The growing implementation of AI is driving demand for memory and storage to support the processing of data and data retention, both for the training sets and the results of AI training used in inference engines. DRAM, NAND flash, HDD and even magnetic tape vendors will benefit from this growing demand for storage and memory. Likely also emerging non-volatile memories will also benefit, especially for end point AI inference applications.
Western Digital recently announced new products to support AI workloads and provided the interesting visual below showing the data workflow for AI applications. WDC called this a six-stage AI Data Cycle framework that defines the optimal storage infrastructures to maximize AI investments and increase the efficiency and low the cost of ownership for AI workflows.
In addition to these SSDs, hard disk drives can provide more cost-effective secondary storage. Finally, data no longer needed for training and some results from the training might be stored in an archival media for longer term retention. This might be particularly appropriate for data that might be used for later training and analysis to find new insights and relationships.