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Google近日发布了全新的JavaScript库——LiteRT.js，旨在显著提升网页浏览器端的机器学习与人工智能工作负载的处理速度。这一举措标志着Google正将其移动端优化的LiteRT运行时引入Web平台，从而使得AI模型能够直接在本地浏览器环境中高效运行，无需依赖服务器端的处理。相较于现有的TensorFlow.js，LiteRT.js展现出了明显的性能优势。据悉，该库利用了WebAs ...

在搭载 M4 芯片的 2024 款苹果 MacBook Pro 笔记本上，谷歌测试发现相比较现有方案， LiteRT.js 速度提升 3 倍。谷歌在官方博文中表示，在运行旧硬件或使用不同引擎的浏览器时，实际性能可能存在差异。

谷歌近日宣布推出一款名为LiteRT.js的新型Javascript库，旨在显著提升浏览器端人工智能（AI）与机器学习（ML）任务的运行效率。该库通过整合WebAssembly、WebGPU及WebNN等前沿技术，为开发者提供了更高效的硬件加速方案，成为TensorFlow.js的重要替代选项。

LiteRT.js runs machine learning models locally with CPU, GPU and emerging NPU acceleration, potentially reducing server infrastructure, inference charges and data movement.

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