> with minimal external dependencies: Python, PostgreSQL, and Kubernetes
What a time to be alive.
All jokes aside, this is really awesome and i'm glad to see more and more tools to make ML more developer friendly and accessible. Out of curiosity do you guys come from a TF, pytorch, jax, etc background?
However, it's only required when running pipelines in the cloud. When running locally (`$ sematic start`), nothing else than Python is required.
Regarding background, we are folks with experience building ML tooling. We've built infra around TF and Pytorch, but none with Jax. That being said, Sematic is agnostic to the framework you want to use.
You can certainly deploy the web app on one server, and run your pipelines on another (or the same). In this case, "locally" would mean that the pipeline and all its steps run on the same host machine. This is totally sufficient in many cases.
Kubernetes becomes interesting when using heterogeneous resources (e.g. GPU nodes for training, high-memory for data processing, etc.), but is not a necessity.
What a time to be alive.
All jokes aside, this is really awesome and i'm glad to see more and more tools to make ML more developer friendly and accessible. Out of curiosity do you guys come from a TF, pytorch, jax, etc background?