Abstract :
Abstract Generative artificial intelligence (AI) has emerged as a powerful tool for creative computing, enabling the generation of novel and diverse content across various domains. In this paper, we delve into the field of generative AI, exploring its underlying principles, techniques, and applications in creative computing. We provide an overview of generative models, including generative adversarial networks (GANs), variational autoencoders (VAEs), and autoregressive models, highlighting their capabilities in generating realistic and diverse outputs. Through a review of state-of-the-art research and case studies, we showcase the creative potential of generative AI in generating images, videos, music compositions, and text-based content. We discuss the unique challenges and opportunities associated with generative AI, including issues related to training data, model complexity, and evaluation metrics. Furthermore, we explore the societal and ethical implications of generative AI, including concerns related to intellectual property rights, authenticity, and misuse. Our study aims to inspire further exploration and innovation in the field of creative computing, leveraging generative AI to push the boundaries of human creativity and expression. By harnessing the power of generative AI, researchers, artists, and creators can unlock new possibilities for artistic expression, storytelling, and design. We believe that creative computing with generative AI has the potential to revolutionize various industries, from entertainment and advertising to education and healthcare, paving the way for a more imaginative and innovative future.
Keyword :
Keywords: Creative, Computing, Harnessing, Power, Generative, Artificial, Intelligence