Especially feedback like yours is super appreciated, as we can gauge opinions and evaluate them against our roadmap, so thanks :).
ZenML unfortunately does not yet work with PyTorch, but it’s one of the biggest points for our roadmap next year.
1. Pytorch is getting better at deployment. The only reason to use TF until recently was its superior deployment capabilities.
2. Google itself finally realized what a clusterfuck TF has been, threw in the towel, and started fresh with Jax.
3. Pytorch is king in research. ML is still very much a research driven field, so whatever researchers choose is going to win sooner or later. Jax is a serious contender though.
Google invested a lot in TF development, and the inertia will keep it alive for a couple more years, but the writing on the wall is clear.
Are you seeing something like an eager mode for your library, or perhaps a pytorch plugin that might use your apis?
So, to answer in short: there is a longer development cycle behind this, but not in the open - and no VC backing.
