Given a trained machine learning model with 85% accuracy that currently requires 2GB of RAM and takes 3 seconds for inference on a standard CPU, propose a detailed optimization strategy. Your plan should include: 1) Techniques to reduce model size without significant accuracy loss, 2) Methods to decrease inference latency, 3) Approaches to optimize memory usage, 4) Quantization strategies appropriate for production deployment, 5) Evaluation metrics to balance between accuracy and efficiency, 6) Specific hardware considerations for edge deployment, 7) Implementation timeline and potential risks.