Webinar 5: Deployed Deep Generative Models

Deployed deep generative models have transformed AI applications, particularly in generating images and text. This session covers understanding these applications, ensuring data cleanliness, and identifying suitable tasks. It explores deep image generative models like DALL-E, Midjourney, and Stable Diffusion, highlighting their use in art and design, and challenges like bias and high computational costs. It also delves into large language models like ChatGPT and Bard, explaining their transformer architectures and uses in customer support and content generation, while addressing issues like potential biases and significant computational requirements.

Sarah Alotaibi is an Assistant Professor in the Department of Computer Science at King Saud University. She holds a B.Sc. and M.Sc. in Computer Science from King Saud University and a Ph.D. in Computer Vision from the University of York in the United Kingdom. Her research focuses on computer vision and machine learning, with an interest in deep learning with statistical and appearance modeling, face modeling, reflectance analysis, and inverse rendering. Dr. Alotaibi has published numerous papers in these areas.