Update generated files

Author: dontcallmedom

_includes/transcripts/sm_architecture.html

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-<div class="slide" role='region' aria-label="Slide 1 of 9" id="slide-1" data-fmt="pdf" data-src="https://www.w3.org/2020/Talks/mlws/sm_architecture.pdf#page=1"><noscript><a href="https://www.w3.org/2020/Talks/mlws/sm_architecture.pdf#page=1">Slide 1</a></noscript></div><div role='region'><p>Hi, I'm Sangwhan Moon from the Technical Architecture Group also known as the TAG.</p>
+<div role='region'><p>Hi, I'm Sangwhan Moon from the Technical Architecture Group also known as the TAG.</p>
 <p>And today I will be talking about how machine learning today will ideally become a part of the web platform.</p>
 <p>To briefly introduce myself as noted earlier I am an elected member of the TAG, team leader then E-commerce Oriented Computers Startup, and finally a PhD student in Natural Language Processing at the Tokyo Institute of Technology.</p>
-<p>I would like to note that the presentation today carries more weight from a personal perspective on the topic rather than the formal group message from the TAG.</p></div><div class="slide" role='region' aria-label="Slide 2 of 9" id="slide-2" data-fmt="pdf" data-src="https://www.w3.org/2020/Talks/mlws/sm_architecture.pdf#page=2"><noscript><a href="https://www.w3.org/2020/Talks/mlws/sm_architecture.pdf#page=2">Slide 2</a></noscript></div><div role='region'><p>Machine learning, namely the sub-field, which involves using large neural networks to approximate various functions through large amounts of training that have been a hot topic in the last couple of years.</p>
+<p>I would like to note that the presentation today carries more weight from a personal perspective on the topic rather than the formal group message from the TAG.</p></div><div role='region'><p>Machine learning, namely the sub-field, which involves using large neural networks to approximate various functions through large amounts of training that have been a hot topic in the last couple of years.</p>
 <p>Due to the social technical impact this has brought to our lives developers and users alike expecting this functionality to become part of the web platform is a natural progression.</p>
-<p>Many operating systems have started providing the APIs that allow you access to these capabilities, sometimes which wire directly to a neural network optimized core processor.</p></div><div class="slide" role='region' aria-label="Slide 3 of 9" id="slide-3" data-fmt="pdf" data-src="https://www.w3.org/2020/Talks/mlws/sm_architecture.pdf#page=3"><noscript><a href="https://www.w3.org/2020/Talks/mlws/sm_architecture.pdf#page=3">Slide 3</a></noscript></div><div role='region'><p>First and foremost we would like to work to have a stronger focus on maximizing impact with smaller incremental changes.</p>
+<p>Many operating systems have started providing the APIs that allow you access to these capabilities, sometimes which wire directly to a neural network optimized core processor.</p></div><div role='region'><p>First and foremost we would like to work to have a stronger focus on maximizing impact with smaller incremental changes.</p>
 <p>All these topic may still be open for debate, how we see this is to focus more on inference rather than try to tackle training and providing a full blown set of APIs from the get-go.</p>
 <p>The reason for this is that we see a larger pool of users on the inference side rather than the training side.</p>
 <p>Mainly because having a browser tab open for weeks doing a training run seems like a less likely scenario.</p>
-<p>Eventually we'd like to see more capabilities added but incremental enhancements allow us as a platform to adapt to actual user needs in the world that focus on fixing easier problems first.</p></div><div class="slide" role='region' aria-label="Slide 4 of 9" id="slide-4" data-fmt="pdf" data-src="https://www.w3.org/2020/Talks/mlws/sm_architecture.pdf#page=4"><noscript><a href="https://www.w3.org/2020/Talks/mlws/sm_architecture.pdf#page=4">Slide 4</a></noscript></div><div role='region'><p>One of the complications in defining a mechanism to run pre-trained neural network models in the browser is to agree on the standard format for packaging and shipping these neural network models.</p>
+<p>Eventually we'd like to see more capabilities added but incremental enhancements allow us as a platform to adapt to actual user needs in the world that focus on fixing easier problems first.</p></div><div role='region'><p>One of the complications in defining a mechanism to run pre-trained neural network models in the browser is to agree on the standard format for packaging and shipping these neural network models.</p>
 <p>Machine learning academia and the ecosystem of frameworks have still not agreed on a common format which makes this challenging for us as a platform, as we must choose from one of the multiple competing proposals.</p>
 <p>But we do not have a particular preference on the specific format, we'd like to see some form of convergence to make life easier for the users of the platform.</p>
-<p>The same applies for the shader language for computation, which as we understand has also has yet to achieve consensus on.</p></div><div class="slide" role='region' aria-label="Slide 5 of 9" id="slide-5" data-fmt="pdf" data-src="https://www.w3.org/2020/Talks/mlws/sm_architecture.pdf#page=5"><noscript><a href="https://www.w3.org/2020/Talks/mlws/sm_architecture.pdf#page=5">Slide 5</a></noscript></div><div role='region'><p>Additionally while it is possible to do a lot of this without a permission as of today, through capabilities already available in the platform such as <a class=dfn>WebGL</a> and <a class=dfn>WebAssembly</a>, at the point of standardization as a platform API, we would like to see this behind the permission if possible.</p>
+<p>The same applies for the shader language for computation, which as we understand has also has yet to achieve consensus on.</p></div><div role='region'><p>Additionally while it is possible to do a lot of this without a permission as of today, through capabilities already available in the platform such as <a class=dfn>WebGL</a> and <a class=dfn>WebAssembly</a>, at the point of standardization as a platform API, we would like to see this behind the permission if possible.</p>
 <p>The reasons for this is not only due to the potential privacy implications, but also due to the power requirements that these APIs may bring to the table.</p>
 <p>This can have negative effects on the battery life for users who get out of a single charge.</p>
-<p>So we believe that the users should have a choice to reject if they are in a situation where they would want to be conservative about power usage.</p></div><div class="slide" role='region' aria-label="Slide 6 of 9" id="slide-6" data-fmt="pdf" data-src="https://www.w3.org/2020/Talks/mlws/sm_architecture.pdf#page=6"><noscript><a href="https://www.w3.org/2020/Talks/mlws/sm_architecture.pdf#page=6">Slide 6</a></noscript></div><div role='region'><p>An extra point that we'd like to bring to the attention of the group is to open questions that remain to integrate these capabilities to the platform.</p>
+<p>So we believe that the users should have a choice to reject if they are in a situation where they would want to be conservative about power usage.</p></div><div role='region'><p>An extra point that we'd like to bring to the attention of the group is to open questions that remain to integrate these capabilities to the platform.</p>
 <p>Due to the current limitations of JavaScript such as the lack of operator overloading it makes it challenging to implement an ergonomic API for vector <a class=dfn>matrix</a> or <a class=dfn>tensor</a> operations on the web platform.</p>
 <p>From a user's perspective, it's a lot more straightforward to have infix functions than to chain the pilot function calls.</p>
 <p>The last question we have is whether there is a path forward to converge with non-browser JavaScript runtimes such as <a class=dfn>Node.js</a>.</p>
-<p>These are points that are open for further discussion.</p></div><div class="slide" role='region' aria-label="Slide 7 of 9" id="slide-7" data-fmt="pdf" data-src="https://www.w3.org/2020/Talks/mlws/sm_architecture.pdf#page=7"><noscript><a href="https://www.w3.org/2020/Talks/mlws/sm_architecture.pdf#page=7">Slide 7</a></noscript></div><div role='region'><p>The TAG has two principles that might be useful for this group to move the work forward.</p>
+<p>These are points that are open for further discussion.</p></div><div role='region'><p>The TAG has two principles that might be useful for this group to move the work forward.</p>
 <p>We have the base guidelines which is the Design Principles documents, which touches on how APIs for the web should be designed, but also the ethical web principles, which we recently released.</p>
-<p>As capabilities such as computer vision, which can be achieved with the work that is being proposed by this group, can also have wider social and ethical implications, we'd like the group to look into the larger scale social impact by bringing these capabilities to the web, to mitigate any potential risks that it may bring to the end user's privacy.</p></div><div class="slide" role='region' aria-label="Slide 8 of 9" id="slide-8" data-fmt="pdf" data-src="https://www.w3.org/2020/Talks/mlws/sm_architecture.pdf#page=8"><noscript><a href="https://www.w3.org/2020/Talks/mlws/sm_architecture.pdf#page=8">Slide 8</a></noscript></div><div role='region'><p>As this is a powerful and complex capability that we have not previously done on the web platform, the TAG would be very interested in doing early reviews on the topic.</p>
-<p>We would be happy to review early proposals from the contributors of the group, through our design reviews repository at github.com/w3ctag/design-reviews We'd also be more than happy to actively engage in any cross working group facilitation needed to make this work happen.</p></div><div class="slide" role='region' aria-label="Slide 9 of 9" id="slide-9" data-fmt="pdf" data-src="https://www.w3.org/2020/Talks/mlws/sm_architecture.pdf#page=9"><noscript><a href="https://www.w3.org/2020/Talks/mlws/sm_architecture.pdf#page=9">Slide 9</a></noscript></div><div role='region'><p>Thank you for listening to my presentation.</p>
+<p>As capabilities such as computer vision, which can be achieved with the work that is being proposed by this group, can also have wider social and ethical implications, we'd like the group to look into the larger scale social impact by bringing these capabilities to the web, to mitigate any potential risks that it may bring to the end user's privacy.</p></div><div role='region'><p>As this is a powerful and complex capability that we have not previously done on the web platform, the TAG would be very interested in doing early reviews on the topic.</p>
+<p>We would be happy to review early proposals from the contributors of the group, through our design reviews repository at github.com/w3ctag/design-reviews We'd also be more than happy to actively engage in any cross working group facilitation needed to make this work happen.</p></div><div role='region'><p>Thank you for listening to my presentation.</p>
 <p>I'll be available in the live session for any questions you may have.</p></div>

_includes/transcripts/tp_interactive_music.html

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-<div class="slide" role='region' aria-label="Slide 1 of 1" id="slide-1" data-fmt="pdf" data-src="https://www.w3.org/2020/Talks/mlws/tp_interactive_music.pdf#page=1"><noscript><a href="https://www.w3.org/2020/Talks/mlws/tp_interactive_music.pdf#page=1">Slide 1</a></noscript></div><div role='region'><p>Hello, everyone, my name is Tero Parviainen, and I would like to share a few thoughts on my experiences making musical applications powered by machine learning models for the web.</p>
+<div role='region'><p>Hello, everyone, my name is Tero Parviainen, and I would like to share a few thoughts on my experiences making musical applications powered by machine learning models for the web.</p>
 <p>Now I run a creative technology and design studio called Counterpoint with my partner, Sam Diggins, and we do a lot of stuff for the web.</p>
 <p>We do experiments on musical instruments, music tools, artistic works, some more commercial oriented work as well, and we quite often end up doing the things we do on the web platform.</p>
 <p>And it's been really good to us.</p>

talks/a_virtual_character_web_meeting_with_expression_enhance_power_by_machine_learning.html

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-
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-title: A virtual character web meeting with expression enhance power by machine learning
+title: "A virtual character web meeting with expression enhance power by machine learning"
 author: Zelun Chen (Netease)
 layout: talk
 format: pdf

talks/accelerate_ml_inference_on_mobile_devices_with_android_nnapi.html

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-
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-title: Accelerate ML inference on mobile devices with Android NNAPI
+title: "Accelerate ML inference on mobile devices with Android NNAPI"
 author: Miao Wang (Google)
 layout: talk
 format: pdf

talks/accelerated_graphics_and_compute_api_for_machine_learning_directml.html

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-
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-title: Accelerated graphics and compute API for Machine Learning - DirectML
+title: "Accelerated graphics and compute API for Machine Learning - DirectML"
 author: Chai Chaoweeraprasit (Microsoft)
 layout: talk
 format: pdf

talks/access_purpose_built_ml_hardware_with_web_neural_network_api.html

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-
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-title: Access purpose-built ML hardware with Web Neural Network API
+title: "Access purpose-built ML hardware with Web Neural Network API"
 author: Ningxin Hu (Intel)
 layout: talk
 format: pdf

talks/collaborative_learning.html

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-
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-title: Collaborative Learning
+title: "Collaborative Learning"
 author: Wolfgang Maß (DFKI)
 layout: talk
 format: pdf

talks/empowering_musicians_and_artists_using_machine_learning_to_build_their_own_tools_in_the_browser.html

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-
 ---
-title: Empowering Musicians and Artists using Machine Learning to Build Their Own Tools in the Browser
+title: "Empowering Musicians and Artists using Machine Learning to Build Their Own Tools in the Browser"
 author: Louis McCallum (University of London)
 layout: talk
 format: pdf

talks/enabling_distributed_dnns_for_the_mobile_web_over_cloud_edge_and_end_devices.html

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-
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-title: Enabling Distributed DNNs for the Mobile Web Over Cloud, Edge and End Devices
+title: "Enabling Distributed DNNs for the Mobile Web Over Cloud, Edge and End Devices"
 author: Yakun Huang & Xiuquan Qiao (BPTU)
 layout: talk
 format: pdf

talks/exploring_unsupervised_image_segmentation_results.html

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-
 ---
-title: Exploring unsupervised image segmentation results
+title: "Exploring unsupervised image segmentation results"
 author: Piotr Migdal & Bartłomiej Olechno ()
 layout: talk
 format: shiny

talks/fast_client_side_ml_with_tensorflow_js.html

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-
 ---
-title: Fast client-side ML with TensorFlow.js
+title: "Fast client-side ML with TensorFlow.js"
 author: Ann Yuan (Google)
 layout: talk
 format: pdf

talks/interactive_ml_powered_music_applications_on_the_web.html

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-
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-title: Interactive ML - Powered Music Applications on the Web
+title: "Interactive ML - Powered Music Applications on the Web"
 author: Tero Parviainen (Counterpoint)
 layout: talk
 format: pdf
 shortname: tp_interactive_music
 thumbnailurl: https://cjx1uopmt0m4q0667xmnrqpk.blob.core.windows.net/ckdo76mfh4sne0772endmrepx/thumbs/thumb-002.jpeg
 videourl: https://app.streamfizz.live/embed/ckdo76mfh4sne0772endmrepx
-slidesurl: https://www.w3.org/2020/Talks/mlws/tp_interactive_music.pdf
+slidesurl: 
 ---

talks/introducing_wasi_nn.html

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-
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-title: Introducing WASI-NN
+title: "Introducing WASI-NN"
 author: Mingqiu Sun & Andrew Brown (Intel)
 layout: talk
 format: pdf

talks/machine_learning_in_web_architecture.html

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-
 ---
-title: Machine Learning in Web Architecture
+title: "Machine Learning in Web Architecture"
 author: Sangwhan Moon ()
 layout: talk
 format: pdf
 shortname: sm_architecture
 thumbnailurl: https://cjx1uopmt0m4q0667xmnrqpk.blob.core.windows.net/ckdo77c2k4srf07726abf6aps/thumbs/thumb-001.jpeg
 videourl: https://app.streamfizz.live/embed/ckdo77c2k4srf07726abf6aps
-slidesurl: https://www.w3.org/2020/Talks/mlws/sm_architecture.pdf
+slidesurl: 
 ---

talks/machine_learning_on_the_web_for_content_filtering_applications.html

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-
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-title: Machine Learning on the Web for content filtering applications
+title: "Machine Learning on the Web for content filtering applications"
 author: Oleksandr Paraska (eyeo)
 layout: talk
 format: pdf

talks/media_processing_hooks_for_the_web.html

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-
 ---
-title: Media processing hooks for the Web
+title: "Media processing hooks for the Web"
 author: François Daoust (W3C)
 layout: talk
 format: shower

talks/mobile_first_web_based_machine_learning.html

@@ -1,6 +1,5 @@
-
 ---
-title: Mobile-first web-based Machine Learning
+title: "Mobile-first web-based Machine Learning"
 author: Josh Meyer & Lindy Rauchenstein (Artie)
 layout: talk
 format: pdf

talks/onnx_js_a_javascript_library_to_run_onnx_models_in_browsers_and_node_js.html

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-
 ---
-title: ONNX.js - A Javascript library to run ONNX models in browsers and Node.js
+title: "ONNX.js - A Javascript library to run ONNX models in browsers and Node.js"
 author: Emma Ning (Microsoft)
 layout: talk
 format: pdf

talks/opportunities_and_challenges_for_tensorflow_js_and_beyond.html

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-
 ---
-title: Opportunities and Challenges for TensorFlow.js and beyond
+title: "Opportunities and Challenges for TensorFlow.js and beyond"
 author: Jason Mayes (Google)
 layout: talk
 format: pdf

talks/paddle_js_machine_learning_for_the_web.html

@@ -1,6 +1,5 @@
-
 ---
-title: Paddle.js - Machine Learning for the Web
+title: "Paddle.js - Machine Learning for the Web"
 author: Ping Wu (Baidu)
 layout: talk
 format: pdf

talks/privacy_first_approach_to_machine_learning.html

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-
 ---
-title: Privacy-first approach to machine learning
+title: "Privacy-first approach to machine learning"
 author: Philip Laszkowicz ()
 layout: talk
 format: pdf

talks/rnnoise_neural_speech_enhancement_and_the_browser.html

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-
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-title: RNNoise, Neural Speech Enhancement, and the Browser
+title: "RNNoise, Neural Speech Enhancement, and the Browser"
 author: Jean-Marc Valin ()
 layout: talk
 format: pdf

talks/we_count_fair_treatment_disability_and_machine_learning.html

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-
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-title: We Count: Fair Treatment, Disability and Machine Learning
+title: "We Count: Fair Treatment, Disability and Machine Learning"
 author: Jutta Treviranus (OCAD University)
 layout: talk
 format: pdf

talks/web_platform_a_30_000_feet_view_web_platform_and_js_environment_constraints.html

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-
 ---
-title: Web Platform: a 30,000 feet view / Web Platform and JS environment constraints
+title: "Web Platform: a 30,000 feet view / Web Platform and JS environment constraints"
 author: Dominique Hazaël-Massieux (W3C)
 layout: talk
 format: shower

talks/wreck_a_nice_beach_in_the_browser_getting_the_browser_to_recognize_speech.html

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-
 ---
-title: Wreck a Nice Beach in the Browser: Getting the Browser to Recognize Speech
+title: "Wreck a Nice Beach in the Browser: Getting the Browser to Recognize Speech"
 author: Kelly Davis (Mozilla)
 layout: talk
 format: pdf