New DeepMind Approach 'Bootstraps' Self-Supervised Learning of Image Representations

The Cambridge Dictionary defines "bootstrap" as: "to improve your situation or become more successful, without help from others or without advantages that others have." While a machine learning algorithm's strength depends heavily on the quality of data it is fed, an algorithm that can do the work required to improve itself should become even stronger. A team of researchers from DeepMind and Imperial College recently set out to prove that in the arena of computer vision. In the updated paper Bootstrap Your Own Latent – A New Approach to Self-Supervised Learning, the researchers release the source code and checkpoint for their new "BYOL" approach to self-supervised image representation learning along with new theoretical and experimental insights. In computer vision, learning good image representations is critical as it allows for efficient training on downstream tasks. Image representation learning basically leverages neural networks that have been trained to produce good representations.