← Deep Learning & Modern AI Chapter 6
Coming Soon

On-Device Intelligence

Running AI models locally: privacy, speed, and the future of edge computing

What You'll Learn

Discover how AI is moving from the cloud to your devices—enabling faster, more private, and more accessible intelligence. This chapter will cover:

01

Why On-Device?

The advantages of running AI locally on phones, laptops, and edge devices.

  • Privacy: Your data never leaves your device
  • Speed: No network latency, instant responses
  • Offline capability: AI that works anywhere
  • Cost: No API fees for inference
02

Model Compression Techniques

How to fit large models into small devices.

  • Quantization: Reducing precision (32-bit → 8-bit → 4-bit)
  • Pruning: Removing unnecessary weights
  • Distillation: Training smaller models to mimic larger ones
  • Real-world examples: LLaMA, Mistral, Phi models
03

Hardware Acceleration

Specialized chips that make on-device AI possible.

  • Apple Neural Engine
  • Google Tensor & Edge TPU
  • Qualcomm NPU
  • NVIDIA Jetson for edge computing
04

Frameworks & Tools

The ecosystem for deploying models on-device.

  • Mobile: Core ML (iOS), TensorFlow Lite, ONNX Runtime
  • Desktop: llama.cpp, Ollama, LM Studio
  • Web: Transformers.js, WebGPU
  • Optimization pipelines and conversion tools
05

The Trade-offs

Understanding when to use on-device vs cloud AI.

  • Model size vs accuracy
  • Battery consumption
  • Memory constraints
  • Hybrid approaches: small models on-device, large in cloud
06

Real-World Applications

How companies are using on-device AI today.

  • Apple Intelligence: Writing tools, photo search, Siri
  • Google Gemini Nano: Summarization, smart replies
  • Autonomous vehicles: Tesla, Waymo
  • Healthcare devices with AI diagnostics

Why This Matters

Privacy-First AI

On-device intelligence means your personal data, conversations, and documents never need to leave your device. This is the future of privacy-preserving AI.

AI for Everyone

No internet? No problem. No money for APIs? No problem. On-device AI democratizes access to intelligence, making it available to billions more people.

Coming Soon!

This chapter is being developed to give you a comprehensive understanding of on-device AI—from the hardware to the software, and everything in between.

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