A SURVEY ON AI-CONTENT GENERATOR

This survey provides an in-depth exploration of AI-driven content generation, covering key areas such as text creation, image synthesis, video generation, and automated coding. By examining advancements in technologies like Large Language Models (LLMs), GANs, and diffusion models, the study highlights AI’s role in transforming diverse fields. Text generation technologies are enabling structured, creative, and conversational outputs, while image and video synthesis models like Imagen and Phenaki are setting new benchmarks for visual quality and realism. In code generation, tools like ChatGPT and GitHub Copilot showcase AI’s ability to translate natural language into efficient, executable code. The survey delves into the mechanisms underpinning these technologies, including transformer-based architectures, hierarchical modeling, and in-context learning. It also emphasizes their practical applications, from streamlining workflows and enhancing creativity to enabling non-experts to leverage sophisticated capabilities. While showcasing these innovations, the paper discusses limitations such as bias in data, high computational costs, and the need for greater contextual understanding in outputs. By synthesizing current research and emerging challenges, this survey offers a comprehensive resource for researchers and practitioners. It underscores the transformative potential of AI in automating and enhancing content generation across domains, paving the way for future advancements in this rapidly evolving field.