>> 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)

(bright upbeat music) >> Announcer: From theCUBE studios in Palo Alto in Boston, connecting with thought leaders around the globe, these are Cloud Native Insights. >> Hi, I'm Stu Miniman, the host of Cloud Native Insights. We talk about cloud native, we're talking about how customers can take advantage of the innovation and agility that's out there in the clouds, one of the undercurrents, not so hidden if you've been watching the program so far. We've talked a bit about serverless, say something that's helping remove the friction, allowed developers to take advantage of technology and definitely move really fast. So I'm really happy to welcome to the program, for coming from Fauna. First of all, I have the CTO and Co-founder, who's Evan Weaver. And also joining him is the new CEO Eric Berg. They said, both from Fauna, talking serverless, talking data as an API and talking the modern database. So first of all, thank you both for joining us. >> Thanks for having us Stu. >> Hi, good to be here. >> All right, so Evan, we're going to start with you. I love talking to founders always. If you could take us back a little bit, Fauna as a project first before it was a company, you of course were an early employee at Twitter. So if you could just bring us back a little bit, what created the Fauna project and bring us through a brief history if you would. >> So I was employee 15 and Twitter, I joined in 2008. And I had a database background, I was sort of a performance analyst and worked on Ruby on Rails sites at CNET networks with the team that went on to found GitHub actually. Now I went to Twitter 'cause I wanted Twitter the product to stay alive. And for no greater ambition than that. And I ended up running the back end engineering team there and building out all the distributed storage for the core business objects, tweets, timelines, the social graph, image storage, the cache, that kind of thing. And this was early in the cloud era. API's were new and weird. You couldn't get Amazon EC2 off the shelf easily. We were racking hardware and code ancient center. And there were no databases or platforms for data of any kind. They really let us the Twitter engineering team focus on building the product. And we did a lot of open source work there. Some of which has influenced Fauna, originally, Twitter's open source was hosted on the Fauna GitHub account, which predated Twitter like you mentioned. And I was there for four years build out the team, basically scaled the site, especially scaled the Twitter.com API. And we just never found a platform which was suitable for what we were trying to accomplish. Like a lot of what Twitter did was itself a platform. We had developers all over the world using the Twitter API to interact with tweets. And we're frustrated that we basically had to become specialists in data systems because there wasn't a data API, we can just build the product on. And ultimately, then data API that we wished we had, is now Fauna. >> Well, it's a story we've loved hearing. And it's fascinating one, is that the marketplace wasn't doing what we needed. Often open source is a piece of that, how do we scale that out? How do we build that? Realized that the problem that you have is what others have. And hey, maybe there's a company. So could you give us that transition, Fauna as a product, as a company, where was it understood that, hey, there's a lot of other people that can take advantage from some of the same tools that you needed before. >> I mean, we saw it in the developers working with the Twitter platform. We weren't like, your traditional database experiences, either manage cloud or on-prem, you have to administrate the machine, and you're responsible for its security and its availability and its location and backups and all that kind of thing. People building against Twitter's API weren't doing that. They're just using the web interface that we provided to them. It was our responsibility as a platform provider. We saw lots of successful companies being built on the API, but obviously, it was limited specifically to interacting with tweets. And we also saw peers from Twitter who went on to found companies, other people we knew in the startup scene, struggling to just get something out the door, because they had to do all this undifferentiated heavy lifting, which didn't contribute to their product at all, if they did succeed and they struggled with scalability problems and security problems and that kind of thing. And I think it's been a drag on the market overall, we're essentially, in cloud services. We're more or less built for the enterprise for mature and mid market and enterprise companies that already had resources to put behind these things, then wasn't sort of the cloud equivalent of the web, where individuals, people with fewer resources, people starting new projects, people doing more speculative work, which is what we originally and Jack was doing at Twitter, it just get going and build dynamic web applications. So I think the move to cloud kind of left this gap, which ultimately was starting to be filled with serverless, in particular, that we sort of backtracked from the productivity of the '90s with the lamp era, you can do everything on a single machine, nobody bothered you, you didn't have to pay anyone, just RPM install and you're good to go. To this Kubernetes, containers, cloud, multi site, multi region world where it's just too hard to get a basic product out the door and now serverless is sort of brought that around full circle, we see people building those products again, because the tools have probably matured. >> Well, Evan, I really appreciate you helping set the table. I think you've clearly articulated some of the big challenges we're seeing in the industry right now. Eric, I want to bring you into the conversation. So you relatively recently brought in as CEO, came from Okta a company that is also doing quite well. So give us if you could really the business opportunity here, serverless is not exactly the most mature market, there's a lot of interest excitement, we've been tracking it for years and see some good growth. But what brought you in and what do you see is that big opportunity. >> Yeah, absolutely, so the first thing I'll comment on is what, when I was looking for my next opportunity, what was really important is to, I think you can build some of the most interesting businesses and companies when there are significant technological shifts happening. Okta, which you mentioned, took advantage of the fact of SaaS application, really being adopted by enterprise, which back in 2009, wasn't an exactly a known thing. And similarly, when I look at Fauna, the move that Evan talked about, which is really the maturation of serverless. And therefore, that as an underpinning for a new type of applications is really just starting to take hold. And so then there creates opportunities that for a variety of different people in that stack that to build interesting businesses and obviously, the databases is an incredibly important part of that. And the other thing I've mentioned is that, a lot of people don't know this but there's a very good chunk of Okta's business, which is what they call their customer identity business, which is basically, servicing of identity is a set of API's that people can integrate into their applications. And you see a lot of enterprises using this as a part of their digital transformation effort. And so I was very familiar with that model and how prevalent, how much investment, how much aid was out there for customers, as every company becoming a software company and needing to rethink their business and build applications. And so you put those two trends together and you just see that serverless is going to be able to meet the needs of a lot of those companies. And as Evan mentioned, databases in general and traditionally have come with a lot of complexity from an operational perspective. And so when you look at the technology and some of the problems that Fauna has solved, in terms of really removing all of that operational burden when it comes to starting with and scaling a database, not only locally but globally. It's sort of a new, no brainer, everybody would love to have a database that scales, that is reliable and secure that they don't have to manage. >> Yeah, Eric, one follow up question for you. I think back a few years ago, you talked to companies and it's like, okay, database is the center of my business. It's a big expense. I have a team that works on it. There have been dealt so much change in the database market than most customers I talked to, is I have lots of solutions out there. I'm using Mongo, I've got Snowflake, Amazon has flavors of things I'm looking at. Snowflake just filed for their IPO, so we see the growth in the space. So maybe if you could just obviously serverless is a differentiation. There's a couple of solutions out there, like from Amazon or whether Aurora serverless solution but how does Fauna look to differentiate. Could you give us a little bit of kind of compared to the market out there? >> Sure, yeah, so at the high level, just to clarify, at the super high level for databases, there tends to be two types operational databases and then data warehouse which Snowflake is an example of a data warehouse. And as you probably already know, the former CEO of Snowflake is actually a chairman of Fauna. So Bob Muglia. So we have a lot of good insight into that business. But Fauna is very much on the operational database side. So the other half of that market, if you will, so really focused on being the core operational store for your application. And I think Evan mentioned it a little bit, there's been a lot of the transformation that's happened if we rewind all the way back to the early '90s, when it was Oracle, and Microsoft SQL Server were kind of the big players there. And then as those architectures basically hit limits, when it came to applications moving to the web, you had this whole rise in a lot of different no SQL solutions, but those solutions sort of gave up on some of the promises of a relational database in order to achieve some of the ability to scale in the performance required at the web. But we required then a little bit more sophistication, intelligence, in order to be able to basically create logic in your application that could make up for the fact that those databases didn't actually deliver on the promises of traditional relational databases. And so, enter Fauna and it's really sort of a combination of those two things, which is providing the trust, the security and reliability of a traditional relational database, but offering it as serverless, as we talked about, at the scale that you need it for a web application. And so it's a very interesting combination of those capabilities that we think, as Evan was talking about, allows people who don't have large DevOps teams or very sophisticated developers who can code around some of the limitations of these other databases, to really be able to use a database for what they're looking for. What I write to it is what I'm going to read from it and that we maintain that commitment and make that super easy. >> Yeah, it's important to know that the part of the reason that operational database, the database for mission critical business data has remained a cost center is because the conventional wisdom was that something like Fauna was impossible to build. People said, you literally cannot in information science create a global API for data which is transactional and consistent and suitable for relying on, for mission critical, user login, banking payments, user generated content, social graphs, internal IT data, anything that's irreplaceable. People said, there can be no general service that can do this ubiquitously a global internet scale, you have to do it specifically. So it's sort of like, we had no power company. Instead, you could call up Amazon, they drive a truck with a generator to your house and hook you up. And you're like, right on, I didn't have to like, install the generator myself. But like, it's not a good experience. It's still a pain in the neck, it's still specific to the location you're at. It's not getting utility computing from the cloud the way, it's been a dream for many decades that we get all our services through brokers and API's and the web and it's finally real with serverless. I want to emphasize that the Fauna it technology is new and novel. And based on and inspired by our experience at Twitter and also academic research with some of our advisors like Dr. Daniel Abadi. It's one of the things that attracted us, Snowflake chairman to our company that we'd solve groundbreaking problems in information science in the cloud, just the way Snowflakes had. >> Yeah, well and Evan, yeah please go on Eric. >> Yeah, I'm just going to have one thing to that, which is, in addition, I think when you think about Fauna and you mentioned MongoDB, I think they're one of a great examples of database companies over the last decade, who's been able to build a standalone business. And if you look at it from a business model perspective, the thing that was really successful for them is they didn't go into try to necessarily like, rip and replace in big database migrations, they started evolving with a new class of developers and new applications that were being developed and then rode that obviously into sort of a land and expand model into enterprises over time. And so when you think about Fauna from your business value proposition is harnessing the technological innovation that Evan talked about. And then combining this with a product that bottoms up developer first business motion that kind of rides this technological shift into you creating a presence in the database market over time. >> Well, Evan, I just want to go back to that, it's impossible comment that you made, a lot of people they learn about a technology and they feel that that's the way the technology works. Serverless is obviously often misunderstood from the name itself, too. We had a conversation with Andy Jassy, the CEO of AWS a couple years ago, and he said, "If I could rebuild AWS from the ground up today, "it would be using all serverless," that doesn't mean only lambda, but they're rebuilding a lot of their pieces underneath it. So I've looked at the container world and we're only starting the last year or so, talking about people using databases with Kubernetes and containers, so what is it that allows you to be able to have as you said, there's the consistency. So we're talking about acid there, not worry about things like cold starts, which are thing lots of people are concerned about when it comes to serverless and help us understand a little bit that what you do and the underlying technologies that you leverage. >> Yeah, databases are always the last to evolve because they're the riskiest to change and the hardest to build. And basically, through the cloud era, we've done this lift and shift of existing on premises solutions, especially with databases into cloud machines, but it's still the metaphor of the physical computer, which is the overriding unit of granularity mental concept, everything like you mentioned, containers, like we had machines then we had Vms, now we have containers, it's still a computer. And the database goes in that one computer, in one spot and it sits there and you got to talk to it. Wherever that is in the world, no matter how far away it is from you. And people said, well, the relational database is great. You can use locks within a single machine to make sure that you're not conflicting your data when you update it, you going to have transactionality, you can have serialize ability. What do you do, if you want to make that experience highly available at global scale? We went through a series of evolutions as an industry. From initially that the on-prem RDBMS to things like Google's percolator scheme, which essentially scales that up to data center scale and puts different parts of the traditional database on different physical machines on low latency links, but otherwise doesn't change the consistency properties, then to things like Google Spanner, which rely on synchronized atomic clocks to guarantee consistency. Well, not everyone has synchronized atomic clocks just lying around. And they're also, their issues with noisy neighbors and tenancy and things because you have to make sure that you can always read the clock in a consistent amount of time, not just have the time accurate in the first place. And Fauna is based on and inspired and evolved from an algorithm called Calvin, which came out of a buddy's lab at Yale. And what Calvin does is invert the traditional database relationship and say, instead of doing a bunch of work on the disk and then figuring out which transactions won by seeing what time it is, we will create a global pre determined order of transactions which is arbitrary by journaling them and replicating them. And then we will use that to essentially derive the time from the transactions which have already been committed to disk. And then once we know the order, we can say which one's won and didn't win and which happened before, happen after and present the appearance of consistency to all possible observers. And when this paper came out, it came out about a decade ago now I think, it was very opaque. There's a lot of kind of hand waving exercises left to the reader. Some scary statements about how wasn't suitable for things that in particular SQL requires. We met, my co-founder and I met as Fauna chief architect, he worked on my team at Twitter, at one of the database groups. We were building Fauna we were doing our market discovery or prototyping and we knew we needed to be a global API. We knew we needed low latency, high performance at global scale. We looked at Spanner and Spanner couldn't do it. But we found that this paper proposed a way that could and we can see based on our experience at Twitter that you could overcome all these obstacles which had made the paper overall being neglected by industry and it took us quite a while to implement it at industrial quality and scale, to qualify it with analysts and others, prove to the world that it was real. And Eric mentioned Mongo, we did a lot of work with Cassandra as well at Twitter, we're early in the Cassandra community. Like I wrote, the first tutorial for Cassandra where data stacks was founded. These vendors were telling people that you could not have transactionality and scale at the same time, and it was literally impossible. Then we had this incrementalism like things with Spanner. And it wasn't till Fauna that anyone had proved to the world that that just wasn't true. There was more marketing around their failure to solve the information science problem, than something fundamental. >> Eric, I'm wondering if you're able to share just order of magnitude, how many customers you have out there from a partnership standpoint, we'd like to understand a little bit how you work or fit into the public cloud ecosystems out there. I noticed that Alphabets General Venture Fund was one of the contributors to the last raise. And obviously, there's some underlying Google technology there. So if you could just customers and ecosystem. >> Yeah, so as I mentioned, we've had a very aggressive product lead developer go to market. And so we have 10s of thousands of people now on the service, using Fauna at different levels. And now we're focused on, how do we continue to build that momentum, again, going back to the model of focus on a developer lead model, really what we're focused on there is taking everything that Evan just talked about, which is real and very differentiated in terms of the real core tech in the back end and then combining that with a developer experience that makes it extremely easy to use and really, we think that's the magic in terms of what Fauna is bringing, so we got 10s of thousands of users and we got more signing up every day, coming to the service, we have an aggressive free plan there and then they can migrate up to higher paying plans as they consume over time. And the ecosystem, we're aggressively playing in the broader serverless ecosystem. So what we're looking at is as Evan mentioned, sometimes the databases is the last thing to change, it's also not necessarily the first thing that a developer starts from when they think about building their application or their website. And so we're plugging into the larger serverless ecosystem where people are making their choices about potentially their compute platform or maybe a development platform like I know you've talked to the folks over at JAMstack, sorry at Netlify and Purcell, who are big in the JAMstack community and providing really great workflows for new web and application developers on these platforms. And then at the compute layer, obviously, our Amazon, Google, Microsoft all have a serverless compute solution. CloudFlare is doing some really interesting things out at the edge. And so there's a variety of people up and down that stack, if you will, when people are thinking about this new generation of applications that we're plugging into to make sure that the Fauna is that the default database of choice. >> Wonderful, last question, Evan if I could, I love what I got somebody with your background. Talk about just so many different technologies maturing, give us a little bit as to some of the challenges you see serverless ecosystem, what's being attacked, what do we still need to work on? >> I mean, serverless is in the same place that Lamp was in the in the early '90s. We have the old conservatives ecosystem with the JAMstack players that Eric mentioned. We have closed proprietary ecosystems like the AWS stack or the Google Firebase stack. As to your point, Google has also invested in us so they're placing their bets widely. But it's seeing the same kind of criticism. That Lamp, the Linux, Apache, MySQL, PHP, Perl, it's not mature, it's a toy, no one will ever use this for real business. We can't switch from like DV2 or mumps to MySQL, like no one is doing that. The movement and the momentum in serverless is real. And the challenge now is for all the vendors in collaboration with the community of developers to mature the tools as those the products and applications being built on the new more productive stack also mature, so we have to keep ahead of our audience and make sure we start delivering and this is partly why Eric is here. Those those mid market and ultimately enterprise requirements so that business is built on top of Fauna today, can grow like Twitter did from small to giant. >> Yeah, I'd add on to that, this is reminiscent for me, back in 2009 at Okta, we were one of the early ISVs that built on in relied 100% on AWS. At that time there was still, it was very commonplace for people racking and stacking their own boxes and using Colo and we used to have conversations about I wonder how long it's going to be before we exceed the cost of this AWS thing and we go and run our own data centers. And that would be laughable to even consider today, right, no one would ever even think about that. And I think serverless is in a similar situation where the consumption model is very attractive to get started, some people sitting there, is it going to be too expensive as I scale. And as Evan mentioned, when we think about if you fast forward to kind of what the innovation that we can anticipate both technologically and economically it's just going to be the default model that people are going to wonder why they used to spend all these time managing these machines, if they don't have to. >> Evan and Eric, thank you so much, is great to hear the progress that you've made and big supporters, the serverless ecosystem, so excited to watch the progress there. Thanks so much. >> Thanks Stu. >> Thanks for having us Stu. >> All right and I'm Stu Miniman. Stay tuned. Every week we are putting out the Cloud Native Insights. Appreciate. Thank you for watching. (bright upbeat music)

(upbeat techno music) >> Live from Barcelona Spain, it's theCUBE. Covering KubeCon CloudNativeCon Europe 2019. Brought to you by Red Hat, The Cloud Native Computing Foundation and Ecosystem Partners. >> Welcome back, this is The Cube's coverage of KubeCon CloudNativeCon 2019. I'm Stu Miniman with Corey Quinn as my cohost, even though he says kucon. And joining us on this segment, we're not going debate how we pronounce certain things, but I will try to make sure that I get Bridget Kromhout correct. She is a Principle Cloud Advocate at Microsoft. Thank you for coming back to The Cube. >> Thank you for having me again. This is fun! >> First of all I do have to say, the bedazzled shirt is quite impressive. We always love the sartorial, ya know, view we get at a show like this because there are some really interesting shirts and there is one guy in a three-piece suit. But ya know-- >> There is, it's the high style, got to have that. >> Oh, absolutely. >> Bringing some class to the joint. >> Wearing a suit is my primary skill. (laughing) >> I will tell you that, yes, they sell this shirt on the Microsoft company store. And yes, it's only available in unisex fitted. Which is to say much like Alice Goldfuss likes to put it, ladies is gender neutral. So, all of the gentleman who say, but I have too much dad bod to wear that shirt! I say, well ya know get your bedazzlers out. You too can make your own shirt. >> I say it's not dad bod, it's a father figure, but I digress. (laughing) >> Exactly! >> Alright, so Bridget you're doing some speaking at the conference. You've been at this show a few times. Tell us, give us a bit of an overview of what you're doing here and your role at Microsoft these days. >> Absolutely. So, my talk is tomorrow and I think that, I'm going to go with its a vote of confidence that they put your talk on the last day at 2:00 P.M. instead of the, oh gosh, are they trying to bury it? But no, it's, I have scheduled enough conferences myself that I know that you have to put some stuff on the last day that people want to go to, or they're just not going to come. And my talk is about, and I'm co-presenting with my colleague, Jessica Deen, and we're talking about Helm 3. Which is to say, I think a lot of times it would, with these open-sourced shows people say, oh, why do you have to have a lot of information about the third release of your, third major release of your project? Why? It's just an iterative release. It is, and yet there are enough significant differences that it's kind of valuable to talk about, at least the end user experience. >> Yeah, so it actually got an applause in the keynote, ya know. (Bridget laughing) There are certain shows where people are hootin' and hollerin' for every, different compute instance that that is released and you look at it a little bit funny. But at the keynote there was a singular moment where it was the removal of Tiller which Corey and I have been trying to get feedback from the community as to what this all means. >> It seems, from my perspective, it seemed like a very strange thing. It's, we added this, yay! We added this other thing, yay! We're taking this thing and ripping it out and throwing it right into the garbage and the crowd goes nuts. And my two thoughts are first, that probably doesn't feel great if that was the thing you spent a lot of time working on, but secondly, I'm not as steep in the ecosystem as perhaps I should be and I don't really know what it does. So, what does it do and why is everyone super happy to con sine it to the dub rubbish bin of history? >> Right, exactly. So, first of all, I think it's 100% impossible to be an expert on every single vertical in this ecosystem. I mean, look around, KubeCon has 7,000 plus people, about a zillion vendor booths. They're all doing something that sounds slightly, overlapping and it's very confusing. So, in the Helm, if you, if people want to look we can say there's a link in the show notes but there, we can, people can go read on Helm.sh/blog. We have a seven part, I think, blog series about exactly what the history and the current release is about. But the TLDR, the too long didn't follow the link, is that Helm 1 was pretty limited in scope, Helm 2 was certainly more ambitious and it was born out of a collaboration between Google actually and a few other project contributors and Microsoft. And, the Tiller came in with the Google folks and it really served a need at that specific time. And it was, it was a server-side component. And this was an era when the Roll by Stacks has control and Kubernetes was, well nigh not existent. And so there were a lot of security components that you kind of had to bolt on after the fact, And once we got to, I think it was Kubernetes 1.7 or 1.8 maybe, the security model had matured enough that instead of it being great to have this extra component, it became burdensome to try to work around the extra component. And so I think that's actually a really good example of, it's like you were saying, people get excited about adding things. People sometimes don't get excited about removing things, but I think people are excited about the work that went into, removing this particular component because it ends up reducing the complexity in terms of the configuration for anyone who is using this system. >> It felt very spiritually aligned in some ways, with the announcement of Open Telemetry, where you're taking two projects and combining them into one. >> Absolutely. >> Where it's, oh, thank goodness, one less thing that-- >> Yes! >> I have to think about or deal with. Instead of A or B I just mix them together and hopefully it's a chocolate and peanut butter moment. >> Delicious. >> One of the topics that's been pretty hot in this ecosystem for the last, I'd say two years now it's been service matched, and talk about some complexity. And I talk to a guy and it's like, which one of these using? Oh I'm using all three of them and this is how I use them in my environment. So, there was an announcement spearheaded by Microsoft, the Service Mesh Interface. Give us the high level of what this is. >> So, first of all, the SMI acronym is hilarious to me because I got to tell you, as a nerdy teenager I went to math camp in the summertime, as one did, and it was named SMI. It was like, Summer Mathematics Institute! And I'm like, awesome! Now we have a work project that's named that, happy memories of lots of nerdy math. But my first Unix system that I played with, so, but what's great about that, what's great about that particular project, and you're right that this is very much aligned with, you're an enterprise. You would very much like to do enterprise-y things, like being a bank or being an airline or being an insurance company, and you super don't want to look at the very confusing CNCF Project Map and go, I think we need something in that quadrant. And then set your ships for that direction, and hopefully you'll get to what you need. And it's especially when you said that, you mentioned that, this, it basically standardizes it, such that whichever projects you want to use, whichever of the N, and we used to joke about JavaScript framework for the week, but I'm pretty sure the Service Mesh Project of the week has outstripped it in terms of like speed, of new projects being released all the time. And like, a lot of end user companies would very much like to start doing something and have it work and if the adorable start-up that had all the stars on GitHub and the two contributors ends up, and I'm not even naming a specific one, I'm just saying like there are many projects out there that are great technically and maybe they don't actually plan on supporting your LTS. And that's fine, but if we end up with this interface such that whatever service mesh, mesh, that's a hard word. Whatever service mesh technology you choose to use, you can be confident that you can move forward and not have a horrible disaster later. >> Right, and I think that's something that a lot of developers when left to our own devices and in my particular device, the devices are pretty crappy. Where it becomes a, I want to get this thing built, and up and running and working, and then when it finally works I do a happy dance. And no one wants to see that, I promise. It becomes a very different story when, okay, how do you maintain this? How do you responsibly keep this running? And it's, well I just got it working, what do you mean maintain it? I'm done, my job is done, I'm going home now. It turns out that when you have a business that isn't being the most clever person in the room, you sort of need to have a longer term plan around that. >> Yeah, absolutely. >> And it's nice to see that level of maturation being absorbed into the ecosystem. >> I think the ecosystem may finally be ready for it. And this is, I feel like, it's easy for us to look at examples of the past, people kind of shake their heads at OpenStack as a cautionary tale or of Sprawl and whatnot. But this is a thriving, which means growing, which means changing, which means very busy ecosystem. But like you're pointing out, if your enterprises are going to adapt some of this technology, they look at it and everyone here was, ya know, eating cupcakes or whatever for the Kubernetes fifth birthday, to an enterprise just 'cause that launched in 2014, June 2014, that sounds kind of new. >> Oh absolutely. >> Like, we're still, we're still running that mainframe that is still producing business value and actually that's fine. I mean, I think this maybe is one of the great things about a company like Microsoft, is we are our customers. Like we also respect the fact that if something works you don't just yolo a new thing out into production to replace it for what reason? What is the business value of replacing it? And I think for this, that's why this, kind of Unix philosophy of the very modular pieces of this ecosystem and we were talking about Helm a little earlier, but there's also, Draft, Brigade, etc. Like the Porter, the CNET spec implementation stuff, and this Cloud Native application bundles, that's a whole mouthful. >> Yes, well no disrespect to your sparkly shirt, but chasing the shiny thing, and this is new and exciting is not necessarily a great thing. >> Right? >> I heard some of the shiny squad that were on the show floor earlier, complaining a little bit about the keynotes, that there haven't been a whole lot of new service and feature announcements. (Bridget laughing) And my opinion on that is feature not bug. I, it turns out most of us have jobs that aren't keeping up with every new commit to an open-source project. >> I think what you were talking about before, this idea of, I'm the developer, I yolo'd out this co-load into production, or I yolo'd this out into production. It is definitely production grade as long as everything stays on the happy path, and nothing unexpected happens. And I probably have air handling, and, yay! We had the launch party, we're drinkin' and eatin' and we're happy and we don't really care that somebody is getting paged. And, it's probably burning down. And a lot of human misery is being poured into keeping it working. I like to think that, considering that we're paying attention to our enterprise customers and their needs, they're pretty interested in things that don't just work on day one, but they work on day two and hopefully day 200 and maybe day 2000. And like, that doesn't mean that you ship something once and you're like, okay, we don't have to change it for three years. It's like, no, you ship something, then you keep iterating on it, you keep bug fixing, you keep, sure you want features, but stability is a feature. And customer value is a feature. >> Well, Bridget I'm glad you brought that up. Last thing I want to ask you 'cause Microsoft's a great example, as you say, as a customer, if you're an Azure customer, I don't ask you what version of Azure you're running or whether you've done the latest security patch that's in there because Microsoft takes care of you. Now, your customers that are pulled between their two worlds is, oh, wait, I might have gotten rid of patch Tuesdays, but I still have to worry and maintain that environment. How are they dealing with, kind of that new world and still have, certain things that are going to stay the old way that they have been since the 90's or longer? >> I mean, obviously it's a very broad question and I can really only speak to the Kubernetes space, but I will say that the customers really appreciate, and this goes for all the Cloud providers, when there is something like the dramatic CVE that we had in December for example. It's like, oh, every Kubernetes cluster everywhere is horribly insecure! That's awesome! I guess, your API gateway is also an API welcome mat for everyone who wants to, do terrible things to your clusters. All of the vendors, Microsoft included, had their managed services patched very quickly. They're probably just like your Harple's of the world. If you rolled your own, you are responsible for patching, maintaining, securing your own. And this is, I feel like that's that tension. That's that continuum we always see our customers on. Like, they probably have a data center full of ya know, veece, fear and sadness, and they would very much like to have managed happiness. And that doesn't mean that they can easily pickup everything in the data center, that they have a lease on and move it instantly. But we can work with them to make sure that, hey, say you want to run some Kubernetes stuff in your data center and you also want to have AKS. Hey, there's this open-source project that we instantiated, that we worked on with other organizations called Vertual Kubelet. There was actually a talk happening about it I think in the last hour, so people can watch the video of that. But, we have now offered, we now have Virtual Node, our product version of it in GA. And I think this is kind of that continuum. It's like, yes of course, you're early adapters want the open-source to play with. Your enterprises want it to be open-source so they can make sure that their security team is happy having reviewed it. But, like you're saying, they would very much like to consume a service so they can get to business value. Like they don't necessarily want to, take, Kelsey's wonderful Kubernetes The Hard Way Tutorial and put that in production. It's like, hmm, probably not, not because they can't, these are smart people, they absolutely could do that. But then they spent their, innovation tokens as, the McKinley blog post puts it, the, it's like, choose boring technology. It's not wrong. It's not that boring is the goal, it's that you want the exciting to be in the area that is producing value for your organization. Like that's where you want most of your effort to go. And so if you can use well vetted open-source that is cross industry standard, stuff like SMI that is going to help you use everything that you chose, wisely or not so wisely, and integrate it and hopefully not spend a lot of time redeveloping. If you redevelop the same applications you already had, its like, I don't think at the end of the quarter anybody is getting their VP level up. If you waste time. So, I think that is, like, one of the things that Microsoft is so excited about with this kind of open-source stuff is that our customers can get to value faster and everyone that we collaborate with in the other clouds and with all of these vendor partners you see on the show floor, can keep the ecosystem moving forward. 'Cause I don't know about you but I feel like for a while we were all building different things. I mean like, instead of, for example, managed services for something like Kubernetes, I mean a few jobs that would go out was that a start up that we, we built our own custom container platform, as one did in 2014. And, we assembled it out of all the LEGOs and we built it out of I think Docker and Packer and Chef and, AWS at the time and, a bunch of janky bash because like if someone tells you there's no janky bash underneath your home grown platform, they are lying. >> It's always a lie, always a lie. >> They're lying. There's definitely bash in there, they may or may not be checking exit codes. But like, we all were doing that for a while and we were all building, container orchestration systems because we didn't have a great industry standard, awesome! We're here at KubeCon. Obviously Kubernetes is a great industry standard, but everybody that wants to chase the shiny is like but surface meshes. If I review talks for, I think I reviewed talks for KubeCon in Copenhagen, and it was like 50 or 60 almost identical service mesh talk proposals. And it's like, and then now, like so that was last year and now everyone is like server lists and its like, you know you still have servers. Like you don't add sensation to them, which is great, but you still have them. I think that that hype train is going to keep happening and what we need to do is make sure that we keep it usable for what the customers are trying to accomplish. Does that make sense? >> Bridget, it does, and unfortunately, we're going to have to leave it there. Thank you so much for sharing everything with our audience here. For Corey, I'm Stu, we'll be back with more coverage. Thanks for watching The Cube. (upbeat techno music)

>> Announcer: Live from Nassau in the Bahamas, it's theCUBE, covering Polygon 18, brought to you by Polyman. >> Welcome back everyone, we're here live with theCUBE's exclusive coverage of Polycon '18. We're in the Bahamas, I'm John Furrier with Dave Vellante, co-founders and co-hosts of theCUBE. We're here with special guest Halsey Minor, entrepreneur, serious serial entrepreneur here on theCUBE. Halsey, great to have you. You're the founder and CEO of VideoCoin, a successful ICO. You had an event last night, kind of an investor thank you event out in the Bahamas Country Club, there, you're here. Man, you're a pro, you're back in the game with this crypto. This is the wave, I mean, I want to get your perspective 'cause you see waves. You've seen CNET, you started that from scratch before online news was anything, you were the pioneer in that. First investor, first operator in salesforce.com, a variety of other successful entrepreneurial adventures. You've got a nose for the waves. So just put it in perspective, what is this wave? >> Yeah, so I actually have an interesting story because I've actually started around 2012, and I launched my first business in 2013. So, the first problem that I saw was, how do you get your money from your bank account and buy Bitcoin? Still a problem, hasn't been fixed, right? So I tried to fix that. Oh well, I did to a certain extent, I did fix the problem. So what I did was created effectively a coin-based converter, and I started out and was going to make it very easy for you to take your bank account, connect it up, seemed logical, and then buy, you know, the currency. The company was called Bit Reserve at the time. So, no bank would touch anybody named Bit in their name. And it was even worse than that, all of us who put our company name into our bank account, we had our bank accounts basically shut down, right? So, I started getting an idea how difficult this was going to be, you know, Coinbase getting a Silicon Valley bank account early on to become a conduit, was very fortuitous. It ultimately took two and a half years and buying a big chunk of New Jersey Bank before we were able to allow you to connect your US bank and your European bank into Uphold to buy currency. So it's really Uphold, Coinbase, maybe like Gitbit, very, very few who've been able to crack that problem. We literally had to buy part of a bank to do it. So that's where I started. So I really looked at it very much as money, as a new monetary system. And I still see unlimited opportunities in that area. It wasn't until really a couple years later that I saw the block chain as the new architecture for the computer, and what I mean by that, is what Bitcoin proved was that if you gave people software and they ran it on their computer and they got paid in some funny kind of digital money, they would convert that money back into fee hock, you know, dollars, and they go buy more computers. And nobody asks anybody to be a Bitcoin miner, they just come and showed up the more, the bigger it got, the bigger the opportunity. And what's most interesting is when you make money or lose money, depends on your cost of power. So for most of these Bitcoin miners, they're near hydroelectric dams. So what I realized, and VideoCoin is in the area of video. It's a direct competitor with Amazon web services, everything they do in video. So there's, it's called encoding which is compress it, there's storage and there's streaming, three basic pieces. So what I realized was, two things: first of all, 20% of servers and data centers are not used at all. They're called zombies, right? So all of these people, the Airbnb, Uber model, they can all of a sudden start earning on assets that are doing nothing. But even if you look out into the future, if video mining, which is what we call it, ends up being like bitcoin mining, then what happens is that the whole thing works on the cost of power. It's not good for Amazon, if they have to be competitive solely based on the cost of power. >> Dave, so he's got an ICO going on, we looked Filecoin, right? So Filecoin was storage and that's infrastructure. You go to VideoCoin, we're streaming right now, we've got video. This is kind of like an interesting digital media infrastructure ... >> Well ... >> What's your take compared to Filecoin? >> What's interesting to me is that I'd love to get Halsey's input on, because you've got the full spectrum here. You started in publishing and now-- >> With five TV shows. >> Dave: Okay. >> Yeah, CNET had five TV shows. >> So right, and so very digital from the beginning and relatively ripe for disruption and then now into banking, which really hasn't been disrupted, but we all think it's coming. So that's an interesting spectrum. It's not Negroponte, I don't think, bits versus atoms, because you've seen, you know tax season get disrupted. That's atoms. So what are the factors that make an industry ripe for disruption? >> Well, I mean the obvious thing is really disruptive technologies, right? And so for the Internet, for me, it was, I started the company in '93 to be on commercial online services like AOL and I saw, I guess, the first browser in '93 and, actually at Sun, and it made me believe the Internet was going to be this incredible thing. And it was really seeing information coming in, and, you know, the Internet wasn't that big back then but I watched a gif of a storm, you know, from one of the weather centers, and so I realized that this information thing was incredibly interesting. And so what all of us did, the way I thought about it and seen it, is we're cracking open databases and we're just letting people have the information. And it was silly things like the ability for me to live in San Francisco but know what the weather was in New York and pack appropriately. This was the magic, I mean, we take all of this for granted. This was magic, right, at the time. You had to go out and buy a USA Today-- >> Check the stock price. >> Yeah, exactly. >> Call your friends in New York. >> Yeah, that was magic. So at a very high level, it was just access to information. At a very high level, what this is is combining information and money into a packet. Right? So now what we can do is, I can gather information from servers about what they're really doing and I can also be paying them at the same time. So you know, it would have actually solved a lot of problems around the Internet, because on the Internet getting paid was hard. And there were so many times we'd go into a meeting and we'd agree on the partnership but we didn't know who was paying who. You know? (laughing) Am I paying you for traffic or are you paying me for content or you know, how is that going? So this kind of comes with a built-in payment system, which I think is what makes it so incredible as a system. >> So we're-- >> And more stable, I am inferring, long-term anyway. Because that whole system that you just described on the Internet all blew up when the funding dried up. >> It blew up and I think, you know, I think there are certainly a lot of risks. The number one thing I would tell everybody in this area is, you know, be very cautious about what in you invest in. There were a lot of companies that, uh-- so my whole description was sort of the Internet bubble was that people say that, well, you know, nine trillion dollars was lost in investing. >> With everything that happened though. >> And when I-- >> The plus.com happened, everything happened. >> And what I said to the people is that it would be great if people had just invested in the survivors, but who knew what they were? The only reason the United States emerged, with, you know, with Salesforce and Ebay and Amazon, etc., the only reason that we emerged dominating the world was 'cause we invested in them all. Right? And so-- >> Even all those things that were called silly ideas actually happened. >> And they ended up happening. It was all a matter of timing, yeah. So you know, what's happening now is very much the same thing. You know, a lot of people are going to invest in a lot of bad ideas, right? But this is all necessary for the good ideas to get funding and for something big to come out of this. >> So I want to get your take on with the VideoCoin and in comparison, you mentioned Amazon, right? So our observation, obviously we're recording all these shows, Amazon web service, among others, the big guys are sucking all the oxygen out of the room. Look at the big whales, Google, Facebook, Amazon, I mean, we can't even run any ads on our site. We actually prefer to just push the content all over the world because it's hard to build a destination site. I mean, people going out of business in the media business. Video, your choices are Ustream now owned by IBM, Twitch TV became Amazon which was Ustream before that. Build your own custom player, set up a CDN, which is actually hard and expensive. Okay, so do I do Facebook live, again controlled by Facebook? So there's an opportunity that you're pursuing. Did you have that in mind? I mean, we see it every day and we know this, but luckily we have a good deal with Ustream, but the point is that is going to be up too. What's the alternative producers, content producers who have streaming, whether it's a pro set like this or someone who's going to have unlimited access to video streaming? >> So the real issues are cost and innovation, okay? And so Hanno Basse, who's the CTO of 20th Century Fox and one of our advisors, right? And all these media companies have the same problem. Nobody is watching broadcast anymore that'll cost them nothing and everybody's now streaming in, which is one-to-one and has a cost associated with it. So that's why, and even worse, videos going to 4k, 8k, VR, data that's going up like this-- >> Data isn't growing as fast either. >> So all these companies are confronted with all these costs and they can't monetize them. Google can monetize it, Amazon can monetize it. >> Tel cos ... >> Netflix, yeah. >> Ouch. >> But they can't monetize it, so it's all cost effectively and no revenue. So the one thing that we offered to VideoCoin by using all this research is we cut the cost 60 to 80%, so that's huge. The other thing is, in the early days, everybody bought Salesforce because it was cheaper. It was 1/10th of the cost. And I used to say to people, in the long run, it's going to be way more innovation, right? Because they're constantly, every quarter, rolling out a new version, right? And they're going to have the ability to connect, an API effectively, and the ability to connect, and the whole ecosystem can arise around that. And that's why their conference has 140,000 people, Dreamforce, because there's a whole ecosystem. >> It's sticky as hell too. >> That's right. >> Hard to get out. >> That's right. So while we are 60 to 80% lower cost, we're also effectively open source at the same time. So the ability to have a community arise and develop software. And so right now, you've seen this huge consolidation because it's actually kind of hard to build new kinds of apps on top of Amazon web services, right? But if you have this open system, and you have all these people are contributing code to it, all of a sudden, there are apps, video apps, that they'll be literally a whole new-- >> So you're going to have an open source contribution piece to your ... ? >> Yeah, I mean basically, everything we build is open source, right, so you know, all the way through to the network. So it creates a palate for people to start innovating in video. Because really what's happening is a lot of innovation is getting hurt by the fact these big guys totally dominate it, right? They don't want to see any innovation outside of the funds they bring you, right? >> Right, so you've heard my rap on this. I'd love to get Halsey's thoughts. So the big guys, you're right, have won. It's like centralization and victory. People here are saying, "No, we want to take it back." The premise that I hear a lot is there's been no innovation in protocols in, you know ... Google built gmail on SMPT, HTTP, DNS, it's all government-funded or academia. >> Yeah. >> And it's just a lack of innovation. >> That's right. >> And now, this is why I counter Warren Buffet and Charlie Monger, is no, we're building out a new set of infrastructure. >> That's right. >> Okay, so where do you guys fit into that? What are your thoughts, first of all, on that premise? And where do you guys fit? >> Yeah, I mean, look, you've got these huge companies that are totally dominant and even though they are, in fact, you know, innovative Silicon Valley companies by label, okay, they have all the same issues-- like I say to people, nobody today believes that anybody can put Amazon web services at risk. If I went to somebody and said, "You know Amazon web services which are worth 3/4 "of the value of the company, or 5/6, "depending on who you talk to, "there's going to be something after that." It would literally be a new concept because everybody's convinced this is Amazon's-- >> John: The winner. >> Yeah, this is their big, this is the way they make all their money-- >> Alright it's over-- >> Right, and if you say to somebody there is going to be a next thing, they would look at you like, you know, like you're foolish. But the reality is when you start changing some basic, underlying infrastructure in the Internet and you start doing things, decentralization, this is the word we're going to be using, you know, we're going to see it in solar power. And solar power is, you know, on a cost to benefit like this so, you know, it isn't going to be long before we're going to have power in our house legitimately, not like, you know, some science-fiction thing, we'll be legitimately powering most of our needs with solar that we connect because the cost is coming down so much. So we're going to see all of this decentralization happening. And in the world of computing, decentralization means that this is going to be the most efficient that computing can ever be. Because just compare using the Uber and Airbnb model of saying anything that's excess, let's turn into value. And I've heard that for every Uber driver, 15 cars go away, right? So the decentralization is going to have a profound effect on the economy and it's going to have a profound effect on these big guys. >> Oh, even those guys are going to get disrupted. >> They're going to get disrupted. And they're 20 years old, it's time for them to get disrupted, I mean, you know ... >> E-commerce is a 20, 30-year-old stack, some say 20, 20-year-old stack on e-commerce, all these things are ready, even what we would consider modern, you know, the miracle of saying oh the weather in New York. I mean that magic is here now in a new way. So I got to ask you the question-- >> Taken for granted. >> I got to ask you a question because you brought up that point. In your history of your career as an entrepreneur because you're doing stuff that's always new and cool, and probably before anyone else sees it, can you talk about some of the ideas that you've seen, not necessarily your ideas, as well others, where the investor said, "That's the dumbest idea "I ever heard"? What billion dollar opportunities have you seen emerge that investors have said, "That's the dumbest idea "I've ever heard"? >> Well, actually, the one that is Salesforce. No VC would put money in. It was really kind of backed by Larry Ellison and me early on. And what's so-- >> John: Google was a dumb idea. We want portals, not search. >> Yeah, so the bet that nobody would take in 2000 was that companies would take their sales information and they would put it in the cloud. Nobody would believe that. Not anyone. And so I used to joke, I used to say the only way it's going to happen is if the sales guy's been waiting two years to get his sales management system in place actually runs over the head of security in the parking lot. That's what it's going to take because it's outsourcing and, you know, the security guys say, "Oh, no, no, no, "we're going to lose all of our data", right? It didn't matter that Salesforce had way more security guys, you know, than these guys had and better, you know, working internally. Nobody believed in it. Literally nobody believed in it. >> This is your point about the decentralization, no one's going to believe, "Wait a minute, "that could never happen." So, in a way, the investor thesis should be, "I want to invest in the dumbest ideas," because that might be the best idea. >> It is. I mean the big, obvious ones that attract billions and billions of dollars, I mean, how many of those end up actually not turning into anything? Right? A lot of them, right? So CDAT was profitable on nine million dollars. I believe that Yahoo was profitable on three million dollars. I think Google was somewhere around 12 to 15 million dollars, right? So there are a lot of these business-- Amazon's obviously the outlier. >> John: It's still not profitable. >> Yeah, it's the outlier. But you know, a lot of these businesses were started by people who used a relatively small amount of money and were very creative. You know, you're going to hear this over and over again. Microsoft never needed any money. They accepted five million dollars from-- >> John: (mumbles) >> Yeah, so this happens a lot. And in fact, I think it's very dangerous when in year five, you're losing three hundred million dollars, right? I mean, five hundred, or whatever it is. There are a lot of things that can go wrong. >> What's the role of community? Because we heard the guy from Locktower Capital say something I thought was really profound, "I don't need VC because, if you're a startup, "you don't have to waste your energy on board meetings "and other things, you can build your business "and use the community as your benchmark." So this plays to your whole picking up the slack kind of thing in efficiency. So entrepreneurs can be more efficient in these communities. This is where the cryptocurrency Blockchain is thriving. What's your thoughts to that and how do you see that community interaction progressing? >> In my career, there's been a sea change in sort of the culture of technology and really everything, right? You know, when I started out, everything was very hierarchical. You know, it's like how far up the chain you got that measured how successful you were. Now it's how big is your network, right? And you know, I was talking to somebody the other day who said VCs are going in and they're measuring these companies' success by how many Instagram and Twitter accounts they have and there's massive fraud going on because people are buying these accounts to pump up their numbers, right? So people are starting to value by the breadth of your network. >> John: Reputable network. >> Reputable, yeah. >> John: Not fake network. >> Yeah, but what I heard is there's actually a Twitter application which I haven't seen that'll go in and tell how many of 'em are real and how many of 'em are not now. So really the community becomes almost the measuring stick for your value. You know, before I'd seen it, I had users. Today, everybody has community members. And so, it becomes sort of, kind of like everything I guess. >> And our media model is all community-based which is, we just naturally go there because that's where the data is. >> That's right. >> That's where the feedback is. >> That's right. >> I mean, I can't get feedback from Facebook and Google, they own the data, right? There's no letters to the editor on Facebook. There's only hate comments. >> But you know before Microsoft and all these came, you know, IBM dominated the world. Nobody ever thought they would go away. AT&T dominated the world and nobody ever thought that they would go away, you know. >> Alright, personal question for you, I got to wrap because I know you got to go. Appreciate your time, by the way. Great story, we could go on for another hour. Personal note, what is the most compelling thing that's moved you, as an entrepreneur, in the crypto market? Like, something that, it could be an anecdote, it could be a situation. When you look at this opportunity, as the world's going to eventually be re-instrumented with data, with new open source and community, what's something that's surprised you or moves you as an entrepreneur saying, "This is freakin' awesome"? >> So this hasn't been done yet but it will be done. So this is what actually motivated me to start Uphold was the ability to turn your phone into your bank and to be able to exchange money and primarily really solving the ability for the poor to be able to move money around without having 10 to 20 to 30% of it taken away. Everybody's talked about this, remittance, and so far, nobody has actually solved that problem. That problem is going to get solved. I mean it's inevitable that the phone becomes the bank. There are so many regulations that are designed to stop that and it's extraordinary. Once you get into it and you see all the ways that have been set up-- >> Byzantine system. >> this problem should have been solved long ago, right? And every phone should be a bank. I mean, it can be connected to a bank, but every phone should have my money in it. I should be able to send it to you instantaneously. >> It shouldn't be like getting into Fort Knox. >> Yeah. I mean, computers, banks have computers, they could make this happen today. They just don't want to. So I think the most profound thing for me is the problem is still not solved, that the problem I set out to solve, which is really creating a more equitable financial system. And we live in a country where the banks make about 37 billion dollars a year in bounced check fees. Think about that. Thirty-seven billion dollars in bounced check fees. So if you just take that out, you just take out, 'cause it all affects people in the lower socioeconomic scale, you create a revolution. Just getting rid of the bank fees that you'll pay for bouncing checks. >> Well, I mean the narratives, like the narrative of taking down gatekeepers or central authorities, is the premise of this ecosystem and you could take that example and apply it to thousands of use cases. >> And banks are rapacious, flat out. American banks are the most rapacious 'cause no other country would allow 37 billion dollars to be taken away in bounced check fees. >> Halsey, congratulations on your success again and great to see you on theCUBE. You're now a Cube alumni, so ... >> Congratulations. >> We hope you'll come back again. >> Yeah, thank you guys. >> We're going to get you in our telegram group, now you'll be 42 members, we just turned on last night. (everyone laughs) We appreciate it and congratulations. >> Thank you very much. >> Thanks for your insight and experience and commentary. Halsey Minor, experienced entrepreneur, pro, here in the trenches, establishing a great new venture. We'll be back with more live coverage after this short break. (electronic music)