Generative AI: Beyond ChatGPT

Abstract

Generative Artificial Intelligence (AI) has become an important area of computer science, changing the way people create, process, and interact with digital content. Although ChatGPT has made Generative AI widely known, its capabilities extend far beyond conversational systems. Generative AI includes several technologies, such as Large Language Models (LLMs), Generative Adversarial Networks (GANs), Variational Autoencoders (VAEs), and Diffusion Models, which can generate text, images, audio, video, software code, and other forms of content. This paper examines the development of Generative AI and its applications in different fields. In education, it can support personalized learning and content generation, while in healthcare it can assist with medical imaging and drug research. In software development, Generative AI can support code generation and debugging. It is also being used in entertainment, business automation, and scientific research. However, the rapid growth of this technology has introduced several challenges, including inaccurate or misleading outputs, privacy concerns, copyright issues, bias in generated content, and security risks. These challenges highlight the importance of responsible development and use of Generative AI. This paper discusses how Generative AI is evolving beyond ChatGPT and explores its potential to support human creativity and problem-solving. It also emphasizes the need for reliable, transparent, secure, and responsible AI systems for future applications.