Sponsored Feature There is a great need for efficient new data storage solutions given the growing trend of businesses now using AI-enabled applications.
Achieve AI readiness with hybrid cloud
Where megabyte and terabyte storage workloads were once common for document-only and single workloads, petabyte (1K terabyte) and even some exabyte (1K petabyte) jobs are now in production.
Factors that have fueled a boom in AI applications include large language models (LLMs) used in everything from facial recognition software to recommendation engines for streaming services, all to improve user experiences and business processes. In industries, there is a growing need for automation, data analysis and intelligent decision making. AI can automate repetitive tasks, analyze large amounts of data to uncover patterns, and make data-driven predictions or recommendations. This leads to potentially increased efficiency, productivity and innovation in various areas.
All this means large amounts of data coming from social networks, GPS transmitters, security cameras, points of sale, remote weather sites and many other sources. This trend requires high-performance storage solutions to handle the large volumes of unstructured data involved in AI training and inference that can be spread across both on-premises and cloud environments.
