What is asynchronous inference in distributed ML systems?

Asynchronous inference decouples request submission from response processing to improve scalability.

In async inference systems, requests are queued and processed independently, allowing higher throughput and better resource utilization. Clients receive responses via callbacks, polling, or message queues. This design reduces blocking but introduces complexity in state management and eventual consistency.