You may not realize it, but the age of AI-powered robots is already upon us. From farms to construction sites and factories, and even college campuses, automated machines are quickly fanning out to new use cases, albeit quietly. But unlike the broken promises we’ve heard for the last several decades about the coming robot revolution, we truly are on the cusp of automated helpers everywhere.
While robots may seem relatively simplistic from the exterior, they are anything but. Compute power had long held the industry back on several axes, but the rise of artificial intelligence has proven to be the breakthrough the industry needed.
It doesn't just require sheer compute horsepower, either: there's a variety of data that has to crunched to power a truly autonomous machine. These applications require systems that can ingest high-resolution video, even up to 4K, crunch data from complex arrays of sensors, encode those streams and then run convolutional neural networks to analyze the incoming data. LIDAR systems and inference engines for path tracing are also an absolute must. That means the real challenge is grappling with the crushing influx and variety of data that needs processed.
That's where Nvidia hopes its Jetson TX2 platform can step in. The third-gen Jetson AGX Xavier Module processes up to 30 trillion operations per second through the combined power of its 512-core Volta GPU, two NVLDA engines, vision processors, and eight core ARM processor. Overall, the SoC can handle a tremendous amount of incoming data from a plethora of sensors, crunch it into a usable form that can be analyzed by advanced AI neural networks, and thus enable a wide range of truly autonomous vehicles.
Nvidia's Jetson TX2 enjoys broad industry uptake, and the company hopes it can find the same success with its new AGX Xavier. Let's look at the machines the current-gen Jetson TX2 powers, and then dive into the AGX Xavier details.