WebML WG Teleconference – 2 February 2023 - 15:00-16:00 UTC

Latest version: https://github.com/webmachinelearning/meetings/blob/main/telcons/2023-02-02-wg-agenda.md


WebML WG Teleconference – 2 February 2023 - 15:00-16:00 UTC
San Francisco (U.S.A. - California)     Thu, 2 February 2023    07:00   UTC-8 hours
Boston (U.S.A. - Massachusetts) Thu, 2 February 2023    10:00   UTC-5 hours
London (United Kingdom - England)       Thu, 2 February 2023    15:00   UTC+0 hours (adjusted for DST)
Berlin (Germany)        Thu, 2 February 2023    16:00   UTC+1 hours (adjusted for DST)
Helsinki (Finland)      Thu, 2 February 2023    17:00   UTC+2 hours (adjusted for DST)
Shanghai (China)        Thu, 2 February 2023    23:00   UTC+8 hours (adjusted for DST)
Tokyo (Japan)   Fri, 3 February 2023    00:00   UTC+9 hours (adjusted for DST)
Corresponding UTC (GMT) Thu, 2 February 2023    15:00 UTC

Other locations: https://www.timeanddate.com/worldclock/fixedtime.html?iso=20230202T15


<https://github.com/webmachinelearning/meetings/blob/main/telcons/2023-02-02-wg-agenda.md#logistics>Logistics

  *   Chair: Anssi
  *   Scribe: ? (see howto<https://github.com/webmachinelearning/meetings/blob/main/scribe-howto.md>, volunteers welcome!)
  *   IRC: irc://irc.w3.org:6667/#webmachinelearning

  *   IRC web client: https://irc.w3.org/?channels=#webmachinelearning

  *   Joining instructions: https://lists.w3.org/Archives/Member/internal-webmachinelearning/2020Apr/0000.html

  *   Minutes: https://www.w3.org/2023/02/02-webmachinelearning-minutes.html


<https://github.com/webmachinelearning/meetings/blob/main/telcons/2023-02-02-wg-agenda.md#agenda>Agenda
<https://github.com/webmachinelearning/meetings/blob/main/telcons/2023-02-02-wg-agenda.md#%E2%84%B9%EF%B8%8F-webnn-api-open-prs-and-issues>ℹ️ WebNN API open PRs and issues
Review open PRs and discuss issues. Identify and fast track any priority changes that should get into the initial CR release train.

  *   Simplify MLContext creation: remove MLDeviceType, remove "high-performance" from MLPowerPreference

     *    PR: webmachinelearning/webnn#322<https://github.com/webmachinelearning/webnn/pull/322>
  *   Rework the sync and async algorithms

     *    issue: webmachinelearning/webnn#316<https://github.com/webmachinelearning/webnn/issues/316>
     *    PR: webmachinelearning/webnn#329<https://github.com/webmachinelearning/webnn/pull/329>
     *   Related PR: webmachinelearning/webnn#323<https://github.com/webmachinelearning/webnn/pull/323>
  *   Improve batchNorm

     *    issue: webmachinelearning/webnn#334<https://github.com/webmachinelearning/webnn/issues/334>
     *   Note: We establish a blueprint here for formal op steps to be applied to all ops.
  *   Simplify the operand layout support of conv2d and pooling 2d operations

     *    issue: webmachinelearning/webnn#324<https://github.com/webmachinelearning/webnn/issues/324>
  *   Define the algorithm of calculating the effective padding for "same-upper" and "same-lower" option

     *    issue: webmachinelearning/webnn#326<https://github.com/webmachinelearning/webnn/issues/326>
  *   Clarify the usage of 32 bit floating point type and consider using double

     *    webmachinelearning/webnn#325<https://github.com/webmachinelearning/webnn/issues/325>

<https://github.com/webmachinelearning/meetings/blob/main/telcons/2023-02-02-wg-agenda.md#%E2%84%B9%EF%B8%8F-webml-wg-charter-2023-2025-last-call>ℹ️ WebML WG Charter 2023-2025 Last Call
Web Machine Learning Working Group Charter for 2023-2025 is now ready for W3C AC review. This is a Last Call for WG participants to provide comments before we merge the WebML WG Charter 2023-2025 PR and submit the updated charter for W3C Advisory Committee review. All issues have been triaged and those that received WG support have been addressed. We expect this charter to be operational starting Q2 2023.

  *   Announcement https://lists.w3.org/Archives/Public/public-webmachinelearning-wg/2022Oct/0002.html

  *   Charter PR w3c/machine-learning-charter#19<https://github.com/w3c/machine-learning-charter/pull/19>
  *   Issues https://github.com/w3c/machine-learning-charter/issues