Hello everyone and thank you for inviting me to present the National Academies about this work on hyperspectral virus detection in vineyards. I'm Luca Brilanti and I'm a professor in the Department of Agriculture and Technology at Fresno State. And the title of this talk is Empowering Autonomous Virus Detection in Vineyards, Hyperspectral Vision Systems, Preaching Science and Industrial Application. This talk will review the work of the Iberbid project. We'll go into the detail of the basics of hyperspectral imaging and then we will present application to virus detection in vineyards and I will summarize the main performance results. And I will conclude with a recapitulative and perspectives. The Iberbid project started operationally in 2020 and is currently ongoing. It's an acronym that stands for Iberbid Spectral Virus Detection in the vineyard. We ask operators from industrial standpoints we have a broken wine company and some super estate as of now and we are currently expanding to other partners. And as universities, the partners involved were Fresno State, which leads the project in association with Cornell University and particularly Dr. Mark Fuchs and the University of California Agricultural and Natural Resources with Dr. Monica Cooper. The founding came from the CDFA, the USDA, the California State University Agricultural Research Institute or CSUNRI and the F3 or Fresno Merced Future of Food Innovative Initiative. To summarize the basics of hyperspectral imaging, I will start by describing what remote sensing is. It's just the measurement of some property of an object by a recording device that is not in physical contact with the object. So if we take the electromagnetic radiation of the sun that impacts against a leaf of a grapevine, our case, that will be the amount of light incident on the leaves. A portion of that energy will be absorbed and used for photosynthesis. A portion of that will be reflected and the portion of that will be transmitted or passed through the leaf. Of course, we are currently working with the reflected portion and we are working with passive devices. That means that we use the energy of the sun as a source of energy. Why are we interested is because we know that diseases can affect the biochemical and biophysical properties of the plants changing their optical signatures. And so an LT leaf will have a different reflectance respected to an infected leaf. And these different schools actually be recorded in different regions of the electromagnetic spectrum through a camera sensor, which is what we have been using and what our spectral cameras are. Now, what are in particular hyperspectral cameras? If we consider any digital device for taking pictures as what we have on our phones, for example, we normally acquire information only into three specific bands, which are the red, green and blue or RGB color codes, which roughly corresponds to 16 million different combinations, unique different combinations of colors. So by combining just these three bands at different intensity from 0 to 255, the four innate bits, we can have a complete representation of all the nuances that we can see through our eyes. When we work with multispectral data, we expand the number of bands, not only to have three different color coding, but a larger amount, which is still into a limited amount. And also the chunk of lights, if you want, that are taken into consideration are fairly large. The difference is that we start also acquiring information into regions of the electromagnetic spectrum that we normally observe with our visible eyes, such as in the near infrared, for example. However, the reconstruction of the electromagnetic radiation remains discrete and it's somewhat incomplete. With hyperspectral data, the electromagnetic radiation instead is rebuilt in a quasi-continuous way because we acquire a very large hundreds of bands of very narrow chunk of lights and so at that point we can actually rebuild in a quasi-continuous way the electromagnetic radiation. Now if you look at the electromagnetic radiation into the electromagnetic reflectance of a grapevine leaf, we go in this case from on the x-axis we have different wavelengths, we go from 400 to 2500 nanometer on the y-axis we have the reflectance. In the visible area, which is actually the focus of this study together with the near infrared, we have the information related to chlorophyll functioning, particularly to leaf pigments, but in the near infrared we have information in the cell structure. In the short web infrared, we have information regarding water content, but also regarding leaf biochemicals such as cellulose, sugar, starch, protein, lignin and so on, particularly COH combinations. And so at the beginning of the HyperVid project we actually worked into the visible and near infrared roughly from 400 to 900 nanometer while now we are actually working into the short web infrared domain as well. The HyperVid project started with multiple steps. We worked first into control conditions in the laboratory. So we have a dark cabinet with a specific illumination and we work with the touched leaves. And in this section we mostly work with visible information. Then we brought the cameras into the field and we mounted that on a tripod. So we're working with still cameras and we acquired images of the full canopies. And then we work with dieralymaetry from ETH. The first part of the work has been complete and was published last year. The second part of the work is about to come out on computers and electronics in agriculture. And the third part of the work will be coming up hopefully toward the end of this year. So all three components of this work, they actually use the same structure. So we acquire data into the field. For each single vine that we acquire images from, we actually also sample leaves for the analysis of the virus through molecular diagnosis or PCR. And this is a very strong difference respect to similar works on the topic where we are not actually building a system based on visual observation, but we are actually building a system against molecular diagnosis. And we are also comparing the performance of the machine or the sensing system with the performance of an expert assessment. So the leaves go to the laboratory for PCR analysis, as I said, and the images they go to the lab for further processing through computational systems. For in the control condition, we have a data set of roughly 500 samples or PCR sends, tested and imaged in the dark cabinet. On the tripod conditions, we have roughly 700 samples. And on the drone, roughly 300. And then the machine learning model is built again on the spectral imagery in order to predict the results of the PCRs and then compare to classification, both on the images and in the field from a couple experts. In the dark conditions, we actually also attempted to differentiate between multiple different viruses. So we had in this data set, non-infected, red blotch, leaf roll, and co-infection of both leaf roll and red blotch. And it is very hard, you know, these images here are fairly, are the ones showing the, some of them are the ones, are some of the images showing the strongest symptoms, but otherwise they tend to be very mild. And actually we also sampled across multiple dates. Therefore the symptoms are at the variable levels of expression. The expert accuracy with this data set is roughly 50%, while a deep learning system based on convolutional neural networks actually achieves an 87% when the symptoms are visible and 86% when the symptoms are not visible. The distinction of red blotch with leaf roll sees that most of the samples are predicted as leaf roll, also because leaf roll was more abundant in this data set with respect to red blotch, but also because red blotch has the tendency to have milder symptoms and so it's actually harder to predict. And the co-infection has the lower accuracy. If we look instead at the spectra into the visible and near-infrared from 500 to 900 nanometer, we see that here in the green line we have the average reflectance of the not-infected samples. On the red we have the average of the infected sample and the ribbons are the standard deviations. You can see that the samples and these are data on the tripod. The samples are very similar or very close to one another. There is not a very strong difference. So there are nuances that needs to be analysed. And in particularly in the green domain we have a large amount of reflected light from the not-infected samples and the infected samples instead reflect more in the red domain and into the red edge. So this is actually consistent with the visual symptoms where we normally see the canopy approximately becoming more red. Even in this case we actually acquire data over multiple dates and so at different levels of expressions. And so we have the ability to differentiate no visible symptoms with 75% accuracy through a PLSDA model that can only use 5 bands of 16 nanometer width while the expert on the RGB images only achieve 54% accuracy which is normal because at this point we don't see the symptoms yet. When we compare the symptoms after variation in multiple dates not only at harvest when the symptoms are more expressed but in multiple dates we have an accuracy of 76.6% with an SVM model that use 18 bands also a 16 nanometer width. And we have compared, I don't go into the details here but besides comparing multiple machine learning models we also have compared multiple dimensionality reduction algorithms different ways to reduce the noise and bump up the signal and so the 16 nanometer actually seems to be the ones that on our multiple essays has given the largest performances. The expert with RGB images is a 78.6% and the expert in the field is a 75.3%. And so as you can see the machine learning models of course outperforms the expert before the expression of the symptoms and is comparable to the expert performances after symptom expression. We also realized as we were acquiring multiple data in multiple time from before the symptom expression during the symptomatic expression of the symptoms on multiple steps until harvest that when the symptoms are not visible we actually have a larger amount of difference into the near infrared while in when the symptoms are visible then the difference into the near infrared attenuates and we have a larger difference into the red area and the red edge. And so this is also particularly important to understand if you want to develop systems that can be used over a longer and extended period of time so therefore more operationally capable in production that we probably need to focus on different areas of the spectrum depending on the time of the season. We attempted a multiclass classification in this case where we had three classes instead of only having infected and not infected we had non-infected, visibly infected and non-visibly infected. Those are the ones that the expert classify are not infected from a visual standpoint but they come out positive at the PCR results. And so overall here the accuracy is roughly 71% we have higher accuracy into the classification of the visibly and non-visibly infected categories because of the ability of working on different regions of the spectrum or giving the machine learning model the ability to differentiate these two classes and utilize different regions of electromagnetic radiation. Now finally the results on the drones we roughly have 264 bind sampled 122 were non-infected 142 were infected with red blotch so these are spectrometry from a drone and up with a pixel accuracy of roughly 7mm and very balanced data set. In this case we acquire a limited number of bands only 40 this is a limitation of the hyperspectral camera that we use for this purpose then we clean up the spectra and we interpolate over a larger amount of wavelengths and we utilize a smoothing filter compare different machine learning algorithms in this case the image was only performed one time at harvest the time of maximum symptomatic expression and here we go back to have the maximum performance that we observed into control conditions because we do not confuse the model with milder symptomatic expression but we only go there one time when the symptoms when the leaves are red when the symptoms are the most expressed and if we compare the accuracy with the expert the expert data roughly at 3.6% accuracy on this data set and so overall we have comparable or superior accuracy but if you look at the confusion matrices here we see that on the left we have the expert performances on the right we have the machine learning performance we see that we have slightly higher false positive with the model roughly 10% respect to the expert that does 8% or whether we have a very strong lower false negative with the model 17% respect to the expert 24% which makes the overall higher accuracy of the system respect to expert assessment if you look at the importance of the different bands we see that the green, the red, the red edge and the near infrared the most important accuracy which opens up also to think that it's possible to have very simplified sensors if we only use if we only if we go at the right time during the season we also applied an inversion of a radiative transfer model or the prospect model in order to estimate what their perspective images really see and so we can see that we have an estimation of the chlorophyll concentration and so the not infected vines have a higher amount of chlorophyll respect to the infected as well as higher amount of carotenoids so the overall the photosynthetic apparatus is in better shape respect to the infected vines of course what we have is that we have a higher amount of anthocyanins into the infected or red color compounds respect to the not infected ones now if I summarize the different performances in control conditions in all models we always have higher or similar accuracy respect to expert assessment when we compare the hyperspectral sensing with expert visual assessment to molecular testing the machine learning model will reach an accuracy of 87% in control condition and similar accuracy is from the drone at harvest the time of a higher symptomatic expression it's harder to have a higher accuracy so high accuracy when we actually focus in the vineyard on the time of variable expression of the symptoms and so if we expand the sensing campaign from a previous reason or at the onset of the reason all the way to harvest and it's important that we try to simplify the hyperspectral sensing in order to build an operational tool based on a limited number of bands that you overscaled directly use upcoming complication will further expand on the results that they presented that will come out this year and what are we actually working on thanks to the latest grant from the California Department of Food and Agriculture Pierce disease glass-winged sharpshooter board we are working on developing systems for presymptomatic binds and white varieties particularly white varieties are an important target for us at the moment because there have been no work at all on these varieties and it's very hard to assess visually the infection we are also working with the full range handled spectroradiometer in order to understand which region of the electromagnetic radiation is actually the most sensitive to the virus infection and we're combining that with the chemical analysis of leaf metabolites also to try to understand the fundamental of the spectral signature and we are trying to go more and more toward an operational tool and so we are expanding our capability to varieties that we have not currently worked on and new vineyards in order to see what possible confounding factors needs to be accounted for in order to allow the growers to use this kind of sensing for their assessment needs thank you to all the people that have worked over the years on this project particular to the Torla Roche Pinel which is leading the work in the lab but also all the students that have collected or analyzed or managed the data information to all the cooperators over the years and if you want to know more about what we are doing you can connect through this QR code thank you for your attention I look forward to your question


The project is a database of about 900 slaves from Fairfield from its inception in 1639 to about 1848 when Connecticut officially abolished slavery. You think of all of the instances and examples of southern slavery that you learned but it was still a really prominent business in the north as much as it was in the south. On the town's website it says there are about 260 slaves during the Revolutionary War period. Over the course of our research Alec and I have found 900 individuals in this same time period living in Fairfield alone. We have found that there are families whose ancestors were slaves have stayed around in the Fairfield Westport and like bridgeport areas. This information could potentially be really helpful to them if they're interested in learning about their ancestry. This research has been a culmination of about 30 years worth of work. Dr. Rosavik started it way back in the early 1990s presenting his first paper at the Historical Society on this topic in 1992. We've been working on the project for about two and a half years when Dr. Rosavik passed away last April. It was his legacy and finishing it through was really important to us and we've gotten a lot of really great support from both the university and the historical society. We have kind of like the jumping off point for a lot of other great research that can come in the future whether it be through the university or at the historical society or just somebody who's interested in the topic.


Should we plan on meeting at the front around one time? 330, okay. 330? Okay. It's all I have. I have a 30, so I'm guessing it doesn't. Yeah, say 334, I'll text you or... Sorry, I'm cardless, but I'm 35, but that sounds good. I was looking out, I've gone off the card. Should be okay. Hopefully we'll miss rush hour coming out. Are you basically in China? What we're gonna do is we're gonna have another card that's gonna take us away to the city. Okay. She would do the wrap around. Got it. So, I'll set the logistics. I'll set the logistics. It's an interesting low... So you guys aren't driving? Yeah, yeah, yeah. There's a car. Oh, okay. It's a van. Oh, okay. Well, I thought you were literally behind the wheel drive. What's the feel of the inside? From the inside, the kind of thing you're worried about. Do you ever drive when you're in China? I do, in Shanghai. In Shanghai's a little better. Yeah. Yeah. It's just like driving to work. I visited Shanghai last year for the first time. There's a great Vietnamese restaurant in the French Quarter. Often? Yeah, I don't know if you've ever tried it, but they fly and push for this every day. I forget the name of it, but there's only one in that. What's the name of it? Is it one of the fancy ones? What's the fancy one? It's got a little patio courtyard area. And it's fairly authentic Vietnamese cuisine. I'm trying to remember if there were some fusion dishes. Yeah. But there's only one in that area there. It's good. You should try it. Do you remember the name? Yeah. Yeah. I don't know if you make it down in that area, or is it so touristy that you just try to stay away? It's a very residential area. There's a bunch of nice restaurants in the area. What do you think about the interesting, internal apartments? So you're over there a lot? Yeah. It's a fairly big area. That's not controversial. It's all down there. How much slower and how long before? Yeah. Yeah. My office is right on the east side of the French concessionaire. Okay. Yeah. Yeah. There's always a new restaurant, so I'm always interested. Yeah. Well, every time I go, I make it a point to have the soup dumplings.  Is that right? Oh, I hope that one, I hope that one didn't. It sounds like, you know, okay, thank you. It was just last year, and, you know, and the restaurant owner, this woman is just sweetheart.  I think I gave that. Having just as good a time as all the tourists are. It was interesting one day. Yeah. It was interesting. Yeah. After the game, right? Yeah. We had a discussion about the, the risk of Chinese economy. Sorry, I can't remember. Yeah. What's your take on Chinese economy right now? I've been advocating about it. They should give up this target or this tournament mentality. And it's getting perverse now. It is the, it's the premier who used to say, we shouldn't have this hard right now. It's the premier for himself. Who's now very stick to it. We're speaking to the system. Exactly. Exactly. Get the hold of it. Exactly, yeah. Once you're sitting in that post, then you're thinking from that post perspective now that what is right of the country. The economy. Yeah. Yeah, exactly. Or trying to massage that. Yes. I love that. I will send you an email and don't get set up. I will be out of the country for three weeks. But I'll be back in early October. We'll talk to it. Hi, Rebecca. I'm Jim. Hi. Hi, Ron. Nice to meet you. Hi, thank you. Nice to meet you. Good day, everyone. My name is Rebecca Blumestine. I'm the deputy editor and chief of the Wall Street Journal and I first of all want to apologize for being late. I don't know if any of you have been caught in TNG and traffic, but I had an appointment outside the center and my apologies. Thanks very much for being here. We have a great panel here. And one thing we really want to do, according to the title of this panel, is to debate whether or not we're in a dot-com bubble. And I'm going to start out by taking a survey of all of you before I introduce our panelists and see what you think. And what I'd like to do is also take a survey at the end and see if any of the opinions here have changed your mind. So could I get a show of hands? How many of you do think walking into this panel that we're in the middle of a bubble? Could I just see a show of hands? Okay, a few hands. So how many don't think we're in the middle of a bubble? Okay, so I'd say that that carries the room at this point. Well, with that, let me introduce our panelists. To my left is Ron Cao, who's founder and managing director of Lightspeed China and has been investing in companies across the tech sector in China for some time. Juning is deputy director of finance at the Shanghai Advanced Institute for Finance. And as we get started here, Ju, I'd love you to get us going with the definition of what a bubble actually is since you're the sitting economist in the room. We're very honored to have Max Levchin here. He's the co-founder of PayPal and Yelp, two rather small internet successes, and is now working in San Francisco-based innovation lab HVP and in the belly of the beast, I'd say. So I'm very interested in getting your view of what's happening. And finally, Jim Yagin, who's co-founder and executive of Truecar USA, which had an IPO just in May, raised $70 million. And even on the day of your IPO, had some interesting comments about whether or not we're in a bubble. So, Ju, I'd love you to get us started. What is a bubble? And what are we talking about here in terms of tech?  That is only after the bubble burst we would be able to know whether we were in the bubble or not. So I've been working with Professor Bob Schiller, who was the Nobel laureate last year at Yale on bubble-related research. And it's just amazing to see how people's disbelief in their living in a bubble can make the bubble become even bigger. I'll give you one example. 400 years ago, back in the Netherlands, one tip of Tilly Bob combined 20 townhouses in the center of Amsterdam. So that is how crazy the bubble could have gone. And now I want to come back to this particular time period. Well, I think by going through the 1998 to 2000 internet bubble, I think the investors, the companies and the regulators have all learned quite a bit about what is a bubble back then. So I think those knowledge has been really helpful in preventing or at least attenuating the extent of having another bubble. And I want to just put two things into perspective. One is from a valuation perspective. Yes, we are looking at some richer valuations than historical average, but it's not as far as to choose standard deviation, which is a little bit too aghast, but it's not too far away from the historical average. So I think we are looking at richer valuations than average, but not that bad. And another perspective is, if you look at the motivation behind this higher valuation, I think that's closely related to the reflow of capital from emerging markets back into the U.S. And in this bigger context and in the context of very low interest rate in the U.S. right now, there's really not any better investment vehicles in the U.S. So in some way, I want to draw the analogy between the internet sector in the U.S. and the real estate sector in China.  Whereas the Chinese real estate sector is probably beyond what most people could imagine. So I'll put this stuff here. So in coming days, we're going to see the IPO of Alibaba, which may be one of the biggest, or the biggest IPO ever in the world. So far this year, I believe in the U.S., there's been a $47 billion raised in IPOs. And we're getting back to 2000 in terms of this level of activity. Ron, do you, from your perch, are you getting worried about what's happening in China, particularly with the Alibaba frenzy? Well, I'm sure this is nil. I mean, the, you know, I was studying this topic and I actually saw the chart right before you showed up there, it showed the number of IPOs from 1997 to 2011. And, you know, in 2000, 99, it was a long time ago. And I think we forgot how big of a party that was, how great of a party that was. You know, there were 300 IPOs in 99, 2000. And I think last year we had, I think less than 100, I think it's about 80 or so, sorry, 30 or so, I saw this data, 30 or so venture-backed tech IPOs. I mean, that's, it's a one-tenth of the number. And we also looked at numbers internally from just, you know, looking at valuation numbers. The, you know, the number of IPOs that, in addition to the number of IPOs, the number of IPOs that had doubling the first day of trading in 99 was about like 100. One third of the IPOs doubled the first day of trading. And, you know, those phenomenon is not, you're not seeing that today. Certainly there are exceptions. Alibaba, I think, you know, it's a company that's been around for so long. It's a great IPOs. It's going to be pretty valued. But on par, I would say we're still, you know, we're going to perhaps a bubble situation, but I think right now we're fairly rational in general. Max, from your perch, what's your opinion? So I think it's just way too easy to oversimplify the whole thing. And I'm opposed to our simplification on the principle basis.  One is important to remember that the stock market is just a proxy for value. It's not actually a true representation of value being created by entrepreneurs. Alibaba is one of the greatest companies ever established, controls 80% of e-commerce in China, has after, seems like a forever existence, something like 46% growth year and year in the last quarter alone. It's, you know, whatever price it fetches, that's what the market thinks how valuable it is, but it is uniquely valuable. So a whole bunch of companies like Alibaba, public and private in the US and worldwide today, and the world has flattened in a sense that there's plenty of these companies outside of the US, but the typical recipient of barbs on the valuation side of things is Uber. And if you think about Uber rationally, it's very easy to see that given their success today and the lock in the network effects, the fact that they have a global and local network effect, all of it together combines into essentially a potential market cap, there I go using market analogies of course, it's a totally addressable market that's roughly Hertz times FedEx. So this could be an enormous, enormous success much in a vein of Alibaba. So those companies deserve the rich valuations and calling them a bubble is insulting to them and to the people that built them. Having said that there's a ton of little companies still working on things that are entirely pedestrian and worthless and will die. And if anything compared to 2000, it's much better because they will never go public. There's plenty of good ones to take public. So the little ones still get aqua hired and there's no better place to put an entrepreneur these days than into a director role in one of these companies that's a rocket ship. So as far as I'm concerned, things are generally pretty rational. Jim, you've actually lived through an IPO. What's your sense of the bubble? Well, it's interesting just four months ago next week would be our four month anniversary of being a public company and the public markets were extremely choppy. Then I remember reading headlines on whether two cars IPO would be a bellwether we were in a bull or a bear market and we priced under guidance and we came out with a market cap of just over 700 million and today we're 1.6 billion. So we've done extremely well in the four months but to Max's point, I don't know that's an indicator of the value that we've been. What's the true value? Right. Given your name, you should be pricing yourself to what your worth. That's right. And so where we think our value is how we address the market that we're addressing and the value that we deliver. We've saved consumers over three and a half billion dollars off the sticker price of a car that's a million and a half consumers and on the other end we've saved automotive retailers over 350 million and have created market efficiency in their marketing spending, customer acquisition costs and I think over time and that's with just over 1% market share. So we have a long ways to go and over time if we can continue delivering that kind of value then hopefully the market will continue to see and it'll translate into our stock price. There's certainly a role of big companies in all this. I know that earlier this year Facebook and the WhatsApp purchase I think is something that set this debated off into an entirely new level. It was valued at 19 billion dollars and we continue to see as Max you just said the dynamic of big companies swallowing up smaller companies. Are you seeing this in China as well with Alibaba and Tencent, this phenomena and do you worry about that? The big companies kind of bulking up as quickly as they can to fend off each other. Well as an early stage investor we actually like that. You like that. So like Max says that not everybody's gonna go public not every company's gonna become great but they have a certain value, a certain period of time. The fact that the giants in China are very competitive right now fighting over turf with commerce and social and eyeballs and traffic. It creates a lot of opportunities for startups. I think this is in terms of venture in China been doing this for about 10 years. This is probably the best time in terms of creating new ideas. Not just one is because the exit market is more healthy. You don't need to just go public or that's not the only route. There's other routes to create exits for companies but also we're probably going to a little bit more at this panel hopefully. Things like mobile, things like peer-to-peer, sharing economy, some of the enterprise technologies are these areas are quite exciting right now. Junior Max, do you have any sense of the big companies threatening to really ruin this for everybody else with such high valuations? I don't think so. I think it's not as though on any given day there are billions and billions of dollars being spent on these acquisitions. Every time something like this happens it's typically reporting where the event, the WhatsApp deal was heavily debated and it's still heavily debated and I don't think Facebook has another five of those tucked away ready to happen. The probably biggest danger of these incredible valuations we see in the public markets is the currency they wind up having not so much in the acquisition scenario but in the scenario of compensating workers. So startups are in Silicon Valley which is why China has such an enormous advantage just being larger have the terrible time of hiring in part because every 21 year old college graduate says well I have a $2 million effective currency offer from Google and $95,000 plus 3% of a company that probably will get acquired by Google anyway. This one seems faster. I just want to make one quick comment. I think for large companies such as Yahoo, such as Time Warner, such as AT&T and Microsoft if we were in the bubble they're making just as dumb decisions as anybody else is. So I mean they have made really crazy acquisitions during the peak of the last internet bubble so there's really not too much peace of mind to have if it is an offer from a large company. I think they sometimes are actually sprouting the party because they're driving like Max said and they're driving the competition even higher for the valuation and for the compensation to the key employees. I think this is true so long as you mean in terms of the high upper echelons of the acquisitions, at the small scale the half a million dollar, a million dollar aqua hard type acquisitions are actually seem to work pretty well. There's no pretense about what's going on just getting engineers paying $100,000, $200,000 signing bonus to their investors which is a strange dynamic but you appreciate it. The thing that I completely agree with is every time you look at the fill in the blank Microsoft buying whatever it is at the most recent ridiculous like you know it will not work out. You know they cannot absorb the company because the desires to take over the synergies seem to really capitalize on that and the only kind of thing that works is you buy and you let it be sort of Google YouTube being the classic success story. Jim have you thought of, you've obviously opted to go alone and that's your strategy but you know Ford comes along or GM, has that been something as you look at possibilities here? There would be very unlikely suitors but we certainly had the big companies come knocking pre IPO. It was quite a frenzy but it did, I think as one of the co-founders and as an entrepreneur it forced us to really sort of go through a self-examination process about what we're trying to do and why we started the business in the first place and how that would change if we didn't go it alone and stay the course. And there's certainly when you're a public company there's always the pressure of the public markets and are you able to withstand that pressure? Are you able to ignore the volatility in the stock price? We never looked at the stock price when we were a private company and we never base our decision on the day-to-day fluctuation in the stock price. Our stock price has grown nearly 136% in four months but it wasn't a linear trajectory. I mean, just this week we had 15% volatility in the stock price and making short-term decisions that compromises the long-term sustainable value in the business and why we started this business is a challenging thing and a trade-off certainly as a public company. So I'll share one more thing. I think relative to China, I think in sort of a follow-up here, you're seeing more of these deals being structured in China where the giants are taking a significant piece of ownership. They won't buy 100%, they'll buy 50%, 51%, 60% in some cases. Trinar is a perfect example of buy-to-buy controlling interest but let the management run with it, make decisions, retain their talent and go for the venture IPO and still be somewhat independent. We just sold a company to Qi Hu in the same similar structure over multi-hundred million dollar acquisition, controlling interest, management team still, it has some cash out but hey, there's still more to do. So I think that we haven't seen as many of those deals in the US. Maybe that's a China phenomenon because talent is even harder, I think even harder to hire in China or retain for that matter. So that's something that's worked out pretty well. I wanna talk for a moment about value creation and Max, to your point earlier, setting aside the stock market, what are you looking at in terms of value creation? Are we talking about jobs? Could we be simply looking at a significant shift that technology is playing around the world across industries, across the way people live? Could we be in many respects seeing the promise finally of what was talked about in the dot-com era? How do you think about value beyond the short-term Wall Street outlook? So in that sense, I think if you define bubble, not economically but sort of humanely as in, is there really a proportionate level of elevation from poverty, improvement of human condition, et cetera, compared to the nominal growth as exhibited by stock markets, no matter what you think of the valuation and the dollar exchange ratio, we are certainly solving harder, more important problems today than we did 10 years ago. 10 years ago, the internet was all about, not all about, but half of it was about something that remained and the other half fizzled. Today, number of companies that I look at that are curing cancers and figuring out how to mine planets for precious metals is way more. Those are not outliers. Those are kind of the sort of things that I like to look at and invest in and help create. So to me, the assessment of how we're doing as an industry is first and foremost around number of human lives that are being changed for the better worldwide. Because of the developing economies participating so much more aggressively, it's actually easier. There's this internal notion of elevating 10 million people out of poverty in China every year, things like that. It's easier to do today, frankly, because technology is reaching us and 10 years ago, starting a farming technology startup in the US was a joke, starting a farming technology startup in China, which just wasn't talked about, but today, we're looking at a half dozen farming agriculture technology startups in the US and it's gonna be 10 times more important in China where urbanization is a huge problem and the food supply, food safety is just continuously a strain. So in that sense, couldn't be more excited about where we are. I mean, value's being created very, very rapidly. I wish there was more investment in those categories, independently you think of the availability of the investment dollars. And you see investment dollars going into more of those social good companies beyond the traditional tech ones. I do. Is the interest to classify them as social good because that almost puts them into this bucket of like, well, those things that aren't really gonna make money, but they're important anyway, I disagree. I think those are fundamentally gonna make a ton of money and they are touching things that are traditionally thought of low margin industries, but a very, very small fraction of a penny and something that's a couple of trillion dollars such as energy is a pretty good amount of potential impactful revenue. So it does appear to be that most venture capitalists are starting to think beyond the standard four year cycle, which is where a lot of this actually came from in Silicon Valley, certainly. One nice side benefit to it is that most bubbles, the ebb and flow goes through at most a decade, typically four to five years at least in my sort of internet memory. If you invested something that's supposed to live for a hundred years or at least 20 years, you're gonna live through a couple of bubbles and you're just gonna condition yourself to not care what your stock is doing. If you're going 15% week and week, whatever, you have another couple of million weeks to think about as a lifespan of your company, that's not an important event. Juneen, should we be looking at value differently than just numbers? Absolutely, I think it meant, well, I think Warren Buffett said something during the last internet bubble, he's saying, well, I'm not going to buy anything I can not understand from an evaluation perspective. So I think valuation is really important because valuation reflects the balance between risk and returns when it comes down to investments. But I want to first add up to Max comments, I think I was in the university leaders forum yesterday and we were talking about how technology has transformed from the education's impact in health, wealth, impact and knowledge. There's so much that has going on due to the contribution of technology innovation. So that's really changing how people live their lives and how we communicate and how we are educated. So I think it's really being underappreciated just from a pure dollar or from a stock price perspective. And related to that, I think, well, what's wrong with a bubble? I think if it's simply a rise and decrease in the share prices, then it's really not a big deal. I think the really true implication or the consequence of a bubble is the misallocation or the prolonged misallocation of resources and risks in this society. I think as long as that is not happening, that people with very good training in other fields are giving up their day jobs and then just trying to become day traders of internet stocks. I think as long as that is not happening, I think that is still within the reasonable range. But if everyone, as it is the case in China right now, everyone is trying to build their biggest chunk of wealth through real estate investment. And that's probably having a worse consequence on the entire society than the internet bubble. Ron, valuation in China. Obviously there are a lot of issues here as Vax was saying that technology can help address and is addressing. Yeah, I mean, we focus on early stage. The valuation fluctuation there is typically not that large over years. I think maybe 2009 was five, six million pre. Now it's maybe 10 million pre. So, but at the serious C and D level, I think that's where you can see there's a huge valuation increase. I think we're, I don't have the numbers, but I suspect a series of C or D are averaging in the 100 to 300 million range. Then if you're investing that round, then you're saying this is gonna be a $2 billion company, right? And we know that's not gonna happen for a lot of those companies. So, and there are fairly aggressive investors that are doing convertible debt. I don't wanna set a valuation. I don't know if it's 200 or 300, but I'll give you money. I'll convert later. In some ways you're protecting principle, but in some ways that's a sign of aggressive pricing to get into the deal. But I think I do echo the things that are being funded are fundamentally different. In China, we're focused more on consumer economy investments. So, my, our nanny just got an iPhone. I mean, that's one month of salary. She's on wage change. She's buying things, I'm sure. So we, and that's very interesting. We are, we're investments in investments in, for example, we did an investment in a company that does, it's a mobile platform to allow you to find a temporary driver. It's called Yi Dai Jia. So if you had a couple drinks and you go out and you can't drive home and drinking driver laws are very strict in China, you open this app and you can find 20 drivers nearby that's willing to work. And what's happening is that these drivers before this app, they would, they're probably a taxi driver or they're just a factory worker. They're not making a lot of money. And we interview a lot of these drivers. They're increasing their salary by twice the amount by working extra 10 hours a week at night time. So this is an example of how technology is helping lives in a direct sense. I just want to add very quickly to Ron's comments. But there is, I think there's a great deal of investment opportunities in that area, but then there's also an additional layer of risk which is the regulation. Absolutely. And for that reason, I didn't talk about Uber because that's more sensitive and here is more about labor and directly applying that. Jim, you have a very different landscape in the US. A crowded one, perhaps. How do you look at value and what your company and other tech companies can bring? Well, a lot of what we do is addressing a lot of inefficiencies in the automotive retail process. I mean, an interesting stat. When you look at the number of new car franchises in the US, it outnumbers the number of Starbucks, Dunkin Donuts and Coffee Bean combined, right? It outnumbers the number of McDonald's, Burger King and Wendy's restaurants combined. It's just a staggering number of dealerships for a purchase that happens once every four or five years and the process that consumers go through and the investments that dealers and manufacturers make, there's still much inefficiency and so what we do in terms of the value creation is saving time and money and time is money and so when we can do those things then hopefully the reallocation of the time and the resource translates into value somewhere else. You mentioned the R word regulation. We're seeing the Facebook acquisition being reviewed in Europe. Obviously there's different countries with different laws where Uber may not be as successful in some places though I might add, I believe the company is facing some of its biggest challenges in Miami. Is regulation something that investors are perhaps underestimating when they bid up these shares and have as much confidence than they do in tech? It's a tough question because it's China, it's a lot of things are moving in progress. Even in the Western world, the technology oftentimes are ahead of regulation. For example, the whole digital asset class, that is something that's got regulators trying to figure out how to deal with that. Certainly the sharing economy where we've made a lot of bets with the Airbnb model, I talked about the E-dive job model. We also invested in a PDP car rental company. If you can rent your house out to someone else, can you rent your car out to someone else? It seems like it could work, so we're experimenting with that. Certainly all those things are touching on regulation. It's unprecedented what happens, something happens. Who's responsible for and is it the platform? Is it the other person? So I think these are things that needs to be worked through. In general, we make an assessment on that risk and there are certain areas you don't wanna be touching. I think if it's sort of areas where it's just not clear and we wanna work it through, we're willing to take that risk in many ways. Juning, are you seeing regulation keeping up here in China and elsewhere or is this gonna continue to be an issue? Well, I personally do not think that is such a huge issue for entrepreneurs and I think going back to Max comments, if you're really keen with one key technology or one business model then it's just a matter of whether you're willing to live long enough to see the eventual success. But I think it is a bigger issue to investors like Ron or, I think if you were looking at there's a timeline for your exit then there's really considerable amount of risk you would have to evaluate. Especially I think in emerging markets including China because the environment is so dynamic and there are so many other factors that could marginally touch upon your particular investment. So I think it is definitely far more important factors to consider than it is in the US or in Europe. I wanna open it up for questions in just one moment but Jim on the topic of regulation, part of the intrinsic nature of what you're doing is budding against franchise laws and some decades old regulations in the US and did you talk about that? Sure, I mean it's remarkable how regulated automotive retail is in the US. The concept of auto e-commerce in the US probably won't happen in our lifetime just because of the franchise laws. One of our investors Elon Musk has his own challenges trying to retail Tesla and in the state of Texas alone he can't sell a Tesla. And so it's a remarkable challenge and we as a company had a near death experience in 2012 purely because of the regulatory environment and whether we were violating advertising laws and our websites and our mobile complied with font size laws, right? And that were there to protect the auto industry and consumers around the print in a classified ad. There's regulatory protections for the franchise system that you mentioned that outlaws brokering in some states and if you get paid in the connection with the sale of a car, which we do, you might be viewed as a broker but how someone pays for a service being rendered doesn't necessarily mean they're a broker. We don't set the price of the vehicle. We don't take possession of the vehicle. We don't take possession of the consumer's money but the laws are written so broadly it can be defined however the incumbent system wants to define it, right? And so we had some real challenges. And Max, before we open it up, I mean PayPal you must have been thinking a lot about banking and the way we finance and running intrinsically into a lot of laws and regulations. How do you frame that in your mind? So actually you regulation as a competitive advantage. So I think one of the things you learn as an entrepreneur having gone and succeeded in a heavily regulated market, you realize that it's a tax you pay and it's a little bit of a seemingly insurmountable amount from the outside looking in but once you've been there you realize it's irrational but it's not insane. There's a lot of regulatory pieces that just really don't make sense but they were there 100 years ago and they're still kind of there waiting for their time in a spotlight in the Senate in the US and the equivalent bodies worldwide. As an entrepreneur if you choose to go into that industry it's always by definition huge and very hard to disrupt and has enormous amount of inefficiency.  So healthcare, energy, education, finance, insurance, any one of those markets are the last laggards in the world of really being reinvented using software. Every one of those things is a trillion dollar opportunity worldwide. So as far as I'm concerned grow a spine and then go for it. I'd like to open it up for questions. I don't know if Fad is in the house. Fad what are your thoughts about the bubble and have any of the opinions up here changed your mind? For these folks because one of the things that really stick in my mind is what are the hidden dangers for a company go public during times of high valuation? I think he's the best qualified person to answer that. At a time well I would say that we were probably undervalued when we weren't out and so I don't know that that was an issue for us being overvalued but from a employee standpoint that Max brought up when you're overvalued as a company if the market say there's a bubble that corrects itself then you have some real employee morale issues. That's just a simple fact of recruiting, retaining and trying to build an environment where employees, you're trying to build a culture around passion of solving a problem but at the same time that they wanna see the rewards and when they see that evaporate because of the bubble then it becomes incredibly challenging for you to manage the business. I think in times of being public independent of what the market is like the employee productivity drops good 15 to 20% of times simply wasted reloading the page on NASDAQ or NYSE. I think the, at PayPal when we went public I one of my jobs was running security for the company just for local security and one interesting thing that occurred is we saw an entirely new traffic pattern emerge when every one of our employees downloaded the Java applet that would connect to a level two quotes on NASDAQ and look at the trades not at the price but at what contracts were being traded for our stock all of this happened within 24 hours of going public even though every single person was locked up for six months. So none of these people traded they were all just looking. So productivity goes quite down. And I just want to add briefly I think it also gives both the management and the ordinary folks this sense of complacency and we're reaching this milestone and then we can finally take a breather and relax for at least some time but then if you're going on the round track because you are so well funded then you might be just taking a slack and going on to the round track so that combination cannot be very good to the company. Ron what have you seen here in China? Well I mean certainly if you have options in terms of when you go public that's the luxury right you can but certainly a market when it's good it's you know you have more flexibility in going public then but you know but I think if you look at companies that have been around for a while it didn't really matter when they put one public didn't really matter right it's sort of Audibaba took many years go public that could have gone many times earlier so it's really it's a complex question but market conditions is probably just one of the few factors. Are there any other questions? Yes. Hi just a thought in terms of the question you asked about is there a difference between 2000 and what you're seeing now? I think there's a huge difference. Just my perception 2000 was a lot about novelty and not really showing how you could actually create value it was just more about can you throw cool stuff up on the screen and have lots and lots of folks look at it whereas if you look at the companies we're talking about now they're fundamentally creating value through process efficiency. I mean the question of does technology create more jobs I think is a misguided question. If you got rid of all technology we'd have 100% employment because we'd all be running around gathering grass and killing rabbits for dinner. That's not the point. The point is that for Truecar he's saving someone from having to go to seven or eight different dealers to find something that's a possible experience. In the case of Yelp he's saving someone from having to call up five or six friends have you been there? What was the restaurant like and so on and so on. What we choose to do with that extra time both societally and personally is really what the issue is. I mean the environment is going to continue to change and there's a societal imperative to reinvest in our society but it's also a personal imperative. You know if you're the guy who's driving the who's the best buggy whip driver in the world and all of a sudden that job no longer exists you have a responsibility to learn how to drive a car. And could you introduce yourself please? My name is Shane Padham CEO of Health Integrated we're a data enabled health care services company in the US. Thanks for that. Anyone else and if you could introduce yourself. Thank you. Name is Eric Moteirowork for AMIA we're a loyalty marketing company Canadian for a global company. The question I have is how much of this bubble question really isn't about thinking about capitalism with a bit of an old frame of mind right. I mean it used to be that if you're an industrial company you do one thing and do one thing really well. So if something is wrong or a question when you're a business model that's it. But if you look at the new economy I mean I think similar points you made right. You're creating value in a very different way. You're not going to you know stop going to Facebook because they're making less money or more money. You're building a customer relationship and a franchise. And so how much of this is we just need to think about valuations and value frankly from a capitalism point of view in a different way than we used to. I don't spend a lot of time thinking about reframing capitalism I trust and it's free market mechanics to guide me. I'm not sure it's actually all that relevant to think about the markets in between the times you're fundraising as an entrepreneur in which it becomes an existential question. And as far as I'm concerned about public markets primarily in terms of how to put off that moment in time when all of your employees start tracking level to quotes. So I'm relatively bearish on participating in markets if I don't have to. How does this play out in China? It is interesting that Alibaba's listing in the U.S. Well I think there are probably two layers of explanations. One is why is Alibaba listed outside. The other is I think why is Alibaba becoming so big I think the Chinese top three technology companies are taking three spots of the top six largest IT companies in the entire world these days and why is that? So I think the gentleman has a valid point in terms of what information technology has created a lot of value by serving the entire society. But at the same time it is also changing the way how wealth is being actually allocated across the society. So there's definitely a stronger sense of winner takes all mentality that is part of the reason behind why I think those companies are able to create more values and having a higher chance of creating more bubbles because they have so much wealth they have to spend. So I think this is related to how, I don't think that is necessarily the entrepreneurs or the investors agenda, but I think it is how the government or the regulators would have to set a line between what if there is such a great deal of wealth being created, how can we have the value of serve the greater good or the bigger part of the society? Yeah, I mean, you know, it takes one data point to create a bubble, it's sort of the crazy deal and everybody feels everything's crazy, but I think what the greed factor in all this is that a young kid with an idea, understand technology can create a billion dollars for this company, for these investors. So a few years ago that wasn't apparent. Right now it's apparent. So everybody say, well, even if I have a one out of a hundred chance probability, I'll invest a million dollars.  But I think, you know, one thing about China, which is interesting, I think it's a slightly different topic, but there's a lot of wealth being created too and it's going to a few hands. So the whole social enterprise, the whole, you know, the whole philanthropy movement is very clear to us on the front line. These are things that people are talking about and people are doing. So hopefully those things translate to really meaningful social enterprises that can help to bring the level up for everybody. We have time for one more question. China Business News. Thanks, you've talked about the Alibaba frenzy and now its price is range from 60 to 66 US dollars per share. So do you think it is kind of overvalued and given the overall regulation and the atmosphere in the United States, how do you think it's prospect down the road and any suggestions for a slum term sustainable development there? Want to take that? Advice for Alibaba? And what do you think Alibaba itself is overvalued with the estimates for it? Well, you know, we're focused on the series A, so that's a research topic for the big banks. But I think what's interesting is that, you know, we interview a lot of people from Alibaba. I think that's interesting, they see the IPO coming and they're looking for other things. I think, you know, put the business model aside and all that. What is Alibaba, what's interesting about Alibaba, it's corporate culture. That to me is very fascinating. Those interviews come across very consistent. It's got a strong alignment of individual interests and also the company's interests where people can fight for the company. That's something that's intangible but I think that's gonna drive the company too for the heights. I found Jack Ma's letter to the shareholders. Fascinating, on corporate governance, around the focus first towards the customer and employees and the shareholders last. I think all the elements in the letter that he addressed the shareholders, if you're gonna invest in this company, expect these things. I think if he can hold true to that, I'd be an investor in the company. Before we take our final vote that I mentioned, I'd like to go around and see if you all have final thoughts that you'd like to share kind of a sound bite or what you predict is gonna unfold as we move on from here, especially in coming weeks with the Alibaba issue. Well, I think, you know, China is not much different than the US. I would say the environment here is very entrepreneurial. I would say as an investor, this is probably, you know, you can never say it's the best time because you never know, but it feels like there's a lot of things we can do that can be really meaningful outcomes. I do agree, there are a lot of areas where that's heavily regulated, that's being disrupted by technology and those are mega opportunities. So, you know, I think, you know, so we're quite excited about, you know, at least the next few years, you can't really see too far away, but the next few years, it would be very interesting companies being built. Well, I think technology have created a lot of really great companies ever in human history, but I also want to caution from a pure academic or research perspective, sometimes great companies can make terrible investments. I think I'm very bullish entrepreneurship. So I think so long as the apparent nature of a kid with the technology knowledge and a billion dollar outcome is more transparent, more believable, people will try more things as long as the market supports those initiatives, we're all gonna be better off and incidentally just to echo your point, I think the, it's a topic for a different panel, but we should never allow ourselves to slow down innovation, simply out of fear that someone's gonna have to finally give up that horse and buggy business that they treasured so successfully for 100 years. The thought of a bubble doesn't give me any anxiety.  I'm in LA and it's been 20 years since we've had an earthquake and everybody knows it's coming, right? And you can build the right foundation and anticipate and survive the earthquake or you can ignore it. Bubbles are bad if you're an investor and investing in the wrong company. If you're an entrepreneur and you ignore it and you're not building a company with sustainable value, then the bubble will get you. I'll say to close, how many of you in the audience feel that we are our pro-bubble that we're in a bubble? I think I see you are hands, okay? How many put your hands up if you, I think we have a relative consensus here of convinced you that we are not in a bubble? Excellent. Well, I'd like to thank our panelists for a really fascinating discussion and thanks to all of you.


Live from Dublin, Ireland, it's theCUBE. Covering Hadoop Summit Europe 2016. Brought to you by Hortonworks. Now your hosts, John Furrier and Dave Vellante. Okay, welcome back everyone. We are here live in Dublin, Ireland. This is theCUBE's SiliconANGLE's flagship program. We go out to the events and extract the signal from the noise. I'm John Furrier. My co-host, Dave Vellante, our next guest is David Hill, Business Development Director at Open Energy Hortonworks Customer. Welcome to theCUBE. Thanks for coming on. Well thank you for having me. Open Energy with an I, not a Y, it's the company name.  The energy economy is the tagline on your site. But I love this business model of arbitraging, pricing of energy, pricing demand, supply and demands, a lot of economics do it. But essentially you're creating a marketplace for energy. Is that right? Did I get that right? Yeah, fundamentally we have built a software distributed energy storage system essentially that is a software that integrates into many different types of an industrial, commercial electricity demand to flex that demand at certain times a day to stop a peaking power plant coming online and to enable the system to work far more effectively. And that's just the electricity systems globally are needing much more flexibility to run as we integrate renewable energy systems, much higher levels of penetration. And so we need more flexibility to operate the system and there's a premium on that. So it sounds like smart energy before we get there I want to ask you, give some examples of where you guys value proposition is, use case of where you guys are practicing your business. So at any given time of day, a system operator in the UK that is called National Grid in the east coast of US that's called PJM need to buy in a certain amount of electricity capacity at certain times a day to deal with unforeseen circumstances. Power station tripping offline for instance or a freak weather event. Traditionally the way you deal with that is you just ramp up a power station quickly to deal with that event. We're looking at doing the absolute opposite on the demand side. Some of our biggest customers in the UK are like water utilities for instance, where a significant amount of water utility demand is water pumping, which is not time dependent. You can sort of modulate the pumps for small periods of time a day without having no impact on the drinking water. So manage energy. Essentially manage energy. But instead of just doing it for energy efficiency purposes, we enable our customers to earn revenue by actually transacting their energy back into the system at certain times a day. So you said, I think I heard you say essentially have developed an energy storage system. Is this through software or? Yes, fundamentally there are thousands of millions of devices out there that have small amounts of storage within them when we heat things, when we cool things, when we pump things, we are fundamentally creating small amounts of stored energy that if you deploy software to aggregate all these small amounts of stored energy you create a sort of an alternative to a battery system that can provide stored energy systems by deferring energy consumption or bringing forward energy consumption for small periods of day. So you ship that energy to a place or you aggregate it through software and then are able to provision it? Yeah, so for instance, if someone needed 10 megawatts of energy for just an hour we could aggregate that 10 megawatts from across the country from thousands of different devices giving us a few kilowatts and minutes here and there and then over that hour you get 10 megawatts and get a whole hour worth of energy from lots of different pumps fridges or heating appliances. And you're buying and selling that too, right? So it's transactions? Yeah, so fundamentally we have to sort of with our industrial commercial customers for the benefit of us deploying our software we give them a revenue stream which we sell into the system and then we take a little cut in the middle. So it sounds like the core competence if your business is option pricing meets technology, meets software is that kind of thing going on? They're math involved, they've got to be some math involved in price supply and charging. I think there's actually, there's an evolution the biggest technological barriers is for us initially is in the internet of things is about actually getting in deploying software, controlling things in a way that makes your customers comfortable. You know, you're talking about assets that is critical to their business process. So it's been a technology play at first then it kind of as you grow your volume then it becomes more of an arbitrage and sort of how can we sort of maximize the value in that in relation to the energy market. Super exciting business. I mean it brings a whole new dimension to surge pricing. Yep. Well, it's a very entrenched business I presume it's highly regulated or maybe not in the UK. I mean one of the reasons why there are sort of interesting software companies emerging like this in the UK is because it's one of the more liberalized electricity sort of markets in the world that enables smaller technology companies to sort of play in the market in a less regulated way than some of the big generation companies. But the big generators are regulated, right?  Is it free for all? The big generators in the UK are allowed to sort of try and make as much money as possible from that generation stack just like we are in terms of the way in which we interact our flexibility in the market and try and operate, yeah, rather like a power station does. So a consumer in the US though has very few choices. We're here, she can buy energy. You're saying the UK consumer has- Yeah, they have a complete option. They can choose which supply they get their energy from and that supply can choose which generator they buy their electricity from. Likewise, consumers can choose to work with us to see if they can realize some potential of the flexibility of their energy. So the dynamics of the market from a public policy standpoint are much more receptive to what you guys are doing. Very much so, because we are all about transferring value from the old traditional supply side model back to the consumer. We're all about making energy more affordable, more reliable and fundamentally cleaner. And that's a market solution that was not a- No, not a substitute, that thing. Can you export that model to the United States? I mean there are certain areas in the United States where it's pretty big, so PGM on the East Coast of the United States there are some big companies who are doing similar type applications that we're doing in the UK. Yeah, so there are certain areas of the United States. Yeah, but it's pockets, it's sort of state by state. Yeah. Right? I think it probably is state regulated anyway in the United States. Okay, so- So it's a big data angle, I guess. Yeah, right. That's what I'm trying to get at. What's the secret data source? You know, not the geeky stuff, but at a high level. So I mean, fundamentally, our currency is data. Fundamentally, our ability to sort of monitor the health of the grid in real time and then sort of interact with the machine in real time. That's how we make our money by fundamentally shifting data around by sort of changing consumption for small periods of the day in relation to market signals. Our ability to compete with other energy sources like traditional power stations or battery technology is because of the dramatic cost reductions in data, communications, technology, storage, analytics. Those cost reduction curves allow us to basically do what we do at a much cheaper level than building a power station. But when your founders were starting the company back in whenever it was 2005, I mean, the state of the art was to take a pipe, stick it into a big Unix box or a Linux box, you know, buy some Oracle licenses, get a database. And if you had any money left over, you'd do some analytics on it. Fundament, yeah. So you kind of the formation of a company predated Hadoop generally, but then you sort of fell into it, right? Yeah, fundamentally. I mean, the reason I'm here, we're so excited is because we've adopted the Hortonworks technology and I see there's a huge leap in the way we do our business because when we first started out, you're right, we were an internet of things business before we even knew what the internet of things was. We knew that there was flexibility and energy in the way energy was consumed that could change the way the energy system worked. So we had to build a whole infrastructure, sort of bespoke infrastructure from the way we connected to things, the way we shipped that information into the database we built. So we knew it was not necessarily the scalable way we were going to change the world, but it was the way we had to prove the concept worked and get some more VC investment in us to then we began to sort of make the product more scalable and adopt certain technologies. How much capital do you guys raise? Over the last, I think, probably seven years, probably in the region of 30 to 30 million pounds. That's not that much cash. Considering Silicon Valley companies, I mean, Macs from PayPal just raised 100 million, some fintech startup. You guys are doing energy. Yeah, but I mean. But you're a software company, right? Yeah, essentially, and also, America tends to raise a little bit more money because the American market's a little bigger than the UK market. Well, plus it's spending all the money on promotion and sales and marketing, right? So software should be a pretty capital efficient business, but it seems to not be anymore because people have to raise so much to compete with the big dogs. But I wanted to ask you about sort of the, he said you're an IoT company before anybody was talking about IoT. John and I have talked a lot on theCUBE about the IoT fever, but slow down, folks, the things that you have to do to actually take advantage. Everybody says instrument the windmills, or instrument, in this case, the grid. But you talked about connectivity as a key first step. So talk a little bit more about the steps that you had to take. What were some of the prerequisites that you had to encounter? I mean, it was difficult, right? I mean, in the context of energy, some of the biggest energy consuming machines out there are old and not very smart. Little story is we once went to a port in the UK where there was a huge two megawatt-sized water pump that when the tide went out, it pumped water back into that port to keep the water level high so the boats didn't hit the ground of the port. Now that two megawatt pump is an amazing storage of energy. I could sort of, when surges of demand, I could turn that pump off and the water's going to stay there for a certain period of time. And we can deal with that with that water pump. But fundamentally, there was no control system at that water pump. The way that water pump was controlled was a guy sat at the end of the port and he watched the water level go down and he cranked that whole thing up when he needed to go. It's hard to automate that. So it's hard to connect that thing to the internet. So fundamentally, the internet of things, there's a lot of very old things that are tough to connect to the internet. And we had to spend a lot of money sort of instrumenting these things up to fundamentally bring these things into our internet of things infrastructure. It's worthwhile doing when you've got a two megawatt pump. It's not so worthwhile doing when you've got a two kilowatt kettle or something. So you pick your low-hanging fruit, knock those down, and then hope all new devices get instrumented from day one. Totally. So this leads on, that's a funny anecdote I guess, but this leads me on to the fact that we are beginning to look with some of the Hortonworks data flow services because that's a really exciting thing for us. Because it means we might be able to start integrating with the machines in a much more efficient and less costly way. Because previously, when we were interested in how much flexibility a certain type of asset had, a fridge or a boiler, we had to sort of hard code that information in that machine to start off with. Now, we can't change every single controller in the world, so we have to sort of work how can we do things on a much more machine learning basis? How can we sort of predict how much flexibility this asset has in real time without having to sort of change the way all these controllers work? So securing a data center is hard enough. People would dig a moat around the data center, try to secure it. Securing the grid is a whole different situation. Can you talk about security and how you guys think about it? Oh, I mean, it is at the heart of what we do. Fundamentally, we are connecting many different bits of critical national infrastructure. We're working with the grid, which is critical national infrastructure, and say, what are utilities? Also critical national infrastructure. So when you're connecting to these two things that you're creating, you're connecting up two pieces of critical national infrastructure. So it is at the heart of everything we do. Traditional sort of very strong firewalls and VPNs. But I mean, one of the reasons we started working with Hortonworks is because of the, it came enterprise-ready. Some of the security systems were very well thought of in terms of the way they were deploying their products in terms of some of the other sort of more off-the-shelf open-source things that might have not been just as ready as it should have. And given its IoT, the service area, obviously for a tax is significant. Yes, very much so. So you need to make sure you have these systems that are secure, and we sort of worked with other companies like Dark Trace as well, to sort of really sort of make sure that our systems are incredibly sort of learning about behavioral pattern changes so we can spot anomalies before they happen. What's your experience with Hortonworks? Obviously your customer, you guys like those guys, you like good experience with them? A happy customer? Yeah, I mean, it's, you know. You guys are talking to the press, so you've been cleared by their, their PR guys and folks over there. Yeah, I mean, I think we are, I think with all these kind of good client-customer relationships, it's definitely more of a partnership with these mutual benefits in us, both growing and learning. How do they help you? A good example. Folks are trying to figure out the, you know, selecting vendors, Hortonworks on point versus others. Because when you're trying to put a new data, sort of a new software infrastructure into your company, you know, you need to make sure the adoption of that is wide-scale to make sure you can really see the benefits of it on a large scale, and they've been incredibly helpful in terms of any of our data scientists, when they've got any sort of queries or problems. So it's a support. Support's been huge. Code reliability. Code reliability. Even when we found any like little bugs, they'll get in contact very quickly and help solve that sort of, they've been incredibly supportive. You don't want to have a patch to load, some cloud flaws. No, exactly.  They've been incredibly supportive of them, you know, wanting to see how we can sort of develop. And you bring all this up back into a data hub of kind of centralized respond when you act on the data. Yeah. Okay. Thoughts for this show and just the industry in general. You guys obviously at the front end of a pretty exciting opportunity. Really fascinating business. I'm really intrigued. I love what you guys do. Congratulations. I mean, I just think it's amazing. Naturally, when you see something that's an exciting concept, like I did many years ago when I joined the company and you realize as this industry grows, as the internet of things and so it grows, it's amazing how all of a sudden the big problems that you had, someone comes along and says we've kind of fixed it and you just, these things, it's amazing how these things naturally happen. It's a brand new opportunity. Yeah. And it's very exciting. The data drives that, that's what we're seeing. Very much so. Complete these green fields, they call them, but. Yeah. Well, thanks so much for sharing the insight. Open energy, David Hill, business development, energy with an eye at the end. Open energy, great business model, love the multifaceted, data driven, option pricing stuff. Reminds me of when I was in business school, Dave. Those days is like, these market places are hard to crack the code on. Yeah. If you can get the data, you can make it work. Totally. David Hill, here inside theCUBE, we're live in London, in Ireland. He said London again. Dave's getting late in the day. We're in Dublin, Ireland, not London, England. You'll know when you're sipping that Guinness tonight. We'll get his factory tonight. Here at the Hortonworks show, Hadoop Simon, we'll be back with more after this short break.


Build. Putin unexpectedly lets out atrocious goals of war in Ukraine. Journalists of Build media tabloid have drawn attention to a passage of the interview of Russian President Vladimir Putin to the propagandist Dmitry Kiselev in which he said it is ridiculous for us to negotiate now just because they are running out of ammunition. Columnist Philip Piatov expressed the opinion that this sentence alone makes it clear. Putin is using every military weakness to attack and achieve his goals of destroying Ukraine and enslaving the Ukrainian people. This exposes the mindset of the dictator and the naivety of those politicians who believe in peace talks with the Russian Federation. The journalist emphasized, Piatov noted that Ukraine is currently suffering losses on several fronts because of not receiving enough weapons and ammunition. And according to the logics of some politicians, Putin should be ready to negotiate under such conditions. But the Russian dictator follows a completely different logic. By negotiation, Putin actually means nothing more than Ukraine's surrender. The columnist explained, Paul Romsheimer, deputy editor-in-chief of the publication, also agrees with this assessment. This is a response to all those who continue to demand steps from Ukraine and the West to make negotiations possible. Despite the failures of 2022, when his troops were not able to take Kyiv and he lost territories in the East and South, Putin's goal has never changed. Putin wants to destroy Ukraine by even greater numbers of his troops and military economy to deprive it of its existence, to erase its culture. As for the West, if we can't do more sooner or later, Putin will achieve that goal. Time is now playing in his favor, the journalist stated. A woman who came to the polling station to vote in the presidential election in Moscow, the capital of Russia, poured brilliant green into the ballot box along with the ballot. The woman was immediately detained and a criminal case was opened against her under article 141 of the Criminal Code of the Russian Federation. He faces a prison sentence of three to five years. An old woman made a fire in another district in Moscow. He was detained and a criminal case was opened against him under the same article. Also, in Voronezh, Rostov and other provinces, cases of brilliant green being poured into ballot boxes were recorded. A criminal case was opened against all those who committed the incident under article 141 of the Criminal Code. There's panic in the Kremlin. Putin's team doesn't know what to do with the situation. Russian President Vladimir Putin's quick reaction to the raid by volunteers of the freedom of Russia Legion, the Russian Volunteer Corps and the Siberian Battalion on the territory of Russia's Belgorod and Kursk regions indicates panic in the Kremlin. Putin has already had time to comment on the breakthrough of fighters of the freedom of Russia. He called the raid by the volunteers an attempt to disrupt elections in Russia and Ukraine's desire to get Trump cards for the exchange of territory in possible negotiations. The statement of the Russian President was explained by the volunteer of the freedom to Russia Legion, Alexei Baranovsky, on the air of Channel 24. According to him, the attitude of the Russian Federation is that the Russian Federation is the only country in the world that has the right to vote for the Russian Federation. The attitude of the Russians to the raid of volunteers depends on their position on the war in Ukraine. The fact that Putin has already made a statement, although even a day has not yet passed from the beginning of the campaign, is a sign that there is panic in the Kremlin. They did not expect the vote to go this way at all, Baranovsky explained. According to him, the Kremlin elite doesn't know what to do with the situation and is starting to fuss. They are even coming up with terrorist attacks on behalf of Alexei Navalny, who died in a colony on February the 16th. Putin's regime is bloody, so you can expect any kind of crime from him. The main thing is that Russian volunteers are ready to fight it. We call on all Russians to join our fight, Baranovsky said. Earlier, a video appeared online in which people calling themselves Navalny's militant squads announced terrorist attacks in Russia during Putin's re-election. The FSB's pattern is clearly visible here. It's no secret that Putin came to power by blowing up houses in Moscow.  He emphasized that a false flag operation is a classic of the Soviet and Russian security services, just as they acted in Soviet times against rebels in Western Ukraine and the Baltic states. Respectively, the same plots Putin's regime uses inside Russian politics.