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This is an important part of the mission and we think about network design and architectures. Really not even for the next three years. We are thinking about the next 20 and 50 years. Grid investments take a long time and we want to make these investments with the economy in mind but also by providing the most reliable grid offer.

Bay: You mentioned artificial intelligence and machine learning in your previous answer. What are some ways AT&T is using AI and ML or considering deploying AI?

raj: A great question, but also a very pertinent one. As a company, we have had researchers working on artificial intelligence for many years. With the advent of much more computing power and much finer grained data, in the last five years, I would say, the opportunity has really opened up. He plays a very important role at AT&T. Again, we’ve approached AI in an evolutionary way about how we instill it.

First, we think of AI as engine and fuel is data. It starts with how we want to collect data and learn from it. This is where most of the machine learning capabilities come into play. We’ve invested in a lot of big data management capabilities over the last few years, ensuring that they are well exposed to our AI engines. Our chief data officer in particular has worked hard to create a democratized ecosystem for both data and AI talent. Especially with 5G, as the amount of data increases, there is a step function here in complexity and we get finer grained visibility and much smarter controls to implement decisions. So, we take these steps in this evolutionary way.

Internally, we have many use cases, including how we can use AI for planning, functions, design decisions and also how we can use it in real time to provide our customers and also the network with better efficiency, better customer experiences under various scenarios. , detect security threats, threat analytics, and how to use feedback loops to continually optimize the network. So many use cases throughout its lifecycle.

Bay: I’m talking about focusing on security, which is on the minds of most executives these days. But it’s not just security, AI and automation, it’s also playing a really important role for 5G functionality. What other avenues are coming into play right now with the capabilities of 5G?

raj: Again, this is a very relevant and very active field of work. Let me tell you a little about how we are structured. When we think of 5G, we think of it as day zero, day one, day two. Day zero is planning activities and forecasting. I can see some natural ways AI and machine learning can help you with your predictions. You actually have your first day creating and designing your network. You want to make the highest efficiency. Again, feedback loops and reinforcement learning help you do this, as well as using deep learning technology to analyze maps and geospatial data, determine where you want to embed the fiber optic and where you want to place a small cell versus a small cell. macro cell. So there is a lot of building engineering that we rely heavily on artificial intelligence, deep learning and neural networks.

Then there is a life cycle that we call the second day. There are opportunities in this, such as energy savings, where we try to optimize the energy footprint of our equipment. Again, carbon footprint is both an institutional priority and a societal priority. We see great opportunities for the economy, but also helping the planet.