Generating a new reality: From autoencoders and adversarial networks to deepfakes

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Abstract

The emergence of artificial intelligence (AI) has brought us to the precipice of a new age where we struggle to understand what is real, from advanced CGI in movies to even faking the news. AI that was developed to understand our reality is now being used to create its own reality. In this book we look at the many AI techniques capable of generating new realities. We start with the basics of deep learning. Then we move on to autoencoders and generative adversarial networks (GANs). We explore variations of GAN to generate content. The book ends with an in-depth look at the most popular generator projects. By the end of this book you will understand the AI techniques used to generate different forms of content. You will be able to use these techniques for your own amusement or professional career to both impress and educate others around you and give you the ability to transform your own reality into something new. What You Will Learn: Know the fundamentals of content generation from autoencoders to generative adversarial networks (GANs). Explore variations of GAN. Understand the basics of other forms of content generation. Use advanced projects such as Faceswap, deepfakes, DeOldify, and StyleGAN2. Who This Book Is For: Machine learning developers and AI enthusiasts who want to understand AI content generation techniques.

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APA

Lanham, M. (2021). Generating a new reality: From autoencoders and adversarial networks to deepfakes. Generating a New Reality: From Autoencoders and Adversarial Networks to Deepfakes (pp. 1–321). Apress Media LLC. https://doi.org/10.1007/978-1-4842-7092-9

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