World Wide Web Consortium (W3C) Workshop Report on Web and Machine Learning
From the World Wide Web Consortium:
This report contains a brief summary and collects highlights from the individual sessions, and links to the presentation videos. This first-ever virtual W3C workshop kicked off with the publication of 34 talks in August 2020 discussing opportunities and challenges of browser-based machine learning, web platform foundations, as well as developer’s, and user’s perspectives into machine learning technologies in the context of the web platform.
The workshop participants identified as a prime standardization opportunity the low-level primitives for machine learning inference exposed through the Web Neural Network API. This work has been incubated at a W3C Community Group since late 2018. Following the workshop, as a concrete next step, the W3C sent an advance notice of the development of a charter for a Web Machine Learning Working Group to standardize the Web Neural Network API.
Direct to Full Text: W3C Workshop on Web and Machine Learning
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Gary Price (email@example.com) is a librarian, writer, consultant, and frequent conference speaker based in the Washington D.C. metro area. He earned his MLIS degree from Wayne State University in Detroit. Price has won several awards including the SLA Innovations in Technology Award and Alumnus of the Year from the Wayne St. University Library and Information Science Program. From 2006-2009 he was Director of Online Information Services at Ask.com. Gary is also the co-founder of infoDJ an innovation research consultancy supporting corporate product and business model teams with just-in-time fact and insight finding.