The integration of AI models into web applications is revolutionizing user experiences, but the large size of these models poses a significant challenge for performance. Slow loading times and unresponsive interactions can frustrate users and hinder adoption. This talk will delve into the critical aspect of efficient AI model caching in Chrome, exploring strategies to optimize model delivery and ensure seamless user experiences.

We'll cover:

- The performance implications of large AI models in web applications.

- Best practices for configuring cache headers to leverage browser caching effectively.

- In-depth comparison of client-side caching techniques: Cache API, Origin Private File System (OPFS), and IndexedDB.

- Advanced strategies for handling user-selected models and large file downloads.

- Security considerations and trade-offs when caching AI models locally.

Whether you're a web developer, AI engineer, or performance enthusiast, this talk will equip you with the knowledge and tools to deliver lightning-fast AI-powered web experiences. Learn how to optimize model loading, reduce latency, and create web applications that seamlessly integrate AI capabilities without compromising performance.