[00:00.000 --> 00:05.620]  So, we were asked by the XR Village to come and just give a little talk about the work
[00:05.620 --> 00:10.400]  that we've been doing at the Idaho National Lab using some XR equipment.
[00:12.200 --> 00:19.200]  So, behind the scenes of our daily lives, there's critical infrastructure that's supplying us.
[00:21.360 --> 00:25.520]  You know, all of the necessary services, you know, water treatment,
[00:25.520 --> 00:31.240]  um, our electricity, and all of that infrastructure needs to be secured.
[00:31.240 --> 00:39.380]  But as, you know, working in the security kind of aspect, we know that these systems
[00:40.280 --> 00:46.740]  definitely aren't as secure as we'd like them to be. And so,
[00:46.740 --> 00:53.620]  um, part of the work that we've been doing at the National Lab in partnership with the
[00:53.620 --> 01:04.100]  Seller Group is to work on securing those systems and helping, um, you know, smaller
[01:04.100 --> 01:08.600]  cities to know that their systems may not be secure, that there are vulnerabilities.
[01:08.780 --> 01:15.040]  And we've been using XR as a component of that, um, of that outreach.
[01:15.580 --> 01:21.540]  So, my name is Colton Heaps, and I've been working with the Idaho National Laboratory
[01:21.540 --> 01:29.020]  for about two years. Um, it's been really exciting to be able to work with, in a laboratory where,
[01:29.020 --> 01:35.480]  um, they have such unique infrastructure. So, for those of you who don't know, the Idaho National
[01:35.480 --> 01:43.800]  Lab is a research laboratory that's focused on nuclear research. And so, um, we have, you know,
[01:43.800 --> 01:52.680]  couple of different reactors out on our, our campus. And with that, you know, um, micro grids
[01:52.680 --> 02:00.900]  and a lot of different infrastructure that enables us some unique cyber security research. And so,
[02:00.900 --> 02:11.840]  um, I will kind of start out by describing the group that I work with, with digital engineering
[02:11.840 --> 02:20.660]  and some terms that I'll be sharing and introduce the, the seller group and then, um, get into how
[02:20.660 --> 02:25.960]  we've been using mixed reality and, uh, virtual reality for that, that work.
[02:27.920 --> 02:34.560]  So, what is digital engineering? Digital engineering focuses on supplying data to
[02:34.560 --> 02:40.780]  researchers regardless of the platform that they're performing research on. So, in, you know,
[02:40.780 --> 02:47.640]  times past, we had, um, researchers passing around documents. Uh, they'd have sacred word
[02:47.640 --> 02:52.640]  documents that had all the information for the projects. Um, that is not a good way to do
[02:52.640 --> 02:58.160]  engineering. So, we're trying to centralize all of that data no matter where it comes from and
[02:58.160 --> 03:07.220]  enable, um, the different platforms to be able to reach out and use that data. So, um, digital
[03:07.220 --> 03:12.900]  engineering helps to provide semi-autonomous design, autonomous operations, and real time
[03:12.900 --> 03:20.160]  anomaly detection. It integrates the threads of data, visualizations, AI and ML and physics models
[03:20.160 --> 03:29.460]  into a cohesive digital twin. And so, a digital twin is, it's a buzz word. Um, so, we're trying,
[03:29.460 --> 03:34.640]  it gets thrown around a lot in industry, but we're trying to define that at the national lab.
[03:34.640 --> 03:42.300]  And so, I like to compare it to, to the iPhone. So, we all know, you know, the impact that the
[03:42.300 --> 03:49.940]  iPhone had on our world. And, um, because of the iPhone, you know, led to other smartphones,
[03:49.940 --> 03:57.520]  rising popularity, and that truly changed our lives. But the iPhone itself is made up of a
[03:57.520 --> 04:02.580]  bunch of smaller technologies that already existed. And those technologies themselves
[04:02.580 --> 04:07.100]  weren't necessarily revolutionary, but the combination of all of those made something
[04:07.100 --> 04:19.380]  special. And so, that is, um, how I see digital twins. And, um, it's the combination of all of
[04:19.380 --> 04:23.980]  these different technologies that have existed in the past, but the combination of all of those
[04:23.980 --> 04:32.060]  together makes it something special. So, what is a digital twin? Like I mentioned, the digital twin
[04:32.060 --> 04:38.260]  is a merging of all these different technologies. The connection of integrated data, sensors and
[04:38.260 --> 04:42.860]  instrumentation from physical assets. So, taking that realtime data from the systems and feeding
[04:42.860 --> 04:53.780]  it back into visualizations and AI ML algorithms. The AI and an online monitoring and advanced
[04:53.780 --> 04:59.600]  visualization with mixed reality and virtual reality. So, that's kind of the INL's definition
[04:59.600 --> 05:06.380]  of the digital twin. And a digital twin mirrors the physical model while using realtime
[05:06.380 --> 05:16.440]  bidirectional communication to perform, you know, this magic. Enabling the user to take in data
[05:16.440 --> 05:26.200]  more efficiently. Giving the operator more data in a way that they can understand. And so, put
[05:26.200 --> 05:30.940]  that into context of the work that we do at the lab. Like I said, nuclear research and working
[05:30.940 --> 05:42.040]  with these nuclear systems. We need to be able to have safe, small modular reactors in the future.
[05:42.220 --> 05:51.900]  And they need to be able to have autonomous corrections. So, broadcasting into the future
[05:51.900 --> 05:56.860]  to see if these things are safe or not. And then if they're, you know, going into a hazardous
[05:56.860 --> 06:05.780]  direction, then they need to be able to fix themselves. But we've been using it with the
[06:05.780 --> 06:12.740]  cyber security group at the INL, specifically the CELR group. So, CELR stands for control
[06:12.740 --> 06:21.840]  environment laboratory resource. And so, CELR is sponsored by DHS's cyber security and
[06:21.840 --> 06:28.980]  infrastructure security agency or CISA. CELR is a lab scale environment with sector specific
[06:28.980 --> 06:36.680]  platforms with operational physical components as well as operational IT and OT environments with
[06:36.680 --> 06:44.040]  real controllers and human machine interfaces to operate the physical components. And so,
[06:44.040 --> 06:50.900]  there are about six of these training platforms that CELR has provided to the public. And each
[06:50.900 --> 06:58.980]  of these platforms have unique HMIs, PLCs and protocols that are used. And so, it takes the
[06:58.980 --> 07:07.400]  breadth of, you know, manufacturer's hardware and protocols that are used in industry and
[07:07.400 --> 07:15.180]  displays them here as a resource publicly available for, you know, international use so that
[07:15.720 --> 07:23.640]  anybody can gain more experience in securing this critical infrastructure. So, the environment
[07:23.640 --> 07:29.760]  is used to train cyber incident responders and expose them that actual networks and malicious
[07:30.600 --> 07:35.740]  activities are similar to what they would see in the real world. Support tool evaluation to
[07:35.740 --> 07:42.580]  determine effectiveness in operations and research mitigation measures that may counter those
[07:42.580 --> 07:50.600]  effects. CELR's capabilities have matured to include six sector specific platforms with six
[07:50.600 --> 07:59.320]  different controllers, HMIs and network protocols. This allows for diverse options of to fully
[07:59.320 --> 08:07.620]  represent a broader range of the nation's infrastructure. And it's definitely a valuable
[08:07.620 --> 08:19.740]  resource that is being provided and helps to supply this resource to smaller cities that may
[08:19.740 --> 08:29.200]  not have the funds to put towards cyber security and securing their infrastructure so they can
[08:29.200 --> 08:54.020]  take advantage of these resources. Okay. So, in the CELR group, while building these systems,
[08:54.020 --> 09:02.620]  they started to reach out to digital engineering just as a way to visualize their, you know,
[09:02.620 --> 09:08.600]  their plans in their new work space. And so, they were planning to build, they had one existing
[09:08.600 --> 09:13.820]  skid, I believe, and they were planning to build more in the space. And so, they wanted to use
[09:13.820 --> 09:20.040]  some of our XR capabilities that we've been using across the lab to visualize these components in
[09:20.040 --> 09:33.140]  their facility and maximize the efficiency of the space. And so, it's maybe not a very exciting way
[09:33.140 --> 09:38.800]  of using mixed reality as it's, you know, seems like everybody's using that now, but it's very
[09:38.800 --> 09:48.540]  valuable and saves so much time and money. And so, we were able to use some virtual reality goggles
[09:48.540 --> 09:57.600]  and take the existing CAD models as geometries and import them as meshes into our visualization
[09:57.600 --> 10:06.520]  software and mainly we use Unity for this. Because of how easy they've made it to work with a
[10:06.520 --> 10:16.540]  variety of hardware. And so, with those CAD models and the BIM model from their facility, so BIM is
[10:16.540 --> 10:25.900]  Building Information Management Model. And they took both of those models and put them into one
[10:25.900 --> 10:32.900]  so they could move each of their training testbeds around the facility, maximize the use of the space
[10:34.320 --> 10:41.740]  and also in the design of the physical testbeds, they were able to see them to scale in front of
[10:41.740 --> 10:47.260]  them, interact with the different components, make sure everything was, you know, would work just
[10:47.260 --> 10:58.300]  how they expected. And so, as that partnership grew with Cellar, we started working a little
[10:58.300 --> 11:08.720]  bit more in public engagement. Which kind of led into us realizing the, how valuable extended
[11:08.720 --> 11:21.350]  reality headsets were in this work. So, with the new testbed designs, they had, you know, an
[11:21.350 --> 11:30.950]  interface similar to this where they were able to have a portion of the HMI in the virtual world
[11:32.010 --> 11:38.330]  and they could click buttons to toggle on different effects, just run through in software the
[11:38.330 --> 11:57.600]  iterations of how things would look and ultimately save time. And so, all of these testbeds, they
[11:57.600 --> 12:03.540]  represent physical critical infrastructure. So, they have the same OT, IT components that are
[12:03.540 --> 12:12.100]  used in, you know, saying like this is just a laboratory space. And so, to help to increase
[12:12.100 --> 12:16.620]  engagement, they have different effects, like that smoke that you can see in the bottom left
[12:16.620 --> 12:28.740]  corner. So, when the system, you know, maybe the HMI is vulnerable to a certain DLL injection, then
[12:28.740 --> 12:36.800]  that can cause some actual physical damage to the system. Maybe, you know, turning off some of the
[12:36.800 --> 12:46.220]  fans in a lab space or reversing fans in a fume hood causing gas to go into the lab space.
[12:47.300 --> 12:59.650]  So, working with this critical infrastructure has physical effects. So, you know, it's not
[12:59.650 --> 13:06.110]  only some database or something that goes down, but it can actually cause harm to a system and
[13:06.110 --> 13:16.860]  people. So, then we worked in public engagement during the first sort of half a year that we were
[13:16.860 --> 13:22.700]  working with Cellar. And as you can tell by the ugly carpet on the ground and the pictures on
[13:22.700 --> 13:29.920]  the slide, we're here at DEF CON. So, we had the opportunity to come to DEF CON as well as an
[13:29.920 --> 13:40.520]  array of different conferences around the nation. So, on the left is a picture of a small test bed
[13:40.520 --> 13:49.940]  that they developed for use in conferences. Because the full test beds are like 6 feet tall.
[13:50.460 --> 13:56.020]  And it would just be a pain to pack those around to conferences. So, they developed a smaller
[13:56.020 --> 14:03.880]  version which still has real IT components. They can, you know, share that with the public.
[14:04.500 --> 14:13.280]  But then in mixed reality and on the let's see, on the left,
[14:15.420 --> 14:22.200]  that man is wearing a Microsoft HoloLens. So, that's a mixed reality system.
[14:22.740 --> 14:29.240]  And what he's seeing is being shown in the middle there. So, because we aren't constrained to any
[14:29.240 --> 14:36.200]  sort of space in virtual or mixed reality, we can make it as representative as we want to.
[14:36.520 --> 14:42.560]  And so, there's a demo that they brought.
[14:44.780 --> 14:49.000]  Hello, hello. There's a small demo that they had brought.
[14:50.880 --> 14:57.540]  Emulates an electrical substation. And so,
[14:57.540 --> 15:05.640]  in the visualization, we modeled out, you know, a representative substation. And then we were also
[15:05.640 --> 15:12.820]  able to expand it out to show more of a suburb or community. And then in the attack, we can show
[15:12.820 --> 15:26.900]  how it affects the entire community losing power. So, at the bottom left, you have the physical
[15:26.900 --> 15:32.640]  skid in the environment, the lab space that they're housed in. So, they just have some computers
[15:32.640 --> 15:42.300]  with webcams that are monitoring these systems. And then anybody can log in and see the attacks
[15:42.300 --> 15:48.620]  and vulnerabilities that are on these systems and then learn how to secure against those attacks.
[15:50.000 --> 15:57.820]  And then the webcam shows a kind of difficult to see view of any effects that might happen if that
[15:57.820 --> 16:10.300]  critical infrastructure is attacked. And so, in the virtual space, again, we modeled out
[16:10.300 --> 16:17.260]  their systems to be able to show others resources that are available. And then we've also tried to
[16:17.260 --> 16:24.300]  make a more representative view of each of these systems. And so, the idea is that using
[16:24.300 --> 16:32.000]  digital engineering and digital twins, we're going to mix together these physical assets
[16:32.540 --> 16:41.380]  with the visualizations. And so, as somebody is working, you know, going through the training
[16:41.380 --> 16:49.340]  online, then that data is being relayed to a visualization that they can use with their team.
[16:49.340 --> 16:58.260]  You know, maybe it's a school or, you know, the workers, the cyber team of that city.
[16:58.320 --> 17:03.620]  And they can have a more engaging training as they go through it.
[17:04.540 --> 17:15.280]  And as well as just relaying state of the system, we merge all of that to a central data
[17:15.280 --> 17:21.740]  warehouse that we can then distribute data between the different systems, whether they need to do,
[17:21.740 --> 17:38.670]  you know, analytics on the data afterwards. Okay. So, some of the other projects that we have,
[17:40.650 --> 17:49.290]  I apologize. So, just to speak of some of the successes that we've had with this system. So,
[17:49.290 --> 17:56.610]  it was developed to be remote during COVID, because COVID sucks. And we wanted to still
[17:56.610 --> 18:04.790]  be able to help people. And so, they were able to see the visualizations of what would happen,
[18:04.790 --> 18:09.890]  be familiar with those things, have an engaging training. But then,
[18:11.270 --> 18:17.570]  Cellar was still able to provide that training on real hardware, not emulated hardware,
[18:18.810 --> 18:27.210]  in a remote setting. And so, one of the groups was a local municipality,
[18:27.210 --> 18:32.330]  and they were able to remote into the environment and train using this
[18:35.110 --> 18:41.950]  using their lab space. And while they were going through the trainings, you know,
[18:41.950 --> 18:47.310]  learning how to secure these systems that they needed to work on in their own municipality,
[18:48.410 --> 18:55.630]  their facility was physically hit. And so, since they were remotely training,
[18:55.630 --> 19:01.730]  you know, not having to travel out to Idaho, they were able to respond to that incident
[19:02.690 --> 19:17.730]  and use the training immediately. So, that's a big win. And so, the idea, again,
[19:17.730 --> 19:23.990]  is to be able to reach out, help as many people who maybe don't have the funding towards these
[19:23.990 --> 19:33.310]  trainings, to put towards cybersecurity research. And so, using mixed reality,
[19:33.630 --> 19:40.670]  we don't have to refill the tanks for these trainings. We don't have to physically do any
[19:40.670 --> 19:45.390]  maintenance. We can just run through training after training after training without worrying
[19:45.390 --> 19:56.090]  if it's going to break. And so, that saves us money as well. Lowers the cost of the resource.
[19:56.150 --> 20:02.250]  And then enables us to just send out these VR goggles or mixed reality goggles to
[20:03.630 --> 20:10.010]  whoever is signed up for the service. And they can still have that engagement.
[20:11.370 --> 20:20.830]  Okay. So, what's next? So, at the right image, might be a little hard to distinguish, but that's
[20:21.390 --> 20:27.970]  a router with some signals coming off of it. And I'm using some quotes right now.
[20:28.270 --> 20:34.490]  Because it's still theoretical. But the research is being done to leverage extended reality
[20:34.490 --> 20:40.410]  capabilities to visualize wireless radio frequency signals. And the goal is to be able to
[20:40.410 --> 20:47.890]  see the radio frequency signals in an environment, identify that it might be abnormal, and then
[20:50.630 --> 20:57.090]  using the geolocation support of these systems, be able to pinpoint the source of the signals.
[21:00.670 --> 21:09.450]  And so, second research effort focuses on expanding the services to train remotely with
[21:09.450 --> 21:14.710]  realtime visualization. Enable cyber incident responders to actually conduct their network
[21:14.710 --> 21:19.470]  analysis or hunt for malicious activities on their laptops while then being able to see the
[21:19.470 --> 21:28.130]  representations of the infrastructure behind them as they work. So, it really has been
[21:31.110 --> 21:38.990]  although these digital twins are still in early stages, and we still have a lot that we can do to
[21:38.990 --> 21:51.070]  improve the use of extended reality headsets in this work, it's already helped us enormously.
[21:54.550 --> 22:05.110]  And so, just to I guess just speak about a little bit about the some of the other work that we've
[22:05.110 --> 22:12.610]  been using these headsets for in the lab space. So, apart from cyber security, it's been
[22:12.610 --> 22:21.090]  instrumental in designer views between these different projects at the lab space. And so,
[22:23.540 --> 22:29.990]  we'll have multiple engineers come in to a visualization and they can view, you know,
[22:29.990 --> 22:36.610]  the new micro reactor that they're building in front of them to scale. And they can walk around,
[22:36.610 --> 22:45.390]  make notes on the on the object, move different components, and talk to each other while it's
[22:45.390 --> 22:55.550]  going on with data being relayed through our own lab built multiplayer server. And so, that
[22:55.550 --> 23:02.170]  has really, you know, saved the national lab millions of dollars for each project that we've
[23:02.170 --> 23:08.790]  been involved in because they've been able to catch mistakes early on before the project was
[23:08.790 --> 23:17.050]  actually built physically. And then share just one more one more project that we've been working
[23:17.050 --> 23:25.310]  on by creating a full digital twin of a nuclear reactor. So, it's a small reactor. It's about
[23:25.310 --> 23:33.850]  five watts used for testing. But we were able to create a digital twin, a high level digital twin
[23:33.850 --> 23:45.610]  that incorporated AI predictive analysis on the system. And so, it would predict 15 minutes in
[23:45.610 --> 23:51.670]  the future using the data that it's learned off of. Predict 15 minutes in the future if the system
[23:51.670 --> 24:00.410]  was going to be passing some sort of a temperature threshold or threshold on the the neutron flux.
[24:00.410 --> 24:09.810]  And because of this, it would then warn the operator and take autonomous control of the
[24:09.810 --> 24:17.030]  system bringing it back into its operating range. And a big portion of that is being
[24:17.030 --> 24:24.010]  able to give the operator a view into what's being what's being learned through the AI
[24:24.750 --> 24:30.330]  and how the digital twin is actually running. And so, we've given them two interfaces between
[24:30.330 --> 24:42.010]  the mixed reality headset and a web display. And it's truly been valuable and has been
[24:42.010 --> 24:49.210]  integral for the research that needs to be done for these smaller modular reactors.
[24:49.950 --> 24:58.230]  So, I will just open it up to any questions if there are any. And seems to just be a microphone
[24:58.230 --> 25:06.870]  right here. And then, if not, we can go and rest. So, there's a there's a microphone right
[25:06.870 --> 25:14.110]  there if you'd like to if you had a question. Which reactor were you modeling? Out of curiosity,
[25:14.110 --> 25:24.810]  was it the ATR or no? I'll just give you this microphone. Which reactor were you
[25:24.810 --> 25:31.750]  modeling? Was that the ATR or a different one? So, you know a little bit about the lab. Nice.
[25:31.890 --> 25:38.930]  So, his question was, which reactor were we modeling in the digital twin? And if it was the
[25:38.930 --> 25:46.850]  ATR or advanced test reactor at the Idaho National Lab? And so, this reactor was actually a university
[25:46.850 --> 25:54.250]  collaboration between the Idaho National Lab and Idaho State University. And so, it was using their
[25:54.250 --> 26:11.280]  AGN 201 reactor. AGN 201. Okay. Thank you. All right. I'll try this. Okay. You were saying that
[26:11.280 --> 26:15.040]  millions of dollars were saved because they were able to catch stuff early. I was just curious,
[26:15.040 --> 26:20.720]  do you have like one example? Like just an anecdote? Yeah. Great question. Thank you. So,
[26:21.520 --> 26:27.260]  his question again was, I had mentioned that we'd saved millions of dollars on construction on
[26:27.260 --> 26:34.260]  these projects using extended reality hardware. And he asked if there were any examples I could
[26:34.260 --> 26:42.340]  share. So, there's some glove boxes that we've been developing to be able to process some different
[26:42.340 --> 26:51.260]  materials. And they were able to, you know, again, we were loading the CAD models from the engineers
[26:51.260 --> 26:58.680]  into extended reality environments. And then they were able to visualize the glove boxes within the
[26:58.680 --> 27:04.620]  space that they were to be built. And they could go around, have design reviews with each other.
[27:05.860 --> 27:11.280]  They noticed that ergonomics on the system was not very good for all of their operators.
[27:11.480 --> 27:17.120]  And so, they had, you know, people put their arms into the virtual glove boxes. And they found that
[27:17.120 --> 27:22.240]  they were going to have to build some platforms for some people to stand on to be able to use
[27:22.240 --> 27:26.300]  the system. And then that just kind of defeats the whole purpose of building this multimillion
[27:26.300 --> 27:32.080]  dollar system, right? And so, they were able to lower things down so that everybody could use the
[27:32.080 --> 27:42.040]  system. On the same project, they were able to move the glove box around in parts, in the parts
[27:42.040 --> 27:46.780]  that it was going to be built into. And check if they were even able to fit it through the doorways
[27:46.780 --> 27:52.380]  of the facility. And so, they were able to determine that there would be some collisions. And
[27:52.380 --> 28:00.200]  they broke a couple of the pieces into even smaller sizes. And then clearances between doorways
[28:00.200 --> 28:06.440]  has always been, seems to always be an issue on whatever project we're on. So, just escape routes
[28:06.440 --> 28:11.240]  and things, they need to have a certain, you know, clearance between the doorways. And they were
[28:11.240 --> 28:18.100]  able to find those and make adjustments. And so, that's a smaller project. Some of the other
[28:18.100 --> 28:24.260]  larger projects that we've been on, you know, if they were able, if they were to go into construction
[28:24.260 --> 28:30.540]  at all on those, before they caught these design changes that needed to be made, then it would have
[28:31.320 --> 28:35.540]  cost millions and millions of dollars. So, yeah, thank you.
[28:40.080 --> 28:44.080]  Can you say a little bit, can people hear me or not?
[28:44.080 --> 28:45.400]  You might need to get closer.
[28:45.400 --> 28:50.500]  Yeah, hello. Can you say just a little bit about why virtual reality, as you've described it,
[28:50.500 --> 28:55.600]  is actually better than traditional, you know, on the flat monitor, you know, which has been used
[28:55.600 --> 29:00.200]  for many, many years now to catch many of the same sorts of mistakes. You know, what's, you know,
[29:00.200 --> 29:05.660]  I noticed that actually that your glove box example is probably a good example. But do you have any
[29:05.660 --> 29:13.120]  thoughts or why is this better than the traditional, you know, flat screen CAD?
[29:13.340 --> 29:22.040]  Yeah. So his question is, how does mixed reality differ from using just normal 2D CAD software
[29:22.940 --> 29:29.860]  and how it's been beneficial? And so how I see it is that
[29:31.200 --> 29:38.320]  with CAD, you need to be familiar with the system to fully understand everything that's going on.
[29:38.320 --> 29:45.300]  And so sharing with stakeholders, especially, it's hard for engineers to portray exactly what's
[29:45.300 --> 29:52.240]  going on. But in mixed reality, it's there. It's just there virtually, and they can walk around
[29:52.240 --> 30:00.060]  the system and have a discussion. And, you know, it removes the need for interpretation
[30:00.060 --> 30:20.350]  of these CAD models or blueprints. Thank you. Hey, man. Are the tools for VR development
[30:20.350 --> 30:28.910]  catching up or caught up to the same tools you would use for a flat screen or is there
[30:28.910 --> 30:35.190]  a difference? That's an interesting question. If the VR tools are caught up to the same tools
[30:35.190 --> 30:41.970]  that we'd be using in traditional CAD modeling. And so we're not actually doing any modeling
[30:41.970 --> 30:51.870]  inside of these, you know, virtual reality systems. Traditional CAD on computers is still superior.
[30:53.370 --> 31:04.530]  You have more precise controls. And it just it allows them to go in greater depth on the design
[31:04.530 --> 31:13.810]  as well. And so we don't do any of the design. But the software is catching up a lot. And already
[31:13.810 --> 31:18.210]  in the, you know, past couple of years that I've been working with these systems, they've matured
[31:18.310 --> 31:26.190]  a lot to where we can import the CAD into the virtual reality. And then if they make any updates
[31:26.190 --> 31:33.310]  to those systems, then it's getting to the point where we can just update it in our virtual system
[31:33.310 --> 31:38.030]  as well. So all of the interactions and things that we've developed as well can transition to
[31:38.030 --> 31:47.070]  the new model. And so I'd say that it's maturing, but it's not quite as mature as we want it to be.
[31:47.070 --> 31:59.840]  Thank you. Okay. Well, let's go rest. Thank you all.