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Comment by netheril96 | Hacker News Reader

For any non trivial deep network, any CPU based training is horrendously slow, even if multithreaded. So, Javascript is doomed at it. Python is not, as it can interact with native binaries which may talk with the GPU.

> Something that I do not agree with myself, as a Node.js and back-end JS developer

NodeJS mostly works when CPU time is not the limiting factor, that is, powering the Web. Neural network is the polar opposite.

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> Python is not, as it can interact with native binaries

It sounds like what you actually mean here is that Python is equally as unsuitable and must instead use native binaries. Which one could just as easily do with JS...

A reasonable argument could be that such native binaries are available in the Python community and already in use as stable existing solutions, but that's more about ecosystem than language suitability.

Additionally, while I'm not too sure what convnet, node-mind, brain.js, etc. referenced in the article are using internally, there are gpu-oriented solutions being written in JS like https://www.npmjs.com/package/weblas

Python is dog slow. This is why it is used as a glue language for C modules. This is the canonical way to do things. Javascript OTOH is decently fast on its own, but you can't really interact with libraries written in C or FORTRAN, as far as I know.

https://github.com/node-ffi/node-ffi

Cool, good to know.

Node has been able to interoperate with C/C for some time, via node-gyp and node-ffi.

Well, somebody could write a NodeJS library that talks to the GPU.

Atwood's Law makes it inevitable that someone will if no one has already.

Absolutely true. https://github.com/kashif/node-cuda

Also of note: https://github.com/nikhilk/node-tensorflow

I think they mean that JS is good for more than just FE which doesn't necessarily mean Neural Networks..

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