>>Live from Las Vegas. That's the Q covering splunk.com 19 brought to you by Splunk. >>You know, kind of leaning on that heavily. Automation, certainly very important. But what does enterprise and what does enterprise security 6.0 bring to the table. So can you take us through the evolution of where you guys are at with, with Splunk, if you want to handle that enterprise security? So yeah, generally enterprise security has traditionally had really, really good use cases for like the external threats that we're talking about. But like you said, it's very difficult to crack the insider threat part. And so we leveraging machine learning toolkit has started to build that into Splunk to make sure that you know, you can protect your data. And, uh, you know, Tyler and I specifically did this because we saw that there was immaturity in the cybersecurity market for insider threat. And so one of the things that we're actually doing in this top, in addition to talking about what we've done, we're actually giving examples of actionable use cases that people can take home and do themselves. >>Like we're giving them an exact sample code of how to find some outliers. They give me an example of what, so the use case that we go over in the talk is a user logs in at a weird time of day outside of their baseline and they exfiltrate a large amount of data in a low and slow fashion. Um, but they're doing this obviously outside of the scope of their normal behavior. So we give some good searches that you can take home and look at how could I make a baseline, how could I establish that there's deviations from that baseline from a statistical standpoint, and identify this in the future and find the needle in the haystack using the machine learning toolkit. And then if I have a sock that I want to send notables to or some sort of some notification to how do we make that happen, how do we make the transition from machine learning toolkit over to enterprise security or however your SOC operates? >>How do you do that? Do you guys write your own code for that? Or you guys use Splunk? So Splunk has a lot of internal tools and there's a couple of things that need to be pointed out of how to make this happen because we're aggregating large amounts of data. We go through a lot of those finer points in the talk, but sending those through to make sure that they're high confidence is the, is the channel you guys are codifying the cross connect from the machine, learning to the other systems. All right, so I've got to ask, this is basically pattern recognition. You want to look at baselining, how do people, can people hide in that baseline data? So like I'll give you, if I'm saying I'm an evil genius, I say, Hey, I knew these guys looking for Romans anomalies in my baseline, so I'm going to go low and slow in my baseline. >>Can you look for that too? Yeah, there are. There absolutely are ways of, fortunately, uh, there's a lot of different people who are doing research in that space on the defensive side. And so there's a ton of use cases to look at and if you aggregate over a long enough period of time, it becomes incredibly hard to hide. And so the baselines that we recommend building generally look at your 90 day or 120 day out. Um, I guess viewpoint. So you really want to be able to measure that. And most insider threat that happen occur within that 30 to 90 day window. And so the research seems to indicate that those timelines will actually work. Now if you were in there and you read all the code and you did all of the work to see how all of the things come through and you really understood the machine learning minded, I'm sure there's absolutely a way to get in if you're that sophisticated. >>But most of the times they just trying to steal stuff and get out or compromise a system. Um, so is there other patterns that you guys have seen in terms of the that are kind of low hanging fruit priorities that people aren't paying attention to and what's the levels of importance to I guess get ahold of or have some sort of mechanism for managing insider threats? I passwords I've seen one but I mean like there's been a lot of recent papers that have come out in lateral movement and privilege escalation. I think it's an area where a lot of people haven't spent enough time doing research. We've looked into models around PowerShell, um, so that we can identify when a user's maliciously executing PowerShell scripts. I think there's stuff that's getting attention now that when it really needs to, but it is a little bit too late. >>Uh, the community is a bit behind the curve on it and see sharks becoming more of a pattern to seeing a lot more C sharp power shells kind of in hunted down kind of crippled or like identified. You can't operate that way, what we're seeing but, but is that an insider and do that. And do insiders come in with the knowledge of doing C sharp? Those are gonna come from the outside. So I mean, what's the sophistic I guess my question is what's the sophistication levels of an insider threat? Depends on the level a, so the cert inside of dread Institute has aggregated about 15,000 different events. And it could be something as simple as a user who goes in with the intent to do something bad. It could be a person who converted from the inside at any level of the enterprise for some reason. >>Or it could be someone who gets, you know, really upset after a bad review. That might be the one person who has access and he's being socially engineered as well as all kinds of different vectors coming in there. And so, you know, in addition to somebody malicious like that, that you know, there's the accidental, you're phishing campaigns here, somebody's important clicks on an email that they think is from somebody else important or something like that. And you know, we're looking fair for that as well. And that's definitely spear fishing's been very successful. That's a hard one to crack. It is. They have that malware and they're looking at, you can say HR data's out of this guy, just got a bad review, good tennis cinema, a resume or a job opening for, and that's got the hidden code built in. We've seen that move many times. >>Yeah, and natural language processing and more importantly, natural language understanding can be used to get a lot of those cases out. If you're ingesting the text of the email data, well you guys are at a very professional high end from Sai C I mean the history of storied history goes way back and a lot of government contracts do. They do a lot of heavy lifting from anywhere from development to running full big time OSS networks. So there's a lot of history there. What does sustain of the yard? What do you guys look at as state of the art right now in security? Given the fact that you have some visibility into some of the bigger contracts relative to endpoint protection or general cyber, what's the current state of the art? What's, what should people be thinking about or what are you guys excited about? What are some of the areas that is state of the art relative to cyber, cyber security around data usage. >>So, I mean, one of the things, and I saw that there were some talks about it, but not natural language processing and sentiment analysis has gotten, has come a long way. It is much easier to understand, you know, or to have machines understand what, what people are trying to say or what they're doing. And especially, for example, if somebody's like web searching history, you know, and you might think of somebody might do a search for how do I hide downloading a file or something like that. And, and that's something that, well, we know immediately as people, but you know, we have, our customer for example, has 1000000001.2 billion events a day. So you know, if the billion, a billion seconds, that's 30 years. Yeah. So like that's, it's, it's a big number. You know, we, we, we hear those numbers thrown around a lot, but it's a big number to put it in perspective. >>So we're getting that a day and so how do we pick out, it's hard to step of that problem. The eight staff, you can't put stamp on that. Most cutting edge papers that have come out recently have been trying to understand the logs. They're having them machine learning to understand the actual logs that are coming in to identify those anomalies. But that's a massive computation problem. It's a huge undertaking to kind of set that up. Uh, so I really have seen a lot of stuff actually at concierge, some of the innovations that they're doing to optimize that because finding the needle in the haystack is obviously difficult. That's the whole challenge. But there's a lot of work that's being done in Splunk to make that happen a lot faster. And there's some work that's being done at the edge. It's not a lot, but the cutting edge is actually logging and looking at every single log that comes in and understanding it and having a robot say, boom, check that one out. >>Yeah. And also the sentiment, it gets better with the data because we all crushed those billions of events. And you can get a, you know, smiley face or that'd be face depending upon what's happening. It could be, Oh this is bad. But this, this comes back down to the data points you mentioned logs is now beyond logs. I've got tracing other, other signals coming in across the networks. So that's not, that's a massive problem. You need automation, you've got to feed the beast by the machines and you got to do it within whatever computation capabilities you have. And I always say it's a moving train hard. The Target's moving all the time. You guys are standing on top of it. Um, what do you guys think of the event? What's the, what's the most important thing happening here@splunk.com this year? I'd love to have both of you guys take away in on that. >>There's a ton of innovation in the machine learning space. All of the pipelines really that I've, I've been working on in the last year are being augmented and improved by the staff. That's developing content in the machine learning and deep learning space that's belongs. So to me that's by far the most important thing. Your, your take on this, um, between the automation. I know in the last year or so, Splunk has just bought a lot of different companies that do a lot of things that now we can, instead of having to build it ourselves or having to go to three or four different people on top to build a complete solution for the federal government or for whoever your customer is, you can, you know, Splunk is becoming more of a one stop shop. And I think just upgrading all of these things to have all the capabilities working together so that, for example, Phantom, Phantom, you know, giving you that orchestration and automation after. >>For example, if we have an EMS notable events saying, Hey, possible insider threat, maybe they automate the first thing of checking, you know, pull immediately pulling those logs and emailing them or putting them in front of the SOC analyst immediately. So that in, in addition to, Hey, you need to check this person out, it's, you need to check this person out here is the first five pages of what you need to look at. Oh, talking about the impact of that because without that soar feature. Okay. The automation orchestration piece of it, security, orchestration and automation piece of it without where are you know, speed. What's the impact? What's the alternative? Yes. So when we're, right now, when we're giving information to our EES or analysts through yes, they look at it and then they have to click five, six, seven times to get up the tabs that they need to make it done. >>And if we can have those tabs pre populated or just have them, you know, either one click or just come up on their screen for once they open it up. I mean their time is important. Especially when we're talking about an insider threat whom might turn to, yeah, the alternative is five X increase in timespan by the SOC analyst and no one wants that. They want to be called vented with the data ready to go. Ready, alert on it. All right, so final few guys are awesome insights. Walking data upsets right here. Love the inside. Love the love the insights. So final question for the folks watching that are Splunk customers who are not as on the cutting edge, as you guys pioneering this field, what advice would you give them? Like if you had to, you know, shake your friend egg, you know, get off your button, do this, do that. What is the, what do people need to pay attention to that's super urgent that you would implore on them? What would you, what would your advice be once you start that one? >>One of the things that I would actually say is, you know, we can code really cool things. We can do really cool things, but one of the most important things that he and I do as part of our processes before we go to the machine and code, the really cool things. We sometimes just step back and talk for a half an hour talk for an hour of, Hey, what are you thinking about? Hey, what is a thing that you know or what are we reading? What and what are we? And you know, formulating a plan because instead of just jumping into it, if you formulate a plan, then you can come up with you know, better things and augmented and implemented versus a smash and grab on the other side of just, all right, here's the thing, let's let's dump it in there. So you're saying is just for you jump in the data pool and start swimming around, take a step back, collaborate with your peers or get some kind of a game thinking plan. >>We spent a lot of hours, white boarding, but I would to to add to that, it's augment that we spent a lot of time reading the scientific research that's being done by a lot of the teams that are out solving these types of problems. And sometimes they come back and say, Hey, we tried this solution and it didn't work. But you can learn from those failures just like you can learn from the successes. So I recommend getting out and reading. There's a ton of literature in that space around cyber. So always be moving. Always be learning. Always be collaborating. Yeah, it's moving training guys, thanks for the insights Epic session here. Thanks for coming on and sharing your knowledge on the cube, the cube. We're already one big data source here for you. All the knowledge here at.com our seventh year, their 10th year is the cubes coverage. I'm John furry with back after this short break.

>> Live from Washington DC. It's the Cube. Covering AWS Public Sector Summit. Brought to you by Amazon Web Services. >> Welcome to the Cube's live coverage of AWS Public Sector, here in our nation's capital. I'm your host Rebecca Knight, along with my co-host, John Furrier. We are joined by Sanjay Sardar, he is the VP Modernization and Digital Transformation at SAIC. Thank you so much for coming on the Cube. >> Thank you for having me. >> So, you are a twenty-five year veteran of data management. Why don't I start by asking you to... Sort of break down the principles of good data management. This is what we're here to talk about. >> Yeah. So... When you say it that way it makes me feel very old. I've done data management for a long time. The key to data management... Some of the principles are understanding, kind of what data you have. Where it is. What's the value of the data. That's the key that everyone's trying to bring. You know in the last twenty years, we've seen an explosion in the amount of data that we were handling. So, really, how do you get through all that data? How do you understand how to manage it? Where do you put it? And then really understand how to use it. What is that value of all of it coming through? Some of if is just machine data and noise. That you're looking at. That's important for certain aspects, but doesn't really add much value to the overall working of the agency or organization that you're with. And others are very valuable data, that you cannot really do anything with, unless you manipulate it in some way, or some fashion. So, data management takes a lot of different practices. And different ways to look at it. So, we've been doing master data management, meta data management for a long time, which helps understand what that data is. But then, what's the provenance of the data? What's the governance of data? What policies surround it? Where's the security of the data? All those factors play into, when you're looking at data as an enterprise. >> Sanjay, talk about SAIC specifically. I mean in long history working with the government and many, many contracts with broad range of services. But now at the modernization focus. The conversation is about agility, speed, modernizing government private, public sponsorships... Partnerships. Responsibility and accountability. All these things are in a melting pot. What is SAIC like today? What's your specific role here in Washington DC for Public Sector? >> Fair enough. So the SAIC is almost a fifty year old company. We've been around the government sector for about that long. We've done everything. We do everything from, data management, to software development, to infrastructure and hardware. Pretty much the whole gamut of IT services. And we've worked with almost every federal agency in the area, in the country. From a modernization perspective, what we're looking at is, the federal government is at this tipping point. We have a lot of legacy systems. We have a lot old aging infrastructure that... That needs to be replaced. That needs to be upgraded and modernized. This is a national security issue. We're getting into a point where things... If they start failing, it would be catastrophic for the US as a whole. So, where we are right now, as we're trying to work with the government, to bring in new technologies. As you said it's a melting pot of things that are happening. Not only has data exploded, but the technologies that are being used, have also exploded. You're seeing a massive consumerization happening. Biggest example is the apple iPhone. When the iPhone came out, that consumer... That model of the Apple iStore... Or, being able to do everything from your phone, is something the government has to get to. That's where you're looking at the UIUX models. That's where you're looking at different workflows being moved to the cloud. How do you handle all that? >> They used to be a government. They used to be a consumer of technology. Now they are a regulator of technology. That's what the discussions are. They're looking at using data and technology for their workload. So, it's not so much a supplier consumption relationship. They're much more active participants in the technology scene. The question is, do they really understand, what's going on? Cause, if you don't understand it, you can't control it, you can't regulate it, you can't utilize it properly. This is the number one conversation around modernization. What are the key factors in your opinion? The discovered needs to do better. Is it the procurement? Is it just awareness? (Sanjay laughing) What's your thoughts? >> That's a lot of questions. A lot of things going on there. And you're right. The government has become a consumer of technology. I mean it used to be back in the days when we were launching... Missions into space and putting men on the moon. The government was a leader in technology. Now with the commercialization, government has actually become a consumer of all these types of technologies, and a creator of tons of data. So, managing that data. Managing and understanding that data is very critical. How do you use it to add value to what the government is doing? And then further down the road, to what the citizens are doing. How do you add value to the citizens' life? In doing that, there's a lot of different things that have to come into play. One. As I said, technology is a big part of it. Understanding what technology to apply. It's not just about replacing technology. That's not what modernization is. Modernization, is how do you change and digitally transform your workloads. Your workflow. How you do business. That's really where the value add comes in. To get there, yeah you have to look at the technology. You have to look at the procurement practices. You have to look at different pricing and consumption models that the government hasn't been used to in a long time. When you look at these, traditional contracting models, they may not apply to some of the new ways of consuming technology. >> The world has changed for the government. >> The world has absolutely changed. >> What will it take though, for the government to become a more savvy buyer? I mean what are some of the things that... >> I think the government is already starting to become a more savvy buyer. Again. Remember the far, as when they talk about it, the federal acquisitions regulations. It's a massive volume that's probably, you know, a thousand pages long. So, there's a lot of opportunity to interpret that correctly. Where we're changing now, is how do you interpret it, so that there's fair practices for all competitors in the government market. And you're starting to see that. You're starting to see procurement officers looking at things differently. You're starting to see CIO's demand different services. They almost cannot do it. The compete in storage powers necessary? It's way too hard to go the old traditional route. >> You know what's interesting Rebecca, we talk about data all the time. We just read Infomatica World, they're kind of a supplier. They do the catalog and stuff for here at Amazon. Multi clouds of big countries, so Amazon is one of the biggest cloud. Andy Jackson who was just on stage last night in Arizona at a conference. Talking about response on recognition. All these hot AI data issues. Everything is a data problem. Right? But, yet we talk about government, but it's not just government. It's public sector. It's federal. But it's also international nation states. Competitiveness. So, there's a lot going on in such a short period in time, where analytics and data are key part, around the future value. So, it's almost the whole world is twisted upside down, from just ten years ago. >> Oh. Easily! >> Your thoughts on what's going on, and what the public sector community... Because a lot of these environments, don't have huge IT budgets. But now we're seeing things like Ground Station. Satellite. New stuff happening. >> So you're right. The explosion of data has really caused government... And in fact, every industry to change. More industries are becoming digital industries than when they were manufacturing ones You know, things like Uber, and all those industries that popped up because of the data. That's where government is also turning into. They are starting to understand that all the decisions that government makes, has to be done through a data driven model. They have to have this evidence based decision making process. And you're seeing that, because of the federal data practices. The data management act. The creation of CDOs in every agency. This is really pushing. The government is really recognizing, data is an asset. It's a value added asset, that they have to use better, to add value to the citizens life. To what they're providing. >> And it wasn't necessarily front and center on the... Quote, "data balance sheet". If you will.. Or the evaluation of data wasn't always looked at that way. >> No. >> Cause that changed the perspective. Understanding and... >> It's a huge shift. Like I said. When you look at the rise of the CDO. The Chief Data Officer in the federal government. That's a really big indication that data is now become and looked at as an asset. The CIO was responsible for all the technology and... They're governing all the technology. And they're the... Owner of that. The Chief Data Officer's now doing the same thing from the data side. The governance. The policy. The usage. The cooperation across multiple agencies. Multiple countries, as you said. >> Are agencies deploying CDOs across all agencies now? >> I think you're seeing more and more of the CDO being put out there. In fact almost all the agencies that I work with, have a CDO already in place, or are hiring one in the next three months. >> Why is modernization such a contentious topic? Is it because everyone has a different definition of what modernization is? It seems to be contentious when I talk about it with folks. It's like, what does it mean? >> I don't know if modernization is a contentious topic in the sense of... I think everybody recognizes that they have to modernize. It's how do you do it? You know, we are in a world where we have so much legacy infrastructure, legacy applications, that are tied so closely to mission. There's a risk of how do you modernize. You don't modernize correctly, you might in fact mission. And when you're talking about thing like in the DOD, where that leads to potential, you know, in theater situations and problems. That's a big problem from the DOD side. In the civilian side of the house, same thing. If your taxes go up by forty five percent because someone messed up on the modernization side, that's a problem. So, we have to be careful. Every agency has a personal journey. SAIC, when we look at this working with our partner systems, we look at an agency's personal journey. Everybody's going to do it differently. So, I think the contention comes in is, how do you do it? When do you do it? What do you attack first? Where do you look at the challenges and value adds are? Because everybody has to do it. Budgets are shrinking, and security is important. >> And workload has kicked around a lot. Applications used to be the old worry. Now an application sits on a server. It runs kind of monolithic. But, the applications are what... And the workloads are what really is the goal. Agency's got their own unique solution. That taxes is for taxes. Make that go better. So. Data and cloud, is different per workload. Per environment. Per mission. >> It very well could be. I think it's ubiquitous that there is a compute and storage factor, that everybody has to use. But the workloads that really transform the digital mission, are very different from agency to agency. So, you have to look at, what are they valuing, and where they are going with it. So, agencies like PTO, they're looking at, how do I more effectively our examiner's time? Versus, agencies like NASA, which are looking at, how do I do higher level compute, and HPC type work? So. >> One of the things you talked about when we first began our conversation. Is not only the explosion in data, but the explosion around the technologies and tools that are used to store and manipulate, and execute decisions on the data. Can you talk a little about what you're seeing. For example AI. I mean this is all the buzz, and all the big technology shows that we go to around the country. And it's maturing... But there's not a lot of adoption in the government. >> So, you're right. Along with this data explosion, we've seen a technology explosion. And with the different types of tools, handling the different sectors of managing data. Storage is one we talk about all the time. Because you have so much data, you can't actually access all that data at once. So, there's segmentation in the data that you have to look at. Companies at Cohesity are doing a good job of handling and managing that segmentation, in their hyper converged storage architectures. But we're also looking at in the AI world. Yes. AI is artificial intelligence. Deep learning. Machine learning. These are all techniques that are working very well for certain types of data usage and data problems. But the adoption is not as wide spread. Because, they're new technologies. I mean AI is where data was, like I said, twenty years ago. So, they're starting to understand, how do I use it. What do I use it for? You know that natural... That learning process that AI goes through. To say, "Okay, I'm going to make something more efficient." How do I do posturing of that data? Where do I actually use that? When you have large volumes of data. Security for example, is a great example. When you look at security logs, lots of volume of data coming out of that. But to use AI to learn which vectors the next security threat's going to to come through? That's a pretty daunting challenge, and not an easy one. And you have to find used cases like that. So, artificial intelligence I think has a large promise in the world. There's image recognition that's working very very well. Image recognition and classification. Natural language processing to look at different core sets of data in the research community. Or, in the pattern community. Those are very good examples of how AI is being used today. But there's a long way to go. And there's a lot to be learnt still. >> There's a lot of technology behind storing, and one of our sponsors that sponsors the Cube, Rebecca's cohesity. They sponsor us and invest in events. I think, always thank the sponsors. They're in the business of scaling up storage. So, it's not that easy to store it. So, you have to not only figure out the business model behind how to use the data. There's also the technology around storing it cleanly without hiring away. Talk about the dynamics around tech, in terms of managing the data. >> Well, so as you said it. There's a storage aspect of it. There's a retrieval aspect of it. There's a time aspect of it. All of that leads to... Yes, data is so valuable and so large and so limitless now. Doing all of those things matter. I mean if you're waiting, even nowadays... If you're waiting even three seconds for any response to come back? You're going to look at it and be like, I got to change my computer out cause it's too slow. That's the kind of area where we're in. When you look at the segmentation of data, nearline storage versus online storage. Well, the nearline has to be almost as fast as the online, cause now we're looking at things where, as you put it. The AI models are looking across vast amounts of data. They're looking at everything. How do you do that well? So that... All of that technology factor plays into it. >> One final thing. And this is just about the mindset of the government right now. Because what you're talking about, is a lot of exploration, and a lot of experimentation that's needed. How would you describe, sort of the federal approach to this? I mean, in fail fast is the motto of Silicone Valley. (Sanjay laughing) But that's a lot harder to do in the government. When lives are at stake. >> Well yeah. And it's cautious to be fair. It's not only lives at stake, but it's tax per dollars. Everybody is putting in there. And we want to make sure that we're doing right. To be fair. The government is looking at a fail fast prototype type models. That do work with, like you know, hackathons, and competitions. That really bring together public sector and private companies, like SAIC and others. To do different things that help kind of with this technology explosion. So for example, We work with USDA. We did multiple hackathons for precision agriculture. That kind of work is... It helps understand, what do we need to do with precision agriculture? What tools make sense? So, we have something we called our innovation factory. Where we have contracted out with multiple Silicone Valley. So we bring that to us, and then we bring that to government. That way the government does not, you know, not precluded by some of the rules that they have. But those type of things really help, that public, private partnership... It has to happen. >> I just want to... On that point real quick. Then we got to break. >> One of the things that you mentioned there is that this new generation kind of mindset. Talk about that dynamic, because there seems to be a new generation, digital natives, emerging into the work force. >> Absolutely. >> Enforcing the change, within the government. Can you validate that? Can you see... Can you share your opinion on how that's impacting everyone? >> Absolutely. Since I joined government over, God, now it's over twelve or thirteen years ago. And I left four years ago. We've been talking about this cliff that's coming up in the human resources side of the house. Where thirty-five percent of the top tier leadership is retiring. That's all getting replaced by new folks entering the market. And all these folks grew up in the iPhone era. None of these guys do anything that is... They are all mobile. They'll work anytime, anywhere. >> Very impatient too. >> Very different mindset. >> Cut the red tape. >> Right. Very different mindset and how to make government work. And that's a good thing. That kind of shake up is actually necessary. As these folks grow into leadership positions. They're going to change how government works. So we got to be ready for it. >> Great. Well Sanjay, thank you so much for coming on the Cube. >> Absolutely. Thank you for having me. >> We'll have more from AWS public sector. I'm Rebecca Knight, for John Furrier. Stay tuned. (theme music)

(Latin music) >> Narrator: Live, from San Juan, Puerto Rico, it's theCUBE! Covering Blockchain Unbound. Brought to by Blockchain Industries. (Latin music) >> Welcome back to our exclusive Puerto Rico coverage, here, this is theCUBE for Blockchain Unbound, the future of blockchain cryptocurrency, the decentralized web, the future of society, the world, of work, et cetera, play, it's all happening right here, I'm reporting it, the global internet's coming together, my next guest is Fred Krueger, a founder and CEO of a new innovative approach called WorkCoin, the future of work, he's tackling. Fred, great to see you! >> Thank you very much, John. >> So we saw each other in Palo Alto at the D10e at the Four Seasons, caught up, we're Facebook friends, we're LinkedIn friends, just a quick shout out to you, I saw you livestreaming Brock Pierce's keynote today, which I thought was phenomenal. >> Yeah, it was a great keynote. >> Great work. >> And it's Pi Day. >> It's Pi Day? >> And I'm a mathematician, so, it's my day! (Fred laughs) >> It's geek day. >> It's geek day. >> All those nerds are celebrating. So, Fred, before we get into WorkCoin, I just want to get your thoughts on the Brock Pierce keynote, I took a video of it, with my shaky camera, but I thought the content was great. You have it up on Facebook on your feed, I just shared it, what was your takeaway of his message? I thought it was unedited, obviously, no New York Times spin here, no-- >> Well first of all, it's very authentic, I've known Brock 10 years, and, I think those of us who have known Brock a long time know that he's changed. He became very rich, and he's giving away, and he really means the best. It's completely from the heart, and, it's 100% real. >> Being in the media business, kind of by accident, and I'm not a media journalist by training, we're all about the data, we open our datas, everyone knows we share the free content. I saw the New York Times article about him, and I just saw it twisted, okay? The social justice warriors out there just aren't getting the kind of social justice that he's actually trying to do. So, you've known him for 10 years, I see as clear as day, when it's unfiltered, you say, here's a guy, who's eccentric, smart, rich now, paying it forward? >> Yep. >> I don't see anything wrong with that. >> Look, I think that the-- >> What is everyone missing? >> There's a little jealously, let's be honest, people resent a little bit, and I think part of it's the cryptocurrency world's fault. When your symbol of success is the Lamborghini, it's sort of like, this is the most garish, success-driven, money-oriented crowd, and it reminds me a little bit of the domain name kind of people. But Brock's ironically not at all that, so, he's got a-- >> If you look at the ad tech world, and the domain name world, 'cause they're all kind of tied together, I won't say underbelly, but fast and loose would be kind of the way I would describe it. >> Initially, yes, ad tech, right? So if you look at ad tech back in say, I don't know, 2003, 2004, it was like gunslingers, right? You wanted to by some impressions, you'd go to a guy, the guy'd be like, "I got some choice impressions, bro." >> I'll say a watch too while I'm at it. >> Yeah, exactly. (John laughs) That was the ad tech world, right? And that world was basically replaced by Google and Facebook, who now control 80% of the inventory, and it's pretty much, you go to a screen, it's all service and that's it. I don't know if that's going to be the case in cryptocurrencies, but right now, initially, you sort of have this, they're a Wild West phenomenon. >> Any time you got alpha geeks, and major infrastructure application developer shift happening, which is happening, you kind of look at these key inflection points, you need to kind of have a strong community self-policing policy, if you look at the original DNS days, 'cause you remember, I was there too, Jon Postel, rest in peace, godspeed, we all know what he did, Vint Cerf with TCP/IP, the core dudes, and gals, back then, they were tight! So any kind of new entrants that came in had to prove their worth. I won't say they were the most welcoming, 'cause they were nervous of people to infect the early formation, mostly they're guys, they're nerds. >> Right, so I think if you look back at domain names, back in the day, a lot of people don't know this, but Jon Postel actually kept the list of domain names in a text file, right? You had basically wanted a domain name, you called Jon up, and you said, "I'd like my name added to the DNS," and he could be like, "Okay, let me add it "to the text file." Again, these things all start in a very sort of anarchic way, and now-- >> But they get commercial. >> It gets commercial, and it gets-- >> SAIC, Network Solutions, in various time, we all know the history, ICANN, controlled by the Department of Commerce up until a certain point in time-- >> Uh, 'til about four years ago, really. >> So, this is moving so fast. You're a student of the industry, you're also doing a startup called WorkCoin, what is the formula for success, what is your strategy, what are you guys doing at WorkCoin, take a minute to explain what you guys are doing, your team, your approach-- >> So let's start with the problem, right? If you look at freelancing, right now, everybody knows that a lot of people freelance, and I don't think people understand how many people freelance. There are 57 million people in America who freelance. It's close to 50%, of us, don't actually have jobs, other than freelancing. And so, this is a slow moving train, but it's basically moving in the direction of more freelancers, and we're going to cross the 50% mark-- >> And that's only going to get bigger, because of virtual work, the global workforce, no boundaries-- >> Right, and so it's global phenomena, right? Freelancing is just going up, and up, and up. Now, you would think in this world, there would be something like Google where you could sit there, and go type patent attorney, and you could get 20 patent attorneys that would be competing for your business, and each one would have their price, and, you could just click, and hire a patent attorney, right? Is that the case? >> No. >> No, okay. >> I need a patent attorney. >> So, what if you have to hire a telegram manager for your telegram channel? Can you find those just by googling telegram manager, no. So basically-- >> The user expectation is different than the infrastructure can deliver it, that's what you're basically saying. >> No, what I'm saying is it should be that way, it is not that way, and the reason it's not that way is that basically, there's no economics to do that with credit cards, so, if you're building a marketplace where it's kind of these people are find each other, you need the economics to make sense. And when you're being charged 3.5% each way, plus you have to worry about chargebacks, buyer fraud, and everything else, you can't built a marketplace that's open and transparent. It's just not possible. And I realized six months ago, that with crypto, you actually could. Not that it's going to be necessarily easy, but, technically, it is possible. There's zero marginal cost, once I'm taking in crypto, I'm paying out crypto, in a sort of open marketplace where I can actually see the person, so I could hire John Furrier, not John F., right? >> But why don't you go to LinkedIn, this is what someone might say. >> Well, if you go to LinkedIn, first of all, the person there might not be in the market, probably is not in the market for a specific service, right? You can go there, then you need to message them. And you just say, "Hey, your profile looks great, "I noticed you're a patent attorney, "you want to file this patent for me?" And then you have to negotiate, it's not a transactional mechanism, right? >> It's a lot of steps. >> It's not transactional, right? So it's not click, buy, fund, engage, it just doesn't work that way. It's just such a big elephant in the room problem, that everybody has these problems, nobody can find these good freelancers. What do you end up doing? You end up going to Facebook, and you go, "Hey, does anybody know any good patent attorneys?" That's what you do. >> That's a bounty. >> Well, it's kind of, yeah. >> It's kind of a social bounty. "Hey hive, hey friends, does anyone know anything?" >> It's social proof, right? Which is another thing that's very important, because, if John, if you were-- >> Hold on, take a minute to explain what social proof is for the folks. >> Social proof is just the simple concept that it's a recommendation coming from somebody that you know, and trust. So, for example, I may not be interested in your video services, John, but I know you, and I am in the business of a graphic designer, and you're like, "Fred, I know this amazing graphic designer, "and she's relatively cheap." Okay, well that's probably good enough for me to at least start looking at her work, and going the next step. On the other hand, if I'm just looking at 100 graphic designers, I do not know. >> It's customized contextual data, around a specific transaction from a trusted source. So you socially, are connected to, or related. >> It, sort of, think about this, it doesn't even have to be a source that you know, it could be just a source that you know of, right? So, to use the Brock example again, Brock's probably not going to be selling his services on my platform, but what if he recommends somebody, people like giving the gift of recommendation. So Brock knows a lot of people, may not be doing as well as him, right? And he's like, "Well, this guy could be a fantastic guy "to hire as social media manager," for example. Helping out a guy that needs a little bit of work. >> And endorsement's a major thing. >> It is giving something, right? You're giving your own brand, by saying, "I stand behind this person." >> Alright, so tell me about where you are with WorkCoin, honestly, people might not know your background, if you check him out on LinkedIn, Fred Krueger, mathematician, Stanford PhD, well-educated, from a centralized organization, like Stanford, has a good reputation, you're a math guy, is there math involved? Obviously, Blockchain's math related, you got crypto, how are you guys building this out, share a little bit of, if you can, show a little leg on the tech-- >> The tech is sort of simple. So basically the way it is, is right now it's built in Google Cloud, but we have an interface where you can fund the thing, and so it's built, first of all, that's the first thing. We built it on web and mobile. And you can basically buy WorkCoins from the platform itself, using Ethereum, and also, we've integrated with Sensei, a different token. So, we can integrate with different tokens, so you're using these tokens to fund the coin, to fund your account, right? And then, once you have the tokens in your account, you can then buy services with them, right? And then the service provider, the minute they finish delivery of the service, to your expectation, they get the coin in their account, and then they can transfer that coin back into Ethereum, or Bitcoin, or whatever, to cash out. >> Okay, so wait, now that product's built, has the coins been issued? Are you guys doing an ICO? Are you raising money? >> So we're in the middle of an ICO-- >> Private? >> Private, only for now. So we've raised just under $4,000,000-- >> Great, congratulations. >> I have no idea if that's good or not-- >> Well, it's better than a zero (laughs). >> It's better than zero, right? It is better than zero, right? >> So there's interest obviously. >> Yeah, so look, we've got a lot of interest in our product, and I think part of the interest is it's very simple. A lot of people can go, "I think this thing makes sense." Now, does that mean we're going to be completely successful in taking over the world, I don't know. >> Well, I mean, you got some tailwinds at your back. One, the infrastructure in e-commerce, and the things that you're going after, are 20-year-old stacks. Number two, the business model, and expectation of the users, is shifting radically, and expectations are different, and there's no actual product that does it (laughs), so. >> So a lot of these ICOs, I think they're going to have technical problems actually building into the specification. 'Cause it's difficult, when you're dealing with the Blockchain, first of all, you're building on some movable platform, right? I met some people just today who are building on Hash-Craft, now, that's great, but Hash-Craft is like one day old, you know? So you're building on something that is one day old, and they've just announced their coin five minutes ago, you know. Again, that's great, but normally as a developer myself, I'm used to building on things that are years old, I mean, even something that's three years old is new. >> This momentum going on, that someone might want to tout Hash-Craft for is, 'cause it's got momentum-- >> It's got total momentum. >> They're betting on an ecosystem. But that brings up the other thing I want to get your thoughts on, because we've observed this at Polycon, we've been watching the industry landscape now, onto our 10th year, there's almost an ecosystem stake in the ground. The good news is, ecosystem's developing. You got entrepreneurs, you got projects, you got funding coming in, but as it's going to be a fight for the ecosystem, because you can't have zillion ecosystems, eventually they have to be-- >> Well, you know-- >> Or can you? >> Here's the problem, that everybody's focused on the plumbing right now, right, the infrastructure? But, what they should be focusing it on is the app. And I've a question for you, and I've asked this question to my advisors and investors, which are DNA Fund, and I say-- >> Let's see if I get it right, it's a test here on the spot, I love this, go. >> Okay, so here's the question, how many, in your wallet right now, on your mobile phone, show me how many Blockchain apps you have right now. >> Uh, zero, on my phone? >> Okay, zero. >> Well I have a burner phone for my other one, so (laughs). >> But on any phone, on any phone that you possess, how many Blockchain apps do you have on your phone? >> Wallet or apps? >> An app that you-- >> Zero. >> An app, other than a wallet, zero, right? Every single person I've asked in this conference has the same number, zero. Now, think about this, if you'd-- >> Actually, I have one. >> Uh, which one? >> It's called Cube Coin. >> Okay, there you go, Cube Coin. But, here's the problem, if you went to a normal-- >> Can I get WorkCoin right now? >> Yeah, well not right now, but I have it on my wallet. So for example, it's in test flight, but my point is I have a fully functional thing I can go buy services, use the coin, everything, in an app. I think this is one of the things-- >> So, hypothetically, if I had an application that was fully functional, with Blockchain, with cryptocurrency, with ERC 2 smart contracts, I would be ahead of the game? >> You would be ahead of the game. I mean, I think-- >> Great news, guys! >> And I think you absolutely are thinking the right thinking, because, everybody's just looking at the plumbing, and, look, I love EOS, but, it's sort of a new operating system, same as Hash-Craft, but you need apps to run on your thing-- >> First of all, I love chatting with you, you're super smart, folks out there, Fred is someone you should check out, you got great advisor potential. You're right on this, I want to test something out with you, I've been thinking about this for a while. If you think about the OSI model, OSI stack, for the younger kids, that was a key movement that generated the key standards in the stack for inner networking, and physical devices. So, it was started from the bottom up. The top of the stack actually never standardized, it became the presentation session layer, they differentiated, then eventually became front end. If you look at what's happening now, the top of the stack is really the ones that's standardizing, or standardizing with business logic, the bottom of the stack has many different versions of say, Blockchain, so the question is is that, it might be the world that will never have a TCP/IP moment, it might be that the business app logic will dictate to some sort of abstraction layer, down to programmable plumbing. You see this with cloud with DevOps. So the question is, do see it that way? I'm thinking out loud here, but when I'm seeing the trend here, it's just that, people who make the business logic decisions first, and nail those, that they're far more successful swapping out and hedging on the plumbing. >> Look, I think you mentioned the word alpha geek, and I think you've just defined yourself as an alpha geek. Let's just go in Denzel Washington's set in the movie Philadelphia, talk to me like I'm a five year old, okay? What is the problem you're solving? >> The app, you said it, it's the app! >> My point is like, everybody is walking around with apps, if the thing doesn't fit on an app, it's not solving any problem, that's the bottom line. I don't care whether you're-- >> You're validating the concept that all that matters is the app, the plumbing will sort itself out. >> I think so. >> Is that a dependency, or is it an interdependency? >> What do you need in a plumbing? Here's how I think you should think. Do I need 4,000 transactions per second? I would say, rarely, most people are not sitting there going, "I need to do 4,000 transactions per second." >> If you need that, you've already crossed the finish line, you probably want a proprietary solution. >> Just to put things in perspective, Bitcoin does 300,000 transactions per day. >> Well, why does Ripple work? Ripple works because they nailed the business model. >> I'll tell you what I think of Ripple-- >> What's your take? >> Why ripple works, I think all, and I'm not the first person to say this, but I think that, the thing that works right now, the core application of all this stuff, is money, right? That's the core thing. Now, if you're talking about documents on the Blockchain, is that going to be useful, perhaps. In a realist's say in the Blockchain, perhaps. Poetry on the Blockchain, maybe. Love on the Blockchain? Why ban it, you know? >> Hey, there's crypto-kiddies on the Blockchain, love is coming next. >> Love is coming next. But, the core killer app, the killer app, is money. It's paying people. That is the killer app of the Blockchain right now, okay? So, every single one of the things that's really successful is about paying people. So what is Bitcoin? Bitcoin is super great, for taking money, and moving it out of China, and into the United States. Or out of Nigeria, and into Switzerland, right? You want to take $100,000 out of Nigeria, and move it to Switzerland? Bitcoin is your answer. Now, you want to move money from bank A to bank B, Ripple is your answer, right? (John laughs) If you want to move money from Medellin, Colombia, that you use in narcos, Moneiro is probably your crypto of choice, you know? (John laughs) Business truly anonymous. And I think it's really about payment, right? And so, I look at WorkCoin as, what is the killer thing you're doing here, you're paying people. You're paying people for work, so, it's designed for that. That's so simple. >> The killer app is money, Miko Matsumura would say, open source money, that's his narrative, love that vision. Okay, if money's the killer app, the rest is all kind of window dressing around trying to race to-- >> I think it's the killer, it's the initial killer app. I think we need to get to the point where we all, not all of us, but where enough of us start transacting, with money, with digital money, and then after digital money, there will be other killer apps, right? It's sort of like, if you look at the internet, and again, I'm repeating somebody else's argument-- >> It's Fred Krueger's hierarchy of needs, money-- >> Money starts, right? >> Money is the baseline. >> The initial thing, what was the first thing of internet? I was on the internet before it was the internet. It was called the ARPANET, at Stanford, right? I don't know if you remember those days-- >> I do remember, yeah, I was in college. >> But the ARPANET, it was email, right? We had the first versions of email. And that was back in 1986. >> Email was the killer app for 15, 20 years. >> It was the killer app, right? And I think-- >> For 15 or 20 years. >> Absolutely, well before websites, you know? So I think, we got to solve money first. And I bless everybody who has got some other model, and maybe they're right, maybe notarization of documents on the internet is a-- >> There's going to be use cases for Blockchain, some obvious low-hanging fruit, but, that's not revolutionary, that's not game-changing, what is game-changing is the promise of a new decentralized infrastructure. >> Here's the great thing that's absolutely killer about what this whole world is, and this is why I'm very bullish, it's, if you look at the internet of transmitting value, from one node to another node, credit cards just do not do a very good job of that, right? So, you can't put a credit card inside a machine, very well, at all, right? It doesn't work! And very simple reason, why? Because you get those Amex fraud alerts. (John laughs) Now the machine, if he's paying another machine, the second machine doesn't know how to interpret the first machine's Amex fraud alerts. So, the machine has to pay in, the machine's something that's immutable. I'm paying you a little bit of token. The classic example is the self-driving car that pays the gas pump, 'cause it's a gas self-driving car, it pays it to fill up, and the gas pump may have to pay its landlord in rent, and all of this is done with tokens, right? With credit cards, that does not work. So it has to be tokens. >> Well, what credit cards did for other transactions a little bit simplifies your things, there's a whole 'nother wave coming, that just makes it easier and reduces the steps. >> It reduces the friction, and that's why I think, actually, the killer app's going to be marketplaces, because, if you look at a marketplace, whether it's a marketplace like ours, for freelancers, or your marketplace for virtual goods, and like wax, or whatever it is, right? I think marketplaces, where there's no friction, where once you've paid, it's in. There's no like, I want my money back. That is a killer app, it's an absolute killer app. I think we're going to see real massive consumer adoption with that, and that's ultimately, I think, that's what we need, because if it's all just business models, and people touting their 4,000 transactions a second, that's not going to fly. >> Well Fred, you have a great social graph, that's socially proved, you got a great credentials, in mathematics, PhD from Stanford, you reinvent nine, how many exits? >> Nine exits. >> Nine exits. You're reinventing freelancing on the Blockchain, you're an alpha geek, but you can also explain things to a five year old, great to have you on-- >> Thank you very much John. >> Talk about the WorkCoin, final word, get the plugin for WorkCoin, can people use it now, when is it going to be available-- >> Look, you can go check out our platform, as Miko said, Miko's an advisor, and Miko said, "Fred, think of it as a museum, "you can come visit the museum, "you're not going to see a zillion, "but you can do searches there, you can find people." The museum is not fully operational, right? You can come and check it out, you can take a look at the trains at the museum, the trains will finally operate once we're finished with our ICO, we can really turn the thing on, and everything will work, and what I'd like you to do, actually, you can follow our ICO, if you're not American, you can invest in our ICO-- >> WorkCoin dot-- >> Net. >> Workcoin.net >> Workcoin.net, and, really, at the end, if you have some skill that you can sell on the internet, you're a knowledge worker, you can do anything. List your skill for sale, right? And then, that's the first thing. If you're a student at home, maybe you can do research reports. I used to be a starving student at Stanford. I was mainly spending my time in the statistics department, if somebody said, "Fred, instead of grading "undergrad papers, we'll pay you money "to do statistical work for a company," I would be like, "That would be amazing!" Of course, nobody said that. >> And anyways, you could also have the ability to collaborate with some quickly, and do a smart contract, you could do some commerce, and get paid. >> And get paid for it! >> Hey, hey! >> How 'about that, so I just see-- >> Move from the TA's grading papers payroll, which is like peanuts-- >> And maybe make a little bit more doing something that's more relevant to my PhD. All I know is there's so many times where I've said, my math skills are getting rusty, and I was like, I'd really wish I could talk to somebody who knew something about this distribution, or, could help me-- >> And instantly, magically have them-- And I can't even find them! Like, I have no idea, I have no idea how I would go and find people at Stanford Institute, I would have no idea. So if I could type Stanford, statistics, and find 20 people there, or USC Statistics, imagine that, right? That could change the world-- >> That lowers the barriers, friction barriers, to-- >> Everybody could be hiring graduate students. >> Well it's not just hiring, collaborating too. >> Collaborating, yeah. >> Everything. >> And any question that you have, you know? >> Doctor doing cancer research, might want to find someone in China, or abroad, or in-- >> It's a worldwide thing, right? We have to get this platform so it's open, and so everybody kind of goes there, and it's like your identity on there, there's no real boundary to how we can get. Once we get started, I'm sure this'll snowball. >> Fred, I really appreciate you taking the time-- >> Thanks a lot for your time. >> And I love your mission, and, we support you, whatever you need, WorkCoin, we got to find people out there to collaborate with, otherwise you're going to get pushed fake news and fake data, best way to find it is through someone's profile on WorkCoin-- >> Thanks. >> Was looking forward to seeing the product, I'm John Furrier, here in Puerto Rico for Blockchain Unbound, Restart Week, a lot of great things happening, Brock Pierce on the keynote this morning really talking about his new venture fund, Restart, which is going to be committed 100% to Puerto Rico, this is where the action will be, we will be following this exclusive story, continuing, we'll be back with more, thanks for watching. (soothing electronic music)