As AI moves closer to the client, the next generation of web applications will need to run intelligent, real-time experiences directly in the browser. Thanks to WebGPU, developers can now run high-performance, GPU-accelerated machine learning workloads on the client side — enabling personalization, AI-assisted interactions, and visual computation without relying on a backend model server.

This talk explores how React developers can leverage WebGPU and modern ML runtimes to build responsive, privacy-preserving AI user interfaces capable of running real-time inference in the browser. Through practical examples, we’ll look at how to integrate on-device embeddings, text and vision models, gesture recognition, and dynamic AI-driven UI behaviors into modern React applications.

We’ll walk through how WebGPU differs from WebGL, what optimizations it unlocks, and how frameworks like TensorFlow.js, ONNX Runtime Web, and WebGPU-native pipelines can be combined with React for highly interactive experiences. Attendees will also learn best practices for orchestrating GPU workloads without blocking the UI thread, managing streaming inference, and structuring React components to handle continuous, high-frequency data updates.

By the end of this session, developers will understand how to build AI-powered interfaces that feel fast, fluid, and deeply interactive — without expensive servers, latency issues, or privacy trade-offs. This talk is ideal for React developers, frontend engineers, and product teams exploring how AI can elevate the user experience in modern web applications.