JFT-300M is an internal Google dataset used for training image classification models. Images are labeled using an algorithm that uses complex mixture of raw web signals, connections between web-pages and user feedback. This results in over one billion la
JFT-3B is an internal Google dataset and a larger version of the JFT-300M dataset. It consists of nearly 3 billion images, annotated with a class-hierarchy of around 30k labels via a semi-automatic pipeline. In other words, the data and associated labels