What are the main challenges of real-time inference in AI?

What are the main challenges of real-time inference in AI?

The main challenges include latency, data quality, model complexity, and resource constraints.

Can you explain how latency affects real-time inference?

Latency refers to the delay before a transfer of data begins following an instruction. In real-time inference, high latency can lead to outdated or irrelevant results.

What can be done to reduce latency in AI models?

To reduce latency, techniques like model optimization, hardware acceleration, and edge computing can be employed.

Are there specific industries that face more challenges with real-time inference?

Yes, industries like healthcare, finance, and autonomous vehicles often face significant challenges due to the need for immediate and accurate decisions.