Powerful generative AI features are quickly becoming a baseline in modern development. Potential blockers include privacy concerns, the need for a stable connection, and the costs associated with using or hosting models. However, we can now leverage generative AI directly in the browser on the user's device using emerging Web APIs like WebNN, combined with higher-level frameworks, for a better developer experience. In my session, I’ll discuss the current state of in-browser ML and AI features, compare the main players, and show you how to start building an offline-ready, future-proof, standards-based web application.

With the rapid adoption of AI models in software products, Chrome’s introduction of local-first, on-device AI models offers developers a powerful new way to build intelligent and fast AI features directly within the browser. This talk will explore Chrome’s Built-in AI models, their architecture, APIs, developer tooling, and also demonstrate how it supports low-latency AI experiences without relying solely on cloud-deployed models.

We’ll walk through the architecture behind Chrome’s on-device models, discuss real-world edge cases and common concerns from integrating the built-in AI APIs, and outline key system and compatibility requirements that every developer should know. This talk will also mention the evolution of Chrome’s AI ecosystem, from its early releases to current capabilities, along with a preview of upcoming features and insights from its developer community.

For advanced listeners in the audience, this talk will include Chrome’s hybrid AI support pairing with Firebase to extend applications with cloud-backed storage and processing, enabling developers to blend on-device intelligence with online workflows.

To keep this talk interactive and practical, I will use my open-source Chrome extension project built during the recently concluded Chrome AI hackathon as a demo, highlighting how the Prompt and Summariser APIs are being used in the Chrome extension.

AI progress is running away on the server-side, where the GPUs live, but the web platform is never that far behind. In this talk we're going to explore the incredible applications you can build in the browser today and in the near future.

You'll see how to build an offline-capable, speech to speech language translation app, a babelfish, using nothing but the web platform. Through this app we'll explore the different ways we can run AI models in the browser today and what may be built into the browser in the future. From low-level standards to high-level experiments, you'll learn how to work with AI on the web.

Bio: 

Phil is a developer relations engineer for Langflow at IBM and Google Developer Expert living in Melbourne, Australia. He loves working with JavaScript, TypeScript or Ruby to build web applications and tools to help developers. He once helped build a website that captured the world's favourite sandwich fillings. He has too many GitHub repositories.

Away from the keyboard, Phil listens to ska punk, hangs out with his miniature dachshund (also called Ruby), and is on a mission to discover the world's best beers.

Phil tweets at @philnash and you can find him elsewhere online at https://philna.sh.

AI has revolutionized web application internationalization. This talk demonstrates how modern AI technologies create a transformative shift in making web content globally accessible. Instead of traditional localization workflows costing thousands per language, we can now automate translation, transcription, and voice generation at a fraction of the cost. Through live demos and real-world examples, we’ll explore how this disrupts conventional approaches and empowers small teams to reach global audiences. The talk will also showcase practical implementation patterns attendees can apply to their projects.