Building the telecommunications network of tomorrow today

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So that’s an important part of the mission and we’re thinking about network design and architectures. It’s really not even for the next three years. We are thinking about the next 20 and 50 years. Network investments take a lot of time and we want to make those investments with an eye on the economy, but also with a view to the most reliable network offer.

Laurel: You mentioned artificial intelligence and machine learning in an earlier answer. What are some ways AT&T is using AI and ML, or is considering using artificial intelligence?

Raj: Great question and a very topical one too. As a company, researchers have been working on AI for years. With the advent of much more computing power and much more finer data, the opportunity has really sprung up with the last, I’d say, five years. It plays a very important role at AT&T. Again, we’ve approached AI in an evolutionary way about how we imbue 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 the machine learning capabilities come in. We have invested in many big data management capabilities over the years to ensure they are properly exposed to our AI engines. Our chief data officer, in particular, has worked very hard to build a democratized ecosystem for both the data and AI capabilities. There’s a step function here in complexity as the amount of data increases, especially with 5G, and we get kind of finer visibility, and we have much more intelligent controls to then apply decisions to. So we take those steps in that evolutionary way.

Internally, we have many use cases, including how to use AI for scheduling, functions, AI for design decisions, as well as in real-time to help our customers and the network under different scenarios to provide better efficiency and customer experiences, detecting security threats, threat analysis and the use of feedback loops to continuously optimize the network. So many use cases throughout the lifecycle.

Laurel: I’m talking about that focus on security, which is highly valued by most executives these days. But not only security, AI and automation also play a very important role for 5G functionality. In what other ways does that come into play with the capabilities of 5G now?

Raj: Again, this is very topical and a very active area of ​​work. Let me give you some context on how we are structured. When we think of 5G, we think of it as day zero, day one, day two. Day zero is the planning of activities and forecasts. I see some natural ways AI and machine learning can help you with your forecasting. There is your first day, namely building and designing your network. You want to do the greatest efficiency. Again, the feedback loops and amplification of learning help you with that, as does the use of deep learning technology to analyze maps and geospatial data, to determine where to have buried fiber and where to place a small cell versus a macro. cell. So there is a lot of construction technology in which we are highly dependent on AI, deep learning and neural networks.

Then there is a life cycle, which we call day two. Therein lie opportunities, things like energy savings where we try to optimize the energy footprint of our equipment. Again, both a business priority, but also a social priority on the carbon footprint. We see great opportunities for the economy but also for helping the planet.