Speaking of making machine learning-powered experiences fast & ubiquitous via the Web, check out the latest work from our friends on TensorFlow.js:

In March we introduced a new WebAssembly (Wasm) accelerated backend for TensorFlow.js (scroll further down to learn more about Wasm and why this is important). Today we are excited to announce a major performance update: as of TensorFlow.js version 2.3.0, our Wasm backend has become up to 10X faster by leveraging SIMD (vector) instructions and multithreading via XNNPACK, a highly optimized library of neural network operators.

You can see the performance improvements for yourself:

Check out this demo of our BlazeFace model, which has been updated to use the new Wasm backend: https://tfjs-wasm-simd-demo.netlify.app/ To compare against the unoptimized binary, try this version of the demo, which manually turns off SIMD and multithreading support.