AI and Machine Learning: Key Challenges in Colocation Data Centers
In my last blog , I talked about some of the hype going on in the industry over artificial intelligence (AI) and machine learning (ML). The blog gets into what the current AI techniques are capable of on a fundamental level today, and I also offered a definition for these often-misunderstood terms in the context of data centers. In this post, I’d like to develop the discussion by describing 3 key challenges that the industry needs to address and resolve if AI tools are to be broadly adopted to achieve their full value for colocation providers. Three Things to Overcome Before Broad AI Adoption The first challenge is instrumenting the data center. The old adage “garbage in, garbage out” applies here more than ever. Despite their “black box” nature, machine learning algorithms and deep neural networks are not magic. Like any analytics engine, they need large volumes of good data to act on. Those with well implemented DCIM suites are probably in good shape. But part of this challenge ...