Modern generative AI is characterized by the rise of neural networks, which are inspired by the structure of the human brain and trained to identify patterns within data. After training, these networks can make decisions or predictions autonomously, without explicit programming for specific tasks. Generative AI systems learn from data independently and are capable of producing new digital content, including text, audio, and visual art. Recent advancements have begun to address obstacles such as computational demands, data quality, and training stability.
This edited volume on generative AI offers fresh insights, innovative methods, and a discussion of security, ethical, and legal issues, as well as emerging trends. It covers a range of topics and technologies, including generative transformers and text generation, models for human-like speech synthesis, generative AI for image creation, data synthesis for privacy, and the influence of generative AI in areas such as Industry 4.0, astronomy, and brain tumor detection. The book also includes two chapters dedicated to ethical and legal perspectives.
Generative AI Unleashed: Advancements, Transformative Applications and Future Frontiers is an essential resource for researchers, engineers, advanced students, and educators working in fields that are being transformed by generative AI.
