I don't know how many of you are following this story. Probably none of you, really. Because I don't know how many of you are parents to infants right now. But this is a big story in the United States right now. Over the last few months, there is a substantial, significant shortage in baby formula. And this is not a minor issue. This is a major issue.  I mean, this is how we feed babies. Baby formula is crucial. And there has been and is right now a significant shortage all over the United States in baby formula. There is, it's more so in some parts of the country than other parts of the country. But in places like Texas, it is a severe shortage. Some grocery stores, supermarkets, empty, empty. Now, this was ostensibly triggered by the closing of a Michigan facility that produced about 50% of Abbott's formula product. And but it can't just be that. Because even before the closure of this plant, there were already shortages. And of course, when you have shortages, prices go up. Prices are going up in baby formula quite faster than price inflation across other products. So what's going on? Because in a free market, even if a plant closes, you don't actually get shortages. What happens is prices go up. People ramp up production. They fill the gap as they ramp up production and they fill with more supply, prices start dropping. But here, while the plant in Michigan was closed, nobody stepped in to fill the supply problem. And the question, of course, is why? Why are there still shortages? Indeed, many retailers are rationing their baby formula. Now, some of this can be explained like everything these days. Every economic problem that we have, the Biden administration and the Democratic economist say, well, it's COVID. It's the pandemic. The pandemic caused it. Supply chain issues, eh. But is it really? The fact is that there's no shortage in baby formula in Canada. There's no shortage in baby formula in the European Union. As far as we know, there's no shortage in baby formula anywhere in the world except for the United States. If this was a supply chain issue, if this was an issue that was resulted from the pandemic, then they would have been universal. They wouldn't have been localized to particular geography, to particular countries like the United States. So again, what is going on? Now, part of it is, again, going back to COVID. During COVID, some parents stockpiled. And manufacturers saw this as increased demand. They produced more. And then the baby formula just sat on the shelf. So they interpreted that as a dream. In other words, the demand supply signals were distorted because of stockpiling. There was cause not by any economic issue, but because of fear that resulted from COVID. And yeah, I mean, that is possible that these kind of, these mothers panic.  The manufacturers saw that there was no increased demand. They slowed down production. And there's some mismatches going on. And that might be global. But you'd expect that to pretty much quickly realign itself. One would hope. Robert, thank you for the tip. Thanks for being here. So I don't think it's just that. It can't just be the pandemic. So what is it? Well, here I have to get full credit to my now one of the economists I land up following the most these days. I've talked about him before. Scott Linsicum, who runs a, what do you call it, a sub-stack by the name of capitalista. Capitalisto, something like that. He writes about for the dispatch and he writes excellent stuff and he does excellent work. You know, he's more of a somebody who summarizes, does research summarizes the basic knowledge about a particular field and takes on issues like baby formula and digs in and to figure out what is actually going on. He's very good. Alejandro asks if he's an anarchist. I don't think he's an anarchist. I highly recommend his work. So I get a lot of info and the stuff on the baby formula, basically I've been following it through Scott on Twitter. Scott has an excellent Twitter feed. So you can go on Twitter and follow him. Definitely do that. Not John Cochran this time, although I'm a big fan of John Cochran's. Scott is a policy kind of economic policy kind of guy. He really digs into the details and into the trenches. So if it's not the pandemic, what's going on? Well, we know that when these kind of distortions, this wheat phenomena, places where suddenly supply and demand don't match up, where the market seems to fail, where markets are not working, where they don't behave like free markets, maybe it's because they're not free. So let's look at some of the ways. The baby formula market is not free. Now, I'm using this not because this is unique. I want to spend a little time on this and dig into this. Not because I think most of you particularly care about baby formula, but because I want to show you the distortive effects of government intervention all across the economy. Just imagine if this is happening with baby formula, what is going on with 1,000 other products, with 1,000 other products that are sold, that are used, that are imported, exported, regulated in the United States. So if we can take one baby formula and see how devastating regulations and tariffs and taxes and controls are, hopefully we can extrapolate that to more than just baby formula. Hopefully we can learn from this one example on how bad it is. I have interviewed Scott. I'm just going to call him Scott. Forget his last name, Scott. You can find the interview on my Ingenuism podcast. So the Ingenuism podcast I interviewed Scott on free trade. All right, so let's look at some of the things that are maybe not so free market around baby formula. For example, one of the things that you would expect to happen if you close a plant in Michigan that reduces the supply by this one manufacturer, Abbott, the largest supply of baby formula in the United States by half because the plant is shut down. What you'd expect is that people start looking around the world for surplus capacity in the production of baby formula. Let's say Europe, a very advanced baby formula market with a lot of companies that produce baby formula. And you would buy more from Europe. And you would say, please, send us more baby formula to the United States. We could really use it. Send it over here. And that's how the supply and demand get balanced out. The supply increases. The problem with that is multiple problems with that. One is the United States, we have really high tariffs on baby formula. On baby formula, we have really high tariffs, 17.5%. Now, it's a complicated system. It's 17.5% up to a certain quantity, and it can get higher, and it can get a little lower. But you can use 17.5%. So basically, you're paying 17.5% more for baby formula than they are in Europe for exactly the same thing. Because basically, American consumers are being taxed. It's not hurting the Europeans, it's hurting American consumers because of this tariff, 17.5%, which means that when production is eliminated in the US, we can just turn to Europe and bring it in. Because the price is going to be dramatically higher. 17.5% is almost 20% higher. I want to emphasize this to all of you who in the Trump era thought that tariffs were cool. We could penalize the Chinese. No, you're penalizing your own people. You're penalizing people who feed babies. Now, and to that, a lot of people said, we need to bring production home. We need to bring the production to the United States. Well, OK, baby formula production for a variety of reasons we'll get to in a minute, is mostly done in the United States. But now what happens when there's a problem with production in the United States? When one of your plants gets shut down, they were shut down by the FDA because they discovered deadly bacteria in the plant, not in the food, in the formula in the plant, then what do you do then? The whole beauty of a global supply chain, the whole beauty of having multiple sources of places where you can source material, the whole point of having a diversified sources is that whether production oversees something happens, a earthquake, a tsunami, or whatever, or whether it happens domestically, there's always access to other markets. The whole beauty of globalization, the whole beauty of free trade is you're not just going to get one place concentrating. You're going to get multiple sources. So for example, we could have gone to Europe and brought in. And indeed, we could have gone to Canada and brought in baby formula. I'll tell you why we can't go to Canada in a minute. But let's focus still on Europe. We've got the tariffs, one. But second, the FDA doesn't permit European companies to sell baby formula in the United States. Now why, you might ask, isn't baby formula sold in Europe pretty safe? Troy, wow, thank you. Really, really appreciate that. Thank you, Troy, for the 500 Australian dollars jumping in here with support. That's great. Why is it that we fear European baby food? Indeed, by many measures, European baby food, not baby food, baby formula, is safer than American baby formula. The regulations in Europe are stricter. Indeed, many parents who are into healthy baby formula try to import, try to buy baby formula in Europe and bring it in to the US even when there's no shortage. Now, they have to be careful because the customs will usually seize that baby formula and not allow it into the United States. Why? Because it hasn't met the arbitrary desires of the FDA. Europeans don't label their baby formula, and they food generally the same way as the FDA labels it in the United States. They don't provide you with the same kind of nutritional information that they're supposed to if they're going to sell in the United States. And on top of that, in order to sell baby formula in the United States, you have to register with the FDA, and you have to fill out the forms, and you have to spend all the money and the bureaucracy in order to become established as a baby formula producer and seller. So not only do we have high tariffs, but we also have major non-tariff, non-financial, non-tax restrictions on the ability of countries like Europe to sell a baby formula in the US. And then on top of that, we have restrictions in Canada. Now, here you can blame the Trump administration's trade negotiators as part of the renegotiating of NAFTA. You remember they renegotiated NAFTA because Trump was a free trader. All of you guys told me. Everybody said, no, no, no, you don't get it. Trump is really just twisting the arms. He's really just using tariffs to get more free trade. He really believes in free trade. Well, he had an opportunity. He could have pushed NAFTA to be a true free trade agreement. He could have, God forbid, just lower tariffs to zero on baby formula, on everything else. But here's an example. The NAFTA 2.0, negotiated by the Trump administration with Canada and Mexico, actually has provisions in it to explicitly discourage Canadian suppliers from producing baby formula. Why, you say, why would they do that? Well, to protect the American baby formula producers. But more importantly, to protect one of the most powerful lobbies in Washington DC. And that lobby is the milk lobby. You didn't know there was a dairy lobby, dairy products lobby in Washington DC. Huge, powerful, lots of money. It's Wisconsin and Minnesota and Michigan and all the states where dairy is a big deal. They don't want. They don't want Canada to use its dairy for the production of baby formula. Imagine if NAFTA 2.0 had declared baby formula to be zero tariffs with Canada. Canada would have invested heavily because it's got a lot of milk, got a lot of milk products, dairy products. They would have invested heavily in increasing production of baby formula, lowered the prices, and maybe made it less profitable for the dairy industry in the United States to run its little scam. God, there's so many layers to this. Everywhere you look, there's a special interest group pushing for something. And it all around some innocuous product like baby formula. Who cares? So Canada, which was about to make a Chinese company, was about to make a large investment in Canada in increasing the production of baby formula. Didn't because they couldn't then export it to the United States because the Trump administration wanted to protect dairy farmers in the upper Midwest. And as a consequence, played dramatic restrictions on Canada, the quantity of baby formula that Canada could export to the United States. And it goes on and on and on in terms of the complexity and the ridiculousness of the whole thing. It's absurd. But there's one more layer I want to get into. And then we'll move on. I mean, remember that dairy farmers also have price and income supports. The government often buys their excess milk. There's a million ways in which the government is subsidizing and controlling milk production and milk distribution and milk prices. And everything that comes out of milk, from baby formula on the one hand, all the way to cheese and everything else on the other hand. Milk in the United States is one of the most heavily controlled, regulated, subsidized products. Ooh, but you're on. It's a national security issue. Really? Really? So we will see. So that's a situation, but I want to add to this one more thing. And that is the special supplemental nutrition program for women, infants, and children called WIC. It's one of the 1,000 different welfare programs that the United States provides poor people. And in this particular program, low-income Americans add up a little 185% of the poverty line. That's almost double the poverty line. They get, basically, to buy formula at approved retailers at dramatically reduced costs. Now, what happens is that to buy this formula, to make it possible to sell it at dramatically reduced costs to these poor people, the USDA, which administers the program, it's the Department of Agriculture, basically has these large contracts with baby formula manufacturers. And they basically drive down prices dramatically. So they buy it from the formula manufacturers, and then make it available for people to distribute. And it turns out that half the formula, half the formula sales in the United States are done through the WIC, through the special supplemental nutrition program for women, infants, and children. Half. Now, when they negotiate prices with the infant manufacturers, infant formula manufacturers, they negotiate really, really, really low prices. They have incredible market power. They're buying half. On average, they get 92% below wholesale prices. In other words, the formula manufacturers are losing money on what they sell to the government. But they want to sell to the government because they get shelf space, they get visibility, they get the credibility of selling to the government. And then they try to ramp up prices on the other side to try to make up for it. And of course, they don't face foreign competition. So they don't have to worry about that. So they can afford to lose money to the government as long as they can make money off of regular consumers. Now, this has an unbelievable destructive and restorative effect on the market. Again, it's no free market. The government is a massive purchaser. Now, you can extrapolate the consequence of this to what would happen or what is happening when the government is a massive purchaser, for example, medical drugs from Big Pharma. The same kind of restorative practice has happened. The same kind of malinvestment, lack of proper investment happens. Half the market for baby formula is controlled by a single buyer that demands unprofitable prices and compliance with piles of state and federal regulations. That's how you get a concentrated market. Who else is going to be able to do this? Nobody else can sell to the government except three big companies. And they have to be massive and huge so that they can make money elsewhere so they can subsidize the sale to the government. Gene, thank you.  And again, we've talked about there's no competition international. Price signals are completely distorted. In a free market, when you have shortages, prices should go up. And again, encourage production. But here, most of production is sold at 92% discount. So prices are not significant enough to cause increases in production. They're getting the same price from the government. These are long-term contracts. So again, you can see how this would affect drug prices. You could see how this would affect the medical industry. It's just unbelievable that this is America, that people are under the delusion that this is somehow capitalism, under the delusion that somehow we live in a free society. The baby formula crisis that we have today is not caused as Elizabeth Warren and Joe Biden would like us to believe by greedy corporations. It's caused by bad US policy, bad US policy, by Republicans and Democrats. Bad US policy in terms of tariffs, bad US policy in terms of FDA restrictions, bad US policy in terms of structuring a welfare program that distorts markets and therefore hurts everybody. If you want to do welfare, there are far more efficient ways of doing it. One of the advantages Scandinavia has over the United States is that they're more efficient at distributing welfare. They don't distort the market as much as America in the welfare system, which is unbelievably destructive. So US policy makes any kind of shock to the system worse. Trade barriers make everything more expensive, restrict consumer options. And again, we're not talking about, ooh, baby formula from China and who knows what they're putting into it. We're talking about German and manufacturers in the Netherlands who, again, are being regulated by their own states. So imagine a world in which the president of the United States facing a crisis in baby formula. And again, it's really a crisis.  Would say, OK, I'm going to get a bill through Congress that does a few things. One, it eliminates tariffs on baby formula, eliminates them, zeroes them out. Two, it requires the FDA to allow into the United States any baby formula that has been approved by an equivalent regulatory agency outside of the FDA, outside of the United States. So I'm not going all out lezific capitalism here, right? Not ready for that yet, the world. But just common sense, just simple stuff. If the Germans have approved it, it's probably OK for Americans to. Three, we're going to do away with this subsidy for poor mothers. We're going to give them instead of voucher and make them consumers. We're going to make a voucher for a particular amount of money so we'll subsidize, we'll continue to subsidize. But we, the government, won't be buying the formula. We'll let consumers buy the formula. We'll just subsidize their purchase. We'll give them a voucher to buy formula. And now increase the market, not shrink it. What if you just passed a simple bill like that? We're going to zero out tariffs on baby formula. We're going to change FDA regulations to allow the importation of baby formula if it's been approved by an equivalent agency overseas. By the way, you can do the same thing with drugs. Why do we need Europeans to prove it and the Israelis to prove it and Australians to prove it? And then the Americans maybe will approve it too. Why can't there be some reciprocity under the assumption that all those agencies use basically the same methodology and are very, very similar to one another? Given that we already have those agencies, I'd like to do away with all of them. How about somebody in the political spectrum offering actually a market solution to these problems? Now, what does the Biden administration want to do? They want to do the same thing that the Nationalists want to do. They want to do the same thing that the Trumpists want to do. Oh, let's use the emergency production powers act or whatever it's called to force domestic producers to make more. Let's bring the supply chains back home. No, that's exactly why we have the disaster we have. We need a diversity of sources. We need to be able to produce goods all over the world. Thank you for listening or watching The Iran Book Show. If you'd like to support the show, we make it as easy as possible for you to trade with me. You get value from listening. You get value from watching. Show your appreciation. You can do that by going to iranbookshow.com.  Also, if you'd like to see The Iran Book Show grow, please consider sharing our content and of course, subscribe. Press that little bell button right down there on YouTube so that you get an announcement when we go live. And for those of you who are already subscribers and those of you who are already supporters of the show, thank you. I very much appreciate it.


All right, Rock. What's up, Defcon? How you doing? So I have a little bit of a problem here. I can't see on my own laptop, so I'm going to be like walking back and forth, taking a peek at what my slides actually say, and then talking a little bit about them. So my talk is titled Every Breath You Take. A lot of people in this track are talking about, you know, anonymity, privacy, hiding from the internet more or less. I take kind of a cynical approach to that. I don't think it's really possible. In a way, I don't think it's so bad. You can do some useful things with it. So I'm going to go a bit into data gathering analysis and some other cool things you can do. So the main focus of my talk is just data everything that you can possibly do. So I'll walk through a little bit of what I mean by data. We're all smart people here that have our own views of what you mean by data. It could be stuff over the network, stuff in the physical world, anything like that. Gathering, persistence, mirroring, analysis, and kind of forecasting, targeting, what you can do with this data once you get it. So first of all, a quick little introduction. So you know who I am? I'm Jim O'Leary, a.k.a. Jimmy Oh. So I've been doing security work for a while. I'm mostly a corporate, stiff, white-hack guy. I have undergrad background in comp science, like, so that's why I'm really interested in a lot of this human-computer interaction and what it means going forward. And so I am employed. I'm not speaking on behalf of my employer right now, so anything I say is just going to get myself in trouble. And so a little story to get things started. So we started off with this little picture of the world, right? I'd say that it doesn't matter if you're a creationist or like one of these science guys, it's really hardcore. At some point the world happened, right? And we're in it right now. And there's this feedback loop that takes place to kind of maintain the systems that are going on and like, you know, the room you're in right now. And you just try to abstract it up to where you are, right? So you're in a room, you're in Vegas, you're in Nevada, you're in the United States, you're in the Earth, right? So the whole scope of kind of like, it's just tough to appreciate, right? Like you can't grasp all this in one thought. Like everything that's going on right now, it's just amazing. So eventually, right? Depending again on your views, but, you know, we showed up at some point and we're here right now. So the Earth, right? Kind of spins that guy out. And now we have a feedback loop with our environment, right? So it's hot outside.     And I'm also trying to introduce this guy. So this first guy actually could have just been life in general, right? Now we're these higher intelligent beings. We're self-aware. So we can also do things to ourselves, right? And then see how that creates, oops, I'm going to trip over wires here. See, you know, what kind of situations those result in. So lastly, and I can just skip to my whole, like, big picture here, right? So we have computers and everybody in this room works pretty closely with computers, probably spends, I don't know, say like eight hours a day at least on one. And my whole talk here, right, is just trying to kind of bridge this whole loop together to do something useful, right? A lot of people are kind of scared for good reason of the lines between the computer and the person, because it usually isn't a direct line, right? If you're doing something over the internet, there are millions, well, not millions, but lots and lots of people, they can potentially be looking at what you're doing. And even since you're working in their system that they define, like there's no way that they won't be able to know what you're doing, unless you make your own internet, I guess. So my data definition here, this is where I start off more on the physical kind of stuff. It's just everything that you can possibly gather, right? It can be like what time it is right now, where you're at, temperature, all this stuff. You can kind of read it, but, you know, basically I sum it up as just a bunch of stuff. And it is what it is. So on top of your data, you can also classify it into a bunch of different classifications. So this is just a really small subset, but some of which will be interesting to the security folks, right? We have your private data that you want to keep to yourself, public data you don't mind broadcasting, personally identified data, all this kind of stuff that you should be pretty familiar with already. And this is when I made you to walk to see what my slides actually say. So gathering is really, you know, kind of observing this data and pulling it down and getting yourself in a situation where you can actually do something with it. So there are a bunch of different models for gathering this data. You know, like Push is something proactive like email or, you know, even in Twitter where you're like actually doing something to create the transmission of data. Pull is a little different, right? So when I want to check all my blogs, I just go to, you know, like Google Reader, check out everything everybody's pushed to me. It's a little different. Voluntary and involuntary. So like I said, any of these opt-in models or it's like Twitter, I send somebody a status update. Like I'm actually volunteering into submitting this data. Involuntary stuff gets interesting, right? This is where your ISP is sitting between all your web requests and you and they're looking at, you know, what you like to browse for, you know, so they can provide targeted ads or start selling your stuff. That's when it gets a little interesting. The other interesting thing here is that a lot of systems say like AOL and Messenger back in the day and I think to this day, right, your status and profile are, you know, just public all the time. And so most people don't really grasp that, right? Because they have this notion of here are my buddies on my buddy list and these are the people that can talk to me. They don't also realize that anybody can query this information and pull it down. So self-regulating, self-aware are more of like you'll see this theme a bunch in my talk where I start running down things that are bigger than I can actually like appreciate. So those things are more just, you know, exercises left to the mind of the reader. And then inadvertent is interesting. I think you'll see that as a pretty common theme and why I'm so hopeless that you can actually keep stuff private, right? You have the AOL data leakage thing. You have, what is it, like Lexus Nexus. Pretty much anybody that does anything with your data is going to lose it at some point. And so how this all started for me and this is more the person to the computer line is I got one of these scales about three years ago and it's pretty sweet, right? The weight, your body fat, actually my boy Vich right there had one back in college and so it's kind of the inspiration. But so it's a pretty sweet little thing, right? You get an actual concrete number as to what you are pretty much at that point, right? It's not everything you are, but it's a measurable, you know, representation of self. So that's cool. It can give you a snapshot of what you are like at any given time. The more interesting thing is right when you start gathering this data. So for a while I would be like, I weigh like 100 something pounds. You know, I'd hop on like a week later and be like, okay, yeah, I weigh more or less the same but I don't remember what I weighed last time. So I started hanging up this sheet right outside my shower.   But it's just cool that it gathered the data and see what happens. So, you know, here's just some readings from, I guess, way back in the day. And that's turned into, these are like both front and back. It's about two and a half years worth of data that I just haven't even put into a system yet, right? Because I know it's there and it's kind of interesting but I also am either like lazy or doing other things. And so at some point, I'll get around to actually putting that in and analyzing. But even just taking quick looks, right?  So I was like, hey, you know, that's not so bad. So once I got on this kick, I started seeing like what other things I could personally measure about myself at any given time. So right now, if you saw me when you walked in, I was kind of like fidgeting with this like brozier kind of thing. But it's this heart rate monitor strap and watch that I have right now. So this big honkin watch is taking my heart rate right now. So it's 115 because I'm kind of walking around a little nervous. And also like altitude, temperature, all this stuff, right? So they market it actually as a personal computer instead of a watch. This thing is a beast. It's not cheap, but it's pretty nasty.  This is the client software they shipped with it that is pretty sweet. This is me just going for a 20 minute run around my neighborhood, something that I do like fairly frequently and would never capture. Now that I have the hardware to do so, I might as well do it, right? I don't think that anything particularly useful is going to come out of this information, but just the fact that I can capture it is cool to me, so I'll do it. So this is a little, actually I'll give it the next one, a little more interesting just from the altitude side of things. It's cool to see that this thing really works. I can't wait to go take it snowboarding this winter because it'll be pretty sweet. It'll do your vertical speed and everything like that. But you can see how just normal like kind of boring things turn into real computatable data and click around on things.  And you can see that the heart stuff is really pretty cool. I think that some more people should look into this body hacking. There's a whole lot of stuff online, but you know, it can be pretty dangerous. It's like overclocking your heart stuff. That's not, you know, particularly safe. But you can see here, right, where I was kind of pushing it from time to time. I think like if you go over 170 beats per minute, you're going to definitely be feeling it. And it's not even that sustainable. So this is stuff that I didn't even like try to slow down. I just had to slow down and take a break. So at one point I think I cracked, it was like 182, like really just pushing myself. I think that, you know, if I were in a little worse shape, it would be a bad idea to be like running all these experiments on my heart just out in the middle of the woods.  A lot of us in here are big fans of complex systems and everything like that. So, you know, the human body number one is just super, super complex. So you should be really interested in that to begin with. Second of all, like your own, right? This is what you are working with every day, right? And once you're out of there, you're out of there. So it's really interesting to kind of, you know, get some benchmarks on where you are personally and even just track the stuff. I think that if you get enough of it, you can create a pretty good representation of what somebody's life more or less has been like and kind of model out at least some of the, you know, less of these like soft human skills or soft human characteristics. But just the fact like, hey, this guy was here. He was doing this stuff. He weighed this much. It's just really interesting stuff to gather all this data. People that are worried about losing this data, I don't really know why, right? It's terribly uninteresting to almost anybody but me. Maybe my insurance would be interested in this, but even then, I don't know, if anybody can think of some good reasons why my like heart rate might not want to be leaked out. We'll talk in the Q&A. So some of my friends out in Seattle have, you know, kind of come to learn that I'm this weird data gathering kind of guy. So one of my buddies gave me this radiation like gamma detector USB thing, right? So I don't have it with me today because I think that just trying to get on the plane with a lot of these things is a little interesting, right? You have to take off your like heart rate strap and then try to explain the radiation monitor. I think that it's a little strange, right? And we're not even at the best part yet.  This is me waking up in the morning and the radiation level is in my room. I don't know why they dropped down. This is just a 15-minute sample. But, you know, I guess I woke up, brushed my teeth and became less radioactive as the day went on. So, you know, just more cool stuff. It's available and if you think about it from like a world modeling concept, like if you haven't seen the Matrix, go see it several times. And I think that may be where I'm ending up with a lot of this stuff. I'm going to kind of recreate my own mini world and I have like, you know, be playing the Sims with myself. It could be the gyms. And now for the most one part of the talk. And this has been by far the most popular data gathering exercise I've done. But, you know, blood alcohol content, really cool stuff. So this nifty little product here is called the Alko Hawk. It has Do Not Drink and Drive written all over it.  You know, it fits right in the glove box, all this stuff. But you can see that there are a couple different types of people that buy this device. And this is going to be way too small to read. But I did want to squeeze the two types of people joke into my slide somewhere. So the first group, right, it's kind of like these data dorks like me that, you know, they're going to be drinking anyways. They might as well try to gather some data on the fund that they're having and see what they can grab from it. Then we go down one more and we grab some water real quick. Yeah, yeah, just water. I can even blow into the Alko Hawk to show you. And what we're doing here. So this guy, you know, now uses it as a proactive kind of measure. So he got busted once through like a 0.173 or something like this. You know, pretty high. And he's like, now I'm never going to do that again. I got the Alko Hawk to save me. And then towards the very bottom of the spectrum, this is a little bit of a sad story. But these are the Amazon reviews, by the way. This woman is buying her second Alko Hawk because like her husband is an alcoholic and she makes him blow into it every day when he comes home from work. And somehow this thing, you know, fell into the couch and broke. And she's buying her second one. I think I know how it broke the first time. But, you know, it's just interesting to see the spectrum, right?  And then you have these people that are using it as like a, I don't know, relationship maintenance gauge or something like that. So let me see here. I think you're all familiar with the XKCD comic as well. This is Bomber's Curve. Yeah, give it up for XKCD. It's pretty sweet. But as you can see, and I've tested this a little bit. I don't think it actually works out too well with me.  After that everything just tends to level off. And so like some data here, right? Most people, has anybody ever blown into a breathalyzer? All right, well, it's actually, you know, more than your average, I don't know, population as far as representative samples. So I don't know if that means we have a lot of criminals in the room or just like people with access to cool equipment. But, you know, you never really have an idea as far as what you're actually at until it's potentially too late, right? You shouldn't be drinking and driving anyways. But even, you know, drinking and operating heavy machinery, perhaps, is something that might be a little more tempting to do. So you can see here just some data that I've pulled off my fridge where I keep most of this stuff. You know, a couple of Hanuken, out playing pool, I wait 45 minutes. I come home, I blow 0.027, I believe. And it's like, oh, it's not too bad. And then you try to, you know, some of my friends take this and extrapolate it out so they're like, all right, I can go drink eight beers and drive home. It'll be totally cool. I don't think that's what this is by design for either. And then the, let's see, another time. I was at a Mariners game. I had three beers and I came home and I blew 0.094 and I was like, wow, this is shocking. You know, I didn't feel that bad. So I had to go recreate it, you know, do it again. And it was 0.072 the next time. So there's a lot of variable to be taken into account of too, right? I think, you know, if I eat a sausage instead of a hot dog, I'll lose a little bit. It depends on how hydrated I am that day. All this kind of stuff. Let me see. Coors light's not very high in alcohol content there. You can see that I pound, there's about like a pitcher, a little bit more. And then, you know, just kind of drinking it over the course of the night. Got out there, blew like a 0.08. So, you know, pretty reasonable. And then this last one was when I was really trying to push it a little bit. Some of my friends are having like a competitive drinking game. And, you know, we all drank pretty significantly. And with the intentions of blowing into the alcoholic pretty much by the time we got home, instead, everybody just fell asleep. So this is seven hours later when I woke up. I blew a 0.121. Pretty significant. Pretty significant.  But I had the data to back it up to be like, look, I was legitimately very drunk. And she, you know, just makes it a little bit more okay. So, yeah, you know, I haven't really measured myself as far as like drinking beers and going out on an autocrossing course and seeing how many cones I run into or something like that. But this is a coordination, you know, oriented sport here. You know, be it as it may, it's not really that involved. But you can see, this is the morning I woke up with the 0.121. I had a 9 a.m. softball game. And so these are batting average. I think I'm on the right and my friend's on the left. But, you know, we're pretty consistent. I think, you know, you can, there's this whole realm of statistics you can take with baseball and softball. But people are more or less consistent over the course of different games. Yeah, when I was legally drunk, I just couldn't hit the ball. And I think that just comes down to the whole coordination thing. It's pretty cool to see like that. So with that in mind, has anybody been drinking today?  Yeah? All right. So I have the alcohol with me. And I'm going to actually, so give it away to the highest blower right now. So if I could get like five people, and I'll continue with my talk. And so actually, you can grab some round of there. The one thing that we're going to have to wait for, you need to, maybe like you can't drink a beer and then blow into it, right? Because it's going to contaminate the results.  Anybody else? Anybody else?  No? And so yeah, I mean this gets to come home with you. All right. So you just got to give it a really deep from the lungs kind of breath. And so I'd wait until this yellow light stops flashing and then give it a go. And so I'll just keep on moving along as people are blowing and then announce the results. Yeah. Give it a shot. All right. Very nice. So 0.023. You know, respectable. Respectable for what is it? Like just afternoon or something like that. Yeah. Give the man a hand, right? All right. You can just grab it.  So this whole thing I'm trying to get out of this, right, is data awareness.  I think that I've really learned now after this feedback loop, right, you tend to, you know, run around the block and this thing that does my body fat percentage also takes like how much water I have, so how hydrated I am. So I'm at the point now where I can hop on my scale and pretty much know what my body fat and almost weight are going to be when I step on there. So did you press this button? All right, cool. So this is the same now, like whenever I have a couple beers and I'm feeling a little buzzed. I'm like, I wonder what my alcohol level is right now. So last night I actually went out with these two guys. We did some pretty good drinking until about like three in the morning. So at 3.30, I blew a .087. You know, it's pretty respectable for having drank a good amount. And then I didn't hydrate before bed, which is a big mistake. So I woke up at 7 and blew a .02. So, I mean, not crazy, but it would have made my morning a lot more enjoyable had I not been too tired and lazy to actually drink some water. And the water, I'm staying in a circus, circus. Not that good. So, anyways, a little tangent there. So data awareness, right? The fact that I'm aware of this stuff now, right? Just gives me another kind of... What do you got there? Zero. Oh, all right. We have a... Oh, really? All right. Well, you, my friend, are good to go and do anything you want to do. Pop one out. So, yeah, getting back to awareness, right? If you look at where we are right now, right? This is like the anti-awareness capital of the world.  So, you know, some things that point this out. Try to find a clock anywhere near a gaming table. They keep the lights at the same level all the time to trick your body and to think, you know, it's like, what is it, two in the afternoon now? It's really two in the morning and you've been gambling for the last 10 hours. What else is there? The tokenization of your actual cash, right? People have been working for a while to get this notion of, like, I'm working for money. Now, we have another .02. Was the other one .02, three? I think it was, right? So, you got a .0003. And this good thing, I bought the three-digit accuracy model or else we'd have some problems. But, yeah, this abstract tokenization of your money just means, like, you just see it as you're playing a game.  So, the free drinks are a problem. And, like, you can definitely, I don't know if the pit bosses would let you bring the alcohol to a table or not, but they don't like you talking on the phone.  They don't want you to know what's going on in the outside world. All you should think about is putting your money on the table right now.  So, moving a little bit from the awareness to kind of, like, the privacy security side of things, which is, what do we got there? Oh, 013, not bad. And then, yeah, this is the last one. I guess you may just have to brush it off. And so, my only request is that this makes it to the TCP IP drinking game at some point, too. Just, or, you know, it should be passed around. And so, yeah, now moving on to, like, data, what you do with this data, this is more stuff that's taking place on the internet, more digital, digital, instead of any of this physical to digital transaction, or, yeah, moving, jumping around. So, talking about data gathering, right, and this goes back to, I talk a little bit about the AOL presence or anything that it'll give status on somebody. You should be able to, if it's a one-time thing and you have access to it, there's nothing stopping you from storing that yourself locally. So, you can potentially have a local database that you maintain of everything all your friends have ever done online and such. What do we got there? Oh, you got to repeat it for some reason. I didn't like it. So, you just got to hold on. I hope you take it down. You got the PBR hat on and everything. I feel like you're the, you know, the favorite. So, yeah, if you can gather all this information on people, it's just pretty cool stuff to do. You know how it'll affect your friendships and everything. I personally don't do this, but it's just interesting to be able to mind what people are doing. So, this harvesting can be pretty expensive, though.  Oh, one-seven. So, we have a winner right here, my man, the .023. Very nice, very nice. Came out of the gate strong, put up some numbers that held up. I got to say, a little disappointed, though. No legal intoxication at, you know, DEF CON at one in the morning afternoon. But, anyways, back to stuff that actually matters. So, this data harvesting can be expensive and really time consuming. A lot of the kind of big search engines and stuff will do this for you. I think Greg Conti's talk that's going on either next door, I know it's at the same time, so I didn't like the competing with him was a little difficult because we're talking, at least this part of my talk is really similar as far as, like, all this data that's getting piled up on the internet, what's it going to mean to you down the road? So, this quick demo, I actually don't have internet on here, so I'm going to skip over that and just keep talking. But, the best thing you can do, right, is just speak HTTP. Like, write your own clients. So, don't mess with browsers anymore. Just to pull this data if you're interested in it, just speak raw HTTP, parse the HTML, grab what you want out there, and store it. So, social networking has a huge component to all this. There's the hacking social networking talk, which is good, I caught it blackout. But, at least from my perspective, I keep stepping on that cable.  But, the news feed in Facebook, right, when that first came out, it was a really big deal. A lot of people didn't like it. I saw that, you know, using the news feed, I could see that all my friends were joining these, I hate the news feed groups, and they were learning about them using the news feed. So, it's a little ironic. But, you know, people really hated it at first. The thing is, with any of these kind of invasive technologies, they say, hey, you know, I guess you can opt out of it now and all this stuff.  People liked it too much, and, you know, the users can really be worn down to just accept privacy compromises pretty easily, right? If you just offer enough cool stuff, people will give it up. So, this is like the, you know, candy bar for the password study that gets done every year, and everybody gives it away, or like, you know, the hot girl asks you for your password and you give it to her. I think that, you know, the bar is actually kind of low when it comes to what people will compromise for usability. So, let me see. And I came into the Facebook bank a little on the late side. You know, I graduated 04. I didn't have it because I went to a small school. Sorry, I didn't mean to cough directly into the microphone. But, you know, I feel like I'm an old, crappy guy now when I say kids these days. But, if I go back, and I need to go back to Boston and stuff like that, I hang out with some college kids and they're just totally embracing this, right? Everybody has digital cameras. You go out to a party.  Now, everybody's going to capture digitally, and it's not going anywhere, right? It's going to be there forever. So, I liken this to the Facebook paparazzi a little bit. Yeah, alright, so that thing's going online somewhere. And I'd actually say hi to my digital audience, on YouTube or whatever, it's getting recorded. But, yeah, so you go to a party now, and you're just trying to have a good time, and everybody's taking pictures of you, and you're like, dude, just cut it out, man. But it's just that, you know, I'm hanging out with these younger kids that are totally used to doing it now, and it's just the way it is. Also, it's added some, I guess, interesting complications to the dating scene in general, right? People always have this problem now. It wasn't existent before about the interrelationship struggle. So, on Facebook, right, you can be single, or it's complicated, and it's always with somebody else, right? So, say you're in a long-term relationship, it ends. Big move, right? It's who's going to set their status a single first. You know, somebody's going to have some feelings about that, like genuinely, which is really interesting, right? Because this is one of those divides where it hops from the digital, or the physical to the digital, and then the digital back to the physical, right? Like, your feelings actually get hurt because somebody changed their relationship status. And also, you get into a new relationship, then, you know, the talk starts coming like, hey, how come you guys aren't in a relationship on Facebook yet? And, you know, then it's kind of like, it's just a little, not exactly uncomfortable. It's funny that this kind of, I don't know, totally abstract representation of what's going on in your life has come to mean so much, and even so commonplace, right, that non-techy nerds will start asking you these questions. My space, I don't know, I guess I do mean to bash them, but they have pretty much more of the same thing. I think that a lot of people on there are actually a lot more willing to just give up all the information you could possibly want.  He's just like, oh, just keep giving it to me.  So persistence, how am I doing on time? Is it 1.37 right now? Is it all right? All right, cool. Persistence is more this kind of capturing that I talked about with digital photography will do it. I'm kind of doing it right now and persisting like I'll log my work out I'm getting right now. But also, if I move up and down, my altitude will change a little bit. And it'll be cool that I can even play this along with the stream of the video, right? And you'll see probably when I goofed up, my heart rate went up a little bit. It's just kind of interesting stuff. But the thing with kind of like this whole Web 2.0 and how was it like times, person of the year was you, is that all these kind of nodes are getting connected now, right? So just now, I think like a handful of people have taken pictures of me just on stage, right? So before, maybe you'd get one like corporate photographer who like that was his job to come take one picture of the thing captured in the moment now. Pretty much anybody can do it and does do it. And so you end up with just lots and lots of representations of the same thing. And they're all more or less pretty true, right? Like if somebody photoshopped, you know, like a beer in my hand or something like that, then all these other copies of the same event would work to kind of like bring out the truth. So let me see. Yeah, and so a little Wu-Tang quote here, you got, you know, what's been done can't be undone, son. So if you don't want something to be captured, just don't do it to begin with. But, you know, once the bits are uploaded to the network, you know, in the worst case situation, you know, somebody's spying on your traffic so they got it, your ISP is looking at everything they do, everything you do so they have it.  I don't want people to see it. You remove the tag that, you know, indicated it was you. I don't know. There's still a lot of residue, at least in their system, your system, just tying it all together, right? So once it happens, it's pretty much happening. If it's been captured digitally, there's no finding it. So everybody knows, right, this is kind of like the time-tested principle, that security through obscurity, horrible idea. I don't think people really thought about privacy through obscurity, right? People are like, I'm going to take all these naked pictures of myself, but I'm just going to put them on my hard drive and that'll be cool. But then you get owned, right? And then they end up all over the internet. So I think that the only way to really guarantee that these kind of breaches don't happen, or even, you know, the case where you post it on, you know, like a lockdown, like Google share, you know, some box you shared, even that will get owned at some point. So if you really think that you can capture something and, you know, keep it from all prying eyes, you're kind of hopeless as my take. So, you know, this is just a real quick, like if you don't, if you want privacy, either, you know, don't do what you are about to do and want to keep private, or, you know, do it, don't tell anybody about it, or do it, tell your friends about it. But you know, the more this information spreads, the more out of your control it's going to be, and, you know, you just end up losing your control over it. I think that jumps into, like, the sex-tabe era, right? I think we're in right now.  Kim Kardashian, right? Britney Spears' kind of questionable photos there, but so Britney is a little bit different because she was famous first, but everybody else uses kind of like a springboard celebrity. And so I think that it's interesting now. The problem is when everybody starts doing this, it's going to become a lesser, you know, like a lesser of a phenomenon. So people are just going to be like, oh yeah, whatever, here's another sex-tabe out. I don't even care. So it's going to get more and more extreme as we go forward in society, right? I think people just tend to, like, water down there, I don't know, shock system. You start seeing too many things. You become really indifferent to it, and you just need to get one up to a little bit more. So, and this is, here's a dun dun dun. This is what a lot of people are talking about here, is who else is in between these arrows that go between the computer and you. And the answer is, right, there are a lot of people. Let me see what we've got going on here. So a little proactive stuff you can do, I like to call it data elusiveness, is if you need to send something to somebody, right? You say you have some pictures, you want to send them to a friend of yours. A lot of people right now just use web mail, email or anything like that, and when you don't realize it, there's just a lot of residue whenever you use any of these systems. The copy, and this should have been animated, but isn't. So there's you, there's your friend, there's the service over there. It's going to end up on a remotely accessible host somewhere on the internet, probably forever, right? So I think that if you are going to send something to somebody, you should do it on your own terms. It doesn't take that much code to actually write your own little, kind of like Dropbox, host it on one of your boxes, and just go from there. You can even write a client that you give to all your friends, right, that will provide some encryption. So you say, hey, you want to send me a file? Great, here's this program to run. You know, they have to trust you to the point where they'll actually run your code. But you know, run this, it's going to do a lot of, you know, super secret stuff that is going to encrypt it, maybe obfuscate it a little bit, and then dump it directly over an encrypted channel to your box. And so it really ups the level of security in the system.  But it will kind of like up the ante where people aren't just going to accidentally get it exposed, right? With the webmail example, a lot of people will use the same passwords all over the place.  It's really kind of devastating if you end up in that situation. So on top of that, right, just use SSL, almost everywhere, right, with this new DNS thing that came out, like that should scare you enough. But everybody, almost everybody now, will offer at least an SSL initial connection to like webmail, not necessarily by default, right, so opt into it if you can. So here's just, this is more probably very difficult to read text, but it does sum up kind of everything I've been getting at, like pretty well. So you have this couple out in Washington, and they ended up getting charged for murder based on the phone history, the text message history that they had exchanged between each other. So I think this first thing, I can't really read it here, but they talked to the police and they said, oh yeah, I didn't send any text messages to this girl, and the girl said, oh yeah, the only thing that I got from him is like an I love you, or something like that. I think this is the, I can't really see it, but the one thing I want to stress, right, is if the government comes to knocking to any of these people that host your data and have the residue, right, they're just going to sell you out like that, because that's pretty much what they have to do. It's in their best interest legally from a business perspective. You don't really want to fight the government. So these guys thought that they could just erase the text messages on their phone, and actually in like a pseudo smart move for murderers, I guess, they sent cover up messages to each other that they left on their phone. So they deleted the old messages, then they started asking questions about the guy that they bumped off, and then they, you know, when they figured that their phones got turned over, they'd have like this kind of like cover up to show to the police. But so the, let me see, phone provider sold them out, right, they ended up going to jail. It was also interesting that the, kind of like one of the basis, they were trying to kick this guy out of the house who they were all living in, but he had some pornographic pictures of the woman stored digitally or something like this, and it was just another thing, right? So they were fighting over control to pictures that she had taken in the first place. You know, if you'd never had the data out there, it never would have led to that problem. So I think like data control is really, really powerful. I don't know, I think people here get it pretty well, but it's just like one of my messages to you, right? Data itself very powerful, and then control the data, and keeping it yours if you can is good. So I'm running out of time a little bit. I talked about this moment in time principle, but some places will show you, like instant messaging platforms, for example, they'll show you somebody's current status, but they won't go back and show you every status that they've ever set in their whole life. So this is where it comes down to you just grabbing it if you want to, and maintaining a database locally. Personamies, you can check it out. I think just Google that. But, you know, they're the digital representations of self, so a lot of people will have to do a lot of monitoring on what their digital footprint actually is, right? So me giving this talk, probably going to up some Google results somewhere, they're going to tie me to DeathCon. Although Jim O'Leary, very popular name, and you know, kind of just, you get usually a bunch of just white Irish guys of which I am one. So, let me see. But you know, it'll just add a little bit to it, only in my just being here and having some web presence. So data analysis is where it gets really interesting. This is where I'll host more stuff online, and I'll say it at the end, but I should say it right now. It'll be on, it's in the slides too, but like dl.jimeo is jimio.com, and then slash d-c-o-f for DeathCon. I'll probably link it up, but this is where you can actually find some code on some fun things you can do with data. So, and I would demo these, but it's more interesting actually to look at the code and look at the data sets. So, this first thing, I called it kind of BrotherGeta, and I dropped this phrase, you know, this is like a pretty common cliche. I was looking for a code review or something at work. I was like, oh, kind of BrotherGeta code review, and I was like, oh, that's kind of funny. I wonder what else a brother may like. So, I wrote something that would just, you know, pin Google looking for that phrase and extract all the results. It's really pretty interesting. So, I'll put a link up to that, and the code's pretty cool. This is for unlawful kernel knowledge. I'm a little bit interested in extracting, not so much meaning, but a lot of, like, inadvertent things out of data sets too. So, this guy, and the code, again, is interesting, and it gets a little bit long, but it'll parse news articles looking for instances where, let me think here. So, if you take the first letter of every word in the article and put them all together, it'll look for instances of swear words. So, for unlawful kernel knowledge, bam. So, that's a little interesting, just because people will drop things in there. Also interesting is the inadvertent haiku finder. So, the same thing. It works on these articles. It has a big back-end database for not really natural language processing. NLP is misused right there, but correlating one piece of data to the words, and then it looks for people that accidentally wrote haikus in their articles. It's pretty cool stuff. And so, the links will be online for the code and the actual applications. But, you know, it's just totally useless, right? Who's actually gonna do anything cool with that? But interesting. So, lastly, and this goes back to my first point where I'm just gathering all this data. What do you do when you have all of it, this physical to digital representation? I think you can do some really, really sweet modeling as far as, you know, what happens if I go back in time and make this decision instead of the other one. I don't think we're there yet as far as, like, gathering all the data and even being able to project enough. But I think it's kind of cool stuff. And also, going back in time, right, I bet most people in here maybe will blog or at least have something that they keep up to date online to react to events that are taking place in the world.  But even the fact that we found, like, one thing was really cool. Now that we have everybody blogging, you go back, you look at something like just the net activity on September 11th that really just captures something that is going to be super interesting to future generations, right? Like, we're just putting so much of what's going on in the real world into the digital world. And I think as long as we can keep it, which a lot of the kind of privacy people kind of poo poo on, but I think it's going to be there anyways because once it's out there, it's out there, if you can keep it, you can just go back and, you know, get a real good sense of, like, what was going on, how people felt about it. It's really cool stuff. So, yeah, so, you know, just wrapping it up a little bit, the forecasting targeting stuff is what you want to do when you get all this data pulled in providing you do it correctly. You can get a lot of benefit out of it. And I think, you know, a lot of people are anti-marketing, anti-advertising, but I actually don't mind it if it's actually targeted to me as something that I'm legitimately interested in. So, I don't mind kind of giving up some of the information in exchange for, like, better results. So, with that, I think I'm running out of time. We'll give this guy his alcohock, which he, you know, won Farron Square and give you the box with this handy little leather case. And then I think that's it. I'm going to end up in a Q&A room somewhere. So, thanks for your time.  Thanks.


Hello, welcome back everyone, live coverage here at VMware Explorer, 13th year with theCUBE here, formerly VMworld, theCUBE's been there since 2010 when Paul Morris was the CEO, I'm John Furrier, host of theCUBE, Dave Vellante, on the other side, my co-host Rob Streche, leading our CUBE research team, The Collective. Now, you can see a lot more research coming out of our team, theCUBE and the data, our data leg and our technology. And of course, we're more excited to have our friend on theCUBE, Sanjay Poonan, CEO of Cohesity, formerly VMware, formerly SAP. You are on in the early days, 2010 with theCUBE and great friend, great to see you. Always a pleasure. Super excited to have you on theCUBE. As you know, open invitation anytime in Palo Alto, you're busy running Cohesity and hot market. How's it going? John, it's been great and congratulations to you and Dave and Rob on your success. Yes, 2010, I was at SAP and the name was still theCUBE, but I remember having a thoughtful, deliberate conversation. And you know what we talked about? The SAP workloads like ERP and so on, running on this cloud platform called AWS. That was our first conversation because AWS was starting. And then I remember Andy Jassy doing a little video piece for us because we put our mobility platform. And then in 2011, I think you were at AWS re-invent and it was the first time Andy had any external guest at re-invent and I was his first guest. So it's been great and yeah, the great fun at Cohesity. We could talk about that. It's been a year since I took the role. We have really cementing our brand as the best platform of the next generation of these data security management companies winning a lot of high profile customers. And as you know, you kind of build one success at a time. Well, before we get to the Cohesity story, what's going on there? I want to just comment on what you just said because if you think about at that time in 2011, 2012, 2013, cloud was not obvious. But for entrepreneurs and folks in the tech inner circles, yeah, it was obvious. Something's happening big here. Not like the AI moment now, but like not as big. It was poo pooed by everybody.  No security in the cloud. I'm just talking to Raghu over there earlier. And he's like, oh yeah, I remember people were pissing on security all the time in the cloud and just how things can change so fast. And you've been involved in so many inflection points, Sanjeev. But I got to ask you because like, you've been on both sides of the conversation. Technology wave, business wave, bubble wave and managed through that effectively. What is your take on generative AI?  And you're in the cloud. This generative AI is a gift. Yes. What do you make of it? You've seen many waves. Yeah, I think it's exactly as you described. When in 2011, 2012, as I was at SAP, I think there was some denial of, how could this company called Amazon actually build a cloud? And of course the rest is history because what Andy Jassy has done and now Adam's continuing is nothing short of incredible. 85 billion dollar machine and Azure and Google have followed their footsteps in doing well too. We saw a continued wave since that time and prior in modernization of cybersecurity because threats especially ransom where we play very much in that wave. But I think generative AI, that third wave is going to be bigger than both of those. I think it'll be bigger than cloud and security because it's going to transform everything we do. It is the essence of being able to ask a computer to summarize the library of information and come back with something that's undisputable. So if you're writing essays and you wanted to summarize, I remember when we all wrote papers in college, we'd go back and pull out every book and even after the internet came back, we tried to scour everything. This summarization capability, the idea of summarizing a large amount of content which is the heart and soul of generative AI is so transformative of everything. And I've been playing around with chat, GPT and BARC. It's amazing what this capable can do and then finding the application of generative AI into enterprise software, like what we're doing now at Cohesity. We'll tell you a little bit what we're doing generative AI. I think this is going to be transformational. So I predict it's going to be bigger than what we've seen in cloud and cybersecurity. You asked me if I like to write before we came on camera and I'm like, you know, I don't really love it. But what AI does, and Dave Vellante quoted this problem we were on the super cloud event, he said it makes, because mainly the writing is the first use case for chat GPT, but AI makes a great person exceptional and a good person great. And so like I find that I'm a great note taker. I like to write, but I just don't like to script it up and put it into like, because I didn't get an English, I'm a computer science guy, right? So like, yeah, writing the perfect novels not on my bucket list item, but AI can help me. And so that's the use case for all aspects of foundational models. So cybersecurity. Okay, let's simulate an attack. Let's use AI to assist us. So you're seeing this augmentation, extension as the key value. How does that play in the tech app world? Because I can see the infrastructure, but the workloads are going to be AI workloads. What do they look like? That's the question everyone's asking. What does an AI look like? I think so that you're not AI washing, which is going to happen in any new areas.  I think I've encouraged CEOs of enterprise companies or bigger companies or small companies to really think through use cases that are very compelling. I think Satya Neda put it pretty well. We should think about general AI as a very good first draft summary of something. Okay, so if you're trying to say, summarize everything that Leo Tolstoy wrote and give it back to me, not war and peace, but in a half page, one page, it's going to do it better than anybody else. Or summarize all the works of Einstein and come back to me with a summary. So when you look at that summarization capability, about 12 months ago when this started to happen, I began to think that it had some application to Cohesity because in essence, you should think about a lot of the world's data protection backup data, secondary data, if it's on our platform, is sort of this tape that's very hard to search. So imagine trying to find that 1980s Michael Jackson song on a highly compressed data. That's what we've done. However, generative AI turns that on its head. Let me tell you how. I went up to Microsoft, spent some time with Satya Nader and as you know, I've been friends with them for many years and asked them, I have an idea here of how I think generative AI and open AI at that time could apply to Cohesity. What are your thoughts? In essence, if we have hundreds of petabytes or exabytes on our platform, highly compressed in our data, could we use open AI and generative AI to search that large backup of Cohesity data and come back with a summary to a customer of what they had stored in there for years? For example, let's say I'm a CISO of a bank and 10 years ago, there was a breach of my bank and the former CISO wrote up a whole bunch of documents about it, but it's in my backup. I want to use generative AI to search my entire backup and come back with a summary of what that CISO wrote. Beautiful use case. So here I am talking to something that's like, yeah, this is a use case in computer science called retrieval augmented generation, RAG. Go back and download all the computer science documents on that and implement it and you're on it. And I talked later to the AI team at Microsoft, later on to the AI team at Google. And in essence, that's what we've done. We've patented that idea because we think we're far ahead of everybody else's data protection and using RAG, retrieval augmented generation, to our industry. We're going to release it in the fall, we're super excited about it. And that application to us is going to be probably the biggest innovation Cohesity has worked out since Moet founded the company. It's remarkable. So that's how we've got to think. Now we're also doing some incredible things with AI and security. ransomware hunting, data entropy, detecting when you do a mass store, when you do more sort of surgical restores. All of those things are AI capabilities that we're building or building into the platform.  So there's a lot of AI already in it. But this generative AI capability to us, I think is going to be mind blowing in terms of where we could take the company. And I'd encourage every CEO to do the same thing. I was going to say, and I mean, you guys, I was at AWS when you did the deal with them and landing on S3 and being able to back up to when store in Amazon. And I think when you look at what you're doing through the partnerships that you've built, the data is everywhere. And so how are you looking at it for keeping that data, especially when somebody's like backups, I was also, I ran all of the backups and DR for John Hancock, MainLife Financial in North America long time ago, I used to get letters from the SEC like on a weekly basis. Hey, I need this person's email from with the words market timing in these emails. Okay, now I got a phone. E-discovery. Yeah, yeah. So e-discovery type stuff. How do you look at it, keeping the AI, not only the results, but the data actually separated? Are you doing different models for you or looking to do different models for each customer? Yeah, really good question. I think the first way to think about it is, I think what happened in the last 10 years, every one of the traditional backup companies that had not modernized through a hyper-converged scale-out architecture was sort of left behind in architectural no man's land. And that's what Moet founded. We were the first to take his ideas of Nutanix hyper-converged to the secondary data space. Everybody else since that copied architecture. So we were the first to, so we have the best product today in an architected, cloud-ready architecture for doing data management. Now, AI adds on top of that the ability to do things like search or ransomware detection and security and so on and so forth. But we believe it has to be done in a responsible way. So if you don't have access or authority to be able to ask that query about what happened 10 years ago, you won't be allowed to do it. And that's what we call responsible AI. So you govern it by role-based access controls. You govern it with the appropriate governances. You only are allowed to do it on your data that you're backed up, not the world's data. So I don't believe that we're gonna be worried about the meaning of life questions, right? I mean, Googles have to not answer like is the computer sentient. We're not asking, you're asking AI-based questions on your data you're backed up and you won't be able to ask those questions. We are not allowed to do it because of security controls around it, right? So we're trying to govern this with a lot of controls. But even then, you're probably gonna have to worry about things that people get wrong. What if this summary that comes back to me isn't accurate, right? So you're gonna have to link to the source documents you found it from. So if someone says, listen, I actually wanna make sure that the summary that you found is accurate. You link, here's the actual document I summarized it from. You can read the detail behind it. You'll have a bibliography of where it found these sources from. And I think as we get better, the model will get better and better at being able to summarize with accuracy. I asked chat GPT when it first came out, summarize for me everything Sanjay Poon has talked about analytics. You remember my first foray at SAP was analytics. And it was, I came back with stuff that was pretty, you know, all over the map. I refined the search and it was actually not so bad, the second or third. And I think that's what's gonna happen with Genevieve in the consumer world. We're gonna get more and more tighter about refining what that person has spoken on a particular topic. I would love to say, hey, summarize what John Furrier has written in his entire or spoken about Andy Jassy. Because you've been one of the best at being able to interview him through his years. And that summary. I got a lot of content on it. Yeah, I mean, if you could summarize it, that's a good starting point to somebody else who's saying, I'd like to understand everything that Andy Jassy's talked about with John Furrier. If you could ask our cube AI any question, what would you ask it about you? What does Sanjay Poon in? What's the most controversial thing Sanjay Poon has said on the cube that got him in trouble? I don't know. With his PR team afterwards. I don't know.  There's still time left in this. I know, we could go anywhere you want. I've always been reprimanded by my PR team.   See, it came up with a few things. It says accepting criticism is a thing you were big popular on making a decision during a layoff on someone. And then there was an interaction with D.R.A.S.H. Oh, let's talk about that. That's an actual response from our cube AI. D.R.A.S.H. and I finally, after all of that, we're actually, I mean, you know, I've not close friends with them, but I wouldn't consider anything. We were competitive. And when we finally met, we were at an advisory board. We're coming back on a flight. He said, let's take a picture and show to the whole world that there isn't this. And my view is in general, listen, we don't have to be competitively dismissive about all the companies. I think in my younger days, I probably did a lot of things, tweeted a lot of things that were stupid. And I'm willing to admit, like, whatever, seven, eight, 10 years older, I'm wiser about those things. I tell our people right now when we compete, to compete with integrity. I tell people among our competitors, they are good products, but now I'm going to tell you why I'm 10x better. But I don't have to dismiss them to talk about why I'm better. Anybody who throws fud out at companies and mud slings, they're not going to win long term. People know that you're a good competitor and you are actually in high integrity, so I can vouch for you there. I was just making the comment that we have our own language. We have 38,000 videos all with transcripts. We love it. And that's got a lot of charting in it. It's a treasure trove. So, you've got to be on it many times. So we think that's going to be augmenting our first. And isn't your son building the AI models now? No, he's pursuing the reputation. Oh, OK, got it. But I got some more four years inside the family that are doing all of this. I can take it everywhere. That's awesome. Really appreciate your time. I want to get a quick sound bite from you on your presence here at VMworld this year. And if you can comment on the state of the VMware ecosystem as it goes, this transition to Broadcom. Because the obvious trend is the bigger booths, a lot more bigger booths, and not a lot of mid-sized booths than a lot of little ones. It's almost like the mid-range of the ecosystem has been kind of hollowed out a little bit. So what's your presence here? I know you don't have to. Listen, I have a fantastic respect. Raghu came and spoke at our virtual conference. We did Catalyst virtual this time. I met for breakfast with Hawk Tan at a lot of respect, largely because Broadcom's big customer bars. They're one of our top customers. And Davidson, their CIO, they back up a lot of their workloads with us, so we're honored that they're top semiconductor company. So our view is that as VMware prepares for that, I think now it's a matter of when not, if it's likely to happen, they're getting all the approvals. I think that you're going to see, as he points out, there's going to be the public cloud players, and there's going to be the private cloud players. He's positioned very clearly that in the private cloud, VMware customers are in good hands. I believe that's going to be us. And our use case, as one of the top, we do VMs, databases, NAS files, and M365 better than anybody else. And our top workload is VMware. The largest customers who run on VMware back up and protect their data with us, we win them. Because our scale and speed are second to nobody, right? And then you add security like ransomware protection, threat hunting, cyber vaulting, we're ahead of people there. And now with AI, I think we'll take the next leap. So our mission, because we're much more an enterprise player, a lot of the other players are more mid-market in our competition. So our message to the top VMware customers is we're going to come here. We still think hopefully this conference continues going into next year. We will be of a presence here. We'll take care of our customers, whether it's on the show floor or on hotels nearby. I think coming back to Vegas is probably a good decision. I think there was sort of like, also Moscone, I think was kind of going through it's a little bit of, do you want to be there on that? A lot of crime there. Yeah, I mean, I didn't want to go there, but it's a tough situation. But I wish, I'm just saying, I only love for so many. I mean, I come here and I walk down the show floor. It's just so nice to see people whom I've known for many years, kind of taking pictures and selfies together again and high-fiving. So I feel like I'm forever part of the VMware family. And also the AI has given everyone a spirit of youth, youthful energy. I mean, Jensen was fantastic this morning, right? I mean, can I just say 30 seconds is the first time I met Jensen because in 2012, 2013 when I joined the company, we wanted to do a VDI integration with NVIDIA. And there were engineers at VMware who were not fully supportive. We got Jensen to come in 2013, I think it was a 2013 conference. He stood up on a table like this, guys, with his leather jacket, same leather jacket, he's wearing, okay? And just spoken, like 100 people gathered around him about the benefits of VDI passed through the GPU. And I was a Jensen convert from that point in time. You get hold court.  I consider him, and it's so great to see company when I tracked at the time, his 20 billion market gap. When it was 200, I said, you're gonna be 500. And now he's almost a trillion. I'm very happy for him and that NVIDIA VMware partnership. So, you know, they're also a customer. We're gonna do more with them. So excited about this time. It's great to see you. Good to see you too. In person. Last minute we have left, put a quick plug in for what's going on at Cohesity. What's new? Give us some staffs. Give it a little commercial out for Cohesity. Yeah, I think, listen, we talked about this. We're getting more and more public ready. The big step is getting cash will positive preparing for when you're public companies about profitable growth. I strengthened the executive team. I made some announcement of a new CFO who was at great experience taking companies public. And, you know, we're winning in the market. I've enterprise proposition. Our customer base is phenomenal. We had Salesforce talking publicly why they picked us over alternative. So I'm excited about these new customers coming in. The way we win is we're a multi-cloud story. Okay, VMware is one, but then you've got AWS Azure and others. We are the best at security and AI. Those are the three vectors. A multi-cloud data management story. The best at cybersecurity for protection against ransomware. And now generative AI opens it all up. Those are the three vectors. You'll see us as we talk more as a potentially public company one day. And I look forward to the continued dialogue with you guys. Yeah, we're looking forward to seeing more of you. Sanjeev, thank you for coming on theCUBE. Really appreciate it. Okay, live coverage here. VMware Explore 2023 of theCUBE's 13th year, covering this conference formerly VMworld. We'll be right back with more. I'm John Furrier. Rob Stretchy, live day one coverage. We'll be right back.


Looks like shorts to me. Hey look, I have dresses. You guys are hilarious. What do you do? Yeah, they're in here. Go put this on. Oh, not you, the other kid. We need the other kid now. Does that fit pretty good? Comfortable? Do you feel like you could ride into battle against a bunch of ogres wearing them? Yeah. Okay, it must be good.