Towards the end of 2020, I had the opportunity to give a talk on Deepfakes in the 60th AI4EU WebCafe. With deepfakes being already with us for more than two years now, we have already witnessed several real-world cases of deepfakes with both positive and negative impact, while their use has recently been commoditized by popular apps such as ZAO and Reface.

A lot of our research and development activities rely on large collections of web media content sourced from social media platforms, such as YouTube and Twitter, and then manually curated and annotated by our researchers with the purpose of creating “ground truth” datasets. This helps us train machine learning models on specific tasks and then benchmark those models along with competing approaches in order to select the best method per case.