Hi guys, this is Rich here on behalf of Rich TV Live. We are five days, 17 hours, 49 minutes and 32 seconds away from history in Canada. And you can find all the tools you need at www.richtvlive.com, hover over news, hover over stocks, go to contact us and join our secret stock picks group. It's a social media platform, absolutely free. All you got to do is download Amino on your phone or on your computer and you can join our free group. You can join our slide group discord and follow us on all social media to get 24 hour alerts seven days a week and bam. I got to give the credit to this to Andrew Ellington who is one of our members.  And I was like, yeah, I don't know, I don't know. At the time it was at five cents, guys, bam, it exploded 51% yesterday. It's up again pre-market already 6%. It's absolutely on fire. It's 100% by top 1% signal strength and they are in the cannabis sector. It's true. You need to put this on your watch. Just put this on your radar immediately. This is on full alert. Look at this. Up 213% in the last month, 273% in the last three months, 646% in the last year. Unbelievable. And look at the news, favorable outlook continues to boost extraordinary expectations for the cannabis industry. Pureation Inc. garners interest from 330 billion beverage industry brand name players. This is 34 minutes ago. Let's just click on that. Pureation Inc. OTC, US OTC Pura today released an online management presentation to provide more detail on its corporate restructuring to concentrate resources on its rapidly expanding cannabis-infused beverage business. The presentation includes details on the recently announced spin-off of its cannabis cultivation business and the pending dividend distribution of spin-off stock. The presentation also includes details on the company's current two cannabis-infused beverages and the recently announced letter of intent to acquire a company with a third cannabis sector beverage. The presentation highlights the company's overall strategy to optimize the movement of major brand name beverage industry players into the cannabis sector in addition to reporting recent interest shown by some brand name players into purations experience in the cannabis-infused beverage sector. This is so big. View the presentation on the company's website or read the narrative from the presentation included in this entirety below. Pureation cannabis-infused beverage industry restructuring strategy presentation. Major beverage industry players are jockeying for position in the nascent cannabis beverage-infused market. Canada's legalization of recreational marijuana is huge which goes into effect in five days. Triggered Fortune 500 size interest in the cannabis sector up until Canada's vote to legalize recreational marijuana, large corporations and investment houses remained on the sidelines. Now Corona Beer, parent to consolation brands, has jumped into the cannabis sector making a $4 billion investment. Coca-Cola is eyeing the CBD sector and Molson Coors Brewing Company has announced a partnership to develop a non-alcoholic cannabis-infused beverage for the Canadian market, soft drink sales in the US, total $112 billion annually and alcohol beverage sales in the US total $223 billion with a beat. With such household brand names in the industry producing over $330 billion in sales annually, now taking interest in cannabis-infused beverages, Pureation finds itself in an enviable position. Having not only already developed and produced a cannabis-infused beverage, but also having earned over a year's worth of hard knocks experience marketing and distributing its cannabis-infused beverages. Pureation's cannabis-infused beverages are on shelves in sports nutrition retailers, liquor stores and dispensaries. The company's experience has of late attracted the attention of some beverage industry heavy weights. Wow! My goodness, interest could potentially grow into a more committed relationship. Look for an upcoming interview of Pureation CEO Brian Shibley to be published next week to learn more about the recent interest in Pureation cannabis-infused beverage experience. Pureation's 600% cannabis-infused beverage sales growth experience. That's right, 600% cannabis-infused beverage sales growth experience. Pureation debuted its ever-ex-CBD sports water early last year at Arnold Schwarzenegger's Arnold Sports Festival. Everex has since become the leading CBD-infused beverage in the sport nutrition marketplace. The company reported 600% sales growth in the second quarter of this year and recently announced a 1 million annual revenue benchmark being potentially within reach for 2018. The company has its first THC-infused beverage, THC Saver, under development and has recently announced a letter of intent to acquire a company with a third cannabis sector beverage. The acquisition is anticipated to be completed later this month. This company is on fire. Thank you, Andrew Ellington. You are a scholar, my friend, for bringing this winner. Pureation's history from cannabis extraction patent to beverage producer. Pureation entered the cannabis sector when it acquired the rights to patented cannabis extraction process from North American cannabis holdings, Inc., USMJ. The entrepreneurial business plan has evolved into the acquisition with the company now concentrating its cannabis sector expertise and experience exclusively on the production of cannabis-infused beverages. Today, the company maintains its patented cannabis extraction license as part of its strategy to produce a differentiated cannabis-infused beverages. Pureation's cannabis cultivation spin-off. The streamline and concentrate all its resources on the production of cannabis-infused beverages. Pureation has recently spun off its cannabis cultivation operation. The spin-off was affected due to the execution of Securities Exchange Agreement with Nouveau Life Pharmaceuticals Inc., N-O-U-V. Pureation sold its cannabis cultivation business in exchange for a convertible purchase note issued by N-O-U-V. Pureation and N-O-U-V have agreed to recapitalization plan for N-O-U-V and a post-recapitalization conversion of the purchase note into a number of common N-O-U-V shares. Submission issued one N-O-U-V common share for every five shares of puration common shares issued N-O-U-V standing. All of the N-O-U-V common shares issued in conversion of the purchase note are slated for distribution to puration shareholders in a dividend distribution. Wow! Look for presentation coming soon from N-O-U-V on its business plans for the cannabis cultivation business. This is huge! Pureation's pending stock dividend distribution. Now that the Securities Exchange Agreement between N-O-U-V and puration is finalized, N-O-U-V is working to rapidly come current with its financial reports. Once N-O-U-V is current, the company will initiate a recapitalization following the recapitalization. The purchase note will be converted into N-O-U-V common shares and puration will initiate the necessary steps to issue the converted N-O-U-V shares to puration shareholders through a dividend distribution. The first steps leading to the stock dividend distribution are underway and the combined management teams are committed to prompt a delivery of the planned stock dividend. Goldman small cap, puration research report speculative buy and target is 25 cents. That's right, 25 cents for PURRA, P-U-R-A. Put it on your watch list, put it on your radar, remember Rich TV Live is strictly for education, entertainment purposes, do your due diligence, do your research before you invest in anything that we talk about here on Rich TV Live. If you like this video, smash the like button, comment down below, share the video everywhere the market is about to open and I want to bring this to you first because it is going up pre-market. It was up 51% yesterday, it's up again today and it's probably going to keep climbing. Goldman small cap research issued a research report on puration Inc. published October 10th yesterday. The report includes a speculative buy rating with a target price per share of 25 cents. The report provides an in-depth overview and analysis of puration successes, approach, new initiatives, and upcoming milestones. So you can view this report right on Goldmanresearch.com and yeah, what do you guys think about this? Comment down below, it's a big winner, it's already up big since Andrew Ellington brought it to our attention and it is up right now again pre-market. It's true. Look at this, let's look at it right now, it was up 51% yesterday which is insane and up another 8% pre-market, it just keeps climbing, keep your eye on it, put it on your radar, put on your watches, 100% buy on bar chart, top 1% signal strength, long-term the trend strength is in the top 1% long-term indicators fully support a continuation of the trend. It's true. We are 5 days, 17 hours, 39 minutes and 30 seconds away from history. Have a great day. This is your boy Rich. If you're not winning, you're not watching, I'm out, peace.


Hey guys, welcome to snow break containment zone. So this is a new updated tier list, which includes mousey or shadow car test Scott kin and you have catch a client. So this is for January 2024 and let's start off this tier list with tier C. So we have here Nita and I nearly called her Tina. Nita and Haru for tier C, not much really to cover, not much of a change in terms of from my previous tier list, although I think I'm not sure if they're gonna go up some time, but definitely they are right now at tier C. No details on that. So tier B, I have here Frisha hushed. Again, Frisha has his kit is I think for me is limited at this point. She's going to be useful as mainly as a support. Moxie here as a support as well, especially if you don't have her S for her orange tier. Frisha on the other hand, the lower tier, the four star tier is actually very still serviceable. Still, if you are, especially if you're beginning this game, you can actually begin with her. Fisha hushed really going to go back to her. She really requires a lot of investment in her kit. So I'm really, really putting her at tier B. Life here, very fun character tier B. Fanny four star is also here and Marion four stars here. Anya and Cherno is actually here. Anya, sad to say, has been replaced by another operative in terms of Viao's best friend. So she remains at tier B and Cherno remains at tier B as well. So those are my two tiers, guys. If you have any questions and comments for the previous two tiers and the current two tiers that I'm discussing, please put them down in the comment section. I'll be glad to answer them there. Next would be tier A. We have Marion Swift for tier A. In this tier, you have a lot of supports here, including Yao for healing, Shensheng for healing as well, but a lot of goodies in her bag. So most of the supports are here. Akasha is also a good operative to have decent in the mid game. That is why she's here. She also has good ultimate energy recovery. And the last is series if you are in need of a shield for your team. Okay, so that is for tier A. Next we go to tier S. So tier S is where I think you guys should invest more on these characters. So these characters have a different ceiling depending on if you have invested in their manifestation or not. Life Wild Hunt, while she is here in tier S, she could be tier SS, especially if she is all decked out, complete manifestations. She has tremendous damage for her standard skill. But again, she requires a lot of love and a lot of copies. That is why I'm going to put her at tier S. Tess is going to replace Akasha here because of the ultimate energy recovery theme within their kit. That is why she is in tier S with life. Tess is definitely going to be situational. She's not a support for everyone or for every operative. But if you use her correctly, she is going to be great for your team. Next up is going to be Haru Absconditus for tier SS. I think so far, she's the greatest mob killer, mob sweeper in the game. I cannot think of anybody close to her at this point. She has good damage, very good damage with her pistol though. And I suggest you build her if you have her right now. Magsir Shado Ka, I'm actually hesitant to put her in tier SS, although she compliments shotguns and snipers very well, especially for Yao. But again, I might say that her use is pretty limited. But once you use her, she gives you a lot of or a great value towards your operative, especially if you run her as support. So again, she's one of the top supports that we have in the game. Massive damage if you pair her with a shotgun and also with a sniper rifle. But it goes down drastically in terms of damage output for the other types of weapons. And last for tier SS, you have Katya Blue Bolt, so our new operative. Okay, my thoughts on Katya. Why put her here? Number one, the fun factor, the easy factor for Katya. I think Mobile and PC will have a fun time using her. You don't really need to bother yourself with reloading. All you have to concentrate is reposition, use her standard skill, and shoot. That is it. Probably heal, probably have some buffs for support or other things for support. But she definitely can put down a lot of bosses, I tell you. Especially if you play her well time, her dodges, time, her standard skill. I know that in her standard skill, her damage is actually, is actually halved, almost halved, like 48%. But definitely it makes up for her, you know, for the speed of her shots. So again, if you level up her M1, it will really, really give you more, you know, more frequency or speed to her shots for her basic shot and also for her standard skill shot. So again, although she doesn't have the best damage, but the volume of her shots will definitely catapult her to SS tier. Now with all of the buffs that we have recently for her, definitely she's staying in SS tier. And the last tier is going to be SSS. So this tier are the goddess tier. I hope you are not disappointed with my selections. We have Chen Xing, DPS goddess, what can I say, hands down. Again, a lot of damage for this girl, especially if multiple weakness on a boss, definitely have her bring her a lot of damage. Next up is going to be Yao, Winster Solstice. So Yao definitely is going to have a have better days ahead with Moxier Shadowcaw. So definitely have her as one of your primary damage dealers. Again, really depends on the play style if you're into a sniper or not. But if you're into a sniper, definitely you'll have a, you know, you'll have a field day in dealing a lot of damage. Next up is going to be Fanny Coronet. Fanny definitely still is one of the top damage dealers. Her only limitation actually is the reload, which I really, really hate. But the damage output and if you really know how to time your reload and your shots and your dodge, definitely you do a lot of damage with Fanny. Really, really DPS goddess at this point. And the last is going to be Akasha Kaguya. So Akasha Kaguya best all around support. I don't think she has a limitation on which team you should bring her. The others really have limitations like for example, Shadowcaw and Tess Kotkin. But for her, Akasha Kaguya, I don't think you have a limitation with her. She has one of the best debuffs in the game. And what can I say, it has a lot of, you know, bells as well in keeping your enemies together, lowering down their elemental resistance. And that is it guys. So hopefully you are happy with the tier list that I put together. Also I'll be putting a link to the description of this video just in case you want to look at it more often. So I'll put a link in the description of the video as for quick reference. So again guys comment down in the comment section. Did I get this right? Also please do put your in your inputs. And I really, really appreciate it. So thank you very much for staying this far. Take care. Stay safe. This is The Warden and I'm out of here.


Good morning. I'm Kristen Filetti and welcome to News Desk on SiliconANGLE TV for Tuesday, June 11, 2013. NetApp's new version of their flagship storage OS, Clustered Data on Tap, has been announced today. Join us now to provide details on what this new software can do as SiliconANGLE founder, John Furrier. Good morning, John. Good to have you back. Good to be here. Thanks for having me. So NetApp has introduced a new storage operating system, Clustered on Tap, as their main innovation for their existing and future customers. So John, what's so important about this announcement? Let's start with that. Well, I think it's important because all the big competition, IBM and HP, are all having a big show here this week in Las Vegas, where I'm at right now. But fundamentally, the bigger trend is that the cloud and Amazon has shown the way for kind of a new way to do things for businesses and information technology. And with cloud infrastructure and, say, big data, the tsunami of data that's being generated by mobile devices, and you're seeing things with the NSA prison, big data is being used for a lot of things, including surveillance, as well as business value, is creating a massive innovation boom. And this is creating a lot of wealth opportunities, and quite frankly, refactoring the market. So the marketplace of big companies supplying IT, technology, computing, storage, and networking is under massive reconstruction. It's reforming in real time, and it's happening on an accelerated basis. So this is an opportunity for companies to change their leadership position and take new territory or get new leadership position in their products. And what NetApp is introducing today is fundamentally a shift to this new model of software-driven enterprises, software-led infrastructure. And the cluster on tap is a huge announcement for NetApp in the sense that it's going to be the fundamental platform or operating system for all of their storage devices, which literally has been installed in the thousands and thousands of corporate enterprises, large scale enterprises, medium-sized enterprises. And NetApp has been a very, very successful storage company, but yet is still smaller than, say, EMC, IBM, and HP relative to their sizes of company. So this shift to this new operating system is a major platform upgrade and change for NetApp, which gives them the ability to kind of hold down their install base customer base as well as get new customers. So it's a significant announcement for NetApp in the sense that they are betting the company on this approach. Will software-defined storage be the preferred architecture? And the answer from our standpoint is yes, because that is where everyone's going. I think Amazon and Cloud, in particular, and big data tsunami that's happening is really driving that trend. So this is a really big deal for NetApp and their customers. So, John, why is NetApp introducing this cluster on tap? And what sort of trends are you seeing in the software-defined storage market? You know, NetApp is introducing some compelling software that they've been working on for many years that's going to modernize their customer base as well as bring them new business in the area of software-defined storage. And this is kind of really kind of points to the big trend of what Cloud has done, Amazon and OpenStack and other environments, plus big data has driven a major transformation for large enterprises. And the key thing, as I pointed out on my blog post today on Forbes, is that any time there's a market reformation, there's always opportunities for new leadership positions. And NetApp is definitely taking advantage of that. And they've always been a great software-driven storage company of thousands and thousands of clients using their storage platform. And now they're essentially upgrading and modernizing their infrastructure with new software operating system. And really what it is, is that CIOs and large businesses are reinvesting in their infrastructure to essentially modernize their capabilities to deliver Cloud capabilities as well as big data and mobile, et cetera. So all the things that are happening with Apple, iOS, Cloud and big data really points to the trends. And we saw that recently with the NSA prism thing, where we're seeing big data applications being used for surveillance, but more importantly, is they're being used for business use. NetApp is realizing that they don't have a clustered software environment that they really will lose share. And this is a major step in the company's direction to do that. And these are opportunities. And Cloud is creating new economics, and that's really the opportunity for NetApp. Tell us what software-defined storage is. And why are all these storage companies introducing the concept of SDS? Software-defined storage basically means that new software is being written with virtualization and new technology to take storage from a place to store data to a place where you can store data and use it very, very fast and using it in a way that allows for scale. And NetApp, in particular, as well as all the other storage vendors, IBM, EMC, HP, and others, the focus is on what they call scale-out storage, meaning to handle all the new cloud technologies and the big data that's happening with mobile. You need massive amounts of more storage. So storage is continuing to grow, the drives and the systems that store all the data. However, getting the data out and making it usable, say on an iPhone or an Android phone, is really the focus. And that takes new software paradigms, and that's really what the hype's all about. The reality is that companies that don't offer software for developers to use will not be around much longer. So what NetApp is essentially doing is recognizing this transformation for essentially businesses, the chief information officer in these large companies, to take their storage, which is still growing and not stopping, and putting a software layer on top of it so that people can write new software, write new apps. And these apps is what people are focusing on. I heard Mark talking about the iOS kill switch, things around finding the device, being more agile and faster to write code. And this is really kind of where the tsunami is happening. Certainly on the consumer side, Android and iPhone is showing the way for these new applications. But these large companies where people work, it's just not that robust, but you're seeing more like an Android, iPhone environment for corporations. This is actually leading to new opportunities for people to drive more business. So massive innovation boom for these large enterprises to provide new apps and new technologies. And with cloud, like an Amazon-like environment, and with software, companies like NetApp can actually provide an infrastructure that actually does that. So software is the key to success. We're seeing it on the consumer side and on the business side, you're seeing this massive transformation. So that kind of software layer allows for all kinds of new possibilities. So with NetApp, they have thousands of customers, so they have to kind of maintain that and support that as well as be positioned for a new headroom and new capabilities so people can grow in the future. In this new modern era of storage, what is it that customers are seeking and looking for? Well, I think one thing is that you're seeing data as the new currency. Someone was saying it's the new natural resource. Data exhausts is a term that people use. And with the NSA news recently around the surveillance, you're seeing data is being used in a variety of different ways. So one thing that's clear is data is forever. The other thing is that you're seeing is people are used to services, really fast new capabilities. No one wants to have a phone or a computer where it's just slow bloated. And people are recognizing that with phones in particular, mobile phones, that's the first environment. That's the first screen people are using now. It's not the other way around. It used to be the desktop computer or the laptop first and then phone second. That's actually reversing the trend and you're seeing people use their phone connecting to other systems. So that's the user experience. On the business side, people are actually using phones and tablets and cloud to actually do work. So the people who actually have to create value businesses have to have this environment. This is a modern era that's really, really exploding. So you're seeing that service level and ultimately storage still needs to be around to be stored. So NetApp is not going anywhere. EMC, HP, IBM, we're all retruing their technologies to be software driven and software led. So that will enable new applications. And this is a massive transformation in businesses. So anyone who's been in the workforce since the 80s has seen this transition. Certainly people entering the workforce now want an environment where they're not locked down and chained to a desk. They want to use their phone wherever they are on a mobile capability. And also they want real time capability. They want the ability to access data. That is fundamentally changing the game. So how does NetApp compare to their competitors? Well, NetApp is interesting, right? I mean, there's a Silicon Valley company that's done extremely well. I wrote a post about this. They have a 20 year history of innovation. They've always been kind of a leader, but they're smaller than say EMC. EMC's got a lot more capability and investment behind it and marketing dollars. EMC, HP, and IBM all have big presence. And I think NetApp's focus here is to use software as a way to continue to innovate. Although smaller than the other guys, NetApp has thousands and thousands of customers. But you're seeing NetApp really trying to compete with EMC, HP, and IBM, as well as the slew of other startups that are coming out of Silicon Valley and around the world. So the storage paradigm is absolutely changing. And there's two things that are happening. One is more storage is being purchased to store data. At the same time it's being commoditized, meaning people don't want to deal with stuff that's stored on device. They don't care where it's stored. They just want the data. So NetApp has a good story there because they can now offer that software. So again, this comes back down to, I don't care where it's stored, I just want to use the data. And that's where NetApp is trying to be competitive. And they have a tough road ahead of them, but ultimately this is a major announcement for them and we'll give them a chance to compete and aggressively take new territory. Again, when the marketplace is refactoring and reforming, all the chips are on the table to use my Vegas analogy. And the opportunity is who can play the right hand here and win that. And NetApp thinks they can move the ball down the field and have a good approach here. Well, John, we don't have much time left, but quickly before you go, do you see software defined storage by NetApp impacting their business model and their financial performance? Absolutely. In fact, that's one of the reasons why I posted on Forbes today because it's much more of a business site. We have posts on SiliconANGLE as well, given more of the detail analysis. And Wikibon has the deep dive on the technical side, but here's the bottom line for NetApp. They have thousands and thousands of customers and a lot of their customers are looking at alternatives like open source commodity hardware and that is a major force to their business model and potentially has ramifications on the financial side. So they have an installed base of customers as well as new customers, the next Pinterest, the next Facebook want to buy drives, these new companies. So for them, this is a significant stake in the ground and allow them to maintain their existing business, provide those new capabilities of cloud and big data at the same time, offer that scale out capability to attract new customers. So my take on this is it's gonna be upshot for their financials and ultimately their business. So we'll see how they roll that out, but ultimately this puts them in a good position to continue on the financial side, which so I think it's good news for the stock price and certainly their business prospects. Well, John, thanks so much for sharing your insight with us this morning. Great to see you again. Thanks. And later this morning on Newsdesk, LG introduces a game service to its TVs and is Gorilla Glass coming to your automobile. But up next, SiliconANGLE founding editor, Mark Risen Hopkins shares an exclusive interview with us regarding software defined storage and the net up announcement.


Live from Washington D.C., if the Cube. Covering Inforum DC 2018, brought to you by Infor. Well, welcome back to Washington D.C. We are live here in the convention center at Inforum 18, along with Dave Vellante. I'm John Walls. It's a pleasure now. Welcome to the Cube. Lee Martin, who is the senior director of the Dynamic Science Labs at Infor. And good afternoon to you, Lee. Good afternoon. Thank you for having me. Thank you for being here. All right, well, tell us about the labs first off. Obviously, data science is a big push at Infor. What do you do there? And in why is data science such a big deal? Yeah, so Dynamic Science Labs is based in Cambridge, Massachusetts. We have about 20 scientists with backgrounds in math and science areas. So typically PhDs in statistics and operations research in those types of areas. And we've really been working over the last several years to build solutions for Infor customers that are math and science based. So we work directly with customers, typically through a proof of concept. So we'll work directly with customers, we'll bring in their data, and we will build a solution around it. We like to see them implement it and make sure we understand that they're getting the value back that we expect them to have. And then once we prove out that piece of it, then we look for ways to deliver it to the larger group of Infor customers, typically through one of the cloud suites, perhaps functionality that's built into a cloud suite or something like that. Well, give me an example. I mean, so as you think, you're saying that you're using data that's math and science based for application development or solution development, if you will. Like how? So I'll give you an example. So we have a solution called Inventory Intelligence for Healthcare, which we're, it's moving towards a more generalized name of inventory intelligence because we're going to move it out of the healthcare space and into other industries. But this is a product that we built over the last couple of years. We worked with a couple of customers. We brought in their loss in data, so their loss in customers. We bring the data into an area where we can work on it. We have a scientist in our team actually, she's one of the senior directors in the team, Don Rose, who led the effort to design and build this design and build the algorithm underlying the product. And what it essentially does is it allows hospitals to find the right level of inventory. Most hospitals are overstocked, so this gives them an opportunity to bring down their inventory levels to a manageable place without increasing stockouts. So obviously it's very important in healthcare that you're not having a lot of stockouts. And so we spent a lot of time working with these customers, really understanding what the data was like that they were giving to us. And then Don and her team built the algorithm that essentially says, here's what you've done historically. So it's based on historic data. At the item level, at the location level, what have you done historically and how can we project out the levels you should have going forward so that they're at the right level where you're saving money, but again, not implementing, you're not increasing stockouts. So it's a lot of time and effort to bring those pieces together and build that algorithm and then test it out with the customers. You try it out a couple of times. You make some tweaks based on their business process and exactly how it works. And then, like I said, we've now built that out into originally a standalone application and in about a month, we're going to go live in Cloud Suite Financial, so it's going to be a piece of functionality inside of Cloud Suite Financial. So, John, if I may, I'm going to digress for a moment here because the first data scientist that I ever interviewed was the famous Hillary Mason, who's, of course, now at Cloudera, but and she told me at the time that the data scientist is part mathematician, part scientist, part statistician, part data hacker, part developer and part artist. And so, you know, it's an amazing field that Hal Varian, who was the Google economist said, you know, it's going to be the hottest field in the next 10 years. And it's sort of proven true, but to leave my question is, so you guys are practitioners of data science and then you bring that into your product. And what we hear from a lot of data scientists, other than that sort of, you know, Penelope of skill sets, is they spend more time wrangling data and the tooling isn't there for collaboration and how are you guys dealing with that? How has that changed inside of Infor? It is true. And we actually really focus on first making sure we understand the data and the context of the data. So it's really important if you want to solve a particular business problem that a customer has, to make sure you understand exactly what is the definition of each and every piece of data that's in all of those fields that they send over to you before you try to put them inside an algorithm and make them do something for you. So it is very true that we spend a lot of time cleaning and understanding data before we ever dive into the problem solving aspect of it. But, and to your point, there are, there is a whole list of other things that we do after we get through that phase. But it's still something we spend a lot of time on today and that has been the case for, you know, a long time now. We, wherever we can, we apply, you know, new tools and new techniques, but actually just a simple act of going in there and saying, what am I looking at? How does it relate? Let me ask the customer to clarify this and make sure I understand exactly what it means. That part doesn't go away because we're really focused on solving the customer solution and then making sure that we can apply that to other customers so really knowing what that data is that we're working with is key. So I don't think that part has actually changed too much. There are certainly tools that you can look at and people talk a lot about visualization so you can start thinking, okay, how can I use some visualization to help me understand the data better? But just that whole act of understanding data is key and core to what we do because we want to build the solution that really answers the business problem. The other thing that we hear a lot from data scientists is that they help you figure out what questions you actually have to ask. So it sort of starts with the data, you analyze the data, maybe you visualize the data as you just pointed out and all these questions pop out. So what is the process that you guys use? You have the data, you've got the data scientist, you're looking at the data, probably asking all these questions, of course I'm getting questions from your customers as well. You're building models maybe to address those questions, training the models to get better and better and better and then you infuse that into your software. So maybe is that the process? Is it a little more complicated than that? Maybe you could fill in the gaps. So my personal opinion and I think many of my colleagues would agree with me on this starting with the business problem for us is really the key. There are ways to go about looking at the data and then pulling out the questions from the data but generally that is a long and involved process because it takes a lot of time to really get that deep into the data. So when we work we really start with what's the business problem that the customer's trying to solve and then what's the data that needs to be available for us to be able to solve that and then build the algorithm around that. So for us it's really starting with the business problem. Okay, so what are some of the big problems? We heard this morning that there's a problem in that there's more job openings than there are candidates and productivity. Business productivity is not being impacted. So there are two big chewy problems that data scientists can maybe attack and you guys seem to be passionate about those. So how does data science help solve those problems? So I think that at INFOR, I'll start off by saying at INFOR there's actually, I talked about the folks that are in our office in Cambridge but there's quite a bit of data science going on outside of our team and we are the data science team but there are lots of places inside of INFOR where this is happening. Either in products that contain some sort of algorithmic approach, the HCM team for sure, the talent science team which works on HCM. That's a team that's led by Jill Strange and we work with them on certain projects in certain areas. They are very focused on solving some of those people related problems. For us we work a little bit more on the, some of the other areas we work on is sort of the manufacturing and distribution areas. We work with the healthcare side of things. So supply chain, healthcare. Exactly, so some of the other areas. Because there are, like I said, there are some strong teams out there that do data science, it's also incorporated with other things like the talent science team. So there's lots of examples of it out there. In terms of how we go about building it, so we, you know, like I was saying, we work on answering the business question up front, understanding the data, and then really sitting with the customer and building that out. And so the problems that come to us are often through customers who have particular things that they want to answer. So a lot of it is driven by customer questions and particular problems that they're facing. Some of it is driven by us. We have some ideas about things that we think would be really useful to customers. Either way, it ends up being a customer collaboration with us, with the product team, that eventually we want to roll it out to, to make sure that we're answering the problem in the way that the product team really feels it can be rolled out to customers and better used and more easily used by them. I assume it's a non-linear process. It's not like somebody comes to you with a problem and is, okay, we're going to go look at that. Okay, now we've got an answer. I mean, it's, you're more embedded into the development process than that. Can you just explain that? So we do have, we have a development team in Prague that does work with us. And it's depending on whether we're going, we think we're going to actually build a more, a product with aspects to it like a UI versus just a backend solution. It depends on how, you know, how we've decided we want to proceed with it. So for example, I was talking about inventory intelligence for healthcare. We also had pricing science for distribution. Both of those were built initially with UIs on them and customers could buy those separately. Now that we're, you know, in the cloud suites, that those are both being incorporated into the cloud suite. So we have, going back to where I was talking about our team in Prague, we sometimes build product, sort of a fully encased product working with them. And sometimes we work very closely with the development teams from the various cloud suites. And the product management team is always there to help us figure out sort of the long-term plan and how the different pieces fit together. You know, kind of big picture. You've got AI, right? And then the machine learning, pumping all kinds of data your way. So in historical time frames, it's all pretty new, this confluence, right, in terms of development. Where do you see it, like, 10 years from now, 20 years from now? What's that, what potential is there? We talk about human potential, unlocking human potential. Well, unlock it with that kind of technology. What are we looking at, do you think? You know, I think that's such a fascinating area and area of discussion and sort of thinking, forward thinking. I do believe in sort of this idea of augmented intelligence, and I think Charles was talking a little bit about that this morning, although not in those particular terms. But this idea that computers and machines and technology will actually help us do better and be better and be more productive. You know, so this idea of doing sort of the rote everyday tasks that we no longer have to spend time doing, you know, that'll free us up to think about the bigger problems and hopefully, you know, in my best self wants to say, we'll work on, you know, famine and poverty and all those problems in the world that really need our brains to focus on and work. And then the other interesting part of it is if you think about sort of the concept of singularity and are computers ever going to actually be able to think for themselves, you know, that's sort of another interesting piece when you talk about what's going to happen down the line. Maybe it won't happen in 10 years, maybe it will never happen, but there's definitely a lot of people out there who are well known and sort of tech and science who talk about that and talk about the fears related to that. That's a whole other piece, but it's fascinating to think about, you know, 10 years, 20 years from now, where are we going to be on that spectrum? How do you guys think about bias in AI and in data science? Because, you know, humans express bias, tribalism. There's inherent, that's inherent in human nature. If machines are sort of mimicking humans, how do you deal with that and adjudicate? Yeah, and it's definitely a concern. It's another, there's a lot of writings out there and articles out there right now about bias in machine learning and in AI, and it's definitely a concern. I actually read, so just being aware of it, I think is the first step, right, because as scientists and developers develop these algorithms, going into it consciously knowing that this is something they have to protect against, I think is the first step, for sure. And then, you know, I was just reading an article just recently about another company who is building sort of a bias tracker, so a way to actually monitor your algorithm and identify places where there is perhaps bias coming in. So I do think we'll start to see more of those things. It gets very complicated because when you start talking about deep learning and networks and AI, it's very difficult to actually understand what's going on under the covers, right? It's really hard to get in and say, this is the reason why your AI told you this, that's very hard to do. So it's not going to be an easy process, but I think that we're going to start to see that kind of technology. Well, we heard this morning about some sort of systems that could help my interpretation automate and speed up and minimize the hassle of performance reviews. Yes. And that's the classic example. You know, an assertive woman is called abrasive or aggressive and assertive man is called a great leader. So this is just a classic example of bias.  Your thoughts as a woman in tech and maybe can AI help resolve some of those biases? Yeah. Well, first of all, I want to say, you know, I'm very pleased to work in an organization where we have some very strong leaders who happen to be women. So I mentioned Don Rose, who designed our IAH solution. I mentioned Jill Strange, who runs the talent science organization. Half of my team is women. So particularly inside of sort of the science area inside of INFOR, I've been very pleased with the way we've built out some of that skill set. And I'm also a member, an active member of WIN. So the women's INFOR network is something I'm very involved with. So I meet a lot of people across our organization, a lot of women across our organization who have, you know, just really strong technology supporters, really intelligent sort of go getter type of people. And it's great to see that inside of INFOR. I think there's a lot of work to be done for sure. And you can always find stories, you know, from other, whether it's coming out of Silicon Valley or other places where you hear some really sort of arcane sounding things that are still happening in the industry. And so some of those things, it's, you know, it's disappointing certainly to hear that. But I think Van Jones said something this morning about how, and I liked the way he said it and I'm not going to be able to say it exactly, but he said something along the lines of, like the ground is there, the formation is starting to get us moving in the right direction. And I think, you know, I'm hopeful for the future that we're heading in that way. And I think, you know, again, he sort of said something like once the groundswell starts going in that direction, people will really jump in and we'll see the benefits of being more diverse, whether it's across, you know, having more women or having more people of color or however, you know, however things expand. And that's just going to make us all better and more efficient and more productive. I think that's a great thing. You know, there's a spectrum, right? On the one side of the spectrum, there's intolerable and unacceptable behavior, which is just, this should be zero tolerance in my opinion, there's a passion of ours in theCUBE. The other side of that spectrum is inclusion. And it's a challenge that we have as a small company. And I remember having a conversation earlier this year with an individual and we talked about quotas. And I don't think that's the answer. And her comment was no, that's not the answer. You have to endeavor to reach deeper beyond your existing network, which is hard sometimes for us because you're so busy, you're running around, it's like, okay, it's the convenient thing to do. But you got to peel the onion on that network and actually take the extra time and make it a priority. I mean, your thoughts on that? No, I think that's a good point. I mean, if I think about who my circle of, my circle is, right? And the people that I know and I interact with, you know, if I only reach out to the smallest, the smallest group of people, I'm not getting really out, you know, beyond my initial circle. So I think that's a very good point. And I think that that's, we have to find ways to be more interactive and pull from different areas. I think it's interesting, bring, so coming back to data science for a minute, if you sort of think about the evolution of where we got to, how we got to today, where, you know, now we're really pulling people from science areas and math areas and technology areas and data scientists are coming from lots of places, right? And you don't always have to have a PhD, right? You don't necessarily have to come up through that system to be a good data scientist. And I think to see more of that and really people going beyond, beyond just sort of the traditional circles and the traditional paths to really find people that you wouldn't normally identify, you know, to bring into that path is going to help us just in general be more diverse in our approach. Well, it certainly seems like it's embedded in the company culture. I think the great reason for you to be so optimistic going forward, not only about your job but about the way your company is going about doing your job. What would you advise young people generally who want to crack into the data science field, but specifically women who have clearly are underrepresented in technology? Yeah, so I think we're starting to see more and more women enter the field. Again, it's one of those people know it and so there's less of a, because people are aware of it, there's more, there's more tendency to be more inclusive. But I definitely think, you know, just go for it, right? I mean, just if it's something you're interested in and you want to try it out, you know, go to a coding camp and take a science class and there's so many online resources now. I mean, there's, you know, the massive online courses that you can take. So even if you're hesitant about it, there are ways you can kind of be at home and try it out and see if it's the right thing for you. Just stick your toe in the water. Yes, exactly, exactly. Try it out and see and then decide if it's the right thing for you. But I think there's lots of different ways to sort of check it out. Again, you can take a course, you can actually get a degree. There's a wide range of things that you can do to kind of experiment with it and then find out if it's right for you. If you're not happy with the hiring opportunities out there, just start a company. That's my advice. That's right. I agree, I definitely agree. We appreciate the time and great advice too. Thank you so much. That's absolutely great. Lee Martin joining us here. At Inform 18, we're live in Washington, D.C. You're watching the exclusive coverage right here on theCUBE.