Edge computing brings computation and data storage closer to where it is needed, to improve response times and save bandwidth. Now more AI is being incorporated into edge devices, from IoT devices to smartphones to automobiles, as edge compute power increases and AI algorithms improve. As the edge computer processes, only a subset of data generated by sensors is sent to the cloud, saving on bandwidth and cloud storage costs, according to a recent account in Forbes. Decisions can be made faster using AI models on the edge that have been trained via machine learning in the cloud. A deep learning model deployed at the edge may see slower inferencing.

NVIDIA is challenging you to show us how you can transform robotics, industrial IoT, healthcare, security, or any other industry with a powerful AI solution built on the NVIDIA Jetson platform. You'll not only get the chance to win amazing prizes, but also a trip to present your project to CEOs, executives, and industry peers at the world's biggest event for GPU innovation and Artificial Intelligence (AI)--the GPU Technology Conference (GTC). Check out the "Prizes" section for details. AI is empowering the world's brightest minds to create amazing breakthroughs in a wide range of industries. Today, NVIDIA GPUs simulate human intelligence, run deep learning algorithms, and act as the brains of computers, robots, and self-driving cars.

Robotic Assistance Devices (RAD), an innovator in artificial intelligence and robotics and master distributor for SMP Robotics Systems announced it is advancing its complete line of autonomous robotic guards with the NVIDIA Jetson embedded computing platform. Using NVIDIA Jetson, an embedded AI supercomputer ideal for intelligent machines, RAD robotics can achieve higher levels of autonomy, while adding advanced people and vehicle detection on the moving robot. The new RAD product line-up offers global security teams situational awareness tools to deliver unprecedented deployment flexibility and operational productivity. Using the Jetson platform's high-performance, power-efficient supercomputing for deep learning and computer vision, RAD autonomous robotic systems can be more predictive, accurate, productive and easily reconfigured for a variety of tasks. RAD will demonstrate new Jetson-powered vision capabilities on its autonomous robotic systems at the ISC West Conference and Expo, being held April 5-7, at the Sands Expo Center in Las Vegas.

Start developing applications with advanced AI and computer vision today using NVIDIA's deep learning tools, including TensorRT and DIGITS. Webinar access will be emailed to you. Sign up anyway to get the recording! A renowned GPGPU developer and systems architect, Dustin Franklin works to deploy CUDA-accelerated embedded applications and solve challenging sensor processing problems on Jetson, NVIDIA's low-power, high-performance embedded platform. Dustin and his team utilize the parallel compute horsepower of NVIDIA GPUs for real-time computer vision, autonomous navigation, and other toolsets, to enable new product categories and industries.