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_includes/talk-list1.html

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 <div class="talks"><details class=talk><summary><div class="grid"><a href="talks/privacy_first_approach_to_machine_learning.html"><img src="https://cjx1uopmt0m4q0667xmnrqpk.blob.core.windows.net/ckdor50iyc9lm07729dsrtpqu/thumbs/thumb-001.jpeg" alt="Watch Privacy-first approach to machine learning" width=200 class="tn"></a><a href="talks/privacy_first_approach_to_machine_learning.html">Privacy-first approach to machine learning</a><span class="summary"> by Philip Laszkowicz - 11 min <span></span></span></div></summary><p><a href="talks/privacy_first_approach_to_machine_learning.html">11 minutes presentation</a></p><dl><dt>Speaker</dt><dd>Philip Laszkowicz</dd><dt>Abstract</dt><dd>The presentation will discuss how developers should be building modern web apps and what is missing in the existing ecosystem to make privacy-first ML possible including the challenges with WASI, modular web architecture, and localized analytics.</dd></dl></details>
-<details class=talk><summary><div class="grid"><a href="talks/machine_learning_and_web_media.html"><img src="https://cjx1uopmt0m4q0667xmnrqpk.blob.core.windows.net/cke43ihp10fub0731lohsnpmo/thumbs/thumb-001.jpeg" alt="Watch Machine Learning and Web Media" width=200 class="tn"></a><a href="talks/machine_learning_and_web_media.html">Machine Learning and Web Media</a><span class="summary"> by Bernard Aboba (Microsoft) - 7 min <span></span></span></div><span class=added>Added on 2020-08-26</span></summary><p><a href="talks/machine_learning_and_web_media.html">7 minutes presentation</a></p><dl><dt>Speaker</dt><dd>Bernard Aboba (Microsoft)</dd><dt>Abstract</dt><dd>The presentation will discuss efficient processing of raw video in machine learning, highlighting the need to minimize memory copies and enable integration with WebGPU.</dd></dl></details>
+<details class=talk><summary><div class="grid"><a href="talks/machine_learning_and_web_media.html"><img src="https://cjx1uopmt0m4q0667xmnrqpk.blob.core.windows.net/cke43ihp10fub0731lohsnpmo/thumbs/thumb-001.jpeg" alt="Watch Machine Learning and Web Media" width=200 class="tn"></a><a href="talks/machine_learning_and_web_media.html">Machine Learning and Web Media</a><span class="summary"> by Bernard Aboba (Microsoft) - 7 min <span></span></span></div></summary><p><a href="talks/machine_learning_and_web_media.html">7 minutes presentation</a></p><dl><dt>Speaker</dt><dd>Bernard Aboba (Microsoft)</dd><dt>Abstract</dt><dd>The presentation will discuss efficient processing of raw video in machine learning, highlighting the need to minimize memory copies and enable integration with WebGPU.</dd></dl></details>
 <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>
 <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>
-<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>
+<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></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>
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_includes/talk-list1_zh.html

@@ -1,6 +1,6 @@
 <div class="talks"><details class=talk><summary><div class="grid"><a href="talks/privacy_first_approach_to_machine_learning.html"><img src="https://cjx1uopmt0m4q0667xmnrqpk.blob.core.windows.net/ckdor50iyc9lm07729dsrtpqu/thumbs/thumb-001.jpeg" alt="Watch 隐私优先的机器学习方法" width=200 class="tn"></a><a href="talks/privacy_first_approach_to_machine_learning.html">隐私优先的机器学习方法</a><span class="summary"> by Philip Laszkowicz - 11 min <span></span></span></div></summary><p><a href="talks/privacy_first_approach_to_machine_learning.html">11 minutes presentation</a></p><dl><dt>Speaker</dt><dd>Philip Laszkowicz</dd><dt>Abstract</dt><dd>这次演讲将讨论开发人员应该如何构建现代web应用程序，以及现有的生态系统中哪些缺失使得隐私优先的机器学习成为可能，包括WASI、模块化web架构和本地化分析所面临的挑战。</dd></dl></details>
-<details class=talk><summary><div class="grid"><a href="talks/machine_learning_and_web_media.html"><img src="https://cjx1uopmt0m4q0667xmnrqpk.blob.core.windows.net/cke43ihp10fub0731lohsnpmo/thumbs/thumb-001.jpeg" alt="Watch 机器学习和 Web 媒体" width=200 class="tn"></a><a href="talks/machine_learning_and_web_media.html">机器学习和 Web 媒体</a><span class="summary"> by Bernard Aboba (微软) - 7 min <span></span></span></div><span class=added>Added on 2020-08-26</span></summary><p><a href="talks/machine_learning_and_web_media.html">7 minutes presentation</a></p><dl><dt>Speaker</dt><dd>Bernard Aboba (微软)</dd><dt>Abstract</dt><dd>演讲将讨论机器学习中对原始视频的有效处理，强调最小化内存拷贝和与WebGPU集成的必要性。</dd></dl></details>
+<details class=talk><summary><div class="grid"><a href="talks/machine_learning_and_web_media.html"><img src="https://cjx1uopmt0m4q0667xmnrqpk.blob.core.windows.net/cke43ihp10fub0731lohsnpmo/thumbs/thumb-001.jpeg" alt="Watch 机器学习和 Web 媒体" width=200 class="tn"></a><a href="talks/machine_learning_and_web_media.html">机器学习和 Web 媒体</a><span class="summary"> by Bernard Aboba (微软) - 7 min <span></span></span></div></summary><p><a href="talks/machine_learning_and_web_media.html">7 minutes presentation</a></p><dl><dt>Speaker</dt><dd>Bernard Aboba (微软)</dd><dt>Abstract</dt><dd>演讲将讨论机器学习中对原始视频的有效处理，强调最小化内存拷贝和与WebGPU集成的必要性。</dd></dl></details>
 <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>
 <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>
-<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>
+<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></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>
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