Web Neural Network API 2022-05-10 > 2022-09-01

[anssiko]

• Name of spec to be reviewed: Web Neural Network API

• URL of spec: https://www.w3.org/TR/webnn/

• What and when is your next expected transition? CR in Q4 2022.

• What has changed since any previous review? This is the first formal i18n review request.

• Please point to the results of your own self-review: Internationalization Checklist webmachinelearning/webnn#262

• Where and how to file issues arising? https://github.com/webmachinelearning/webnn/issues

• Pointer to any explainer for the spec? https://github.com/webmachinelearning/webnn/blob/main/explainer.md

Other comments: Thank you for your review!

[anssiko]

@aphillips I infer from the Review radar activity that this request has been Completed. Thank you for your review.

We have also made available the WG's input to the i18n checklist webmachinelearning/webnn#262 for this API.

[anssiko]

@aphillips, I'm marking the i18n review as completed in the WebML WG's wide review tracker webmachinelearning/webnn#239. Feel free to close this issue.

Thanks to the whole group for your review. Should you have further comments, our WG is always happy to allocate time to discuss with you.

[anssiko]

Hi again Internationalization WG!

NB: I'm piggypacking on this issue to retain context. Based on our self-assessment there are no new i18n issues since your previous review, so please consider this for your information only, not a formal review request.

We're looking to publish a new CR Snapshot of the Web Neural Network API in Q1'24 and wanted to give you a heads up with the following high-level summary of changes for your information and review:

Since the initial Candidate Recommendation Snapshot the Working Group has gathered further implementation experience and added new operations and data types needed for well-known transformers to support generative AI use cases. In addition, the group has removed select features informed by this implementation experience: higher-level operations that can be expressed in terms of lower-level primitives in a performant manner, and support for synchronous execution. The group has also updated the specification to use modern authoring conventions to improve interoperability and precision of normative definitions and is developing a new feature, a backend-agnostic storage type, to improve performance and interoperability between the WebNN, WebGPU APIs and purpose-built hardware for ML.

We have considered your earlier review feedback and continue to evaluate our work using your Internationalization Checklist, with our latest status tracked in webmachinelearning/webnn#262

[aphillips]

@anssiko

Thanks for the ping! I'm glad to hear your group is making good progress.

Please follow the Process and request a new review from I18N with enough time for us to complete it before you do your transition request. If there is nothing new of interest to us, it should be quick and painless.

[anssiko]

@aphillips, a new delta review request: #223