determined

Congrats on the launch! This looks interesting, however I feel like this space is quite crowded. You mentioned that your most important feature is the fact that you are open-source, but off the top of my head I can think of several projects: * Kubeflow: https://github.com/kubeflow/kubeflow * MLFlow: https://github.com/mlflow/mlflow * Pachyderm: https://github.com/pachyderm/pachyderm * DVC: https://github.com/iterative/dvc * Polyaxon: https://github.com/polyaxon/polyaxon * Sacred: https://github.com/IDSIA/sacred * pytorch-lightning + grid: https://github.com/PyTorchLightning/pytorch-lightning * DeterminedAI: https://github.com/determined-ai/determined * Metaflow: https://github.com/Netflix/metaflow * Aim: https://github.com/aimhubio/aim * And so many more... In addition to this list, several other hosted platform offer experiments trackin

Hi William -- we have absolutely not copied any of Lightning's APIs. In fact, our PyTorch API makes some significantly different design choices than Lightning does -- e.g., we require users to step optimizers and run the backward pass explicitly, which is a bit lower-level but allows for more flexibility when using the API. For instance, here is an example of a GAN using our PyTorch API: https://github.com/determined-ai/determined/blob/master/exam... This is a port of this PyTorch Lightning example: https://github.com/PyTorchLightning/pytorch-lightning/blob/m... Despite the former being a port of the latter, there are significant differences between the two APIs. More broadly, we welcome competition in this space and think there's a lot that we can all learn from one another.

Congratulations to the Grid team on the fundraise and the announcement! Exciting stuff. It seems like there is an emerging consensus that (a) DL development requires access to massive compute, but (b) if you’re only using off-the-shelf PyTorch or TensorFlow, moving your model from your personal development environment to a cluster or cloud setting is too difficult — it is easy to spend most of your time managing infrastructure rather than developing models. At Determined AI, we’ve spent the last few years building an open source DL training platform that tries to make that process a lot simpler (https://github.com/determined-ai/determined), but I think it's fair to say that this is still very much an open space and an important problem. Curious to take a look at Grid AI and see how it compares to other tools in the space -- some other alt