Episode 31: The Technology Behind Deepfakes

In Episode 29 of Pardon The Disruption, the team discussed the world of Deepfakes. But what is the underlying technology behind Deepfakes? Generative Adversarial Networks (GAN), is extremely interesting and could have profound implications for distorting reality when it comes to generating fake videos or images. Created by the researcher Ian Goodfellow at the age of 28, Generative Adversarial Networks are two artificial neural networks which compete against each other. In the case of deep fake images, one network (the generator) tries to generate an image which the other network discriminates (the discriminator). In essence, the generator is trying to fool the discriminator into believing the data, or image, is fake - and it continues to generate images until this objective is met. - What are Generative Adversarial Networks (GANs)? (2:14) - The role of the Generator and Discriminator in GANs (5:00) - Why Is This Important? (8:50) - Where will GANs be used in the future? (9:25) - Deep fake images are just the start (10:20) - Generating Complete Data (14:00) - Variational Auto-Encoders (What JPG did for image compression) (14:44) - Faking Social Media profiles (20:10) - Machine-Brain Interfaces (21:41) Links used in the show: A Beginner's Guide to GANs: https://skymind.ai/wiki/generative-adversarial-network-gan Play with GANs (The GAN Lab): https://poloclub.github.io/ganlab/ ________________________________________________________________ Leave some feedback: • What should we talk about next? Please let us know on Twitter - twitter.com/rumjog or in the comments below. • Enjoyed this episode? Let us know your thoughts in the comments, and please be sure to subscribe. ⚡️ Subscribe to Podcast: Google Play: bit.ly/2Cl97VS iTunes: apple.co/2SEndI8 Spotify: spoti.fi/2W7OB2N Stitcher: bit.ly/2XXwLkA SoundCloud: bit.ly/2Y0t25Z 🧔 Bio: The world is changing and so is the way we work. At Rumjog, we provide clients with consulting services to help rethink business. We advise at every stage of the change lifecycle from constructing strategies to solution implementation. ☕️ Direct Contact: [email protected]