Hugo Touvron

Hugo Touvron, a PhD student at Facebook AI Research and the primary author of the Data-efficient Image Transformers paper, shares insights on revolutionizing vision models. He explains how novel training strategies and a unique distillation token dramatically improve sample efficiency. The conversation dives into the balance of data augmentation, the implications of transformers compared to CNNs, and challenges in achieving data-driven models. Hugo also reflects on his experiences in a corporate PhD program and the future prospects of transformers in computer vision.