How AI Taught Itself to See [DINOv3]

How can we train a general-purpose vision model to perceive our visual world? This video dives into the fascinating idea of self-supervised learning. We will discuss the basic concepts of transfer learning, contrastive language-image pretraining (CLIP), and self-supervised learning methods, including masked autoencoder, contrastive methods like SimCLR, and self-distillation methods like DINOv1, v2, and v3. I hope you enjoy the video! 00:00 Introduction 00:33 Why do features matter? 01:11 Learning features using classification 02:14 Learning features using language (CLIP) 04:09 Learning fea…