John provides a great synthesis of how the AI movement is evolving and where the long-term business building and wealth creation opportunities really are. Also, a great discussion on the jobs of the future.
Sramana Mitra: Let’s start by introducing our audience to yourself as well as to Dell EMC and its work in the realm of artificial intelligence.
John Roese: I’m the Global Chief Technology Officer for Dell EMC. We’re the largest infrastructure technology provider in the world now. It’s a collection of companies from the coming together of Dell and EMC about two years ago. The purpose of the company, just so everybody remembers, is to build the essential infrastructure company of the future. Here, infrastructure broadly ranges from the physical component of servers, storage, and networking to the virtualization of layers and acceleration of processing.
It’s a very big mission but very exciting especially in these days where IT systems and information is more and more important and critical to business success and digital transformation.
Your second half of the question is around artificial intelligence and machine learning. It’s not a new concept. I was doing neural networks work in undergraduate 30 years ago. But in the last year, we’ve seen tremendous advancements in semiconductors, programming frameworks, algorithmic enhancements, availability of data, and the ability to process it.
All of these things have given us a whole new approach to bringing matching intelligence into our systems. This is not just a new class of application but a transformational change of bringing machine intelligence into the IT stack. So, it is as important to transform the way infrastructure works as it is to build the applications that will sit on top of that infrastructure.
For us, it is a tier one technology inflection – one that will pervade the entire stack. We’ll do everything from transforming the way that clouds are built and technology is developed to influencing the path of semiconductors and memory technologies to make these kinds of systems run faster and better.
Again, our vision is to make sure that we have infrastructure that can enable these technologies to be used and infrastructure that can exploit AI and ML to allow those infrastructures to scale beyond human capacity and human potential, which is incredibly important given the demands that are coming at us from a data and industry perspective.
Sramana Mitra: Give us examples of where you are applying AI to your strategy.
John Roese: Let me start with a high level point of view that might be a little bit different than maybe how other people talk about AI. Because we’re in the early days of machine intelligence within the IT stack, there is some common thinking that artificial intelligence and machine intelligence will enter our lives in one way. I think we’re all realizing that this is going to be an incredibly multi-dimensional journey.
One of the things we’ve been thinking about for the last year to two years is what are those major areas where the interaction between humans and AI world are likely to manifest and how many of them are distinctly different that require different strategies. If you try to build a technology to solve the general space of machine intelligence, that’s probably too broad. On the other hand, if you try to build a specific product without understanding that it might be in a domain, you might be too narrow. There’s a layer in the middle that we think has been helpful to think through the proliferation of machine intelligence. There are three very distinct ways in which the addition of machine intelligence to the IT stack is materializing. They actually have very different requirements, outcomes, and impacts.
At the highest level, there’s clearly a tremendous amount of work around using artificial intelligence and machine intelligence to transform the user experience. Whether that’s a voice assistant like Alexa or something much lower level like the backend of a contact center, what’s interesting about them is, there aren’t that many of them. They are fairly high level. Their purpose in life is to make human beings’ lives easier.
The AI and machine learning is entirely focused on entering your existence as a human being. Success depends on the application of intelligence to make the human task simpler or make it go away. From our perspective, these are incredibly resource-intensive applications. They require huge amounts of data and processing. From our perspective, we build the infrastructures that can scale to keep up with the demand of these types of environments.
In many cases, we use these techniques to make managing a modern data center or an IT environment a bit simpler for the human being. I just gave a speech talking about this. Because it’s AI applied to the human experience, we tend to obsess on it. We think that it’s the only thing that AI and ML are actually going to do.