Accelerate Training
and Inference Workloads
Whether it comes to autonomous driving, speeding up reporting of cancer data, or accelerating data science discovery, enterprises are adopting AI, ML, and DL technologies to process, analyze and act on rapid influxes of new large data sets.
These complex and rapidly expanding AI use cases require ingestion of vast amounts of data to train the algorithms, which drives the demand for storage infrastructure that is powerful, flexible and highly scalable.