Abstract
In recent years, the field of generative artificial intelligence (AI) has witnessed remarkable advancements, transforming various domains from art and music to language and healthcare. Advanced techniques, such as conditional generation, style transfer, and unsupervised learning, showcase the cutting-edge research shaping the field. The ability of generative AI models to create novel content autonomously has sparked immense interest and innovation. Future directions provide speculations for potential breakthroughs, challenges, and opportunities for further research and innovation.
Generative AI Foundations, Developments, and Applications serves as a resource to understanding generative AI across various domains including natural language processing, computer vision, and drug discovery. It explores the theoretical foundations, latest developments, and practical applications of generative AI. Covering topics such as prompt engineering, multimodal data fusion, and natural language processing, this book is an excellent resource for computer scientists, computer engineers, practitioners, professionals, researchers, scholars, academicians, and more.
Coverage:
The many academic areas covered in this publication include, but are not limited to:
Advanced Optimization Techniques
Communication Skills
Crop Health Monitoring
Data Augmentation
Deep Convolutional Generative Adversarial Networks (DCGANs)
First-Year Medical and Dental Students
Generative Artificial Intelligence (GAI)
Insurance Industry
Machine Vision
Multi/Hyperspectral Imaging
Multimodal Data Fusion
Narrative Machines
Natural Language Processing (NLP)
Prompt Engineering
Retrieval Augmented Generation (RAG) Pipeline
Unsupervised Learning
Generative AI Foundations, Developments, and Applications serves as a resource to understanding generative AI across various domains including natural language processing, computer vision, and drug discovery. It explores the theoretical foundations, latest developments, and practical applications of generative AI. Covering topics such as prompt engineering, multimodal data fusion, and natural language processing, this book is an excellent resource for computer scientists, computer engineers, practitioners, professionals, researchers, scholars, academicians, and more.
Coverage:
The many academic areas covered in this publication include, but are not limited to:
Advanced Optimization Techniques
Communication Skills
Crop Health Monitoring
Data Augmentation
Deep Convolutional Generative Adversarial Networks (DCGANs)
First-Year Medical and Dental Students
Generative Artificial Intelligence (GAI)
Insurance Industry
Machine Vision
Multi/Hyperspectral Imaging
Multimodal Data Fusion
Narrative Machines
Natural Language Processing (NLP)
Prompt Engineering
Retrieval Augmented Generation (RAG) Pipeline
Unsupervised Learning
| Original language | English |
|---|---|
| Publisher | IGI Global Publishing |
| Number of pages | 378 |
| DOIs | |
| Publication status | Published - 1 Mar 2025 |