What is the difference between latency and throughput in machine learning?

What is the difference between latency and throughput in machine learning?

Latency refers to the time it takes to process a single request, while throughput is the number of requests processed in a given time.

Can you give me an example of how latency affects model performance?

Sure! In real-time applications like self-driving cars, high latency can lead to delayed responses, affecting safety.

How can I improve throughput in my ML model?

You can improve throughput by optimizing your model architecture, using batch processing, or leveraging parallel computing.

Is there a trade-off between latency and throughput?

Yes, often increasing throughput can lead to higher latency, so it's important to find a balance based on your application needs.