To deploy a model in js (as a web page) all you need is a static S3 or GCS bucket.
First of all, what you have described is far from the reality.
Had this come true, only inference will be in javascript, through some language agnostic standardized model format, not training. The model is just a blackbox function for the js runtime to call. The amount of javascript to make this happen will be surprisingly slim anyway.
First of all, what you have described is far from the reality.
Did you try any of the links I included? This is the reality for all of them and they are a few years old. They have a model file loaded from bucket url and never make another network request thereafter.
It's actually the recommended workflow from https://js.tensorflow.org/ where you'd find tons of other examples.
But you're right, this is for inference only. I would not do training in JS.
What I mean reality here is the running nn model in browser is possible, but not practically efficient, so even with its perceived simplicity, people would under most occasions, run the inference in the cloud, with its controllability and performance, like using customized hardware. After all, running inference is about to run it reliably and fast, until the day when nn operations are ubiquitous and common enough to be standardized and shipped in performant runtime that come out-of-box, browser inference is still a dream that is too good to be true.
Comments
First of all, what you have described is far from the reality.
Had this come true, only inference will be in javascript, through some language agnostic standardized model format, not training. The model is just a blackbox function for the js runtime to call. The amount of javascript to make this happen will be surprisingly slim anyway.
Did you try any of the links I included? This is the reality for all of them and they are a few years old. They have a model file loaded from bucket url and never make another network request thereafter.
It's actually the recommended workflow from https://js.tensorflow.org/ where you'd find tons of other examples.
But you're right, this is for inference only. I would not do training in JS.
What I mean reality here is the running nn model in browser is possible, but not practically efficient, so even with its perceived simplicity, people would under most occasions, run the inference in the cloud, with its controllability and performance, like using customized hardware. After all, running inference is about to run it reliably and fast, until the day when nn operations are ubiquitous and common enough to be standardized and shipped in performant runtime that come out-of-box, browser inference is still a dream that is too good to be true.