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There are tremendous commercial opportunities in using academic research to develop technologies that can solve problems in such domains as medicine, robotics & automation, logistics, and various other industries. Exploiting these opportunities, however, still requires significant innovation in hardware and software frameworks, coupled with cutting-edge academic research. The best academic literature results typically can't be directly applied to a product due to misalignment with market needs, and/or the product's inability to repeatedly and reliably perform its function under non-ideal (real-world) conditions. Our panel comprises renowned academics who used their research skills to develop products for real-world use cases and became successful entrepreneurs. They'll share their approaches to integrating their research into commercial products and explain the challenges they overcame on their journeys to becoming successful entrepreneurs.

We are excited to bring Transform 2022 back in-person July 19 and virtually July 20 - August 3. Join AI and data leaders for insightful talks and exciting networking opportunities. The rapidly growing sectors of edge computing and the industrial metaverse were targeted by new technology developments, like sensor architecture, released by Nvidia last week at its GTC 2022 conference. Last week, the company also debuted the Isaac Nova Orin, its latest computing and sensor architecture powered by Nvidia Jetson AGX Orin hardware. Nvidia's main focus is pursuing a tech-stack-based approach starting with new silicon to help manufacturers make sense of the massive amount of asset, machinery, and tools data they generate. In addition, predictive maintenance is core to many organizations' Maintenance, Repair, and Overhaul (MRO) initiatives.

It's been years since developers found that Nvidia's main product, the GPU, was useful not just for rendering video games but also for high-performance computing of the kind used in 3D modeling, weather forecasting, or the training of AI models--and it's on enterprise applications such as those that CEO Jensen Huang will focus his attention at the company's GTC 2022 conference this week. Nvidia is hoping to make it easier for CIOs building digital twins and machine learning models to secure enterprise computing, and even to speed the adoption of quantum computing with a range of new hardware and software. Digital twins, numerical models that reflect changes in real-world objects useful in design, manufacturing, and service creation, vary in their level of detail. For some applications, a simple database may suffice to record a product's service history--when it was made, who it shipped to, what modifications have been applied--while others require a full-on 3D model incorporating real-time sensor data that can be used, for example, to provide advanced warning of component failure or of rain. It's at the high end of that range that Nvidia plays.

Did you miss a session at the Data Summit? Nvidia packed about three years' worth of news into its GPU Technology Conference today. Flamboyant CEO Jensen Huang's 1 hour, 39-minute keynote covered a lot of ground, but the unifying themes to the majority of the two dozen announcements were GPU-centered and Nvidia's platform approach to everything it builds. Most people know Nvidia as the world's largest manufacturer of a graphics processing unit, or GPU. The GPU is a chip that was first used to accelerate graphics in gaming systems.

GTC is all about four days of discovery. Come explore what's driving transformation in your industry--from the power of AI to the collaborative virtual worlds of NVIDIA Omniverse, and beyond. And discover the technological advancements and groundbreaking research that are making it possible to take on the world's greatest challenges--together. Join us this March and discover how to accelerate your life's work.