Video Generation with AI (Full Colour Edition)

Video generation is rapidly emerging as one of the most exciting applications of generative AI, bringing together computer vision, deep learning, multimodal AI, diffusion models, and spatiotemporal reasoning to create coherent and increasingly realistic moving images. Yet understanding how AI video generation models work—and how to move from experimentation to production—can be challenging.

Video Generation with AI: Working with Diffusion Transformers and Multimodal Learning provides a practical and accessible guide to the technologies behind modern AI-generated video and video generative models. Author Joseph Enochs draws on his experience leading enterprise AI projects to explain how diffusion transformers, multimodal large language models, multimodal encoders, and spatiotemporal architectures work together to generate high-quality video.

The book explores the foundations of generative AI for video, helping readers understand the architectures and techniques used in modern video generation systems. It also examines how diffusion models and transformers can be trained and fine-tuned, how multimodal information can be incorporated into video generation, and how AI systems can maintain consistency across individual frames and longer sequences.

With technical explanations and practical examples, readers can learn how to progress from AI video generation experiments to production-ready systems. The book also considers applications of generative video technology across creative industries, media, industrial environments, scientific workflows, and human-machine collaboration.

Whether you are exploring text-to-video AI, generative video models, multimodal AI, computer vision, or the future of AI-powered video creation, this book provides a useful foundation for understanding the rapidly evolving field.

What You Will Learn

• Understand the fundamental architectures behind modern AI video generation and video generative models.
• Explore how diffusion transformers and transformer-based architectures are used for generative video.
• Train and fine-tune AI models using diffusion transformers and multimodal encoders.
• Understand the role of multimodal learning and multimodal large language models in video generation.
• Learn techniques for maintaining temporal coherence and visual consistency across complex scenes and video sequences.
• Explore spatiotemporal architectures used to model movement, frames, and long-range video relationships.
• Apply generative AI and AI video generation to creative, media, industrial, and scientific workflows.
• Understand approaches to text-to-video generation and AI-powered video synthesis.
• Evaluate, troubleshoot, and improve AI-generated video quality at scale.
• Learn how to move from isolated AI experiments toward production-ready generative video systems.
• Explore the growing role of AI-generated video in creative industries and human-machine collaboration.

About the Author

Joseph Enochs is a technology executive, AI strategist, and award-winning speaker with over 15 years of experience in driving transformative Enterprise Data and AI solutions. He currently serves as Managing Director of AI/ML and Emerging Technologies at EVT, where he pioneers the development of accessible and ethical Generative AI systems. Joseph has delivered keynote presentations on AI’s role in enterprise transformation, most recently for The Profound Podcast and Disney’s Internal JETA Training Academy.