 From the Palace of Fine Arts in San Francisco, it's theCUBE, covering AT&T Spark. Now, here's Jeff Frick. Hey, welcome back, everybody. Jeff Frick here with theCUBE. We're at the Palace of Fine Arts in San Francisco at the AT&T Spark event. It's really all about 5G and what 5G is going to enable. You know, this is a really big technology that's very, very close. I think a lot closer than most people understand. And one of the most important components of 5G is it was designed for the ground up, really not so much for people-to-people communications as much as machine-to-machine communications. So we're really excited to have someone who's right in the thick of that and talk about the implications, especially as another topic we hear all the time, which is edge computing. So it's Alicia Abella. She is the VP of Operational Automation and Program Management from AT&T Labs. Alicia, welcome. Thank you for having me, Jeff. Absolutely. So we were talking a little bit before we turned on the cameras about 5G and edge computing and how the two, while not directly tied together, are huge enablers of one another. I wonder if you can unpack a little bit about why is 5G such an important component to kind of the vision of edge computing? Sure, absolutely, yeah, happy to do so. So edge computing is really about bringing processing power closer to the end device, closer to the end user, where a lot of the processing data analytics has to occur. And you want to do that because you want to be able to deliver the services and applications close to the edge, close to where the customer is, so that you can deliver on the speeds that those applications need. 5G plays a role because 5G is promising to be very fast and also very reliable and very secure. So now you've got three things to your advantage, paired up with edge to be able to deliver on a lot of these use cases that we hear a lot about when we talk about 5G, when we talk about edge. Some example use cases are the autonomous vehicle. The autonomous vehicle is a classic example for edge computing as well as 5G. And in fact, it illustrates a kind of continuum because you can have processing that always has to remain in the car. Anything related to safety, that processing has to happen right on that device, the device in this case being the car. But there are other processing capabilities like maybe updates to real-time maps that could happen on the edge. You still have to be near real-time so you want to have that kind of processing and updating happening at the edge. Then maybe you have something where you want to download some new entertainment or move it to your car. Well, that can reside back at the data center further away from where the device or the car is. So you've got this continuum. So really, what the 5G does is really open up the balance of how you can distribute that store computing communications. Because it's always about latency. At the end of the day, it's always about latency. And as much as we want to get as much compute close, oh, and also I guess power, power and latency. Power and edge actually go hand-in-hand as well. It's a big deal, right? So what you're saying is because of 5G and the fact that now you have a much lower latency, faster connectivity port, you can now have some of that stuff maybe not at the edge and enable that edge device to do more other things. Yes. So I often like to say that we are unleashing the device away from having it be tethered to the compute processor that's handling it and now you can go mobile. Because now what you do is if the processing is happening on the edge and not on the device, you save them battery life, but you also make the device more lightweight, easier to manage, easier to move around, the form factor can become smaller. So there's also an advantage to edge computing to the device as well. Right. It's pretty interesting. There was a Nvidia keynote or demo in the keynote of running a video game on the Nvidia chips in a data center and pumping a really high resolution experience back out to the laptop screen. I think is what he was using it for. And it's a really interesting use case in how when you do have these fast reliable networks, you can shift the compute and not just pure compute but the graphics, et cetera, and really start to redistribute that in lots of different ways that were just not even fathomable before you had to buy the big gaming machine, you had to buy the big giant GPU, you had to have that locally and all that horse, all that was running on your local machine. You just showed a demo where it's all running back in their data center. That's right. The Santa Clara really opens up a huge amount of opportunity. That's right. So edge computing is really distributed in nature. I mean, it is all about distribution and distributing that compute power wherever you need it, sprinkling it across the country, right? Of where you need it. So we've gone, there's been this like pendulum shift where we started with the main frame, big rooms, right? Lots of air conditioning. Right, right. And then the pendulum swung over to the PC and that server, client server model where now you had your PC and you did your computing locally. And then it swung back the other way for cloud computing where everything was centralized again and all that compute power was centralized. And now it's the pendulum swinging back again the other way to this distributed model where now you've got your compute capabilities distributed across the country where you need it. So interesting. I mean, networking was kind of the last of the virtualized platform between storage and compute and then finally networking. But if you really start to think of a world with basically infinite power, compute, infinite store and infinite networking, basically asymptotically approaching zero pricing and think of the world from that way, we're not there. We're never going to get to that absolute place but it really opens up a lot of different ways to think about what you could do with that power. So I wonder if there's some other things you can share with us at labs as you guys are kind of looking forward to this 5G world. What are some of the things that you see that just, wow, I would have never even thought that that was even in the realm of possibility that some people are coming up with? Yeah. Any favorites? Yeah, oh, I think one of our favorites is certainly looking at the case of manufacturing. Even though it's a very, you would think of manufacturing as very fixed. The challenge with manufacturing is that a lot of those robotics and capabilities that are in the manufacturing assembly lines, for example, they're all based on wired wires and they can't change and upgrade what they're doing very quickly. So being able to deliver 5G, have things that are wireless and have edge compute capabilities that are very powerful means that they can now shift and move around their assembly lines very quickly. So that's gonna help the economy, help those businesses be able to adapt more quickly to changes in their businesses. And so that's one that is quite exciting to us. And I would say the next one that's also exciting for us would be, we talked about autonomous vehicles already because that one's kind of far out, right? That one, I- I don't think it's as far out as most people think actually. I think we've covered a lot of autonomous vehicle companies and there's just so much research being done now. I don't think it's as far out as people think. Yes. And so I think we are definitely committed to deploying edge compute. And in the process, from a more technical perspective, I think one of the things that we are going to be interested in doing is, and you alluded to it before, is how do you manage all those applications and services and distribute them in a way that is economical, that we can do it at scale, that we can do it on demand. So that too is part of what's exciting about being able to deploy edge. It's pretty easy to the manufacturing example because it came up again in the keynote to really embracing software defined, embracing open source. And the takeaway is moving at the speed of software development, not moving at the speed of hardware development because software moves a lot faster. Yes it does. And can it be more flexible to either to respond to market demands or competitive demands or just to innovate a lot faster. So really taking that approach and obviously a lot of conversation about you guys in the open stack community and the open source projects enables you and your customers to start to adapt to software defined innovation as opposed to just pure hardware defined innovation. That's right. That's right, yeah. All right, well at least I gave you the final word. Any surprises in the hall talk or no? You've got a chat coming up. So why don't you give us a quick preview for what your conversation will be about later today. Yeah, thank you Jeff. So yeah, so later I'll be talking about AT&T's initiatives around encouraging women to pursue STEM fields in particular computer science. It turns out that the number of women getting undergraduate degrees in computer science peaked in the mid 80s. And it's been going downhill since and last year only 17% of women were getting degrees in computer science. So AT&T's mission and what we announced today was a million dollar donation to the Girls Who Code organization. That's one of many different nonprofit organizations that AT&T is involved with to make sure that we continue to encourage young women and also underrepresented minorities and others who want to get in the STEM fields to get involved because technology is changing very quickly. We need people who can understand the technology. We can develop the software we talked about and we need to get that pipeline filled up. And so we're very committed to helping the community and helping to encourage young girls to pursue degrees in STEM. That's great. Girls Who Code's a fantastic organization. We've had them on Anita Borg. I mean, there's so much good work that goes on out there. So that's a great announcement and congratulations. And I'm sure that's meaningful contribution. Yeah, thank you. So Alicia, thanks for stopping by and good luck this afternoon and we'll see you next time. Thank you, Jeff. Appreciate it. She's Alicia, I'm Jeff. You're watching theCUBE. She's Spark in downtown San Francisco. Thanks for watching.