High Performance Storage for AI and Analytics

The importance of data management, access, protection, and compliance has continued to grow with the emergence of generative AI. The sheer volumes of data required to create and fine-tune effective LLM models represent a challenge for many organizations. A well-known rule of data science is that data acquisition and preparation require eighty percent of the effort, while the remaining twenty percent involves actual data processing; a similar claim can be made for generative AI. In both cases, sub-optimal big data storage capabilities can impede both analytic and generative AI progress. Our expert panel will discuss successful high-performance data strategies from the vendor, user, and market analyst perspectives.