August 2nd, 2017

Machine learning comes to your browser via JavaScript

Data Analytics, HTML/CSS/JavaScript, Java Web Development, others, Programing, Scripting and JVM Languages, by admin.

There’s now a JavaScript library for executing neural networks inside a webpage, using the hardware-accelerated graphics API available in modern web browsers.

Developed by a team of MIT graduate students, TensorFire can run TensorFlow-style machine learning models on any GPU, without requiring the GPU-specific middleware typically needed by machine learning libraries such as Keras-js.

TensorFire is another step towards making machine learning available to the broadest possible audience, using hardware and software people are already likely to possess, and via advances in how accurate model predictions can be served with a fraction of the resources previously needed.

The machine learning power is in your browser

TensorFire works using the WebGL standard, a cross-platform system for rendering GPU-accelerated graphics in browsers. WebGL supports GLSL, a C-like language used to write shaders, which are short programs used to transform data directly on the GPU.

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