My name is Roger Meyer At Siemens living in Switzerland Did some computer system engineering in the past like embedded computer hacking and so on and with him my department We started with githlap Hey all Fabio Hoeser Software architect at Siemens mostly doing frontend stuff and you know as a side hobby maintaining the githlap platform at Siemens so We heard a lot about githlap how it's used in big companies and really cool scenarios today already So we kind of thought hey How can we bring the idea and kind of the DevOps culture as we rolled it out with and Siemens a bit better to you So we decided let's pack that into a story who is familiar with Gauls law in this room Some people yeah, that's lovely Gauls law quiet old but for us it's still kind of through so you'll see it here Basically to summarize a complex system will never work You always have to start small and kind of scale it up from there and today We're going to show you why this is The truth for so many things and hopefully you can learn one or the other thing from there as well cool, so just one Slide about Siemens how we started out in the past Siemens wasn't like this multi Million-dollar company since the beginning we started actually are quite small so there are two guys We're not from Siemens. That's kind of where the name is coming from You know in a backyard machine shop, so it was pretty much a early-day German startup already and the other funny thing is the first patent kind of shows you that seems all about innovation and you know researchy thing was actually Filed in the jail, so Vernon from Siemens Invented the whole electro government galvanization in jail and it kind of start from there So small small startup, but you see 1847 so quite a while back And we've built electrical cars before it has But they haven't been that successful during that time Exactly so you see small company and I would say we had more or less success So Siemens still existing nowadays, but of course it's a bit more complex at this point So you see a ton of stuff what we are building. So for example the tube here was also Built by by Siemens at least some of them and the other really nice thing you see here Those are in fact silos. So Siemens exist as so many different smaller companies As anyone we really love to not talk to each other So a ton of silos over there and you know, it's mainly focused on business to business So it's really hard to kind of grasp the connection to the customers You know all this big company mumbo jumbo as I think most people here are familiar with that kind of thing So you see also in terms of number and two people that was kind of cool now It's a 380,000 people so you actually see the scale just got much bigger and the whole complexity You know kind of really showed himself. So that's kind of the you know Outcoming situation we have and you know for us it was kind of the challenge How do we build a DevOps culture around this really fractured federalistic kind of company structure? Yeah, you see also many different cultures are involved 190 countries so also in a like human to human interaction level the challenges are certainly there and you know If you're interested we have also couple open shops there Cool so That's kind of the major part of the story we're going to tell you today and we try to answer the question What is this code? So this kind of code is our lovely baby code Siemens come That's our adaption of github, which we're using within Siemens and we really try to you know brand this idea So it's not only github yet another instance. It's really a community It's a brand which is behind of that. So now you could quite easily say hey We take a github we add a little bit of Siemens sauce and we have code Siemens come but Roger kind of showed you how this whole off story started Yeah at the early beginning as you see in 2013 we got In love with github the UI looked a little bit different. We had that nice fox logo And if you look at the application architecture, there were just three little pieces So the cool thing was it was a MIT license. So as we are addicted to open source software especially within from the embedded system development and so on I'm my origin in and Developer self-service. So this was one of the of the major topics for us So that people we don't need an administrator creating kind of users admins and so on and creating repos So having the people we're being able to just use it in 2013 Yeah, you can imagine we have probably all the version controls that exists on the planet in use within the company and of course then also all the build tools and We have co-paces with over 20 years of history. So a Lot of those. Yeah, and there was no company white source code hosting during that time So then we started Preparing that in-house for us BT GitLab at the early days. It was called the plan was to have it available for about a hundred people so for the embedded CPU module platform users and so on and We we are heavily using internal social network networks during that time. This was Socialcast and I was suggesting hey, of course, it is nice. I have a solution for my team But guys we need a common platform code Siemens come my colleague just registered the name and a few months later. I Told my boss I made of our 100 people GitLab instance code Siemens come and we will have other people joining us on the platform and They were okay So you see already here, it's quite an entrepreneurial kind of spirit, you know, which which we try to to go forward I mean it was a hefty discussion You can imagine you have like a small server and everyone is kind of honky-dory and suddenly of like people you don't even know on the Platform playing around and of course the computer cost is gonna rise and rise and rise But even back then we kind of thought hey this are you ideal logistic kind of idea? We had and the route you want to take is the right thing to do and all the details will figure out later on the way One important topic. Yeah, this was and during the early days. I made that had we didn't had the platform up and running But later on as we had the platform up and running just took a picture put that as a logo and Then one of our community members created that fancy logo so people are identifying themselves So we have now stickers people putting that on their notebooks and so on We were focusing on Not we did not focus on complainers. So this was an important topic for us So we had a lot of people that were addicted to on the way of working with kid Hey, we need kid. We don't like use that version control and so on and we focused on the people that were on fire with us for that common Coding platform and so we've been we've established an ambassador circle. So we have monthly calls and all those people the power users Contributing to our documentations and so on And of course now a day People do really identify themselves also with the platform. So if you meet Siemens developer Ask him. Do you know code Siemens come? I'm pretty sure he will know it. Yeah I mean the platform is sadly just the in-house thing, but I would say that logo is quite cool I mean if you're a developer, you kind of can relate to code and we brought some stickers with us So if you're interested in code and stickers, feel free to reach out to us At the very early beginning as we are all developers To make this platform a success and to bring this out to the whole company. It was key for us to have a Great team that is doing this and So at the very early beginning we defined the team charter So we really as we have enough silos within the company already the goal was to really have Cross silo thinker people To have people with a strong open-source mindsets that are that have worked within communities as maintainers as Contributors and so on so to bring in that Colorative way of working into the company So it's not like an administrative crew that is looking at a green lamp So we we have a team of eight people that is doing development and operations all the things For that whole platform. Yeah, and also the vision. It's quite all but still valid Colaborate on code and share within minutes You can imagine in the past. There were a lot of if you had two teams have to work together Which kind of version control to use which servers and setting all those things up took a long long time in the past Nowadays, it's just code teams come create group at your members bank. I Mean, you know the stuff which Russia just showed you kind of sounds benign, right? I mean, it's quite clear Everyone needs to have a vision everyone needs to have girls But we've seen it in the past. It's you kind of get really stuck with technology, right? I mean, there are so many great tools out there the open source world You know comes up with new tools every week about that the end of a day You know, we really try to solve it like a human issue We want to collaborate and the tool is just a secondary thing after all and you know all those things to give up We really found a tool which facilitates this ideology. It's all about the people behind it And you know to kind of maintain this idea and also have this community spirit within Siemens You really need to establish such community You need to find the right people in the open source world. You would say hey We want to have all maintainer personality Within Siemens kind of the same story So we're really always on the hunt for those maintainer people which really also can lead this cultural change Cool. So now we heard a lot about vision strategy kind of this matter thing and it's really important to kind of start from there So I think that was around 2015 or so where we had the platform. We were already in the thousands of user area You will see some current numbers a bit later in the presentation But this talk is all about the DevOps CICD It's not about what the Siemens folks have, you know in terms of vision already. So 2015 was kind of the day where we started with CICD We already heard a lot about You know see our runner in the restricted environment and the company and normally It's a thing that you have to go to your local IT department. You order a server You have to wait a couple of months and for us. This is not really, you know Inline with DevOps and CICD culture. So we kind of had the urge to change this However, we have not the capabilities to change it and of course you could nowadays Make beautiful fancy terraform setups or play around with Ansible and AWS and in the early days This wasn't possible. We also didn't really had the monetary fund to you know with four people Offer CI capabilities for a whole company with 300,000 people So that's why we kind of said hey, let's start small like as all things should be and you actually see it there That's not just Photograph we downloaded from the internet. No those were indeed the CI server, which means kind of you know Backed our whole platform for more than 80 percent over. I think more than a year We actually came up with a name for this kind of pattern and you know at least we're here from Switzerland this kind of You know saying already spread itself. It's junkyard computing Thanks to the ease of use of the key lab runner You can set up new machines in a matter of minutes if you have old machines laying around and you have a Good enough set up in terms of network and everything you can Literally on a minute base set up in your runners new capabilities and it's quiet cost effective So that was the idea where we really started out had those old runners, but people loved it They joined our platform. They could build Free CI stuff without maintaining their own server. So it was all there It was was already based on Docker So people could actually really bring their own Docker image and it this was something which you know never exists That's even some people literally about writing us an email like hey, is this possible? I don't have to pay anything It's like yes sure. I mean you're working for this company and that's That's benign as it sound and nowadays it's like usual thing But back in the past it was a huge paradigm change and you know it kind of sells itself, right? You get sia for free. You get a enormously stable service You get a state-of-the-art Docker image all based on you the problem So this really took off and I think not sure how many builds do we have per month? 1.5 million Per month so it's about you said 44k per day. Yeah So during our talk they're building a lot And and today We have our infrastructure on AWS So there's no junker compute anymore So this was really at the early day to give the whole topic a strong push and and to increase the adoption across the company Yeah, and that's really something we can recommend you a ton So if you have a github installation somewhere in your like a company and you know want to advertise that Having something like shared CRN There is a really really awesome way to argue with your department head or with the Definements department because you suddenly see how well everything works and how much the saving can be You don't have like your part-time administrators anymore, which you know after our Maintain a server and have to build it to the company. You have a really nice Centralized and cool maintained github runners set up. So I would say we only do doctor bills on our on our shared runners and We went through all the Linux distros We went through a lot of kernel box and stuff as we have a quite a high load on those things So now at the moment we are with the nixOS and for the runners Exactly So this was indeed a huge milestone for us and the really sad part of the whole story a lot of part-time Jenkins administrator They you know they have had to take care of more time to do important things So Support is always a really important question, right? I mean now we have this big platform everyone uses it I think it's kind of time to hire tons of tons of telephone supporters But that's not something we really want right good lab is a tool for developers and if you're familiar with the github community if you Already created an issue in the github issue tracker and to be honest I can highly recommend you to interact with the community. You noticed they have top-notch people So if you have an issue and you ask them they can really help you and that's kind of something We also want to do I mean roger is a developer I myself mainly or a developer and we also want to create a platform and a community which helps other developers So why should we hire support folks which didn't have the capabilities and like the rights to change anything? So we kind of said hey Let's create a community which educates themselves So that's kind of a help yourself ethos. We try to establish and in the same role mass github You know we started out with a documentation portal sounds easy and thanks to github pages. It is indeed really easy But getting the community Being part of that is a bit harder. So you also see the phone. That's a real thing. That's our support phone It has no connection at all. So so far we could probably say with zero support requests Right and you know, there are many many other ways how you can solve this whole support topic You know without having huge support stuff. I mean In our case, we're still eight people maintaining and supporting all the people Of course, we have the whole community supporting the people as well. So that's really lovely to see So people have for example if the if there is a question on the in on the internet social network Usually they get an answer within half an hour From other developers or from core team members and so on. So the people is really Greatly engaged And we receive also merge requests for our dog's page and our road map is fully transparent for all the people So all the people can see what we're working on what our next step. So we're discussing and you can imagine the time You have those it tickets I want to have this this And for us this was kind of a super important thing to don't have those Classical help desk topic and it's not only about the support So, you know, we we didn't just show you that this slide to say hey, you know Look at us. We don't have any support work to do is something even more important because having Not a help desk but really give power to the community enabled us to have this DevOps culture within Siemens So, you know rather than support ticket and you get a response like oh, you should do it like this You really have the folks teaching each other a I have this maven spring boot script, you know to automate this with gilab See I and then we'll do some automated security tests Stuff like that is really part of our documentation also part of our culture. So, you know people really educate each other We more or less have know how bubbles, you know We have the maven bubble and you have the go guy bubble and you know people can really go into those communities and you know Just exchange with each other and that helped us rolling out this Tremendous CI movement which happened at Siemens. I mean in the first half year We maybe had like 10,000 builds per month and as Roger just said we have more than 40 K Builds per day at this point. So without having this distributed knowledge how this would not be possible So it's not only about giving the people the right tool and giving them access It's also about the mindset and the collaboration of the culture And having a team that is able to handle also all those questions from experts. I guess that's that's Another topic super important to really have people that are able to answer all the question and giving direction on the issue tracker. No Being able to say no Yeah, so now this is kind of the inner circle and how we collaborate with and Siemens But I think more important is it going to be how do we collaborate with the bigger circle meaning the whole github community? And I think Roger can say some words upstream first so this is I've learned a lot also during the Linux Linux and a bootload of kernel hacking and all those things Usually you don't like to have patches and maintain patches and port them to the next version and so on and for us It was absolutely clear. We go without patches. We only deploy upstream Nothing else if you want to have new features we contribute them upstream We do not patch our instance As soon as they're merged upstream we're gonna deploy the next version so we shape every month We do about for production deployments per month Of course also configuration change security patch and so on and This was one of the main reasons why we why we've started using githl app It's open source and you can imagine as a company's like Siemens you have special needs and That's why we want to be able to Make that happen if you have a Special configuration we want to have in place or we did GPG code signing everything githl app the open ID connect The provider Bunch of security features like to FA enablement per group and and Our session list you have within your user profile and many many many other things and this is um Yeah, so We're also a little bit proud that we are one of the the biggest Contributor to githl app itself. So we're not only using Open source software and we're heavily contributing to several pieces also maintaining add-on libraries like the Python githl app maintained by max and So those are the things we're doing with the team of these a people and with Diego working on upstream topics Primarily for us on githl app, but maybe already disclaimer here, right? So we filtered out githl app on purpose because Of course the biggest contributor and there are a ton of I would even consider them githl app heroes You know like private people working on githl app like crazy as well But it's still cool and you see many many companies there and the list is by far not finished There's so many con companies contributing to githl app And you know, it's not only about contributing to the code base itself for us. It's also the cultural aspect It's exchanging yourself with the githl app folks with the community around githl app because there's so many things we can of course learn as Well, and you know, we will love this every day to kind of get new ideas how to do CI Which we can then you know take into our culture and adapt it within Siemens again So this whole exchange with the broader community and with githl app itself It's so valuable and you know, we can also highly recommend you to try contribute as githl app Famously says everything starts with a merge request. It's actually really easy. You don't have to be a programming hero They're really welcoming and I can just highly recommend it and as Roger said for us It was a huge cost saving as well to not maintain local patches or having to talk to 30,000 people and saying them like oh, no, sorry, we cannot accept your patch But you know this patch we want to have that would have been a possible with the team size we have so Ops room first is certainly the way to go and we would highly recommend it to you as well. Yeah Save money and time and get rid of that maintenance in the nightmare you will face Another topic as we've mentioned call slow Start with a simple system and we started a simple system and at the early beginning We just had one server on Bare metal later on we moved to AWS Now we have we had one server until 20,000 people so we reached the end of that drop-down so to increase the machine size and For us it was The most important topic was reliability of the service as we are developers as well so we were heavily focusing on Availability reliability on security crash reporting lock metrics and so on so all the non-functional requirements as you can imagine in the business Businesses we are at Siemens Those things are running for 20 years Super-reliable management systems for building or airports or whatever thing and and so the quality aspects are Super important for us and of course for all the users. So those were our primary focus and then We already had the plan to split the things out and as we know the github architecture quite well as we are Contributing to several parts on github itself, of course We had to plan ready to scale up nowadays we have about two github is For front-end nodes three sidekicks one pages and a gatekeeper For the internet access so we provide several service also via the internet so we can have contractors and so on on board and of course Kubernetes is nice and We might do this one day But at the end your our customers our developers they don't care about the fence technology We are going to use they want to have a reliable service that is running all the time and I guess in many cases you see people or projects building so sophisticated super nice fantastic architectures for what Because they are addicted to it to technology, but don't forget about your customer and the people that what are their expectations and Yeah, we like to use Kubernetes in the future, but We are focusing on happy developers. That's the most important thing And the people they know us they know the people within the core team So we are visible we are persons are behind the service. So if we if you break things We do incident incident Blockposts internally tell the people hey, what what happens? What was wrong? We're talking to the people and explaining The good things as well, of course Oh Right, so, you know, this is pretty much yet another story why goals law in our case worked out Just beautifully and we certainly also want to show you where we are now where github is now So you see github in? 2019 if you can remember on the previous slide you had this really nice architecture diagram of github in the 2013's that's the current github architecture diagrams. So I will consider it a little bit more complex So also they heavily moved into a more complex area because you know you have to if you want to have more feature and more speed The company itself grew as well And on Siemens on the other hand you see the service is established So, you know if you say hey, where's your code the answer is always it's a code Siemens come It's kind of the place to be because people like it there. We don't have to force them It's just a thing Everyone can contribute so you know we have just one big instance for the whole company people can make the repository internally That's all up to the each individual person and the product of course and you know if you're part of Siemens You have this huge You know like of different repositories who can collaborate with and you know We really try to bring the open source culture in and so far we really succeeded and then of course like I said CICD with one and a half million builds every month I would really say yes the whole culture thing also kind of changed and you know It's now completely normal if you create a project and code Siemens come you also have CI enabled because again, it's free It's easy And welcome good lab to the club of complex application architectures So we have tons of them So just maybe a rundown about the numbers so code Siemens come what's the scale you see it's 32,000 people and I think we are already on 33 more or less now. So, you know, even though We're already on a really high number. It still grows if I would be you know on the stock market I would certainly invest into this growing curve There is no end in sight and the funny thing is Siemens is around 20,000 software developers. So we're already kind of beat this market and Now have you know people from finance on there because they really love the issue board and the Kanban, you know board feature So it's not only developers which love the tool. It's also all the folks around You see those people actually do work on code Siemens come so they have not just registered They also have a ton of projects. So every person around two projects and you know for us a really important metric good lab is all about collaboration and Just having multiple projects. That's not really an indication for anything at all for us Also, the nodes are important. So every, you know comment you write in an issue or in a merge request It's counted as a note. So if more than three million nodes people actually indeed collaborate with each other I mean at least I myself don't write comments just to myself. So that's kind of an indication that people really talk to each other Then of course, you know, this year builds now. We're actually this week. We beat just 17 million I said it still goes rapidly and you know, we see that the exponential curve still goes on and As mentioned a lot of different countries. So the culture on code Siemens come the whole exchange is certainly really interesting and Beneath all of that you have eight people keeping this thing running more or less on the side. So that's quite a challenge Beautifully so Roger some famous last words It's all about people I would say that's That's the most important topic. It's not just Picking some people together and say hey, that's your goal. Go ahead. So having them being Have the technical skills and the people skills To drive the direction to to bring that adoption into the company and of course being transparent in all the things you're doing so Since the beginning we were talking about all our ideas and stuff and and have our roadmap visible for all the people Within the company. So it's not like We're cool. You have to walk the talk That's Key of course focus on your customers for developers from developers and that's why it's super important to have Developers within such a team. We are able to answer any question from the Colonel hacker To the Java spring boot guy to the Node.js guy and so on. We are able to handle this That's why we need no help desk. That's why we have documentation and so on and of course give and take it's Contributing stuff to open source projects to in-house projects or to the documentation and so on Living that spirit Within the company so the people see out there not just within their little island Here with the team We are collaborating with all the people if you see for a conference for example having a There the speaker The conference schedule and website is also in code teams come I see an issue there. I Create a merge request since in the past people did send emails, but the living that spirit of collaboration and In in the in-house world, but also in the open source world. That's that's the thing exactly So marks in the Roger will in the upcoming live session show you how this really looks like behind the scenes How one of the Siemens DevOps project actually do look like We are certainly available afterwards in the break if you have any question and with this kind of guideline Roger just showed you can by yourself kind of do the same thing as we we at least hope so thank you very much and See you later. Thank you


All right, so I have the latissimus dorsi here on the superficial side. So I made the exact same cut that I made to isolate the latissimus dorsi, and I went ahead and bisected that muscle to reveal the deeper intercostal muscles. So these are the muscles along the rib that are really important in breathing. And ordinarily there's a lot of fat. You can see this yellowing that's adipose tissue. That needs to be cleared off.  So in order to see these muscles you have to clear away the fat. And then if we move along the stomach you have the rectus abdominal muscles, which they're straight muscles that run up pretty much the full length of the abdomen. And then continuing on you have the obliques. So you have the external oblique, underneath that is the internal oblique. And then you'll have to look really closely to see the transverse abdominis, which if you see there are these, the stripe pattern there, which corresponds to the transverse abdominis. So the transverse abdominis kind of extends over and across the abdomen, whereas the internal oblique kind of stops short of that. So it's the external, the internal, and then more medial is the transverse abdominis.


From the SiliconANGLE Media office in Boston, Massachusetts, it's theCUBE. Now, here's your host, Dave Vellante. Welcome to this CUBE Conversation. My name is Dave Vellante. I'm one of the co-hosts of theCUBE and we're going to have a conversation to really try to explore, does infrastructure matter? You hear a lot today, oh, ever since I've been in this business, I've heard, oh, infrastructure is dead, hardware is dead, but we're going to explore that premise. And with me is Randy Arsenault and Steve Keniston. They're both global market development execs at IBM guys. Thanks for coming in and let's riff on this topic. So here's what I want to do. I want to start with data. We were just recently at the MIT chief data officer event 10 years ago that role didn't even exist. Now data is everything. So I want to start off with, you hear this bromide data is the new oil. And we've said, you know what? Data actually is more valuable than oil. Oil I can put in my car, I can put in my house, I can't put it in both. Data is, it doesn't follow the laws of scarcity. I can use the same data multiple times and I can copy it and I can find new value. I can cut costs, I can raise revenue. So data in some respects is more valuable. What do you think, Randy? Yeah, I would agree. And I think it's also to your point kind of a renewable resource, right? So data has the ability to be reused regularly to be repurposed. So I would take it even further. We've been talking a lot lately about this whole concept that data is really evolving into its own tier. So if you think about a traditional infrastructure model where you've got sort of compute a network and applications and workloads and on the edge you've got various consumers and producers of that data. The data itself as those pieces have evolved the data has been evolving as well. It's becoming more complicated. It's becoming certainly larger and more voluminous. It's better instrumented. It carries much more metadata. It's typically more proximal with code and compute. So the data itself is evolving into its own tier in a sense. So we believe that we want to treat data as a tier. We want to manage it, protect it, wrap the services around it that enable it to reach its maximum potential in a sense. So guys, we want to make this interactive in a way and I'd love to give you my opinions as well if you guys are okay with that. But so I want to make an observation, Steve. If you take a look at the top five companies in terms of market cap in the U.S. Apple, Google, Facebook, Amazon, and of course Microsoft, which is now over a trillion dollars, they're all data companies. They've surpassed the banks, the insurance companies, the exon mobiles of the world as the most valuable companies in the world. What are your thoughts on that? Why is that? I think it's interesting but I think it goes back to your original statement about data being the new oil. And unlike oil, you said you can put it in the house but you can't put it in your car, you also want it to burn, it's gone. But with data, you have it around, you generate more of it, you keep using it and the more you use it and the more value you get out of it, the more value the company gets out of it. And so the reason why they continue to grow in values is because they continue to collect data, they continue to leverage that data for intelligent purposes to make user experiences better, their business better, to be able to go faster, to be able to do new things faster. It's all part of this growth. So data is one of the superpowers. The other superpower of course is machine intelligence or whatever he talks about as AI. You know it used to be that processing power doubling every 18 months was what drove innovation in the industry. Today it's a combination of data which we have a lot of. It's AI and cloud for scale and we're going to talk about cloud but I want to spend a minute talking about AI. When I first came into this business, AI was all the rage but we didn't have the amount of data that we had today. We didn't have the processing power. It was too expensive to store all this data. That's all changed. So now we have this emerging machine intelligence layer being used for a lot of different things but it's sort of sitting on top of all these workloads that's being injected into databases and applications. It's being used to detect fraud, to sell us more stuff in real time, to save lives and we're going to talk about that but it's one of these superpowers that really needs new hardware architectures. So I want to explore machine intelligence a little bit. It really is a game changer, isn't it? It really is and tying back to the first point about sort of the evolution of data and the importance of data. Things like machine learning and adaptive infrastructure and cognitive infrastructure have driven to your point a hard requirement to adapt and improve the infrastructure upon which that lives and runs and operates and moves and breathes. So we always had hardware evolution or development or improvements in networks and the basic components of the infrastructure being driven again by advances in material science and silicon, et cetera. Well now what's happening is the growth and importance and dynamicity of data is far outpacing the ability of the physical sciences to keep pace, that's a reality that we live in. So therefore things like cognitive computing, machine learning, AI are kind of bridging the gap almost between the limitations we're bumping up against in physical infrastructure and the immense unlocked potential of data. So that intermediary is really where this phenomenon of AI and machine learning and deep learning is happening and you're also correct in pointing out that it's everywhere. I mean it's imbuing every single workload, it's transforming every industry at a fairly blistering pace. IBM's been front and center around artificial intelligence and cognitive computing since the beginning. We have a really interesting perspective on it and I think we bring that to a lot of the solutions that we offer as well. Ginny Rametti of a couple of years ago actually used the term incumbent disruptors and when I think of that I think about artificial intelligence and I think about companies like the ones I mentioned before that are very valuable, they have data at their core, most incumbents don't. They have data all over the place, they might have a bottling plant at the core, the manufacturing plant or some human process at the core. So to close that gap, artificial intelligence from the incumbent standpoint is they're going to buy that from companies like IBM. They're going to procure Watson or other AI tools or maybe use open source AI tools but they're going to then figure out how to apply those to their business to do whatever, fraud detection or recommendation engines or maybe even improve security and we're going to talk about this in detail but Steve, there's got to be new infrastructure behind that. We can't run these new workloads on infrastructure that was designed 30, 40 years ago. Exactly, I mean I think, I am truly fascinated by with this growth of data is now getting more exponential and we think about why is it getting more exponential? It's getting more exponential because the ease at which you can actually now take advantage of that data is going beyond the big financial services companies, the big healthcare companies, right? We're moving further and further and further towards the edge where people like you and I and Rainey and I have talked about the maker economy, right? I want to be able to go in and build something on my own and then deliver it to either as a service, as a person, a new application or as a service to my infrastructure team to go then turn it on and make something out of that. That infrastructure, it's got to come down in cost but all the things that you said before, performance, reliability, speed to get there, intelligence about data movement, how do we get smarter about those things? All of the underlying ways we used to think about how we manage, protect, secure that it all has evolved and it's continuing to evolve. Everybody talks about the journey, the journey to cloud, why does that matter? It's not just the cloud, it's also the componentry underneath and it's got to go much broader, much bigger, much faster. Well, and I would just add, just to amplify what Steve said about this whole maker movement. One of the other pressures that that's putting on corporate IT is it's driving, essentially driving product development and innovation out to the very edge, to the end user level. So you have all these very smart people who are developing these amazing new services and applications and workloads. When it gets to the point where they believe it can add value to the business, they then hand it off to IT who is tasked with figuring out how to implement it, scale it, protect it, secure it, et cetera. That's really where I believe IBM plays a key role or where we can play a key role and add a lot of value is we understand that process of taking that from inception to scale and implementation in a secure enterprise way. And I want to come back to that. So we talked about data as one of the superpowers and AI and the third one is cloud. So again, it used to be processor speed. Now it's data plus AI and cloud. Why is cloud important? Because cloud enables scale. There's so much innovation going on in cloud. But I want to talk about cloud 1.0 versus cloud 2.0. IBM talks about the new era of cloud. So what was cloud 1.0? It was largely lift and shift.  It was a lot of test and dev, a lot of startups who said, hey, I don't need to have IT like us, like theCUBE. We have no IT. So it's great for small companies. A great way to experiment and fail fast and pay for, you know, by the drink. That was 1.0. Cloud 2.0 is emerging as different. It's hybrid, it's multi-cloud, it's massively distributed systems, distributed data on-prem in many, many clouds. And it's a whole new way of looking at infrastructure and systems design. So as Steve, as you and I have talked about, it's programmable, so it's the API economy. Very low latency. We're going to talk more about what that means. But that concept of shipping code to data, wherever it lives, and making that cloud experience across the entire infrastructure, no matter whether it's on-prem or in cloud A, B, or C. It's a complicated problem. It really is. And when you think about the fact that, you know, the big challenge we started to run into when we were talking about cloud 1.0 was shadow IT, right? So folks really wanted to be able to move faster and they were taking data and they were actually copying it to these different locations to be able to use it for them simply and easily. Well, once you broke that mold, you started getting away from the security and the corporate governance that was required to make sure that the business was safe, right? But following the rules slowed business down, so this is why they continued to do it. In cloud 2.0, and I like the way you position this, right, is the fact that I no longer want to move data around. Moving data within the infrastructure is the most expensive thing to do in the data center. So if I can move code to where I need to be able to work on it, to get my answers, to do my AI, to do my intelligent learning, that all of a sudden brings a lot more value and a lot more speed and time is money, right? If I can get it done faster, I get more value out of it. And just, you know, people often talk about moving data, but you're right on. The last thing you want to do is move data and just think about how long it takes to back up. The first time you ever backed up your iPhone or how long it took, well, and that's relatively small compared to all the data in a data center. There's another subtext here from a standpoint of cloud 2.0 and it involves the edge. The edge is this kind of new thing. And we have a belief inside of Wikibon and theCUBE that we talk about all the time that a lot of the inference is going to be done at the edge. What does that mean? It means you're going to have factory devices, autonomous vehicles, medical device equipment that's going to have intelligence in there with new types of processors and we'll talk about that. But a lot of the inferences, the conclusions will be made real time. And by the way, these machines will be able to talk to each other. So you'll have machine to machine communication. No humans need to be involved to actually make a decision as to where should I turn or what should be the next move on the factory floor. So again, a lot of the data is going to stay in place. Now, what does that mean for IBM? You still have an opportunity to have data hubs that collect that data, analyze it, maybe push it up to the cloud, develop models, iterate and push it back down. But the edge is a fundamentally new type of approach that we've really not seen before and it brings in a whole ton of new data. Yeah, it's a great point and it's a market phenomenon that has moved and is very rapidly moving from smartphones to the enterprise. So your point is well taken. If you look at the fact, as we talked about earlier, that compute is now proximal to the data as opposed to the other way around and the emergence of things like mesh networking and high bandwidth local communications, peer-to-peer communications. It's not only changing the physical infrastructure model and the best practices around how to implement that infrastructure. It's also fundamentally changing the way you buy them, the way you consume them, the way you charge for them. So it's, that shift is changing and having a ripple effect across our industry in every sense, whether it's from the financial perspective, the operational perspective, the time to market perspective. It's also, and we talk a lot about industry transformation and disruptors that show up in industry Uber being the most obvious example and just got an industry from the bare metal and recreate it. They are able to do that because they've mastered this new environment where the data is king. How you exploit that data cost-effectively, repeatably, efficiently is what differentiates you from the pack and allows you to create a brand new business model that didn't exist prior. So that's really where every other industry is going. You talked about those big five companies in North America that are the top companies now because of data. I often think about Rewind, you know, 25 years. Do you think Amazon, when they built Amazon, really thought they were gonna be in the food service business, the video surveillance business, the drone business, all these other, the book business, right? Maybe the book business, right? But their architecture had to scale and change and evolve with where that's going all around the data because then they can use these data components and all these other places to get smarter, bigger, and grow faster. And that's why they're one of the top five. So this is a really important point, especially for the young people in our audience. So it used to be that if you were in industry, if you were in healthcare, or you were in financial services, or you were in manufacturing, you were in that business for life. Every industry had its own stack. The sales, the marketing, the R&D, everything was wired to that industry and that industry domain expertise was really not portable across businesses because of data and because of digital transformations, companies like Amazon can get into content, they can get into music, they can get into financial services, they can get into healthcare, they can get into grocery. It's all about that data model being portable across those industries. It's a very powerful concept that you would have. And I mean, IBM owns the weather company, right? So I mean, there's a million examples of traditional businesses that have developed ways to either enter new markets or expand their footprint in existing markets by leveraging new sources of data. So you think about a retailer or a wholesale distributor, they have to vary accurately or as accurately as possible, forecast demand for goods and make sure logistically the goods are in the right place at the right time. Well, there are a million factors that go into that. There's weather, there's population density, there's local cultural phenomena, there's all sorts of things that have to be taken into consideration. Previously, that would be near impossible to do. Now you can sit down, again as an individual maker, I can sit down on my desk and I can craft a model that consumes data from five readily available public APIs or data sets to enhance my forecast and I can then create that model, execute it and give it to my IT guide to go scale out. Okay, so I want to start getting into the infrastructure conversation. Again, remember the premise of this conversation does infrastructure matter. We want to explore that. I want to start at the high level with cloud, multi-cloud specifically. We said cloud 2.0 is about hybrid multi-cloud. I'm going to make a statement so if you guys chime in. My assertion is that multi-cloud has largely been a symptom of multi-vendor. Shadow IT, different developers, different workloads, different lines of business, saying, hey, we want to do stuff in the cloud. It's happened so many times in the IT business. And then how is going to govern it? How is this going to be secure? Who's got access control? On and on and on. What about compliance? What about security? Then they throw it over to IT and they say, hey, help us fix this. And so IT has said, look, we need a strategy around multi-cloud. It's horses for courses. Maybe we go to cloud A for our collaboration software, cloud B for the cognitive stuff, cloud C for the cheap and deep storage. Different workloads for different clouds. But there's got to be a strategy around that. So I think that's kind of point number one. And IT is being asked to kind of clean up this stuff. But the future, today the clouds are loosely coupled. There may be a network that connects them. But there's not a really good way to take data or rather, to take code, ship it to data wherever it lives and have it be a consistent, what you were talking about, an enterprise data plane. That's emerging. And that's kind of really where the opportunity is. And then you maybe move into the control plane and the management piece of it and then bring in the edge. But envision this mesh of clouds, if you will, whether it's on-prem or in the public cloud or some kind of hybrid, where you can take metadata and code, ship it to wherever the data is, leave it there. Much smaller, ship five megabytes of code to a petabyte of data, as opposed to waiting three months to try to ship petabytes over the network. It's not going to work. So that's kind of the spectrum of multi-cloud. Moosely coupled today, going to this tightly coupled mesh. Your guys' thoughts on that? Yeah, that's a great point. And I would add to it or expand it even further to say that it's also driving behavioral, fundamental behavioral and organizational challenges within a lot of organizations and large enterprises. Cloud and this multi-cloud proliferation that you spoke about, one of the other things it's done that we talk about, but probably not enough, is it's almost created this inversion situation where in the past you'd have the business saying to IT, I need this, I need this supply chain application, I need this vendor relationship database, I need this order processing system. Now, with the emergence of this cloud and how easy it is to consume and how cost-effective it is, now you've got the IT guys and the engineers and the designers and the architects and the data scientists pushing ideas to the business. Hey, we can expand our footprint and our reach dramatically if we do this. So you get this much more bi-directional conversation happening now, which frankly, a lot of traditional companies are still working their way through, which is why you don't see 100% cloud adoption everywhere. But it drives those very productive, full-duplex conversations at a level that we've never seen before. I mean, we encounter clients every day who are having these discussions, they're sitting down across the table and IT doesn't just have a seat at the table, they are often deriving the go-to-market strategy. So that's a really interesting transformation that we see as well, in addition to the technology. So there are some amazing things happening, Steve, underneath the covers and the plumbing and infrastructure. And look, we think infrastructure matters, that's kind of why we're here, we're infrastructure guys. But I want to make a point. So for decades, this industry is marked to the cadence of Moore's law. The idea that you can double processing speeds every 18 months, disk drive, processors, disk drives, they followed that curve. You could plot it out. The last 10 years, that started to attenuate. So what happened is chip companies would start putting more cores onto the real estate. Well, they're running out of real estate now. So now what's happening is we've seen this emergence of alternative processors. Largely came from mobile, now you have ARM, doing a lot of offload processing, a lot of the storage processing that's getting offloaded, those are ARM processors. And video with GPUs, powering a lot of AIs. You're even seeing FPGAs, they're simple, they're easy to spin up. A6, making a big comeback. So you're seeing these alternative processors powering things underneath where the x86 is, and of course they're still running applications on x86. So that's one sort of big thing, big change in infrastructure to support this distributed systems. The other is Flash. We saw Flash basically take out spinning disk for all high speed applications. We're seeing the elimination of SCSI, which is a protocol that sits in between the disk, and the rest of the network, that's going away. You're hearing things like NVMe and Rocky and PCIe, basically allowing storage to directly talk to the processor. Now, envision this multi-cloud system where you want to ship metadata and code anywhere. These high speed capabilities interconnects, low latency protocols are what sets that up. So there's technology underneath this, and obviously IBM is an inventor of a lot of this stuff, that is really going to power this next generation of workloads, your comments. Yeah, I think all that 100% true, and I think the one component we're feeding a little bit about even in the infrastructure is the infrastructure software. There's hardware, we talked about a lot of hardware components that are definitely evolving to get us better, stronger, faster, more secure, more reliable, and that sort of thing. And then there's also infrastructure software, so not just the application databases or that sort of thing, but software to manage all this. And I think in a hybrid multi-cloud world, you've got these multiple clouds. For all practical purposes, there's no way around it anymore. Marketing gets more value out of the Google analytic tools in Google's cloud, and developers get more value out of using the tools in AWS. They're going to continue to use that. At the end of the day, I, as a business, though, need to be able to extract the value from all of those things in order to make different business decisions to be able to move faster and surface my clients better. There's hardware that's going to help me accomplish that, and then there are software things about managing that whole set of componentry so that I can maximize the value across that entire stack. And that stack is multiple clouds, plus internal clouds, external clouds, everything. Yeah, so it's a great point. And you're seeing clear examples of companies investing in custom hardware. You see Google has its own chip, Amazon has its own chip, IBM's got Power 9 on and on. But none of this stuff works if you can't manage it. So like I talked before about programmable infrastructure, we talked about the data plane and the control plane. That software that's going to allow us to actually manage these multiple clouds as at least a quasi single entity, something like a logical entity, certainly within workload classes and in Nirvana across the entire network. Well, and the principle, or one of the principle drivers of that evolution, of course, is containerization, right? So the containerization phenomenon, and obviously with our acquisition of Red Hat, we're now very keenly aware and acutely plugged into the whole containerization phenomenon, which is great. You're seeing that becoming almost the, I can't think of a good metaphor, but you're seeing containerization become the vernacular that's being spoken in multiple different types of reference architectures and use case environments that are vastly different in their characteristics. Whether they're high throughput, low latency, whether they're large volume, whether they're edge specific, whether they're more consolidated or hub and spoke models. Containerization is becoming the standard by which those architectures are being developed and with which they're being deployed. So we think we're very well positioned working with that emerging trend and that rapidly developing trend to instrument it in a way that makes it easier to deploy, easier to instrument, easier to develop. So that's key. And I wanna sort of focus now on the relevance of IBM. Can I just tie one thing they're saying? Because that whole containerization thing back to your original point Dave about moving data being very expensive and the fact that the fact that you want to move code out to the data now with containers, microservices, all of that stuff gets a lot easier, development becomes a lot faster and you're actually pushing the speed of business faster. Well, and the other key point is we talked about moving code to the data. As you move the code to the data and run applications anywhere, wherever the data is, using containers, the Kubernetes, et cetera, you don't have to test it. It's going to run assuming you have the standard infrastructure in place to do that and the software to manage it. That's huge because that means business agility. It means better quality and speed. All right, let's talk about IBM. The world is complex. This stuff is not trivial. The more clouds we have, the more edge we have, the more data we have, the more complex it gets. IBM happens to be very good at complex. Three components of the innovation. Cocktail, data, AI and cloud. IBM, your customers have a lot of data. You guys are good with data. It's a very strong analytics business. Artificial intelligence, machine intelligence, you've invested a lot in Watson. That's a key component of your business and cloud. You have a cloud. It's not designed to compete knock heads on the race to zero with the cheap and deep storage clouds. It's designed to really run workloads and applications, but you've got all three ingredients. As well, you're going hard after the multi-cloud world. For you guys, you've got infrastructure underneath. You've got hardware and software to manage that infrastructure, all the modern stuff that we've talked about. That's what's going to power the customer's digital transformations. And we'll talk about that in a moment. But maybe you could expand on that in terms of IBM's relevance. Sure, so again, using the kind of maker, the maker economy metaphor. Bridging from that individual level of innovation and creativity and development to a broadly distributed, globally available workload or information source of some kind. The process of that bridge is about scale and reach. How do you scale it? So that it runs effectively, optimally, is easily managed, all looks and feels the same, falls under the common umbrella of services. And then how do you get it to as many endpoints as possible, whether it's individuals or entities or agencies or whatever, scale and reach. IBM is all about scale and reach. I mean, that's kind of our stock and trade. We are able to take solutions from small, kind of departmental level or kind of skunkworks level and make them large, secure, repeatable, easily managed services and make them as turnkey as possible. Our services organization has been doing it for decades, exceptionally well. Our product portfolio supports that. You talked about Watson and kind of the cognitive computing story. We've been a thought leader in this space for decades. I mean, we didn't just arrive on the scene two years ago when machine learning and deep learning and IOC started to become prominent and say, this sounds interesting, we're gonna plant our flag here. We've been there. We've been there for a long time. So I kind of, from an infrastructure perspective, I kind of like to use the analogy that our whole technology ethos is built on AI. It's built on cognitive computing and sort of adaptive computing. Every one of our portfolio products is imbued with that same capability. So we use it internally. We're kind of built from AI for AI. So maybe that's the answer to this question, but so what do you say to somebody who says, well, I wanna buy my flash storage from Pure. I wanna buy my database from Oracle. I wanna buy my Intel servers from Dell, whatever. And I wanna control them. And I gotta go build it myself. Why should I work with IBM? Do you get that a lot and how do you respond to that, Steve? I think this whole new data economy has opened up a lot of places for data to be stored anywhere. I think at the end of the day, it really comes down to management. And one of the things that I was thinking about as you guys were conversing is the enterprise class or enterprise need for things like security and protection and that sort of thing that rounds out the software stack in our portfolio. One of the things we can bring to the table is, sure, you can buy piece parts and componentry from different people that you want, right? And in that whole notion around fail fast, sure, you can get some new things that might be a little bit faster, that might be here first. But one of the things that IBM takes a lot of pride into is the quality of their delivery of both hardware and software, right? So to me, even though the infrastructure does matter quite a bit, the question is how much and to what degree? So when you look at our core clients, the global 2000, right, they want to fail fast. They want to fail fast securely. They want to fail fast and make sure they're protected. They want to fail fast and make sure they're not accidentally giving away the keys to the kingdom. At the end of the day, a lot of the large vendor, a lot of the large clients that we have need to be able to protect their IP, their brain trust. They're, but also need the flexibility to be creative and create new applications that gain new customer bases. So the way I look at it and when I talk to clients and when I talk to folks is, is we want to give you them that while also making sure they're protected and secure. Now that said, I would just add that and 100% an accurate depiction. The data economy is really changing the way, not only infrastructure is deployed and designed, but the way it can be.  To your point, if you want to go kind of best of breed or you want to have a solution that includes multi-vendor solutions, that's okay. I mean, the whole idea of using, again, for instance, containerization, thinking about Kubernetes and Docker, for instance, as a protocol standard or a platform standard across heterogeneous hardware, that's fine, like we will still support that environment. We believe there are significant additive advantages to looking at IBM as a full solution or a full stack solution provider and our largest, you know, most mission critical application clients are doing that. So we think we can tell a pretty compelling story and I would just finally add that we also often see situations where in the journey from the kind of maker to the largely deployed enterprise class workload, there's a lot of pitfalls along the way and there's companies that will occasionally, you know, bump into one of them and come back six months later and say, okay, we encountered some scalability issues, some security issues, let's talk about how we can develop a new architecture that solves those problems without sacrificing any of our advanced capabilities. All right, let's talk about what this means for customers. So everybody talks about digital transformation and digital business. So what's the difference in a business and a digital business, it's how they use data. In order to leverage data to become one of those incumbent disruptors using Jenny's term, you've got to have a modern infrastructure. If you want to build this multi-cloud, you know, connection point enterprise data pipeline to use your term, Randy, you've got to have modern infrastructure to do that. That's low latency that allows me to ship data to code that allows me to run applications anywhere, leave the data in place, including the edge and really close that gap between those top five data value companies and yourselves. Now, the other piece of that is you don't want to waste a lot of time and money managing infrastructure. You've got to have intelligence infrastructure, you've got to use modern infrastructure and you've got to redeploy those labor assets toward higher value, more productive for the company activities. So we all know IT labor is a choke point and we spend more on IT labor, managing loans, provisioning servers, tuning databases, all that stuff. That's got to change in order for you to fund digital transformations. So that to me is the big takeaway as to what it means for customers. And we talk about that, sorry, we talk about that all the time and specifically in the context of the enterprise data pipeline and within that pipeline, kind of the newer generation, machine learning, deep learning, cognitive workload phases. The data scientists who are involved at various stages along the process are obviously kind of scarce resources, they're very expensive. So you can't afford for them to be burning cycles, managing environments, spinning up VMs and moving data around and creating working sets and enriching metadata. That's not the best use of their time. So we've developed a portfolio of solutions specifically designed to optimize them as a resource, as a very valuable resource. So I would vehemently agree with your premise. We talk about the rise of the infrastructure developer. So at the end of the day, I'm glad you brought this topic up because it's not just customers, it's personas. IBM talks to different personas within our client base or our prospect base about why is this infrastructure important to them? And one of the core components is skill. When we talk about this rise of the infrastructure developer, what we mean is I need to be able to build composable, intelligent, programmatic infrastructure that I as IT can set up, not have to worry about a lot of risk about it breaking and have to do a lot of troubleshooting, but turn the keys over to the users now. Let them use the infrastructure in such a way that helps them get their job done better, faster, stronger, but still keeps the business protected. So don't make copies into production and screw stuff up there. But if I want to make a copy of the data, feel free, go ahead and put it in a place that's safe and secure and it won't get stolen and it also won't bring down the enterprise as it's trying to do its business. Very key, key components to, we talk about AI infused data protection, AI infused storage. At the end of the day, what is an AI infused data center? It needs to be an intelligent data center and I don't have to spend a lot of time doing it. The new IT person doesn't want to be troubleshooting all day long. They want to be in looking at things like ARM and VME. What's that going to do for my business to make me more competitive? That's where IT wants to be focused. Yeah, and it's also, just to kind of again, build on this whole idea. We haven't talked a lot about it, but there's obviously a cost element to all this, right? I mean, enterprises are still very cost conscious and they're still trying to manage budgets and they don't have an unlimited amount of capital resources. So things like the ability to do fractional consumption. So buy, you know, paper drink, right? Buy small bits of infrastructure and deploy them as you need. And also to Steve's point, and this is really Steve's kind of area of expertise and where he's a thought leader is kind of data efficiency. You also can't afford to have copy sprawl, excessive data movement, poor production schemes, slow recovery times and recall times. You've got to, especially as data volumes are ramping, you know, geometrically, the efficiency piece and the cost piece is absolutely relevant. And that's another one of the things that often gets lost in translation between kind of the maker level and the deployment level. So I wanted to do a little thought exercise.  Cloud 2.0 is also about, we're moving from a world of remote cloud services to one where you have this mesh, which is ubiquitous of digital services.  So all these digital services, what am I talking about? AI, blockchain, 3D printing, autonomous vehicles, edge computing, quantum, RPA and all the other things in the Gardner hype cycle. You'll be able to procure these as services. They're part of this mesh. So here's the thought exercise. When do you think that owning and driving your own vehicle is no longer going to be the norm? All right. Interesting thesis question. Okay, answer if you like. Why do you ask the question? Well, because these are some of the disruptions. So the questions are designed to get you thinking about the potential disruptions. You know, is it possible that our children's children aren't going to be driving their own car? It's a cultural change. When I was 16 years old, I couldn't wait. But you're starting to see a shift their quasi-autonomous vehicles. It's all sort of the rage. Personally, I don't think they're quite ready yet, but it's on the horizon. Okay, I'll give you another one. When will machines be able to make better diagnoses than doctors? Actually, both of those are, so let's hit on autonomous and self-driving vehicles first. I agree that they're not there yet. I will say that we have a pretty thriving business practice and competency around working with ADAS providers. And there's an interesting perception that ADAS autonomous driving projects are like there's 10 of them around the world, right? Maybe there's 10 metal level ADAS projects around the world. What people often don't see is there is a gigantic ecosystem building around ADAS, all the data sourcing, all the telemetry, all the hardware, all the network support, all the services. I mean, building around this is phenomenal and it's growing at a ridiculous rate. So we're very hooked into that. We see tremendous growth opportunities there. If I had to guess, I would say within 10 to 12 years, there will be functionally capable, viable autonomous vehicles, not everywhere, but they will be, you will be able as a consumer to purchase one. Yeah, that's good. Okay, and so that's good. I agree, the timeline is not within the next three to five years. All right, how about retail stores? Will retail stores largely disappear? Where, Randy and I were just someplace the other day and I said, then there used to be a brick and mortar there and we were walking through the Cambridge side of Galleria and now the third floor, there's no more stores, right? Up there is gonna be all offices. They've shrunk it down to just two floors of stores and I highly believe that it's because the retailers online are doing so well. I mean, think about, it used to be tricky and how do you get in and I need the Walmart mentality, go get with Amazon and that became very difficult. Look at places like Bombus or Casper or all the luggage plate, all this little individual boutique selling online, selling quickly, never having to have to open up a store, speed of deployment, speed of product, I mean, it's phenomenal. Yeah, and frankly, if Amazon could, and they're investing billions of dollars and they're trying to solve the last mile problem, if Amazon could figure out a way to deliver 95% of their product catalog prime within four to six hours, brick and mortar stores would literally disappear within a month and I think that's a factual statement. Okay, I'll give you another one. Well, banks lose control, traditional banks lose control of the payment systems.  Yeah, that's another one with an interesting philosophical element to it, because people and some of it's generational, right? Like our parents' generation would be horrified by the thought of taking a picture of a check or using blockchain or some kind of a fintech payment service. Or any Bitcoin. Right, Bitcoin. Or any kind of, yeah, exactly. You guys own Bitcoin? I do, my dad asked me. You own Bitcoin? I do. I own Bitcoin too. We're here. So we're here. We're old. And we're hip. We're waiting it out though, it's fine. By the way, I just wanted to mention that we don't hang out in the mall that's actually right across the street from our office. I want us to just add that to the previous comment. So there is a philosophical piece of it though. Like our generation, we're fairly comfortable now because we've grown up in a sense with these technologies being adopted. Our children, the concept of going to a bank for them will be foreign. I mean, it will make, if they'll have no context for the context, for the process of going to speak face to face to another human that just won't exist. Well, will automation, whether it's robotic process automation, other automation, 3D printing, will that begin to swing the pendulum back to onshore manufacturing? Maybe Terrace will help too. But again, the idea that machine intelligence increasingly will disrupt businesses, there's no industry that's safe from disruption because of the data context that we talked about before.  And as a sales rep, you're in the field and you're trying to think about, okay, what does that mean? What does that mean for me to explain to my customer? So we put together this whole thing about what does transformation mean? One was the taxi service, right? And the other one was retail. So another one was FinServe. I mean, you're hitting on all the core things, right? But this transformation, I mean, it goes so deep and so wide. When you think about exactly what Randy said before about Uber just transforming just the taxi business, retailers and taxis now and hotel chains and that sort of thing. The know your customer, they're getting all of that from data, data that I'm putting in. Not that they're doing work to extract out of me that I'm putting in. So that autonomous vehicle comes to pick up Steve Keniston. It knows that Steve likes iced coffee on his way to work, gives me a coupon on a screen. I hit the button. It automatically stops at Starbucks for me and it pre-ordered it for me. You're talking about that whole ecosystem wrapped around just autonomous vehicles and data now? It's unbelievable. Yeah, and we're not far off from the minority report era of anthropomorphic advertising targeted at an individual in real time. I mean, that's gonna happen. It's almost there now. I mean, to Steve's point, you will get, if I walk into Starbucks, my phone says, hey, why don't you use some points while you're here, Randy? So that's happening. And facial recognition, it's all coming together. And again, underneath all this is infrastructure. So infrastructure clearly matters. If you don't have the infrastructure to power these new workloads, you're in trouble. Yeah, and I would just add, and I think we're all in agreement on that. And from my perspective, from an IBM perspective, through my eyes, I would say, we're increasingly being viewed as kind of an arms dealer and that's probably a horrible analogy, but we're being viewed as a supplier to the providers of those services, right? So we provide the raw materials and the machinery and the tooling that enables those innovators to create those new services and do it quickly, securely, reliably, repeatedly at a reasonable cost, right? So it's a step back from direct engagement with customers and clients and architects, but that's where our whole industry is going, right? We are increasingly more abstracted from the end consumer. We're dealing with the sort of assembly. We're dealing with the assemblers. They take the pieces and assemble them and deliver the services. So we're not as often doing the assembly as we are providing the raw materials. Guys, great conversation. I think we set a record in terms of the industry. I'd like to say thank you very much for coming on. No problem, thanks, Dave. Yeah, this was great. Thank you so much. Thank you for watching, everybody. We'll see you next time. You're watching The Cube.


Boom What's up money geeks? Mr. V here welcome to another video guys So in this video we are going to talk about tickets and bought see our C H torch light energy So this is one that we cover here on the channel and we've talked about it I recommended the stock told you guys I love a lot of the direction that these companies go until That's why I said it buying the stock So today there's been some movement and people were you know sending me messages asking me what to do next So that's what I want us to talk about it But before we get started guys via new to the channel We talked about how to earn money how to save money how to invest and build wealth So if that's something that interests you go ahead and hit that subscribe button and your notification belt So you don't miss out on your content. So guys when it comes to torchlight No energy. I told you guys when they announced that they were going to partner or merge with Metamateria so torchlight itself is got like a natural gas company But I was looking at the deal that they had with meta material So they were moving from natural gas slowly into clean tech and meta material was a really good partner with them because Metamateria as a company develops really excellent materials that are used for No different industries. No like aerospace and defense and you can see them in Automotives so they build all these different technologies and their materials Like next level. That's what I call them meta materials and also they're bringing in all these nano technology in the material space So if you can look at the company meta material Look at the industries that they service it gives you a hint as to why the company is poised to succeed They're not just narrow-minded. So we have aerospace and defense. They have automotive. They have consumer electronics They have energy which is huge because in the clean energy space They the material really does help with solar panels. They absorb even more energy and they're in the medical space So overall meta material Really has you know the technology that's gonna put them At least in the clean tech space for the future. So the merger was actually announced last year But as of this year torchlight energy, it seems we can find that so Toshlight energy that was September of 2021. That's when they announced that merger with meta material But they right now they have actually mentioned the fact that there they would merge by the end of the month So I might even see a little spike in this stock again To was the end of the month But remember guys just about a month ago or month and a half ago when I did a video here on the channel I did my top five stocks under five dollars Toshlight energy was number one on that list and at that point the stock was trading at about a dollar 40 or dollar 50 so for those of you guys that bought this stuff back then you're doing pretty good and congratulations For this massive win and then so the questions I've been getting from some of you guys is what do I do next with this? So here is what I usually tell people and I do it myself if you invest in a particular stock And that stock mustn't double. So you are a hundred percent in profit or two hundred percent in profit Let's say you bought it at a dollar fifty what I would do is I would take out my initial investment and a little bit of profit and Use that money now to go find my next victim And then I just leave the rest in that stock because again This stock has a long-term potential and that's why I'm holding it long term because I see the potential there So take out your initial investment and some profit if you can afford it and then use that so you can find another stock and Invested and that's how you continue to grow that account So don't be greedy savages when you see opportunities like this take advantage of it and the thing that I want you to take A little bit of profit is because this stock is running Based on the fact that the company just announced everything bring it up here So the company just announced that they're declaring a special preferred dividends And so a lot of people are not jumping and buying so the special preferred dividends right now If you are a shareholder of record as of June 24th, so that's coming up You'll be entitled to receive one share of series a preferred stock on a one-for-one Basis so that's that's good for shareholders again for me. I'm looking at these long terms I don't really care about this gives either way I'm holding the stock so and one important thing is that the company also announced that The deal with meta material will close by the end of the month So the end of this month you would see that deal come to fruition, which is sweet So I like the fact that they're making this progress and moving in the right direction I'm still in love for the company as far as the fundamental the fact that Torchlight right now is debt-free to me that is I mean that's a sign of a healthy company Not having any debt So I like the move even this shot squeeze here is good for some quick profit as a matter of fact I actually day-traded it today made some profit, but long term. I'm still holding I expect a pullback after that merger To you know, bring the stock back to where it belongs and I want to see the fundamentals of Metamaterial their products and actually some profitability start driving the stock in the right direction That's where you could become confident that it's actually moving the right direction for right now is moving because There is this news about the stock The dividends and also it's actually the meme Movement kind of pushing it a little bit. So I would definitely secure profit if you were string trading this one Maybe right now is a good time to start looking at putting Trailing stop or maybe a stop loss slash take profit for a bracket order So that's what I would do again for a quick recap here torchlight and meta-material Merger is probably gonna complete at the end of the month and then torchlight has actually announced kind of a special Dividends for preferred stocks and so if you hold the stock and by the end of January 24th You should be entitled to receive one share of your series a preferred stock On a one for one basis. So that's good again. Let me know in the comment section what you guys think about is Again, if you're new to the channel, we talk about how to earn money how to save money How to invest and build wealth if that's something that interests you go ahead and hit that subscribe button and the notification bell So you don't miss out on your content also guys if you're looking to get there with investing Webo has their promotion where if you sign up and deposit a hundred dollars You get free stocks links in the description below and as always guys. Do your due diligence.


Thank you ladies and gentlemen. I'd like to talk about the Helmau Mount in Central Poland. This is the work of a team of collaborators of Jezo Cittore, who was the leader of the project, because he was responsible for geomorphology and geochemistry and myself for the geophysics. This slide you can see how the area looks from an aerial view. It's a really impressive hill for the area of Central Poland which is relatively flat and there's a scene from far away, a really impressive forested hill that imposes itself over 200 meters on the area around it. It's seen from quite far away and this place has been a subject of archaeological interest as it is home to a hill fort or a stronghold which is dated to the early medieval. As you can see, we started this project over here because of cultural heritage management regions as it's a really important and quite original archaeological site in the area, but not much is known about it except that it exists and unfortunately it has fallen to chlorine which is visible in these areas over here and you can see how the chlorine and forestation of this area has been going on at least since the 1940s on this as you can see on this archival picture, aerial picture. Basically it's a really big problem because this is quite an extensive area, quite a large archaeological site and the quarrying is quite serious. It's going on, it's still taking place and it's expanding so we need to do something to see if the areas that are potentially liable for quarrying perhaps need some form of legal protection as an archaeological monument. We started this research from acquiring lidar data as is I guess the most typical and the method that opened woodlands to Polish archaeologists since it appeared for free on the internet and caught everyone by surprise. You can have this data has been acquired for for non-archeological purposes, the entire country's can now probably many people will be talking about it so I won't go into details and the point cloud was visualized, created a DEM and visualized and of course I guess depending on who you are if you're a more of a geography type of person you'll probably see the really visible quarrying over here and if you're an archaeologist you'll probably notice the impressive quite impressive rapids and quite well preserved. The central one towering over well three meters in the terrain which is quite a rare thing because most hill forts and strongholds from this in this area are in lowlands and they have been subject to destruction plowing and various other agro-technical activities which have influenced their state of preservation. This is not the case here and in fact even before any any fieldwork was started the new data the amount of new data arriving from this lidar data set was was extremely huge as we can see a few in this area, a few other previously unknown delimitations, fortifications however you may call them where we're not noticed by us. This is a quite an important place in the history of Poland as it has been described by the Polish famous Polish chronicle Janusz Lwogelius and he names this place as a important important center of administration of the of the Polish early medieval Polish state and in fact even even now even until recently it's been used in it has even a symbolical meaning it's quite an interesting place if you go there it's a bit magical maybe that's not too scientific but it's really interesting quiet and special place and just at the base of these ramparts and you get rock carvings made by people from the 19th century asking god to give Poland buckets independence so it was a place of pilgrimage of various people praying for for various stuff before before this project it was studied by rescue excavations of Janina Kaminska which were she basically was looking for the chronological differentiation of the area which is always was a really important aspect of studying hillforts in strongholds and she noted in some limited small-scale really small-scale excavations in the chronicle stratigraphy that she proposed two phases of the hillfort from the 10th century 11th to 13th century Jerzy Sikora in 2004 and 2005 before the invention of Ilar was interested in this place and also did some field walking that revealed previously unknown outer outer ramparts this has been a part of a larger program that we have been conducting with this team since 2013 I think and this was started in 2013 and it encompassed this the study of the topic of medieval strongholds and hillforts in the area of central Poland and this was a non-invasive project with the use of non-invasive methods remote sensing geophysics field walking geochemistry etc and some more light visualizations which are quite important in the differentiation of archaeological features because what most people use are hill shaded DEMs which are quite good but in the context of terrain forms that have high changes in the topography the hill shades have this quite serious drawback that they the artificially created shadow obscures certain features in the shadows and special areas located on on slopes so we also have been using generally open source software for crew after acquiring the data cloud the point cloud for creation of DEM models in this case are done in saga and also in a really visualization toolbox which is really a really a great tool and just a comparison why this why we chose this area as topic of our presentation is indeed the medieval strongholds in this area and generally are quite so relatively small features this is all in one scale as you can see this is the the Mount Helmow stronghold which is a really impressive and really quite a landscape feature which is quite suitable for large-scale non-invasive perspective but there is one problem doing the lidar doing all the field walking is a really great thing and it has opened us for woodland archaeology which was previously a blank area for for Polish archaeologists basically and I remember doing surveys in heavy forested areas before lidar and basically even if someone is really good in the field it's getting lost is quite easy but there's another problem because our program of non-invasive research of these filipers included geophysics and this is quite quite some time ago maybe perhaps it won't be to it won't be not true if we say what a big pioneering is for that and not a lot of large-scale geophysics were done in forested areas generally a really difficult area for geophysics which is really important to remember because you've got lots of sources of noise and lots of sources that do not allow you to carry out the surveys in a continuous manner which I think is the most important thing for the geophysical results is that the results are not one small area over here one small area over there is there in the continuity and this was indeed the problem here and I just like to note that it's really important to choose the right time of year because our first attempt at this area was in May of 2013 which was not a good idea because it basically didn't look like this at the time I guess and there wasn't Vietnam but that's the way I imagine it looked and nothing could be done and fortunately we had the the ledger of postponing that and now you can see it basically at the end of November yeah at the end of November so at the end of November it actually quite well was quite nice doing these surveys the trees if they're not too dense they're not really a big problem for doing the measurements the biggest problem in my opinion are the small kind of bushes and those kind of areas but fortunately even though this is a protected area protected ecological area these can be cut out so I guess it's really important to choose the right time of year and the right kind of preparation in order to do this there's the results encompassing over five hectares of magnetic radiometry which is this method used with a small scale sensor just like to add that in geophysics there's now a fashion and really good progress progressive thing happening that people are having more and more sensors with mobile mobilized hearts and stuff like that you won't really get to use that in a forest so handheld systems are also quite a good idea to use and these are the results which I'd like to just quickly go over and the question is usually at that time when we were doing the surveys a lot of people were asking us yeah but why are you doing everything is no we can see the ramparts we can see everything and that was that's a question that appears quite often not only in areas with visible topography but generally with regards to geophysics and I can say that it was really really worth it we didn't know what will happen because that's usually a question that appears how do you think the survey will go and the right answer you should give is I don't know we will see and we saw that our work really really paid off lots of interesting data not only from a purely archaeological perspective but we can see that the noisy background of the bedrock shallow bedrock which is an important piece of information for us to note that there's a lot of the background is magnetic so there might not be a lot of contrasts the most important aspect of this research was in fact that even though the most prevalent data was from the ramparts we actually got to see the construction within the magnetic data of how they were created and calibrating this information with a lot of excavations from similar medieval ramparts we could propose basically perhaps how these ramparts were created and with what material of course there were some features that are not too clearly visible but for instance this kind of outline enclosure over here which is not a terrain form it's a purely sub subterranean feature which is not previously known and some areas that suggest the sunken features which was one of the big questions and generally a big research question regarding the teleports were they used were they used as constant habitation in settlements or were they used for defensive purposes or ritual purposes because there's not a lot of pottery found there and also other landscape features which you can't really register in any other method that which didn't really come out really that well in other methods which are visible here linear feature really really small amplitude anomalies that lead to certain areas that we propose there are dates and this is the zoom in on this area so these are this is the area of the outline ramparts that were previously unknown there's quite a challenge to do these measurements over here because of a slope and this area started looking more getting lots of you know low vegetation over here so and the really dangerous area where you could easily kill yourself if you wanted to or not wanted to even of the creeping endangering and destructive force of the contemporary and historical quarry we also tried some earth resistance which is a different method as you can see a lot of features were discovered over here all these black spots for the lower visibility areas these are actually this is a really big problem and in the woodland survey with this method of earth resistance is that this is actually the root system of trees which I guess it must be really interesting for people who study trees but maybe not exactly correct this is a form of noise so that was a really big problem taking all of this into account we created an integrated geophysical dataset so creating a kind of landscape approach to it with other features that could be read out from this data in potential guard towers so from and geochemistry provided really interesting results with a simplified field method of phosphate analysis which showed that in fact the phosphate was quite high which suggested a constant adaptation of this area the pottery which due to the lack of plowing was not too visible on this area was not to you didn't create a comprehensive dataset that really didn't put anything significant into our study but this was carried out nonetheless and this is the our summary of what we know based on only on purely and solely geophysical approaches to the area as a as a personal note this was a this survey was quite a challenge and there were a lot of questions being asked what will happen what will be done there's also if you take geophysical a number of ways of handbooks some people even write it you can't do geophysics in the forest and I guess not because it's legal and they will shoot you but that it's impossible due to the terrain obstacles so I guess the important lesson of the lesson we learned is that you have to be kind of elastic you these preconceptions that we have of various methods are quite important we should treat them seriously but each place requires a specific approach and this approach even despite that it was a challenge yielded a new interpretation a really significant amount of archaeologically sensitive data and important data for the heritage management of this area and perhaps better protection and basically it gave us a lot more than those small-scale excavations in the 50s that were carried out but again in the 50s these possibilities didn't exist thank you for your attention