of autonomous driving software at NVIDIA, has been a key player in this transition. She worked on the ground floor of autonomous vehicle development at both NVIDIA and robotaxi company Zoox, and is now developing solutions for the coming generation of software-defined vehicles. Tariq is working to redefine how the world views personal transportation, transforming it into an experience that surprises and delights. She spoke with NVIDIA AI Podcast host Katie Washabaugh about her decade in AV development, the many ways in which software can improve mobility and what’s on the road ahead for intelligent transportation. https://blogs.nvidia.com/blog/2022/02/09/sarah-tariq-software-defined-vehicles

From active noise cancellation to digital assistants that are always listening for your commands, audio is perhaps one of the most important but often overlooked aspects of modern technology in our daily lives. Audio Analytic has been using machine learning that enables a vast array of devices to make sense of the world of sound. We spoke with Dr. Chris Mitchell, CEO and founder of Audio Analytic about the challenges, and the fun, involved in teaching machines to listen.

Browse through MORF Gallery — virtually or at an in-person exhibition — and you’ll find robots that paint, digital dreamscape experiences, and fine art brought to life by visual effects. The gallery showcases cutting-edge, one-of-a-kind artwork from award-winning artists who fuse their creative skills with AI, machine learning, robotics and neuroscience. Scott Birnbaum, CEO and co-founder of MORF Gallery, a Silicon Valley startup, spoke with NVIDIA AI Podcast host Noah Kravitz about digital art, non-fungible tokens, as well as ArtStick, a plug-in device that turns any TV into a premium digital art gallery. https://blogs.nvidia.com/blog/2022/01/19/morf-gallery-ceo-scott-birnbaum/

Fewer than 4,000 tigers remain worldwide, according to Tigers United, a university consortium that recently began using AI to help save the species. Jeremy Dertien is a conservation biologist with Tigers United and a Ph.D. candidate in wildlife biology and conservation planning at Clemson University. He spoke with NVIDIA AI Podcast host Noah Kravitz about a project deploying AI-equipped cameras to monitor poaching in central India, where more than 70 percent of the remaining tiger populations reside. https://blogs.nvidia.com/blog/2021/11/18/jeremy-dertien-tigers-united/

What started as Nick Walton’s college hackathon project grew into AI Dungeon, a popular text adventure game with over 1.5 million users. Walton is the co-founder and CEO of Latitude, a Utah-based startup that uses AI to create unique gaming storylines. He spoke with NVIDIA AI Podcast host Noah Kravitz about how natural language processing methods can generate infinite open-ended adventure plots for interactive games like AI Dungeon, which draws an average of 150,000 new players each month. https://blogs.nvidia.com/blog/2021/01/05/nick-walton-ai-podcast/

One of AI’s greatest champions has turned to fiction to answer the question: how will technology shape our world in the next 20 years? Kai-Fu Lee, CEO of Sinovation Ventures and a former president of Google China, spoke with NVIDIA AI Podcast host Noah Kravitz about AI 2041: Ten Visions for Our Future. The book, his fourth available in the U.S. and first work of fiction, was in collaboration with Chinese sci-fi writer Chen Qiufan, also known as Stanley Chan. Lee and Chan blend their expertise in scientific forecasting and speculative fiction in this collection of short stories, which was published in September. Among Lee’s books is the New York Times bestseller AI Superpowers: China, Silicon Valley, and the New World Order, which he spoke about on a 2018 episode of the AI Podcast. https://blogs.nvidia.com/blog/2021/12/15/kai-fu-lee-ai-2041/

Leonardo da Vinci’s portrait of Jesus, known as Salvator Mundi, was sold at a British auction for nearly half a billion dollars in 2017, making it the most expensive painting ever to change hands. However, even art history experts were skeptical about whether the work was an original of the master rather than one of his many protégés. Steven Frank is a partner at the law firm Morgan Lewis, specializing in intellectual property and commercial technology law. He’s also half of the husband-wife team that used convolutional neural networks to determine that this painting was likely an authentic da Vinci. He spoke with NVIDIA AI Podcast host Noah Kravitz about working with his wife, Andrea Frank, a professional curator of art images, to authenticate artistic masterpieces with AI’s help. https://blogs.nvidia.com/blog/2021/12/01/steven-frank-ai-art/

‌Moondust‌,‌ ‌minerals‌ ‌and‌ ‌soil‌ ‌types‌ ‌are‌ ‌just‌ ‌some‌ ‌of‌ ‌the‌ ‌materials‌ ‌that‌ ‌can‌ ‌be‌ ‌quickly‌ ‌identified‌ ‌and‌ ‌analyzed‌ ‌with‌ ‌AI‌,‌‌ ‌based‌ ‌on‌ ‌images‌ ‌of‌ ‌them.‌ ‌ ‌ ‌ Migel‌ ‌Tissera‌ ‌is‌ ‌co-founder‌ ‌and‌ ‌CTO‌ ‌of‌ ‌Metaspectral,‌ ‌a‌ ‌Vancouver-based‌ ‌startup‌ ‌that‌ ‌provides‌ ‌an‌ ‌AI-based‌ ‌data‌ ‌management‌ ‌and‌ ‌analysis‌ ‌platform‌ ‌for‌ ‌ultra-high-resolution‌ ‌images.‌ ‌ ‌ He‌ ‌spoke‌ ‌with‌ ‌‌NVIDIA‌ ‌AI‌ ‌Podcast‌‌ ‌host‌ ‌Noah‌ ‌Kravitz‌ ‌about‌ ‌how‌ ‌Metaspectral’s‌ ‌technologies‌ ‌help‌ ‌space‌ ‌explorers‌ ‌make‌ ‌quicker‌ ‌and‌ ‌better‌ ‌use‌ ‌of‌ ‌the‌ ‌massive‌ ‌amounts‌ ‌of‌ ‌image‌ ‌data‌ ‌they‌ ‌collect‌ ‌out‌ ‌in‌ ‌the‌ ‌cosmos.‌ ‌ ‌ In‌ ‌addition‌ ‌to‌ ‌space,‌ ‌the‌ ‌startup’s‌ ‌platform‌ ‌is‌ ‌used‌ ‌across‌ ‌industries‌ ‌such‌ ‌as‌ ‌agriculture,‌ ‌forensics‌ ‌and‌ ‌recycling.‌ ‌ Show notes: https://blogs.nvidia.com/blog/2021/11/03/migel-tissera/

The more advanced modern technologies become, the more they can help us understand the past. Chris Downum and Leszek Pawlowicz, researchers in the Department of Anthropology at Northern Arizona University, are using GPU-based deep learning algorithms to categorize sherds — tiny fragments of ancient pottery. They spoke with NVIDIA AI Podcast host Noah Kravitz about analyzing sherds to learn more about American Southwest culture, circa 825 to 1300 A.D. https://blogs.nvidia.com/blog/2021/10/20/ai-pottery-anthropology/

Lennon and McCartney. Ashford and Simpson. Many of our all-time favorite tunes have come from songwriting duos. Now, anyone can find a snazzy compositional partner in AI. Maya Ackerman is the CEO of WaveAI, a Silicon Valley startup using AI and machine learning to, as the company motto puts it, “unlock new heights of human creative expression.” She spoke with NVIDIA AI Podcast host Noah Kravitz about WaveAI’s LyricStudio software, an AI-based lyric and poetry writing assistant. https://blogs.nvidia.com/blog/2021/10/06/lyricstudio-ai-podcast/

Endangered species can be difficult to study, as they are elusive, and the very act of observing them can disrupt their lives. Now, scientists can take a closer look at endangered species by studying AI-generated 3D representations of them. Sifei Liu, a senior research scientist at NVIDIA, has worked with her team to create an algorithm that can reconstruct 3D meshes — graphics models used to display the edges, vertices and overall shape of an object — from 2D inputs like images and videos. Liu spoke with NVIDIA AI Podcast host Noah Kravitz about her team’s project, called Online Adaptation for Consistent Mesh Reconstruction in the Wild. Liu and her team have presented the project at various prominent conferences, including NeurIPS 2020.

Machines have long played games - think of Deep Blue or AlphaGo. Now they're building them. GANTheftAuto creator Harrison Kinsley talks about his creation on the latest episode of the AI Podcast. https://blogs.nvidia.com/blog/2021/09/08/gantheftauto/

At GE Renewable Energy, CTO Danielle Merfeld and technical leader Arvind Rangarajan are among those making advances throughout renewable energy. Merfeld and Rangarajan spoke with NVIDIA AI Podcast host Noah Kravitz about how the company uses AI and a human-in-the-loop process to make renewable energy more widespread. The International Energy Agency has set a goal to reach a net zero energy sector by 2050. To reach this goal, 88 percent of electricity needs to come from renewable sources. Wind energy will account for 40 percent of that, but today only makes up 8 percent of renewable energy. https://blogs.nvidia.com/blog/2021/08/25/ge-ai-energy/

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/

Drawing on his trifecta of degrees in math, music and music technology, Tlacael Esparza, co-founder and CTO of Sunhouse, is revolutionizing electronic drumming. Esparza has created Sensory Percussion, a combination of hardware and software that uses sensors and AI to allow a single drum to produce a complex range of sounds depending on where and how the musician hits it. In the latest installment of the NVIDIA AI Podcast, Esparza spoke with host Noah Kravitz about the tech behind the tool, and what inspired him to create Sunhouse. Esparza has been doing drumstick tricks of his own for many years — prior to founding Sunhouse, he toured with a variety of bands and recorded drums for many albums. Esparza’s musical skill and programming knowledge formed the basis for Sensory Percussion. Partnering with his brother, Tenoch, and with support from a New York University startup accelerator, Sunhouse was born in 2014. Since then, it’s become successful with live performers. Esparza is especially proud of its popularity in the New York jazz community and among drumming legends like Marcus Gilmore and Wilco’s Glenn Kotche. https://blogs.nvidia.com/blog/2021/03/31/sunhouse-tlacael-esparza/

Call it Moneyball for AI. In his just released book, "Genius Makers," New York Times writer Cade Metz tells the funny, inspiring — and ultimately triumphant — tale of how a dogged group of AI researchers bet their careers on the long-dismissed technology of deep learning. https://blogs.nvidia.com/blog/2021/03/17/ai-cade-metz

Since NVIDIA announced construction of the U.K.’s most powerful supercomputer — Cambridge-1 — Marc Hamilton, vice president of solutions architecture and engineering, has been (remotely) overseeing its building across the pond. Cambridge-1, which will be available for U.K. healthcare researchers to work on pressing problems, is being built on NVIDIA DGX SuperPOD architecture for a whopping 400 petaflops of AI performance. Located at KAO Data, a data center using 100% renewable energy, Cambridge-1 will rank among the world’s top 3 most energy-efficient supercomputers on the current Green500 list. Hamilton points to the concentration of leading healthcare companies in the U.K. as a primary reason for Cambridge-1’s location. AstraZeneca, GSK, Oxford Nanopore and more have already announced their intent to harness the supercomputer for research in the coming months.

Pooja Rao, a doctor, data scientist and entrepreneur, wants to make cutting-edge medical care available to communities around the world, regardless of their resources. Her startup, Qure.ai, is doing exactly that, with technology that’s used in 150+ healthcare facilities in 27 countries. Rao is the cofounder and head of research and development at the Mumbai-based company, which started in 2016. The company develops AI technology that interprets medical images, with a focus on pulmonary and neurological scans. https://blogs.nvidia.com/blog/2021/02/18/pooja-rao-qure-ai/

Not many can claim to be a computer programmer, nonfiction author and poet, but Brian Christian has established himself as all three. Christian has just released his newest book, The Alignment Problem, which delves into the disparity that occurs when AI models don’t do exactly what they’re intended to do. The book follows on the success of Christian’s previous work, "The Most Human Human and Algorithms to Live By." Now a visiting scholar at UC Berkeley, Christian joined AI Podcast host Noah Kravitz to talk about the alignment problem and some new techniques being used to address the issue. The alignment problem can be caused by a range of reasons — such as data bias, or datasets used incorrectly and out of context. As AI takes on a variety of tasks, from medical diagnostics to parole sentencing decisions, machine learning researchers are expressing concern over the problem. Listen to the full podcast to hear about this and more — including Christian’s book club experience with Elon Musk and why he chose to double major in philosophy and computer science.

Sam Liang is making things easier for the creators of the NVIDIA AI Podcast — and just about every remote worker. He’s the CEO and co-founder of Otter.ai, which uses AI to produce speech-to-text transcriptions in real time or from recording uploads. The platform has a range of capabilities, from differentiating between multiple people, to understanding accents, to parsing through various background noises. And now, Otter.ai is making live captioning possible on a variety of platforms, including Zoom, Skype and Microsoft Teams. Even Liang’s conversation with AI Podcast host Noah Kravitz was captioned in real time over Skype. This new capability has been enthusiastically received by remote workers — Liang says that Otter.ai has already transcribed tens of millions of meetings. Liang envisions even more practical effects of Otter.ai’s live captions. The platform can already identify keywords. Soon he thinks it’ll be recognizing action items, helping manage agendas and providing notifications. https://blogs.nvidia.com/blog/2021/01/21/otter-ai-sam-liang/

Canadian high schooler Ana DuCristea has a clever solution for the quarantine blues, as days blur into weeks. Using AI and natural language processing, she programmed an app capable of setting customizable reminders so you won’t miss any important activities, like baking banana bread or whipping up Dalgona coffee. DuCristea, who’s familiar with Python and has taken a variety of online AI courses, set to work on the app after winning a Jetson Nano Developer Kit this summer at AI4ALL, an AI summer camp. She’d long been frustrated with the simplicity of current reminder apps and decided to create her own solution. Using Python and the Nano, DuCristea developed an app in just two months that integrates with mobile and PC messaging program Discord. With the app, users can message a bot on Discord requesting a reminder for a specific task, date and time.

Brendon Cassidy, CTO and chief scientist at Super Hi-Fi, uses AI to give everyone the experience of a radio station tailored to their unique tastes. Super Hi-Fi, an AI startup and member of the NVIDIA Inception program, develops technology that produces smooth transitions, intersperses content meaningfully and adjusts volume and crossfade. Started three years ago, Super Hi-Fi first partnered with iHeartRadio and is now also used by companies such as Peloton and Sonos. Results are showing that users like this personalized approach. Cassidy notes that they tested MagicStitch, one of their tools that eliminates the gap between songs, and found that customers listening with MagicStitch turned on spent 10 percent more time streaming music. https://blogs.nvidia.com/blog/2020/12/23/super-hifi-ai/

Anima Anandkumar is setting a personal record this week with seven of her team’s research papers accepted to NeurIPS 2020. The 34th annual Neural Information Processing Systems conference is taking place virtually from Dec. 6-12. The premier event on neural networks, NeurIPS draws thousands of the world’s best researchers every year. Anandkumar, NVIDIA’s director of machine learning research and Bren professor at CalTech’s CMS Department, joined AI Podcast host Noah Kravitz to talk about what to expect at the conference, and to explain what she sees as the future of AI. https://blogs.nvidia.com/blog/2020/12/09/neurips-nvidia-caltech-anima-anandkumar/

We've got an expert on AI powered translation joining us on the show today. Spence Green is CEO at Lilt, a Silicon Valley based AI-powered enterprise translation software and services company. Lilt's mission is to make more of the world's information accessible to more of the world's people, regardless of where they were born and what language they speak. Spence is here to talk to us about how they're doing it.

Pindar Van Arman, an American artist and roboticist, designs painting robots that explore the differences between human and computational creativity. Since his first system in 2005 he has built multiple artificially-creative multiple robots. The most famous, Cloud Painter, was awarded first place at Robotart 2018. PIndar, his robots, and their work have been featured all over the media, including on NPR, BBC, HBO, Vice, and the documentary "Machine" a film about artificial intelligence. You can see and learn more about Pindar on his website, cloudpainter.com. In fact, unless you're driving, you should go ahead and load it into your browser right now, so you can look at the art you listen to him talk. For more from Pindar Van Arman, check out: http://www.cloudpainter.com http://www.artonomo.us And explore his work on NVIDIA's AI Art Gallery: https://www.nvidia.com/ai-art-gallery/pindar-van-arman

Jeff Herbst is a fixture of the AI startup ecosystem. Which makes sense since he’s the VP of business development at NVIDIA and head of NVIDIA Inception, a virtual accelerator that currently has over 6,000 members in a wide range of industries. Ahead of the GPU Technology Conference, taking place Oct. 5-9, Herbst joined AI Podcast host Noah Kravitz to talk about what opportunities are available to startups at the conference, and how NVIDIA Inception is accelerating startups in every industry. Learn more about NVIDIA Inception at https://www.nvidia.com/en-us/deep-learning-ai/startups/ Follow Jeff Herbst at @jeffatNvdia

Today we're talking graphics, the intersection of AI and graphics specifically. There may be no better guest to talk AI and graphics than our guest today, David Luebke. David is vice president of graphics research at NVIDIA. He co-founded NVIDIA Research in 2006, after eight years on the faculty of the University of Virginia.

It’s a modern television trope – detectives trying to solve a case “enhance” a blurry image, digitally, giving them a crystal clear image of their suspect. Until recently, this was little more than science fiction. Now, however, it’s a key tool for photographers around the world. Topaz Labs pioneered the intersection of deep learning and photo noise reduction. Their sprawling suite of image editing plugins are relied by pro and amateur photographers alike. We spoke with Topaz founder and CTO, Feng “Albert” Yang, to learn where AI and photography are going next.

It's all come full circle. Real-time graphics technology, namely, GPUs, sparked the modern AI boom. Now modern AI, driven by GPUs, is remaking graphics. This episodes guest is Aaron Lefohn, senior director of realtime rendering research at NVIDIA. Aaron's international team of scientists played a key role in founding the field of AI computer graphics. They were the first to bring AI to real-time computer graphics. They invented key technologies that brought ray tracing to real time computer graphics. Now they're at the forefront of combining AI and ray tracing to rapidly increase the realism of real-time graphics.

Hugging Face is more than just an adorable emoji — it’s a company that’s demystifying AI by transforming the latest developments in deep learning into usable code for businesses and researchers. Research engineer Sam Shleifer spoke with AI Podcast host Noah Kravitz about Hugging Face NLP technology, which is in use at over 1,000 companies, including Apple, Bing and Grammarly, across fields ranging from finance to medical technology. Hugging Face’s models serve a variety of purposes for their customers, including autocompletion, customer service automation and translation. Their popular web application, Write with Transformer, can even take half-formed thoughts and suggest options for completion. Shleifer is currently at work developing models that are accessible to everyone, whether they are proficient coders or not. In the next few years, Shleifer envisions the continued growth of smaller NLP models that power a wave of chat apps with state-of-the-art translation capabilities.

Michael Kirk and Raphael Attie, scientists at NASA’s Goddard Space Flight Center, regularly face terabytes of data in their quest to analyze images of the sun. This computational challenge, which could take a year or more on a CPU, has been reduced to less than a week on Quadro RTX data science workstations. Kirk and Attie spoke to AI Podcast host Noah Kravitz about the workflow they follow to study these images, and what they hope to find. The lessons they’ve learned are useful for those in both science and industry grappling with how to best put torrents of data to work.

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.