Learn how to harness the power of Apple Intelligence to build truly intelligent applications for iPhones, iPads, and Macs. This book is a practical, in-depth guide for developers who want to move beyond experimentation and integrate artificial intelligence into real production apps with confidence.
After reading this book, you will know how to work with Apple Intelligence and Siri, integrate on-device models for fast and private intelligence, and connect to powerful external model providers such as OpenAI to bring ChatGPT-level capabilities into your applications.
Artificial intelligence is already transforming how software is built and how users interact with technology. Developers who understand how to apply it effectively gain a decisive advantage. This book teaches you how to use artificial intelligence not as a gimmick, but as a practical tool to enhance functionality, automate complex workflows, and deliver intelligent experiences to your users.
With this book, you will
How artificial neural networks work How Apple Intelligence works How to implement Apple's on device models to take your applications to the next level How to access OpenAI models to incorporate ChatGPT level intelligence into your apps. How to train your own models How to build a neural network from scratch How to train a neural network with the MLX framework and more!
Chapter 1 Requirements Setup
Chapter 2 Introduction to Apple Intelligence Introduction to Artificial Intelligence Artificial Neural Networks Model Architectures Apple Models
Chapter 3 Code Completion Coding Assistant External and Local Models
Chapter 4 Image Playground Genmojis Writing Tools
Chapter 5 Local Large Language Models Foundation Models Framework
Chapter 6 Language Recognizer Tokenizer, Tagger and Embeddings Translation Framework
Chapter 7 Vision Framework Image Classification Barcode Detection Text Recognition Document Recognition Face, Body and Hand Detection Person Segmentation
Chapter 10 Create ML and Core ML Cloudflare Access to OpenAI GPT Models
Chapter 11 How Neural Networks Work Network Architecture Network Training and Optimization Forward Propagation, Backpropagation, and Gradient Descent MLX Framework