How do you defeat "deepfakes"? According to Google, you develop more of them. Google just released a large, free database of deepfake videos to help research develop detection tools. Google collaborated with "Jigsaw", a tech "incubator" founded by Google, and the FaceForesenics Benchmark Program at the Technical University of Munich and the University Federico II of Naples. They worked with several paid actors to create hundreds of real videos and then used popular deepfake technologies to generate thousands of fake videos.
A perfect storm arising from the world of pornography may threaten the U.S. elections in 2020 with disruptive political scandals having nothing to do with actual affairs. Instead, face-swapping "deepfake" technology that first became popular on porn websites could eventually generate convincing fake videos of politicians saying or doing things that never happened in real life--a scenario that could sow widespread chaos if such videos are not flagged and debunked in time. The thankless task of debunking fake images and videos online has generally fallen upon news reporters, fact-checking websites and some sharp-eyed good Samaritans. But the more recent rise of AI-driven deepfakes that can turn Hollywood celebrities and politicians into digital puppets may require additional fact-checking help from AI-driven detection technologies. An Amsterdam-based startup called Deeptrace Labs aims to become one of the go-to shops for such deepfake detection technologies.
As coverage of deepfake technology becomes more prevalent, it's reasonable to wonder how these videos even work. Advancements in motion capturing and facial recognition over the past decade have been staggering – and terrifying. What used to be limited to only the most well-funded computer scientists and movie studios is now a tool in the hands of comedy outlets and state-run media. By definition, deepfakes are videos in which a person's face and/or voice are replaced with someone else's by an AI. The underlying technology and machine learning processes rose to popularity in the early '90s, evolving from a field of academic research.
The term Deepfake itself is a combination of'Deep Learning' and'Fake'. Belonging to the larger body of Machine Learning, Deep Learning depends on artificial neural networks to process raw information. Deepfake is AI-dependent technology which is used to create or modify video that implies false situations. This term first came into being back in 2017. That is when a Reddit user (called deepfakes) began applying deep learning technology to swap celebrity faces onto people performing in pornographic videos.
If you're worried about the malevolent potential of deepfake video, you're not alone – so is Facebook. The company has launched a project to sniff out deepfake videos, and it's pledging more than $10m to the cause. It has pulled in a range of partners including Microsoft for help. Deepfakes are videos that use AI to superimpose one person's face on another. They work using generative adversarial networks (GANs), which are battling neural networks.