Parameter Server approaches for online learning at Twitter allow models to be updated continuously based on new data and improve predictions in real-time. Version 1.0 decouples training and prediction to increase efficiency. Version 2.0 scales training by distributing it across servers. Version 3.0 will scale large complex models by sharding models and features across multiple servers. These approaches enable Twitter to perform online learning on massive datasets and complex models in real-time.