 From around the globe, it's theCUBE with digital coverage of AWS re-invent Executive Summit 2020. Sponsored by Accenture and AWS. And welcome back to theCUBE's coverage of AWS re-invent 2020. This is a special programming for the Accenture Executive Summit where all the thought leaders are going to extract a signal from the notes, share with you their perspective of this year's re-invent conference as it respects the customer's digital transformation. Brian Bohan is the director and head of Accenture, AWS Business Group at Amazon Web Services. Brian, great to see you. And Chris Wegman is the Accenture Amazon Business Group technology lead at Accenture. Guys, this is about technology vision, this conversation. Chris, I want to start with you because Andy Jackson's keynote, you heard about the strategy of digital transformation, how you got to lean into it, you got to have the guts to go for it, and you got to decompose, he went everywhere. So what did you hear? What was striking about the keynote because he covered a lot of topics. Yeah, it was epic as always from Andy. A lot of topics, a lot to cover in the three hours. There was a couple of things that stood out for me. First of all, hybrid. The concept, the new concept of hybrid and how Andy talked about it, bringing the compute and the power to all parts of an enterprise, whether it be at the edge or in the big public cloud, whether it be in an outpost or wherever it might be, with containerization now, being able to do Amazon containerization in my data center, and that's awesome. I think that's going to make a big difference, all that being underneath the Amazon console and billing and things like that, which is great. I'll also say the chips, right? I know compute is always something that we always kind of take for granted, but I think again this year, Amazon and Andy really focused on what they're doing with the chips and compute. And the compute is still at the heart of everything in cloud and that continued advancement is making an impact and will continue to make a big impact. Yeah, I would agree. I think one of the things that really, I mean, the container thing was, I think really kind of a nuanced point. You got Deepak Singh on the opening day with Andy Jassy and he runs a container group over there, a small little team. He's on the front stage. That really is the key to the hybrid. I think this showcases this new layer and taking advantage of the Graviton, two chips that I thought was huge. Brian, this is really a key part of the platform change. Not change, but the continuation of AWS. Higher level service, building blocks that provide more capabilities, heavy lifting, as they say, but the new services that are coming on top really speaks to hybrid and speaks to the edge. It does. Yeah, and you know, I think Andy talked about and we talked about it. We really want to provide choice to our customers first and foremost. And you can see that in the array of services we have. We can see it in the hybrid options that Chris talked about, being able to run your containers through ECS or EKS anywhere, I just give the customer's choice. And one of the things that I'm excited about as you talk about going up the stack and on the edge are things will certainly outpost, right? So now outpost was launched last year, but then with the new form factors and then you look at services like panorama, right? Being able to take computer vision and embed machine learning and computer vision and do that as a managed capability at the edge for customers. And so we see this across a number of industries. And so what we're really thinking about is customers no longer have to make trade-offs and have to think about those choices that they can really deploy natively in the cloud and then they can take those capabilities, train those models and then deploy them where they need to whether that's on-premises or at the edge, whether it be in a factory or retail environment. When we start, I think we're really well positioned when hopefully next year we start seeing the travel industry rebound and the need more than ever really to kind of rethink about how we kind of monitor and make those environments safe. Having this kind of capability at the edge is really going to help our customers as we come out of this year and hopefully rebound next year. You know, Chris, I want to go back to you for a second. It's hard to pick your favorite innovation from the keynote because, you know, just reminded me there, Brian, just reminded me of some of the things I forgot happened. It was like a buffet of innovation. Some keynotes have one or two, it was like 20. You got the industrial piece that was huge. Computer vision machine learning, that's just a game changer. The Kinect thing came out of nowhere in my opinion. I mean, it's a call center technology. It says boring as hell. What are you going to do with that? Turns out it's a game changer. It's not about the calls with the contact. That's intermediating in the stack as well. So again, a feature that looks old is actually new and relevant. What was your favorite innovation announcement? It's hard to say. I will say my personal favorite was the Mac OS. I think that is a phenomenal just addition, right? And the fact that AWS has worked with Apple to integrate the Nitro chip into the iMac and offer that out, a lot of people are doing development for iOS and that stuff. And that's just made a huge benefit for the development teams. But I will say, I'll come back to Kinect. You mentioned it, but you're right. It's a boring area, but it's an area that we have seen huge success with since Kinect was launched. And the additional features that Amazon continues to bring, obviously with the pandemic and all that customer engagement through the phone, through OmniChannel has just been critical for companies, right? And to be able to have those agents at home working from home versus being in the office, it was a huge advantage for several customers that are using Kinect. We did some great stuff with some different customers. But the continued technology, like you said, the call translation and during a call to be able to pop up those keywords and have a supervisor listen is awesome. And some of that was already being done, but we are stitching multiple services together. Now that's right out of the box. And that simplification is only going to make that go faster and make us to be able to innovate faster for that piece of the business. It's interesting, not to get all nerdy and business school like, but you got systems of record, systems of engagement. If you look at the call center and the Kinect thing, what got my attention was not only the model of disintermediating that part of the engagement on the stack, but what actually cloud does to something that's a feature or something that could be an element, like say call center, the old days of calling the 800 number and getting some support. You got info chip, you have machine learning, you actually have stuff in the stack that actually makes that different now. So the thing that impressed me was Andy was saying, you could have machine learning detect pauses, voice inflections. So now you have technology making that more relevant and better and different. So a lot going on. This is just one example of many things that are happening from a disruption innovation standpoint. What do you guys think about that? Is that, am I getting it right? Can you share other examples? I think you are, right? And I think what's implied there and what you're saying and even in the Mac OS example is the ability, we're talking about features, right? Which by themselves you're saying, well, wow, what's so unique about that? But because it's on AWS and now because whether you're a developer working on, you know, with Mac OS and you have access to the 175 plus services that you can then weave into your new applications. Talk about the connect scenario. Now we're embedding that kind of inference and machine learning to do what you say. But then your data lake is also most likely running in AWS, right? And then the other channels whether they be mobile channels or web channels or in store physical channels, that data can be captured and that same machine learning can be applied there to get that full picture across the spectrum, right? So that's the power bringing it together on AWS, the access to all those different capabilities and services and then also where the data is and pulling all that together for that end to end view. Can you guys give some examples of work you've done together? I know this stuff we've reported on in the last session we talked about some of the connect stuff but that kind of encapsulates where this is all going with respect to the tech. Yeah, I think one of them, you know it was called out in Doug's partner summit is our SAP Data Lake accelerator, right? Almost every enterprise has SAP, right? And SAP, getting data out of SAP has always been a challenge, right? Whether it be through data warehouses and SAP BW, what we've focused on is getting that data when you're on have SAP on AWS getting that data into the data lake, right? Getting it into a model that you can pull the value out and the customers can pull the value out and use those AI models. So that was one thing we worked on in the last 12 months super excited about seeing great success with customers. You know, a lot of customers had ideas they want to do this, they had different models what we've done is made it very simplified framework that allows customers to do it very quickly get the data out there and start getting value out of it and iterating on that data. We saw customers are spending way too much time trying to stitch it all together and trying to get it to work technically and we've now cut all that out and they can immediately start getting down to the data and taking advantage of those different services that are out there by AWS. Brian, you want to weigh in as things you see as relevant builds that you guys done together that kind of tease out the future and connect the dots to what's coming? I'm going to use a customer example. We worked with, it just came out with Unilever around their blue air connected smart air purifier. I think it's interesting about that. I think it touches on some of the themes we're talking about as well as some of the themes we talked about in the last session which is we started that program before the pandemic Unilever recognized that they needed to differentiate their product in the marketplace, move to more of a services oriented business which we're seeing as a trend. We enabled this capability so now it's a smart air purifier that can be remote managed. And now in the pandemic hit they are in a really good position obviously with a very relevant product and capability to be used. And so that data then as we're talking about is going to reside on the cloud. And so the learning that can now happen about usage and about filter changes, et cetera can find its way back into future iterations of that product. And I think that's keeping with what Chris is talking about where we might be systems of record like an SAP. How do we bring those in and then start learning from that data so that we can get better on our future iterations? Hey Chris, on the last segment we did on the business mission session, Andy Tay from your team talked about partnerships within Accenture and working with other folks. I want to take that now on the technical side because one of the things that we heard from Doug's keynote and during the partner day was integrations and data were two big themes. When you're in the cloud technically the integrations are different. You're going to get unique things in the public cloud that you just not going to get on premise access to other cloud native technologies and companies. How do you see the partnering of Accenture with people within your ecosystem and how the data and the integration play together? What's your vision? Yeah, I think there's two parts of it. One, there's from a commercial standpoint, right? So marketplace, you heard Dave talk about that in the partner summit, right? That marketplace is now bringing together this ecosystem in a very easy way to consume by the customers and by the users and bringing multiple partners together. And we're working with our ecosystem to put more products out in the marketplace that are integrated together already. I think one from a technical perspective though, if you look at Salesforce, I talked a little earlier about Connect. Another good example technically underneath the covers how we've integrated Connect and Salesforce, some of it being pre-built by AWS and Salesforce, other things that we've added on top of it I think are good examples. And I think as these ecosystems, these ISVs put their products out there and start exposing more and more APIs on the Amazon platform, opening it up, having those pre-built network connections there between the different VPCs of the different areas within the customer's network. And having that all opened up and connected and having all that networking done underneath the covers, it's one thing to call the APIs, it's one thing to have access to those. And that's been a big focus of a lot of ISVs and customers to build those APIs and expose them, but having that network infrastructure underneath and being able to stay within the cloud, within AWS to make those connections to pass that data, we always talk about scale, right? It's one thing if I just need to pass like a simple user ID back and forth, right? That's fine. We're not talking massive data sets, whether it be seismic data or whatever it be, passing those large data sets between customers across the Amazon network is going to open up the world. Yeah, I see huge possibilities there and love to keep on the story. I think it's going to be important and something to keep track of. I'm sure you guys will be on top of it. You know, one of the things I want to dig into with you guys now is Andy had kind of this philosophical thing on his keynote about societal change and how tough the pandemic is, everything's on full display. And this kind of brings out kind of like where we are and the truth. If you look at the truth, it's a virtual event. I mean, it's a website and you got some sessions out. They would do in remote best weekend and you got software and you got technology and you know, the concept of a mechanism, it's software, it does something, it does a purpose. Essentially, you guys have a concept called living systems where growth strategies powered by technology. How do you take the concept of a living organism or a system and replace the mechanism, staleness of computing and software? And this is kind of an interesting because we're on the cusp of a major inflection point post COVID, forget the digital transformation being so, that's, yes, that's happening. There's other things going on in society. What do you guys think about this living systems concept? Yeah, so I, you know, I'll start, but you know, I think the living system concept, you know, it started out very much thinking about how do you rapidly change a system, right? And because of cloud, because of DevOps, because of, you know, all these software technologies and processes that we've created, you know, that's where it started, it making it much easier, making it much faster, being able to change rapidly. But you're right, I think as you now bring in more technologies, the AI technology, self healing technologies, again, you heard Andy and his keynote talk about, you know, the systems and services they're building to detect problems and give resolve those problems, right? Obviously automation is a big part of that. You know, living systems, you know, being able to bring that all together and to be able to react in real time to either what a customer, you know, asks, you know, either through the AI models that have been generated and turning those AI models around much faster and being able to get all the information that came in in the last 20 minutes, right? You know, society is moving fast and changing fast and, you know, even in one part of the world, if something, you know, in 10 minutes can change and being able to have systems that react to that, learn from that and be able to, you know, pass that on to the next country, especially in this world of COVID and, you know, things changing very quickly and diagnosis and medical response, all that so quickly, to be able to react to that and have systems pass that information, learn from that information is going to be critical. That's awesome. Brian, one of the things that comes up every year is, oh, the cloud's scalable. This year, I think, you know, we've talked on theCUBE before, years ago, certainly with Accenture and Amazon, I think it was like three or four years ago, you know, the cloud's horizontally scalable but vertically specialized at the application layer. But if you look at the data lake stuff that you guys have been doing, where you have machine learning, the data's horizontally scalable and then you got the specialization in the app, changes the whole vertical thing. Like you don't need to have a whole vertical solution or do you. So how has this year's cloud news impacted vertical industries? Because it used to be, oh, oil and gas, financial services. They got a team for that, we got a stack for that. Not anymore, is it going away? What's changing? Well, you know, it's a really good question. And I don't think, I think what we're seeing and as I said on a call this morning, talking about banking and capital markets and I do think the challenges are still pretty sector specific. But what we do see is the kind of commonality. When we start looking at the, we talked about the industry solutions that we're building as a partnership, most of them follow the pattern of ingesting data, analyzing that data, and then being able to provide insights and then actions, right? So if you think about creating that, yeah, that kind of common chassis of that ingest of the data lake and then the machine learning. And you talk about the announces around SageMaker and being able to manage these models. What changes then really are the very specific industries algorithms that you're writing, right? Within that framework. And so we're doing a lot and connect is a good example of this too. Where you look at it, yeah, customer service is a horizontal capability that we're building out. But then when you snap it into insurance or retail banking or utilities, there are nuances then that we then extend and build so that we meet the unique needs of those industries. And that's usually around those models. Yeah, and I think this year was the first reinvent that I saw real products coming out that actually solved that problem. I mean, it was there last year SageMaker was kind of moving up the stack, but now you have apps embedding machine learning directly in and users don't even know it's in there. I mean, Chris, this is kind of where it's going, right? I mean, yeah. You saw those announcements, right? How many, how many announcements where machine learning is just embedded in? I mean, so, you know, code guru, DevOps guru, the panorama we talked about, it's just there. Yeah, I mean, having that knowledge about the linguistics and the metadata, knowing the business logic, those are important specific use cases for the vertical. And you can get to it faster, right? Chris, how is this changing on the tech side? Your perspective? Yeah, you know, I keep coming back to, you know, AWS and cloud makes it easier, right? None of this stuff, you know, all this stuff can be done and has some of it has been done. But you know, what Amazon continues to do is make it easier to consume by the developer, by the customer and to actually embed it into applications much easier than it would be if I had to go set up the stack and build it all and then embed it, right? So it's short-cutting that process. And again, as these products continue to mature, right? And some of this stuff is embedded. It makes that process so much faster. It reduces the amount of work required by the developers, the engineers to get there. So I'm expecting you're going to see more of this, right? I think you're going to see more and more of these multi-connected services by AWS that has a lot of the AIML, pre-configured data lakes, all that kind of stuff embedded in those services. So you don't have to do it yourself and continue to go up the stack. And we always talk about Amazon's bill for builders, right? But, you know, builders, you know, have been super specialized and we're becoming, you know, as engineers, we're being asked to be bigger and bigger and to be, you know, be able to do more stuff. And I think, you know, these kind of integrative services are going to help us do that. And certainly needed more now when you have hybrid edge that are going to be operating with microservices on a cloud model and with all those advantages that are going to come around the corner for being in the cloud. I mean, there's going to be, I think there's going to be a whole clarity around benefits in the cloud with all these capabilities and benefits. Cloud Guru thinks my favorite this year because it just points to why that could happen. I mean, that happens because of the cloud data. If you're on premise, you may not have a little cloud guru. You got to get more data. So, but they're all different. Edge certainly will come in too. Your vision on the edge, Chris, how do you see that evolving for customers? Because that could be complex new stuff. How is it going to get easier? Yeah, it's super complex now, right? I mean, you got to design for, you know, all the different edge, you know, 5G protocols are out there and solutions, right? You know, Amazon's simplifying that. Again, I come back to simplification, right? I can build an app that works on any 5G network that's been integrated with AWS, right? I don't have to set up all the different layers to get back to my cloud or back to my bigger data set. Now, it's kind of choking. I don't even know where to call the cloud anymore. I got big cloud, which is essential when I go down and I got a cloud at the edge, right? So, what do I call that? It's just really computing. It's another thing. Exactly, so, you know, again, I think is this next generation of technology with the edge comes, right? And we put more and more data at the edge. We're asking for more and more compute at the edge, right? Whether it be industrial or, you know, for personal use or consumer use, you know, that processing is going to get more and more intense to be able to manage it under a single console, under a single platform and be able to move the code that I develop across that entire platform, whether I have to go all the way down to the, you know, to the very edge at the 5G level, right? Or all the way back into the bigger cloud and how that process in there, be able to do that seamlessly is going to be allow the speed of development that's needed. Well, you guys done a great job and no better time to be a techie or interested in technology or computer science or social science, to that matter. This is a really perfect store, a lot of problems to solve, a lot of things, a lot of change happening, positive change opportunities, a lot of great stuff. Final question, guys, five years working together now on this partnership with AWS and Accenture. Congratulations, you guys are in pole position for the next wave coming. What's exciting you guys, Chris, what's on your mind? Brian, what's getting you guys pumped up? Well, again, I come back to, you know, Andy mentioned it in his keynote, right? We're seeing customers move now, right? We're seeing, you know, five years ago, we knew customers were going to do this. We built the partnership to enable these enterprise customers to make that journey, right? But now, you know, even more, we're seeing them move at such great speed, right? Which is super excites me, right? Because I can see, you know, being in this for a long time now, I can see the value on the other end. And I really have been wanting to push our customers as fast as they can through the journey. And now they're moving out of, they're getting, they're getting the religion, they're getting there. They see they need to do it to change your business. So that's what excites me. It's just the, excites me. It's just the speed at which we're going to see the movement. Yeah, I agree with that. I mean, so, you know, obviously getting customers to the cloud is super important work. And we're obviously doing that and helping accelerate that. It's, it's what we've been talking about when we're there, all the possibilities that become available, right? Through the common data capabilities, the access to the 175 some odd AWS services. And I also think, you know, and this is, this is, you know, kind of permeated through this week at re-invent is the opportunity, especially in those industries that do have an industrial aspect, you know, manufacturing aspect or is a really strong physical aspect of bringing together IT and operational technology and the business with all these capabilities. And I think edge and pushing machine learning down to the edge and analytics at the edge is really going to help us do that. And so I'm super excited by all that possibilities. I feel like we're just scratching the surface there. It's a great time to be building out. And, you know, this is a time for reconstruction, reinvention, big theme. So many storylines in the keynote and the events. It's going to keep us busy here. It's looking angle in the cube for the next year. Gentlemen, thank you for coming on. I really appreciate it. Thanks. Thank you for having us. All right, great conversation. You're getting technical. We're going to go on another 30 minutes. A lot to talk about. A lot of storylines here at AWS re-invent 2020, the censure executive summit. I'm John Furrier. Thanks for watching.