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Merge branch 'slide-index'
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‎talks/slide-index/ay_tensorflow.json

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[
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{
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"start": "00:09",
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"title": "Fast client-side ML with TensorFlow.js"
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},
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{
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"start": "01:00",
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"title": "What is TensorFlow.js"
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},
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{
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"start": "01:31",
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"title": "Performance Overview"
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},
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{
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"start": "03:12",
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"title": "The WebAssembly backend"
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},
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{
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"start": "04:22",
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"title": "WebAssembly: our wishlist"
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},
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{
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"start": "04:56",
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"title": "The WebGL backend"
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},
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{
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"start": "05:29",
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"title": "WebGL: our wishlist"
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},
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{
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"start": "06:49",
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"title": "The WebGPU backend"
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},
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{
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"start": "07:31",
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"title": "WebGPU: Performance"
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},
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{
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"start": "07:59",
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"title": "Future web standards wishlist"
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}
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]

‎talks/slide-index/ba-media.json

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[
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{
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"start": "00:08",
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"title": "Machine Learning and Web Media"
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},
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{
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"start": "00:36",
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"title": "The Pandemic of 2020: A Pivotal Moment"
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},
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{
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"start": "03:23",
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"title": "Machine Learning and the Media Pipeline"
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},
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{
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"start": "04:07",
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"title": "Insertable Streams - Encoded Media"
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},
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{
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"start": "04:53",
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"title": "The Current State of Encode/Decode APIs"
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},
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{
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"start": "05:49",
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"title": "Insertable Streams - Relation to other efforts"
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},
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{
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"start": "06:16",
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"title": "AV1 Support"
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}
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]

‎talks/slide-index/cc_directml.json

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[
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{
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"start": "00:10",
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"title": "Accelerated graphics and compute API for Machine Learning - DirectML"
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},
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{
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"start": "00:32",
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"title": "What & Why"
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},
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{
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"start": "02:26",
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"title": "Under the hood"
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},
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{
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"start": "04:19",
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"title": "Windows ML"
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},
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{
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"start": "05:12",
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"title": "TensorFlow"
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},
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{
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"start": "06:09",
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"title": "SonoCNS"
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},
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{
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"start": "07:18",
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"title": "Auto Reframe"
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},
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{
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"start": "08:12",
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"title": "Super Resolution"
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},
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{
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"start": "09:16",
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"title": "YOLO V4"
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},
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{
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"start": "09:42",
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"title": "Style Transfer"
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},
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{
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"start": "10:11",
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"title": "Resources"
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}
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]

‎talks/slide-index/dhm-web-platform-overview.json

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[
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{
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"start": "00:08",
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"title": "Web Platform: a 30,000 feet view / Web Platform and JS environment constraints"
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},
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{
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"start": "00:33",
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"title": "Goal"
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},
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{
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"start": "01:05",
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"title": "Web Platform"
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},
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{
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"start": "02:14",
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"title": "Web Platform Specificities"
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},
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{
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"start": "02:25",
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"title": "Anchored in the Network"
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},
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{
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"start": "02:49",
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"title": "User Agent"
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},
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{
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"start": "03:23",
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"title": "Standards-based"
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},
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{
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"start": "03:46",
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"title": "Cross-Platform"
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},
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{
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"start": "04:16",
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"title": "Impact?"
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},
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{
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"start": "04:26",
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"title": "Constraint: concurrency"
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},
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{
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"start": "05:43",
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"title": "Constraint: same-origin policy"
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},
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{
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"start": "06:32",
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"title": "Constraint: tracking protection"
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},
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{
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"start": "07:22",
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"title": "Constraint: platform neutrality"
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},
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{
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"start": "08:34",
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"title": "Web Platform Pillars"
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},
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{
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"start": "09:37",
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"title": "Machine Learning ♥ Web Platform"
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}
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]

‎talks/slide-index/en_onnxjs.json

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[
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{
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"start": "00:09",
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"title": "ONNX.js - A Javascript library to run ONNX models in browsers and Node.js"
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},
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{
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"start": "00:29",
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"title": "JS-based Client-side applications"
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},
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{
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"start": "01:45",
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"title": "JS-based Clientside Machine Learning"
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},
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{
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"start": "03:48",
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"title": "ONNX.JS Background -ONNX"
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},
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{
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"start": "04:44",
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"title": "ONNX converters for popular frameworks"
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},
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{
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"start": "05:44",
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"title": "ONNX Community"
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},
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{
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"start": "06:26",
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"title": "ONNX.js"
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},
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{
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"start": "11:31",
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"title": "Model inference with ONNX.JS"
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},
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{
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"start": "11:56",
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"title": "HTML example to use ONNX.js"
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},
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{
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"start": "12:17",
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"title": "Using NPM and bundling tools to use ONNX.js"
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},
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{
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"start": "12:27",
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"title": "ONNX.js Demo"
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},
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{
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"start": "13:13",
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"title": "We’d love to embrace your contribution"
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}
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]

‎talks/slide-index/fd-media-hooks.json

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[
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{
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"start": "00:08",
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"title": "Media processing hooks for the Web"
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},
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{
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"start": "00:33",
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"title": "Main media scenarios"
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},
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{
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"start": "02:03",
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"title": "Media content"
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},
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{
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"start": "02:19",
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"title": "Media encoding/decoding pipeline"
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},
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{
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"start": "03:10",
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"title": "Media processing scenarios"
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},
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{
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"start": "03:34",
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"title": "Processing hooks needed!"
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},
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{
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"start": "03:58",
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"title": "Existing hooks for…① progressive media playback"
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},
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{
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"start": "04:38",
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"title": "Existing hooks for…② adaptive media playback"
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},
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{
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"start": "04:56",
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"title": "Existing hooks for…③ real-time conversations"
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},
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{
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"start": "05:29",
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"title": "Existing hooks for…④ synthesized audio playback"
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},
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{
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"start": "05:51",
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"title": "Summary of Existing Hooks"
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},
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{
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"start": "06:07",
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"title": "Media pipeline in JavaScript / WebAssembly"
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},
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{
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"start": "06:31",
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"title": "Main requirements for efficient media processing"
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},
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{
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"start": "07:26",
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"title": "WebCodecs"
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},
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{
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"start": "09:10",
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"title": "Other media features and specs that may impact processing"
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},
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{
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"start": "11:22",
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"title": "Conclusion"
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}
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]

‎talks/slide-index/jb_model.json

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[
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{
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"start": "00:08",
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"title": "A proposed web standard to load and run ML models on the web"
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},
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{
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"start": "00:18",
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"title": "Model Loader API"
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},
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{
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"start": "01:16",
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"title": "Why use machine learning in a web pageas opposed to on the server?"
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},
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{
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"start": "02:08",
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"title": "Why create a new web standard?"
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},
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{
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"start": "02:31",
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"title": "Speed matters for ML"
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},
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{
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"start": "03:16",
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"title": "The web provides APIs for acceleration today. They help!"
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},
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{
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"start": "04:04",
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"title": "Running on native hardware can be even faster"
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},
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{
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"start": "04:41",
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"title": "How could the web platform accelerate ML?"
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},
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{
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"start": "05:08",
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"title": "Operation-level APIs for ML"
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},
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{
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"start": "05:58",
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"title": "Graph APIs open up more performance gains"
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},
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{
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"start": "07:04",
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"title": "WebNN API"
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},
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{
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"start": "07:15",
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"title": "Application-specific ML APIs are easiest for developers"
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},
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{
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"start": "08:21",
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"title": "The model loader API balances flexibility and performance"
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},
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{
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"start": "09:09",
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"title": "Summarizing the options for ML APIs on the web"
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},
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{
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"start": "09:52",
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"title": "Caveat: it’s early days and there are big challenges"
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},
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{
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"start": "11:47",
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"title": "The current plan"
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}
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]

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