One of the primary driving forces in the rapidly evolving research areas of Machine Learning (ML) and Artificial Intelligence (AI) is Challenges such as MNIST, ImageNet, VAST and HPC Challenge.

While groundbreaking results have been achieved in the past decade for natural signals (such as image and audio), abilities such as detection, identification and geolocation of radiofrequency (RF) signals received relatively less treatment.

The RFChallenge at MIT—one of the fruits of the USAF-MIT AI ACCELERATOR—aims to encourage the RF community in developing new AI inspired algorithms, and stimulate research which incorporates contemporary notions and novel ML techniques, leading to enhanced spectral awareness and interference rejection capabilities.