Open Daily: 10am - 10pm | Alley door pickup 10am - 7pm 3038 Hennepin Ave Minneapolis, MN
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  • Open Daily: 10am - 10pm
    Alley-side Pickup: 10am - 7pm

    3038 Hennepin Ave Minneapolis, MN
    612-822-4611

Open Daily: 10am - 10pm | Alley-side Pickup: 10am - 7pm
3038 Hennepin Ave Minneapolis, MN
612-822-4611
On-Device AI: ML Foundations for iOS Developers

On-Device AI: ML Foundations for iOS Developers

Schmitt, Stefan

Paperback

Programming

ISBN13: 9798183889956
Publisher: Independently Published
Published: Jun 23 2026
Pages: 166
Weight: 0.46
Height: 0.42 Width: 6.00 Depth: 9.00
Language: English
A practical blueprint for building production iOS apps with on-device AI.

On-Device AI is written for experienced iOS engineers who want to move beyond API calls and understand how to deploy, optimize, and operate machine-learning models locally on Apple silicon.

The book focuses on the craft of shipping models on the device itself. It skips Python-based data science and concentrates on the mobile problems that decide whether an AI feature works in production: thermal behavior, memory use, latency budgets, privacy, model integration, and graceful failure. It treats the model not as a magic black box, but as a fallible computational asset, like a database or a network stack.

Why now: the Apple Neural Engine, unified memory, and Core ML have made local inference practical for real user-facing apps. The opportunity is not just to call AI services, but to build private, responsive intelligence directly into the software people already carry.

You will learn to:

  • think in probabilities instead of deterministic if-else logic
  • work with the Apple Neural Engine, compiled Core ML models, and the Core ML/Vision stack
  • architect model integration, error handling, and graceful fallbacks
  • budget latency, memory, and power for production
  • know when not to use AI

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