Dell Technologies Realize magazine Issue 2 | Page 31

“We are entering an era when the compute infrastructure, amount of data, and the algorithms are all coalescing so we can get to knowledge and wisdom at scale. I think that justifies saying that we’re entering a new era—the data era.” control and optimization. Then there are public clouds, which give you aggregation at an industry level. Edge is the newest layer, and it offers a place where you can push some of your processing and analytics capabilities out to the physical location of the people and devices you interact with in real time. There are two advantages of doing this. bandwidth—it takes a lot of time, energy, and money to move huge quantities of data back and forth across the internet. The edge gives you the ability to run the analytics locally so that you don’t have an urgency to move all the data into the cloud or into a private data center. You might eventually move the data, but you don’t have to move it in a priority manner that costs a lot of money. 29 What are those advantages? First, because the compute and analytics are close to where the users are, the speed-oflight issue that we have when we move data over distance is no longer an issue. You can operate and make decisions in real time. This is incredibly important for things like autonomous vehicles and their ability to react to their environment. But there are several use cases— in factories, healthcare, gaming—where the goal is, first and foremost, to do things quickly and not have the latency of crossing the internet involved in the real-time service. The other advantage to the edge is—as much as we think the internet has infinite There’s a lot of hype around AI, both positive and negative. Where do you see AI having the greatest impact? I’m very bullish on machine intelligence. I believe we can’t progress without sharing the burden of thinking tasks with machines, and AI is a set of tools that allows us to do that. Largely today, we don’t use machines to do thinking tasks. We store data. We process data. But the actual empirical decision almost always happens at a human level. As we look at the world today, there are so many things that, quite frankly, are incredibly inefficient and would improve if machines were to take over more of that responsibility.