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Mostly a tech demo of something that hasn't really been shown to be possible until now. We've seen lots of GPU heavy models that achieve similar things like thi
by huras 5y ago
Mostly a tech demo of something that hasn't really been shown to be possible until now. We've seen lots of GPU heavy models that achieve similar things like this (often requiring VRAM outside what most consumer GPUs can usually handle), but here I show (after a lot of effort on my part) that cool effects like that are in fact possible to make run decently fast even on mobile web. Hopefully it's inspirational and might nudge some people to try making more cool creative tfjs models that can run on the device (preserving privacy and activating a new layer of fun that's only possible once you get these things real time) rather than hidden behind an API. (I thought that would happen 5 years ago but the phase shift still hasn't really happened for some reason.)
- comboy 5y agoIt sounds like potentially a very decent feat. Some writeup would be nice, even in a comment. How does it work? What problems did you encounter? etc.
- fault1 5y agoBut this is just this just doing a forward evaluation of a NN, not training, right? Ironically, I remember the first Javascript demos (from 1996) I ever saw was a neural net demo: https://web.archive.org/web/19961226105339/http://www.ozemail.com.au/~infoxs/programs/nn/neural.htm https://web.archive.org/web/19961226105339/http://www.ozemai... Probably could be ported easily to ES 2.0 which still runs in most recent browsers. Just like in the late 80s, there was a hype cycle around neural nets in the late 90s.
- ShamelessC 5y ago> But this is just this just doing a forward evaluation of a NN, not training, right? It's been my experience that disabling automatic differentiation for a neural net still uses 50-100% as much memory in the forward pass/inference.