Shandani, welcome, repeat guest, get nice and close to the microphone last year. We had Vinny on talking about his new book, The New Polymath, which essentially a polymath is an individual with a wide variety of expertise, right? I think I called you a renaissance man. You were very humble and said, no, Dave, I'm not a renaissance man, but you knew a lot of people that were renaissance men of technology and you profiled them in your book. And we're here to talk about a new book. It's called the IT Switch Hitter. Is that right? The Technology Switch Hitter. The Technology Switch Hitter. Right? Better than the IT. Better title. So I'm not good at titles. So tell us about the Technology Switch Hitter. It sounds like part two of The New Polymath. First of all, how'd The New Polymath go? Maybe you could summarize the premise of the book and then we can talk about the Technology Switch Hitter. Well, thank you for having me again. You're welcome. Good to see you at another event. Good to see your show continue to grow. So thank you. Dave, The New Polymath, as you summarized, what's about this new world where we are seeing companies learn to take a little bit of information technology, a little bit of biotech, a little bit of nano tech, a little bit of clean tech, a little bit of help tech, come up with just amazing new products, not just because they wanted to show off and say, hey, we've got all these disciplines, but because they're trying to solve some really what I call grand challenges, we face as mankind. So there's ecological issues, there's health issues, there are information technology issues that this combination of technologies is allowing us to solve. So Polymath Renaissance Man meant to describe these companies that are learning to embed so many different disciplines. How has the book done? It's done well, but more importantly, I've had a chance to go present probably 50 different events around the world and talk about this new world of compound innovation. So it's probably exposed the idea to another 15, 20, 25,000 people as part of the events. So in that sense, it's been very gratifying. What are some of the events that you've done? One event in London, Capgemini in Amsterdam, a Lexmark event in Lexington, Kentucky, all over the ice cool and Toronto. Book signings and all of them? Yes, but more importantly, just a very wide range of, I was at Arizona State in Tempe, bunch of students and alum and professors, very different setting from some of the more corporate oriented events that I presented. Just great to see so many different audiences interested in innovation and so on. So we're talking about solving some of the problems. I wonder if you could go in and we talked about this a little bit last year, but for those folks in the audience who aren't familiar with the book, maybe give us some examples of some of the problems that you're talking about, that the new Polymath, the technology Renaissance individual is helping to solve. So one example from the book was something called the GE net zero project. In their view, none of us should have to pay utility bills. So they have an initiative. In their world, they're looking at each one of us, in fact, being able to sell back to the electricity grid, a bunch of power. Now, how do you do that? To be able to do that? Our vision is we would have next generation solar panels. We would have scaled down wind turbines at our home. We would have next generation LED lighting appliances that are smart. So we can have the spin cycle at six o'clock and the watch cycle at nine o'clock. We would have interfaces to the smart grids that utilities are building. We would have all kinds of home energy managers. So when you step back, you look at it and you go, what is this initiative? Is it an information technology initiative? Yes, it is because it's got software and sensors and so on. Is it a clean tech initiative? Of course it is. Is it a nano tech initiative going forward? Because some of the technologies involve next generation composites and so on. Of course it is. So a combination of a whole bunch of sciences coming together in one initiative. That's incredibly visionary. I mean you think about humans becoming a power generation node, selling energy back to the energy companies who then would presumably offset a lot of the billions in capital expense that they have to go through and still profit from being able to resell that energy. Some of the utilities call it their next power plant because it means they don't have to invest that much capex in a new power plant. So they're willing to come up with variable pricing if you consume less or can sell back to them the power that we may be generating. So all this has to be worked through over the next few years. But in Germany it's amazing to see how much of this is already happening. A lot of German farms and houses are selling back to the grid. So the technology switch hitter sounds like a very thematic picking up on the new polymath and you know it's interesting Vinny. We were just here a short year ago talking about it and it's amazing how much has changed since I mean you know the role of the data scientist for example we were just talking about all over to Oliver Busman about the changing role of the CIO how infrastructure applications and devices are completely flipping that role on its head the importance of security and the CISO etc. So you wouldn't have thought that in a year so much had changed that it would be fodder for a new development new book. But talk about what's new and the technology switch hitter and you know why the book why now. So it's actually a slightly different theme than what you just talked about. Okay it talks about two converging trends that I see. One is that traditional technology buyers are learning to embed technology in their products and become technology vendors. So that's one side of the switch hitter equation. What do I mean. So Nike shoes have sensors. Cars have all kinds of sensors and software and satellite support. Grills have Bluetooth. Moen has remote controls for showers. I cannot find a single industry. You know when I started to do my research I thought maybe 8 or 10 industry and medical devices auto etc were leading the charge. But I'm now up to 30 industries that are coming up with smart products smart services right. So I'm talking to townships that are coming up with the next generation parking garage that have sensors and parking you know to tell us which parking spaces are empty next generation charging stations for electrical vehicles. I cannot find an industry that is not thinking about technology embedded product. So in that sense these companies are learning to become technology vendors because now they have to think about spare parts. Now they're learning about my God Moore's law. Software testing yeah exactly you just got to retrain their channel got to retrain their sales force. They're learning about Moore's law right. Think about GPS when it first came out in cars. It was three four five thousand dollars. Well the sales person still expects to charge that. You can pull out your iPhone and say why would I pay you five hundred dollars for that. You know so so they're learning all these new nuances of becoming technology vendors. Okay so that's one vector one one. On the other hand the more I look at particularly the consumer tech industry if you peel the onion behind an apple or an Amazon or a Google or a Facebook the well run ones it is amazing the industrial best practices these companies have deployed. Okay so you go into the Apple retail store the average retailer who's been in business a hundred years drools about Apple's retail metrics. You know the sales per square foot the consumer satisfaction etc etc. If you look at Facebook's data centers this is stuff that IBM and Accenture should have been designing. I mean it is quantum better than what the corporate data center is today. If you look at Amazon supply chain innovations right. Postal injections and so on. This is stuff that Walmart and FedEx used to do twenty years ago. Okay these vendors are becoming the new buyers in the sense that they are propagating new industrial best practices that now the P&G's and the Kimberley Clarks are saying my God why aren't we doing that right. So you see the other vector these technology vendors are becoming more like buyers they're becoming the new best practice leaders on the other hand buyers are becoming more like technology vendors. So the thesis of the book is anymore we can't pretend to be just a buyer or a vendor right. We can't just say I'm a consumer of technology or I'm a producer of technology. We've got to become at both sides you know and that has some dramatic impact on IT right. Because IT has traditionally been a consumer and deployer of technology now they've been forced into becoming producers of technology. On the other hand you know we can't afford to have software vendors who say I deserve 90% gross margins because these customers understand how to produce technology how to deploy it. They understand the economics of technology much better than they did 10 years ago. So there's some profound impact that the industry is going to go through. Interesting premise Vinny so essentially you're by implication saying that the way in which traditional buyers are actually applying technology is becoming maybe more important than the traditional way in which we as an industry have looked at the sellers of technology. For example Microsoft software having such an impact on me because of an operating system that compared to the examples you just gave it just seems outdated right that an operating system would have all that value the value really is in the way in which whether it's automobile companies you mentioned medical device companies manufacturers are applying technology to create new business capabilities. Absolutely and quite often what's interesting is if you go to Daimler for example right doesn't make Mercedes. They have a thousand software engineers who have nothing to do with the CIO. It reports to the R&D and product engineering group. So over and over again I'm seeing examples of companies buyers of technology who are because they're deploying technology and product are very worried about the brand, they're very worried about the product are learning to become deploy a new version of technology consumption and technology manufacturing. It's dramatic actually. Many of them are avoiding IT in their product areas. Yeah but they're certainly not avoiding technology. Oh no, no, no. That's all about technology. The new form factors, you know, the phenomenon that I heard at an event a couple of months ago is what I call the Monday morning quarterback, okay. The dramatic difference between all of us the technologies we have Sunday night, right. The HDTVs and the iPads and the iPods at home, the home entertainment at home and then we go on Monday morning to the UI and the old laptops and the old technology is so dramatic that many CIOs are finally saying bring your own technology. There's a term called BYOT. Bring your home technologies. Let's work with that, right. Now many of the CEOs are going to the CIOs and saying where's my iPad? But the smarter the CEOs are saying there is a consumer out there that is used to the iPad and Google and Facebook. What can I sell to them? Why does my product have to be 10 years old? Why can't it be a new form factor which embeds technology, which embeds industrial design principles that an Apple has shown that the consumer is ready for, right. So there's a revolution going on. Yeah, Apple sort of paved the way for mobile adoption and now we're here at Sapphire. We're talking to Vinnie Mershandani who's the author of The New Polymath. He's got a new book coming out called The Technology Switch Hitter. We're talking about the premise of that book.  To me, this is a new take, a deeper take on the whole consumerization of IT. And people have been talking about that and sort of scratching the surface. You're really getting deep into how those technologies are becoming embedded.  There's undertones of that smarter planet. It's a great vision. But you're really coming up with some examples and then sort of combining that with this notion of the consumer tech drive and how companies like Amazon and Facebook are completely changing industry. And not just changing the technology industry, but how they're inspiring the sick codes that have nothing to do with technology to also become technology vendors. I mean, that is the big awakening in a number of companies where they say, if a consumer is used to a Kindle, they're used to, they will likely try a medical device. That looks like this. They'll likely try a lawnmower, which is much more technologically savvy than it was five years ago. They're much more likely to try a new service that is technologically savvy than they were a few years ago, okay? I mean, if you look at Mary Meeker's numbers, right? We have so many devices, so many, you know, so many web services in our daily life. Why wouldn't we try a new form factor in any product, right? We're used to books becoming Kindles. Why wouldn't we try that with how we refill the Walgreen prescriptions or how we look at shoes or how we look at, you just saw a commercial for, you know, under armor here, you know, the shirt they had with the sensor. Smart shirt. It's a smart shirt, right? Smart products are everywhere. I mean, what does this mean for data, right? Because we're talking about devices. You're talking about big data. Billions of devices, and every one of these devices, these embedded devices has microprocessors, they've got tons of lines of code, and it's generating data. It's a sensor on the internet. There are those who believe that as open source software increasingly commoditizes traditional software, Microsoft, SAP, IBM, et cetera, that data becomes the next source of competitive advantage. Do you share that vision in regards to the work that you've done and the research that you've done, do you see that fitting into your scenarios here? I mean, it's almost to the point where our current definition of big data is going to be outdated in a couple of years. It's going to be a tiny data looking back, really. Correct. Now, you know, there are some exciting opportunities from the analysis of that data. There's also a whole bunch of new ethical considerations as we now share even more personal data through our devices. Privacy issues.  We'll be transmitting all kinds of location data. We'll be transmitting all kinds of, you know, food data as our appliances, you know, collect information on what we're cooking and when we're cooking and all that. We haven't even touched the surface in terms of privacy issues that are coming up. You know, let's talk about that a little bit because there's such talk about security in our industry and not a lot of talk. It's certainly at the CIO level, the traditional enterprise CIO level, about privacy. And based on what you just said, it's going to become increasingly important. It's not the same as security. There's relationships there, but there's also business practices and ethics and maybe new laws that have to come down that really adjudicate privacy in a much different way than security. In some ways, security is intellectually more clean cut. I want to be secure. Privacy, it's like, well, where do you draw the line? David, the funny thing is, let me go back to the new polymath, right? In the 40 or 50 presentations that I've done. Every time I go to a campus setting, the chapter on ethics gets a lot of attention. When I go into a business setting, I don't even raise the topic because it's a very uncomfortable discussion in a business setting. Unfortunately, you know, most companies would rather just avoid the topic. They know it's coming, but they'd rather avoid the topic. And it's not just privacy.  It's not a very comfortable discussion. In fact, one of the guys I quoted in the book made a great point which was, we don't have a 10 commandments for our industry, you know, which is anytime we unleash a new technology, we kind of just throw it out there and wait for society to react, right? We don't have a framework for saying, hey, you talk about data, right? People collect data knowing fully well it's at risk of losing it, right? Isn't it much better not to collect that data? But we just assume, we just kind of accept that it's okay to collect more and more data. So like I said, I don't think we'll resolve the issue in the next couple of minutes, but it's not a very comfortable discussion in the industry. But it'd be worthwhile framing the issue because I've been thinking about this a lot actually and with theCUBE and SiliconANGLE and Wikibon, we've been covering a lot of the whole big data issues. It's hot, right? You know, the game and we want to be where the action is. We did the Strata conference and we talked to Tim O'Reilly about this issue of privacy versus security. I thought he had a good angle on it. He basically said, look, this is an opportunity for companies, so I see the same thing. Companies don't want to talk about it. It's almost like, yeah, we'll figure that out some other day or it's security. We'll solve security, we'll take care of privacy too. Tim's take on it was different. He sees this as an opportunity, as an opt-in opportunity, if you will. Like when we're on our mobile devices and we want to find a place, and Google asks us, can we use your location? We say, sure, because we're trying, we're getting value out of that interaction. And his premise was that data becomes more valuable as organizations package that data, it becomes an opportunity. And as a consumer, I'm going to want to opt-in. Your example about cooking devices, conveying information about what's being cooked and when and there's potentially a way to turn that into a rich data source of information for a consumer that I might like to have access to. Whether it's recipes or other ideas, I don't really know, I can't really envision that. But do you see that as, as you look out, you take your telescope out as the potential bit flip here in this industry on privacy where consumers are saying, all right, I want to opt-in because I see a greater good both for me and my colleagues, my peers. Well, quite often we don't give them the choice. And if you give them the choice, most consumers would probably opt-in, but they wouldn't want that shared in every single scenario that they can't think about, right? So I mean, the thorny issue is, is if you ask the consumers, that's one decision point, which freezes many of them. The second thing is, if you ask them where it can be used. It's too confusing. It's too confusing, right? So that's what I'm saying. We don't have an industry framework. And so everybody kind of goes along and says, well, I'm sure some lawyer somewhere will figure this out. Somebody else's issue, we don't take responsibility for, you know, having a framework as an industry. What, I wonder if we could talk a little bit about Sapphire. So we always have such interesting conversations in Sapphire. We don't even talk about SAP, but so, you know, SAP is a company where last year we heard the co-CEO discussion. Hey, we've got co-CEOs, Kumbaya. It seems to be working pretty well. And so hats off to those guys. We've had them both on theCUBE. We had Jim Hangeman-Shinabe yesterday and we've had Bill McDermott on earlier and they seem to be doing a good job there. The side-base acquisition was fresh. Like, okay, we were kind of scratching our heads, all right, mobile really? And like, yeah, really. So that's good. So we're seeing this transformation. We've seen a lot of the analogy of the app store. Just heard their CIO talking about that, running their business on iPads and so forth. But the fact of the matter is that SAP, the predominance of SAP's business, like many of the enterprise companies is maintenance. They're making money by extracting rent from their customers. Oracle does that, Symantec does that, that's the name of the game. I get the sense that SAP is really trying to innovate, they're pouring money into R&D and they are trying to turn this steamship, but that's going to take a long time, isn't it? I mean, the marketing seems to be way ahead of the actual dollars. Is that a fair perception on my part or on my message? Oh, no, I mean, I think it's one. First of all, Jim and Bill, very compatible. We had dinner with Jim on Sunday, hell of a nice guy. I mean, these are nice, fun executives to be around. Okay, so, SAP is- And in the case of McDermott, he's cool. Well, frankly, I find Schnabe very, very personable. Oh, absolutely, yeah, yeah, yeah. I think a great sense of humor, humble in a lot of ways. So, this is a good company to do business. They're making these- People like doing business with SAP, right? Right, right. The, I, this year, even more than last year, I'm convinced that this is a legacy vendor, right? Which keeps doing nice things, nice extensions to the legacy code, but they kind of feel compelled to talk about mobile this, social this, cloud this, because it's fashionable for them to talk about it. The core of the company, the customers keep writing them checks, not just because it's a good, good rental model, is because they've run the backbone of many of the biggest companies in the world, okay? And I think the one thing I'd like SAP to just acknowledge is we may not be the most innovative, we're not an apple, okay?  I wish they would start focusing more on efficiency, right? Because they always like to say, oh, we do so much innovation for 20 billion, and I like to turn around and say, but you cost your customers 80 billion a year. Compared to that, the innovation quotient is very low. So, how about reducing that 80 billion down to 60 billion? Now, how do you come up with those numbers, just in terms of the investment around? The ecosystem around SAP, you know, the data centers, the offshore application management. She said spend a dollar on SAP license, you're going to spend four on all the other stuff around it. Every single year, right? So, I wish they would become a lot more aggressive about managing that ecosystem. You know, like Apple does, I mean, they go through a certification project, they control that ecosystem pretty tight. SAP has very little control over its ecosystem, right? So, it's, again, I've mentioned this every year for the last several years. I wish they would become more aggressive in managing the ecosystem around it. So, you're more of an application guy, I'm more of an infrastructure person, so I can see how they can attack that infrastructure with things like virtualization. We had a partner on before SAP systems integrator. He was talking about EMC's V block, which is a logical block of infrastructure, compute storage and networking. I can see how they simplify that infrastructure layer. You're proposing a similar type of approach at the application layer. Absolutely, I mean, you look at, talk about infrastructure, right? I know for a fact, some of the SAP customers are paying $2.5, $3 a gigabyte a month to their outsourcers. If Amazon can do it for 15 cents, right? I mean, there is a benchmark out there. You're not just dreaming this stuff out there. They could be putting some pressure there. If you look at application management, salesforce.com supports 75,000 customers. Not, it's not the same footprint as SAP has, but 75,000 customers with a handful of people. Every SAP customer has got an offshore provider doing hundreds of bodies, right? There is something dramatically off that you can bring multi-tenant concepts from the application world and kind of expect your partners to start doing some of that, right? I wonder if I could get your perspective on, I mean, again, I'm more familiar with, let's say, for instance, PC software and the whole concept of bloatware, the vast majority of functionality in Microsoft Office we never need, we never use, and there's a whole suite of applications coming. I mean, I think of companies like 37 Signals that does project management.  Fantastic. Does that same model project into the enterprise world? I mean, or is that not the case? Because these big companies are using all this function. Is there similar kind of bloatware in the enterprise, or is it just too valuable to pull the plug on those functions? It is probably even more in the enterprise world. Yes, it is. Well, that's encouraging, then, because that says a company like SAP could really truly innovate by simplifying. The opportunities to innovate may not be the right term, they make more efficient. Yeah, yeah, you're right. It's not innovation, it's attack efficiency. Countless opportunities, right? And this is where the research from the consumer tech world that I'm seeing is even more dramatic. When you look at the efficiencies that the way the Facebook runs its data center or Amazon runs its supply chain, you go, why can't it happen in the enterprise? Yeah, and why wouldn't new emerging enterprise software vendors take that Zynga model and develop enterprise applications that are secure, that are functional? I mean, they're going to do that, right? This is inevitable. Or IT, when I say IT broadly defined, not just the CIO, but all the ecosystem of vendors that makes up the IT spend are going to gradually become more and more trivial. So I think SAP actually has a good chance of figuring this out, because if they're developing all these applications for iPad, I mean, iPad users aren't going to accept anything, but dead simple. You buy that? This is rejected. New form factor, yeah, in every aspect of life. All right, Vinnie, Vinnie, Mershandani, I'm standing guest as usual.  Appreciate you taking a little bit of time out of your busy schedule. The new Polymath is his book last year, the Tech Switch Hitter this year. Later in the year. When is it coming out? Well, I'm not even finished with the research. So you're in the research phase, so it'll be fall? Yeah, publishing world is a little old fashioned. It takes a while to get. Good stocking stuffer, folks out there, looking for something for your significant other, your child in business school, or your friend, or just yourself. So treat yourself to the Tech Switch Hitter. Vinnie, Mershandani, look for that later this year. Vinnie, thanks very much for coming on theCUBE. Appreciate it. Always a pleasure. Great to see you.


Adding Fractions with Unlike Denominators Although we are focusing on addition, remember that whenever you add, subtract, or compare fractions, the denominators must be the same. When working with different denominators, you must change them to a common denominator before solving the problem. In this lesson, we will be going through fraction concepts, fraction terms, adding fractions with like denominators, and finally, adding fractions with unlike denominators. Fraction Concepts A common fraction has two components, the top number and the bottom number. The top number is the number of pieces we are talking about. These pieces are shaded, eaten, taken away, etc. The bottom number is the number of pieces in the whole object. A common fraction can be read three ways. This fraction can be read as two-fourths, two divided by four, or two out of four. Fraction Terms Numerator The top of a fraction, the number of parts being talked about. Denominator The bottom of a fraction, the number of parts in the whole object. Common Denominator A number that can be divided by the denominators of two or more fractions. For example, with two-thirds and three-fourths. Twelve is able to be divided by the denominators three and four. Improper Fraction A fraction that looks incorrect or upside down because the numerator is larger than the denominator. Mixed Number A combination of whole number and a fraction. Adding Fractions with Like Denominators When adding fractions with the same denominator, you only add the numerator. The denominator remains the same. Why do denominators remain the same? Three-fifths plus one-fifth is similar to saying three oranges plus one orange. You are adding like things. Adding Fractions with Unlike Denominators There are three steps for adding fractions with unlike denominators. First, find a common denominator. Second, rename the fractions so that they have the same denominator. Third, add the like fractions. Step Number One Finding a Common Denominator A common denominator is found by listing the multiples of the original denominators. For the fractions of one-fourth and two-sixth, we list the multiples of four and six because they are the denominators. All of the circle numbers are common denominators. Always choose the smallest number. Step Number Two Rename the fractions so they have a common denominator. In the previous example, we used the denominators of four and six to find the least common denominator of twelve. Now we take the answer of twelve and change the original fractions. What do we have to do to four to increase it to twelve? We multiply it by three. If you multiply the bottom of the fraction by three, you must do the same to the top. What about the six? What do we have to do to the six to get twelve? We multiply it by two. Remember, whatever you do to the bottom, you must do to the top. So we have now successfully converted our original fractions of one-fourth and two-sixths into fractions we can add together because they have a common denominator. Step Number Three Add the like fractions. Now we can do three-twelfths plus four-twelfths to get a final answer of seven-twelfths. Now that we know the steps to add unlike fractions, let's practice them. First, we'll work on finding the least common denominator in some practice problems shown below. Pause the video here and try to find the least common denominator for each of the problems. Click Play once you are ready to move on. Here are the least common denominators for each set. Why choose the smallest common denominator? Just as replacing the divot in Gulf is proper Gulf etiquette, presenting a fractional math answer in lowest terms is proper Math etiquette. Consider these two answers. It is quite easy to see that four and twelve can be reduced by four. However, the larger the numbers, the more difficult reducing it will be. Previously, we found common denominators for the numbers four and nine with a final answer of thirty-six. Below, use these fractions and rename them to a denominator of thirty-six. Pause the video here and click Play once you think you know the answers. The correct answers are shown here. You have completed this learning object, adding fractions with unlike denominators.


I think our stuff is getting so good and so out there that the internet has to stop it. There's just too much going on. Too much. Yeah. We had a fun thing. Yeah. It was, Wirecast was like, I'm out of here. Yeah. They just left. All right. So what's this, Lydia? Okay. Um, this is the new Feather STM32F405 Feather coming soon, so the PCBs are going to be fabbing these very soon. We also have an upcoming E-Ink Gizmo, if you see the TFT Gizmo and you're like, wow, I'd like that, but with E-Ink, you're in luck. Coming soon. Think, Inc. Gizmo. Uh, we also got, uh, finally wrapping up the Itsy Bitsy NRF 52840. It's an Itsy Bitsy, but it got Bluetooth in it. One circuit python, so wonderfully. It could be great for little keyboard builds. Okay. And I have a video of us trying out, uh, Catalyst on Cat, uh, yeah, Catalyst on Catalina. Take it away, Colin. What is this? This is Bluefruit LE Connect running on macOS via the new Catalyst available in macOS and Catalina. This is our Bluefruit app. And it's on a Mac. It's on a Mac. We're using Catalyst. Very quick. All right. Easy to set up. And this is a circuit playground of Bluefruit. And here we see it represented. It sees it. And we're going to connect, connecting, beautiful popover translation of the macOS. I don't believe it unless you can change the colors on this. And that is the test, isn't it? So we'll go into controller. Yeah. And we'll go color picker. Yeah. If I... There we go. And then let's go green. Look at that. Look at that. So how long did this take you to get working? Ten minutes. Okay. It took longer to download Xcode. Yeah. Oh, much. All right. Thank you so much, Colin. Cheers. Okay. Then we have this cool project. It's, uh, logo, uh, turtle inside of a turtle. See, okay. It's a turtle, turtle. Turtle. It's turtles all the way. It's a turtle. It's a turtle. It's a turtle. It's a turtle. It's a turtle. It's a turtle. turtle. It's turtles all the way down here. That's the image that we transferred. Gizmo, inside of a 3D printed turtle. It looks like the turtle graphics. Feetsies on a magnetic. A little USB tail. And there's a tail USB. And it's kinda neat. It's cute. Over. We have spots for some magnets here. Four of them. And then we have access to the NeoPixels. The two buttons switch. Everything else there. And uh... It's not out yet. It's not fits. Don't ask. That's about what we're... Look it back in the vault. Crazy secrets. Okay.


What should you bring with you to your location? What materials do you need to have? Kyle, you will need to have a pencil, a post-it note, and the chart. OK, I will actually have. I will be giving you the post-it notes. Don't forget about the text, though, OK? You'll need your text and a pencil, and you're right, Kyle. We will give you those post-it notes so you have them. Question? Trying to find. What are we doing again? I forgot the first step. That's I appreciate you asking. You're going to be looking for text evidence. Within both Alyssa's diary and the poem, that shows how the characters feel and how they perceive the English language. OK, you're welcome. Any other questions before we begin? What should the voice level be? A one. Perfect.


From San Mateo, it's theCUBE, covering Scalar Innovation Day, brought to you by Scalar. Hello everyone, welcome to the special Innovation Day with theCUBE here in San Mateo, California, heart of Silicon Valley, I'm John Ford, the Cube, our next guest is Steve Newman, the co-founder of Scalar. Congratulations, thanks for having us. You guys got a great company here. Thanks, yeah, glad to have you guys here. So tell the story, what's the backstory? You guys founded, interesting pedigree of founders, all tech entrepreneurs, tech savvy, tech athletes as we say, tell the backstory, how did it all start and how did it all come together? So I guess I traced the story back to, I was part of the team that built the original Google Docs and a lot of the early people here at Scalar either were part of the Google Docs team or other people we met while we were at Google. And really Scalar is an outgrowth of the, it's a solution to problems we were having trying to run that system at Google. Google Docs of course became part of a whole ecosystem with Google Drive and Google Sheets and all these applications working together is a very complicated system and keeping that humming behind the scenes became a very complicated problem. Well congratulations, Google Docs is used by a lot of people, so it's been great success. Scalar's different though, you guys are taking a different approach than the competition, what's unique about it? Can you share kind of like the history of where it's going and where it came from and where it's going? Yeah, so maybe it'd be helpful like just to kind of set the context a little bit. Through the blackboard. Yeah, so I talked about it's kind of put a little flesh on what I was saying about this very complicated system that we were trying to run in the whole Google Drive ecosystem. There are all these trends in the industry nowadays that move to the cloud and microservices and Kubernetes and serverless and can use deployment. Every, like these are all great innovations makes people are building more complex applications, they're evolving faster, but it's making things a lot more complicated. And to make that concrete, imagine that you're running an e-commerce site back in the dot com web 1.0 era. So you're gonna have a web server, maybe a patchy. You've got MySQL database behind that with your inventory and your shopping carts. You may be an email gateway and some kind of payment gateway. And that's about it, that's your system. Each one of these pieces involved, going to fries, buying a computer, driving it over to the data center, slotting it into a rack. You know, a lot of sweat went into every one of those boxes, but there's only about four boxes. That's your whole system. And if you wanted to go faster, you threw more hardware at it, more RAM. Exactly, and not literally through, but literally carried. You literally brought in more hardware. And so, took a lot of work just to do that simple system. Fast forward a couple of decades, if you're running an e-commerce site today, well, you're certainly not seeing the inside of a data center. Stripe will run the payments for you. Somebody Amazon will run the database server and say, you know, like, this is much, much, you know, one guy can get this going in an afternoon, literally. But nobody's running this today. This is not a competitive operation today. If you're an e-commerce today, you also have personalization and advertising based on the service history or purchase history.    And trying to actually understand what's working, what's not working, why isn't it working, and dragging that down and fixing it, this is the challenge today. And this is where we come in. And that's the main focus for today is that you can figure it out, but the complexity of the moving parts is the problem. Exactly. So, you know, and so you see, oh, you know, 10% of the time that somebody comes in to open their shopping cart, it fails. Well, you know, the problem pops out here, but the root cause turns out to be a problem with your database system back here, and figuring that out, you know, that's the challenge. Okay, well let's grab a seat and continue. So with cloud technology, economics has changed. How is cloud changing the game? So it's interesting, it changes the game for our customers, and it changes the game for us.  It's a lot easier to scale up and down, so you can do much more ambitious things, and you can move a lot faster, but you have these complexity problems. For us, what it presents an economy of scale opportunity. So to, you know, we step in to help you on the telemetry side. What's happening in my system? Why is it happening? When did it start happening? What's causing it to happen? That all takes a lot of data, log data, other kinds of data. So every one of those components is generating data, and by the way, for our customers, now that they're running 150 services instead of four, they're generating a lot more data.  We've taken an approach where we're able to service all of our customers out of a single centralized cluster, meaning we get an economy of scale. Each one of our customers gets to work with, basically a log management engine that's to scale to our scale rather than the individual customer scale. So the older versions of log management had the same kind of complexity challenges you just drew about e-commerce. As the data types increase, so does their complexity. Is that right? So the complexity increases, but you also get into just a data scale problem. You know, suddenly you're generating terabytes of data, but you only want to devote a certain budget to the computing resources that are going to process that data because we can share our processing across all of our customers. We fundamentally change the economics. It's a little bit like when you go and run a search on Google, thousands, literally thousands of servers in that 10th of a second that Google is processing the query, 3,000 servers on the Google side may have been involved. Those aren't your 3,000 servers.  But for a millisecond there, those 3,000 servers are all for you. And that's a big part of how Google is able to give such amazing results so quickly, but instill economically for them. And that's basically, on a smaller scale, that's what we're doing is taking the same hardware and making it all of it available to all of the customers. People talk about metrics as the solution to scaling problems. Is that correct? So, this is a really interesting question. So, you know, metrics are great.  And, you know, and it's a great way to boil down, you know, so I've had 83 million people visit my website today and they did 163 million things in this area and that succeeded and da, da, da, da. You can't make sense of that. You can boil it down to, you know, this is the amount of traffic on the site. This was the error rate. This was the average response time. So, these, you know, these are great, it's a great summarization to give you an overall flavor of what's going on. The challenge with metrics is that they tend to measure, they can be a great way to measure your problems, your symptoms. Sites up, it's down, it's fast, it's slow. When you want to get to then the cause of that problem, all right, exactly why is the site down? I know something's wrong with the database, but what's the error message? What's the exact detail here? A metric isn't gonna give that to you and in particular when people talk about metrics, they tend to have in mind a specific approach to metrics where this flood of events and data very early is distilled down. Let's count the number of requests, measure the average time and then throw away the data and keep the metric. So that's efficient, you know, throwing away data means you don't have to pay to manage the data and it gives you this summary, but then as soon as you want to drill down, you don't have any more data. So if you want to look at a different metric, one that you didn't set up in advance, you can't do it. And if you need to go into the details, you can't do it, an interesting story about that. You know, when you were at Google, you mentioned a lot of problem statements came from Google, but one of the things I love about Google is they really kind of nail the SRE model and they clearly decoupled roles, you know, developers and site-reliably engineers who are essentially one-to-many relationship with all the massive hardware. And that's a nice operating model, it's had a lot of efficiencies, it was tied together. But you guys are kind of saying, in a way, does developers use the cloud? They become their own SREs in a way because the cloud can give them that kind of Google-like scale in smaller ways, not like Google size, but that similar dynamic where there's a lot of compute and a lot of things happening on behalf of the application. Or the engineer, the developer. As developers become the operator through their role, what challenges do they have? And how do you see that happening? Because that's an interesting trend because as applications become larger, cloud can service them at scale. They then become their own SREs. What do you, how does that roll out? What's, how do you see that? Yeah, so I mean, and so this is something we see happening at more and more of our customers. And one of the implications of that is you have all these people, these developers who are now responsible for operations. But they're not special, you know, they're not that specialist SRE team. They're specialists in developing code, not in operations. They're, you know, they minor in operations. And they don't think of it as their real job. You know, that's the distraction. Something goes wrong. All right, they're called upon to help fix it. They wanna get that done as quickly as possible so they can get back to their real job. So they're not gonna make the same mental investment in becoming an expert at operations and an expert at the operations tools and the telemetry tools.  And so they need, they need tools that have a gentle learning curve, have a gentle learning curve and are gonna make it easy for them to get in, not really know what they're doing on this side of things, but find an answer, solve the problem and get back out. And that's kind of the concept you guys have of speak to truth. Exactly. And we mean a couple of things by that. Sort of most literally, our tool is a high performance solution. You hand us your terabytes of log data. You ask some question, you know, what's the trend on this error and this service over the last day? And we give you a quick answer. Big data, scan through it, give you a quick answer. But really it's, you know, that's just part of the overall chain of events which goes from the developer with a problem until they have a solution. So they have to figure out even how to approach the problem, what question to ask us. You know, they have to pose the query in our interface. And so we've done a lot of work to simplify that learning curve where instead of a complicated query language, you can click a button, get a graph and then start breaking down that, just visually break that down, which okay, here's the error rate, but how does that break down by server or user or whatever dimension and be able to drill down and explore in a very kind of straightforward way. How would you describe the culture at Scalar?  You haven't even done a B round yet, got an A round. You guys self-funded it, got customers early, they pushed you, getting now 300 plus customers. What's the culture like here? So, you know, this has been a fun company to build in part because, you know, the heart of this company is the engineering team. Our customers are engineers. So, you know, we're kind of the same group and that keeps the, you know, it kind of keeps the inside and the outside very close together. And I think that's been part of the culture we've built is, you know, we all know why we're building this, what it's for. You know, we use Scalar extensively internally, but even if we weren't, it's the kind of thing we've used in the past and we're gonna use in the future. And so, you know, I think people are really excited here because, you know, we understand why. And you have an opinion of the future on how it should roll out. What's the big problem statement that you guys are solving as a company? How would you boil that down if asked by a customer and engineer out there? What real problem are you solving?  You know, at the end of the day, it's giving people the confidence to keep, you know, building these kind of complicated systems and move quickly. Because, and this is the business pressure everyone is under. You know, whatever business you're in, it has a digital element. And your competitors are doing the same thing and they're building these sophisticated systems and they're adding functionality and they're moving quickly. You need to be able to do the same thing, but it's easy then to get tangled up in this complexity. So, at the end of the day, we're giving people the ability to understand those systems and... And the functionality and the software is getting stronger and stronger, more complicated with service meshes and microservices as applications start to have these ability to stand up and tear down services on the fly. That's only gonna yield more data. Exactly, you get more data and it gets more complicated. Actually, if you don't mind, there's a little story I'd like to tell. So, hold on just while I clear this out. So, this is gonna go back to Google and again, you know, kind of part of the inspiration of, you know, how we came to build Scalar. And so, this is gonna be a story of frustration, of, you know, a problem we got ourselves into that... Frustration and motivation. Yeah. So, we were working on this project. It was building a file system that could tie together Google Docs, Google Sheets, Google Drive, Google Photos. And the block diagram looked kind of like the thing I just erased. But there was one particular problem we had that took us months and literally months and months and months to track down. You know, you'd like to solve a problem in a few minutes or a few hours, but this one took months. And it had to do with the indexing system. So, you have all these files in Google Drive, you wanna be able to search.  You'd think, you know, Google search is a solved problem. But actually, so, Google Web Search is for things the whole world can see. There's also like Gmail Search, which is for things that only one person can see. So, it's lots of separate little indexes. Those were both solved problems at Google. Google Drive is for things a few people can see. You share it with your coworker or whoever. And it's actually a very different problem. But we looked at the statistics and we found that the average document, or average file was shared with about 1.1 people. In other words, things were mostly private or maybe you share with one or two people. So we said, we're just gonna make, if something's shared to three people, we're just gonna make three copies of it. And then now we have just the Gmail problem. Each copy is for one person. And we did the math on how much work is this gonna be to build these indexes. And in round numbers, we were looking at something like at the time, this would be so much larger now, but at the time we had maybe one billion documents and files in the system. Each one was shared to about 1.1 people. Maybe it was a thousand words long on average and maybe it would change, be edited once per day on average. So we had about a trillion word updates per day, if you multiply all that together. And so we allocate, we put a number request and purchased machines to handle that much traffic. And we started bringing up the system and it immediately collapsed. It was completely overloaded. And we checked our numbers and we checked them again. Yeah, 1.1, about a billion, whatever. But the work into the system was just way beyond that. And we looked at our metrics, so measuring the number documents, measuring each of these things, all the metrics looked right. To make a month's long story short, these metrics and averages were hiding some funny business. There turned out there was this type of use case where you'd have occasional documents that were shared to thousands of people. And there was a specific example. It was the sign up sheet for the Google company picnic. This was a spreadsheet. It was shared to about 5,000 people. So it wasn't the whole company, but a big chunk of Mountain View, which meant it was, I don't know, let's say 20,000 words long because it had the name and a couple of things for each person. This is one document, but shared to 5,000 people. And during the period people were signing up, maybe it was changing a couple thousand times per day. So you multiply out just this document and you get 200 billion word updates for that one document in a day where we were estimating a trillion for the whole earth. And so there was something like 100 documents in this category. So Google was hamstringing your own thing. We were hamstringing our own thing. There were about 100 examples like this. So now we're up to 20 trillion and that was the whole problem, these 100 files. And we would have never found that until we got way down into the details of the logs, which we didn't have the tools to do. And this took months. Because we didn't have the tools, because we didn't have Scalar. Yeah, yeah, yeah. And I think this is the kind of anomaly you might see with web services evolving with microservices, where someone has an API interface with some other SaaS as apps start to rely on each other. This is a new dynamic we're seeing as SLAs are also tied together. So the question is, whose fault is it? Exactly, you have the whose fault is it? And also things get so much more varied now. Again, web 1.0 e-commerce, you buy a thing, you buy a thing, that's all the same. Now you're building a social media site or whatever. You've got eight followers, you've got eight million followers. This person has three movies rented on Netflix. This person has 3,000 movies. Everything's different. And so then you get these funny things hiding. Yeah, you're flying blind if you don't get all the data exposed. It's like a blind person trying to read Braille, as we heard earlier. Steve, thanks so much for sharing the insight. Great story. I'm John Furrier, here for the CUE for Innovation Day at Scaleless Headquarters. Thanks for watching.


Self-importance, lack of empathy, and a constant need for praise and attention characterize narcissism. Narcissists may harm others for power. We'll talk about ego, relationships, and identification. What is Narcissism? Narcissists are grandiose, need praise, and lack empathy. Narcissists believe they deserve special care. They may abuse others for praise and attention. Narcissism can be taught, especially if a kid is constantly praised and prioritized. Remember that not all reared in such environments become narcissistic. Genetics, brain chemistry, and early events can also cause narcissism. Narcissism, real, entitled, or evil. Narcissism is a psychological disorder. Some narcissists are selfish or self-centered, but narcissism goes beyond that. Narcissists crave praise, attention, and lack remorse. They may be deceptive. These habits hurt egos and others. Narcissists merit our compassion and have deep psychological and emotional issues. Therapy can help narcissists change. Narcissistic relationships. Narcissism hurts relationships. Narcissists may have trouble forming long-term relationships due to their self-centeredness. They may struggle to empathize, causing conflict. Exploiting others can damage alliances. In romantic partnerships, narcissists may be critical, dismissive, and unresponsive. If their spouse doesn't measure up, they may become aggressive. Narcissists compete for respect in friendships. They may also be critical and unhelpful. They may work hard but criticize others and avoid cooperation. They may abuse others for career advancement. How to spot narcissism? Several signs point to narcissism. An exaggerated sense of self-importance, a lack of empathy for others, a need for constant admiration and attention, a tendency to manipulate or exploit others. Overconfidence. Narcissists often exaggerate their abilities. They may feel unique and expect others to like them. Arrogance and inconsideration may result. They lack of empathy. Empathy includes understanding and feeling others' feelings. To boost self-esteem, narcissists may seek attention and praise. If unappreciated, they may become irate. If you notice a pattern, beware. Help them get professional help. Are you narcissistic? The signs are identical. They include high self-esteem, a lack of empathy, a need for constant praise and attention, and a desire to manipulate or exploit others. Trouble with forming relationships may suggest narcissism. Do you fight a lot? Are you rude? Especially if you feel superior? Are you kind to everyone? If you suspect you might be a narcissist, expert help is beneficial for many reasons. A mental health professional can help you understand how narcissism affects your relationships and well-being. They can also help you design better relationships and habits. Mental health professionals can also help you learn care and understanding. Mental health professionals can help you build respectful, empathetic, and trustworthy connections. They can help a narcissist improve their life. Everyone deserves the opportunity to experience healthy relationships based on mutual respect, empathy, and trust. Hi, I'm Amy Golding, director of psychology for the Workplace Mental Health Institute. We hope you liked the video. If you did, make sure to give it a thumbs up. We have more and more videos being released each week, so when you subscribe, you'll get a notification letting you know when a new one's just been published. So make sure to hit that subscribe button and don't miss out on this vital information for yourself, your colleagues, and your loved ones.