Not every AI workload belongs in the same place. Large language models often fit logically in the cloud because they can serve as general-purpose engines that improve with scale and draw value from broad, up-to-date knowledge.
But the AI workloads moving into production are not just text and language, and we’re increasingly seeing enterprises adopt multimodal models for AI video, audio, and image generation and seeing massive advantages across compute usage, control of IP, and ability to customize the look and feel of creative output.
