Skip to content

Commit 37b9dbf

Browse files
anssikoanssiko
authored
Merge branch 'master' into agenda
2 parents 73d3388 + d89fccd commit 37b9dbf

File tree

75 files changed

+4520
-39
lines changed

Some content is hidden

Large Commits have some content hidden by default. Use the searchbox below for content that may be hidden.

75 files changed

+4520
-39
lines changed

‎_data/talks.json

Lines changed: 36 additions & 7 deletions
Original file line numberDiff line numberDiff line change
@@ -58,6 +58,17 @@
5858
"video": "https://app.streamfizz.live/embed/ckdo77c2k4srf07726abf6aps",
5959
"noslide": true,
6060
"duration": "04:29"
61+
},
62+
"ph_embedded": {
63+
"title": "Extending W3C ML Work to Embedded Systems",
64+
"author": "Peter Hoddie",
65+
"affiliation": "Moddable Tech",
66+
"bio": "<p>Peter is the chair of Ecma TC53, ECMAScript Module for Embedded Systems, working to bring standard JavaScript APIs to IoT.</p><p>He is a delegate to Ecma TC39, the JavaScript language standards committee, where his focus is ensuring JavaScript remains a viable language on resource constrained devices.</p><p>He is a co-founder and CEO of Moddable Tech, building XS, the only modern JavaScript engine for embedded systems, and the Moddable SDK, a JavaScript framework for delivering consumer and industrial IoT products.</p><p>Peter is the co-author of “IoT Development for ESP32 and ESP8266 with JavaScript”, published in 2020 by Apress, the professional books imprint of Springer Nature.</p><p>He contributed to the ISO MPEG-4 file format standard.</p><p><a href='https://www.moddable.com/peter-hoddie'>Additional bio information</a></p>",
67+
"abstract": "<p>JavaScript's dominance on the web often obscures its many successes beyond the web, such as in embedded systems. New silicon for embedded systems is beginning to include hardware to accelerate ML, bringing ML to edge devices. These embedded systems are capable of running the same modern JavaScript used on the web. Would it be possible for the embedded systems to be coded in JavaScript in a way that is compatible with the ML APIs of the web?</p><p>This talk will briefly present two examples of JavaScript APIs developed for the web to support hardware features -- the W3C Sensor API and the Chrome Serial API. It will describe how each has been bridged to the embedded world in a different way -- perhaps suggesting a model for how W3C ML JavaScript APIs can bridge the embedded and browser worlds as well.</p>",
68+
"video": "https://app.streamfizz.live/embed/ckey25zw0qdx70731i0vzodxh",
69+
"thumbnail": "https://cjx1uopmt0m4q0667xmnrqpk.blob.core.windows.net/ckey25zw0qdx70731i0vzodxh/thumbs/thumb-001.jpeg",
70+
"duration": "06:57",
71+
"added": "2020-09-11"
6172
}
6273
} ,
6374
{
@@ -258,14 +269,28 @@
258269
"abstract_zh": "Paddle.js是适用于各种Web运行时的高性能JavaScript DL框架，它有助于通过Web社区构建PaddlePaddle生态系统。本演讲将介绍Paddle.js的设计原理，实现，使用场景以及该项目想要探索的未来工作。",
259270
"duration": "05:51"
260271
},
261-
"en_ml5js": {
262-
"title": "ML5.js",
263-
"title_zh": "ML5.js",
272+
"ys_ml5": {
273+
"title": "ml5.js: Friendly Machine Learning for the Web",
264274
"author": "Yining Shi",
265-
"affiliation": "New York University",
275+
"affiliation": "New York University, RunwayML",
266276
"affiliation_zh": "纽约大学",
267277
"bio": "ml5.js contributor and adjunct professor at Interactive Telecommunications Program (ITP)",
268-
"bio_zh":"ml5.js贡献者和交互电信项目(ITP)的兼职教授"
278+
"bio_zh":"ml5.js贡献者和交互电信项目(ITP)的兼职教授",
279+
"added": "2020-09-14",
280+
"video": "https://app.streamfizz.live/embed/ckf25pb70u0xk07316xa68ovz",
281+
"thumbnail": "https://cjx1uopmt0m4q0667xmnrqpk.blob.core.windows.net/ckf25pb70u0xk07316xa68ovz/thumbs/thumb-001.jpeg",
282+
"duration": "08:56"
283+
},
284+
"wl_pipcook": {
285+
"title": "Pipcook, a front-end oriented DL framework",
286+
"author": "Wenhe Eric Li",
287+
"affiliation": "Alibaba",
288+
"bio": "ML/DL on web, contributor of ML5 & tfjs, memebr of pipcook, SDE @ Alibaba",
289+
"abstract": "We are going to present a front-end oriented platform based on TensorFlow.js. We will cover what is pipcook, the design philosophy, as well as some examples & use cases in our internal community. Apart from that, we will show a brandy new solution to bridge the flourish python DL/ML environment and javascript runtime in both browsers and nodejs.",
290+
"duration": "10:17",
291+
"video": "https://app.streamfizz.live/embed/ckev83mzuaq7g073183lhuwje",
292+
"thumbnail": "https://cjx1uopmt0m4q0667xmnrqpk.blob.core.windows.net/ckev83mzuaq7g073183lhuwje/thumbs/thumb-001.jpeg",
293+
"added": "2020-09-09"
269294
},
270295
"op_content-filtering": {
271296
"title": "Machine Learning on the Web for content filtering applications",
@@ -396,12 +421,16 @@
396421
"duration": "06:00",
397422
"added": "2020-08-26"
398423
},
399-
"ac_live-encoding": {
424+
"ac_encoding": {
400425
"title": "AI-Powered Per-Scene Live Encoding ",
401426
"author": "Anita Chen",
402427
"affiliation": "Fraunhofer FOKUS",
403428
"bio": "Project Manager at Fraunhofer FOKUS",
404-
"abstract": "This presentation will provide an overview of utilizing machine learning methods in automating per-title encoding for Video on Demand (VoD) and live streaming in order to improve the viewing experience. It will also address the behaviors of various regression models that can predict encoding ladders in a browser in real-time, including a future outlook in terms of optimization."
429+
"abstract": "This presentation will provide an overview of utilizing machine learning methods in automating per-title encoding for Video on Demand (VoD) and live streaming in order to improve the viewing experience. It will also address the behaviors of various regression models that can predict encoding ladders in a browser in real-time, including a future outlook in terms of optimization.",
430+
"duration": "9:13",
431+
"thumbnail": "https://cjx1uopmt0m4q0667xmnrqpk.blob.core.windows.net/ckf5026qg98gu0731ugc6eaqb/thumbs/thumb-001.jpeg",
432+
"video": "https://app.streamfizz.live/embed/ckf5026qg98gu0731ugc6eaqb",
433+
"added": "2020-09-16"
405434
},
406435
"zc_expression": {
407436
"title": "A virtual character web meeting with expression enhance power by machine learning",

‎_includes/related-issues/ac_encoding.html

Lines changed: 1 addition & 0 deletions
Original file line numberDiff line numberDiff line change
@@ -0,0 +1 @@
1+
<div class=related><p>Related conversations on <a href='https://github.com/w3c/machine-learning-workshop/issues'>GitHub</a>:</p><ul><ul><li><a href='https://github.com/w3c/machine-learning-workshop/issues/new'>Open a new issue</a></li></ul></ul></div>

‎_includes/related-issues/ac_live-encoding.html

Lines changed: 1 addition & 0 deletions
Original file line numberDiff line numberDiff line change
@@ -0,0 +1 @@
1+
<div class=related><p>Related conversations on <a href='https://github.com/w3c/machine-learning-workshop/issues'>GitHub</a>:</p><ul><ul><li><a href='https://github.com/w3c/machine-learning-workshop/issues/new'>Open a new issue</a></li></ul></ul></div>

‎_includes/related-issues/jmv_rnnoise.html

Lines changed: 1 addition & 1 deletion
Original file line numberDiff line numberDiff line change
@@ -1 +1 @@
1-
<div class=related><p>Related conversations on <a href='https://github.com/w3c/machine-learning-workshop/issues'>GitHub</a>:</p><ul><ul><li><a href='https://github.com/w3c/machine-learning-workshop/issues/new'>Open a new issue</a></li></ul></ul></div>
1+
<div class=related><p>Related conversations on <a href='https://github.com/w3c/machine-learning-workshop/issues'>GitHub</a>:</p><ul><li><a href='https://github.com/w3c/machine-learning-workshop/issues/100'>#100 Noise suppression with DSP+DNN, WebNN and Web Audio API feature gaps</a></li></ul></div>

‎_includes/related-issues/kd_speech.html

Lines changed: 1 addition & 1 deletion
Original file line numberDiff line numberDiff line change
@@ -1 +1 @@
1-
<div class=related><p>Related conversations on <a href='https://github.com/w3c/machine-learning-workshop/issues'>GitHub</a>:</p><ul><ul><li><a href='https://github.com/w3c/machine-learning-workshop/issues/new'>Open a new issue</a></li></ul></ul></div>
1+
<div class=related><p>Related conversations on <a href='https://github.com/w3c/machine-learning-workshop/issues'>GitHub</a>:</p><ul><li><a href='https://github.com/w3c/machine-learning-workshop/issues/99'>#99 Speech recognition privacy issues and solutions</a></li></ul></div>

‎_includes/related-issues/lmc_musicians.html

Lines changed: 1 addition & 1 deletion
Original file line numberDiff line numberDiff line change
@@ -1 +1 @@
1-
<div class=related><p>Related conversations on <a href='https://github.com/w3c/machine-learning-workshop/issues'>GitHub</a>:</p><ul><ul><li><a href='https://github.com/w3c/machine-learning-workshop/issues/new'>Open a new issue</a></li></ul></ul></div>
1+
<div class=related><p>Related conversations on <a href='https://github.com/w3c/machine-learning-workshop/issues'>GitHub</a>:</p><ul><li><a href='https://github.com/w3c/machine-learning-workshop/issues/97'>#97 Action-Response Cycle bottlenecks in interactive music apps</a></li></ul></div>

‎_includes/related-issues/ph_embedded.html

Lines changed: 1 addition & 0 deletions
Original file line numberDiff line numberDiff line change
@@ -0,0 +1 @@
1+
<div class=related><p>Related conversations on <a href='https://github.com/w3c/machine-learning-workshop/issues'>GitHub</a>:</p><ul><li><a href='https://github.com/w3c/machine-learning-workshop/issues/62'>#62 Applicability to non-browser JS environments</a></li></ul></div>

‎_includes/related-issues/tp_interactive_music.html

Lines changed: 2 additions & 1 deletion
Original file line numberDiff line numberDiff line change
@@ -1 +1,2 @@
1-
<div class=related><p>Related conversations on <a href='https://github.com/w3c/machine-learning-workshop/issues'>GitHub</a>:</p><ul><li><a href='https://github.com/w3c/machine-learning-workshop/issues/97'>#97 Action-Response Cycle bottlenecks in interactive music apps</a></li></ul></div>
1+
<div class=related><p>Related conversations on <a href='https://github.com/w3c/machine-learning-workshop/issues'>GitHub</a>:</p><ul><li><a href='https://github.com/w3c/machine-learning-workshop/issues/93'>#93 Memory copies</a></li>
2+
<li><a href='https://github.com/w3c/machine-learning-workshop/issues/97'>#97 Action-Response Cycle bottlenecks in interactive music apps</a></li></ul></div>

‎_includes/related-issues/wl_pipcook.html

Lines changed: 1 addition & 0 deletions
Original file line numberDiff line numberDiff line change
@@ -0,0 +1 @@
1+
<div class=related><p>Related conversations on <a href='https://github.com/w3c/machine-learning-workshop/issues'>GitHub</a>:</p><ul><li><a href='https://github.com/w3c/machine-learning-workshop/issues/102'>#102 Neural network-oriented graph database</a></li></ul></div>

‎_includes/related-issues/ys_ml5.html

Lines changed: 1 addition & 0 deletions
Original file line numberDiff line numberDiff line change
@@ -0,0 +1 @@
1+
<div class=related><p>Related conversations on <a href='https://github.com/w3c/machine-learning-workshop/issues'>GitHub</a>:</p><ul><ul><li><a href='https://github.com/w3c/machine-learning-workshop/issues/new'>Open a new issue</a></li></ul></ul></div>

‎_includes/talk-list1.html

Lines changed: 1 addition & 0 deletions
Original file line numberDiff line numberDiff line change
@@ -3,4 +3,5 @@
33
<details><summary><div class="grid"><span>PENDING </span><a>ML hardware advancements: leveraging for performance while retaining portability</a><span class="summary"> by Cormac Brick (Intel) <span></span></span></div></summary><dl><dt>Speaker</dt><dd>Cormac Brick (Intel)</dd><dd>Cormac leads Edge Inference IP architecture at Intel with a focus on both silicon and software. Cormac joined Intel as part of Movidius Acquisition in 2016 where he lead Machine Intelligence.</dd><dt>Abstract</dt><dd>There are a lot of interesting innovations coming in hardware technology, including hardware acceleration, weight compression, weight sparsity, low precision.</dd></dl></details>
44
<details class=talk><summary><div class="grid"><a href="talks/opportunities_and_challenges_for_tensorflow_js_and_beyond.html"><img src="https://cjx1uopmt0m4q0667xmnrqpk.blob.core.windows.net/ckdobxb1t766z0772f2e19nqo/thumbs/thumb-001.jpeg" alt="Watch Opportunities and Challenges for TensorFlow.js and beyond" width=200 class="tn"></a><a href="talks/opportunities_and_challenges_for_tensorflow_js_and_beyond.html">Opportunities and Challenges for TensorFlow.js and beyond</a><span class="summary"> by Jason Mayes (Google) - 10 min <span></span></span></div></summary><p><a href="talks/opportunities_and_challenges_for_tensorflow_js_and_beyond.html">10 minutes presentation</a></p><dl><dt>Speaker</dt><dd>Jason Mayes (Google)</dd><dd>Developer Advocate for TensorFlow.js</dd><dt>Abstract</dt><dd>This talk will give a brief overview of TensorFlow.js, how it helps developers build ML-powered applications along with examples of work that is pushing the boundaries of the web, and discuss future directions for the web tech stack to help overcome barriers to ML in the web the TF.js community has encountered.</dd></dl></details>
55
<details class=talk><summary><div class="grid"><a href="talks/machine_learning_in_web_architecture.html"><img src="https://cjx1uopmt0m4q0667xmnrqpk.blob.core.windows.net/ckdo77c2k4srf07726abf6aps/thumbs/thumb-001.jpeg" alt="Watch Machine Learning in Web Architecture" width=200 class="tn"></a><a href="talks/machine_learning_in_web_architecture.html">Machine Learning in Web Architecture</a><span class="summary"> by Sangwhan Moon - 4 min <span></span></span></div></summary><p><a href="talks/machine_learning_in_web_architecture.html">4 minutes presentation</a></p><dl><dt>Speaker</dt><dd>Sangwhan Moon</dd></dl></details>
6+
<details class=talk><summary><div class="grid"><a href="talks/extending_w3c_ml_work_to_embedded_systems.html"><img src="https://cjx1uopmt0m4q0667xmnrqpk.blob.core.windows.net/ckey25zw0qdx70731i0vzodxh/thumbs/thumb-001.jpeg" alt="Watch Extending W3C ML Work to Embedded Systems" width=200 class="tn"></a><a href="talks/extending_w3c_ml_work_to_embedded_systems.html">Extending W3C ML Work to Embedded Systems</a><span class="summary"> by Peter Hoddie (Moddable Tech) - 6 min <span></span></span></div><span class=added>Added on 2020-09-11</span></summary><p><a href="talks/extending_w3c_ml_work_to_embedded_systems.html">6 minutes presentation</a></p><dl><dt>Speaker</dt><dd>Peter Hoddie (Moddable Tech)</dd><dd><p>Peter is the chair of Ecma TC53, ECMAScript Module for Embedded Systems, working to bring standard JavaScript APIs to IoT.</p><p>He is a delegate to Ecma TC39, the JavaScript language standards committee, where his focus is ensuring JavaScript remains a viable language on resource constrained devices.</p><p>He is a co-founder and CEO of Moddable Tech, building XS, the only modern JavaScript engine for embedded systems, and the Moddable SDK, a JavaScript framework for delivering consumer and industrial IoT products.</p><p>Peter is the co-author of “IoT Development for ESP32 and ESP8266 with JavaScript”, published in 2020 by Apress, the professional books imprint of Springer Nature.</p><p>He contributed to the ISO MPEG-4 file format standard.</p><p><a href='https://www.moddable.com/peter-hoddie'>Additional bio information</a></p></dd><dt>Abstract</dt><dd><p>JavaScript's dominance on the web often obscures its many successes beyond the web, such as in embedded systems. New silicon for embedded systems is beginning to include hardware to accelerate ML, bringing ML to edge devices. These embedded systems are capable of running the same modern JavaScript used on the web. Would it be possible for the embedded systems to be coded in JavaScript in a way that is compatible with the ML APIs of the web?</p><p>This talk will briefly present two examples of JavaScript APIs developed for the web to support hardware features -- the W3C Sensor API and the Chrome Serial API. It will describe how each has been bridged to the embedded world in a different way -- perhaps suggesting a model for how W3C ML JavaScript APIs can bridge the embedded and browser worlds as well.</p></dd></dl></details>
67
</dl>

‎_includes/talk-list1_zh.html

Lines changed: 1 addition & 0 deletions
Original file line numberDiff line numberDiff line change
@@ -3,4 +3,5 @@
33
<details><summary><div class="grid"><span>PENDING </span><a>机器学习硬件的改进：在保持可移植性的同时利用性能</a><span class="summary"> by Cormac Brick (英特尔) <span></span></span></div></summary><dl><dt>Speaker</dt><dd>Cormac Brick (英特尔)</dd><dd>Cormac在英特尔领导Edge推理IP架构。2016年英特尔收购Movidius，Cormac加入英特尔，他曾在那里领导机器智能的研发。</dd><dt>Abstract</dt><dd>硬件技术中有很多有趣的创新，包括硬件加速，重量压缩，重量稀疏性，低精度。</dd></dl></details>
44
<details class=talk><summary><div class="grid"><a href="talks/opportunities_and_challenges_for_tensorflow_js_and_beyond.html"><img src="https://cjx1uopmt0m4q0667xmnrqpk.blob.core.windows.net/ckdobxb1t766z0772f2e19nqo/thumbs/thumb-001.jpeg" alt="Watch TensorFlow.js 及以后的机遇与挑战" width=200 class="tn"></a><a href="talks/opportunities_and_challenges_for_tensorflow_js_and_beyond.html">TensorFlow.js 及以后的机遇与挑战</a><span class="summary"> by Jason Mayes (谷歌) - 10 min <span></span></span></div></summary><p><a href="talks/opportunities_and_challenges_for_tensorflow_js_and_beyond.html">10 minutes presentation</a></p><dl><dt>Speaker</dt><dd>Jason Mayes (谷歌)</dd><dd>TensorFlow.js 的开发者</dd><dt>Abstract</dt><dd>这次演讲将简要介绍TensorFlow.js，它如何帮助开发人员构建基于机器学习的应用程序，以及一些推动web边界的例子，并讨论了web技术堆栈的未来方向，以帮助克服web中使用机器学习的障碍，这是TF.js社区遇到的。</dd></dl></details>
55
<details class=talk><summary><div class="grid"><a href="talks/machine_learning_in_web_architecture.html"><img src="https://cjx1uopmt0m4q0667xmnrqpk.blob.core.windows.net/ckdo77c2k4srf07726abf6aps/thumbs/thumb-001.jpeg" alt="Watch Web 架构中的机器学习 " width=200 class="tn"></a><a href="talks/machine_learning_in_web_architecture.html">Web 架构中的机器学习 </a><span class="summary"> by Sangwhan Moon - 4 min <span></span></span></div></summary><p><a href="talks/machine_learning_in_web_architecture.html">4 minutes presentation</a></p><dl><dt>Speaker</dt><dd>Sangwhan Moon</dd></dl></details>
6+
<details class=talk><summary><div class="grid"><a href="talks/extending_w3c_ml_work_to_embedded_systems.html"><img src="https://cjx1uopmt0m4q0667xmnrqpk.blob.core.windows.net/ckey25zw0qdx70731i0vzodxh/thumbs/thumb-001.jpeg" alt="Watch Extending W3C ML Work to Embedded Systems" width=200 class="tn"></a><a href="talks/extending_w3c_ml_work_to_embedded_systems.html">Extending W3C ML Work to Embedded Systems</a><span class="summary"> by Peter Hoddie (Moddable Tech) - 6 min <span></span></span></div><span class=added>Added on 2020-09-11</span></summary><p><a href="talks/extending_w3c_ml_work_to_embedded_systems.html">6 minutes presentation</a></p><dl><dt>Speaker</dt><dd>Peter Hoddie (Moddable Tech)</dd><dd><p>Peter is the chair of Ecma TC53, ECMAScript Module for Embedded Systems, working to bring standard JavaScript APIs to IoT.</p><p>He is a delegate to Ecma TC39, the JavaScript language standards committee, where his focus is ensuring JavaScript remains a viable language on resource constrained devices.</p><p>He is a co-founder and CEO of Moddable Tech, building XS, the only modern JavaScript engine for embedded systems, and the Moddable SDK, a JavaScript framework for delivering consumer and industrial IoT products.</p><p>Peter is the co-author of “IoT Development for ESP32 and ESP8266 with JavaScript”, published in 2020 by Apress, the professional books imprint of Springer Nature.</p><p>He contributed to the ISO MPEG-4 file format standard.</p><p><a href='https://www.moddable.com/peter-hoddie'>Additional bio information</a></p></dd><dt>Abstract</dt><dd><p>JavaScript's dominance on the web often obscures its many successes beyond the web, such as in embedded systems. New silicon for embedded systems is beginning to include hardware to accelerate ML, bringing ML to edge devices. These embedded systems are capable of running the same modern JavaScript used on the web. Would it be possible for the embedded systems to be coded in JavaScript in a way that is compatible with the ML APIs of the web?</p><p>This talk will briefly present two examples of JavaScript APIs developed for the web to support hardware features -- the W3C Sensor API and the Chrome Serial API. It will describe how each has been bridged to the embedded world in a different way -- perhaps suggesting a model for how W3C ML JavaScript APIs can bridge the embedded and browser worlds as well.</p></dd></dl></details>
67
</dl>

0 commit comments

Comments
 (0)