The Army Rapid Capabilities Office (RCO) conducted an initial Signal Classification Challenge with industry and academia to promote advanced research to explore deep learning algorithms and the application of artificial intelligence (AI) for blind signal classification and characterization. This was a first step towards reducing the cognitive burden on Army EW personnel by providing them with a machine learning capability to identify and classify signals of interest embedded in a dense EM environment. This presentation will describe data generation (how was gnu radio used as part of this architecture) and the composition of the datasets in addition to highlighting future Army RCO efforts and opportunities.