3 ms·
Jax, for those that haven't heard of it, is the thing y'all want.
by nmca 7y ago
Jax, for those that haven't heard of it, is the thing y'all want.
- mcbuilder 7y agoWith the release of pytorch mobile, people building products will want to use stuff from the Pytorch universe, while researchers who just want to prototype an idea and want a numpy like accelerated interface will look at jax.
- mlevental 7y agowhy would you use Jax over pytorch? even if it has technical merits it lacks an ecosystem of readily available models to study and tweak.
- nmca 7y agoAt some point you stop caring about being able to import a set of imagnet pretrained weights and start caring about extreme flexibility. Think about implement ting, say "Scene Representation Networks" https://arxiv.org/abs/1906.01618 https://arxiv.org/abs/1906.01618 in each of the three frameworks. Tf is a pig, pytorch is slow, and Jax is going to crush the problem. The lack of say, keras.applications is a shame, but it won't last, and if you have a GPU or 8 the power of optimized (p/v)map definitely makes up for it.
- chillee 7y agoI mean, the authors implemented it in pytorch: https://github.com/vsitzmann/scene-representation-networks https://github.com/vsitzmann/scene-representation-networks Do you have any particular evidence that PyTorch is slow here?
- chillee 7y agoI talk about Jax in the article. It's very cool, especially if you need higher order derivatives. However, it's not meant to be a full neural network library, and unless Google invests significantly into it, it won't take off significantly imo.