(upbeat music) (upbeat music) >> Hi everybody, welcome back to our coverage of the Cloud Native Security Con. I'm Dave Vellante, here in our Boston studio. We're connecting today with Palo Alto, with John Furrier and Lisa Martin. We're also live from the show floor in Seattle. But right now, I'm here with Andy Thurai who's from Constellation Research, friend of theCUBE, and we're going to discuss the intersection of AI and security, the potential of AI, the risks and the future. Andy, welcome, good to see you again. >> Good to be here again. >> Hey, so let's get into it, can you talk a little bit about, I know this is a passion of yours, the ethical considerations surrounding AI. I mean, it's front and center in the news, and you've got accountability, privacy, security, biases. Should we be worried about AI from a security perspective? >> Absolutely, man, you should be worried. See the problem is, people don't realize this, right? I mean, the ChatGPT being a new shiny object, it's all the craze that's about. But the problem is, most of the content that's produced either by ChatGPT or even by others, it's an access, no warranties, no accountability, no whatsoever. Particularly, if it is content, it's okay. But if it is something like a code that you use for example, one of their site projects that GitHub's co-pilot, which is actually, open AI + Microsoft + GitHub's combo, they allow you to produce code, AI writes code basically, right? But when you write code, problem with that is, it's not exactly stolen, but the models are created by using the GitHub code. Actually, they're getting sued for that, saying that, "You can't use our code". Actually there's a guy, Tim Davidson, I think he's named the professor, he actually demonstrated how AI produces exact copy of the code that he has written. So right now, it's a lot of security, accountability, privacy issues. Use it either to train or to learn. But in my view, it's not ready for enterprise grade yet. >> So, Brian Behlendorf today in his keynotes said he's really worried about ChatGPT being used to automate spearfishing. So I'm like, okay, so let's unpack that a little bit. Is the concern there that it just, the ChatGPT writes such compelling phishing content, it's going to increase the probability of somebody clicking on it, or are there other dimensions? >> It could, it's not necessarily just ChatGPT for that matter, right? AI can, actually, the hackers are using it to an extent already, can use to individualize content. For example, one of the things that you are able to easily identify when you're looking at the emails that are coming in, the phishing attack is, you look at some of the key elements in it, whether it's a human or even if it's an automated AI based system. They look at certain things and they say, "Okay, this is phishing". But if you were to read an email that looks exact copy of what I would've sent to you saying that, "Hey Dave, are you on for tomorrow? Or click on this link to do whatever. It could individualize the message. That's where the volume at scale to individual to masses, that can be done using AI, which is what scares me. >> Is there a flip side to AI? How is it being utilized to help cybersecurity? And maybe you could talk about some of the more successful examples of AI in security. Like, are there use cases or are there companies out there, Andy, that you find, I know you're close to a lot of firms that are leading in this area. You and I have talked about CrowdStrike, I know Palo Alto Network, so is there a positive side to this story? >> Yeah, I mean, absolutely right. Those are some of the good companies you mentioned, CrowdStrike, Palo Alto, Darktrace is another one that I closely follow, which is a good company as well, that they're using AI for security purposes. So, here's the thing, right, when people say, when they're using malware detection systems, most of the malware detection systems that are in today's security and malware systems, use some sort of a signature and pattern scanning in the malware. You know how many identified malwares are there today in the repository, in the library? More than a billion, a billion. So, if you are to check for every malware in your repository, that's not going to work. The pattern based recognition is not going to work. So, you got to figure out a different way of identification of pattern of usage, not just a signature in a malware, right? Or there are other areas you could use, things like the usage patterns. For example, if Andy is coming in to work at a certain time, you could combine a facial recognition saying, that should he be in here at that time, and should he be doing things, what he is supposed to be doing. There are a lot of things you could do using that, right? And the AIOps use cases, which is one of my favorite areas that I work, do a lot of work, right? That it has use cases for detecting things that are anomaly, that are not supposed to be done in a way that's supposed to be, reducing the noise so it can escalate only the things what you're supposed to. So, AIOps is a great use case to use in security areas which they're not using it to an extent yet. Incident management is another area. >> So, in your malware example, you're saying, okay, known malware, pretty much anybody can deal with that now. That's sort of yesterday's problem. >> The unknown is the problem. >> It's the unknown malware really trying to understand the patterns, and the patterns are going to change. It's not like you're saying a common signature 'cause they're going to use AI to change things up at scale. >> So, here's the problem, right? The malware writers are also using AI now, right? So, they're not going to write the old malware, send it to you. They are actually creating malware on the fly. It is possible entirely in today's world that they can create a malware, drop in your systems and it'll it look for the, let me get that name right. It's called, what are we using here? It's called the TTPs, Tactics, Techniques and procedures. It'll look for that to figure out, okay, am I doing the right pattern? And then malware can sense it saying that, okay, that's the one they're detecting. I'm going to change it on the fly. So, AI can code itself on the fly, rather malware can code itself on the fly, which is going to be hard to detect. >> Well, and when you talk about TTP, when you talk to folks like Kevin Mandia of Mandiant, recently purchased by Google or other of those, the ones that have the big observation space, they'll talk about the most malicious hacks that they see, involve lateral movement. So, that's obviously something that people are looking for, AI's looking for that. And of course, the hackers are going to try to mask that lateral movement, living off the land and other things. How do you see AI impacting the future of cyber? We talked about the risks and the good. One of the things that Brian Behlendorf also mentioned is that, he pointed out that in the early days of the internet, the protocols had an inherent element of trust involved. So, things like SMTP, they didn't have security built in. So, they built up a lot of technical debt. Do you see AI being able to help with that? What steps do you see being taken to ensure that AI based systems are secure? >> So, the major difference between the older systems and the newer systems is the older systems, sadly even today, a lot of them are rules-based. If it's a rules-based systems, you are dead in the water and not able, right? So, the AI-based systems can somewhat learn from the patterns as I was talking about, for example... >> When you say rules-based systems, you mean here's the policy, here's the rule, if it's not followed but then you're saying, AI will blow that away, >> AI will blow that away, you don't have to necessarily codify things saying that, okay, if this, then do this. You don't have to necessarily do that. AI can somewhat to an extent self-learn saying that, okay, if that doesn't happen, if this is not a pattern that I know which is supposed to happen, who should I escalate this to? Who does this system belong to? And the other thing, the AIOps use case we talked about, right, the anomalies. When an anomaly happens, then the system can closely look at, saying that, okay, this is not normal behavior or usage. Is that because system's being overused or is it because somebody's trying to access something, could look at the anomaly detection, anomaly prevention or even prediction to an extent. And that's where AI could be very useful. >> So, how about the developer angle? 'Cause CNCF, the event in Seattle is all around developers, how can AI be integrated? We did a lot of talk at the conference about shift-left, we talked about shift-left and protect right. Meaning, protect the run time. So, both are important, so what steps should be taken to ensure that the AI systems are being developed in a secure and ethically sound way? What's the role of developers in that regard? >> How long do you got? (Both laughing) I think it could go for base on that. So, here's the problem, right? Lot of these companies are trying to see, I mean, you might have seen that in the news that Buzzfeed is trying to hire all of the writers to create the thing that ChatGPT is creating, a lot of enterprises... >> How, they're going to fire their writers? >> Yeah, they replace the writers. >> It's like automated automated vehicles and automated Uber drivers. >> So, the problem is a lot of enterprises still haven't done that, at least the ones I'm speaking to, are thinking about saying, "Hey, you know what, can I replace my developers because they are so expensive? Can I replace them with AI generated code?" There are a few issues with that. One, AI generated code is based on some sort of a snippet of a code that has been already available. So, you get into copyright issues, that's issue number one, right? Issue number two, if AI creates code and if something were to go wrong, who's responsible for that? There's no accountability right now. Or you as a company that's creating a system that's responsible, or is it ChatGPT, Microsoft is responsible. >> Or is the developer? >> Or the developer. >> The individual developer might be. So, they're going to be cautious about that liability. >> Well, so one of the areas where I'm seeing a lot of enterprises using this is they are using it to teach developers to learn things. You know what, if you're to code, this is a good way to code. That area, it's okay because you are just teaching them. But if you are to put an actual production code, this is what I advise companies, look, if somebody's using even to create a code, whether with or without your permission, make sure that once the code is committed, you validate that the 100%, whether it's a code or a model, or even make sure that the data what you're feeding in it is completely out of bias or no bias, right? Because at the end of the day, it doesn't matter who, what, when did that, if you put out a service or a system out there, it is involving your company liability and system, and code in place. You're going to be screwed regardless of what, if something were to go wrong, you are the first person who's liable for it. >> Andy, when you think about the dangers of AI, and what keeps you up at night if you're a security professional AI and security professional. We talked about ChatGPT doing things, we don't even, the hackers are going to get creative. But what worries you the most when you think about this topic? >> A lot, a lot, right? Let's start off with an example, actually, I don't know if you had a chance to see that or not. The hackers used a bank of Hong Kong, used a defect mechanism to fool Bank of Hong Kong to transfer $35 million to a fake account, the money is gone, right? And the problem that is, what they did was, they interacted with a manager and they learned this executive who can control a big account and cloned his voice, and clone his patterns on how he calls and what he talks and the whole name he has, after learning that, they call the branch manager or bank manager and say, "Hey, you know what, hey, move this much money to whatever." So, that's one way of kind of phishing, kind of deep fake that can come. So, that's just one example. Imagine whether business is conducted by just using voice or phone calls itself. That's an area of concern if you were to do that. And imagine this became an uproar a few years back when deepfakes put out the video of Tom Cruise and others we talked about in the past, right? And Tom Cruise looked at the video, he said that he couldn't distinguish that he didn't do it. It is so close, that close, right? And they are doing things like they're using gems... >> Awesome Instagram account by the way, the guy's hilarious, right? >> So, they they're using a lot of this fake videos and fake stuff. As long as it's only for entertainment purposes, good. But imagine doing... >> That's right there but... >> But during the election season when people were to put out saying that, okay, this current president or ex-president, he said what? And the masses believe right now whatever they're seeing in TV, that's unfortunate thing. I mean, there's no fact checking involved, and you could change governments and elections using that, which is scary shit, right? >> When you think about 2016, that was when we really first saw, the weaponization of social, the heavy use of social and then 2020 was like, wow. >> To the next level. >> It was crazy. The polarization, 2024, would deepfakes... >> Could be the next level, yeah. >> I mean, it's just going to escalate. What about public policy? I want to pick your brain on this because I I've seen situations where the EU, for example, is going to restrict the ability to ship certain code if it's involved with critical infrastructure. So, let's say, example, you're running a nuclear facility and you've got the code that protects that facility, and it can be useful against some other malware that's outside of that country, but you're restricted from sending that for whatever reason, data sovereignty. Is public policy, is it aligned with the objectives in this new world? Or, I mean, normally they have to catch up. Is that going to be a problem in your view? >> It is because, when it comes to laws it's always miles behind when a new innovation happens. It's not just for AI, right? I mean, the same thing happened with IOT. Same thing happened with whatever else new emerging tech you have. The laws have to understand if there's an issue and they have to see a continued pattern of misuse of the technology, then they'll come up with that. Use in ways they are ahead of things. So, they put a lot of restrictions in place and about what AI can or cannot do, US is way behind on that, right? But California has done some things, for example, if you are talking to a chat bot, then you have to basically disclose that to the customer, saying that you're talking to a chat bot, not to a human. And that's just a very basic rule that they have in place. I mean, there are times that when a decision is made by the, problem is, AI is a black box now. The decision making is also a black box now, and we don't tell people. And the problem is if you tell people, you'll get sued immediately because every single time, we talked about that last time, there are cases involving AI making decisions, it gets thrown out the window all the time. If you can't substantiate that. So, the bottom line is that, yes, AI can assist and help you in making decisions but just use that as a assistant mechanism. A human has to be always in all the loop, right? >> Will AI help with, in your view, with supply chain, the software supply chain security or is it, it's always a balance, right? I mean, I feel like the attackers are more advanced in some ways, it's like they're on offense, let's say, right? So, when you're calling the plays, you know where you're going, the defense has to respond to it. So in that sense, the hackers have an advantage. So, what's the balance with software supply chain? Are the hackers have the advantage because they can use AI to accelerate their penetration of the software supply chain? Or will AI in your view be a good defensive mechanism? >> It could be but the problem is, the velocity and veracity of things can be done using AI, whether it's fishing, or malware, or other security and the vulnerability scanning the whole nine yards. It's scary because the hackers have a full advantage right now. And actually, I think ChatGPT recently put out two things. One is, it's able to direct the code if it is generated by ChatGPT. So basically, if you're trying to fake because a lot of schools were complaining about it, that's why they came up with the mechanism. So, if you're trying to create a fake, there's a mechanism for them to identify. But that's a step behind still, right? And the hackers are using things to their advantage. Actually ChatGPT made a rule, if you go there and read the terms and conditions, it's basically honor rule suggesting, you can't use this for certain purposes, to create a model where it creates a security threat, as that people are going to listen. So, if there's a way or mechanism to restrict hackers from using these technologies, that would be great. But I don't see that happening. So, know that these guys have an advantage, know that they're using AI, and you have to do things to be prepared. One thing I was mentioning about is, if somebody writes a code, if somebody commits a code right now, the problem is with the agile methodologies. If somebody writes a code, if they commit a code, you assume that's right and legit, you immediately push it out into production because need for speed is there, right? But if you continue to do that with the AI produced code, you're screwed. >> So, bottom line is, AI's going to speed us up in a security context or is it going to slow us down? >> Well, in the current version, the AI systems are flawed because even the ChatGPT, if you look at the the large language models, you look at the core piece of data that's available in the world as of today and then train them using that model, using the data, right? But people are forgetting that's based on today's data. The data changes on a second basis or on a minute basis. So, if I want to do something based on tomorrow or a day after, you have to retrain the models. So, the data already have a stale. So, that in itself is stale and the cost for retraining is going to be a problem too. So overall, AI is a good first step. Use that with a caution, is what I want to say. The system is flawed now, if you use it as is, you'll be screwed, it's dangerous. >> Andy, you got to go, thanks so much for coming in, appreciate it. >> Thanks for having me. >> You're very welcome, so we're going wall to wall with our coverage of the Cloud Native Security Con. I'm Dave Vellante in the Boston Studio, John Furrier, Lisa Martin and Palo Alto. We're going to be live on the show floor as well, bringing in keynote speakers and others on the ground. Keep it right there for more coverage on theCUBE. (upbeat music) (upbeat music) (upbeat music) (upbeat music)

(upbeat music) >> Man: From the Computer History Museum in the heart of Silicon Valley, it's theCUBE! Covering Food IT. Fork to farm. Brought to you by Western Digital. >> Welcome back everybody, Jeff Frick here with theCUBE. We're in Mountain View, California at the Computer History Museum at Food IT, a really interesting conference about 350 people talking about the impacts of IT and technology in the agricultural space. Everything from farming, through to how you shop, how you consume, and what happens to the waste that we all, unfortunately, throw away way too much. We're excited to have our next guest, Mike Wolf, he's the creator and curator of The Spoon and the Smart Kitchen Summit. Mike, welcome! >> Hey, thanks for having me, I'm excited! >> Absolutely! So first off, before we jump in, what do you think of the show here? >> It's great! It's very focused on agriculture and the food chain, which is crucial. I focus a lot on the kitchen, when food gets to our homes, what we do with it, but this is where it all starts, so it's really important. >> It's so much stuff going on-- >> Yeah. >> With the kitchen and food preparation with all these services that will-- >> Yeah. >> Either bring you your meal, or they'll bring you pre-portioned and uncooked meals. So let's talk about a little bit, what is the Smart Kitchen Summit, and what is The Spoon? >> So I focused on the smart home a lot over my career. I've written a book on how to network your home, but about four or five years ago I noticed no one's really talking about how we're going to recreate the kitchen. We've focused from a digital home perspective on the living room. We saw the Netflix revolution, over-the-top, we've seen huge market value creation in the living room. But the kitchen was kind of left behind. So I said, let's start a conversation, let's focus on how we can recreate cooking in the kitchen. And the Smart Kitchen Summit is entering it's third year, it's kind of become the premier event about how technology will reshape how we get food, bringing her home, how we cook it, and how we eat it. >> Well it's funny though, because people would always say, you know, "I have the iPad on the front of my fridge, "it'll tell me when it's time to go get milk." So clearly, that's a pretty-- >> Yeah. >> Pretty low... Not of real significant use in this case, I would imagine, there's a lot more to it than that. >> Yeah, I think tablets and screens, and connecting to things with apps is like five percent of what's interesting. If you look at the refrigerator, the internet refrigerator, I was just talking to an LG guy, they created the first internet refrigerator in 2000, and it was $20,000, and no one bought it, 'cause everyone said "Why would I want to "connect my refrigerator "to the internet?" >> Right, right. >> Well, I kind of think we're at this point where now it becomes interesting. We can maybe have the fridge understand what our food is. The fridge itself is kind of a... The family bulletin board, so why not put a big screen on there if it's only a couple extra hundred dollars? >> Right. >> And so I think there's all sorts of ways in which we're getting food, like you said, new ways like Blue Apron, Cooking By Numbers services, new ways to cook food that are coming from the professional kitchen, like sous vide, high-precision cooking technology that's democratized for technology, and things like automated beer brewing appliances. I've always wanted a beer, brew beer, but my wife said "No way, you're going to have "the smelly..." >> Right. >> "Beer coming in my house." But I can use technology to make this automated and easy? I'm one of those guys that say "Let's do that." Then I can brag to my friends that I've actually made beer at home. >> Right, right. >> So. >> Well, it's funny 'cause we saw this other thing in the kitchen not that long ago, right? Where everybody had to have a Wolf, and it was kind of this, you know, kind of professionalize your kitchen with all these really heavy-duty, you know... >> Yeah. >> Appliances, that really, most people probably don't need a Wolf so they can keep their flambe at the perfect temperature-- >> Yeah. >> For extended periods of time. >> Yeah. >> So what are some of these things that are coming down the line that people haven't really thought of that you see as you study this phase? >> Well, so our research shows that everyone, almost every age group is using more digital technology in the kitchen, and that's iPhones, smart phones, and tablets, because what they're doing is looking for what they're going to have for dinner. So that starts the process of digitization in the kitchen, and so you've seen almost for 15, into 17, years now services like Allrecipes and Yummly creating kind of this digital recipe services. Now, we've also seen, really one of the most popular videos on the internet, BuzzFeed Tasty was the biggest video publisher for many months this year, doing a couple billion views a year, per month of these simple cooking videos. So... >> Right. >> A lot of it is very much generational. So millennials are grabbing on to these how-to-cook, you know, how-to-cook videos. They're very interested in cooking, but the definition of cooking is changing, so what they're seeing is the worrying about cooking through online, but also maybe applying cooking technology in a new way. Whether that's a very simple cooking appliance, like a sous vide circulator, or maybe an air fryer, or if you want to go high-end something, like a June Oven. So if you look forward, starting to add artificial intelligence, image recognition, and these type of technologies to the cooking process could make things a lot easier and make things faster, and kind of give you cooking super powers that you may otherwise not have. >> Right. It's so interesting! It continues to be a trend over and over, that it's kind of the hollowing of the middle, right? You are either you don't ever cook, right? >> Yeah. >> Everything is DoorDash, or however you get your... The meal. Or you kind of get to these specialty items where you're way into it as a hobby and, I mean, those videos, the cooking videos-- >> Yeah. >> Are fascinating to me, the popularity of those things. >> Yeah. >> But if you're kind of stuck in the middle, in the no-man's-land of what we think of maybe as a traditional kitchen, that's probably not a great place to be. >> Yeah, I think, you know, I'm that... I'm a different archetype depending on the day of the week, right? I may be in the middle of the week, and I'm tired, I have kids, I don't want to cook. Maybe something that automates my cooking maybe makes it easy with food delivery, it's fully cooked. That would be a great idea! But maybe on the weekend, I want to become, like, a maker, and really, like I say, the only maker space in the home, right now, besides the garage, is the kitchen. It's where I'm actually using my hands to make stuff. And I think that's great nowadays when we're all spending so much time in front of screens, moving around ones and zeros with our mouses, I think... Our research shows that people want to cook, but the definition of cooking is changing. So they may be assembling salads, or, and they're buying something from Costco and they're calling that cooking. But I think if we can have technology that allows us to actually make stuff in the home, where it's fresh and tastes good, it's healthy, and we feel like we're rewarding a craft, I think there's a lot of people who would want that. >> That's so interesting, that it's makers and craftsmanship, and you think back to kind of the traditional, beautiful cookbooks, right? That people would buy, maybe to actually use, maybe just 'cause they want to be associated with that type of activity and those types of photographs and stuff. So it's a very different way to think about it, as a maker versus, you know, just got to get the food out for the kids, I'm tired on a Thursday night at 6 p.m. >> Yeah, sometimes it's just sustenance, right? That's why packaged food is great. We like these protein bars. They're expensive, but they provide everything in one in, like, a flat piece of food. But at the same time, there's a whole food movement. Ever since John Mackey founded Whole Foods back in the early 80's, until the time that Amazon acquired it, the customer base has been growing. What I think is interesting is we can potentially see the democratization of better quality food. As you see, the decentralization of processed food, right? So over the past 100 to 200 years, all the technology around food has been towards centralized processing, and putting it into cans, making it... But what happens is you take all the nutritional value out of it. >> Right. >> But if you can start to think about bringing fresher food in the home, at a lower cost through optimized value chains, like what maybe Amazon can do with Whole Foods. Maybe that brings fresher food to the home at a lower cost, or it gets beyond the five to ten percent of the consumer, which is buying from Whole Foods. >> Right. >> It's a high-end type of retail channel, right? But I think everyone wants better food, so I think that's where I think technology could play a process. >> Well, just specifically, what are you thoughts on the Amazon acquisition of Whole Foods, and the impact of that? Not only for those two companies, specifically, but as a broader impact within the industry? >> I am excited for what Amazon could do with this technology. I live in Seattle, so I've been watching they're, what I would call lab experiments with Amazon Go, which is this recreation of the grocery store, this idea of walk in, walk out, don't ever talk to the cashier, that's really fascinating. Then you get Whole Foods, which is a pretty traditional retailer, even though it's kind of created the organic food movement in a lot of ways. I think bringing Amazon technology into theirs is really exciting, but I also think it validates the need for physical store fronts. I think Amazon's been trying to do online delivery, rolling trucks at your home for ten years. They've been working on Amazon for us for ten years, and they haven't been really... They haven't really reached massive scale. So I think this validates the idea of you need physical store fronts. Those physical store fronts may look very different in ten years, but the fact that Amazon is going to need that as a distribution point, as a point of presence in different neighborhoods, I think is fascinating. >> Alright, well, Mike we're almost out of time. I'll give you the last word. Where should people go to get more information about what you're up to? >> Yeah, go to TheSpoon.tech if you want to see our writing, podcast, and the future of food and cooking. And if you want to come to our event, go to SmartKitchenSummit.com. >> Alright, he's Mike Wolf, I'm Jeff Frick, you're watching theCUBE from Food IT. A lot of really interesting stuff. Again, it's all the way from the farm, the germination of the seeds, all the way through to what you eat, how you eat, and what you do with the stuff you don't. So thanks a lot Mike. >> Yeah, thanks! >> Alright, I'm Jeff Frick, you're watching theCUBE. We'll be right back after this short break. Thanks for watching. (upbeat music)

>> Announcer: From the Computer History Museum, in the heart of Silicon Valley, it's theCUBE. Covering Food IT: Fork to Farm, brought to you by Western Digital. >> Hey welcome back everybody Jeff Frick here with theCUBE. We're at the Food IT show at the Computer History Museum here in Mountain View, California. Really an amazing show, 350 people, all kind of pieces of the spectrum from academia to technology, to start-ups to Yamaha. Who thought Yamaha was into food tech, I didn't think that. To start-ups and we're really excited to have two of the partners form the Mixing Bowl and the Better Food Ventures, Brita Rosenheim and Seana Day welcome. >> Thank you. >> Thanks Jeff. >> So first off, congratulations on the event, what are your impressions? you guys been doing this for a couple years now I think. Bigger, badder, better? >> No I think this is great. We've has a fantastic turn out and the content's always very interesting and the interaction between the audience and the speakers is fantastic. >> Yeah, we just finished up a panel, IoT, Internet of Tomatoes, so there's always some great conversations really going. >> I think we're talking about that later this afternoon. >> Oh fantastic. >> It is interesting right, because all the big megatrends of cloud and we cover these in tech infrastructure all the time and big data and sensors and IoT and drones and these things. Really, all being brought to bare in agriculture from everything from producing the food to eating the food to the scraps that we don't eat I guess. >> No, you're spot on, some of the big macro challenges are what's driving a lot of the innovation. As you said food scraps, but waste is a major challenge. Labor, certainly here in California is something that we've seen a lot of innovation around solving some of those labor pain points. Certainly sort of environmental sustainability and resource management, you know, how are we using water, how are we using our inputs. Those are a lot of big themes that are driving interest in this sector and driving investment. >> Right so you guys are talking about some of the investments, like you guys put on a show, but you also have an investment arm, so you're looking for new technologies that play in this space correct? >> Yeah, Better Food Ventures makes early stage, seed investments so really kind of, not ideation stage, but pretty close after that. So working with entrepreneurs and really helping them, nurture them, and grow into hopefully successful companies. We've made 12 investments so far, I think seven of them have stepped up to priced equity so. >> Excellent, and you guys have brought this architecture landscape of the innovation. We won't share this on camera because it's way too many names for you to see, but obviously you can go online. >> Seana: It's available for download on our website MixingBowlHub.com. >> It's fascinating, there are literally what, a dozen categories and many firms within each category per side, so I wonder if you can give us a little bit more color on this landscape. I had no idea, the level of innovation that's happening in the food tech space, you just don't think about it probably if you're not in the industry. >> I'll let Seana kick off, between Seana and I, we cover Fork to Farm, so Seana covers from the farm, all the way through distribution and the area that I focus on, distribution all the way to consumer consumption. So we have a nice harmony there. We'll start at the beginning with Seana. >> Looking at over 3,000 companies. >> Jeff: 3,000? >> 3,000 between the two of our sort of database's. My coverage area is really infield technologies, hardware, software, applications. So anything from sensors, drones, soil moisture, weather, crop management, farm management software, all the way through as Brita said, distribution. So looking at supply chain management, logistics, trading platforms, collaboration platforms, so there's a lot going on. Every time, I roll out one of these technology landscapes. I'm always adding categories, which is sort of representative of the way that the market is evolving. I think that there is a lot of interesting stuff happening now in the post-harvest part of this market that more investors are starting to pay attention to. We've heard of that more today's even as well. Technologies that are focused on minimizing waste in the supply chain, making things more efficient helping shorten that supply chain so that we've got fresher food. More local options for consumers. >> I've been tracking the space for the last six or seven years, and to echo Seana's point on every time you put a new map out, you know we're thinking about different categories I mean every single year you've looked at it, the ecosystem has changed so much in terms of even how you categorize or even think of the different innovations that are shaping the space. I focus on, the way I look at my map is from in-home media consumption, discovery, so media, marketing, advertising, all the way through eCommerce, so both the B2B and B2C eCommerce platforms, all the way through restaurant and retail. So grocery, delivery, hyper-local marketing and the like. >> So can you explain the crazy success of these little, event handling, short food videos that are just taking the internet by storm? It's fascinating right? >> Yeah, BuzzFeed's tasty. >> Media consumption is really something to see. >> Yeah, I think BuzzFeed really took the traditional food media category by surprise. They really created the new, literally, video content for consumption that is extremely addicting, short, it makes everything seem approachable. It's kind of the bite-size version of the Food Network and I find myself. >> Off the chart right? >> You can't stop. Whether I'll make it or not you know, like the twirling potato and. (Brita chuckling) >> So the other, the sub-theme for this years conference is Fork to Farm and I'm just curious right. Because we've seen consumerization of IT impact all the different industries that we cover. It is really the end user at the end point that's driving the innovation back upstream. I wonder if you could speak to kind of the acceleration of that trend over time. Or is it relatively recent or you know there's some specific catalyst that you've seen as you've studied the market that has really driven an acceleration of that? >> Seana: Do you want to start with consumer and then we'll get back into the grower side of that? >> Yeah, I mean, I think you've seen kind of the long evolution since my web grocer cosmos of 10, 15 years ago and you know, people thinking, I'm never going to buy food online really don't have that trust level and you know kind of eCommerce in general, mobile technology in general has changed the consumers expectation and purchase and consumption patterns, period, for all other goods, so we've gotten to a point where there is a level of trust of if something is going to come to you in the mail there's just an expected level of trust or you can send it back. So that's kind of lent itself to this food category. I think in one way, that's been an overall industry shift in terms of the changing expectations of the consumer. You want to push a button, you've got your shoes, your lipstick you know your dog toys at the push of a button, why not your food. So the problem with that is food is very different it's has to be hot or cold, you have the cold chain speed, the manual labor involved. Just kind of the cost infrastructure is totally different than sending a box of lipstick and makeup to a consumer so I think you've seen a tremendous amount of funding in this on-demand delivery category a ton of different Uber for this, Uber for that, around the food space. Meal kits, but I think the reality of running those businesses have proven to be very difficult in terms of making the costs work out in terms of a business model so. >> Don't they all know why Van failed? They all probably too young to miss the Webvan and AT&T. >> Yeah, that being said, there's some opportunity there it's just about getting to the right scale. So obviously Amazon just bought Whole Foods last week I think there is room for a brick and mortar approach here but there, I think on-demand delivery's not going away in the food category, so who can actually deliver that because the consumer's not going to say, oh the business model doesn't make sense, I don't want this anymore. They just don't want to pay for it. Somebody has to figure out a way to. >> Oh that other pesky little detail About. And Seana it used to be if we make it they will eat right? I guess that doesn't hold true anymore. >> Well, you know it's a different adoption dynamic in the grower part of the technology adoption curve the consumers tend to pick things up more quickly than the traditional Ag player, Ag stake holder, the growers have been a little bit more tentative in terms of trying to figure out what kinds of technologies actually work. They're all of a sudden confronted with this idea of data overload. All of a sudden, you go from having no data to more data than you know what to do with. That's driving some of these adoption dynamics. People really trying to figure out what works, what business models are sustainable in agriculture and I know unsustainable from a resource standpoint. But just, will that business be around in six to nine to 12 months to support the technology that's in the field. So it's been a little slower I would say, on the production agriculture and grower side in terms of that uptake, but you know the other challenge that I think we face in terms of those models is really the flow of data. The flow of information is still very silo'd and in order to get the kind of decision support tools and the supply chain efficiencies that we're looking for in the food system, we really need to figure out how to integrate those data sources better. What's coming out of the field, what's happening in the mid-stream processing, and then what's happening on the supply chain and logistics side before you get to that consumer who's demanding it. But there's a lot of stages of information that need to harmonize before we can really have a more optimized system. >> Right, and are you seeing within the data side specifically some of the traditional players, like Tableau and clearly there's been a lot of activity in big data for awhile we've been going to Hadoop Summit and Hadoop World for ever and ever, are those people building Ag specific solutions or are there new players that really see the specific opportunity and better position to build you know the analytics to enable the use of that data? >> I think the big IT incumbents are looking at this very, very carefully. But there's are a lot of nuances to agriculture that are different from some of the other vertical industries and there's been a lot of observing from the sidelines down there, less from the deployment of actual technologies. Until people really understand how this market is starting to shake out. I think IBM and some of those big tech players are definitely on the fringes here, but I think again, we've got this challenge of how do you actually deliver value to growers. So, you've got all this data and you can crunch all this data how do you present that in a way that a grower can make a better decision about their operation. And oh, by the way, does the grower trust that data. That sort of is the challenge that I think we're still in the early innings in terms of of how that. It will come, but we're still in the early innings. >> Which is always the case right, to go from kind of an intuition, we've always done it this way, you know, like three generations of grandfathers that have worked this land too, you know here's the data, you can micro-optimize for this, that and the other and really take a different approach. >> I's say one of the challenges both on the Ag side, but also even on the food side, that there's a lot of start-ups that you meet with that are all about big data, big data, but big data really needs to be big data. So the incumbents are really the only ones that are in the position to crunch that amount of data. You can't actually get the insights when you don't have scale so there's a tremendous amount of companies that have a really interesting, innovative, approach to collecting data, to how you can use it and all they need is scale. That's virtually impossible unless they're acquired by or have a partnership with, which isn't going to happen a larger incumbent so big data, you really need a tremendous amount of data points to actually get to something that's useful. >> Alright, well, Seana and Brita thanks for taking a few min utes again, where can people go to get the pretty download it's a lot of data on this thing. >> It's MixingBowlHub.com so that's available both the AdTech landscape and the Food Tech landscape. >> Alright great, well again thanks, for inviting us to the show, really great show and congrats to you both for pulling it off. >> Thank you very much. >> Thanks very much. >> Alright, Brita, Seana, I'm Jeff you're watching theCUBE we're at FoodIT in the Computer Science Museum in Mountain View, California. We'll be back after the short break. Thanks for watching.