Building an Efficient, Future-proof AI Infrastructure Platform with Pure Storage and NVIDIA
Organizations—particularly those with data scientists and others tasked with turning mountains of data into insight and action—are looking for new solutions to help drive improved business outcomes. Research from TechTarget’s Enterprise Strategy Group points out two important issues: Most organizations still take weeks to gain insight from their data, and then take additional weeks to act on those insights.
To shorten both time to insight and time to action, organizations are turning to artificial intelligence (AI) and analytics. While AI is hardly a new, unproven technology for most organizations, benefitting from production-scale AI workloads can be a formidable task. After all, standing up an AI pilot project in the public cloud may let organizations sample AI’s benefits quickly and inexpensively, but those solutions often don’t scale economically. That is particularly true when it comes to AI use cases that are both compute- and storage-intensive, such as in healthcare and life sciences, manufacturing, financial services, and any other industry marked by massive data sets and the need for extremely low latency. These two critical requirements can in some cases rule out public cloud solutions. Fast-growing organizations and those generating and processing more data encounter data models that are more complex and less forgiving to things like performance bottlenecks and latency. This is particularly true in analytics workloads, which benefit substantially from the predictable performance at scale delivered by AI tools.
To offset performance, latency, and cost concerns, organizations need to look for a modern, future-proof AI infrastructure built upon cutting-edge, scale-out architecture specifically designed for demanding AI and analytics workloads. At the same time, they need an infrastructure platform that can start small, if necessary, and scale quickly as workload requirements change with demand. This on-premises solution must deliver the benefits of a public cloud—agility, scalability, security—along with the upsides of on-premises infrastructure in terms of performance, resilience, availability, and cost predictability.