>> From theCUBE Studios in Palo Alto and Boston, bringing you data-driven insights from theCUBE and ETR. This is breaking analysis with Dave Vellante. >> Moore's Law is dead, right? Think again. Massive improvements in processing power combined with data and AI will completely change the way we think about designing hardware, writing software and applying technology to businesses. Every industry will be disrupted. You hear that all the time. Well, it's absolutely true and we're going to explain why and what it all means. Hello everyone, and welcome to this week's Wikibon Cube Insights powered by ETR. In this breaking analysis, we're going to unveil some new data that suggests we're entering a new era of innovation that will be powered by cheap processing capabilities that AI will exploit. We'll also tell you where the new bottlenecks will emerge and what this means for system architectures and industry transformations in the coming decade. Moore's Law is dead, you say? We must have heard that hundreds, if not, thousands of times in the past decade. EE Times has written about it, MIT Technology Review, CNET, and even industry associations that have lived by Moore's Law. But our friend Patrick Moorhead got it right when he said, "Moore's Law, by the strictest definition of doubling chip densities every two years, isn't happening anymore." And you know what, that's true. He's absolutely correct. And he couched that statement by saying by the strict definition. And he did that for a reason, because he's smart enough to know that the chip industry are masters at doing work arounds. Here's proof that the death of Moore's Law by its strictest definition is largely irrelevant. My colleague, David Foyer and I were hard at work this week and here's the result. The fact is that the historical outcome of Moore's Law is actually accelerating and in quite dramatically. This graphic digs into the progression of Apple's SoC, system on chip developments from the A9 and culminating with the A14, 15 nanometer bionic system on a chip. The vertical axis shows operations per second and the horizontal axis shows time for three processor types. The CPU which we measure here in terahertz, that's the blue line which you can't even hardly see, the GPU which is the orange that's measured in trillions of floating point operations per second and then the NPU, the neural processing unit and that's measured in trillions of operations per second which is that exploding gray area. Now, historically, we always rushed out to buy the latest and greatest PC, because the newer models had faster cycles or more gigahertz. Moore's Law would double that performance every 24 months. Now that equates to about 40% annually. CPU performance is now moderated. That growth is now down to roughly 30% annual improvements. So technically speaking, Moore's Law as we know it was dead. But combined, if you look at the improvements in Apple's SoC since 2015, they've been on a pace that's higher than 118% annually. And it's even higher than that, because the actual figure for these three processor types we're not even counting the impact of DSPs and accelerator components of Apple system on a chip. It would push this even higher. Apple's A14 which is shown in the right hand side here is quite amazing. It's got a 64 bit architecture, it's got many, many cores. It's got a number of alternative processor types. But the important thing is what you can do with all this processing power. In an iPhone, the types of AI that we show here that continue to evolve, facial recognition, speech, natural language processing, rendering videos, helping the hearing impaired and eventually bringing augmented reality to the palm of your hand. It's quite incredible. So what does this mean for other parts of the IT stack? Well, we recently reported Satya Nadella's epic quote that "We've now reached peak centralization." So this graphic paints a picture that was quite telling. We just shared the processing powers exploding. The costs consequently are dropping like a rock. Apple's A14 cost the company approximately 50 bucks per chip. Arm at its v9 announcement said that it will have chips that can go into refrigerators. These chips are going to optimize energy usage and save 10% annually on your power consumption. They said, this chip will cost a buck, a dollar to shave 10% of your refrigerator electricity bill. It's just astounding. But look at where the expensive bottlenecks are, it's networks and it's storage. So what does this mean? Well, it means the processing is going to get pushed to the edge, i.e., wherever the data is born. Storage and networking are going to become increasingly distributed and decentralized. Now with custom silicon and all that processing power placed throughout the system, an AI is going to be embedded into software, into hardware and it's going to optimize a workloads for latency, performance, bandwidth, and security. And remember, most of that data, 99% is going to stay at the edge. And we love to use Tesla as an example. The vast majority of data that a Tesla car creates is never going to go back to the cloud. Most of it doesn't even get persisted. I think Tesla saves like five minutes of data. But some data will connect occasionally back to the cloud to train AI models and we're going to come back to that. But this picture says if you're a hardware company, you'd better start thinking about how to take advantage of that blue line that's exploding, Cisco. Cisco is already designing its own chips. But Dell, HPE, who kind of does maybe used to do a lot of its own custom silicon, but Pure Storage, NetApp, I mean, the list goes on and on and on either you're going to get start designing custom silicon or you're going to get disrupted in our view. AWS, Google and Microsoft are all doing it for a reason as is IBM and to Sarbjeet Johal said recently this is not your grandfather's semiconductor business. And if you're a software engineer, you're going to be writing applications that take advantage of all the data being collected and bringing to bear this processing power that we're talking about to create new capabilities like we've never seen it before. So let's get into that a little bit and dig into AI. You can think of AI as the superset. Just as an aside, interestingly in his book, "Seeing Digital", author David Moschella says, there's nothing artificial about this. He uses the term machine intelligence, instead of artificial intelligence and says that there's nothing artificial about machine intelligence just like there's nothing artificial about the strength of a tractor. It's a nuance, but it's kind of interesting, nonetheless, words matter. We hear a lot about machine learning and deep learning and think of them as subsets of AI. Machine learning applies algorithms and code to data to get "smarter", make better models, for example, that can lead to augmented intelligence and help humans make better decisions. These models improve as they get more data and are iterated over time. Now deep learning is a more advanced type of machine learning. It uses more complex math. But the point that we want to make here is that today much of the activity in AI is around building and training models. And this is mostly happening in the cloud. But we think AI inference will bring the most exciting innovations in the coming years. Inference is the deployment of that model that we were just talking about, taking real time data from sensors, processing that data locally and then applying that training that has been developed in the cloud and making micro adjustments in real time. So let's take an example. Again, we love Tesla examples. Think about an algorithm that optimizes the performance and safety of a car on a turn, the model take data on friction, road condition, angles of the tires, the tire wear, the tire pressure, all this data, and it keeps testing and iterating, testing and iterating, testing iterating that model until it's ready to be deployed. And then the intelligence, all this intelligence goes into an inference engine which is a chip that goes into a car and gets data from sensors and makes these micro adjustments in real time on steering and braking and the like. Now, as you said before, Tesla persist the data for very short time, because there's so much of it. It just can't push it back to the cloud. But it can now ever selectively store certain data if it needs to, and then send back that data to the cloud to further train them all. Let's say for instance, an animal runs into the road during slick conditions, Tesla wants to grab that data, because they notice that there's a lot of accidents in New England in certain months. And maybe Tesla takes that snapshot and sends it back to the cloud and combines it with other data and maybe other parts of the country or other regions of New England and it perfects that model further to improve safety. This is just one example of thousands and thousands that are going to further develop in the coming decade. I want to talk about how we see this evolving over time. Inference is where we think the value is. That's where the rubber meets the road, so to speak, based on the previous example. Now this conceptual chart shows the percent of spend over time on modeling versus inference. And you can see some of the applications that get attention today and how these applications will mature over time as inference becomes more and more mainstream, the opportunities for AI inference at the edge and in IOT are enormous. And we think that over time, 95% of that spending is going to go to inference where it's probably only 5% today. Now today's modeling workloads are pretty prevalent and things like fraud, adtech, weather, pricing, recommendation engines, and those kinds of things, and now those will keep getting better and better and better over time. Now in the middle here, we show the industries which are all going to be transformed by these trends. Now, one of the point that Moschella had made in his book, he kind of explains why historically vertically industries are pretty stovepiped, they have their own stack, sales and marketing and engineering and supply chains, et cetera, and experts within those industries tend to stay within those industries and they're largely insulated from disruption from other industries, maybe unless they were part of a supply chain. But today, you see all kinds of cross industry activity. Amazon entering grocery, entering media. Apple in finance and potentially getting into EV. Tesla, eyeing insurance. There are many, many, many examples of tech giants who are crossing traditional industry boundaries. And the reason is because of data. They have the data. And they're applying machine intelligence to that data and improving. Auto manufacturers, for example, over time they're going to have better data than insurance companies. DeFi, decentralized finance platforms going to use the blockchain and they're continuing to improve. Blockchain today is not great performance, it's very overhead intensive all that encryption. But as they take advantage of this new processing power and better software and AI, it could very well disrupt traditional payment systems. And again, so many examples here. But what I want to do now is dig into enterprise AI a bit. And just a quick reminder, we showed this last week in our Armv9 post. This is data from ETR. The vertical axis is net score. That's a measure of spending momentum. The horizontal axis is market share or pervasiveness in the dataset. The red line at 40% is like a subjective anchor that we use. Anything above 40% we think is really good. Machine learning and AI is the number one area of spending velocity and has been for awhile. RPA is right there. Very frankly, it's an adjacency to AI and you could even argue. So it's cloud where all the ML action is taking place today. But that will change, we think, as we just described, because data's going to get pushed to the edge. And this chart will show you some of the vendors in that space. These are the companies that CIOs and IT buyers associate with their AI and machine learning spend. So it's the same XY graph, spending velocity by market share on the horizontal axis. Microsoft, AWS, Google, of course, the big cloud guys they dominate AI and machine learning. Facebook's not on here. Facebook's got great AI as well, but it's not enterprise tech spending. These cloud companies they have the tooling, they have the data, they have the scale and as we said, lots of modeling is going on today, but this is going to increasingly be pushed into remote AI inference engines that will have massive processing capabilities collectively. So we're moving away from that peak centralization as Satya Nadella described. You see Databricks on here. They're seen as an AI leader. SparkCognition, they're off the charts, literally, in the upper left. They have extremely high net score albeit with a small sample. They apply machine learning to massive data sets. DataRobot does automated AI. They're super high in the y-axis. Dataiku, they help create machine learning based apps. C3.ai, you're hearing a lot more about them. Tom Siebel's involved in that company. It's an enterprise AI firm, hear a lot of ads now doing AI and responsible way really kind of enterprise AI that's sort of always been IBM. IBM Watson's calling card. There's SAP with Leonardo. Salesforce with Einstein. Again, IBM Watson is right there just at the 40% line. You see Oracle is there as well. They're embedding automated and tele or machine intelligence with their self-driving database they call it that sort of machine intelligence in the database. You see Adobe there. So a lot of typical enterprise company names. And the point is that these software companies they're all embedding AI into their offerings. So if you're an incumbent company and you're trying not to get disrupted, the good news is you can buy AI from these software companies. You don't have to build it. You don't have to be an expert at AI. The hard part is going to be how and where to apply AI. And the simplest answer there is follow the data. There's so much more to the story, but we just have to leave it there for now and I want to summarize. We have been pounding the table that the post x86 era is here. It's a function of volume. Arm volumes are a way for volumes are 10X those of x86. Pat Gelsinger understands this. That's why he made that big announcement. He's trying to transform the company. The importance of volume in terms of lowering the cost of semiconductors it can't be understated. And today, we've quantified something that we haven't really seen much of and really haven't seen before. And that's that the actual performance improvements that we're seeing in processing today are far outstripping anything we've seen before, forget Moore's Law being dead that's irrelevant. The original finding is being blown away this decade and who knows with quantum computing what the future holds. This is a fundamental enabler of AI applications. And this is most often the case the innovation is coming from the consumer use cases first. Apple continues to lead the way. And Apple's integrated hardware and software model we think increasingly is going to move into the enterprise mindset. Clearly the cloud vendors are moving in this direction, building their own custom silicon and doing really that deep integration. You see this with Oracle who kind of really a good example of the iPhone for the enterprise, if you will. It just makes sense that optimizing hardware and software together is going to gain momentum, because there's so much opportunity for customization in chips as we discussed last week with Arm's announcement, especially with the diversity of edge use cases. And it's the direction that Pat Gelsinger is taking Intel trying to provide more flexibility. One aside, Pat Gelsinger he may face massive challenges that we laid out a couple of posts ago with our Intel breaking analysis, but he is right on in our view that semiconductor demand is increasing. There's no end in sight. We don't think we're going to see these ebbs and flows as we've seen in the past that these boom and bust cycles for semiconductor. We just think that prices are coming down. The market's elastic and the market is absolutely exploding with huge demand for fab capacity. Now, if you're an enterprise, you should not stress about and trying to invent AI, rather you should put your focus on understanding what data gives you competitive advantage and how to apply machine intelligence and AI to win. You're going to be buying, not building AI and you're going to be applying it. Now data as John Furrier has said in the past is becoming the new development kit. He said that 10 years ago and he seems right. Finally, if you're an enterprise hardware player, you're going to be designing your own chips and writing more software to exploit AI. You'll be embedding custom silicon in AI throughout your product portfolio and storage and networking and you'll be increasingly bringing compute to the data. And that data will mostly stay where it's created. Again, systems and storage and networking stacks they're all being completely re-imagined. If you're a software developer, you now have processing capabilities in the palm of your hand that are incredible. And you're going to rewriting new applications to take advantage of this and use AI to change the world, literally. You'll have to figure out how to get access to the most relevant data. You have to figure out how to secure your platforms and innovate. And if you're a services company, your opportunity is to help customers that are trying not to get disrupted are many. You have the deep industry expertise and horizontal technology chops to help customers survive and thrive. Privacy? AI for good? Yeah well, that's a whole another topic. I think for now, we have to get a better understanding of how far AI can go before we determine how far it should go. Look, protecting our personal data and privacy should definitely be something that we're concerned about and we should protect. But generally, I'd rather not stifle innovation at this point. I'd be interested in what you think about that. Okay. That's it for today. Thanks to David Foyer, who helped me with this segment again and did a lot of the charts and the data behind this. He's done some great work there. Remember these episodes are all available as podcasts wherever you listen, just search breaking it analysis podcast and please subscribe to the series. We'd appreciate that. Check out ETR's website at ETR.plus. We also publish a full report with more detail every week on Wikibon.com and siliconangle.com, so check that out. You can get in touch with me. I'm dave.vellante@siliconangle.com. You can DM me on Twitter @dvellante or comment on our LinkedIn posts. I always appreciate that. This is Dave Vellante for theCUBE Insights powered by ETR. Stay safe, be well. And we'll see you next time. (bright music)

>> Narrator: Live from San Juan, Puerto Rico It's theCUBE. Covering Blockchain Unbound. Brought to you by Blockchain Industries. (latin music) >> Hello and welcome back to theCUBE exclusive coverage in Puerto Rico for Blockchain Unbound I'm John Furrier, your host, here covering all the action in Puerto Rico as the global society and industry come together. Our next guest is Marhall Taplits he's the Chief Strategy Officer and Co Founder of Nynja.biz, check out their site, Nynja.biz. Marshall, thanks for joining me. >> Thank you. >> So tell about what you guys do. You guys are doing some disruptive stuff, tell us about what you guys do, then it will jam into a conversation. >> Sure, so are you familiar with WeChat in China, for example? >> Yeah. >> Okay great. So I've personally been living in China 15 years, so we've watched kind of the birth of the Chinese internet, which as we know, is a little different than the regular internet. >> A lot of mobile users. >> A lot of mobile users, 800 million China mobile subscribers alone. WeChat, basically, is a platform that started off as just a messenger but basically what it's done is it's integrated into every facet of Chinese society. To give you an example, you go to a restaurant, you scan the QR code, the menu comes up, you pick the food, you pay for the food, it comes, you walk out. Everything like that is in China. Everything like that is in Wuzhen China. So what we've done is we've kind of taken this concept, and we're working on a global version of it, that's cryptocurrency based, and we are working specifically with Chinese companies in order to help them go global as part of the China One Belt One Road program and working with companies like Alibaba, what have you, in order to help Chinese companies go overseas and take what they've built in China but operate globally with cryptocurrency. >> Are you guys in China? Cause it's been hard for companies to start companies in China. So you're living in China or you're working in China? >> Yeah so because we live in Shenzhen, right next to it is Hong Kong. Hong Kong is where our company is based. Hong Kong, as you know, previous British colony, the legal system, and the financial system-- >> And you domicile in Hong Kong, that's where you're based? >> Me personally in Shenzhen, but the company is in Hong Kong. So we also have a Wyoming corporation in the US. >> That's where all the action is. >> That's right >> That's where WeChat is >> That's right >> Alibaba's got Alipay and then there's more business to business with their app. So I get that WeChat's been highly successful. In fact we have a huge following on WeChat, Sou Kanai, Niki Bond, free content. But that brings up the question of Chinese kind of showing the way with mobile expansion, so their users are heavily mobile savy. >> Marshall: That's right. >> This is pretty obvious when you think about it, but in America and around the world, that's going to translate to the new user experience. So in your opinion, how would you describe the expectations that users have? Because you're living on the front end of the wave of what mobile's doing, I mean there's a lot of gamification going on, some if it's kind of creepy, but what is your view of the expectations that users have and what's different about what's currently available in the webstac, and the 20 year old e-commerce stacks, that are out there? >> Sure, I think the most important thing is reducing friction, all right. You don't want to be using platforms where you can not do it wherever you are whenever you are, you don't want to have to go through payment processes, you don't want to have to re-authenticate yourself across whatever platforms you use. And interestingly, when I first went to China, it was all about copying what was in the west over to there, but actually it's kind of the opposite now, right, so we basically want to take this concept of the frictionless digital life, and make it a global opportunity. And especially with BlockChain and cryptocurrency you have that really as an opportunity, because if you look at all the apps that are out there, and the platforms that are out there, the only ones that have gone past a billion users, WhatsApp, Instagram, whatever are the free ones. But as soon as you layer in payment, it becomes very locked. And as big as WeChat is, and as big as LINE is, but ultimately it's locked into the Rem and B system or Reo in Korea, what have you, so the cryptocurrency is really the first opportunity that the world's had to create platforms that can get up to a billion, two billion, three billion users that are able to pay. And we just think that's a once in a lifetime opportunity and we want to be part of it. >> So I got to ask you about the impact that cloud computing has had on this, obviously we've seen cloud computing destroy the data center model, allow people to get time to value faster, mobile on top, big data analytics using data, all this stuff's awesome stuff. So the question is, is that, that's kind of a horizontally disruptive view, so these stacks that are built old way where I got to own the stack end to end, yeah there's some standardization on the lower end of the stack. But now you're thinking about more of a horizontal, I got jurisdictions, I got regions, I got countries, I got sovereignty, all these things are in the melting pot of the cryptocurrency BlockChain, de-centralized applications, are major impacts to all those things. How do you see that playing out because, that's kind of what developers worry about, oh shit will this work on that chain? I got Neo I got this I got that, so the plumbing is totally a moving train right now. >> Marshall: That's right. >> But the business models are pretty obvious. So there's like a business ops thing going on. What Dev opts did for Cloud, you got this new abstraction thing going on with this world. What's your view on that, do you agree? Or what's your take? >> Yeah well you pretty much nailed it. I mean basically what's happening is over the last 10 or 15 years people have finally accepted that having your own server is kind of silly, you know, and most people now will just spin up whatever they need in terms of resources on TheCloud. But over the last couple years, you're really going more toward Edge Cloud, where the way the clouds work, is that basically it's pushing to get the least amount of latency and store the data as close to the user as possible. And then there's also regulatory in some countries now in terms of, if your users are from this country, you have to legally store the data in this area. So this is all kind of evolving. And if you look at the BlockChain technology, I think it's the payment version of that. So for example, everyone's always concerned about getting in and out of Fiat Currency, and how am I going to get back to dollars, and this and that, but I think what's going to wind up happening, is this is going to get pushed towards the edges and there will be opportunities and ways with exchanges and what have you to get in and out. But more importantly, it's going to be like, just other currencies, so for example, I live in China but I come to the US a few times a year, I also travel to Europe, I have some dollars, I have some Euros, I have some Rem and B, when I leave China, I don't immediately sell all of my Rem and B, I just keep it because at some point I'm going to need it. And I think what's going to happen in the cryptocurrency space is, especially on the larger BlockChains, like Ethereum and Neo and what have you, is people are just going to get used to keeping some of it and they're going to stop worrying about what the exact exchange rate is and how am I going to get in and out, and this and that, and they're just going to start treating it as part of their currency stack that they keep. >> Yeah as long as there's some level of stability. It's just like, I remember when I was growing up, there was no Euro, every country had their own currency. You had the French Franc, the Swiss Francs, the Deutsche Mark, Lira, etc, etc. But you're seeing that the viability of the money aspect, cause at the end of the day there's two things that we've identified in analysis, and I was talking about it last night, talked about it this morning on theCUBE, is the killer apps for BlockChain cryptocurrency, these sorts of apps is two things, money and marketplaces. >> Marshall: That's right. >> Everything else is just kind of circling around those two. >> Well there's more but certainly that's the main part of it >> Money, moving around. So the UK just announced with coin based, the Financial Conduct Authority, reading the news yesterday, has essentially said we're going to allow for the fast payment system to convert to Fiat. This is a government, the UK is a nation. This is the beginning, to your point, that if they don't get up to speed, the edge of the network will democratize them and kind of circle the wagons, if you will, so it's already happening. >> Yeah and I think what governments are starting to realize is hey guys this is just a technology and not only do you don't really have jurisdiction to control it, but also that you don't even have the technical means. So Wyoming is a good example of regulation coming into play, that just kind of accepts the presence that this now exists, right. And they're not going to try to make it something and fit it into the old way. So, and in terms of the stability of these coins, I think it is important because people want stability, but in other ways, if you don't look at the exchange rate, it's actually way more stable than the current system, and I'll give an example. In the last month or two, the prices of cryptocurrency have dropped almost 40%. Now if the stock markets and the global affects markets drop 40%, you'd have blood in the streets. But the crypto market is asset based instead of debt based and because it's so structurally sound it's able to handle these wild swings without actually collapsing the system, so in may ways, it's way more stable, and then as the market gaps and the buy in of these currencies get bigger and bigger, of course it's going to be more stable over time. >> Well I mean its stable from a fail standpoint, but a lot of emotional instability. People losing money for the first time. >> But that's just because they're-- >> That's a lot of speculation, right? >> There's a lot of speculating and then if they're down they feel like they lost but, that's life. >> People that are into the game, like you, were long on this. So what would you explain to someone, cause I have two, a lot of friends that have two schools of thought, that's a total scam, don't associate with that, to oh my god, that's the next biggest wave, lets get our surfboards out there and lets get on this, there's a multiple set coming in, it's the biggest thing we've seen, and everything in between. How do you explain it to people for the first time? >> It's just your traditional curve, there's early adopters and what have you, and if you were one of the guys buying up domaine names in the early 90s, you know some people would say I can't believe you're spending $100,000 buying up domaine names, but some of them now are worth, you know, tens of millions of dollars. But again, this is the speculatory piece of it. And there's no shortage of opportunities for speculation and I encourage everybody to speculate a little bit because what it does is it gets you a taste of the technology. And usually, when you have some money on the line, you pay more attention, so if speculation is what gets people interested, and it gets them watching it and understanding the technology and using it, then I'm all for it, but people shouldn't be speculating with money they don't have. Anything could happen in the short term. Nobody knows what's going to happen with any specific currency. But in terms of the technology itself, this is a revolution way bigger than the internet itself. This is where you're getting, not only, communications like the internet, but financing governance and all as one. Programmable money, programmable contracts, that wipes out finance, it wipes out legal, it whites out governance in many ways. So this is a huge evolution in human society, and we've termed this Open Unity actually. And so we believe that society has to reach a state of open unity in order to go into the singularity as we would envision it wanting to be, as something that's under our control. >> Yeah and I think one of the things, first of all that's a great statement, well said. I'll just kind of put some reality on that, connect the dots, is that if you look at the trajectory of cloud computing, Amazon Web Services was laughed at years ago. S3 came out, compute storage building, basic building blocks and a slew more services. What Cloud did for software developers, and what they've disrupted from a business standpoint, dev ops, it's proven. What open source has done, even going back to the old red-hat days and linux, is that now a tier one global citizen in software, you look at those two trends, you can connect that dots to what you just said. And what made Cloud great was they made application developers have access to programmable infrastructure. >> Marshall: Exactly. >> You're talking about a whole nother level of software programmability, money, marketplace, society, >> Yeah you hit it on the head. >> We're there right? >> That's exactly right, so when a programmer wants to start a business, instead of going to create an LLC, and getting their EIN Tax ID or whatever, and when they want to go into Europe, and dealing with that and then trying to open a bank account, which is almost impossible, internationally now, instead of that, you just have your SDKs and your APIs or whatever and you've got access to money, program adding, you can take money, you can move money around, globally, frictionless, permissionless, with governancy, smart contracts-- >> They might not not need an SDK dashboard, its a console, click, click, click, smart contracts, governance, turn key. >> And one of the things we're working on with Nynja in particular, is this kind of on-demand marketplace and putting together a de-centralized teams for work. And this is all driven by smart contracts. So one of the issues with the economy is the huge booms and busts that people have in the economy. And if you look at the root cause of that, my personal opinion, is that it's because of payment terms. So for example, if I do work for you, and then there's an invoice, but it's not due for 30 days, now your business may be structurally sound, but the truth is your cashflow is all over the place. With BlockChain technology, we can actually do real time payments. You could be paid minute by minute, hour by hour. Real time, program, contract. So we're going to create very flat even money flows through the entire economy globally, and we're going to just completely remove these booms and busts that are really nothing more than just cashflow issues that are compounded and compounded at a global level. >> I mean I lived through the dot com bubble, I was actually part of it on the front end, on the euphoria side, as well as on the crash. Part of the whole search paradigm, google right there. Key words, all that stuff happening, growth, massive growth. So I saw that, the scammers in there, or the bubble people, that's what we called them. But the reality is, everything happened. It was pet foods online, you could get shopping delivered to your house. So again, to your point, it's a little euphoric right now, but what's different is, is you have now, community data. See what I see happening is, it's not a major bubble crash, because self government, self governing, self governance, is a community dynamic. So I think there's going to be a lot of self healing, inside the networks themselves. You're already seeing it here, a lot of people, bad act is being identified, investors flight to quality, looking at quality deals. Interesting times, your thoughts? >> Well I mean you know, we've been through many evolutions of society, we've had surf-dom, we've had monarchies, we've had representative democracies, we have all these things, and I just think the next evolution is decentralized governance. And we don't even know what that means yet, because it's just starting, but I think we can all, if we can close our eyes and really think about it. I think it's pretty obvious what the issues are with our current system and not just the US, but globally, and I think we have an opportunity here to build in organic program governance. And what's really special about BoxChain technology is if I program it to do X, it's going to do X. So we don't need to, I don't need to know who you are to trust you. I don't need to worry about where we're going to sue each other, or we're going to have arbitration if things go wrong. We're just going to make an agreement, and we're going to program it that way, and that's it. And now the next phase is, I could build on top of that trusting that that's just going to happen. So you can create these chains of trust, and that can happen anywhere in the world. So I think this is a whole nother-- >> Sounds like a bunch of web services. >> Well in many ways, in terms of the architecture, sure you could absolutely think of it like that. >> The reusability, the leverage is amazing. All right, so I want to just end the segment Marshall, take a minute to end the segment, to talk about what you're working on, Nynja coin, Nynja, N-Y-N-J-A .biz, you guys have a product, you got a BlockChain enabled platform, you got a coin, take a minute to explain what you're working on. >> Basically we want to provide the tools and services to help people live in this new reality. So in order to basically function in the world that we're entering into, we're going to need tools that far surpass what's currently available in terms of the messengers, the web sites, all these things. We need to be operating at a level that takes communication completely frictionless, payment completely frictionless, and governance completely frictionless. And we have to put this all together, and that's what we're doing with Nynja. We're staring with a global communicator, which is basically, if you want to take WeChat, telegram, whatever, but we have about 50 additional features that really take communications to the next level. And then on top of it, creating the baseline with cryptocurrency payment, and also smart contract wizards and helping people kind of get these teams going and get paid and organize their financial life in a de-centralized way. So we're just basically going to be the next generation of these messenger type platforms with BlockChain integrated. And what you're going to see is that over the next couple years you're going to get to the first companies that are achieving not just a billion or two billion or three billion users, but paying users, and we're going to be one of the probably three to five platforms that are offering tools at the global level like this. >> And have you got an IC already or not? >> We've just started our private ICO about two weeks ago. We're getting tremendous support in Asia. Quite frankly, the US is not seeing it as much-- >> Is it a utility token or security? >> Utility Token, and I think it's really telling, interesting, coming here. It's the first time I've been doing the presenting. We spoke yesterday at the d10e and we also spoke at d10e in Korea a week or two ago, and the response is incredible. And I think the reason is because-- >> The Asian market gets it. >> Well they're already living in this world within their own confines in terms of the messenger with their payment and governance built in, so when I tell them that we're going to do this globally with crypto, immediately they get it. I'm having trouble here, especially in these five minute pitches which is ridiculous, it's like a chop shop, I don't know how to communicate the idea within this short time frame, so, what I'm looking for while we're here this week is just to find people who really want to take an hour or two or even people like yourself who want to do interviews and just kind of really talk to people and really explain-- >> Well platform is complex, a lot of pieces to it. It's a system, but the value you offer is essentially offering developers, who are building products, for tools that you've built so they can scale faster. That sounds like your value. >> That's right and although I can't say specifically, we're also working on a deal that's going to get us started with about 15 million active users on day one, so that's very exciting and we're really really excited about that. >> And the coins will be utility of measures, what? >> Sorry? >> Well your utility coins going to be measuring what, what's the main token economics that drives the-- >> For the ICO economics? >> Your Nynja Coin. >> So basically we're releasing 5 billion tokens, 45% of them will be sold. There's five cents a token, so the hard cap, by definition is about 112 million, actually we're planning to do the public sale in April, but we may cancel it or postpone it just because the private sale is going really well, but we'll see how that goes. But in terms of once it's live, this will basically be the utility token of the entire eco-system, so anybody, not just within our Nynja App or platform, but even people, I don't know if you know XMPP federation, like back in the day-- >> Yeah you know about real messaging >> If you could think of us as the next version of XMPP federation, but using cryptocurrency in order to avoid bad actors by making it very expensive to do bad things, and very cheap to do good things and globally. >> So it's like Twitter you can create a bot instantly, but if there's coins involved, you'd have to spend to get it. >> That's right and also people could spin up nodes that are basically their own Twitters and decide if those Twitters of their own, their Nynja boxes of their own, are either just internally, or you could specify specifically context or group of context-- >> We agree, that's a great way to get bad actors out because it costs them money. And it's de-centralized, there's no single spot. >> That's right, if email came out today, when cryptocurrency existed, there would be no spam. Because it would be expensive as hell to send more than a few a second, but it would still be free and for everybody generally, and you wouldn't even have spam. So we think we can do that for messaging globally. >> Great. Marshall, thanks so much for coming on theCUBE, really appreciate it, check out Nynja. Marshall Taplits is the Chief Strategy Officer and co-founder of Nynja.biz, check them out online. Check out the website, it's in Asia, bringing that culture of mobile and fast moving, real time apps, to the rest of the developers. This is theCUBE coverage in Puerto Rico for BlockChain Unbound exclusive two days of coverage. We'll be right back with more, after this short break, thanks for watching.