The Impact, Advancements and Applications of Generative AI

Abstract

Generative AI is a subfield of artificial intelligence ecosystem based on developing systems that can generate creative outputs, such as music, images, text content, and more. By harnessing the power of deep learning techniques, specifically generative models, these systems have the ability to create content that matches human-generated creations autonomously. The key to generative AI lies in its ability to learn from datasets and patterns and generate new content that exhibits similar traits. Generative models, such as generative adversarial networks (GANs) and variational autoencoders (VAEs), form the basis of generative AI. GANs consist of two components : (1) a generator and (2) a discriminator network engaged in a competitive & consistent process of generating and evaluating content. VAEs, employ an encoder-decoder architecture to learn and generate new output. This is research on Generative AI and its impact cutting across all verticals.