Multitenancy allows multiple users to share hardware resources while processing inference requests simultaneously. This concept enhances efficiency in machine learning systems, as seen in technologies like Nvidia's multi-instance GPUs, which can partition a single GPU into smaller units for different applications. By utilizing distinct sessions and credentials, users can optimize their interaction with shared infrastructures.
