1 00:00:06,000 --> 00:00:08,719 Speaker 1: Welcome to the Fear and Greed Business Interview. I'm Sean Aylmer. 2 00:00:09,039 --> 00:00:10,920 Speaker 1: Listeners get in touch with us all the time on 3 00:00:10,960 --> 00:00:13,840 Speaker 1: this podcast. Sometimes it's a common about a story. Sometimes 4 00:00:13,880 --> 00:00:16,479 Speaker 1: they've got feedback. Sometimes it's because they're doing something a 5 00:00:16,480 --> 00:00:19,119 Speaker 1: bit different and want to tell people about it. Today's 6 00:00:19,200 --> 00:00:22,120 Speaker 1: interview is one of those. Recently we were contacted by 7 00:00:22,200 --> 00:00:26,400 Speaker 1: Joel Bell, a former Australian Army engineer now living and 8 00:00:26,440 --> 00:00:29,319 Speaker 1: working in North Carolina in the US. Also a fan 9 00:00:29,400 --> 00:00:30,880 Speaker 1: of Fear and Greed for the last five years, so 10 00:00:30,960 --> 00:00:34,120 Speaker 1: we like that. He's a director of Bot Built b 11 00:00:34,200 --> 00:00:37,000 Speaker 1: U T b U I L T bot Built, a 12 00:00:37,040 --> 00:00:41,320 Speaker 1: startup using robots to build houses. Joel joins me this 13 00:00:41,400 --> 00:00:43,680 Speaker 1: morning from the US. Joel, Welcome the Fear and Greed. 14 00:00:43,920 --> 00:00:47,800 Speaker 2: Hey, Sean nicely on the call. Long time listener, first 15 00:00:47,840 --> 00:00:49,560 Speaker 2: time caller. Is that how we do it? 16 00:00:50,120 --> 00:00:54,000 Speaker 1: That's something like that that'll do? Tell me Bot Built 17 00:00:54,800 --> 00:00:55,680 Speaker 1: what is it exactly? 18 00:00:56,280 --> 00:00:59,200 Speaker 2: So? Bob Build is a tech startup based in North Carolina. 19 00:00:59,280 --> 00:01:02,040 Speaker 2: As you mentioned, we use robots to build homes and 20 00:01:02,160 --> 00:01:06,200 Speaker 2: what that means is we rescue automotive robots who used 21 00:01:06,200 --> 00:01:09,400 Speaker 2: to build cars. We say rescue because we buy them 22 00:01:09,440 --> 00:01:13,120 Speaker 2: secondhand on eBay. We give them an a lily. Yeah literally, 23 00:01:13,200 --> 00:01:17,959 Speaker 2: on eBay they go out of tolerance for automotive manufacturing. 24 00:01:18,760 --> 00:01:21,640 Speaker 2: So we buy them, give them an AI powered brain, 25 00:01:22,360 --> 00:01:25,640 Speaker 2: and we have them build house frames so the walls 26 00:01:25,680 --> 00:01:27,600 Speaker 2: are the house. We use them to build those. 27 00:01:28,560 --> 00:01:33,119 Speaker 1: Wow. Okay, and I presume if you've got robotics building 28 00:01:33,360 --> 00:01:38,040 Speaker 1: the frames, things like tolerances and measurements and stuff like 29 00:01:38,120 --> 00:01:39,760 Speaker 1: that are pretty spot on. 30 00:01:40,280 --> 00:01:44,280 Speaker 2: Yeah. So the way the system works is we first 31 00:01:44,400 --> 00:01:47,400 Speaker 2: take the PDF floorplan so you could send me a 32 00:01:47,440 --> 00:01:51,160 Speaker 2: blueprint today. We have artificial intelligence that we've developed that 33 00:01:51,320 --> 00:01:54,240 Speaker 2: reads that blueprint turns it into computer code. So we 34 00:01:54,320 --> 00:01:57,640 Speaker 2: pick up every dimension, every door, every window, or the 35 00:01:57,680 --> 00:02:01,400 Speaker 2: ceiling and floor joist layouts. We put that into the AI, 36 00:02:01,520 --> 00:02:04,440 Speaker 2: which writes the code for the robots to follow. And 37 00:02:04,560 --> 00:02:07,360 Speaker 2: then the really cool part is that we don't tell 38 00:02:07,400 --> 00:02:09,760 Speaker 2: the robots how to build the house. We tell them 39 00:02:09,840 --> 00:02:13,359 Speaker 2: what to build, but the artificial intelligence inside the robots 40 00:02:13,840 --> 00:02:16,400 Speaker 2: goes ahead and plans all that all on their own, 41 00:02:16,480 --> 00:02:19,440 Speaker 2: so there's no human involvement. We joke that all the 42 00:02:19,520 --> 00:02:22,040 Speaker 2: humans have to do is reload the nail guns and 43 00:02:22,120 --> 00:02:24,359 Speaker 2: the robots go ahead and build everything exactly as it's 44 00:02:24,400 --> 00:02:27,160 Speaker 2: drawn on the plan by the engineer, very few errors. 45 00:02:27,240 --> 00:02:30,480 Speaker 2: Every nail's perfect, every stud's in exactly the right place, 46 00:02:30,960 --> 00:02:32,639 Speaker 2: which means that we get a really good result for 47 00:02:33,040 --> 00:02:34,920 Speaker 2: the homeowner at the end, but also the builder saves 48 00:02:34,919 --> 00:02:37,560 Speaker 2: time and money. It's a very cool product. 49 00:02:38,680 --> 00:02:41,600 Speaker 1: How did you end up a lot in that? I'm 50 00:02:41,639 --> 00:02:44,160 Speaker 1: going to go the AI part first, right, So how 51 00:02:44,240 --> 00:02:48,919 Speaker 1: did you introduce AI into the process to the point 52 00:02:49,720 --> 00:02:52,680 Speaker 1: that it can actually the robots can be told by 53 00:02:52,800 --> 00:02:56,519 Speaker 1: AI what to do and how to build it. 54 00:02:57,320 --> 00:02:59,880 Speaker 2: So the first part is the reading of the plan, 55 00:03:01,200 --> 00:03:04,560 Speaker 2: and if you think about it, that's the really human part. 56 00:03:05,080 --> 00:03:08,000 Speaker 2: The human part is interpreting what's drawn on the page 57 00:03:08,880 --> 00:03:13,280 Speaker 2: and turning that into usable code for the robots. So 58 00:03:13,800 --> 00:03:16,400 Speaker 2: we have a large language model which everyone would have 59 00:03:16,440 --> 00:03:19,480 Speaker 2: heard of before that we've trained. We've processed something like 60 00:03:19,639 --> 00:03:22,720 Speaker 2: ten million square feet. I've been in the US so 61 00:03:22,800 --> 00:03:26,280 Speaker 2: long now, I think in imperiod. I'm not sure if 62 00:03:26,760 --> 00:03:29,079 Speaker 2: the comparison for that, but ten million square feet. 63 00:03:29,120 --> 00:03:31,000 Speaker 1: You've still got the accent, Joel, It's okay, he's still 64 00:03:31,040 --> 00:03:31,400 Speaker 1: one of us. 65 00:03:31,600 --> 00:03:33,200 Speaker 2: Yeah, yeah, it gets me in a lot of doors 66 00:03:33,240 --> 00:03:37,400 Speaker 2: in the us, which is great. They love Australians over here. 67 00:03:37,720 --> 00:03:41,560 Speaker 2: But we've trained our AI on about ten million square 68 00:03:41,600 --> 00:03:44,560 Speaker 2: feet of blueprints and what that means is that it 69 00:03:44,680 --> 00:03:47,480 Speaker 2: recognizes everything that's on the blueprint. So it recognizes a door, 70 00:03:47,600 --> 00:03:51,760 Speaker 2: it recognizes a dimension, a toilet, cook top, anything that's 71 00:03:51,800 --> 00:03:53,440 Speaker 2: on the plan, that AI will read it because that's 72 00:03:53,480 --> 00:03:56,160 Speaker 2: what we've taught it to do. The next part of 73 00:03:56,240 --> 00:04:02,280 Speaker 2: the AI is what's called motion planning. So the CTO Barrett, 74 00:04:02,840 --> 00:04:04,800 Speaker 2: who's the one of the co founders, he used to 75 00:04:04,840 --> 00:04:06,680 Speaker 2: work at NASA. He used to build robots for NASA, 76 00:04:07,480 --> 00:04:10,880 Speaker 2: and then when did his PhD at Duke University over 77 00:04:10,920 --> 00:04:14,240 Speaker 2: here in North Carolina, and his PhD was all about 78 00:04:14,280 --> 00:04:16,760 Speaker 2: motion planning, which is where the robots do their own 79 00:04:16,839 --> 00:04:21,040 Speaker 2: mathematics so that they're intelligent. They plan their own movements 80 00:04:21,880 --> 00:04:24,080 Speaker 2: based on the shape of the house we've told them 81 00:04:24,120 --> 00:04:27,320 Speaker 2: to build. So we just stack two by four studs 82 00:04:27,400 --> 00:04:30,000 Speaker 2: up next to them. They go and pick up the wood, 83 00:04:30,160 --> 00:04:32,320 Speaker 2: place it on the table, cut it, nail it all 84 00:04:32,800 --> 00:04:35,279 Speaker 2: all on their own and so it's a two step 85 00:04:35,360 --> 00:04:38,760 Speaker 2: process there reading the plans and then planning their own motions. 86 00:04:39,160 --> 00:04:42,960 Speaker 1: So what's the finished product when it leaves builds factory. 87 00:04:44,000 --> 00:04:45,000 Speaker 1: What does it look like. 88 00:04:45,720 --> 00:04:48,520 Speaker 2: So you get the wall panels or the wallframes we 89 00:04:48,600 --> 00:04:51,719 Speaker 2: call them in Australia, very very common. Almost every house 90 00:04:51,760 --> 00:04:55,360 Speaker 2: in Australia is built from factory built wall frames. We'll 91 00:04:55,400 --> 00:04:57,680 Speaker 2: shift them to site, stand them up and you get 92 00:04:57,680 --> 00:04:59,680 Speaker 2: all the benefits of the speed and accuracy on site. 93 00:04:59,720 --> 00:05:02,720 Speaker 2: Int of what's very common here is stick building. So 94 00:05:02,839 --> 00:05:06,640 Speaker 2: you have a team of framers who would just get 95 00:05:06,680 --> 00:05:08,240 Speaker 2: a pile of lumber and build the house from it. 96 00:05:08,480 --> 00:05:12,240 Speaker 2: We prefabricate it so it's much faster and more cost efficient. Yeah. 97 00:05:12,320 --> 00:05:13,320 Speaker 1: So how much cheaper is it? 98 00:05:14,000 --> 00:05:16,040 Speaker 2: We think we can take about just with this product, 99 00:05:16,080 --> 00:05:17,839 Speaker 2: we can take ten percent off the cost of building 100 00:05:17,880 --> 00:05:20,279 Speaker 2: a house, which is significant. It costs about five hundred 101 00:05:20,279 --> 00:05:22,960 Speaker 2: thousand dollars build a house, say fifty thousand dollars. That's 102 00:05:23,000 --> 00:05:24,000 Speaker 2: a significant saving. 103 00:05:24,279 --> 00:05:26,400 Speaker 1: Okay, stay with me, Joel, we'll be back in a minute. 104 00:05:33,040 --> 00:05:36,560 Speaker 1: My guest this morning is Joel Bell, director of bot Build. 105 00:05:37,720 --> 00:05:39,800 Speaker 1: I'd like to know how you, Joel, ended up in 106 00:05:39,880 --> 00:05:42,760 Speaker 1: North Carolina at bot Build as the founder of bote Build, 107 00:05:43,120 --> 00:05:46,799 Speaker 1: given that your background is in engineering but with the military. 108 00:05:47,600 --> 00:05:51,000 Speaker 2: Yeah, so I was an Army engineer for a long time. 109 00:05:51,120 --> 00:05:53,719 Speaker 2: I did that for about sixteen years in total. Quit 110 00:05:53,839 --> 00:05:57,280 Speaker 2: that back in twenty twenty three. I then did an 111 00:05:57,400 --> 00:06:01,480 Speaker 2: MBA at Melbourne Business School. Shout out to m very 112 00:06:01,520 --> 00:06:04,279 Speaker 2: good business school for those that are considering doing an MBA. 113 00:06:04,920 --> 00:06:06,880 Speaker 2: I had the opportunity to do in exchange here in 114 00:06:06,960 --> 00:06:09,560 Speaker 2: North Carolina at the University of North Carolina at a 115 00:06:09,600 --> 00:06:12,280 Speaker 2: great business school here. Came over here, fell in love 116 00:06:12,360 --> 00:06:14,680 Speaker 2: with the place. It's a really beautiful part of the world, 117 00:06:14,839 --> 00:06:17,480 Speaker 2: North Carolina. The people were wonderful. There's a lot of 118 00:06:18,040 --> 00:06:20,760 Speaker 2: a lot of tech development here. It's a real research center, 119 00:06:21,120 --> 00:06:22,920 Speaker 2: a lot of business going on. It's a real growth 120 00:06:23,000 --> 00:06:25,360 Speaker 2: area as well. I'd spent a lot of time in 121 00:06:25,400 --> 00:06:28,560 Speaker 2: the US with the military. I really like Americans and 122 00:06:28,720 --> 00:06:30,680 Speaker 2: working with them, so I've been thinking about coming here 123 00:06:30,720 --> 00:06:33,360 Speaker 2: for a little while. And then, of course I met 124 00:06:33,400 --> 00:06:36,680 Speaker 2: a pretty girl, My wonderful girlfriend, Courtney, gave me a 125 00:06:36,760 --> 00:06:39,120 Speaker 2: real reason to come back. So I found Bob Built 126 00:06:39,520 --> 00:06:42,320 Speaker 2: just on LinkedIn, connected with the founders. They were looking 127 00:06:42,360 --> 00:06:44,760 Speaker 2: for someone like me. At the same time. I was 128 00:06:44,800 --> 00:06:47,760 Speaker 2: looking for a job, so a business degree and with 129 00:06:47,880 --> 00:06:50,880 Speaker 2: a background in construction to build out some of this product. 130 00:06:51,360 --> 00:06:53,920 Speaker 2: So I made a connection, came over here, and now 131 00:06:53,920 --> 00:06:55,360 Speaker 2: I have a house and a baby on the way. 132 00:06:55,520 --> 00:06:57,760 Speaker 2: So the Americans have stuck with me for a little while. 133 00:06:58,000 --> 00:07:02,280 Speaker 1: Congratulations, well done, how big bot built At this point. 134 00:07:02,560 --> 00:07:05,640 Speaker 2: We've built forty houses at this point, so it's not 135 00:07:05,680 --> 00:07:08,120 Speaker 2: a sciences sperm anymore. But we are still a startup, 136 00:07:08,480 --> 00:07:10,480 Speaker 2: so we're on that journey, which has also been really 137 00:07:10,560 --> 00:07:14,680 Speaker 2: fascinating to observe how that goes. Raising funds, building out 138 00:07:14,680 --> 00:07:17,520 Speaker 2: the business, funding your customers, getting the product out there, 139 00:07:17,600 --> 00:07:20,239 Speaker 2: doing the marketing, which is a lot of the stuff 140 00:07:20,240 --> 00:07:23,480 Speaker 2: that I work on. It's fun. I'm not the robot guy. 141 00:07:23,560 --> 00:07:25,120 Speaker 2: I get to go out and sell the robots, which 142 00:07:25,160 --> 00:07:28,200 Speaker 2: is the fund yet and I get to talk on 143 00:07:28,440 --> 00:07:31,320 Speaker 2: podcasts like this about how great the product is. But yeah, 144 00:07:31,480 --> 00:07:33,280 Speaker 2: we're looking to scale up now. So we've got a 145 00:07:33,280 --> 00:07:35,400 Speaker 2: product that works, we've got a product that customers really like, 146 00:07:35,480 --> 00:07:38,000 Speaker 2: and then looking to scale so how big can you get? 147 00:07:39,120 --> 00:07:41,720 Speaker 2: We see this being in every state in the US 148 00:07:42,200 --> 00:07:46,120 Speaker 2: and internationally, so we've had some discussions with Australian manufacturers. 149 00:07:46,680 --> 00:07:50,160 Speaker 2: The product works in Australia because timber is timber. Australian 150 00:07:50,200 --> 00:07:53,560 Speaker 2: houses are very similar to American houses. There are some 151 00:07:53,640 --> 00:07:56,120 Speaker 2: differences obviously, but the fun thing is we can have 152 00:07:56,200 --> 00:07:58,760 Speaker 2: the AI teach itself how to build an Australian house. 153 00:08:00,000 --> 00:08:01,640 Speaker 2: It's just a matter of training it on the Australian 154 00:08:01,680 --> 00:08:04,640 Speaker 2: Building Code and we'll see robots building houses in Australia 155 00:08:05,200 --> 00:08:07,240 Speaker 2: in the not too distant future. Is the plan? 156 00:08:07,920 --> 00:08:10,120 Speaker 1: So what's the size of the price? You've built forty 157 00:08:10,360 --> 00:08:12,960 Speaker 1: in an environment in the US where, to be honest, 158 00:08:13,000 --> 00:08:15,040 Speaker 1: the building environment and this is just based on James 159 00:08:15,080 --> 00:08:17,640 Speaker 1: Hardish sare price that rather than any particular knowledge hasn't 160 00:08:17,680 --> 00:08:19,600 Speaker 1: been great the last couple of years. 161 00:08:19,640 --> 00:08:19,920 Speaker 2: It really. 162 00:08:20,120 --> 00:08:22,040 Speaker 1: I mean that renovations have been good, but new builds 163 00:08:22,080 --> 00:08:25,440 Speaker 1: hasn't been great. What's the outlook then, I mean, if 164 00:08:25,480 --> 00:08:27,520 Speaker 1: you can build homes and be successful in a not 165 00:08:27,640 --> 00:08:30,280 Speaker 1: say great environment, then plenty of opportunity. 166 00:08:30,960 --> 00:08:34,120 Speaker 2: Yeah. One of the things that really struck me moving 167 00:08:34,200 --> 00:08:36,720 Speaker 2: to the US is just the size of the opportunity. 168 00:08:37,360 --> 00:08:40,280 Speaker 2: So we haven't seen a drop in new homes in 169 00:08:40,360 --> 00:08:44,439 Speaker 2: the US, but they're building one point five million homes 170 00:08:44,480 --> 00:08:47,800 Speaker 2: every year in this country and the vast majority of 171 00:08:47,880 --> 00:08:51,719 Speaker 2: those are single family built from timber, so very very 172 00:08:51,800 --> 00:08:56,080 Speaker 2: big market, very big opportunity and similar to Australia where 173 00:08:56,160 --> 00:09:00,400 Speaker 2: builders have thin margins. It's a tough industry construction. They're 174 00:09:00,440 --> 00:09:03,040 Speaker 2: looking to save wherever they can and home builders want 175 00:09:03,080 --> 00:09:05,480 Speaker 2: a better product. In order to save money, we've had 176 00:09:05,520 --> 00:09:08,560 Speaker 2: to cut costs and I don't think anyone would disagree 177 00:09:08,600 --> 00:09:11,959 Speaker 2: that the quality of housing in Australia hasn't been improving. 178 00:09:12,720 --> 00:09:15,200 Speaker 2: And in order to build more houses we need to innovate. 179 00:09:15,559 --> 00:09:18,360 Speaker 2: And this is the key here. It works. We're competing 180 00:09:18,440 --> 00:09:21,120 Speaker 2: in a very strong market, but we're saving builders money 181 00:09:21,240 --> 00:09:23,760 Speaker 2: and we're saving developers money and giving home owners a 182 00:09:23,800 --> 00:09:24,320 Speaker 2: better product. 183 00:09:25,559 --> 00:09:29,440 Speaker 1: So it works saving money. I presume safety is another issue, 184 00:09:29,480 --> 00:09:32,440 Speaker 1: which when you've got robots doing it rather than individuals, 185 00:09:32,800 --> 00:09:34,080 Speaker 1: that's probably benefit there too. 186 00:09:35,160 --> 00:09:38,760 Speaker 2: Yeah. So my dad Mick Bell, shout out dad. He 187 00:09:39,640 --> 00:09:41,400 Speaker 2: used to run a wall frame a RIF Trust plant 188 00:09:41,440 --> 00:09:44,160 Speaker 2: and he's been a carp under his whole life. And 189 00:09:44,440 --> 00:09:47,559 Speaker 2: his hands tell the story. I like to talk about this. 190 00:09:47,720 --> 00:09:50,080 Speaker 2: So he's had a number of surgeries on his hands 191 00:09:50,080 --> 00:09:52,439 Speaker 2: because it's backbreaking work building. It's difficult, you're out in 192 00:09:52,480 --> 00:09:55,240 Speaker 2: the sun all day, takes a long time and it's 193 00:09:55,360 --> 00:09:58,679 Speaker 2: very manual and so if we can displace some of 194 00:09:58,720 --> 00:10:01,520 Speaker 2: that very dangerous work, then that's a benefit there. The 195 00:10:01,600 --> 00:10:06,000 Speaker 2: phrase we use in robotics is dirty, dull, and dangerous 196 00:10:06,440 --> 00:10:09,160 Speaker 2: is what robots are good for. And this is definitely 197 00:10:09,360 --> 00:10:12,400 Speaker 2: in the dull and dangerous bracket. So if we can 198 00:10:12,440 --> 00:10:17,160 Speaker 2: have robots help out humans, make it faster, improve humans productivity, 199 00:10:17,160 --> 00:10:18,280 Speaker 2: and that's a win for everybody. 200 00:10:18,640 --> 00:10:20,120 Speaker 1: I got to ask you, Joel, what's your dad think 201 00:10:20,200 --> 00:10:23,680 Speaker 1: about you doing via robotics what he spent his life 202 00:10:23,800 --> 00:10:24,280 Speaker 1: laboring on. 203 00:10:24,920 --> 00:10:29,080 Speaker 2: It's just another tool, It's the next evolution my dad. 204 00:10:29,760 --> 00:10:34,160 Speaker 2: My dad did his apprenticeship before power tools, which probably 205 00:10:34,280 --> 00:10:36,920 Speaker 2: dates him, but he talks about buying his first ever 206 00:10:37,040 --> 00:10:41,000 Speaker 2: electric drill after he finishes apprenticeship, and it's just the 207 00:10:41,080 --> 00:10:44,679 Speaker 2: next evolution of that. It's the future. We talk a 208 00:10:44,720 --> 00:10:47,360 Speaker 2: lot in Australia and across the West. It's the problem 209 00:10:47,400 --> 00:10:49,800 Speaker 2: here in the US as well of an aging population 210 00:10:50,520 --> 00:10:53,400 Speaker 2: struggling to get young people to join the trades. There's 211 00:10:53,400 --> 00:10:57,199 Speaker 2: a labor shortage across the market. The only way to 212 00:10:57,280 --> 00:11:00,600 Speaker 2: improve that is through automation and robotics. This is an 213 00:11:00,640 --> 00:11:04,280 Speaker 2: area that's been severely lacking in innovation in that space 214 00:11:04,840 --> 00:11:05,560 Speaker 2: for a while. 215 00:11:05,840 --> 00:11:07,400 Speaker 1: Good luck with a Joel and thank you for talking 216 00:11:07,440 --> 00:11:08,080 Speaker 1: to Fear and Greed. 217 00:11:08,320 --> 00:11:09,120 Speaker 2: Appreciate it. Sean. 218 00:11:09,559 --> 00:11:12,319 Speaker 1: That was Joel Bell, director at Bot Built. This is 219 00:11:12,400 --> 00:11:14,680 Speaker 1: the Fear and Greed Business Interview. Join us every morning 220 00:11:14,720 --> 00:11:17,240 Speaker 1: for the full episode of Fear and Greed business news 221 00:11:17,440 --> 00:11:19,880 Speaker 1: you can use. I'm Sean Elmer. Enjoy your day.