Building the Foundation of The Spatial Web, with VERSES founder Gabriel Rene

The web page is a deceptively simple invention, but its creation -- and more importantly, its cross-programmability -- made the World Wide Web the technological powerhouse it has become. Gabriel Rene founded VERSES to encourage similar similar developments in spacial computing.
Alan: Today's guest is Gabriel Rene, an architect and founder of The VERSES Foundation. He's a technologist, entrepreneur, researcher, media and music producer, whose 25-year career in the technology, telecom and entertainment industry has granted him the knowledge and experience to consistently invent unique business verticals, and to navigate the novel challenges of the emerging global digital entertainment, marketing, e-com, mobile and spatial technology markets. aAs a deep technology pioneer, mobile executive, and corporate strategist, Gabriel has built multiple innovative technology companies, developed groundbreaking enterprise and consumer software, and forged strategic partnerships with multiple Fortune 50 companies. Rene has worked with -- and advised some of -- the world's largest brands, spanning media conglomerates, telcos, media manufacturers, mobile manufacturers, governments, and major brands. As a C-level executive founder, he has demonstrated unique leadership, strategic and operational capabilities in growing businesses from zero to $25-million in annual revenues. As an advisor and board member, he has helped multiple startups and founders navigate their way to success. Gabriel serves as the executive director of the VERSES Foundation, an organization at the intersection of Block Chain, Virtual Reality, and Artificial Intelligence technologies designed to power Web 3.0 and dedicated to the interoperable adoption of spatial technologies across every major industry. As the founder and executive director of VERSES, the Global Advisory Board Member and co-chair of the AR Cloud Committee, and a founding member of the Open AR Cloud. With that, I want to welcome Gabriel Rene. Thank you for joining us on the show.
Gabriel: Thank you, Alan. It's a pleasure to be here.
Alan: Where can people find you online if they want to look into it?
Gabriel: Well, if it's me personally, you can find me @GabrielRene at LinkedIn, and you can also find me on Twitter under the same name. And then with VERSES, you can go to VERSES.io to get all the latest information on us.
Alan: So let's unpack this. Tell me what you're doing at VERSES right now, and I want to get the full understanding of what is VERSES, and why it's important for people listening.
Gabriel: So I guess the first place to start is way back in 1990 or so. There was a young, talented researcher by the name of Tim Berners-Lee, who was working at the CERN Institute, and he was developing a new set of technologies which have come to be known as the World Wide Web protocols. So those are all the HTTP, which was hypertext transfer protocol, and HTML, which is a hypertext markup language. That, combined with a browser, which he developed as an open source standard, and on top of the domain structure that had been pre-existing -- which we'd been using from the email era of .coms and .edu, .org, etc. -- he created this you URL format, which essentially made pages programmable, gave us the ability to link content on those pages, and the ability to network those pages. This, of course, became the World Wide Web.
The majority of our technologies and power and advantages and capability today, whether in business or personal lives, in public or private sector, come from the benefits of these core protocols that enable the network. But it's fundamentally a network of pages and text and media. And now, with the dawn of new interfaces that come with XR technologies -- particularly augmented reality for the real world, or more for the physical world, and VR more for a digital world -- we need a new set of protocols that enable us to essentially, instead of creating web pages, create web spaces; a programming language for spaces, if you will. We need a way to connect those spaces, so we can teleport objects, content, and information between them, much like we do with links and media content today on the web, which we call hyperspace transfer protocol, or HSTP. Our nonprofit Foundation is developing and maintaining these open source spatial domain and protocol standards, and using them to connect all of the various emerging technologies that we feel are part of this Web 3.0 architecture, which we call the spatial web.
Alan: All right. So... you used a lot of terminology there. Let's break it down for people. What would a use case be for a business to use the spatial web?
Gabriel: It's it's one of the hardest questions to ask, because--
Alan: I'm full of the hard questions, my friend. This is not a podcast for amateurs; you are a professional in the space. If anybody can explain it, I have faith in you, my friend.
Gabriel: Well, if we're talking about XR for business, let's talk about the long term value of XR as opposed to the value today. We'll certainly circle back around and talk about the practicalities, the importance of certain applications today, but let's talk about the long term benefits.
Alan: Love it.
Gabriel: So, when we think about spatial technologies as they relate to business, just like the web technologies of today or the Internet technology we've been using for a while, they give us the advantage of something we call network effects. Network effects are the ability to connect to other parties, whether that's inside our organizations or outside of our organizations; across many different spheres. The power of those communication technologies come by virtue of a protocol, and protocols are basically just a recipe -- or format -- for coming up with some sort of structure for how parties can communicate. So, the idea that spatial computing itself is a new form of computer; at one point, we used to drive horses and carriages around, and then the emergence of the automobile came about. But the roads were still mud and dirt roads. So it's really difficult to actually get from Point A to Point B with a car. When the ability to create standardized cement and asphalt roads emerged, that sort of format and standard for that enabled cars to then navigate between Point A and Point B very, very quickly.
Obviously, this transformed things, like our mail service and our messaging service; our postal service. The basis for protocols -- whether they're roads for cars, whether they're are cables for electricity, whether it's the Internet and web protocols that we use today -- create an effect where we're able to network and communicate with each other at scale. So specifically, as it relates to augmented and virtual reality content; today, there is no ability for you to send me an augmented reality object -- let's say an architectural diagram. You and I cannot collaborate with it from two different parts of the world in VR without being in the same app. Furthermore, we can't then teleport it to, say, the boss's corner office of his twenty-third-floor building in New York. Because there is no spatial address for that location. So what you need to be able to do is, for any form of network, you need to have a standard for an address, whether that's a home address, whether it's a telephone number, or radio number, or what we call web addresses. We create spatial addresses that suddenly allow you to teleport objects and information. Now, the other thing that's critically important is--
Alan: Just, sorry, just to interject for one second. This isn't just an address of a street. This is three dimensional.
Gabriel: Correct.
Alan: So this could be a space in the air.
Gabriel: Yeah. So, imagine a spatial coordinate. That would be a three-dimensional point in space. If I want to get to a building, I can follow the roads and it can get me from Point A to Point B, but it's essentially a two dimensional map that I'm using. If I want to get something to someone in a particular location in space, I don't have a digital address for that. And so part of what VERSES does is it makes that address available, and then makes it so that a physical building or location can be part of what we would call a "spatial domain," and a spatial domain is just like a web domain today. If you have control over that domain, then you get to control the rights and permissions within that space, as it relates to digital content, digital information, and even robotics and other IoT devices.
Alan: Everybody would have to buy into this.
Gabriel: That's correct. The ultimate value here is, how do you create standard methodology and format for interactions in space, whether it's for a human or for a robot? And then how do you create rights and permissions that can become standardized with respect to how content can be accessed in a space as opposed to a page.
Alan: I just want to give people a picture of this. This actually came up in a conversation around the legal aspects of augmented reality and how Burger King recently did a marketing campaign where you could take your phone and point their app at McDonald's or the competitor ad, and it would catch on fire in AR and then give you a coupon or something. But then the legal question came of, well, who owns the digital space around that billboard, or around that poster?
Gabriel: Yeah.
Alan: This is exactly what you're talking about; being able to identify digital space in three dimensions, and apply it or assign it to somebody.
Gabriel: Yeah, exactly. So, there's two levels. One is kind of around rights and permissions and policy around what we might call spatial content. But again, imagine spatial content is really digital information in space; information of what a drone can do, or an automated vehicle or a robot, is actually also information in space. So, you can control the flight path of drones, or where automated cars can and cannot park, or whether charges need to occur if they go from Point A to Point B. The same functionality enables a user to not just have a permissions-based restrictions, but really, what they're supposed to do. The ability to have field workers across any industry -- construction, warehouses, logistics, etc. -- actually follow digital information as, like, arrows in space that might route them. For example, in a warehouse, instead of a pick-and-pack worker looking at a nine-digit code on their screen and trying to find that box in space, you can actually just have a marker right on the box itself. They can look through an iPhone -- which uses ARKit now -- or a Magic Leap headset, or a Microsoft Hololens headset or the other smart glasses that'll be coming, and that worker now can just follow that arrow right to that location, pick that object, and move it from Point A to Point B from, let's say, the pick-and-pack area to the dock, and then registering that interaction back into the warehouse management system. But interestingly enough, it also allows you to walk into a retail location, be identified spatially, pick up a 7Up can, and walk out of the location and have it trigger and transaction. This same functionality enables all kinds of different use cases.
Alan: Indeed; this is some deep stuff, here. This really will impact everything we do.
Gabriel: Yes, in the same way that the web technologies really transformed our world. I mean, you could look at it as the power of computing on one level -- spatial computing -- but on the other level, you need to look at the power of networks, which would be spatial networking. So in one sense, we often tend to look through the lens of computers. We go back and we look at the PC Revolution, which was incredibly powerful. But it really wasn't until those became connected to other networks, like the World Wide Web or like the Internet, that we got these network effects, where we add value to each other by virtue of our our ability to communicate and share. That's where we are right now.
Spatial computing is just creating the PCs of this spatial web era. But in order to get a spatial web, we need a way to have a spatial network protocol, much like the World Wide Web protocols or the Internet protocols that are designed for three dimensional space, that are designed with the sort of rights and permissions that deal with privacy and security issues that we're lacking in Web 2.0, that will then get us the most benefit from the Internet of Things. And from AI, and edge computing and spatial transactions and all these other wonderful sci-fi functions that we'd like to have.
Alan: Sounds like a very, very good use case for the block chain.
Gabriel: It is. In the Internet of Things sort of industry 4.0 narrative, which Deloitte and McKinsey and Gartner and Accenture and others are really promoting as this key era of digital transformation for all businesses. They refer to something called a digital twin. Are you familiar with this term?
Alan: Actually, I am. We actually had the head of VR for Shell on today, and we were talking about digital twins of oil rigs; how it will create a digital twin in order to test, what if we have to replace this big piece of machinery? They create a digital twin, and they'll remove it digitally and say, "oh, okay, well, it fits coming out, but the new one going in is going to hit these pipes." Doing that digitally, allowed them to pre-visualize that. That was one of the use cases that came up today in the conversation. So, maybe you can unpack it a bit.
Gabriel: Digital twin is essentially a three-dimensional visualization of a physical world thing or location, and may contain the processes involved in it. For example, the most traditional use is you have a number of sensors on something, let's say an engine in a car. Those sensors, then, are giving you information about temperature and speed and potentially the amount of fluids. And right now we look at like a dashboard or sort of dials and numbers. A digital twin of that would actually just show the engine. We'd see that information projected into the engine: "Oh, the engine's getting hot, but it's one particular area that's getting hot. In fact, it's one part that's getting hot." Now that lets you as the owner, or even a third party, be able to access that information, whether it's in a test environment inside of Toyota, or if it's in a maintenance capacity. Suddenly you've got this three-dimensional visualization that you can think of as a real time soft copy of a physical thing. Not to go too far out, but with these concepts of the AR Cloud where you have a digital twin of everything and everyone in the world -- where you've got essentially a real time soft copy of the world in three-dimensions, right? Sort of a three-dimensional mesh of everything, or as Charlie Fink likes to say, "painting the world with data." The problem about thinking of it through this lens of visualization or projection technologies only, is that it turns out a lot of really important information is tied to our physical environment.
For example, that engine. The question really becomes, "am I looking at the right engine or is this the copy?" The data associated with the identity of that part: is it accurate? And who should have permissions, or the ability to access that information? Who can move it? Who can update it? Who can share it? Block chain becomes a very powerful -- or, let's call it distributed ledger technologies, which includes block chain, but also includes several other approaches to what we call a trusted data layer for the spatial web -- it becomes a real requirement in certain cases where you want to have proof that the history of the information associated with that digital twin has a unique, verifiable I.D., all of the behaviors and activities around it can be permissioned and rights can be associated with it, and even transactions can be attached to it using crypto currencies or other form of digital payments. Block chains takes digital twins and turns them into smart twins; they become smart assets and digital twins sort of merging together. Now you've got verifiable data, and this becomes very critical when we start to look at industrial environments or high-transactional environments. We want to rely on those data sets. And it also allows them to be shareable. Now you've got a single source of truth for the data around this three-dimensional object.
Alan: Very interesting. If we're looking at these digital twins of things in the world, for example -- and I make this comment when I do speaking engagements -- that every single thing in the world is going to need a digital version of it. Like, everything. From a pair shoes, to a coffeemaker, to everything. Everything will have a 3D version of it. One of the things that we've been working on is content management, or digital asset management system, for retailers to deal with the fact that every product that they sell is going to need to be shown in 3D. So, how do you impress upon people that this is coming in? And what are the timelines around this? Is this something that's 20 years out, or is this something that -- I know from my theories, but I would love to hear your idea of when do you think this is going to be something that every company needs?
Gabriel: Well, I would say that right now, if you're a company that deals with the physical activity of people moving objects in three dimensional space, whether this is in a warehouse, whether this is in a retail environment, whether this is a supply chain, you can begin -- and should begin -- using these technologies immediately. The test that we've been doing here in Los Angeles in some local warehouses, where we're able to create these spatial workflows, tasking and routing functionality, practically doubles the amount of time it takes for even a seasoned to pick-and-pack worker to be able to do X number of picks in a given day. That's with holding a phone with one hand. So, as we begin to work with Magic Leap and Hololens and some of these others, and you're able to do hands-free, and the headsets become able to be worn for longer periods, et cetera, et cetera, we expect that to increase over time. But right now, today, those kinds of advantages exist. There are other companies, you know, working on spatial visualization.
Alan: One of the things I saw at AWE -- actually, I think it was two years ago -- was a company that helped pick-and-pack workers to better stack and pack a pallet. And it sounds very trivial, but you consider; pallets go in the back of trucks, and if they're not completely full, you're wasting a lot of volume space. And if they're not packed efficiently... nobody's going to unpack a pallet just to make sure that, you know, an extra box could fit on there. But if you could look at the pallet and see digitally where the best angle of the boxes or items would be to maximize that space, we could save a lot of transportation costs.
Gabriel: This is exactly what you were just talking about earlier with the digital twin... was it an oil plant or oil rig.
Alan: Yeah, an oil rig.
Gabriel: Yeah. So they were running a simulation inside of a digital twin of, "we want to move this object from here to here. What's easiest path, or how will it fit?" It's the exact same spatial question as, "where should these boxes go and in what order?" It's really the gamification of reality. The difference in that case is, you're projecting that information into the physical world and using it as a way to actually fulfill the workflow or the activity, which is really profound, when you realize the implications of this across any physical activity.
Alan: It's crazy that this can be used for moving a $100-million manufacturing machine--.
Gabriel: That's right.
Alan: --or a $10 box. And the value is still there, because there's a value across every single part of the enterprise.
Gabriel: That's right. And what's also fascinating is that this reduces error rates to near zero, because -- provided your data is accurate -- there is just no excuse for picking the wrong box. Right? I think Ori Inbar has made some suggestions about the benefits of the AR Cloud as adding trillions of dollars to the global economy over the next several decades. I actually think he's wrong. I think he's off by a significant exponential margin, because when you start to add the benefits and the functionality of those activities, and then you start to make those activities themselves transactional, it's probably an entirely new era. You know, we did go from 10-trillion dollars in the 1950s global GDP -- about when digital transformation started -- to nearly 100-trillion now, in about 70 years. You can see over the next two or three decades, there is a likelihood of even an accelerated, exponential growth of GDP. Of course, I think a lot of us would like to see global markers for health beyond mere economic numbers, but that certainly would help.
Alan: It would be great if we could -- I explained to you my mission, to inspire and educate future leaders to think in a socially, economically and environmentally-sustainable way. It's taken me decades to articulate that one specific mission, because businesses are measured by one measure only, and that's profitability. We need to start thinking about, how do we compensate businesses for the social, environmental and economic aspects of their business? And in equal thirds, because without the environmental sustainability, we're all going to die anyway. And if we don't have the social responsibility of it, then what's the point of creating these efficiencies if it's just going to make people be unemployed, and we have no economy, nobody can spend any money anyway? So, we really have to think of all three together, and we need to -- I don't know how -- but we need to somehow change the way we measure the value of companies. And I think, yeah... I don't know how to get there yet, but I think it's true education of the next generations, in my opinion.
Gabriel: Oh, that is clearly a critical part, and thank you, for your dedication to that aspect of it, Alan. You know, it's hard to ignore that today is Earth Day. As we sit here, we're faced with an existential threat that a certain proportion of the population is able to acknowledge, and another portion is simply ignoring. And sadly, too few of our leaders fall into that second camp. You said a sentence that we use a lot at VERSES, which is kind of a famous quote from Peter Drucker, which is that we can't manage what we can't measure. So the power of spatial computing technologies is that we begin to measure -- I want to make a quick statement here. Sometimes when I say spatial, I don't mean just XR. IoT is providing spatial information. All of the--
Alan: Spacial audio; being able to walk down the street and have audio cues guide you. It can be sent.
Gabriel: That's right. And even the ability to just do an Amazon Go-like transaction is actually a spatial transaction. So, spacial is the trend of the entire industry 4.0 era. I mean, you can even see the term as it relates to edge compute or ubiquitous AI, or decentralized distributed computing blocking. Obviously, the spatial computing aspect of XR. But but the important part I'd like to note is that as we're using all of those technologies, now we're able to measure in reliable ways where we can trust the data, what's taking place in the world. So whether you start to look at mining facilities and doing Lidar scans of mining facilities, and able to then have that information be available, shareable, even the information that will come from the apps of the future become our appliances. Right?
Alan: I got to stop you for one second, because you mentioned mining, and we've worked with some of the biggest mining companies in the world. Michelle Ash used to be the head of innovation for Barrick Gold. And in one of her talks -- this is one of the reasons why we started working with them -- she mentioned something about the accuracy of being able to take the measurements; so, they drill down and they take core samples. Within a very good margin, they know how much gold is in a certain area of land. She mentioned, maybe in the near future, being able to just know that information and visualize it in spatial computing ways to show investors, here's where the gold is; the safest place to store that gold is in the ground. So, let's not dig one ton of rock out for every gram of gold, and let's focus on keeping it where it is -- it's safe there, we know where it is when we need it -- but really, does the world -- as humanity -- do we as people need more gold dug out of the ground?
The answer is no, we don't. We have tons and tons of gold sitting in storage lockers that can be used for industrial applications, or jewelry or whatever. We don't need to dig more out. If we can fundamentally use spatial computing and spatial visualization for investing in things that we don't actually need to dig out of the ground, I thought that was a really unique way to position it.
Gabriel: Absolutely. Who did you say that you spoke with? Was that at Barrick?
Alan: Yeah, Barrick Gold. Michelle Ash.
Gabriel: I don't know if it was Michelle, but I was speaking at an event last year that XPRIZE and Peter Diamandis was doing with Deloitte. I spoke to someone from Barrick about the exact same thing.
Alan: That would've been Michelle for sure.
Gabriel: Yeah. Michelle Ash, is that it?
Alan: Yep.
Gabriel: But what's fascinating about that is, the other thing that you need there is you really then need distributed ledger technology to validate the numbers. The goal.
Alan: Yep.
Gabriel: But there's kind of two levels of validation there. Show me the spatial thing; show me where exactly we're talking about. Then give me the data and way that I know has been tampered with. So, you can see that the two together become really powerful ways of rethinking about what we extract, how we extract it, and how we use it. And over time, as we begin to use personal IoT sensors and wearables, everything that we are doing becomes tracked, so the ability to now manage the world in an entirely different way -- whether it's our businesses or our lives or our ecological resources -- becomes possible, but only because we begin to spatially network all these technologies, not because they're computers by themselves.
Alan: Interesting. Yeah, I think it's going to open up incredible possibilities. Right now, mining companies, for example, they have a formula. If they know that if they dig a certain amount of rock out based on their studies, they'll get a certain amount of gold. But at what point does recycling gold from old electronics actually become more cost-effective than digging it out of rock? At what point can we start to really look at what we've already extracted, and how do we recycle that? And I think if you can track the materials down to that level -- like, we got this much gold out of recycling from recycled electronics versus digging it into the ground -- and that goes into the full score of the environmental score of a company making those electronics? That's what you're talking about, right?
Gabriel: What we'd like to know is that that data's both accurate and can be relied upon; it can't be tampered with. And then it also makes it shareable, but it also makes that data itself monetizeable.
Alan: Ah.
Gabriel: So now you can create data marketplaces, and actually incentivize people to then share that information. This is a lot of these sort of open data formats, or things that are happening. Like, here in Los Angeles, there's an entire open data open map project that's in partnership with Esri, which is one of our partners, that is allowing all this public information to be presentable and usable and remixable and able to be analyzed by the public. And as we start to think about the entire planet as a single ecosystem, which clearly it is, but we haven't been thinking of it that way very well.
Alan: No, we still think in terms of countries for some reason.
Gabriel: Well, I think, you know, it's that... yeah. Nation states and platforms are the same thing, and today's platforms and larger than some of our nation states. So it is now time to come to the realization that these are single ecosystems, and ecosystems trade. They trade carbon, they trade nitrogen, they trade air, they trade water. This is how nature naturally works. I think we've just gotten to the point now where our technologies are able to digitally do what nature's been doing for billions of years.
Alan: Yeah, it's... it's so vast, and it's so hard for people to wrap their heads around. So let's take it back to what people can do now to leverage these technologies in their current business. Because, we've talked way out there on how spatial computing is going to allow Internet of Things sensors to provide real-time data in a reliable manner that will really allow all businesses to reduce their carbon footprints, their impact socially and environmentally, but also their bottom line. Their economics.
Gabriel: While increasing profit.
Alan: At the end of the day, until we change how we measure companies, they're measured based on profit. I've had so many different interviews on this podcast, and the one major one that comes out every single time is training. You cannot dispute the fact that virtual and augmented reality training makes good business sense. What are some of the other use cases outside of that?
Gabriel: Well, I actually think the number one use case, which we'll see emerge over the next decade -- which I think is roughly the timeline for transition from mobile to spatial; not a complete conversion, but rather the dominant interface, and that's not that long period of time, especially in the enterprise space -- the number one thing will actually be spatial workflow management. So the real problem we have just from a practical day-to-day business challenge is that most businesses are operational, meaning that they have physical activities that take place; in a field, in an office, in a building, in a logistics capacity. Right now, those, you can train people in VR, which is wonderful to be able to do that.
We've seen some wonderful work coming out around the Hololens 2, which looks at like scale, you'll be able to have sort of the ability to have that training be on the object itself, because you can project the information onto that piece of equipment itself. "You push this button, then pull this lever, then..." and so you go from this sort of virtual environment, which is 100 percent safe, to then like an environment where they're actually interfacing with the physical object by projecting the digital twin onto it and then walking through a series of steps. That's wonderful. That's super powerful.
Alan: I got to stop you because I learned something in my last podcast. The company, a AR-Experts, they were building digital twins and overlaying them on top of physical objects, and then creating the digital overlay. They realized that most people that are actually working on this would prefer not to have the whole physical or digital overlay on top; just the information they need on top of it, which is interesting because they were making a full, beautiful, replicated digital twin of the object and overlaying it on top of that. But they're like, "we can't see the real one; take that thing out of the way."
Gabriel: I think that, for the time being, a lot of the challenges will be around the UX. We don't know what the optimal UX is in three-dimensional space with regard to physical things. And I think people like, you know, Timoni West and others at Unity are doing great work around exploring what those spatial digital interactions and user experiences really need to be over time. I mean, if we look back at the history of digital maps -- MapQuest days -- used to give us the entire list of 20 turns, and you have to keep going back, figure out which turn you're supposed to be on, find the number, not crash, then okay, now I make a right turn in 250 yards. Then with Google Maps, it gives us a better option, where we can see the path. But even then, what's most useful is actually the audio, because it just gives you what you need when you need it. And spatial will probably have to do something very similar. I don't need to know the next five steps or the next four objects. Just give me the next one and then the next one. And the thing is that in the world of video games, we figured all this out. We just haven't been able to apply it to the world. But when we do, I believe that we're going to see just enormous efficiency gains, improvement, retention, and the profit margins are just going to go through the roof.
The interesting challenge there is that as we're augmenting humans with this digital information -- these new sort of spatial workflows and tasking -- it does also pave the road to robotic automation. So there is a number of questions that come up around, how humans and robots work together in the same spaces? What happens when automation replaces humans? And obviously, there are larger ethical and economic and regulatory considerations that have to happen around all of this. But as a business, immediately, you can start to see advantages. And my argument is get out there and start making mistakes first. The ones that learn from these mistakes are going to be the ones that dominate in the next decade. For example, in the warehouse space, we're projecting a 45 percent profit margin increase from the ability to do spatial workflow picking at scale. And I can tell you right now that that is a competitive logistics industry. And if you're not keeping up with technology, with the spatial transformation, you're likely to be unable to compete in the next decade.
Alan: That's a pretty bold statement.
Gabriel: Well, we're testing it live. We're seeing it every day right now.
Alan: I know. That's why I said it's a bold statement. I didn't dispute it! I've seen it all. We're doing the test, too, and it's like, training alone is in the order of 50 to 75 percent better training retention rates, and like near zero error rates when you're using real-time AR. So when you're saying a 45 percent increase in productivity and profit, it sounds ridiculous. Like, if you take any enterprise and say, "we're going to increase your profits by 4 percent," they would bend over backwards.
Gabriel: Yeah.
Alan: When you say, "well, here's a solution that's going to increase by 45 percent," they don't even... they can't even fathom it.
Gabriel: Yes. I think that for the next couple years, we're going to see the sort of stutter effects of businesses trying to figure out when to invest, when to begin testing, what to do. And the headsets are kind of working okay. The software is pretty good. The integrations into their traditional systems are just beginning to exist -- that's some of the work we're doing now. But it is not easy to get on board. The on ramp is not great. And the argument -- the business case -- is kind of there. But the ability to realize it feels a little ephemeral. But I believe that, shortly thereafter, we're going to see the thing hit a knee and start to skyrocket, as more and more use cases come to light and more and more companies start to gain benefits. We've seen this before. We saw it with the Web. We saw it with the power of a Web page. "Why would I want a Web page? We're in the phone book; promoting in the newspaper." And then we saw the same thing happen again with social. "Why do I as a business, need to talk to my customers? Well, this makes no sense. We've got a customer service team. I don't need Twitter. I don't need a Facebook page." And we saw it again with mobile. "Why do I have to reformat my site so that it's smaller? No one's going to look," and what have it.
Every company that began to drive and acclimate to that new atmosphere of digital transformation became the winners. And Facebook figured out quickly that they needed to be mobile first. And that's one of the reasons they dominated. Spatial is just the next step; it's the logical step. It's where billions of dollars and interface value are being invested. So, it's really just up to your listeners today to work with companies like MetaVRse and VERSES and others to try to figure out what those early pilots are. Get out there, break a couple eggs, and figure out how to make spacial web scramble.
Alan: I love it. Make some scrambled eggs. I love it! Oh, man. Is there anything else? We've talked about a lot here. I always ask this question: What problem in the world do you want to see solved using XR and spatial web?
Gabriel: Well, we believe that we are standing at a fork in the road -- a generational fork in the road -- and that this generation, in effect, has one of the most amazing challenges in the history of the species. And it really comes down to, we are facing existential-level threats with climate change, the depletion of our environmental resources, the devastation of both the plant and animal kingdoms, our coral reefs. I mean, today is Earth Day. These are things we think about for maybe a day, and then we go back to all of the behaviors that are continuing [the problems]. The result of which occurred because of our rapid growth in the industrial era, through our inventions and technologies. We need to now look forward and take this option for a second path, which isn't the end of the species, but is a -- for the first time -- the ability to have a civilization 5.0; a global civilization that works together, that starts to treat the resources of the planet as a single ecosystem.
And these technologies at scale have come with risks. We're looking at 50 billion cameras out here in the next decade or so. There'll be a billion drones. There'll be AI embedded into everything. Sensors picking up levels of mood tracking and facial recognition and pupil dilation, and all kinds of personal and private information. We could make far worse mistakes than we've made for the last hundred and fifty years with these powerful exponential technologies. So the choice that we really have, and the choice that we've founded VERSES to help support, is to use these technologies -- this sort of digital tidal wave -- to solve the physical, rising tide of planetary devastation, in order to not just solve the problems of the last 150 years, but to paint a new picture of a future that isn't just a Black Mirror future, but is a white mirror future; where we are taking care of our planet and each other, where we're all benefiting from the network effects of economies that are more equitable, and that we maintain our privacy and security and trust at scale.
I want a really cool sci-fi future that doesn't look like the dystopian sci-fi novels and stories and films that we're used to, and I think we need to start talking about what that future looks like. So, we're incredibly grateful to people like you and others in the space that are having these conversations, and starting to pick apart these stories, so that we can tell these stories to each other. Because, frankly, that's the kind of world that we'd like to build.
Alan: Well, what else can we say? Gabriel, thank you so much for joining me on the show.
Gabriel: It's been an honor, Alan. Thank you very much.