AppsConf 2025

📌 How can AI improve without compromising privacy?

As AI becomes integral to mobile experiences, privacy concerns continue to rise. Traditional machine learning requires sending user data to the cloud, raising security risks. But what if we could build smarter AI without ever exposing personal data?

This is where Federated Learning on iOS transforms mobile AI. Instead of transferring raw data, models train directly on devices, and only encrypted updates are shared—aligning with Apple’s privacy-first vision.

In this session, we’ll deep dive into Federated Learning, covering:
✔️ How Federated Learning is shaping the future of AI on iOS
✔️ Implementing privacy-preserving machine learning using Swift, Core ML, and Create ML
✔️ Performance optimizations for real-world applications

This talk is for developers, architects, and AI enthusiasts looking to integrate on-device AI while maintaining data privacy, security, and efficiency.

Join us to explore this game-changing shift in iOS AI development and learn how to build the next generation of privacy-first, AI-powered applications. 🚀