Generative and intelligent features are quickly becoming a core part of modern web experiences—but they often come with trade-offs: privacy concerns, reliance on internet connectivity, and the cost of using cloud-based APIs. What if you could bring powerful AI directly into the browser, on the user's device?

In this session, we’ll explore the full landscape of browser-based AI and machine learning—no servers required. From text generation and image recognition to real-time transcription and offline copilots, the web platform now provides a rich toolbox of APIs and tools to enable truly private, performant, and intelligent experiences.

What You’ll Learn:
✅ The current state of in-browser AI and ML: what’s possible today, and what’s coming
✅ How to run AI models fully offline using WebAssembly, ONNX Runtime Web, and Transformers.js
✅ Deep dive into key technologies: WebNN, WebGPU, Web Workers, and WASM
✅ Real-world use cases for text, vision, and audio AI—without touching a server
✅ Trade-offs and best practices for choosing between client-side, hybrid, and cloud-based approaches
✅ Strategies to build privacy-first, offline-capable, and standards-aligned AI experiences on the web
✅ Live demo: a fully browser-based AI app with zero server calls and full user privacy

Whether you're building productivity tools, creative apps, or next-gen web experiences, this session will give you a clear and actionable understanding of how to harness AI directly in the browser—securely, sustainably, and at scale.

Audience: Web developers exploring AI integration without relying on the cloud, focused on privacy, performance, or offline support

Keywords: browser-based AI, web standards, WebNN, WebGPU, WebAssembly, privacy-first AI, offline AI, edge AI, generative AI, web platform

Outline:
- Why Browser-Based AI?
- Core Technologies Behind AI in the Browser
- Running Models Locally
- Trade-Offs and Patterns
- Development Best Practices
- Live Demo + Q&A