We recently released Autograd for Torch, which greatly simplified our workflow when experimenting with complex deep learning architectures. The Twitter Cortex team is continuously investing in better tooling for manipulating our large datasets, and distributing training processes across machines in our cluster.
Today we’re open-sourcing four components of our training pipeline, so the community using Torch and/or Autograd can simplify their workflows when it comes to parallelizing training, and manipulating large, distributed datasets.
Once again, we’re pleased to sponsor and participate in #MesosCon. As heavy users of both Mesos and Apache Aurora to power our cloud infrastructure, we’re excited to be part of this growing community event.