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W3C workshop about Machine Learning APIs in ECMAScript/JavaScript


Ecma TC53 Chair presents at W3C virtual workshop on Web and Machine Learning

Geneva, 16 September 2020

This W3C workshop concerns Machine Learning APIs in ECMAScript/JavaScript in the browser. Peter Hoddie of Moddable and Chair of Ecma TC53, ECMAScript Modules for Embedded Systems, explored how Machine Learning work could be extended to low cost, resource constrained embedded devices. That would be a big win because the web is just part of the world of digital devices. If developers could share their Machine Learning knowledge, experience, and even code across more devices, that could only accelerate availability of products that benefit users. Embedded silicon providers are already beginning to integrate Machine Learning hardware accelerators in the embedded silicon that powers IoT products. Resource constrained embedded devices are very low cost microcontrollers and not powerful enough to run Linux or Node.js, but powerful enough to run standard ECMAScript/JavaScript.

TC53 is currently defining standard ECMAScript/JavaScript APIs for low level device operations -- digital, I2C, serial, network sockets, etc. From there, the TC is building on that foundation to support sensors, displays, and more.

The presentation is available on the W3C website.

For more information: please contact Patrick Luthi, Secretary General of Ecma International at media@ecma-international.org.


 

 

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