This episode of Over the Edge features an interview between Matt Trifiro and Mat Yarger, co-founder of DigitalMRV. At Digital MRV, Mat develops strategy and solutions around the use of data for environmental and energy systems. Mat describes how data can help us overcome climate change, what systems need updating, and the future we can work towards together.
This episode of Over the Edge features an interview between Matt Trifiro and Mat Yarger, co-founder of DigitalMRV. At Digital MRV, Mat develops strategy and solutions around the use of data for environmental and energy systems, including smart cities and critical infrastructure.
In this episode, Mat describes how data can help us overcome climate change, what systems need updating, and the future we can work towards together.
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“With data, there are just so many different things you can do. It applies to every sector as we're transitioning into digitization and automation. We see the huge uptick of AI right now and everything around that. But data security and trust in data is really paramount to building the right systems moving forward.”
“One area that was the most open to [new tech] because there is a high, high need for transparency right now, is climate. What I'm doing is still very tied to everything I've done in the past: like cybersecurity, protecting the data, compartmentalizing it, enabling trust in the data, those kinds of things. But the space that is the most ready to scale that out is climate and environmental impact.”
“The big problems are how we can take that analog process, and look at the standards that are out there. Let's digitize all those different standards, or pick the ones that have the most impact and progressively digitize them. How do we implement them into the facilities that are getting built or ready to transition and earn these carbon credits or new incentive models?”
“I'm sure you're familiar with the cyberpunk future of how things can go and Blade Runner and all that kind of stuff. But I think if we do this right, we've got this really cool solar punk future where it's super high tech, super futuristic, we've got trees growing on all of our buildings and we're sharing data, and I'm giving you energy from the energy that I'm creating from my solar panels, and it's just a really fluid utopian society like I know that's super optimistic and positive, but I think if we do it right and we get the right people involved and we don't step on the common person and their data, then it's achievable.”
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02:18 Mat’s journey into tech
05:27 How Mat got into his field
07:46 How tech ties into climate
09:45 The problems Mat’s trying to solve
12:57 What is the carbon market?
13:54 Circular emission tracking
14:52 Why data is useful
18:38 About Project Iota
24:48 About Project Alvarium
29:06 How Mat’s business was formed
35:17 What Mat sees for the future
37:30 The climate we’re striving for
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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 DellTechnologies.com/SimplifyYourEdge for more information or click on the link in the show notes.
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Connect with Mat Yarger on LinkedIn
[00:00:00] Narrator 1: Hello, and welcome to Over the Edge. This episode features an interview between Mat Trifiro and Matt Yarger, co-founder of Digital r v. At Digital M R v, Matt develops strategy and solutions around the use of data for environmental and energy systems. In this episode, Matt explains how data can help us overcome climate change.
And how his company keeps track of that data. He talks about the importance of digitizing systems that are currently analog. He also describes the climate future we can work towards together. Before we get into it, here's a brief word from our sponsors.
[00:00:39] Narrator 2: 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 that you can generate more value. Learn more by visiting Dell technologies.com/simplify your edge for more information, or click on the link in the show notes.
[00:01:06] Matt Trifiro: Two years ago when I started the Over the Edge podcast, it was all about Edge Computer. That's all anybody could talk about.
But since then I've realized the edge is part of a much larger revolution. That's why I'm pretty proud to be one of the founding leaders of a nonprofit organization called the Open Grid Alliance for oga. The OGA is all about incorporating the best of edge technologies across the entire spectrum of connectivity.
From the centralized data center to the end user devices, the open grid will span the globe and will improve performance and economics of new services like private, 5G and smart retail. If you want to be part of the open grid movement, I suggest you [00:01:40] start@opengridalliance.org. Where you can download the original Open Grid manifesto and learn about the organization's recent projects and activities, including the launch of its first innovation zone in Las Vegas, Nevada.
And now
[00:01:50] Narrator 1: please enjoy this interview between Matt Trifiro and Matt Yarger of digital r v.
[00:01:57] Matt Trifiro: Hey Matt, how you doing
[00:01:58] Mat Yarger: today? I'm doing all right. I'm ready to get my day rolling. So this is a good way to start it. Where are you coming from? I'm based outta Delaware right now.
[00:02:06] Matt Trifiro: Nice East Coast. So, you know, let's, let's just start early on, like how'd you get into technology?
Like what was the, what was the spark?
[00:02:14] Mat Yarger: So that's kind of interesting. When I was a kid, I had like no plans of getting into technology. I wasn't your typical, like I started coding when I was 11 and hacking video games and all that kind of stuff. Like you typically hear with guys in the space. My dad was a stone mason.
I worked out physical labor from 10 to 18, like building chimneys and stuff. But I was in ROTC in high school and my plan was, I'm gonna go to the Air Force and I'm gonna get out of this little town that has nothing going on, and I'm gonna be a pilot and I'm gonna go to college. And like that was my plan.
And then one day, you know, I graduate high school, it's been about three months. I'm ready to go do my thing. I'm driving to the closest Air Force recruiter, which is about two hours away from me. And then, My truck starts to overheat and my radiator is all messed up. And so I pull into a parking lot and I look up and there's an army recruiter and a marine recruiter, and I was like, well, crap.
Can't make it to the Air Force recruiter today. Let's go talk to these guys. I walk in and I talk to 'em and. They're like, yeah, we don't have anything flying unless you wanna be a crew chief, but we've got this cool job with the top secret [00:03:20] clearance and you get to go down to Florida for six months and learn a whole bunch of tech stuff and we don't really know what it does, but you get a $20,000 sign on bonus and coming from the middle of nowhere, I was like $20,000 in the top secret clearance.
Like, yeah, let's, let's do that. That sounds great. So, I had great scores. I got into that. I made it through the training and that was signals. I started learning about technology and how signals work and refraction and all that kind of stuff. And then I got up to Fort Mead in Maryland and my first job there was working in a network management center.
So I started talking to networking engineers and un I quickly progressed to be a system administrator. On the floor. And that's where I really started to dig into computers and, and just how it all works and transitioning legacy systems and managing data and like understanding all those interesting things.
Wow, that's
[00:04:10] Matt Trifiro: amazing. And what was the kind of work that did you, that you did? I. So that
[00:04:13] Mat Yarger: was, that was my job. I started, I went through the signals course and I was gonna be a signals analyst and then I quickly went into a technology focused position instead of a signals position. I volunteered for deployment, uh, went to Iraq while I was there, got to do some interesting night operations and picking up bad guys and all that kind of stuff.
And then I came back and I reenlisted for the cyber mos. It was the first Army reenlistment for the cyber mos. So I got to go through what is cyber mos. Cyber MOS is your military job. So like I was a cybersecurity analyst or a cyber analyst, and it's pretty much understanding everything about how networks operate, how data moves from one system to another, how you can take advantage of it, like what the single point of failures are, how to do man in the middle attacks.[00:05:00]
I had to do my c h net plus SEC plus, all that kind of stuff, and then go from there for another three to four years until I got out. Yeah,
[00:05:07] Matt Trifiro: really interesting. And you're now a founder of a company and we'll come back and talk about that in great detail, but to sort of foreshadow, it's a, a, a company that is working in carbon measurement and global warming.
So how did that transition happen? What, what got you into this field of work? So
[00:05:23] Mat Yarger: I did a lot of varied things around computer science and networking and data security, cyber operations planning, things like that help stand up cyber command in a lot of different capacities. So I got to touch a lot of different technological areas.
I got out and I did digital forensics for a little bit, and then I started researching blockchain. But the, the military and working for the government is where I got the bug of, like with data, there is just so many different things you can do. It applies to every sector As we're transitioning into digitization and automation, like we see the huge uptick of AI right now and everything around that.
But data security and trust and data is really paramount to building the right systems moving forward. I did that from a national perspective, and I was really impact focused on doing like operations that have a real tangible impact in people's lives. I did the digital forensics side as well, which is breaking the hardware and breaking into laptops and doing cases on, you know, child pornography rings and sex trafficking circles and all kinds of crazy stuff like that.
After about two years of that, like you're either cut out for it or you're not. And I decided it was not cut out for that because it's, it's really heavy after, after you get into it. And so then I started doing the research into the blockchain space and I figured out that, you know, 99% of them are like crypto and [00:06:40] token focus.
And that wasn't really interesting to me. I've never been like the FinTech kind of guy, but securing the data from like criminal cases and sharing data with. The FBI and local law enforcement and all that kind of stuff more effectively. I was like, there's gotta be a better way for us to do
[00:06:55] Matt Trifiro: this. Yeah, so chain of custody and authentication of the data and its source.
Yeah, it's just
[00:07:01] Mat Yarger: really, it's really hard to trust. People and organizations online because you don't have that face-to-face interaction anymore. And we have the technologies to solve those problems. Now it's just they're not where they need to be yet. And I think we made a lot of progress in the last five years with blockchain and how that can tie into that and like the real use cases for it and not just NFTs and, you know, cryptocurrencies.
But after my digital forensics time, I was with the Iotta Foundation for about four to five years. I just got out of there last fall and started my own company as you, as you mentioned earlier. And I got to work with smart cities. I got to work with mobility, social impact solutions. I got a lot of things with the UN and different governments around like social impact and how to use these technologies to impact people's lives.
And there's just so many barriers to getting it out and building like real products with it at scale, from regulatory perspectives or misunderstandings of the technology. But the one area that. Was the most open to it because there is a high, high need for transparency right now is climate. What I'm doing is still very tied to everything I've done in the past is still very like cybersecurity, protect the data, compartmentalize it, enable trust in the data, those kind of things.
But the space that is the most [00:08:20] ready. To scale that out is climate and environmental impact and understanding, you know, is this facility reducing emissions from entering the environment? Is this facility pro producing emissions? And how much are those? Because there's so many green washing conversations that happen right now where.
A company will say, Hey, we produced 2000 times of emissions of carbon emissions this year, and then it comes out that they actually produced 200,000 tons of carbon emissions because the data just wasn't there. It wasn't transparent, it wasn't reported properly, it wasn't managed properly. That's a solvable problem, and that's, there's a lot of money going into the climate sector to utilize new data solutions to solve those kinds of problems.
[00:08:59] Matt Trifiro: Yeah, that's interesting. And I, I imagine my guests might be wondering, well, okay, this is an interesting story, but where's the edge in here? And you mentioned facilities, that is the edge, like that's global. That's everywhere. That's the the factory, that's the, the farm, that's the everything. Mm-hmm. That may be having an impact on, on climate or carbon emissions or something like that.
So let's talk about some of the problems first. You mentioned like, well, you can't necessarily measure or you don't, can't trust the measurement. Let's talk about specifically in your line of work, what things do we need to measure? What do we need to measure them, and then what do we need to do to make it.
Useful and trustworthy. What are the problems and what are the, what are the ways we can start solving for that?
[00:09:40] Mat Yarger: Yeah, so there's a thousand different standards or methodologies as they call them out there for establishing how and what we measure. The un UN F C and the various UN organizations around climate change have standards there.
There's the carbon market standards like gold standard Vera, American Carbon [00:10:00] Registry, c a r. Those are the four predominant carbon market standards, and then there's other stakeholders in the ecosystem as well that verify it. But the process right now is just really, really analog and that's where a lot of the problem comes from.
It's not, you're seeing a lot of uptick in, you know, tokenizing carbon credits and those kind of things because people think the problem's, liquidity and bringing money into the market. That's not what the problem is though. The problem is there's a lot of money that wants to come into these solutions, but they don't know what solutions to put the money into.
And if we don't have the data to show the impact that these solutions make, then people aren't willing to put their money into them. So it's really a supply issue and not a liquidity issue. It's because the way that this happens, and the way these projects are verified and validated currently is they send a guy to the facility.
He's there for a few weeks with a clipboard. He walks around taking notes and taking pictures. He comes back and he writes a report, and then maybe a year later, if they're lucky, they get to start earning some credits for the impact they're making. Oftentimes it's 2, 3, 4, 5 years later that they finally get to start earning.
So that timeline of verifying the impact and them earning credits to like help make the technologies. Sustainable and operationally sound from just like a business perspective is really, really difficult, and it can be really, really expensive. So the big problems are how can we now. Take that analog process, look at the standards that are out there.
Let's digitize all those different standards, or pick the ones that have the most impact and progressively digitize them. And then how do we implement them into the facilities that are getting built or ready to transition and earn these carbon credits or, or new incentive [00:11:40] models. And a lot of that is integrating.
Edge capabilities or remote sensing capabilities, taking the data points into parameters that are already outlined in the standards and digitizing how they're monitored and collected, and automating as much of that reporting process as we can, and then providing some transparency around it. So we've got a facility in Chile that's a landfill.
It's a landfill gas facility, so they have big tarps over sections of the landfill that capture the methane and the carbon dioxide that comes out from the normal biological decomposition. And because they're capturing that, it reduces all those emissions from going into the atmosphere. They then use the methane and the carbon dioxide to actually produce energy, and that energy goes back to the local community.
So not only is it reducing emissions, it's enabling more proper management waste, and it's producing sustainable energy for the local community. So there's all kinds of benefits from this, but there's a very big barrier to getting that kind of knowledge and understanding out there, especially when everyone's focused on solar and wind.
Wow.
[00:12:42] Matt Trifiro: Yeah, that's really interesting. Um, there's a lot to unpack in there. Let's talk about some, some basic concepts that maybe not everybody understands or they may not understand completely. So you mentioned a carbon market, like what is that? Mm-hmm.
[00:12:52] Mat Yarger: So the carbon market is essentially, there's different ways to look at it.
The, the predominant focus of it right now is the offsetting market. There's a voluntary side and there's a compliance side. The compliance side is like the EPA saying, Hey, if you're producing emissions, you have to report those emissions. There's different scopes. There's scope one, two, and three. Scope One is your direct emissions.
Scope two is the emissions that come from the, the systems you're connected with. So like what kind of energy are you consuming? Where's the energy coming from? Right? And then scope three [00:13:20] is like, Based on products that you're selling. This is a, a really simplistic explanation. Mm-hmm. But it's a good way to understand it.
So if I'm selling products, what's the impact of those? If I'm selling laptops, you know, where are those laptops coming from? What's the impact? I have to power the factory,
[00:13:35] Matt Trifiro: then I have to put the silicon and the other stuff into the case. And all of that is, is creating waste or,
[00:13:41] Mat Yarger: uh, and then you gotta ship it out to the consumer.
And then what happens when they're done with it and they throw it away? Like, all that
[00:13:46] Matt Trifiro: data, the, the full costing of everything. Yeah.
[00:13:49] Mat Yarger: It's the full circular tracking of the emissions, not just your emissions from making the laptop or your emissions from powering the factory that produce the laptop, paying for the energy, but your emissions from ordering all the materials and shipping out the final product and understanding what your customer's doing with it, and if they're recycling it.
Do you have programs around that?
[00:14:08] Matt Trifiro: Wow. And I, and I can imagine if we actually had all that data in near real time. And accurate, the kinds of models we could build and the efficiencies we could pull out of the system.
[00:14:20] Mat Yarger: Mm-hmm. Yeah, exactly. It's just the, the data's not digitized and if it is, it's, it's a PDF that an auditor put together and submitted on an annual basis, but yeah, that, that's, you said that the guy
[00:14:31] Matt Trifiro: with the clipboard, you literally mean the guy with the clipboard in a pen.
Writing stuff down and maybe somebody enters it into Excel and then maybe some, and it's a pdf. Wow, okay. Yeah,
[00:14:42] Mat Yarger: it's all manual right now.
[00:14:44] Matt Trifiro: The whole process is manual. All right. And it's a lot of data. Okay. It's a ton of data.
[00:14:48] Mat Yarger: Okay. And if we can gather that data, Yeah, but not invalidate someone's privacy.
That's where my real like barrier comes in, is we need that kind of data, but I don't want [00:15:00] to know what you're doing with your laptop. I don't want to know where you're taking it. I don't wanna know what coffee shop you're working in to get the Scope three emissions. I don't. That's too much. There's, there's a line that we need to establish to say, this is the data we need, this is how we can acquire that data in real time.
This is who has authority over that data. So if it is, you know, coming from after I sell the product and it's your data, Then how do I get that data from you in a way that is still conscious of your privacy and things of that nature, or allow you to get some incentives for sharing that data with me. So that's where I think the really interesting part comes in is how do I incentivize you to share your data with me?
Maybe I give you a reduction on the cost of the laptop of 10, 15, 20% because you're allowing me to take specific data, and that data is something that I'm getting incentives for me as a product manufacturer. I'm getting carbon credits because I'm reducing the impact of the products that I'm selling and the way I'm verifying and reporting.
I'm reducing. That impact is taking data from the systems that you're using. So how can I incentivize you to share that, but still ensure I'm protecting your privacy? Wow. I'm
[00:16:06] Matt Trifiro: sort, I'm sort of, I've, I've, I'm actually speechless cuz that is, that is a very ambitious but clearly valuable thing to do. So let's, let's talk about simple things like collecting the data.
All right. So we don't, we don't want the guy with the clipboard doing the pdf, right? We need sensors. Right now my laptop has sensors in it, and so I can probably use those. My phone has sensors in it, but like the tarp in, in South America doesn't when you get sensors everywhere. How, how do we do that? And then, uh, maybe this will, will bridge nicely into some of the open source projects that you've worked on, project Iotta being, being one of the more interesting [00:16:40] ones.
Let's talk about the, the data collection and the IOT devices and how that all works. And then what, what Iotta does. Yeah,
[00:16:46] Mat Yarger: so I'll use the the landfill example again because it is a, a real example that we have gone through iterations on the landfill was established. They wanted to capture the methane.
They found a product supplier that had a TARP system that also had sensors and, and ways to process the methane that they captured. Cuz it's not just putting a tarp over it. Because if you put the tarp over it and the methane builds up, then eventually you've got a methane bomb. It's gonna explode.
Mm-hmm. You gotta do something with that methane. You gotta pull it out from under the tarp and you have to process it. So there's small industrial facilities at the landfill that get integrated. They can process. This methane and use it to create energy and fuel turbines and things of that nature. And those industrial systems are where the sensors come into place.
So there's pressure sensors, there's flow sensors, temperature sensors, composition, understanding how much of this is methane, how much is nitrogen, how much is car dioxide, and then how much of, like, where's the methane going? Are they just burning it off so that it doesn't enter the atmosphere and converting it to carbon dioxide.
Which is better but not optimal still? Or are they utilizing it for the energy consumption of the device on site and where's that energy going? With the landfill instance, we had about seven sensors that we actually needed, so we took an edge device. We sent it down to the, the location. We said, Hey, plug this up to your network.
We've already installed the necessary software on it. They plugged it up. Uh, we were able to connect to it. We updated anything that needed to be updated, and then we started to pull the data from those seven sensors from the existing SCADA system in place. And then we took the data, we locked it down [00:18:20] on the device, we encrypted it, and we put it on a ledger, a distributed ledger, which is where the Iotta side comes into play.
Okay, so tell
[00:18:26] Matt Trifiro: me about Project Iotta. Where, where did it come from? What problems was it trying to solve and what's the project look like today?
[00:18:33] Mat Yarger: So Iotta is an open source distributor ledger technology, and it focuses on real-time transactions with zero Bs. And this is what. Incentivized me to make that transition from US government to working for a German nonprofit.
It was a pretty big jump for me to go from, you know, cleared activities in that whole space to working for a company in a completely different country, completely remotely on technologies that are still being established. And so when I was doing my research, I looked into a lot of different technologies, but I said, if this doesn't have the ability to send a lot of data, At very minimal costs.
If it's not energy efficient in the way that it does that, I mean, if I can't just send data without having to use tokens and cryptocurrency, then it doesn't meet the needs that I see for solving these real problems. Iota was the only one I. That I saw that actually checked those boxes. I can send data in real time.
I can put data on the ledger. I can compartmentalize it with tools like Toyota Streams, which is essentially like a decentralized data stream, like an M Q T T, but on a ledger. Mm-hmm. And it has encryption and everything built into it. And then I can allow access to that data. Because it's on the ledger.
Anybody that connects to the ledger can pull that data as long as they know where to look. But if they don't know where to look, they would never see the data because it's all encrypted. You can't tell one message from another message or one data point from another data point because it just looks like encrypted [00:20:00] garble.
[00:20:00] Matt Trifiro: And so I'm gonna ask some really, really kind of intentionally naive questions because I think there's interesting answers in here. So when I think of. Crypto and ledgers. I do think about cryptocurrency, which has kind of had a bad, a bad name, but I think about like mining and energy waste. Right. And I also think about like the, the ledger being distributed, meaning it's hosted by a large number of people, so there's no single point of failure necessarily.
Like how does that actually work with Iota? Like how does all that come together in a, in a way that meets your needs?
[00:20:31] Mat Yarger: Yeah, so that's one of the things I found really endearing is that there are no miners with iotta. That was, uh, a point of like centralization from my perspective of a lot of the other protocols.
If you've got six or seven companies that are hosting all of the mining equipment, then you've got a big point of centralization and your decentralized protocol and kind of defeats the point from my perspective with Iotta there. Is no mining. There's only one kind of node and anybody can host it, so it's permissionless.
Anybody can contribute to the network. Anybody can add a node to the network to help decentralize where the data goes. There's hundreds of nodes that are on the network from hundreds of different sources, and you can run them on anything we've run. Nodes on S P 32 devices, so very, very lightweight devices.
We've got relationships with St. Micro, which are running node capabilities on their STM 32 s, which is like an enterprise variation of an S P 32, if you will. You can implement a node in pretty much anything, whether it be your cell phone, your pc, a laptop, a raspberry pie, and we run them effectively on those kind of devices.
So that was important for me because it shows that you don't need a lot of energy. To connect to the network [00:21:40] and anybody can do it. It's a really open and decentralized and permissionless approach from that when it comes to data. And then the other interesting aspect was there's the decoupling of.
Transactions and value. You don't have to send a token to send data across the network. With everything else, I had to send tokens and put the data in the token transaction. Mm-hmm. With iota, I can send a thousand data points and data transactions. And then that can incentivize the use case for a token.
So if it's negotiating energy between an electric vehicle and a charging station, the coupling of those devices can be the data transactions, and then the payment is where the token can come in. Yeah. So that gave me a lot more flexibility with the kind of solutions I saw in the future. And then it has this really interesting collaborative consensus model I call it, because.
It's, it's like a pay it forward system. When you publish a message onto the network, you have to verify two other messages, and that's how they get rid of the miners. Every time I publish a message or a data point, I verify two other data points that are on the network and then that just keeps growing and it helps us scale out.
So we've been able to achieve thousands of transactions a second with really low energy footprint with zero fees, and that's something I still haven't seen from any other protocol. That's
[00:22:54] Matt Trifiro: very high rate of transaction. That's, that's cool. So if, if I wanted to use the Theta capabilities as a private company or as a nonprofit, do I need to create my own network of nodes with people that are willing to contribute to my project?
Or is this just a giant community of everybody putting the nodes together and it can be used for anything?
[00:23:14] Mat Yarger: It is, um, a holistic protocol. It doesn't have a specific market that it's focusing on [00:23:20] anymore. It initially, it was focused on those iot use cases, and that's why it doesn't have minors, and that's why it was targeted for implementation in those kind of devices.
So anybody can contribute onto it When it comes to enterprise use cases, There's always a little bit of risk in new technologies, so I've always advised companies like start out with your own network so that you can learn the technology and you can understand what kind of data you wanna put on there, how you want that data to be managed, how you want to share it with other participants in your business ecosystem.
And then, If that's something you just need to scale out from a private implementation, you can do that really easily. Or if that's something you want to provide real transparency on and say, Hey look, here's our energy footprint. You can go onto this permissionless ledger and you can see the transactions that are showing our footprint.
Then you connect to the main net or the The open IODA ledger. Right? So I
[00:24:10] Matt Trifiro: could have a private ledger on my private nodes if I wanted to. I could use the public ledger or a combination of both, I imagine. Yeah. Yeah.
[00:24:16] Mat Yarger: Okay. You can run two nodes on one device and you can have secure IP data that you're sharing with various departments and businesses on the private ledger.
And then you can bridge that with applications in between that say this data from that network we want to publish on the main net. Yeah,
[00:24:32] Matt Trifiro: that's neat. Okay. Now, um, another project that is in this universe that you're in is Project Al. Can you tell us a little bit about that and how it released to Project Iota?
[00:24:41] Mat Yarger: Yeah, so Al's really interesting started discussions with Dell and Intel in late 2018 to early 2019 around data confidence. Uh, because once you can get the data on a public permissionless ledger and anybody can see the providence of [00:25:00] it, and anybody can see like where it's coming from, they can verify digital signatures on that data.
That provides a lot of interesting use cases. And so one use case that we started exploring was how do we actually quantify the confidence we have in that data once it's on the ledger? How do we know that data hasn't been manipulated? How do we know that the data is actually from the source and it isn't being impacted by a man in the middle attack or something like that?
And so with the Dell and Intel relationship, we started to figure out, well, There's the data that you put on, but then there's also annotations of what's happening to the data at the various points of the data supply chain. Because the IOTA ledger is as effective and efficient as it is, you can implement something that takes an annotation from a trusted execution environment where the data's produced.
You can then implement it into an edge routing like solution and say, this is where the data came from. We verified the signature on this router, and then we're going to publish it or send it to this edge processing device. The edge processing device thing can then create a log and saying, this is what we did to the data on this device.
We encrypted it, et cetera, and then we published it on the ledger. And so you can verify the full data trail as well. And that's where the data confidence came from. Because if you can say, I know where the data was produced, I know what kind of systems routed it. I know those systems were secure, they were encrypted at rest.
They didn't have open access to them. They had their security requirements updated. I know the edge processing and what happened to the data. So the data may or may not have been manipulated, but if it was, I know what manipulations were done to it. And then I know that. [00:26:40] At the cloud level, once this data gets to me, I can see, here's the data.
Here's everything that happened to it before it got here. I can trust it. And that's really what the data confidence Fabric or Project Alva, as it's now known, was focused on is let's track that data trail, let's create annotations along that data trail so that we can quantify the impact or quantify the trust and confidence we have in that data.
And then once applications like what we're seeing with iai advance on networks like this. Then, you know, the data that's going into this algorithm isn't gobbledygook or manipulated data or false information. It's something that can be verified, that can be trusted and has a high degree of confidence.
Yeah,
[00:27:20] Matt Trifiro: so you have the, the data itself, the payload, and then you have the audit trail of everything that it passed through and you could go and debug it or, you know, build up trust around it, or answer questions about it or improve it. That's really interesting. And Al is designed to use iota, like those are.
Projects that, that are tied together pretty tightly. At
[00:27:42] Mat Yarger: this point, yeah. So originally they tried with Ethereum and Hyperledger, but they couldn't put as much data on the ledgers because of the way that their consensus is structured. Hyperledger is a very permission system, so it's, it's great for business cases, but it doesn't go across ecosystems very well unless that Hyperledger instances.
Scaled out into those different ecosystems, if that makes sense. And then Ethereum has the token requirements. So you have to send tokens to send data. And so what often happened with Al and the Ethereum environment is they had to batch all those annotations into one [00:28:20] hash. And so there's a hash that would then go with the token use case on the Ethereum ledger.
So it was really limiting the transparency and availability of the data that came from the ovarian implementation. But with Iotta, since we have, you know, all those different data functionalities and then the token capability, they could just send the data over the ledger or secure the data over the ledger and allow easier access to it.
So it really opened up the flexibility of it.
[00:28:44] Matt Trifiro: Yeah. So now you've, you've taken these technologies. You've identified, as you said, something that has a real impact and you've created a business around it. Can you tell us how the business got formed? This is a digital mrv. Tell us how it got formed, what state you're at, and what problem you're trying to solve.
[00:28:58] Mat Yarger: The digital M r V side of things, digital, Mr. V means digital monitoring, reporting, and verification. That's where the R V comes from and the MV process was. The analog climate process that we kind of went through earlier. Mm-hmm. And the digital M R V process is the initiative to digitize the analog process.
So we're working closely with Gold Standard, which is one of the leading carbon market standards that I mentioned. We had those two initial pilots. One was a landfill, one was an anaerobic bio digester, which is essentially like an industrial composting facility, if you will. That's not moving the compost.
It's just letting the bio digestion happen naturally. And so we got all the data from those facilities and then we were like, well, the carbon market standards and the compliance markets and everything don't have the infrastructure for us to actually send this data to them. So what are we gonna do now?
And so with the digital MRV side, we've been working with Gold Standard. We have what we call the open collaboration on Digitizing for Impact. And we have 70 [00:30:00] plus members in that. We had a few hundred applications, but we. Constricted it down to 70 plus members spread in three working groups. One is the Digital MRV Working Group, which is establishing standards and guidance on digitizing mrv and digitizing the verification of the data and the MRV process.
The second is the digital infrastructure group. So what APIs do we need once we have this kind of data in these facilities, and how do we connect it to. The registries so that these facilities can more seamlessly earn carbon credits. And then the third is a tokenization working group, which is where does the crypto side and potentially NFTs and all that actually come to play because the, there was a huge issue with the carbon markets where a bunch of crypto companies came out and started tokenizing carbon credits.
And then it, it turned out that the carbon credits they were tokenizing were not high quality carbon credits. And that goes back to the whole confidence and quality issue. And so all the carbon market standards were like, Absolutely not. You cannot tokenize carbon credits anymore, but they see blockchain and tokenization has use cases.
They're just trying to establish guidance on what the right use cases are and then how to use those technologies for the market. The new entity is focused on taking the data from these facilities and solving that supply problem and establishing standards around data confidence so that we can quantify.
The confidence we have before these things are certified and before the creation of carbon credits. And if we can scale that out across the infrastructure of waste facilities or energy facilities, waste water, solar, a number of other implementations, then that helps combat a lot of the green washing concerns and then helps the entire market scale up.
So [00:31:40] we're really trying to focus on that data problem, establishing that quantification and confidence and trust in the data and the process and helping. Bridge all the liquidity that's out there to come into these kind of projects. So we're working with project developers, methodology developers, and trying to really scale out how these solutions are digitized.
[00:31:58] Matt Trifiro: This is a for-profit company? Yeah. This will be a
[00:32:00] Mat Yarger: for-profit US-based entity. And how will it make money? The data side is a protocol. So we're taking an iot ledger type implementation. We're essentially using it as a single source of truth. So every facility we connect to puts its data on this ledger, and then that data lives on the ledger.
And if that facility or project developer or owner wants to share that data, they can, but we have access to it so that we can help them use it for carbon credits and other incentives so we can take a percentage of whatever that entity earned through. What we're trying to enable for them. And so it operates as a software, as a service, essentially.
We have the platform that we're scaling out, we implement it into the facilities. The facility managers can look and say, okay, here's our emissions and these are issues that we're coming up with and we're scaling features around that kind of product. And then we're taking their data and we're implementing it into the voluntary carbon market as first step, but eventually we'd like to implement it into the compliance market, which is, you know, how does the EPA then get this data?
And then how can organizations and facilities say, this is our footprint based on regulatory requirements
[00:33:01] Matt Trifiro: as well? Right. So I, I've got this huge difficult problem of proving that I'm in compliance and a bunch of guys with clipboards writing PDFs to do it or mm-hmm. I have this monetization opportunity where I can enter my carbon credits into the market and get paid for them or compensated for them, but they're, they're locked in these old [00:33:20] systems and you're just making it digital and, and software based.
[00:33:24] Mat Yarger: Yeah, I'm trying to create that full digital pipeline and make it as seamless as possible. I look at it as, as a data logistics. So if you have a product and you want to ship it and you open up an Amazon marketplace, like Web Front, then you send your products to Amazon and they handle all the logistics of your products for you.
Mm-hmm. You just send it to their warehouse and they manage getting it to the customer. Right? That's essentially what we want to do, but with data, we want to get all your data, send it to us as a warehouse, and we'll get it out to all the different customers that want to use your data or access it, whether it's carbon credits, whether it's regulatory requirements, or whether you just want to see if we can monetize that data for you because they're, once you get this level of digitization, it's not just card and
[00:34:05] Matt Trifiro: credits.
Yeah, I was gonna say, this could apply to, to everything. From how, how many electric cars are on the road? Creating demand for my charging station or, mm-hmm. I mean, any, any sort of data that, you know, maybe today is not easy to share or is not comfortably shared because there's trust issues or I, I need anonymization issues.
You mentioned privacy early on. Wow. It's a, that's a, that's a big, how big is your team?
[00:34:31] Mat Yarger: Right now it's less than 10. Okay. It's a small team.
[00:34:34] Matt Trifiro: All right. Are you, how are, how are you
[00:34:35] Mat Yarger: funded? We're going through the, the final stages right now. We've got some angel investors lining up, so we're actually going through our initial raise right now.
But everything that we have up to this point is self-funded or grant
[00:34:46] Matt Trifiro: funded. That's really cool. That's really cool. Okay. Let's talk about the future of all the sort of new technologies that are out there that could help. Your cause, which is to make, let's say climate [00:35:00] data more accessible and more useful to have this impact on the planet.
What are the technologies that excite you the most?
[00:35:06] Mat Yarger: Hmm, that's a good question. You know, it's really interesting because this, the, the digitization in this industry is so nascent. There's a lot of like interesting new technologies, but I don't think we're at a point where we can use them in the near future.
Like there's. Machine learning is something that's really easy, helps the data processing. That's something that we've gotta implement in these facilities. It just helps the efficiency, like zero trust architectures and from a security perspective, I think are exciting. And how do you secure the data and all that kind of stuff.
I love what I'm seeing with the chat GPTs and the auto GPTs and the open AI type of stuff, but I'm worried about how open that access is. And so with my data, Perspective. I'm a big fan of contextually defined networks, and that's essentially what this is. This protocol is a context defined network. It's a network that only shares environmental data, and so I'm hoping that, you know, three to five years from now, we've got a.
A thousand different facilities connected to this network, putting data onto it. And then we can take a chat g p t kind of model and put it on that data in a context define network. So there's, there's barriers to where the algorithm can access data from. And it's only focused on environmental data. It's not getting any lead in from other types of data sources that aren't relevant.
It's all high trust, high quality data. And then we can say, look, if you implement this kind of. Facility in this area, it's gonna reduce the emissions from this cause and that's gonna have this kind of impact on the local community. So I think just figuring out how to pull those extrapolations from the data is gonna [00:36:40] be the most exciting thing.
And utilizing some of these, like chat, he PT type of solutions on that is gonna be really, really exciting. Yeah,
[00:36:48] Matt Trifiro: I can even imagine like third parties developing. Data analysis or manipulation services that aren't the absolutely consumer or the creator, but they're like, look, we can attach to your data in a way that's trusted and anonymous and will annotate the ledger and all that, and we'll do this like magic to it, either categorizing it or counting it or whatever you do.
And I could sign up for those data manipulation services. That's a, yeah. Wow. It's fascinating when you think about. Like making all that data available and thinking about, mm-hmm. Lowering the barrier to building services like that, that either consume or manipulate the data. Yeah. Yeah. Like
[00:37:22] Mat Yarger: I'm sure you're familiar with like the cyber punk future of how things can go and the Blade Runner and all that kind of stuff.
But I think if we do this right, we've got this really cool solar punk future where it's. Super high tech, super futuristic. We've got trees growing on all of our buildings and we're sharing data and I'm giving you energy from the energy that I'm creating for my solar panels, and it's just a really fluid utopian society.
Like I know that's super optimistic and and positive, but I think if we do it right and we get the right people involved and we. Don't step on the common person in their data, then it's achievable. I get nerdy and, and super. Yeah, no, no, I
[00:38:01] Matt Trifiro: love it. I love it. No, no, I, your, your passion is
[00:38:03] Mat Yarger: very infectious. The, the immediate one is certifying projects because that's how they earn carbon credits and the carbon market standards certify projects.
So Gold standard will certify a project and say, This project is something that we trust. [00:38:20] It has the right impact, and you can invest in it by buying carving credits that come from it. If you have a company and you're producing a lot of emissions and the technology to, to solve that is just not achievable right now.
But you look at all these other options coming in, you know, the global south, whether it's landfill gas or biodigesters or solar or whatever, and you say, I can put a thousand dollars into this and it's gonna create 10 times more impact than if I put a thousand dollars into reducing my own emissions. I think certifying those kind of projects and allowing companies that are creating emissions that wanna find ways to invest in new technologies to offset those emissions is.
Where the big focus is right now. So what's slow us down in certification? It's the big analog process, and there's just like too many people that have to come in and provide oversight at this point. So if we can reduce the number of people that need to provide oversight over facility by digitizing that pipeline as much as possible, and we can push the carbon market standards to accept and certify these more readily because they are digitized, and I think that opens up a multi-billion dollar like opportunity in the industry.
Yeah, that's great.
[00:39:29] Matt Trifiro: Hey Matt, this has been a fascinating interview. I'm really excited about your new company. I wish you the best. If people wanna find out about Digital mrv or wanna reach out to you, how, how can they find you and your company Online? Digital
[00:39:43] Mat Yarger: r v, we use Twitter and LinkedIn pretty proficiently.
I'm pretty, pretty active on Twitter as my preferred social media platform, so you can follow me there. My dms are open if you have any opportunities or. You just want to talk about it or, or what have you. I'm, I'm always open to do that with people and as you said, I can [00:40:00] be kind of infectious at times, so I like to get people excited about new things that can create a real impact.
You wanna have you
[00:40:06] Matt Trifiro: back in a year and find out what's happened.
[00:40:08] Mat Yarger: Yeah, hope, hopefully we, we've made some really big strides. We got a lot of, uh, points on our roadmap and a lot of milestones to achieve over the next 12 months, so hopefully we can accelerate and, and get it done. Awesome.
[00:40:19] Matt Trifiro: Well thank you Dean for being on the show.
It's been a great conversation.
[00:40:21] Mat Yarger: Yeah, it's been great. I appreciate it.
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