Artificial intelligence has made great strides in many technology sectors, however, it has yet to impact the design and applications of radio frequency (RF) and wireless systems. This is primarily due to the industry''s preference towards field programmable gate array (FPGA) systems. Conversely, the deep learning revolution has been fueled by GPUs and the ease with which they may be programmed for highly parallel computations. The next generation RF and wireless technology will require wide-band systems capable of real-time machine learning with GPUs. Working with strategic partners, we''ve designed a software configurable wide-band RF transceiver system capable of performing real-time signal processing and machine learning with a Jetson TX2. We discuss system performance, collection of RF training data, and the software used by the community to create custom applications. Additionally, we''ll present data demonstrating applications in the field of RF machine learning and deep learning.