People want faster decisions. They want decisions in near real time. And a lot of the talk today about big data is really focused on bringing that real time like capability to big data. What's the best way to do that? A lot of people equate Hadoop with big data. A lot of people are trying to bring SQL capabilities to Hadoop. Well, there's more to big data than Hadoop. And we're here with Bernie Spang of IBM to talk about that. Bernie is the director of strategy and marketing at IBM database and software systems. He's up here from New York at the Wikibon offices. Hi, everybody, I'm Dave Vellante. Bernie, welcome back to theCUBE. Thank you, Dave. Good to be here. So we last talked to you live at IBM's IOD, which was a fantastic event. I've said a number of times that IBM is basically taking its analytics business and really super glued it to the big data meme. And it's done a tremendous job of that. According to Wikibon, the number one big data player. And you really got there through a series of hard work, acquisitions, a lot of thinking, building out a great portfolio, leveraging your excellent services business to really begin to solve customer problems. So it didn't happen overnight, but the market really is favoring... The wind is at your back, as they say. Yeah, well, first of all, thank you for that. And I'd agree. One of the important things that we've done and is having an impact amongst our clients is looking at the complete problem. It's not just about data. It's not just about analytics. And it's not just about any one technique. So when we look at big data analytics, if you put those things together, one way to think about it is it's the tops on bottoms. I mean, having great analytics without the data systems to support it gets you nowhere. And having great data systems without applying the innovative analytics gets you nowhere. So you need both of those things. And when we talk about big data, we mean all data and all paradigms that you're going to apply to get value, business value from that data. Yeah, so when I talk about big data and the Wikibon definition is essentially data that is either too big or too fast or too different that you can't handle it in traditional ways. And I think that's, you know... That's fair. It's a vague definition, but it's a good one. It means you've got to do something different. And of course, Hadoop is different. You've got function shipping, and so that's why I think a lot of people equate Hadoop with big data. And I know personally my first entry into the big data world came through Hadoop. But there's much more to it than that. Talk about that a little bit. Yeah, certainly. And I agree. A lot of people, the first thing they were exposed to beyond traditional relational database management was Hadoop as a new paradigm. But there are others. There's time, sorry, streams computing, analyzing data in motion that never even lands on a storage device. So before you persisted, you're actually analyzing it and making decisions. And it gets back to your point about too fast, right? And too much. I mean, if you're talking about, you know, our great example, if you're talking about telemetry coming from medical devices, right? And our great advertisement that we had, you know, the example of one of our clients, a neonatal care unit, analyzing the telemetry coming off 17 different monitors for each newborn in the thing. You know, doctors and nurses used to look at those data points every 20, 30 minutes and write notes and look for patterns. Now you do that on the fly and you can never store all that data and analyze it over time and get an answer in time to make a difference. Now with this kind of stream processing, they're finding life-threatening infection up to 24 hours faster than they were able to before. And it still makes the hair on the back of my neck stand up whenever I tell this story because you think about that's reality, a big data and applying it to the real world that makes a difference. Well, and of course the smarter planning initiative is, you know, the inference when you watch those commercials is okay, I got machines making decisions and machines can make decisions a lot faster than humans and I know it's not just machines, but that's different. So I think we agree on that. Yeah. Good. Now let's talk about the role of our DBMS in this whole big data space. You guys have announced blue acceleration, you've got a growing portfolio. Before we dig into blue acceleration, let's talk a little bit about our DBMS. Does that fit into big data? Yeah, certainly. And actually I just did some recent blogging on exactly this point. What role does a relational database system have in big data? I'll do you one better. I mean, we've got our IMS system that's been powering the biggest, most complex, high performance applications around the world for 40 years now. And when the IMS team looks at some of these data channels that people are talking about, wow, look at this big data thing, they chuckle, because it still pales in comparison to the volume of velocity. Now that's a pre-relational system. Okay, so now you got the relational system. So my answer is the same across all these. We don't wanna throw the baby out of the bathwater. You don't wanna repeat the same mistake. All those people when mid-range and PCs came around up, the mainframe's dead. Nobody needs a mainframe anymore because look at all these things we can do with these other systems. And the reality of it is we've been growing mainframe mips every year since the death was declared. And we continue to grow new clients using system Z. So what's the moral of that story? Just because there's a new tool that does something new and better than the old one, doesn't mean it does everything new and better than the old one. It's about using the right best tool for each job. And the relational database system still does things better than any other type of data system. When you're talking about the kinds of work it was designed to do, like running SAP transactional workloads or loss and in for any of the ERP examples would be one good example. Now, that doesn't mean that system and the relational database system should stand still. You also want to extend and enhance it for these new demands, the higher performance. And so that's where blue acceleration comes in. Yeah, so the advantage, of course, is you've got, we love, of course, SiliconANGLE Wikibon. We love the disruption. We love things like Hadoop. We love things like NoSQL. It's helping make the database market interesting. We're seeing it five, six, seven years ago. It wasn't that interesting. And now it's like the hottest thing going. But at the same time, you've got this trillion dollars of IT investment built up and maybe it's multiple trillions and people just can't rip and replace. So you've got existing clients that are saying, okay, help me. I need to get from point A to point B without disrupting my business. How do I, I hear that from CIOs all the time. That's what I care about. So talk about blue acceleration. Where did it come from? How does it fit into the whole DB2 piece? Okay, so first of all, blue acceleration is actually a set of technology innovations that came from a collaboration with IBM Research and our development labs. There are actually 10 labs around the world involved in this. More than 25 patents have been filed for these innovations and it includes in memory or dynamic in memory columnar data management. And by dynamic in memory, you mean it's processing the data in memory but it has the intelligence to dynamically move data from storage into memory as it's needed. So you're not limited to in memory only and you don't have performance degradation if your data set is bigger than your available memory. That's an important differentiation of why we call it dynamic in memory. It's columnar processing and storage of data as opposed to traditional row based for the relational. And again, right tool for each job. The, for certain types of scan work and analytics work, the columnar based storage is much more efficient and you can do better compression and better cluster processing. But there's more than that. There's also parallel vector processing innovations in blue. So fanning the work across multiple processors and then using the advances in the modern chip technology and IBM Power chips and Intel x86 chips to be able to load multiple data sets for each instruction. So you're able to do parallel processing in every instruction cycle and then you fan that out across multiple cores. Then we've got actionable compression. So not only do you get the benefit of compression from columnar storage, but now we've got patented actionable compression which actually enables the processing and work in doing analytics on the compressed data without having to decompress it. So that not only adds to the space savings with the compression value, but adds to the performance boost. And then finally data skipping would be the fourth technology advantage. And that's the intelligence to know where you can skip entire sections of data and not have to process it. So you think in terms of compressing it into memory, doing columnar processing, so you can focus on the particular column you worry about that filters the data. You do data skipping that further reduces the amount of data you're processing. And then you fan out the resulting work on multiple processors and you load each processor core up with multiple data sets. So all these things build up to deliver what we've seen in early clients and partners have seen eight to 25 times faster on complete analytics workloads and specific analytic queries. We've seen more than 1,000 times faster with this technique. So what are you measuring, eight to 25X or 1,000? As you're talking about sort of wall clock time to complete a task? Yeah, in that case you're talking about running a report or doing a complex analytics query in context with answering a question. So it gets back to your point, right? This is all about getting faster answers so you can make better decisions. So even if you take the eight times faster number not the 25 times faster, think of today where you might have a client may have an analytic workload that runs all day, right? And the 25 times face 24 hours to get an answer back. Well, what if that's only an hour? How many more questions can you ask in the day, right? How many more answers are you gonna get and you're making decisions within the day as opposed to the next day based on yesterday's data? That's where this gets exciting. And because of the compression capabilities and the dynamic in memory nature, we're talking about terabytes and into the tens of terabytes of data for this kind of speed of thought analytics. And when you couple this with our Cognos BI software as an example, you're talking about the difference between I wanna see this report click, let me go get a cup of coffee or go out to lunch. When I come back, I'll have the report to look at versus click, there's the answer. Oh, I see that, huh? Now I wanna see it over here. Click, now I get the refresh. It's that speed of thought analytics that's gonna enable clients to do more things faster. I had Steve Mills on theCUBE down at 590 Madison Avenue a couple of weeks ago. He had this big flash announcement. I wanna ask you about flash a little later on, but one of the things he said, Mills is awesome, he said that, hey look, in memory, technology's been around since there's been memory. But so why are we suddenly talking about it so much now? What has changed so that it's really come to the fore? I mean, everybody's talking about it in memory. So a couple of things. First of all, memory itself has, the cost has come down. So you can have more memory, therefore you can load more data in memory and do more things with it. So that's a fundamental thing. But the real big difference is that when most people are talking about this in-memory excitement and these in-memory databases, they're really using that as a shorthand for in-memory columnar. And it's this columnar-based approach instead of the row-based approach coupled with being able to process it in memory. That is the big advantage on the speed here. And that's really what people are excited about. It's that dramatically faster answer. Now the other thing is it's also dramatically easier. It's much simpler. And that's another important value of the blue acceleration. It's not just speed, it's also simplicity.  And you get top performance automatically. There's no building indices, aggregates, there's no ongoing database tuning. Like you have to do if you're doing analytics against your traditional row-based approach. And it's this dramatic difference that is why, I'm running into analysts who are surprising me because they're talking about this capability among the set of no-SQL technologies, which had me scratch in my head the first time. I said, wait, it's still SQL. The SQL doesn't change. It's still relational data management. It's the same schema. It's just a different storage model and this columnar processing. And they say, yeah, but to your point, it's a dramatically different technology, a different approach that now enables me to do things faster, cheaper, simpler than I've ever been able to do. No, without any application changes. Yeah, in this case, right, and that gets back to your point of the CIA. How do I get from here to there? And why do we put blue acceleration in DB2? And we've declared when we announced this that this technology is starting out and being introduced in DB2 for the reporting and analytics workload, but we're gonna expand it for other types of data workloads and then other products. And I can tell you how we're using it in Informix already next. But the point being, if I don't have to move the data out and get a completely different system that I set up, why should I? Why add the complexity and the cost? And the beautiful thing about blue acceleration is you can have within a single database, row-based tables, columnar-based tables, all in the same database, all accessed with the same SQL. But you optimize it, so the tables that are being used for analytics and reporting are optimized in columnar form and the tables that are required for operational or transactional updates are in the row-based form, so you get the best performance. Yeah, so that's an interesting subtle, sort of nuanced, but it's an interesting part of the value proposition. So I want to come back to the value proposition, but before we do, the way I want to get there is to talk a little bit about something that you just said, which is, you know, the databases today, if you think about databases, and I'd love to sort of test this on you, I mean, they're relatively small, if you think about it. You try to avoid calls on them, because you don't want to go to disk, because disk kills performance, but now within memory technologies, that starts to change flashes. It's changing that as well. How do you see this type of capability changing the way in which databases will be designed in the future, the amount of data that I can bring into databases, and how will that affect processes? Because processes are pretty rigidly built up around databases today. Do you see that change? Oh, it definitely will change. And, you know, our client and partner that were at our launch, I think really captured the story well. So we had one of our clients, Ken Collins from BNSF Railway, was talking about his experience with Blue, and he tried to break it, tried to throw, you know, bad sequel.   And it was coming back in seconds when he was working against Blue. And he said, you know, it's making me wonder, is there anything, is there a bad sequel anymore? Do you have to do this tuning and have sequel specialists? Because if even bad sequel can come back with an answer in a matter of seconds, it changes the paradigm. And when you can fit so much data in memory, and even when it doesn't fit in memory, it can be in flash, which takes away the disk, you know, issue. And because it's dynamic in memory, what I talked about with Blue Acceleration, it's all handled by the system. You don't have to worry about where it is. It completely changes the amount of data you can use this technology on. And that's where it comes into the big data. So back to your question of, so how does a relational database fit in big data? Because, geez, we, you know, we don't put more than a terabyte in our relational database because it's slow. Well, that's the old one. That's your grandfather's relational database system. And that's what's different now when you bring in things like Blue Acceleration. Okay, so we're talking, let's go back to the value proposition. We're talking speed, we're talking simplicity. Give us some, you know, and to say whatever else you want about the value prop, the sort of economics of this, but then tie it to some examples. And specifically, if you can talk about some examples with Blue Acceleration. Yeah, so the other one I'll mention is, you know, we had our partner Temenos, banking, core banking software. And the discussion there was about all the financial banking data. So talk about, this is structured data. This is not unstructured social, you know, none of that domain. This is all real financial structured data. And he was talking about the volume of data that exists, what he referred to as gold dust data. It's in these systems that you can't touch. You can't apply analytics to it because of the performance requirements and the operational and the security. And they don't have the time or resources to be able to set up warehouses to do analytics on this data, but they know there's value in that data if they could just analyze it. And he was talking about how when they're testing, they're bringing the Blue Acceleration capabilities to bear here, because it can be within the same database system. And they can have the row based approach to optimize for the transactional performance, but now they can actually, you know, I call it snapshot data marts, right? You can take a snapshot of the transactional operational data in the same system and now put it in a columnar blue, what we refer to as a blue table, and get this second or sub-second response time to these complex queries that up until now you just couldn't do. And he was excited, you know, for Temenos and bringing this capability to their software because they intend to provide capabilities in their software that enabled their customers, the banks, to provide services to their clients, to provide new services for marketing and sales and being able to take that data and offer it as value, whole new revenue streams are possible. Another area to look is in Telcom, right? The gold dust data that exists in all the calls and tweets and, you know, the text messages and everything, you know, that can be monetized if you can get at all and analyze it and do reporting on it, that's of value.  Do you have all these assets in your portfolio? Tie it together with us and help us better understand IBM's how they fit together in the overall strategy? Sure, just a quick thing, just to hit on the ones we haven't talked about. So the time series capability in Informix is another great example of no SQL technology. It's not standard SQL relational tables, it's really an optimized system for time series or time stamp data and Informix also has a spatial database capability. So when you talk about the big data challenge of dealing with data from meters, smart meters and sensors that are time stamped and location stamped, we see clients who are using traditional relational approach, relational database approach on that. Those systems are just falling over as they scale up the number of meters and sensors and whatnot. It just doesn't work. So it's another great big data no SQL example where if you apply the right tool to the job, dramatically faster performance, two to five times faster using half to a fifth of the processor cores and requiring a half to a third of the storage space. So now all of a sudden you can do, capture a lot more of this data and do reporting and analytics on it than you could ever afford to do before. Another great example. The big insights is our Hadoop-based capability, right? I mean, I'm a fan of reminding people that big data does not equal Hadoop, but let's not forget Hadoop is an important part of the big data story. InfoSphere Streams does the stream processing on data in motion. And then these are what I just outlined are software. So these are multi-platform software offerings. And then what we've done with our pure data system, which is a part of the pure system family, is you take the software and integrate it with hardware into an integrated system, building expertise, targeting a specific workload, have a single integrated management of the system, support, et cetera, what we refer to as expert integrated systems, right? That delivers appliance simplicity, rapid time to value ease of management by having that integrated package, right? And we've got pure data systems that are optimized for transactions, for analytics, for operational analytics. And the most recent one we announced was the pure data system for Hadoop. So we've got software and systems, why? Because some of our clients need the flexibility of multi-platform software to do their custom solutions. We've got clients who want the appliance simplicity of an integrated system. And the time value that delivers. We also have our software integrated and delivered with system Z. That's another deployment choice. System Z delivers the highest qualities of service on the planet, security, reliability, efficiency. That's another deployment choice that many of our clients require. And then there's cloud agility. So delivering our capabilities via cloud services, whether that be on the IBM smart cloud or through partners who deliver cloud-based services. So that software flexibility, appliance simplicity, systems equalities of service, and cloud agility are four fundamental deployment options. So you've got something for everybody there. And if I want the cheap and deep, lowest cost approach, I can just, in a pure Hadoop scale out, you got that too. If you're looking for a Hadoop, and that's where you're focused, and you're looking for low cost, you can have a download it for free and put it on your software. And support is optional. You can come back for support optionally if you want. And then it's the same big insights, Hadoop-based big insights offering that as your needs evolve, if you need a larger set of capabilities in an enterprise class scale environment, you can move up to the enterprise version. And then if you want it as a expert integrated systems to speed and simplify deployment, you get it as a pure data system. Right, and obviously you have your services organization out doing deep industry probes and tremendous expertise in those parts of the organization that can apply these technologies across your portfolio in ways to drive business value. Exactly, all services end, I'd also add our IBM research team. So one of my favorite areas these days is in energy and utilities, and that whole smart energy. And we're working with the smart energy team at IBM research, right, at our Watson research lab, and organizations around the world using streams to analyze the data in motion through the grid. Landing that data in a time series database, right, to do the reporting analyst and the smart meter management, feeding that data and other data into a pure data systems, perhaps powered by the Natesa technology to do broader analytics and deeper analytics amongst different types of data. And then the most recent add to this storyline is the clients that were then going the step further and using a Hadoop-based system to also bring in text information, sentiment analysis from their customers, documents from the customer relationship management to bring that to bear. So when I hear those stories like, this is exactly the message, right, it's using the right best tool for each job, looking across all your available data, both inside and outside your company, all types, all structures, and figuring out how you can extract the most data from it to get better answers and better decisions for the business. I feel like we're hitting, and we talk about all this sort of, what I would call, internet of things or something called the industrial internet, as some of the next big wave, IBM obviously calls it smarter planet, the next big wave of big data, if you will. You're seeing these GE ads now, GE's getting into it big time, so it's his old saying, right, you got one lawyer in town, they can't make any money, two lawyers, they both get rich, so you got IBM and GE, GE, of course, a customer of yours, but now doing this whole industrial internet, you guys have the smarter planet. I think people are really gonna start picking up on that, but the time is now that the technology is available to do that, and you guys, you and GE and others, each have your parts of the value chain, but that is an explosion. Oh, we're definitely seeing it, and it's not, it's smarter manufacturing, I think all those lines, transportation, the vehicles and all the sensors along the routes and doing analytics on that, it's distribution networks, trucks and fleet management. Supply chain with just the healthcare. Healthcare, right, all the telemetry you're getting from the devices, we're wearing them now, all the stories of... Watches and all these companies doing watches. Exactly, so that is a big data wave that we're in right now, that all these different capabilities I just talked you through, certainly apply, and we recently had this, when we did the Blue Acceleration Launch, we did it at our Almond and Research Center, where the relational database was invented and the disk drive was invented, and we had one of our VPs from research talk about the global technology outlook for the next five to 10 years, and the next big wave is gonna be in audio and video, and doing a better job of mining and utilizing that information automatically and adding it to the mix. So we've got a way to go here. Being able to sort of scan the content in there without having to spend 30 minutes watching the video, and metadata, it's just... Exactly. It's incomprehensible how large this is gonna be. We try to size the big data market and it's five billion here, grow into whatever 50 billion, but this is hundreds of billions, if not trillions of dollars of opportunity that we're talking about here. Yes, if you define big data as all data and all possible ways to extract value from that data, absolutely. So it's enormous, we're here watching this and excited to be a part of this trend. Bernie, I'll give you a last word. Advice to CIOs, everybody has at least attuned to the fact that there's value in data. A lot of companies, it's a bell curve, obviously. Some are leading the charge, others are trying to figure out what is this big data thing? How do I actually monetize? Where do I start? What advice would you give to CIOs who are looking to get started? Now, my advice would be, you're gonna wanna start small and specific and demonstrate a return on investment, absolutely. But do that after you've looked at the broad picture and the strategic scope of how data can impact your business. And then from that, narrowing in on what's the first most important thing that we wanna do and demonstrate success and do it in a way that it's an obvious first step in a complete roadmap. I've seen too many cases where, jumped in on the hot project, right? A vendor or one of my technical team came in with a hammer and said, our biggest problem is a nail. And we jumped right on that. And yeah, that might have worked, but it didn't turn out to be the biggest problem or it kinda was a dead end project that didn't fit into bigger things. So when you're talking to CIOs and you're talking to business leaders as well who are focused in on this, it's make sure you look at the broad picture first, lay out a roadmap and then take the first step. Excellent, all right, Bernie. Well, IBM making moves and big data. And of course we're following here at wikibon.org and siliconangle.com. Check out SiliconANGLE for all the blogs, check out Wikibon for all the research, the free research. Bernie, really appreciate you coming in, sharing IBM's insight, it's portfolio. We've got a lot going on there and we're really proud to be covering it. This is Dave Vellante of Wikibon. Thanks for watching everybody and we'll see you next time.


Live from Madrid, Spain. It's theCUBE, covering HPE Discover Madrid 2017. Brought to you by Hewlett Packard Enterprise. Welcome back to Madrid, everybody. This is theCUBE, the leader in live tech coverage. My name is Dave Vellante. I'm here with Peter Verst. This is day one of HPE Discover Madrid. Olivier Frank is here as the Worldwide Senior Sales Director for Alliances for IoT at HPE and Kurt Bayer, otherwise known as Bagger in English in America. He's Vice President of IoT Solutions for Amia, PTC. Did I get that right? Yeah, you did it. Bayer, all right, well thank you for sharing that with me. Welcome to theCUBE, gentlemen. Thank you. Olivier, let me start with you. The relationship between PTC and HPE is not brand new. You guys got together a while back. What catalyzed that getting together? Yeah, it's a great question and thank you for inviting us. It's a great pleasure to be on theCUBE and for me the first time, so thank you for that. Yeah, you know, the partnership is all about action and doing things together. So we did start about a year ago with, you may remember FlowServe and Industrial Pump that we showcased. And since then we've been working very closely together to actually allow our customers to go and test the technology themselves. So I would say the partnership has matured. We now have two live environments that customers can visit, one in Europe, in Germany, in Aachen, with the RWTH University, and one in the US, near Houston, with a text mark who you know because they also came to the show. Right, okay, Kirk, give us the update on PTC. Company's been in business for a long time. IoT is like a tailwind for you. That's right, PTC is mostly known for CAD and PLM. So for 30 years they have made the 3D CAD software for when you design and make an aircraft or a car engine. But over the last five years, PTC have moved heavily into IoT, spend a billion on acquiring and designing software, a software platform that can connect and calculate and show in augmented reality. So let me build on that because PTC, as a CAD company, as a PLM company, has done a phenomenal job of using software and technology to be able to design things to a level of specificity and tolerance that just wasn't able to be done before, and it's revolutionized how people build products. But now because technology's advanced, you can leverage that information in your drawings, in your systems to create a new kind of an artifact, a digital twin that allows a business that's working closely with you to actually render that in an IoT sense and add intelligence to it. Have I got that right? You got it exactly right. So making the copy, we can draw it and we can design the physical part and we can make the digital twin of the physical part with sensors. So in that way you can look back and see if the calculation, the design, the engineering you have made is the right fit or you need to change things. So you can optimize product with having the live digital twin of the things that you design physically. So it's like a model, except it's not a model. It's a real world instantiation. The model is an estimate, right? The digital twin is actual, it's real data. It's feeded by live data, so you have a real copy of what's going on. And we use it for not only closing the loop of designing products, but also to optimize in the industrial 40 to optimize operation and creating manufacturing of things. And we use it to connect things so you can do predictive maintenance or you can turn products to be a service. Instead of selling an asset, the company can buy, by click, by use because the product are connected. I want to really amplify this, Dave, because it's really important. I want to test this with you. Because the whole concept of using technology, IoT technology, to improve the operational efficiency, to improve the service ability to evolve your business models, your ability to do that is tied back to the fidelity of the models you're using for things that are delivering the services. And I don't think the world fully understands the degree to which it's a natural leap from CAD and related technologies into building the digital artifacts that are going to be necessary to make that all work. Have I got that right? You got it completely right. So it is moving from having live informations from the physical object. So if you go to augmented reality, so you have the opportunity to look at things and get live information about temperature, power, streaming of water and all these things that goes on inside the product. You also have the opportunity to understand if there's something wrong with the product, you can click on it and you can be directed on how to change and survey things live when the augmented reality is more built by the cat drawing in the beginning that is combined with sensor information. And simulate and test and all the other things that are hard, but obviously to do that, you need a whole bunch of other technology and I guess that's where HPE comes in. Exactly. In fact, to bounce on that thought, we talk a lot about connected operation where we are showing the digital twin, but one of the new use case that we're showing on the floor here is what we call smart product engineering. So we're basically using the cat environment of Creo, running on that edge line with edge compute, enterprise compute capability, manageability and security and running on that same platform then simulation from companies like Ansys, right? And then doing 3D printing, quick prototyping and basically instrumenting the prototype we're using a bike, the saddle stem of a bike to showcase and then we get able to connect and collect the data, we're partnering with national instruments who also well known and re-inject the real data into the digital model. So again, the engineers can compare their thought and their design assumptions with the real physical prototype and accelerate time to market. PTC has been a leader in starting with the cat and then pulling it through product lifecycle management, PLM. So talk about how this is going to alter the way PLM becomes a design tool for digital business. If I'm right. You're right. It becomes an industrial innovation platform from creating the product to the full lifecycle of it. All the way out to the business model. All the way to the business model and talking about analytics. So if you have a lot of data and you want to make sure you get some decision made fast about predictive maintenance, that's an area where we are partnering with HP. So we have a lot of power close in the edge, close to the products that can do the calculations from the devices from the product and do some fast results in order to do predictive maintenance and only send the results away from the location. So what are some of the things you guys are most excited about, Olivier? Well, really excited about making those use cases, being the smart product engineering or the predictive maintenance, work for our customers. So behind, let's say we have great solutions. Now we're partnering on the sales front to kind of go together to customers. We have huge install base on both sides and picking the right customers interesting this digital transformation and make it real for them, right? Because we know it's a journey. We know it's kind of the crawl, walk, run. And it's really about accelerating, turning insights into information and into actions. And that's really where we are, you know, very much excited to work together. And so it's not just, so the collaboration is extending to go to market is what I'm hearing. And so what's the uptake been like? What are customers, our customers must be asking you, where do I start? What do you tell them? Before you start, it's important that you have a business case or business value. You understand what you want to achieve by integrating an IoT solution. That's important. Then you need to figure out what is the data? What is the fast solution I need to take? And then you can start deciding on the planning of your implementation of the IoT. Can I go back one step further? Tell me if I got that. And that one step further is, look, every innovation and adoption happens faster when you can take an existing asset and create new value. Exactly. So isn't PTC actually starting by saying, hey, you've already got these designs. You've already got these models. Reuse them, create new life, give them new life, create new value with them. Do things in ways that now you can work with your customers totally differently. And isn't that kind of where it starts? It does. And you already have a good portion of what you need. So in order to make a fast value out of your new product or the new thing you can do with the product, connecting the products, then PTC and HP is a good platform to move on. The pre-tested, pre-certified packaging, the software with the hardware is allowing our customer to go faster to proof of concept and then to production. So we have a number of workshops, customers can come. Again, as I mentioned at the beginning, in Germany, in Aachen or in Houston at our TextMark facility, where we can basically walk the talk with customers and start those early POCs, defining the business success factors, the business value they want to take out of it and basically get the ball rolling. But it's really exciting because we're touching really some of the key transformation of our enterprise system. And don't forget that you need a partner that can do a good job in service because you need an organization that can help you get it through and HP are a strong service organization too. Well, this idea of the Intelligent Edge has a lot of obviously executive support at Hewlett Packard Enterprise. The kid's buzzing at the Cube today. Meg Whitman's in the house where she's right next door and we're going to do a quick cutaway to Meg. Give her a shout out, trying to get her over here to talk about her six year tenure here. But that top down executive support has been so critical in terms of HPE getting early into the Edge IoT, Intelligent Edge, you call it. Tom Bradovich, obviously a leader who's coming on. You mentioned national instruments, PTC. You guys were first really from a traditional IT business to really get into that space. We're also the first to converge OT and IT. So we're showing on the floor what we're doing in end of line quality testing for automotive, for example, taking PXI standard, which is like instrumentation and real time data acquisition into our converge at system. So what I found is really amazing. You take the same architecture and we can do it Edge to core to cloud, right? That's very powerful. One software framework, one IT architecture that's spun out. Not some time in the future, but right now. So we're talking about a three, maybe even a three A, it's four tier data model, where you've got data at the Edge, real time. Maybe you don't persist all of it or a lot of it. We call it experience data or primary data at the Edge, event data or secondary data, and then business optimization data at the top level. So let's unpack that a little bit and get your perspective. So the Edge, obviously you talk about real time, decision-making, autonomous cars, you're not going to go back to the cloud to make that decision. That what you call a core, that's, what did you call it? The hybrid IT, that's an aggregation point, right? To collect a lot of the data from the Edge. And then the cloud maybe is where you do the deep analysis and do the deep modeling. And that cloud can be on-prem or it can be in the public cloud. Is that a reasonable data model for the flow of data for Edge and IoT? I believe it is, because some of these products generate a lot of data, and you need to be able to handle that data. And honestly, connectivity is not for free. And sometimes it's difficult if it's in the industry floor, manufacturing floor, you need good connectivity, but you still have limitations. So if you can do the local analytics and then you only send the results to the core, then it's a perfect model. And then there's a lot of regulations around data. So for many countries and especially in Europe, there's boundaries around the data. It's not all that you can move to a cloud, and especially if it's out of the country. So the model makes a good hybrid in-between speed, connectivity, analytics, and the legislation around it. And you both have solutions at each layer? Absolutely, so in fact, so PTC can run at the Edge, at the core, or in the cloud. And of course, we are powering the three pillars. And I think what's also interesting to know is that with the advance in artificial intelligence, as was exposed during the main session, data is pivotal. You need to keep a lot of data in order to learn from those data, right? So I think it's quite fascinating that we're going to store more and more data and probably make some useful right away, but maybe store some that we will come back to. That's why we're working also with companies like OSIsoft, an historian, which is collecting these timestamp data for later utilization. But I wanted also to say that what's great working with PTC is that it's kind of a workflow, a media, in terms of collecting the data, contextualizing them, and then visualization and then analytics. But we're developing a rich ecosystem because in this complex world of IoT, again, it's kind of an art and a science. And the ability to partner ourselves, but also our, let's say, friendly partners is very, very quickly. Guys, oh good, last word. I would say we started with a digital twin. And for some companies, they might be late to get the digital twin. The longer you have had collecting data from a live product, the stronger you will be. The better model you can do because you have the bigger data. So it's a matter of getting the data in to the twin. That's exactly what our research suggests. We've got a lot of examples of this. It's a difference between sampling and having an entire corpus of data. Thank you. Kurt, Olivier, thanks very much for coming here with you. Thank you so much. Great segment, guys, sorry. Thank you. Okay, keep it right there, everybody. Dave Vellante for Peter Burris. We'll be back in Madrid right after this short break.


rd complaints around council cuts during this debate. One of the key things sometimes is that it is the extra time for janitors to be able to keep schools open, which are often the first cuts that are made. That's something that we need to consider as well. Jeremy Balfour did outline very specifically about fostering community, and I think not only to day centres but also church halls are key to that. Christine Grahame mentioned feeling disconnected. I've met many constituents since the pandemic who have told me just a similar story, and how sometimes they have not gone back to their lives, even though they feel confident enough to do that, and who in the past would have attended libraries and different groups being held who haven't reconnected with their old lives. I think that there was something in that we need to look at. There's clearly something very good going on in the north of Glasgow with all the rattling and wrapping that seems to be going on in that part of the city. I think that there's something in where we need to develop for older citizens an opportunity to reconnect with the groups that they've maybe stopped attending or don't necessarily have reconnected to their old lives. Across society, there's many other areas that I think we need to focus on. It was mentioned college and university support workers being one of key groups. I've always said to the Scottish Government and wanted to see the Scottish Government press ahead with GP link workers, and I really welcome the recruitment that has gone on around that. I've met many of them here in the capital, in the most deprived communities here in Edinburgh, but one of the things that struck me is the work that they've had to undertake is to build capacity again. So they've had to go out and establish walking groups, they've had to start book clubs, they've had to look at gardening and growing clubs and groups, and that sometimes takes away from a lot of their work. Now, I think, again, where they do that, how they have funding for that is something at this debate needs to also really consider as well, because small grants are often key to achieving that. In 2018, ahead of the Government strategy, Scottish Conservatives published our strategy to help tackle loneliness, and I congratulate Annie Wells for her consistent work on this and campaigning and publication of that loneliness action plan, but it's clear that small resource, small grants is still a problem and something that we need to see addressed, and I know that Christine Grahame and Bob Dorris touched upon that. I raised the issue with the minister with regard to the £10 million commitment that the Scottish Government has. I hope that it's not gone down to £6 million, and I hope that, out of this debate, the Government will take that away and look again, because I think for the third sector and local organisations, I know anyway, haven't even applied or looked to this £3.8 million. So, whether or not coming out of this debate, we can generally look at small grants, which can be part of this. I also think that the UK Government have a role to play in this, with UK levelling up funding potentially being part of this discussion as well. However, let's try to take forward that funding opportunity, because I think that it's really important, especially when you look at pressures on delivering many of these local services as well. Is there any time to... Is there a little bit of time, Mr... Bob Dorris? Just very briefly, you mentioned small grants and funding opportunities. In this chamber, during other debates we've spoken about social prescribing, and I'm just wondering if there's an opportunity for those boarding clubs and those other clubs out there that link workers and GPs could be using small grants that they have to sidepost towards some of those organisations within all our communities that do such a good job. I absolutely agree, and I think one of the key aspects of this is actually, although we don't need to look towards this, is the preventative spend part of this for our health service as well. For GPs who often will tell me that they often see many people coming consistently about loneliness issues, that if there's an opportunity to fund services and get people reconnected again, it makes a huge difference for our public services as well to make sure that people actually are fulfilling their lives. As Stuart McMillan made, I think the most important speech today for me, and I think that that is one of the aspects of what I hope the minister will meet with others who have been working on this, because bereavement counselling and support groups are invaluable. I congratulate Ben on the work and campaigning that he's done. I've long advocated bereavement being included in the school curriculum, but for support groups to be established in schools is an easy win, and something which I think when you look at the work going on in schools, I hope that some in the Scottish Government across portfolio, and I'm sure that some in the minister will find she is working on a lot. There's a real opportunity to make a difference here, and I hope that's taken forward. There's also an opportunity for young carers who have similar asks and support needs, and some good work has gone on that recently, but I hope that's something we take forward. Social media was mentioned, I think, by the minister at the very beginning, and it's something I've long been concerned around. I organised a summit with Twitter and Facebook when I was first elected. The conclusion that we drew was that young people need to switch off social media and get away from it. Many politicians would probably agree as well. One of the key messages that we have to do is look at where people really are investing too much of their lives in social media and get back to just resilience building, which sadly is not this generation of today, something that we have seen. I also think in terms of older citizens. One of the biggest mistakes that I think was made was around RVS and changes around meals on wheels, from a daily hot meal service to once a week of frozen meals being delivered. It wasn't often the frozen meals that people wanted. It was that personal connection with another human coming into their home once a day. I hope that's maybe something we could look at again. That was expensive to deliver, but it's important that we do. Finally, to conclude, I think that there's a lot of good opportunities coming out of this debate. We'll be supporting all the amendments today, and I hope that this is the start of maybe a conversation of how we really do tackle loneliness across our country. Thank you very much, Mr Briggs. I now call Emma Roddick to wind up the debate, Minister, around 10 minutes please. Thank you, Presiding Officer. First of all, can I express my thanks as well to everyone who has attended the debate today for their insightful and interesting contributions? I think that we've struck a good balance between the challenging issues that we're here to discuss and also sharing good news and best practice. I suspect that some organisations mentioned today might be looking at the official report for some help with their future funding applications. As two colleagues wondered aloud in their contributions, I can confirm that I am indeed being kept very busy, but they'll also be aware that I'm no stranger to travelling, so I'll be delighted to see first-hand the difference that our support is making at a local level, whether that's in Aberdeen, Dumfries, vintage vibes or Glasgow, especially if I can get one of those sausage rolls. It is clear that everyone in this chamber is familiar with social isolation or loneliness, whether that be through personal experience or because it has touched the lives of family, neighbours or constituents. Social isolation and loneliness are not new problems, but they are problems that can be difficult to own up to and difficult to overcome. Many of today's contributions mentioned excellent examples of work going on and the length and breadth of Scotland. I've enjoyed hearing about the net and matter in Paul O'Kane's region and how much the informal chats that this facilitated really meant to the people who make use of the service. I appreciated Stuart McMillan's contribution backed by Miles Briggs on bereaved children and young people. While this is a topic that the Minister for Children and Young People is leading on, I think he'll be aware what a personal matter this is to me, growing up grieving myself after losing my dad and mama ages four and twenty-three, so he won't be surprised that I am aware of the issues he raises and very glad to hear of the work that is being done in Inverclyde. I know what an isolating experience being bereaved as a child can be and I would love to hear more about it from him or perhaps Ben at a later time. I was also glad to hear Emma Harper talk about the work of Change Mental Health, an organisation that I'm very familiar with. Loneliness and social isolation are so tied in with mental health and wellbeing and I think we've seen that come through quite clearly in the debate today. Miles Briggs was right to talk about social media and I do agree that while digital exclusion is something that we need to tackle and overcome, some people maybe go too far the other way and spend a lot of time on social media which just reinforces that feeling of loneliness. I want to pick up on comments from Bob Dorris and others who rightly pointed out that funding at a very local level is what we need here if it's going to be effective in communities and I can tell them that we are prioritising community organisations so that the majority of the social isolation and loneliness fund will be paid to smaller community organisations working at a local level. Being a Highlands and Islands MSP, I recognise the difficulties pointed out by Paul O'Kane and Emma Harper and those smaller community organisations may of course include local men's sheds like the ones that Christine Graham rightly lauded earlier. I absolutely value the work that befrenders like those Jackie Dunbar mentioned at Aberdeen linking lives and other organisations do in communities and I know what a difference a friendly chat can make. I was listening to her contribution and it just made me remember how chatty some patients were during my time at the ambulance service and like the experience of third sector volunteers and workers described by Annie Wells it was it was very obvious that I was the only conversation they'd had for days and possibly weeks and I'd asked if they were able to get out to the roadside to the ambulance and they'd gush this long response and tell me all about the birds in the garden and what had been on the radio that morning and they were just desperate to chat but whether they would have called a befrenders service if I've given them the number is a different story I think maybe they feel the shame that Maggie Chapman talked about or they don't want their family to worry or they maybe don't even want to admit to themselves that they are lonely so it's so important that we continue to talk about social isolation and loneliness to tackle stigma and enable people to open up to one another and reach out for help when they need it. The application process for our new three-year social isolation and loneliness fund closed at the end of last week and the applications are currently being assessed. Funding for successful projects will begin later this summer and I'm very much looking forward to seeing that work going forward in tandem with our new delivery plan and the impact that this will create. Before I finish I do want to talk for a minute about poverty because Ruth Maguire was right to focus on the stress of poverty and the lack of opportunity for people who are spending so much of their time just trying to navigate impossible personal budgeting. Carol Mocken talked about deprivation being missing from the motion today. All I can say is I'm sorry she didn't write the Labour amendment because I would have been very happy to accept that change and I hope she knows that it's missing from a motion but it's not missing from our action. We know that poverty is a key driver of poor mental health and that those already struggling with poor mental health and money worries are likely to be amongst the hardest hit by the current cost of living crisis. That is linked to social isolation. As I mentioned earlier people are forced to choose between social activities and paying their bills. Well that's not really a choice at all and there's a real danger that we will see the problems associated with isolation and loneliness increasing further as a result. Tackling poverty and protecting people from harm is one of three critical and interdependent missions for this Government alongside our focus on the economy and strengthening public services. We recognise the pressure on household budgets which is why last year and this we have allocated almost £3 billion to support policies which tackle poverty and protect people as far as possible during the on-going cost of living crisis. As well as the game-changing Scottish child payment we support families in a variety of ways including free childcare, free bus travel for under 22s, offering free school meals to all pupils and primaries one to five and in special schools and we have tripled our fuel and security fund to £30 million in the year ahead. We recognise the incredible contribution that Scotland's unpaid carers make to our communities as well as the pressures that many carers are under. Our national carers strategy sets out a cross-government approach to carers issues including social isolation and loneliness. There is a whole chapter dedicated to carers social and financial inclusion, encompassing social security, financial support services, employment and actions to help mitigate the impact of the cost of living crisis. We will continue to use all the powers and resources available to us to provide immediate support to families and tackle the underlying causes of poverty. I thank the minister for giving me a very important point about poverty and social exclusion isolation. Does she agree with me that the community housing association movement in particular in Scotland shows great strength at building community wealth, holding assets, locally giving local control and creating that rich tapestry of activity that can engage the community in an otherwise barren landscape? Absolutely. I was just about to mention Emma Harper who talked about the work that is going on in her region with housing associations and how they are taking on that extra role and responsibility in building communities as well as homes. Emma Harper, Christine Grahame, Ruth Maguire and others were right to point out that it is only with the full economic and fiscal powers of an independent nation that ministers can use all the levers that other Governments have to tackle inequalities. We are giving careful consideration to what further measures we can introduce to reduce poverty as far as possible within our powers, and the First Minister is convening an anti-poverty summit tomorrow, which will help to guide future action. Last month, I contributed to the debate on a wellbeing economy, reminding colleagues that a successful country means so much more than having high GDP. A wellbeing economy means delivering conditions for people to thrive and delivering fairly so that everyone benefits. Personal wellbeing, including indicators around loneliness and social support, is a key part of that. Another important consideration for a wellbeing economy is that of place. There is also a noticeable effect of place on experiences of social isolation and loneliness. The extent to which people interact is heavily determined by their lived environment. Do we all live in neighbourhoods where it is easy to bump into folk for a chat? No. The results of the most recent Scottish household survey were published last week, and some of them clearly indicate room for improvement. For example, only 62 per cent of people agree that there are places to socialise and meet new people in their neighbourhood. We have to do what we can to improve that situation. However, 88 per cent agreed that people in their neighbourhood are kind to each other, and 89 per cent agreed that if they were alone and needed help, they could rely on someone to help them. As Marie McNair pointed out, we saw a glimpse of that community spirit in action throughout the pandemic. If we are to really tackle social isolation and loneliness, we need to retain that now and in the future. Only by everyone taking a share of the responsibility, individuals, communities, public and private sectors, local and national government, will we really be able to make an impact and create lasting change for the people of Scotland. I am committed to playing my part in taking forward this important work and I am heartened to see that others across the chamber feel the same way. Thank you.


The study examines the ground state properties of a multi-component repulsive femigastrapt in a harmonic trap, using fixed node diffusion Monte Carlo method to investigate how energetic properties and correlation functions evolve as the number of components changes. Analytical expressions are derived for weak interactions within local density approximation for any number of components and one plus one particle using an exact solution. The system fermionizes in the limit of strong interactions. This article was offered by N. Matveeva and G. E. Astrakarchik.


The Hot Seed podcast is back, better than ever. We have new guests on the show. I'm joining the Hot Seed today by Ustad Muhammad Imhambo, Hafidahullah wa ta'ala. As-salamu alaykum wa rahmatullahi wa barakatuh. How are you doing? Wa alaykum as-salam wa rahmatullahi wa barakatuh. JazakAllah Khairan, very well. We're very pleased to be here. We have new topics being discussed. For centuries people have been following the madahib and all of a sudden, at the start of the 19th century you guys come along and say, get rid of the madahib. No, I'm not saying get rid of the madahib. Atheism is a fundamentally irrational belief. It doesn't make any sense. Ultimately, are we saying that there are no differences between men and women? To be honest, that is something that I just find ridiculous. We have a new set being used. But we still have the same old classical solutions. You can still vote for your favourite topic. You can still ask your own questions. Welcome to season two of the Hot Seed.


When she told me how much I received, I realized there was an extra $600. This is a government I describe as promises made, promises kept. And it was really exciting to receive this. My name is Anthony Herman. I live right here in this community of La Fague Chousel. I'm a retired teacher. I taught for pretty much 30 plus years. I'm retired as an agricultural teacher. Retired in 2000. I am Claudette Ajoda. I am a retired teacher. I started teaching in St. Lucia at a school which was called Vibhutai Project. So I taught at Antropo Secondary School. I retired in 2001 after teaching for like 20, 22 years. Initially I heard that the Honorable Prime Minister made a promise to give pensioners a blessing of $600 at the end of November. I heard that a few weeks ago. And then the day salaries came in I called and I said check my salary for me please. So the young lady in the credit union checked it and when she told me how much I received I realized there was an extra $600 so I think I screamed her ears. She may have become deaf because that $600 came in. I didn't even know how to say it. It was perfect timing. When I heard, in fact I heard my neighbor screaming and dancing in the house. So I went outside and said what's the matter? And she says to me we have it, we have it. I said what do you have? And she says well $600 I said from where? And what? She said you didn't know? I said no. The government had promised $600 to pensioners at the end of November. I said oh my, I actually paid for $600 so the Lord has handed me $600. So I was pretty excited. He honored his promise and I respect him and I give him thanks. Philip J Pierre, I thank you with all my heart and soul for that gift, for that blessing. I am sure every single government pensioner is grateful to you but some of us just don't express how we feel. Sometimes you're afraid, sometimes you're shy. I'm usually shy but I needed to say thank you so much for that blessing. I am also an entertainer and since COVID I haven't worked. Since March 2020 I haven't worked. So I've been relying heavily on pension, on the pension and the extra $600. It's just amazing. Thank you. The Bible says what does God require of man? And the answer is to work humbly, to do justly and to love mercy. So this afternoon I take this opportunity to pray for the Prime Minister and his cabinet and especially the Prime Minister that he will continue to work humbly. He will continue to love mercy and do justly. And when I talk about just do justice, I'm talking about the vulnerable, the underprivileged, the indigents, those that do not have a voice. He will have to be the voice of those many. But you know what? This is a government I describe as promises made, promises kept.