Pedro Cuenca is a Machine Learning Engineer at Hugging Face working on diffusion software, models, and applications. He has 20+ years of software development experience in fields like Internet applications (in Spain, he helped create the first interactive educational portal, the first book store, and the first free ISP) and, more recently, iOS. As a co-founder and CTO of LateNiteSoft, he worked on the technology behind Camera+, a successful iPhone photography app. He created deep-learning models for tasks such as photography enhancement and super-resolution. He was also involved in the development and operations behind dalle-mini. He brings a practical vision of integrating AI research into real-world services and the challenges and optimizations involved.

Apolinário Passos is a Machine Learning Art Engineer at Hugging Face working across different teams on multiple machine learning for art and creativity use-cases. Apolinario has 10+ years of professional and artistic experience, alternating between holding art exhibitions, coding, and product management, having been a Head of Product in World Data Lab. Apolinario aims to ensure that the ML ecosystem supports and makes sense for artistic use cases.

Jonathan Whitaker is a data scientist and deep learning researcher focused on generative modeling. He has previously worked on several courses related to the topics covered in this book, including the Hugging Face diffusion models class and Fast.AI’s ‘From Deep Learning Foundations to Stable Diffusion’ which he co-created with Jeremy Howard in 2022. He has also applied these techniques in industry during his time as a consultant and now works full-time on AI research and development at Answer.AI.