Distributed Inference

A computing approach in which processing tasks are distributed across multiple interconnected computers that work together as a single system.

A training approach that distributes model training across multiple machines or accelerators to reduce training time and enable larger models or datasets.

A Graphics Processing Unit (GPU) is a specialized parallel processor designed to perform large-scale mathematical computations efficiently, making it the primary hardware for training and running AI models.

A specialized hardware device designed to speed up compute-intensive workloads such as AI training and inference by efficiently executing parallel operations.

The process of making an AI model available for inference by deploying it behind an interface that accepts requests and returns predictions or generated outputs.