On this episode of the Six Five Media Webcast, Dave Nicholson is joined by Kyndryl, Intel, and Dell Technologies representatives Kevin Hazard, Nuri Cankaya, and Jonathan Seckler for a conversation on Making Enterprise AI Real. This comprehensive discussion outlines how enterprises can implement AI swiftly, the innovative AI factory model by Dell, readiness for current AI applications, and the crucial role of companies like Kyndryl, Intel, and Dell Technologies in facilitating AI integration within corporate strategies.
Their discussion covers:
- The transformative potential of AI factories by Dell for enterprises to scale AI infrastructure.
- The need for enterprises to adopt new skills and expertise to capitalize on AI technologies, with guidance from Kyndryl.
- Intel’s introduction of advanced CPU and GPU technologies tailored for enhanced AI capabilities and infrastructure.
- The readiness of enterprises for AI integration, featuring insights from Intel on technology, ecosystem support, and development programs.
- Strategies for enterprises to kick-start their AI initiatives, including planning for future technology advancements with Dell’s AI Ops and partnership insights.
Learn more at Kyndryl, Intel, and Dell Technologies.
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Transcript:
Dave Nicholson: Welcome to this Six Five Media production. My name is Dave Nicholson, and I am Chief Research Officer at The Futurum Group. Today, we’re going to be diving into an interesting discussion about accelerating AI, specifically, how does an enterprise make it through this AI journey that we’ve all been talking about? What’s critical for the acceleration, time to value-wise, that we need to look at? I’ve got a bit of a dream team here of individuals. Very, very happy to have join us today, Kevin Hazard, Vice President, Marketing Technology and Data at Kyndryl, Nuri Cankaya, Dr. Nuri Cankaya, Vice President of AI Marketing at Intel, and Jonathan Seckler, Head of Server and Networking Marketing at Dell Technologies. Gentlemen, welcome all.
Jonathan Seckler: Hi, David. Thanks.
Kevin Hazard: Thanks.
Nuri Cankaya: Thanks for having us.
Dave Nicholson: Yeah. Let’s start out with Jonathan. Jonathan, Dell has made a pretty big splash in the world of AI recently with this effort to democratize AI and specifically lots of conversations about what Dell refers to as an AI factory. Walk us through those announcements.
Jonathan Seckler: If you think about it? So recently at Dell Technologies world, we introduced the Dell AI factory and the way to think about it is, and I’m going to take a stand here as being the most senior person on the webcast. Back in the 20th century, we had data centers, right? Data centers were an IT’s job and data centers was really all about protecting the company. It was protecting the company data, it was managing and giving access to that data. It was very much a data center. In order to move toward AI, you need to use your company’s data. But IT’s role has fundamentally changed now. Now they’re not just the custodians of data, but they’re actually leading the generational change to use AI to deliver outcomes. So the data center or the concept has to change.
We have to go away from it being the shrine to data, to being more of a factory, more of a process where you have data on one side and it flows through the system and insights, outcomes, and ultimately business value come out the other end. So an AI factory is how data gets used in an enterprise to drive value. I think the biggest challenge to all of that is more than just the infrastructure that we provide. What we find is that a lot of big enterprises just don’t have that kind of expertise on hand yet. That’s why you really need a strong partner who knows what they’re doing when it comes to data and when it comes to AI, like Kyndryl. So Kevin, I was hoping that you would tell us a little bit about what you guys are doing with AI, with the AI factory.
Kevin Hazard: Sure. As we support some of the broader kind of use cases for a lot of our customers that go into their mission-critical workloads, we’ve seen that evolution from that legacy data shrine of a data center perspective into more of a modern, like let’s look at this entire environment as a system and seeing that evolution and then also seeing all of the developments that are happening within the market just around whether it’s AI, whether it’s generative AI, there are so many opportunities that we see our customers coming to us for and saying, help me make sense of this. There’s a lot of fear and uncertainty and doubt around what that all could mean for them. But in taking a very measured approach to both understanding their data foundation and footprint and the possibility and opportunity to build on top of that, we’re able to take a consultative approach with those customers to say, what are some use cases that you can start to play with this stuff?
Not publicly facing, not high risk, not jeopardizing a lot of mission-critical workloads, but what are the ways that you can get your foot in the water and say, what can we get out of this that we haven’t been able to do before? As you go through those exercises, you observe where that data foundation may require a little bit more factorization, I guess, right? Where you’re going from these silos and you’re trying to find the ways for them all to talk together and for these large language models or RAGs to really be used on all those things in a way that delivers the outcomes from a business perspective that everyone’s really expecting and that’s the promise of generative AI and AI in general.
When we think about whether enterprises are really ready for AI, I think that there are a couple of different answers to that. That’s really, I’m sure that from a business perspective, we all hear all the facts and figures of the amount that it’s going to be saved and the amount of free time that employees are going to have to do higher value activities and drive more projects for the company. But on the other side, the more conservative perspective is that our systems, our security, our privacy, all of these concerns, the legal liability, all the concerns around those things are a big challenge for enterprises that are trying to balance that conservative perspective as well as the ambition and the desire to drive value with AI.
Dave Nicholson: Nuri, Intel sits at sort of the foundational layer, creating the actual silicon that gets integrated into systems by Dell, and of course Kyndryl helps customers connect that technology and create value out of that technology. But what’s Intel’s perspective on what’s going on within enterprises on the AI front?
Nuri Cankaya: Absolutely. I think Jonathan really touched on the boom. It’s happening with many enterprises. At Intel, we really want to bring AI everywhere. This is something that as a tagline, we are highlighting because I think with Dell, we are really trying to create that systems approach because it’s not just the GPUs, AI accelerators, it starts from the PC like we are now discussing AI PC. Then on the data center side, Kevin mentioned the importance of the data preparation and all this retrieval-augmented generation. These are need terms, but I think Dell provides that factory approach, which we love from Intel because we really want our customers to achieve their outcomes. Most of the time they’re really doing something with AI, either to accelerate their innovation because things were taking a lot of time before and they want to hit that easy button and get the boost from AI, or they want to really save cost and invest on other projects.
From both, let’s say perspectives like make money or save money, it’s the business outcome that Dell brings into the table with the AI factory. As Intel, we love it because our products are really designed to enable that. So if I go to the product route, so if you look at Gaudi, for example, Gaudi is an AI accelerator, it’s a specific ASIC device. It’s not a GPU. We intentionally mention that because if you look at the AI acceleration needed at the enterprises, it’s going to just go skyrocket here. By 2030, just gen AI will drive a trillion dollars market value for enterprises. So everybody needs to be accelerating their game. I think with the close partnership with Dell, we are bringing that components like Gaudi, like Zion on the data center side and also on the software side with Intel Cyber. We are really bringing that platform approach for systems, and Kevin’s maybe highlight on the solutions that Kyndryl provides on top of that really helps the enterprises accelerate their journey on AI because again, everybody needs to be accelerated. As our job, we really want to bring AI everywhere.
Dave Nicholson: Kevin, we’d like to talk about the shiniest, newest sexiest thing in AI, and that’s often a generative AI conversation. But under the umbrella of AI, we have of course machine learning and the optimization of all sorts of processes that don’t sound as exciting, but when you’re shaving 15% off of the cost of doing business, that’s very exciting to a business. So Dell will build systems that address all sectors of the AI conversation, whether it’s inference or training for generative AI, but certainly advanced machine learning. How do Kyndryl and Dell work together with a client to help clients understand what they need? I get the sense that a lot of clients feel like they need some AI, but they’re not exactly sure where to start. So what does that Dell and Kyndryl relationship look like from a customer perspective?
Kevin Hazard: Well, to a large extent, it’s a matter of, I think there either co-creation sessions that happen. We have Kyndryl Vital, which is a group that focuses specifically on co-creation of ideation. We have Kyndryl consult that goes in and does more of an intentional, like let’s build out a roadmap for what all this looks like. But a lot of it is meeting people where they are and understanding, creating that roadmap or creating that landscape of where they are currently, from an enterprise architecture perspective. Then finding the ways that you, I know that we are using the word accelerate a lot, but finding the ways to accelerate with the things that are being developed by Intel, by Dell, by some of our other partners where we don’t have to go and completely throw out everything that’s happened before. We may have to refactor it, we may have to modernize it in some capacity.
We may have to supercharge it in some capacity, but it’s a matter of really finding people where they are and then helping them to understand this is the stepwise approach to getting where you want to be. At the beginning of that process, I think there’s an element of let’s all sit down and have a real heart-to-heart honest conversation about what we are willing to risk and what we’re willing to put out there and what we want to keep close to the vest. That process of really establishing how far you want to go and then also establishing the data governance of how you’re going to approach that stuff is really critical before you really make any of those moves. But in those conversations with vital or with consults, we’re leveraging to whatever extent we can, the systems and the offerings of partners like Dell to drive the most value without having to go and build versus finding that thing that fits, fits the use case and fits the need immediately.
Dave Nicholson: Jonathan, I was struck at Dell Tech world this year by just how much, to use an analogy, imagine you’re in the Kentucky Derby and there are 10 horses in the race. It felt like Dell owned all of the horses in the sense that you were embracing fit for function. The question is how important is it to be part of an open architecture environment or to at least offer that as an alternative? What does that look like when you’re going to market with Kyndryl and of course Intel as a partner? What does that look like?
Jonathan Seckler: Well, so I like to think that we’re actually living in 2025 right now. We’re about a year. We’d like to think ahead of the game a little bit, but I think that, Nuri, I think hit it on the head actually. He talked about AI anywhere and this idea that, and it goes back to the AI factory idea as well, that you’re going to be using your data. That data is going to be used to create value. So you have to start thinking about how does IT deliver value as opposed to how does IT solely act as a custodian? But at the same time where that value is created could be anywhere, and you can’t do it with just one vendor and you certainly can’t do it and expect to pay more and more every single time that you do it.
So you need to be able to run your applications. You need to be able to get that value out of the infrastructure that you’re planning for, which is, I think one of the reasons that Dell and Intel have such a strong partnership over time is that there are accelerators that are needed for some applications, but often you can run that AI application in an Edge location. You can run that application for your internal audiences, and you can do it on infrastructure that you either already have or that you’re already planning on acquiring. So it’s a good story and a good, it’s a good economic story, it’s a good productivity story for our customers.
Kevin Hazard: John, there’s an element too there around still having it inside of your four walls is really beneficial too. While we have use cases where there’s the kind of public cloud or even private cloud hosting other places, maybe useful, especially as there’s variables when it comes to whether it’s the AI models or the other tools you’re bringing in, like having a little bit more control. We’re not necessarily going to go back into the server hugger days where everybody’s going and petting their server in their closet, but at the same time, having a little bit more control over and isolation of that data I think really is beneficial in the midst of all this change and evolution.
Jonathan Seckler: That’s right. 70% of mission-critical data still is on premise, and it’s not cheap to get it out. So we think that to extract the value that you want to extract from your data, you’re going to need to at least start with where the data is at, how you deploy it, as you point out, could be deployed anywhere, but you need to have those considerations upfront.
Nuri Cankaya: I want to highlight that that’s really the IP of the companies. They really depend on that data. I think when AI came into fruition with especially cloud solution providers, it created a lot of uncertainty about “Am I going to share all my data with the cloud providers? Is it going to be a part of the training data set for the next large language model? If I ask a GPT, tell me the reverse engineer of that one.” So this was really critical questions for the chief security officers, but now especially with the chief digital transformation officers, we see this is an important part of AI journey where you should be close to your data in a secure environment. Also, just to highlight to Kevin’s point on openness, I think we have to provide a choice to developers because developers play a crucial role in this AI journey for enterprise customers.
They have to use open platforms and they can customize, and they have the flexibility because as of today, the industry is like, you have to buy the appliance, it’ll solve all your problems. Not exactly. I think with the Dell’s AI factory, we are providing that openness to developers and enterprises where they can choose where to develop, which model to use, which language and which transformer approach they can select. Then partners like Kyndryl will enable the developers from that open source perspective and use some of the learnings that will accelerate the innovation. So I’m really excited about this journey on the open source and security angles.
Dave Nicholson: Nuri, from an Intel perspective, from a personal perspective, are you enjoying just a little bit, the fact that we’re all focused on hardware a little bit now. Everybody was told years ago that it just didn’t matter anymore? But it kind of does, doesn’t it?
Nuri Cankaya: Exactly. I think again, back to Jonathan’s maybe approach, the history repeats itself. I think we have seen the mainframes and then the think lines. We have seen the cloud and then now we are seeing AI is going, both sides of, the machines are getting more smarter, fast. The Moore’s Law is definitely there. It’s accelerating and getting cheaper. I think AI just added the top flavor to this because everybody needs that productivity, acceleration, deep learning to really boost the innovation at the enterprise level. So we love it because we definitely see from all perspectives, like individuals are getting more productive with the copilot plus PCs.
A lot of applications like Adobe is driving some of the things on the visual and we have seen every single day, I think when you check your social accounts, you see, wow, there’s a new video model, this is the new audio model. The models are getting more better and better. For enterprises like solutions like RAG is enabling them to act fast and having that easy button will definitely make a big change in the enterprise, both cost saving and innovation. So for Intel, I think this is just the start of the journey. We are so excited where we are today with Dell, and again, getting that factory approach and getting it into scale to many customers just excites us.
Dave Nicholson: Jonathan, what do you think are some of the biggest challenges or headwinds that we face as we move forward from Dell’s perspective?
Jonathan Seckler: I think the biggest challenge that we’ve talked to customers about and talked to prospects about is everyone’s very excited about the promise of AI. I think the number one concern is how do I get started? That’s why I think it’s so important to be able to partner with someone that you can trust like Kyndryl, right? I think that the expertise is being built over time, but there’s not a lot of companies with benches of developers waiting to develop in these new platforms. That being said, clearly as you look at the promise of AI around automation, and you look at the promise around new business value and of productivity and the headwinds that you’re going to struggle with are not going to be hardware issues.
Really, they’re going to be people, people will change as a result of the new technologies, these new capabilities that came out. History is a great example. We went through the dot com era 20 something years ago, and roles changed. The role of IT changed. I think it’s changing again. I think that as people, the people in IT and the people who are actually doing the work are, become more and more comfortable with what they’re doing and more and more understand the possibilities of what they can do. You’re going to see just this pun intended acceleration of AI in the world.
Dave Nicholson: Jonathan, we were children in the year 2000, I’m not sure.
Jonathan Seckler: Speak for yourself. Yeah.
Dave Nicholson: Puzzled by that last statement. What’s really struck me from this conversation is the fact that you have three global companies that are working together, that come together and rally around the needs of an enterprise customer. I can tell you from the classes that I teach in the Wharton CTO program, the CTOs and CIOs are struggling with this question right now. Last year was the sort of FOMO era, fear of missing out. They felt there was only one answer to the problem. 2024 seems to be the era of rationality, where folks like Dell are coming out and saying, hold on folks.
There are a whole bunch of different aspects to this AI thing. A whole bunch of ways to solve the problems. I’ll leave the audience with one stat. On average when you say general purpose server, AI server, there can be a 10 x delta. Those are very generic things to say, but this concept of openness that folks like all of you are driving should serve to stabilize some of those costs involved. Kevin, do you have any final thoughts and then we’ll turn to you Nuri?
Kevin Hazard: Well, one of the things that Kyndryl being a business that focuses on the mission-critical infrastructure for a lot of our customers around the world, one of the things we tout ourselves on is that we eat our own cooking. To a large extent within the marketing organization, my team is leading a lot of our own marketing use cases around how we do a lot of this AI, how do we implement it and incorporate it into our work and our jobs and what we deliver back to the business, which then delivers the outcomes back to the entire company. In that process, we have a task force that went out and found 193 different use cases specifically for marketing. We have under 400 people in marketing. So we’ve got one use case for every two people that we have within marketing basically. It’s a matter of prioritizing those things and going through it.
But in that process of us trying to understand what we can do ourselves, we’ve tapped into every other part of Kyndryl’s AI think tank and found so many more resources and so much more opportunity that we just feel like we’re at the tip of the iceberg and we’re finding ways ourselves to figure a lot of this stuff out. In the process, giving that feedback back to our own delivery partners in the different markets that can then productize that for our own customers. So we’re really excited about this inflection point where nobody wants to be left behind, but nobody wants to fall off the edge either.
Finding that way that we can both push and model and help and then also learn from the engagements that we have with our customers to drive value ourselves. I think that that is something that we all have the opportunity to do amongst ourselves too, where we can share our own expertise and our own learnings to then power our partners to help either build the silicone a little bit differently or put it together in a way that the network sitting in a certain way that can deliver better response rates and latency and those kinds of things. All of those pieces are really critical for us at this point because everything just feels brand new and there’s just so much opportunity. So we’re really excited about it.
Dave Nicholson: Nuri, final thought and then we’re going to hand it off to Jonathan to wrap us up.
Nuri Cankaya: Absolutely. So I think we discussed that one, but I want to make sure the biggest blocker today for many companies is really looking at the solution ecosystem, the software part. I want to highlight working with Dell, we are really driving some developer enablement with a lot of activities. We call them Intel AI summits. So we have done 43 of them globally and we had to almost do a hundred of those even. It’s in many major cities. So I think getting to learn about the solutions that the companies can use easily and how to accelerate through the Dell’s AI factory is really critical.
In those four to five hour in-person workshops, we really want to make sure people get hands-on use the platform. One last thing is, as Intel, we are a true believer of the open source and we believe in order to bring that AI to enterprises, we are now a part of the open platform for enterprise with The Linux Foundation. In the heart of that Intel based hardware, we add that software layer because we want the customers to use some open source models to accelerate because I think we will hit that roadblock on, I want to go fast, there’s multiple alternatives in the market and I can do it on my term. So those are key, I think enterprise deployment solutions that Dell and Kyndryl can provide to customers easily.
Dave Nicholson: Fantastic. Jonathan, we got about a minute left. I know you need to get back to reminding your colleagues about how cool networking and servers are in the year 2024 and forward. I know it takes a fair bit of time tweaking them. Wrap us up, some final thoughts from Dell’s perspective.
Jonathan Seckler: So I guess maybe three final thoughts from Dell. Number one is the promise of AI is almost unlimited, and we have to take an approach that brings AI or starts AI projects now so that we can see the benefits tomorrow. That’s why it’s really great talking with Kevin and Nuri on this, and you, David on this call. I think, hopefully it will give our enterprise customers the ideas that they need to take the next step. I think the second thing about all of this, which is really fascinating, is that Nuri said it earlier and while you mentioned that an AI server versus a regular server, there’s like a 10 x difference.
We’re going to see that reduce over time because I think in the future, every A server is potentially an AI server, and so we want to build the future today for that. Then third thought to hear more about where we’re going at Dell. I know this is going to be coming out this summer, but in November at Super Compute 2024, we’ve already got an exciting slate of announcements and things to talk about. So come see us with Intel and with Kyndryl, I hope as well, to learn more.
Dave Nicholson: SC24 baby, I’ll be there. It’s Atlanta, isn’t it?
Jonathan Seckler: Atlanta this year. Yeah.
Nuri Cankaya: Yeah. We will be all having that. I think in-person meeting there this year.
Dave Nicholson: Atlanta. “HotLanta” We’ll see each other in three dimensions.
Jonathan Seckler: Awesome.
Dave Nicholson: Well, gentlemen, this has really been a pleasure. Intel, Kyndryl, Dell altogether. We could go on for hours, but we’re not allowed to. Thanks again. Great discussion from Dave Nicholson of The Futurum Group. Thanks for tuning in.
Author Information
David Nicholson is Chief Research Officer at The Futurum Group, a host and contributor for Six Five Media, and an Instructor and Success Coach at Wharton’s CTO and Digital Transformation academies, out of the University of Pennsylvania’s Wharton School of Business’s Arresty Institute for Executive Education.
David interprets the world of Information Technology from the perspective of a Chief Technology Officer mindset, answering the question, “How is the latest technology best leveraged in service of an organization’s mission?” This is the subject of much of his advisory work with clients, as well as his academic focus.
Prior to joining The Futurum Group, David held technical leadership positions at EMC, Oracle, and Dell. He is also the founder of DNA Consulting, providing actionable insights to a wide variety of clients seeking to better understand the intersection of technology and business.
