1 00:00:15,356 --> 00:00:22,836 Speaker 1: Pushkin. Imagine you're running a factory. You've got to put 2 00:00:22,876 --> 00:00:26,356 Speaker 1: out a consistent, high quality product that your customers will buy, 3 00:00:27,076 --> 00:00:30,676 Speaker 1: but you have no control over the raw materials that 4 00:00:30,756 --> 00:00:34,356 Speaker 1: come into your factory every day. One day, half of 5 00:00:34,396 --> 00:00:38,396 Speaker 1: what comes in is literal garbage. The next mixed in 6 00:00:38,476 --> 00:00:42,356 Speaker 1: with your usual inputs is some random lithium ion battery. 7 00:00:42,796 --> 00:00:48,156 Speaker 1: It's a fire hazard and also a surfboard weird. And 8 00:00:48,236 --> 00:00:50,596 Speaker 1: you have to deal with all this stuff and still 9 00:00:50,716 --> 00:00:54,916 Speaker 1: keep getting your product out the door. This is literally 10 00:00:54,956 --> 00:00:59,596 Speaker 1: the way the recycling business works. Recycling plants take in 11 00:00:59,636 --> 00:01:03,996 Speaker 1: a largely random, occasionally hazardous stream of stuff, a stream 12 00:01:04,036 --> 00:01:07,156 Speaker 1: of stuff that changes in a pretty unpredictable way from 13 00:01:07,236 --> 00:01:10,476 Speaker 1: day to day, from hour to hour, and then recycling 14 00:01:10,516 --> 00:01:13,716 Speaker 1: plants have to turn that random stream of inputs into 15 00:01:14,156 --> 00:01:18,556 Speaker 1: aluminum and plastic and cardboard that other companies will buy 16 00:01:18,876 --> 00:01:22,316 Speaker 1: and use to make new stuff. This is why my 17 00:01:22,396 --> 00:01:27,076 Speaker 1: guest today calls recycling the most demented form of manufacturing 18 00:01:27,116 --> 00:01:29,836 Speaker 1: on the planet, and it's why she and her colleagues 19 00:01:29,876 --> 00:01:32,596 Speaker 1: are trying to use technology to bring some order to 20 00:01:32,676 --> 00:01:42,276 Speaker 1: the recycling chaos. I'm Jacob Goldstein, and this is what's 21 00:01:42,316 --> 00:01:44,316 Speaker 1: your problem the show where I talk to people who 22 00:01:44,356 --> 00:01:48,036 Speaker 1: are trying to make technological progress. My guest today is 23 00:01:48,196 --> 00:01:51,836 Speaker 1: Rebecca who Troms. She's the co founder and CEO of 24 00:01:51,876 --> 00:01:55,756 Speaker 1: a company called Glacier. Rebecca's problem is this, how do 25 00:01:55,796 --> 00:01:59,156 Speaker 1: you use AI and robotics to make recycling a somewhat 26 00:01:59,236 --> 00:02:03,276 Speaker 1: less demented business. If Rebecca and her colleagues are successful, 27 00:02:03,596 --> 00:02:06,796 Speaker 1: they'll not only help recycling plants work better, they'll help 28 00:02:06,836 --> 00:02:09,516 Speaker 1: companies figure out how to recycle more of this that 29 00:02:09,516 --> 00:02:11,556 Speaker 1: they're sending out into the world in the first place. 30 00:02:12,716 --> 00:02:15,916 Speaker 1: Our conversation started with Rebecca talking about the moment around 31 00:02:15,916 --> 00:02:18,636 Speaker 1: five years ago when she and her co founder decided 32 00:02:18,636 --> 00:02:19,516 Speaker 1: to start the company. 33 00:02:21,076 --> 00:02:25,196 Speaker 2: I was, you know, even at the time, obsessed with trash, 34 00:02:25,356 --> 00:02:28,036 Speaker 2: just obsessed with where does all of our stuff go? 35 00:02:28,196 --> 00:02:29,716 Speaker 2: And it's one of those I call it like a 36 00:02:29,716 --> 00:02:32,556 Speaker 2: Matrix moment or a red pill moment where once you 37 00:02:32,996 --> 00:02:35,356 Speaker 2: realize that you've never thought about where all of your 38 00:02:35,356 --> 00:02:37,956 Speaker 2: garbage goes after you put your bins on the curb, 39 00:02:38,316 --> 00:02:42,796 Speaker 2: you can't unsee that, right. And so this was also 40 00:02:42,836 --> 00:02:44,596 Speaker 2: around the time where there was a lot of change 41 00:02:44,596 --> 00:02:47,756 Speaker 2: happening in the recycling industry. So we're rewinding to roughly 42 00:02:47,796 --> 00:02:51,796 Speaker 2: twenty eighteen twenty nineteen. One cataclysmic shift for the industry 43 00:02:51,916 --> 00:02:55,076 Speaker 2: is that China, who had previously been the world's largest 44 00:02:55,116 --> 00:02:59,636 Speaker 2: buyer of recycled feedstock to make into new things. They 45 00:02:59,716 --> 00:03:03,036 Speaker 2: basically said very rapidly, you know what we're taking in 46 00:03:03,116 --> 00:03:05,956 Speaker 2: the world's recycling, but most of this is trash. People 47 00:03:06,036 --> 00:03:07,916 Speaker 2: are not sorting it well enough. We're getting a ton 48 00:03:07,956 --> 00:03:10,556 Speaker 2: of contamination, and we don't want to end up as 49 00:03:10,596 --> 00:03:14,396 Speaker 2: the planet's landfill or incinerator. So we're going to drastically 50 00:03:14,436 --> 00:03:18,316 Speaker 2: increase the bar on quality of what we're accepting. And 51 00:03:18,396 --> 00:03:21,356 Speaker 2: then that caused shockwaves throughout the globe and certainly for 52 00:03:21,396 --> 00:03:23,956 Speaker 2: the US, where suddenly recyclers for the first time in 53 00:03:23,996 --> 00:03:26,316 Speaker 2: a long time, were like, the game is not to 54 00:03:26,476 --> 00:03:29,436 Speaker 2: just crank through all this recycled material, bail it and 55 00:03:29,476 --> 00:03:32,676 Speaker 2: ship it overseas. We actually need to invest a lot 56 00:03:32,756 --> 00:03:38,236 Speaker 2: more in increasing the bar on quality and on purity rate. 57 00:03:38,436 --> 00:03:40,916 Speaker 2: And what's even more challenging is that a lot of 58 00:03:40,956 --> 00:03:43,356 Speaker 2: the backbone, historically and even to this day, is still 59 00:03:43,396 --> 00:03:46,836 Speaker 2: just people standing next to conveyor belts sifting through our 60 00:03:46,956 --> 00:03:50,156 Speaker 2: recycling in our trash and of course that's not only 61 00:03:50,316 --> 00:03:53,436 Speaker 2: very dangerous, it's not a very well compensated job. There's 62 00:03:53,436 --> 00:03:55,636 Speaker 2: a lot of hazards there. But also there's this massive 63 00:03:55,916 --> 00:03:57,036 Speaker 2: sort of labor shortage. 64 00:03:57,156 --> 00:04:00,356 Speaker 1: Yes, it seems like a robot friendly moment, a robot 65 00:04:00,436 --> 00:04:03,636 Speaker 1: friendly environment. So like, what's your move, what's your first move? 66 00:04:03,796 --> 00:04:06,796 Speaker 2: So my co founder had already at the time, he 67 00:04:06,836 --> 00:04:08,316 Speaker 2: wasn't my co founder, he was just a friend of 68 00:04:08,356 --> 00:04:11,276 Speaker 2: a friend. He was already pretty intent on this idea 69 00:04:11,316 --> 00:04:15,196 Speaker 2: that hey, you know, automation AI, all of these technologies 70 00:04:15,276 --> 00:04:18,276 Speaker 2: are so good now that for the first time, we 71 00:04:18,316 --> 00:04:24,276 Speaker 2: could feasibly rapidly commercialize a purpose built industrial robot, specifically 72 00:04:24,316 --> 00:04:25,516 Speaker 2: for recycling sortation. 73 00:04:26,196 --> 00:04:26,516 Speaker 1: Huh. 74 00:04:26,516 --> 00:04:29,556 Speaker 2: And it's not going to cost us massive amounts of capital, 75 00:04:29,636 --> 00:04:31,676 Speaker 2: and we can actually do it in a matter of 76 00:04:31,796 --> 00:04:33,036 Speaker 2: like a couple of years. 77 00:04:33,156 --> 00:04:35,916 Speaker 1: So this idea that oh, now is the moment? Is 78 00:04:35,916 --> 00:04:39,276 Speaker 1: it computer vision? Like, what is the underlying technology that 79 00:04:39,396 --> 00:04:42,276 Speaker 1: made five years ago or whatever? The moment when oh, 80 00:04:42,276 --> 00:04:43,796 Speaker 1: we can do this in a way that hasn't been 81 00:04:43,796 --> 00:04:44,356 Speaker 1: done before. 82 00:04:45,116 --> 00:04:47,556 Speaker 2: Yeah, Honestly, it's the confluence of a lot of things. 83 00:04:47,636 --> 00:04:49,676 Speaker 2: So I'll break it down into sort of the computer 84 00:04:49,796 --> 00:04:53,196 Speaker 2: vision piece and then also the hardware or the robotics piece. 85 00:04:53,996 --> 00:04:57,476 Speaker 2: When you think about where industrial automation has come from 86 00:04:57,556 --> 00:05:00,836 Speaker 2: even to this day, a lot of those technologies are 87 00:05:00,876 --> 00:05:06,396 Speaker 2: operating in really well defined, truly repetitive roat environments. So 88 00:05:06,436 --> 00:05:08,916 Speaker 2: think about a robot at a warehouse, and it's literally 89 00:05:08,996 --> 00:05:13,356 Speaker 2: just palatizing identical boxes over and over again. And so 90 00:05:13,436 --> 00:05:16,516 Speaker 2: to harken back to this idea of recycling plants as 91 00:05:16,556 --> 00:05:20,476 Speaker 2: being this extremely volatile manufacturing environment, even if you have 92 00:05:20,716 --> 00:05:25,596 Speaker 2: automation that's just sorting let's say aluminum cans, right, You're 93 00:05:25,636 --> 00:05:28,596 Speaker 2: talking about aluminum cans that your computer vision needs to 94 00:05:28,636 --> 00:05:33,076 Speaker 2: detect in infinite varieties, not just thinking about the wide 95 00:05:33,156 --> 00:05:35,236 Speaker 2: variety of cans that are on the market in all 96 00:05:35,276 --> 00:05:38,316 Speaker 2: of their colors and designs, but also the fact that 97 00:05:38,316 --> 00:05:41,356 Speaker 2: they show up not as pristine cans but crinkled in 98 00:05:41,436 --> 00:05:45,156 Speaker 2: various ways, stuffed into bags. Like, there's so much heterogeneity 99 00:05:45,196 --> 00:05:50,516 Speaker 2: that even just identifying that item on conveyor belt that, 100 00:05:50,556 --> 00:05:53,196 Speaker 2: by the way, has dozens of other types of items 101 00:05:53,196 --> 00:05:57,076 Speaker 2: on it is already a massive challenge that only recently 102 00:05:57,156 --> 00:05:59,356 Speaker 2: has been something that we can adapt to in a 103 00:05:59,436 --> 00:06:02,436 Speaker 2: cost effective way. And then you can layer onto that 104 00:06:02,476 --> 00:06:04,956 Speaker 2: the fact that now you're not only seeing those items 105 00:06:04,996 --> 00:06:08,236 Speaker 2: with this computer vision system, but you also need to 106 00:06:08,236 --> 00:06:10,756 Speaker 2: find a way to actually go and grab that material 107 00:06:10,876 --> 00:06:13,476 Speaker 2: and sort it into the right location. So when we 108 00:06:13,516 --> 00:06:17,076 Speaker 2: talk about advances in sort of off the shelf parts 109 00:06:17,116 --> 00:06:19,516 Speaker 2: that you used to design and make your robot, or 110 00:06:19,556 --> 00:06:22,796 Speaker 2: even like the gripping technology that's available, a lot of 111 00:06:22,836 --> 00:06:25,996 Speaker 2: that even a decade ago, would have required an immense 112 00:06:26,036 --> 00:06:28,276 Speaker 2: amount of r and D, with a much bigger team 113 00:06:28,516 --> 00:06:30,396 Speaker 2: and a much higher price tag to get to the 114 00:06:30,396 --> 00:06:32,596 Speaker 2: same point that we've gotten to after just a couple 115 00:06:32,596 --> 00:06:32,996 Speaker 2: of years. 116 00:06:33,316 --> 00:06:35,276 Speaker 1: Tell me about the first one you built. Tell me 117 00:06:35,316 --> 00:06:37,596 Speaker 1: about building a prototype and putting it in the world. 118 00:06:37,916 --> 00:06:40,316 Speaker 2: Man, So there are a lot of different stages to 119 00:06:40,356 --> 00:06:43,236 Speaker 2: our prototyping. The first prototype, if you want to go 120 00:06:43,276 --> 00:06:46,156 Speaker 2: way back, was when I hadn't even decided to start 121 00:06:46,196 --> 00:06:48,276 Speaker 2: this company with my co founder yet, but I did 122 00:06:48,316 --> 00:06:50,996 Speaker 2: tell him I would help him learn about the industry 123 00:06:51,116 --> 00:06:52,716 Speaker 2: see if there was some sort of a business to 124 00:06:52,716 --> 00:06:56,276 Speaker 2: be had, and we met in his kitchen in San 125 00:06:56,316 --> 00:06:59,276 Speaker 2: Francisco where he had a little corner set up. So 126 00:06:59,436 --> 00:07:02,836 Speaker 2: like very very simple. I think that it actually involved 127 00:07:02,916 --> 00:07:06,716 Speaker 2: a used yogurt tub as like this rotating wheel with 128 00:07:06,756 --> 00:07:09,236 Speaker 2: a piece of string tied around it, Like that's how 129 00:07:09,316 --> 00:07:11,916 Speaker 2: janky we were talking, but it worked and we were like, Okay, 130 00:07:12,276 --> 00:07:15,036 Speaker 2: there's something here. The first piece of equipment we actually 131 00:07:15,076 --> 00:07:18,516 Speaker 2: installed into a recycling facility also tells you a lot 132 00:07:18,516 --> 00:07:21,556 Speaker 2: about the constraints that these facilities are under. I was 133 00:07:21,676 --> 00:07:25,996 Speaker 2: kind of thinking we had to have this super built out, sophisticated, 134 00:07:26,036 --> 00:07:29,436 Speaker 2: polished thing that we've proven out to the nines in 135 00:07:29,476 --> 00:07:32,036 Speaker 2: the lab, and we actually called up a number of 136 00:07:32,116 --> 00:07:34,956 Speaker 2: recycling facility operators nearby and one of them was like, 137 00:07:35,036 --> 00:07:37,156 Speaker 2: you know what, when you got something, just like bring 138 00:07:37,196 --> 00:07:40,356 Speaker 2: it in here and try it out, because literally I 139 00:07:40,436 --> 00:07:43,916 Speaker 2: remember him saying, if your robot can pick one more 140 00:07:43,956 --> 00:07:46,796 Speaker 2: can than I would have gotten otherwise, Like it's already 141 00:07:46,796 --> 00:07:47,356 Speaker 2: worth it to me. 142 00:07:47,716 --> 00:07:51,596 Speaker 1: Just try it. Was there a rat moment, tell me more, 143 00:07:51,836 --> 00:07:54,076 Speaker 1: did you see a rat? 144 00:07:54,076 --> 00:07:54,556 Speaker 2: Literally? 145 00:07:54,796 --> 00:07:56,956 Speaker 1: I was like, what is that not a metaphor not 146 00:07:56,996 --> 00:07:58,156 Speaker 1: a metaphor a rodent? 147 00:07:59,276 --> 00:08:02,836 Speaker 2: I have seen many rats. Literally, Even on that first 148 00:08:02,876 --> 00:08:05,156 Speaker 2: install there was a moment where I was like literally 149 00:08:05,276 --> 00:08:08,716 Speaker 2: army crawling under a conveyor belt to fasten one of 150 00:08:08,756 --> 00:08:11,196 Speaker 2: the legs of the robot, and I came eye to 151 00:08:11,236 --> 00:08:13,276 Speaker 2: eye with a rat, who then, of course ground a 152 00:08:13,276 --> 00:08:14,596 Speaker 2: piece of food that was on the floor and then 153 00:08:14,636 --> 00:08:18,556 Speaker 2: scurried away. Right, there are many friendly critters running around 154 00:08:18,556 --> 00:08:19,436 Speaker 2: some of these facilities. 155 00:08:19,836 --> 00:08:21,916 Speaker 1: Was there any part of you that kind of loved it? 156 00:08:22,156 --> 00:08:23,796 Speaker 2: Oh, one hundred percent. 157 00:08:24,236 --> 00:08:26,996 Speaker 1: So let's talk about where you are today, both on 158 00:08:27,036 --> 00:08:29,916 Speaker 1: a kind of micro level, like what your robot or 159 00:08:29,956 --> 00:08:31,836 Speaker 1: robots look like, and then also a little more macro 160 00:08:31,916 --> 00:08:34,076 Speaker 1: of like the scope of the business. Do you have 161 00:08:34,156 --> 00:08:37,196 Speaker 1: like one basic robot what to look like or you 162 00:08:37,196 --> 00:08:37,996 Speaker 1: got a bunch of them? 163 00:08:38,276 --> 00:08:42,476 Speaker 2: Yeah, so we have one base model of robot. We 164 00:08:42,556 --> 00:08:45,996 Speaker 2: actually are already working with several dozen customers across the country. 165 00:08:46,036 --> 00:08:48,996 Speaker 2: But if you imagine any sort of conveyor belt in 166 00:08:49,036 --> 00:08:52,436 Speaker 2: an industrial facility, our robot think of it almost like 167 00:08:52,476 --> 00:08:54,636 Speaker 2: a table, right, So it's got four legs and it 168 00:08:54,716 --> 00:08:57,996 Speaker 2: kind of sits over that belt, and then the guts 169 00:08:57,996 --> 00:09:00,436 Speaker 2: of the robot or the mechanisms doing the picking are 170 00:09:00,636 --> 00:09:03,276 Speaker 2: kind of over the top of that conveyor system. So 171 00:09:03,316 --> 00:09:06,156 Speaker 2: you've got these arms that are going back and forth. 172 00:09:06,796 --> 00:09:09,516 Speaker 2: They can pick up something from the belt and then 173 00:09:09,556 --> 00:09:11,516 Speaker 2: they carry it off to one of those sides of 174 00:09:11,516 --> 00:09:14,476 Speaker 2: the belt. Where they actually drop it into the right location. Okay, 175 00:09:14,756 --> 00:09:17,036 Speaker 2: so that's the robot. And now one other thing we 176 00:09:17,076 --> 00:09:19,516 Speaker 2: haven't really talked about is this computer vision system. 177 00:09:19,596 --> 00:09:20,476 Speaker 1: So that's yeah. 178 00:09:20,716 --> 00:09:23,916 Speaker 2: Imagine basically like a camera with some lights to illuminate 179 00:09:23,956 --> 00:09:26,556 Speaker 2: the belt sitting on this little rig that's a little 180 00:09:26,556 --> 00:09:29,916 Speaker 2: bit upstream of the robot. So the material passes under 181 00:09:29,956 --> 00:09:33,116 Speaker 2: the camera, the camera has a second to process or 182 00:09:33,076 --> 00:09:35,236 Speaker 2: a should I say, a couple milliseconds to process what 183 00:09:35,316 --> 00:09:38,276 Speaker 2: it's seeing, and then not only does it tell the 184 00:09:38,356 --> 00:09:40,756 Speaker 2: robot you know, hey, there's a can coming in this 185 00:09:40,796 --> 00:09:43,316 Speaker 2: location picket and then put it into this other spot, 186 00:09:43,676 --> 00:09:46,756 Speaker 2: but what we're also finding is that that data as 187 00:09:46,796 --> 00:09:51,436 Speaker 2: a standalone is also able to massively advance these operator's 188 00:09:51,476 --> 00:09:56,196 Speaker 2: abilities to understand and optimize their facilities. So that's opened 189 00:09:56,276 --> 00:09:58,676 Speaker 2: up a whole new world of use cases. 190 00:09:58,396 --> 00:10:01,916 Speaker 1: Because they weren't gathering data in that kind of way before. 191 00:10:01,996 --> 00:10:04,796 Speaker 1: They only sort of knew what was coming through in 192 00:10:04,836 --> 00:10:06,556 Speaker 1: a very gross macro way. 193 00:10:07,316 --> 00:10:10,876 Speaker 2: Right, And this gets back to you know, recycling facility operators. 194 00:10:10,876 --> 00:10:13,396 Speaker 2: I have so much admiration for how they have gotten 195 00:10:13,476 --> 00:10:16,876 Speaker 2: really resourceful with trying to understand their operations. But you know, 196 00:10:16,916 --> 00:10:18,676 Speaker 2: to give you a sense of things. The state of 197 00:10:18,716 --> 00:10:21,076 Speaker 2: the art in the industry to this day is still 198 00:10:21,356 --> 00:10:23,836 Speaker 2: mostly manual audits. And when I say that, I mean 199 00:10:23,916 --> 00:10:26,596 Speaker 2: imagine taking a half ton of material off your line 200 00:10:27,036 --> 00:10:29,956 Speaker 2: and then literally having two to four people hands sort 201 00:10:30,076 --> 00:10:34,436 Speaker 2: and categorize and wigh each item to understand what's coming through, 202 00:10:34,476 --> 00:10:37,036 Speaker 2: and then assuming that that half ton is representative of 203 00:10:37,076 --> 00:10:39,676 Speaker 2: like the thousands of tons coming through your facility on 204 00:10:39,716 --> 00:10:42,196 Speaker 2: a yearly basis. I often tell the story of one 205 00:10:42,236 --> 00:10:46,076 Speaker 2: of our early data customers, this gentleman who runs a 206 00:10:46,116 --> 00:10:49,596 Speaker 2: recycling facility in California. When he met me, he was 207 00:10:49,596 --> 00:10:51,676 Speaker 2: telling me that he had mounted a goat pro camera 208 00:10:52,396 --> 00:10:55,916 Speaker 2: above his conveyor belt, the one that was basically supposed 209 00:10:55,956 --> 00:10:57,956 Speaker 2: to be all trash leaving the facility, but he knew 210 00:10:57,956 --> 00:11:00,436 Speaker 2: he was missing some good stuff, and he would spend 211 00:11:00,476 --> 00:11:03,076 Speaker 2: an hour a day after work going frame by frame 212 00:11:03,316 --> 00:11:07,196 Speaker 2: through some random snippet and manually tallying how many cans 213 00:11:07,236 --> 00:11:10,356 Speaker 2: and bottles were on that line, and then using that 214 00:11:10,436 --> 00:11:12,716 Speaker 2: to back into what he would try and change in 215 00:11:12,716 --> 00:11:15,156 Speaker 2: his operation the next day, and then he would check 216 00:11:15,156 --> 00:11:17,716 Speaker 2: that day to see if it changed anything. And so 217 00:11:17,756 --> 00:11:19,916 Speaker 2: imagine his delight when I told him, hey, actually we 218 00:11:19,956 --> 00:11:22,276 Speaker 2: can mount our own camera on there, and suddenly we'll 219 00:11:22,316 --> 00:11:24,676 Speaker 2: just give you access to a dashboard. 220 00:11:24,556 --> 00:11:27,556 Speaker 1: A machine will literally count everything that goes. 221 00:11:27,516 --> 00:11:30,556 Speaker 2: Literally in real time. So we're seeing that, you know, 222 00:11:30,596 --> 00:11:32,476 Speaker 2: the robot is this incredible foot in the door with 223 00:11:32,516 --> 00:11:36,476 Speaker 2: a lot of our facility partners, but that everyone's starting 224 00:11:36,476 --> 00:11:39,116 Speaker 2: to realize that, hey, actually this data can also help 225 00:11:39,196 --> 00:11:42,076 Speaker 2: us understand the entire world, not just the location where 226 00:11:42,076 --> 00:11:43,156 Speaker 2: the robot is sitting either. 227 00:11:43,636 --> 00:11:46,356 Speaker 1: So at this point is it kind of a robot 228 00:11:46,396 --> 00:11:49,036 Speaker 1: business on the front, but really you're like a computer 229 00:11:49,156 --> 00:11:51,716 Speaker 1: vision data AI business. 230 00:11:52,116 --> 00:11:54,956 Speaker 2: So a lot of customers come to us saying, you know, 231 00:11:54,956 --> 00:11:57,396 Speaker 2: I literally had a gentleman tell me a couple months 232 00:11:57,436 --> 00:11:59,236 Speaker 2: ago like I would never pay you to tell me 233 00:11:59,276 --> 00:12:01,436 Speaker 2: what I already know about my trash. And I'm like, 234 00:12:01,516 --> 00:12:03,596 Speaker 2: I'm not going to convince you that you don't already 235 00:12:03,636 --> 00:12:06,076 Speaker 2: know everything about your trash. But you know you want 236 00:12:06,076 --> 00:12:08,516 Speaker 2: a robot, Let's get you a robot. And that has 237 00:12:08,556 --> 00:12:10,516 Speaker 2: sense of all the conversation where we're just sort of 238 00:12:10,596 --> 00:12:12,236 Speaker 2: starting to show him this data and he's like, oh, 239 00:12:12,276 --> 00:12:14,516 Speaker 2: actually I didn't realize that this was the case. The 240 00:12:14,556 --> 00:12:16,636 Speaker 2: flip side is also true where someone's like, I don't 241 00:12:16,636 --> 00:12:18,956 Speaker 2: know if I need a robot yet, but I'm really interested 242 00:12:18,956 --> 00:12:20,956 Speaker 2: to see what I'm losing on the back end. We 243 00:12:21,036 --> 00:12:23,636 Speaker 2: install that camera and then suddenly, lo and behold that 244 00:12:23,716 --> 00:12:25,876 Speaker 2: data makes the case that, holy cow, I'm losing so 245 00:12:25,956 --> 00:12:27,716 Speaker 2: much stuff. I don't just need one robot. I maybe 246 00:12:27,796 --> 00:12:30,396 Speaker 2: need two or even three robots. Right, So it's kind 247 00:12:30,396 --> 00:12:33,836 Speaker 2: of this mutually reinforcing flywheel that's been really integral to 248 00:12:33,876 --> 00:12:35,276 Speaker 2: the success of our business so far. 249 00:12:36,076 --> 00:12:39,476 Speaker 1: Tell me about your work with Amazon and with Colgate Palmolith. 250 00:12:39,676 --> 00:12:41,476 Speaker 1: What are you doing for them with them? 251 00:12:41,996 --> 00:12:45,756 Speaker 2: Yeah, So to start, maybe just I'd love to explore 252 00:12:45,756 --> 00:12:48,036 Speaker 2: this idea of what is a circular economy because it's 253 00:12:48,036 --> 00:12:50,996 Speaker 2: a buzzword that gets thrown out a lot, but it's 254 00:12:51,036 --> 00:12:54,156 Speaker 2: really important to understand why Amazon and Coliate and their 255 00:12:54,196 --> 00:12:57,716 Speaker 2: peers matter here. Right now, we are living in mostly 256 00:12:57,756 --> 00:13:00,076 Speaker 2: a linear economy. In other words, someone makes a thing, 257 00:13:00,156 --> 00:13:02,396 Speaker 2: we consume a thing, and then we dispose of it. Right. 258 00:13:02,476 --> 00:13:05,356 Speaker 2: A circular economy tries to turn that process into a circle. 259 00:13:05,436 --> 00:13:07,636 Speaker 2: So instead of throwing it out in a landfill forever 260 00:13:08,036 --> 00:13:10,996 Speaker 2: or incinerating it, that material gets brought back to the 261 00:13:10,996 --> 00:13:13,956 Speaker 2: front end and reused somehow to make new stuff that 262 00:13:13,996 --> 00:13:15,916 Speaker 2: we can then consume. And the ideal is to make 263 00:13:15,956 --> 00:13:18,996 Speaker 2: this go on forever so that we limit our resource consumption. 264 00:13:19,556 --> 00:13:22,316 Speaker 2: So now that we have this growing base of recycling 265 00:13:22,316 --> 00:13:25,716 Speaker 2: facilities that are you know, gathering data, that are getting 266 00:13:25,716 --> 00:13:28,796 Speaker 2: a better understanding of what's coming into their facilities, what's 267 00:13:28,836 --> 00:13:31,556 Speaker 2: actually being bailed and sent out to the end markets, 268 00:13:32,076 --> 00:13:35,756 Speaker 2: We're working with companies like Amazon and Colgate on a 269 00:13:35,836 --> 00:13:37,836 Speaker 2: number of fronts. You know, the first is even just 270 00:13:37,876 --> 00:13:41,556 Speaker 2: to understand where is all of that packaging going to 271 00:13:41,596 --> 00:13:45,836 Speaker 2: their credit They and several of their peers have realized 272 00:13:45,876 --> 00:13:49,356 Speaker 2: that there's a paradigm shift possible now from we have 273 00:13:49,476 --> 00:13:52,796 Speaker 2: designed a thing that's technically recyclable, you know, our packaging 274 00:13:52,916 --> 00:13:56,516 Speaker 2: R and D engineers have made this awesome mono material 275 00:13:56,676 --> 00:14:02,396 Speaker 2: HDPE toothpaste tube in Colgate's example, to now trying to understand, okay, 276 00:14:02,436 --> 00:14:04,596 Speaker 2: well we made this thing that is recyclable, is it 277 00:14:04,676 --> 00:14:08,116 Speaker 2: actually getting recycled? And that was a lens that we 278 00:14:08,196 --> 00:14:12,116 Speaker 2: couldn't really get at scale before and so now with 279 00:14:12,156 --> 00:14:15,516 Speaker 2: Glacier's technology, we're able to monitor in real time, you know, 280 00:14:15,716 --> 00:14:18,956 Speaker 2: how much of these tubes are actually ending up at 281 00:14:18,996 --> 00:14:21,796 Speaker 2: the recycling facility, and once they're in the facility, are 282 00:14:21,876 --> 00:14:23,956 Speaker 2: they ending up in the right place, are they being 283 00:14:23,996 --> 00:14:26,836 Speaker 2: sorted correctly such that they can actually be turned into 284 00:14:26,876 --> 00:14:29,516 Speaker 2: new stuff, or are they ending up in the landfill, 285 00:14:29,556 --> 00:14:32,636 Speaker 2: in which case you know, suddenly this recyclable tube isn't 286 00:14:32,716 --> 00:14:34,956 Speaker 2: very recyclable at all. So we're starting to answer these 287 00:14:34,996 --> 00:14:36,516 Speaker 2: really really critical questions. 288 00:14:37,276 --> 00:14:40,876 Speaker 1: So Colgate knows whatever how many tubes of toothpaste they 289 00:14:40,916 --> 00:14:43,276 Speaker 1: sold in a city, and if you are working in 290 00:14:43,276 --> 00:14:46,796 Speaker 1: the recycling facility for that city, you can actually count 291 00:14:46,836 --> 00:14:49,716 Speaker 1: how many tubes of that toothpaste came down the recycling 292 00:14:49,716 --> 00:14:51,676 Speaker 1: line and how many tubes of that toothpaste wound up 293 00:14:51,676 --> 00:14:54,236 Speaker 1: in the bin. I mean, is that the reductive version 294 00:14:54,276 --> 00:14:54,836 Speaker 1: of what you're. 295 00:14:54,716 --> 00:14:58,236 Speaker 2: Saying, essentially? Yeah, And where we're even seeing now, like 296 00:14:58,316 --> 00:15:01,836 Speaker 2: with these rapid advances in AI and in detection, that 297 00:15:02,436 --> 00:15:04,676 Speaker 2: first of all, it's no small feet to even define 298 00:15:04,716 --> 00:15:06,436 Speaker 2: what is a tube and how do you tell the 299 00:15:06,436 --> 00:15:09,836 Speaker 2: difference between a toothpaste tube versus a sunscreen versus a 300 00:15:09,876 --> 00:15:12,836 Speaker 2: lotion tube. But now we're getting to the point where 301 00:15:12,836 --> 00:15:15,876 Speaker 2: we can actually say the brand of toothpaste, it is 302 00:15:16,076 --> 00:15:19,196 Speaker 2: like from all of those visual markings, and so we're 303 00:15:19,236 --> 00:15:21,916 Speaker 2: just seeing this sort of Cambrian explosion of interest from 304 00:15:22,116 --> 00:15:24,956 Speaker 2: a wide variety of different you know, packaging producers and 305 00:15:25,076 --> 00:15:29,396 Speaker 2: brands to really start understanding this previous black box on 306 00:15:29,516 --> 00:15:32,556 Speaker 2: what happens once they release this packaging into the wild 307 00:15:32,796 --> 00:15:33,836 Speaker 2: for consumers to buy. 308 00:15:34,236 --> 00:15:38,476 Speaker 1: So, I understand that California has a law that is 309 00:15:38,796 --> 00:15:41,676 Speaker 1: in some fashion supposed to put companies like on the 310 00:15:41,716 --> 00:15:44,436 Speaker 1: hook for their for their products right after they're used, 311 00:15:44,436 --> 00:15:49,036 Speaker 1: to incentivize companies to have their products be recycled. Right. 312 00:15:49,116 --> 00:15:52,116 Speaker 1: Is that am I characterizing that law right? And is 313 00:15:52,116 --> 00:15:53,276 Speaker 1: it relevant to your business? 314 00:15:53,516 --> 00:15:56,436 Speaker 2: Yes? So I believe you're referring to EPR or extended 315 00:15:56,476 --> 00:16:00,316 Speaker 2: producer Responsibility laws. For those who may not have heard 316 00:16:00,316 --> 00:16:04,476 Speaker 2: of EPR, it's essentially this premise that, you know, if 317 00:16:04,556 --> 00:16:07,356 Speaker 2: our recycling and waste system is supposed to find a 318 00:16:07,356 --> 00:16:09,756 Speaker 2: way to do something good with all the stuff throwing out, 319 00:16:09,796 --> 00:16:12,076 Speaker 2: the people making all the stuff that we're throwing out 320 00:16:12,076 --> 00:16:14,356 Speaker 2: should probably have some skin in the game to make 321 00:16:14,396 --> 00:16:18,236 Speaker 2: sure that that stuff gets either disposed of or reused properly. Right, 322 00:16:18,316 --> 00:16:23,196 Speaker 2: And so EPR laws are already in effect throughout Europe, 323 00:16:23,556 --> 00:16:26,476 Speaker 2: throughout Canada, some other regions, and then they've been passed 324 00:16:27,116 --> 00:16:29,476 Speaker 2: in a number of states in the US, including California. 325 00:16:30,036 --> 00:16:34,036 Speaker 2: Now while EPR in the US is still in its infancy. 326 00:16:34,116 --> 00:16:36,316 Speaker 2: In other words, it's been passed in a number of states, 327 00:16:36,316 --> 00:16:38,636 Speaker 2: but there's a lot of hairiness to figuring out how 328 00:16:38,676 --> 00:16:42,636 Speaker 2: to actually implement the system across all the producers selling 329 00:16:42,716 --> 00:16:46,076 Speaker 2: into a state and all of the recyclers operating in 330 00:16:46,116 --> 00:16:48,036 Speaker 2: that state. It is, I think a step in the 331 00:16:48,076 --> 00:16:51,476 Speaker 2: right direction because in a lot of ways it helps 332 00:16:51,516 --> 00:16:54,916 Speaker 2: to create that circle we were talking about earlier. You know, 333 00:16:55,036 --> 00:16:58,476 Speaker 2: you're seeing that a lot of brands and producers are 334 00:16:58,556 --> 00:17:01,036 Speaker 2: starting to take even more of a vested interest in 335 00:17:01,196 --> 00:17:04,156 Speaker 2: understanding what is happening to all of their packaging, because 336 00:17:04,196 --> 00:17:06,676 Speaker 2: they know that imminently they're going to need to start 337 00:17:06,676 --> 00:17:09,156 Speaker 2: proving the sort of end of life outcomes for that 338 00:17:09,196 --> 00:17:12,356 Speaker 2: packaging in order to you know, one, not be heavily 339 00:17:12,396 --> 00:17:15,316 Speaker 2: fined and then two maybe even have a right to 340 00:17:15,316 --> 00:17:16,796 Speaker 2: continue selling into that state. 341 00:17:17,916 --> 00:17:21,196 Speaker 1: It seems good that Amazon and Kolgay Palmolive are trying 342 00:17:21,236 --> 00:17:23,356 Speaker 1: to figure out if the things they make that are 343 00:17:23,356 --> 00:17:26,916 Speaker 1: recyclable are actually being recycled, but it seems like for 344 00:17:26,996 --> 00:17:29,156 Speaker 1: that sort of thing to happen at a meaningful scale, 345 00:17:29,236 --> 00:17:31,676 Speaker 1: you would need laws basically, right. I mean, if the 346 00:17:31,676 --> 00:17:34,676 Speaker 1: companies are just incurring the cost either out of the 347 00:17:34,676 --> 00:17:36,876 Speaker 1: goodness of their heart or in the hopes of you know, 348 00:17:37,076 --> 00:17:41,356 Speaker 1: generating goodwill that will lead to higher revenues, those seem 349 00:17:41,436 --> 00:17:45,276 Speaker 1: like marginal cases. Are the EPR laws such that you 350 00:17:45,316 --> 00:17:48,436 Speaker 1: think it will become a meaningful part of your business, 351 00:17:48,436 --> 00:17:50,556 Speaker 1: a meaningful part of the world, that companies will in 352 00:17:50,596 --> 00:17:52,596 Speaker 1: fact be on the hook to figure it out, or like, 353 00:17:52,676 --> 00:17:53,756 Speaker 1: what do you think is going to happen? 354 00:17:53,796 --> 00:17:56,116 Speaker 2: You know, I will say that early indicators are that 355 00:17:56,396 --> 00:17:58,756 Speaker 2: all of these states are taking it quite seriously. So 356 00:17:59,036 --> 00:18:02,396 Speaker 2: in addition to requiring a lot of these brands and 357 00:18:02,436 --> 00:18:06,316 Speaker 2: producers to pay into a massive fund upfront to even 358 00:18:06,396 --> 00:18:09,556 Speaker 2: just start implementing some of this movement, a lot of 359 00:18:09,596 --> 00:18:12,676 Speaker 2: these states are also you know, we're seeing that some 360 00:18:12,716 --> 00:18:15,196 Speaker 2: of the kind of like early deadlines and fines for 361 00:18:15,316 --> 00:18:18,556 Speaker 2: non compliance are actually being upheld, which I think is 362 00:18:18,916 --> 00:18:21,316 Speaker 2: a really strong signal to the market. Hey, this is 363 00:18:21,316 --> 00:18:24,876 Speaker 2: something that needs to get taken seriously. Now to your point, 364 00:18:24,916 --> 00:18:27,036 Speaker 2: I do think that at the end of the day, 365 00:18:27,076 --> 00:18:31,996 Speaker 2: whatever flavor this legislation takes. The key to make sure 366 00:18:31,996 --> 00:18:36,396 Speaker 2: that recycling is still a viable and sustainable value proposition 367 00:18:37,196 --> 00:18:39,836 Speaker 2: is that there needs to be some sort of an 368 00:18:39,916 --> 00:18:43,796 Speaker 2: end market for that material, right because let's say these brands, 369 00:18:44,076 --> 00:18:46,516 Speaker 2: even if they're required to pay billions of dollars into 370 00:18:46,556 --> 00:18:51,196 Speaker 2: this EPR system, if there's no one on the back 371 00:18:51,316 --> 00:18:54,836 Speaker 2: end to receive that material that these recycling facilities are sorting, 372 00:18:54,916 --> 00:18:57,476 Speaker 2: then recycling can't really happen. At the end of the day. 373 00:18:57,676 --> 00:19:00,556 Speaker 1: Someone needs to buy the bail of. 374 00:19:00,556 --> 00:19:05,596 Speaker 2: Plastic exactly exactly. But if they can have guarantee that 375 00:19:05,676 --> 00:19:09,316 Speaker 2: there is a buyer on the other side, right that 376 00:19:09,316 --> 00:19:12,116 Speaker 2: that person or that company will buy at a certain price, 377 00:19:12,196 --> 00:19:15,516 Speaker 2: then suddenly they can sustain that business quite well for 378 00:19:15,596 --> 00:19:18,116 Speaker 2: the long run. And so to that point, you know, 379 00:19:18,156 --> 00:19:20,956 Speaker 2: one other model that's often brought up in the realm 380 00:19:20,956 --> 00:19:25,556 Speaker 2: of legislation is actually minimum recycled content laws, because it 381 00:19:25,636 --> 00:19:28,116 Speaker 2: kind of gets at the same issue from the other side, 382 00:19:28,156 --> 00:19:29,036 Speaker 2: where you say. 383 00:19:28,916 --> 00:19:32,956 Speaker 1: Basically creating demand, creating demand for a bale of recycled 384 00:19:32,956 --> 00:19:35,356 Speaker 1: plastic coming out of the recycling facility. 385 00:19:35,036 --> 00:19:39,716 Speaker 2: Exactly, and it kind of disentangles the market for recycled 386 00:19:39,716 --> 00:19:43,276 Speaker 2: feedstock from the market for virgin feedstock, which is another 387 00:19:43,356 --> 00:19:45,916 Speaker 2: great way to kind of catalyze the movement of that 388 00:19:46,036 --> 00:19:52,556 Speaker 2: material throughout that recycling ecosystem. 389 00:19:52,676 --> 00:20:03,916 Speaker 1: We'll be back in just a minute. What are you 390 00:20:03,916 --> 00:20:05,996 Speaker 1: trying to figure out right now? What's a big thing 391 00:20:05,996 --> 00:20:06,876 Speaker 1: you're trying to figure out? 392 00:20:07,116 --> 00:20:09,716 Speaker 2: We are at a really exciting inflection point, a glacier 393 00:20:09,836 --> 00:20:14,236 Speaker 2: because of I think two big things here. The first 394 00:20:14,436 --> 00:20:19,516 Speaker 2: is just how do we scale smoothly and rapidly. You know, 395 00:20:19,556 --> 00:20:22,356 Speaker 2: we've gone from a year ago we were making maybe 396 00:20:22,476 --> 00:20:25,276 Speaker 2: one robot every three months, and now we have the 397 00:20:25,316 --> 00:20:28,116 Speaker 2: capacity to make three to four robots per month, and 398 00:20:28,156 --> 00:20:30,316 Speaker 2: we're expecting to go even faster by the end of 399 00:20:30,356 --> 00:20:32,796 Speaker 2: this year in the next six months. And then the 400 00:20:32,836 --> 00:20:35,436 Speaker 2: other big frontier for us, in addition to just you know, 401 00:20:35,476 --> 00:20:37,316 Speaker 2: how do we scale and get more of our stuff 402 00:20:37,356 --> 00:20:39,676 Speaker 2: out there, is what the heck do we do with 403 00:20:39,716 --> 00:20:42,796 Speaker 2: all of this data? Right? We've already seen that the 404 00:20:42,876 --> 00:20:46,236 Speaker 2: early use cases for this information people are taking to 405 00:20:47,236 --> 00:20:50,996 Speaker 2: really in droves. But there's a much more built out 406 00:20:51,076 --> 00:20:53,156 Speaker 2: version of the data platform where we say, you know, 407 00:20:53,196 --> 00:20:54,996 Speaker 2: we don't just have a camera in one or two 408 00:20:55,036 --> 00:20:57,956 Speaker 2: points throughout your facility. We can actually get sensors to 409 00:20:58,196 --> 00:21:01,476 Speaker 2: sort of blanket the facility, and in that regard, we 410 00:21:01,476 --> 00:21:03,956 Speaker 2: can take a huge step towards becoming more like that 411 00:21:04,276 --> 00:21:08,436 Speaker 2: manufacturer who has information on every single step of their 412 00:21:08,436 --> 00:21:11,756 Speaker 2: process and respond in real time and know exactly what's 413 00:21:11,796 --> 00:21:12,996 Speaker 2: going on at each stage. 414 00:21:13,076 --> 00:21:15,236 Speaker 1: So, I mean, let's just talk about the recycling business 415 00:21:15,276 --> 00:21:17,796 Speaker 1: for a minute. The facilities you're talking about, they're just 416 00:21:17,836 --> 00:21:18,716 Speaker 1: private companies. 417 00:21:18,876 --> 00:21:21,596 Speaker 2: The vast majority of them are. So this is a 418 00:21:21,636 --> 00:21:24,396 Speaker 2: common misconception about recycling, is that you know, these are 419 00:21:24,476 --> 00:21:27,956 Speaker 2: all you know somehow like public entities buy our estimation 420 00:21:27,996 --> 00:21:30,996 Speaker 2: about eighty or eighty five percent of these recycling facilities 421 00:21:31,196 --> 00:21:34,596 Speaker 2: are privately owned, and they can be anything from a 422 00:21:34,636 --> 00:21:38,156 Speaker 2: family owned business all the way up to the massive 423 00:21:38,196 --> 00:21:41,716 Speaker 2: waste companies like Waste Management, Republic Services, Waste Connections. These 424 00:21:41,716 --> 00:21:44,956 Speaker 2: are publicly traded companies that also own many of these 425 00:21:44,956 --> 00:21:46,156 Speaker 2: recycling plants as well. 426 00:21:46,676 --> 00:21:51,956 Speaker 1: And the recycling plants are buying recycling from municipalities like 427 00:21:52,116 --> 00:21:56,956 Speaker 1: they do they pay for whatever tans and plastic jugs. 428 00:21:57,156 --> 00:22:00,956 Speaker 2: It's actually a very interesting question. It depends a lot 429 00:22:01,036 --> 00:22:03,716 Speaker 2: on the condition of those end markets. We talked about 430 00:22:03,796 --> 00:22:07,196 Speaker 2: so in today's climate where those markets are really volatile 431 00:22:07,356 --> 00:22:11,196 Speaker 2: and a little bit uncertain, oftentimes, you know, these recycling 432 00:22:11,196 --> 00:22:14,636 Speaker 2: facilities will get paid by municipalities in order to take 433 00:22:14,676 --> 00:22:17,876 Speaker 2: any process that material. But what's interesting is, you know, 434 00:22:17,916 --> 00:22:20,996 Speaker 2: back during the heyday of recycling, when you know, China 435 00:22:21,076 --> 00:22:23,956 Speaker 2: was buying everything, there was no shortage of you know, 436 00:22:24,036 --> 00:22:27,116 Speaker 2: appetite for that material. The equation flipped. 437 00:22:27,236 --> 00:22:30,436 Speaker 1: My sense is some recycling is quite efficient and a 438 00:22:30,476 --> 00:22:33,276 Speaker 1: good business, and some is not very efficient in a 439 00:22:33,276 --> 00:22:35,756 Speaker 1: bad business. Right, give me the like stack ranking for 440 00:22:35,836 --> 00:22:38,396 Speaker 1: recycling best thing to recycle to worst. 441 00:22:38,596 --> 00:22:40,116 Speaker 2: Yeah, the I mean, at the end of the day, 442 00:22:40,156 --> 00:22:43,996 Speaker 2: the best things to recycle, according to a recycling facility operator, 443 00:22:44,036 --> 00:22:45,996 Speaker 2: would be the things that most reliably will make you 444 00:22:46,036 --> 00:22:49,356 Speaker 2: the most money. So top of the stack would be 445 00:22:49,636 --> 00:22:52,716 Speaker 2: aluminum cans, because there's always a market for those. They're 446 00:22:52,756 --> 00:22:56,476 Speaker 2: super easily recyclable, and to recycle an aluminum can actually 447 00:22:56,636 --> 00:22:59,636 Speaker 2: uses about ninety five percent less energy than to make 448 00:22:59,676 --> 00:23:03,436 Speaker 2: that aluminum can from that virgin or And this gets 449 00:23:03,476 --> 00:23:06,236 Speaker 2: back to the point about the sort of cost spread 450 00:23:06,316 --> 00:23:10,596 Speaker 2: between recycled versus virgin feed stuff. Right, the harder and 451 00:23:10,636 --> 00:23:13,156 Speaker 2: more costly it is to make it virgin, the more 452 00:23:13,316 --> 00:23:15,636 Speaker 2: of a willing market there is for that recycled material. 453 00:23:16,076 --> 00:23:18,836 Speaker 1: So cans are great, they always work as a business. 454 00:23:18,956 --> 00:23:20,556 Speaker 1: Aluminum cans are good. Okay, what's next. 455 00:23:20,636 --> 00:23:23,316 Speaker 2: Aluminum cans are great. Next is we're going to get 456 00:23:23,316 --> 00:23:27,396 Speaker 2: a little technical here. HDPE natural. So this is HDPE 457 00:23:27,476 --> 00:23:29,676 Speaker 2: is a type of plastic resin. If you look at 458 00:23:29,676 --> 00:23:33,076 Speaker 2: the little Chasing Arrows recycling logo, it's resin number two 459 00:23:33,676 --> 00:23:36,596 Speaker 2: and most commonly takes the form of milk jugs. Right, 460 00:23:36,836 --> 00:23:38,916 Speaker 2: that's sort of translucent white. 461 00:23:38,836 --> 00:23:41,036 Speaker 1: The gallon milk jug exactly exactly. 462 00:23:41,116 --> 00:23:43,716 Speaker 2: Yeah, and then from there, you know, I'd say it's 463 00:23:43,756 --> 00:23:48,556 Speaker 2: probably pet bottles. So that's triangle number one. That's like 464 00:23:48,596 --> 00:23:51,756 Speaker 2: your water bottles, your soda bottles. This is actually a 465 00:23:51,796 --> 00:23:55,516 Speaker 2: type of resin where we forecast a huge gap in 466 00:23:55,556 --> 00:23:58,156 Speaker 2: the supply versus what's going to be demanded about five 467 00:23:58,196 --> 00:24:00,756 Speaker 2: years from now. So that's a really interesting interesting one 468 00:24:00,796 --> 00:24:01,236 Speaker 2: to watch. 469 00:24:01,916 --> 00:24:04,756 Speaker 1: And then why I can imagine demand going up, But 470 00:24:04,756 --> 00:24:08,836 Speaker 1: why can't they just make more of them from virgin petroleum. 471 00:24:09,516 --> 00:24:13,356 Speaker 2: Yeah. It's a combination of legislative requirements around minimums recycled 472 00:24:13,356 --> 00:24:17,876 Speaker 2: content combined with sort of like the nature of the 473 00:24:17,956 --> 00:24:21,956 Speaker 2: end markets that are demanding pet. So you know, pet 474 00:24:22,156 --> 00:24:26,636 Speaker 2: could be used by the you know, water beverage bottle manufacturers, 475 00:24:26,756 --> 00:24:29,516 Speaker 2: but a lot of that pet also gets absorbed into 476 00:24:29,556 --> 00:24:34,716 Speaker 2: markets you wouldn't imagine, like carpet or mattresses or other textiles. 477 00:24:34,836 --> 00:24:37,756 Speaker 1: So the bad news is that there's plastic everywhere. But 478 00:24:37,796 --> 00:24:39,436 Speaker 1: the good news is at least they can use their 479 00:24:39,436 --> 00:24:40,676 Speaker 1: recycled bottles. 480 00:24:40,676 --> 00:24:44,676 Speaker 2: Exactly exactly, so that that's one turf that's getting pretty heated. 481 00:24:45,516 --> 00:24:47,316 Speaker 2: And then to at least a round out the sort 482 00:24:47,356 --> 00:24:49,996 Speaker 2: of container side of things. The other very common thing 483 00:24:50,036 --> 00:24:53,436 Speaker 2: that gets sorted is HGPE color. So h again it's 484 00:24:53,476 --> 00:24:56,836 Speaker 2: triangle number two, but it's it's been dyed, right. So 485 00:24:56,876 --> 00:24:59,236 Speaker 2: this is typically things like your shampoo bottles or your 486 00:24:59,316 --> 00:25:00,596 Speaker 2: laundry detergent. 487 00:25:00,276 --> 00:25:02,636 Speaker 1: Jumps, and so is that also like pretty good? Are 488 00:25:02,676 --> 00:25:04,996 Speaker 1: we still at pretty good on the stack? That's all. 489 00:25:05,076 --> 00:25:08,076 Speaker 2: That's all pretty good. I'd say those every single recycling 490 00:25:08,076 --> 00:25:10,956 Speaker 2: facility you go to will sort out those commodities. Okay, 491 00:25:11,276 --> 00:25:14,516 Speaker 2: And I'll mention here that there's a big time honorable 492 00:25:14,596 --> 00:25:18,476 Speaker 2: mention for cardboard and for paper. I was focusing on containers, 493 00:25:18,556 --> 00:25:21,196 Speaker 2: but a lot of people talk about plastics a ton. 494 00:25:21,596 --> 00:25:24,996 Speaker 2: The majority of the recycling stream is still paper and cardboard, right, 495 00:25:25,076 --> 00:25:27,676 Speaker 2: so that stuff like that's almost table stakes for a 496 00:25:27,716 --> 00:25:29,956 Speaker 2: recycling facility. Just you have to get that right if 497 00:25:29,956 --> 00:25:31,036 Speaker 2: you want to stay profitable. 498 00:25:31,316 --> 00:25:33,436 Speaker 1: And that's a reasonable business as well. 499 00:25:33,916 --> 00:25:36,116 Speaker 2: Yes, that's a very reasonable business. A lot of these 500 00:25:36,156 --> 00:25:39,396 Speaker 2: recycling facilities actually talk about something called the Amazon effect. 501 00:25:39,476 --> 00:25:42,836 Speaker 2: In other words, as you know, e commerce and shipping 502 00:25:42,996 --> 00:25:46,316 Speaker 2: has become the way we buy things. Cardboard has just 503 00:25:46,396 --> 00:25:49,756 Speaker 2: inundated the recycling stream, which is great because you can 504 00:25:49,756 --> 00:25:52,596 Speaker 2: always sell cardboard now there's a really hot market, but 505 00:25:52,676 --> 00:25:55,516 Speaker 2: also not so great because maybe your facility was built 506 00:25:55,556 --> 00:25:57,636 Speaker 2: ten to twenty years ago before this became a thing, 507 00:25:57,716 --> 00:25:59,276 Speaker 2: and now you have to find a way to sort 508 00:25:59,276 --> 00:26:01,236 Speaker 2: of jerry rig it to handle all of these massive, 509 00:26:01,236 --> 00:26:03,276 Speaker 2: oversized boxes that are coming through your stream. 510 00:26:03,436 --> 00:26:07,316 Speaker 1: So what that we recycle is dumb, isn't really getting recycled, 511 00:26:07,516 --> 00:26:08,756 Speaker 1: doesn't make sense whatever. 512 00:26:09,236 --> 00:26:11,636 Speaker 2: Yeah, this is a very long tail of things. 513 00:26:11,756 --> 00:26:14,716 Speaker 1: You know I mentioned for everything else. Yeah, it is. 514 00:26:14,676 --> 00:26:17,876 Speaker 2: The everything else. And this points me to what I 515 00:26:17,916 --> 00:26:20,756 Speaker 2: often tell people is a misconception. But recycling is the 516 00:26:20,756 --> 00:26:23,276 Speaker 2: phenomenon of wish cycling and I was guilty of this 517 00:26:23,316 --> 00:26:25,276 Speaker 2: too until I started Glacier and learn a bit more, 518 00:26:25,356 --> 00:26:27,116 Speaker 2: which is this idea that if you're not sure if 519 00:26:27,156 --> 00:26:28,996 Speaker 2: something is recyclable, a lot of people who want to 520 00:26:29,036 --> 00:26:30,836 Speaker 2: do good for the planet are like, I'll toss it 521 00:26:30,836 --> 00:26:33,756 Speaker 2: into the recycling bin in case they can do something 522 00:26:33,796 --> 00:26:35,556 Speaker 2: with it. And in fact, this ends up being a 523 00:26:35,636 --> 00:26:37,996 Speaker 2: huge problem for these facilities because most of the time 524 00:26:38,036 --> 00:26:40,036 Speaker 2: they can't do something with it, much as we wish 525 00:26:40,116 --> 00:26:42,916 Speaker 2: they could. So a lot of these contaminants that people 526 00:26:42,916 --> 00:26:47,156 Speaker 2: throw in there are things like those plastic bags or 527 00:26:47,316 --> 00:26:50,836 Speaker 2: you know, those films and flexibles, which some facilities can recycle, 528 00:26:50,876 --> 00:26:54,796 Speaker 2: but most can't. It's things that have plastic in them, 529 00:26:55,156 --> 00:26:58,196 Speaker 2: but it's not kind of standard plastic. So for example, 530 00:26:59,236 --> 00:27:03,156 Speaker 2: one very confusing and insidious example that gets brought up 531 00:27:03,236 --> 00:27:06,236 Speaker 2: often is children's toys. Right, maybe they're made out of 532 00:27:06,276 --> 00:27:09,036 Speaker 2: some bulky plastic. You're like, hopefully this can be recycled, 533 00:27:09,036 --> 00:27:11,836 Speaker 2: but chances are that toy has various different grades of 534 00:27:11,836 --> 00:27:14,236 Speaker 2: plastic on it that aren't easy to pull apart. And 535 00:27:14,316 --> 00:27:17,676 Speaker 2: heaven forbid it's an electronic toy with the batteries still 536 00:27:17,676 --> 00:27:20,156 Speaker 2: in it, because that can literally cause an explosion or 537 00:27:20,156 --> 00:27:24,156 Speaker 2: a fire and blow up the facility. 538 00:27:26,036 --> 00:27:28,036 Speaker 1: We'll be back in a minute with the lightning round. 539 00:27:37,636 --> 00:27:39,636 Speaker 1: Let's do a lightning round. It's going to be a 540 00:27:39,636 --> 00:27:43,356 Speaker 1: little more random. So I know you were a consultant. 541 00:27:43,396 --> 00:27:45,276 Speaker 1: Is it right that you were a management consultant? 542 00:27:45,516 --> 00:27:47,236 Speaker 2: I was a management consultant. 543 00:27:47,276 --> 00:27:50,916 Speaker 1: I'm curious you know now you run a company, right, 544 00:27:51,036 --> 00:27:54,076 Speaker 1: I'm curious what do you know now from running a 545 00:27:54,116 --> 00:27:57,156 Speaker 1: company that you wish you knew when you were you know, 546 00:27:57,356 --> 00:27:58,876 Speaker 1: telling people how to run their company. 547 00:28:00,436 --> 00:28:04,156 Speaker 2: Yeah. I think a lot of what I've learned running 548 00:28:04,196 --> 00:28:10,036 Speaker 2: Glacier has been around always identifying and then sort of 549 00:28:10,076 --> 00:28:13,916 Speaker 2: like revalidating what is that north star metric or objective 550 00:28:14,276 --> 00:28:18,436 Speaker 2: that we're aiming for, and then making sure that anything 551 00:28:18,476 --> 00:28:21,396 Speaker 2: else we're working on or anything we're communicating is in 552 00:28:21,476 --> 00:28:22,116 Speaker 2: support of that. 553 00:28:22,196 --> 00:28:23,676 Speaker 1: So, like, you're still a consultant. 554 00:28:26,076 --> 00:28:29,676 Speaker 2: Absolutely, I mean, honestly, I think, like running Glacier, A 555 00:28:29,676 --> 00:28:31,596 Speaker 2: lot of people think that the tech is the hard part, 556 00:28:31,596 --> 00:28:34,396 Speaker 2: and don't get me wrong, it's insanely hard, insanely challenging. 557 00:28:34,716 --> 00:28:37,876 Speaker 2: But when you think about something as cross functional as 558 00:28:37,876 --> 00:28:41,356 Speaker 2: a circular economy, like I'd say, the majority of my 559 00:28:41,596 --> 00:28:45,116 Speaker 2: day gets spent thinking about how to align incentives right, 560 00:28:45,276 --> 00:28:50,516 Speaker 2: like recycling facilities, brands, manufacturers, local legislators, Like they all 561 00:28:50,596 --> 00:28:53,516 Speaker 2: kind of want different things, So how do you explain 562 00:28:53,556 --> 00:28:56,956 Speaker 2: initiatives or proposals to each of those parties in a 563 00:28:56,996 --> 00:28:59,436 Speaker 2: way that makes sense to them and gets everyone growing 564 00:28:59,436 --> 00:29:00,156 Speaker 2: in the same direction. 565 00:29:00,276 --> 00:29:02,316 Speaker 1: So if the answer nothing is the answer, you feel 566 00:29:02,316 --> 00:29:04,276 Speaker 1: like you're actually still doing what you were doing. 567 00:29:04,316 --> 00:29:07,516 Speaker 2: No, I mean I would say that, you know, one 568 00:29:07,556 --> 00:29:10,036 Speaker 2: big mindset shift for me that has been very healthy 569 00:29:10,236 --> 00:29:14,236 Speaker 2: is I'm definitely a perfectionist and a type a personality. 570 00:29:14,516 --> 00:29:15,076 Speaker 1: You know, by. 571 00:29:14,996 --> 00:29:19,236 Speaker 2: Upbringing and in management consulting, you're really encouraged to lean 572 00:29:19,276 --> 00:29:22,116 Speaker 2: into that, right, Like people are paying you big bucks 573 00:29:22,156 --> 00:29:25,036 Speaker 2: to make sure that you got every every single last 574 00:29:25,076 --> 00:29:29,436 Speaker 2: detail down to the decimal place right everywhere. And so 575 00:29:30,836 --> 00:29:33,116 Speaker 2: you know, I'd say that my consulting days were great 576 00:29:33,156 --> 00:29:35,916 Speaker 2: for training me on like how to make sure I 577 00:29:35,996 --> 00:29:38,796 Speaker 2: knew what details mattered and really like make sure that 578 00:29:38,956 --> 00:29:42,556 Speaker 2: everything lined up. But with an early stage startup, it's 579 00:29:42,556 --> 00:29:44,996 Speaker 2: the opposite where like you don't have time to be 580 00:29:45,356 --> 00:29:49,476 Speaker 2: perfecting everything, and so that has actually allowed me to 581 00:29:49,596 --> 00:29:53,076 Speaker 2: sort of flex towards how quickly can I move and 582 00:29:53,156 --> 00:29:55,956 Speaker 2: still be efficient, Right, Like, what is the right sort 583 00:29:55,996 --> 00:29:59,116 Speaker 2: of balance of making sure that you're putting out high 584 00:29:59,156 --> 00:30:01,676 Speaker 2: quality work and that things are generally moving the right direction, 585 00:30:01,756 --> 00:30:05,156 Speaker 2: but also realizing that actually it's okay and probably good 586 00:30:05,476 --> 00:30:07,956 Speaker 2: that certain balls are getting dropped, because, as one of 587 00:30:07,996 --> 00:30:10,356 Speaker 2: my mentors told me, if you find that you are 588 00:30:10,396 --> 00:30:14,436 Speaker 2: doing everything perfectly and nothing is failing, you're probably not 589 00:30:14,516 --> 00:30:15,476 Speaker 2: moving fast enough. 590 00:30:16,076 --> 00:30:18,556 Speaker 1: Yeah. I interviewed the guy who started planning at the 591 00:30:18,596 --> 00:30:22,556 Speaker 1: satellite company, and he told me that he was upset 592 00:30:22,556 --> 00:30:25,716 Speaker 1: when none of their satellites were failing. It meant they 593 00:30:25,716 --> 00:30:27,996 Speaker 1: weren't launching soon enough, they were spending too long to 594 00:30:28,036 --> 00:30:30,516 Speaker 1: work on it. It's the same, That's exactly right. 595 00:30:30,556 --> 00:30:33,316 Speaker 2: That's been a massive learning and frankly a pretty painful 596 00:30:33,316 --> 00:30:35,276 Speaker 2: one in the early years of Glacier, when all I 597 00:30:35,276 --> 00:30:37,196 Speaker 2: wanted was to make sure that every single thing I 598 00:30:37,196 --> 00:30:40,876 Speaker 2: outputed was going to work. And you know, at the 599 00:30:40,956 --> 00:30:42,036 Speaker 2: end of the day, I was like, I just got 600 00:30:42,076 --> 00:30:43,636 Speaker 2: to get get rid of some of those sort of 601 00:30:43,676 --> 00:30:46,636 Speaker 2: controlling tendencies if I really want this company to scale 602 00:30:46,676 --> 00:30:47,556 Speaker 2: at the rate that it needs to. 603 00:30:47,836 --> 00:30:52,196 Speaker 1: What's one tip to stop being to type A when 604 00:30:52,196 --> 00:30:53,076 Speaker 1: you're running a startup. 605 00:30:53,476 --> 00:30:56,156 Speaker 2: Honestly, I don't know if this is healthy, but my 606 00:30:56,236 --> 00:30:58,356 Speaker 2: approach was to kind of just like overwhelm myself. 607 00:30:58,356 --> 00:31:00,356 Speaker 1: You give yourself too many things to do so that 608 00:31:00,436 --> 00:31:03,036 Speaker 1: you have to just pass them on before you're done 609 00:31:03,036 --> 00:31:03,356 Speaker 1: with them. 610 00:31:03,916 --> 00:31:07,276 Speaker 2: Yeah, and I'd say it wasn't our intentional per se, 611 00:31:07,356 --> 00:31:09,756 Speaker 2: because it's certainly not a very pleasant ex experience to 612 00:31:09,756 --> 00:31:14,396 Speaker 2: go through. But I often joke that, you know, I 613 00:31:14,396 --> 00:31:18,036 Speaker 2: think starting an early stage company was maybe the only 614 00:31:18,116 --> 00:31:20,116 Speaker 2: thing that could have broken me of some of these 615 00:31:20,156 --> 00:31:24,916 Speaker 2: perfectionist habits, because I really had to go through sort 616 00:31:24,956 --> 00:31:28,956 Speaker 2: of the dark side of pulling all nighters, working myself 617 00:31:28,956 --> 00:31:31,516 Speaker 2: to the bone, realizing, you know, like what is this 618 00:31:31,596 --> 00:31:34,636 Speaker 2: all for, and having that sort of existential crisis moment 619 00:31:34,676 --> 00:31:37,356 Speaker 2: to say, Okay, I don't want to give up on Glacier, 620 00:31:37,436 --> 00:31:39,436 Speaker 2: and I know we've got an immense amount of potential 621 00:31:39,476 --> 00:31:42,796 Speaker 2: ahead of us, so I now need to fundamentally rethink 622 00:31:42,916 --> 00:31:46,676 Speaker 2: how I'm balancing this list of a thousand priorities if 623 00:31:46,716 --> 00:31:48,596 Speaker 2: I want to do it and still be around in 624 00:31:48,636 --> 00:31:50,276 Speaker 2: a successful leader years from now. 625 00:31:51,236 --> 00:31:53,676 Speaker 1: Are you less of a perfectionist in your non work 626 00:31:53,756 --> 00:31:55,116 Speaker 1: life now than you used to be? 627 00:31:55,996 --> 00:31:59,836 Speaker 2: Uh? Absolutely? It's like amazing what perspective gives. 628 00:31:59,556 --> 00:32:00,316 Speaker 1: You on things. 629 00:32:00,396 --> 00:32:03,716 Speaker 2: Just a lack of time, yes, yeah, yeah, some would 630 00:32:03,716 --> 00:32:06,556 Speaker 2: call it just a raw lack of time. I do 631 00:32:06,636 --> 00:32:09,876 Speaker 2: think that it really sort of for you to think 632 00:32:09,996 --> 00:32:13,156 Speaker 2: much bigger picture about what matters to you and make 633 00:32:13,196 --> 00:32:15,996 Speaker 2: sure that you're carving time out for that and then 634 00:32:16,116 --> 00:32:18,396 Speaker 2: just not sweating the details. And the amazing thing is 635 00:32:19,436 --> 00:32:21,756 Speaker 2: once you start doing that and you realize that the 636 00:32:21,796 --> 00:32:23,996 Speaker 2: world isn't going to end because you forgot to do 637 00:32:24,076 --> 00:32:26,356 Speaker 2: this thing or decided not to do that thing perfectly, 638 00:32:26,796 --> 00:32:29,156 Speaker 2: it gets easier and easier to do right. So that's 639 00:32:29,156 --> 00:32:30,156 Speaker 2: been really healthy for me. 640 00:32:36,676 --> 00:32:40,396 Speaker 1: Rebecca who Trums, is the co founder and CEO of Glacier. 641 00:32:41,556 --> 00:32:44,876 Speaker 1: Please email us at problem at pushkin dot fm. We 642 00:32:44,916 --> 00:32:48,636 Speaker 1: are always looking for new guests for the show. Today's 643 00:32:48,676 --> 00:32:52,516 Speaker 1: show was produced by Trinamnino and Gabriel Hunter Chang. It 644 00:32:52,636 --> 00:32:56,516 Speaker 1: was edited by Alexander Garreton and engineered by Sarah Briguerra. 645 00:32:56,836 --> 00:32:58,996 Speaker 1: I'm Jacob Goldstein and we'll be back next week with 646 00:32:59,036 --> 00:33:07,676 Speaker 1: another episode of What's Your Problem