[grobclaw]

While I would love for that to happen. Quite recently (e.g. [1], also discussed on HN, I believe) the Julia community seemed content with more niche applications, quite deliberately choosing not to challenge the biggies (TensorFlow, Torch, etc.) on deep learning, because the amount of mainainers needed to be competitive was just not there.

Is there reason to expect this to change? Maintaining something like Torch and keeping it competitive in terms of speed is a HUGE amount of work for systems development, writing insane numbers of GPU kernels, etc. After having read it, I wouldn't quite yet call the tone of the discussion you linked "serious talk"...

[1]: https://discourse.julialang.org/t/state-of-machine-learning-...