It looks like MLX is a part of this initiative. https://github.com/apple/corenet lists "MLX examples" as one of the components being released in April.

As mentioned in the "mlx_examples/open_elm": "MLX is an Apple deep learning framework similar in spirit to PyTorch, which is optimized for Apple Silicon based hardware."

It's a layer on top of PyTorch, and it has code to translate PyTorch models into MLX.

So, is CoreNet the equivalent of Keras, whereas MLX is the Jax/PyTorch equivalent?

Sounds reasonable. Apple writes the following about MLX: "The design of MLX is inspired by frameworks like NumPy, PyTorch, Jax, and ArrayFire."

Not quite. The closest equivalent would be something like fairseq. It's config (yaml) driven.