“How can you take the trust that you have in the data center when you deliver data, and how can you stretch that from the far edge, to a gateway, to an edge server, to the core, to the cloud?” Steve Todd, Fellow & VP of Data Innovation and Strategy at Dell Technologies, predicted years ago that the problem of data trust on the edge would be important today. In this conversation, he discusses the long process behind building a solution.
“How can you take the trust that you have in the data center when you deliver data, and how can you stretch that from the far edge, to a gateway, to an edge server, to the core, to the cloud?” Steve Todd, Fellow & VP of Data Innovation and Strategy at Dell Technologies, predicted 25 years ago that the problem of data trust on the edge would be important today. In this conversation, he discusses the long process behind building a solution.
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“The light bulb went on; there's an intersection, I believe, between distributed ledgers and delivering trusted data.”
"The other thing I think that is happening at just the right time, is the importance of AI, the importance of model building and deployment of inference towards the edge. Everybody's investing in that right now and there hasn't been a corresponding level of investment into knowing that the data is trustworthy."
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Timestamps:
(01:35) How Steve got started in tech and his career journey
(08:16) The intersection between distributed ledgers and delivering trusted data
(11:04) How can you take the trust you have in the data center and stretch it to the edge?
(14:11) The power of open sourcing Project Alvarium, a community building Data Confidence Fabric
(22:11) How did Steve predict this need years ago?
(29:43) What does Steve see coming next?
(34:35) What is the Hedera network?
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Over the Edge is brought to you by Dell Technologies to unlock the potential of your infrastructure with edge solutions. From hardware and software to data and operations, across your entire multi-cloud environment, we’re here to help you simplify your edge so you can generate more value. Learn more by visiting dell.com/edge for more information or click on the link in the show notes.
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Over the Edge is hosted by Bill Pfeifer, and was created by Matt Trifiro and Ian Faison. Executive producers are Matt Trifiro, Ian Faison, Jon Libbey and Kyle Rusca. The show producer is Erin Stenhouse. The audio engineer is Brian Thomas. Additional production support from Elisabeth Plutko.
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Follow Bill on LinkedIn
Connect with Steve Todd on LinkedIn
Bumpy Landing: Distributed Ledgers In A Centralized World
Building Data Confidence at the Edge
Producer: [00:00:00] Hello and welcome to Over the Edge. This episode features an interview between Bill Pfeiffer and Steve Todd, who until his recent retirement served as fellow and VP of Data Innovation and Strategy at Dell Technologies. Steve spent 25 years as a software engineer building new products related to data storage systems.
He later served as the Director of Global Innovation at EMC before it was bought by Dell. He's a longtime inventor of tech, and after spending 25 years thinking about trust inside the data center, he's tackling the issue of data trust on the edge. In this conversation, he dives into the long process of building a solution to stretch data confidence from the far edge up to the cloud.
But before we get into it, here's a brief word from our sponsors.
Narrator: Over the Edge is brought to you by Dell Technologies to unlock the potential of your infrastructure with Edge solutions. From hardware and software to data and operations, across your entire multi cloud [00:01:00] environment, we're here to help you simplify your Edge so that you can generate more value.
Learn more by visiting dell. com. Slash Edge for more information or click on the link in the show notes.
Producer: And now please enjoy this interview between Bill Piper and Steve Todd, fellow and VP of Data Innovation and Strategy at Dell Technologies.
Bill Pfeifer: All righty. Today we have the pleasure of speaking with Steve Todd, one of the most fantastic people inside of Dell Technologies.
Super excited about this. This should be really fun. Steve, welcome to the show and thanks so much for the time.
Steve Todd: Thanks, Bill. Let's have a great chat.
Bill Pfeifer: Fantastic. All right. So let's start by going back in time. How did you get started in technology?
Steve Todd: Well, I was a computer science major in the University of New Hampshire, and lo and behold, a technology company called Data General built a new building right off campus.
And they were looking for interns. And the [00:02:00] specific task that this facility was going to focus on was building disk drives and other peripherals. So immediately, actually as a co op or an intern, I got into the data storage industry from the software perspective.
Bill Pfeifer: Wow. Okay. And that led you forward to EMC and into Dell.
Steve Todd: Right, EMC acquired Data General in 1999, I believe, and roughly 15 or 16 years later, Dell acquired EMC.
Bill Pfeifer: So you're one of those crazy unicorns in the tech industry that's had one job, sort of give or take.
Steve Todd: Yeah, my, my hire date is maybe two years after Michael Dell's start date. Although I didn't start working until 30 years into his career.
So figure that one out.
Bill Pfeifer: That's really funny. So for a while before Dell Body [00:03:00] MC, your title was the Director of Global Innovation. Yeah. at EMC. That just sounds, that could go in so many different directions, but it sounds really fun. Can you talk a little bit about what that was, how it came about, what you did?
Steve Todd: Sure. I mean, going back to the days of data general, I spent 25 years Solely, as a software engineer, building new products related to data storage systems. After a while, the pressure of that and the routine of delivering products caused me to look around, and I really enjoyed EMC's innovation culture.
They had a director of innovation, and I had a meeting with him and said, I'm interested in getting more involved in this global innovation program that you're running. What can I do? And he said, well, Steve, I'm leaving next week. Do you want my job? [00:04:00] I didn't know what it was about necessarily and what it all involved, because it certainly was not software engineering, which was all I had done up to that point.
But I said, I can't turn this down. This, this sounds really cool. So I took the job in 2011. So 25 years after I started at Durham, New Hampshire campus with Data General.
Bill Pfeifer: That sounds like a red flag. How, how would I get into your job? Oh, you want it? Good habit. I'm going to run away. I'm going to be over here.
You just, you just, I'm going to put your name on this right now. Okay. It
Steve Todd: was a shock, but, but the truth is that I had spent a couple of years working with Dell's innovation lead. And I trusted him. And I knew that he was leaving because he had a great opportunity outside and he had built really a thriving program that I could just step right into and run.
Wow. And you know what's interesting? It was the job entitled really running innovation contests [00:05:00] globally. Traveling and meeting with our EMC employees around the world to help them establish university research projects. I actually ran the EMC Fellow and Distinguished Engineer program for a while. So, there wasn't a lot of software innovation for me personally, but there was this network effect where I met everybody who was working on innovation across the company.
As well as people outside the company too.
Bill Pfeifer: Wow. That's quite a jump and quite an amazing opportunity. Just, even just, I mean, by the sound of it, I want the job. That sounds pretty cool. Just run around and encourage people to innovate and show them how to innovate and help them innovate. So what did you do after that?
What, what brought you into being a fellow at Dell?
Steve Todd: Well, I would say that that job was when I became a fellow at Dell, right? So the, there's a couple reasons that when I put my nomination in, it was [00:06:00] accepted, right? And the first one was that I had a 25 year track record, Of innovation, right? Creating brand new software projects that we would ideate on, brainstorm, build, deliver, and that had experienced customer adoption.
So I had all that to put on my application, but I also had this global innovation job. Where you could establish that I was visible externally outside the company. And that external presence, building research projects with universities worldwide, but also meeting with customers worldwide who wanted to understand at the time EMC's innovation strategy, that brought me a level of public visibility that helped with that fellow nomination process.
And the other piece was at that point in time. For five or six years, I had been a corporate blogger. So there, right when blogging took off in the mid [00:07:00] 2000s, the first decade of the new millennium, they were looking for employees to write about EMC's products. And being that I had built a lot of them, I had some insight that also increased my visibility with our customers who were curious about how we came up with our product ideas and how we built them.
Bill Pfeifer: Boy, that's got to be a whole series of interesting stories too. The story behind how different things came to be. That's often super interesting, and there's usually more drama than you would expect behind the scenes. And I had to be careful
Steve Todd: what I said because it was public.
Bill Pfeifer: Yeah.
Steve Todd: But what was the most surprising thing was that this external public blog connected me with my co workers like never before, right?
Because they started hearing the stories about how these things were built. And they had their own ideas and would internally get in touch with me. And I met a lot of people that way as well, right? So my network really grew in, in, you know, when I became a blogger, but also when I became [00:08:00] the director of global innovation.
Bill Pfeifer: Really cool. You've been through a lot. So you started out writing software for hardware and working in the data center space. Now you're in the distributed ledger space. Mostly by choice, right? Because as a fellow, you're, you're relatively independent and just kind of driving toward the future. So how do you get from software and hardware into distributed ledger, more of a pure software space?
Steve Todd: Right. So I would say that the, the 25 years that I built products as a software engineer before the global innovation job, my area of focus was delivering trusted data. From storage systems to applications and back again. And that was really C and Dell EMC's brand. People bought our data center products because when we delivered data to an [00:09:00] application, the application trusted it.
And when the application wrote data to the storage system, they trusted that we would store properly and retrieve it. And we would do it fast. So I love that problem. Let's call it a plumbing problem. Right? The trusted movement of data between Storage medium and an application. Well, when Edge came around and the data sources might be sensors on some manufacturing floors and the data has to jump over five different hops and countries and networks and vendors to arrive at an application somewhere out there, how do you deliver trusted data?
And that's when, you know, I was studying distributed ledgers. And blockchain, for example, just to see how it worked, because I was curious. I was fascinated by blockchain and Bitcoin and distributed ledgers. [00:10:00] The light bulb went on, right? There's an intersection, I believe, between distributed ledgers and delivering trusted data.
And that was kind of the new software path that I set on after I did the innovation job globally.
I hadn't actually connected it like that, but that makes a lot of sense, right? Storing data inside a data center, you have to have trust that the data, once you release it, is going to get to the disk and be trustworthy and be intact and maintain its integrity and such.
But now, using Distributed Ledger, you're doing that from One end device to another end device across a network, across whatever hands touch it and things like that. So for listeners who don't know, we're talking loosely leading toward Project Elvarium, which many folks may not know about. So Steve, can you give us just kind of a quick elevator pitch on what that is?
Sure. Project Elvarium [00:11:00] is an open source community, an open source project, building a technology called Data Confidence Fabric. Or DCF. And again, to go back to the data centers, you're right. Our customers that built data centers trusted the data path, right? The trusted delivery of data because they bought a highly qualified solution that was in one location.
That they had control over. And when you started thinking about, well, how can I take the trust that you have in the data center when you deliver data? How can I stretch that from the far edge to a gateway, to an edge server, to the core, to the cloud? And I discovered that distributed ledgers are actually a technology that stretches or can stretch in a highly decentralized way.
across an entire [00:12:00] edge ecosystem. So it's almost like a ledgers or trusted storage systems that you can read or write from very quickly to help you with the delivery of trusted data. So that's what Project Elverium is. It's a community of companies trying to build data confidence fabrics. So you can measure the confidence of your data.
Bill Pfeifer: And that gives us things like carbon credit tracking, where you can validate that the endpoint wasn't played around with the data's real, the data maintains its integrity throughout. So as you're trading these carbon credits, they're actually based on something with integrity and it's not greenwashing, things like that.
Steve Todd: Right. And the first, the first project that this public community did was a climate use case. So as sensor data. For example, the first project we did was keeping track of how much methane was being captured and not released into the [00:13:00] environment. And there was a half a dozen sensors that would help you measure that.
So when you came up with the final number, how many tons of methane were not released into the environment, You also had a confidence score that came along with that. And that was basically a signal to the industry that we use this data confidence fabric approach to track the integrity of the data from creation to transit to display.
Bill Pfeifer: And there's, there's enough potential there. We could talk about Alverium. All day. And some of the spinoff things that you've been working on all day. But what I wanted to talk about here was you built Elverium, super cool. And in a community in collaboration with a number of other folks, then you open sourced it.
Dell isn't really known, so far as I know, for open sourcing software projects, which must have been a really interesting internal [00:14:00] conversation. Hey, I, I spent a bunch of time building this thing. Now we're going to give it away. Is that okay? Can you take us through the logic of Why that makes sense for a project like Alvarium, for a company like Dell.
How do you manage to take something open source and why?
Steve Todd: So I think that there's a couple different ways to answer that question, right? The first one is, What was the argument that I used internally? And then the second one was, what was the argument that was used against me internally to say, no, let's not do that.
The argument was essentially, we need as a company, Dell Technologies, to play in the edge space. I mean, we're great at doing storage, servers, networking, data protection. Our sweet spot has always been the data center. And so, there's money to be made selling these technologies on the edge. And [00:15:00] I argued that the biggest problem that our customers would worry about is trusting the data.
Because I mentioned, as I mentioned earlier, that the heterogeneity of an edge ecosystem in terms of the number of different vendors that that come together, the number of different geographic zones and networks and countries that the data may have to cross represents the opportunity for corruption, malicious activity, And any other number of problems that can cause you to not trust the data.
So that was the argument that I used. That here's an opportunity to work with the industry on basically a trust standard or a mechanism that would really, really help our customers. And they bought into the argument. However, at the time, It was right after the Dell and EMC acquisition [00:16:00] and Dell Technologies had too many products.
We had 20 or 25 different products that we sold and so we were trying to whittle those down. And, and streamline the portfolio so customers could understand it. And there was a worry that project Elverium was so different with distributed ledger technology and not necessarily a hardware project that it might confuse our customer base.
And so what we settled on was, let's treat it as an external research project. Let's donate the code and see if other vendors wanted to come and help us try and build a data confidence fabric for the first time. And so from that perspective, it was a little bit low key. In terms of, we didn't trumpet the fact that we had invented this and we're donating it, but we just let people [00:17:00] know and kind of contacted companies out of band, right?
And said, do you think you're interested in coming to this party and trying to build this idea? And that approach was the right thing, right? Ultimately, the Dell executives approved the open source project. And we had the freedom to research and experiment with other companies and the momentum began to build as a result of that approach.
Bill Pfeifer: So it was really almost a volume problem. We had too many things going on inside Dell, and so it got freed. That's, that's a fascinating reason. I didn't see that one coming.
Steve Todd: Well, you know, if you think about the Dell and EMC acquisition, At the time EMC had VMware, RSA, Documentum, several different storage systems, so on and so [00:18:00] forth down the line, right?
So there's the portfolio streamlining that had to happen. And because we came about right at that time, we almost went through a backdoor approach where we got approval, but no, you know, not a, an all out blessing in marketing. of data confidence fabric and Project Delbarium as being the next big thing.
Bill Pfeifer: And so rather than killing it, you managed to, to release it so that it could continue to live. That's awesome. I'm sure that wasn't easy. I'm sure that took a lot of effort on your part.
Steve Todd: Yeah, it's, it took persistence and perseverance to, to keep it alive, but fortunately we had a mix of big companies. Like Intel, who are very interested in their trustworthy edge technologies.
And, you know, smaller companies and startups like IOTA, who would build a distributed ledger just for the use case and the sensor trust that we were looking [00:19:00] for. So, there wasn't a lot of companies that, that piled in right from the beginning, but there were some really good ones that helped us move the message forward.
Bill Pfeifer: Nice. It's definitely a problem that needs to be solved. And when you frame it as that extension of trust. Right? It's like moving data around inside your data center where you control all the wires and it doesn't leave the walls out in the world and you can trust it the same amount or find out how much you can trust it and the data can keep track of its own trust score.
That's really cool. So, what's missing to bring Elverium to market? to mainstream enterprises, right? It's currently open sourced, but how does it move from being a small project that solves a future problem, an upcoming problem, to something that everyone knows, everyone wants, everyone uses?
Steve Todd: Well, what's been missing for the last three or four years was basically the orchestration and configuration of data confidence fabrics.[00:20:00]
If I have a sensor sending data to a controller board, sending data to a gateway, sending data to a server, how do I manage all those hardware platforms? in a trusted way to cooperate and calculate a score from birth to delivery. So, in the interim, we didn't have any sort of tool that could do this. We just did it manually, right?
We set up all these pieces of hardware, then we went to each one, installed Project Delverium, and created manually a data confidence fabric. So that we could demonstrate a real working hardware configuration at a customer's site. But what happened after we did that was, Dell came up and delivered Native Edge.
Which was first announced at Project Frontier. You know, as I was pitching this idea inside of [00:21:00] Dell, I pitched it to Dan Cummins, who's a fellow fellow and CTO of the Edge Business Unit. He said, Steve, this is a great idea. This is the right problem to solve. You're solving it properly. But it won't work if you don't have a platform to deliver it.
So let me build the platform and when it's out there, come back. And so I think that was the missing piece, right? Dell native edge solution can drop images that are coordinated together across multiple pieces of edge hardware. And we, we were looking at some, some open source solutions that did the same thing, but they weren't product ready.
And Native Edge is being sold right now. So that potential integration, which is what we're working on right now, we found to be very interesting.
Bill Pfeifer: Nice. So how did you see this [00:22:00] coming years ago, right? You've been working on Elverium for years and right now. We can talk to the listeners on this podcast, for instance, and it sounds cutting edge and just in time.
And, you know, like if you, if you talked to us about this a year or two ago, we probably just would have collectively looked at you funny and walked away. But now we go, wow, yeah, that's, that's a problem that needs to be solved, but you've been working on this for years. How do you see something coming that far in advance that you have time to build it and work through all of the.
the processes and such and integrations and build up this community.
Steve Todd: Yeah, I think in this particular example, the problem of trust on the edge was really, really obvious to me because I had spent the last 25 years worrying about trust inside a data center. And that problem was hard [00:23:00] enough to solve. In a constrained environment like a data center, we had to bundle together technologies like RAID technology, mirrored write caching, load balancing and failover, storage area networks.
There's so many, we call them trust insertion points that we had to layer together so that the application could seamlessly Enjoy the delivery of trusted data. When I looked at the permutations of technologies that you have to string together to deliver edge data, I said to myself, this is the right problem to solve.
So that was evident to me the first time I heard the word edge computing, and I began to look at the complexity and the heterogeneity of the data path. And I, I became super passionate and motivated. About solving it, but I didn't know how. [00:24:00] So I think that's the starting point, Bill, is just anticipating a customer problem that there was no doubt.
It was going to be there.
Bill Pfeifer: Wow. And now the world is your data center.
Steve Todd: That's right. The world is a data center. And the other thing I think that is happening at just the right time is the importance of AI. The importance of model building and deployment of inference towards the edge is everybody's investing in that right now, and there hasn't been a corresponding level of investment into knowing that the data is trustworthy.
Right, so that's why we think Project Elverium is the right solution at the right time because the industry is heavily focused on the development and deployment of AI and less focused on the development and deployment and delivery of trustworthy data.
Bill Pfeifer: Mm [00:25:00] hmm. Yeah, it's, it's definitely an interesting thing.
AI at the edge pretty dramatically changes the economics of data. Right. We talk about big data and you know, these masses, these huge, huge masses of data that are super dramatic and people use to train different things. Then at the edge, we're looking at small data and how do you take a couple of key data points and use that to make a sale or to change someone's experience or to save a life?
But then you have to be able to trust and track and, you know, maintain that data because it's actually worth something like individual data points become worth something as opposed to just en masse, which is a gives you very different opportunities, but predicated on trust, assuming you can trust that data.
That it's worth doing something with. That's, that's cool.
Steve Todd: I think there's, there's safety critical inference that's happening all [00:26:00] over the industry, right? On a manufacturing floor, for example. If you see the right combination of sensor data coming at you, You have only an instant to make a decision about whether to shut down something, for example.
But if you're shutting down your systems because of false positives, if you're getting data from a source that's been spoofed or corrupt, you're hurting your business in a situation where safety is not an issue, perhaps. So that's where the confidence analysis of data. And when I say confident, I mean measurably understanding a confidence score or knowing conclusively the source of the data and who's touched it along the journey can really help these safety critical or mission critical decisions that have to [00:27:00] happen on the far edge.
Bill Pfeifer: I love that idea of the confidence score because Even if you had a fully trained person standing there, they're almost never going to be absolutely 100 percent certain of exactly what's going on in a complex system. So it's always kind of, I'm 90 percent certain this is going to be a problem. We have to do something now.
So putting that into tracking the data and, you know, evaluating it with AI, the AI is going to be a certain percentage confident. The data is going to be a certain percentage reliable and combine all that together. You can start to set your thresholding. If it's a legitimate safety thing, then be very conservative.
If it's not, then be less conservative and don't destroy the business and, you know, things like that. So you can make really intelligent decisions based on those heuristics. That gives you a lot more power to run your AI and make decisions intelligently. That's really going to change the way we think about things, I think.
Steve Todd: And I think there's an [00:28:00] opportunity for this confidence score analysis to work in partnership with humans, right? For, for an inference algorithm to say, I'm seeing a condition that might cause me to shut this down, but I'm on, I'm on, I'm unclear as to the data source. There's some uncertainty or lack of confidence in the data that's preventing me from shutting down the system.
What should I do? As opposed to a fact where an inference algorithm may say, I'm a hundred percent confident in these inputs. And I know a hundred percent sure that I should shut down that machine over there right now. And the other thing I haven't mentioned, Bill, about a data confidence fabric, because it's backed by distributed ledgers, if an inference algorithm, for example, makes the wrong decision, you can go to the ledger and you can see the inputs, the decisions, and And the output, and you can not only audit [00:29:00] that if you're, if it's a highly regulatory environment, but you can also debug, maybe your inference algorithm is bad.
What caused it to do something that it shouldn't have done? So there's, there's additional benefits beyond trust, right? There's audibility after the fact. Again, because immutability is part of a distributed ledger value proposition.
Bill Pfeifer: Yeah. Yeah. That observability becomes critical. Why did you make that decision?
And yeah, maybe it was the wrong decision in the moment, but then you can refine it and fix it for the next time. But if you don't see that, then it's just a black box and random things happened and you can't trust the AI. And you have to pull it out or whatever. Right, right. Wow. So what do you see coming next?
I mean, at this point you're neck deep in Alvarium, I would imagine. And that's going to, that's going to continue. Your next big thing, is there something else that you're watching? Is it evolution of Alvarium and [00:30:00] adoption of it? What's next on your radar?
Steve Todd: So I would, I would use the word monetization or maybe data monetization to describe what's, what's next on my radar.
Interestingly, one of the reasons I got into studying blockchain and distributed ledgers was because I did this research project with University of California, San Diego, studying the value of data. Right? What is, what is the price or the dollar cost of a given data set or a database? And we work with all these enterprise companies, and all of them said, we'd love to know what the value of our data is, but we're too busy to look into that right now.
It's just so far down on our list of priorities that I began to say, all right, enterprises aren't necessarily interested in knowing the value of all their data sets. But when I saw the blockchain protocol and I noticed That [00:31:00] Bitcoin cryptocurrency was part of the protocol when a piece of data moved from one thing to another, right?
For example, a Bitcoin from one wallet to another. I began to understand that, you know, ledgers are not only this, can be this immutable, single source of truth, but they have this ability to carry value between entities. So, I believe that if you're using data confidence fabrics, for example, and you can bring your data to a data marketplace and say, buy this from me.
You can get more for your money if you can prove the origin, the ownership, the journey that that data traveled. If you have the providence of it that's provable to a third party. [00:32:00] Now you're talking about infinite number of data monetization possibilities for our customers who are generating so much data on the edge.
And looking for alternative avenues for monetization beyond just reducing risk or improving the operations of their manufacturing floor, for example. So I believe that that data monetization angle is inevitable, right? And that, that ledgers with their natural ability to move value from one wallet to another.
can facilitate that. And the corollary to that data monetization is the use of smart contracts to not only perform that transfer, but perform other actions based on trigger events that you see entering your ledger. So, for example, already we've, we've looked at Project Alvarium [00:33:00] and Alvarium's use of ledgers.
And can we insert smart contracts into this confidence score generation that pays people for providing, for example, trust as a service, right? Can a vendor come in like a telco or some other network operator that said, I'll give you the network and I'll provide a trusted, compliant environment for your data to flow across?
Thank you very much. But I'm going to be keeping track of what I do and bill you at the end of the month. Well, smart contracts. Enable that type of complex payments, which is very difficult to do in centralized environments.
Bill Pfeifer: Yeah, boy, that's going to be the granularity and detail that you could get to with that would be absolutely amazing.
I [00:34:00] could see that. Another thing that I know you've been doing some work with lately is the Hedera network. Can you talk a little bit about what that is, what that means?
Steve Todd: Sure. As Dell sells our infrastructure to our customers, whether it be servers, networks, storage, data protection, many of them are looking at Web3 or they're looking at deploying their own DLT node, right?
Their own, their own decentralized ledger. Or maybe joining something like in Ethereum and they're, they're coming to Dell and they're saying, can you help me architect this solution, whether it's writing a web three application, whether it's deploying a server that becomes a node and someone else's network for a ledger.
And we didn't have inside the company. A lot of experience ourselves [00:35:00] doing it. And so when we discovered this decentralized ledger, distributed ledger called Hedera, we found out that if you wanted to become part of the Governing Council, you needed to get a server up and running in your own company and have that server install the Hedera Hashgraph software.
And then join dozens of other servers around the world and actually operate that distributed ledger. And at the same time, a governing council members needed to create an application that ran on top of that network. So, it was a great opportunity for us to learn what are the pitfalls, what are the problems with Web3 technologies, distributed ledger technologies, Dell technologies.
We would need to allocate our own digital wallets inside the company for either paying or [00:36:00] receiving gas fees. As the Hedera network runs and how do you create these policies and manage these corporate wallets? So we've been, we've been doing that inside of Dell technologies for the last couple of years.
And as a result, when our customers come to us and ask about. How do our servers run under a distributed ledger load? How do you set it up from a security standpoint? How do you manage corporate wallets and how do you, how does that affect your balance sheet as you do your quarterly results? These are all the problems that now Dell has experience with because we are part of the Hedera Governing Council and it's really helped us help our customers.
Bill Pfeifer: Wow. So what does that become inside of Dell? How does that change Dell's operations or enhance operations? I mean, what does it do for the company itself? Sounds like a [00:37:00] lot of learning, which is fantastic. And, um, You know, helps Dell consult with customers and answer questions and understand things to build better technology, but what's the actual benefit for Dell for other customers as well?
Why would a customer, why would a typical company want to be directly a part of that network necessarily?
Steve Todd: You know, in addition to the learning, the fact that Dell is an infrastructure company, we really get the peek under the hood. And see the speeds and feeds and how our server performs based on the spikes of activity, because this is a public ledger, right?
Anybody in the world can write an application on this public ledger. We can really begin to understand how our servers handle the load. And are there things we can do? to speed up that process. Similarly, as the popularity of the Hedera network grows, the data [00:38:00] for the ledger is going to spill out and need additional storage somehow.
So we can now start to look at what are storage architectures that work with servers in distributed ledger contexts. And then finally, you know, Bill, another big learning is how do those ledger applications Interoperate and interact with your corporate systems of records. Right, so if I want to write some sort of application that does something on a public ledger but also leverages internal data, the crossing of those boundaries is a security analyst's nightmare.
However, if we can figure out how to do that in a safe and secure way, it could result in business advantage for Dell and then therefore our customers as we pass those learnings on to them.
Bill Pfeifer: So starting to filter the data based [00:39:00] on whether it can be shared, whether it's internal, sharing it internally, but not externally.
So that becomes integrated with security and compliance and policies and, Ooh, goodness. Okay.
Steve Todd: Right. And. And you know, when it comes to Dell internally beginning to write, let's say we want to join or form an ecosystem of partners that work together on a joint application that uses the Hedera distributed ledger, we'll know how to do that, right?
Because not only do, are we learning how to write DApps, right, for, for ledgers, but we also operate the ledger itself. It was just too good of an opportunity to pass up, you know, not only for the learnings that can help our customers, but internal benefits as well.
Bill Pfeifer: Wow. And again, the world becomes your data center.
Steve Todd: That's
Bill Pfeifer: the
Steve Todd: way it's shifting.
Bill Pfeifer: Yeah, that's, that's going to be tough to get, to get [00:40:00] heads wrapped around as we get more and more distributed. I, I wasn't thinking of. Trust as being such a blocker, but yeah, I can see that for monetizing data and for using AI out at the edge and making real decisions. and tracking those decisions.
And that just, I can see why you were looking at this as the next big thing. It looks like the next big thing. And you were ready to catch it perfectly on time. Hats off to you on that one. That's amazing.
Steve Todd: Yeah, I think, and we've written the first white paper that, that talks about that experience of implementing Hedera.
And we called it Bumpy Landing. Ha ha ha! Right? Bumpy landing, distributed ledgers in a centralized world. Because again, we're, a lot of the IT companies out there are still operating in centralized paradigms [00:41:00] and trying to bring in A server with this decentralized software running on it and getting it to interoperate is just a challenge for anybody's IT department around the world.
And so we've, we've documented the problems that we've found so far and published those learnings for people to look at in a white paper.
Bill Pfeifer: Okay. Bumpy landing. I'll have to look for that. I want to read that. I don't know if it'll be fun to read or not. We'll see. You're a nerd. You'll love it. Good stuff.
Good stuff. Wow. I could, I could talk about this stuff all day, but I think we've probably been at this for a good while. So Steve, how can people find you online, learn more about what you're up to, keep track of what you're up to next?
Steve Todd: So I have a public blog that I maintain and I write about things I'm interested in.
It's stevetod. typead. com and certainly my LinkedIn [00:42:00] profile as well are the two places that I tend to publish my external thoughts, whether they be blog posts, white papers, videos, you know, that's certainly been one of the benefits of social media for me. is when I do have ideas to bring them externally and meet people.
And the other, the other thing would be to get involved with Project Elverium. It's part of the Linux Foundation. It's in the LF Edge group. And that team meets every other week and is talking about the coolest topic ever, right? Data confidence fabrics and how to build them. So those are, those are two ways, I think, for people to get involved and learn more.
Bill Pfeifer: Yep. How to trust your data moving forward is going to be. A huge topic and being able to be in on that relatively on the ground floor would be an amazing opportunity. I agree. Well, thanks so much for spending the time with us. This was a fantastic conversation. I love it. I'm definitely thinking about data [00:43:00] trust differently than I was an hour ago.
It makes sense. The evolution from trust inside a data center to trust outside a data center. You make it sound so simple. Oh, that's all. That's an amazing journey. And I appreciate you, the time and the willingness to, to share your perspective. Thank you so much.
Steve Todd: Yeah. Thanks, Bill. I love the great questions and let's do it again.
Fantastic. I'd love to.
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