How Transformers Finally Ate Vision – Isaac Robinson, Roboflow
This talk explores the evolution of computer vision models, detailing how transformers, despite lacking inherent inductive biases for vision, ultimately surpassed traditional convolutional neural networks (CNNs). This shift was driven by massive, specialized pre-training techniques and leveraged infrastructure advancements from large language models, enabling transformers to learn visual patterns effectively.
Europe 2026 17 min