Indeed, deployment is a whole set of interesting issues. We haven't deployed any learned models in production yet at OpenAI, so it's not at the top of our list.
If the data and models were small and training was quick (on the order of compilation time), I'd just keep the training data in git and train the model from scratch every time I run make. But the data is huge, training requires clusters of machines and can take days, so you need a pipeline.
If the data and models were small and training was quick (on the order of compilation time), I'd just keep the training data in git and train the model from scratch every time I run make. But the data is huge, training requires clusters of machines and can take days, so you need a pipeline.
An industrial strength system looks like this: https://code.facebook.com/posts/1072626246134461/introducing...