On this special episode of the Futurum Tech Webcast – Interview Series, I am joined by Ross Mauri, General Manager for IBM Z, for a conversation around one of our favorite topics: AI. This conversation is the second in a three-part series with IBM Z.
In our conversation we discussed the following:
- An overview of the IBM Telum Processor for IBM Z and what it will enable for their customers
- A deep dive into real world use cases
- An exploration into technical and operation assurance
- How IBM Z is aligning with IBM’s overall strategic initiatives
It was a great conversation and one you don’t want to miss. Want to learn more about what IBM Z and what they are doing in this space? Check out their website.
Also, be sure to check out the other episodes in the series:
The Magic In Optimizing App Modernization: Finding the Right Approach for Each Workload
A Look at the Role of IBM Z in Digital Transformation
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Transcript:
Daniel Newman: Hey, everyone, I’m Daniel Newman, principal analyst at Futurum Research. And I’m joined here by Ross Mauri, General Manager at IBM Z. Second video in this series. Excited to have you back and talk a little bit about IBM, the main frame and AI. And in case anyone missed it, we did have another conversation already about app modernization. So I hope you tune into it. But this one, Ross, we’re going to talk about something near and dear to my heart and becoming increasingly near and dear to your heart and that’s AI.
Ross Mauri: That’s right. Looking forward to it.
Daniel Newman: Yeah, it’s going to be a good conversation. Excited to be here. So the Telum announcement, congratulations. Very exciting. Talk a little bit about that. Give the overall thought process on Telum, the evolution, why you’re getting more focused on AI in this particular rev because I think everybody would just like to hear a little bit. And by the way, this is part of that great research and development that comes out of IBM.
Ross Mauri: That’s right. So Telum is the microprocessor that’s going to be in the next generation IBM Z system. And why we did a hot chip special announcement and focus around it was because we were pretty proud of the innovation that’s in it, but we also wanted to signal to the market, into our clients how serious we were about going beyond, advance the analytics on the platform and going to full deep learning and being able to bring AI into their most important transactions. I mean, that was really the goal.
Our clients have such a wealth of data that’s created operationally on IBM Z. And for many years, clients could do analytics and analysis and SQL queries and all things on that data. More and more, they were copying it off so that they could try to do AI on it off platform. And many of them told us that not only was that too costly, but more importantly, they couldn’t connect them back then to the operational system. So it’s back to their operational system and using their business insights, but at full velocity.
Daniel Newman: Yeah, I think every, and obviously everyone out there is hearing about AI, a lot about AI. And a lot of us think about it maybe as a data center cloud thing. Some people might think about it as almost an edge on device because we have our at home smart speakers and our phones and we’re doing natural language processing, but maybe not so much thinking about AI in the role that your business, the mainframe and how you’re approaching it. Talk a little bit about that broader use case and why you’re putting so much energy in this next generation around AI.
Ross Mauri: Sure, so our clients run very large transaction, would be called transaction systems, whether it’s an airline reservation system or it’s a large core banking system, you name it. These are very large, very complex, but they’re transaction systems. So transactions that have to have integrity in the entire transaction because they build in one or more absolute financial things that are going to get changed and written in a ledger or moved from one account to another.
So within these systems, my clients have been saying, “We really would like to be able to do more and more use of data.” I’ll just put it that way. I don’t know if they ever said to me AI, but they wanted to use more analytics. That was what they were saying. And if you step back and look at the transaction processing, a medium sized client of ours could be doing 15,000 transactions a second through their system. A large client could be doing 50,000 and beyond that.
We have clients that do well more than a billion of these complex transactions per day. So it’s the speed and the scale of their transaction system, but being able to in a very small window, two to four milliseconds, be able to do a full AI deep learning inference call. That’s what in talking to them, it came down. And so the Telum processor is designed to be that beast that can do a lot of those inferences every second.
And the use cases that our clients are talking about are think of things like fraud detection for our credit card, our banking card, our payment card. How we many swipes of those cards go on every day? I mean a lot. And most card companies can’t do 100% fraud detection on the swipe in that two to four milliseconds. So we said, we can fix that problem. We can change things so that you can do it on everyone regardless of how many transactions per second you do. So that was the genesis of it I think. And now the use cases are really broadening out well beyond just say credit card processing.
Daniel Newman: Yeah, that’s a good one. And then as I’m listening, I’m registering my mind, all right, I’m going to hit you on a few more of these because I do want to hear about that because a lot of the market, no matter which particular side of infrastructure architecture software AI we’re on, it’s all about improving experiences. It’s about more contextualization of data. It’s about being able to do things in real time.
You’re talking about fraud detection, which is a value add that most people don’t actually recognize until it’s their card that’s being fraudulently swiped. But there has to be more cases than that because that’s been an area we’ve heard a lot about. Can you share a little bit more? I mean, you’re probably talking to some customers. I know you can’t give divulge too much, but what are some of the other cases that you mentioned that are popping out?
Ross Mauri: So I’ll just tell you the cases that we’re actively working on clients today either they’re in production, they’re in pre-production or they’re waiting until next year. And so there’s lots of things like settlement, but there’s upsell opportunity, so upsell of a revenue opportunity during a transaction and then there’s things that go out of, I would say, finances. Believe it or not, we’re working with a very large health provider in the United States because they’ve figured out with us, with my scientists that there’s some medical imaging applications that actually can be done the best in a transaction format being done with IBM Z.
So we’re off into… We’re well beyond say banking and financial services now. And of course insurance, so loan origination, loan granting, things like that. We’ve got multiple clients we’re working with us on that, but we’re now off… We’re into healthcare. And I think you’re going to see us in other industries because again, the data that’s available is powerful. You have to access it in this really short windows, during the transaction in order to get that business insight, that business value and make a decision and do it tens of thousands, hundreds of thousands a time a second.
Daniel Newman: Yeah, I see so much opportunity. And I just think to myself about whether it is a decision being made by a healthcare provider in that second. I mean, there’s so much complexity inside of the healthcare space that has nothing to do with the systems available, it has to do with the red tape. But once we can break down some of those silos, same thing in finances, in FinTech to make sure that we’re managing because security and safety is one of those big things. Of course giving healthcare providers the best data and information to be able to make decisions in the moment to take care of patients.
Those are all meaningful. And material experience enhancements that can be done and that volume of processing, it’s one of those things, I guess, none of us really think of about, but to… When you’re swiping your credit card, nobody’s sitting there going, “God, there’s a million credit cards being swiped this second.” And the technology required to enable one of these transaction companies that manage this to, do this and do it securely. It’s unbelievable.
So the fact is is that behind that curtain, Z is the technology that many of these financial institutions are using. And of course, as we move, modernize into things like the blockchains being used to support these things, you will also be a very important technology behind that. So that’s going to be something that… Those applications I’m sure are going to be stories that are going to start to come out more and more, hopefully in maybe a future conversation that we’ll have.
Ross Mauri: I can even give you a couple right now.
Daniel Newman: All right, do it.
Ross Mauri: So not many people know this, but we actually have IBM Zs in the IBM public cloud. And you can only access them through a platform as a service known as the Hyper Protect Services. So how do you access those services like you would on any public cloud? You sign up, you pay, you access through APIs like any cloud. But what those services do is they bring banking grade security and confidential computing to the masses.
So we have 100 startups in an accelerator. Most are FinTechs. There’s a few Insuretechs, there’s a few HealthTechs. Why would they come to the… Oh, why would they come off of other hyperscalers onto the IBM cloud? It’s because of this capability of confidential computing, digital ledger based applications that can be totally secure while the data’s at rest, in flight and in use. We can protect all of it. We can protect it from any type of access. So there’s always insider threat you hear about.
With our confidential computing environment, we give the client, the end user, what we call as technical assurance. What you get from the hyperscalers is you get operational insurance. You sign a contract that says operationally, they won’t allow a human with the right privilege to touch your data. With ours, we can’t touch your data. The IBM team, the SRE team, the system programmers behind the IBM cloud, even if they wanted to, without the keys that you hold, it’s keep your own key, no one can touch your data.
So confidential computing, privacy of your data, security of your data, blockchain based applications running now at scale. 10,000 transactions a second for blockchain based data. And we’re going to go way beyond that. So again, I’ve just told about the hundred of startups we have, which is, to me was just how do I get to the companies that have vision, technical capability, they’re getting funding, but they might not have access to resources like global bank would? Now they can do it via the IBM public cloud and the Hyper Protect Services.
Daniel Newman: Yeah, I actually had the chance to participate a little bit in that. I met with some of those startups, I talked to them, provided some feedback to your teams when they were going through the review and the judging process because there was a big contest I remember on that to. So I had a lot of fun with that. And by the way, that’s an important point to reiterate is that 10,000 transactions on the blockchain because a lot of people think that that’s been a limiting factor with the blockchain.
It can’t handle volume the same way of traditional compute. And so you’re starting to see with your technology behind it, that it is possible to handle that volume of transactions because we’re going to need both. You need that ledger to manage and you also need to be able to do the volume to be able to get value out of that. And so it sounds like you’re doing both. Now you mentioned technical and operational assurance. And I like that you mentioned that because bad actors are unfortunately a problem in every society.
And of course, companies take a lot of steps when they’re vetting people, clearances and make sure that the people they can get into data centers, anyone that’s ever been to one of these tier one data centers has seen… It’s no joke to be able to get inside of one of these places. But having said that, reiterating the fact that with technical assurance, people cannot. Operational, there’s bad actors, there is risk, there is a possibility and we’ve actually seen it happen.
Ross Mauri: That’s right.
Daniel Newman: And so you can’t just say, “Oh yeah, well, it’s vetted and careful and so it never happens.” It has happened. Data has gotten out. It’s caused breaches. It’s caused leaks. It’s caused denial of services that have been noted. And some of us have maybe lost access to some of our favorite apps at time and we don’t necessarily always know why. That happens. But I just wanted to reiterate that before I got to the next question because you did talk about operational AI. What about that? Because that’s a little bit less maybe cool or sexy, but operational AI has got to be part of your story with what you’re building out.
Ross Mauri: Yeah, it’s actually a critical element. I mean, I look could AI and IBM Z in two flavors. I mean, there’s the business insight which we’ve been talking about, but then there’s this operational excellence. So using things like AIOps to really be able to oversee the operations of a system that’s so complex. And having so many transactions, it is beyond human scope already is critical for us. And that’s just one example of bringing AI into the system.
I think we’re going to have MLOps for machine learning and I think we’re going to be bringing AI inside the IBM Z for anomaly detection and other types of security protections, but also to help balance workloads and things that again, humans used to have to tune by hand and be really knowledgeable about. Well, we’re smart enough now to leverage AI, build the right models and have the system take care of itself. So there’s going to be… So there’s business insights that are very important from an AI point of view. There’s how a client will operate the system. And then it’s the AI within the system that will continue to make it that much more capable and I would say valuable to our clients.
Daniel Newman: Well, we’ve seen the investments that IBM’s made in observability and this is a little microcosm of that, observability within the hardware and your product line. So let’s wrap up and go from… We went from macro to micro. Let’s go back to macro a minute. We’re hearing a lot about obviously Arvin Krishna since taking over spinoff of Kyndryl . The company’s really narrowed in its focuses into the hybrid cloud and the AI and data services space. Talk a little bit about how your business is aligning with those strategic initiatives and of course what you’re seeing more broadly across the organizations.
Ross Mauri: So Arvin really has brought a focus to a clear and concise strategy and that really is hybrid cloud and AI as you said. And within that, I’ve realigned our investments, especially in software around those two key pillars. And I think that the integration within IBM and I would say the meaningfulness of how Z is positioned within the full IBM strategy hasn’t been stronger in decades.
So we are right in the middle, the heart of Arvin strategy. And we also connect out to other divisions of IBM that are helping to implement that strategy like IBM Consulting or perhaps the folks that are putting forth the data fabric. We’re connected within the IBM products and services lines. And also again, implementing all of the key technologies, use cases and proof points that show that IBM is the hybrid cloud and enterprise AI partner to have.
Daniel Newman: Yeah, you definitely firing on all cylinders. It seems that the narrative is starting to be better understood and better adopted. And this is something I can tell you as an analyst I’ve been waiting for just to see how do we address the simplification that is required for the market to fully understand and appreciate. Unfortunately sometimes being in so many things and this is something that IBM is famous for because you’re curious. It’s a curious company and curious companies tend to invent a lot of things. But sometimes when you’re curious about so many things, you need to make it digestible. That’s what I’ve noticed. Seemingly you’ve got your business focused on those same initiatives. And having that consistent across all the different businesses is very important.
Ross Mauri: That’s great. That’s right. And IBM Investor Day recently I think highlighted that because it was a very clear picture of the whole company, how all the pieces fit together. And I know you were watching, you saw IBM Z well positioned within that.
Daniel Newman: Absolutely, even commented a few times about it. Thanks, Ross for chatting on this one and I look forward. Let’s jump over to another topic here in a little bit.
Ross Mauri: Absolutely, thank you.
Author Information
Daniel is the CEO of The Futurum Group. Living his life at the intersection of people and technology, Daniel works with the world’s largest technology brands exploring Digital Transformation and how it is influencing the enterprise.
From the leading edge of AI to global technology policy, Daniel makes the connections between business, people and tech that are required for companies to benefit most from their technology investments. Daniel is a top 5 globally ranked industry analyst and his ideas are regularly cited or shared in television appearances by CNBC, Bloomberg, Wall Street Journal and hundreds of other sites around the world.
A 7x Best-Selling Author including his most recent book “Human/Machine.” Daniel is also a Forbes and MarketWatch (Dow Jones) contributor.
An MBA and Former Graduate Adjunct Faculty, Daniel is an Austin Texas transplant after 40 years in Chicago. His speaking takes him around the world each year as he shares his vision of the role technology will play in our future.
