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Edge AI Performance with Android Kotlin
Optimizing hardware acceleration via NPU, GPU, and DSP. Advanced quantization and model pruning
This book is 100% completeLast updated on 2026年04月27日
Master high-performance Edge AI by orchestrating NPUs, GPUs, and DSPs for real-time mobile intelligence. Run complex models at 60 FPS using advanced quantization, weight pruning, and NDK optimization. Leverage Kotlin 2.x and zero-copy pipelines to build battery-efficient and thermally stable AI features. The definitive engineering guide for shipping the "last mile" of AI deployment on modern...
This book is 100% completeLast updated on 2026年04月27日
Master high-performance Edge AI by orchestrating NPUs, GPUs, and DSPs for real-time mobile intelligence. Run complex models at 60 FPS using advanced quantization, weight pruning, and NDK optimization. Leverage Kotlin 2.x and zero-copy pipelines to build battery-efficient and thermally stable AI features. The definitive engineering guide for shipping the "last mile" of AI deployment on modern...
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About the Book
Master the Art of High-Performance Edge AI on Android
Push the boundaries of mobile intelligence with Volume 2: Edge AI Performance with Android Kotlin. This masterclass volume moves beyond basic model execution to explore the deep hardware orchestration required to run complex neural networks at 60 FPS on mobile silicon.
In this book, Edgar Milvus provides an engineering-first approach to optimizing AI workloads. You will learn to navigate the "Memory Wall", handle Thermal Throttling, and master the heterogeneous compute landscape of modern Android SoCs.
What's Inside:
- Hardware Acceleration: Deep dives into targeting NPUs, GPUs, and DSPs via NNAPI and AICore.
- Advanced Quantization: Techniques for INT8 and FP16 Post-Training Quantization and Quantization-Aware Training (QAT).
- Model Pruning & Sparsity: Reducing model complexity while maintaining accuracy for high-speed inference.
- NDK & C++ Optimization: Writing custom operations in C++ to achieve zero-copy image processing performance.
- Real-time Vision & Audio: Architecting pipelines for 60 FPS video segmentation and low-power audio sentinels.
- Modern Kotlin Integration: Using Kotlin 2.x Context Receivers, Flow, and Coroutines for high-concurrency AI tasks.
Build Production-Ready AI Features
From Knowledge Distillation to Thermal-Aware Schedulers, this volume provides the practical exercises and professional-grade code snippets needed to ship AI-powered apps that are fast, battery-efficient, and thermally stable.
Whether you are a Senior Android Developer or an ML Engineer, this book is your definitive guide to the "Last Mile" of mobile AI deployment.
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