KubeCon + CloudNativeCon + Open Source Summit + AI_dev China 2024

In today's interconnected world, deploying and accessing machine learning (ML) models efficiently poses significant challenges. Traditional methods rely on cloud GPU clusters and constant internet connectivity. However, WebAssembly (Wasm) and WebGPU technologies are revolutionizing this landscape. This talk explores leveraging Wasm and WebGPU for deploying Single Layer Models (SLMs) directly within web browsers, eliminating the need for extensive cloud GPU clusters and reducing reliance on constant internet access. We showcase practical examples and discuss how Wasm enables efficient cross-platform ML model execution, while WebGPU optimizes parallel computation within browsers. Join us to discover how this fusion empowers developers and users alike with unprecedented ease and efficiency in browser-based ML, while reducing dependence on centralized cloud infrastructure and internet connectivity constraints.

在当今互联世界中，高效部署和访问机器学习（ML）模型面临着重大挑战。传统方法依赖于云GPU集群和持续的互联网连接。然而，WebAssembly（Wasm）和WebGPU技术正在彻底改变这一局面。本次演讲探讨了如何利用Wasm和WebGPU在Web浏览器中直接部署单层模型（SLMs），消除了对庞大云GPU集群的需求，减少了对持续互联网访问的依赖。我们展示了实际示例，并讨论了Wasm如何实现高效的跨平台ML模型执行，以及WebGPU如何优化浏览器内的并行计算。加入我们，发现这种融合如何赋予开发人员和用户在基于浏览器的ML中前所未有的便利和效率，同时减少对集中式云基础设施和互联网连接的依赖。