That’s an important part of the mission and we’re thinking about architectures and network design. It really isn’t even for the next three years. We are thinking about the next 20 and 50 years. Investments in networks take a long time, and we want to make those investments with economics in mind, but also largely ensuring the most reliable network offering.
Laurel: You mentioned artificial intelligence and machine learning in a previous answer. What are some of the ways AT&T is using AI and ML, or thinking about implementing AI?
rah: Great question and also very timely. As a company, we have had researchers working on AI for many years. With the advent of much more computing power and much finer-grained data, the opportunity has really opened up in the last, I’d say, five years. It plays a very important role in AT&T. Again, we’ve approached AI in an evolutionary way in how we infuse it.
First, we think of AI as the engine and the fuel is the data. It starts with how we want to collect data and learn from it. That’s where a lot of machine learning capabilities come into play. We’ve been investing in a lot of big data management capabilities over the past few years, making sure they’re well exposed to our AI engines. Our chief data officer in particular has worked very hard to establish a democratized ecosystem for both data and AI capabilities. There’s a stepped function here in complexity as the amount of data increases, particularly with 5G, and we get finer-grained visibility, and we have much smarter controls to then apply decisions. So, we’re taking those steps in that evolutionary way.
We have a lot of use cases internally, including how we can use AI for planning, features, AI for design decisions, but also in real time to help our customers, as well as the network, in various scenarios to deliver greater efficiency and better experiences for customers. , detecting security threats, threat analysis, and how to use feedback loops to constantly optimize your network. So many use cases throughout the life cycle.
Laurel: I mean that focus on security, which is top of mind for most executives these days. But not only security, AI and automation also play a really important role for 5G functionality. What other ways is 5G capabilities coming into play right now?
rah: Again, this is very timely and a very active area of work. Let me give you a bit of context on how we are structured. When thinking about 5G, we think of it as day zero, day one, day two. Day zero is planning and forecasting activities. I can see some natural ways that AI and machine learning can help you through your forecast. There’s your first day, which is actually building and designing your network. You want to make the most efficiency. Again, feedback loops and reinforcement learning help you do that, as well as using deep learning technology to analyze maps and geospatial data, to determine where you want to have fiber optics buried, and where you want to put a small cell in. place of one macrocell. So there’s a lot of construction engineering that we rely heavily on AI, deep learning, and neural networks.
Then there is a life cycle, which we call day two. In that, there are opportunities, things like energy savings where we’re trying to optimize the energy footprint of our team. Again, both a corporate priority and a social priority in the carbon footprint. We see great opportunities for the economy but also to help the planet.