>> Announcer: Live from Vancouver, Canada. It's theCUBE covering OpenStack Summit North America 2018, brought to you by Red Hat, the OpenStack Foundation and its ecosystem partners. >> Welcome back, I'm Stu Miniman and my cohost John Troyer and you're watching theCUBE, the worldwide leader in tech coverage and this is exclusive coverage from OpenStack Summit 2018 in Vancouver. Usually this time of year it is a little bit overcast, but for the second time the OpenStack Summit has been here, the sun is shining. It has been gorgeous weather but we are in here really digging in and understanding it One of the people I have gotten to know through this community especially, is our wrap up guest today, Sean Michael Kerner, who is a senior editor with eWeek, amongst other bi-lines that you have. Pleasure to see you. >> Great, good seeing you too Stu. >> Alright, so we let you keep on the Toronto Bluejays hat >> Thank you, there we go. >> We have had quite a few Canadians on our program here. >> Well, seeing as how you're here in Canada, it's not all that surprising. >> It's lovely. They have you working on Victoria Day. >> Yeah, that's unfortunate but I will take Memorial Day off in a week, so it works out. >> Excellent. So Sean, for our audience that might not know you, give us a little bit about your background. You've been to umpteen of these shows. >> Sure. I have been with the same publication roughly, I guess 15-16 years at this point. I've been writing before there was cloud, core living and Opensource stuff, networking. And then through the magic of technology, I shifted a little bit to security, which is a core focus for me. I have been to every OpenStack Summit since the San Diego Summit, I guess, 2011. Somebody can correct me afterwards. I did miss the Sydney Summit for various reasons, but yeah, I've been to a bunch of these things, so interesting to see how things have shifted over the years from nothing to certain heights to where we are now. >> Alright, so bring us up to that, as to where we are now. Attendance is down a little bit. They haven't been talking a lot about it but quality I guess is here. Sessions, they've broadened down a bit of the scope. We have been digging into it, but want to get your take so far. >> Yeah, well it's like anything else, there are standard hype cycles, as it were and there's a trough of disillusionment. I wouldn't call this a trough of disillusionment, but when you get to a certain plateau, people just, there'sn't as much interest. In the early days, I remember the San Diego Summit I went to. They didn't schedule it properly. They didn't know how many people they were going to have, and they had to line up around the corner and stuff. That was six years ago, but that is when OpenStack was new. There was no such thing as the Foundation, and everyone was trying to figure out what was what. And, there was no clue at this point. Cloud is a well understood thing. There are competitive efforts or complimentary efforts, as the Foundation would probably like to put it; whether it's CNCF, there's the public cloud and it's different. There is, with all respect to the OpenStack Foundation and its member projects, there's not as much excitement. This in now a stable, mature ecosystem and because of that, I don't think there's as much of a draw. When something is brand new and shiny, you get more of a draw. If they would have put the name Blockchain somewhere, maybe, maybe they would have had a few more. They put Kubernetes in there, which is fine, but no machine learning or artificial intelligence quite yet, though that's a topic somewhere in there too. >> Yeah, John, you've been making a lot of comments this week talking about we've matured and the lower layer pieces just work a bit more. Give us your take about that. >> Sure. That's the way it seems. There wasn't a whole lot of talk about the release, news release, and all the different components, even the keynotes. But, the people we have talked to, both on the vendor and the customer side, they have working production OpenStack environments. They're very large. They require very few admins. They work. They're embedded in telecom and banking, et cetera. It's here and it's working. >> Yeah, that's so something that happened, maybe three cycles ago at this point, because they used to have the release the same time as the Summit and the Design Summit. It was together, so, there was essentially a celebration of the release. People would talk about the release and then they desegrigated that. I think that took a lot of steam out of the reason why you got developers to attend. So, when you don't have the Design Summit, there's this separate open endeavor, there's the forum, I don't quite understand how that works here now. There isn't as much momentum. Yeah, I agree with you. There has been very little talk about Queens. In each of the project update sessions I have been to, and I have been to a couple, there has always been a slight on Rocky, what's coming. I think we are on the second milestone of Rocky, at this point, so there's some development, but at this point it is incremental featurettes. There is no whiz bang. OK, we're going to have flying cars, you know send a Tesla to outer space kind of Earth shattering kind of news, literally, because that's not where it's at. It's just incremental tuck in features in stability and that kind of thing. >> Alright, you talk space and thinks like that and it brings to mind a certain attendee of the program that has actually been to outer space and maybe one of the more notable moments of the show so far. Give us your take on Mr. Shuttleworth. >> Well, I'm a big fan of Mr. Shuttleworth, top to bottom. Hey Mark. Big fan, always have been. He has his own opinion on things of course. Usually in a keynote you don't tend to take direct aim at competitors and he chose to do that. It made some people a little uncomfortable. I happened to be sitting in the front row, where I like to sit, and there was some Red Hat people, and there were some frantic emails going back and forth. And people were trying to see what was going on et cetera. I think, for me, a little bit of drama is okay. You guys go to more shows than I do, and sometimes you get these kind of sales kind of things. But in an open community, there's almost an unwritten rule, which perhaps will be written after this conference, that whether or not everybody is a business competitor or not, is that this is neutral territory as it were and everybody is kind of friendly. In the exhibit hall, you can say this and that, we are better, whatever, but on the stage you don't necessarily do that, so there was some drama there. Some of my peers wrote about that and I will be writing about it as well. It's a, I prefer to write about technology and not necessarily drama. Whether somebody is faster, better, stronger than others, you let the number prove them out. When we talk about Opensource, Opensource Innovation without Canonical, there probably wouldn't have been an OpenStack. All the initial OpenStack reference and limitations are on Canonical. They got a number of large public clouds, as does Red Hat. I think they both have their tactical merits and I'm sure on some respects Red Hat's better and on some respects Canonical is better, but him standing up there and beating on the competition was something that across the 13 summits I have been I have never seen before. One guy I talked to my first OpenStack Summit was in San Diego and the CTO of VMware at the time came up to, VMware was not an OpenStack contributor at the time, they were thinking about it, and he was fielding questions about how it was competitive or not and he was still complimentary. So there has always been that kind of thing. So, a little bit of an interesting shift, a little bit of drama, and gives this show something memorable, because you and I and others will be able to talk about this five years from now, et cetera. >> You talked about something you would write up. I mean part of your job is to take things back to the readers at eWeek. >> Yeah. >> What are the things, highlights you're going to be covering? >> The highlights for me, Stu and I talked about this at one point off the camera, this is not an OpenStack Summit necessarily, they're calling it Open Infrastructure. I almost thought that they would change, we almost thought that they would change the name of the entire organization to the Open Infrastructure Foundation. That whole shift, and I know the foundation has been talking about that since Sydney last year, that they're going to shift to that, but, that's the take away. The platform itself is not the only thing. Enabling the open infrastructure is nice. They're going to try and play well and where it fits within the whole stack. That gets very confusing because talking about collaboration is all fine and nice, but that is not necessarily news. That is how the hot dog is made and that's nice. But, people want to know what's in that dog and how it is going to work. I think it's a tougher show for me to cover than it has been in past years, because there has been less news. There's no new release. There was Kata 1.0 release and there was the Zuul project coming out on its own. Zuul project, they said it was 3.0, it was actually March was Zuul 3.03. Kata Container project, okay, interesting, we'll see how it goes. But a tougher project, tougher event for me to cover for that reason. Collaboration is all fine and nice. But, the CNCF CloudNativeCon KubeCon event two weeks ago, or three weeks ago, had a little bit more news and a lot it's same kind of issues come up here. So, long winded answer, tough to come up with lessons learned out of this, other than everyone wants to be friends, well some people want to be. And, collaboration is the way forward. But that is not necessarily a new message. >> When I think about Kubernetes, we are talking about the multi cloud world and that's still, the last few years, where it's been. Where does OpenStack really fit in that multi cloud world? One of the things I have been a little disappointed actually, is most of the time, when I'm having a conversation, it's almost the, yeah, there's public cloud, but we are going to claw things back and I need it for governments, and I need all of these other things. When I talk to customers, it is I'm going to choose what I put in my data center. I'm going to choose how I use probably multiple public cloud finders. It is not an anti-public cloud message, and it feels a little bit on the anti-public cloud mass. I want to work with what you're hearing when you >> talk to users? >> When I talk to users, vast majority of people, unless it's something, where there's regulatory issues or certain legacy issues or private cloud, public cloud period. The private cloud idea is gone or mostly gone. When I think about private clouds, it's really VmWare. We have virtualized instances that sitting there. >> What's OpenStack? >> OpenStack is fine, but how many are running OpenStack as a private cloud premise? >> Yeah, so what's OpenStack then? >> When I think of OpenStack, Oracles public cloud. Oracle is not here surprisingly. Oracle's public cloud, Larry Ellison, who I know you guys have spoken to more than once on theCUBE at various points on Oracle World and other things. Oracle's public cloud, they want to compete against AWS. That's all. OpenStack IBM cloud, all OpenStack. The various big providers out of China are OpenStack based. OEH is here. So that's where it fits in is that underlying infrastructure layer. Walmart uses it. Bestbuy, all these other places, Comcast, et cetera; ATT. But individual enterprises, not so much. I have a hard time finding individual enterprises that will tell me we are running our own private cloud as OpenStack. They will tell me they're running VmWare, they will tell me they're running REV or even some flavor of Citrix end server, but not a private cloud. They may have some kind of instances and they will burst out, but it's not, I don't think private cloud for mid tier enterprises ever took off the way some people thought five years ago. >> That's interesting. Let's go meta for a second. You talked about things you do and don't write about, you don't necessarily write the VC's are not here necessarily, but you don't write about necessarily financial stuff. >> Sometimes. There was actually at the Portland summit, I did a panel with press and analysts at the time and afterwards there might have been four different VC's that came up to me and asked me what I thought about different companies. They were looking at different things where they would invest. And I remember, we looked at the board and one VC who shall remain nameless, and I said you know what, we'll look at this board with all these companies and five years from now, three quarters of them will not be here. I think I was probably wrong because it is more than that. There are so many. I wrote a story, I don't remember the exact name of it, but I wrote a story not that long ago about OpenStack deadpool. There are so, multiple companies that raised funding that disappeared. In the networking space, there were things like Plumgrid, they mminorly acquired for assets by Vmware, if I'm not mistaken. There was Pivotal, Joshua McKenzie, one of the co-founders of OpenStack itself, got acquired by Cisco. But they would have collapsed perhaps otherwise. Nebula Computing is perhaps, it still shocks me. They raised whatever it was 50 odd million, someone will correct me afterward. Chris Kemp, CTO of NASA who helped start it. Gone. So, there has been tremendous consolidation. I think when VC's lose money, they lose interest really fast. The other thing you have to think about, from the VC side, they don't write too much on the financial. My good friend Fredrick, who didn't make it, Where are you, Fredrick, where are you? Does more on that funding side. But has there been a big exit for an OpenStack company? Not really, not really. And without that kind of thing, without that precedence it's a tough thing, especially for a market that is now eight years old, give or take. >> Even the exits that had a decent exit, you know that got bought into the say IBM's, Cisco's of the world, and when you look a couple of years later, there's not much left of those organizations. >> Yeah. It's also really hard. People really don't want to compete against, well, some people want to compete against AWS. But, if you're going to try to go toe to toe with them, it's a challenge. >> Okay, so what brings you back here every year? You're speaking at the show. You're talking to people. >> What brings me back here is regardless of the fact that momentum has probably shifted, it's not in that really hype stage, OpenStack's core infrastructure, literally, core infrastructure that runs important assets. Internet assets, whether it certain public cloud vendors, large Fortune 500 companies, or otherwise. So it's an important piece of the stack, whether it's in the hype cycle or not, so that brings me back, because it's important. It brings me back because I have a vested interest. I have written so much about it so I'm curious to see how it continues to evolve. Specifically, I'm speaking here on Thursday doing a panel on defending Cloud Counsel Security as a core competence, a core interest for me. With all these OpenStack assets out there, how they're defended or not is a critical interest. In the modern world, cyber attacks are a given. Everybody should assume they're always under a constant state of attack and how that security works is a core area of interest and why I will keep coming back. I will also keep coming back because I expect there to be another shift. I don't think we have heard the end of the OpenStack story yet. I think the shift towards open infrastructure will evolve a little bit and will come to an interesting conclusion. >> Alright, last thing is what's your favorite question you're asking at this show. Any final things you want to ask us as we wrap? >> Yeah, my favorite, well, I want to ask you guys, what the most interesting answer you got from all the great people you interviewed because I'm sure some of it was negative and you got mostly positive as well. >> Well, we aren't used to answering the questions Stu. >> I'm used to being on the other side here, right. >> Well, I do say we got a lot of stuff about some interesting and juicy cases, like I say, the practitioners I talked to were real. I was always impressed by how few administrators it takes to run a huge OpenStack based cloud once it's set up. I think that's something interesting to me. You asked some folks about a public cloud a lot. >> Yeah, so it has been interesting. For me, it's, we've reached that certain maturity level. I was looking at technology. What's kind of the watermark that this is going to come to? We had said years ago, I don't think you're going to have somebody selling a billion dollars worth of distribution on OpenStack. So, that story with how Kubernetes and Containers and everything fits in, OpenStack is part of the picture, and it might not be the most exciting thing, but then again, if you watch Linux as long as most of us have, Red Hat took a really long time to get a billion dollars and it was much more than just Linux that got them there. This still has the opportunity to be tooling inside the environment. We have talked to a number of users that use it. It's in there. It's not that the flagpole, we're an OpenStack company anymore because there really aren't many companies saying that that is the core of their mission, but that is still an important piece of the overall fabric of what we are covering. >> Exactly right. >> Alright, we on that note, Sean Michael Kerner, we really appreciate you joining us. Please support good technology journalism because it is people like him that help us understand the technology. I read his stuff all the time and always love chatting with him off the record and dragged him on here and Fredrick from Techron Show we are disappointed you could not join us, but we'll get you next time. For Jon Troyer, I'm Stu Miniman, be sure to join us for the third day tomorrow of three days of wall to wall live coverage here from OpenStack Summit 2018 in Vancouver. And once again, thank you for watching theCUBE. (upbeat music)

>> Live from Boston, Massachusetts, it's The Cube! Covering IBM Chief Data Officer Summit, brought to you by IBM. >> Welcome back to The Cube's live coverage of IBM's Chief Data Strategy Summit, I'm your host Rebecca Knight, along with my cohost Dave Vellante. We have a big panel today, these are our social influencers. Starting at the top, we have Christopher Penn, VP Marketing of Shift Communications, then Tripp Braden, Executive Coach and Growth Strategist at Strategic Performance Partners, Mike Tamir, Chief Data Science Officer at TACT, Bob Hayes, President of Business Over Broadway. Thanks so much for joining us. >> Thank you. >> So we're talking about data as a way to engage customers, a way to engage employees. What business functions would you say stand to benefit the most from using data? >> I'll take a whack at that. I don't know if it's the biggest function, but I think the customer experience and customer success. How do you use data to help predict what customers will do, and how do you then use that information to kind of personalize that experience for them and drive up recommendations, retention, upselling, things like that. >> So it's really the customer experience that you're focusing on? >> Yes, and I just released a study. I found that analytical-leading companies tend to use analytics to understand their customers more than say analytical laggards. So those kind of companies who can actually get value from data, they focus their efforts around improving customer loyalty by just gaining a deeper understanding about their customers. >> Chris, you want to jump in here with- >> I was just going to say, as many of us said, we have three things we really care about as business people, right? We want to save money, save time, or make money. So any function that meets those qualifications, is a functional benefit from data. >> I think there's also another interesting dimension to this, when you start to look at the leadership team in the company, now having the ability to anticipate the future. I mean now, we are no longer just looking at static data. We are now looking at anticipatory capability and seeing around corners, so that the person comes to the team, they're bringing something completely different than the team has had in the past. This whole competency of being able to anticipate the future and then take from that, where you take your organization in the future. >> So follow up on that, Tripp, does data now finally trump gut feel? Remember the HBR article of 10, 15 years ago, can't beat gut feel? Is that, we hit a new era now? >> Well, I think we're moving into an era where we have both. I think it's no longer an either or, we have intuition or we have data. Now we have both. The organizations who can leverage both at the same time and develop that capability and earn the trust of the other members by doing that. I see the Chief Data Officer really being a catalyst for organizational change. >> So Dr. Tamir I wonder if I could ask you a question? Maybe the whole panel, but so we've all followed the big data trend and the meme, AI, deep learning, machine learning, same wine, new bottle, or is there something substantive behind it? >> So certainly our capabilities are growing, our capabilities in machine learning, and I think that's part of why now there's this new branding of AI. AI is not what your mother might have thought AI is. It's not robots and cylons and that sort of thing that are going to be able to think intelligently. They just did intelligence tests on the different, like Siri and Alexa, quote AIs from different companies, and they scored horribly. They scored much worse than my, much worse than my very intelligent seven-year old. And that's not a comment on the deficiencies in Alexa or in Siri. It's a comment on these are not actually artificial intelligences. These are just tools that apply machine learning strategically. >> So you are all thinking about data and how it is going to change the future and one of the things you said, Tripp, is that we can now see the future. Talk to me about some of the most exciting things that you're seeing that companies do that are anticipating what customers want. >> Okay, so for example, in the customer success space, a lot of Sass businesses have a monthly subscription, so they're very worried about customer churn. So companies are now leveraging all the user behavior to understand which customers are likely to leave next month, and if they know that, they can reach out to them with maybe some retention campaigns, or even use that data to find out who's most likely to buy more from you in the next month, and then market to those in effective ways. So don't just do a blast for everybody, focus on particular customers, their needs, and try to service them or market to them in a way that resonates with them that increases retention, upselling, and recommendations. >> So they've already seen certain behaviors that show a customer is maybe not going to re-up? >> Exactly, so you just, you throw this data in a machine learning, right. You find the predictors of your outcome that interest you, and then using that information, you say oh, maybe predictors A, B, and C, are the ones that actually drive loyalty behaviors, then you can use that information to segment your customers and market to them appropriately. It's pretty cool stuff. >> February 18th, 2018. >> Okay. >> So we did a study recently just for fun of when people search for the term "Outlook, out of office." Yeah, and you really only search for that term for one reason, you're going on vacation, and you want to figure out how to turn the feature on. So we did a five-year data poll of people, of the search times for that and then inverted it, so when do people search least for that term. That's when they're in the office, and it's the week of February 18th, 2018, will be that time when people like, yep, I'm at the office, I got to work. And knowing that, prediction and data give us specificity, like yeah, we know the first quarter is busy, we know between memorial Day and Labor Day is not as busy in the B to B world. But as a marketer, we need to put specificity, data and predictive analytics gives us specificity. We know what week to send our email campaigns, what week to turn our ad budgets all the way to full, and so on and so forth. If someone's looking for The Cube, when will they be doing that, you know, going forward? That's the power of this stuff, is that specificity. >> They know what we're going to search for before we search for it. (laughter) >> I'd like to know where I'm going to be next week. Why that date? >> That's the date that people least search for the term, "Outlook, out of office." >> Okay. >> So, they're not looking for that feature, which logically means they're in the office. >> Or they're on vacation. (laughter) Right, I'm just saying. >> That brings up a good point on not just, what you're predicting for interactions right now, but also anticipating the trends. So Bob brought up a good point about figuring out when people are churning. There's a flip side to that, which is how do you get your customers to be more engaged? And now we have really an explosion in reinforcement learning in particular, which is a tool for figuring out, not just how to interact with you right now as a one off, statically. But how do I interact with you over time, this week, next week, the week after that? And using reinforcement learning, you can actually do that. This is the the sort-of technique that they used to beat Alpha-Go or to beat humans with Alpha-Go. Machine-learning algorithms, supervised learning, works well when you get that immediate feedback, but if you're playing a game, you don't get that feedback that you're going to win 300 turns from now, right now. You have to create more advanced value functions and ways of anticipating where things are going, this move, so that you see things are on track for winning in 20, 30, 40 moves, down the road. And it's the same thing when you're dealing with customer engagement. You want to, you can make a decision, I'm going to give this customer a coupon that's going to make them spend 50 cents more today, or you can make decisions algorithmically that are going to give them a 50 cent discount this week, next week, and the week after that, that are going to make them become a coffee drinker for life, or customer for life. >> It's about finding those customers for life. >> IBM uses the term cognitive business. We go to these conferences, everybody talks about digital transformation. At the end of the day it's all about how you use data. So my question is, if you think about the bell curve of organizations that you work with, how do they, what's the shape of that curve, part one. And then part two is, where do you see IBM on that curve? >> Well I think a lot of my clients make a living predicting the future, they're insurance companies and financial services. That's where the CDO currently resides and they get a lot of benefit. But one of things we're all talking about, but talking around, is that human element. So now, how do we take the human element and incorporate this into the structure of how we make our decisions? And how do we take this information, and how do we learn to trust that? The one thing I hear from most of the executives I talk to, when they talk about how data is being used in their organizations is the lack of trust. Now, when you have that, and you start to look at the trends that we're dealing with, and we call them data points verses calling them people, now you have a problem, because people become very, almost analytically challenged, right? So how do we get people to start saying, okay, let's look at this from the point of view of, it's not an either or solution in the world we live in today. Cognitive organizations are not going to happen tomorrow morning, even the most progressive organizations are probably five years away from really deploying them completely. But the organizations who take a little bit of an edge, so five, ten percent edge out of there, they now have a really, a different advantage in their markets. And that's what we're talking about, hyper-critical thinking skills. I mean, when you start to say, how do I think like Warren Buffet, how do I start to look and make these kinds of decisions analytically? How do I recreate an artificial intelligence when machine-learning practice, and program that's going to provide that solution for people. And that's where I think organizations that are forward-leaning now are looking and saying, how do I get my people to use these capabilities and ultimately trust the data that they're told. >> So I forget who said it, but it was early on in the big data movement, somebody said that we're further away from a single version of the truth than ever, and it's just going to get worse. So as a data scientist, what say you? >> I'm not familiar with the truth quote, but I think it's very relevant, well very relevant to where we are today. There's almost an arms race of, you hear all the time about automating, putting out fake news, putting out misinformation, and how that can be done using all the technology that we have at our disposal for disbursing that information. The only way that that's going to get solved is also with algorithmic solutions with creating algorithms that are going to be able to detect, is this news, is this something that is trying to attack my emotions and convince me just based on fear, or is this an article that's trying to present actual facts to me and you can do that with machine-learning algorithms. Now we have the technology to do that, algorithmically. >> Better algos than like and share. >> From a technological perspective, to your question about where IBM is, IBM has a ton of stuff that I call AI as a service, essentially where if you're a developer on Bluemix, for example, you can plug in to the different components of Watson at literally pennies per usage, to say I want to do sentiment analysis, I want to do tone analysis, I want personality insights, about this piece, who wrote this piece of content. And to Dr. Tamir's point, this is stuff that, we need these tools to do things like, fingerprint this piece of text. Did the supposed author actually write this? You can tell that, so of all the four magi, we call it, the Microsoft, Amazon, Google, IBM, getting on board, and adding that five or ten percent edge that Tripp was talking about, is easiest with IBM Bluemix. >> Great. >> Well, one of the other parts of this is you start to talk about what we're doing and you start to look at the players that are doing this. They are all organizations that I would not call classical technology organizations. They were 10 years ago, look at a Microsoft. But you look at the leadership of Microsoft today, and they're much more about figuring out what the formula is for success for business, and that's the other place I think we're seeing a transformation occurring, and the early adopters, is they have gone through the first generation, and the pain, you know, of having to have these kinds of things, and now they're moving to that second generation, where they're looking for the gain. And they're looking for people who can bring them capability and have the conversation, and discuss them in ways that they can see the landscape. I mean part of this is if you get caught in the bits and bites, you miss the landscape that you should be seeing in the market, and that's why I think there's a tremendous opportunity for us to really look at multiple markets of the same data. I mean, imagine looking and here's what I see, everyone in this group would have a different opinion in what they're seeing, but now we have the ability to see it five different ways and share that with our executive team and what we're seeing, so we can make better decisions. >> I wonder if we could have a frank conversation, an honest conversation about the data and the data ownership. You heard IBM this morning, saying hey we're going to protect your data, but I'd love you guys, as independents to weigh in. You got this data, you guys are involved with your clients, building models, the data trains the model. I got to believe that that model gets used at a lot of different places, within an industry, like insurance or across retail, whatever it is. So I'm afraid that my data is, my IP is going to seep across the industry. Should I not be worried about that? I wonder if you guys could weigh in. >> Well if you work with a particular vendor, sometimes vendors have a stipulation that we will not share your models with other clients, so you just got to stick to that. But in terms of science, I mean you build a model, right? You want to generalize that to other businesses. >> Right! >> (drowned out by others talking) So maybe if you could work somehow with your existing clients, say here, this is what we want to do, we just want to elevate the waters for everybody, right? So everybody wins when all boats rise, right? So if you can kind of convince your clients that we just want to help the world be better, and function better, make employees happier, customers happier, let's take that approach and just use models in a, that may be generalized to other situations and use them. If if you don't, then you just don't. >> Right, that's your choice. >> It's a choice, it's a choice you have to make. >> As long as you're transparent about it. >> I'm not super worried, I mean, you, Dave, Tripp, and I are all dressed similarly, right? We have the model of shirt and tie so, if I put on your clothes, we wouldn't, but if I were to put on your clothes, it would not be, even though it's the same model, it's just not going to be the same outcome. It's going to look really bad, right, so. Yes, companies can share the models and the general flows and stuff, but there's so much, if a company's doing machine learning well, there's so much feature engineering that's unique to that company that trying to apply that somewhere else, is just going to blow up. >> Yeah, but we could switch ties, like Tripp has got a really cool tie, I'd be using that tie on July 4th. >> This is turning into a different kind of panel (laughter) Chris, Tripp, Mike, and Bob, thanks so much for joining us. This has been a really fun and interesting panel. >> Thank you very much. Thank you. >> Thanks you guys. >> We will have more from the IBM Summit in Boston just after this. (techno music)