Evolution and Real-world Applications of Generative Artificial Intelligence and Data Mining in a Digital World

Abstract

By learning from patterns in vast datasets using models like GPT (for text), DALL·E (for images), and Codex (for code), generative artificial intelligence (Gen-AI) has become a veritable tool in data mining. This paper provides a detailed analysis of the evolution and creative impact of data mining in Gen-AI. It traces the origin of AI to the 1956 Dartmouth Conference, highlighting the subsequent advancements in technologies such as machine learning and data mining that have progressively sped-up the digital growth of AI. The paper also highlights some real-world applications of data mining in Gen-AI such as healthcare, finance, manufacturing, social media, retail and cybersecurity. It reveals how data mining powers Gen-AI and how Gen-AI enhances data mining. Owing to the fact that Gen-AI relies on data mining to learn patterns and generate new content, the paper raises several concerns on the relationship such as bias and discrimination, data privacy and security and intellectual property and copyright. The paper also illustrates a design for Gen-AI and data mining use case tailored for field of computer science.