  The launch of ChatGPT has garnered global attention, marking a significant
milestone in the field of Generative Artificial Intelligence. While Generative
AI has been in effect for the past decade, the introduction of ChatGPT has
ignited a new wave of research and innovation in the AI domain. This surge in
interest has led to the development and release of numerous cutting-edge tools,
such as Bard, Stable Diffusion, DALL-E, Make-A-Video, Runway ML, and Jukebox,
among others. These tools exhibit remarkable capabilities, encompassing tasks
ranging from text generation and music composition, image creation, video
production, code generation, and even scientific work. They are built upon
various state-of-the-art models, including Stable Diffusion, transformer models
like GPT-3 (recent GPT-4), variational autoencoders, and generative adversarial
networks. This advancement in Generative AI presents a wealth of exciting
opportunities and, simultaneously, unprecedented challenges. Throughout this
paper, we have explored these state-of-the-art models, the diverse array of
tasks they can accomplish, the challenges they pose, and the promising future
of Generative Artificial Intelligence.
