YouTube

How to Generate AI Images: GANs, Stable Diffusion & Visual Language Models Explained in 8 Minutes.

29 Jun 2026

7:32

9 reproducciones

How does AI create images that look real—even when the people, places, or scenes never existed? In this video, Luka Anicin explores the evolution of AI image generation, from Generative Adversarial Networks (GANs) to Diffusion Models like Stable Diffusion, DALL·E, and Midjourney, and finally to Visual Language Models (VLMs) that can both generate and understand images. You'll learn how GANs sparked the first wave of realistic AI-generated images, why diffusion models became the dominant approach for modern image generation, and how Visual Language Models are pushing AI beyond image creation into image understanding and multimodal reasoning. Topics covered: • What GANs (Generative Adversarial Networks) are and how they work • Why ThisPersonDoesNotExist became a breakthrough AI demonstration • How Diffusion Models generate images from noise • Stable Diffusion, DALL·E, and Midjourney explained • What Visual Language Models (VLMs) are • How AI combines image understanding and language generation • The strengths and limitations of GANs, Diffusion Models, and VLMs • The future of multimodal AI systems Whether you're studying Generative AI, Machine Learning, Computer Vision, or AI Engineering, this video will help you understand the technologies powering today's most advanced image-generation systems. @Saras_AI_Institute