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Align charter with template and clarify some of its context
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dontcallmedom authored Feb 3, 2023
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<header id="header">
<aside>
<ul id="navbar">
<li><a href="#background">Motivation and Background</a></li>
<li>
<a href="#scope">Scope</a>
</li>
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"https://github.com/w3c/machine-learning-charter/issues">issues</a>.
</p>
<p class="mission">
The <strong>mission</strong> of the <a href="">Web Machine Learning
The <strong>mission</strong> of the <a href="https://www.w3.org/groups/wg/webmachinelearning">Web Machine Learning
Working Group</a> is to develop APIs for enabling efficient machine
learning inference in the browser.
</p>
<div class="noprint">
<p class="join">
<a href="https://www.w3.org/2004/01/pp-impl/#####/join">Join the Web
<a href="https://www.w3.org/groups/wg/webmachinelearning/join">Join the Web
Machine Learning Working Group.</a>
</p>
</div>
<section id="details">
<table class="summary-table">
<tr id="Status">
<th>Charter Status</th>
<td>See the <a href="https://www.w3.org/groups/wg/webmachinelearning/charters">group status page</A> and <a href="#history">detailed change history</a>.
</td>
</tr>
<tr id="Duration">
<th>
Start date
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<i class="todo">CFP + 2 years</i>
</td>
</tr>
<tr>
<th>
Charter extension
</th>
<td>
See <a href="#history">Change History</a>.
</td>
</tr>
<tr>
<th>
Chairs
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</tr>
</table>
</section>
<section id=bg>
<section id=background>
<h2>Motivation and Background</h2>
<p>
Computer Vision enables computers to gain understanding from images
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the browser (as opposed e.g. to in the cloud) enhances privacy, since input
data such as locally sourced images or video streams stay within the
browser's sandbox. Local processing also enables machine learning use
cases that require low latency, such as object detection in immersive
web experiences.
cases that require low latency, such as object detection in real-time
communications and immersive web experiences.
<p>
Currently, machine learning inference in the browser uses the WebGL
Currently, machine learning inference in the browser uses WebAssembly
and the WebGL
graphics API with limited or no access to platform capabilities
beneficial for ML such as CPU parallelism, general-purpose GPU, or
dedicated ML hardware accelerators.
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for hardware execution;
</li>
<li>Allows to setup input from various sources on the Web, e.g. array
buffers, media streams, schedule the asynchronous hardware execution,
buffers and media streams, schedule the asynchronous hardware execution,
and retrieve the output when hardware execution completes.
</li>
</ul>
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Recognition.
</p>
<p>
The APIs in scope of this group will not be tied to any particular
platform and will be implementable on top of existing major platform
The APIs in scope of this group are not be tied to any particular
platform and are to be implementable on top of existing major platform
APIs, such as Android Neural Networks API, Windows DirectML, and
macOS/iOS Metal Performance Shaders and Basic Neural Network
Subroutines.
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To avoid overlap with existing work, alignment with the Basic
Linear Algebra Subprograms (BLAS) interface is out of scope. The
WebGPU shaders and WebAssembly SIMD are expected to address the
BLAS compatibility requirement, see the Coordination section for
BLAS compatibility requirement, see the <a href="#coordination">Coordination section</a> for
details.
</p>
<p>
Interoperability between the WebNN and WebGL APIs is out of scope.
Integration between the WebNN and WebGL APIs is out of scope, as the group focuses its efforts on integration with WebGPU APIs.
</p>
<ul class="out-of-scope"></ul>
</section>
</section>
<section id="deliverables">
<h2>
Deliverables
</h2>
<p>
More detailed milestones and updated publication schedules are
available on the <a href=
"https://www.w3.org/groups/wg/webmachinelearning">group home page</a>.
Updated document status is available on the <a href=
"https://www.w3.org/groups/wg/webmachinelearning">group publication status page</a>.
</p>
<section id="normative">
<h3>
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inference that can take advantage of hardware acceleration.
</p>
<p class="draft-status">
<b>Draft state:</b> Working Draft
<b>Draft state:</b> W3C Working Draft
</p>
<p>
<b>Adopted Draft:</b> The <span class="todo">title, stable URL,
and publication date of the <a href=
"https://www.w3.org/Consortium/Process/#adopted-draft">
Adopted Draft</a></span> which will serve as the basis for
work on the deliverable.
<p class="milestone">
<b>Expected completion:</b> Q1 2025
</p>
<p>
<b>Exclusion Draft:</b> The <span class="todo">title, stable
URL, and publication date of the most recent <a href=
"https://www.w3.org/Consortium/Process/#exclusion-draft">
Exclusion Draft</a></span>.
<b>Adopted Draft:</b> <a class="todo" href="https://www.w3.org/TR/2023/WD-webnn-20230124/">https://www.w3.org/TR/2023/WD-webnn-20230124/</a>, 2023-01-24 <span class="todo">(this will change before the AC review starts)</span>
</p>
<p class="milestone">
<b>Expected completion:</b> Q1 2025
<p>
<b>Exclusion Draft:</b> <a href="https://www.w3.org/TR/2021/WD-webnn-20210622/">https://www.w3.org/TR/2021/WD-webnn-20210622/</a>, 2021-06-22<br>
Exclusion period began 2021-06-22; Exclusion period ended 2021-11-19.
</p>
<p><b>Exclusion Draft Charter:</b> <a href="https://www.w3.org/2021/04/web-machine-learning-charter.html">https://www.w3.org/2021/04/web-machine-learning-charter.html</a>
</p>
</dd>
</dl>
</section>
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</li>
</ul>
</section>
<section id="timeline">
<h3>Timeline</h3>
<ul>
<li>Q2 2023: Candidate Recommendation for WebNN</li>
<li>Q1 2025: Recommendation for WebNN</li>
</ul>
</section>
</section>
<section id="success-criteria">
<h2>
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"Proposed Recommendation">Proposed Recommendation</a>, each normative
specification is expected to have <a href=
"https://www.w3.org/Consortium/Process/#implementation-experience">at
least two independent implementations</a> of every feature defined in
the specification.
least two independent, interoperable implementations</a> of every feature defined in
the specification, where interoperability can be verified by passing open test suites, and two or more implementations interoperating with each other. In order to advance to Proposed Recommendation, each normative specification must have an open test suite of every feature defined in the specification..
</p>
<p>
Each specification should contain a section detailing all known
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</p>
<p>
There should be testing plans for each specification, starting from
the earliest drafts.
the earliest drafts. To promote interoperability, all changes made to specifications in Candidate Recommendation or to features that have deployed implementations should have tests. Testing efforts should be conducted via the <a href="https://github.com/web-platform-tests/wpt">Web Platform Tests</a> project.
</p>
<p>
Each specification should contain a section on accessibility that
describes the benefits and impacts, including ways specification
features can be used to address them, and recommendations for
maximising accessibility in implementations.
</p>
<p>
To promote interoperability, all changes made to specifications
should have <a href=
'https://www.w3.org/2019/02/testing-policy.html'>tests</a>.
</p>
</section>
<section id="coordination">
<h2>
Coordination
</h2>
<p>
For all specifications, this Working Group will seek <a href=
"https://www.w3.org/Guide/process/charter.html#horizontal-review">horizontal
review</a> for accessibility, internationalization, performance,
"https://www.w3.org/Guide/documentreview/#how_to_get_horizontal_review">horizontal
review</a> for accessibility, internationalization,
privacy, and security with the relevant Working and Interest Groups,
and with the <a href="https://www.w3.org/2001/tag/" title=
"Technical Architecture Group">TAG</a>. Invitation for review must be
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being worked on in the Community Group for the Recommendation
track.
</dd>
</dl>
<dl>
<dt>
<a href="https://www.w3.org/2020/gpu/">GPU for the Web Working
Group</a>
</dt>
<dd>
The GPU for the Web Working Group defines a WebGPU Shading
Language that may be used to implement traditional machine
The GPU for the Web Working Group defines access to GPU devices with the <a href="https://www.w3.org/TR/webgpu/">WebGPU API</a>, and a <a href="https://www.w3.org/TR/WGSL/">WebGPU Shading
Language</a> that may be used to implement traditional machine
learning algorithms efficiently. The Web Machine Learning Working
Group should coordinate with this group to avoid overlap and
to enable interoperability between the WebNN and WebGPU APIs.
Group will coordinate with this group to avoid overlap and
to ensure proper integration of WebNN with WebGPU APIs.
</dd>
</dl>
<dl>
<dt>
<a href="https://www.w3.org/community/webassembly/">WebAssembly
Community Group</a>
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The WebAssembly Community Group incubates a proposal for a
128-bit SIMD support in WebAssembly that can be used to implement
traditional machine learning algorithms efficiently. The Web
Machine Learning Working Group should coordinate with this group
Machine Learning Working Group will coordinate with this group
to avoid overlap.
</dd>
<dt><a href="https://www.w3.org/groups/wg/webrtc">WebRTC Working Group</a></dt>
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<dl>
<dt><a href="https://tc39.es/">ECMA TC39</a></dt>
<dd>TC39 defines the JavaScript language whose primitives are key in how WebNN access data (e.g. <code>ArrayBuffer</code>). Possible work on <a href="https://github.com/tc39/proposal-operator-overloading#matrixvector-computations">operator overloading</a> would also impact possible evolutions of the WebNN API.</dd>
</dl>
<dl>
<dt><a href="https://github.com/openxla">OpenXLA Project</a></dt>
<dd>
OpenXLA Project develops StableHLO, a portable ML compute
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meetings will be archived for public review, and technical
discussions and issue tracking will be conducted in a manner that can
be both read and written to by the general public. Working Drafts and
Editor's Drafts of specifications will be developed on a public
repository and may permit direct public contribution requests. The
Editor's Drafts of specifications will be developed in public
repositories and may permit direct public contribution requests. The
meetings themselves are not open to public participation, however.
</p>
<p>
Information about the group (including details about deliverables,
issues, actions, status, participants, and meetings) will be
available from the <a href="">Web Machine Learning Working Group home
available from the <a href="https://www.w3.org/groups/wg/webmachinelearning">Web Machine Learning Working Group home
page.</a>
</p>
<p>
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This group will seek to make decisions through consensus and due
process, per the <a href=
"https://www.w3.org/Consortium/Process/#Consensus">W3C Process
Document (section 3.3</a>). Typically, an editor or other participant
Document (section 5.2.1, Consensus</a>). Typically, an editor or other participant
makes an initial proposal, which is then refined in discussion with
members of the group and other reviewers, and consensus emerges with
little formal voting being required.
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<p>
This charter is written in accordance with the <a href=
"https://www.w3.org/Consortium/Process/#Votes">W3C Process Document
(Section 3.4, Votes)</a> and includes no voting procedures beyond
(Section 5.2.3, Deciding by Vote)</a> and includes no voting procedures beyond
what the Process Document requires.
</p>
</section>
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standards, W3C seeks to issue Recommendations that can be
implemented, according to this policy, on a Royalty-Free basis. For
more information about disclosure obligations for this group, please
see the <a href="https://www.w3.org/2004/01/pp-impl/">W3C Patent
Policy Implementation</a>.
see the <a href="https://www.w3.org/groups/wg/webmachinelearning/ipr">licensing information</a>.
</p>
</section>
<section id="licensing">
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</h2>
<p>
This charter has been created according to <a href=
"https://www.w3.org/Consortium/Process/#GAGeneral">section 5.2</a> of
"https://www.w3.org/Consortium/Process/#GAGeneral">section 3.4</a> of
the <a href="https://www.w3.org/Consortium/Process/">Process
Document</a>. In the event of a conflict between this document or the
provisions of any charter and the W3C Process, the W3C Process shall
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The following table lists details of all changes from the initial
charter, per the <a href=
"https://www.w3.org/Consortium/Process/#CharterReview">W3C Process
Document (section 5.2.3)</a>:
Document (section 4.3, Advisory Committee Review of a Charter)</a>:
</p>
<table class="history">
<tbody>
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</tbody>
</table>
</section>
<section id="changelog">
<h2>Change log</h2>
<p>Changes to this document are documented in this section.</p>
</section>
</section>
</main>
<hr>
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<a href="mailto:[email protected]">Dominique Hazael-Massieux</a>
</address>
<p class="copyright">
<a href=
"https://www.w3.org/Consortium/Legal/ipr-notice#Copyright">Copyright</a>
© 2021 <a href="https://www.w3.org/"><abbr title=
"World Wide Web Consortium">W3C</abbr></a><sup>®</sup> ( <a href=
"https://www.csail.mit.edu/"><abbr title=
"Massachusetts Institute of Technology">MIT</abbr></a>, <a href=
"https://www.ercim.eu/"><abbr title=
"European Research Consortium for Informatics and Mathematics">ERCIM</abbr></a>,
<a href="https://www.keio.ac.jp/">Keio</a>, <a href=
"https://ev.buaa.edu.cn/">Beihang</a> ), All Rights Reserved.
Copyright
© 2023 <a href="https://www.w3.org/">World Wide Web Consortium</a>.
<abbr title="World Wide Web Consortium">W3C</abbr> <a href=
"https://www.w3.org/Consortium/Legal/ipr-notice#Legal_Disclaimer">liability</a>,
<a href=
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