**1. Algorithm Choice**  
- **Selected:** YOLOv8n (lightweight version)  
- **Why:**  
  - Fast detection (0.5s/image on CPU)  
  - Works well with small datasets (40 images)  
  - Accurate for motherboard components  

**2. Hardware Impact**  
- **Training:**  
  - GPU recommended (4x faster training)  
  - CPU works but slower  
- **Deployment:**  
  - CPU sufficient for basic use  
  - GPU better for high volume  

**3. Video Handling**  
- **Approach:** Process each frame individually  
- **Changes Needed:**  
  - Add frame-by-frame processing  
  - Include tracking to follow memory modules  
  - Optimize for speed (lower resolution helps)  

**Key Facts:**  
- Same model works for images/video  
- CPU processing is practical  
- No architecture changes needed between image/video modes.