Generative AI for visualization

Jhanjhi, N. Z.; Shah, Imdad Ali; Nawaz, Sarfraz

Abstract

The primary objective of this chapter is focused on improvement and helping Generative AI for visualization such as automating the design of visuals and making it easier to understand patterns, trends, and outliers. Recent advances in machine learning (ML) and artificial intelligence (AI) have produced potent generative AI tools and techniques that can generate text, code, graphics, and other media in response to human commands. The technology has generated a lot of curiosity, which has led to conjecture about the fields—visualization included—that such methods could replace or enhance. Still unknown, though, is whether visualization tasks would be especially well-suited to the use of generative artificial intelligence. In recent years, generative artificial intelligence (GenAI) has advanced significantly and shown outstanding performance in a variety of generating tasks across multiple disciplines, including computational design and computer vision. A lot of academics have tried to use GenAI's enhanced generative capacity for various tasks by integrating it into visualization frameworks. We map the present and future capabilities of generative AI throughout the various stages of the visualization lifecycle and highlight key potentials and problems using real-world examples from the field. AI provides answers for a wide range of issues that both consumers and business owners face. Computer-based information can benefit economic growth, organizations, managers, and buyers. Without a doubt, AI improves human lives. Artificial intelligence has the potential to improve economic growth and raise everyone's standard of living. People and businesses everywhere are eager to invest in human resources, and e-business is crucial to continuously providing customers with the easiest way to purchase goods and services. AI and ML are being applied in an increasing number of different use cases as a result of the emergence of new, significantly enhanced AI and ML technology and applications. The widespread use of AI solutions in people's daily lives and the operations of several organizations raises the possibility of new risks and weaknesses.

• Publication Date: Sep 27, 2024
• Deposit Date: Dec 12, 2024
• Publisher: IGI Global
• Peer Reviewed: Peer Reviewed
• Pages: 63-82
• Book Title: Generative AI for Web Engineering Models
• ISBN: 9798369337035
• DOI: https://doi.org/10.4018/979-8-3693-3703-5.ch003
• Public URL: https://uwe-repository.worktribe.com/output/13364552