The @w3c Web & Machine Learning workshop, scheduled for March 24 & 25 in #Berlin 🇩🇪, aims to collaboratively build a roadmap for enrich the #WebPlatform with the right foundations for #MachineLearning
w3.org/2020/01/machine-learn…
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Chaired by @anssik and @KellyJayDavis, this new #W3CWorkshop, hosted by @Microsoft, will help review existing work in this space, how it fits together and how well it fits the need of end-users and industry
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Among notable existing work in this space, the #MachineLearning for the Web #CommunityGroup is evaluating what primitives Web browsers should provide as #APIs to make Machine Learning inference fast, enabling one-click deployment of ML-based #apps
w3.org/community/webmachinel…
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The main deliverable the group is discussing at the moment is the Web Neural Network API (WebNN) webmachinelearning.github.io…
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The expectation is that such an API would help with JS-based frameworks already being used today to run #MachineLearning inference in browsers: #TensorFlowJS (@nsthorat is on the workshop committee), the #javascript
version of #ONNX, PaddlePaddle
Registration for the W3C ML on the Web workshop opened, it’s in Berlin in March. Come hang!
w3.org/2020/01/machine-learn…
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The workshop will also discuss how other related technologies fit in that landscape: other computing APIs such as #WebGPU, #WebAssembly, but also ML-based #APIs such as the speech recognition API wicg.github.io/speech-api/ or the shape
detection API wicg.github.io/shape-detecti…
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If you think you have a useful perspective to contribute, please consider registering to the Web & #MachineLearning #W3CWorkshop before Feb 21 w3.org/2020/01/machine-learn…
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