Upcoming commission: storage for machine learning

Data storage is an often-overlooked part of machine learning and other AI deployments.

This article will appear in Computer Weekly. It will cover:

  • Definitions of machine learning/deep learning
  • Its storage requirements including
    • Sizing, capacity, performance (to match compute)
    • Scale
    • Media (SSD vs HDD, hybrids of the two)
    • Parallelism
    • Throughput vs IOPS
    • Locations – including use of the cloud

For this article we are open to comments from vendors, as well as analysts, consultants and other experts. Examples of ML use cases and how systems were designed to run it are most welcome.

Initial pitches and leads by Wednesday May 29th by email please.