ml5-library VS uWebSockets.js

Important APIs - ml5 for in-browser detection, face-api that uses tensorflow-node to accelerate on-server detection. VueUse for a bunch of useful component tools like the QR Code generator. Yahoo's Gifshot for creating gif files in-browser etc.

> Have we seen any creator of a deep learning library, take a similar position if not stopping any support for anyone using it for mass surveillance?

ml5.js license:

> This license gives everyone as much permission to work with this software as possible as long as they comply with the ml5.js Code of Conduct [...]

ml5.js code of conduct:

> Do not: [...] Use ml5.js to build tools of mass surveillance and prediction to repress the rights of people

https://github.com/ml5js/ml5-library/blob/main/LICENSE.md

Not sure how enforcable this is but it exists.

See also: https://ml5js.org/

"The library provides access to machine learning algorithms and models in the browser, building on top of TensorFlow.js with no other external dependencies."

(5) ml5.js

ML.js

I used ml5js.org , p5js.org and https://teachablemachine.withgoogle.com to train the Banana images. When you create a new image project on Teachable Machine, you can output the p5js and basically use it right out of the box - I customized js, css, and html from there.

Going forward: I'll be 100% into JavaScript. You can use JavaScript in so many fields nowadays. Websites React, Mobile Apps React Native, Machine Learning TensorFlow & ML5, Desktop Applications Electron, and of course the backend Node as well. It's kind of a no-brainer. Of course, they all have specific languages that are better, but for now, JavaScript is a bit of a catch-all.

Yeah they made ml5.js for this reason: https://ml5js.org/

I do feel like Google could do better communicating all of their different tools though. Their ecosystem is large and pretty confusing - they've got so many projects going on at once that it always seems like everyone gets fed up with them before they take a second pass and make them more friendly to newcomers.

Facebook seems to have taken a much more focused approach as you can see with PyTorch Live

From other comments, a lot of JavaScript developers who want to use TensorFlow had never heard of TensorFlow.js or ml5.js!

If you have never heard of Soketi, to give you a brief overview, it is a WebSocket server that was built on top of uWebSockets.js and has great compatibility with Pusher Protocol.

# Clone the repo w/ submodules git clone --recursive https://github.com/uNetworking/uWebSockets.js.git # Cd into the folder cd uWebSockets.js # build make

have you tried https://github.com/uNetworking/uWebSockets.js/

If you'd like to test cluster mode, then use v19.3.0 as it described here https://github.com/uNetworking/uWebSockets.js/issues/593

The fastest node framework is uWebSockets (as they claim, I didn't try it yet), so if Kita's goal is to maximize performance - you should check on it.

I'm serving several hundred thousands queries per second from a single nodejs server (multithreaded) with this: https://github.com/uNetworking/uWebSockets.js/

https://github.com/uNetworking/uWebSockets.js/ ^ this is the best for performance