Building scalable systems to understand content

This post details the development and scaling of FBLearner Flow, a general-purpose platform for machine learning pipelines, and Lumos, a computer vision platform built on top of FBLearner Flow. It highlights the transition of FBLearner Flow from a research project to a production-scale system supporting 1.2 million AI experiments per month. Lumos is presented as the engine for image and video understanding, enabling engineers to train and deploy models without deep learning expertise. Specific applications discussed include automatic alt text (AAT) for the visually impaired, with an update to include actions, and visual search capabilities powered by object recognition and image embeddings. The post emphasizes the iterative nature of model improvement through data labeling and the use of semantic clustering for data generation.