Modular networks with dynamic routing for multi-task recurrent modules

A system for training a neural network model, comprising:

• a hardware processor;
• and
• a memory that stores computer program code, which, when executed by the hardware processor, implements:
• a multitask neural network model;
• a modular neural network model that has a shared encoder, one or more task-specific decoders, and one or more policy networks that control connections between the shared encoder and the one or more task-specific decoders in accordance with multiple tasks;
• a combiner that combines an output of the multitask neural network model to form a final output;
• and
• a model trainer that trains the modular neural network model, including training the one or more policy networks, and that trains the multitask neural network model for the multiple tasks.