Data is the new oil for modern tech, transforming countless industries and providing invaluable insight as organizations leverage artificial intelligence (AI) and machine learning. But this data-rich futurewhere information once bound for cold storage becomes an actionable, strategic assetcomes with challenges. More data must be stored safely at reasonable cost over longer time spans, even as enterprises forge a data foundation layer to transform every type of data they own from a liability to be stored and defended into an asset to be leveraged.

Enterprises need the right storage infrastructure to manage this transition and unlock the potential value in their data. In this blog post, we outline how storage has evolved to combat the challenges of AI, ML, and big data and how the new generation of data storage offers a better solution than traditional stacks.

To make a successful data storage layer for AI and ML operations using large amounts of data, your infrastructure must provide:

It is tough to find all of these characteristics in a traditional storage system. In fact, they look incompatible at first glance. Often, we must stack several different technologies to accomplish this:

Rather than create a complicated stack, a new answer has emerged over the last few years: Next-Generation Object Storage. This solution uses all-flash and hybrid (flash and spinning media) object stores to combine the characteristics of traditional object stores with those usually found in block and file storage. The result:

The challenges posed by AI and ML to data infrastructure have been resolved to some extent by the new generation of object stores.

Object storage now offers much more than it did in the past. It can offload several tasks from the rest of the infrastructure. It is faster and can form the data foundation layer for todays capacity needs and tomorrows next-generation and cloud-native applications. Finally, next-generation object stores make it easier to implement new initiatives based on ML and AI workloads. It allows for a quick start with the potential to grow and evolve the infrastructure as required by the business.

Read more from the original source:

The Evolution of ML Infrastructure Gigaom - Gigaom