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How Google Uses WebAssembly

8 engineering articles about WebAssembly from Google's engineering team

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We're excited to introduce LiteRT.js, the newest member of the LiteRT family! LiteRT.js is our powerful solution for running machine learning models directly in the browser, extending Google's cross-platform edge AI runtime to the web. Built for JavaScript developers, LiteRT.js delivers state-of-the-art ML model inference performance on WebGPU and upcoming WebNN, with a fallback to WebAssembly for CPU. This post provides a quick tour of LiteRT.js and gives web developers everything they need to get started.
Ping Yu, Marko Ristić, Matthew Soulanille, Chintan Parikh
6 min read
Includes Code
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The Web AI Summit 2024, hosted by Google on October 18, 2024, focused on client-side AI for developers, showcasing how machine learning models can operate offline in web browsers.
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The article discusses the development of 'Purrfect Code', a programming puzzle game designed for developers, using Flutter, Dart, and the Flame game engine.
Google for Developers
10 min read
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The article discusses the development of the I/O Crossword, a collaborative game that integrates various Google technologies, including the Gemini API, Flutter, and Firebase.
Jay Chang, Kelvin Boateng
5 min read
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The article recaps the Google I/O 2024 event, highlighting advancements in AI technologies aimed at making AI accessible for developers.
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The article discusses how Google is simplifying cross-platform development for developers by recommending specific technologies and frameworks.
Maru Ahues Bouza, Brandon Badger
3 min read
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This article provides essential dos and don'ts for web developers looking to integrate machine learning (ML) using MediaPipe Solutions.
Jen Person
6 min read
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Intermediate
The article discusses the implementation of MediaPipe on the web, highlighting how it enables cross-platform multimodal applied ML pipelines through WebAssembly and XNNPack.
Michael Hays and Tyler Mullen from the MediaPipe team
4 min read
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