CS5720 - Week 8
Slide 159 of 160

Edge AI and Mobile Deployment

What is Edge AI?

Edge AI brings artificial intelligence to edge devices - smartphones, IoT sensors, embedded systems - where computation happens locally rather than in the cloud.
Key Benefits:

Low Latency - Real-time responses
Privacy - Data stays on device
Offline Capability - Works without internet
Reduced Bandwidth - No cloud transfer
Cost Efficiency - No cloud compute costs

Deployment Challenges

  • 💾
    Resource Constraints
    Limited memory, storage, and compute power
  • 🔋
    Power Efficiency
    Battery life and thermal management
  • 🔧
    Hardware Diversity
    Different chips, accelerators, and architectures

Model Optimization Techniques

🔢
Quantization
Reduce precision from 32-bit to 8-bit or less
✂️
Pruning
Remove unnecessary weights and connections
🧪
Knowledge Distillation
Train smaller student from larger teacher
🏗️
Efficient Architectures
MobileNet, EfficientNet, SqueezeNet

Deployment Platforms

TensorFlow Lite
Android/iOS/Embedded
Core ML
Apple Ecosystem
ONNX Runtime
Cross-Platform
OpenVINO
Intel Hardware
TensorRT
NVIDIA GPUs
Prepared by Dr. Gorkem Kar