What strategies can be employed to reduce model serving latency?

To reduce model serving latency, several strategies can be implemented: 1) **Model Optimization**: Techniques like model pruning, quantization, and knowledge distillation can be used to make models smaller and faster. 2) **Resource Allocation**: Ensure adequate hardware resources (CPUs/GPUs) to handle concurrent requests efficiently. 3) **Caching**: Store frequently requested predictions to avoid recomputation. 4) **Asynchronous Processing**: Implement asynchronous request handling to allow incoming requests to be processed without blocking. 5) **Load Balancing**: Distribute requests evenly across multiple instances of the model to enhance throughput.