-
Notifications
You must be signed in to change notification settings - Fork 3
/
Copy pathcharter.html
716 lines (706 loc) · 28.7 KB
/
charter.html
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
386
387
388
389
390
391
392
393
394
395
396
397
398
399
400
401
402
403
404
405
406
407
408
409
410
411
412
413
414
415
416
417
418
419
420
421
422
423
424
425
426
427
428
429
430
431
432
433
434
435
436
437
438
439
440
441
442
443
444
445
446
447
448
449
450
451
452
453
454
455
456
457
458
459
460
461
462
463
464
465
466
467
468
469
470
471
472
473
474
475
476
477
478
479
480
481
482
483
484
485
486
487
488
489
490
491
492
493
494
495
496
497
498
499
500
501
502
503
504
505
506
507
508
509
510
511
512
513
514
515
516
517
518
519
520
521
522
523
524
525
526
527
528
529
530
531
532
533
534
535
536
537
538
539
540
541
542
543
544
545
546
547
548
549
550
551
552
553
554
555
556
557
558
559
560
561
562
563
564
565
566
567
568
569
570
571
572
573
574
575
576
577
578
579
580
581
582
583
584
585
586
587
588
589
590
591
592
593
594
595
596
597
598
599
600
601
602
603
604
605
606
607
608
609
610
611
612
613
614
615
616
617
618
619
620
621
622
623
624
625
626
627
628
629
630
631
632
633
634
635
636
637
638
639
640
641
642
643
644
645
646
647
648
649
650
651
652
653
654
655
656
657
658
659
660
661
662
663
664
665
666
667
668
669
670
671
672
673
674
675
676
677
678
679
680
681
682
683
684
685
686
687
688
689
690
691
692
693
694
695
696
697
698
699
700
701
702
703
704
705
706
707
708
709
710
711
712
713
714
715
716
<!DOCTYPE html>
<html lang="en-US">
<head>
<meta charset="utf-8">
<title>
[DRAFT] Web Machine Learning Working Group Charter
</title>
<link rel="stylesheet" href="https://www.w3.org/2005/10/w3cdoc.css" type=
"text/css" media="screen">
<link rel="stylesheet" type="text/css" href=
"https://www.w3.org/OldGuide/pubrules-style.css">
<link rel="stylesheet" type="text/css" href=
"https://www.w3.org/2006/02/charter-style.css">
<style>
main {
max-width: 60em;
margin: 0 auto;
}
ul#navbar {
font-size: small;
}
dt.spec {
font-weight: bold;
}
dt.spec new {
background: yellow;
}
ul.out-of-scope > li {
font-weight: bold;
}
ul.out-of-scope > li > ul > li{
font-weight: normal;
}
.issue {
background: cornsilk;
font-style: italic;
}
.todo {
color: #900;
}
footer {
font-size: small;
}
</style>
</head>
<body>
<header id="header">
<aside>
<ul id="navbar">
<li><a href="#background">Motivation and Background</a></li>
<li>
<a href="#scope">Scope</a>
</li>
<li>
<a href="#deliverables">Deliverables</a>
</li>
<li>
<a href="#success-criteria">Success Criteria</a>
</li>
<li>
<a href="#coordination">Coordination</a>
</li>
<li>
<a href="#participation">Participation</a>
</li>
<li>
<a href="#communication">Communication</a>
</li>
<li>
<a href="#decisions">Decision Policy</a>
</li>
<li>
<a href="#patentpolicy">Patent Policy</a>
</li>
<li>
<a href="#licensing">Licensing</a>
</li>
<li>
<a href="#about">About this Charter</a>
</li>
</ul>
</aside>
<p>
<a href="https://www.w3.org/"><img alt="W3C" height="48" src=
"https://www.w3.org/Icons/w3c_home" width="72"></a>
</p>
</header>
<main>
<h1 id="title">
[DRAFT] Web Machine Learning Working Group Charter
</h1><!-- delete PROPOSED after AC review completed -->
<p style="padding: 0.5ex; border: 1px solid green">
This draft charter is available on <a href=
"https://github.com/w3c/machine-learning-charter">GitHub</a>. Feel free
to raise <a href=
"https://github.com/w3c/machine-learning-charter/issues">issues</a>.
</p>
<p class="mission">
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/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
</th>
<td>
<i class="todo">[dd monthname yyyy] (date of the "Call for
Participation", when the charter is approved)</i>
</td>
</tr>
<tr id="CharterEnd">
<th>
End date
</th>
<td>
<i class="todo">CFP + 2 years</i>
</td>
</tr>
<tr>
<th>
Chairs
</th>
<td>
Anssi Kostiainen (Intel)
</td>
</tr>
<tr>
<th>
Team Contacts
</th>
<td>
<a href="mailto:[email protected]">Dominique Hazaël-Massieux</a>
(0.1 <abbr title=
"Full-Time Equivalent">FTE</abbr>)
</td>
</tr>
<tr>
<th>
Meeting Schedule
</th>
<td>
<strong>Teleconferences:</strong> bi-weekly<br>
<strong>Face-to-face:</strong> we will meet during the W3C's
annual Technical Plenary week; additional face-to-face meetings
may be scheduled by consent of the participants, usually no more
than 3 per year.
</td>
</tr>
</table>
</section>
<section id=background>
<h2>Motivation and Background</h2>
<p>
Computer Vision enables computers to gain understanding from images
or videos. Natural Language Processing enables interaction between
computers and human languages. Speech Recognition and Speech
Synthesis enable computers to recognize and translate spoken language
into text and vice versa.
Bringing these experiences to the web in a privacy-preserving manner
requires efficient machine learning inference capabilities built into
the browser.
</p>
<p>Enabling Machine Learning inference in
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 real-time
communications and immersive web experiences.
<p>
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.
</p>
</section>
<section id="scope" class="scope">
<h2>
Scope
</h2>
<p>
The Web Machine Learning Working Group develops a Web API aiming to expose generic capabilities to the Web
required to provide close-to-native machine learning performance in
the browser.
This Web API for neural network inference hardware acceleration:
</p>
<ul>
<li>Allows construction of a neural network computational graph by common
building blocks required by well-known model architectures: constant
values and base operations such as convolution, pooling, softmax,
normalization, fully connected, and activation;
</li>
<li>Allows compilation of the neural network to native optimized format
for hardware execution;
</li>
<li>Allows input to be set up from various sources on the Web, e.g. array
buffers and media streams, schedule the asynchronous hardware execution,
and retrieve the output when hardware execution completes.
</li>
</ul>
<p>
This Working Group puts priority on building blocks required by
well-known model architectures such as recurrent neural network
(RNN), long short-term memory (LSTM) and transformers in the fields
of Computer Vision, Natural Language Processing and Speech
Recognition.
</p>
<p>
The APIs in scope of this group are not tied to any particular
platform and are implementable on top of existing major platform
APIs, such as Android Neural Networks API, Windows DirectML, and
macOS/iOS Core ML and Basic Neural Network Subroutines.
</p>
<p>
For each high-level building block that decomposes into well-known
lower-level operations, the APIs will informatively define a generic
emulation path to allow for future extensibility.
</p>
<p>The Working Group may also work on a higher-level API to load a custom pre-trained Machine Learning model for inference in the browser.</p>
<section id="section-out-of-scope">
<h3 id="out-of-scope">
Out of Scope
</h3>
<p>
The scope is limited to development of interfaces that expose
inference capabilities of the modern platforms beneficial or
purpose-built for ML. Training capabilities are out of scope due to
limited availability of respective platform APIs.
</p>
<p>
This Working Group will not define any hardware features or
algorithms.
</p>
<p>
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 <a href="#coordination">Coordination section</a> for
details.
</p>
<p>
Integration between the WebNN and WebGL APIs is out of scope, as the group focuses its efforts on integration with WebGPU APIs.
</p>
</section>
</section>
<section id="deliverables">
<h2>
Deliverables
</h2>
<p>
Updated document status is available on the <a href=
"https://www.w3.org/groups/wg/webmachinelearning/publications/">group publication status page</a>.
</p>
<section id="normative">
<h3>
Normative Specifications
</h3>
<p>
The Working Group will deliver the following W3C normative
specifications:
</p>
<dl>
<dt id="webnn" class="spec">
<a href="https://www.w3.org/TR/webnn/">Web Neural Network API</a>
</dt>
<dd>
<p>
This specification defines an API to enable neural network
inference that can take advantage of hardware acceleration.
</p>
<p class="draft-status">
<b>Draft state:</b> W3C Candidate Recommendation
</p>
<p class="milestone">
<b>Expected completion:</b> Q1 2027
</p>
<p>
<b>Adopted Draft:</b> <a class="todo" href="https://www.w3.org/TR/2025/CRD-webnn-20250129/">https://www.w3.org/TR/2025/CRD-webnn-20250129/</a>, 2025-01-29
</p>
<p>
<b>Exclusion Draft:</b> <a href="https://www.w3.org/TR/2024/CR-webnn-20240411/">https://www.w3.org/TR/2024/CR-webnn-20240411/</a>, 2024-04-11<br>
Exclusion period began 2024-04-11; Exclusion period ended 2024-06-10.
</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>
<section id="ig-other-deliverables">
<h3>
Other Deliverables
</h3>
<p id="ethical-issues">
The Working Group develops <a href=
"https://www.w3.org/TR/webmachinelearning-ethics/">Ethical
Principles for Web Machine Learning</a> Working Group Note
documenting ethical issues associated with using Machine Learning
on the Web, to help identify what mitigations its normative
specifications should take into account.
</p>
<p>
Other non-normative documents may be created such as:
</p>
<ul>
<li>Use case and requirement documents;
</li>
<li>Test suite and implementation report for the specification;
</li>
<li>Primer or Best Practice documents to support web developers
when designing applications.
</li>
</ul>
</section>
<section id="timeline">
<h3>Timeline</h3>
<ul>
<li>Q1 2027: Recommendation for WebNN</li>
</ul>
</section>
</section>
<section id="success-criteria">
<h2>
Success Criteria
</h2>
<p>
In order to advance beyond <a href=
"https://www.w3.org/policies/process/#RecsCR">Candidate Recommendation</a>, each normative
specification is expected to have <a href=
"https://www.w3.org/policies/process/#implementation-experience">at
least two independent interoperable implementations</a> of every feature defined in
the specification, where interoperability can be verified by passing open test suites.
</p>
<p>
Each specification should contain separate sections detailing all known
security and privacy implications for implementers, Web authors, and
end users.
</p>
<p>
Each specification should contain a section detailing ethical considerations describing how implementers and Web authors should mitigate risks associated with ethical issues, such as <a href="#ethical-issues">the ones the group will be documenting</a>.
</p>
<p>
There should be testing plans for each specification, starting from
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>This Working Group expects to follow the
TAG <a href="https://www.w3.org/TR/design-principles/">Web Platform Design Principles</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/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/groups/other/tag/" title=
"Technical Architecture Group">TAG</a>. Invitation for review must be
issued during each major standards-track document transition,
including <a href="https://www.w3.org/policies/process/#RecsWD"
title="First Public Working Draft">FPWD</a>. The Working Group is
encouraged to engage collaboratively with the horizontal review
groups throughout development of each specification. The Working
Group is advised to seek a review at least 3 months before first
entering <a href="https://www.w3.org/policies/process/#RecsCR"
title="Candidate Recommendation">CR</a> and is encouraged to
proactively notify the horizontal review groups when major changes
occur in a specification following a review.
</p>
<p>
Additional technical coordination with the following Groups will be
made, per the <a href=
"https://www.w3.org/policies/process/#WGCharter">W3C Process
Document</a>:
</p>
<section>
<h3 id="w3c-coordination">
W3C Groups
</h3>
<dl>
<dt>
<a href=
"https://www.w3.org/community/webmachinelearning/">Web Machine
Learning Community Group</a>
</dt>
<dd>
The Web Machine Learning Community Group developed the
Web Neural Network API adopted by this Working Group. It is
expected that the Community Group will continue drive technical
work around other specifications in its scope. This Working Group
will work with the Web Machine Learning Community Group
on shaping the <a href="#tentative">Tentative Specifications</a>
being worked on in the Community Group for the Recommendation
track.
</dd>
<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 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 will coordinate with this group to avoid overlap and
to ensure proper integration of WebNN with WebGPU APIs.
</dd>
<dt>
<a href="https://www.w3.org/community/webassembly/">WebAssembly
Community Group</a>
</dt>
<dd>
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 will coordinate with this group
to avoid overlap.
</dd>
<dt><a href="https://www.w3.org/groups/wg/webrtc">WebRTC Working Group</a></dt>
<dd>
The WebRTC Working Group defines the <code>MediaStream</code>
interface and related media processing APIs that enable integration
with Machine Learning capabilities afforded by the WebNN API.
</dd>
<dt><a href="https://www.w3.org/2001/tag/">Technical Architecture Group</a></dt>
<dd>Given the well-known ethical risks of bias in the use of Machine Learning, the Web Machine Learning Working Group will work with the Technical Architecture Group to ensure its work align with the <a href="https://w3ctag.github.io/ethical-web-principles/">W3C TAG Ethical Web Principles</a>.</dd>
</dl>
</section>
<section>
<h3 id="external-coordination">
External Organizations
</h3>
<dl>
<dt><a href="https://tc39.es/">ECMA TC39</a></dt>
<dd>TC39 defines the JavaScript language whose primitives are key in how WebNN accesses 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>
</section>
</section>
<section class="participation">
<h2 id="participation">
Participation
</h2>
<p>
To be successful, this Working Group is expected to have 6 or more
active participants for its duration, including representatives from
the key implementors of this specification, and active Editors and
Test Leads for each specification. The Chairs, specification Editors,
and Test Leads are expected to contribute half of a working day per
week towards the Working Group. There is no minimum
requirement for other Participants.
</p>
<p>
The group encourages questions, comments and issues on its public
mailing lists and document repositories, as described in <a href=
'#communication'>Communication</a>.
</p>
<p>
The group also welcomes non-Members to contribute technical
submissions for consideration upon their agreement to the terms of
the <a href="https://www.w3.org/Consortium/Patent-Policy/">W3C Patent
Policy</a>.
</p>
<p>
Participants in the group are required (by the <a href=
"https://www.w3.org/policies/process/#ParticipationCriteria">W3C
Process</a>) to follow the W3C <a href=
"https://www.w3.org/policies/code-of-conduct/">Code of
Conduct</a>.
</p>
</section>
<section id="communication">
<h2>
Communication
</h2>
<p id="public">
Technical discussions for this Working Group are conducted in
<a href="https://www.w3.org/policies/process/#confidentiality-levels">
public</a>: the meeting minutes from teleconference and face-to-face
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 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="https://www.w3.org/groups/wg/webmachinelearning">Web Machine Learning Working Group home
page.</a>
</p>
<p>
Most Web Machine Learning Working Group teleconferences will focus on
discussion of particular specifications, and will be conducted on an
as-needed basis.
</p>
<p>
This group primarily conducts its technical work on GitHub issues.
The public is invited to review, discuss and contribute to this work.
</p>
<p>
The group may use a Member-confidential mailing list for
administrative purposes and, at the discretion of the Chairs and
members of the group, for member-only discussions in special cases
when a participant requests such a discussion.
</p>
</section>
<section id="decisions">
<h2>
Decision Policy
</h2>
<p>
This group will seek to make decisions through consensus and due
process, per the <a href=
"https://www.w3.org/policies/process/#Consensus">W3C Process
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.
</p>
<p>
However, if a decision is necessary for timely progress and consensus
is not achieved after careful consideration of the range of views
presented, the Chairs may call for a group vote and record a decision
along with any objections.
</p>
<p>
To afford asynchronous decisions and organizational deliberation, any
resolution (including publication decisions) taken in a face-to-face
meeting or teleconference will be considered provisional. A call for
consensus (CfC) will be issued for all resolutions (for example, via
email, GitHub issue or web-based survey), with a response period from
one week to 10 working days, depending on the chair's evaluation of
the group consensus on the issue. If no objections are raised by the
end of the response period, the resolution will be considered to have
consensus as a resolution of the Working Group.
</p>
<p>
All decisions made by the group should be considered resolved unless
and until new information becomes available or unless reopened at the
discretion of the Chairs.
</p>
<p>
This charter is written in accordance with the <a href=
"https://www.w3.org/policies/process/#Votes">W3C Process Document
(Section 5.2.3, Deciding by Vote)</a> and includes no voting procedures beyond
what the Process Document requires.
</p>
</section>
<section id="patentpolicy">
<h2>
Patent Policy
</h2>
<p>
This Working Group operates under the <a href=
"https://www.w3.org/Consortium/Patent-Policy/">W3C Patent Policy</a>
(Version of 15 September 2020). To promote the widest adoption of Web
standards, W3C seeks to issue Web specifications 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/groups/wg/webmachinelearning/ipr/">licensing information</a>.
</p>
</section>
<section id="licensing">
<h2>
Licensing
</h2>
<p>
This Working Group will use the <a href=
"https://www.w3.org/copyright/software-license/">W3C Software
and Document license</a> for all its deliverables.
</p>
</section>
<section id="about">
<h2>
About this Charter
</h2>
<p>
This charter has been created according to <a href=
"https://www.w3.org/policies/process/#GAGeneral">section 3.4</a> of
the <a href="https://www.w3.org/policies/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
take precedence.
</p>
<section id="history">
<h3>
Charter History
</h3>
<p>
The following table lists details of all changes from the initial
charter, per the <a href=
"https://www.w3.org/policies/process/#CharterReview">W3C Process
Document (section 4.3, Advisory Committee Review of a Charter)</a>:
</p>
<table class="history">
<tbody>
<tr>
<th>
Charter Period
</th>
<th>
Start Date
</th>
<th>
End Date
</th>
<th>
Changes
</th>
</tr>
<tr>
<th>
<a href="https://www.w3.org/2021/04/web-machine-learning-charter.html">Initial Charter</a>
</th>
<td>
2021-04-20
</td>
<td>
2023-04-30
</td>
<td>
Initial charter
</td>
</tr>
<tr>
<th>
Second charter
</th>
<td>
2023-04-06
</td>
<td>
2025-04-30
</td>
<td>
Update to latest status of work and charter template
</td>
</tr>
<tr>
<th>
This charter
</th>
<td>
2025-@@
</td>
<td>
2027-@@
</td>
<td>
Update to latest status of work (removing tentative deliverable on model loader API) and charter template
</td>
</tr>
</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>
<footer>
<address>
<a href="mailto:[email protected]">Dominique Hazael-Massieux</a>
</address>
<p class="copyright">
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/policies/#disclaimers">liability</a>,
<a href=
"https://www.w3.org/policies/#trademarks">trademark</a>
and <a href=
"https://www.w3.org/copyright/software-license/" title="W3C Software and Document Notice and License">permissive document
use</a> rules apply.
</p>
<hr>
<p>
<a href="https://github.com/w3c/machine-learning-charter/">Yes, it's on
GitHub!</a>.
</p>
</footer>
</body>
</html>