A necessary prerequisite to detecting deepfakes is the ability to quickly and autonomously process video assets. However, training a video recognition model can take up to 50 times more data and 8 times more processing power than training a static image classification model. This talk explores a ground-breaking new technology that will significantly increase video processing speeds, improving our ability to deal with the ever increasing volume of deepfake videos.