Thomas Steiner
Exploring the Future of Web AI with Google
#1about 2 minutes
Introducing Google's fund for web AI innovation
The Google AI fund supports developers building on-device, cloud, or hybrid AI solutions to encourage ecosystem growth.
#2about 2 minutes
Optimizing on-device AI with right-sized models
Avoid performance issues by selecting the smallest model that delivers acceptable quality for the specific use case and device.
#3about 4 minutes
Using built-in browser models to reduce overhead
Browsers can provide built-in models for common tasks, which reduces redundant downloads and offers developers simple, high-level APIs.
#4about 4 minutes
Standardizing web AI APIs across different browsers
New AI capabilities are being standardized through proposals like navigator.ai, with developers using polyfills to provide cloud-based fallbacks in unsupported browsers.
#5about 4 minutes
Navigating the web AI API release process
New web AI APIs become available through a phased rollout, starting with developer flags and origin trials before being shipped in stable browser releases.
#6about 4 minutes
Competing with built-in browser AI user interfaces
Developers face a new challenge as browsers increasingly add their own AI-powered UI, which can compete with or interfere with custom application features.
#7about 8 minutes
How developers can prevent browser AI interference
Developers may need new HTML attributes or APIs to prevent default browser AI behaviors from conflicting with their own custom implementations, similar to disabling autocomplete.
#8about 5 minutes
Connecting web apps to local OS-level AI models
To avoid redundant downloads, web applications can potentially access local OS-level models through methods like local web servers or future browser-OS integrations.
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