Distributed training is a model training paradigm that involves spreading training workload across multiple worker nodes, therefore significantly improving the speed of training and model accuracy.

Abstract: Sim-to-real gap has long posed a significant challenge for robot learning in simulation, preventing the deployment of learned models in the real world. Previous work has primarily focused on ...

Abstract: Recent advances in autonomous system simulation platforms have significantly enhanced the safe and scalable testing of driving policies. Although existing simulators have greatly accelerated ...

* Distribute training across multiple GPUs with Ray Train with minimal code changes. * Stream training data from Hugging Face datasets with Ray Data's distributed workers. * Save and load distributed ...

Northrop Grumman Corporation NOC recently secured a $225.1 million contract to design, develop and deliver training materials for the E-130J weapons systems training program. The contract was awarded ...