> easier ways to train models locally, better pruned models for embedded device inference (e.g. running on a Jetson Nano), easier ways to fine-tune for specific

> easier ways to train models locally, better pruned models for embedded device inference (e.g. running on a Jetson Nano), easier ways to fine-tune for specific contexts I think there are steps being taken in this direction (check out [1] and [2] for interesting lightweight transpile / ad-hoc training projects) but there is a lack of centralized community for these constrained problems. [1] https://github.com/emlearn/emlearn https://github.com/emlearn/emlearn [2] https://github.com/BayesWitnesses/m2cgen https://github.com/BayesWitnesses/m2cgen