Today AWS is pleased to announce that it is working with Facebook, Microsoft, and the Partnership on AI on the first Deepfakes Detection Challenge. The competition, to which we are contributing up to $1 million in AWS credits to researchers and academics over the next two years, is designed to produce technology that can be deployed to better detect when artificial intelligence has been used to alter a video in order to mislead the viewer. We plan to host the full competition dataset when it is made available later this year, and are offering the support of Amazon machine learning experts to help teams get started. We want to ensure access to this data for a diverse set of participants with varied perspectives to help develop the best possible solutions to combat the growing problem of “deepfakes.”
The same technology which has given us delightfully realistic animation effects in movies and video games, has also been used by bad actors to blur the distinction between reality and fiction. “Deepfake” videos manipulate audio and video using artificial intelligence to make it appear as though someone did or said something they didn’t. These techniques can be packaged up in to something as simple as a cell phone app, and are already being used to deliberately mislead audiences by spreading fake viral videos through social media. The fear is that deepfakes may become so realistic that they will be used to the detriment of reputations, to sway popular opinion, and could in time make any piece of information suspicious.
The Deepfakes Detection Challenge invites participants to build new approaches that can detect deepfake audio, video, and other tampered media. The challenge will kick off in December at the NeurIPS Conference with the release of a new dataset generated by Facebook which comprises tens of thousands of example videos, both real and fake. Competitors will use this dataset to design novel algorithms which can detect a real or fake video, and the algorithms will be evaluated against a secret test dataset (which will not be made available to ensure there is a standard, scientific evaluation of entries).
Building deepfake detectors will require novel algorithms which can process this vast library of data (more than 4 petabytes). AWS will work with DFDC partners to explore options for hosting the data set, including the use of Amazon S3, and we will make $1 million in AWS credits available to develop and test these sophisticated new algorithms. All participants will be able to request a minimum of $1,000 in AWS credits to get started, with additional awards granted in quantities of up to $10,000 as entries demonstrate viability or success in detecting deepfakes. Participants can visit www.aws.amazon.com/aws-ml-research-awards to learn more and request AWS credits.
The Deepfakes Detection Challenge steering committee is sharing the first 5,000 videos of the dataset with researchers working in this field. The group will collect feedback and host a targeted technical working session at the International Conference on Computer Vision (ICCV) in Seoul beginning on October 27, 2019. Following this due diligence, the full data set release and the launch of the Deepfakes Detection Challenge will coincide with the Conference on Neural Information Processing Systems (NeurIPS) this December.
To support participants in this endeavor, AWS will also be providing access to Amazon ML Solutions Lab experts and solutions architects to help provide technical support and guidance to contestants to help teams get started in the challenge. The Amazon ML Solutions Lab is a dedicated service offering for AWS customers that provides access to the same talent that built many of Amazon’s machine learning-powered products and services. These Amazon experts help AWS customers utilize machine learning technology to build intelligent solutions that to address some of the world’s toughest challenges like predicting famine, identifying cancer faster, and expediting assistance to areas hard hit by natural disasters. Amazon ML Solutions Lab experts will be paired with Challenge participants to provide assistance throughout the competition.
In addition to serving as a founding member of the Partnership on AI, AWS is also joining the non-profit’s Steering Committee on AI and Media Integrity. The goal, as with sponsorship of the Deepfakes Deception Challenge, is to coordinate the activities of media, tech companies, governments, and academia to promote technologies and policies that strengthen trust in media and help audiences differentiate fact from fiction.
To learn more about the Deepfakes Detection Challenge and receive updates on how to register and participate, visit www.Deepfakedetectionchallenge.ai. Stay tuned for more updates as we get closer to kick-off!
About the Author
Michelle Lee is vice president of the Machine Learning Solutions Lab at AWS.