> At first glance, it seems to be a GPU/TPU based NumPy?
Yes, with a compiler to make this fast.
> The thing is, TF has more than tensor ops. It has pre-defined NN layers, data loading/serialization, distributed training, metrics, and model serving.
Yes, it is a simpler and smaller API.
For things like data loading, you can use the tool of your choice -- TF, pytorch, whatever. For pre-defined NN layers, there are libraries that build this as a very thin wrapper around JAX's low-level API, see e.g. lax, which is include in JAX.
Yes, with a compiler to make this fast.
> The thing is, TF has more than tensor ops. It has pre-defined NN layers, data loading/serialization, distributed training, metrics, and model serving.
Yes, it is a simpler and smaller API.
For things like data loading, you can use the tool of your choice -- TF, pytorch, whatever. For pre-defined NN layers, there are libraries that build this as a very thin wrapper around JAX's low-level API, see e.g. lax, which is include in JAX.