Are We Calling Everything a DIGITAL TWIN?

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is coming way faster than people have any idea.
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And the AI is what's driving that.
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So it's gonna re-engineer all what we do.
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Next two years, three years, it's going to be a completely different landscape.
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Year, two years with all sorts of new things, new bits of software written in, Claude, kids saying, oh, I've got this new reality capture program that can do this and this and this, flooded with cheap scanning devices, cheap reality capture devices.
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I think there's going to be an awful lot of noise at that lab.
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So my question is, what does your industry call a digital twin?
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And it's what drove me to now ask this question.
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Scanning just captures some data, but what do you do with that data?
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And yes, maybe you take it and make a CAD model or a BIM model, then what happens?
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You get the right staff and other capabilities that know their stuff.
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We're actually de-risking projects versus another engineer sees this is a value and a de-risking opportunity.
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I was quite provocative coming from this industry.
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Not even everyone knew that.
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And I said, stop calling your drone fly through your model, a digital twin, because it's not on its own.
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I think some people off kind of deliberately.
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It found the exact same differences in 30 minutes.
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I think that is absolutely where things are going.
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These digital twins are now going to be diffed by AI that every industry is going to be impacted by it.
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I can't see it not changing.
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Hey guys, before we listen to the full episode, we wanted to ask if you're liking this content, would you please subscribe to the channel and like the video?
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It really helps me and our team grow this podcast and bring in more awesome guests to the channel.
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Thank you.
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And back to the episode.
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Welcome to the studio.
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Thanks for coming in today, gentlemen.
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I appreciate it.
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Thank you.
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Thanks for having us.
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So this is the first of a new series of roundtable podcasts.
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We've said we're launching.
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And instead of it being only about the guest, which we usually do a little deeper dive on solo episodes, the whole point of this is picking a topic and bringing people around to talk about this topic specifically.
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And this is our digital twin focused conversation.
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Oh, very cool.
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Digital twin.
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That's a big, that's a big topic.
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Please don't ask to divine.
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We're not defining it.
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That's how we're going to start.
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No one has.
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I'll just have a right there.
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Well, I have a feeling this will be a fun conversation.
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Even before hitting record, there's laughing and jokes happening.
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So I think it'll be a good one.
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Before we get rolling into conversation, I think the best thing to do is to lay the ground, you know, letting people know who it is that's having this conversation, a little bit of your backgrounds, what you guys do, because I think that will give perspective to what, you know, the again, the perspective you guys are each speaking from as we have the conversation.
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So let's keep these to about one hour per person.
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OK, maybe not that long.
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Yeah.
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Yeah, in a couple minutes, give us a little bit of your kind of your your whole background of like, from the perspective of this conversation, digital twin, in the industry, the technologies, give us a little bit of your introduction to yourself and and what you're doing.
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And we'll make our way around.
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Start with you, Kelly.
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All right.
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So Kelly Watts, I have a company called Digital Twin Consulting.
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I like to be pretty obvious about what I do.
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So Matt and I know each other a long time because I used to work at Faro, the global director there many years ago when you're at DeWalt and Stantec.
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Previous to that was at Trimble Navigation.
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So I've been in this space for, oh, geez, at least 15, 17 years, something like that.
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After I left Faro, I had my own reality capture company called VisualPlan.
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Caught an impetus with that.
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It was a 360 camera that was put in my hand by Matt Daly, who we, a common friend, worked for an instruction site, merged with DroneDeploy, just got acquired by Procore 10 years after leaving Faro for almost the same price that Faro was acquired for.
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$920 million versus $860 million.
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That's hard to believe.
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The money's in the software today.
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But in my reality capture days, I spent a lot of time, large critical infrastructure, working with SLAM, working with 360 imagery and drones, really large, fast capture.
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Really pushed the boundaries on that quite painfully.
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Did some threshold as well.
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But what I found is that a lot of consulting.
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Every time I touched data...
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people want to do more with the data, especially on the operations side.
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So the IT integrations with CMS, the IoT integrations with telemetry.
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And I found myself under a pretty large infrastructure project with DFW Airport building their digital twin.
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So I was there full time for four years as a consultant helping that program.
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Also installing physical LiDAR for movement of traffic, of passenger movements.
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So that's another program I ran.
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And then I ran an AI simulation.
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program contracts there as well.
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And then kind of spun out to, was always doing a little bit of side work, but now full-time doing this.
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So anyways, that's a little bit about my background.
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Awesome.
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That's awesome.
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I guess I'm next.
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I'm Jason Sansusi, not Clark.
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Um, inside joke from earlier.
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So I'm the Chief Product Officer at Flight Technologies.
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We talk about product and where it is, the software side.
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Yes.
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We do change detection for telco towers, and we also do verified walkouts for fiber.
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Obviously, with BEAD and lots of other programs that are out there, there's my background.
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I spent about 25 years as a remote sensing and GIS scientist.
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Spent about half my career in defense and intelligence, the other half in commercial.
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Had a fun conversation with Matt this morning about all of that.
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Been dipping my hand into coaching, mentoring, consulting, have a nonprofit.
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Do a lot of different, literally wear different hats.
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I was literally wearing a whole different outfit earlier today.
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We're not going there.
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And we'll again later.
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I will probably be the funny one, but I may also try to be the controversial one.
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So I'm just glad I'm on the show.
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And actually, one more thing.
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So the thing that I'm here to really try to get across is that it's not that people have a digital twin.
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It's that they use it and that they open it and they use it a second time and maybe a third time and maybe get another one.
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And I think that the technology that we're using is...
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We're doing amazing things with reality capture.
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I think we're still in based on the conversation we were having earlier.
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I think we're still not selling it very well and tying it to a decision very well.
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And I think we'll talk about that.
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Yep, so my name's Carlos Femer.
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I'm the Vice President of Geomatics Remote Sensing at HDR Engineering.
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So within there, Geomatics Remote Sensing is a loaded topic too.
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So we have our survey and register surveyors that we do.
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We have drones, LiDAR, geophysics, non-destructive testing.
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So we kinda like the data acquisition pieces.
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What we find, especially when we get to the topic of digital twins,
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Really, it's not one LiDAR system.
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It's not one drone.
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It's a hybrid of using survey LiDAR drones, you know, fit for purpose, whatever that's put together.
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But kind of my background, been fortunate to be around some very innovative folks.
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So back in 97 to 01, worked with CNC Technologies.
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That's Thomas and Jimmy Chance, son of John Chance.
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They sold to Oceaneering, you know, five, 10 years ago.
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But back then, you know, being part of that innovation where they said, you know, they put one of the first commercial autonomous underwater vehicles to survey in the Gulf of America.
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That was, at the time, Gulf of Mexico.
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But just seeing how they did that back in the day, that was very impressive.
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Went on to John Chance, worked offshore in their offshore group as a systems engineer.
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doing a lot of stuff in supporting, then moving over to the land group, spent another seven years there, was a VP COO and then president of that division.
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Really a good opportunity where we had airborne LIDAR,
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and conventional survey.
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And we said, how do we blend that together?
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And that's going to maybe tie in later on, because at the time you're doing these 500 mile pipelines conventionally, what can we do and bring it?
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So we said, let's add aerial, you know, helicopters to it.
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That'll do the front end.
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And then you can do the subsurface with boundary.
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So that was a unique approach.
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And, you know, that's going to tie over to Digital Twin shortly.
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Yeah.
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And then on the digital twin side, been fortunate, like with some big IOC companies around the world, doing digital twins at some major refineries, doing digital twins in military academies, bridges, dams, emergency response.
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I think we'll get into more detail with that, but super fortunate to be in the industry, be at the right place at the right time, see how technology has evolved, and I'm happy to be here.
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Last but not least.
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Hi, I'm Jeremy Pilgrim.
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I've come across here from the UK to represent the British interest in this market and not to talk about Brexit.
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I've been around Digital Twins and RealityCapture for a very long time.
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I think we established that I was 3D scanning before you were born.
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Yes, we did.
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LAUGHTER
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There you go.
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That was a very, very long time ago.
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And so I've been aware of point clouds and what they can do and the benefits of just getting the data into an object-oriented form, initially through CAD, then through BIM.
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I operate in a tiny little vertical.
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I'm sat here amongst you multidisciplinary guys dealing with what I call the hero assets of the airports and the telecoms networks and the...
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huge bridges and infrastructure things, and I just deal with schools.
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Schools.
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Schools that people forget need management in terms of their buildings.
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We all think of schools as that place where we teach kids, and that's the sole purpose of those buildings.
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But they're...
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They're not looked at as a big asset.
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They're cash poor.
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They're not very forward thinking in what they're trying to do with the operations of the buildings.
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And we're trying to cover many bases.
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We're trying to create digital twins, introduce them to digital twins.
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We're trying to bring in the air quality now.
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Most people are bringing in the air quality to look at how they optimize the building management system to reduce their cost of operation.
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But we're looking at it from the cognitive function and the cognitive ability of children, because the building has got one purpose, to teach children.
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And we've got to think about how we make that building right and the most advantageous to the learning opportunity with our children.
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They get a short period of time to learn.
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And we've got to make it as best we can.
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And that's been my goal for, well, since pretty much 1996.
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So 30 years now, working just in one vertical.
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I keep trying to break out.
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It's holding you tight.
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I did some beach huts in Scarborough.
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I did a lighthouse in Scarborough.
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We've done some farms recently.
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But no, schools are where it's at for me.
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And I don't think I'll ever break out of it.
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Yeah, that's awesome.
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Well, I actually I think it's it's very interesting.
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Like you said, many people, most people I know in the industry that touch scanning, modeling, drones, all of that, they work in a lot of different industries.
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And you're a good example of like there's enough work in a single niche, you know, and you're not it's not like it's just you trying to work in schools.
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You have a business of 40 people.
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Yep.
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And all you do is schools.
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Yes.
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In just the UK.
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Yes.
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Yes.
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Uh, and, and there's, and there's even more opportunity within your space for growth, for, you know, improvement in how people use data and 24,000 schools in the UK and I've only done 5,000 of them.
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Yeah.
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So yeah, yeah.
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That's awesome.
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It's a way to go.
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Well, thanks for the intros.
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Uh, as said, I think, uh, it gives a little perspective to like, we've got a nice mix here of, you know, people that have worked on the whole.
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hardware side on the software side consulting within you know large corporation working in different disciplines a whole mix and I like to let the guests honestly be the ones driving this conversation but I try to be involved where I can as well and especially because I've worked with multiple of you actually on projects
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You know, the short story for for my entrance into this conversation is coming from the survey side as well, getting in scanning in about 2009, built my service company doing scanning all over the place.
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And it's what inspired me to start RCN and start the podcast on the conference is seeing all these different types of people using this data.
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And saying, I think if we start pulling people together and talking about the different uses of technology from different verticals and different, you know, industries and backgrounds, it'll share and inspire people to think, hey, if he's using that over there for that purpose, how could we come over here and use it for this other one?
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And so this breakdown of industries.
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It even goes all the way to how we purposely have formatted our conference where and I'm not going to go deep into that.
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This isn't for me to sell the conference, but it's relevant because some people go, well, that conference has too many different industries.
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Like I only want to go to an industrial industry conference.
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I only want to go to an architecture one.
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The purpose for ours is like there's only one stage and you're going to watch a variety of talks from different industries.
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But the whole point is you might see that one industry is further ahead than the other.
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And if you would have only chosen to go to your track or your conference, you would have only seen what's being done in your space.
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when you open yourself up to learn from other industries and other people, it's what might inspire some innovation or some change that you're not seeing done in your space.
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So even in our conversation today, I think we'll see a bit of that kind of unfold.
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Archon CTA button here.
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Well, one thing I like about your conference is the common thread, though, is reality capture.
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And it's one of the few places you go anywhere in the world, and it's not a BIM conference.
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It is someone who's got some experience with photogrammetry or LIDAR or SLAM or mobile mapping or something that connects them as a community.
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So I think that's really cool.
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I don't know of another event that's quite like that.
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Yeah, it is the through line.
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In fact, I think three of you have actually spoken at the conference.
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So I continue to use this community to draw people in to share there, to share on here, to share through content.
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Next.
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Yeah.
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We have one more person to pull in.
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Maybe for good reason.
220
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You'll find out.
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But.
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It is the through line is, you know, when I started the conference, it came from my experience, which was scanning.
223
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I started getting pulled into other industries that I didn't have information, you know, knowledge and working in in when I first started in scanning for buildings.
224
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I had never been in buildings before.
225
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I didn't know anything about architecture.
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We came from survey working out in the field and oil and gas.
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And then it was like scanning is what pulled us into that and then into forensics and then into airports and in the military, you know, all these different industries.
228
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And it's what drove me to now ask this question around digital twin, right?
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Is scanning just capture some data, but what do you do with that data?
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And yes, maybe you take it and make a CAD model or a BIM model, but then what happens?
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Can I pose a question to the group?
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That may include the answer to the question that you're asking.
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I was at a conference last week.
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It was the ISE Expo in Nashville, and it was primarily around broadband fiber.
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I was walking around saying Digital Twin, which is a category word, good for investors and search engines and stuff like that.
236
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But I had a moment with almost everyone that I walked up to with the floor where they had to interpret what?
237
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About 20 times I was corrected.
238
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What do you mean a walkout?
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Like, what's a walkout?
240
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Oh, it's basically what you just said.
241
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But they had to interpret for me.
242
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So I about 20 times I started calling it a walkout and immediately everyone knew what the heck I was talking about.
243
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I'm like, wow.
244
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Well, so my question is, what does your industry call a digital twin?
245
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I mean, I can get into this topic.
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And I wrote a blog about three years ago and really perked a lot of people's interest.
247
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I was quite provocative coming from this industry.
248
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And not even everyone knew that.
249
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And I said, stop calling your drone fly-through, your BIM model a digital twin, because it's not on its own.
250
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And that, I think, pissed some people off, kind of deliberately.
251
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But it made us rethink and reevaluate, well, where does the coin term come from?
252
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What was the inherent purpose of that term?
253
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And it does have more meaning.
254
00:18:32.954 --> 00:18:37.277
So the problem is that the word gets hijacked.
255
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by everyone that likes it because it's a descriptive term.
256
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I mean, I can say, well, it's, I can see it and it's the same.
257
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And it's a, it's a twin of what I can see.
258
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And, and unfortunately, whether it be vendors, whether it be, uh, people in certain verticals that really attracted to the term, they use it.
259
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But for a leader,
260
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that is doing a little bit of research and they have certain anticipated outcomes they expect.
261
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It's very confusing.
262
00:19:02.533 --> 00:19:17.058
And going through, especially with DFW Airport, running those leadership meetings with EVPs and having them all have these different ideas of how this magical, mythical thing could solve all these.
263
00:19:17.078 --> 00:19:20.519
It was absolutely crazy how many different thoughts.
264
00:19:20.619 --> 00:19:23.160
And really trying to understand, well,
265
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What do we want this project to do?
266
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And what really is it?
267
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How do we define it?
268
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You know, and then, you know, the platform's not the digital twin.
269
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It's a data model, the way I look at it.
270
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It's a data model that we feed to build decision process.
271
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And that can mean different things for different people, and that's okay.
272
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But we've got to kind of set the boundaries of what that needs to be for a construction project, a design project, or an operation, or something that's going to make sense for that use case.
273
00:19:53.373 --> 00:20:02.240
I'll just answer that by saying, from my perspective, I used the term digital twin before, but I actually only ever used the term digital looky-likey.
274
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Looky-likey?
275
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Is that a UK term?
276
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Digital looky-likey.
277
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It's a Jeremyism of a digital looky-likey, because then it stops all this discussion.
278
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Yeah.
279
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Because...
280
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Is it a digital twin when I've now got a feedback loop of information going from the model back into the building?
281
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And has it become a twin now or not?
282
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And rather than have that discussion, it's a looky-likey.
283
00:20:32.077 --> 00:20:32.317
Yeah.
284
00:20:32.897 --> 00:20:52.361
And just one alternative view is, you know, so so fortunately, I've been in the industry and in probably 20 years and in heard different companies, IOC companies, different operators, state DOTs, even other AEC firms.
285
00:20:52.681 --> 00:20:58.642
And like in our case, what we found is like, you know, like a digital twin would be.
286
00:20:59.802 --> 00:21:02.003
specific to a niche that's out there.
287
00:21:02.063 --> 00:21:02.943
And I'll give an example.
288
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You could have a connected or disconnected twin, and it depends on the use case.
289
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And I'll use a dam for one example.
290
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So in a dam, if I have a dam that's located in a rural area that's out there and their inspection cycle is once every five years.
291
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So if I have a digital twin of that physical asset and I can get it to multiple stakeholders with SMEs in different states,
292
00:21:29.315 --> 00:21:32.618
And somebody can now take it and measure and get value from it.
293
00:21:32.638 --> 00:21:34.460
It depends on if you could get value from it or not.
294
00:21:34.780 --> 00:21:40.665
If it's just a mirror without value or context and I can't derive anything from it, that's something.
295
00:21:41.186 --> 00:21:48.693
But in a case where you can bring it up, use AI, do crack detection, what's the alternative?
296
00:21:48.933 --> 00:21:52.736
The alternative is somebody has to go there, physically repel,
297
00:21:53.717 --> 00:22:00.601
and then go there and then they're gonna measure this by hand and they're gonna annotate it and then they're gonna bring it back and put it in CAD.
298
00:22:01.061 --> 00:22:10.026
But if you have a digital model of it where you can derive the value from it and that acts as your, and I could continue deriving value.
299
00:22:10.046 --> 00:22:12.027
Now there's extra value I can do for,
300
00:22:13.270 --> 00:22:14.571
I ran the cracks last time.
301
00:22:14.591 --> 00:22:15.852
Let me look at exposed rebar.
302
00:22:16.333 --> 00:22:16.933
What else do you want?
303
00:22:16.953 --> 00:22:17.974
I want to see spalling.
304
00:22:18.014 --> 00:22:19.335
Sweet, I can do spalling too.
305
00:22:19.855 --> 00:22:25.800
We never have to go back out to that site, theoretically, and we can rerun models and derive value from it.
306
00:22:26.141 --> 00:22:28.803
So that's kind of like some folks say, like a digital twin, it has to be connected.
307
00:22:28.823 --> 00:22:29.764
It has to be connected.
308
00:22:30.404 --> 00:22:34.466
I think it could be disconnected in certain use cases where you could derive value.
309
00:22:34.806 --> 00:22:43.009
Or we did do some emergency rail responses or emergency response, landslide response, where we did the top side.
310
00:22:43.749 --> 00:22:53.013
And then we installed some inclinometers with IoT that was feeding data that was able to detect and tell where the landslide was happening is between
311
00:22:53.713 --> 00:23:01.519
you know, 18 and 22 feet, and it hasn't been stabilized, and you're monitoring it, but you're also monitoring the top side, too.
312
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So I guess our take is you could have something disconnected, you could have it connected, and, you know, there's value in both.
313
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I think there are core components that we need to at least set some boundaries about what this thing we call a twin is.
314
00:23:20.677 --> 00:23:23.943
And without spending this whole podcast on defining a digital twin.
315
00:23:23.963 --> 00:23:25.305
This is the digital twin podcast.
316
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Go for it.
317
00:23:27.000 --> 00:23:31.481
We really need to think about that it's a change over time scenario.
318
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What that fidelity and frequency of change, that can be defined based on the use case.
319
00:23:36.442 --> 00:23:37.823
So in your case, it might be.
320
00:23:38.063 --> 00:23:39.183
Every two or five years.
321
00:23:39.343 --> 00:23:39.543
Right.
322
00:23:40.203 --> 00:23:43.524
In some cases, it may be a weekly job site photography.
323
00:23:44.004 --> 00:23:55.107
But I think the idea is that you have a living model that's changing and tracking over time based on your use case, that you can virtually connect with that model to make decisions.
324
00:23:56.047 --> 00:23:59.189
And, you know, there is a simulation component, which makes it difficult.
325
00:23:59.249 --> 00:24:02.131
But I think those are key things.
326
00:24:02.271 --> 00:24:03.992
It can't just be a single one and done.
327
00:24:04.012 --> 00:24:04.272
Right.
328
00:24:04.592 --> 00:24:06.173
Because then it's just a static model.
329
00:24:06.534 --> 00:24:09.275
And it's an exhibit that you're looking at.
330
00:24:09.695 --> 00:24:16.780
But if you're repeating that capture for an inherent use case and change tracking is a really good one, I think that, you know, you get there.
331
00:24:18.081 --> 00:24:18.841
That's my thought anyway.
332
00:24:19.321 --> 00:24:20.242
I 100% agree.
333
00:24:20.282 --> 00:24:24.125
So I think we're dialing it in because to your point, the first one is your baseline.
334
00:24:24.465 --> 00:24:26.867
The second one is, okay, has anything changed?
335
00:24:27.327 --> 00:24:29.809
Now you can, I mean, that's tremendous value.
336
00:24:29.949 --> 00:24:32.791
If you have, you know, the first time you do it, there's your base.
337
00:24:33.091 --> 00:24:36.133
You do it again on whatever cycle that was, two year, five years.
338
00:24:36.153 --> 00:24:36.814
You do it again.
339
00:24:37.574 --> 00:24:40.737
And these four items have changed.
340
00:24:40.757 --> 00:24:42.699
You know, you use AI and say, what's changed?
341
00:24:43.139 --> 00:24:53.109
Now, if you say, now go focus, that's a lot of value to say, if you're gonna go back to that asset, I would focus on these four areas because we know those might've changed.
342
00:24:53.509 --> 00:25:01.817
Then you move it one more step further, the third time you do it, now you can say, we could do some predictive analytics with AI to say,
343
00:25:02.317 --> 00:25:03.178
Here's your baseline.
344
00:25:03.378 --> 00:25:04.680
Here's your change that grew.
345
00:25:05.060 --> 00:25:06.301
Here's your third iteration.
346
00:25:06.762 --> 00:25:12.828
And now I can say, if I do nothing else, this might expect to grow in this geography, in this weather environment.
347
00:25:13.269 --> 00:25:15.051
So I'm in agreement with you.
348
00:25:15.171 --> 00:25:17.634
So you're bringing in real-time elements like weather.
349
00:25:18.194 --> 00:25:20.455
That's an important layer of context.
350
00:25:20.675 --> 00:25:26.898
The idea of a twin is that you're getting inherent context in different sources to allow you to make better decisions.
351
00:25:27.158 --> 00:25:27.359
Right?
352
00:25:27.719 --> 00:25:33.622
And then the other part you mentioned there is forecasting the future based on the baseline data that you have, whether using AI or
353
00:25:34.722 --> 00:25:37.343
simulation or forecasting models, whatever.
354
00:25:37.823 --> 00:25:42.484
But the idea is you're bringing in multiple data sources, not just a reality capture.
355
00:25:42.504 --> 00:25:46.886
It might be a reality capture, BIM, IoT, weather, any of these things.
356
00:25:46.906 --> 00:25:52.767
There are multiple factors that are complex for humans to understand, and that they mean different things on their own.
357
00:25:52.807 --> 00:25:56.928
But when you bring it together, that's why I say about digital twins, 1 plus 1 doesn't equal 2.
358
00:25:57.349 --> 00:25:58.149
It has to be more.
359
00:25:58.449 --> 00:26:01.850
There has to be a reason why we're bringing this data in to give us some
360
00:26:02.690 --> 00:26:07.492
new basis, new knowledge from bringing that data together.
361
00:26:07.872 --> 00:26:09.273
Oh, here's a fun thought.
362
00:26:09.413 --> 00:26:11.013
I completely agree when you talk about numbers.
363
00:26:11.454 --> 00:26:12.914
So one thing that always...
364
00:26:12.934 --> 00:26:13.494
I went to grade school.
365
00:26:13.534 --> 00:26:13.635
Ever.
366
00:26:15.215 --> 00:26:21.258
One thing that's always very interesting for me, and it has been my entire career, is accuracy.
367
00:26:21.978 --> 00:26:26.960
And I think this can get into a lot of different areas, but the thing that's interesting for me related to accuracy is
368
00:26:28.645 --> 00:26:37.108
Everyone in this industry seems to use their technology accuracy tolerance as kind of a badge of honor.
369
00:26:37.328 --> 00:26:40.130
You're like, I can get some millimeter.
370
00:26:40.250 --> 00:26:47.773
And, you know, the conversation I think actually needs to be had with our actual customers is why.
371
00:26:48.593 --> 00:26:50.133
Why do you have that tolerance?
372
00:26:50.434 --> 00:26:51.994
Can we tie a decision to it?
373
00:26:52.454 --> 00:26:53.535
What does that decision make?
374
00:26:54.815 --> 00:26:56.137
What does that tolerance require it to be?
375
00:26:56.237 --> 00:27:04.767
Like if I go back to telecom, which is the hat that I'm wearing right this second, if I just need to make a yes no decision on a fiber corridor,
376
00:27:05.690 --> 00:27:07.651
I don't need centimeter, millimeter grade anything.
377
00:27:08.071 --> 00:27:10.993
I can do it with a quick survey.
378
00:27:11.774 --> 00:27:21.099
Now, if I need to build something and I'm doing make ready or anything like that, then yes, I will need something with more horsepower, with bigger GBs and millimeter.
379
00:27:21.559 --> 00:27:25.302
But there's two charts that never get put on top of each other.
380
00:27:25.762 --> 00:27:26.522
There's the...
381
00:27:27.623 --> 00:27:30.605
The price versus accuracy, right?
382
00:27:30.685 --> 00:27:37.510
Where it's like, yeah, man, I can go from subfoot to, or I can go from like subfoot imagery to centimeter imagery.
383
00:27:37.890 --> 00:27:38.651
Yeah, that looks like this.
384
00:27:38.931 --> 00:27:40.592
Centimeter, millimeter, looks like this.
385
00:27:41.353 --> 00:27:46.957
Because there's a whole lot more QC, a lot more processes, a lot more processes and control and all of those things.
386
00:27:47.417 --> 00:27:50.900
The thing that comes with that is now, what is the consequence curve?
387
00:27:50.920 --> 00:27:51.180
Yeah.
388
00:27:52.272 --> 00:27:58.135
That's pretty flat along a majority with maybe a pretty big step.
389
00:27:58.756 --> 00:27:59.156
And that's it.
390
00:27:59.176 --> 00:28:00.077
It doesn't go like this.
391
00:28:00.297 --> 00:28:02.238
It goes like this and then it goes like that.
392
00:28:02.818 --> 00:28:14.565
So if it's a high, if it's something that's going to, if you're going to over bit it, essentially you're going to say, man, I'm going to give you millimeter activity for everything.
393
00:28:15.229 --> 00:28:16.849
but it's going to cost you millions of dollars.
394
00:28:17.189 --> 00:28:18.410
And we'll do it over and over and over again.
395
00:28:19.210 --> 00:28:24.671
Or I'm going to underperform, and then I'm just going to keep getting change orders because I'm never ever going to actually answer the question.
396
00:28:25.151 --> 00:28:26.731
So accuracy is part of it.
397
00:28:26.751 --> 00:28:30.092
The other part is completeness of the capture.
398
00:28:30.392 --> 00:28:32.973
So line of sight, resolution.
399
00:28:33.453 --> 00:28:38.134
So there's an element of quality and completeness, and accuracy is part of that scope.
400
00:28:38.634 --> 00:28:40.374
But it all has to match the business problem.
401
00:28:40.414 --> 00:28:41.654
So what problem are we going to solve?
402
00:28:42.135 --> 00:28:44.275
What is the cheapest, fastest way I can solve the problem?
403
00:28:44.715 --> 00:28:47.237
I mean, at the end of the day... For purpose.
404
00:28:47.257 --> 00:28:48.197
For purpose, yeah.
405
00:28:48.277 --> 00:28:50.018
And then... We're at the opposite end of the scale.
406
00:28:50.299 --> 00:28:51.419
Yeah, yeah.
407
00:28:51.700 --> 00:28:57.843
To me, the cost is everything because of the market that I'm dealing with.
408
00:28:58.164 --> 00:29:05.548
And as far as accuracy is concerned, I'd probably make your toes curl on what we would accept in terms of...
409
00:29:05.648 --> 00:29:08.650
I always... People say, so what is the accuracy?
410
00:29:08.830 --> 00:29:09.291
Well, I...
411
00:29:09.751 --> 00:29:17.155
Rather than me give you numbers that you're going to sneer at, let me just tell you that use this model to get a really, really good deal on your carpet.
412
00:29:17.515 --> 00:29:19.836
But just don't cut the carpet to match them all.
413
00:29:23.408 --> 00:29:28.849
Yeah, going back to your accuracy, I mean, so I'm just going to go back to like the, like inspection.
414
00:29:29.450 --> 00:29:38.132
Ideally, kind of like compute cycle, you know, you have, you have, you know, the Intel model where compute doubles every couple years.
415
00:29:38.572 --> 00:29:44.493
Compute cycles are going to continue to improve now with NVIDIA and other things that are happening and the GPUs.
416
00:29:53.315 --> 00:30:02.741
Obviously, they want to achieve the to identify the smallest possible crack possible, because if it was two inches, I can't see that two millimeter crack.
417
00:30:03.261 --> 00:30:07.083
And that's important to to capture the technology change.
418
00:30:07.103 --> 00:30:08.684
And I'll just use Skydo as an example.
419
00:30:08.724 --> 00:30:10.625
We did a pretty large dam.
420
00:30:11.466 --> 00:30:16.129
And at the time with the S2, this is going back four or five years.
421
00:30:16.789 --> 00:30:18.851
that has a 12 megapixel camera.
422
00:30:19.051 --> 00:30:23.195
What that meant was to get millimeter GSD, I had to be closer.
423
00:30:23.795 --> 00:30:29.600
Now the X10 has a 50 millimeter, which means I can do that further out and capture it.
424
00:30:30.061 --> 00:30:31.562
And then the time that it takes.
425
00:30:31.602 --> 00:30:36.066
So like we're doing digital twins of huge assets, two days.
426
00:30:36.646 --> 00:30:37.907
Let's talk about a survey now.
427
00:30:38.128 --> 00:30:41.310
If I mobilize a crew to go out to a site,
428
00:30:42.031 --> 00:30:42.912
to do the minimal.
429
00:30:43.232 --> 00:30:45.054
That might be one or two days as well.
430
00:30:45.854 --> 00:30:48.096
And then I have a MOBE and DEMOBE there, four days.
431
00:30:48.116 --> 00:30:49.757
So I might be adding one extra day.
432
00:30:50.298 --> 00:30:52.540
So the incremental cost, like you said, that curve,
433
00:30:53.722 --> 00:30:56.724
I think the collection is probably comparable.
434
00:30:57.044 --> 00:30:58.585
There's probably not much there.
435
00:30:59.085 --> 00:31:01.866
I think where it gets on the back end is the processing time.
436
00:31:02.347 --> 00:31:07.329
That's where you're adding probably a lot more time to post-process and get to the result.
437
00:31:07.709 --> 00:31:11.992
But now we're doing things where if your workflow is tight, you can build it.
438
00:31:12.652 --> 00:31:20.174
and say, go run and throw some, you know, multiple GPU cycles at it, and then it'll run seven days.
439
00:31:20.394 --> 00:31:38.220
And as long as it doesn't crash, which software does, and then you have to check it, then you might have to restart it, but then you build it in tiles and then, so there's smart ways, you know, we've messed up over and over to figure, beat our head against the wall, where we said, build this in one cycle,
440
00:31:38.960 --> 00:31:42.041
And then three days in, it crashes, and you start again back to zero.
441
00:31:42.521 --> 00:31:44.201
Now we're like, no, never again.
442
00:31:44.221 --> 00:31:46.262
We're going to put it in tiles.
443
00:31:46.302 --> 00:31:49.302
So if it has 700 tiles, you go three days.
444
00:31:49.722 --> 00:31:50.682
I did 300.
445
00:31:51.303 --> 00:31:51.963
It crashes.
446
00:31:52.383 --> 00:31:54.623
The next time you do it, it's on 301.
447
00:31:54.703 --> 00:31:55.443
I said, love it.
448
00:31:55.864 --> 00:31:59.184
So, you know, you might have missed overnight five hours of processing.
449
00:31:59.224 --> 00:32:04.685
So I think even that, my point on the post-processing, I think that's also starting to come down if you do it right.
450
00:32:05.165 --> 00:32:07.326
So, you know, I think...
451
00:32:08.106 --> 00:32:14.852
It does need to be fit for purpose, but that's the challenge is like clients don't know to say, I want two millimeter accuracy.
452
00:32:15.312 --> 00:32:18.495
They just know find the cracks or whatnot.
453
00:32:18.735 --> 00:32:22.398
The other thing I just want to caveat, too, is we do a lot of physical inspection.
454
00:32:22.438 --> 00:32:24.580
So we also think this is a tool to complement.
455
00:32:24.660 --> 00:32:29.945
Like we have like at the firm I'm with has a tremendous rope inspection team.
456
00:32:30.265 --> 00:32:31.926
Some of times, you know, there's visual inspection.
457
00:32:32.727 --> 00:32:36.472
inspections and sometimes there's hands on that you have to touch.
458
00:32:37.133 --> 00:32:43.902
And I like the, you know, the government mandates as a that's a state and federal mandate that this iteration happens.
459
00:32:43.942 --> 00:32:45.424
And I think it's a smart thing to do.
460
00:32:45.985 --> 00:32:48.869
So my point there, even on the physical inspection,
461
00:32:49.950 --> 00:32:57.915
You know, some of these tools we're talking about is a complement tool to a system from a safety aspect, observation, collecting additional data and other things.
462
00:32:57.955 --> 00:33:06.280
So even where it's not required on the physical, still a tremendous value if you're out there anyway and you train that group up.
463
00:33:06.360 --> 00:33:16.286
So, yeah, as long as it's fit for purpose and the time of how what it costs, I think, is still going to start to continue to come down.
464
00:33:16.306 --> 00:33:16.546
Yeah.
465
00:33:17.580 --> 00:33:23.168
So I think one thing we've got to start to reimagine is what do we do with the data after the project?
466
00:33:23.668 --> 00:33:28.755
Because we're so focused often on, we're doing this exercise to build a design.
467
00:33:29.256 --> 00:33:32.780
We're doing this exercise to support a certain kind of thing.
468
00:33:32.981 --> 00:33:34.302
And then it's just disposable.
469
00:33:34.843 --> 00:33:42.389
And that's really unfortunate, especially for those creators that are out there building this wonderful, you know, exhibit.
470
00:33:42.409 --> 00:33:46.673
I'd like to have it, you know, move into an operational use case.
471
00:33:47.173 --> 00:33:49.275
So, and construction's notorious for that.
472
00:33:49.335 --> 00:33:52.278
You know, like, when we look at construction, how many opportunities there are for
473
00:33:52.818 --> 00:34:00.826
data that we're not going to ever see again until we rip out a wall or a ceiling or concrete or, you know, having an excavator hit a utility.
474
00:34:01.286 --> 00:34:02.467
You know, it blows me away.
475
00:34:02.487 --> 00:34:08.894
I just wrote a five-series article on this with Drone Deploy and pointing out, like, re-challenge, like, how do we rethink this?
476
00:34:09.274 --> 00:34:14.919
We're going to make RealityCapture a data fabric for the organization that's going to live past the project.
477
00:34:15.560 --> 00:34:17.442
So if we reimagine, well, what does that mean?
478
00:34:17.562 --> 00:34:19.284
What do we want for operations?
479
00:34:19.364 --> 00:34:20.506
Operations need to be at the table.
480
00:34:20.866 --> 00:34:21.467
What do I want?
481
00:34:21.527 --> 00:34:22.308
Or land fiber.
482
00:34:22.328 --> 00:34:29.276
I mean, what a wonderful asset to document and have, you know, for the life of that building.
483
00:34:29.316 --> 00:34:32.479
I mean, 20 years, you're going to want to know where these utilities are located.
484
00:34:32.499 --> 00:34:32.980
30 years.
485
00:34:33.200 --> 00:34:34.261
30 years, whatever, right?
486
00:34:34.361 --> 00:34:36.284
50 years for some of the water utilities and stuff.
487
00:34:36.822 --> 00:34:47.105
So I think if we're going to start to think about twins, we have to think beyond a project single-purpose use case and think about how the organization uses them.
488
00:34:47.265 --> 00:34:51.127
In your case, you are using it years over years for your integrity program.
489
00:34:51.587 --> 00:34:56.068
But what about, you're using it also pre-planning and organization and other stakeholders using that data.
490
00:34:56.648 --> 00:34:58.749
But could we use it for other purposes?
491
00:34:58.769 --> 00:35:00.430
I don't think anyone's going to argue with that.
492
00:35:00.450 --> 00:35:04.191
I think all of us here completely understand and have bought into the...
493
00:35:05.071 --> 00:35:10.532
A single twin, a single model, a single twin will give you what's there.
494
00:35:12.073 --> 00:35:14.333
The next one will say, what's changed?
495
00:35:14.573 --> 00:35:18.754
And that's actually what people are making decisions on and spending money on and all of those things.
496
00:35:19.054 --> 00:35:19.914
It's that diff.
497
00:35:19.994 --> 00:35:26.536
And the thing that AI is helping with, without completely jumping the shark here, is AI is really good at that.
498
00:35:27.136 --> 00:35:30.637
AI is really good at finding the difference between those two models.
499
00:35:31.272 --> 00:35:31.532
Right.
500
00:35:31.592 --> 00:35:31.833
Right.
501
00:35:32.173 --> 00:35:36.838
But sometimes it might be a static capture of, you know, just before you close the walls.
502
00:35:36.858 --> 00:35:37.259
Yeah.
503
00:35:37.279 --> 00:35:38.680
So your electrical utilities.
504
00:35:38.700 --> 00:35:38.860
Sure.
505
00:35:39.321 --> 00:35:46.849
But I will want a certain degree of resolution as a facility owner than I would care as a construction.
506
00:35:47.089 --> 00:35:47.290
Right.
507
00:35:47.330 --> 00:35:49.031
I just want to know how much dip rock is on the wall.
508
00:35:49.692 --> 00:35:49.953
Right?
509
00:35:50.013 --> 00:35:51.595
So I have blurry images.
510
00:35:52.016 --> 00:35:52.716
It doesn't matter.
511
00:35:53.337 --> 00:35:57.563
The other thing is we only care what was captured in that day or in that week.
512
00:35:58.044 --> 00:35:59.366
So I don't actually have a full site.
513
00:35:59.406 --> 00:36:01.529
I have a bunch of captures over time.
514
00:36:02.030 --> 00:36:05.214
So what I'm saying is, as an owner, how do I want my data?
515
00:36:05.855 --> 00:36:09.157
What are my requirements as an owner or maintenance person?
516
00:36:09.317 --> 00:36:10.558
How do I want my data?
517
00:36:10.938 --> 00:36:15.660
And do those specifications start to come down to the construction or design project?
518
00:36:16.261 --> 00:36:21.343
So that's what I think about reimagining how we capture the data for the longer period.
519
00:36:21.364 --> 00:36:30.268
MARK MANDELYIERIERIERIERIERIERIERIERIERIERIERIERIERIERIERIERIERIERIERIERIERIERIERIERIERIERIERIERIERIERIERIERIERIERIERIERIERIERIERIERIERIERIERIERIERIERIERIERIERIERIERIERIERIERIERIERIERIERIERIERIERIERIERIERIERIERIERIERIERIERIERIERIERIERIERIERIER
520
00:36:35.762 --> 00:36:42.626
But if it adds a step of work for the operator, it's going to quietly die.
521
00:36:42.866 --> 00:36:43.326
Politely.
522
00:36:43.386 --> 00:36:44.086
It'll politely die.
523
00:36:44.127 --> 00:36:44.987
Be like, this is really great.
524
00:36:45.447 --> 00:36:47.708
Six weeks later, why do you have a clipboard?
525
00:36:48.069 --> 00:36:48.529
What's going on?
526
00:36:49.858 --> 00:36:50.739
We have to build for that.
527
00:36:50.779 --> 00:36:55.383
Look, we know the executives and the investors, and they were going to buy the flashy.
528
00:36:55.503 --> 00:36:56.804
And honestly, I was guilty of this.
529
00:36:57.405 --> 00:37:04.711
I was working with the CEO, and we were building this product at first, and the only people we were talking to were the people that he wanted to sell to.
530
00:37:05.011 --> 00:37:05.692
They were his buddies.
531
00:37:05.732 --> 00:37:06.412
They were his friends.
532
00:37:06.753 --> 00:37:07.633
We were building it for them.
533
00:37:08.274 --> 00:37:08.794
And it was...
534
00:37:10.010 --> 00:37:10.991
Looks really cool.
535
00:37:11.671 --> 00:37:13.772
Like there's models, you can spin it around.
536
00:37:13.792 --> 00:37:14.973
It's connected to this database.
537
00:37:14.993 --> 00:37:15.773
It's complete blah, blah, blah.
538
00:37:16.014 --> 00:37:16.754
Great, wonderful.
539
00:37:17.714 --> 00:37:25.179
Soon as we started to give it to the field operators, provided training, the friction was there.
540
00:37:25.499 --> 00:37:27.580
The friction was like, look, you've now added a step.
541
00:37:28.421 --> 00:37:29.461
You didn't take a step away.
542
00:37:30.522 --> 00:37:32.343
You just made what I'm doing right now pretty.
543
00:37:34.428 --> 00:37:35.770
I'm going to stop using this.
544
00:37:35.950 --> 00:37:42.978
Or is it structured, connected, and better for the downstream processes in years to come and worth that extra step?
545
00:37:43.038 --> 00:37:43.919
Well, I'm saying it doesn't matter.
546
00:37:43.939 --> 00:37:44.639
But you didn't sell it to them.
547
00:37:45.160 --> 00:37:47.663
Yeah, it's like the executive will buy it.
548
00:37:48.642 --> 00:37:52.383
The field teams get it renewed and renewed and renewed.
549
00:37:52.403 --> 00:37:55.124
The executive, it's going to die in an audit in two years.
550
00:37:55.204 --> 00:37:56.165
It's going to be gone.
551
00:37:56.345 --> 00:37:58.146
And the engagement, it's going to die.
552
00:37:58.406 --> 00:38:01.547
Yeah, so I think we're hitting on a real important topic here.
553
00:38:01.607 --> 00:38:05.708
And it is the topic about we're changing the way we work.
554
00:38:06.089 --> 00:38:10.490
We're creating a digital workflow to replace a manual workflow.
555
00:38:11.050 --> 00:38:12.191
So we have to map that out.
556
00:38:12.611 --> 00:38:14.732
And that means identifying the stakeholders
557
00:38:15.192 --> 00:38:19.556
how they do work today and how they're planning, how we want them to reimagine their work tomorrow.
558
00:38:20.197 --> 00:38:22.419
And to be able to do that across the organization.
559
00:38:22.439 --> 00:38:30.547
So for example, in a maintenance situation, let me break this down for like on the DFW side, we have an issue with identifying problems.
560
00:38:30.747 --> 00:38:36.272
So what is going on with the equipment, which includes telemetry and a rules engine and predictive insights.
561
00:38:36.372 --> 00:38:36.873
Okay, fine.
562
00:38:37.493 --> 00:38:41.258
So now I have a list of insights of what's going on with my equipment.
563
00:38:41.618 --> 00:38:46.744
I'm going to use a visualization to understand how it's connected in a system, a system assistance approach.
564
00:38:47.165 --> 00:38:52.371
I might have some reality capture to understand the physical condition of that asset and physical location.
565
00:38:52.651 --> 00:38:53.632
I need to know where it is.
566
00:38:54.433 --> 00:38:56.154
What that also helps me to do is do better.
567
00:38:56.615 --> 00:38:57.996
Next part of the process is planning.
568
00:38:58.236 --> 00:39:03.440
So a work planning group, their responsibility is to make sure the planning of the work is accurate, complete.
569
00:39:03.460 --> 00:39:07.583
Could be OSHA standards, could be a scissor lift, all of those things that go into proper planning.
570
00:39:07.603 --> 00:39:09.485
There's like nine core steps of a planner.
571
00:39:09.945 --> 00:39:11.446
So the planner needs to have 100% planned work
572
00:39:14.289 --> 00:39:20.594
And we're reducing, again, the work identification, going back and forth to the site to identify and diagnose, do it remotely.
573
00:39:20.934 --> 00:39:24.077
Same with the planner, back and forth, making sure we gather all materials.
574
00:39:24.217 --> 00:39:25.118
And it goes to a scheduler.
575
00:39:25.658 --> 00:39:28.080
So a scheduler can now look at the work in a different way.
576
00:39:28.440 --> 00:39:29.301
I can group work.
577
00:39:29.601 --> 00:39:31.443
I understand there's certain things I can do together.
578
00:39:31.723 --> 00:39:32.544
I can be more efficient.
579
00:39:32.724 --> 00:39:36.447
If I have to have a third-party contractor on site, I'm going to bring them on for an hour or two.
580
00:39:36.967 --> 00:39:38.549
No, I want to bring them on for an eight-hour day.
581
00:39:38.569 --> 00:39:43.613
I'm going to make sure we utilize this work effectively, but I'll understand those conflicts or whether they're going to happen.
582
00:39:44.033 --> 00:39:45.535
So we get better work scheduling.
583
00:39:45.715 --> 00:39:47.416
And then we get into work execution.
584
00:39:47.877 --> 00:39:51.240
So the work execution is another phase, another team that have to go and do the work.
585
00:39:51.260 --> 00:39:52.361
They have the proper plans.
586
00:39:52.721 --> 00:39:53.902
They have good schedules.
587
00:39:53.922 --> 00:39:54.823
They're not interrupted.
588
00:39:55.203 --> 00:39:56.064
They complete the work.
589
00:39:56.644 --> 00:40:00.888
And then you have the last part, which is the QA and the closeout.
590
00:40:01.328 --> 00:40:02.629
So was the work done properly?
591
00:40:03.430 --> 00:40:08.232
So in our case, the first part of rolling out, we had QAs involved.
592
00:40:08.632 --> 00:40:11.493
The QAs were not wanting to do digital twin.
593
00:40:11.513 --> 00:40:12.734
They thought it was going to replace them.
594
00:40:12.754 --> 00:40:13.814
It was a big threat.
595
00:40:14.514 --> 00:40:19.296
But in the past, they'd look at one out of 10, one out of 20 actual job sites.
596
00:40:19.336 --> 00:40:20.777
There's no way they can get to everything.
597
00:40:21.457 --> 00:40:27.219
But now they were able to see the closeout on everything and be able to see the machine behavior.
598
00:40:27.679 --> 00:40:33.342
And the cool thing that we did is when the machine behavior didn't change, it would knock that work order back out.
599
00:40:33.462 --> 00:40:34.862
And now they could say, well, wait a second.
600
00:40:35.582 --> 00:40:36.723
You didn't do this properly.
601
00:40:36.923 --> 00:40:38.504
Or did you do your troubleshooting?
602
00:40:38.524 --> 00:40:39.784
What did you do?
603
00:40:39.864 --> 00:40:41.725
So it enabled them to actually be more
604
00:40:42.345 --> 00:40:47.089
effective, and then also what we started seeing as we started using, it took three months, minimum.
605
00:40:47.109 --> 00:40:49.150
It took a year to get a program really going.
606
00:40:49.250 --> 00:40:51.912
Three months of solid, just like going to the gym, right?
607
00:40:51.932 --> 00:40:55.475
So when you go to the gym, if you don't want to go to the gym, you can't force someone to go to their gym.
608
00:40:55.495 --> 00:41:00.159
So you have to be bought in, so it might be culture, the high level and the management level.
609
00:41:00.699 --> 00:41:02.239
And then someone actually has to want to make change.
610
00:41:02.259 --> 00:41:04.000
You're going to find your champions, right?
611
00:41:04.420 --> 00:41:07.281
But they start going to the gym every day, and they start getting better.
612
00:41:07.301 --> 00:41:10.002
And they say, well, wait, I'm getting healthier.
613
00:41:10.022 --> 00:41:12.002
My company is doing better.
614
00:41:13.042 --> 00:41:15.063
My process is getting better.
615
00:41:15.083 --> 00:41:18.504
So that was really important to institutionalize that.
616
00:41:18.804 --> 00:41:27.747
So change management, mapping the digital processes, understanding the stakeholders and benefits, measuring the KPIs, and seeing that continuous improvement, that is part of the bigger program.
617
00:41:27.767 --> 00:41:28.907
That's the tough part.
618
00:41:29.407 --> 00:41:32.250
But when you can do it, the change is huge.
619
00:41:32.270 --> 00:41:39.236
Like, you know, you look at a program like this, this one site, $150 million in service contracts at 15% wrench time.
620
00:41:39.476 --> 00:41:40.978
Like, it should be 45%.
621
00:41:41.738 --> 00:41:45.041
So your productivity out of your contract is one-third of what it should be.
622
00:41:45.742 --> 00:41:49.085
Plus, you're not getting work done, so things are not getting fixed.
623
00:41:49.165 --> 00:41:52.769
So it means your capital program is suffering.
624
00:41:52.809 --> 00:41:53.670
Things are breaking.
625
00:41:54.070 --> 00:41:57.013
It impacts your operational improvements or your operational downtimes.
626
00:41:57.314 --> 00:42:00.277
So it's a cascading effect of a reactive environment.
627
00:42:00.557 --> 00:42:08.325
And that's one thing with digital twins or reality capture or modeling help us to work virtually and digitally to make improvements.
628
00:42:08.705 --> 00:42:15.910
So that sounds like it only works on your big, using my term again, hero asset of an airport.
629
00:42:16.270 --> 00:42:17.691
This is a big thing.
630
00:42:17.751 --> 00:42:21.814
It's lots of regulations, lots of complexity, lots of safety.
631
00:42:22.355 --> 00:42:30.100
And comparing that to my use case of a school, that there ain't none of that.
632
00:42:30.220 --> 00:42:32.221
And nobody's going to pay for those things.
633
00:42:33.440 --> 00:42:35.062
And it depends on the client, right?
634
00:42:35.202 --> 00:42:38.865
But I'm just thinking out loud on the school.
635
00:42:39.385 --> 00:42:50.774
I think there's some opportunity you know better than all of us put together of what that ROI or to help share what it could be.
636
00:42:51.234 --> 00:42:53.996
I'm just thinking back to the case that you were talking about earlier.
637
00:42:54.777 --> 00:43:07.044
You know, years ago at a large IOC refinery, I think one of the two things that I noticed, one was, you know, what's the buy-in?
638
00:43:07.184 --> 00:43:10.066
You know, this, do you have the right buy-in to get the right stakeholders?
639
00:43:10.827 --> 00:43:11.427
Do you need that?
640
00:43:12.047 --> 00:43:12.588
Yes and no.
641
00:43:13.088 --> 00:43:14.909
Some places you need it, some places you don't.
642
00:43:15.589 --> 00:43:19.632
And what I mean by that is, do you need absolute executive buy-in for that?
643
00:43:20.863 --> 00:43:21.663
it'd be nice to have.
644
00:43:22.484 --> 00:43:29.647
The other piece too is sometimes you can, with the executive buy-in, you could get all the stakeholders, everybody's in harmony, everything works perfect.
645
00:43:29.867 --> 00:43:33.869
And then you pull out your ROI across the board and it works out.
646
00:43:35.230 --> 00:43:39.032
The nice part about the work, I believe, the digital twins that we're doing,
647
00:43:40.137 --> 00:43:41.437
It doesn't have to be an all or nothing.
648
00:43:41.717 --> 00:43:47.239
If you start off like in what we did in this case is, you know, what is the benefit to an engineer to a refinery?
649
00:43:47.719 --> 00:43:50.660
Okay, what is the benefit to a maintenance team?
650
00:43:51.180 --> 00:43:57.821
Just those two stakeholders alone could have the ROI of the whole capture cost to begin with.
651
00:43:58.281 --> 00:44:00.742
And what we found is like in certain projects,
652
00:44:01.282 --> 00:44:05.324
You get a couple of stakeholders on board and then the emergency team says, wait, I want some of that.
653
00:44:05.524 --> 00:44:07.765
And then the fire team says, well, I could benefit of that.
654
00:44:07.785 --> 00:44:13.567
So if there's a fire, I can click on this pipe and know what product it is and know where the shutoff valves are.
655
00:44:13.767 --> 00:44:16.268
And I can know that by having access to it.
656
00:44:16.988 --> 00:44:20.890
So, you know, that's the case, you know, I'm trying to make the point of,
657
00:44:21.730 --> 00:44:26.473
It'd be perfect to have perfect buy-in, and it never always happens.
658
00:44:26.494 --> 00:44:29.416
Yeah, like don't let good get in the way of perfect.
659
00:44:29.576 --> 00:44:32.458
And I think what you're saying, too, is the maturity of this stuff, right?
660
00:44:32.678 --> 00:44:35.480
You can't, you know, day one say everybody uses it.
661
00:44:35.620 --> 00:44:37.762
It is how do you bring them on in layers.
662
00:44:37.862 --> 00:44:40.223
And that goes with the type of data you're capturing, right?
663
00:44:40.243 --> 00:44:43.586
So with schools, I would do a lot of 360 capture.
664
00:44:44.066 --> 00:44:46.428
because I need visualization, baseline visualization.
665
00:44:46.668 --> 00:44:48.029
I don't need to capture everything.
666
00:44:48.049 --> 00:44:49.109
A classroom is a classroom.
667
00:44:49.129 --> 00:44:54.213
You want mechanical rooms, electric rooms, or rooftop units, whatever the user is.
668
00:44:54.553 --> 00:44:57.495
But the added piece might be, like you said, the security.
669
00:44:57.515 --> 00:45:06.901
If there's any hot topic there about, and I don't know if that's possible within the thing, but simulations of, like you said, active shooter, emergency, other things, is there a possibility?
670
00:45:06.921 --> 00:45:09.543
I don't know if active shooter is in the UK, sorry.
671
00:45:09.563 --> 00:45:10.063
That's true.
672
00:45:10.083 --> 00:45:10.684
That's true.
673
00:45:10.704 --> 00:45:11.444
I use knives.
674
00:45:11.504 --> 00:45:12.365
Okay, I'll give you that one.
675
00:45:12.645 --> 00:45:24.448
I'm just well, but you you shared that as an example, though, of of even looking at what you've seen in the U.S. versus what you guys are doing in the U.K.
676
00:45:24.989 --> 00:45:29.490
There are certain requirements now for mapping for emergency response.
677
00:45:30.130 --> 00:45:39.053
And that might be the stepping stone of, OK, well, if we're capturing, if we have to capture for that anyways, then we can start layering in.
678
00:45:39.193 --> 00:45:40.133
Here's what else we can do.
679
00:45:40.153 --> 00:45:50.617
And then you start to upsell and kind of build the program from the ground up, as opposed to there's already executive buy in and budget to do, you know, A to Z for every purpose.
680
00:45:50.637 --> 00:45:51.737
Sometimes you have to build a ROI out.
681
00:45:54.278 --> 00:46:00.602
Indoor maps for emergency response, I think it's 16 or 17 states now have legislated.
682
00:46:00.622 --> 00:46:03.943
And I think about six of them have funded doing that.
683
00:46:04.044 --> 00:46:14.209
But they've set PDF as a standard and you can have a single line drawing just showing where you can go in and where you can go out of the building.
684
00:46:14.890 --> 00:46:18.712
So it's not a particularly high bar, but it's a starting point.
685
00:46:19.432 --> 00:46:20.493
It's a starting point.
686
00:46:21.153 --> 00:46:39.922
In the UK, our Department for Education has gone a lot further than that in stipulating that in order to be a good school in terms of a good responsible body operating schools in terms of how you manage your estate, then BIM...
687
00:46:40.742 --> 00:46:47.484
is required at some point, but they've also created a digital spine down the estate's data.
688
00:46:47.524 --> 00:46:52.725
So they're starting to build a national data set where all of this comes together.
689
00:46:52.745 --> 00:46:58.166
So we don't use the term digital twins with these people because it just frightens them.
690
00:46:58.206 --> 00:46:59.126
It doesn't mean anything.
691
00:46:59.806 --> 00:47:02.767
They are very good data people, and they understand that,
692
00:47:03.347 --> 00:47:08.714
If they can count the number of blocks that they've got and the square meters of all of those blocks, that's a beginning.
693
00:47:08.734 --> 00:47:10.175
They've got a reference for all of those.
694
00:47:10.416 --> 00:47:12.458
They know the number of flaws in all of them.
695
00:47:12.979 --> 00:47:22.029
That's starting to build the spine that all of the other data attaches to and forms the basis of the metadata side of your digital twin.
696
00:47:22.870 --> 00:47:33.113
Well, there was a major fire that happened in the UK eight, nine years ago, where the mandating a BIM for these public biddies came from, I remember.
697
00:47:33.133 --> 00:47:35.113
I remember being interviewed on it when I was at Faro.
698
00:47:35.833 --> 00:47:39.014
And that particular event, I think, changed a lot of the legislation.
699
00:47:39.054 --> 00:47:40.354
We've mandated a BIM since 2016, I think.
700
00:47:42.415 --> 00:47:46.056
Yeah, math kind of works out roughly about that eight years ago, yeah.
701
00:47:46.116 --> 00:47:48.597
So every public building is designed in BIM.
702
00:47:48.697 --> 00:47:52.017
But as we were discussing on this, Mark, that...
703
00:47:52.037 --> 00:47:52.758
So, great.
704
00:47:53.618 --> 00:48:02.100
Incrementally, over the next 50 years, we're going to get BIM of everything, except how many of those do you think have passed into operations?
705
00:48:02.480 --> 00:48:02.680
Yeah.
706
00:48:03.060 --> 00:48:04.921
In schools, I could tell you the exact number.
707
00:48:05.781 --> 00:48:06.441
Can anybody guess?
708
00:48:07.001 --> 00:48:09.602
The 5,000-day work time?
709
00:48:09.662 --> 00:48:10.622
No, it's zero.
710
00:48:10.822 --> 00:48:11.282
Zero.
711
00:48:11.322 --> 00:48:12.782
Zero for those.
712
00:48:12.842 --> 00:48:13.983
There is a process for it.
713
00:48:14.003 --> 00:48:15.203
There is a soft landings process.
714
00:48:15.223 --> 00:48:29.146
We have the RICS stages for building and between stage six and seven from completion to operations, there's a soft landings process of BIM into operations.
715
00:48:29.526 --> 00:48:31.147
And it doesn't go.
716
00:48:32.047 --> 00:48:33.307
Nobody pushes that button.
717
00:48:33.667 --> 00:48:36.268
So we're never going to get there from the ground up.
718
00:48:37.429 --> 00:48:45.794
I think personally part of it is just the culture, at least older generation, are a little clumsy with 3D.
719
00:48:46.415 --> 00:48:50.878
And navigating a BIM model in the past, I mean, software's getting a lot more intuitive.
720
00:48:51.198 --> 00:48:52.839
Things are getting a little easier to work with.
721
00:48:53.200 --> 00:48:56.682
But, I mean, one of the first things I was in was in the forensic market.
722
00:48:56.762 --> 00:48:58.643
Actually, that's where Matt and I met initially.
723
00:48:58.663 --> 00:49:00.365
I built the forensic market out for Faro.
724
00:49:00.945 --> 00:49:05.826
But you had to have a snap 2D view before you do anything and then start to introduce the 3D.
725
00:49:06.206 --> 00:49:07.026
Quartz wouldn't take it.
726
00:49:07.106 --> 00:49:09.947
It was only 2D forever, right?
727
00:49:10.027 --> 00:49:12.307
But it is the familiarity and the comfort level.
728
00:49:12.327 --> 00:49:16.988
But the new generation growing up with 3D data, it becomes very natural.
729
00:49:17.128 --> 00:49:27.609
And just the way data moves quickly and you can navigate quickly, and that whole change is making it user friendly, I think.
730
00:49:27.629 --> 00:49:28.790
And that's a big difference.
731
00:49:28.850 --> 00:49:30.110
If it's not easy to use,
732
00:49:31.070 --> 00:49:34.013
I mean, why would I struggle if I could just go back to my own method?
733
00:49:34.033 --> 00:49:46.226
We've taken our school models, and we have a customer who's written a program in Minecraft that he runs the models through a blender, gives them to the children, and that is their school.
734
00:49:46.367 --> 00:49:46.747
They can...
735
00:49:47.887 --> 00:49:49.088
navigate around their school.
736
00:49:49.208 --> 00:49:50.089
It looks like their school.
737
00:49:50.109 --> 00:49:51.790
They've got their teachers in there.
738
00:49:52.431 --> 00:49:55.793
And they've also got a program of biophilic design.
739
00:49:55.833 --> 00:50:02.338
So you can plant plants, earn points, and with those points, you can modify the building to be more energy efficient.
740
00:50:02.859 --> 00:50:09.984
And then you can push a button to test how energy efficient your new building materials are in your building according to the design of the building.
741
00:50:10.325 --> 00:50:12.686
And then when you're finished, you can blow it all up with TNT.
742
00:50:13.327 --> 00:50:15.168
So I'm going to push back.
743
00:50:15.208 --> 00:50:16.289
Who's that stakeholder for?
744
00:50:17.530 --> 00:50:18.130
That sounds fun.
745
00:50:18.871 --> 00:50:23.112
I'm going to push back against the familiarity thing and the older generations.
746
00:50:23.472 --> 00:50:29.795
I think there's unfamiliarity will fade, and it fades faster with the newer generations, right?
747
00:50:29.815 --> 00:50:30.975
Because it's like, nope, I get it.
748
00:50:30.995 --> 00:50:31.596
I've been doing this.
749
00:50:31.616 --> 00:50:33.476
I've been playing Minecraft since I was four.
750
00:50:34.637 --> 00:50:34.957
Cool.
751
00:50:35.257 --> 00:50:36.477
So they can navigate really quickly.
752
00:50:36.998 --> 00:50:42.360
I still maintain if you are not removing steps from operations,
753
00:50:43.651 --> 00:50:45.573
You might as well not have a software to sell.
754
00:50:46.193 --> 00:50:50.897
Like if you're not actually removing steps, there is no impetus to change for them.
755
00:50:51.337 --> 00:50:54.059
You can train you can train unfamiliarity.
756
00:50:54.759 --> 00:51:02.025
You can't get them to do more steps than what they're currently doing without quietly killing your program.
757
00:51:04.155 --> 00:51:07.457
I mean, the whole purpose is to create efficiencies.
758
00:51:07.557 --> 00:51:10.359
So if you don't create efficiencies, you shouldn't be doing it.
759
00:51:11.139 --> 00:51:19.264
Whether efficiency is safety, whether it is, you know, speed or quality or whatever that might be, you know, we have to buy in as an organization.
760
00:51:19.284 --> 00:51:20.284
But we know this is a bad way.
761
00:51:20.304 --> 00:51:21.525
But this efficiency might only be seen in the C-suite.
762
00:51:21.905 --> 00:51:25.427
then everybody else might not see those efficiencies.
763
00:51:25.787 --> 00:51:26.608
And this is where I come back to.
764
00:51:26.628 --> 00:51:28.049
It's the engagement of these people.
765
00:51:28.069 --> 00:51:28.929
That's what I was saying.
766
00:51:28.949 --> 00:51:30.330
You don't see it.
767
00:51:30.630 --> 00:51:31.291
It's engagement.
768
00:51:31.651 --> 00:51:33.132
But you've got to have those conversations.
769
00:51:33.192 --> 00:51:36.134
And a lot of what we do is map out how they do.
770
00:51:36.234 --> 00:51:45.139
I just walk in a day of the boots of the person that's doing their job and then connect the dots and say, well, if you did it this way, would that be better?
771
00:51:45.560 --> 00:51:48.722
And that's the whole mapping of the journey of how you work.
772
00:51:49.342 --> 00:51:54.305
And then reengineering that digitally is what's probably one of the most important things.
773
00:51:54.625 --> 00:52:02.249
I think it's done very well with construction in terms of the documentation we're using weekly for coordination and planning and scheduling.
774
00:52:02.709 --> 00:52:03.870
I mean, it's become a staple.
775
00:52:04.150 --> 00:52:05.651
It really has over the last 10 years.
776
00:52:05.671 --> 00:52:12.855
I remember the first time, it was just an allergy to taking too many pictures to the point where it's like, well, I can see my whole job site at the end of the day.
777
00:52:13.535 --> 00:52:22.242
I mean, so I think you see opportunities, Barrett, but you have to re-engineer the expectations of what people do or doing with, or what they're doing with the data.
778
00:52:22.462 --> 00:52:23.883
Well, and what's fun is- But I hear what you're saying.
779
00:52:23.943 --> 00:52:27.566
Well, what I was going to say is that you can actually design those things.
780
00:52:27.666 --> 00:52:27.886
Sure.
781
00:52:28.227 --> 00:52:30.508
In, you could design them, have those conversations.
782
00:52:30.548 --> 00:52:31.869
We have conversations with our field crews.
783
00:52:32.270 --> 00:52:33.090
Yeah.
784
00:52:33.270 --> 00:52:34.251
Would this be easier?
785
00:52:34.591 --> 00:52:38.595
Yeah, man, right now we're printing PDFs and we're literally drawing on them and then we're scanning them after them.
786
00:52:38.615 --> 00:52:41.277
Like, wow, that sounds absolutely garbage.
787
00:52:41.577 --> 00:52:41.697
Yeah.
788
00:52:41.757 --> 00:52:42.718
Let's not do that anymore.
789
00:52:42.858 --> 00:52:44.059
Would it make it easier if you did this?
790
00:52:45.560 --> 00:52:47.401
But for them, the model is invisible.
791
00:52:48.061 --> 00:52:50.343
It's being built and they don't even know it.
792
00:52:50.423 --> 00:52:58.869
It doesn't matter to them because what it has now done is now tied that C-suite efficiency to their day-to-day.
793
00:52:59.487 --> 00:53:01.448
You know, sometimes there's just obstacles.
794
00:53:01.468 --> 00:53:04.549
You just have no idea they're obstacles until you get in the field.
795
00:53:04.729 --> 00:53:05.590
You know, connectivity.
796
00:53:06.150 --> 00:53:07.110
That's a big one, right?
797
00:53:07.130 --> 00:53:07.931
You can't just anticipate.
798
00:53:07.951 --> 00:53:08.631
Everyone's going to use it.
799
00:53:08.651 --> 00:53:11.552
You get out there and your tablet doesn't work because there's no connectivity.
800
00:53:11.592 --> 00:53:13.193
Like, that's a problem we can afford.
801
00:53:13.413 --> 00:53:13.673
Right?
802
00:53:13.753 --> 00:53:17.134
You know, even like the sun reflecting off on an iPad can't see it.
803
00:53:17.414 --> 00:53:18.195
It's a pain in the end.
804
00:53:18.275 --> 00:53:19.315
I don't want to use it, right?
805
00:53:19.916 --> 00:53:20.856
We had language issues.
806
00:53:21.116 --> 00:53:28.524
Actually, a lot of the maintenance people were Arabic, and they didn't, you know, okay, well, I understand why they print things, and they're writing on work orders.
807
00:53:28.904 --> 00:53:32.648
So, like, that's why it's so important to really truly understand what that...
808
00:53:33.442 --> 00:53:39.766
that day in a life is before you can design and implement something that's gonna truly change that way of working.
809
00:53:39.846 --> 00:53:40.927
How does that, question?
810
00:53:41.267 --> 00:53:54.195
Jeremy, back to you mentioning, you get it all the way to the point that BIM is, BIM is a requirement, right, in the UK, and it's supposed to hand off to facilities?
811
00:53:55.095 --> 00:53:58.898
It's supposed to, but nobody's ever mandated that that should happen.
812
00:53:58.998 --> 00:54:00.319
That part is not mandated.
813
00:54:00.500 --> 00:54:00.660
No.
814
00:54:00.860 --> 00:54:02.221
But it's suggested?
815
00:54:03.702 --> 00:54:05.304
It's implied.
816
00:54:05.324 --> 00:54:06.004
Yes, it is.
817
00:54:06.224 --> 00:54:06.905
Okay.
818
00:54:07.065 --> 00:54:12.529
What, from your perspective with what you've seen over there, why do you think it hasn't gone any further?
819
00:54:14.030 --> 00:54:19.373
I think it's the appreciating the big picture of why it's there and what you're going to do with it.
820
00:54:19.793 --> 00:54:30.499
And it comes back to the engagement argument that I keep coming back to, that the people on the site, their job is to keep that site safe and warm.
821
00:54:31.059 --> 00:54:32.880
And that's what they do.
822
00:54:33.080 --> 00:54:35.621
So do the doors lock?
823
00:54:35.701 --> 00:54:36.742
Do the toilets flush?
824
00:54:37.462 --> 00:54:38.784
and is the heating on?
825
00:54:39.324 --> 00:54:41.467
And... Are the paper towels the right way?
826
00:54:41.607 --> 00:54:43.109
Are the paper towels the right way?
827
00:54:43.129 --> 00:54:43.650
Yes, which...
828
00:54:44.210 --> 00:54:45.352
Sorry, another inside joke.
829
00:54:45.472 --> 00:54:47.054
It's a UK thing, is it?
830
00:54:48.255 --> 00:54:49.036
Don't get me started.
831
00:54:52.500 --> 00:54:53.241
But it's...
832
00:54:53.261 --> 00:54:55.504
So those people are not...
833
00:54:56.405 --> 00:55:10.351
pointed towards the efficiency of seeing the model and understanding it, it's much higher than them in the C-suite where the people who can see the requirement are there, but they're failing to get it down to the right person.
834
00:55:10.371 --> 00:55:18.074
And we've got a real problem of, we need to upskill all of our people who are working with this data and
835
00:55:18.374 --> 00:55:24.019
Well, I don't even know if it's a skill as much as an appreciation for change management.
836
00:55:24.140 --> 00:55:31.467
It is appreciation to sit with someone and give them the time and to have the patience to walk them through.
837
00:55:31.527 --> 00:55:35.691
Like, you know, when we were doing our Monday, Wednesday, Friday meetings, every day we instituted it.
838
00:55:35.971 --> 00:55:37.713
Actually started with five and we went down to three days.
839
00:55:38.313 --> 00:55:42.417
And we have people that were just didn't want to be there, you know, people that were really nervous about it.
840
00:55:42.817 --> 00:55:43.978
But we repeat the process.
841
00:55:44.098 --> 00:55:46.481
And don't try to train the whole system.
842
00:55:47.041 --> 00:55:47.882
Pick one thing.
843
00:55:48.262 --> 00:55:53.167
Pick one thing that the tool will do for you every day that you can just learn.
844
00:55:53.227 --> 00:55:54.989
It's just like anything if you're learning habits.
845
00:55:55.449 --> 00:55:56.150
And it grew.
846
00:55:56.230 --> 00:55:59.273
And I tell you, like, it was really fun to watch.
847
00:55:59.833 --> 00:56:02.515
Like there's over 350 people that use that tool every day now.
848
00:56:03.056 --> 00:56:05.878
And it's like, it just took one thing that you look at each day.
849
00:56:05.918 --> 00:56:06.559
This is not hard.
850
00:56:06.799 --> 00:56:08.340
We'll go in 20 minutes, 30 minutes.
851
00:56:08.360 --> 00:56:09.301
Let's check these things.
852
00:56:09.361 --> 00:56:09.902
Okay, great.
853
00:56:10.342 --> 00:56:14.366
But then it became a learning environment because you have experienced people, you have junior people.
854
00:56:14.666 --> 00:56:17.068
We're all virtually looking to problem solve, right?
855
00:56:17.648 --> 00:56:19.890
And that learning environment was wonderful.
856
00:56:19.930 --> 00:56:22.032
And, you know, the process wasn't so intimidating.
857
00:56:22.052 --> 00:56:23.573
It was like, click one, two, three.
858
00:56:23.613 --> 00:56:25.175
Well, that's actually pretty easy, right?
859
00:56:25.535 --> 00:56:33.320
So then people started, you know, we would have the junior people now start to use the tool in the conversation and allow them to solve the problems.
860
00:56:33.760 --> 00:56:37.002
You know, and then they would start using it on their own time, come back with solutions.
861
00:56:37.022 --> 00:56:39.104
It grew, but you have to build that culture.
862
00:56:39.144 --> 00:56:40.305
It is change management.
863
00:56:40.325 --> 00:56:43.427
It's so often just not, it's implied.
864
00:56:43.527 --> 00:56:44.167
Okay, we have it.
865
00:56:44.247 --> 00:56:44.787
There you go.
866
00:56:44.807 --> 00:56:45.108
Use it.
867
00:56:45.608 --> 00:56:47.089
I don't know what to do with it.
868
00:56:47.109 --> 00:56:48.329
What are you talking about?
869
00:56:48.349 --> 00:56:49.170
I don't even know how to open it.
870
00:56:49.190 --> 00:56:50.250
What's my password?
871
00:56:51.091 --> 00:56:55.833
There's this anticipation that people are just going to inherently just pick it up and do it.
872
00:56:55.873 --> 00:56:56.833
There's a lot more work.
873
00:56:57.294 --> 00:57:01.836
I think we're hoping the next generation will because the kids have grown up with the devices.
874
00:57:02.216 --> 00:57:07.499
We're hoping they will, but we are just hoping, aren't we?
875
00:57:07.599 --> 00:57:08.999
What are you going to do with it and why?
876
00:57:09.199 --> 00:57:12.541
Do you feel like the technology is at the point that...
877
00:57:14.697 --> 00:57:17.199
I feel like there's still a lot of challenges throughout.
878
00:57:17.319 --> 00:57:34.692
You know, if you're starting from scratch with a whole digital twin program of capturing and then modeling and then what platform data will be hosted in and if they're linking data or live information or is there anywhere in the technology stack that is still a bottleneck to more organizations?
879
00:57:34.712 --> 00:57:35.973
Yeah.
880
00:57:37.174 --> 00:57:38.755
going kind of for a full program?
881
00:57:38.916 --> 00:57:41.378
And understanding your fidelity and frequency, number one.
882
00:57:41.558 --> 00:57:43.800
Like, what do you really need for the use case?
883
00:57:43.940 --> 00:57:50.125
And I think in operations, a lot of time, it is not the highly accurate assets.
884
00:57:50.165 --> 00:57:53.088
In your case, it is because you have an inspection process.
885
00:57:53.548 --> 00:57:57.251
But a basic visualization, like you're talking about, I need mapping and wayfinding.
886
00:57:57.291 --> 00:58:01.335
I need to know some basic elements or from an emergency planning perspective.
887
00:58:01.375 --> 00:58:01.575
Yeah.
888
00:58:01.915 --> 00:58:03.136
So I think that's number one.
889
00:58:03.176 --> 00:58:04.997
Number two is, like, look at what data you have.
890
00:58:05.417 --> 00:58:06.238
What can be purposed?
891
00:58:06.278 --> 00:58:10.841
Don't let perfection be in the road of good, right?
892
00:58:10.861 --> 00:58:16.545
So like at DFW, we had a bunch of BIM models, but it was like a $2 million project per terminal.
893
00:58:16.565 --> 00:58:18.886
It's like, well, that's a pretty heavy investment.
894
00:58:19.767 --> 00:58:21.589
Should we do that right now or should we defer that?
895
00:58:21.649 --> 00:58:22.650
We have plans.
896
00:58:22.670 --> 00:58:23.431
We have GIS.
897
00:58:23.491 --> 00:58:24.372
We have other data.
898
00:58:25.172 --> 00:58:27.675
The telemetry data was important because we needed insight.
899
00:58:27.755 --> 00:58:31.759
So start with what you had and scale it and get to value quick.
900
00:58:31.999 --> 00:58:33.541
That's the key is get to value quick.
901
00:58:33.621 --> 00:58:39.667
Find a problem that is solvable in a short amount of time with a minimum investment that has a high impact.
902
00:58:40.367 --> 00:58:42.490
Get buy-in and then start to grow.
903
00:58:43.931 --> 00:58:44.811
Yeah, you go ahead.
904
00:58:44.851 --> 00:58:51.596
No, no, just thinking out loud and like in other industries and other verticals, one thing that I've found and everybody has their own thing that works for them.
905
00:58:52.497 --> 00:58:58.421
One thing I found is like, you know, getting a champion because because like, you know, we talk about inspections.
906
00:58:58.521 --> 00:59:00.903
We do, you know, you might inspect in all states.
907
00:59:01.768 --> 00:59:03.829
and then you go to this one that really needs it.
908
00:59:04.489 --> 00:59:08.611
But if you don't have a champion that wants to use it, has no passion, not interested, guess what happens?
909
00:59:09.111 --> 00:59:09.772
It's not happening.
910
00:59:10.312 --> 00:59:18.756
So you go to another area that you get somebody passionate that wants to do it, you get that champion on board, and then you could, I call it handholding,
911
00:59:19.436 --> 00:59:21.698
that, you know, because they're interested and you bring it.
912
00:59:21.998 --> 00:59:23.880
And then I need handholding on stuff I don't know.
913
00:59:24.020 --> 00:59:25.261
I don't think that's a bad term.
914
00:59:25.641 --> 00:59:27.382
Stuff I don't know, show me.
915
00:59:27.462 --> 00:59:28.083
I want to learn.
916
00:59:28.403 --> 00:59:30.565
And if you know better, bring me along to do that.
917
00:59:30.985 --> 00:59:39.592
So, you know, one of the things that we found was like getting a champion that wants to take it and share with it.
918
00:59:39.612 --> 00:59:43.475
I'm just thinking back to your case where if it's zero, if you had –
919
00:59:44.235 --> 00:59:46.896
a champion to say, I'm going to, you know, might cost you time.
920
00:59:46.916 --> 00:59:53.579
You might think, well, that technically that's not free work, but you know, this, this is a paid service.
921
00:59:54.160 --> 01:00:04.244
But if you get one champion and I don't know how you identify it and that person takes it on and the other person that sees the value, like, man, they're not going to outdo me.
922
01:00:04.664 --> 01:00:05.905
I'm going to, I want some of that too.
923
01:00:05.965 --> 01:00:09.867
I mean, so is there a possibility to, to walk it potentially?
924
01:00:10.247 --> 01:00:23.233
I think a really interesting example from the oil and gas space, so when I had my reality capture company, we tried deliberately to use low-cost, fast methods to capture large capture sites, or things that you had very limited time.
925
01:00:23.894 --> 01:00:25.955
Oil tanks were a use case for us.
926
01:00:26.495 --> 01:00:37.770
where we set up a process where we are helping the blue collar worker wear that hard hat and to get inside the tank where it's dark and using lighting configurations that we set up so they could capture the tank.
927
01:00:37.810 --> 01:00:40.714
And we got it down to maybe half hour, 45 minutes.
928
01:00:40.734 --> 01:00:42.836
They're able to do the top, the inside, the exterior.
929
01:00:42.856 --> 01:00:43.377
Yeah.
930
01:00:43.537 --> 01:00:52.501
upload it to, we were using Cupix at the time, and now the guys in Marathon could visually see and see all the chalk lines and everything.
931
01:00:52.521 --> 01:00:57.543
And we broke it down into six steps where they're going to use the visualization and how they're using it.
932
01:00:58.043 --> 01:01:05.686
But that guy in the field in his truck knew that he could call me when he's in the field and something happened and he needs it fixed now.
933
01:01:06.287 --> 01:01:08.848
It was a partnership and a relationship that...
934
01:01:09.868 --> 01:01:11.129
he would be successful with it.
935
01:01:11.269 --> 01:01:13.431
And those champions, like you said, were really critical.
936
01:01:13.831 --> 01:01:16.113
There are thousands of tanks now being done this method.
937
01:01:16.293 --> 01:01:20.876
And it was a really cool use case that we built that spread.
938
01:01:21.196 --> 01:01:24.618
And it was QI2 Elements, I think, was our customer.
939
01:01:24.699 --> 01:01:26.240
And they had, like, all the oil majors.
940
01:01:26.260 --> 01:01:27.480
They were bought by Baker Hughes.
941
01:01:27.961 --> 01:01:29.102
But, you know, it was a simple...
942
01:01:29.842 --> 01:01:32.543
visualization use case that we were able to solve.
943
01:01:33.083 --> 01:01:40.666
But we had to map out, you know, the cleaning, the post-cleaning, you know, it was used, and they do two or three captures, right?
944
01:01:41.046 --> 01:01:46.068
It wasn't a difficult process, but it sure saved a lot of time and effort.
945
01:01:46.188 --> 01:01:50.350
I'm going to take it down a slightly different road, because I'm going to answer your bottleneck question with
946
01:01:51.434 --> 01:01:55.875
This is the bottleneck that has been in the remote sensing industry for 30 years.
947
01:01:56.335 --> 01:02:01.157
And it's now it's ballooning into every industry is, yes, I can capture all this data.
948
01:02:02.257 --> 01:02:03.718
Some of this is pretty heavy.
949
01:02:04.658 --> 01:02:12.360
So getting it somewhere, getting it to the next level is something that is going to continue to be an issue at scale.
950
01:02:13.061 --> 01:02:15.621
I mean, you guys have, what, 90 pilots that are doing it.
951
01:02:15.681 --> 01:02:17.482
I mean, it's a big lift.
952
01:02:17.522 --> 01:02:20.183
We have 250 crews out collecting drone data.
953
01:02:21.303 --> 01:02:23.246
It's a big list and they're out in the middle of nowhere.
954
01:02:23.266 --> 01:02:24.187
What are they using?
955
01:02:24.207 --> 01:02:24.808
Hotel Wi-Fi?
956
01:02:25.208 --> 01:02:27.751
Like, so it's but it's not just that piece.
957
01:02:27.951 --> 01:02:31.316
Then it's all of the integrations that we want to do.
958
01:02:31.656 --> 01:02:34.239
Okay, well, that API key will not expire that did this.
959
01:02:34.339 --> 01:02:34.840
Oh, this user.
960
01:02:34.860 --> 01:02:36.702
I mean, there's a lot to it.
961
01:02:37.343 --> 01:02:50.866
So the thing that's interesting that I think is a very cool opportunity going forward, and this came up many times last week, and this is why fiber is going so crazy in this country right now, is analytics.
962
01:02:51.086 --> 01:02:52.707
Push the analytic to the data.
963
01:02:52.847 --> 01:02:53.527
Not the other way around.
964
01:02:54.167 --> 01:02:56.368
Is how much can we do on the edge?
965
01:02:56.408 --> 01:02:59.669
Because if this is like big data, which is a lot of people do.
966
01:02:59.689 --> 01:03:00.889
I mean, Google has BigQuery.
967
01:03:00.929 --> 01:03:02.109
I mean, it's big.
968
01:03:02.129 --> 01:03:02.609
This is big.
969
01:03:02.629 --> 01:03:03.009
It's heavy.
970
01:03:03.750 --> 01:03:04.490
It's a bottleneck.
971
01:03:05.270 --> 01:03:12.397
How much can we actually push to the edge to be able to even just filter the amount of information that's coming?
972
01:03:12.778 --> 01:03:18.023
The thing that's interesting, like I worked on a project not that long ago that we captured a LiDAR scan.
973
01:03:18.043 --> 01:03:19.004
It was a large area.
974
01:03:19.124 --> 01:03:21.627
And interestingly enough, the only deliverable was a CSV.
975
01:03:21.647 --> 01:03:21.967
CSV.
976
01:03:23.377 --> 01:03:25.258
But sometimes you give them what they want.
977
01:03:25.358 --> 01:03:26.199
You don't push it.
978
01:03:26.279 --> 01:03:28.260
Like one of the things, exactly that.
979
01:03:28.320 --> 01:03:31.382
So you go capture this amazing data that we got.
980
01:03:31.642 --> 01:03:32.403
We learn our lesson.
981
01:03:33.003 --> 01:03:34.504
We've captured some aging data.
982
01:03:34.704 --> 01:03:38.826
And we're like, we're going to give you, you want the CSV, but we'll give you just a little bit more love.
983
01:03:39.427 --> 01:03:40.528
And they're like, I don't want that.
984
01:03:40.548 --> 01:03:41.328
I want the CSV.
985
01:03:41.348 --> 01:03:45.911
So what we do is we'll do the CSV and give you that and show this.
986
01:03:45.931 --> 01:03:46.551
And like, what's that?
987
01:03:46.751 --> 01:03:47.692
Like, well, we caught this.
988
01:03:47.872 --> 01:03:48.632
We captured this too.
989
01:03:48.652 --> 01:03:49.593
And like, yeah.
990
01:03:49.713 --> 01:03:52.135
And then something else comes up, and I'll give an example.
991
01:03:52.175 --> 01:03:54.536
We do a lot of these rail yards, rail surveys.
992
01:03:54.636 --> 01:03:55.937
All they want is CSVs.
993
01:03:56.457 --> 01:03:59.799
So you go out and you capture that, and then they give a call.
994
01:03:59.819 --> 01:04:00.960
Well, I need two more points.
995
01:04:00.980 --> 01:04:02.301
I'm like, sweet.
996
01:04:02.421 --> 01:04:03.582
And you send it to them in 30 minutes.
997
01:04:03.602 --> 01:04:05.063
Well, you don't have to go back in the field.
998
01:04:05.263 --> 01:04:05.503
No.
999
01:04:06.003 --> 01:04:06.724
We pull that out.
1000
01:04:07.064 --> 01:04:07.444
Show me.
1001
01:04:08.084 --> 01:04:08.825
Then you show it.
1002
01:04:08.845 --> 01:04:13.308
So I think it's one of those things where you give them what they need.
1003
01:04:13.368 --> 01:04:17.090
But you show them the value as well, I think.
1004
01:04:17.890 --> 01:04:28.373
I think it's also why, and I think this is interesting around when we were talking about digital twin as a topic for this conversation, right?
1005
01:04:29.053 --> 01:04:46.297
And I think most people in the industry, at least from my perspective, when they think of digital twin, they are thinking of examples, Kelly, like you have been involved in of a whole airport program and linking all this data and using it for facilities management.
1006
01:04:47.617 --> 01:05:04.431
And I think those big scenarios are the rarity still where all these things we're talking about now, they are using the same types of technologies to solve specific problems, usually on a project by project basis.
1007
01:05:04.471 --> 01:05:15.120
Like there's so much of that happening across every industry using, you know, using different scanner tools or drone tools or survey tools to extract information.
1008
01:05:15.440 --> 01:05:18.441
CSV files or CAD drawings or floor plans or models.
1009
01:05:20.681 --> 01:05:34.904
And I guess even from just the terminology again of digital twin, it's like, I think that's why from an industry perspective, the term digital twin is still confusing of when everybody starts using it to say, okay, I scanned this and gave you a point cloud.
1010
01:05:34.924 --> 01:05:35.584
That's a digital twin delivery.
1011
01:05:35.604 --> 01:05:42.745
Or I, or, or, or, or, or, or, or, or, or, or, or, or, or, or, or, or, or, or, or, or, or, or, or, or, or, or, or, or, or, or, or, or, or, or, or, or, or, or, or, or, or, or, or, or, or, or, or, or, or, or, or, or, or, or, or, or, or, or, or, or, or, or, or, or, or, or, or, or
1012
01:05:43.305 --> 01:05:48.850
Or I've linked every live system to this BIM model that was, you know, QC'd with scan data.
1013
01:05:48.950 --> 01:05:49.991
That's a digital twin.
1014
01:05:50.111 --> 01:05:52.073
You can call it 1LS is connected.
1015
01:05:52.653 --> 01:05:53.033
Yeah.
1016
01:05:53.434 --> 01:05:59.199
So I think if we boil back to the topic of this conversation.
1017
01:06:00.867 --> 01:06:08.151
Let's even just now with the amount of conversation we've had, let's redefine digital twin.
1018
01:06:08.812 --> 01:06:16.056
Is it that all of this is a level of digital twin work, that it's a visual twin, a not connected digital twin?
1019
01:06:16.176 --> 01:06:22.000
Or is that term really saved for the higher maturity level of this work?
1020
01:06:23.040 --> 01:06:26.561
I think so, to be honest, because I've been through the pain of this.
1021
01:06:27.181 --> 01:06:28.942
Everyone wants to redefine words.
1022
01:06:28.962 --> 01:06:30.202
I like that term.
1023
01:06:30.542 --> 01:06:32.943
I remember, okay, let's just step back to reality capture.
1024
01:06:32.963 --> 01:06:34.243
Do you remember when that term came out?
1025
01:06:34.724 --> 01:06:36.384
I don't remember when, but I remember watching it.
1026
01:06:36.404 --> 01:06:38.605
I was starting at Farrow, and we're like doing LiDAR.
1027
01:06:38.625 --> 01:06:39.945
I was like, what is reality capture?
1028
01:06:39.965 --> 01:06:42.846
We're not... No, we're LiDAR.
1029
01:06:42.986 --> 01:06:44.246
We're not photogrammetry.
1030
01:06:44.266 --> 01:06:45.207
Who are these...
1031
01:06:45.407 --> 01:06:46.827
I don't want to be in the same bucket there.
1032
01:06:47.367 --> 01:06:50.008
But I mean, I think there's been a lot of redefining words over time.
1033
01:06:50.668 --> 01:06:55.231
You know what a level of accuracy is or you know what a level of detail is.
1034
01:06:55.511 --> 01:06:57.313
And they have meaning.
1035
01:06:57.513 --> 01:06:59.935
If you try to take that and try to invent it for something else...
1036
01:07:01.132 --> 01:07:02.853
I mean, visualization is okay.
1037
01:07:03.853 --> 01:07:05.453
Reality capture is okay for certain things.
1038
01:07:05.653 --> 01:07:06.694
The models are okay.
1039
01:07:07.194 --> 01:07:14.176
So I think that we need to have some conditions on what it is, otherwise we don't know what it is.
1040
01:07:14.256 --> 01:07:15.016
Nobody knows what it is.
1041
01:07:15.056 --> 01:07:16.817
No, that's fair, but if you take a look at AI.
1042
01:07:17.157 --> 01:07:26.740
So AI, you have, I mean, just as an example, you got deep learning, you got machine learning, and if you really break AI apart, there's some sub-components of it that are there.
1043
01:07:26.820 --> 01:07:29.101
And that's why we're like, when we talk about like the digital twin,
1044
01:07:29.821 --> 01:07:31.129
you know, that
1045
01:07:32.068 --> 01:07:37.891
The maturity levels, I think you have level zero to five and in between there, but fit for purpose.
1046
01:07:38.271 --> 01:07:43.254
Like for instance, if I just do a capture of something and it's not really tied to survey, it's not tied to control.
1047
01:07:43.274 --> 01:07:55.400
I mean, anytime we do a digital twin of a vertical asset that we're gonna do AI and have to run, where we're at now in the industry, which is pretty sweet, is you can do an asset now.
1048
01:07:56.200 --> 01:07:59.222
And five years ago, we just highlighted the cracks.
1049
01:07:59.997 --> 01:08:06.905
Now we can put the digital twin all the way together and then not only highlight it, but draw it in 3D.
1050
01:08:06.945 --> 01:08:18.459
So if I have a state plane NAT83 project in Louisiana South or something, and I have it tied to control, because we said survey control and I have LiDAR,
1051
01:08:19.572 --> 01:08:30.437
and I have a hundred plus tall asset, and I pull points from there, because what happens, what we found, is if you have just ground control points on a tall asset, your top will shift.
1052
01:08:30.778 --> 01:08:35.180
Well, then that's not true model, so it has to be tied to control and everything else,
1053
01:08:36.416 --> 01:08:41.682
and you run the AI and you can draw it, now you can deliver that quickly onto your CAD asset.
1054
01:08:41.722 --> 01:08:51.452
But I think depending on the value that you can derive from it, like a digital, it's a mirror of an asset that you can derive value immediately from.
1055
01:08:52.033 --> 01:08:57.939
If I just went out and did it just willy-nilly, just created something and it's off,
1056
01:08:58.600 --> 01:09:02.562
Can I really derive the value that and get planometrics from truly?
1057
01:09:02.943 --> 01:09:03.403
Not really.
1058
01:09:04.183 --> 01:09:06.285
It has to be really done a certain way.
1059
01:09:06.925 --> 01:09:11.148
So I think on the different levels, it's the value component of it.
1060
01:09:11.188 --> 01:09:12.608
Can you pull the value out?
1061
01:09:13.169 --> 01:09:14.830
And then is it time-based?
1062
01:09:14.930 --> 01:09:16.431
Because the other part too is a time-based.
1063
01:09:17.091 --> 01:09:31.630
If you're doing it for the purpose of a baseline to do your inspection, for example, and the intent is to come back in a couple years to have to do it again and to do it in a couple years to do it again, and it's part of your workflow, I'm just thinking about if I get a frequency of every second,
1064
01:09:32.465 --> 01:09:47.773
which is required in certain cases or once a week, or the frequency requirement of this asset is every two years, and I still can do that, I'm still implementing or doing that time-based component for this structure that you can build on.
1065
01:09:48.273 --> 01:09:48.874
So it's...
1066
01:09:50.322 --> 01:09:51.442
It's a tough one.
1067
01:09:51.502 --> 01:09:54.663
I think, you know, because we hear clients too, they're like, you know, I want this.
1068
01:09:55.343 --> 01:09:56.303
And you know, they're calling it.
1069
01:09:56.323 --> 01:09:58.424
And that's another funny thing we joke around about.
1070
01:09:58.444 --> 01:10:03.485
But like if a client says, I'm gonna give you this money to do this component, which is what we're talking about.
1071
01:10:03.885 --> 01:10:05.105
And they call it a digital twin.
1072
01:10:05.125 --> 01:10:07.285
I said, I'm happy to provide this digital twin.
1073
01:10:07.665 --> 01:10:08.866
You know, this is a great idea.
1074
01:10:09.886 --> 01:10:13.467
Versus I heard folks, you know, like, you know, argue with an operator.
1075
01:10:13.487 --> 01:10:14.447
Well, you can't really call that.
1076
01:10:15.007 --> 01:10:15.147
And,
1077
01:10:15.767 --> 01:10:17.848
They just burned themselves, shot themselves in the foot.
1078
01:10:17.888 --> 01:10:23.812
Like that was, you know, you walk the client with it too.
1079
01:10:23.872 --> 01:10:26.514
So it's, I don't know.
1080
01:10:26.754 --> 01:10:31.317
I think there's maturity levels and that's where I think...
1081
01:10:32.523 --> 01:10:33.623
there's different opinions.
1082
01:10:33.783 --> 01:10:35.424
Yeah.
1083
01:10:35.444 --> 01:10:38.345
Well, we've argued this to death in the Digital Twin Consortium.
1084
01:10:38.385 --> 01:10:40.585
I'm on the Mobility Transportation Group.
1085
01:10:40.605 --> 01:10:41.846
And we built the models.
1086
01:10:42.806 --> 01:10:49.068
And whether it's descriptive, whether it's proactive, predictive, automated, get to full automation.
1087
01:10:49.108 --> 01:10:51.429
So those are levels of maturity.
1088
01:10:51.469 --> 01:10:52.749
But there's certain components.
1089
01:10:52.829 --> 01:10:56.050
And I was at a conference, a Digital Twin conference, last week in Denver.
1090
01:10:56.830 --> 01:11:00.732
And the conversation was, do you need 3D to be a digital twin?
1091
01:11:02.172 --> 01:11:07.819
You've got the whole engineering community there, Arup, and all the others are saying, well, I like my GIS.
1092
01:11:07.859 --> 01:11:08.700
It's a digital twin.
1093
01:11:09.281 --> 01:11:14.707
And that's fine, but you're losing the whole business process of how you look at the world in 3D.
1094
01:11:15.367 --> 01:11:16.949
And I think that you can't take that away.
1095
01:11:16.969 --> 01:11:17.450
Yeah.
1096
01:11:19.752 --> 01:11:24.876
The whole point of looking at things real to life or in 3D give you a different dimension.
1097
01:11:25.617 --> 01:11:26.898
You're not getting that from the map.
1098
01:11:26.958 --> 01:11:28.859
And I mean, I get my ortho images.
1099
01:11:28.879 --> 01:11:30.520
I love them from the drones and all of that.
1100
01:11:31.041 --> 01:11:34.943
But there has to be a boundary of what is considered A or B.
1101
01:11:35.084 --> 01:11:37.325
Otherwise, it's a slippery slope.
1102
01:11:37.345 --> 01:11:39.847
You look at me, he's all like an ortho, like a drone ortho.
1103
01:11:39.867 --> 01:11:41.128
Drone guy, like you're drunk.
1104
01:11:43.488 --> 01:11:45.870
Now the remote sensing guy, way before drones had existed.
1105
01:11:45.990 --> 01:11:47.812
It didn't mean it like that.
1106
01:11:51.435 --> 01:11:52.716
Yeah.
1107
01:11:52.936 --> 01:12:01.324
The path I naturally fell into to start thinking about Digital Twin, again, started in the survey side, then into scanning.
1108
01:12:01.764 --> 01:12:04.767
To me, it was the idea of, you know...
1109
01:12:05.527 --> 01:12:12.332
If we've always been scanning and making CAD models or BIM models, why now call that digital twin?
1110
01:12:12.712 --> 01:12:13.253
Yeah.
1111
01:12:13.473 --> 01:12:14.494
It's always been a thing.
1112
01:12:15.054 --> 01:12:28.724
And actually, Carlos, even to kind of your point, even if we're doing it multiple times and they're getting value out of it, if we've never called that a digital twin in the past, why adopt that term for it now?
1113
01:12:29.124 --> 01:12:30.245
This is just my perspective.
1114
01:12:30.265 --> 01:12:30.585
Yeah.
1115
01:12:30.969 --> 01:12:35.842
When, you know, we when I got started scanning, we were in oil and gas facilities and.
1116
01:12:36.983 --> 01:12:38.364
It was all project-based.
1117
01:12:38.784 --> 01:12:45.267
Nobody was scanning the whole facility and keeping the whole facility updated and having access to it whenever they wanted.
1118
01:12:45.467 --> 01:12:53.550
It was always like, we'd go to this facility and there'd be two different companies there doing different surveys or different scans for different use cases.
1119
01:12:53.990 --> 01:12:58.032
We were scanning the same tank multiple times, different control networks.
1120
01:12:58.072 --> 01:12:59.713
It was like, it was piecemeal work.
1121
01:12:59.773 --> 01:13:03.875
Everybody's doing it for measurement, for a purpose, for a project.
1122
01:13:04.835 --> 01:13:10.357
And my thought as I started hearing the term digital twin, I didn't know what all it meant either.
1123
01:13:10.437 --> 01:13:20.720
But I started envisioning even before hearing that term, like, man, at some point, it just seems like it would make sense that that whole facility would get scanned.
1124
01:13:21.300 --> 01:13:25.721
not all these people at different times, and then it gets thrown away and it's wasted money.
1125
01:13:26.181 --> 01:13:33.503
That client would actually save money if they just did the whole facility and built a program to keep that updated and live.
1126
01:13:33.523 --> 01:13:43.005
So they could, at any point, an engineer, a mechanical engineer, a safety person, they could just get into that data and access true, accurate information
1127
01:13:44.323 --> 01:13:53.451
And then this idea, as I started learning about the operation side or the facilities management side of like, OK, to me, the scan data is not digital twin.
1128
01:13:53.551 --> 01:13:54.892
The model is not digital twin.
1129
01:13:54.952 --> 01:14:01.617
It's really that that like ongoing living true information that's that's used from a front.
1130
01:14:01.637 --> 01:14:03.919
Yeah, from from that data stream.
1131
01:14:05.220 --> 01:14:12.964
It's that program of actually keeping something like that alive and used, not a static model, a static scan, just drone data.
1132
01:14:13.765 --> 01:14:19.468
And even if we're using it for AI to extract, you know, extract cracks or those are all.
1133
01:14:19.968 --> 01:14:23.349
you know, deliverables and value for projects.
1134
01:14:23.369 --> 01:14:24.109
You said it right there.
1135
01:14:24.129 --> 01:14:25.669
You said they're deliverables, right?
1136
01:14:25.710 --> 01:14:28.890
And they're deliverables for a certain purpose or need.
1137
01:14:28.990 --> 01:14:37.713
But when you come back to the twin, it's a unified model of different data sources that can solve various problems, but is updated over time.
1138
01:14:38.373 --> 01:14:41.194
So does it have to solve problems to be?
1139
01:14:41.214 --> 01:14:41.654
Yeah, it has to.
1140
01:14:41.694 --> 01:14:42.794
I think it has to.
1141
01:14:42.934 --> 01:14:43.954
I think it has to.
1142
01:14:43.974 --> 01:14:45.555
I mean, you've got to look at the original term.
1143
01:14:45.575 --> 01:14:46.455
The potential to solve problems.
1144
01:14:47.295 --> 01:14:53.926
The original term came from, you know, using a simulation that you have to do with NASA, right?
1145
01:14:53.946 --> 01:15:01.357
So, like, Michael Grease, when he created the term, they're building digital twins before they put these rockets in space.
1146
01:15:01.397 --> 01:15:01.978
And they have to...
1147
01:15:02.499 --> 01:15:07.722
they have to simulate problems that would be in a spatial environment.
1148
01:15:07.842 --> 01:15:14.865
And so those simulations and understanding spatial, that was the whole point of this term, right?
1149
01:15:14.905 --> 01:15:19.508
So, you know, we're taking it and then we're making it our own in our own environment.
1150
01:15:19.868 --> 01:15:24.050
I think that's fine, but it still needs to match up with some of the core principles.
1151
01:15:24.110 --> 01:15:26.451
Otherwise, the whole term loses its meaning.
1152
01:15:27.052 --> 01:15:28.292
And, yeah, I think it's always...
1153
01:15:30.093 --> 01:15:34.860
It's always easy for us to call it the next new thing, especially from a product perspective.
1154
01:15:35.261 --> 01:15:36.062
No, people are buying.
1155
01:15:36.603 --> 01:15:38.686
I've had literally Willow was digital 20.
1156
01:15:38.906 --> 01:15:40.849
No, no, we're not digital 20.
1157
01:15:41.270 --> 01:15:41.510
We're AI.
1158
01:15:41.530 --> 01:15:41.951
We're this.
1159
01:15:42.051 --> 01:15:45.315
It's like, it's what's term of selling, right, at the time.
1160
01:15:45.355 --> 01:15:46.457
Search engine optimization.
1161
01:15:46.497 --> 01:15:50.961
I literally talked to an executive at an airport and we're talking about, oh, I don't want a digital twin.
1162
01:15:51.221 --> 01:15:52.121
I don't need to see my problem.
1163
01:15:52.141 --> 01:15:53.302
I need to solve a problem.
1164
01:15:53.322 --> 01:15:54.263
So you want a decision problem.
1165
01:15:54.283 --> 01:15:54.884
Yes, I need that.
1166
01:15:54.984 --> 01:15:55.204
Okay.
1167
01:15:55.644 --> 01:15:56.285
Okay.
1168
01:15:56.605 --> 01:15:59.227
Well, I'm like, okay, well, what is your interpretation?
1169
01:15:59.447 --> 01:16:03.670
Like you have this negative interpretation of a twin now being just a visualization tool.
1170
01:16:03.690 --> 01:16:04.771
That's not enough, right?
1171
01:16:05.292 --> 01:16:11.116
So again, it's all about, we have to be careful with words because words have meanings and that gets confusing.
1172
01:16:11.517 --> 01:16:13.058
I've dealt with a lot of confusion.
1173
01:16:13.078 --> 01:16:14.719
I think a lot of us have too, right?
1174
01:16:14.799 --> 01:16:15.820
And it can be frustrating.
1175
01:16:16.000 --> 01:16:20.826
Yeah, I think, you know, so once you start adding in, like, okay, now I'll add a video feed.
1176
01:16:20.846 --> 01:16:24.410
So you have this model and you can derive value.
1177
01:16:24.610 --> 01:16:27.253
It is a deliverable, but it's one that's...
1178
01:16:28.758 --> 01:16:31.119
It's a document that's gonna be built upon.
1179
01:16:31.439 --> 01:16:36.040
And just because of frequency is every two years versus a week, I'm still going back to that.
1180
01:16:36.360 --> 01:16:41.361
But if I start coming in and start adding crack meters, okay, that's live data fed daily.
1181
01:16:41.801 --> 01:16:47.403
I'm doing a video feed, I'm doing a water gauge, all these different things that are component IOT.
1182
01:16:48.423 --> 01:16:49.843
They're just built on top.
1183
01:16:50.284 --> 01:16:57.166
All it's doing is just slapping on to a known location that's on it, and it's a connected sensor.
1184
01:16:57.206 --> 01:17:06.389
So I think just kind of all of those things, going back to deriving value from it, that using it over and over again, it just...
1185
01:17:07.790 --> 01:17:20.377
The difference of it being connected daily versus connected every two year, I think depending on the industry and the asset and the cadence, if the intent is, if you're a one and done, it's just a mirror object reality mesh.
1186
01:17:20.877 --> 01:17:26.080
If you're building it to where you're deriving value from, and I could do it again two weeks from now from another state,
1187
01:17:27.100 --> 01:17:32.084
measure, do some things with the intent to go capture it again and mesh it together and build on it.
1188
01:17:32.624 --> 01:17:35.367
That's, you know, that would be kind of that time base too.
1189
01:17:35.407 --> 01:17:38.649
So I think it depends on the industry and other things you're dealing with.
1190
01:17:38.829 --> 01:17:42.692
Again, your high value, big hero assets.
1191
01:17:43.833 --> 01:17:51.056
That there's a justification for having this level of predictability.
1192
01:17:51.076 --> 01:18:02.322
But when you come back to a simple use case of, it's a building, and what I actually want is a spatial database of the objects within the building.
1193
01:18:02.362 --> 01:18:06.944
I want to know that window, what is its lifespan?
1194
01:18:07.524 --> 01:18:08.785
So where is it on its life cycle?
1195
01:18:10.339 --> 01:18:13.422
Plot it against its bathtub curve in terms of its maintenance cost.
1196
01:18:13.942 --> 01:18:15.123
What's its cleaning schedule?
1197
01:18:15.343 --> 01:18:17.986
What are the maintenance requirements for it?
1198
01:18:18.366 --> 01:18:22.990
And I just want to know that I've got the right data attached to the right window.
1199
01:18:24.492 --> 01:18:28.355
But at some stage, I may wish to do some thermal analysis on my building.
1200
01:18:28.395 --> 01:18:30.877
And so what things should I tackle first?
1201
01:18:30.937 --> 01:18:32.399
So, yeah, we've done solar.
1202
01:18:32.419 --> 01:18:33.640
Yes, we've done LED.
1203
01:18:34.260 --> 01:18:34.781
What's next?
1204
01:18:35.061 --> 01:18:41.164
Because solar and LED are big ticket savings, but your next savings on the fabric are much lower down.
1205
01:18:41.184 --> 01:18:51.329
So we'll do some analysis on the building and figure out whether some thermal cladding on the walls is going to help, whether putting more thermally efficient windows in will help, whether putting some more lagging in the roof will help.
1206
01:18:51.929 --> 01:18:54.030
That we're going to model those things.
1207
01:18:55.090 --> 01:18:56.611
But once we've done it, it's a one and done.
1208
01:18:57.732 --> 01:18:58.572
Is that a digital twin?
1209
01:19:00.059 --> 01:19:11.867
I think the process of what you're doing is you're using the virtual replica to, I don't want to say the word simulate, because you're getting to a decision based on the data that you have.
1210
01:19:12.207 --> 01:19:13.768
You're not using synthetic data, right?
1211
01:19:13.788 --> 01:19:14.328
But we're calculating.
1212
01:19:14.388 --> 01:19:16.149
But you're calculating, right?
1213
01:19:16.169 --> 01:19:19.932
So I think those decisions are really important, and that would be an inherent part.
1214
01:19:20.492 --> 01:19:24.835
We would say you're either forecasting or simulating, but you're making decisions based on the model,
1215
01:19:25.575 --> 01:19:29.219
and based on the information that you've aggregated to make that decision.
1216
01:19:29.239 --> 01:19:30.320
It's a complex ecosystem.
1217
01:19:30.360 --> 01:19:31.321
It's a building.
1218
01:19:31.381 --> 01:19:34.864
All of those bits and pieces are all connected and worked together.
1219
01:19:34.945 --> 01:19:38.328
As long as you're updating your information over time.
1220
01:19:38.508 --> 01:19:39.649
If you only have a static...
1221
01:19:39.669 --> 01:19:40.630
So you have a digital twin.
1222
01:19:41.311 --> 01:19:44.714
Can I upgrade it from digital looky-lakey?
1223
01:19:44.734 --> 01:19:48.458
You have a digital twin, it just may die.
1224
01:19:49.820 --> 01:19:50.120
It may.
1225
01:19:50.261 --> 01:19:53.863
You use it and then you archive it.
1226
01:19:54.243 --> 01:19:58.145
It becomes a record if you're not keen to work with it.
1227
01:19:58.546 --> 01:20:01.888
So I guess, you know, go with a record, because that's a posh way of saying it's gone to die.
1228
01:20:02.348 --> 01:20:03.509
Yes, true.
1229
01:20:03.569 --> 01:20:04.169
Sorry.
1230
01:20:04.309 --> 01:20:05.030
I wanted to use it.
1231
01:20:06.384 --> 01:20:09.105
I think you brought up earlier about like the software.
1232
01:20:09.125 --> 01:20:15.028
So one of the things that we found is, you know, the other critical piece of it is I think things are getting easier.
1233
01:20:16.128 --> 01:20:18.829
And what I mean by that is in the past, this is what happened.
1234
01:20:19.390 --> 01:20:20.230
You go take your...
1235
01:20:21.576 --> 01:20:25.859
you know, drone data, LiDAR data, survey data, bring it into your laptop or desktop.
1236
01:20:26.440 --> 01:20:27.220
You process it.
1237
01:20:27.240 --> 01:20:30.383
You might share it with folks that also need that software.
1238
01:20:30.903 --> 01:20:31.283
Painful.
1239
01:20:32.164 --> 01:20:47.335
Now what we're looking at is like with Bentley, iTwin, and Flex, with Autodesk, with their software and other products, you know, too many to name, you can now take the whole model, the whole replica of...
1240
01:20:48.156 --> 01:20:56.720
in full fidelity and get the full context that's pyramided in performance at the click of a Google Chrome web browser.
1241
01:20:57.280 --> 01:20:58.880
So there's no heavy lifting.
1242
01:20:58.981 --> 01:21:00.081
I could get it from the iPad.
1243
01:21:00.421 --> 01:21:01.422
I could get it from the phone.
1244
01:21:01.922 --> 01:21:09.285
So those heavy lift pieces that were painful before is at an email that you send to somebody with a link.
1245
01:21:09.925 --> 01:21:21.696
And with the link, if you're within a – you have your credentials for it and it's seamless, you can get into it and interact with that model and start making some decisions from the field and stuff like that.
1246
01:21:22.277 --> 01:21:25.960
So back to the point of if your case where you have the building –
1247
01:21:26.881 --> 01:21:46.529
that there's, you know, this is what happens today, but if there's another method where you're putting it online and giving them access if it's secure, and then they start using it and say, hey, we changed this piece, I need you to go update it, or I want to put video feeds on it, and I want to do these other sensors, those are some things that now you're turning it into a living system.
1248
01:21:46.729 --> 01:21:50.333
document because of, you know, new web capability.
1249
01:21:50.593 --> 01:21:53.656
That's not new, but I'm saying like sharing it in a new fashion.
1250
01:21:53.716 --> 01:21:56.839
Can I say it's really fun that we're all like really, really trying to help you.
1251
01:21:57.160 --> 01:21:57.820
We got this.
1252
01:21:58.221 --> 01:21:59.642
We're like, we got this.
1253
01:22:00.723 --> 01:22:04.147
Let's let's help him fix schools.
1254
01:22:04.387 --> 01:22:06.589
We're slide and say it with me.
1255
01:22:06.929 --> 01:22:08.211
And they will bring it to the US.
1256
01:22:08.231 --> 01:22:08.571
I let it.
1257
01:22:09.692 --> 01:22:10.693
See?
1258
01:22:11.494 --> 01:22:16.598
One thing that's interesting is this discussion has been tiptoeing around something that's very fascinating.
1259
01:22:16.618 --> 01:22:22.823
If you've ever worked in, like, a county GIS or a city or a state, what's fascinating— Now, I said GIS.
1260
01:22:22.963 --> 01:22:25.245
I don't know if that's a three-letter word in this conversation, but—
1261
01:22:26.746 --> 01:22:36.895
The thing that's fascinating is if you look at the base layers that they have available, they are updated so constantly by so many different organizations.
1262
01:22:37.315 --> 01:22:38.076
They paid for this.
1263
01:22:38.116 --> 01:22:38.736
They paid for that.
1264
01:22:38.776 --> 01:22:39.617
It's at this resolution.
1265
01:22:39.637 --> 01:22:40.218
It's at this time.
1266
01:22:41.058 --> 01:22:46.183
If you ever, ever, ever want to just see pure almost waste.
1267
01:22:47.268 --> 01:22:51.110
Just take a look at that because it's like, look, it's at that point.
1268
01:22:51.130 --> 01:22:58.313
It's like, OK, yeah, I have twenty nine base maps between two thousand and twenty three and two thousand and twenty six.
1269
01:22:58.893 --> 01:23:00.754
Do you need that many base maps?
1270
01:23:01.514 --> 01:23:02.815
What were they all bought for?
1271
01:23:03.255 --> 01:23:05.676
And do you have any idea or did someone just say?
1272
01:23:06.376 --> 01:23:07.156
You need this.
1273
01:23:07.436 --> 01:23:11.158
You should have gone to the Esri User Conference.
1274
01:23:11.178 --> 01:23:12.318
I've been there many, many times.
1275
01:23:12.338 --> 01:23:19.340
They had an entire hall of the map gallery of just every data layer you could buy.
1276
01:23:20.060 --> 01:23:20.721
I was amazed.
1277
01:23:20.761 --> 01:23:22.021
And then there's a book that goes with it.
1278
01:23:22.041 --> 01:23:22.661
There's a book.
1279
01:23:22.801 --> 01:23:24.802
Oh, no, you need a book.
1280
01:23:25.562 --> 01:23:33.985
The thing that, to tie it back, is the thing that I would say that we as an industry would need to be careful with, with anything related to this topic, is,
1281
01:23:35.192 --> 01:23:37.634
Yes, it needs to be outcome driven.
1282
01:23:37.875 --> 01:23:39.176
Yes, it needs to do this.
1283
01:23:39.216 --> 01:23:41.058
Yes, it needs to have all the things that we've discussed today.
1284
01:23:41.398 --> 01:23:46.002
But it also just needs to be a responsible product that we're generating for our customer.
1285
01:23:46.663 --> 01:23:48.024
And not like, hey, you know what?
1286
01:23:48.104 --> 01:23:55.271
I'm going to go scan all 20,000 of your towers every year for perpetuity because I think it's a cool idea.
1287
01:23:56.212 --> 01:23:58.374
Because there are people that would love to be able to do that.
1288
01:23:58.414 --> 01:24:00.056
That's what Google did with Street View, isn't it?
1289
01:24:01.264 --> 01:24:03.566
It turned out pretty successful, to be honest.
1290
01:24:04.507 --> 01:24:05.808
So, I mean, that's a big show.
1291
01:24:05.868 --> 01:24:07.189
See, there you go.
1292
01:24:07.710 --> 01:24:09.652
Oh, wow.
1293
01:24:09.732 --> 01:24:10.452
Wow, I like that.
1294
01:24:10.472 --> 01:24:11.413
We're going to go ahead and do that?
1295
01:24:11.533 --> 01:24:11.693
Okay.
1296
01:24:12.494 --> 01:24:15.317
Edit, edit.
1297
01:24:18.760 --> 01:24:19.320
There you go.
1298
01:24:19.340 --> 01:24:19.821
Take two.
1299
01:24:19.841 --> 01:24:20.021
Yeah.
1300
01:24:22.108 --> 01:24:24.229
I just the whole conversation.
1301
01:24:24.349 --> 01:24:33.432
It's like I'm getting flashbacks, just flashbacks of that, because there are so many different resources and ways to think about this and people selling it.
1302
01:24:33.472 --> 01:24:41.435
And this is where we need to be careful, because even each individual, just the five of us right here have slightly different definitions of what this is.
1303
01:24:41.895 --> 01:24:45.437
Slightly different standards that we uphold slightly different verbiage that we use.
1304
01:24:46.590 --> 01:24:50.115
I think we as an industry, do we need to standardize it?
1305
01:24:50.816 --> 01:24:59.086
Not necessarily, but I do think we need to communicate its value better of what particular decision it's doing besides just...
1306
01:25:00.181 --> 01:25:15.594
You need this full, super-resolution, crazy technological, you know, digital twin that's going to allow you to do all of these things and hit all these KPIs and your ROI is going to go like this.
1307
01:25:16.635 --> 01:25:21.779
When I'm standing there in the field with an operator who cares about none of that, I'm going to say,
1308
01:25:22.416 --> 01:25:30.819
Yeah, that just wants to be able to get home earlier to their family because they now are no longer having to wait for the printer.
1309
01:25:30.879 --> 01:25:32.139
Maybe I need to go buy some paper.
1310
01:25:32.179 --> 01:25:32.939
Maybe crap.
1311
01:25:32.959 --> 01:25:33.760
My pen's not working.
1312
01:25:33.800 --> 01:25:36.560
I need to get some more pens like all of these things in the field.
1313
01:25:36.841 --> 01:25:42.182
And then, oh, by the way, I still have four hours of work when I get home to be able to digitize all this and then get it up into this thing.
1314
01:25:42.202 --> 01:25:44.083
And oh, man, my Internet just went down.
1315
01:25:45.484 --> 01:25:54.593
I think we all just as an industry need to start to think about how do we make that person's lives easier because they're the ones are actually going to do the work.
1316
01:25:55.113 --> 01:26:01.700
I think a digital twin means nothing if it doesn't produce a go do for someone in the field and it makes their life easier.
1317
01:26:02.381 --> 01:26:03.502
That's just my opinion.
1318
01:26:04.783 --> 01:26:06.004
You think you I think I agree.
1319
01:26:06.184 --> 01:26:07.085
Yeah.
1320
01:26:08.086 --> 01:26:09.728
But I think that.
1321
01:26:10.996 --> 01:26:32.313
This is why I think it's important to drive these conversations, though, is that because the industry is confused and there's terms being used all over the place and there's a desire and a demand growing for these technologies and adoption in different industries and project types, the fact that everyone's kind of all over the place is
1322
01:26:33.342 --> 01:26:41.407
makes it really hard for the industry to actually grow because if that client calls up and says, hey, I'm ready to try to build this program.
1323
01:26:42.047 --> 01:26:56.695
If you call someone who doesn't understand this stuff, then now we're putting in that client's head, well, hey, the only option for a digital twin program they want to build is someone bringing in this low-end camera that doesn't actually solve problems.
1324
01:26:56.775 --> 01:26:58.236
It's just another visualization tool.
1325
01:26:58.416 --> 01:27:01.498
Or, oh, the second guy I called said it's going to be
1326
01:27:02.298 --> 01:27:13.992
$100 million and it has to have all this data, you know, you're going to get a different answer, a different workflow, a different technology, a different capability from every single person you talk to.
1327
01:27:15.219 --> 01:27:22.604
And that's why I think the group conversation, cross industry, cross technology, having these conversations, sharing case studies.
1328
01:27:23.665 --> 01:27:30.649
Yes, at the end of the day, each industry, each client, each owner has different problems to solve.
1329
01:27:31.390 --> 01:27:38.155
And however we piecemeal technology to solve problems for them, if it's valuable to them and they pay for it, that's a successful project.
1330
01:27:38.495 --> 01:27:41.597
A successful service, a successful collaboration with a client.
1331
01:27:43.133 --> 01:27:44.653
So I agree.
1332
01:27:46.034 --> 01:27:50.855
It is driven by the value of each individual opportunity, really.
1333
01:27:51.975 --> 01:28:09.980
But I think it's where the terms and the language we use still becomes important is that when we know confusion is out there, then we need to start sharing that information because even the people that are newer to the space, if they start throwing terms around, then it just causes more confusion.
1334
01:28:10.420 --> 01:28:12.261
The more we can help each other,
1335
01:28:13.221 --> 01:28:24.985
give each other tools to use and like, hey, now after hearing this podcast, the next time I talk to the client about what's possible with data, I have something else completely in my head about the possibilities.
1336
01:28:25.525 --> 01:28:26.786
And this happens.
1337
01:28:27.266 --> 01:28:35.068
Maybe I'll reach out to one of those people I heard on the podcast and get some insights or some ideas or pull them in to help because I've got these schools that...
1338
01:28:38.315 --> 01:28:40.256
We need to solve problems in these schools, you know.
1339
01:28:40.296 --> 01:28:40.597
We do.
1340
01:28:40.917 --> 01:28:41.237
We do.
1341
01:28:41.737 --> 01:28:43.599
We've got to find the answer to it.
1342
01:28:44.119 --> 01:28:52.124
But it's a good base point for you guys and your big assets and your big budgets.
1343
01:28:52.485 --> 01:28:55.507
It's a good base point to look at and see what's the actual value
1344
01:28:56.387 --> 01:28:57.688
in where does this start from?
1345
01:28:58.209 --> 01:28:59.730
What's the simple use case?
1346
01:29:00.351 --> 01:29:03.433
And I think we're at that end of the scale on this.
1347
01:29:04.214 --> 01:29:15.624
But at the same time, we're trying to use some of the same technology, the same ideas, but we're trying to create a simple use case for non-technical users as well.
1348
01:29:16.024 --> 01:29:16.564
People who...
1349
01:29:17.785 --> 01:29:25.428
can't necessarily interpret a technical drawing, but we want them to use three-dimensional data to work with.
1350
01:29:26.048 --> 01:29:38.952
But it's the tools that come into play then, and this is the bit where we can all get excited because we can build nice tools, because I think there will become a point where you point a phone camera at a boiler in a plant room and click on the...
1351
01:29:40.252 --> 01:29:44.157
the boiler, and it will get you all of the management information about that boiler.
1352
01:29:44.577 --> 01:29:48.562
There are three boilers there, and they are boiler one, two, and three.
1353
01:29:49.763 --> 01:29:52.026
Oh, no, did I come in the other door the other day when I named them?
1354
01:29:52.326 --> 01:29:54.268
And they're... Well, two's right, anyway.
1355
01:29:54.849 --> 01:29:55.670
Two's definitely right.
1356
01:29:55.990 --> 01:29:56.411
And it's a...
1357
01:29:56.951 --> 01:29:57.151
So...
1358
01:29:57.792 --> 01:29:59.893
It's the simple use cases like that.
1359
01:29:59.953 --> 01:30:03.735
Can I point my phone camera at a door and say, is this a fire door?
1360
01:30:03.895 --> 01:30:05.736
Is it a one hour or a 30 minute fire door?
1361
01:30:06.516 --> 01:30:08.417
This wall, is that a fire retardant wall?
1362
01:30:08.958 --> 01:30:11.699
What is the compartmentation of this area?
1363
01:30:12.459 --> 01:30:17.622
To, from a simple use case for people to be able to use in dead simple tools,
1364
01:30:18.242 --> 01:30:32.248
And that's where we all get to play with a bit of software development and design and build the tools so that the noddy user, sorry, that probably doesn't translate, but the simple user can work with that data to get the best value out of it.
1365
01:30:32.568 --> 01:30:33.449
And at the same time.
1366
01:30:34.269 --> 01:30:50.454
the man who wants to analyze whether solar panels and batteries are an answer for this building, can play with the model and twist solar panels around and watch the energy use intensity change dynamically as he moves them and creates his array and decides, that's what I want.
1367
01:30:50.994 --> 01:30:57.997
That same data then passes to the man who's fitting them, and he can do all of his working at heights training
1368
01:30:58.937 --> 01:31:06.723
with a headset on, on the ground and safe, hopefully, but safe, using that exact same model, using that exact same data.
1369
01:31:06.944 --> 01:31:10.026
And I think that is a digital twin.
1370
01:31:10.126 --> 01:31:14.310
I agree with what your explanation, I think, is definitely a digital twin.
1371
01:31:14.930 --> 01:31:25.219
You know, what you're talking about is you're unifying different data sources, work management tools, other information that's in other business systems that gives you context, and then you're giving location.
1372
01:31:25.979 --> 01:31:27.400
And that is the key part.
1373
01:31:27.440 --> 01:31:34.426
GIS has done some of this for years where you'd have different layers of information in a spatial mapping capability.
1374
01:31:34.907 --> 01:31:37.429
But, you know, the digital tin brings it a step further.
1375
01:31:38.129 --> 01:31:40.271
And it is about context.
1376
01:31:40.531 --> 01:31:41.933
Humans have... Are you in context?
1377
01:31:41.953 --> 01:31:42.593
Well, look at this.
1378
01:31:42.613 --> 01:31:46.757
Like, as creatures, when we have a business problem, you're usually like, well, let's go take a look at it.
1379
01:31:47.217 --> 01:31:51.518
And when I walk in the door, like, you know, we were looking at your lobby here for the validation study.
1380
01:31:51.998 --> 01:31:53.058
I don't know if that's going to work.
1381
01:31:53.318 --> 01:31:54.058
What's the lighting like?
1382
01:31:54.078 --> 01:31:54.878
What's the ceiling like?
1383
01:31:55.238 --> 01:31:57.959
You know, I didn't know there was a sculpture there, and it had color on it.
1384
01:31:57.979 --> 01:32:01.199
All those little pieces of detail were really important to make that decision.
1385
01:32:01.720 --> 01:32:08.641
So as humans, we need to go and see and look through the same eyes at the problem so we have this common understanding, right?
1386
01:32:08.901 --> 01:32:12.841
But the visualization allows us to do that, which is really cool, and it's exciting.
1387
01:32:13.162 --> 01:32:14.582
But you still need further context.
1388
01:32:14.722 --> 01:32:14.942
Mm-hmm.
1389
01:32:15.602 --> 01:32:15.782
Yeah.
1390
01:32:16.282 --> 01:32:35.906
Well, and one more thing that comes to mind, too, when we again look at different use cases or can we use the same data for many use cases, then we get into the thing that we also talk a lot about, which is the actual nuts and bolts of, well, what gear should we use and what workflow and is control important?
1391
01:32:36.267 --> 01:32:41.968
Are we trying to get within six inches of accuracy or do we need millimeter cracks mapped?
1392
01:32:42.748 --> 01:32:58.836
When we start looking at the deliverables, the use case, the industry, and we really narrow into, well, here's what they want, and this is what's going to be used for across these different business units, then you can start to answer the questions like, well, how do we get there?
1393
01:32:59.397 --> 01:32:59.817
Because...
1394
01:33:01.195 --> 01:33:07.600
That is also a very complex part of the industry that some people say, oh, that's really the easy part now.
1395
01:33:07.680 --> 01:33:09.442
We can just scan it in a day.
1396
01:33:10.002 --> 01:33:16.087
Well, you're like, okay, it's not that easy if you're doing 3 million square feet of an airport turn on.
1397
01:33:16.147 --> 01:33:16.787
It's construction.
1398
01:33:16.827 --> 01:33:19.890
You want it to also be engineering-grade accuracy.
1399
01:33:19.950 --> 01:33:20.230
Oh, yeah.
1400
01:33:20.290 --> 01:33:27.358
And I think you can have different layers of data, but it has to be, disclaimer, you know, like... You have to know it.
1401
01:33:27.439 --> 01:33:34.807
Like the controls analytics at DATW, they didn't want to do any 3D modeling unless it was exactly to this quality.
1402
01:33:34.847 --> 01:33:35.068
Why?
1403
01:33:35.128 --> 01:33:39.293
Because someone's going to pick it up, use it for the wrong purpose, and then you're in trouble.
1404
01:33:39.313 --> 01:33:39.413
Yeah.
1405
01:33:40.394 --> 01:33:46.717
But then it discounts how you could use data from an operational perspective, and it inflates the cost of what I have to do to get a deliverable.
1406
01:33:47.317 --> 01:33:52.799
So how do we take a step back and say, OK, well, we have different layers of data for different purposes.
1407
01:33:53.239 --> 01:33:55.140
We still need to identify that data.
1408
01:33:55.520 --> 01:33:59.502
If it's SLAM or 360 imagery, this is fit for this purpose.
1409
01:33:59.902 --> 01:34:02.803
But I still need my terrestrial for a design or modeling use case.
1410
01:34:03.183 --> 01:34:09.646
So really breaking that down and having what it can and can't be used for is really important.
1411
01:34:09.686 --> 01:34:12.287
Well, and very specifically, write it down.
1412
01:34:12.908 --> 01:34:16.830
Work with your customer to have a written decision tolerance.
1413
01:34:17.410 --> 01:34:20.152
This is what it is, because here's what I've seen happen.
1414
01:34:20.372 --> 01:34:33.339
I've been guilty of this, is I'm going to use the best, you know, RTK, PPK, all the things to be able to get you to, you know, I can, I'm going to fly 20 feet over and I'm going to get this and you're going to see all this crazy detail.
1415
01:34:34.900 --> 01:34:50.850
They're implicitly thinking and assuming, they're assuming, everyone knows what happens when you assume, they're assuming that they're gonna be able to do all of these things, because they're imagineering all of these things and what's real and what's make-believe, then get blurred.
1416
01:34:51.690 --> 01:34:58.632
If you write down in advance like you have a good enough working knowledge, you've been out with them in the field and you say, hey, we're going to write this down.
1417
01:34:58.732 --> 01:35:08.155
Your decision tolerance for this decision is six inches or three degrees of of, you know, of angle difference.
1418
01:35:08.535 --> 01:35:18.918
Like if you actually write it down, then the decisions that are made off of it flow through from the outcome to the technology instead of from the technology to the outcome.
1419
01:35:19.802 --> 01:35:24.363
The guy that's just bought your data, that you've just agreed, and you've just written it down.
1420
01:35:25.044 --> 01:35:27.604
Great, you've now got a nice legal basis for your contract.
1421
01:35:27.624 --> 01:35:28.745
That's gonna work.
1422
01:35:28.765 --> 01:35:30.705
And that is superb.
1423
01:35:30.745 --> 01:35:35.587
But in five years' time, I pick up that model, and I think, oh,
1424
01:35:36.267 --> 01:35:36.767
Oh, it's a model.
1425
01:35:37.068 --> 01:35:37.528
It looks great.
1426
01:35:37.728 --> 01:35:38.529
It's already been measured.
1427
01:35:38.569 --> 01:35:39.549
Let's design from it.
1428
01:35:40.430 --> 01:35:44.013
There's a lot of detail here, so it must be to this tolerance.
1429
01:35:44.313 --> 01:35:50.837
And how many times do you read the disclaimer in the top right of a drawing frame that says, do not take measurements from this?
1430
01:35:51.538 --> 01:35:51.818
Sure.
1431
01:35:52.038 --> 01:35:52.999
No, and I'll agree with that.
1432
01:35:53.359 --> 01:35:53.840
And that's...
1433
01:35:54.780 --> 01:35:59.303
The point of it is so that you can actually work the deal and do the work.
1434
01:35:59.483 --> 01:35:59.723
Yes.
1435
01:35:59.863 --> 01:36:03.605
Now you actually have to follow through and continue.
1436
01:36:03.625 --> 01:36:04.966
We want these things to live on.
1437
01:36:05.086 --> 01:36:05.627
They have to live on.
1438
01:36:05.687 --> 01:36:06.347
And become.
1439
01:36:06.627 --> 01:36:07.388
Yeah.
1440
01:36:07.648 --> 01:36:10.169
It's not someone picking up a drawing on the shelf and reading a disclaimer.
1441
01:36:10.189 --> 01:36:11.210
It's going to have its own existence.
1442
01:36:11.350 --> 01:36:11.730
Yeah.
1443
01:36:11.770 --> 01:36:12.331
As a twin.
1444
01:36:12.491 --> 01:36:12.831
Correct.
1445
01:36:12.871 --> 01:36:15.332
That is interoperable and connected.
1446
01:36:15.432 --> 01:36:18.494
And you're saying the right term there about interoperability is really.
1447
01:36:18.554 --> 01:36:18.774
Yeah.
1448
01:36:18.874 --> 01:36:21.775
Because things need to be scalable, modular that you can grow, right?
1449
01:36:22.156 --> 01:36:30.000
If things are different, you know, fidelity is one thing, frequency is one thing, but if they don't fit together, you know, it.
1450
01:36:30.800 --> 01:36:34.044
How do you pass on that tolerance that you agreed on enlightening?
1451
01:36:34.144 --> 01:36:34.765
That's one.
1452
01:36:35.045 --> 01:36:40.852
You know, it needs to be categorized in a certain use case, used for purpose.
1453
01:36:40.872 --> 01:36:49.983
So the way you label it, categorize it within the twin, that you should know, because of how you're dealing with the data, what you can do with the data.
1454
01:36:50.463 --> 01:37:04.518
I would say, though, it is it's a it's a problem that has existed up to this point and still is, is that what you're saying is if someone in the future grabs that data, how can you know its accuracy?
1455
01:37:04.558 --> 01:37:05.859
And you can't if.
1456
01:37:06.740 --> 01:37:13.323
And I have seen it on projects a lot as well, where a client had someone do a scan three years ago, whatever.
1457
01:37:13.723 --> 01:37:14.903
Now they have data.
1458
01:37:15.304 --> 01:37:16.744
They don't know what device was used.
1459
01:37:16.764 --> 01:37:17.785
They don't know the workflows.
1460
01:37:18.085 --> 01:37:21.386
And there's nothing in that data that tells them exactly what it was.
1461
01:37:21.466 --> 01:37:22.727
So we do two things right now.
1462
01:37:23.007 --> 01:37:23.987
Which more people need to do.
1463
01:37:24.847 --> 01:37:25.708
So one of the things...
1464
01:37:26.228 --> 01:37:29.509
So one of the things we do on every project is we're going to do a survey report.
1465
01:37:29.569 --> 01:37:30.570
It has all the tolerances.
1466
01:37:30.650 --> 01:37:41.133
It has what survey equipment we use, what, you know, if we're tying in like a like a like a bridge or or some kind of asset, we're going to have a survey report.
1467
01:37:41.153 --> 01:37:42.854
We're going to say we meet ASPRS.
1468
01:37:42.914 --> 01:37:43.474
It does this.
1469
01:37:43.534 --> 01:37:44.054
Here's the check.
1470
01:37:44.334 --> 01:37:45.755
Here's the this is the tolerance.
1471
01:37:46.095 --> 01:37:47.776
Somebody wants to know what it is.
1472
01:37:47.896 --> 01:37:48.296
Look at it.
1473
01:37:48.796 --> 01:37:51.477
The other thing, too, but that's one component because they're disconnected.
1474
01:37:52.077 --> 01:38:00.905
The other piece is we have metadata that would go along with that asset or that deliverable, like if it's a LIDAR case.
1475
01:38:01.405 --> 01:38:02.186
Here's the LIDAR.
1476
01:38:02.406 --> 01:38:03.567
Here's the metadata for it.
1477
01:38:04.048 --> 01:38:05.329
Here's what was shot.
1478
01:38:05.729 --> 01:38:07.111
Here's the tolerance.
1479
01:38:07.571 --> 01:38:10.914
And then I just think you don't say what it's used for, fit for purpose.
1480
01:38:10.934 --> 01:38:11.695
This is what it is.
1481
01:38:12.115 --> 01:38:16.479
So somebody could look at it three years from now and say, man, that tolerance is better than I thought it would be.
1482
01:38:16.679 --> 01:38:18.120
I can use it for this, this, and this.
1483
01:38:18.821 --> 01:38:26.145
I don't care how they want to use it because, but if you specify it, it's available for somebody to make a valid decision from that.
1484
01:38:26.165 --> 01:38:37.252
Part of that, like specifying it, the problem is we live in a project role with your standard project folder that's in a project management tool, which is not accessible by IT and operations.
1485
01:38:37.612 --> 01:38:42.515
There is this caveat of them not being able to get that information effectively.
1486
01:38:43.035 --> 01:38:55.787
So one of the things I propose in my articles is an ontological relationship model, where that is built on top of your data, which means that you have a top-level ontology, means the relationships between things.
1487
01:38:55.807 --> 01:39:04.795
If I go to Google and I type in things, I'm typing in key terms, and the relationship with the terms gives me something that's relevant back within a certain constraint.
1488
01:39:04.835 --> 01:39:07.678
So we look at a project, I have assets.
1489
01:39:08.338 --> 01:39:09.519
I have locations.
1490
01:39:10.259 --> 01:39:14.802
I have services that were rendered by parties with certain intents.
1491
01:39:15.683 --> 01:39:23.048
And those relationships, that if you can build those relationships into your twin, then I can query my data.
1492
01:39:23.088 --> 01:39:26.530
Say, OK, well, I want a visualization.
1493
01:39:27.010 --> 01:39:28.852
I'm planning to use it for this purpose.
1494
01:39:29.352 --> 01:39:31.113
And I know my intent is this accuracy.
1495
01:39:31.233 --> 01:39:35.256
I should be able to ask my twin to be able to give me that information.
1496
01:39:35.676 --> 01:39:38.099
But a basic ontology will allow us to do that.
1497
01:39:38.119 --> 01:39:50.815
So are you suggesting then that your tolerances and your survey details go into the ontology against the objects and that the semantic layer can then interpret that at the same time?
1498
01:39:50.875 --> 01:39:51.616
Correct, correct.
1499
01:39:51.636 --> 01:40:11.435
And if I start to label that metadata and information that's in that contract and relate it to who did the work, so you're the party that was involved, if those relationships are driven, it's actually not that hard to understand how and you should use the data for what purpose, who did it at what time.
1500
01:40:11.896 --> 01:40:14.078
All of that information can be surfaced effectively.
1501
01:40:14.498 --> 01:40:25.487
But the way we work with projects today, which is part of its paper, PDFs, folders, the data becomes a silo and disconnected.
1502
01:40:25.507 --> 01:40:31.412
And it's really hard to get and infer the real meaning of that project because it's just not available.
1503
01:40:31.612 --> 01:40:33.293
Or it might be available, I can't get it.
1504
01:40:33.413 --> 01:40:34.254
I like silos.
1505
01:40:34.514 --> 01:40:34.774
Yeah?
1506
01:40:34.875 --> 01:40:35.435
And I always say I like it.
1507
01:40:35.455 --> 01:40:36.656
All your business does it, right?
1508
01:40:36.676 --> 01:40:37.697
Yeah.
1509
01:40:38.017 --> 01:40:48.701
No, I like silos from the simple use case of, I like my financial data to be separate to my HR data, but I want it to be able to be connected.
1510
01:40:49.021 --> 01:40:50.462
Correct, yeah.
1511
01:40:50.802 --> 01:40:54.184
So I always say to people, stop fighting silos, accept them.
1512
01:40:54.644 --> 01:40:54.944
Right.
1513
01:40:55.064 --> 01:41:00.966
And start connecting them or having the ability to bridge between your silos.
1514
01:41:01.166 --> 01:41:05.008
And geospatial data is a brilliant bridge between silos.
1515
01:41:05.028 --> 01:41:05.208
It is.
1516
01:41:05.548 --> 01:41:07.389
And that's where the digital twin comes in.
1517
01:41:07.809 --> 01:41:11.390
Well, and projects are based on contract and project number.
1518
01:41:12.090 --> 01:41:16.031
But in facilities, it's around asset and facility and other things.
1519
01:41:16.371 --> 01:41:19.032
And that's where this huge disconnect happens, right?
1520
01:41:19.092 --> 01:41:25.294
It's like, I can't find, like, I have assets that are in the same space that span over, like, 12 different projects.
1521
01:41:25.914 --> 01:41:26.954
So which is the right one?
1522
01:41:26.974 --> 01:41:27.894
What's the most current one?
1523
01:41:28.395 --> 01:41:31.836
So if you don't make those connections, it's really hard to make sense of it.
1524
01:41:32.316 --> 01:41:34.576
So you throw it away and you go out to the site.
1525
01:41:34.636 --> 01:41:35.256
And start again.
1526
01:41:35.597 --> 01:41:35.897
Yeah.
1527
01:41:37.337 --> 01:41:37.638
Okay.
1528
01:41:39.560 --> 01:41:40.421
We've been at this a while.
1529
01:41:41.542 --> 01:41:42.042
We're like...
1530
01:41:42.263 --> 01:41:44.145
It's a topic that we can... We're like halfway.
1531
01:41:44.305 --> 01:41:44.786
No, I'm just kidding.
1532
01:41:44.806 --> 01:41:46.067
We can yap all day.
1533
01:41:46.407 --> 01:41:46.668
I do...
1534
01:41:46.768 --> 01:41:50.632
I want to make sure we kind of shift and hit a couple different angles, though.
1535
01:41:51.113 --> 01:41:51.313
Um...
1536
01:41:53.252 --> 01:42:11.556
So my next question being, if we're kind of looking, we've talked a lot about some different use cases of capture and delivery and analyzing data and trying to get in people's heads and maybe our own as well as what is really digital twin?
1537
01:42:11.596 --> 01:42:12.897
How should we think about this topic?
1538
01:42:14.337 --> 01:42:17.718
Let's shift to the current,
1539
01:42:18.658 --> 01:42:24.802
that we're actually seeing in the industry, the opportunity around this and the direction that we're headed.
1540
01:42:26.443 --> 01:42:41.532
And I think it would be interesting to kind of hit on a couple of different things, both from the technology perspective of what are some of like, let's say that we're getting the ear of all of our vendors, of all the different technologies that we're using.
1541
01:42:41.552 --> 01:42:44.874
Like, what are some of the pain points we're still running into in, in, in,
1542
01:42:45.314 --> 01:42:50.195
being practitioners that are doing this work and seeing it on the ground.
1543
01:42:50.215 --> 01:42:53.116
Like, what are some of our pain points when it comes to the technologies?
1544
01:42:54.536 --> 01:42:56.997
And so I want to hit on the technologies a little bit.
1545
01:42:57.557 --> 01:43:02.738
I want to hit on where we think that there is still really prime opportunity.
1546
01:43:03.078 --> 01:43:06.079
What industries for some of this work?
1547
01:43:06.719 --> 01:43:08.860
And then I also want to hit on workforce a little bit.
1548
01:43:09.600 --> 01:43:16.302
So I hear a lot about the lack of talent in the industry, the growth and demand of these technologies.
1549
01:43:16.342 --> 01:43:22.825
But, you know, education is not putting out students that are ready to just come in and do a lot of this technical work.
1550
01:43:24.145 --> 01:43:31.448
And so I want to talk about like, you know, when we talk about talent, what are the jobs that are needed for the future of where these things are going?
1551
01:43:31.488 --> 01:43:31.648
So.
1552
01:43:32.288 --> 01:43:35.751
I think in this next little bit, maybe we could hit on a couple of these angles.
1553
01:43:35.771 --> 01:43:46.359
I'm talking about the talent coming out of school, that I think the children going into school now, the jobs that they will be doing when they come out, we haven't even thought of yet.
1554
01:43:46.799 --> 01:43:49.661
So how do you educate them to be ready?
1555
01:43:50.142 --> 01:43:55.966
We're sat here as employers running businesses and saying, we want the kids to be ready.
1556
01:43:56.026 --> 01:43:57.728
But when they went into the school system,
1557
01:43:58.967 --> 01:44:03.470
What we're doing today is nothing like the world was when they started.
1558
01:44:03.510 --> 01:44:05.351
So what are the schools supposed to do?
1559
01:44:05.651 --> 01:44:20.519
So I actually have a really good answer to that because I've experienced it over the last 20 years, is when I was an early employer in the remote sensing and GIS space, we were getting four-year graduates out of a university, University of Colorado.
1560
01:44:20.980 --> 01:44:26.083
And it took us three to six months to get them job ready because they were learning things.
1561
01:44:27.903 --> 01:44:40.707
So the answer to that and what actually works with now Pikes Peak State College and some other industries is they partner directly with employers that are doing today's work with today's technology.
1562
01:44:41.287 --> 01:44:43.048
And they don't become the instructors.
1563
01:44:43.088 --> 01:44:44.408
They become the mentors.
1564
01:44:44.548 --> 01:44:47.069
They become the internship opportunities.
1565
01:44:47.089 --> 01:44:48.769
They become the apprenticeship programs.
1566
01:44:49.349 --> 01:44:50.150
That's the only way.
1567
01:44:52.553 --> 01:45:08.638
throughout time that we are going to be able to answer that question is the people doing the work today need to be engaged with the students today and shadow them, mentor them, get them to understand, build them under, let them understand the path.
1568
01:45:09.318 --> 01:45:20.842
And then instead of just shipping them off to college and, you know, go, go become a philosophy major or go get a bachelor's in, in drone, uncrewed aerial systems.
1569
01:45:22.506 --> 01:45:26.010
By the time they get out, what I've experienced is they're not going to be worth anything.
1570
01:45:26.030 --> 01:45:27.872
So let me challenge that a little bit.
1571
01:45:28.012 --> 01:45:28.493
No, please.
1572
01:45:28.633 --> 01:45:28.953
Yeah.
1573
01:45:28.973 --> 01:45:30.895
So just a challenge on this area.
1574
01:45:30.915 --> 01:45:31.055
No.
1575
01:45:31.075 --> 01:45:33.218
So, so, I mean, I could just talk from our experience.
1576
01:45:33.258 --> 01:45:36.341
So we were going after, you know, we have a pretty.
1577
01:45:36.361 --> 01:45:37.302
Yeah.
1578
01:45:38.083 --> 01:45:38.883
large drone fleet.
1579
01:45:39.764 --> 01:45:41.905
And Emory Riddle has a UAS program.
1580
01:45:42.465 --> 01:45:51.350
And we brought a person in that's a rock star and came in, hit the ground running, and then started already off the bat saying, what about this?
1581
01:45:51.370 --> 01:45:53.591
I'm like, that improves our program.
1582
01:45:53.671 --> 01:45:54.551
That's a good idea.
1583
01:45:54.591 --> 01:45:55.332
Let's talk about it.
1584
01:45:55.352 --> 01:45:56.132
Let's do that.
1585
01:45:56.552 --> 01:45:58.153
The other thing, so that's one example.
1586
01:45:58.193 --> 01:46:04.216
The other thing on a survey, you got universities like Nichols and others that have a geomatics program.
1587
01:46:04.616 --> 01:46:05.137
These folks...
1588
01:46:05.937 --> 01:46:10.759
our four years in college with a specialty and survey and we're looking for surveyors.
1589
01:46:11.319 --> 01:46:30.384
So they're coming in and to your point, I like your, what you said too, because so I think you got programs, the right programs that are, you know, if someone were coming from philosophy, I agree a hundred percent, but if you're coming from a geomatics program, you get them in as an intern, you'll, you know, you let them see your culture, let them try some things, do some things.
1590
01:46:30.885 --> 01:46:32.785
And then we're also trying to do some partnering back.
1591
01:46:32.805 --> 01:46:35.386
So we'll go out and talk at some of the universities and, you know,
1592
01:46:35.426 --> 01:46:38.409
you know, get some interest for what we're doing, too.
1593
01:46:38.770 --> 01:46:46.498
I'm just making the point that there are universities that are putting out good talent that are hitting the ground running in our experience.
1594
01:46:46.518 --> 01:46:50.362
And let me be very clear, not to be contrary, but, like, yes, I agree with you.
1595
01:46:51.243 --> 01:46:55.188
The point is that those universities, especially Amber, I know it very well,
1596
01:46:55.915 --> 01:46:57.797
They are partnering with industry.
1597
01:46:57.837 --> 01:46:58.117
Yeah.
1598
01:46:58.357 --> 01:46:59.898
They're not, it's not a silo.
1599
01:47:00.078 --> 01:47:01.740
Like, you love silos.
1600
01:47:01.760 --> 01:47:06.844
A lot of universities will be very siloed and say, hey, I'm going to teach a drissi.
1601
01:47:07.164 --> 01:47:08.965
Who the hell uses a drissi anymore?
1602
01:47:09.246 --> 01:47:14.290
The problem is that the universities used to be the incubators of knowledge and would hold that...
1603
01:47:14.970 --> 01:47:17.251
that innovation, and it's backwards today.
1604
01:47:17.391 --> 01:47:22.073
The industries have the innovation and need to teach the schools.
1605
01:47:22.554 --> 01:47:26.755
And I hear this because we've supported numerous education programs.
1606
01:47:26.795 --> 01:47:29.657
I just did, you know, University of Texas, Capstone.
1607
01:47:29.677 --> 01:47:31.558
I had four classes I managed last fall.
1608
01:47:32.098 --> 01:47:38.901
I bring them in, I teach them what we do, and you know, some are good or not, but they're real world skills.
1609
01:47:39.021 --> 01:47:40.262
I mean, I built a digital twin
1610
01:47:41.122 --> 01:47:43.984
curriculum for Mohawk College like seven years ago.
1611
01:47:44.064 --> 01:47:44.784
Before it wasn't.
1612
01:47:44.844 --> 01:47:45.104
Why?
1613
01:47:45.144 --> 01:47:48.126
Because I was doing the work and they asked me to do it and I didn't know better.
1614
01:47:48.146 --> 01:47:49.486
It was a lot more work than expected.
1615
01:47:51.067 --> 01:47:52.788
But it's like, it's that partnership.
1616
01:47:52.848 --> 01:47:56.750
If you don't have the partnership with the universities, they can't catch up.
1617
01:47:57.351 --> 01:48:01.813
And there's that backwards, you know, relationship, which is really interesting.
1618
01:48:02.197 --> 01:48:02.417
Yeah.
1619
01:48:02.677 --> 01:48:03.398
Yeah.
1620
01:48:03.418 --> 01:48:11.102
I I was actually walking at the local university here, which Boise State has actually really bought into what we're doing with the conference.
1621
01:48:11.202 --> 01:48:20.928
And they, you know, last year we had one hundred and sixty students from the university come through the conference to hear different sessions, to see the technology.
1622
01:48:21.469 --> 01:48:24.651
We had a whole panel of professors from the university and.
1623
01:48:26.671 --> 01:48:38.275
Just a week ago, I went and walked their new construction management building and we're talking about, hey, we could come do some of this testing and training on scanners because we want to come scan at your university.
1624
01:48:38.295 --> 01:48:40.815
You have nice buildings to use for tests of different devices.
1625
01:48:41.196 --> 01:48:45.617
And they're like, at the same time, we want the students to see what you guys are doing and get industry buy-in.
1626
01:48:46.097 --> 01:48:52.059
But they're also, while we're walking, the leader of that whole program is saying,
1627
01:48:52.959 --> 01:48:55.823
We need professors like we have multiple open roles.
1628
01:48:56.323 --> 01:49:02.751
We can't find, you know, we need people to come in that are actually interested in growth and interested in the technology.
1629
01:49:03.111 --> 01:49:06.795
Some of our current professors, they're like, I'm retiring in a few years.
1630
01:49:06.916 --> 01:49:08.357
I don't care about the new technology.
1631
01:49:08.397 --> 01:49:09.939
I just want to focus on what I'm doing now.
1632
01:49:10.480 --> 01:49:10.800
And so
1633
01:49:11.721 --> 01:49:20.383
In order for the industry, you know, for the universities to actually grow and catch up to industry, there has to be the right fit, the right people.
1634
01:49:20.763 --> 01:49:30.426
Just like we're talking about in industry, they have to have the champions that are like, I want to actually get in and learn and dig and teach this stuff and find ways to bring industry in.
1635
01:49:30.446 --> 01:49:35.207
And it seems like there's there's a challenge there from internal.
1636
01:49:35.367 --> 01:49:35.767
No, I agree.
1637
01:49:35.807 --> 01:49:41.290
And I think you mentioned earlier, too, like this year, LSU just launched a digital twin certificate.
1638
01:49:41.570 --> 01:49:43.591
So this is one that's an official program.
1639
01:49:43.631 --> 01:49:49.293
Folks are signing up for it, laying out what the what a digital twin is, you know, kind of the crawl, walk, run approach.
1640
01:49:49.933 --> 01:49:52.875
And and, you know, it's kind of building up on where where.
1641
01:49:53.555 --> 01:49:55.396
you know, what the need is at the time.
1642
01:49:55.416 --> 01:50:05.980
So I think like even on the universities, somebody going through that program is gonna have a good opportunity to hit the ground running to get exposed to that because now they're like, you know, what is a digital twin?
1643
01:50:06.040 --> 01:50:06.940
How they're getting into it?
1644
01:50:06.960 --> 01:50:17.204
So you got academia and other folks that are defining it and also to help shape it around use cases and still a muddy subject.
1645
01:50:17.344 --> 01:50:22.006
But like I said, I don't think it's that muddy, to be honest, because, you know, if
1646
01:50:23.326 --> 01:50:26.369
You know, if a client says something about it, you know, I'll go back to that.
1647
01:50:26.389 --> 01:50:41.421
If a client says this is what it is and then and and you have something where, you know, you're updating things over time and you're attaching documents and people are using it on a week in week out basis to derive value, those type of things.
1648
01:50:42.702 --> 01:50:49.303
So on the university side, with that digital twin certificate at this university, I think that's only going to continue to get better.
1649
01:50:49.423 --> 01:50:52.144
The University of Central Florida has a good program that's been out for a while.
1650
01:50:52.204 --> 01:50:54.684
Soheil is in our community.
1651
01:50:55.845 --> 01:50:58.205
He's got a background in urban development.
1652
01:50:58.225 --> 01:50:59.605
He's got hands-on skills.
1653
01:51:00.066 --> 01:51:08.647
But even he's coming to the conferences, he's doing work with different user groups to understand, well, what do my students need to know to be successful?
1654
01:51:09.067 --> 01:51:11.928
And it's those universities that are reaching out and bringing people in.
1655
01:51:12.368 --> 01:51:14.010
that the ones that are going to be successful.
1656
01:51:14.090 --> 01:51:24.342
And those programs, too, are placing students, and they're involved in scopes of work, especially like the post-bachelors, you know, the master's programs and the PhDs programs.
1657
01:51:24.362 --> 01:51:27.546
Like the simulation school out of the University of Central Florida is phenomenal.
1658
01:51:27.966 --> 01:51:29.088
They are really good things.
1659
01:51:29.468 --> 01:51:30.429
But they're few or four between.
1660
01:51:30.449 --> 01:51:31.550
There's a lot that don't know.
1661
01:51:31.590 --> 01:51:35.433
And academia is not going to read a book and create a program like this.
1662
01:51:35.893 --> 01:51:38.635
You know, like survey, there's a standard.
1663
01:51:38.655 --> 01:51:39.456
You can follow it.
1664
01:51:39.936 --> 01:51:42.699
This is a whole Wild West thing to explain.
1665
01:51:42.739 --> 01:51:43.319
It's IT.
1666
01:51:43.359 --> 01:51:44.360
It's integration.
1667
01:51:44.880 --> 01:51:45.721
It's telemetry.
1668
01:51:45.761 --> 01:51:46.702
It's OT.
1669
01:51:46.862 --> 01:51:47.743
There's a lot there.
1670
01:51:48.403 --> 01:51:51.105
So, like, how do you compartmentalize that and build skills?
1671
01:51:51.165 --> 01:51:51.366
Yeah.
1672
01:51:51.926 --> 01:51:59.413
And this might be part of the answer, but like in the case of like LSU, they partner with with industry to develop that.
1673
01:51:59.473 --> 01:52:07.801
So you got folks that have been doing it for 20 years and saying, now let me put a certificate around it with the backing of the university to get it out to students.
1674
01:52:07.821 --> 01:52:10.864
So it goes back to your point of of a collaboration piece.
1675
01:52:11.324 --> 01:52:13.747
So it's not it wasn't done in like in a in a bucket.
1676
01:52:13.947 --> 01:52:15.148
It was it was an industry.
1677
01:52:16.085 --> 01:52:17.726
A little hit on universities.
1678
01:52:17.886 --> 01:52:20.408
We could probably talk about that forever.
1679
01:52:21.389 --> 01:52:27.214
Let's shift to, okay, maybe we don't know all the roles we need in the next five years, 10 years.
1680
01:52:27.634 --> 01:52:34.900
What are some of the immediate gaps we're seeing in skillset and personnel in the industry?
1681
01:52:35.285 --> 01:52:40.288
Fielders, people to go on the field and capture the data using the technology.
1682
01:52:40.388 --> 01:52:42.850
Yeah, and post processors, I think all of it.
1683
01:52:43.510 --> 01:52:45.592
Those two are everywhere.
1684
01:52:45.652 --> 01:52:46.853
They're literally needed everywhere.
1685
01:52:46.873 --> 01:52:51.396
If you looked on Indeed, you looked on, I mean, they're a constant need.
1686
01:52:52.196 --> 01:52:56.139
And I think a lot of the, I mean, I'm not hitting on this generation.
1687
01:52:56.160 --> 01:52:58.001
I have children of this generation.
1688
01:52:58.501 --> 01:53:02.705
And they're like, no, I want to be a YouTube star, a gamer, a YouTuber.
1689
01:53:02.725 --> 01:53:04.066
Like, I want to do all these things, right?
1690
01:53:04.226 --> 01:53:13.975
And it's like, wait, these are like skilled trades that may or may not actually, where the big needs are right now, not necessarily need to go to college for.
1691
01:53:13.995 --> 01:53:14.095
Yeah.
1692
01:53:14.555 --> 01:53:17.477
Like, I would say not even community college, necessarily.
1693
01:53:17.557 --> 01:53:20.399
I think they can go into these programs that are sponsored by...
1694
01:53:20.780 --> 01:53:29.566
So my nonprofit has a registered apprenticeship program, we talked about it earlier, and we want to prep people while they are in high school to be ready to go
1695
01:53:30.642 --> 01:53:35.323
Hitting the ground running with the latest technology, the latest software, a mentor, and a path.
1696
01:53:35.923 --> 01:53:36.783
If they choose it, great.
1697
01:53:36.903 --> 01:53:38.204
If they don't, great.
1698
01:53:38.604 --> 01:53:39.064
It's fine.
1699
01:53:39.344 --> 01:53:39.984
But they're there.
1700
01:53:40.364 --> 01:53:41.264
So they're available.
1701
01:53:41.685 --> 01:53:44.305
I like some of the STEM schools, like the high school STEM schools.
1702
01:53:44.325 --> 01:53:46.706
They do really, really good with that kind of program.
1703
01:53:46.726 --> 01:53:51.847
And I think, yes, like it's those people, like I'll hire them right now.
1704
01:53:52.465 --> 01:53:59.531
But I think the other side of this, like you're talking about what's now, what's future, like the robotics, robotics has come in so, so fast and heavy.
1705
01:53:59.851 --> 01:54:03.815
So the CES show in, in January, and I was just blown away.
1706
01:54:04.255 --> 01:54:10.461
And you got Elon Musk taking two car lines out of service to just produce Optimus' for 30 grand.
1707
01:54:10.961 --> 01:54:11.582
Like I'm,
1708
01:54:12.322 --> 01:54:18.544
It is coming way faster than people have any idea, and the AI is what's driving that.
1709
01:54:18.905 --> 01:54:21.105
So it's going to re-engineer all what we do.
1710
01:54:21.225 --> 01:54:26.528
Like, it really will, like, next two years, three years, it's going to be a completely different landscape.
1711
01:54:26.588 --> 01:54:27.488
So what needs to happen?
1712
01:54:29.221 --> 01:54:30.902
is Elon needs to build the drone.
1713
01:54:31.622 --> 01:54:32.642
That's what it needs to happen.
1714
01:54:32.662 --> 01:54:34.983
And the reason being- He's got to do that.
1715
01:54:35.023 --> 01:54:36.184
A drone that flies on Mars.
1716
01:54:36.304 --> 01:54:53.711
The reason being is because you had DJI dominating the market and we have some tremendous, I joke around all about that a little bit, but we have some tremendous, Skydio's tremendous, you got WingTress, tremendous, and a bunch of other drone companies.
1717
01:54:54.191 --> 01:54:57.573
But I mean, if you look at the consumer side, they're all focused on commercial.
1718
01:54:58.193 --> 01:55:03.116
So on the consumer side, selfishly, I think Elon would do a great job.
1719
01:55:03.837 --> 01:55:05.738
I'm just saying.
1720
01:55:05.958 --> 01:55:06.879
He's amazing.
1721
01:55:06.899 --> 01:55:08.219
But I heard what Elon does.
1722
01:55:08.239 --> 01:55:09.440
It just thinks different.
1723
01:55:09.480 --> 01:55:13.783
I mean, I'll do quick little two tangents and then tie into what you just said.
1724
01:55:15.244 --> 01:55:18.025
When he came in and he says, we're going to build rockets, what's the problem?
1725
01:55:18.085 --> 01:55:20.387
You buy a rocket and it has all these things.
1726
01:55:20.407 --> 01:55:22.988
The selling point before was, here's the selling point.
1727
01:55:23.009 --> 01:55:24.910
You get all this stuff in it and this does this.
1728
01:55:25.450 --> 01:55:26.091
but it's the rocket.
1729
01:55:26.472 --> 01:55:28.875
And he came back, he says, you need a reusable rocket.
1730
01:55:28.955 --> 01:55:34.443
And then when he started selling, I was watching the documentary, when he started selling reusable rockets, nobody wants a used rocket.
1731
01:55:34.463 --> 01:55:35.425
And he's saying, what do you mean?
1732
01:55:35.965 --> 01:55:38.990
I wanna be on the 300th flight of an airplane, not the first one.
1733
01:55:39.350 --> 01:55:39.671
Yeah.
1734
01:55:40.432 --> 01:55:44.756
He made a point, but you go back to the robot, he's saying, you know, he's redoing the hand.
1735
01:55:44.796 --> 01:55:50.561
He said, you know, I could buy components, but he said one of the hardest things is the hands of the robot.
1736
01:55:50.862 --> 01:55:53.624
And he said, so he's spending a ton of time getting it right.
1737
01:55:54.285 --> 01:55:58.349
So I think that approach to the robotics in the future is...
1738
01:55:58.689 --> 01:55:59.890
And I think AI, you know, is huge.
1739
01:56:00.010 --> 01:56:01.050
He's his customer.
1740
01:56:01.330 --> 01:56:01.510
Right.
1741
01:56:01.610 --> 01:56:04.772
You know, the first million robots are going right into his plans to be used.
1742
01:56:04.792 --> 01:56:07.573
Like, talk about, like, the ability to train.
1743
01:56:07.753 --> 01:56:08.793
It's going to be for the whole one.
1744
01:56:09.153 --> 01:56:10.174
And then, yeah, all of it.
1745
01:56:10.334 --> 01:56:11.134
Deal on subject.
1746
01:56:11.494 --> 01:56:13.055
Was he right when he said that LiDAR's dead?
1747
01:56:14.295 --> 01:56:21.122
I think the question, I'll go into this, it was the multimodal challenge that vehicles face.
1748
01:56:21.142 --> 01:56:23.845
Because you've got radar, LIDAR, imagery.
1749
01:56:24.045 --> 01:56:27.729
It's the multimodal, it's the complexity of multimodal.
1750
01:56:28.730 --> 01:56:31.674
I read one of his engineers wrote an article, and it was really fascinating.
1751
01:56:31.914 --> 01:56:35.297
They picked one modality, and they got really good at that modality.
1752
01:56:35.978 --> 01:56:40.280
So, and there's some inherent flaws with LiDAR, water, and, you know, certain things.
1753
01:56:40.620 --> 01:56:42.041
So they got really good with imagery.
1754
01:56:42.361 --> 01:56:47.363
But I think it's a multimodal problem that they solve more than LiDAR being a problem.
1755
01:56:48.704 --> 01:56:49.124
For him.
1756
01:56:49.544 --> 01:56:50.064
Yeah.
1757
01:56:51.345 --> 01:56:52.325
In that use case.
1758
01:56:52.345 --> 01:56:53.006
Yeah.
1759
01:56:53.986 --> 01:56:59.789
But it's, I have to say, I was slightly insulted in a, uh, one of his cars.
1760
01:57:00.849 --> 01:57:25.576
looking at the little screen while it's showing the difference between trucks and suvs and compact cars and i'm looking and thinking oh that's exactly like my car and there's a picture of a truck there and sorry by that i mean a uh a big arctic it's uh the semi i think you call them but it's uh and and i'm thinking how's it got that so wrong i felt personally insulted because it was my car that it was
1761
01:57:27.877 --> 01:57:28.838
Yeah, best guesses.
1762
01:57:29.799 --> 01:57:31.540
Yeah, so technology is not perfect.
1763
01:57:31.600 --> 01:57:37.924
But robotics going back to our industry and data capture, like we deployed a robot in an essential utility plant for gathering data, right?
1764
01:57:38.285 --> 01:57:38.905
So I've been through that.
1765
01:57:38.925 --> 01:57:40.486
We did a drone in the box as well.
1766
01:57:40.806 --> 01:57:43.768
The drone in the box, like Exxon's buying like a hundred of those things, man.
1767
01:57:43.909 --> 01:57:47.131
Like it is the repeatability of a use case.
1768
01:57:47.171 --> 01:57:48.632
If it's repeatable and you can...
1769
01:57:49.092 --> 01:57:50.112
continuously do that.
1770
01:57:50.553 --> 01:57:51.753
But it's still going to draw people.
1771
01:57:51.893 --> 01:57:52.893
Someone's going to take care of it.
1772
01:57:52.913 --> 01:57:54.234
Someone's going to train the mission.
1773
01:57:54.254 --> 01:57:55.394
Someone's going to deal with the data.
1774
01:57:55.854 --> 01:57:57.655
So I think people are going to transition.
1775
01:57:57.995 --> 01:57:59.335
But we've got to kind of anticipate.
1776
01:57:59.375 --> 01:58:01.756
That automation is coming fast and heavy.
1777
01:58:02.156 --> 01:58:03.277
So how do you embrace it?
1778
01:58:03.477 --> 01:58:05.877
And how do you be agile and move to different skill sets?
1779
01:58:05.997 --> 01:58:07.058
And to be specific with AI.
1780
01:58:08.502 --> 01:58:09.523
Bad data?
1781
01:58:10.303 --> 01:58:11.824
AI can't fix it.
1782
01:58:11.844 --> 01:58:13.485
So it's always going to be garbage in, garbage out.
1783
01:58:13.725 --> 01:58:15.566
It's going to tell you it's bad, just faster.
1784
01:58:15.746 --> 01:58:20.109
Just faster.
1785
01:58:20.349 --> 01:58:29.675
I feel like the robotics piece, at least when we think about a lot of what we're talking about with capture and diddletwin modeling, whatever, I feel like...
1786
01:58:30.435 --> 01:58:31.616
It's going to be a while.
1787
01:58:32.897 --> 01:58:41.022
My assumption is that it will be quite some time before this idea that like all capture technicians are replaced.
1788
01:58:41.702 --> 01:58:50.448
I think that what we'll first see is the types of clients and projects where there is going to be continuous work.
1789
01:58:50.608 --> 01:58:50.788
Right.
1790
01:58:51.088 --> 01:58:53.669
So installing a robot.
1791
01:58:53.749 --> 01:58:56.669
And this is where the early days of even the spot has been tested, right?
1792
01:58:56.689 --> 01:59:05.350
Is like on a construction site where we instead of just scanning it once, well, it's too expensive to scan it every week with a technician and all the processing time.
1793
01:59:05.631 --> 01:59:20.113
But if we can install a robot on that site and now there's no human involvement and it could scan it every night while there's no workers and upload the data, I think the robotics will be in those like continuous updating states.
1794
01:59:20.593 --> 01:59:28.680
Where, you know, even being in a service industry, I don't yet see the fear of like, oh, we're not going to need any scan technicians.
1795
01:59:28.740 --> 01:59:30.362
All scanners are going to be replaced.
1796
01:59:30.742 --> 01:59:32.324
But some people do question that.
1797
01:59:32.724 --> 01:59:39.010
I think we're a ways out before there's so many robots out and that they're just everywhere on every capture prospect.
1798
01:59:39.050 --> 01:59:39.270
Right.
1799
01:59:40.017 --> 01:59:40.958
I don't know.
1800
01:59:41.058 --> 01:59:41.778
I don't know.
1801
01:59:41.878 --> 01:59:42.459
I don't know.
1802
01:59:42.499 --> 01:59:43.399
I think there's a big...
1803
01:59:43.479 --> 01:59:45.341
I'm a little sure of... Yeah.
1804
01:59:45.381 --> 01:59:50.784
It's going to be sure of robots, but I think the reality is that it's still not going to replace...
1805
01:59:51.025 --> 01:59:56.108
It's going to give an opportunity for the dull, the dirty, the dangerous, which is why these things for robotics exist.
1806
01:59:56.628 --> 02:00:02.072
Those are going to go down, and so safety metrics go... Like, all of these things happen, and then there's this gap.
1807
02:00:02.693 --> 02:00:08.717
This time is now available for higher human skills that will never go away.
1808
02:00:08.737 --> 02:00:09.137
Yeah.
1809
02:00:09.337 --> 02:00:09.617
Right?
1810
02:00:09.657 --> 02:00:12.639
So all of the crap I really didn't want to do anyway, yeah, I'll let robots do it.
1811
02:00:12.659 --> 02:00:13.940
That's why they're being developed.
1812
02:00:13.960 --> 02:00:14.860
100%.
1813
02:00:14.960 --> 02:00:18.202
All of this other stuff, it is now all of this.
1814
02:00:18.222 --> 02:00:22.364
And oh, by the way, these things break, and these things do this, and I need to understand it, and I still think...
1815
02:00:22.664 --> 02:00:24.025
It's just expansion.
1816
02:00:24.085 --> 02:00:24.946
It's evolution.
1817
02:00:26.081 --> 02:00:26.962
Yeah, I don't know.
1818
02:00:27.102 --> 02:00:32.145
I think the robots are coming, but I'm with you, too, that it's going to be a little ways out.
1819
02:00:32.165 --> 02:00:41.651
And I'm thinking of an example of, you know, we did a big building, had to be done over a time of period with folks walking around and, and, uh,
1820
02:00:42.131 --> 02:00:44.894
So, you know, you're going to have some specialized folks that are going to be there.
1821
02:00:44.954 --> 02:00:46.576
Consider it the soft skills.
1822
02:00:46.996 --> 02:00:49.899
Hey, ma'am, you know, would you mind if we got into here?
1823
02:00:49.919 --> 02:00:51.721
Some of them are, you know, get out of here.
1824
02:00:51.741 --> 02:00:52.862
You're not supposed to be in this area.
1825
02:00:53.002 --> 02:00:53.542
Insensitive.
1826
02:00:53.743 --> 02:00:55.504
You don't want the robot just kicking the door open.
1827
02:00:57.386 --> 02:00:59.648
So I think you're going to have that always.
1828
02:01:00.268 --> 02:01:04.472
And I think that's going to continue because we got aging infrastructure that's tremendous.
1829
02:01:04.532 --> 02:01:11.257
So, you know, back to that point, I think the demand for personnel learning it is here and it's going to grow.
1830
02:01:11.317 --> 02:01:15.000
But I also think that there's value in learning that.
1831
02:01:15.901 --> 02:01:26.253
skill and then get, you know, then at a point when you get, you know, if a robot does that role, now you know that there's value in learning that and understanding it and then having the higher value too.
1832
02:01:26.334 --> 02:01:28.136
So you make it a win-win.
1833
02:01:28.156 --> 02:01:29.617
The robot would do it in high school.
1834
02:01:30.158 --> 02:01:31.480
Well, so... Teenagers around.
1835
02:01:31.500 --> 02:01:31.680
Yeah.
1836
02:01:31.880 --> 02:01:37.845
I think, you know, things that have high coordination planning and that there's not repealability, it's going to go away.
1837
02:01:37.865 --> 02:01:41.968
But if you look at something like autonomous vehicles, they're becoming normal, right?
1838
02:01:42.048 --> 02:01:45.071
I mean, there's a lot of autonomous vehicles that are growing rapidly.
1839
02:01:45.471 --> 02:01:47.773
So look at mobile mapping as a DOT function.
1840
02:01:48.093 --> 02:01:49.414
I mean, that could be...
1841
02:01:50.135 --> 02:01:51.575
pretty autonomous, right?
1842
02:01:52.036 --> 02:02:10.861
And with the automated workflows of pushing data cloud and things like this, what I'm saying is there's going to be this whole base layer of things that we didn't do or were too costly to do that are all of a sudden going to be open up opportunities because of automation and robotics and not needing people to do these things, right?
1843
02:02:11.061 --> 02:02:13.222
And I go back to this optimist with 30 grand.
1844
02:02:13.262 --> 02:02:14.122
It's like, it's crazy.
1845
02:02:14.162 --> 02:02:17.923
I mean, certainly I'm frustrated about how slowly they fold the laundry.
1846
02:02:18.323 --> 02:02:20.004
I'm like, that's got to change.
1847
02:02:20.024 --> 02:02:21.224
Like, you're fired, right?
1848
02:02:21.765 --> 02:02:23.305
But you got to do that 100 times faster.
1849
02:02:23.645 --> 02:02:25.506
But it's coming quickly.
1850
02:02:25.646 --> 02:02:26.567
And you can repeat this.
1851
02:02:26.667 --> 02:02:29.788
And you look at the factories with all the machine vision.
1852
02:02:29.828 --> 02:02:38.732
So they're putting cameras on people working all over India and all these different places because the AR can train what the robot can do.
1853
02:02:39.172 --> 02:02:40.132
And there's a huge connection.
1854
02:02:40.172 --> 02:02:43.633
It was an AWE conference, and they're talking about robotics and AR.
1855
02:02:43.773 --> 02:02:51.375
And if you can do it in AR and all this putting on the gloves and showing what you're doing in manufacturing, all of that stuff can be replicated.
1856
02:02:51.795 --> 02:02:55.856
So it's coming a lot faster with AI than anyone can even really anticipate.
1857
02:02:56.256 --> 02:03:03.097
But I'm saying that the high-quality, high-level work that takes a technician and human judgment, that's not going to go well.
1858
02:03:03.277 --> 02:03:27.184
Yeah, that's where I look at it as just like we do all the tools that have sure, right, like slam scanners coming out over the last several years to the extent where they're replacing certain types of work from terrestrial or high end survey or I look at the robotics the same way of like, it's just going to shift the need for that human with the high end skills to go to the more critical projects.
1859
02:03:27.745 --> 02:03:28.445
And and.
1860
02:03:29.045 --> 02:03:37.949
the same way that we look at, well, how is Gaussian splatting and radiance fields and all that, now stepping into, does it replace some use case for photogrammetry projects?
1861
02:03:38.629 --> 02:03:40.450
I think it just continues to expand.
1862
02:03:42.451 --> 02:03:43.772
The data's going to grow.
1863
02:03:43.812 --> 02:03:45.192
The data's growing, for sure.
1864
02:03:45.292 --> 02:03:56.718
And the hardware is getting less and less expensive, more and more accessible, and more, with fewer skills, you can actually go, so will that drive a...
1865
02:03:57.598 --> 02:04:00.560
everybody down to the bottom on price, on RealityCapture.
1866
02:04:00.580 --> 02:04:02.682
I think you got, I think, for certain types of...
1867
02:04:02.722 --> 02:04:03.482
Absolutely.
1868
02:04:03.522 --> 02:04:11.208
I mean, I have my phone, and I can capture data with my phone today, and I have done it, and I'm quite impressed with what you can do with it for certain things.
1869
02:04:11.248 --> 02:04:11.428
Yep.
1870
02:04:11.829 --> 02:04:13.310
I'm not gonna pay someone to go do that.
1871
02:04:13.630 --> 02:04:15.351
Now I have Matterport camera.
1872
02:04:15.371 --> 02:04:16.011
I can go do that.
1873
02:04:16.052 --> 02:04:17.432
I have Insta360.
1874
02:04:17.693 --> 02:04:20.894
But I'm going to call Matt when I have to do my terminal at DFW.
1875
02:04:20.974 --> 02:04:22.676
There's no way I'm going to try to do that myself.
1876
02:04:22.816 --> 02:04:25.657
What's stopping a kid with a cheap scanner now saying, oh, I can do that.
1877
02:04:25.917 --> 02:04:27.038
I've just got to capture that.
1878
02:04:27.138 --> 02:04:29.059
Insurance and other requirements.
1879
02:04:29.099 --> 02:04:30.740
Depends on their company you work for.
1880
02:04:30.820 --> 02:04:34.383
What stops a kid from doing that is like, okay, do you have the insurance to cover it?
1881
02:04:34.443 --> 02:04:36.324
What's your technical capability?
1882
02:04:36.344 --> 02:04:37.404
What's your professionalism?
1883
02:04:37.444 --> 02:04:38.345
What's your track record?
1884
02:04:38.805 --> 02:04:41.127
Because I want to make sure it's right.
1885
02:04:41.827 --> 02:04:43.528
And do I want to take a chance on the low bidder?
1886
02:04:43.548 --> 02:04:45.029
And I think folks have been bid.
1887
02:04:45.089 --> 02:04:45.950
Right.
1888
02:04:46.170 --> 02:04:47.411
Agreed.
1889
02:04:47.451 --> 02:04:50.653
I think the clarity around requirements becomes so much more important.
1890
02:04:52.074 --> 02:05:06.744
The change of these technologies and it becoming so easy is it it means there does need to be silos and there needs to be clearer lines between, OK, where can these different technologies and use cases actually fit?
1891
02:05:06.764 --> 02:05:07.244
Yeah.
1892
02:05:08.885 --> 02:05:14.171
For instance, like, you know, going into a house to scan for furniture.
1893
02:05:14.291 --> 02:05:17.755
Well, you don't now need to use a high-end $100,000 scanner.
1894
02:05:18.236 --> 02:05:19.497
That used to be the only option.
1895
02:05:19.517 --> 02:05:20.078
Yeah.
1896
02:05:20.118 --> 02:05:23.662
You didn't have any projects that they're producing.
1897
02:05:24.043 --> 02:05:25.024
It's unbelievable.
1898
02:05:25.044 --> 02:05:25.144
Yeah.
1899
02:05:25.524 --> 02:05:30.787
So I think it's going to be that the high volume, easy, low accuracy.
1900
02:05:31.187 --> 02:05:37.971
I do think that those smaller devices will make that so fast, so easy that that will become a high volume game.
1901
02:05:39.011 --> 02:05:43.393
And just about any technician can learn to go grab a unit and go capture that.
1902
02:05:43.754 --> 02:05:52.258
But then it shifts to those higher, higher, you know, higher accuracy, critical projects, getting in hospitals, getting in airports, getting in refineries.
1903
02:05:52.818 --> 02:06:01.506
Or even large schools, especially if they start going to the use case of it's still going to be engineering and construction accuracy.
1904
02:06:01.866 --> 02:06:05.149
That's not your quick iPhone scan right now.
1905
02:06:05.709 --> 02:06:12.135
So that's why I think these conversations around this are so important is we have to keep defining some of these things.
1906
02:06:12.235 --> 02:06:15.258
Because as new devices are coming out, they are so cheap.
1907
02:06:15.818 --> 02:06:18.500
And now the people paying ask that same question.
1908
02:06:18.520 --> 02:06:19.201
Why do I have to pay?
1909
02:06:19.301 --> 02:06:23.143
I just hire someone with that little device instead of everything you're proposing.
1910
02:06:23.283 --> 02:06:26.084
The technology advantage lasts, what, one procurement cycle?
1911
02:06:26.464 --> 02:06:26.744
That's it.
1912
02:06:27.184 --> 02:06:27.664
That's all you got.
1913
02:06:28.765 --> 02:06:29.385
That is what you get.
1914
02:06:29.585 --> 02:06:32.787
You get one procurement cycle of that advantage, and then you're done.
1915
02:06:33.047 --> 02:06:34.807
And you're right, and shorter and shorter, and then that's it.
1916
02:06:35.328 --> 02:06:41.030
If you tie your pricing, this is something I actually talk a lot about, if you tie your pricing to the decision,
1917
02:06:42.565 --> 02:06:44.707
The continuous need for the decision.
1918
02:06:45.368 --> 02:06:47.810
Now you're generating an MSA.
1919
02:06:48.051 --> 02:06:52.335
Now you're not just having a one-off project where it's like this is super big and this is super.
1920
02:06:52.736 --> 02:06:58.742
Now it's continuously priced based on the decision, disconnected from the technology.
1921
02:06:59.565 --> 02:07:00.605
Then you build yourself a little more.
1922
02:07:00.625 --> 02:07:02.086
Users don't care about technology.
1923
02:07:02.146 --> 02:07:02.966
They call them.
1924
02:07:03.006 --> 02:07:03.887
They don't care.
1925
02:07:04.027 --> 02:07:04.767
They don't care.
1926
02:07:04.867 --> 02:07:05.988
Solve the problem.
1927
02:07:06.008 --> 02:07:06.688
Yes.
1928
02:07:06.708 --> 02:07:07.448
Keep me out of the news.
1929
02:07:07.929 --> 02:07:08.629
Solve my problem.
1930
02:07:10.930 --> 02:07:18.993
There was an IOU in a large state on the West Coast that that was the executive guidance.
1931
02:07:19.673 --> 02:07:22.615
Like, I'm going to go with the company that keeps me out of the news.
1932
02:07:23.235 --> 02:07:23.435
Yeah.
1933
02:07:24.365 --> 02:07:25.105
that was the bar.
1934
02:07:25.846 --> 02:07:28.547
Now to do that, there's a lot that goes into it.
1935
02:07:28.587 --> 02:07:34.691
You can't hire the kid that just got their 107 and went to Best Buy and got a drone because that kid's going to put you in the news.
1936
02:07:34.751 --> 02:07:35.451
I can guarantee it.
1937
02:07:35.971 --> 02:07:37.572
So that's the difference.
1938
02:07:37.632 --> 02:07:40.654
And I think we've been dancing around it a little bit, but I think that's it.
1939
02:07:40.674 --> 02:07:41.915
So we're going to start selling on fair.
1940
02:07:42.875 --> 02:07:43.676
It's not fear.
1941
02:07:43.716 --> 02:07:45.438
Fear and certain the intent, all three.
1942
02:07:45.538 --> 02:07:46.679
It's all of it, right?
1943
02:07:46.719 --> 02:07:47.580
It's not just fear.
1944
02:07:47.680 --> 02:07:49.041
It's the decision, right?
1945
02:07:49.341 --> 02:07:50.863
It's the weight of the decision.
1946
02:07:50.983 --> 02:07:51.683
I'm not going to.
1947
02:07:51.723 --> 02:08:01.712
So if I'm using this technology, I'm making a decision like and be very specific in the drone industry, like especially in construction, it's huge right now, right?
1948
02:08:02.233 --> 02:08:05.055
Where I'm going to spend money based on this decision.
1949
02:08:05.916 --> 02:08:12.662
I and not a little bit amount of money like I'm not gonna spell like three four five hundred thousand dollars today based off the information.
1950
02:08:13.583 --> 02:08:18.968
If I can't trust it, I can't trust the person and the method and the method is where the premium lives.
1951
02:08:19.148 --> 02:08:19.328
Right.
1952
02:08:19.388 --> 02:08:20.790
Not the technology, but the method.
1953
02:08:22.591 --> 02:08:25.113
That is where that conversation goes.
1954
02:08:25.694 --> 02:08:25.934
Right.
1955
02:08:26.334 --> 02:08:27.696
It's like you have to be able to do that.
1956
02:08:27.936 --> 02:08:30.218
If you can't do that, it's repeatability and trust.
1957
02:08:30.298 --> 02:08:30.538
Right.
1958
02:08:30.718 --> 02:08:31.940
If you don't have those things.
1959
02:08:32.796 --> 02:08:35.937
No one's going to work with you, especially at this enterprise scale.
1960
02:08:36.397 --> 02:08:39.898
DFW would never work with you if you had no idea what the hell you're doing.
1961
02:08:40.438 --> 02:08:40.919
Oh, really?
1962
02:08:41.239 --> 02:08:41.739
Right?
1963
02:08:42.179 --> 02:08:44.139
I mean, maybe they would.
1964
02:08:44.159 --> 02:08:44.760
I don't know.
1965
02:08:44.860 --> 02:08:45.760
He knows a guy.
1966
02:08:45.780 --> 02:08:47.641
Yeah, he plays golf with somebody.
1967
02:08:48.821 --> 02:08:51.002
But that's it, right?
1968
02:08:51.042 --> 02:08:51.582
That's the thing.
1969
02:08:53.637 --> 02:08:53.877
Okay.
1970
02:08:55.058 --> 02:08:55.738
No, you okay.
1971
02:08:56.199 --> 02:08:56.699
Okay.
1972
02:08:56.719 --> 02:08:57.460
No, you okay.
1973
02:08:58.961 --> 02:08:59.501
Okay.
1974
02:08:59.681 --> 02:09:00.482
No, we're not doing that?
1975
02:09:00.702 --> 02:09:00.962
Yeah.
1976
02:09:00.982 --> 02:09:01.482
Yeah.
1977
02:09:01.542 --> 02:09:02.583
What?
1978
02:09:03.764 --> 02:09:11.849
Overall take on the future of the trajectory that we're headed on for this industry for these technologies.
1979
02:09:14.265 --> 02:09:15.106
What's your perspective?
1980
02:09:15.166 --> 02:09:18.191
Being people that work in this space, have been for a while.
1981
02:09:18.692 --> 02:09:21.696
What's your take on the direction we're headed?
1982
02:09:21.716 --> 02:09:24.100
I think we're going to be fucking loving it.
1983
02:09:24.120 --> 02:09:24.300
Yeah.
1984
02:09:25.030 --> 02:09:34.536
year, two years with all sorts of new things, new bits of software written in, Claude, kids saying, oh, I've got this new reality capture program that can do this and this and this.
1985
02:09:36.017 --> 02:09:41.701
And flooded with cheap scanning devices, cheap reality capture devices.
1986
02:09:42.421 --> 02:09:50.266
I think there's going to be an awful lot of noise at that level that will distract all of us for an annoying period of time.
1987
02:09:52.067 --> 02:09:52.448
Some of it.
1988
02:09:52.628 --> 02:09:53.588
Yeah, I think really good.
1989
02:09:53.608 --> 02:09:53.708
Yeah.
1990
02:09:54.744 --> 02:09:55.724
I definitely agree.
1991
02:09:55.744 --> 02:09:56.825
There's going to be a lot of noise.
1992
02:09:56.905 --> 02:09:57.625
There already is.
1993
02:09:57.645 --> 02:09:58.065
There already is.
1994
02:09:58.085 --> 02:10:04.787
You know, and especially for the people that are new to the industry and they can go online and find things and they think, oh, this is perfect.
1995
02:10:04.827 --> 02:10:06.908
And they don't know requirements.
1996
02:10:06.928 --> 02:10:08.828
They don't know how to look at data.
1997
02:10:08.908 --> 02:10:10.149
That is very risky.
1998
02:10:10.569 --> 02:10:11.229
But I do think...
1999
02:10:11.849 --> 02:10:19.818
there's going to be a lot of massive growth and need because you don't have to prove it the same way you did five, 10 years ago.
2000
02:10:20.258 --> 02:10:22.260
We know there's value in these things.
2001
02:10:22.741 --> 02:10:24.443
We know what the arguments are.
2002
02:10:24.583 --> 02:10:32.412
The right company that's been doing it a long time that knows their industry can clearly talk about the value propositions for your customers.
2003
02:10:33.012 --> 02:10:38.354
So it's no longer an if, it's a yes, we're going to do it, and it's going to expand more and more.
2004
02:10:38.694 --> 02:10:42.695
And the technology is helping us do it quicker, better quality, more automated.
2005
02:10:42.955 --> 02:10:46.276
And I'll offer to piggyback on that.
2006
02:10:46.456 --> 02:10:52.878
The other thing, just as a trend across the board, is I'll go back to we have aging infrastructure.
2007
02:10:53.198 --> 02:10:54.638
Things are being done a certain way now.
2008
02:10:55.318 --> 02:11:00.280
The way things are being done right now is a manual method in some industries.
2009
02:11:00.880 --> 02:11:06.022
Those industries are now adopting drones and other technologies.
2010
02:11:06.422 --> 02:11:13.744
So those folks are being supplemented, you know, as a complement tool to utilize and being trained to do that.
2011
02:11:14.264 --> 02:11:16.365
And some firms are like, we don't want no part of that.
2012
02:11:16.465 --> 02:11:18.965
I mean, I know some firms are like, you know, we don't touch survey.
2013
02:11:18.985 --> 02:11:24.907
We don't do that as engineering firms, which it's a de-risk capability.
2014
02:11:24.927 --> 02:11:27.828
You get the right staff and other capabilities involved.
2015
02:11:27.908 --> 02:11:30.870
that know their stuff, we're actually de-risking projects.
2016
02:11:30.990 --> 02:11:38.055
But some other engineering firms might look at that and say, well, that's a, you know, that's a, we don't want no problem.
2017
02:11:38.115 --> 02:11:41.617
You know, we don't want, it's a misconception about what survey might be.
2018
02:11:42.077 --> 02:11:43.498
And they're like, nope, we outsource that.
2019
02:11:43.538 --> 02:11:44.399
We sub that out.
2020
02:11:44.979 --> 02:11:49.763
We think it's a risk versus another engineer sees this is a value and a de-risking opportunity.
2021
02:11:50.203 --> 02:11:54.426
So it's going to get flooded, like everybody's saying here, but maybe in a good way.
2022
02:11:55.732 --> 02:11:57.313
In addition, the noise is coming.
2023
02:11:57.333 --> 02:12:03.878
It's already here, like you said, but if you target the right folks in the right companies,
2024
02:12:05.075 --> 02:12:05.656
I think there's a way.
2025
02:12:05.676 --> 02:12:08.157
And then maybe one last component is like the folks that are learning.
2026
02:12:08.938 --> 02:12:09.899
Folks are vibe coding.
2027
02:12:10.239 --> 02:12:14.342
Folks are learning that capability right now.
2028
02:12:15.122 --> 02:12:21.587
But there's other kids and other things that are learning the right way that are picking it up and doing it right.
2029
02:12:22.107 --> 02:12:25.890
And, you know, I think the future is bright for a lot of these young folks.
2030
02:12:26.530 --> 02:12:30.292
stars, I call them, that are coming in and saying, I want to learn from the right mentors.
2031
02:12:30.432 --> 02:12:32.174
I want to learn from the right capabilities.
2032
02:12:32.914 --> 02:12:35.976
And I want to find the right resources to learn.
2033
02:12:39.840 --> 02:12:44.982
That's in the noise, but there's some gold nuggets, you know, some gems in the noise, I believe.
2034
02:12:45.422 --> 02:12:48.683
Futuristic one for you, where things could possibly go.
2035
02:12:48.703 --> 02:12:56.626
I know in the drone world, we're talking about BV loss and drones, you know, drone in a dock and all of these things.
2036
02:12:56.666 --> 02:13:08.071
The thing that's interesting, and this is something that I know that, especially talking about critical infrastructure, we never know when the thing that we want to find happens.
2037
02:13:08.942 --> 02:13:19.766
So my thought for the future is, what if we get to a point where data capture is almost instantaneous and persistent?
2038
02:13:20.046 --> 02:13:20.406
Almost.
2039
02:13:20.606 --> 02:13:23.207
Like, there is definitely persistent surveillance systems, right?
2040
02:13:23.727 --> 02:13:24.467
Near real time.
2041
02:13:24.507 --> 02:13:27.288
Time dominant, as we would call it in the ISR world.
2042
02:13:27.728 --> 02:13:28.028
Cool.
2043
02:13:28.408 --> 02:13:29.769
We have now time dominant.
2044
02:13:31.388 --> 02:13:44.731
I think if we're looking at the future, I think that's probably where it's going, where everything's not just connected, but I can get a real look without deploying a person, not rolling a truck, not even launching.
2045
02:13:44.811 --> 02:13:52.372
I mean, it could be a launch out of a dock, but but even more than that, there could be persistent surveillance at these critical infrastructure sites.
2046
02:13:52.412 --> 02:14:00.234
That's able to do this photogrammetry or or Gaussian splots or this technology created digital twin every single minute.
2047
02:14:00.754 --> 02:14:12.137
Every like I'm wondering if that is something that we're getting to the technology with the compute with edge with fiber with all of these technologies in the next five to 10 years.
2048
02:14:13.117 --> 02:14:18.618
I see us going there because instead of I need to now deploy an asset even out of a dock.
2049
02:14:19.979 --> 02:14:28.561
I just know for especially for critical infrastructure anytime I need information I don't have to call up a satellite I don't have to deploy a plane I don't even have to play the drone.
2050
02:14:29.790 --> 02:14:30.330
It's there.
2051
02:14:30.510 --> 02:14:34.651
I have the information that I need, and it could be with the embedded sensors that we've already talked about.
2052
02:14:35.112 --> 02:14:42.154
I other IOT devices, robotics, all robotics, flying robotics, round robotics, water robotics, all of those things.
2053
02:14:42.374 --> 02:14:46.035
And just imaging systems and technologies that have been around for a really long time.
2054
02:14:46.055 --> 02:14:46.835
So I already trusted.
2055
02:14:48.336 --> 02:14:52.617
But the lift to get them persistent today is too high.
2056
02:14:53.682 --> 02:14:54.663
I don't think that's going to be that way.
2057
02:14:54.683 --> 02:14:55.583
I think the angles and stuff you need.
2058
02:14:55.603 --> 02:14:58.165
Some of these geometries are, like, really, really complex.
2059
02:14:58.205 --> 02:14:59.646
I mean, maybe so, maybe so.
2060
02:15:00.027 --> 02:15:02.068
But I'm saying you need something that's going to move around.
2061
02:15:02.088 --> 02:15:04.190
If you get some static things or some robots.
2062
02:15:04.430 --> 02:15:05.291
I'm not even talking static.
2063
02:15:05.311 --> 02:15:06.832
I'm thinking things that actually move around.
2064
02:15:06.852 --> 02:15:11.455
Like, I don't know, a flying orb that is able to capture crazy modalities.
2065
02:15:11.495 --> 02:15:14.838
I mean, I think that is actually where things are going.
2066
02:15:14.878 --> 02:15:15.879
Things are getting smaller.
2067
02:15:15.899 --> 02:15:17.320
Things are computes getting higher.
2068
02:15:17.340 --> 02:15:17.440
Yeah.
2069
02:15:17.940 --> 02:15:19.261
And you don't need to save the data.
2070
02:15:19.281 --> 02:15:20.963
See, this is the interesting thing.
2071
02:15:21.223 --> 02:15:24.486
It's an event-driven system that is report by exception.
2072
02:15:25.026 --> 02:15:34.034
So if you're doing edge processing, you have a model, and you're driving your device, and you're looking for something, it is processing as you go.
2073
02:15:34.435 --> 02:15:36.056
And it's throwing away the data it doesn't need.
2074
02:15:36.437 --> 02:15:37.938
So then it just reports by section.
2075
02:15:37.998 --> 02:15:40.660
And you don't have, like, MQTT brokers and data streams.
2076
02:15:41.121 --> 02:15:42.742
It is just pushing what it finds.
2077
02:15:42.762 --> 02:15:43.163
Pushing decisions.
2078
02:15:43.183 --> 02:15:43.603
Pushing decisions.
2079
02:15:43.783 --> 02:15:49.266
Yes, and I mean, you already have the same use cases with fixed sensors, like cameras, LiDAR, radar.
2080
02:15:49.426 --> 02:15:51.727
All of those sensors have been doing this for a long time, right?
2081
02:15:51.747 --> 02:15:53.008
So I don't think it's that far away.
2082
02:15:53.508 --> 02:15:57.590
And they're starting to do edge processing on robots, absolutely.
2083
02:15:58.010 --> 02:16:11.097
So especially when there's repetitiveness in terms of a physical environment, oil and gas plants, things like that, multiple sensors can go and do their round, collect what they're doing, and when they see an anomaly, they report the anomaly.
2084
02:16:11.517 --> 02:16:14.879
I just think we've been teasing it for the last few years now.
2085
02:16:15.059 --> 02:16:17.520
I think within the next five years, it's going to be real.
2086
02:16:17.760 --> 02:16:24.423
Well, it's because AI is accelerating our capabilities to learn and train at an exponential rate.
2087
02:16:24.783 --> 02:16:29.005
That it's just things that I'm able to create today, I just wouldn't comprehend that three
2088
02:16:29.986 --> 02:16:36.591
And I'm going back to like we had a Ph.D. gentleman, Chase, that was A.I., just just a guru.
2089
02:16:37.532 --> 02:16:41.335
But he had found some reports where they did some testing of like some high end folks.
2090
02:16:41.736 --> 02:16:43.617
I mean, as humans, we fatigue.
2091
02:16:44.058 --> 02:16:44.978
So over time.
2092
02:16:45.078 --> 02:16:49.582
But what they did is like even experts that trained and they said, now let me do a stand by stand.
2093
02:16:49.602 --> 02:16:51.764
And at some point, this A.I.
2094
02:16:51.824 --> 02:16:54.747
model that was properly trained started to surpass what.
2095
02:16:55.367 --> 02:16:56.629
the expert was able to do.
2096
02:16:56.709 --> 02:17:05.680
So everything you're talking about is in line with, you know, technically with a good training set, they could do it better, you know, for, for certain tasks and repeatability, right.
2097
02:17:06.020 --> 02:17:09.304
And yeah, atrophy of a human, you know, we're, we're creative creatures.
2098
02:17:09.825 --> 02:17:13.529
We think contextually we're the, we're probably the smartest robots, uh,
2099
02:17:13.589 --> 02:17:15.190
that are over there because we're multimodal.
2100
02:17:15.570 --> 02:17:17.992
We touch, smell, see, communicate.
2101
02:17:18.432 --> 02:17:21.775
So as a human being, we're very complex creatures.
2102
02:17:22.315 --> 02:17:32.662
But we get bored doing repetitive tasks, and we are fallible, and we're not as repeatable as something that is like a robot that's built just to do the exact same thing over and over.
2103
02:17:32.682 --> 02:17:48.411
Well, and the use case, making this very, very personal, is we were working with an offshore vendor to be able to take our models and compare them to CDs, RFDSs and say, hey, is there a difference just between what's documented and what's currently on the tower?
2104
02:17:49.591 --> 02:17:59.857
We literally took AI, same information, input it, trained it, stripped it down, found the process in the same day, same day.
2105
02:18:00.640 --> 02:18:03.822
It took them 48 hours to get to return a product to us.
2106
02:18:03.862 --> 02:18:04.983
Did they get it done in a day?
2107
02:18:05.303 --> 02:18:07.505
Probably, and we just got it later because it was over the weekend.
2108
02:18:08.245 --> 02:18:14.510
It took this model 30 minutes to come the same findings that it took someone to do.
2109
02:18:14.890 --> 02:18:19.193
They were looking over 400 different items, assets on the tower,
2110
02:18:20.586 --> 02:18:25.548
it found the exact same differences in 30 minutes or less.
2111
02:18:25.588 --> 02:18:27.049
And this was just working on my laptop.
2112
02:18:27.189 --> 02:18:29.570
I mean, this is not a high compute anything, it's a Lenovo.
2113
02:18:29.750 --> 02:18:35.253
So what I'm saying is that I think that is absolutely where things are going, where
2114
02:18:36.033 --> 02:18:46.055
These digital twins are now going to be diffed by AI in such a way that every industry is going to be impacted by it.
2115
02:18:46.436 --> 02:18:47.656
I can't see it not changing.
2116
02:18:47.676 --> 02:18:52.817
The automatic segmentation identification and the relationship of data to objects too is huge.
2117
02:18:53.537 --> 02:19:01.239
I was using the one scanner we've been talking about, scanned a major league baseball stadium, chiller room, and all these different assets.
2118
02:19:01.299 --> 02:19:04.440
And I ran it through the algorithm with this software platform,
2119
02:19:04.980 --> 02:19:12.026
Every segmented pipe identified, you know, and I was like 500 objects within, you know, a snap of a finger.
2120
02:19:12.046 --> 02:19:13.588
Then I took the as-built schedule.
2121
02:19:14.188 --> 02:19:21.815
I took it in an AI, a safe AI offline, and just qualified as I deal my data responsibly.
2122
02:19:21.835 --> 02:19:22.796
They tore around here.
2123
02:19:22.816 --> 02:19:23.757
Let's just be very careful here.
2124
02:19:23.777 --> 02:19:24.217
Yeah, that's right.
2125
02:19:24.357 --> 02:19:29.221
extracted the data schedule, digitized it, and was able to relate that data to the object.
2126
02:19:29.581 --> 02:19:33.484
We're talking about a couple hours, which would take days of manual tagging.
2127
02:19:33.884 --> 02:19:38.707
Like, that's where the automation of Digital Twin is going to make this an actual proposition.
2128
02:19:39.048 --> 02:19:40.709
Well, it would be very specific.
2129
02:19:41.369 --> 02:19:43.671
Experts fatigue on the 400th tower
2130
02:19:45.432 --> 02:19:48.533
that engineer that is going to miss something.
2131
02:19:49.033 --> 02:19:51.674
It is no doubt going to happen.
2132
02:19:52.134 --> 02:19:52.875
It's cool.
2133
02:19:53.615 --> 02:19:54.395
Oh, dinner's ready.
2134
02:19:54.475 --> 02:19:54.775
Okay.
2135
02:19:55.296 --> 02:19:56.176
Oh, the dog.
2136
02:19:56.216 --> 02:19:57.336
Yeah, beer 30.
2137
02:19:57.396 --> 02:19:59.217
Yeah, it's almost beer 30 now, isn't it?
2138
02:19:59.257 --> 02:20:02.838
So, yes, I think AI is, that's just it.
2139
02:20:02.878 --> 02:20:04.559
It's now going to say, hey, you know what, engineer?
2140
02:20:04.919 --> 02:20:06.660
I want you to look at these five things.
2141
02:20:06.940 --> 02:20:07.240
That's it.
2142
02:20:07.420 --> 02:20:08.200
Just look at these five things.
2143
02:20:08.720 --> 02:20:10.081
Well, I feel like.
2144
02:20:12.375 --> 02:20:18.994
I would summarize a thought around AI impacting our industry by agreeing with these people
2145
02:20:19.980 --> 02:20:22.823
statements that I think you wanted to say the word.
2146
02:20:22.863 --> 02:20:23.383
Real crazy.
2147
02:20:24.264 --> 02:20:25.005
No, no.
2148
02:20:25.925 --> 02:20:34.533
But, but I still think that a lot of people don't know enough about AI yet that there is still this fear of AI.
2149
02:20:35.153 --> 02:20:42.540
But I still would say with as much as we're saying it's replacing the need for the humans to sit and analyze this for two days, I don't.
2150
02:20:42.740 --> 02:21:03.580
what it's still going to do is create more desire for more digital twin programs, for more value out of the data that still in the short term, in the next few years, every role is still so critically needed because the robots aren't replacing the need to go scan next month or in the next six months.
2151
02:21:03.600 --> 02:21:03.781
Like...
2152
02:21:04.381 --> 02:21:05.162
They're still needed.
2153
02:21:05.182 --> 02:21:06.162
Or to process that data.
2154
02:21:06.242 --> 02:21:13.007
Or process it, or learn how to draft it, or model, or manage the process, even if it replaces parts of analyzing data.
2155
02:21:14.108 --> 02:21:27.258
I would still say all of these new technologies and AI, it still is just fueling the growth of every industry, wanting to do even more reality capture, digital twin mapping, use of data.
2156
02:21:27.398 --> 02:21:32.942
It's really transforming the volume, I think, in the next few years.
2157
02:21:34.334 --> 02:21:36.917
the IT projects are no longer as intimidating.
2158
02:21:37.037 --> 02:21:46.808
Data integration, IoT, all these things are now, they're accessible, whereas they were a closed group that could execute on those projects in the past.
2159
02:21:47.188 --> 02:21:53.755
And the mountains of data can be connected and relationships driven, you know, way faster than ever before.
2160
02:21:53.775 --> 02:21:55.277
Oh, it's like being a stereo compiler,
2161
02:21:55.677 --> 02:21:56.517
way back in the day.
2162
02:21:57.238 --> 02:21:58.938
Like, that was the niche, man.
2163
02:21:58.958 --> 02:22:02.480
It's like, no, no, no, I need this and this and this, and I can only do this.
2164
02:22:02.500 --> 02:22:06.581
And there's a small group of people that can actually do this correctly.
2165
02:22:08.242 --> 02:22:10.603
All those gates are wide open now.
2166
02:22:13.844 --> 02:22:16.665
Okay, we've hit all the topics.
2167
02:22:18.005 --> 02:22:19.186
Well, no, but we don't.
2168
02:22:20.586 --> 02:22:20.866
This is rare.
2169
02:22:20.886 --> 02:22:21.487
The door's locked.
2170
02:22:21.507 --> 02:22:22.387
We're not leaving it.
2171
02:22:23.367 --> 02:22:24.248
That was round one.
2172
02:22:26.958 --> 02:22:35.928
So I think as we wrap up, because, man, the one danger of getting a group like this together is we could sit here and talk about it forever.
2173
02:22:36.809 --> 02:22:46.499
But I do think that what we talked through is going to give some good perspective and insight for people on what is a group like this thinking about the industry?
2174
02:22:46.539 --> 02:22:47.480
Where are the challenges going?
2175
02:22:48.041 --> 02:22:49.162
is there still opportunity?
2176
02:22:49.222 --> 02:22:50.163
Should we be afraid?
2177
02:22:50.183 --> 02:22:54.386
I think, I feel like we've hit pretty good on all of them.
2178
02:22:54.586 --> 02:23:06.356
But I would like to still leave room to go around and, and make sure, you know, if there's anything that you want to share or that you didn't hit on that you would like to, now's your, your final words.
2179
02:23:08.678 --> 02:23:12.141
And we can popcorn style whoever's ready instead of going in a circle.
2180
02:23:15.723 --> 02:23:19.707
I think the last subject we were talking about AI there, I think that,
2181
02:23:21.507 --> 02:23:30.352
our data sets of our models and our reality capture point clouds and the photogrammetry are all just going to be...
2182
02:23:30.912 --> 02:23:36.035
It's just food for the AI engines to munch on and give us back answers.
2183
02:23:36.675 --> 02:23:48.542
And our job is to make sure that they are good, clean, connected data sets so that the... People can start asking these questions of their buildings.
2184
02:23:49.522 --> 02:23:51.764
I want to know how to optimize my building.
2185
02:23:51.784 --> 02:23:54.807
I want to know how to improve the energy performance of my building.
2186
02:23:56.308 --> 02:24:01.253
It will be, they will be asking AI engines those questions.
2187
02:24:01.994 --> 02:24:08.079
And it's our job to make sure that we get all of that data as best we can so that we don't get the rubbish in, rubbish out.
2188
02:24:08.119 --> 02:24:08.900
We actually...
2189
02:24:09.600 --> 02:24:21.424
stop making million-dollar decisions on $10 data, we've got to start getting the right data to match what we need and building it ready for AI.
2190
02:24:21.504 --> 02:24:22.084
Don't fight it.
2191
02:24:23.225 --> 02:24:23.725
Get it ready.
2192
02:24:24.225 --> 02:24:25.865
Yeah, no, that's a great point.
2193
02:24:26.806 --> 02:24:29.747
It's a big question mark around...
2194
02:24:30.803 --> 02:24:41.245
the robotics and around being able to ask data is like, it's just going to drive more need for that information to be able to do all these amazing things that the technology can do.
2195
02:24:41.325 --> 02:24:47.607
So this industry and these technologies and this ecosystem become the foundation for all of that to actually work.
2196
02:24:48.027 --> 02:24:54.729
And again, as soon as an organization gets a taste of that and it turns from, Oh, we just did that for one building.
2197
02:24:55.149 --> 02:24:59.650
Now we need every building and every portion of every building today.
2198
02:24:59.670 --> 02:25:00.430
Take an IFC.
2199
02:25:01.190 --> 02:25:17.036
of a school, put it in, drop it into ChatGPT and tell it some basic information about the construction type and ask it what you expect the optimal energy performance of that building should be, how much energy should it be using and it will give you the answers.
2200
02:25:17.616 --> 02:25:20.197
It will tell you how it's worked it out and that's today.
2201
02:25:21.337 --> 02:25:29.540
And it's only just starting to realize that 3D is a thing within the standard AI engines at the moment.
2202
02:25:29.860 --> 02:25:33.161
And they're starting to realize where the power is in that.
2203
02:25:33.221 --> 02:25:34.201
And wow.
2204
02:25:34.761 --> 02:25:38.583
So that, I think, is going to be the big change.
2205
02:25:38.603 --> 02:25:39.583
We want to ask...
2206
02:25:40.323 --> 02:25:41.685
questions of our buildings.
2207
02:25:42.005 --> 02:25:44.528
And we've got the digital twin.
2208
02:25:44.708 --> 02:25:45.869
Let's go with that term.
2209
02:25:46.269 --> 02:25:48.432
And we've got that data all there.
2210
02:25:48.492 --> 02:25:51.475
And I now want to interact with it by talking to my building.
2211
02:25:52.956 --> 02:25:53.156
Yeah.
2212
02:25:53.176 --> 02:25:53.757
Hello, building.
2213
02:25:54.490 --> 02:26:01.133
What are we going to do today to make you... ...to make you operate better?
2214
02:26:01.493 --> 02:26:04.535
And there was a problem last night.
2215
02:26:04.575 --> 02:26:05.995
Somebody told me that this happened.
2216
02:26:07.356 --> 02:26:08.316
What did you do about it?
2217
02:26:08.496 --> 02:26:09.017
Well, it won't be.
2218
02:26:09.297 --> 02:26:11.098
It'll be saying to me, there was a problem last night.
2219
02:26:11.418 --> 02:26:13.379
And I solved it for you.
2220
02:26:13.399 --> 02:26:14.159
This is what I did.
2221
02:26:14.699 --> 02:26:15.079
Hmm.
2222
02:26:15.740 --> 02:26:16.220
That's awesome.
2223
02:26:16.654 --> 02:26:19.455
Yeah, I think to me, it's you got to paint the vision.
2224
02:26:19.695 --> 02:26:21.396
You know, we know the technologies are here.
2225
02:26:21.416 --> 02:26:23.376
We know things are possible.
2226
02:26:23.896 --> 02:26:26.377
Where do we want to be in our organization?
2227
02:26:26.417 --> 02:26:41.122
And it's important for the HDRs and the leaders that are in our industry to be able to help paint that vision, but then also to break it into bite-sized pieces, into technical roadmaps, and to be able to do really simple proofs of concepts.
2228
02:26:41.722 --> 02:26:45.665
with the data sources that are going to be needed to solve actual business problems.
2229
02:26:46.125 --> 02:27:00.413
And that whole planning part is really important because the trap is we go out and we see something shiny, we implement technology without thinking about the data, the governance, the security, all these things that start to kind of come back at you.
2230
02:27:00.854 --> 02:27:04.376
And you had the hype curve that you start to crash, right?
2231
02:27:04.896 --> 02:27:12.382
So, I mean, there's so much opportunity with whether it be robotics, whether it be AI, with what's happening in reality capture.
2232
02:27:12.402 --> 02:27:21.730
It's really, we need to really know where we're going and have a plan to get there and to quickly fail fast or learn and then have a plan to scale.
2233
02:27:21.910 --> 02:27:23.131
Like, that's the big thing for me.
2234
02:27:23.151 --> 02:27:25.333
Yeah.
2235
02:27:25.659 --> 02:27:34.688
Yeah, I think like this morning, so I have a newsletter I put out every Tuesday, and this morning was about technology, talking about just reflecting on 30 years.
2236
02:27:34.888 --> 02:27:37.150
So, and I'm going to go a step back.
2237
02:27:37.190 --> 02:27:44.297
I started with GPS to AI, but I remember just from our discussion right now, when I started in GPS, I was like,
2238
02:27:45.118 --> 02:27:50.539
I had folks working there that was like, man, we surveyed by chain, like physical chain, and they would, that's how they surveyed.
2239
02:27:51.020 --> 02:27:53.480
And I've worked with the folks that did that.
2240
02:27:53.520 --> 02:27:58.762
I never had to do it, but I'm saying just hearing, so the technology is gonna continue to evolve.
2241
02:27:59.322 --> 02:28:03.443
Just reflecting on that time period too, I think a lot of things,
2242
02:28:04.829 --> 02:28:05.630
It's going to blow up.
2243
02:28:05.930 --> 02:28:11.316
I mean, where we're at now with the infrastructure issues and challenges is nobody's fault.
2244
02:28:11.356 --> 02:28:14.260
I'm just talking about aging infrastructure agents.
2245
02:28:14.320 --> 02:28:14.960
It is what it is.
2246
02:28:15.561 --> 02:28:21.688
So there's going to be a tremendous demand for LIDAR specialists, drone operators.
2247
02:28:21.748 --> 02:28:23.910
I think it's going to, you know, there's a need, you know.
2248
02:28:24.691 --> 02:28:30.953
Drone in the box and other things are coming, that's going to be a complement tool for fit-for-purpose scenarios, not for everything.
2249
02:28:31.413 --> 02:28:39.176
So there's still going to be a need for a ton of drone operators, a ton of LiDAR specialists, a ton of surveyors still into the future.
2250
02:28:39.416 --> 02:28:40.397
I think it's bright.
2251
02:28:40.637 --> 02:28:48.240
So I would encourage somebody looking at the industry to not be afraid of it, to embrace it and really consider it.
2252
02:28:49.240 --> 02:28:49.400
Yep.
2253
02:28:51.870 --> 02:28:53.351
This has been a lot of fun for one.
2254
02:28:53.472 --> 02:28:56.575
So thank you again for inviting us all here.
2255
02:28:56.635 --> 02:28:57.455
This is a lot of fun.
2256
02:28:57.475 --> 02:28:58.957
I hope they just get more fun from here.
2257
02:29:00.338 --> 02:29:09.627
I think the industry is really, really good, especially with the people in this room and the many, many more that are outside are really good at capturing reality.
2258
02:29:10.468 --> 02:29:11.309
We're really good at it.
2259
02:29:12.130 --> 02:29:16.154
I think that the industry still struggles to...
2260
02:29:18.190 --> 02:29:23.554
sell what the reality capture is actually for.
2261
02:29:24.074 --> 02:29:28.037
And that is a decision that someone has to make tomorrow morning.
2262
02:29:29.337 --> 02:29:32.119
That's why we are here, right?
2263
02:29:32.159 --> 02:29:36.082
We need to understand what that looks like and how we best...
2264
02:29:37.057 --> 02:29:50.294
Equip the industry to do that with our experience, our knowledge, our anything that we can with events like this, events like Archon, events like, you know, you have the expo next, like all the things that are out there.
2265
02:29:50.915 --> 02:29:53.118
Conversations like this just need to keep happening.
2266
02:29:53.778 --> 02:29:54.099
Mm hmm.
2267
02:29:54.780 --> 02:29:54.960
Yep.
2268
02:29:57.153 --> 02:29:57.693
Great points.
2269
02:29:58.194 --> 02:29:59.034
Great takeaways.
2270
02:30:00.856 --> 02:30:12.185
Yeah, the only things I would add, one is I think as the demand grows and there is a lack of talent, at least that's where it sits today.
2271
02:30:12.805 --> 02:30:17.509
The one more, you know, one more thing I would throw in is the need for collaboration.
2272
02:30:17.529 --> 02:30:18.390
Yeah.
2273
02:30:19.211 --> 02:30:26.016
There are people and companies and individuals and professionals that are really good at pieces of everything that we've talked about.
2274
02:30:26.576 --> 02:30:28.498
Really good at the survey and the capture.
2275
02:30:28.598 --> 02:30:29.699
Really good at the modeling.
2276
02:30:29.719 --> 02:30:31.520
Really good at understanding the business value.
2277
02:30:32.020 --> 02:30:40.907
This is my whole reason for saying, like, we need to pull people together because the best way to solve all these problems is to actually...
2278
02:30:41.547 --> 02:30:42.368
solve them together.
2279
02:30:42.708 --> 02:30:44.049
Bring those puzzle pieces together.
2280
02:30:44.350 --> 02:30:57.302
You can look at this beautiful puzzle you want to build of everything has a digital twin over the next 10 years, but if all the puzzle pieces are separated and you never put them together, it's going to stay a problem.
2281
02:30:58.863 --> 02:31:06.186
And I think that it's a challenge for most businesses to try to tackle every single aspect of this on their own.
2282
02:31:06.887 --> 02:31:14.190
So building relationships with people across the industry is one of the things that I've seen help solve a lot of the problems.
2283
02:31:14.430 --> 02:31:18.592
Knowing who to call and ask these questions to or, hey, have you tried this platform?
2284
02:31:18.792 --> 02:31:21.173
Or, hey, what was the problem you ran into on that again?
2285
02:31:22.153 --> 02:31:36.006
It's the shared learning, the shared insights, and then you end up finding the opportunities to actually go tackle something together, I think is another big driver because we can't do it all on our own.
2286
02:31:36.547 --> 02:31:40.610
There's no way for one company to trial all these platforms and tell you which one to use and
2287
02:31:41.891 --> 02:31:42.351
It's a lot.
2288
02:31:42.391 --> 02:31:44.552
So I would continue to just encourage.
2289
02:31:45.552 --> 02:31:53.834
Well, first, thanks for coming and talking, because if I put out a post and said, hey, I want to do these roundtables and nobody responded, just get crickets.
2290
02:31:56.774 --> 02:31:58.034
We wouldn't get anywhere.
2291
02:31:58.074 --> 02:32:06.476
So it takes the community buying into this idea of collaboration and sharing and wanting to share their voice, actually showing up and doing it.
2292
02:32:06.536 --> 02:32:08.536
So thank you for doing so.
2293
02:32:09.937 --> 02:32:10.477
You're welcome.
2294
02:32:11.492 --> 02:32:12.000
And, uh...
2295
02:32:13.010 --> 02:32:13.930
It won't be the last time.
2296
02:32:14.331 --> 02:32:15.151
I always say that.
2297
02:32:15.171 --> 02:32:17.972
I always say that to people at the end of the podcast.
2298
02:32:17.992 --> 02:32:19.693
I'm like, it won't be the last time people hear from you.
2299
02:32:19.753 --> 02:32:22.474
So now we just got to get Jason.
2300
02:32:22.494 --> 02:32:24.995
I think the others are all coming to the conference.
2301
02:32:25.015 --> 02:32:29.517
We got to convince Jason to... No, he'll be there and I got to go.
2302
02:32:29.557 --> 02:32:34.439
That's what...
2303
02:32:35.839 --> 02:32:42.302
But no, come to the conference, meet cool people, play with technology, build relationships, and...
2304
02:32:44.181 --> 02:32:45.421
And, ooh, the fishing trip.
2305
02:32:45.582 --> 02:32:46.262
Oh, did you go?
2306
02:32:46.502 --> 02:32:47.322
I'm a little jealous.
2307
02:32:47.342 --> 02:32:48.162
I think I might have to do it.
2308
02:32:48.182 --> 02:32:49.483
And you're in my backyard, too.
2309
02:32:49.523 --> 02:32:55.925
Like, I'm from Vancouver originally, so that's just a short jaunt away.
2310
02:32:56.185 --> 02:32:56.926
It was a good time.
2311
02:32:57.386 --> 02:33:01.647
Carlos had a seat, but work called, and he ended up missing it.
2312
02:33:01.687 --> 02:33:03.688
Fly before you were out of cell service.
2313
02:33:03.728 --> 02:33:05.029
Yeah.
2314
02:33:05.049 --> 02:33:05.509
Next time.
2315
02:33:05.749 --> 02:33:07.449
Next time, just turn it off and say, I was already there.
2316
02:33:07.469 --> 02:33:08.870
That's right.
2317
02:33:08.930 --> 02:33:09.090
Yep.
2318
02:33:10.480 --> 02:33:10.822
All right.
2319
02:33:10.962 --> 02:33:11.505
It's been fun.
2320
02:33:11.706 --> 02:33:12.550
Thank you guys for coming.
2321
02:33:12.871 --> 02:33:15.102
And we will see you guys on the next conversation.
2322
02:33:15.122 --> 02:33:15.263
Bye.