Join René and Devon Tilly from The Art of Construction podcast as they discuss rethinking project management in construction, his journey in creating ALICE, and the magic that happens when we let algorithms do the heavy data crunching, allowing us to focus all our energy on doing our jobs better.
If you'd rather read, here's the approximate (automated) transcript:
"Welcome to the art of construction, the podcast dedicated to helping you grow your business. Together, we'll explore the world of construction with some of the best minds of the industry.
Your host, Devon Tilly, a micro-influencer and sometimes disruptor. We'll take you on a journey that will lead your business to the next level.
What's up art of construction. I'm not going to do a lot of talking today because the artificial intelligence is going to do it all for me. Just kidding. But we're going to go in and we're going to learn about AI through the guru of AI and a company called ALICE. And so art construction, I'm so excited for this is that the main message that we want to convey to you today is that ALICE is an AI-powered construction simulation platform.
They work with some of the world's biggest construction companies to help them rethink the way they schedule and manage their projects, using artificial intelligence. As you know, the construction segment can be slow to adapt new technology, the tools that may use for project scheduling and management.
So the old Excel PowerPoint and P6 they're decades old, right? So ALICE is a breath of fresh air and I'm so stoked to come in and learn about that. Through AI, ALICE enables their customers to create millions of potential schedules at once, and they analyze those options to find the path that best suits their business goals.
So how is this going to be better for this tribe? Companies can save weeks of production, time and millions of dollars in costs. We're going to talk about how we manage with AI those two things we don't have enough of: time and money. And we get to have Rene Morkos, who is the founder of ALICE. And also an adjunct professor at Stanford.
So we have a lot of information coming into studio AOC. So let's go talk about how we can stop scheduling and start optimizing with ALICE technologies, lock and load, tribe.
What's your favorite beverage?
There we go. I, my, my sales manager, I didn't know what that was till he came on board and he loves those things.
So I, I know what that is now. So. Awesome. What is your favorite place you've traveled?
Tell us one story from that.
The bars are crazy. It's really crazy. Yeah. But you're like hanging out and some guys walks in the with machine gun, rocks up, takes a few shots and then sort of, you know, SWAT walks out again, lots of, lots of crazy stories, but not for public consumption just yet.
All right. Well, we'll leave it at that. What's your favorite hobby or interest that we're going to talk about breaking down these construction silos and I'm so stoked to have a master of AI. Cause we've, I really don't know if I know enough about it. And I think it's really good to talk about that and tools around artificial intelligence that we're going to talk about really moving forward, that you, that we passionately call the art of construction, but what do you do outside of that Rene?
You mean there is an area outside of construction?
I'm kidding. I got into mountaineering like three or four years ago, so yeah, I'll do like one expedition a year. Yeah. Awesome. We'll give, I got to hear a story for mountaineering. Give us one experience story from that. I did I was supposed to climb this mountain called Aconcagua, which is a 7,000 meter mountain.
I continued this December, but you to COVID I got canceled. So my last one was the third highest in North America, which is a mountain called Orizaba. So yeah, about. So I think 20,018 and a half thousand feet, if I remember correctly. Wow. Yeah. Sunrise, you know, you're, you're kind of on the mountain.
Sun's rising behind you. Volcanoes kind of erupting in the background. Yeah. Spewing smells super surreal. Super thrilled. One of the best experiences of my life. Wow. Gorgeous view up there. Yeah. And just completely exhausted. I think it must've been like 10 Fahrenheit's freezing, you know, and then got up there, took a few photos.
Yeah. Like life-changing. Yeah. So yeah, I highly recommend it. Wow. What a way to set the stage and from research, it sounds like we could probably spend a whole podcast talking about your life story, but what's the short version. Short version dad wasn't construction gave me a good piece of advice.
When I graduated high school, he's like, son, do anything you want? Just don't do construction. I was like, great. Got it. Know exactly what I need to do now. So first job I would, I didn't like clots. I would cut cut class. I would literally like not go to school and go, go to construction sites. And I had offered to work for free.
I mean, I didn't care. I liked building stuff. I really, really liked that there is something about like changing reality that way, you know, you go home and you're like, it wasn't there before I, before I was here now it's there. It's going to be there for a very long time. No, there was just something about that.
That, that got me out of bed. First job out of school went to Afghanistan. Worked for a contractor, a true story. The slogan on the company, it was horror construction of Stan. Take it easy. We'll build it again. Great, great business model. Lots of repeat customers.
Yeah. So did that for awhile. Truthfully, I got tired of getting bombed applied to a bunch of places. Did my master's at USC then got into Stanford, kept looking for this tool. Really? Didn't find I went to Stanford, started doing my PhD. Yeah. Did what they call an industrial PC six months on six months off.
And you know, six months of work, six months of research, and then, you know, graduated and found the Dallas. We won this competition on campus, this entrepreneurship competition and that kind of kick-started things. And then I was what, six, six, six years, and some change ago. So, yeah. And I've been building this, the world's first generative construction simulator ever since.
Outstanding. So now tell us when, when and where was it that you first saw the potential for AI to help improve scheduling? Oh, that's really easy. There's two specific moments. The first was I was building these land next strips for F sixteens, you know, in Kabul, on the airport. Really exotic destination, you know, kind of an exotic project, but ultimately it was just a slob, you know?
And now I remember sitting there, you know, sun's rising really, really cold. And a lot of people don't realize what, you know, kind of sense in the MLS. Right. Freezing cold, you know, you could see a breath and I'm looking at, you know, this very large slob and I'm trying to figure out how 30, 30 people are the guys.
I was like, okay, do I, you know, put five of them here and then we'll have him do like steel and then move them over there. And then they'll do like formwork work or do I move the former Kaiser? You know, how do I sequence this darn thing? And I remember thinking like, man, I gotta be stupid. Like, can't figure this out, you know?
And so I was like, okay. And then when I left, I was like, I want to go learn how the pros do this. And that's why I wanted to study. Right. Because I got all this responsibility so early, I was managing five projects, 114 people. And so, you know, I. Kept looking for that tool. Right. And that was kind of the first moment, right?
Like really sort of trying to figure out like how to sequence this work. Like what do I do with these 30 peoples the fastest way to build it? And like I said, I, I clearly remember, like I was thinking hard. Like I can't, I can't figure it out and years later, by the way. And then once I started studying AI and started doing the research, I realized like, yeah, these solutions tend to have like, you know, three, four 30, 40 million, you know, solutions.
Right. There's no wonder that you can't kind of figure it out. Well, you can figure out is you always figure out a solution. It's about finding the optimal solution. That's where that's the tricky part. A human will find a solution, right. And then did my PhD, you know, the six months year I was working, I was working for this company in the Netherlands, a little places.
And we're building again, kind of a cool project, which was the cruise ship terminal for the city of Amsterdam. Right. And they were late. There were six weeks late on this darn thing and that's 50,000 years a day. So you can kind of imagine that the mood of the room and these folks are yelling at each other.
And as they're yelling at each other, that the subcontractor was like, it can't work any faster. I can't work any faster. And I get up look out of the window and there's a hundred thousand square foot of empty space and six people standing. And that's when the second thing hit me, which was like, Oh my God, construction sites are empty.
And really, I mean, you know, just drive down any construction site anywhere in the world, or think of any constructions that you've been on. There are pockets of very intense work, but if you walk through the site, most of the area is empty. Then those two observations were basically what led to ALICE. So I went back and started optimizing, how do you increase space usage and measured?
How much space is used in construction sites for construction in general, which is 3%, by the way, it's kind of crazy. Or the asset space asset utilization in construction sites is 3%. I did that experiment in Netherlands and I ended at twice in the us. And so as I was looking at that the, the answer was you know, I started develop algorithms that could increase space usage.
And from there I ended up unraveling the ALICE story.
Wow. Fascinating. So how was ALICE founded then, so that you gave those great examples of those key kind of moments in time. And I really appreciate you sharing that with us because that's, you know, we learn by doing, but then when wins. Okay. What, when did it officially start and then let's get into the ALICE story?
Well, the cool thing about it, you know, it's that there was never any concept of this thing was ever actually going to be worth anything. You know, I have this incredibly golden opportunity, right. To sit in a great institution and just go to the library and read stuff. You know, it was just a fascinating thing for me.
I, I really, really enjoyed it. So I was thinking around with these prototypes now, and I mean, Alison 2011 was like really square dancing on the screen, you know? We entered this competition called basis. It's a big deal on campus. It's like the big entrepreneurship competition. And, you know, we, we ended up beating 103 other teams, some of them, you know, from Harvard, some from Berkeley.
And we won first place. We were voted the best product coming out of Stanford university that year. And the, that gave us $20,000 in prize money, you know, which was. For a PhD student, a hell of a lot of money. Right. And yeah, I mean, that was basically my, my, my annual income. And then, you know, the lawyers called me up and they said, Hey, w w we'll give you this thing called deferred payment.
That's what, that was it for payment. And I said, Oh, you can pay us later. No after you raise all the money. So it was like, that sounds like a scam. So, yeah, so I woke up in a, in a dorm room on campus and I was like, heck, I think I was strong with a company. And you know, then. Like, I mean, one thing led to another, you know, Silicon Valley, I guess that its thing.
I mean the classic story, right? Four guys in a basement, you know, first on campus and then elsewhere, I mean, super, super scrappy. Right. And I was the lowest paid person to Alison till we made any money. And that took a while. Yeah, we were working, huh? 16. I mean, I remember regularly phone calls at like 2:00 AM, 3:00 AM, you know, going through stuff like trying to figure out how to get it to work.
No, it was just a big sort of technical problem. Like how do you, how the heck do you, you know, encode all this complexity with co-construction and, you know, feel that I love. And I'm highly aware on the complexity of it into something that a computer can understand. Right? Most people thought that was impossible.
I still hear that like, Oh, it can't be done. Then we did it. The crack that took us three and a half years, it took me six years of my PhD, three and a half years in the company for us to really say, okay, we've cracked it. We've cracked the problem. No, we've got a prototype that takes all the boxes. So that was kind of it.
I, I really appreciate you open it up. René, talking about how you were skipping class to be out on a construction site to then I couldn't, couldn't stop learning when you found your passion. Right. And that's what we love when we get to have lifelong learners coming to the art of construction and good things happen when you say.
You know, we just kept scrapping and kept working until we figured it out. So I want to kind of get into the weeds and talk to us. How does the tool work now that you said we've cracked the code and how do you upload projects, details and you know, what are the different products of Oh yeah. So, so, so it's, it's, it's really cool.
So here's, here's basically the question that you're trying to answer, right? It's how the heck do you encode all this complexity that you call construction into something that computers can understand. And the solution actually is almost counterintuitive. And here's why what you have to do is you have to split split planning from scheduling, right?
You've got to split the rules that govern your construction project away from the solution of how it's going to get built. And that's the thing that has never been done before. Right. And so in the planning stage, you set up a rule set, you say state, basically things like, and it sounds very abstract, but it's actually very straightforward.
What tasks do you need? What resources do you need for those tasks? What objects are you building? What are they? Production rates or calendars, right? What resources are available, right. Really really common construction language, right? You set that up in the plan and you send it to the, we used to call a scheduler, but we now started calling the simulator.
That's the big deal because ALICE doesn't schedule sheet simulates. ALICE is actually moving those crews and cranes and all of that stuff around to build your project will then you know, the computer. And so that's basically, you know how we did it, right? You there's three phase the software, you set up the plan, you set up the rule set.
You send that rule sets to the simulator that crunches all those rules for you. That's the really boring part. Why anybody would want to spend their life crunching constraints is beyond me. And then, you know, I generates millions of solutions, picks the best ones for you to analyze, and you can click on those expanded and each simulation has a schedule estimate 40.
And advanced analytics with it. That's that's how it works. Three phases. Right? The product currently has to the platform, I should say, as two products, which is the preconstruction product and the managed construction product. So in the pre-construction product, you set up the rules, set, run, lots of simulations explore as we call it.
For the first time ever, you can explore options in great detail, generate them and then select them and, and, you know put them for, you know, take them for construction. Right? The other product that we have is managed, which is once you've selected an option, now you update progress on the fly and the tool is incredibly powerful.
It can, you can update progress and then say, you know, what's the impact on my schedule, what's the impact of the delay on my schedule. If I do nothing. That's fairly easy. Lots of things can do that today, but the really cool thing that nothing else can do is you can say, well, okay, re sequence around that delay, try, you know, adding cranes, try and Incruse try changing the whatever crane radii.
I try, you know, adding over time, try faster and concrete try re sequencing and the tool will do all that for you. Right. Crunching moons and Moana simulations, and then give you the optimal solution to mitigate whatever delay you're on. Gold. So I'm going to try to recap what what I heard from you there, René, and you challenge me if I'm missing something because I'm just blown away right now with what you're saying and want to make sure the Arctic construction tribe is getting all this.
So what we went out to solve is how do you encode construction complexity that we can understand is that w did I hear that kind of the overarching, is that accurate? How do you encode. All the complexity, we can call construction into something. A computer can understand. Yeah. Awesome. So, and, and then you planning broke away from scheduling is two kind of key things of aha moments.
And then you turned scheduler into a simulator. And I think that's really an important thing where you said, because I've been learning the words matter, right? Scheduling is different than, than simulation, but you're taking a tool that's managing those things. Yeah. And then you break it down into plan with rules, setting the rules to output solutions.
And that's where I'm hearing the art is where the artists are doing this planning and design. The, of is the gooey middle that nobody wants to deal with the rules and the complex and all the stuff that we get stuck spending a lot of time of. And the solutions is the construction and construction is messy.
Right. And you talked about how can we reschedule around delays? Cause that never happens. Right? And so you talk about how you can put in fast drying, concrete versus applying over time and solutions to actually be able to manage the of so you can be better artists and better constructors. Is that what I'm hearing?
Do you hit the nail on the head? That's exactly it. That's exactly it like a lot of people don't realize what, you know rather it didn't eliminate the need for architects, right? The value of an architect is not creating copies of blueprints, the value of an architect. Cause they understand space and, and time and all that.
Right. The value of a structural engineer, isn't sitting there with a calculator, you know, crunching out, you know discrete element calculations, how structures work, they set up SAP. Right. Snap 2000. And that's the art, right? Same thing with Ellis. It's exactly what you said. That plan, that rule set.
That's what the construction experience gives you. ALICE does not do that by itself. It's th the, the art of setting it up, you set it up and then you interpret the results. So that's, that's exactly how it works and you let them go. Yeah. I'm so passionate about the, of the data, the building information, modeling people forget about the information, and then they get confused by the information.
Right. And so those that, that gooey center. Is something that we're trying to fast track. When you talk about back at the beginning, when you said a hundred thousand square foot of space, and there's only six people there. Well, maybe these people, instead of doing the gooey middle could get back out on the job site or using other tools to build better buildings, which is the passion or underlying tone of the art of construction and why we're honored to have affiliates like ALICE to help share our stories of all the time you put into it.
Right. I, this is a. When you say we're a construction company that, that happens to make software. Right. I really love this field. Like this software is really designed, you know, who designed it, who I design it for. It's designed for that person, that project engineer, when she's on site and she's thinking drought, it's 7:00 PM.
And I know I've got another two hours to basically, you know, work through this. Right. And you're stressed, there's liquidated damages. You're trying to figure out like, you know what. You know, what what do I do, right. And, and you now have this incredibly powerful tool that can crunch a heck of a lot of computing.
I mean, the thing that's, that's incredible, right, is that you can buy an hour of Amazon, easy to crunch time for 1.30 cents. That is like, trust me, that's mindblowing. Like you can buy that much computing firepower for one sentence. Right. Well, we figured it out. We were like, wait, you guys are going to sell us.
Like what. Like it's crazy. So why the heck not leverage it? Right. And to me, like the point is that folks and construction can go home earlier and there's less risk I've been in those projects. Right? The, when those liquidated damages kind of looking down the barrel. Yeah. Right. And it's not a good feeling, your career's at stake, you know, heck you know that somebody could get fired.
Somebody could lose their job over this. It's it's stressful. And this is what this tool is designed to do. Right. It, it, it it's, it can't do everything in the world, but it can crunch a hell of a lot of complexity and give you some really, really key insights that you haven't been able to do before.
Awesome gold. So let's get it. What kind of projects is, is best suited for? Cause I, I raised my hand and say, I'm blown away by what you just said, Amazon in 1.30 cents. But I, I don't quite get that, but I wanted help the art of construction tribe. When you talk about that person that. Wants to not ma not have the stress of the work and wants to leave at a decent time to go home and be with their family at dinner versus out there saying, I got to just keep hustling through this to figure it out.
And so what kind of project is ALIS best suited for? And to what degree is the computing power of ALICE's AI better at scheduling those projects than humans would be to manage the two things we don't have enough of time and money. ALICE is best suited for projects where you actually care about how it's getting built.
And what I mean by that is that projects that have resource allocation requirements. How many crews, how many cranes, what production rates, so on and so forth. The projects that we've seen really big success on is in our infrastructure. Because they tend to self perform their work, these production rates, they have a clear idea of how to build it, right.
Renewable energy, for example, solar wind. We've seen a lot of success with, right. The tool itself can run any type of project. Which we've, which is interesting. We've run out on anything you can think of from parking lots to $3.7 billion airport you know, oil and gas pipelines and so on and so forth.
Right? The sweet spot is PR like self-perform infrastructure you know, renewable energy tunnels. Bridget, you know, anywhere where you have resource allocation requirements, like I care about how it's getting built, which crews are doing, what, at what time, what my production rates are, you know, production level schedule.
So that's basically where we see a lot of success. And there's one more question, which was. Great answer. So what kind of best suited for, and I'd love a, at the end of this next question, and maybe say we're big on modular design. And I think that would be a key thing of blending offsite and onsite construction.
If you guys have done anything with that, but the other question of this, a part of the series is what degree is the computing power of ALICE's AI better at scheduling those projects than humans would. I can give you a great answer to that question. We've noticed a pattern at Stanford over the last couple of decades.
And that pattern is as follows when you use algorithms or AI to generate lots and lots of solutions versus comparing it to a human solution. One solution that a human created, right. Or two you'll tend to see about a 20, 25% improvement. Right. And we've seen that sort of over and over again. Pretty pretty neat piece of information and unsurprisingly with ALICE, you'll see those numbers, right?
I think the average duration savings are about 17%. In average labor and equipment savings are about 13%. That's just fascinating. Have you guys done anything with blending onsite and offsite construction and the shoe boxes? Is it calm, but all the, you know, the future of taking the parts and components to, for the industrialized construction in Dallas, Oh, yeah, modular and prefab.
It turns out, and this was a surprise to me that modular construction companies or, or sites like shits vertically integrated modular, and prefabrication companies have a higher need for something like this. And the reason is that because what people don't realize is the factories that produce the prefab have still limited capacity.
So the question becomes, okay, well, if I've got 10 pre-fab panels, which constructions are those send them to, right. Or if those panels are delayed, what do I do on site wallet waiting for them? Right. So there's lots of different kinds of Applications to the right. I mean, ALICE is effectively, what we've done is digitize the single unit of demand, which is a construction site.
You have a simulation that that's, that's alive and kind of breathing, I guess, but, you know, you can build this thing over and over again. So whatever it is, you can. CD immediately see the impact of prefabbing that this element versus that element of, should I focus on prefabbing this thing? Or should I, you know, if the children didn't show up or the pre-Title owners and they show up, what should I do?
And so, yeah, we've, we've done quite a bit of work in that regard. Yeah. That's fascinating. And what, with all the different components, it sounds like you can better control things that it feels like you can't control are out of control because there's the, you don't, you can't manage those algorithms yourself.
Without a tool like this. Yeah, absolutely not a complete grade. There's too many, too many variables. Like most people are, and this is, this really just, just angers me right? When people are like, Oh, construction, that's sophisticated. Right? And that's like BS. Right? We build the biggest, most complex things in the world.
Period. The biggest operations problems, the biggest operations, some management problems, operational problems are in construction. Right. And the reason by the way that we are behind other fields and digitization is precisely because it's more complicated than everything else. That's why we have to wait for, for design to get digitized.
Right. It's like, I mean, I really, you know, digitizing something like banking. I don't know what a joke like, that's so simple and these, you know, bankers think they're so sophisticated. It's like, yeah, obviously you guys think it's just to get it because you've been, do you digitize your field, you know, 20 years ago, the easiest thing to digitize.
For us we've had to, until now the processing speeds, weren't fast enough to crunch BIM BIM as a technology that was invented in the eighties. But because buildings are bigger, more complex than machines, which is where parametric design was first used. We have to wait till the early two thousands for us to be able to do parametric design, which has been right for architecture.
It everybody in the art of construction as to hear what you just said, because you put it into context because we get confused like, well, am I doing something wrong? Like w w why are people telling us this? And one of my mentors, he's like, I own a window and door company in Colorado. And there's a lot of complexities to windows and doors because they're the structural element of holds up a building.
But they're also this beauty cap, both inside and outside of. Every building right with the hood ornament, walking through the front door. Right. And so I've always been passionate about windows and doors. And one of my mentors was like, Devin, you know what? I've owned a window company for 30 years. And, and people always used to always say, it's not rocket science, it's just windows and doors.
And he's like, you know what? You Dex X actually just sold his window dealership last year. And he said, I spent the last five years saying, you know what, God dang it. It is rocket science, what we do in this. Right. Because there's so many moving parts and complexities. But the key thing that I heard from you was the computational power to actually make computational design, be a key thing, and then getting the warriors and the true heroes out in the field with a smartphone that can have that computing power to connect the field to the office.
That's what had to get done. Right? Yeah. I mean the, the first thing I have to get digitized is the input to construction and design. We wait for the engineers or the architects to finish their jobs. We can go build it. That's what we do. Right. And so until we digitize that piece of the puzzle, we could not digitize construction.
Right. The other thing that I like to point out is like, yeah, because people in construction are a little bit skeptical. Most of the stuff that has been thrown at us has sucked. Yeah, then was supposed to then was supposed to solve all these problems. Right. And you read these, these, these conferences from the eighties, right.
It was going to be this like magic bullet and centralized information, you know, database, right. Where you would like run all these, all these Elise you'd save all of the simulations, the, the, the architecture, the construction engineering, the acoustics, the lighting, everything would be in this kind of central model.
Right. But them up to now has been a design tool. It is not been a construction tool. And, and I, you know, yes, you can do clock detection. Great. That's still a design, you know, issue.
And, and, and, and it's changing. I mean, you know, it's, it's, we were wrong the last, you know, industries to get digitized, but also the incredibly good news is it's happening and it's not just ALICE. Right. And you know, like any anywhere else. Sure. You know, the, the, the real innovators are, the companies are doing incredible work.
There's fewer of them, but they are there. And what's what's happening. This is the most exciting time to be in construction. My mind in the last, probably 2000 years, because what's happening in construction is there's a new ecosystem that is coming at us. And I'm convinced of this. The value of the fundamental value proposition of the general contractor is going to change over the course of the next 10 to 15 years.
Yeah. And René and it's people like you that have went and put in the time to actually make a tool at work. So we're so honored to have you be a leader of the tribe to talk to this. So can you dive, dive a little deeper into the solutions of ALICE and does this relate to concepts like generative?
That's what ALICE is. ALICE is a genitive construction. So, so for anybody on the call that doesn't know what generative designers you'll be an expert in about 30 seconds. Right. And so, all right, listen up here, tribe, let's say you're designing a cylinder, like a cup of some sort, right? So, you know, you draw like a circle, a circle and a plane between them.
Right. Does that make sense? Perfect. So if someone comes along and says, Hey, I want a bigger cup. You want, okay, we'll drop. You got to redraw everything. Someone comes along and says, I want a smaller cup. I'm like, okay, you're going to redraw the cup every time there's a change. So somebody came along and said, no, no, no.
I'm going to have these things called parameters. I mean, on a hiding a radius. Right. And if I want a different size cup, I'll change the parameter and the tool. Redraws the option, right? That's a parametric design tool, right? So generative is I'm too lazy to change the parameters manually. I want the computer to do that for me.
So generally the tools you'll tend to give it ranges, right? I want you to try all the Heights from, you know, whatever one inch or two inches to three inches, and I want you to do it by 0.1 inch or, and the tool that goes through all of those, those options, and usually calculate something. So the, in, in architecture, usually what you're calculating is rentable area, you know, And so, you know, the tool goes, it goes through like, like tens of thousands of iterations of the design.
The building gets bigger and smaller and rotates and all that sort of stuff. And you know, it spits out like here's the big is the most rentable area that you need. You can have Syngenta design has been done in design since, like I said, the eighties, it was, it started mechanical engineering. The technology by the way has been available.
I think also since like the late eighties ArchiCAD, right. The problem was the processors. Buildings are bigger, more complicated than engines. The processes were not strong enough to crunch this and that started to happen in the early two thousands. Right. So, yeah. And so then janitor construction is, is basically, is, is that it allows you to generate long sorts of options.
You know, the computer generates you foreign calculates in our case cost in time. Right? I love it. Can you, can you talk a couple of case studies? So like what kind of companies had the most success using Allis and what those are? Yeah, so we did on a lot of work, for example, with Parsons Parsons construction.
We did a highway with them in Canada, you know, worth somewhere around half a billion dollars and humans with P six, you know, versus the humans with ALICE. Two separate teams working and the humans with ALICE found the solution that was 69 days faster and 34, I think, or 35. I forget that those days were, were accepted, you know, by the project team.
And so that's, that's one option. We did another project with one of the largest construction companies in France tunneling project figured out a, save the need for a TBM. On that project, right? A tunnel boring machine a really interesting project. The big deal with tunnels is removing the soil.
I actually did not know that, but so Alice model, all irregular stuff, right. Which was crews and cranes and sequence and all that kind of stuff. And then also modeled in a removing the soil. Right. We've done we just did a commercial job where the build group, right. And that was that was on the, you know, seven, 7:00 PM.
ABC news, I think. But we figured out how to reduce the number of amount of format required from 10 to six. Right? Yeah, lots of, lots of projects around the world. You know, we've got clients, we started running projects now with McKinsey and Accenture, really, really great work we've done with them.
We've run. Other clients are, you know let's see, wig, Austin bridge and road. We have kicked off large wind farms in Australia, for example, and I'm talking, you know, North of a billion dollars. So yeah, hopefully that gives us a better idea of where we're at. Awesome. Well, I'm curious, how did the name out?
Why the name Alice. Pretty easy. It was about three 42 in the morning. I want to go to bed. I'm like, you know, I need, I need a name, you know, cause th the tri constraint method, which was the PhD title was with probably not going to not going to ring. So I was, you know, it was like a candy in the name, like, you know, probably something with an, a.
Like, you know, artificial, artificial construction, AI, artificial, construction engineering, a a Alice. Okay, cool. That was like a three-minute process. You know, it was like artificial intelligence, construction, engineering. Great. I was, I was literally thinking like, it's a good place holder. I just want to go to bed and we'll, we'll come up with a better name later, you know, that's like six years on.
It's like, okay, we haven't come up with a name. So I guess we're stuck with it. I just adore these conversations cause it's like how it really happens and how much good shit can get done when you thoughtfully get shit done. Right. It does. Does that really matter? Right. I still think this story's cool.
When you talk about, you know, artificial intelligence, like that's just how the mind and how the algorithms worked in your head to put it together. That's awesome. So we talked about it earlier about. You know, th this whole misconception of it's going to artificial intelligence is going to take over my job, but I get such a, it just drives me crazy.
Cause on the other, and you talk about how there's nobody, construction's not sexy and it's, we can't get people to work in this field. And like, I'm so passionate. We're actually. Putting a whole podcast where I'm bringing in and we're going to really start dedicating and speaking to the warriors in the field and really elevate the trades.
You talked about those big companies you work with, but who's the hero that went out and made it work. Right. And so what's your take about the whole stigma of this is going to replace. Project managers or are you like me where it's just project managers is going to help us all do our jobs better because we still need a lot more people to do these new things.
It's just changing how they are. Construction is done. What's your take on that René? Absolutely. The, I was told something really cool by one of the innovation guys, Exxon. Right. A gentleman called they need Vermont. And what he told me is that what technology does is it changes the art of tomorrow and the science of today.
And so what he was saying was, and I, and I really was like, that's exactly it, that's a really good explanation. Here's an example. Right. You know, today's technology, let's assume it's you think of P six, right? Primavera or Xcel or whatever you use it. Right. And so what that does is it does some crunching for you, the, you know, the, the crunch of some of these variables for you.
And then you got to add a layer of human intuition or intelligence on top of it. And today, in my opinion, that that layer is really substantially a heavier lift. Right. What technology does, is it changes? What would that layer of intuition into science, into number-crunching? And so what else does is, is it really moves, but does a lot of that number crunching for you and now enables you to push way past that with your intuition again?
Right. The comes up like AI, taking someone a job. I'll tell you when it will. When a computer has consciousness and it will wake up in the morning and think that itself, I need to build a hospital and it will go down to the bank and basically secure it $250 million loan and figured out that it needs to build an 80 bed hospital.
Yes. That then, then when he could work I have not seen any generalized AI that is successful as of yet. And I still believe that we are some time away from it. Right. Whether we will crack it or not. Right. And so in terms of, you know, people inside being skeptical, like, yeah, like I said, there's a lot of stuff out there then that has not been great.
Right. And, and in this changing, there are a number of companies, you know, that are doing really, really cool stuff. Right. But Yeah. In terms of in terms of artificial intelligence, taking someone's job, like we have not seen it. We have not seen like every single time is the exact same pattern. The AI becomes a thing doing the crunching, the human does.
What's sets up what needs to be crunched and then interprets the results. Right. And that's the same pattern over and over again. I have never seen, you know, AI. Remove someone's, you know, take someone's job. It will. And I'll tell you what if, what you want to base your career on is crunching numbers.
Then I hope your salary you'll be happy with a salary of 1.30 cents an hour. Right? If you want to base your salary on something that tells the machines, what the crunch, then you will have a very safe job for a very long. The name of the game is how many machines can you control? That's what it's it's it's about the construction company of the future will be successful based on three things.
How quickly can it identify cutting edge technology and startups? How quickly can it evaluate those technologies and how quickly and effectively can it integrate those technologies, this current workflow? That's what the game's about. And the reason startups exist is, is in some ways we're merely the R and D arms of these giant companies.
The only thing that's changed is that they have a little less control because they don't own it, but the hell of a lot less risk, right. The VCs have taken the risk. Right. But it's, it's the name of the game is how many machines can you control? That's basically it, there, you have it. I mean, there is the way it's going to work.
And I, when you, when you understand the science, which we believe in the science behind that, then the data becomes real information and the building information modeling and the parametric objects and all of these things come to life with the computational power. So what's sort of going ongoing working relationships.
Do you have with your clients and what, what is your customer support look like? For your customers ongoing as everybody I'm sure is intrigued and want going to come check out Alice. Yeah, thanks for asking it. So we've kind of figured this part of the puzzle out at this point customers come to us, they you know, ask us about the tool, give some demos, answer questions, hopefully very difficult technical questions.
At some point, you know, 98, 99% of the cases, people are like, Whoa, this looks serious. Like I want to try this out. We usually sign a contract put that in place 12 months and we train you. We basically give you a crash course and artificial intelligence for construction, generative, construction, parametric, construction, all these concepts.
How does it work? Right. There's a theoretical body of knowledge that we share it with you, right? That's the first step we share the theory. We share the tool. We run you through examples, and then our team basically gives you a white glove treatment and helping you set up your first project. People tend to learn the tool very quickly.
You know, it, it takes truthfully as soon as many times, you know, day and a half, two days to learn the tool in a really advanced way. Right. When people learn the tool and then they're off to the races. And that what's really for like in the last, you know, in three months we've had people come to us and said, I never thought I'd say this, but I actually like scheduling.
Right. And it's fun. It really is like, cause you're, you're spending time on the fun stuff, you know, you'll pick up to do the crunchy food because if you're in the people business, which I love people, but it drives me crazy when schedules don't work. Right. So if you can get back to the art of scheduling, but have tools to help you with that, it becomes fun again.
That's just fascinating. So we're going to, how, how can people learn more and try out Alice now that we got them all intrigued and thank you for all your information on. How AI and how Ellis came to be on our website. Alice technologies.com. There's a, there's a contact sort of form, fill it out, let us know what you're working on and we'll happy to help.
We're also going to be launching a course on Coursera, even though that's probably, you know, maybe six, eight weeks away, but folks will be able to kind of take the class, so to speak and see what the technology can do. Awesome. Well, we'll make sure we put links to everything in the show notes. We make these global and timeless, but there's the only constant is change.
Right. And we'll continue to put all that information out there and we're honored to have you come in and share your story and be part of the art of construction tribe and close out. We always ask this question that I'm asking fascinating when we get leaders of the tribe to come in and kind of give us their take.
But René, what is your crystal ball for connecting technology to handshakes? And the future of the art of construction results, right. Create something that, that friggin works and works incredibly well. And if you do that, then the handshakes will happen in the future of construction will happening.
Right. Awesome. Well, what is that one thing you want to leave our warriors out there in the art of construction to think about, to go out and crush it, to grow their business? What is that one thing you want to leave us with René? The name of the game is how many machines do you control. Awesome. Thank you so much for coming in, sharing us your story.
Thanks so much. Really appreciate it. Thank you.
Wow. I'm going to be listening back to that one a few times to really take AI in my business and hopefully your business to the next level tribe. I love so many lessons learned on that. And a few of them, I just want to highlight is that tribe. We are lifelong learners and doers, and we will always find a solution to get shit done.
And that's what we do on the art of construction. But there's times when you have to pause and say, How do we find the optimal solution? And that's what René has shared with us. Right. And so the comments that he said, the quote and reference from the Exxon, I believe he said it was art of tomorrow into the science of today.
And, and that just hit me right in the heart because that's how I started this thing. Like I was so sick of the way it was done, and I only knew what I knew. Right. But I wanted to get out there and learn more as a lifelong learner in the Arctic construction. And we started this global megaphone to say, build a movement and then you'll get to have leaders like René, come in and talk about his story of how we do that.
And you know, a computer is not going to take over the world. It's you are to construction, changing the algorithms and how we work with machine learning. An AOC can take over the world, and that's not just this brand, but it's truly the art of construction. Right. And we have the right to be suspicious. I love how he kind of called us out in the industry and how things work.
Right. Because. When he talked about, you know, 19 in the eighties of them is going to change the world. And here we are recording this at nine 53 on March 24th of 2021 mountain standard time for this timestamp. I think people are still most willing, not BIM stands for that live in construction. Right. And so, as we talk about breaking down these silos, we have the right to be suspicious, but I can tell you when we have leaders, like we just said, Steve burrows back in and he says, I truly believe this is the greatest time to be in construction.
And René who's lived passionate and construction the same way. Right? This is the greatest time. But you better not bury your head in the sand again, because it's easy to get jaded because it's the greatest time to be in there to construction. If. You look at it and you understand the new rules of the game and go back and listen to this because René shared with us the rules of the game, and it boils down to how many machines you can control with the right core values and the people pulling the valves. Thank you so much, René and ALICE, we're big fans of what you're doing and we can't wait to have more collaboration and conversation through AI on the Art of Construction, crush it out there, tribe.