Enterprise storage providers are embracing artificial intelligence and machine learning to create AI-enabled intelligent infrastructure. The focus and maturity of each vendorâ€™s offering varies. Some are focused on individual array health, relying more on fault data than predictive analytics. Others focus on application-level performance and availability. Both approaches offer significant benefits to customers.
Category: Machine Learning
Antonio Neri, CEO of HPE, declared at its Discover event last week that HPE is transforming into a consumption-driven company that will deliver “Everything as a Service” within three years. In addition, Neri put forward the larger concept of “cloudless” computing. Are these announcements a tactical response to the recent wave of public cloud adoption by enterprises, or are they something more strategic?
In 2019 the level of interest that companies expressed in using artificial Intelligence (AI) and machine learning (ML) exploded. Their interest is justifiable. These technologies gather the almost endless streams of data coming out of the scads of devices that companies deploy everywhere, analyze it, and then turn it into useful information. But time is the secret ingredient that companies must look for as they look to select an effective AI or ML product.