Data Storage for AI

Capture the value of artificial intelligence with high-capacity, high-performance data storage across the six stages of the AI Data Cycle.

Introducing the AI Data Cycle Framework

AI models operate in a self-perpetuating, continuous loop of data consumption and generation. As AI grows and evolves, it creates even more data across six distinct stages — an AI Data Cycle with specific storage requirements at every stage.

1

Raw data archives and content storage

2

Data preparation and ingestion

3

AI model training

4

Interface and prompting

5

AI inference engine

6

New content generation

Download the AI Data Cycle Brief