The AI Podcast

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/

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.

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.”

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/

Autonomous vehicles are one of the most complex AI challenges of our time. The networks running in the car must act as an intricate symphony, requiring intensive training, testing and validation on massive amounts of data to operate safely in the real world. Clément Farabet is the Vice President of AI Infrastructure at NVIDIA, and is the proverbial maestro behind the AV development orchestra. He’s applying nearly 15 years of experience in deep learning — including building Twitter’s AI machine — to teach neural networks how to perceive and react to the world around them. Farabet sat down with NVIDIA’s Katie Burke Washabaugh on the latest episode of the AI Podcast to discuss how the early days of deep learning led to today’s flourishing AV industry, and how he’s approaching DNN development. Tapping into the performance of the NVIDIA SaturnV supercomputer, Farabet is designing a highly scalable data factory to deliver intelligent transportation in the near term, and is looking ahead to the next frontiers in AI.

What if we could map our immune system to create drugs that can help our bodies win the fight against cancer and other diseases? That’s the big idea behind immunotherapy. The problem: the immune system is incredibly complex. Enter Immunai, a biotechnology company that’s using AI technology to map the human immune system and speed the development of new immunotherapies against cancer and autoimmune diseases. On this episode of NVIDIA’s AI Podcast, host Noah Kravitz spoke with Luis Voloch, CTO and Co-Founder of Immunai, about tackling the challenges of the immune system with a machine learning and data science mindset.

AI and electric vehicle technology breakthroughs are transforming the automotive industry. These developments pave the way for new innovators, attracting technical prowess and design philosophies from Silicon Valley. Mike Bell, senior vice president of digital at Lucid Motors, sees continuous innovation coupled with over-the-air updates as key to designing sustainable, award-winning intelligent vehicles that provide seamless automated driving experiences. NVIDIA’s Katie Burke Washabaugh spoke with Bell on the latest AI Podcast episode, covering what it takes to stay ahead in the software-defined vehicle space. Bell touched on future technology and its implications for the mass adoption of sustainable, AI-powered EVs — as well as what Lucid’s Silicon Valley roots bring to the intersection of innovation and transportation. https://blogs.nvidia.com/blog/2022/07/06/lucid-motors-podcast/

Want to learn about AI and machine learning? There are plenty of resources out there to help — blogs, podcasts, YouTube tutorials — perhaps too many. Machine learning engineer Santiago Valdarrama has taken a far more focused approach to helping us all get smarter about the field. He’s created a following by posing one machine learning question every day on his website bnomial.com. Think of it as Wordle for those who want to learn more about machine learning.

It may seem intuitive that AI and deep learning can speed up workflows — including novel drug discovery, a typically years-long and several-billion-dollar endeavor. But professors Artem Cherkasov and Olexandr Isayev were surprised to find that no recent academic papers provided a comprehensive, global research review of how deep learning and GPU-accelerated computing impact drug discovery. In March, they published a paper in Nature to fill this gap, presenting an up-to-date review of the state of the art for GPU-accelerated drug discovery techniques. Cherkasov, a professor in the department of urologic sciences at the University of British Columbia, and Isayev, an assistant professor of chemistry at Carnegie Mellon University, join NVIDIA AI Podcast host Noah Kravitz this week to discuss how GPUs can help democratize drug discovery. In addition, the guests cover their inspiration and process for writing the paper, talk about NVIDIA technologies that are transforming the role of AI in drug discovery, and give tips for adopting new approaches to research.

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

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/

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/

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/

‌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 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.

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

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

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

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

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

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

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

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

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

We brought back one of NVIDIA’s best explainers, Will Ramey, to provide an introduction to today’s AI boom and the key concepts behind it. Ramey, senior director and global head of developer programs at NVIDIA, led a webinar, "Deep Learning Demystified," as part of this year's GTC Digital online conference. https://developer.nvidia.com/gtc/2020/video/s22555

On this episode of the NVIDIA AI Podcast, we interview Stanford Professor Margot Gerritsen about what’s next in data science, the growing role of women in data science, and how data science intersects with modern AI. For more, tune into Professor Gerritsen's Women in Data Science podcast https://www.widsconference.org/podcast.html

Kathy Baxter, the architect of ethical AI practice at Salesforce, is helping her team and clients create more responsible technology. To do so, she supports employee education, the inclusion of safeguards in Salesforce technology, and collaboration with other companies to improve ethical AI across industries.

Matthew Putman, this week’s guest on the AI Podcast, knows that the devil is in the details. That’s why he’s the co-founder and CEO of Nanotronics, a Brooklyn-based company providing precision manufacturing enhanced by AI, automation and 3D imaging.

What John Madden was to pro football, Neda Cvijetic is to autonomous vehicles. No one’s better at explaining the action, in real time, than Cvijetic. Cvijetic, senior manager of autonomous vehicles at NVIDIA, drives our NVIDIA DRIVE Labs series of videos and blogs breaking down the science behind autonomous vehicles.

National Pothole Day is Jan. 15. Its timing is no accident. All over the Northern hemisphere, potholes are at their suspension-wrecking, spine-shaking worst this month. Thanks to AI, one startup is working all year long to alleviate this menace. Benjamin Schmidt, president and co-founder of RoadBotics, is using the tech to pave the way to better roads.

Spell, founded by Serkan Piantino, is making machine learning as easy as ABC. Piantino, CEO of the New York-based startup and former director of engineering for Facebook AI Research, explained to AI Podcast host Noah Kravitz how he’s bringing compute power to those that don’t have easy access to GPU clusters.

You can’t have an AI podcast and not interview someone using AI to make podcasts better. That’s why we reached out to serial entrepreneur Andrew Mason to talk to him about what he’s doing now. His company, Descript Podcast Studio, uses AI, natural language processing and automatic speech synthesis to make podcast editing easier and more collaborative.

At Oracle, customer service chatbots use conversational AI to respond to consumers with more speed and complexity. Suhas Uliyar, vice president of bots, AI and mobile product management at Oracle, stopped by to talk to AI Podcast host Noah Kravitz about how the newest wave of conversational AI can keep up with the nuances of human conversation.

Doina Precup is applying Romanian wisdom to the gender gap in the fields of AI and computer science. The associate professor at McGill University and research team lead at AI startup DeepMind spoke with AI Podcast host Noah Kravitz about her personal experiences, along with the AI4Good Lab she co-founded to give women more access to machine learning training. Growing up in Romania, Precup attended a high school that specialized in computer science and a technical university. She didn’t experience gender disparity in these learning environments. “If anything, programming was considered a very good job for women, because you did not need to be working in the fields,” she explained. It made the gap in Canadian universities and companies even more noticeable. At McGill, Precup saw that female students were hesitant to speak up or pursue graduate studies. Together with Angelique Mannella, CEO of AM Consulting and an Amazon employee, Precup was inspired to start the AI4Good Lab in 2017.

When your appliances break, the last thing you want to do is spend an hour on the phone trying to reach a customer service representative. Using computer vision, Drishyam.AI is eliminating service lines to help consumers more quickly. Satish Mandalika, the CEO and founder of the deep learning-based image recognition platform, spoke with AI Podcast host Noah Kravitz about the company. “Customer support is ripe for disruption,” Mandalika said. Drishyam.AI is changing the game by giving customers an app that they use to take a picture of the product they need help with at any time of day or night, rather than calling a help line. Using computer vision, Drishyam.AI analyzes the issue and communicates directly with manufacturers, rather than going through retail outlets. This is more efficient because a product’s lifetime warranty is usually held by the company that made it, rather than the stores selling it like Home Depot and Lowe’s.

Though creating an autonomous robot that can tidy a room seems like enough of an achievement, Tokyo-based Preferred Networks goes one step further. By integrating natural language processing (NLP) into their technology, their robots respond to commands and adjust their actions. Jun Hatori, a software engineer at Preferred Networks, stopped to talk with AI Podcast host Noah Kravitz about the company’s latest developments.

AI is still young, but software is available to help even relatively unsophisticated users harness it. That’s according to Ian Buck, general manager of NVIDIA’s accelerated computing group, who shared his views in our latest AI Podcast. Buck, who helped lay the foundation for GPU computing as a Stanford doctoral candidate, will deliver the keynote address at GTC DC on Nov. 5. To sign up for GTC DC, visit https://nvda.ws/2Jzg7T1 and use the 'GMPOD' promo code for a 20% discount.

Have you ever wondered what it takes to produce the complex imagery in films like Star Wars or Transformers? The man behind the magic, Colie Wertz, is here to explain. Wertz is a conceptual artist and modeler who works on film, television and video games. He sat down with AI Podcast host Noah Kravitz to explain his specialty in hard modeling, in which he produces digital models of objects with hard surfaces like vehicles, robots and computers. To make these images, Wertz has taken to using AI art tools such as GauGAN, a real-time painting web app that allows users to create realistic landscapes using generative adversarial networks.

In the future imagined by Pinar Yanardag, a postdoctoral research associate at MIT Media Lab, AI will collaborate with humans, not replace them. This is the concept behind her project, “How to Generate (Almost) Anything,” which she created with other students from the MIT Media Lab and professionals in the Boston area. Yanardag sat down with AI Podcast host Noah Kravitz to talk about this project, along with her other new creations.

We’ve all chosen the self-checkout stand over the human cashier, thinking it’ll take less time. But somehow, things take a terrible turn. The barcodes aren’t scanning, there’s a pop-up scolding you for not placing the product in the bagging area (though you did, of course), and an employee is coming over to fix the chaos. It would’ve taken less time to go to the cashier. Focal Systems is applying deep learning and computer vision to automate portions of retail stores in order to streamline store operations and get customers in and out more efficiently, without the pitfalls of the traditional self-checkout. CEO Francois Chaubard sat down with AI Podcast host Noah Kravitz to talk about how the company is changing retailers.

College students are many things — sleepy, overly caffeinated, stressed — but above all, they are hungry. Kiwi Campus is here to help. Co-founder and CEO of Kiwi Campus, Felipe Chávez, joined AI Podcast host Noah Kravitz to talk about Kiwi and its delivery service. Based in Berkeley, Calif., the company specializes in creating a robotic ecosystem for last mile delivery. Its solution is the Kiwibot. The small autonomous robot delivers orders seven days a week from 10 AM to 8 PM. Its coverage area includes UC Berkeley and the surrounding streets.

Charter Communications is working to make customer service smarter even before an operator picks up the phone. Charter Communications, also known as Spectrum, is using AI to improve their customer service and process data more intelligently. Senior Director of Wireless Engineering Jared Ritter took a break from his presentations at GTC Santa Clara to talk to AI Podcast host Noah Kravitz about Charter’s perspective on customer relations.

Artificial intelligence thrives on data, the more the better. But when we’re talking about putting data in many industries, such as health care, to work, things can get very complicated, very quickly. Walter De Brouwer is CEO of Doc.ai, a Silicon Valley based company that’s building a medical research platform that can address this issue with federated learning.

Imagine staring into the high-beams of an oncoming car. Now imagine trying to pick out a speck of dust in the glare of the headlights. That’s the challenge Olivier Guyon and Damien Gratadour face as they try to find the dull glint of an exoplanet — a planet orbiting a star outside our solar system — beside the bright light of its star. The pair -- Guyon is an instrument developer for Japan’s Subaru Telescope, and an astronomer at the University of Arizona; and Gratadour is an associate professor at the Observatoire de Paris and an instrument scientist at the Australian National University -- spoke with AI Podcast host Noah Kravitz about how they’re using GPU-powered extreme adaptive optics in very large telescopes to image nearby habitable planets.

The words “data science” often inspire feelings of dread or confusion. But Virtualitics, an AI-based analytics platform, is bringing creativity and excitement to the field through machine learning and immersive virtualization. In our latest episode of the AI Podcast, Virtualitics Machine Learning Projects Head Aakash Indurkhya spoke with AI Podcast host Noah Kravitz about why VR can now be so useful.

Some say style never fades, and now with the help of AI, finding one’s fashion sense is about to get a whole lot easier. Fashion ecommerce startup Stitch Fix is piecing together a seamless balance between AI-powered decision making and human judgement. We spoke with Stitch Fix Chief Algorithms Officer Brad Klingenberg about how the company is using AI to help us all dress better.

We’re all aware of the race to deliver self driving cars that will allow consumers to sit back and be chauffeured wherever they wish. But the implications of self-driving trucks might actually be bigger, in the short term. Our guest today is Chuck Price, Chief Product Officer of TuSimple, which is developing commercially ready level four fully autonomous driving solutions for the logistics industry: self-driving trucks. So let’s talk trucks.

AI is bringing convenience to your healthcare experience. Health insurance company Anthem helps patients personalize and better understand their healthcare information through AI. We spoke with Rajeev Ronanki, senior vice president and chief digital officer at Anthem, about how AI makes data "meaningful and useful," for the healthcare giant.

SAS Chief Operating Officer Oliver Schabenberger spoke with us about how organizations can use AI and related technologies.

The path to self driving vehicles is usually marked by six milestones, or levels, from level 0, or no automation, to level 5, or full autonomy. Jianxiong Xiao, CEO of of startup AutoX, has his sights set on level 4, defined by the National Highway Traffic Administration as “a car capable of performing all driving functions under certain conditions."

Sticky. Kind. Chronic. Reefer. Forget the dated slang. These days the word is ‘opportunity.’ The market for legal cannabis in the United States was estimated at $12 billion last year, up 30% year over year from 2017, and it’s projected to grow to $44 billion by 2020. Our guests this episode is Vincent Harkiewicz, is CEO and co-founder of Boulder, Colorado-based Grownetics, a startup that sits at the intersection of agtech, marjijuana, data analytics and artificial intelligence.

Tara Chklovski is CEO and founder of Iridescent, a non-profit that provides access to hands on learning opportunities to prepare underrepresented children and adults for the future of work. She’s been called everything from the “pioneer empowering the incredible tech girls of the future,” to a “CEO science superstar hero.” Tara is here to talk about a bunch of things, including the UN’s AI for Good Global Summit this May in Geneva, and the AI World Championship, part of the AI Family Challenge, May 18 in Silicon Valley.

Good news: astronomers are getting new tools to let them see further, better than ever before. The bad news: they’ll soon be getting more data than humans can handle. To turn the vast quantities of data that will be pouring out of these instruments into world-changing scientific discoveries, Brant Robertson, a visiting professor at the Institute for Advanced Study in Princeton and an associate professor of astronomy at UC Santa Cruz, is turning to AI.

In 2015 today's guest penned an article called "Robot Propaganda" for Wired magazine. It contained this then bold prediction: "we are likely to see versions of these bots deployed on U.S. audiences as part of the 2016 presidential election campaigns." Well we all know how that turned out. Sean Gourley, founder and CEO of Primer, joined us to talk about bots, propaganda and fake news and how they relate to the work his own company is doing in natural language understanding and generation.

Robots can do amazing things. Compare even the most advanced robots to a three-year old, however, and they can come up short. UC Berkeley Professor Pieter Abbeel has pioneered the idea that deep learning could be the key to bridging that gap: creating robots that can learn how move through the world more fluidly and naturally. We caught up with Abbeel, who is director of the Berkeley Robot Learning Lab and cofounder of Covariant AI, a Bay Area company developing AI software that makes it easy to teach robots new and complex skills, at GTC 2019.

UC Berkeley's Gerry Zhang talks about his work using deep learning to analyze signals from space for signs of intelligent extraterrestrial civilizations. And while we haven't found aliens, yet, the doctoral student has already made some extraordinary discoveries.

Not sure who will win the NBA playoffs? Looking for coaching when putting together your fantasy football team? Swish Analytics uses AI to help you pick winners. Corey Beaumont, co-founder and head of engineering at the startup, explains how Swish Analytics takes the same kind of mathematical models lenders use to assess whether a borrower is a good risk and applies them to the $1 trillion sports betting market.

GOAT Group helps sneaker enthusiasts get their hands on authentic Air Jordans, Yeezys and a variety of old-school kicks with the help of AI. Michael Hall, director of data at GOAT Group explains how in a conversation with AI Podcast host Noah Kravitz.

You probably recognize the name Nuance from their work with speech recognition and virtual assistant technology. They’re one of the pioneers of voice recognition technology. Of course Nuance Communications has gotten into AI, but what you might not know is they’ve also gotten into using AI to chart the course of the healthcare industry and how physicians can use artificial intelligence to make people healthier and make their work better, Karen Holzberger is the vice president and general manager of Nuance’s Healthcare diagnostic solutions business.

At some point in life, every man faces the same great challenge: sorting out his children's Lego pile. Thanks to GPU-driven deep learning, Francisco "Paco" Garcia is one of the few men who can say they've conquered it. Here's how.

You don't need to be an an academic or to work for a big company to get into deep learning. You can just be a guy with a NVIDIA GeForce 1080 Ti and a Generative Adversarial network. Jason Antic, who describes himself as "a software guy," began digging deep into GANS. Next thing you know: he’s created an increasingly popular tool that colors old black-and-white shots to make them look good. Interested in digging into AI for yourself? Listen and get inspired.

SoundHound made its name as music identification service. Since then, SoundHound has become much more. It's leveraged its 10 plus years in data analytics to create a voice recognition tool companies can bake into any product. Here to tell us how SoundHound has grown into a major player in voice driven Ai is SoundHoud VP of Product Marketing Mike Zagorsek.

With “Fake News” embedding itself into, well, our news, it’s become more important than ever to distinguish between content that is fake or authentic. That’s why Vagelis Papalexakis, a professor of computer science at the University of California, Riverside, developed an algorithm that detects fake news with 75 percent accuracy.

Voice recognition is one thing, creating natural sounding artificial voices is quite another. Lyrebird - a member of NVIDIA’s Inception startup program - uses deep learning to take this a step further, with a system that's able to listen to a human voices and generate speech that mimics the sound of the original, human, speaker. We spoke with Lyrebird co-founder Jose Solero about the benefits of this technology, and why he feels the need to educate the public about what's possible.

Dr. Kai-Fu Lee has been at the center of artificial intelligence for decades. dr. Lee developed the world's first speaker independent continuous speech recognition system, selected as the most important innovation of the year by BusinessWeek, and that was back in 1988. In the three decades since, Dr. Lee has led teams at Apple, Silicon Graphics, Microsoft and Google. In 2009 Dr. Lee left Google to start Sinovation Ventures, which now manages a $2 billion fund focusing on technology startups in China and the United States. His latest book, "AI Superpowers: China, Silicon Valley, and the New World Order," ranks number six on the New York Times Business Books best sellers list.

Intuit Senior Vice President and Chief Data Officer Ashok Srivastava on how the personal finance giant is using AI to help make us all smarter about our finances.

When you hear of AI and machine learning, it’s easy to think of technology companies leading the charge. Capital One is determined to change that. In a conversation with AI Podcast host Noah Kravitz, Nitzan Mekel, managing vice president of machine learning at Capital One, explained how the banking giant is integrating AI and machine learning into customer-facing applications such as fraud-monitoring and detection, call center operations and customer experience.

DOOM, of course, is foundational to 3D gaming. 3D gaming, of course, is foundational to GPUs. GPUs, of course, are foundational to deep learning, which is, now, thanks to a team of Italian researchers, two of whom we're bringing to you with this podcast, being used to make new levels for... DOOM.

What's a meme? And what makes a meme, dank? Today's guest is Lawrence Pierson, a PhD student in theoretical astrophysics at Stanford University, will answer these questions, and more. He's the author a paper detailing how he and a classmate built a neural network to generate memes. Some of them are even funny.

Robots following coded instructions to complete a task? Old school. Robots learning to do things by watching how humans do it? That’s the future. Earlier this year, Stanford’s Animesh Garg and Marynel Vázquez shared their research in a talk on “Generalizable Autonomy for Robotic Mobility and Manipulation” at the GPU Technology Conference last week. We caught up with them to learn more about generalizable autonomy - the idea that a robot should be able to observe human behavior, and learn to imitate it in a way that’s applicable to a variety of tasks and situations. Like learning to cook by watching YouTube videos, or figuring out how to cross a crowded room for another.

Any sufficiently advanced technology is indistinguishable from magic. As the years have passed what passed since the invention of the personal computer, what passes in the world of technology has changed dramatically. So what’s next? Voice computing is once answer. Voice computing is one of the hottest and most fascinating areas of today’s’ technology landscape. Peter Cahill is the CEO of Voysis, an Irish startup using AI to make voice computing more realistic, and a part of more online retail experiences everywhere.

Airport control towers are icons of the aviation industry. But a Canadian startup wants to use artificial intelligence to make them a relic of the past. Searidge Technologies believes AI powered video systems can do a better job.

Credit scores are a funny thing. Funny might not be the right word, but you know what we mean. You can't have a credit score unless you have a credit history. You have to use your credit to keep your score up, but if your score's not good enough, you can't get credit. But never fear, AI and machine learning are here to help. Our guest on this episode is Ajay Gopal, he's with Deserve, a startup that's using machine learning to extend credit to people who may not have a typical credit history.

NVIDIA researchers are gearing up to present 19 accepted papers and posters, seven of them during speaking sessions, at the annual Computer Vision and Pattern Recognition conference next week in Salt Lake City, Utah. Joining us to discuss some of what's being presented at CVPR, and to share his perspective on the world of deep learning and AI in general is one of the pillars of the computer science world, Bill Dally, chief scientist at NVIDIA.

Smarts are always in fashion, and our next guest has that in spades. Costa Colbert has been chasing down how brains — both real and artificial — work for 30 years. Dr. Colbert — who holds degrees in fields ranging from neural science to electrical engineering — is known for his studies of information transmission in pyramidal neurons of the mammalian hippocampus and neocortex. At MAD Street Den his team is putting modern deep learning techniques to work for retailers in a wide variety of ways — including using Generative Adversarial Networks to create images of models wearing clothes.

NetFlix has changed the way we watch television for the better. The streaming video pioneer is much more than just an entertainment giant for the 21st century — it’s also a pioneer when it comes to using machine learning. While Justin Basilico, a research director with NetFlix, can’t share all the spoilers, he knows better than anyone how entertainment and machine learning intersect.

Think of it as like a USB port for your body. Emil Hewage is the co-founder and CEO at Cambridge Bio-Augmentation Systems, a neural engineering startup. They UK startup is building interfaces that use AI to help plug medical devices int our nervous systems. CBAS was named one of the top startups at Y Combinator’s Winter ‘17 cohort by TechCrunch and won the top prize with accelerator MassChallenge UK 2015.

Wayne Thompson was into big data, before big data was cool. Now the world — even much of our GPU Technology Conference — revolves around the kinds of challenges the 25-year veteran of analytics software developer SAS Institute has made a career of helping enterprises master. How did that happen? We asked Thomson, Chief Data Scientist of SAS Data Science Technologies to talk about the big data, big models, and big computations driving deep learning, and to give us some perspective about what makes today’s deep learning technologies different.

This week's episode features Bryan Catanzaro, vice president of applied deep learning research at NVIDIA, and if you've been following the podcast for a while, you know that an earlier episode featuring Bryan is one of the most popular podcasts we've done. Bryan is going to walk us through some of the latest developments at NVIDIA research... as well as share a story that involves Andrew Ng and cats.

Grab the goods and go. AiFi co-founder and CEO Steve Gu wants to give every store — from Mom and Pop bodegas to supermarket chains — the ability to let customers saunter out of the door without so much as a wave at a checker. The benefits involve more than just convenience: stores will have a better idea of how their customers behave and get a real-time bead on their inventory. To do that, our latest guests and his team at startup AiFi rely on advanced sensor fusion, simulation, and deep learning.

Clean, cheap fusion energy would change everything for the better. Our next guest, William Tang, has spent a career at the forefront of that field, currently as principal research physicist at the Princeton Plasma Physics Laboratory. He’s also one of the world’s foremost experts on how the science of fusion energy, and high-performance computing intersect. Now, he sees new tools — deep learning and artificial intelligence — being put to work to enable big-data-driven discovery in key scientific endeavors, such a the quest to deliver Fusion energy.

Deep learning has helped machines understand how to move pieces around a board to master, and win, Go, the most complicated game mankind has ever invented. Now it's helping a new generation of chemists better understand how to move molecules around to model new kinds of materials. Our guest, Olexandr Isayev, an assistant professor at the UNC Eshelman School of Pharmacy, at the University of North Carolina at Chapel Hill, joined our show to explain how deep learning, Go, sci-fi, and computational chemistry intersect.

How do you win a fast-paced first-person shooter? Answer: it helps to have a good GPU, of course. How do you win one of the world’s most high profile robotics competitions? You guessed it, it helps to have a good GPU. Doug Morrison of the Australian Center for Robotic Vision helped lead the team that developed Cartman, a custom-built, cost-effective robotic system that picked and placed its way to victory in the 2017 Amazon Robotics Challenge global finals in Nagoya Japan last year.

We talk a lot about technology, and data, specifically, impacting all facets of modern life. In this episode we're going to look at data's role in addressing one of the biggest threats to life as we know it: cancer. We'll talk to Dr. Richard Wender, chief cancer control officer at the American Cancer Society about how technology is key to redefining how we look at, and fight, cancer.

One of the things that makes the weather so dangerous is that it's so hard to predict. Tornadoes, hail, high winds and flash floods cause billions of dollars worth of property damage, and injure or kill hundreds of people in the United States each year. Knowing when storms may strike can save lives, and property. Our guest is part of a team at the National Center for Atmospheric Research that's doing just that. We spoke with David John Gagne, a postdoctoral fellow at the National Center for Atmospheric Research about his work with deep learning at the GPU Technology Conference in Silicon Valley this week.

Accountants have spreadsheets. Novelists have word processors. Now, deep learning promises to help take some of the grunt out of legal grunt work. Here's how one startup is using deep learning to help lawyers get legal work done faster and more accurately.

Ever since the internet went mainstream people have been struggling with perhaps the ultimate question: what do I call my web site? What domain name do I register? But almost as quickly as that became a question in people's mind, a secondary question came up: what's my domain name going to be worth? Well thanks to AI we have a better answer to that than ever. Joining us for this episode: Jason Ansel, senior principal engineer with GoDaddy, which is using AI to help you better understand the value of your domain name.

Sarcasm? On the Internet? You're kidding. But sarcasm is no joke. Long before today's sentiment analysis systems struggled to accurately understand human communication, people struggled to understand one another's sarcasm. Now, thanks to the work of Dr. Pushpak Bhattacharyya and his team computers are beginning to understand one of humanity's most challenging, and amusing, modes of communication. Dr. Bhattacharyya, director of IIT Patna, and a professor at the Computer Science and Engineering Department at IIT Bombay has spent the past few years using GPU-powered deep learning to detect sarcasm.

AI is being used to enhance and improve life in varied and often incredible ways. But what if we could use AI to improve the end of our lives, too? Our guest today is Anand Avati, a graduate student in the Artificial Intelligence Lab at Stanford University's Computer Science Department. Anand is co-author of a research paper entitled "Improving Palliative Care with Deep Learning" which details his team's use of a deep learning system to predict patient mortality with the aim of improving access to palliative care for critically-ill patients.

AI is getting better, and it's finding its way into more parts of our lives with each passing day. And talking about the future artificial intelligence has become a surefire way to spawn a thousand debates about the future, and nature, of humankind ourselves. Our guest today, Ken McLeod, is an award winning science fiction author whose work dives deep into the relationship between man and machine. His latest book, "The Corporation Wars: Emergence" is the final volume in an acclaimed trilogy whose cast of characters includes sentient robots, computer AIs that oversee Earth from afar, and, of course, emulated human minds running in digital simulations.

Love. The search for love. The search even for someone you just kind of like. It's been the subject of poems, novels, songs, you name it. For as long as humans have been around, they've been looking for love. But what if you could use AI to automate the process? To help you with everything from finding your true match, to swiping through all those not quite true matches. Oscar Alsing, our guest on this episode, will talk about how he's used AI, and Tinder, to do just that.

Election polling is an inexact science. If you've been paying attention to American politics at all over the past year or two, you don't need us to tell you that. But what if instead of asking voters their opinions on the candidates or the issues you took a different approach, one that involves artificial intelligence... and cars. Joining us for this edition of the AI podcast is Timnit Gebru, a post-doctoral researcher at Microsoft Research in New York and a newly minted PhD from the Stanford Artificial Intelligence Laboratory. Timnit is co-author of a paper titled "Using Deep learning and Street View to Estimate the Demographic Makeup of Neighborhoods Across the United States."

Think you've got no artistic talent? You do now. Vincent AI is an application that lets you pick up a stylus, sketch out a few lines on a screen, and watch as your scribbles are turned into a work of art inspired by one of seven artistic masters. We speak with Monty Barlow, machine learning director for Cambridge Consultants, the technology development house behind this amazing demo.

Ever see a photo of an amazing looking meal, maybe in a food magazine or an Instagram feed, and wish you had the recipe to make it yourself? Thanks to a project born out of MIT's Computer Science and Artificial Intelligence Laboratory we're a step closer to being able to do that. We talk with Nick Hynes, one of the minds and stomachs behind this effort just in time for Thanksgiving and the holiday food season.

Whether you're wandering through the sprawling virtual worlds of Grand Theft Auto... or just trying out a new couch in Ikea's virtual living room, virtual worlds are everywhere. But there's as problem. There just aren't enough artists to build all these virtual worlds and populate them with foes... or furniture. We spoke with Artomatix co-founder Eric Risser about how deep learning can help artists fill such burgeoning virtual worlds.

Tired of waiting in checkout lines? Malong Technologies offers technology that may one day let you grab what you want and go. We spoke to this startup about how it's turning its prowess in some of the world's top image recognition contests into a service businesses can use to put image recognition to work.

Picture this, you find yourself in a tattoo parlor. But none of the dragons, flaming skulls, or gothic font lifestyle mottos you see on the wall seem like something you want on your body. So what do you do? You turn to AI, of course. We spoke to two members of the development team at Tattoodo.com, who created an app that uses deep learning to help you create the tattoo of your dreams.

This might be the first time we've been able to say this, but we might have spoilers ahead on this episode. Joining us we have Zack Thoutt, a data scientist and a developer from Boulder, Colorado. Zack has done something we've all wanted to have done: he's working on finishing the books behind HBO's Game of Thrones - a Song of Ice and Fire - by putting an AI system to work with sometimes comical results.

The robots that have taken on tasks in the real world - which is to say the world where physics apply - are primarily programmed to do a specific job, such as welding a joint in a car or sweeping up cat hair. So what if robots could learn, and take it a step further - what if they could teach themselves, and pass on their knowledge to other robots? Where could that take machines, and the notion of machine intelligence? And how fast could we get there? Those are the questions our guest Sergey Levine, an assistant professor at UC Berkeley's department of Electrical Engineering and Computer Sciences, is finding answers to.

The next time you don’t recognize a transaction listed on your monthly Paypal statement, rest assured: AI will likely identify the culprit and help ensure it won’t happen again. With advances in machine learning and the deployments of neural networks, logistic regression-powered models are expanding their uses throughout PayPal, Vadim Kutsyy, a data scientist at the online payments company, told host Michael Copeland on this week’s edition of the AI Podcast.

We are here at the mothership of NVIDIA with this summer's Jetson interns. And Mokshith Voodarla, Mark Thies, Isaac Wilcove -- all recruited at top robotics competitions -- are building some amazing things with our Jetson embedded computing platform and deep learning, including a delivery robot, a robot that recognizes and disposes of trash, and a remote control car that can find people who are trapped in a building during a fire or earthquake.

AI systems have been trained to take photos and transform them into the style of great artists like Van Gogh, Picasso, or J.M.W. Turner. Take a photo, pick a style, and what emerges looks kind of like the lost work of an artistic master. Now, AI is heading in a different artistic direction: music. The soaring music featured on today's podcast, which made its debut at our GPU Technology Conference, was composed by an AI system developed by our guest, Pierre Barreau, head of Luxembourg-based startup Aiva Technologies.

We’ve heard of robots working in warehouses, picking the right windshield or a box of wiring harnesses from shevles. But what about making sure those shelves are stocked with the right stuff, in the right place, at the right time? Marc Gyongosi thinks that flying robots – better known as drones – are right for the job. Marc is the CEO founder of IFM, or Intelligent Flying Machines, which is pretty much what IFM does.

Purple shirts, haircuts, and cats. How are these three all related? According to deep learning pioneer Andrew Ng, they all played a part in AI’s growing presence in our lives. Ng, formerly of Google and Baidu, and the founder of his new company, Deeplearning.ai, joined this week’s episode of the AI Podcast to share his thoughts on AI being the new electricity.

Our guest on this segment, Paul Wigley, of the Australian National University, was part of a team of scientists who applied AI to an experiment to create a Bose-Einstein condensate. And in doing so they had a question: if we can use AI as a tool in this experiment, can we use AI as its own novel, scientist, to explore different parts of physics and different parts of science?

Tim Anglade, a consultant with HBO's "Silicon Valley," has engineered an app that solves an important problem for all of us: is that a hot dog... or not? The app was dreamed up by the writers and producers of HBO's hit comedy and brought to the real world by Anglade thanks to deep learning.

We all know about driverless cars, driverless cars get all the love and all the attention, because we don't want to drive. But we're going to talk in this segment about autonomous trucks, how and why we need autonomous trucks in many ways just as much as we need autonomous cars. To do that, we're talking to Xiaodi Hou the CTO and co-founder of TuSimple, a company that is bringing driverless trucks to the road.

We all know how far AI, and in particular deep learning, have pushed speech recognition, whether that is with Apple Siri, Amazon Alexa, or Google Assistant, Our guest on this segment, Syed Ahmed, is directing the power of AI towards another form of communication, American Sign Language. And what Syed has done is set up a deep learning model that translates American Sign Language into the English Language.

Over the last few years data intensive machine learning solutions have supplanted rule-based software systems at many technology-based companies. Think about Amazon, Netflix, and Uber. But the gaming world hasn't exactly followed suit, at least not as quickly. Most games are still a delicate mix of hard-wired behavior in the form of traditional code, and somewhat more responsive behavior in the form of large collections of rules. Our guest, Danny Lange, VP of AI and Machine Learning at Unity Technologies, is taking a different tack, using deep learning to help with game creation, that subtle combination of art, story, and software.

In recent years hedge funds have taken the lead in algorithmic investing - or robo-trading as it’s sometimes called. But there’s no reason the hedge fund world should have all the good stuff. In this episode of the AI Podcast, we speak with Gaurav Chakravorty, co-founder of qplum, a startup that’s working to bring that same machine learning investing approach to the rest of us.

How an argument in a bar led Google's Ian Goodfellow to create Generative Adversarial Networks - deep learning systems that argue with each other - an AI breakthrough that promises to help researchers build systems that can learn with less human intervention.

Whatever sport we follow, we all love a good highlight reel - and we want those highlights now. And whether they're following StarCraft II, League of Legends, or Heroes of the Storm, eSports fans are no different. To highlight the kills, and thrills, of a great eSports competition, Yale Song, Senior Research Scientist at Yahoo! Research, turned to AI.

With self-driving cars generating so much buzz, it’s hard to believe that a self-piloting air taxi is, err, flying under the radar. But not for long. We spoke with Arne Stoschek, head of autonomous systems at Airbus A3 (pronounced “A-cubed”), the Silicon Valley-based advanced products and partnerships outpost of Airbus Group about a plan to bring a self-piloted air taxi to the Bay Area’s skies.

We spoke with Xuchen Yao, co-founder of Kitt.ai, a startup using AI to build better chat experiences, about how voice and chat are turning into rich, interactive interfaces for a new generation of AI-powered services.

Are AI and VR the peanut butter and chocolate of computing? Are they a match made in heaven? We spoke with Michael Ludden, who heads up IBM Watson's AI and VR labs, about how these two technologies intersect at this week's GPU Technology Conference.

We spoke with Innit Chief Technology Officer Hristo Bojinov about all the surprising ways deep learning can help us better manage the very personal relationship we all have with food — from meal planning to kitchen inventory to cooking the perfect roast chicken.

We spoke with the team at Marble, which has turned AI loose on the streets of San Francisco delivering food in San Francisco's vibrant Mission District.

We spoke with Princeton researcher Aylin Caliskan, co-author of a headline-grabbing paper published in Science magazine earlier this month. Her paper details how learning machines can sometimes learn all too well, picking up our biases as well as our brilliance.

Previous episodes discussed deep learning systems trained to master games like Chess, Go, and even Texas Hold 'Em. But training a deep neural net on a racing game like Mario Kart 64? What can you learn from that? A lot, it turns out, explains Kevin Hughes.

If you're looking for the impact of deep learning, look to the end of your fork. We spoke with Blue River Technology co-founder and CTO Lee Redden about how the startup put deep learning to work tending 10% of the lettuce produced in the United States, and how deep learning promises to unleash a new agricultural revolution.

We spoke with Michael Bowling, a professor at the University of Alberta whose team of researchers created a GPU-trained AI that has defeated professional poker players at heads-up no-limit Texas hold’em. The work promises to yield applications in the real world, where — unlike games such as Go and Chess — we often have to make decisions based on incomplete information.

We speak with Matthew McKown, CEO of Conservation Metrics, about how deep learning techniques helped rediscover a bird that was once thought extinct, and how GPU-powered AI now helps biologists crunch vast quantities of data to spot trends that would have been impossible to detect before.

We talk with Dr. Bradley Erickson, a Mayo Clinic neuroradiologist, who uses AI to predict tumor genomics using MRIs. His method could give doctors easier access to invaluable genetic information. Information that could predict how quickly a tumor will progress, and if it will respond to specific drugs and other treatments.

Medicine — particularly radiology and pathology — have become more data-driven. The Massachusetts General Hospital Center for Clinical Data Science — led by Mark Michalski — promises to accelerate that, using AI technologies to spot patterns that can improve the detection, diagnosis and treatment of diseases.

University of Kentucky Computer Science Professor Brent Seales caused a worldwide sensation when he and his team were able to use non-invasive scans to unlock writings on the ancient En-Gedi scroll to reveal the earliest copy of a Pentateuchal book — Leviticus — ever found in a Holy Ark. Now he’s turning his expertise to more ancient texts, this time from the lost Roman city of Herculaneum.

If you want to bring autonomous vehicles to the mainstream, fast, first you’ve got to go fast. We spoke with Jonathan Cooke, chief marketing officer of Roborace, the first ever driverless electric racing championship, who wants to turn autonomous racing into a spectator sport that will spark the creation of more powerful, capable automotive AI.

Cybersecurity is a cat-and-mouse game where the mouse always has long had the upper hand because it’s so easy for new malware to go undetected. Dr. Eli David, an expert in computational intelligence and CTO of Deep Instinct, wants to use AI to change that, bringing the GPU-powered deep learning techniques underpinning modern speech and image recognition to the vexing world of cybersecurity.

Whether brewing hearty stouts or crisp lagers, flavor is a fickle thing. Not only is it hard to create consistently good brew, as humans our ability to identify - and remember - flavors is flawed. Yet brands worth billions rely on creating consistent flavors. We talk to Jason Cohen, founder of Gastrograph, who is using AI to help businesses that create beer, chocolate, wine, coffee, and spirits better understand flavor.

It’s easy to think of AI as cold, unbiased, objective. Not quite, suggests Narrative Science Chief Scientist Kris Hammond explains, because we never know when AI will repeat our biases back to us.

Take brains, a few hundred bones and a pink Barbie jeep. What have you got? For inventive hackers, a new sport filled with f-words -- fast, furious, frugal. Founder of the Power Racing Series Jim Burke talks about why he’s bringing autonomous vehicles to a racing event built on the backs of $500 kiddie cars.

Deep learning promises to do more than just reshape city streets. We talked to Lynn Richards, president and CEO of the Congress for New Urbanism and Charles Marohn, president and co-founder of Strong Towns, about how. AI will do much more than automate driving. It promises to help create more liveable cities. And help put expensive infrastructure where we need it most.

Autonomous vehicles will need to do much more than master object detection. Self-driving vehicles will need technology able to integrate visual computing, artificial intelligence, and high-performance computing, NVIDIA's Danny Shapiro explains.

Deep learning isn't just for research scientists anymore. Hobbyists can use consumer grade GPUs and open-source DNN software to tackle common household tasks from ant control to chasing away stray cats.

Bryan Catanzaro, vice president for applied deep learning research at NVIDIA, talks about how we know an AI technology is working, the potential for AI-powered speech, and where we’ll see the next deep learning breakthroughs.

Think of our inaugural episode of The AI Podcast as a guide for the perplexed. Host Michael Copeland speaks with NVIDIA's Will Ramey about the history behind today's AI boom and the key concepts you need to know to get your head around a technology that's reshaping the world.