WebML WG Teleconference – 10 August 2023 - 14:00-15:00 UTC

Latest version: https://github.com/webmachinelearning/meetings/blob/main/telcons/2023-08-10-wg-agenda.md


WebML WG Teleconference – 10 August 2023 - 14:00-15:00 UTC
See the timezone table ...
<https://github.com/webmachinelearning/meetings/blob/main/telcons/2023-08-10-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/2023Jun/0000.html

  *   Minutes: https://www.w3.org/2023/08/10-webmachinelearning-minutes.html


<https://github.com/webmachinelearning/meetings/blob/main/telcons/2023-08-10-wg-agenda.md#agenda>Agenda
<https://github.com/webmachinelearning/meetings/blob/main/telcons/2023-08-10-wg-agenda.md#%E2%84%B9%EF%B8%8F-announcements>ℹ️ Announcements

Implementation Status of WebNN Operations updated per WG's feedback:

  *   Updated status page: https://webmachinelearning.github.io/webnn-status/

  *   Summary of changes: webmachinelearning/webmachinelearning.github.io#52<https://github.com/webmachinelearning/webmachinelearning.github.io/pull/52>

<https://github.com/webmachinelearning/meetings/blob/main/telcons/2023-08-10-wg-agenda.md#%E2%84%B9%EF%B8%8F-webnn-v2-text-to-image-and-text-to-text-use-cases-and-requirements>ℹ️ WebNN v2: text-to-image and text-to-text use cases and requirements

Discuss transformer-based generative AI use cases for text-to-image and text-to-text models. Solicit input on new ops and data types required to support selected models informed by prototyping efforts. Background material:

  *   Transformers.js presentation by Joshua Lochner<https://lists.w3.org/Archives/Public/www-archive/2023Jun/att-0000/Transformers_js.pdf>
  *   Transformer models presentation by Dwayne Robinson<https://lists.w3.org/Archives/Public/www-archive/2023Jun/att-0005/2023-06-29_WebNN_and_Transformers_Progress_W3C.pdf>
  *   Transformer-based models and use cases discussion: webmachinelearning/webnn#375<https://github.com/webmachinelearning/webnn/issues/375>

<https://github.com/webmachinelearning/meetings/blob/main/telcons/2023-08-10-wg-agenda.md#%E2%84%B9%EF%B8%8F-webidl-and-infra-standard-conventions>ℹ️ WebIDL and Infra standard conventions

The zk-conventions-integration integration branch is now ready for review as announced on our last call. Let's discuss how to do the final review of this branch to get it merged into main soon as discussed on our last call<https://www.w3.org/2023/06/29-webmachinelearning-minutes.html#t03>.

These changes align the entire specification with modern specification conventions and add stylistic improvements on top that make navigating this specification more delightful experience.

The following resources are made available to the group to assist in this review task:

  *   Preview<https://zolkis.github.io/webnn/> of zk-conventions-integration
  *   Diff<https://services.w3.org/htmldiff?doc1=https%3A%2F%2Fwebmachinelearning.github.io%2Fwebnn%2F&doc2=https%3A%2F%2Fzolkis.github.io%2Fwebnn%2F> between main and zk-conventions-integration (note: diff is slow to load)
  *   Issues addressed and PRs merged to<https://github.com/webmachinelearning/webnn/issues/210#issuecomment-1326361748> zk-conventions-integration
  *   Commits<https://github.com/webmachinelearning/webnn/compare/main...zk-conventions-integration> ahead of main

<https://github.com/webmachinelearning/meetings/blob/main/telcons/2023-08-10-wg-agenda.md#%E2%84%B9%EF%B8%8F-new-features>ℹ️ New features

  *   Allow 0 size dimensions
     *    issue: webmachinelearning/webnn#391<https://github.com/webmachinelearning/webnn/issues/391>

<https://github.com/webmachinelearning/meetings/blob/main/telcons/2023-08-10-wg-agenda.md#%E2%84%B9%EF%B8%8F-enhancements>ℹ️ Enhancements

  *   split() into sizes not widely supported
     *    issue: webmachinelearning/webnn#392<https://github.com/webmachinelearning/webnn/issues/392>
  *   Clarify the restriction for minValue and maxValue of MLClampOptions
     *    issue: webmachinelearning/webnn#396<https://github.com/webmachinelearning/webnn/issues/396>