>>Okay. We're back with Ari Basu, who is Cisco's resident philosopher, who also holds a master's in computer science. We're gonna have to unpack that a little bit and Najati chair he who's technical lead at Cisco. Welcome guys. Thanks for coming on the cube. >>Happy to be here. Thanks a >>Lot. All right, let's get into it. We want you to explain how Cisco validated the SBRI technology and the proof points that, that you have, that it actually works as advertised. So first Outre tell first, tell us about Cisco tech. What does Cisco tech do? >>So T is otherwise it's an acronym for technical assistance center is Cisco's support arm, the support organization, and, you know, the risk of sounding like I'm spotting a corporate line. The, the easiest way to summarize what tag does is provide world class support to Cisco customers. What that means is we have about 8,000 engineers worldwide, and any of our Cisco customers can either go on our web portal or call us to open a support request. And we get about 2.2 million of these support requests a year. And what these support requests are, are essentially the customer will describe something that they need done some networking goal that they have, that they wanna accomplish. And then it's tax job to make sure that that goal does get accomplished. Now, it could be something like they're having trouble with an existing network solution, and it's not working as expected, or it could be that they're integrating with a new solution. >>They're, you know, upgrading devices, maybe there's a hardware failure, anything really to do with networking support and, you know, the customer's network goals. If they open up a case for request for help, then tax job is to, is to respond and make sure the customer's, you know, questions and requirements are met about 44% of these support requests are usually trivial and, you know, can be solved within a call or within a day. But the rest of tax cases really involve getting into the network device, looking at logs. It's a very technical role. It's a very technical job. You're look you're, you need to be conversing with network solutions, their designs protocols, et cetera. >>Wow. So 56% non-trivial. And so I would imagine you spend a lot of time digging through through logs. Is that, is that true? Can you quantify that like, you know, every month, how much time you spend digging through logs and is that a pain point? >>Yeah, it's interesting. You asked that because when we started this on this journey to augment our support engineers workflow with zebra solution, one of the things that we did was we went out and asked our engineers what their experience was like doing log analysis. And the anecdotal evidence was that on average, an engineer will spend three out of their eight hours reviewing logs, either online or offline. So what that means is either with the customer live on a WebEx, they're going to be going over logs, network, state information, et cetera, or they're gonna do it offline, where the customer sends them the logs, it's attached to a, you know, a service request and they review it and try to figure out what's going on and provide the customer with information. So it's a very large chunk of our day. You know, I said 8,000 plus engineers, and so three hours a day, that's 24,000 man hours a day spent on long analysis. >>Now the struggle with logs or analyzing logs is there by out of necessity. Logs are very contr contr. They try to pack a lot of information in a very little space. And this is for performance reasons, storage reasons, et cetera, BEC, but the side effect of that is they're very esoteric. So they're hard to read if you're not conversant, if you're not the developer who wrote these logs or you or you, aren't doing code deep dives. And you're looking at where this logs getting printed and things like that, it may not be immediately obvious or even after a low while it may not be obvious what that log line means or how it correlates to whatever problem you're troubleshooting. So it requires tenure. It requires, you know, like I was saying before, it requires a lot of knowledge about the protocol what's expected because when you're doing log analysis, what you're really looking for is a needle in a haystack. You're looking for that one anomalous event, that single thing that tells you this shouldn't have happened. And this was a problem right now doing that kind of anomaly detection requires you to know what is normal. It requires, you know, what the baseline is. And that requires a very in-depth understanding of, you know, the state changes for that network solution or product. So it requires time, tenure and expertise to do well. And it takes a lot of time even when you have that kind of expertise. >>Wow. So thank you, archery. And Najati, that's, that's about, that's almost two days a week for, for a technical resource. That's that's not inexpensive. So what was Cisco looking for to sort of help with this and, and how'd you stumble upon zebra? >>Yeah, so, I mean, we have our internal automation system, which has been running more than a decade now. And what happens is when a customer attaches a log bundle or diagnostic bundle into the service request, we take that from the Sr we analyze it and we represent some kind of information. You know, it can be alert or some tables, some graph to the engineer, so they can, you know, troubleshoot this particular issue. This is an incredible system, but it comes with its own challenges around maintenance to keep it up to date and relevant with Cisco's new products or new version of the product, new defects, new issues, and all kind of things. And when I, what I mean with those challenges are, let's say Cisco comes up with a product today. We need to come together with those engineers. We need to figure out how this bundle works, how it's structured out. >>We need to select individual logs, which are relevant and then start modeling these logs and get some values out of those logs, using pars or some rag access to come to a level that we can consume the logs. And then people start writing rules on top of that abstraction. So people can say in this log, I'm seeing this value together with this other value in another log, maybe I'm hitting this particular defect. So that's how it works. And if you look at it, the abstraction, it can fail the next time. And the next release when the development or the engineer decides to change that log line, which you write that rag X, or we can come up with a new version, which we completely change the services or processes, then whatever you have wrote needs to be re written for that new service. And we see that a lot with products, like for instance, WebEx, where you have a very short release cycle that things can change maybe the next week with a new release. >>So whatever you are writing, especially for that abstraction and for those rules are maybe not relevant with that new release. With that being sake, we have a incredible rule creation process and governance process around it, which starts with maybe a defect. And then it takes it to a level where we have an automation in place. But if you look at it, this really ties to human bandwidth. And our engineers are really busy working on, you know, customer facing, working on issues daily and sometimes creating these rules or these pars are not their biggest priorities, so they can be delayed a bit. So we have this delay between a new issue being identified to a level where we have the automation to detect it next time that some customer faces it. So with all these questions and with all challenges in mind, we start looking into ways of actually how we can automate these automations. >>So these things that we are doing manually, how we can move it a bit further and automate. And we had actually a couple of things in mind that we were looking for and this being one of them being, this has to be product agnostic. Like if Cisco comes up with a product tomorrow, I should be able to take it logs without writing, you know, complex regs, pars, whatever, and deploy it into this system. So it can embrace our logs and make sense of it. And we wanted this platform to be unsupervised. So none of the engineers need to create rules, you know, label logs. This is bad. This is good. Or train the system like which requires a lot of computational power. And the other most important thing for us was we wanted this to be not noisy at all, because what happens with noises when your level of false PE positives really high your engineers start ignoring the good things between that noise. >>So they start the next time, you know, thinking that this thing will not be relevant. So we want something with a lot or less noise. And ultimately we wanted this new platform or new framework to be easily adaptable to our existing workflows. So this is where we started. We start looking into the, you know, first of all, internally, if we can build this thing and also start researching it, and we came up to Zeum actually Larry, one of the co co-founders of Zeum. We came upon his presentation where he clearly explained why this is different, how this works, and it immediately clicked in. And we said, okay, this is exactly what we were looking for. We dived deeper. We checked the block posts where SBRI guys really explained everything very clearly there, they are really open about it. And most importantly, there is a button in their system. >>So what happens usually with AI ML vendors is they have this button where you fill in your details and sales guys call you back. And, you know, we explain the system here. They were like, this is our trial system. We believe in the system, you can just sign up and try it yourself. And that's what we did. We took our, one of our Cisco live DNA center, wireless platforms. We start streaming logs out of it. And then we synthetically, you know, introduce errors, like we broke things. And then we realized that zebra was really catching the errors perfectly. And on top of that, it was really quiet unless you are really breaking something. And the other thing we realized was during that first trial is zebra was actually bringing a lot of context on top of the logs. During those failures, we work with couple of technical leaders and they said, okay, if this failure happens, I I'm expecting this individual log to be there. And we found out with zebra, apart from that individual log, there were a lot of other things which gives a bit more context around the root columns, which was great. And that's where we wanted to take it to the next level. Yeah. >>Okay. So, you know, a couple things to unpack there. I mean, you have the dart board behind you, which is kind of interesting, cuz a lot of times it's like throwing darts at the board to try to figure this stuff out. But to your other point, Cisco actually has some pretty rich tools with AppD and doing observability and you've made acquisitions like thousand eyes. And like you said, I'm, I'm presuming you gotta eat your own dog food or drink your own champagne. And so you've gotta be tools agnostic. And when I first heard about Z zebra, I was like, wait a minute. Really? I was kind of skeptical. I've heard this before. You're telling me all I need is plain text and, and a timestamp. And you got my problem solved. So, and I, I understand that you guys said, okay, let's run a POC. Let's see if we can cut that from, let's say two days a week down to one day, a week. In other words, 50%, let's see if we can automate 50% of the root cause analysis. And, and so you funded a POC. How, how did you test it? You, you put, you know, synthetic, you know, errors and problems in there, but how did you test that? It actually works Najati >>Yeah. So we, we wanted to take it to the next level, which is meaning that we wanted to back test is with existing SARS. And we decided, you know, we, we chose four different products from four different verticals, data center, security, collaboration, and enterprise networking. And we find out SARS where the engineer put some kind of log in the resolution summary. So they closed the case. And in the summary of the Sr, they put, I identified these log lines and they led me to the roots and we, we ingested those log bundles. And we, we tried to see if Zeum can surface that exact same log line in their analysis. So we initially did it with archery ourself and after 50 tests or so we were really happy with the results. I mean, almost most of them, we saw the log line that we were looking for, but that was not enough. >>And we brought it of course, to our management and they said, okay, let's, let's try this with real users because the log being there is one thing, but the engineer reaching to that log is another take. So we wanted to make sure that when we put it in front of our users, our engineers, they can actually come to that log themselves because, you know, we, we know this platform so we can, you know, make searches and find whatever we are looking for, but we wanted to do that. So we extended our pilots to some selected engineers and they tested with their own SRSS. Also do some back testing for some SARS, which are closed in the past or recently. And with, with a sample set of, I guess, close to 200 SARS, we find out like majority of the time, almost 95% of the time the engineer could find the log they were looking for in zebra analysis. >>Yeah. Okay. So you were looking for 50%, you got to 95%. And my understanding is you actually did it with four pretty well known Cisco products, WebEx client DNA center, identity services, engine ISE, and then, then UCS. Yes. Unified pursuit. So you use actual real data and, and that was kind of your proof proof point, but Ari. So that's sounds pretty impressive. And, and you've have you put this into production now and what have you found? >>Well, yes, we're, we've launched this with the four products that you mentioned. We're providing our tech engineers with the ability, whenever a, whenever a support bundle for that product gets attached to the support request. We are processing it, using sense and then providing that sense analysis to the tech engineer for their review. >>So are you seeing the results in production? I mean, are you actually able to, to, to reclaim that time that people are spending? I mean, it was literally almost two days a week down to, you know, a part of a day, is that what you're seeing in production and what are you able to do with that extra time and people getting their weekends back? Are you putting 'em on more strategic tasks? How are you handling that? >>Yeah. So, so what we're seeing is, and I can tell you from my own personal experience using this tool, that troubleshooting any one of the cases, I don't take more than 15 to 20 minutes to go through the zebra report. And I know within that time either what the root causes or I know that zebra doesn't have the information that I need to solve this particular case. So we've definitely seen, well, it's been very hard to measure exactly how much time we've saved per engineer, right? What we, again, anecdotally, what we've heard from our users is that out of those three hours that they were spending per day, we're definitely able to reclaim at least one of those hours and, and what, even more importantly, you know, what the kind of feedback that we've gotten in terms of, I think one statement that really summarizes how Zebra's impacted our workflow was from one of our users. >>And they said, well, you know, until you provide us with this tool, log analysis was a very black and white affair, but now it's become really colorful. And I mean, if you think about it, log analysis is indeed black and white. You're looking at it on a terminal screen where the background is black and the text is white, or you're looking at it as a text where the background is white and the text is black, but what's what they're really trying to say. Is there hardly any visual cues that help you navigate these logs, which are so esoteric, so dense, et cetera. But what XRM does is it provides a lot of color and context to the whole process. So now you're able to quickly get to, you know, using their word cloud, using their interactive histogram, using the summaries of every incident. You're very quickly able to summarize what might be happening and what you need to look into. >>Like, what are the important aspects of this particular log bundle that might be relevant to you? So we've definitely seen that a really great use case that kind of encapsulates all of this was very early on in our experiment. There was, there was this support request that had been escalated to the business unit or the development team. And the tech engineer had really, they, they had an intuition about what was going wrong because of their experience because of, you know, the symptoms that they'd seen. They kind of had an idea, but they weren't able to convince the development team because they weren't able to find any evidence to back up what they thought was happening. And we, it was entirely happenstance that I happened to pick up that case and did an analysis using Seebri. And then I sat down with the attack engineer and we were very quickly within 15 minutes, we were able to get down to the exact sequence of events that highlighted what the customer thought was happening, evidence of what the, so not the customer, what the attack engineer thought was the, was a root cause. It was a rude pause. And then we were able to share that evidence with our business unit and, you know, redirect their resources so that we could change down what the problem was. And that really has been, that that really shows you how that color and context helps in log analysis. >>Interesting. You know, we do a fair amount of work in the cube in the RPA space, the robotic process automation and the narrative in the press when our RPA first started taking off was, oh, it's, you know, machines replacing humans, or we're gonna lose jobs. And, and what actually happened was people were just eliminating mundane tasks and, and the, the employee's actually very happy about it. But my question to you is, was there ever a reticence amongst your team? Like, oh, wow, I'm gonna, I'm gonna lose my job if the machine's gonna replace me, or have you found that people were excited about this and what what's been the reaction amongst the team? >>Well, I think, you know, every automation and AI project has that immediate gut reaction of you're automating away our jobs and so forth. And there is initially there's a little bit of reticence, but I mean, it's like you said, once you start using the tool, you realize that it's not your job, that's getting automated away. It's just that your job's becoming a little easier to do, and it's faster and more efficient. And you're able to get more done in less time. That's really what we're trying to accomplish here at the end of the day, rim will identify these incidents. They'll do the correlation, et cetera. But if you don't understand what you're reading, then that information's useless to you. So you need the human, you need the network expert to actually look at these incidents, but what we are able to skin away or get rid of is all of the fat that's involved in our, you know, in our process, like without having to download the bundle, which, you know, when it's many gigabytes in size, and now we're working from home with the pandemic and everything, you're, you know, pulling massive amounts of logs from the corporate network onto your local device that takes time and then opening it up, loading it in a text editor that takes time. >>All of these things are we're trying to get rid of. And instead we're trying to make it easier and quicker for you to find what you're looking for. So it's like you said, you take away the mundane, you take away the, the difficulties and the slog, but you don't really take away the work, the work still needs to be done. >>Yeah. Great guys. Thanks so much. Appreciate you sharing your story. It's quite, quite fascinating. Really. Thank you for coming on. >>Thanks for having us. >>You're very welcome. Okay. In a moment, I'll be back to wrap up with some final thoughts. This is Dave Valante and you're watching the, >>So today we talked about the need, not only to gain end to end visibility, but why there's a need to automate the identification of root cause problems and doing so with modern technology and machine intelligence can dramatically speed up the process and identify the vast majority of issues right out of the box. If you will. And this technology, it can work with log bundles in batches, or with real time data, as long as there's plain text and a timestamp, it seems Zebra's technology will get you the outcome of automating root cause analysis with very high degrees of accuracy. Zebra is available on Preem or in the cloud. Now this is important for some companies on Preem because there's really some sensitive data inside logs that for compliance and governance reasons, companies have to keep inside their four walls. Now SBRI has a free trial. Of course they better, right? So check it out@zebra.com. You can book a live demo and sign up for a free trial. Thanks for watching this special presentation on the cube, the leader in enterprise and emerging tech coverage on Dave Valante and.

(contemplative upbeat music) >> Hello and welcome to this CUBE Conversation. I'm John Furrier, your host of theCUBE, here in Palo Alto, California. Got a great topic on expanding capabilities for urgent computing. Dan Stanzione, he's Executive Director of TACC, the Texas Advanced Computing Center, and Rajesh Pohani, VP of PowerEdge, HPC Core Compute at Dell Technologies. Gentlemen, welcome to this CUBE Conversation. >> Thanks, John. >> Thanks, John, good to be here. >> Rajesh, you got a lot of computing in PowerEdge, HPC, Core Computing. I mean, I get a sense that you love compute, so we'll jump right into it. And of course, I got to love TACC, Texas Advanced Computing Center. I can imagine a lot of stuff going on there. Let's start with TACC. What is the Texas Advanced Computing Center? Tell us a little bit about that. >> Yeah, we're part of the University of Texas at Austin here, and we build large-scale supercomputers, data systems, AI systems, to support open science research. And we're mainly funded by the National Science Foundation, so we support research projects in all fields of science, all around the country and around the world. Actually, several thousand projects at the moment. >> But tied to the university, got a lot of gear, got a lot of compute, got a lot of cool stuff going on. What's the coolest thing you got going on right now? >> Well, for me, it's always the next machine, but I think science-wise, it's the machines we have. We just finished deploying Lonestar6, which is our latest supercomputer, in conjunction with Dell. A little over 600 nodes of those PowerEdge servers that Rajesh builds for us. Which makes more than 20,000 that we've had here over the years, of those boxes. But that one just went into production. We're designing new systems for a few years from now, where we'll be even larger. Our Frontera system was top five in the world two years ago, just fell out of the top 10. So we've got to fix that and build the new top-10 system sometime soon. We always have a ton going on in large-scale computing. >> Well, I want to get to the Lonestar6 in a minute, on the next talk track, but... What are some of the areas that you guys are working on that are making an impact? Take us through, and we talked before we came on camera about, obviously, the academic affiliation, but also there's a real societal impact of the work you're doing. What are some of the key areas that the TACC is making an impact? >> So there's really a huge range from new microprocessors, new materials design, photovoltaics, climate modeling, basic science and astrophysics, and quantum mechanics, and things like that. But I think the nearest-term impacts that people see are what we call urgent computing, which is one of the drivers around Lonestar and some other recent expansions that we've done. And that's things like, there's a hurricane coming, exactly where is it going to land? Can we refine the area where there's going to be either high winds or storm surge? Can we assess the damage from digital imagery afterwards? Can we direct first responders in the optimal routes? Similarly for earthquakes, and a lot recently, as you might imagine, around COVID. In 2020, we moved almost a third of our resources to doing COVID work, full-time. >> Rajesh, I want to get your thoughts on this, because Dave Vellante and I have been talking about this on theCUBE recently, a lot. Obviously, people see what cloud's, going on with the cloud technology, but compute and on-premises, private cloud's been growing. If you look at the hyperscale on-premises and the edge, if you include that in, you're seeing a lot more user consumption on-premises, and now, with 5G, you got edge, you mentioned first responders, Dan. This is now pointing to a new architectural shift. As the VP of PowerEdge and HPC and Core Compute, you got to look at this and go, "Hmm." If Compute's going to be everywhere, and in locations, you got to have that compute. How does that all work together? And how do you do advanced computing, when you have these urgent needs, as well as real-time in a new architecture? >> Yeah, John, I mean, it's a pretty interesting time when you think about some of the changing dynamics and how customers are utilizing Compute in the compute needs in the industry. Seeing a couple of big trends. One, the distribution of Compute outside of the data center, 5G is really accelerating that, and then you're generating so much data, whether what you do with it, the insights that come out of it, that we're seeing more and more push to AI, ML, inside the data center. Dan mentioned what he's doing at TACC with computational analysis and some of the work that they're doing. So what you're seeing is, now, this push that data in the data center and what you do with it, while data is being created out at the edge. And it's actually this interesting dichotomy that we're beginning to see. Dan mentioned some of the work that they're doing in medical and on COVID research. Even at Dell, we're making cycles available for COVID research using our Zenith cluster, that's located in our HPC and AI Innovation Lab. And we continue to partner with organizations like TACC and others on research activities to continue to learn about the virus, how it mutates, and then how you treat it. So if you think about all the things, and data that's getting created, you're seeing that distribution and it's really leading to some really cool innovations going forward. >> Yeah, I want to get to that COVID research, but first, you mentioned a few words I want to get out there. You mentioned Lonestar6. Okay, so first, what is Lonestar6, then we'll get into the system aspect of it. Take us through what that definition is, what is Lonestar6? >> Well, as Dan mentioned, Lonestar6 is a Dell technology system that we developed with TACC, it's located at the University of Texas at Austin. It consists of more than 800 Dell PowerEdge 6525 servers that are powered with 3rd Generation AMD EPYC processors. And just to give you an example of the scale of this cluster, it could perform roughly three quadrillion operations per second. That's three petaFLOPS, and to match what Lonestar6 can compute in one second, a person would have to do one calculation every second for a hundred million years. So it's quite a good-size system, and quite a powerful one as well. >> Dan, what's the role that the system plays, you've got petaFLOPS, what, three petaFLOPS, you mentioned? That's a lot of FLOPS! So obviously urgent computing, what's cranking through the system there? Take us through, what's it like? >> Sure, well, there there's a mix of workloads on it, and on all our systems. So there's the urgent computing work, right? Fast turnaround, near real-time, whether it's COVID research, or doing... Project now where we bring in MRI data and are doing sort of patient-specific dosing for radiation treatments and chemotherapy, tailored to your tumor, instead of just the sort of general for people your size. That all requires sort of real-time turnaround. There's a lot AI research going on now, we're incorporating AI in traditional science and engineering research. And that uses an awful lot of data, but also consumes a huge amount of cycles in training those models. And then there's all of our traditional, simulation-based workloads and materials and digital twins for aircraft and aircraft design, and more efficient combustion in more efficient photovoltaic materials, or photovoltaic materials without using as much lead, and things like that. And I'm sure I'm missing dozens of other topics, 'cause, like I said, that one really runs every field of science. We've really focused the Lonestar line of systems, and this is obviously the sixth one we built, around our sort of Texas-centric users. It's the UT Austin users, and then with contributions from Texas A&M , and Texas Tech and the University of Texas system, MD Anderson Healthcare Center, the University of North Texas. So users all around the state, and every research problem that you might imagine, those are into. We're just ramping up a project in disaster information systems, that's looking at the probabilities of flooding in coastal Texas and doing... Can we make building code changes to mitigate impact? Do we have to change the standard foundation heights for new construction, to mitigate the increasing storm surges from these sort of slow storms that sit there and rain, like hurricanes didn't used to, but seem to be doing more and more. All those problems will run on Lonestar, and on all the systems to come, yeah. >> It's interesting, you mentioned urgent computing, I love that term because it could be an event, it could be some slow kind of brewing event like that rain example you mentioned. It could also be, obviously, with the healthcare, and you mentioned COVID earlier. These are urgent, societal challenges, and having that available, the processing capability, the compute, the data. You mentioned digital twins. I can imagine all this new goodness coming from that. Compare that, where we were 10 years ago. I mean, just from a mind-blowing standpoint, you have, have come so far, take us through, try to give a context to the level of where we are now, to do this kind of work, and where we were years ago. Can you give us a feel for that? >> Sure, there's a lot of ways to look at that, and how the technology's changed, how we operate around those things, and then sort of what our capabilities are. I think one of the big, first, urgent computing things for us, where we sort of realized we had to adapt to this model of computing was about 15 years ago with the big BP Gulf Oil spill. And suddenly, we were dumping thousands of processors of load to figure out where that oil spill was going to go, and how to do mitigation, and what the potential impacts were, and where you need to put your containment, and things like that. And it was, well, at that point we thought of it as sort of a rare event. There was another one, that I think was the first real urgent computing one, where the space shuttle was in orbit, and they knew something had hit it during takeoff. And we were modeling, along with NASA and a bunch of supercomputers around the world, the heat shield and could they make reentry safely? You have until they come back to get that problem done, you don't have months or years to really investigate that. And so, what we've sort of learned through some of those, the Japanese tsunami was another one, there have been so many over the years, is that one, these sort of disasters are all the time, right? One thing or another, right? If we're not doing hurricanes, we're doing wildfires and drought threat, if it's not COVID. We got good and ready for COVID through SARS and through the swine flu and through HIV work, and things like that. So it's that we can do the computing very fast, but you need to know how to do the work, right? So we've spent a lot of time, not only being able to deliver the computing quickly, but having the data in place, and having the code in place, and having people who know the methods who know how to use big computers, right? That's been a lot of what the COVID Consortium, the White House COVID Consortium, has been about over the last few years. And we're actually trying to modify that nationally into a strategic computing reserve, where we're ready to go after these problems, where we've run drills, right? And if there's a, there's a train that derails, and there's a chemical spill, and it's near a major city, we have the tools and the data in place to do wind modeling, and we have the terrain ready to go. And all those sorts of things that you need to have to be ready. So we've really sort of changed our sort of preparedness and operational model around urgent computing in the last 10 years. Also, just the way we scheduled the system, the ability to sort of segregate between these long-running workflows for things that are really important, like we displaced a lot of cancer research to do COVID research. And cancer's still important, but it's less likely that we're going to make an impact in the next two months, right? So we have to shuffle how we operate things and then just, having all that additional capacity. And I think one of the things that's really changed in the models is our ability to use AI, to sort of adroitly steer our simulations, or prune the space when we're searching parameters for simulations. So we have the operational changes, the system changes, and then things like adding AI on the scientific side, since we have the capacity to do that kind of things now, all feed into our sort of preparedness for this kind of stuff. >> Dan, you got me sold, I want to come work with you. Come on, can I join the team over there? It sounds exciting. >> Come on down! We always need good folks around here, so. (laughs) >> Rajesh, when I- >> Almost 200 now, and we're always growing. >> Rajesh, when I hear the stories about kind of the evolution, kind of where the state of the art is, you almost see the innovation trajectory, right? The growth and the learning, adding machine learning only extends out more capabilities. But also, Dan's kind of pointing out this kind of response, rapid compute engine, that they could actually deploy with learnings, and then software, so is this a model where anyone can call up and get some cycles to, say, power an autonomous vehicle, or, hey, I want to point the machinery and the cycles at something? Is the service, do you guys see this going that direction, or... Because this sounds really, really good. >> Yeah, I mean, one thing that Dan talked about was, it's not just the compute, it's also having the right algorithms, the software, the code, right? The ability to learn. So I think when those are set up, yeah. I mean, the ability to digitally simulate in any number of industries and areas, advances the pace of innovation, reduces the time to market of whatever a customer is trying to do or research, or even vaccines or other healthcare things. If you can reduce that time through the leverage of compute on doing digital simulations, it just makes things better for society or for whatever it is that we're trying to do, in a particular industry. >> I think the idea of instrumenting stuff is here forever, and also simulations, whether it's digital twins, and doing these kinds of real-time models. Isn't really much of a guess, so I think this is a huge, historic moment. But you guys are pushing the envelope here, at University of Texas and at TACC. It's not just research, you guys got real examples. So where do you guys see this going next? I see space, big compute areas that might need some data to be cranked out. You got cybersecurity, you got healthcare, you mentioned oil spill, you got oil and gas, I mean, you got industry, you got climate change. I mean, there's so much to tackle. What's next? >> Absolutely, and I think, the appetite for computing cycles isn't going anywhere, right? And it's only going to, it's going to grow without bound, essentially. And AI, while in some ways it reduces the amount of computing we do, it's also brought this whole new domain of modeling to a bunch of fields that weren't traditionally computational, right? We used to just do engineering, physics, chemistry, were all super computational, but then we got into genome sequencers and imaging and a whole bunch of data, and that made biology computational. And with AI, now we're making things like the behavior of human society and things, computational problems, right? So there's this sort of growing amount of workload that is, in one way or another, computational, and getting bigger and bigger. So that's going to keep on growing. I think the trick is not only going to be growing the computation, but growing the software and the people along with it, because we have amazing capabilities that we can bring to bear. We don't have enough people to hit all of them at once. And so, that's probably going to be the next frontier in growing out both our AI and simulation capability, is the human element of it. >> It's interesting, when you think about society, right? If the things become too predictable, what does a democracy even look like? If you know the election's going to be over two years from now in the United States, or you look at these major, major waves >> Human companies don't know. >> of innovation, you say, "Hmm." So it's democracy, AI, maybe there's an algorithm for checking up on the AI 'cause biases... So, again, there's so many use cases that just come out of this. It's incredible. >> Yeah, and bias in AI is something that we worry about and we work on, and on task forces where we're working on that particular problem, because the AI is going to take... Is based on... Especially when you look at a deep learning model, it's 100% a product of the data you show it, right? So if you show it a biased data set, it's going to have biased results. And it's not anything intrinsic about the computer or the personality, the AI, it's just data mining, right? In essence, right, it's learning from data. And if you show it all images of one particular outcome, it's going to assume that's always the outcome, right? It just has no choice, but to see that. So how we deal with bias, how do we deal with confirmation, right? I mean, in addition, you have to recognize, if you haven't, if it gets data it's never seen before, how do you know it's not wrong, right? So there's about data quality and quality assurance and quality checking around AI. And that's where, especially in scientific research, we use what's starting to be called things like physics-informed or physics-constrained AI, where the neural net that you're using to design an aircraft still has to follow basic physical laws in its output, right? Or if you're doing some materials or astrophysics, you still have to obey conservation of mass, right? So I can't say, well, if you just apply negative mass on this other side and positive mass on this side, everything works out right for stable flight. 'Cause we can't do negative mass, right? So you have to constrain it in the real world. So this notion of how we bring in the laws of physics and constrain your AI to what's possible is also a big part of the sort of AI research going forward. >> You know, Dan, you just, to me just encapsulate the science that's still out there, that's needed. Computer science, social science, material science, kind of all converging right now. >> Yeah, engineering, yeah, >> Engineering, science, >> slipstreams, >> it's all there, >> physics, yeah, mmhmm. >> it's not just code. And, Rajesh, data. You mentioned data, the more data you have, the better the AI. We have a world what's going from silos to open control planes. We have to get to a world. This is a cultural shift we're seeing, what's your thoughts? >> Well, it is, in that, the ability to drive predictive analysis based on the data is going to drive different behaviors, right? Different social behaviors for cultural impacts. But I think the point that Dan made about bias, right, it's only as good as the code that's written and the way that the data is actually brought into the system. So making sure that that is done in a way that generates the right kind of outcome, that allows you to use that in a predictive manner, becomes critically important. If it is biased, you're going to lose credibility in a lot of that analysis that comes out of it. So I think that becomes critically important, but overall, I mean, if you think about the way compute is, it's becoming pervasive. It's not just in selected industries as damage, and it's now applying to everything that you do, right? Whether it is getting you more tailored recommendations for your purchasing, right? You have better options that way. You don't have to sift through a lot of different ideas that, as you scroll online. It's tailoring now to some of your habits and what you're looking for. So that becomes an incredible time-saver for people to be able to get what they want in a way that they want it. And then you look at the way it impacts other industries and development innovation, and it just continues to scale and scale and scale. >> Well, I think the work that you guys are doing together is scratching the surface of the future, which is digital business. It's about data, it's about out all these new things. It's about advanced computing meets the right algorithms for the right purpose. And it's a really amazing operation you guys got over there. Dan, great to hear the stories. It's very provocative, very enticing to just want to jump in and hang out. But I got to do theCUBE day job here, but congratulations on success. Rajesh, great to see you and thanks for coming on theCUBE. >> Thanks for having us, John. >> Okay. >> Thanks very much. >> Great conversation around urgent computing, as computing becomes so much more important, bigger problems and opportunities are around the corner. And this is theCUBE, we're documenting it all here. I'm John Furrier, your host. Thanks for watching. (contemplative music)

>>Mm. Okay, we're back. Digging into the infrastructure to make hybrid work possible. High performance, cost effective, scalable and secure. That's what it's all about. So far, we've covered the rapid migration to WiFi 60 technology and the role that switching is going to play. And now we're gonna get into private five g to do that. Let's welcome Masumi here. Who is vice president and general manager of mobile cable and the Iot business at Cisco and Greg Dorey, who is the vice president of product management for the networking experiences group of Cisco. He's responsible for Catalyst access that whole portfolio enterprise five G Cisco DNA spaces, Cisco, Iasi A lot of stuff there. Uh, Greg gentlemen, welcome, >>Dave. Thank you for having us. >>Yeah, our pleasure. So let's start with you on the topic of private five g five g. What do we need to know about that? And more specifically, you know what's unique about Cisco's private five G? >>So, most importantly, delivering private five G in enterprise terms that's super important to look at five p. Many of our peer groups might have got it wrong. We're looking at private five g with the lens of enterprise. What enterprise really needs is five g going to come and displace a lot of existing technology? Or is it going to help augment the technology that enterprise has an excellent Their digitisation is you need. I wanted to start Dave with the basic premise of hybrid work, and what hybrid work really means. Is it only for knowledge worker or is it for all workers? So we strongly believe hybrid work needs to empower all workers. It's not only connecting remote workers but also bringing people things and space together. And I strongly believe the combination of WiFi six n five g for private network is going to accelerate that journey, bringing people things and space together in a very, very cohesive way. Why are our offer is so unique? We are going to create a continent. Enterprises don't have to make a hard choice. They will be using WiFi technology and five G technology hand in hand without creating a disruption on their policy and identity systems. They don't have to rethink. Do I have to go and build a new background is a common background that will support both WiFi as well as five t Most importantly, delivering this enter offer as a service with the ease of consumption is of operation and trusted environment that they can put their mission critical workloads on. >>I like it. So couple takeaways there are inclusive of all workers, not just knowledge workers non disruptive. Everybody loves to hear that. And of course, the as a service model is key. So let me stay with you. I mean, we can't wait for five g, right? It's lightning fast. They've got super low latency, very high bandwidth. So that's what everybody is excited about. The question, though, is is five g gets introduced. You know it's going to power things like Coyote Networks. Is that going to replace WiFi and legacy Wired broadband? >>Absolutely not. So we see private five years, an augmentation to the enterprise on top of WiFi WiFi. As you heard in the previous conversation, WiFi is bringing more capability with WiFi six and WiFi 16 and five G is going to be yet another augmentation. WiFi and fight. The will coexist within enterprise for many years to come. I would like my friend Greg to talk a little bit about this continuum. Greg. >>Yeah, I think it's sort of like I like to say it's an and not an AR because there's enough use cases out there. Richard Pryor Spectrum And you know, spectrum >>is a constraint, so >>you have private five G, your WiFi six and both offer opportunities. So, for example, in an indoor carpet setting where you're basically connecting your phone for basic browsing or connecting your laptop, WiFi is sufficient. But if it's a process automation, uh, factory where you need seven nines of reliability, private five g is a better technology. Similarly outdoor large areas. It's probably private. Five g right like this, you can have easy handoff between public and private, so it's use case driven, and once it's used case driven, it's going to be an are because there's so many next time use cases, whether it's a are we are drones, self driving cars, you name it right, like And so I think these two technologies five g and Y 5 60 is gonna work hand in hand to deliver awesome outcomes for our customers. >>Yeah, and just the data volumes are gonna be incredible. We always talk about the data volumes. You ain't seen nothing yet is what I always say. But the thing is, every new tech that's introduced into the enterprise, you can almost be certain that is going to bring adoption challenges. And not only that also is going to bring changes in the way you do things. And that brings new complexities from an operational standpoint. So my question is, how are you addressing this with the introduction of five g. >>Dave, this is a fantastic question, and this is why we have spent me and Greg have spent tremendous amount of time to create continual. I'll start with the foundation first, back down. So we have been building this enterprise backbone, supporting what Wild Connexion as well as WiFi Connexion. We wanted to make sure that as private five G camps within enterprise, you don't have to rethink and reimagine your background is the common backbone that will support both WiFi WiFi six WiFi 60 as well as private five g. You rest assured that it is the same backbone that we have heard in the previous section on the Cap 90 that will also support a private key access. The second aspect of private five G is as you build any new technology into enterprise. Oftentimes we get into this trap to get to an outcome. We move fast and we create asylum. And then that silo operation creates a barriers to mainstream it. So upfront we have to think about not creating another silent and how we're doing it. Number one is a device that can connecting to WiFi network or a private five G network. You don't have to reimagine or rethink how I'm going to manage. The identity will create continue of the common identity across the WiFi access or five t access in the same environment. The second aspect of that is, how are we going to reach in all our staff are enterprise staff is well trained with WiFi technology and white technology. Now five G comes with tremendous amount of value and benefit, but it also comes with inherent technology complexity, learning problems. This is where our simple to consume simple to operate model of sass comes to play. That we're going to take all those complexity away. It is a cloud deliberate service enterprise don't have to go through this massive learning car. Adopting this technology last but not list on how you're going to manage your capital. Any new technology and enterprise, Oftentimes you need a huge amount of upfront investment to adopt the technology to get to the other side of getting the outcome. So again, our business model of SARS will allow Enterprise to adopt this new technology and pay as you go model to meet with enterprise needs. Finally, I also wanted to pass to break to touch a little bit more on how we are thinking about this common identity across any access in the enterprise. Greg to your >>So we we talk about it in two different ways. One is a lot of enterprises today use our identity and secure management platform. We call it Isis Co ice platform. And so years and years of policy and identities Excess service, radio service they use, uh, etcetera are plugged in already into our eyes. Right. So if you can share that with this private five years as a service, uh, infrastructure that Muslims been building, we think we'll be able to create that bridge because we're not forcing enterprises to create new identities, a new policy. So thats sort of step one to make it easier. Uh, you also talk through something where, in the case of a public five g network, for example, the It's very convenient because you take your phone out of your pocket and it's connected to the network, right? Was this for WiFi? You have to log into an S I D in your hotel or in your home and home. It's automatic, but that's that logging process that creates friction. And that's a problem, because then you can't be seamless. So we initiated what we call us open roaming, right? Like that's, uh, identity federation that we first created between identity owners. Could be carriers could be, um, anything that anyone who owns an identity and they will share with venues. And so if the sharing happens, then that Onboarding can be automatic and once on boarding is automatic, then it's easy to pass off between five and five G. And so that's again another way in which you can lower the adoption barriers because you share across public private G and WiFi networks. So these are two concrete examples of how we thought about lowering the barriers of adoption. As we enter into this heterogeneous >>world, >>I can't wait. Let's let's talk about how this thing scales in the go to market, what are the most likely or maybe preferred or obvious routes to market for private five g Francisco >>so they stay tuned when when they announce more about it. But I can also assure you that exposed to the spectrum is a challenge for many enterprises when it comes to cellular technology. In some countries, there are more spectrum accessible by enterprise. In many countries, that's not the case. So we have talked to very carefully that how do we bring this offer to the market? Partnering with many service providers and mobile operators, where in countries where we don't have direct access to the spectrum, our partnership with mobile operators that you will hear more about as we come to mobile world Congress is going to allow our enterprise to consume this technology even if they don't have the spectrum in places where the enterprise might have direct spectrum access. We'll also bring in our relativist providers to hide the complexity of the new technology on top of our cell services or a cloud deliberate services. This is the augmentation with the partnership with menaces providers and mobile operators that will ease this journey for enterprises are most important. Primitive in this journey is to keep it simple for enterprise. Make it intuitive and trust it from day one. >>Outstanding. Okay. Assume, Greg, Thanks so much. It's great to have you guys. I really appreciate your time. >>Thank you. Thank you. Mm mm.

>>we're back, we're assessing the as a service space. H. P. S. Green Lake announcements, my name is Dave balanta, you're watching the cube die on Hinchcliffe is here along with Holger muller, these are the constellation kids, extraordinary analysts guys. Great to see you again. I mean it super experienced. You guys, you deal with practitioners, you deal your technologist, you've been following this business for a long time. Diane, We spoke to Holger earlier, I want to start with you uh when you look at this whole trend to as a service, you see a lot of traditional enterprise companies, hard traditionally hardware companies making that move for for a lot of obvious reasons are they sort of replicating in your view, a market that you know well and sas what's your take on how they're doing generally that trend and how HP is >>operating well. Hp has had a unique heritage. They're coming at the whole cloud story and you know the Hyper Scaler story from a different angle than a lot of their competitors and that's mostly a good thing because most of the world is not yet on the cloud, They actually came from H. P. S original world, their line of servers and networks and so on. Um and and so they bring a lot of credibility saying we really understand the world you live in now but we want to take you to that that as a service future. Uh and and you know, since we understand you so well and we also understand where this is going and we can adapt that to that world. Have a very compelling story and I think that with green like you know, was first started about four years ago, it was off to the side uh you know, with all the other offerings now it's it's really grown up, it's matured a lot and I think you know, as we talked about the announcements, we'll see that a lot of key pieces have fallen into place to make it a very compelling hybrid cloud option for the enterprise. >>Let's talk about the announcement. Was there anything in particular that stood out the move to data management? I think it's pretty interesting is a tam expansion strategy. What's your take on the >>announcement? Well, the you know, the unified analytics uh story I think is really important now. That's the technology piece where they say, they say we can give you a data fabric, you can access your data outside of its silos. It doesn't address a lot of the process and cultural issues around data ownership inside the enterprise, but it's you know, having in the actual platform and as you articulating it as a platform, that's one of the things that was also evident, they were getting better and better at saying this is a hybrid cloud platform and it has all the pieces that you would expect, especially the things like being able to bring your data from wherever it is to wherever people needed to be. Uh you know, that's the Holy Grail, so really glad to see that component in particular. I also like the cloud adoption framework saying we understand how to take you from this parochial world of servers that you have and do a cloud date of hybrid world and then maybe eventually get you get you to a public cloud. We understand all the steps and all the components uh I think that's uh you know, I have a study that fully in depth but it seems to have all the moving parts >>chime in anything stand out to, you >>know, I think it's great announcements and the most important things H. P. S and transformation and when you and transformation people realize who you've been, the old and they're here. Maybe the mass of the new but an experienced technology but I will not right away saying oh it's gonna happen right. It's going to happen like this is gonna be done, it's ready, it's materials ready to use and so on. So this is going to give more data points, more proof points, more capabilities that HB is moving away from whatever they were before. That's not even say that to a software services as a service as you mentioned provider. It's >>been challenging, you look at the course of history for companies that try to go from being a hardware company to a software company, uh HP itself, you know, sort of gave up on that IBM you could say, you know semi succeeded but they've they've struggled what's different >>That will spend 30 billion, >>30 >>four. Exactly. So and of course Cisco is making that transition. I mean every traditional large companies in that transition. What about today? Well, first of all, what do you think about HP es, prospects of doing so? And are there things today in the business that make that, you know more faster, whether it's containers or the cloud itself or just the scale of the internet? >>I mean it's fascinating topic, right? And I think many of the traditional players in the space failed because they wanted to mimic the cloud players and they simply couldn't muster up the Capex, which you need to build up public cloud. Right? Because if you think of the public cloud players then didn't put it up for the cloud offering, they put it up because they need themselves right, amazon is an online retailer google as a search and advertising giant Microsoft is organic load from from from office, which they had to bring to the cloud. So it was easier for them to do that. So no wonder they failed. The good news is they haven't lost much of their organic load. Hp customers are still HP customer service, celebrity security in their own premises and now they're bringing the qualities of the cloud as a service, the pay as you go capabilities to the on premise stack, which helps night leader to reduce complexity and go to what everybody in the post pandemic world wants to get to, which is I only pay for what I use and that's super crucial because business goes up and down. We're riding all the waves in a much, much faster way than ever before. Right before we had seven year cycles, it was kind of like cozy almost now we're down to seven weeks, sometimes seven days, sometimes seven hour cycles. And I don't want to pay for it infrastructure, which was great for how my business was two years ago. I want to pay for it as I use it now as a pivot now and I'm going to use >>Diane. How much of this? Thank you for that whole girl. How much of this is what customers want and need versus sort of survival tactics on the vendors >>part. So I think that there, if you look at where customers want to go, they know they have to go cloud, they had to go as a service. Um, and that they need to make multiple steps to get there. And for the most part, I see green light is being a, a highly credible market response to say, you know, we understand IT better, we helped build you guys up over the last 30 years. We can take you the rest of the way, here's all the evidence and the proof points, which I think a lot of the announcements provide uh, and they're very good on cloud native, but the area where the story, um, you may not be the fullest strength it needs to be is around things like multi cloud. So when I talked to almost any large organization C I O. They have all the clouds need to know, how do I make all this fit together? How do I reconcile that? So for the most part, I think it's closely aligned with actual customer requirements and customer needs. I think these have additional steps to go >>is that, do you feel like that's a a priority? In other words, they got to kind of take a linear path. They got to solve the problem for their core customer base or is it, do you feel like that's not even necessarily an aspiration? And it seems like customers, I want them to go. There is what I'm >>inferring that you're, so I do. Well let's go back to the announcement specifically. So there's there are two great operational announcements, one around the cloud physics and the other one around info site. It gives a wealth of data, you know, full stack about how things are operating, where the needs are, how you might be able to get more efficiencies, how you can shut down silicon, you're not using a lot of really great information, but all that has to live with a whole bunch of other consoles and everybody is really craving the single piece of glass. That's what they want is they want to reduce complexity as holder was saying and say, I want to be able to get my arms around my data center and all of my cloud assets. But I don't want to have to check each cloud. I want it in one place. So uh, but it's great to see those announcements position them for that next step. They have these essential components that are that look, you know, uh, they look best to breed in terms of their capabilities are certainly very modern now. They have to get the rest of that story. >>Hope you were mentioning Capex. I added it up I think last year the big four include Alibaba, spent 100 billion on the Capex and generally the traditional on prem players have been defensive around cloud. Not everything is moving to the cloud, we all know that. But I, I see that as a gift in a way that the companies like HP can build on top of into Diane's point that, you know, extend cross clouds out to the edge, which is, you know, a trillion dollar opportunity, which is just just massive. What are your thoughts on HBs opportunities there and chances of maybe breaking away from the pack >>I think definitely well there's no matter pack left, like there's only 23, it's a triumvirate of maybe it's a good thing from a marketing standpoint. There's not a long list of people who give me hardware in my data center. But I think it increases their chances, right? Like I said, it's a transformation, there's more credibility, there's more data point, there's more usage. I can put more workloads on this. And I see, I also will pay attention to that and look at that for the transformation. No question. >>Yeah. And speaking of C. I. O. S. What are you hearing these days? What's their reaction to this whole trend toward as a service? Do they, do they welcome it? Do they feel like okay it's a wait and see. Uh I need more proof points. What's the sentiment? >>Well, you have to divide the Ceo market basically two large groups. One is the the ones that are highly mature. They tend to be in larger organizations are very sophisticated consumers of everything. They see the writing on the wall and that for most things certainly not everything as a service makes the most sense for all the reasons we know, agility and and and speed, you know, time to value scalability, elasticity, all those great things. Uh And then you have the the other side of the market which they really crave control. They have highly parochial worlds that they've built up um that are hard to move to the cloud because they're so complex and intertwined because they haven't had that high maturity. They have a lot of spaghetti architecture. They're not really ready to move the cloud very quickly. So the the second audience though is the largest one and it's uh you know, the hyper scales are probably getting a lot of the first ones. Um, but the bigger markets, really the second one where the folks that need a lot of help and they have a lot of legacy hardware and software that they need to move and that H P. E understands very well. And so I think from that standpoint they're well positioned to take advantage of an untapped market are relatively untapped market in comparison. Hey, >>in our business we all get pulled in different directions because it would get to eat. But what are some of the cool things you guys are working on in your research that you might want people to know about? >>Uh, I just did a market overview for enterprise application platforms. I'm a strong believer that you should not build all your enterprise software yourself, but you can't use everything that you get from your typical SAs provider. So it's focusing on the extent integration and build capabilities. Bill is very, very important to create the differentiation in the marketplace and all the known sauce players basically for their past. Right? My final example is always to speak in cartoons, right? The peanuts, right? There's Linus of this comfort blanket. Right? The past capability of the SARS player is the comfort blanket, right? You don't fit 100% there or you want to build something strategic or we'll never get to that micro vertical. We have a great enterprise application, interesting topic. >>Especially when you see what's happening with Salesforce and Service now trying to be the platform platforms. I have to check that out. How about >>Diane? Well and last year I had a survey conducted a survey with the top 100 C IOS and at least in my view about what they're gonna do to get through this year. And so I'm redoing that again to say, you know, what are they gonna do in 2022? Because there's so many changes in the world and so, you know, last year digital transformation, automation cybersecurity, we're at the top of the list and it'll be very interesting. Cloud was there too in the top five. So we're gonna see what, how it's all going to change because next year is the year of hybrid work where we're all we have to figure out how half of our businesses are in the office and half are at home and how we're gonna connect those together and what tools we're gonna make, that everybody's trying to figure >>out how to get hybrid. Right, so definitely want to check out that research guys. Thanks so much for coming to the cubes. Great to see you. >>Thanks. Thanks Dave >>Welcome. Okay and thank you for watching everybody keep it right there for more great content from H. P. S. Green Lake announcement. You're watching the cube. Mm this wasn't

(upbeat music) >> Welcome to the CUBE Conversation. I'm Lisa Martin. I'm talking next with Sanzio Bassini, the Head of High Performance Computing at Cineca, at DELL technologies customer. Sanzio, welcome to the CUBE. >> Thank you, it's a pleasure, it's a pleasure. >> Likewise, nice to see you. So tell us a little bit about Cineca. This is a large computing center, but a very large Italian nonprofit consortium. Tell us about it. >> Yes, Cineca been founded 50 years ago, from the university systems in Italy. For a statutory mission, which is to support, the scientific discovery, and the industry innovations, using the High Performance Computing and the correlated methodologies like a, Artificial Intelligence, which is one of the, you see the more, in a, in a adopted in those days, but together with the big data processing and and simulation. Yes, we are a consortium, which means that this is a private not-for-profit organizations. Currently, our member of the consortium, almost all the universities in Italy and also all the national agencies for those selected structures. Uh. The main quarter of Cineca is in Bologna, which is in the heart Nation, with the bunch of presence in Milan, in Rome and in Naples, so we are a consultation organization. >> And I also read that you were, are the top 10 out of the top 500 of the world's fastest super computers. That's a pretty big accomplishment. >> Yes. That is a part of our institutional missions, the last 10 to 15 years we have been to say, frequent flyers in the top 10. There been at least two, three systems that have been ranked at the top 10. Apart, the.., whatever would be the meaning of such an advance market, there's a lot of its criticalities. We are well aware. The idea is that we're enabling the scientific discovery, by means of providing the most advanced systems and the co-designing, the most advanced HPC systems to promote and support the, what is the, excellence in science. And that being part of European high-performance computing IT system. That is the case. >> Excellent. Now, talk to me about some of the challenges that Cineca is trying to solve in particular, the Human Brain Project. Talk to us a little bit about that and how you're leveraging high-performance computing to accelerate scientific discovery. >> Um, The Human Brain Project is one of the flagship project that has been co-founded by the European commission and that the participating member states. Is not as another situations that are undertaking, it's definitely a joint collaboration between members states and the European commission. There are two different right now, flagships together with another, that is in progress, which is that the quantum of flagship, the first two flagship abroad that that has been lost. The commission for operation with the participating states has been one on the digraph vein on which also we are participating in directly together with the CNR, is the national business counselor. And the second for which we are core partners of the HPC that is, the Human Brain Project. That, that is a big flagship, one million offer, of newer investment, co-founded by the participating states and that the European commission. The project it's going to set up, in what to do be the, third strategic grant agreement that they will go over the next three years, the good, the complete that the, the whole process. Then we see what is going to happen at Africa. We thought that their would be some others progress offer these big projects. It's project that would combine both the technology issues, like the designing the off high-performance computing systems that meet the requirements of the community and the big challenge, scientific challenges correlated to the physiological functions of the human brain center, including the different farm show survey to do with the behavior of the human brain. A from the pathological point of view, from the physiological point of view, that better understand the could be the way for, for a facing that. Let's say the pathology, some of those are very much correlated with respect to aging, and that it would impact the, the health, the public health systems. Some other that are correlating with what would be the support for the physiological knowledge of the, of the human brains. And finally that they, let me say, technological transfer stuff that represented the knowing off at the physiological, behavior of the human brain. Just to use a sort of metaphor to have happen from the point of view of there computational performance, the human brain is a, a, a, more than Exoscale systems, but with a energy consumption, which is very low, we are talking about some hundreds of Watts. So some hundreds of watts of energy, would provide a an extreme and computational performance. So if would could organized the technology of the high-performance computing in terms of interconnections now we're morphing the computing systems and exploitations of that kind of technologies, in I build a system that it might provide the computational power that would represent a tremendous and tremendous step ahead, in order to facing the big challenges of our base, like energies, personalized medicine, try not to change food for all those kinds of big socioeconomic challenges that we are facing. >> Yes I was reading that besides, sorry Sanzio I was reading that besides the Human Brain Project, there are other projects going on, such as that you mentioned, I'd like to understand how Cineca is working with Dell technologies. You have to translate, as you've mentioned a minute ago, the scientific requirements for discovery into high-performance computing requirements. Talk to me about how you've been doing that with partners like Dell technologies. >> Yes, in particularly in our computing architectures, we had the need to address the capability to facing the data processing involved with backed off the Human Brain Project and general speaking that is backed off the science vendor, that would combine the capability also to provide the cloud access to the system. So by main soft containers technologies and the capability also, to address what would be the creation of a Federation. So Piper problems with people proceeded in a new world. So at the end that the requirements and the terms of reference of the would matter will decline and the terms of a system that would be capable to manage, let's say, in a holistic approach, the data processing, the cloud computing services and the opportunity before for being integrated that in a Federation of HSBC system in Europe's, and with this backed off, that kind of thing, we manage a competitive dialogue procurement processor, I think I the sentence would share together with the different potential technology providers, what would be the visuals and those are the constraints (inaudible) and those other kinds of constraints like, I don't want to say, I mean, environmental kind of constraints and uh, sharing with this back of the technology provider what would it be the vision for this solution, in a very, let's say hard, the competitive dialogue, and at the end, results in a sort of, I don't want to say Darwinian processes, okay. So I mean, the survivors in terms of the different technology providers being Dell that shown the characteristics of the solution that it will be more, let's say compliant. And at the same time are flexible with respect of the combinations of very different constraints and requirements that has been the, the process that has been the outcomes of such a process. >> I like that you mentioned that Darwinian survival of the fittest and that Dell technologies has been, it sounds like a pretty flexible partner because you've got so many different needs and scientific needs to meet for different researchers. Talk to me about how you mentioned that this is a multi-national effort. How does Cineca serve and work with teams not only in Italy, but in other countries and from other institutes? >> Definitely the volume commitment that together with the, European member states is that by means of scientific merits and the peer review process, roughly speaking the arc of the production capacity, would be shared at the European level. That it's a commitment that, that there's been, that there's been a shared of that together with France, Germany, Spain, and, and with the London. So, I mean, our, half of our production capacity, it's a share of that at the European level, where also of course the Italian scientist can apply in the participates, but in a sort of offer emulations and the advanced competition for addressing what it would be the excellence in science. The remaining 50% of our production capacity is for, for the national community and, somehow to prepare and support the Italian community to be competitive on the worldwide scenario on the European and international scenario, uh that setting up would lead also to the agreement at the international level, with respect of some of the options that, that are promoted the progress in a US and in Japan also. So from this point of view, that mean that in some cases also the, access that it would come from researchers the best collaborations and the sharing options with the US researchers their or Japanese researchers in an open space. >> Open space for, it sounds like the Human Brain Project, which the HPC is powering, which has been around since 2013 is really facilitating global collaboration. Talk to me about some of the results that the high-performance computing environment has helped the Human Brain Project to achieve so far. >> The main outcomes that it will be consolidated in the next phase that will be need the by rural SPC that is the Jared undertaking um entities, that has been created for consolidating and for progressing the high-performance computing ecosystem in Europe. It represented by the Federations of high-performance computing systems at European level, there is a, a, an option that, that has been encapsulated and the elaborated inside the human brain flagship project which is called the FEHIPCSE that stand for Federation of a High-Performance Computing System in Europe. That uh provide the open service based on the two concepts on one, one is the sharing of the Heidi at a European level, so it means that the, the high demand of the users or researchers more properly. It's unique and Universal at the European level. That didn't mean better the same, we see identity management, education management with the open, and the access to the Cineca system, to the SARS system in France, to the unique system in, uh Germany to the, Diocese system in a Switzerland, to the Morocco System in a Spain. That is the part related to what will be the federated, the ID management, the others, et cetera, related to what will be the Federation off the data access. So from the point of view, again, the scientific community, mostly the community of Human Brain Project, but that will be open at other domains and other community, make sure that data in a seamless mode after European language, from the technological point of view, or let's say from the infrastructure point of view, very strong up, from the scientific point of view, uh what they think they may not, will be the most of the options is being supported by Cineca has to do with the two specific target. One is the elaboration of the data that are provided by the lands. The laws are a laboratory facility in that Florence. That is one of the four parts, and from the bottom view of the provisions of the data that is for the scattering, the, the data that would come from the mouse brains, that are use for, for (inaudible) And then the second part is for the Mayor scale studies of the cortex of the of the human brain, and that got add-on by a couple of groups that are believing that action from a European level their group of the National Researcher Counsel the CNR, that are the two main outcome on which we are in some out reference high-performance computing facilities for supporting that kind of research. Then their is in some situations they combinations of the performance a, capability of the Federation systems for addressing what will be the simulations of the overall human brain would take a lot of performance challenge simulation with bacteria that they would happen combining that they SPC facility as at European level. >> Right! So I was reading there's a case study by the way, on Cynic that Dell technologies has published. And some of the results you talked about, those that the HPC is facilitating research and results on epilepsy, spinal cord injury, brain prostheses for the blind, as well as new insights into autism. So incredibly important work that you're doing here for the Human Brain Project. One last question Sanzio, for you, what advice would you give to your peers who might be in similar situations that need to, to build and deploy and maintain high-performance computing environments? Where should they start? >> (coughs laughs) I think that at, at a certain point, that specific know how would became sort of a know how that is been, I mean, accumulated and then by some facilities and institutions around the world. There are the, the federal labs in US, the main nation model centers in Europe, the big facilities in Japan. And of course the, the big university facilities in China that are becoming, how do you say, evident and our progressively occupied increasing the space, that to say that that is somehow it, that, that, that the, those institutions would continues collaborate and sharing that there are periods I would expect off what to do, be the top level systems. Then there is a continuous sharing of uh knowledge, the experience best practices with respect off, let's say the technologies transfers towards productions and services and boosterism. Where the situation is big parenta, in the sense that, their are focused what it would be, uh the integration of the high-performance computing technology into their production workflow. And from the point of view, there is the sharing of the experience in order to provide the, a sort of, let's say, spreads and amplifications of the opportunity for supporting innovation. That is part of are solution means, in a Italy but it also, eh, er sort of um, see objective, that is addressed by the European options er supported by the European commission. I think that that sort of (inaudible) supply that in US, the, that will be coming there, sort of you see the max practice for the technology transfer to support the innovation. >> Excellent, that sharing and that knowledge transfer and collaboration. It seems to be absolutely fundamental and the environment that you've built, facilitates that. Sanzio thank you so much for sharing with us, what Cineca is doing and the great research that's going on there, and across a lot of disciplines, we appreciate you joining the program today. Thank you. >> Thank you, it's been a pleasure, thank you very much for the opportunity. >> Likewise, for Sanzio Bassini. I'm Lisa Martin. You're watching this cube conversation. (calming music)

>>from around the globe. It's the Cube presenting innovation for good, brought to you by on shape. >>Hello, everyone, and welcome to Innovation for Good Program, hosted by the Cuban. Brought to You by on Shape, which is a PTC company. My name is Dave Valentin. I'm coming to you from our studios outside of Boston. I'll be directing the conversations today. It's a very exciting, all live program. We're gonna look at how product innovation has evolved and where it's going and how engineers, entrepreneurs and educators are applying cutting edge, cutting edge product development techniques and technology to change our world. You know, the pandemic is, of course, profoundly impacted society and altered how individuals and organizations they're gonna be thinking about an approaching the coming decade. Leading technologists, engineers, product developers and educators have responded to the new challenges that we're facing from creating lifesaving products to helping students learn from home toe how to apply the latest product development techniques and solve the world's hardest problems. And in this program, you'll hear from some of the world's leading experts and practitioners on how product development and continuous innovation has evolved, how it's being applied toe positive positively affect society and importantly where it's going in the coming decades. So let's get started with our first session fueling Tech for good. And with me is John Hirschbeck, who is the president of the Suffers, a service division of PTC, which acquired on shape just over a year ago, where John was the CEO and co founder, and Dana Grayson is here. She is the co founder and general partner at Construct Capital, a new venture capital firm. Folks, welcome to the program. Thanks so much for coming on. >>Great to be here, Dave. >>All right, John. >>You're very welcome. Dana. Look, John, let's get into it for first Belated congratulations on the acquisition of Von Shape. That was an awesome seven year journey for your company. Tell our audience a little bit about the story of on shape, but take us back to Day zero. Why did you and your co founders start on shape? Well, >>actually, start before on shaping the You know, David, I've been in this business for almost 40 years. The business of building software tools for product developers and I had been part of some previous products in the industry and companies that had been in their era. Big changes in this market and about, you know, a little Before founding on shape, we started to see the problems product development teams were having with the traditional tools of that era years ago, and we saw the opportunity presented by Cloud Web and Mobile Technology. And we said, Hey, we could use Cloud Web and Mobile to solve the problems of product developers make their Their business is run better. But we have to build an entirely new system, an entirely new company, to do it. And that's what on shapes about. >>Well, so notwithstanding the challenges of co vid and difficulties this year, how is the first year been as, Ah, division of PTC for you guys? How's business? Anything you can share with us? >>Yeah, our first year of PTC has been awesome. It's been, you know, when you get acquired, Dave, you never You know, you have great optimism, but you never know what life will really be like. It's sort of like getting married or something, you know, until you're really doing it, you don't know. And so I'm happy to say that one year into our acquisition, um, PTC on shape is thriving. It's worked out better than I could have imagined a year ago. Along always, I mean sales are up. In Q four, our new sales rate grew 80% vs Excuse me, our fiscal Q four Q three. In the calendar year, it grew 80% compared to the year before. Our educational uses skyrocketing with around 400% growth, most recently year to year of students and teachers and co vid. And we've launched a major cloud platform using the core of on shape technology called Atlas. So, um, just tons of exciting things going on a TTC. >>That's awesome. But thank you for sharing some of those metrics. And of course, you're very humble individual. You know, people should know a little bit more about you mentioned, you know, we founded Solid Works, co founded Solid where I actually found it solid works. You had a great exit in the in the late nineties. But what I really appreciate is, you know, you're an entrepreneur. You've got a passion for the babies that you you helped birth. You stayed with the salt systems for a number of years. The company that quiet, solid works well over a decade. And and, of course, you and I have talked about how you participated in the the M I T. Blackjack team. You know, back in the day, a zai say you're very understated, for somebody was so accomplished. Well, >>that's kind of you, but I tend to I tend Thio always keep my eye more on what's ahead. You know what's next, then? And you know, I look back Sure to enjoy it and learn from it about what I can put to work making new memories, making new successes. >>Love it. Okay, let's bring Dana into the conversation. Hello, Dana. You look you're a fairly early investor in in on shape when you were with any A And and I think it was like it was a serious B, but it was very right close after the A raise. And and you were and still are a big believer in industrial transformation. So take us back. What did you see about on shape back then? That excited you. >>Thanks. Thanks for that. Yeah. I was lucky to be a early investment in shape. You know, the things that actually attracted me. Don shape were largely around John and, uh, the team. They're really setting out to do something, as John says humbly, something totally new, but really building off of their background was a large part of it. Um, but, you know, I was really intrigued by the design collaboration side of the product. Um, I would say that's frankly what originally attracted me to it. What kept me in the room, you know, in terms of the industrial world was seeing just if you start with collaboration around design what that does to the overall industrial product lifecycle accelerating manufacturing just, you know, modernizing all the manufacturing, just starting with design. So I'm really thankful to the on shape guys, because it was one of the first investments I've made that turned me on to the whole sector. And while just such a great pleasure to work with with John and the whole team there. Now see what they're doing inside PTC. >>And you just launched construct capital this year, right in the middle of a pandemic and which is awesome. I love it. And you're focused on early stage investing. Maybe tell us a little bit about construct capital. What your investment thesis is and you know, one of the big waves that you're hoping to ride. >>Sure, it construct it is literally lifting out of any what I was doing there. Um uh, for on shape, I went on to invest in companies such as desktop metal and Tulip, to name a couple of them form labs, another one in and around the manufacturing space. But our thesis that construct is broader than just, you know, manufacturing and industrial. It really incorporates all of what we'd call foundational industries that have let yet to be fully tech enabled or digitized. Manufacturing is a big piece of it. Supply chain, logistics, transportation of mobility or not, or other big pieces of it. And together they really drive, you know, half of the GDP in the US and have been very under invested. And frankly, they haven't attracted really great founders like they're on in droves. And I think that's going to change. We're seeing, um, entrepreneurs coming out of the tech world orthe Agnelli into these industries and then bringing them back into the tech world, which is which is something that needs to happen. So John and team were certainly early pioneers, and I think, you know, frankly, obviously, that voting with my feet that the next set, a really strong companies are going to come out of the space over the next decade. >>I think it's a huge opportunity to digitize the sort of traditionally non digital organizations. But Dana, you focused. I think it's it's accurate to say you're focused on even Mawr early stage investing now. And I want to understand why you feel it's important to be early. I mean, it's obviously riskier and reward e er, but what do you look for in companies and and founders like John >>Mhm, Um, you know, I think they're different styles of investing all the way up to public market investing. I've always been early stage investors, so I like to work with founders and teams when they're, you know, just starting out. Um, I happened to also think that we were just really early in the whole digital transformation of this world. You know, John and team have been, you know, back from solid works, etcetera around the space for a long time. But again, the downstream impact of what they're doing really changes the whole industry. And and so we're pretty early and in digitally transforming that market. Um, so that's another reason why I wanna invest early now, because I do really firmly believe that the next set of strong companies and strong returns for my own investors will be in the spaces. Um, you know, what I look for in Founders are people that really see the world in a different way. And, you know, sometimes some people think of founders or entrepreneurs is being very risk seeking. You know, if you asked John probably and another successful entrepreneurs, they would call themselves sort of risk averse, because by the time they start the company, they really have isolated all the risk out of it and think that they have given their expertise or what they're seeing their just so compelled to go change something, eh? So I look for that type of attitude experience a Z. You can also tell from John. He's fairly humble. So humility and just focus is also really important. Um, that there's a That's a lot of it. Frankly, >>Excellent. Thank you, John. You got such a rich history in the space. Uh, and one of you could sort of connect the dots over time. I mean, when you look back, what were the major forces that you saw in the market in in the early days? Particularly days of on shape on? And how is that evolved? And what are you seeing today? Well, >>I think I touched on it earlier. Actually, could I just reflect on what Dana said about risk taking for just a quick one and say, throughout my life, from blackjack to starting solid works on shape, it's about taking calculated risks. Yes, you try to eliminate the risk Sa's much as you can, but I always say, I don't mind taking a risk that I'm aware of, and I've calculated through as best I can. I don't like taking risks that I don't know I'm taking. That's right. You >>like to bet on >>sure things as much as you sure things, or at least where you feel you. You've done the research and you see them and you know they're there and you know, you, you you keep that in mind in the room, and I think that's great. And Dana did so much for us. Dana, I want to thank you again. For all that, you did it every step of the way, from where we started to to, you know, your journey with us ended formally but continues informally. Now back to you, Dave, I think, question about the opportunity and how it's shaped up. Well, I think I touched on it earlier when I said It's about helping product developers. You know, our customers of the people build the future off manufactured goods. Anything you think of that would be manufacturing factory. You know, the chair you're sitting in machine that made your coffee. You know, the computer you're using, the trucks that drive by on the street, all the covert product research, the equipment being used to make vaccines. All that stuff is designed by someone, and our job is given the tools to do it better. And I could see the problems that those product developers had that we're slowing them down with using the computing systems of the time. When we built solid works, that was almost 30 years ago. If people don't realize that it was in the early >>nineties and you know, we did the >>best we could for the early nineties, but what we did. We didn't anticipate the world of today. And so people were having problems with just installing the systems. Dave, you wouldn't believe how hard it is to install these systems. You need toe speck up a special windows computer, you know, and make sure you've got all the memory and graphics you need and getting to get that set up. You need to make sure the device drivers air, right, install a big piece of software. Ah, license key. I'm not making this up. They're still around. You may not even know what those are. You know, Dennis laughing because, you know, zero cool people do things like this anymore. Um, and it only runs some windows. You want a second user to use it? They need a copy. They need a code. Are they on the same version? It's a nightmare. The teams change, you know? You just say, Well, get everyone on the software. Well, who's everyone? You know, you got a new vendor today? A new customer tomorrow, a new employee. People come on and off the team. The other problem is the data stored in files, thousands of files. This isn't like a spreadsheet or word processor, where there's one file to pass around these air thousands of files to make one, even a simple product. People were tearing their hair out. John, what do we do? I've got copies everywhere. I don't know where the latest version is. We tried like, you know, locking people out so that only one person can change it At the time that works against speed, it works against innovation. We saw what was happening with Cloud Web and mobile. So what's happened in the years since is every one of the forces that product developers experience the need for speed, the need for innovation, the need to be more efficient with their people in their capital. Resource is every one of those trends have been amplified since we started on shape by a lot of forces in the world. And covert is amplified all those the need for agility and remote work cove it is amplified all that the same time, The acceptance of cloud. You know, a few years ago, people were like cloud, you know, how is that gonna work now They're saying to me, You know, increasingly, how would you ever even have done this without the cloud. How do you make solid works work without the cloud? How would that even happen? You know, once people understand what on shapes about >>and we're the >>Onley full SAS solution software >>as a service, >>full SAS solution in our industry. So what's happened in those years? Same problems we saw earlier, but turn up the gain, their bigger problems. And with cloud, we've seen skepticism of years ago turn into acceptance. And now even embracement in the cova driven new normal. >>Yeah. So a lot of friction in the previous environments cloud obviously a huge factor on, I guess. I guess Dana John could see it coming, you know, in the early days of solid works with, you know, had Salesforce, which is kind of the first major independent SAS player. Well, I guess that was late nineties. So his post solid works, but pre in shape and their work day was, you know, pre on shape in the mid two thousands. And and but But, you know, the bet was on the SAS model was right for Crick had and and product development, you know, which maybe the time wasn't a no brainer. Or maybe it was, I don't know, but Dana is there. Is there anything that you would invest in today? That's not Cloud based? >>Um, that's a great question. I mean, I think we still see things all the time in the manufacturing world that are not cloud based. I think you know, the closer you get to the shop floor in the production environment. Um e think John and the PTC folks would agree with this, too, but that it's, you know, there's reliability requirements, performance requirements. There's still this attitude of, you know, don't touch the printing press. So the cloud is still a little bit scary sometimes. And I think hybrid cloud is a real thing for those or on premise. Solutions, in some cases is still a real thing. What what we're more focused on. And, um, despite whether it's on premise or hybrid or or SAS and Cloud is a frictionless go to market model, um, in the companies we invest in so sass and cloud, or really make that easy to adopt for new users, you know, you sign up, started using a product, um, but whether it's hosted in the cloud, whether it's as you can still distribute buying power. And, um, I would I'm just encouraging customers in the customer world and the more industrial environment to entrust some of their lower level engineers with more budget discretionary spending so they can try more products and unlock innovation. >>Right? The unit economics are so compelling. So let's bring it, you know, toe today's you know, situation. John, you decided to exit about a year ago. You know? What did you see in PTC? Other than the obvious money? What was the strategic fit? >>Yeah, Well, David, I wanna be clear. I didn't exit anything. Really? You >>know, I love you and I don't like that term exit. I >>mean, Dana had exit is a shareholder on and so it's not It's not exit for me. It's just a step in the journey. What we saw in PTC was a partner. First of all, that shared our vision from the top down at PTC. Jim Hempleman, the CEO. He had a great vision for for the impact that SAS can make based on cloud technology and really is Dana of highlighted so much. It's not just the technology is how you go to market and the whole business being run and how you support and make the customers successful. So Jim shared a vision for the potential. And really, really, um said Hey, come join us and we can do this bigger, Better, faster. We expanded the vision really to include this Atlas platform for hosting other SAS applications. That P D. C. I mean, David Day arrived at PTC. I met the head of the academic program. He came over to me and I said, You know, and and how many people on your team? I thought he'd say 5 40 people on the PTC academic team. It was amazing to me because, you know, we were we were just near about 100 people were required are total company. We didn't even have a dedicated academic team and we had ah, lot of students signing up, you know, thousands and thousands. Well, now we have hundreds of thousands of students were approaching a million users and that shows you the power of this team that PTC had combined with our product and technology whom you get a big success for us and for the teachers and students to the world. We're giving them great tools. So so many good things were also putting some PTC technology from other parts of PTC back into on shape. One area, a little spoiler, little sneak peek. Working on taking generative design. Dana knows all about generative design. We couldn't acquire that technology were start up, you know, just to too much to do. But PTC owns one of the best in the business. This frustrated technology we're working on putting that into on shaping our customers. Um, will be happy to see it, hopefully in the coming year sometime. >>It's great to see that two way exchange. Now, you both know very well when you start a company, of course, a very exciting time. You know, a lot of baggage, you know, our customers pulling you in a lot of different directions and asking you for specials. You have this kind of clean slate, so to speak in it. I would think in many ways, John, despite you know, your install base, you have a bit of that dynamic occurring today especially, you know, driven by the forced march to digital transformation that cove it caused. So when you sit down with the team PTC and talk strategy. You now have more global resource is you got cohorts selling opportunities. What's the conversation like in terms of where you want to take the division? >>Well, Dave, you actually you sounds like we should have you coming in and talking about strategy because you've got the strategy down. I mean, we're doing everything said global expansion were able to reach across selling. We got some excellent PTC customers that we can reach reach now and they're finding uses for on shape. I think the plan is to, you know, just go, go, go and grow, grow, grow where we're looking for this year, priorities are expand the product. I mentioned the breath of the product with new things PTC did recently. Another technology that they acquired for on shape. We did an acquisition. It was it was small, wasn't widely announced. It, um, in an area related to interfacing with electrical cad systems. So So we're doing We're expanding the breath of on shape. We're going Maura, depth in the areas were already in. We have enormous opportunity to add more features and functions that's in the product. Go to market. You mentioned it global global presence. That's something we were a little light on a year ago. Now we have a team. Dana may not even know what we have. A non shape, dedicated team in Barcelona, based in Barcelona but throughout Europe were doing multiple languages. Um, the academic program just introduced a new product into that space that z even fueling more success and growth there. Um, and of course, continuing to to invest in customer success and this Atlas platform story I keep mentioning, we're going to soon have We're gonna soon have four other major PTC brands shipping products on our Atlas Saas platform. And so we're really excited about that. That's good for the other PTC products. It's also good for on shape because now there's there's. There's other interesting products that are on shape customers can use take advantage of very easily using, say, a common log in conventions about user experience there, used to invest of all they're SAS based, so they that makes it easier to begin with. So that's some of the exciting things going on. I think you'll see PTC, um, expanding our lead in SAS based applications for this sector for our our target, uh, sectors not just in, um, in cat and data management, but another area. PTC's Big and his augmented reality with of euphoria, product line leader and industrial uses of a R. That's a whole other story we should do. A whole nother show augmented reality. But these products are amazing. You can you can help factory workers people on, uh, people who are left out of the digital transformation. Sometimes we're standing from machine >>all day. >>They can't be sitting like we are doing Zoom. They can wear a R headset in our tools, let them create great content. This is an area Dana is invested in other companies. But what I wanted to note is the new releases of our authoring software. For this, our content getting released this month, used through the Atlas platform, the SAS components of on shape for things like revision management and collaboration on duh workflow activity. All that those are tools that we're able to share leverage. We get a lot of synergy. It's just really good. It's really fun to have a good time. That's >>awesome. And then we're gonna be talking to John MacLean later about that. Let's do a little deeper Dive on that. And, Dana, what is your involvement today with with on shape? But you're looking for you know, which of their customers air actually adopting. And they're gonna disrupt their industries. And you get good pipeline from that. How do you collaborate today? >>That sounds like a great idea. Um, Aziz, John will tell you I'm constantly just asking him for advice and impressions of other entrepreneurs and picking his brain on ideas. No formal relationship clearly, but continue to count John and and John and other people in on shaping in the circle of experts that I rely on for their opinions. >>All right, so we have some questions from the crowd here. Uh, one of the questions is for the dream team. You know, John and Dana. What's your next next collective venture? I don't think we're there yet, are we? No. >>I just say, as Dana said, we love talking to her about. You know, Dana, you just returned the compliment. We would try and give you advice and the deals you're looking at, and I'm sort of casually mentoring at least one of your portfolio entrepreneurs, and that's been a lot of fun for May on, hopefully a value to them. But also Dana. We uran important pipeline to us in the world of some new things that are happening that we wouldn't see if you know you've shown us some things that you've said. What do you think of this business? And for us, it's like, Wow, it's cool to see that's going on And that's what's supposed to work in an ecosystem like this. So we we deeply value the ongoing relationship. And no, we're not starting something new. I got a lot of work left to do with what I'm doing and really happy. But we can We can collaborate in this way on other ventures. >>I like this question to somebody asking With the cloud options like on shape, Wilmore students have stem opportunities s Oh, that's a great question. Are you because of sass and cloud? Are you able to reach? You know, more students? Much more cost effectively. >>Yeah, Dave, I'm so glad that that that I was asked about this because Yes, and it's extremely gratified us. Yes, we are because of cloud, because on shape is the only full cloud full SAS system or industry were able to reach. Stem education brings able to be part of bringing step education to students who couldn't get it otherwise. And one of most gratifying gratifying things to me is the emails were getting from teachers, um, that that really, um, on the phone calls that were they really pour their heart out and say We're able to get to students in areas that have very limited compute resource is that don't have an I T staff where they don't know what computer that the students can have at home, and they probably don't even have a computer. We're talking about being able to teach them on a phone to have an android phone a low end android phone. You can do three D modeling on there with on shape. Now you can't do it any other system, but with on shape, you could do it. And so the teacher can say to the students, They have to have Internet access, and I know there's a huge community that doesn't even have Internet access, and we're not able, unfortunately to help that. But if you have Internet and you have even an android phone, we can enable the educator to teach them. And so we have case after case of saving a stem program or expanding it into the students that need it most is the ones we're helping here. So really excited about that. And we're also able to let in addition to the run on run on whatever computing devices they have, we also offer them the tools they need for remote teaching with a much richer experience. Could you teach solid works remotely? Well, maybe if the student ran it had a windows workstation. You know, big, big, high end workstation. Maybe it could, but it would be like the difference between collaborating with on shape and collaborate with solid works. Like the difference between a zoom video call and talking on the landline phone. You know, it's a much richer experience, and that's what you need. And stem teaching stem is hard, So yeah, we're super super. Um, I'm excited about bringing stem to more students because of cloud yond >>we're talking about innovation for good, and then the discussion, John, you just had it. Really? There could be a whole another vector here. We could discuss on diversity, and I wanna end with just pointing out. So, Dana, your new firm, it's a woman led firm, too. Two women leaders, you know, going forward. So that's awesome to see, so really? Yeah, thumbs up on that. Congratulations on getting that off the ground. >>Thank you. Thank you. >>Okay, so thank you guys. Really appreciate It was a great discussion. I learned a lot and I'm sure the audience did a swell in a moment. We're gonna talk with on shaped customers to see how they're applying tech for good and some of the products that they're building. So keep it right there. I'm Dave Volonte. You're watching innovation for good on the Cube, the global leader in digital tech event coverage. Stay right there. >>Oh, yeah, it's >>yeah, yeah, around >>the globe. It's the Cube presenting innovation for good. Brought to you by on shape. >>Okay, we're back. This is Dave Volonte and you're watching innovation for good. A program on Cuba 3 65 made possible by on shape of PTC company. We're live today really live tv, which is the heritage of the Cube. And now we're gonna go to the sources and talkto on shape customers to find out how they're applying technology to create real world innovations that are changing the world. So let me introduce our panel members. Rafael Gomez Furberg is with the Chan Zuckerberg bio hub. A very big idea. And collaborative nonprofit was initiative that was funded by Mark Zuckerberg and his wife, Priscilla Chan, and really around diagnosing and curing and better managing infectious diseases. So really timely topic. Philip Tabor is also joining us. He's with silver side detectors, which develops neutron detective detection systems. Yet you want to know if early, if neutrons and radiation or in places where you don't want them, So this should be really interesting. And last but not least, Matthew Shields is with the Charlottesville schools and is gonna educate us on how he and his team are educating students in the use of modern engineering tools and techniques. Gentlemen, welcome to the Cuban to the program. This should be really interesting. Thanks for coming on. >>Hi. Or pleasure >>for having us. >>You're very welcome. Okay, let me ask each of you because you're all doing such interesting and compelling work. Let's start with Rafael. Tell us more about the bio hub and your role there, please. >>Okay. Yeah. So you said that I hope is a nonprofit research institution, um, funded by Mark Zuckerberg and his wife, Priscilla Chan. Um, and our main mission is to develop new technologies to help advance medicine and help, hopefully cure and manage diseases. Um, we also have very close collaborations with Universe California, San Francisco, Stanford University and the University California Berkeley on. We tried to bring those universities together, so they collaborate more of biomedical topics. And I manage a team of engineers. They by joining platform. Um, and we're tasked with creating instruments for the laboratory to help the scientist boats inside the organization and also in the partner universities Do their experiments in better ways in ways that they couldn't do before >>in this edition was launched Well, five years ago, >>it was announced at the end of 2016, and we actually started operation with at the beginning of 2017, which is when I joined, um, So this is our third year. >>And how's how's it going? How does it work? I mean, these things take time. >>It's been a fantastic experience. Uh, the organization works beautifully. Um, it was amazing to see it grow From the beginning, I was employee number 12, I think eso When I came in, it was just a nem P office building and empty labs. And very quickly we had something running about. It's amazing eso I'm very proud of the work that we have done to make that possible. Um And then, of course, that's you mentioned now with co vid, um, we've been able to do a lot of very cool work attire being of the pandemic in March, when there was a deficit of testing, uh, capacity in California, we spun up a testing laboratory in record time in about a week. It was crazy. It was a crazy project, Um, but but incredibly satisfying. And we ended up running all the way until the beginning of November, when the lab was finally shut down. We could process about 3000 samples a day. I think at the end of it all, we were able to test about 100 on the order of 100 and 50,000 samples from all over the state. We were providing free testing toe all of the Department of Public Health Department of Public Health in California, which at the media pandemic, had no way to do testing affordably and fast. So I think that was a great service to the state. Now the state has created that testing system that would serve those departments. So then we decided that it was unnecessary to keep going with testing in the other biopsy that would shut down. >>All right. Thank you for that. Now, Now, Philip, you What you do is mind melting. You basically helped keep the world safe. Maybe describe a little bit more about silver sod detectors and what your role is there and how it all works. >>Tour. So we make a nuclear bomb detectors and we also make water detectors. So we try and do our part thio keep the world from blowing up and make it a better place at the same time. Both of these applications use neutron radiation detectors. That's what we make. Put them out by import border crossing places like that. They can help make sure that people aren't smuggling. Shall we say very bad things. Um, there's also a burgeoning field of research and application where you can use neutrons with some pretty cool physics to find water so you could do things. Like what? A detector up in the mountains and measure snowpack. Put it out in the middle of the field and measure soil moisture content. And as you might imagine, there's some really cool applications in, uh, research and agronomy and public policy for this. >>All right, so it's OK, so it's a It's much more than, you know, whatever fighting terrorism, it's there's a riel edge or I kind of i o t application for what you guys >>do. We do both its's to plowshares. You might >>say a mat. I I look at your role is kind of scaling the brain power for for the future. Maybe tell us more about Charlottesville schools and in the mission that you're pursuing and what you do. >>Thank you. Um, I've been in Charlottesville City schools for about 11 or 12 years. I started their teaching, um, a handful of classes, math and science and things like that. But Thescore board and my administration had the crazy idea of starting an engineering program about seven years ago. My background is an engineering is an engineering. My masters is in mechanical and aerospace engineering and um, I basically spent a summer kind of coming up with what might be a fun engineering curriculum for our students. And it started with just me and 30 students about seven years ago, Um, kind of a home spun from scratch curriculum. One of my goals from the outset was to be a completely project based curriculum, and it's now grown. We probably have about six or 700 students, five or six full time teachers. We now have pre engineering going on at the 5th and 6th grade level. I now have students graduating. Uh, you know, graduating after senior year with, like, seven years of engineering under their belt and heading off to doing some pretty cool stuff. So it's It's been a lot of fun building a program and, um, and learning a lot in the process. >>That's awesome. I mean, you know, Cuba's. We've been passionate about things like women in tech, uh, diversity stem. You know, not only do we need more, more students and stem, we need mawr underrepresented women, minorities, etcetera. We were just talking to John Herstek and integrate gration about this is Do you do you feel is though you're I mean, first of all, the work that you do is awesome, but but I'll go one step further. Do you feel as though it's reaching, um, or diverse base? And how is that going? >>That's a great question. I think research shows that a lot of people get funneled into one kind of track or career path or set of interests really early on in their educational career, and sometimes that that funnel is kind of artificial. And so that's one of the reasons we keep pushing back. Um, so our school systems introducing kindergartners to programming on DSO We're trying to push back how we expose students to engineering and to stem fields as early as possible. And we've definitely seen the first of that in my program. In fact, my engineering program, uh, sprung out of an after school in Extracurricular Science Club that actually three girls started at our school. So I think that actually has helped that three girls started the club that eventually is what led to our engineering programs that sort of baked into the DNA and also our eyes a big public school. And we have about 50% of the students are under the poverty line and we e in Charlottesville, which is a big refugee town. And so I've been adamant from Day one that there are no barriers to entry into the program. There's no test you have to take. You don't have to have be taking a certain level of math or anything like that. That's been a lot of fun. To have a really diverse set of kids enter the program and be successful, >>that's final. That's great to hear. So, Philip, I wanna come back to you. You know, I think about maybe some day we'll be able to go back to a sporting events, and I know when I when I'm in there, there's somebody up on the roof looking out for me, you know, watching the crowd, and they have my back. And I think in many ways, the products that you build, you know, our similar. I may not know they're there, but they're keeping us safe or they're measuring things that that that I don't necessarily see. But I wonder if you could talk about a little bit more detail about the products you build and how they're impacting society. >>Sure, so There are certainly a lot of people who are who are watching, trying to make sure things were going well in keeping you safe that you may or may not be aware of. And we try and support ah lot of them. So we have detectors that are that are deployed in a variety of variety of uses, with a number of agencies and governments that dio like I was saying, ports and border crossing some other interesting applications that are looking for looking for signals that should not be there and working closely to fit into the operations these folks do. Onda. We also have a lot of outreach to researchers and scientists trying to help them support the work they're doing. Um, using neutron detection for soil moisture monitoring is a some really cool opportunities for doing it at large scale and with much less, um, expense or complication than would have been done. Previous technologies. Um, you know, they were talking about collaboration in the previous segment. We've been able to join a number of conferences for that, virtually including one that was supposed to be held in Boston, but another one that was held out of the University of Heidelberg in Germany. And, uh, this is sort of things that in some ways, the pandemic is pushing people towards greater collaboration than they would have been able to do. Had it all but in person. >>Yeah, we did. Uh, the cube did live works a couple years ago in Boston. It was awesome show. And I think, you know, with this whole trend toward digit, I call it the Force march to digital. Thanks to cove it I think that's just gonna continue. Thio grow. Rafael. What if you could describe the process that you use to better understand diseases? And what's your organization's involvement? Been in more detail, addressing the cove in pandemic. >>Um, so so we have the bio be structured in, Um um in a way that foster so the combination of technology and science. So we have to scientific tracks, one about infectious diseases and the other one about understanding just basic human biology, how the human body functions, and especially how the cells in the human body function on how they're organized to create tissues in the body. On Ben, it has this set of platforms. Um, mind is one of them by engineering that are all technology rated. So we have data science platform, all about data analysis, machine learning, things like that. Um, we have a mass spectrometry platform is all about mass spectrometry technologies to, um, exploit those ones in service for the scientist on. We have a genomics platform that it's all about sequencing DNA and are gonna, um and then an advanced microscopy. It's all about developing technologies, uh, to look at things with advanced microscopes and developed technologies to marry computation on microscopy. So, um, the scientists set the agenda and the platforms, we just serve their needs, support their needs, and hopefully develop technologies that help them do their experiments better, faster, or allow them to the experiment that they couldn't do in any other way before. Um And so with cove, it because we have that very strong group of scientists that work on have been working on infectious disease before, and especially in viruses, we've been able to very quickly pivot to working on that s O. For example, my team was able to build pretty quickly a machine to automatically purified proteins on is being used to purify all these different important proteins in the cove. It virus the SARS cov to virus Onda. We're sending some of those purified proteins all over the world. Two scientists that are researching the virus and trying to figure out how to develop vaccines, understand how the virus affects the body and all that. Um, so some of the machines we built are having a very direct impact on this. Um, Also for the copy testing lab, we were able to very quickly develop some very simple machines that allowed the lab to function sort of faster and more efficiently. Sort of had a little bit of automation in places where we couldn't find commercial machines that would do it. >>Um, eso Matt. I mean, you gotta be listening to this and thinking about Okay, So someday your students are gonna be working at organizations like like, like Bio Hub and Silver Side. And you know, a lot of young people they're just don't know about you guys, but like my kids, they're really passionate about changing the world. You know, there's way more important than you know, the financial angles and it z e. I gotta believe you're seeing that you're right in the front lines there. >>Really? Um, in fact, when I started the curriculum six or seven years ago, one of the first bits of feedback I got from my students is they said Okay, this is a lot of fun. So I had my students designing projects and programming microcontrollers raspberry, PiS and order we nose and things like that. The first bit of feedback I got from students was they said Okay, when do we get to impact the world? I've heard engineering >>is about >>making the world a better place, and robots are fun and all, but, you know, where is the real impact? And so um, dude, yeah, thanks to the guidance of my students, I'm baking that Maurin. Now I'm like day one of engineering one. We talk about how the things that the tools they're learning and the skills they're gaining, uh, eventually, you know, very soon could be could be used to make the world a better place. >>You know, we all probably heard that famous line by Jeff Hammer Barker. The greatest minds of my generation are trying to figure out how to get people to click on ads. I think we're really generally generationally, finally, at the point where young students and engineering a really, you know, a passionate about affecting society. I wanna get into the product, you know, side and understand how each of you are using on shape and and the value that that it brings. Maybe Raphael, you could start how long you've been using it. You know, what's your experience with it? Let's let's start there. >>I begin for about two years, and I switched to it with some trepidation. You know, I was used to always using the traditional product that you have to install on your computer, that everybody uses that. So I was kind of locked into that. But I started being very frustrated with the way it worked, um, and decided to give on ship chance. Which reputation? Because any change always, you know, causes anxiety. Um, but very quickly my engineers started loving it, Uh, just because it's it's first of all, the learning curve wasn't very difficult at all. You can transfer from one from the traditional product to entree very quickly and easily. You can learn all the concepts very, very fast. It has all the functionality that we needed and and what's best is that it allows to do things that we couldn't do before or we couldn't do easily. Now we can access the our cat documents from anywhere in the world. Um, so when we're in the lab fabricating something or testing a machine, any computer we have next to us or a tablet or on iPhone, we can pull it up and look at the cad and check things or make changes. That's something that couldn't do before because before you had to pay for every installation off the software for the computer, and I couldn't afford to have 20 installations to have some computers with the cat ready to use them like once every six months would have been very inefficient. So we love that part. And the collaboration features are fantastic, especially now with Kobe, that we have to have all the remote meetings eyes fantastic, that you can have another person drive the cad while the whole team is watching that person change the model and do things and point to things that is absolutely revolutionary. We love it. The fact that you have very, very sophisticated version control before it was always a challenge asking people, please, if you create anniversary and apart, how do we name it so that people find it? And then you end up with all these collection of files with names that nobody ever remembers, what they are, the person left. And now nobody knows which version is the right one. A mess with on shape on the version ING system it has, and the fact that you can go back in history off the document and go back to previous version so easily and then go back to the press and version and explore the history of the part that is truly, um, just world changing for us, that we can do that so easily on for me as a manager to manage this collection of information that is critical for our operations. It makes it so much easier because everything is in one place. I don't have to worry about file servers that go down that I have to administer that have to have I t taken care off that have to figure how to keep access to people to those servers when they're at home, and they need a virtual private network and all of that mess disappears. I just simply give give a person in accounting on shape and then magically, they have access to everything in the way I want. And we can manage the lower documents and everything in a way that is absolutely fantastic. >>Feel what was your what? What were some of the concerns you had mentioned? You had some trepidation. Was it a performance? Was it security? You know some of the traditional cloud stuff, and I'm curious as to how, How, whether any of those act manifested really that you had to manage. What were your concerns? >>Look, the main concern is how long is it going to take for everybody in the team to learn to use the system like it and buy into it? Because I don't want to have my engineers using tools against their will write. I want everybody to be happy because that's how they're productive. They're happy, and they enjoyed the tools they have. That was my main concern. I was a little bit worried about the whole concept of not having the files in a place where I couldn't quote unquote seat in some server and on site, but that That's kind of an outdated concept, right? So that took a little bit of a mind shift, but very quickly. Then I started thinking, Look, I have a lot of documents on Google Drive. Like, I don't worry about that. Why would I worry about my cat on on shape, right? Is the same thing. So I just needed to sort of put things in perspective that way. Um, the other, um, you know, the concern was the learning curve, right? Is like, how is he Will be for everybody to and for me to learn it on whether it had all of the features that we needed. And there were a few features that I actually discussed with, um uh, Cody at on shape on, they were actually awesome about using their scripting language in on shape to sort of mimic some of the features of the old cat, uh, in on, shaped in a way that actually works even better than the old system. So it was It was amazing. Yeah, >>Great. Thank you for that, Philip. What's your experience been? Maybe you could take us through your journey within shape. >>Sure. So we've been we've been using on shaped silver side for coming up on about four years now, and we love it. We're very happy with it. We have a very modular product line, so we make anything from detectors that would go into backpacks. Two vehicles, two very large things that a shipping container would go through and saw. Excuse me. Shape helps us to track and collaborate faster on the design. Have multiple people working a same time on a project. And it also helps us to figure out if somebody else comes to us and say, Hey, I want something new how we congrats modules from things that we already have put them together and then keep track of the design development and the different branches and ideas that we have, how they all fit together. A za design comes together, and it's just been fantastic from a mechanical engineering background. I will also say that having used a number of different systems and solid works was the greatest thing since sliced bread. Before I got using on shape, I went, Wow, this is amazing and I really don't want to design in any other platform. After after getting on Lee, a little bit familiar with it. >>You know, it's funny, right? I'll have the speed of technology progression. I was explaining to some young guns the other day how I used to have a daytime er and that was my life. And if I lost that daytime, er I was dead. And I don't know how we weigh existed without, you know, Google maps eso we get anywhere, I don't know, but, uh but so So, Matt, you know, it's interesting to think about, you know, some of the concerns that Raphael brought up, you hear? For instance, you know, all the time. Wow. You know, I get my Amazon bill at the end of the month that zip through the roof in, But the reality is that Yeah, well, maybe you are doing more, but you're doing things that you couldn't have done before. And I think about your experience in teaching and educating. I mean, you so much more limited in terms of the resource is that you would have had to be able to educate people. So what's your experience been with With on shape and what is it enabled? >>Um, yeah, it was actually talking before we went with on shape. We had a previous CAD program, and I was talking to my vendor about it, and he let me know that we were actually one of the biggest CAD shops in the state. Because if you think about it a really big program, you know, really big company might employ. 5, 10, 15, 20 cad guys, right? I mean, when I worked for a large defense contractor, I think there were probably 20 of us as the cad guys. I now have about 300 students doing cat. So there's probably more students with more hours of cat under their belt in my building than there were when I worked for the big defense contractor. Um, but like you mentioned, uh, probably our biggest hurdle is just re sources. And so we want We want one of things I've always prided myself and trying to do in this. Programs provide students with access two tools and skills that they're going to see either in college or in the real world. So it's one of the reason we went with a big professional cad program. There are, you know, sort of K 12 oriented software and programs and things. But, you know, I want my kids coding and python and using slack and using professional type of tools on DSO when it comes to cat. That's just that That was a really hurt. I mean, you know, you could spend $30,000 on one seat of, you know, professional level cad program, and then you need a $30,000 computer to run it on if you're doing a heavy assemblies, Um and so one of my dreams And it was always just a crazy dream. And I was the way I would always pitcher in my school system and say, someday I'm gonna have a kid on a school issued chromebook in subsidized housing, on public WiFi doing professional level bad and that that was a crazy statement until a couple of years ago. So we're really excited that I literally and you know, March and you said the forced march, the forced march into, you know, modernity, March 13th kids sitting in my engineering lab that we spent a lot of money on doing cad March 14th. Those kids were at home on their school issued chromebooks on public WiFi, uh, keeping their designs going and collaborating. And then, yeah, I could go on and on about some of the things you know, the features that we've learned since then they're even better. So it's not like this is some inferior, diminished version of Academy. There's so much about it. Well, I >>wanna I wanna ask you that I may be over my skis on this, but we're seeing we're starting to see the early days of the democratization of CAD and product design. It is the the citizen engineer, I mean, maybe insulting to the engineers in the room, But but is that we're beginning to see that >>I have to believe that everything moves into the cloud. Part of that is democratization that I don't need. I can whether you know, I think artists, you know, I could have a music studio in my basement with a nice enough software package. And Aiken, I could be a professional for now. My wife's a photographer. I'm not allowed to say that I could be a professional photographer with, you know, some cloud based software, and so, yeah, I do think that's part of what we're seeing is more and more technology is moving to the cloud. >>Philip. Rafael Anything you Dad, >>I think I mean, yeah, that that that combination of cloud based cat and then three d printing that is becoming more and more affordable on ubiquitous It's truly transformative, and I think for education is fantastic. I wish when I was a kid I had the opportunity to play with those kinds of things because I was always the late things. But, you know, the in a very primitive way. So, um, I think this is a dream for kids. Teoh be able to do this. And, um, yeah, there's so many other technologies coming on, like Arduino on all of these electronic things that live kids play at home very cheaply with things that back in my day would have been unthinkable. >>So we know there's a go ahead. Philip, please. >>We had a pandemic and silver site moved to a new manufacturing facility this year. I was just on the shop floor, talking with contractors, standing 6 ft apart, pointing at things. But through it all, our CAD system was completely unruffled. Nothing stopped in our development work. Nothing stopped in our support for existing systems in the field. We didn't have to think about it. We had other server issues, but none with our, you know, engineering cad, platform and product development in support world right ahead, which was cool, but also a in that's point. I think it's just really cool what you're doing with the kids. The most interesting secondary and college level engineering work that I did was project based, taken important problem to the world. Go solve it and that is what we do here. That is what my entire career has been. And I'm super excited to see. See what your students are going to be doing, uh, in there home classrooms on their chromebooks now and what they do building on that. >>Yeah, I'm super excited to see your kids coming out of college with engineering degrees because, yeah, I think that Project based experience is so much better than just sitting in a classroom, taking notes and doing math problems on day. I think it will give the kids a much better flavor. What engineering is really about Think a lot of kids get turned off by engineering because they think it's kind of dry because it's just about the math for some very abstract abstract concept on they are there. But I think the most important thing is just that hands on a building and the creativity off, making things that you can touch that you can see that you can see functioning. >>Great. So, you know, we all know the relentless pace of technology progression. So when you think about when you're sitting down with the folks that on shape and there the customer advisor for one of the things that that you want on shape to do that it doesn't do today >>I could start by saying, I just love some of the things that does do because it's such a modern platform. And I think some of these, uh, some some platforms that have a lot of legacy and a lot of history behind them. I think we're dragging some of that behind them. So it's cool to see a platform that seemed to be developed in the modern era, and so that Z it is the Google docks. And so the fact that collaboration and version ing and link sharing is and like platform agnostic abilities, the fact that that seems to be just built into the nature of the thing so far, That's super exciting. As far as things that, uh, to go from there, Um, I don't know, >>Other than price. >>You can't say >>I >>can't say lower price. >>Yeah, so far on P. D. C. S that work with us. Really? Well, so I'm not complaining. There you there, >>right? Yeah. Yeah. No gaps, guys. Whitespace, Come on. >>We've been really enjoying the three week update. Cadence. You know, there's a new version every three weeks and we don't have to install it. We just get all the latest and greatest goodies. One of the trends that we've been following and enjoying is the the help with a revision management and release work flows. Um, and I know that there's more than on shape is working on that we're very excited for, because that's a big important part about making real hardware and supporting it in the field. Something that was cool. They just integrated Cem markup capability. In the last release that took, we were doing that anyway, but we were doing it outside of on shapes. And now we get to streamline our workflow and put it in the CAD system where We're making those changes anyway when we're reviewing drawings and doing this kind of collaboration. And so I think from our perspective, we continue to look forward. Toa further progress on that. There's a lot of capability in the cloud that I think they're just kind of scratching the surface on you, >>right? I would. I mean, you're you're asking to knit. Pick. I would say one of the things that I would like to see is is faster regeneration speed. There are a few times with convicts, necessities that regenerating the document takes a little longer than I would like. It's not a serious issue, but anyway, I I'm being spoiled, >>you know? That's good. I've been doing this a long time, and I like toe ask that question of practitioners and to me, it It's a signal like when you're nit picking and that's what you're struggling to knit. Pick that to me is a sign of a successful product, and and I wonder, I don't know, uh, have the deep dive into the architecture. But are things like alternative processors. You're seeing them hit the market in a big way. Uh, you know, maybe helping address the challenge, But I'm gonna ask you the big, chewy question now. Then we maybe go to some audience questions when you think about the world's biggest problems. I mean, we're global pandemics, obviously top of mind. You think about nutrition, you know, feeding the global community. We've actually done a pretty good job of that. But it's not necessarily with the greatest nutrition, climate change, alternative energy, the economic divides. You've got geopolitical threats and social unrest. Health care is a continuing problem. What's your vision for changing the world and how product innovation for good and be applied to some of the the problems that that you all are passionate about? Big question. Who wants toe start? >>Not biased. But for years I've been saying that if you want to solve the economy, the environment, uh, global unrest, pandemics, education is the case. If you wanna. If you want to, um, make progress in those in those realms, I think funding funding education is probably gonna pay off pretty well. >>Absolutely. And I think Stam is key to that. I mean, all of the ah lot of the well being that we have today and then industrialized countries. Thanks to science and technology, right improvements in health care, improvements in communication, transportation, air conditioning. Um, every aspect of life is touched by science and technology. So I think having more kids studying and understanding that is absolutely key. Yeah, I agree, >>Philip, you got anything to add? >>I think there's some big technical problems in the world today, Raphael and ourselves there certainly working on a couple of them. Think they're also collaboration problems and getting everybody to be able to pull together instead of pulling separately and to be able to spur the ideas on words. So that's where I think the education side is really exciting. What Matt is doing and it just kind of collaboration in general when we could do provide tools to help people do good work. Uh, that is, I think, valuable. >>Yeah, I think that's a very good point. And along those lines, we have some projects that are about creating very low cost instruments for low research settings, places in Africa, Southeast Asia, South America, so that they can do, um, um, biomedical research that it's difficult to do in those place because they don't have the money to buy the fancy lab machines that cost $30,000 an hour. Um, so we're trying to sort of democratize some of those instruments. And I think thanks to tools like Kahn shape then is easier, for example, to have a conversation with somebody in Africa and show them the design that we have and discuss the details of it with them on. But it's amazing, right to have somebody, you know, 10 time zones away, Um, looking really life in real time with you about your design and discussing the details or teaching them how to build a machine, right? Because, um, you know, they have a three D printer. You can you can just give them the design and say like, you build it yourself, uh, even cheaper than and, you know, also billing and shipping it there. Um, so all that that that aspect of it is also super important. I think for any of these efforts to improve some of the hardest part was in the world for climate change. Do you say, as you say, poverty, nutrition issues? Um, you know, availability of water. You have that project at about finding water. Um, if we can also help deploy technologies that teach people remotely how to create their own technologies or how to build their own systems that will help them solve those forms locally. I think that's very powerful. >>Yeah, the point about education is right on. I think some people in the audience may be familiar with the work of Erik Brynjolfsson and Andrew McAfee, the second machine age where they sort of put forth the premise that, uh, is it laid it out. Look, for the first time in history, machines air replacing humans from a cognitive perspective. Machines have always replaced humans, but that's gonna have an impact on jobs. But the answer is not toe protect the past from the future. The answer is education and public policy that really supports that. So I couldn't agree more. I think it's a really great point. Um, we have We do have some questions from the audience. If if we could If I can ask you guys, um, you know, this one kind of stands out. How do you see artificial intelligence? I was just talking about machine intelligence. Um, how do you see that? Impacting the design space guys trying to infuse a I into your product development. Can you tell me? >>Um, absolutely, like, we're using AI for some things, including some of these very low cost instruments that will hopefully help us diagnose certain diseases, especially this is that are very prevalent in the Third World. Um, and some of those diagnostics are these days done by thes armies of technicians that are trained to look under the microscope. But, um, that's a very slow process. Is very error prone and having machine learning systems that can to the same diagnosis faster, cheaper and also little machines that can be taken to very remote places to these villages that have no access to a fancy microscope. To look at a sample from a patient that's very powerful. And I we don't do this, but I have read quite a bit about how certain places air using a Tribune attorneys to actually help them optimize designs for parts. So you get these very interesting looking parts that you would have never thought off a person would have never thought off, but that are incredibly light ink. Earlier, strong and I have all sort of properties that are interesting thanks to artificial intelligence machine learning in particular >>yet another. The advantage you get when when your work is in the cloud I've seen. I mean, there's just so many applications that so if the radiology scan is in the cloud and the radiologist is goes to bed at night, Radiologist could come in in the morning and and say, Oh, the machine while you were sleeping was using artificial intelligence to scan these 40,000 images. And here's the five that we picked out that we think you should take a closer look at. Or like Raphael said, I can design my part. My, my, my, my, my you know, mount or bracket or whatever and go to sleep. And then I wake up in the morning. The machine has improved. It for me has made it strider strider stronger and lighter. Um And so just when your when your work is in the cloud, that's just that's a really cool advantage that you get that you can have machines doing some of your design work for you. >>Yeah, we've been watching, uh, you know, this week is this month, I guess is AWS re invent and it's just amazing to see how much effort is coming around machine learning machine intelligence. You know Amazon has sage maker Google's got, you know, embedded you no ML and big query. Uh, certainly Microsoft with Azure is doing tons of stuff and machine learning. I think the point there is that that these things will be infused in tow R and D and in tow software product by the vendor community. And you all will apply that to your business and and build value through the unique data that your collecting, you know, in your ecosystems. And and that's how you add value. You don't have to be necessarily, you know, developers of artificial intelligence, but you have to be practitioners to apply that. Does that make sense to you, Philip? >>Yeah, absolutely. And I think your point about value is really well chosen. We see AI involved from the physics simulations all the way up to interpreting radiation data, and that's where the value question, I think, is really important because it's is the output of the AI giving helpful information that the people that need to be looking at it. So if it's curating a serious of radiation alert, saying, Hey, like these air the anomalies. You need to look at eyes it, doing that in a way that's going to help a good response on. In some cases, the II is only as good as the people. That sort of gave it a direction and turn it loose. And you want to make sure that you don't have biases or things like that underlying your AI that they're going to result in less than helpful outcomes coming from it. So we spend quite a lot of time thinking about how do we provide the right outcomes to people who are who are relying on our systems? >>That's a great point, right? Humans air biased and humans build models, so models are inherently biased. But then the software is hitting the market. That's gonna help us identify those biases and help us, you know? Of course. Correct. So we're entering Cem some very exciting times, guys. Great conversation. I can't thank you enough for spending the time with us and sharing with our audience the innovations that you're bringing to help the world. So thanks again. >>Thank you so much. >>Thank you. >>Okay. Welcome. Okay. When we come back, John McElheny is gonna join me. He's on shape. Co founder. And he's currently the VP of strategy at PTC. He's gonna join the program. We're gonna take a look at what's next and product innovation. I'm Dave Volonte and you're watching innovation for good on the Cube, the global leader. Digital technology event coverage. We'll be right back. >>Okay? Okay. Yeah. Okay. >>From around >>the globe, it's the Cube. Presenting innovation for good. Brought to you by on shape. >>Okay, welcome back to innovation. For good. With me is John McElheny, who is one of the co founders of On Shape and is now the VP of strategy at PTC. John, it's good to see you. Thanks for making the time to come on the program. Thanks, Dave. So we heard earlier some of the accomplishments that you've made since the acquisition. How has the acquisition affected your strategy? Maybe you could talk about what resource is PTC brought to the table that allowed you toe sort of rethink or evolve your strategy? What can you share with us? >>Sure. You know, a year ago, when when John and myself met with Jim Pepperman early on is we're we're pondering. Started joining PTC one of things became very clear is that we had a very clear shared vision about how we could take the on shape platform and really extended for, for all of the PTC products, particular sort of their augmented reality as well as their their thing works or the i o. T business and their product. And so from the very beginning there was a clear strategy about taking on shape, extending the platform and really investing, um, pretty significantly in the product development as well as go to market side of things, uh, toe to bring on shape out to not only the PTC based but sort of the broader community at large. So So So PTC has been a terrific, terrific, um, sort of partner as we've we've gonna go on after this market together. Eso We've added a lot of resource and product development side of things. Ah, lot of resource and they go to market and customer success and support. So, really, on many fronts, that's been both. Resource is as well a sort of support at the corporate level from from a strategic standpoint and then in the field, we've had wonderful interactions with many large enterprise customers as well as the PTC channels. So it's been really a great a great year. >>Well, and you think about the challenges of in your business going to SAS, which you guys, you know, took on that journey. You know, 78 years ago. Uh, it's not trivial for a lot of companies to make that transition, especially a company that's been around as long as PTC. So So I'm wondering how much you know, I was just asking you How about what PCP TC brought to the table? E gotta believe you're bringing a lot to the table to in terms of the mindset, uh, even things is, is mundane is not the right word, but things like how you compensate salespeople, how you interact with customers, the notion of a service versus a product. I wonder if you could address >>that. Yeah, it's a it's a really great point. In fact, after we had met Jim last year, John and I one of the things we walked out in the seaport area in Boston, one of things we sort of said is, you know, Jim really gets what we're trying to do here and and part of let me bring you into the thinking early on. Part of what Jim talked about is there's lots of, you know, installed base sort of software that's inside of PTC base. That's helped literally thousands of customers around the world. But the idea of moving to sass and all that it entails both from a technology standpoint but also a cultural standpoint. Like How do you not not just compensate the sales people as an example? But how do you think about customer success? In the past, it might have been that you had professional services that you bring out to a customer, help them deploy your solutions. Well, when you're thinking about a SAS based offering, it's really critical that you get customers successful with it. Otherwise, you may have turned, and you know it will be very expensive in terms of your business long term. So you've got to get customers success with software in the very beginning. So you know, Jim really looked at on shape and he said that John and I, from a cultural standpoint, you know, a lot of times companies get acquired and they've acquired technology in the past that they integrate directly into into PTC and then sort of roll it out through their products, are there just reached channel, he said. In some respects, John John, think about it as we're gonna take PTC and we want to integrate it into on shape because we want you to share with us both on the sales side and customer success on marketing on operations. You know all the things because long term, we believe the world is a SAS world, that the whole industry is gonna move too. So really, it was sort of an inverse in terms of the thought process related to normal transactions >>on That makes a lot of sense to me. You mentioned Sharon turns the silent killer of a SAS company, and you know, there's a lot of discussion, you know, in the entrepreneurial community because you live this, you know what's the best path? I mean today, You see, you know, if you watch Silicon Valley double, double, triple triple, but but there's a lot of people who believe, and I wonder, if you come in there is the best path to, you know, in the X Y axis. If if it's if it's uh, growth on one and retention on the other axis. What's the best way to get to the upper right on? Really? The the best path is probably make sure you've nailed obviously the product market fit, But make sure that you can retain customers and then throw gas on the fire. You see a lot of companies they burn out trying to grow too fast, but they haven't figured out, you know that. But there's too much churn. They haven't figured out those metrics. I mean, obviously on shape. You know, you were sort of a pioneer in here. I gotta believe you've figured out that customer retention before you really, You know, put the pedal to the >>metal. Yeah, and you know, growth growth can mask a lot of things, but getting getting customers, especially the engineering space. Nobody goes and sits there and says, Tomorrow we're gonna go and and, you know, put 100 users on this and and immediately swap out all of our existing tools. These tools are very rich and deep in terms of capability, and they become part of the operational process of how a company designs and builds products. So any time anybody is actually going through the purchasing process. Typically, they will run a try along or they'll run a project where they look at. Kind of What? What is this new solution gonna help them dio. How are we gonna orient ourselves for success? Longer term. So for us, you know, getting new customers and customer acquisition is really critical. But getting those customers to actually deploy the solution to be successful with it. You know, we like to sort of, say, the marketing or the lead generation and even some of the initial sales. That's sort of like the Kindle ing. But the fire really starts when customers deploy it and get successful. The solution because they bring other customers into the fold. And then, of course, if they're successful with it, you know, then in fact, you have negative turn which, ironically, means growth in terms of your inside of your install. Bates. >>Right? And you've seen that with some of the emerging, you know, SAS companies, where you're you're actually you know, when you calculate whatever its net retention or renew ALS, it's actually from a dollar standpoint. It's up in the high nineties or even over 100%. >>So >>and that's a trend we're gonna continue. See, I >>wonder >>if we could sort of go back. Uh, and when you guys were starting on shape, some of the things that you saw that you were trying to strategically leverage and what's changed, you know, today we were talking. I was talking to John earlier about in a way, you kinda you kinda got a blank slate is like doing another startup. >>You're >>not. Obviously you've got installed base and customers to service, but But it's a new beginning for you guys. So one of the things that you saw then you know, cloud and and sas and okay, but that's we've been there, done that. What are you seeing? You know today? >>Well, you know, So So this is a journey, of course, that that on shape on its own has gone through it had I'll sort of say, you know, several iterations, both in terms of of of, you know, how do you How do you get customers? How do you How do you get them successful? How do you grow those customers? And now that we've been part of PTC, the question becomes okay. One, There is certainly a higher level of credibility that helps us in terms of our our megaphone is much bigger than it was when we're standalone company. But on top of that now, figuring out how to work with their channel with their direct sales force, you know, they have, um, for example, you know, very large enterprises. Well, many of those customers are not gonna go in forklift out their existing solution to replace it with with on shape. However, many of them do have challenges in their supply chain and communications with contractors and vendors across the globe. And so, you know, finding our fit inside of those large enterprises as they extend out with their their customers is a very interesting area that we've really been sort of incremental to to PTC. And then, you know, they they have access to lots of other technology, like the i o. T business. And now, of course, the augmented reality business that that we can bring things to bear. For example, in the augmented reality world, they've they've got something called expert capture. And this is essentially imagine, you know, in a are ah, headset that allows you to be ableto to speak to it, but also capture images still images in video. And you could take somebody who's doing their task and capture literally the steps that they're taking its geo location and from their builds steps for new employees to be, we'll learn and understand how todo use that technology to help them do their job better. Well, when they do that, if there is replacement products or variation of of some of the tools that that they built the original design instruction set for they now have another version. Well, they have to manage multiple versions. Well, that's what on shape is really great at doing and so taking our technology and helping their solutions as well. So it's not only expanding our customer footprint, it's expanding the application footprint in terms of how we can help them and help customers. >>So that leads me to the tam discussion and again, as part of your strategist role. How do you think about that? Was just talking to some of your customers earlier about the democratization of cat and engineering? You know, I kind of joked, sort of like citizen engineering, but but so that you know, the demographics are changing the number of users potentially that can access the products because the it's so much more of a facile experience. How are you thinking about the total available market? >>It really is a great question, You know, it used to be when you when you sold boxes of software, it was how many engineers were out there. And that's the size of the market. The fact that matter is now when, When you think about access to that information, that data is simply a pane of glass. Whether it's a computer, whether it's a laptop, UH, a a cell phone or whether it's a tablet, the ability to to use different vehicles, access information and data expands the capabilities and power of a system to allow feedback and iteration. I mean, one of the one of the very interesting things is in technology is when you can take something and really unleash it to a larger audience and builds, you know, purpose built applications. You can start to iterate, get better feedback. You know there's a classic case in the clothing industry where Zara, you know, is a fast sort of turnaround. Agile manufacturer. And there was a great New York Times article written a couple years ago. My wife's a fan of Zara, and I think she justifies any purchases by saying, You know, Zara, you gotta purchase it now. Otherwise it may not be there the next time. Yet you go back to the store. They had some people in a store in New York that had this woman's throw kind of covering Shaw. And they said, Well, it would be great if we could have this little clip here so we can hook it through or something. And they sent a note back toe to the factory in Spain, and literally two weeks later they had, you know, 4000 of these things in store, and they sold out because they had a closed loop and iterative process. And so if we could take information and allow people access in multiple ways through different devices and different screens, that could be very specific information that, you know, we remove a lot of the engineering data book, bring the end user products conceptually to somebody that would have had to wait months to get the actual physical prototype, and we could get feedback well, Weaken have a better chance of making sure whatever product we're building is the right product when it ultimately gets delivered to a customer. So it's really it's a much larger market that has to be thought of rather than just the kind of selling A boxes software to an engineer. >>That's a great story. And again, it's gonna be exciting for you guys to see that with. The added resource is that you have a PTC, Um, so let's talk. I promise people we wanna talk about Atlas. Let's talk about the platform. A little bit of Atlas was announced last year. Atlas. For those who don't know it's a SAS space platform, it purports to go beyond product lifecycle management and you You're talking cloud like agility and scale to CAD and product design. But John, you could do a better job than I. What do >>we need to know about Atlas? Well, I think Atlas is a great description because it really is metaphorically sort of holding up all of the PTC applications themselves. But from the very beginning, when John and I met with Jim, part of what we were intrigued about was that he shared a vision that on shape was more than just going to be a cad authoring tool that, in fact, you know, in the past these engineering tools were very powerful, but they were very narrow in their purpose and focus. And we had specialty applications to manage the versions, etcetera. What we did in on shape is we kind of inverted that thinking. We built this collaboration and sharing engine at the core and then kind of wrap the CAD system around it. But that collaboration sharing and version ING engine is really powerful. And it was that vision that Jim had that he shared that we had from the beginning, which was, how do we take this thing to make a platform that could be used for many other applications inside of inside of any company? And so not only do we have a partner application area that is is much like the APP store or Google play store. Uh, that was sort of our first Stan Shih ation of this. This this platform. But now we're extending out to broader applications and much meatier applications. And internally, that's the thing works in the in the augmented reality. But there'll be other applications that ultimately find its way on top of this platform. And so they'll get all the benefits of of the collaboration, sharing the version ing the multi platform, multi device. And that's an extremely extremely, um, strategic leverage point for the company. >>You know, it's interesting, John, you mentioned the seaport before. So PTC, for those who don't know, built a beautiful facility down at the Seaport in Boston. And, of course, when PTC started, you know, back in the mid 19 eighties, there was nothing at the seaport s. >>So it's >>kind of kind of ironic, you know, we were way seeing the transformation of the seaport. We're seeing the transformation of industry and of course, PTC. And I'm sure someday you'll get back into that beautiful office, you know? Wait. Yeah, I'll bet. And, uh and but I wanna bring this up because I want I want you to talk about the future. How you how you see that our industry and you've observed this has moved from very product centric, uh, plat platform centric with sass and cloud. And now we're seeing ecosystems form around those products and platforms and data flowing through the ecosystem powering, you know, new innovation. I wonder if you could paint a picture for us of what the future looks like to you from your vantage point. >>Yeah, I think one of the key words you said there is data because up until now, data for companies really was sort of trapped in different applications. And it wasn't because people were nefarious and they want to keep it limited. It was just the way in which things were built. And, you know, when people use an application like on shape, what ends up happening is there their day to day interaction and everything that they do is actually captured by the platform. And, you know, we don't have access to that data. Of course it's it's the customer's data. But as as an artifact of them using the system than doing their day to day job, what's happening is they're creating huge amounts of information that can then be accessed and analyzed to help them both improve their design process, improve their efficiencies, improve their actual schedules in terms of making sure they can hit delivery times and be able to understand where there might be roadblocks in the future. So the way I see it is companies now are deploying SAS based tools like on shape and an artifact of them. Using that platform is that they have now analytics and tools to better understand and an instrument and manage their business. And then from there, I think you're going to see, because these systems are all you know extremely well. Architected allow through, you know, very structured AP. I calls to connect other SAS based applications. You're gonna start seeing closed loop sort of system. So, for example, people design using on shape, they end up going and deploying their system or installing it, or people use the end using products. People then may call back into the customers support line and report issues, problems, challenges. They'll be able to do traceability back to the underlying design. They'll be able to do trend analysis and defect analysis from the support lines and tie it back and closed loop the product design, manufacture, deployment in the field sort of cycles. In addition, you can imagine there's many things that air sort of as designed. But then when people go on site and they have to install it. There's some alterations modifications. Think about think about like a large air conditioning units for buildings. You go and you go to train and you get a large air conditioning unit that put up on top of building with a crane. They have to build all kinds of adaptors to make sure that that will fit inside of the particulars of that building. You know, with on shape and tools like this, you'll be able to not only take the design of what the air conditioning system might be, but also the all the adapter plates, but also how they installed it. So it sort of as designed as manufactured as stalled. And all these things can be traced, just like if you think about the transformation of customer service or customer contacts. In the early days, you used to have tools that were PC based tools called contact management solution, you know, kind of act or gold mine. And these were basically glorified Elektronik role in Texas. It had a customer names and they had phone numbers and whatever else. And Salesforce and Siebel, you know, these types of systems really broadened out the perspective of what a customer relationship? Waas. So it wasn't just the contact information it was, you know, How did they come to find out about you as a company? So all of the pre sort of marketing and then kind of what happens after they become a customer and it really was a 3 60 view. I think that 3 60 view gets extended to not just to the customers, but also tools and the products they use. And then, of course, the performance information that could come back to the manufacturer. So, you know, as an engineer, one of the things you learn about with systems is the following. And if you remember, when the CD first came out CDs that used to talk about four times over sampling or eight times over sampling and it was really kind of, you know, the fidelity the system. And we know from systems theory that the best way to improve the performance of a system is to actually have more feedback. The more feedback you have, the better system could be. And so that's why you get 16 60 for example, etcetera. Same thing here. The more feedback we have of different parts of a company that a better performance, The company will be better customer relationships. Better, uh, overall financial performance as well. So that's that's the view I have of how these systems all tied together. >>It's a great vision in your point about the data is I think right on. It used to be so fragmented in silos, and in order to take a system view, you've gotta have a system view of the data. Now, for years, we've optimized maybe on one little component of the system and that sometimes we lose sight of the overall outcome. And so what you just described, I think is, I think sets up. You know very well as we exit. Hopefully soon we exit this this covert era on John. I hope that you and I can sit down face to face at a PTC on shape event in the near term >>in the seaport in the >>seaport would tell you that great facility toe have have an event for sure. It >>z wonderful >>there. So So John McElhinney. Thanks so much for for participating in the program. It was really great to have you on, >>right? Thanks, Dave. >>Okay. And I want to thank everyone for participating. Today we have some great guest speakers. And remember, this is a live program. So give us a little bit of time. We're gonna flip this site over toe on demand mode so you can share it with your colleagues and you, or you can come back and and watch the sessions that you heard today. Uh, this is Dave Volonte for the Cube and on shape PTC. Thank you so much for watching innovation for good. Be well, Have a great holiday. And we'll see you next time. Yeah.

>>from around the globe. It's the Cube presenting innovation for good. Brought to you by on shape. >>Okay, we're back. This is Dave Volonte and you're watching innovation for good. A program on Cuba 3 65 made possible by on shape of BTC company. We're live today really live TV, which is the heritage of the Cuban. Now we're gonna go to the sources and talkto on shape customers to find out how they're applying technology to create real world innovations that are changing the world. So let me introduce our panel members. Rafael Gomez Fribourg is with the Chan Zuckerberg bio hub. A very big idea. And collaborative nonprofit was initiative that was funded by Mark Zuckerberg and his wife, Priscilla Chan, and really around diagnosing and curing and better managing infectious diseases. So really timely topic. Philip Tabor is also joining us. He's with silver side detectors which develops neutron detective detection systems. Yet you want to know if early if neutrons and radiation or in places where you don't want them, so this should be really interesting. And last but not least, Matthew Shields is with the Charlottesville schools and is gonna educate us on how he and his team are educating students in the use of modern engineering tools and techniques. Gentlemen, welcome to the Cuban to the program. This should be really interesting. Thanks for coming on. >>Hi. Or pleasure >>for having us. >>You're very welcome. Okay, let me ask each of you because you're all doing such interesting and compelling work. Let's start with Rafael. Tell us more about the bio hub and your role there, please. >>Okay. Yes. As you said, the Bio Hope is a nonprofit research institution, um, funded by Mark Zuckerberg and his wife, Priscilla Chan. Um and our main mission is to develop new technologies to help advance medicine and help, hopefully cure and manage diseases. Um, we also have very close collaborations with Universe California, San Francisco, Stanford University and the University California Berkeley on. We tried to bring those universities together, so they collaborate more of biomedical topics. And I manage a team of engineers in by joining platform. Um, and we're tasked with creating instruments for the laboratory to help the scientist boats inside the organization and also in the partner universities do their experiments in better ways in ways that they couldn't do before >>in this edition was launched five years ago. It >>was announced at the end of 2016, and we actually started operations in the beginning of 2017, which is when I joined um, so this is our third year. >>And how's how's it going? How does it work? I mean, these things >>take time. It's been a fantastic experience. Uh, the organization works beautifully. Um, it was amazing to see it grow from the beginning. I was employee number 12, I think eso When I came in, it was just a nem p off his building and MP labs. And very quickly we had something running about from anything. Eso I'm very proud of the work that we have done to make that possible. Um And then, of course, that's you mentioned now, with co vid, um, we've been able to do a lot of very cool work, um, very being of the pandemic In March, when there was a deficit of testing, uh, capacity in California, we spun up a testing laboratory in record time in about a week. It was crazy. It was a crazy project. Um, but but incredibly satisfying. And we ended up running all the way until the beginning of November, when the lab was finally shut down, we could process about 3000 samples a day. I think at the end of it all, we were able to test about 100 on the road, 150,000 samples from all over the state. We were providing free testing toe all of the Department of Public Health Department of Public Health in California, which, at the media pandemic, had no way to do testing affordably and fast. So I think that was a great service to the state. Now the state has created a testing system that will serve those departments. So then we decided that it was unnecessary to keep going with testing in the other biopsy that would shut down, >>right? Thank you for that. Now, Now, Philip, you What you do is mind melting. You basically helped keep the world safe. Maybe you describe a little bit more about silver side detectors and what your role is there and how it all works. >>Tour. So we make a nuclear bomb detectors and we also make water detectors. So we try and do our part. Thio Keep the world from blowing up and make it a better place at the same time. Both of these applications use neutron radiation detectors. That's what we make. Put them out by a port border crossing Places like that they can help make sure that people aren't smuggling, shall we say, very bad things. Um, there's also a burgeoning field of research and application where you can use neutrons with some pretty cool physics to find water so you can do things like but a detector up in the mountains and measure snowpack. Put it out in the middle of the field and measure soil moisture content. And as you might imagine, there's some really cool applications in, uh, research and agronomy and public policy for this. >>All right, so it's OK, so it's It's much more than you know, whatever fighting terrorism, it's there's a riel edge, or I kind of i o t application for what you guys do. >>You do both Zito shares. You might >>say a mat. I I look at your role is kind of scaling the brain power for for the future. Maybe tell us more about Charlottesville schools and in the mission that you're pursuing and what you do. >>Thank you. Um, I've been in Charlottesville city schools for about 11 or 12 years. I started their teaching, Um, a handful of classes, math and science and things like that. But Thescore board and my administration had the crazy idea of starting an engineering program about seven years ago. My background is an engineering is an engineering. My masters is in mechanical and aerospace engineering. And, um, I basically spent a summer kind of coming up with what might be a fun engineering curriculum for our students. And it started with just me and 30 students about seven years ago, Um, kind of a home spun from scratch curriculum. One of my goals from the outside was to be a completely project based curriculum, and it's now grown. We probably have about six or 700 students, five or six full time teachers. We now have pre engineering going on at the 5th and 6th grade level. I now have students graduating. Uh, you know, graduating after senior year with, like, seven years of engineering under their belt and heading off to doing some pretty cool stuff. So it's It's been a lot of fun building up a program and, um, and learning a lot in the process. >>That's awesome. I mean, you know, Cuba's. We've been passionate about things like women in tech, uh, diversity stem. You know, not only do we need more more students in stem, we need mawr underrepresented women, minorities, etcetera. We were just talking to John her stock and integrate Grayson about this is do you do you feel is though you're I mean, first of all, the work that you do is awesome, but but I'll go one step further. Do you feel as though it's reaching, um, or, you know, diverse base and And how is that going? >>That's a great question. I think research shows that a lot of people get funneled into one kind of track or career path or set of interests really early on in their educational career. And sometimes that that funnels kind of artificial. And so that's one of the reasons we keep pushing back. Um, so our school systems introducing kindergartners to programming on DSO. We're trying to push back how we expose students to engineering and to stem fields as early as possible, and we've definitely seen the fruits of that in my program. In fact, my engineering program, uh, sprung out of an after school in Extracurricular Science Club that actually three girls started at our school. So I think that actually has helped that three girls started the club That eventually is what led our engineering programs that sort of baked into the DNA and also are a big public school. And we have about 50% of the students are under the poverty line, and we should I mean, Charlottesville, which is a big refugee town. And so I've been adamant from Day one that there are no barriers to entry into the program. There's no test you have to take. You don't have to have be taking a certain level of math or anything like that. That's been a lot of fun. To have a really diverse set of kids and or the program and be successful, >>that's phenomenal. That's great to hear. So, Philip, I wanna come back to you. You know, I think about maybe some day we'll be able to go back to a sporting events, and I know when I when I'm in there, there's somebody up on the roof looking out for me, you know, watching the crowd. And they have my back. And I think in many ways, the products that you build, you know, our similar I may not know they're there, but they're keeping us safe or they're measuring things that that that I don't necessarily see. But I wonder if you could talk about a little bit more detail about the products you build and how they're impacting society. >>Sure, So there are certainly a lot of people who are who are watching, trying to make sure things were going well in keeping you safe that you may or may not be aware of. And we try and support ah lot of them. So we have detectors that are that are deployed in a variety of variety of uses with a number of agencies and governments that dio like I was saying, ports and border crossing some other interesting applications that are looking for looking for signals that should not be there and working closely to fit into the operations these folks do Onda. We also have ah lot of outreach to researchers and scientists trying to help them support the work they're doing, um, using neutron detection for soil moisture monitoring is a some really cool opportunities for doing it at large scale and with much less, um, expense or complication then would have been done previous technologies. Mhm. You know, they were talking about collaboration in the previous segment. We've been able to join a number of conferences for that, virtually including one that was supposed to be held in Boston. But another one that was held, uh, of the University of Heidelberg in Germany. And, uh, this is sort of things that in some ways, the pandemic is pushing people towards greater collaboration than there would have been able to do. Had it all but in person. >>Yeah, we did. Uh, the cube did live works a couple years ago in Boston. It was awesome show. And I think, you know, with this whole trend toward digit, I call it the forced march to digital. Thanks to cove it I think that's just gonna continue. Thio grow Raphael one. If you could describe the process that you used to better understand diseases and what's your organization's involvement? Been in more detail, addressing the cove in pandemic. >>Um, so so we have the bio be structured in, Um um, in a way that foster So the combination of technology and science. So we have to scientific tracks, one about infectious diseases and the other one about understanding just basic human biology how the human body functions and especially how the cells in the human body function on how they're organized to create teachers in the body. Um, and then it has the set of platforms. Um, mind is one of them by engineering that are all technology. Read it. So we have data science platform, all about data analysis, machine learning, things like that. Um, we have a mass spectrometry platform is all about mass spectrometry technologies to, um, exploit those ones in service for the scientists on. We have a genomics platform. That is all about sequencing DNA in our DNA. Um, and then an advanced microscopy. It's all about developing technologies, uh, to look at things with advanced microscopes and the little technologies to marry computation on microscope. So, um, the scientists said the agenda and the platforms we just serve their needs, support their needs, and hopefully develop technologies that help them do their experiments better, faster, or allow them to the experiment that they couldn't do in any other way before. Um And so with cove, it because we have that very strong group of scientists that work on. I have been working on infectious disease before, and especially in viruses, we've been able to very quickly pivot to working on that s O, for example, my team was able to build pretty quickly a machine to automatically purified proteins, and it's being used to purify all these different important proteins in the cove. It virus the SARS cov to virus on Dwyer, sending some of those purified proteins all over the world. Two scientists that are researching the virus and trying to figure out how to develop vaccines, understand how the virus affects the body and all that. So some of the machines we built are having a very direct impact on this. Um, Also for the copy testing lab, we were able to very quickly develop some very simple machines that allowed the lab to function sort of faster and more efficiently. Sort of had a little bit of automation in places where we couldn't find commercial machines that would do it. >>Um, God s o mat. I mean, you gotta be listening to this in thinking about, Okay? Some. Someday your students are gonna be working at organizations like Like like Bio Hub and Silver Side. And you know, a lot of young people that just have I don't know about you guys, but like my kids, they're really passionate about changing the world. You know, there's way more important than, you know, the financial angles and that z e I gotta believe you're seeing that you're right in the front lines there. >>Really? Um, in fact, when I started the curriculum six or seven years ago, one of the first bits of feedback I got from my students is they said Okay, this is a lot of fun. So I had my students designing projects and programming microcontrollers raspberry, PiS and order We nose and things like that. The first bit of feedback I got from students was they said Okay, when do we get to impact the world? I've heard engineering is about making the world a better place, and robots are fun and all, but, you know, where is the real impact? And so, um do Yeah, thanks to the guidance of my students, I'm baking that Maurin. Now I'm like Day one of engineering one. We talk about how the things that the tools they're learning and the skills they're gaining eventually you know, very soon could be could be used to make the world a better place. >>You know, we all probably heard that famous line By Jeff Hammond Barker. The greatest minds of my generation are trying to figure out how to get people to click on ads. E. I think we're really generally generationally finally, at the point where you know young students and engineering and really you know it passionate about affecting society. I wanna get into the product, you know, side and understand how each of you are using on shape and and the value that that it brings. Maybe Raphael, you could start how long you've been using it. You know, what's your experience with it? Let's let's start there. >>I begin for about two years, and I switched to it with some trepidation. You know, I was used to always using the traditional product that you have to install on your computer, that everybody uses that. So I was kind of locked into that, but I started being very frustrated with the way it worked, um, and decided to give on ship chance. Which reputation? Because any change always, you know, causes anxiety. But very quickly my engineers started loving it. Uh, just because it's it's first of all, the learning curve wasn't very difficult at all. You can transfer from one from the traditional product to entree very quickly and easily. You can learn all the concepts very, very fast. It has all the functionality that we needed, and and what's best is that it allows to do things that we couldn't do before or we couldn't do easily. Um, now we can access the our cat documents from anywhere in the world. Um, so when we're in the lab fabricating something or testing a machine, any computer we have next to us or a tablet or on iPhone, we can pull it up and look at the cad and check things or make changes that something that couldn't do before because before you had to pay for every installation off the software for the computer, and I couldn't afford to have 20 installations to have some computers with the cat ready to use them like once every six months would have been very inefficient. So we love that part. And the collaboration features are fantastic. Especially now with Kobe, that we have to have all the remote meetings, eyes fantastic, that you can have another person drive the cad while the whole team is watching that person change the model and do things and point to things that is absolutely revolutionary. We love it. The fact that you have very, very sophisticated version control before it was always a challenge asking people, please, if you create anniversary and apart, how do we name it so that people find it? And then you end up with all these collection of files with names that nobody remembers, what they are, the person left and now nobody knows which version is the right one m s with on shape on the version ING system it has, and the fact that you can go back in history off the document and go back to previous version so easily and then go back to the press and version and explore the history of the part that is truly, um, just world changing for us, that we can do that so easily on for me as a manager to manage this collection of information that is critical for our operations. It makes it so much easier because everything is in one place. I don't have to worry about file servers that go down that I have to administer that have to have I t taken care off that have to figure how to keep access to people to those servers when they're at home. And they need a virtual private network and all of that mess disappears. I just simply give give a personal account on shape. And then, magically, they have access to everything in the way I want. And we can manage the lower documents and everything in a way, that is absolutely fantastic. >>Rafael, what was your what? What were some of the concerns you had mentioned? You had some trepidation. Was it a performance? Was it security? You know, some of the traditional cloud stuff and I'm curious as to how How whether any of those act manifested were they really that you had to manage? What were your concerns? >>Look, the main concern is how long is it going to take for everybody in the team? to learn to use the system like it and buy into it because I don't want to have my engineers using tools against their will write. I want everybody to be happy because that's how they're productive. They're happy and they enjoyed the tools they have. That was my main concern. I was a little bit worried about the whole concept of not having the files in a place where I couldn't quote unquote seat in some serving on site, but that that's kind of an outdated concept, right? So that took a little bit of a mind shift. But very quickly. Then I started thinking, Look, I have a lot of documents on Google Drive like I don't worry about that. Why would I worry about my cat on on shape? Right is the same thing. So I just needed to sort of put things in perspective that way. Um, the other, um, you know, their concern was the learning curve right is like how is he will be for everybody to and for me to learn it on whether it had all of the features that we needed and there were a few features that I actually discussed with, um uh, Cody at on shape on. They were actually awesome about using their scripting language in on shape to sort of mimic some of the features of the old cat, uh, in on shaped in a way that actually works even better than the old system. So it was It was amazing. Yeah. >>Great. Thank you for that, Phillip. What's your experience been? Maybe you could take us through your journey with on shape? >>Sure. So we've been we've been using on shaped Silver Side for coming up on about four years now, and we love it. We're very happy with it. We have a very modular product line, so and we make anything from detectors that would go into backpacks? Two vehicles, two very large things that a shipping container would go through and saw. Excuse me. Shape helps us to track and collaborate faster on the design, have multiple people working a same time on a project. And it also helps us to figure out if somebody else comes to us and say, Hey, I want something new. How we congrats modules from things that we already have. Put them together and then keep track of the design development and the different branches and ideas that we have, how they all fit together. A za design comes together and it's just been fantastic from a mechanical engineering background. I will also say that having used a number of different systems and solid works was the greatest thing since sliced bread. Before I got using on shape, I went, Wow, this is amazing. And I really don't want to design in any other platform after after getting on Lee a little bit familiar with it. >>You know, it's funny, right? I will have the speed of technology progression. I was explaining to some young guns the other day how e used to have a daytime er and that was my life. And if I lost that day, timer, I was dead. And I don't know how we weigh existed without, you know, Google Maps. Eso did we get anywhere? I don't know, but, uh, but so So, Matt, you know, it's interesting to think about, um, you know, some of the concerns that Raphael brought up, you hear? For instance, you know, all the time. Wow. You know, I get my Amazon bill at the end of the month It's through the roof in. But the reality is that Yeah, well, maybe you are doing more, but you're doing things that you couldn't have done before. And I think about your experience in teaching and educating. I mean, you so much more limited in terms of the resource is that you would have had to be able to educate people. So what's your experience been with With on shape and what is it enabled? >>Um, yeah, it was actually talking before we went with on shape. We had a previous CAD program and I was talking to my vendor about it, and he let me know that we were actually one of the biggest CAD shops in the state. Because if you think about it a really big program, you know, really big company might employ 5, 10, 15, 20 cad guys, right? I mean, when I worked for a large defense contractor, I think there were probably 20 of us as the cad guys. I now have about 300 students doing cat. So there's probably more students with more hours of cat under their belt in my building than there were when I worked for the big defense contractor. Um, but like you mentioned, uh, probably our biggest hurdle is just re sources. And so we want We want one of things I've always prided myself and trying to do in this programs provide students with access two tools and skills that they're going to see either in college or in the real world. So it's one of the reason we went with a big professional cad program. There are, you know, sort of k 12 oriented software and programs and things. But, you know, I want my kids coding and python and using slack and using professional type of tools on DSO when it comes to cat. That's just that that was a really hurt. I mean, you know, you could spend $30,000 on one seat of, you know, professional level cad program, and then you need a $30,000 computer to run it on if you're doing a heavy assemblies, Um, and so one of my dreams and it was always just a crazy dream. And I was the way I would always pitcher in my school system and say someday I'm gonna have a kid on a school issued chromebook in subsidized housing on public WiFi doing professional level bad and that that was a crazy statement until a couple of years ago. So we're really excited that I literally and, you know, march in, um, you said the forced march the forced march into, you know, modernity, March 13th kids sitting in my engineering lab that we spent a lot of money on doing. Cad March 14th. Those kids were at home on their school shoot chromebooks on public WiFi, uh, keeping their designs going and collaborating. And then, yeah, I could go on and on about some of the things you know, the features that we've learned since then they're even better. So it's not like this is some inferior, diminished version of the cat. And there's so much about it, E >>wanna I wanna ask you that I may be over my skis on this, but we're seeing we're starting to see the early days of the democratization of CAD and product design. It is the the citizen engineer. I mean, maybe insulting to the engineers in the room, but but is that we're beginning to see that >>I have to believe that everything moves into the cloud. Part of that is democratization that I don't need. I can whether you know, I think artists, you know, I could have a music studio in my basement with a nice enough software package. And Aiken, I could be a professional for now. My wife's a photographer. I'm not allowed to say that I could be a professional photographer with, you know, some cloud based software. And so, yeah, I do think that's part of what we're seeing is more and more technology is moving to the cloud >>Philip or Rafael anything. Your dad, >>I think I mean yeah, that that that combination of cloud based cat and then three D printing that is becoming more and more affordable on ubiquitous It's truly transformative, and I think for education is fantastic. I wish when I was a kid I had the opportunity to play with those kinds of things because I was always the late things. But, you know, the in a very primitive way. So, um, I think there's a dream for kids Thio to be able to do this. And, um, yeah, there's so many other technologies coming on, like Arduino and all of these electronic things that live. Kids play at home very cheaply with things that back in my day would have been unthinkable. >>So we know there's a go ahead. Philip Way >>had a pandemic and silver site moved to a new manufacturing facility this year. I was just on the shop floor, talking with contractors, standing 6 ft apart, pointing at things. But through it all, our CAD system was completely unruffled. Nothing stopped in our development work. Nothing stopped in our support for existing systems in the field. We didn't have to think about it. We had other server issues, but none with our, you know, engineering cad, platform and product development and support world right ahead, which was cool, but also a That's point. I think it's just really cool what you're doing with the kids. The most interesting secondary and college level engineering work that I did was project based. It's an important problem to the world. Go solve it and that is what we do here. That is what my entire career has been. And I'm super excited to see See what your students are gonna be doing, uh, in there home classrooms on their chromebooks now and what they do. Building on that. >>Yeah, I'm super excited to see your kids coming out of college with engineering degrees because yeah, I think that project based experience is so much better than just sitting in a classroom, taking notes and doing math problems on. And I think he will give the kids a much better flavor What engineering is really about. Think a lot of kids get turned off by engineering because they think it's kind of dry because it's just about the math for some very abstract abstract concept, and they are there. But I think the most important thing is just that. Hands on a building and the creativity off, making things that you can touch that you can see that you can see functioning. >>Great. So you know, we all know the relentless pace of technology progression. So when you think about when you're sitting down with the folks that on shape and there the customer advisor for one of the things that you want on shape to do that it doesn't do today >>I could start by saying, I just love some of the things that does do because it's such a modern platform and I think some of these, uh, some some platforms that have a lot of legacy and a lot of history behind them. I think we're dragging some of that behind them. So it's cool to see a platform that seemed to be developed in a modern era. And so that's, you know, it is the Google docks. And so the fact that collaboration and version ing and link sharing is, and, like, platform agnostic abilities the fact that that seems to be just built into the nature of the thing so far, that's super exciting as far as things that it to go from there, Um, I don't know. >>Other than price, >>you can't say I >>can't say lower price. >>Yeah, so far on a PTC s that worked with us. Really well, so I'm not complaining. There. You there? >>Yeah. Yeah. No Gaps, guys. Whitespace, Come on. >>We've been really enjoying the three week update Cadence. You know, there's a new version every three weeks and we don't have to install it. We just get all the latest and greatest goodies. One of the trends that we've been following and enjoying is the the help with a revision management and release work flows. Um, and I know that there's more than on shape is working on that we're very excited for, because that's a big important part about making real hardware and supporting it in the field. Um, something that was cool. They just integrated Cem markup capability In the last release that took, we were doing that anyway, but we were doing it outside of on shapes, and now we get to streamline our workflow and put it in the CAD system where we're making those changes anyway, when we're reviewing drawings and doing this kind of collaboration. And so I think from our perspective, we continue to look forward toa further progress on that. There's a lot of capability in the cloud that I think they're just kind of scratching the surface on you. >>I would. I mean, you're you're asking to knit. Pick. I would say one of the things that I would like to see is is faster regeneration speed. There are a few times with comics necessities that regenerating the document takes a little longer than I would like to. It's not a serious issue, but anyway, I'm being spoiled, >>you know. That's good. I've been doing this a long time and I like toe Ask that question of practitioners and to me, it it's a signal like when you're nit picking and that you're struggling to knit. Pick that to me is a sign of a successful product. And And I wonder, I don't know, uh, have the deep dive into the architecture, But are things like alternative processors? You're seeing them hit the market in a big way. Uh, you know, maybe a helping address the challenge, But I'm gonna ask you the big, chewy question now, then would maybe go to some audience questions when you think about the world's biggest problems. I mean, we're global pandemics. Obviously top of mind. You think about nutrition, you know, feeding the global community. We've actually done a pretty good job of that. But it's not necessarily with the greatest nutrition climate change, alternative energy, the economic divides. You've got geopolitical threats and social unrest. Health care is a continuing problem. What's your vision for changing the world and how product innovation for good can be applied to some of the the problems that that you all are passionate about? Big question. But who wants toe start >>not biased. But for years I've been saying that if you want to solve the economy, the environment, uh, global unrest, pandemics education is the case If you wanna if you want to, um, make progress in those in those realms, I think funding funding education is probably gonna pay off pretty well. >>Absolutely. And I think stem is key to that. I mean, all of the, ah lot of the well being that we have today and then industrialized countries, thanks to science and technology, right, improvements in health care, improvements in communication, transportation, air conditioning. Um, every aspect of life is touched by science and technology. So I think having more kids studying and understanding that is absolutely key. Yeah, I agree, >>Philip, you got anything they had? >>I think there's some big technical problems in the world today, Raphael and ourselves there certainly working on a couple of them. Think they're also collaboration problems and getting everybody doing ableto pull together instead of pulling, pulling separately and to be able to spur the idea is onwards. So that's where I think the education side is really exciting. What Matt is doing and and it just kind of collaboration in general when we could do provide tools to help people do good work? Uh, that is, I think, valuable. >>Yeah, I think that's a very good point. And along those lines, we have some projects that are about creating very low cost instruments for low research settings places in Africa, Southeast Asia, South America so that they can do, um, um, biomedical research that it's difficult to do in those place because they don't have the money to buy the fancy lab machines that cost $30,000 an hour. Um, so we're trying to sort of democratize some of those instruments. And I think thanks to tools like Kahn shaped and is easier, for example, to have a conversation with somebody in Africa and show them the design that we have and discuss the details of it with them. Andi, that's amazing. Right? To have somebody you know, 10 time zones away, Um, looking really life in real time with you about your design and discussing the details or teaching them how to build a machine. Right? Because, um, you know, they have a three d printer. You can you just give them the design and say, like, you build it yourself, uh, even cheaper than and, you know, also billing and shipping it there. Um, so all that that that aspect of it is also so super important, I think, for any of these efforts to improve, um, some of the hardest part was in the world from climate change. Do you say, as you say, poverty, nutrition issues? Um, you know, availability of water. You have that project at about finding water. Um, if we can also help deploy technologies that teach people remotely how to create their own technologies or how to build their own systems that will help them solve those forms locally. I think that's very powerful. >>Yeah, that point about education is right on. I think some people in the audience may be familiar with the work of Erik Brynjolfsson and Andrew McAfee, the second machine age where they sort of put forth the premise that, uh, is it laid it out. Look, for the first time in history, machines air replacing humans from a cognitive perspective. Machines have always replaced humans, but that's gonna have an impact on jobs. But the answer is not toe protect the past from the future. Uh, the answer is education and public policy. That really supports that. So I couldn't agree more. I think it's a really great point. Um, we have We do have some questions from the audience. If if we can. If I can ask you guys, um, you know, this one kind of stands out. How do you see artificial intelligence? I was just talking about machine intelligence. Um, how do you see that? Impacting the design space guys trying to infuse a I into your product development. What can you tell me? >>Um, absolutely. Like, we're using AI for some things, including some of these very low cost instruments that will hopefully help us diagnose certain diseases, especially this is that are very prevalent in the Third World. Um, and some of those diagnostics are these days done by thes armies of technicians that are trained to look under the microscope. But, um, that's a very slow process. Is very error prone and having machine learning systems that can, to the same diagnosis faster, cheaper and also little machines that can be taken to very remote places to these villages that have no access to a fancy microscope to look at a sample from a patient that's very powerful, and I we don't do this. But I have read quite a bit about how certain places air, using a Tribune attorneys to actually help them optimize designs for parts. So you get these very interesting looking parts that you would have never thought off. A person would have never thought off, but that are incredibly light ink earlier strong and I have all sort of properties that are interesting thanks to artificial intelligence machine learning in particular, >>yet another, uh, advantage you get when when your work is in the cloud I've seen. I mean, there's just so many applications that so if the radiology scan is in the cloud and the radiologist is goes to bed at night, radiologist could come in in the morning and and say, Oh, the machine while you were sleeping was using artificial intelligence to scan these 40,000 images. And here's the five that we picked out that we think you should take a closer look at or like Raphael said. I can design my part. My, my, my, my, my you know, mount or bracket or whatever and go to sleep. And then I wake up in the morning. The machine has improved. It for me has made it strider strider stronger and lighter. Um And so just when your when your work is in the cloud, that's just that's a really cool advantage that you get that you can have machines doing some of your design work for you. >>Yeah, we've been watching, uh, you know, this week is this month, I guess is aws re invent and it's just amazing to see how much effort is coming around machine learning machine intelligence. You know, Amazon has sage maker Google's got, you know, embedded you no ML and big query. Certainly Microsoft with Azure is doing tons of stuff and machine learning. I think the point there is that that these things will be infused in tow R and D and in tow software products by the vendor community. And you all will apply that to your business and and build value through the unique data that your collecting you know, in your ecosystems. And and that's how you add value. You don't have to be necessarily, you know, developers of artificial intelligence, but you have to be practitioners to apply that. Does that make sense to you, Philip? >>Yeah, absolutely. And I think your point about value is really well chosen. We see AI involved from the physics simulations all the way up to interpreting radiation data, and that's where the value question, I think, is really important because it's is the output of the AI giving helpful information that the people that need to be looking at it. So if it's curating a serious of radiation alert, saying, Hey, like these are the anomalies you need to look at eyes it, doing that in a way that's going to help a good response on. In some cases, the II is only as good as the people. That sort of gave it a direction and turn it loose. And you want to make sure that you don't have biases or things like that underlying your AI that air going to result in, uh in less than helpful outcomes coming from it. So we spend quite a lot of time thinking about how do we provide the right outcomes to people who are who are relying on our systems? >>That's a great point, right? Humans, air biased and humans build models, so models are inherently biased. But then software is hitting the market. That's gonna help us identify those biases and help us, you know? Of course. Correct. So we're entering Cem some very exciting times, guys. Great conversation. I can't thank you enough for spending the time with us and sharing with our audience the innovations that you're bringing to help the world. So thanks again. >>Thank you so much. >>Thank you. >>Okay. You're welcome. Okay. When we come back, John McElheny is gonna join me. He's on shape. Co founder. And he's currently the VP of strategy at PTC. He's gonna join the program. We're gonna take a look at what's next and product innovation. I'm Dave Volonte and you're watching innovation for good on the Cube, the global leader. Digital technology event coverage. We'll be right back

>> Hello everyone. On today's panel, the theme is Drug Discovery and how Artificial Intelligence can make a difference. On the panel today, we are honored to have Dr. Ryan Yates, principal scientist at The National Center for Natural Products Research, with a focus on botanicals specifically the pharmacokinetics, which is essentially how the drug changes over time in our body and pharmacodynamics which is essentially how drugs affects our body. And of particular interest to him is the use of AI in preclinical screening models to identify chemical combinations that can target chronic inflammatory processes such as fatty liver disease, cognitive impairment and aging. Welcome, Ryan. Thank you for coming. >> Good morning. Thank you for having me. >> The other distinguished panelist is Dr. Rangan Sukumar, our very own, is a distinguished technologist at the CTO office for High Performance Computing and Artificial Intelligence with a PHD in AI and 70 publications that can be applied in drug discovery, autonomous vehicles and social network analysis. Hey Rangan, welcome. Thank you for coming, by sparing the time. We have also our distinguished Chris Davidson. He is leader of our HPC and AI Application and Performance Engineering team. His job is to tune and benchmark applications, particularly in the applications of weather, energy, financial services and life sciences. Yes so particular interest is life sciences he spent 10 years in biotech and medical diagnostics. Hi Chris, welcome. Thank you for coming. >> Nice to see you. >> Well let's start with your Chris, yes, you're regularly interfaced with pharmaceutical companies and worked also on the COVID-19 White House Consortium. You know tell us, let's kick this off and tell us a little bit about your engagement in the drug discovery process. >> Right and that's a good question I think really setting the framework for what we're talking about here is to understand what is the drug discovery process. And that can be kind of broken down into I would say four different areas, there's the research and development space, the preclinical studies space, clinical trial and regulatory review. And if you're lucky, hopefully approval. Traditionally this is a slow arduous process it costs a lot of money and there's a high amount of error. Right, however this process by its very nature is highly iterate and has just huge amounts of data, right it's very data intensive, right and it's these characteristics that make this process a great target for kind of new approaches in different ways of doing things. Right, so for the sake of discussion, right, go ahead. >> Oh yes, so you mentioned data intensive brings to mind Artificial Intelligence, you know, so Artificial Intelligence making the difference here in this process, is that so? >> Right, and some of those novel approaches are actually based on Artificial Intelligence whether it's deep learning and machine learning, et cetera, you know, prime example would say, let's just say for the sake of discussion, let's say there's a brand new virus, causes flu-like symptoms, shall not be named if we focus kind of on the R and D phase, right our goal is really to identify target for the treatment and then screen compounds against it see which, you know, which ones we take forward right to this end, technologies like cryo-electron, cryogenic electron microscopy, just a form of microscopy can provide us a near atomic biomolecular map of the samples that we're studying, right whether that's a virus, a microbe, the cell that it's attaching to and so on, right AI, for instance, has been used in the particle picking aspect of this process. When you take all these images, you know, there are only certain particles that we want to take and study, right whether they have good resolution or not whether it's in the field of the frame and image recognition is a huge part of this, it's massive amounts of data in AI can be very easily, you know, used to approach that. Right, so with docking, you can take the biomolecular maps that you achieved from cryo-electron microscopy and you can take those and input that into the docking application and then run multiple iterations to figure out which will give you the best fit. AI again, right, this is iterative process it's extremely data intensive, it's an easy way to just apply AI and get that best fit doing something in a very, you know, analog manner that would just take humans very long time to do or traditional computing a very long time to do. >> Oh, Ryan, Ryan, you work at the NCNPR, you know, very exciting, you know after all, you know, at some point in history just about all drugs were from natural products yeah, so it's great to have you here today. Please tell us a little bit about your work with the pharmaceutical companies, especially when it is often that drug cocktails or what they call Polypharmacology, is the answer to complete drug therapy. Please tell us a bit more with your work there. >> Yeah thank you again for having me here this morning Dr. Goh, it's a pleasure to be here and as you said, I'm from the National Center for Natural Products Research you'll hear me refer to it as the NCNPR here in Oxford, Mississippi on the Ole Miss Campus, beautiful setting here in the South and so, what, as you said historically, what the drug discovery process has been, and it's really not a drug discovery process is really a therapy process, traditional medicine is we've looked at natural products from medicinal plants okay, in these extracts and so where I'd like to begin is really sort of talking about the assets that we have here at the NCNPR one of those prime assets, unique assets is our medicinal plant repository which comprises approximately 15,000 different medicinal plants. And what that allows us to do, right is to screen mine, that repository for activities so whether you have a disease of interest or whether you have a target of interest then you can use this medicinal plant repository to look for actives, in this case active plants. It's really important in today's environment of drug discovery to really understand what are the actives in these different medicinal plants which leads me to the second unique asset here at the NCNPR and that is our what I'll call a plant deconstruction laboratory so without going into great detail, but what that allows us to do is through a how to put workstation, right, is to facilitate rapid isolation and identification of phytochemicals in these different medicinal plants right, and so things that have historically taken us weeks and sometimes months, think acetylsalicylic acid from salicylic acid as a pain reliever in the willow bark or Taxol, right as an anti-cancer drug, right now we can do that with this system on the matter of days or weeks so now we're talking about activity from a plant and extract down to phytochemical characterization on a timescale, which starts to make sense in modern drug discovery, alright and so now if you look at these phytochemicals, right, and you ask yourself, well sort of who is interested in that and why, right what are traditional pharmaceutical companies, right which I've been working with for 20, over 25 years now, right, typically uses these natural products where historically has used these natural products as starting points for new drugs. Right, so in other words, take this phytochemical and make chemicals synthetic modifications in order to achieve a potential drug. But in the context of natural products, unlike the pharmaceutical realm, there is often times a big knowledge gap between a disease and a plant in other words I have a plant that has activity, but how to connect those dots has been really laborious time consuming so it took us probably 50 years to go from salicylic acid and willow bark to synthesize acetylsalicylic acid or aspirin it just doesn't work in today's environment. So casting about trying to figure out how we expedite that process that's when about four years ago, I read a really fascinating article in the Los Angeles Times about my colleague and business partner, Dr. Rangan Sukumar, describing all the interesting things that he was doing in the area of Artificial Intelligence. And one of my favorite parts of this story is basically, unannounced, I arrived at his doorstep in Oak Ridge, he was working Oak Ridge National Labs at the time, and I introduced myself to him didn't know what was coming, didn't know who I was, right and I said, hey, you don't know me you don't know why I'm here, I said, but let me tell you what I want to do with your system, right and so that kicked off a very fruitful collaboration and friendship over the last four years using Artificial Intelligence and it's culminated most recently in our COVID-19 project collaborative research between the NCNPR and HP in this case. >> From what I can understand also as Chris has mentioned highly iterative, especially with these combination mixture of chemicals right, in plants that could affect a disease. We need to put in effort to figure out what are the active components in that, that affects it yeah, the combination and given the layman's way of understanding it you know and therefore iterative and highly data intensive. And I can see why Rangan can play a huge significant role here, Rangan, thank you for joining us So it's just a nice segue to bring you in here, you know, given your work with Ryan over so many years now, tell I think I'm also quite interested in knowing a little about how it developed the first time you met and the process and the things you all work together on that culminated into the progress at the advanced level today. Please tell us a little bit about that history and also the current work. Rangan. >> So, Ryan, like he mentioned, walked into my office about four years ago and he was like hey, I'm working on this Omega-3 fatty acid, what can your system tell me about this Omega-3 fatty acid and I didn't even know how to spell Omega-3 fatty acids that's the disconnect between the technologist and the pharmacologist, they have terms of their own right since then we've come a long way I think I understand his terminologies now and he understands that I throw words like knowledge graphs and page rank and then all kinds of weird stuff that he's probably never heard in his life before right, so it's been on my mind off to different domains and terminologies in trying to accept each other's expertise in trying to work together on a collaborative project. I think the core of what Ryan's work and collaboration has led me to understanding is what happens with the drug discovery process, right so when we think about the discovery itself, we're looking at companies that are trying to accelerate the process to market, right an average drug is taking 12 years to get to market the process that Chris just mentioned, Right and so companies are trying to adopt what's called the in silico simulation techniques and in silico modeling techniques into what was predominantly an in vitro, in silico, in vivo environment, right. And so the in silico techniques could include things like molecular docking, could include Artificial Intelligence, could include other data-driven discovery methods and so forth, and the essential component of all the things that you know the discovery workflows have is the ability to augment human experts to do the best by assisting them with what computers do really really well. So, in terms of what we've done as examples is Ryan walks in and he's asking me a bunch of questions and few that come to mind immediately, the first few are, hey, you are an Artificial Intelligence expert can you sift through a database of molecules the 15,000 compounds that he described to prioritize a few for next lab experiments? So that's question number one. And he's come back into my office and asked me about hey, there's 30 million publications in PubMag and I don't have the time to read everything can you create an Artificial Intelligence system that once I've picked these few molecules will tell me everything about the molecule or everything about the virus, the unknown virus that shows up, right. Just trying to understand what are some ways in which he can augment his expertise, right. And then the third question, I think he described better than I'm going to was how can technology connect these dots. And typically it's not that the answer to a drug discovery problem sits in one database, right he probably has to think about uniproduct protein he has to think about phytochemical, chemical or informatics properties, data and so forth. Then he talked about the phytochemical interaction that's probably in another database. So when he is trying to answer other question and specifically in the context of an unknown virus that showed up in late last year, the question was, hey, do we know what happened in this particular virus compared to all the previous viruses? Do we know of any substructure that was studied or a different disease that's part of this unknown virus and can I use that information to go mine these databases to find out if these interactions can actually be used as a repurpose saying, hook, say this drug does not interact with this subsequence of a known virus that also seems to be part of this new virus, right? So to be able to connect that dot I think the abstraction that we are learning from working with pharma companies is that this drug discovery process is complex, it's iterative, and it's a sequence of needle in the haystack search problems, right and so one day, Ryan would be like, hey, I need to match genome, I need to match protein sequences between two different viruses. Another day it would be like, you know, I need to sift through a database of potential compounds, identified side effects and whatnot other day it could be, hey, I need to design a new molecule that never existed in the world before I'll figure out how to synthesize it later on, but I need a completely new molecule because of patentability reasons, right so it goes through the entire spectrum. And I think where HP has differentiated multiple times even the recent weeks is that the technology infusion into drug discovery, leads to several aha! Moments. And, aha moments typically happened in the other few seconds, and not the hours, days, months that Ryan has to laboriously work through. And what we've learned is pharma researchers love their aha moments and it leads to a sound valid, well founded hypothesis. Isn't that true Ryan? >> Absolutely. Absolutely. >> Yeah, at some point I would like to have a look at your, peak the list of your aha moments, yeah perhaps there's something quite interesting in there for other industries too, but we'll do it at another time. Chris, you know, with your regular work with pharmaceutical companies especially the big pharmas, right, do you see botanicals, coming, being talked about more and more there? >> Yeah, we do, right. Looking at kind of biosimilars and drugs that are already really in existence is kind of an important point and Dr. Yates and Rangan, with your work with databases this is something important to bring up and much of the drug discovery in today's world, isn't from going out and finding a brand new molecule per se. It's really looking at all the different databases, right all the different compounds that already exist and sifting through those, right of course data is mind, and it is gold essentially, right so a lot of companies don't want to share their data. A lot of those botanicals data sets are actually open to the public to use in many cases and people are wanting to have more collaborative efforts around those databases so that's really interesting to kind of see that being picked up more and more. >> Mm, well and Ryan that's where NCNPR hosts much of those datasets, yeah right and it's interesting to me, right you know, you were describing the traditional way of drug discovery where you have a target and a compound, right that can affect that target, very very specific. But from a botanical point of view, you really say for example, I have an extract from a plant that has combination of chemicals and somehow you know, it affects this disease but then you have to reverse engineer what those chemicals are and what the active ones are. Is that very much the issue, the work that has to be put in for botanicals in this area? >> Yes Doctor Goh, you hit it exactly. >> Now I can understand why a highly iterative intensive and data intensive, and perhaps that's why Rangan, you're highly valuable here, right. So tell us about the challenge, right the many to many intersection to try and find what the targets are, right given these botanicals that seem to affect the disease here what methods do you use, right in AI, to help with this? >> Fantastic question, I'm going to go a little bit deeper and speak like Ryan in terminology, but here we go. So with going back to about starting of our conversation right, so let's say we have a database of molecules on one side, and then we've got the database of potential targets in a particular, could be a virus, could be bacteria, could be whatever, a disease target that you've identified, right >> Oh this process so, for example, on a virus, you can have a number of targets on the virus itself some have the spike protein, some have the other proteins on the surface so there are about three different targets and others on a virus itself, yeah so a lot of people focus on the spike protein, right but there are other targets too on that virus, correct? >> That is exactly right. So for example, so the work that we did with Ryan we realized that, you know, COVID-19 protein sequence has an overlap, a significant overlap with previous SARS-CoV-1 virus, not only that, but it overlap with MERS, that's overlapped with some bad coronavirus that was studied before and so forth, right so knowing that and it's actually broken down into multiple and Ryan I'm going to steal your words, non-structural proteins, envelope proteins, S proteins, there's a whole substructure that you can associate an amino acid sequence with, right so on the one hand, you have different targets and again, since we did the work it's 160 different targets even on the COVID-19 mark, right and so you find a match, that we say around 36, 37 million molecules that are potentially synthesizable and try to figure it out which one of those or which few of those is actually going to be mapping to which one of these targets and actually have a mechanism of action that Ryan's looking for, that'll inhibit the symptoms on a human body, right so that's the challenge there. And so I think the techniques that we can unrule go back to how much do we know about the target and how much do we know about the molecule, alright. And if you start off a problem with I don't know anything about the molecule and I don't know anything about the target, you go with the traditional approaches of docking and molecular dynamics simulations and whatnot, right. But then, you've done so much docking before on the same database for different targets, you'll learn some new things about the ligands, the molecules that Ryan's talking about that can predict potential targets. So can you use that information of previous protein interactions or previous binding to known existing targets with some of the structures and so forth to build a model that will capture that essence of what we have learnt from the docking before? And so that's the second level of how do we infuse Artificial Intelligence. The third level, is to say okay, I can do this for a database of molecules, but then what if the protein-protein interactions are all over the literature study for millions of other viruses? How do I connect the dots across different mechanisms of actions too? Right and so this is where the knowledge graph component that Ryan was talking about comes in. So we've put together a database of about 150 billion medical facts from literature that Ryan is able to connect the dots and say okay, I'm starting with this molecule, what interactions do I know about the molecule? Is there a pretty intruding interaction that affects the mechanism of pathway for the symptoms that a disease is causing? And then he can go and figure out which protein and protein in the virus could potentially be working with this drug so that inhibiting certain activities would stop that progression of the disease from happening, right so like I said, your method of options, the options you've got is going to be, how much do you know about the target? How much do you know the drug database that you have and how much information can you leverage from previous research as you go down this pipeline, right so in that sense, I think we mix and match different methods and we've actually found that, you know mixing and matching different methods produces better synergies for people like Ryan. So. >> Well, the synergies I think is really important concept, Rangan, in additivities, synergistic, however you want to catch that. Right. But it goes back to your initial question Dr. Goh, which is this idea of polypharmacology and historically what we've done with traditional medicines there's more than one active, more than one network that's impacted, okay. You remember how I sort of put you on both ends of the spectrum which is the traditional sort of approach where we really don't know much about target ligand interaction to the completely interpretal side of it, right where now we are all, we're focused on is, in a single molecule interacting with a target. And so where I'm going with this is interesting enough, pharma has sort of migrate, started to migrate back toward the middle and what I mean by that, right, is we had these in a concept of polypharmacology, we had this idea, a regulatory pathway of so-called, fixed drug combinations. Okay, so now you start to see over the last 20 years pharmaceutical companies taking known, approved drugs and putting them in different combinations to impact different diseases. Okay. And so I think there's a really unique opportunity here for Artificial Intelligence or as Rangan has taught me, Augmented Intelligence, right to give you insight into how to combine those approved drugs to come up with unique indications. So is that patentability right, getting back to right how is it that it becomes commercially viable for entities like pharmaceutical companies but I think at the end of the day what's most interesting to me is sort of that, almost movement back toward that complex mixture of fixed drug combination as opposed to single drug entity, single target approach. I think that opens up some really neat avenues for us. As far as the expansion, the applicability of Artificial Intelligence is I'd like to talk to, briefly about one other aspect, right so what Rang and I have talked about is how do we take this concept of an active phytochemical and work backwards. In other words, let's say you identify a phytochemical from an in silico screening process, right, which was done for COVID-19 one of the first publications out of a group, Dr. Jeremy Smith's group at Oak Ridge National Lab, right, identified a natural product as one of the interesting actives, right and so it raises the question to our botanical guy, says, okay, where in nature do we find that phytochemical? What plants do I go after to try and source botanical drugs to achieve that particular end point right? And so, what Rangan's system allows us to do is to say, okay, let's take this phytochemical in this case, a phytochemical flavanone called eriodictyol and say, where else in nature is this found, right that's a trivial question for an Artificial Intelligence system. But for a guy like me left to my own devices without AI, I spend weeks combing the literature. >> Wow. So, this is brilliant I've learned something here today, right, If you find a chemical that actually, you know, affects and addresses a disease, right you can actually try and go the reverse way to figure out what botanicals can give you those chemicals as opposed to trying to synthesize them. >> Well, there's that and there's the other, I'm going to steal Rangan's thunder here, right he always teach me, Ryan, don't forget everything we talk about has properties, plants have properties, chemicals have properties, et cetera it's really understanding those properties and using those properties to make those connections, those edges, those sort of interfaces, right. And so, yes, we can take something like an eriodictyol right, that example I gave before and say, okay, now, based upon the properties of eriodictyol, tell me other phytochemicals, other flavonoid in this case, such as that phytochemical class of eriodictyols part right, now tell me how, what other phytochemicals match that profile, have the same properties. It might be more economically viable, right in other words, this particular phytochemical is found in a unique Himalayan plant that I've never been able to source, but can we find something similar or same thing growing in, you know a bush found all throughout the Southeast for example, like. >> Wow. So, Chris, on the pharmaceutical companies, right are they looking at this approach of getting, building drugs yeah, developing drugs? >> Yeah, absolutely Dr. Goh, really what Dr. Yates is talking about, right it doesn't help us if we find a plant and that plant lives on one mountain only on the North side in the Himalayas, we're never going to be able to create enough of a drug to manufacture and to provide to the masses, right assuming that the disease is widespread or affects a large enough portion of the population, right so understanding, you know, not only where is that botanical or that compound but understanding the chemical nature of the chemical interaction and the physics of it as well where which aspect affects the binding site, which aspect of the compound actually does the work, if you will and then being able to make that at scale, right. If you go to these pharmaceutical companies today, many of them look like breweries to be honest with you, it's large scale, it's large back everybody's clean room and it's, they're making the microbes do the work for them or they have these, you know, unique processes, right. So. >> So they're not brewing beer okay, but drugs instead. (Christopher laughs) >> Not quite, although there are pharmaceutical companies out there that have had a foray into the brewery business and vice versa, so. >> We should, we should visit one of those, yeah (chuckles) Right, so what's next, right? So you've described to us the process and how you develop your relationship with Dr. Yates Ryan over the years right, five years, was it? And culminating in today's, the many to many fast screening methods, yeah what would you think would be the next exciting things you would do other than letting me peek at your aha moments, right what would you say are the next exciting steps you're hoping to take? >> Thinking long term, again this is where Ryan and I are working on this long-term project about, we don't know enough about botanicals as much as we know about the synthetic molecules, right and so this is a story that's inspired from Simon Sinek's "Infinite Game" book, trying to figure it out if human population has to survive for a long time which we've done so far with natural products we are going to need natural products, right. So what can we do to help organizations like NCNPR to stage genomes of natural products to stage and understand the evolution as we go to understand the evolution to map the drugs and so forth. So the vision is huge, right so it's not something that we want to do on a one off project and go away but in the process, just like you are learning today, Dr. Goh I'm going to be learning quite a bit, having fun with life. So, Ryan what do you think? >> Ryan, we're learning from you. >> So my paternal grandfather lived to be 104 years of age. I've got a few years to get there, but back to "The Infinite Game" concept that Rang had mentioned he and I discussed that quite frequently, I'd like to throw out a vision for you that's well beyond that sort of time horizon that we have as humans, right and that's this right, is our current strategy and it's understandable is really treatment centric. In other words, we have a disease we develop a treatment for that disease. But we all recognize, whether you're a healthcare practitioner, whether you're a scientist, whether you're a business person, right or whatever occupation you realize that prevention, right the old ounce, prevention worth a pound of cure, right is how can we use something like Artificial Intelligence to develop preventive sorts of strategies that we are able to predict with time, right that's why we don't have preventive treatment approach right, we can't do a traditional clinical trial and say, did we prevent type two diabetes in an 18 year old? Well, we can't do that on a timescale that is reasonable, okay. And then the other part of that is why focus on botanicals? Is because, for the most part and there are exceptions I want to be very clear, I don't want to paint the picture that botanicals are all safe, you should just take botanicals dietary supplements and you'll be safe, right there are exceptions, but for the most part botanicals, natural products are in fact safe and have undergone testing, human testing for thousands of years, right. So how do we connect those dots? A preventive strategy with existing extent botanicals to really develop a healthcare system that becomes preventive centric as opposed to treatment centric. If I could wave a magic wand, that's the vision that I would figure out how we could achieve, right and I do think with guys like Rangan and Chris and folks like yourself, Eng Lim, that that's possible. Maybe it's in my lifetime I got 50 years to go to get to my grandfather's age, but you never know, right? >> You bring really, up two really good points there Ryan, it's really a systems approach, right understanding that things aren't just linear, right? And as you go through it, there's no impact to anything else, right taking that systems approach to understand every aspect of how things are being impacted. And then number two was really kind of the downstream, really we've been discussing the drug discovery process a lot and kind of the kind of preclinical in vitro studies and in vivo models, but once you get to the clinical trial there are many drugs that just fail, just fail miserably and the botanicals, right known to be safe, right, in many instances you can have a much higher success rate and that would be really interesting to see, you know, more of at least growing in the market. >> Well, these are very visionary statements from each of you, especially Dr. Yates, right, prevention better than cure, right, being proactive better than being reactive. Reactive is important, but we also need to focus on being proactive. Yes. Well, thank you very much, right this has been a brilliant panel with brilliant panelists, Dr. Ryan Yates, Dr. Rangan Sukumar and Chris Davidson. Thank you very much for joining us on this panel and highly illuminating conversation. Yeah. All for the future of drug discovery, that includes botanicals. Thank you very much. >> Thank you. >> Thank you.

>> Narrator: Live from Las Vegas it's theCUBE. Covering IBM Think 2018. Brought to you by IBM. >> Hello everyone, welcome to theCUBE here at IBM Think 2018. I'm John Furrier. We're on the ground with theCUBE. In theCUBE studio today we have a live audience on break but I had a chance to meet with the Chief Digital Officer of Hybrid Cloud, Janine Snead, who's just appointed. She's here in set on theCUBE. Great to see you at IBM Think. >> Hi, great to see you. Thanks for having me. >> Thanks for coming on. I'm super excited. When I interviewed Bob Lord last year, Chief Digital Officer, you know we love digital on theCUBE so we get really excited. We're like great, that's awesome. Now IBM's got more Chief Digital Officers being appointed >> Janine: That's right. >> You're the first Chief Digital Officer in a business unit. That's awesome, congratulations. >> Thank you. Yeah we're excited about it. We know and we believe that the future is really in the hands of the web. And we know that customers are engaging with us differently. They want much more of a self service. They want to experience the products without always I'll say a person interacting with them. And we know that from a product perspective there's things that we need to do to make our offerings much more digitally consumable. So we're taking this very seriously. And we put an organization in place Digital within Hybrid Cloud, that truly focuses on the time from a customer goes out and actually does a search, all the way through the buyer journey to the time they get to the product. >> John: You know I've been a student of IBM I actually worked at IBM as a co-op back in my early days. IBM has always been on the leading edge of marketing. And you guys are looking at socially you looked at social in an early way, digital in an early way, but now with the cloud you can actually engage customers digitally. So I've got to ask you, you know, how are you going to do that? >> Janine: Yeah >> John: Because you've got to remember websites are now the fabric of all this that's 30 year old tech stack. You've got cloud now, you've got APIs with the synchronous software packages. You've got blockchain. All these new things. So what's the vision as you guys go out and start putting stakes in the ground for a digital strategy. How are you guys doing it, can you share the vision? >> Yeah, I think it starts with using our own technology. So within the Hybrid Cloud organization, we have a lot of software and we're putting that software out on the cloud. We want customers to engage with us digitally through a technical experience. So we're taking our products, putting product demos, we're putting POTs, we're putting even proof of concept secure in the cloud, guided demos where they can come and experience these offerings without ever engaging with us. Now of course once they're ready they can engage with us but this is truly about a low touch, self service way for customers to engage with our products. >> Now a lot of people, and we talk about this all the time, but the general sentiment online now is you have the kind of crazies out there you've seen that on Reddit, fake news, weaponizing content. Then you have the other side of the spectrum where people are like, I don't want to be sold to. I'm discovering, I want to learn. >> Janine: Yes. >> John: I'm in communities. I know you guys address that. I want you to just clarify, because there's a model now where people just want to be ingratiated in. You know, kick the tires. Which by the way, kicking tires right now is much different than it was years ago because you have APIs. You have SARS source code. You have credits for cloud. >> Janine: That's right. >> What is the digital motion there? I mean obviously it's a light touch. >> Yeah >> But is it still an IBM.com? >> It is. So we're still on IBM.com properties. And we're nurturing with the ecosystem and the communities to also go where they are, but bring them back to the IBM.com properties and engage with them when they're ready. You know, we've done the research. We know that 70% of b2b buyers learn about your products and your services without ever talking to you. So we want to be where those users are and eventually that will be back on our property but we also want to find them where they are. >> You know, one of the things we were talking about before you came on camera here, We've been doing theCUBE for seven years or so plus six shows now to one show. But the thought leadership on theCUBE has always been powerful. And that's seemed to be a great way to get into communities. And IBM's got a lot of thought leaders. So I'm sure you have a plan for thought leaders. You have IBM Fellows. You've got R&D. You've got a lot of content opportunities. >> We do. We've got a lot of partners. So here at this conference we've been talking to a lot of our partners who want to be a part of this experience. We've got great solutions and all of our solutions a lot of them are delivered with partners. And so it's working the community. It's working the ecosystem. And it's doing this together with partners to allow them to contribute and allow customers to come and consume solutions. In much of a use case way, of course you can have product by product by products, but how do you essentially deliver solutions based on use cases. >> So I'll ask you a personal question. How did you get here? Was it like hey, I want to do the digital job, was it an itch that you were scratching, did Bob Lord lure you into the job? (Janine laughs) Did he recruit you? I mean -- >> No, it's -- >> How did you get it? >> It's a great question >> Because this is a great opportunity. >> It is. I'm a product person by training. And I spent the last 18 months in sales. And I enjoyed every minute of that and listening and understanding how our sellers want to consume. Short, snackable type of learning and training and watching what was going on with the digital ecosystem I thought it was a great way to really mix my skills that I have within product with what I just learned from my sales role. And I did nine months in marketing. So I felt like it was kind of a mixture. And we have a huge opportunity here. So the opportunity presented itself. >> Sales always has a my favorite sales expression is people love to buy from people that they like. How are you going to make IBM likable digitally? Is there a strategy there? >> Oh, it's simple. (John laughs) It is so dead simple. It's about the user experience. When users come, you have to give them the best experience possible because you never get a second chance to make a good first impression. So I want to basically set the bar. And we're an MVP right now with a lot of the stuff that we're doing out. >> You mean software and tools and stuff? >> Yeah, no, well, our experience right now so when you come and you experience our tools I'm sorry, our demos and our proof of technologies and our tutorials out on our site it's MVP. We're 45 days old. But it's about the user experience. And so we've been serving users here that are coming to try our stuff. >> So the Digital Technical Engagement, that's the DTE? >> Janine: DTE, yep. >> That's the one that's 45 days? >> That's the one that's 45 days old. >> The IBM site's not 45 days old. >> Yeah, yeah. >> But this new program. So take a minute to explain what the DTE, the Digital Technical Engagement program is. What was the guiding principles behind it >> Yeah >> What's some of the deign objectives is there any new cool tech under the covers? Share a little bit of color on that. >> Sure, sure. Happy to. So back in the fourth quarter of last year we took a look and we said, how are customers consuming? How are we engaging? How are we showing up? And what do we need to do to shift to become more agile and lighten the way that we showed up. And so we really gathered a few smart creatives from the CIO's office, from IBM design, from product and from marketing and we said guys, we're going to run an experiment. We want to set up a site off of IBM.com a page off of IBM.com and it's very simple. Keep it so clean. Keep the user experience clean. Take something like IBM Cloud Private. Give me three product demos. Give me one guided demo where in 10 minutes a client can get through IBM Cloud Private without getting stuck and then give them a way to try it for two weeks. Just experiment. Well, in 90 days we've had 10,500 users try that guided demo and our NPS is 56. >> What does NPS mean? - Net Promoter Score >> That's what I figured, okay. >> So it's about experimentation. And so in this world that we're going into we want to experiment. And so from there, what happened, that proved to be successful. We now have an organization of about 60 people within digital technical engagement deep product experts, but we also have a platform team to drive that experience. >> So there's some real value there. I mean, a lot of people look at website and digital technologies as ad tech, you know, and there's a lot of bad press out there now with Facebook where a lot of people are looking at Facebook as content that got weaponized for fake news and the ad tech has a bad track record of fill out a form, they're going to sell me something. How are you going to change that perception? >> That's a great question. So a lot of the folks that we're working with right now say you have to capture user information capture user information. And for me, I don't want to be bothered. So I'm kind of looking at this maybe a little bit too selfishly saying I want to demo without giving you my information. We have our product demos and our guided demos, we don't collect any information from the user. When you are going to reserve our software for two weeks, up to a month, we do collect some information about you. >> John: You got to. >> We have to. >> At some point. >> So we're keeping it very low touch because we know that's how users want to engage. >> You don't want to gate the hell out of it. >> No, we don't want to gate the hell out of it. We want to keep it just, let them explore without being all over them. Right? >> Talk about the new IBM. You know, one of the things that's transforming right now that I'm impressed with is IBM's constantly reinventing themself. I was impressed with Ginni's keynote. The way she talks about data in the middle, blockchain on one side and AI on the other. I call it the innovation sandwich. >> Janine: Yeah >> How are you applying that vision to digital? I mean not yet obviously, you're only at the beginning. >> Right But that vision is pretty solid. And she brought up Moore's Law and Metcalfe's Law. >> That's right. >> Moore's Law is making things faster, smaller, cheaper. >> Right >> Component wise and speed. >> Yes >> Metcalfe's Law is about network effect and the future of digital is either going to be token economics or blockchain with programatic tooling that gives users great experiences. So how do you tie that together? Maybe it's too early to ask, but-- >> No, no. It's simple. I'm a consumer of this stuff. I'm using the cloud. I'm using the IBM Design Thinking because I brought in three designers from Phil Gilbert's group. Right? I'm embedded in the digital organization basically, regardless of where I sit. So we are adopting best practices that come from IBM's big chief digital office. >> So you get to use your own tools, that's one of the things she said. >> Yeah and we'll embed, we'll get there. Right? >> Yeah >> Well actually, we already are doing, we embedded chat. So we've got Watson Chat running on our SPSS statistics page So it's about the cloud, it's about user experience. It's about applying digital practices from Bob Lord's organization and then it's about Watson. >> I was having a great Twitter thread with a bunch of people that were on Twitter just ranting on the weekend a couple weekends ago about digital transformation. Tom Peters actually jumped in, the famous Tom Peters who wrote the books there, a management consultant, about digital transformation. I love digital transformation, it's overused, but it's legit. People are transforming. So the question was, how do you do it successfully? And all the canned answers came out. Well, you need commitment from the top. You've got to have this and that. And I said look, bottom line, if people don't have the expertise, and if they don't know what they're doing, they can't transform. So it begs the question for skills gap. A lot of people are learning, so there's a learning environment. It's not just sales. Proficiency, getting the product buying. There's a community thirst for learning. How is that incorporated in, if any? >> I think I have a little bit of a different hurdle. The people that we're working with are learning. They're out in the communities they're engaging. I think one of the things that we have to continue to do is continue to show the value of digital transformation. Remember, IBM is a big company. I'm not a ten person startup. Right? We're a bigger organization so what we have to do is show why digital is important back in with our product teams. I think for the most part our marketing teams get it. Because you have to make trade offs. Am I going to invest in this feature in the product or am I going to put in something like eCommerce so you can subscribe and buy. >> Priorities. But you're a product person, so it's all about the trade offs. >> Yeah, it's all about the trade offs, right? So the skills are part of it but some of it is just education on why this is so critical. And then the last thing is passion. You have to bring the skills, the education and then that passionate team that really believes that they can get this done. >> Okay so given that, let's go back to some of the comments I made about the people who we were talking about on Twitter >> Janine: Sure >> Commitment from the top. IBM commitment at the top is there? What are they saying, what's the marching orders? >> The marching orders is we got to go and we're not moving fast enough. Speed, speed, speed, right? So we got to move fast. >> So in an interview with Bob Lord, one of the things we talked about was interesting. He's like I like to just get stuff done. I think he might have used another word. Maybe it was off camera he said that. IBM's got a lot of process. How do you take the old IBM process and make it work for you rather than having digital work for the process? >> Yeah >> It's a lot of internal things but no need to give away too much but it's a management challenge. How do you cut through it? >> I think from a process perspective, these are conversations and you have to explain why. If you could go in and explain why you need to do something differently, then people will listen. I'd like to give an example, okay? I had 26 days to get five products out the door. I formed a team January 2nd. By January 26th, I had to be live. Now I worked with my marketing team and I said I will get into your buyer journey, but I have to launch my Digital Technical Engagement site and my products. They understood. So I went live. Now, will I back back into the process? Sure I will. >> John: But you had good alignment. >> But yeah, we have to move fast, right? So it's explaining why and having mature conversations and then people that really believe in digital they'll support you. >> Great conversation. I'm looking forward to chatting more with you. We're at theCUBE. But I want to ask you one final question before we break. What's your objective? What's the roadmap for you, what's your top priorities? Are you hiring? Who're you looking for? What kind of product priorities, what's the sales priorities? What's your to-do list? >> I think let's start with the customer. So the customer priority is to deliver the best experience possible as they engage with IBM digitally. And that's all about the user experience. From a talent perspective, it's all about diversity, inclusion, and people that come with different skills from technology, to growth hacking, to marketing, and to engineering. And some people that think differently. We want people that, no idea is a bad idea, just come and bring great ideas. >> Well, diversity and inclusion, first of all, half of the users are women. And you also have to have an understanding of the use cases. >> Yeah >> It's not just men using software. >> Yeah, that's right. >> It's a huge deal. >> That's right, that's right. >> Alright well, Janine, great to have you on theCUBE. Thanks for spending the time. >> Thank you. >> Congratulations on the new role. Janine Sneed, Chief Digital Officer from IBM Hybrid Cloud. First IBM Chief Digital Officer in a business unit. I also today have Bob Lord and a lot of other folks doing digital but great to see the digital momentum. >> Thank you. >> It's not just a selling apparatus. It's all about value for users. It's theCUBE bringing you the value here at IBM Think 2018. I'm John Furrier, back with more after this short break. (upbeat music)