- From: Dominique Hazael-Massieux <dom@w3.org>
- Date: Tue, 7 Mar 2023 11:37:53 +0100
- To: "public-webmachinelearning-wg@w3.org" <public-webmachinelearning-wg@w3.org>
The new charter for our Working Group is now under W3C Advisory Committee review - please make sure your Advisory Committee representative brings input (and ideally support) on the review. Dom -------- Message transféré -------- Sujet : VOTE by 2023-04-04/05: Proposed Charter for the Web Machine Learning Working Group Date : Tue, 7 Mar 2023 17:30:51 +0800 Dear Advisory Committee Representative, [This announcement will be forwarded to W3C group chairs] This is a Call for Review of a proposed recharter for the Web Machine Learning Working Group: https://www.w3.org/2023/03/proposed-webmachinelearning-charter.html Please review the charter and indicate your support using this online form: https://www.w3.org/2002/09/wbs/33280/webmachinelearning-charter-2023/ The deadline for responses is 03:59 UTC on 5 April 2023 (23:59, Boston time on 4 April 2023) [0]. The mission of the Web Machine Learning Working Group is to develop APIs for enabling efficient machine learning inference in the browser. This proposed charter is a continuation of the current charter to allow continued work on the Web Neural Network (WebNN) API [1] as it starts its implementation-experience phase through its requested Candidate Recommendation status [2]. The proposed team resource for the group remains unchanged at 0.1 FTE. A diff from the current charter is available [3]. Current participants will not need to re-join the group if the new charter is approved. If you have any questions or need further information, please contact Dominique Hazael-Massieux, Web Machine Learning Working Group Staff Contact, at dom@w3.org. This charter review follows section 4.3 of the W3C Process Document: https://www.w3.org/2021/Process-20211102/#CharterReview Thank you, For Tim Berners-Lee, W3C Director, Dominique Hazael-Massieux, Web Machine Learning Working Group Staff Contact; Xueyuan Jia, W3C Marketing & Communications [0] https://www.timeanddate.com/worldclock/fixedtime.html?msg=4&iso=20230404T2359&p1=43 [1] https://www.w3.org/TR/webnn/ [2] https://github.com/w3c/transitions/issues/491 [3] https://services.w3.org/htmldiff?doc1=https%3A%2F%2Fwww.w3.org%2F2021%2F04%2Fweb-machine-learning-charter.html&doc2=https%3A%2F%2Fwww.w3.org%2F2023%2F03%2Fproposed-webmachinelearning-charter.html
Received on Tuesday, 7 March 2023 10:37:56 UTC