1 00:00:03,000 --> 00:00:06,040 Speaker 1: It's now time for Cannabis Talk one oh one with Blue, 2 00:00:06,400 --> 00:00:09,719 Speaker 1: Joe Grande, and Mark and Craig Wasserman the Pot Brothers 3 00:00:09,760 --> 00:00:13,560 Speaker 1: at Law. We're the world's number one podcast for everything cannabis. 4 00:00:13,640 --> 00:00:15,600 Speaker 1: Hello and welcome to Cannabis Talk one on one, the 5 00:00:15,600 --> 00:00:18,320 Speaker 1: world's number one source for everything cannabis. My day is Blue. 6 00:00:18,360 --> 00:00:21,239 Speaker 1: Alongside of me is Joe grand Yes, and alongside of 7 00:00:21,280 --> 00:00:23,840 Speaker 1: you and I Blue is Canna med here in Pasadena. 8 00:00:23,880 --> 00:00:25,560 Speaker 1: We're still all the way live. We'll be here talking 9 00:00:25,560 --> 00:00:27,800 Speaker 1: to so many amazing people. And thank you guys for 10 00:00:27,840 --> 00:00:30,160 Speaker 1: listening to the podcast Kinnabis Talk one on one. Check 11 00:00:30,160 --> 00:00:32,240 Speaker 1: out our website Cannabis Talk one on one dot com, 12 00:00:32,280 --> 00:00:34,640 Speaker 1: and we're the world's number one source for everything cannabis. 13 00:00:35,040 --> 00:00:37,360 Speaker 1: So many great articles, blogs, and so much good stuff 14 00:00:37,400 --> 00:00:41,479 Speaker 1: to learn their Call us up anytime and check out 15 00:00:41,479 --> 00:00:44,400 Speaker 1: our Instagram page for daily news and information at Cannabis 16 00:00:44,400 --> 00:00:46,280 Speaker 1: Talk one oh one. Will Blue is at the number 17 00:00:46,280 --> 00:00:49,200 Speaker 1: one Christopher right, Hello, I am at Joe Grande fifty 18 00:00:49,240 --> 00:00:51,240 Speaker 1: two and I gotta remind you guys, if you're looking 19 00:00:51,240 --> 00:00:53,000 Speaker 1: for a high quality seed and looking to grow some 20 00:00:53,320 --> 00:00:56,279 Speaker 1: wonderful cannabis, then head the Rocket seeds dot com. Our 21 00:00:56,480 --> 00:00:59,360 Speaker 1: check out the Instagram page at Rocket Underscore Seeds for 22 00:00:59,400 --> 00:01:02,200 Speaker 1: trusted can the best seeds at a fair price, Head 23 00:01:02,240 --> 00:01:07,000 Speaker 1: to Rocket seeds dot com. On the show Blue Interesting People. 24 00:01:07,120 --> 00:01:09,640 Speaker 1: As you know, we all know you've been hearing these podcasts, 25 00:01:09,760 --> 00:01:13,240 Speaker 1: so many phenomenal people that are showing up to can med. 26 00:01:13,400 --> 00:01:17,399 Speaker 1: And now we have the people from Ethical Data Alliance 27 00:01:18,120 --> 00:01:21,080 Speaker 1: and it is I believe the board member, the legal advisor, 28 00:01:21,080 --> 00:01:24,200 Speaker 1: and the director. We have Jeff Hamilton's Dale Hunt and 29 00:01:24,319 --> 00:01:33,240 Speaker 1: is it Ivianna Evian Evian Evian And I met you 30 00:01:33,360 --> 00:01:36,039 Speaker 1: the two nights ago, if I'm not mistaken, at a 31 00:01:36,080 --> 00:01:38,240 Speaker 1: beautiful luncheon out to a little Mexican Russiant. We had 32 00:01:38,240 --> 00:01:40,640 Speaker 1: a great conversation out there that will be in said, 33 00:01:40,640 --> 00:01:42,319 Speaker 1: I'm gonna play like we didn't have a conversation and 34 00:01:42,360 --> 00:01:45,840 Speaker 1: act like what do you guys do with this exactly? 35 00:01:45,880 --> 00:01:51,080 Speaker 1: With this beautiful Ethical Data Alliance is nonprofit organization that 36 00:01:51,160 --> 00:01:53,960 Speaker 1: you guys are grabbing all this great information for the 37 00:01:54,000 --> 00:01:56,040 Speaker 1: breeders and everybody else out there. So tell us a 38 00:01:56,080 --> 00:01:58,640 Speaker 1: little bit about what you guys do. So I'll give 39 00:01:58,680 --> 00:02:02,320 Speaker 1: you a little bit of backstory. Essentially, we about two 40 00:02:02,360 --> 00:02:06,200 Speaker 1: and a half years ago. UM, I'm gonna go way back. Actually, 41 00:02:06,360 --> 00:02:08,240 Speaker 1: so a couple of years ago, there was some ethical 42 00:02:08,280 --> 00:02:13,120 Speaker 1: issues in the industry around breeding and i P and 43 00:02:13,560 --> 00:02:18,120 Speaker 1: breeders writes things along like along those lines. And formerly 44 00:02:18,160 --> 00:02:21,120 Speaker 1: there was a group called the Open Cannabis Project and 45 00:02:21,440 --> 00:02:23,840 Speaker 1: when I'm just gonna call it but what it is. 46 00:02:23,880 --> 00:02:27,680 Speaker 1: But when Filo Skate happened a couple of years ago, UM, 47 00:02:27,720 --> 00:02:30,240 Speaker 1: a few of the board members realized that there was 48 00:02:30,240 --> 00:02:33,840 Speaker 1: still a need for some sort of ethical gatekeepers in 49 00:02:33,880 --> 00:02:38,640 Speaker 1: the industry, especially around data and i P and you know, 50 00:02:38,760 --> 00:02:42,720 Speaker 1: breeders genetics. There's no way to prove providance with genetics. 51 00:02:42,760 --> 00:02:44,840 Speaker 1: You know, somebody could say they have wedding cake, but 52 00:02:45,080 --> 00:02:47,400 Speaker 1: nobody really knows for sure if it is what it is. 53 00:02:47,440 --> 00:02:49,400 Speaker 1: You know, we've all run I've run five different cuts 54 00:02:49,400 --> 00:02:51,640 Speaker 1: of wedding cake over the past few years. So a 55 00:02:51,680 --> 00:02:55,200 Speaker 1: few of the board members and Dale Hunt, Angela Backa, 56 00:02:56,200 --> 00:03:00,000 Speaker 1: and the former director of the Open Cannabis Project who 57 00:03:00,000 --> 00:03:02,679 Speaker 1: now goes by Rosie but Beth Scheckter was her former name, 58 00:03:03,160 --> 00:03:04,799 Speaker 1: we kind of all got together and started to have 59 00:03:04,840 --> 00:03:08,040 Speaker 1: a conversation around how we could keep this importance of 60 00:03:08,080 --> 00:03:12,320 Speaker 1: ethics and data in the industry, and we decided to 61 00:03:12,360 --> 00:03:15,120 Speaker 1: create something called the Ethical Data Alliance and bring in 62 00:03:15,200 --> 00:03:20,760 Speaker 1: some people to create UH protocol basically to move the 63 00:03:20,800 --> 00:03:25,600 Speaker 1: industry forward and to hold ethics around you know what 64 00:03:25,639 --> 00:03:29,040 Speaker 1: we're doing, and a standard, a standard, a standard of 65 00:03:29,200 --> 00:03:32,200 Speaker 1: ethics for the industry, but especially around data and IP 66 00:03:32,280 --> 00:03:34,720 Speaker 1: protection and those things. And as all these people come 67 00:03:34,760 --> 00:03:36,720 Speaker 1: to do this, and I think that very much sounds 68 00:03:36,760 --> 00:03:39,360 Speaker 1: like what you're saying here. What is your specialty that 69 00:03:39,400 --> 00:03:41,640 Speaker 1: you're bringingcause I know we have the breeders, the growers, 70 00:03:41,640 --> 00:03:45,520 Speaker 1: supply chain operators, researchers, genetics, doctors, lawyers. Where do you 71 00:03:45,560 --> 00:03:47,720 Speaker 1: fall in line? UM? I have been a cultivator. I've 72 00:03:47,760 --> 00:03:50,040 Speaker 1: worked with cannabis for quite a long time now, and 73 00:03:50,080 --> 00:03:52,600 Speaker 1: I've been working in the regulated space for seven years, 74 00:03:52,640 --> 00:03:55,760 Speaker 1: and I work with different breeders UM across the board, 75 00:03:55,840 --> 00:03:58,040 Speaker 1: both in the hemp space and the adult use space. 76 00:03:58,240 --> 00:04:01,120 Speaker 1: And then also I teach her to culture at Oaxter 77 00:04:01,240 --> 00:04:04,160 Speaker 1: Dam University. I you know, I care. I care on 78 00:04:04,200 --> 00:04:07,920 Speaker 1: a deep level about genetics and about the breeders. And 79 00:04:07,960 --> 00:04:10,520 Speaker 1: you definitely see that the breeders and the farmers are 80 00:04:10,520 --> 00:04:13,200 Speaker 1: the ones that fall short and we saw a need 81 00:04:13,640 --> 00:04:16,680 Speaker 1: to be able to start to prove providence and to 82 00:04:16,720 --> 00:04:19,440 Speaker 1: be able to start to prove um. You know, there's 83 00:04:19,440 --> 00:04:22,640 Speaker 1: no supply chain story application. And so what we realized 84 00:04:23,120 --> 00:04:25,200 Speaker 1: through some wonderful people actually that we met here at 85 00:04:25,279 --> 00:04:28,520 Speaker 1: KAMMAD Christian Saucier, who could not join us here at 86 00:04:28,560 --> 00:04:31,440 Speaker 1: KAMD this year UM. He was introduced to us by 87 00:04:31,520 --> 00:04:37,359 Speaker 1: Kevin mccernan from Medicinal Genomics, and basically that we realized 88 00:04:37,400 --> 00:04:40,719 Speaker 1: that the application of blockchain was the perfect how we 89 00:04:40,760 --> 00:04:44,359 Speaker 1: could start to storytell everything that we're doing. So the 90 00:04:44,400 --> 00:04:50,000 Speaker 1: Ethical Data Alliance is basically creating a protocol it's called 91 00:04:50,000 --> 00:04:54,320 Speaker 1: the EDEN Protocol UM, which is the Ethical Data Exchange Network, 92 00:04:54,600 --> 00:04:57,880 Speaker 1: and it's a it's a network that will utilize blockchain 93 00:04:57,920 --> 00:05:02,160 Speaker 1: technology so that people can own their own data because 94 00:05:02,160 --> 00:05:04,159 Speaker 1: you know, we all we we can't. You can't look 95 00:05:04,240 --> 00:05:06,920 Speaker 1: up your data for um, you know, Google or all 96 00:05:06,960 --> 00:05:09,720 Speaker 1: these other things that we use. We don't own our 97 00:05:09,720 --> 00:05:12,120 Speaker 1: own data. And the same is true in the cannabis industry. 98 00:05:12,160 --> 00:05:15,280 Speaker 1: So we definitely need a way to tell the supply 99 00:05:15,400 --> 00:05:18,680 Speaker 1: chain story and essentially that's what we've been working to do. 100 00:05:18,800 --> 00:05:22,880 Speaker 1: File file Coin saw the saw what a great thing 101 00:05:22,920 --> 00:05:25,800 Speaker 1: we were working on and gave us a grant um 102 00:05:25,880 --> 00:05:28,400 Speaker 1: and we've been working to build this very cool protocol 103 00:05:28,400 --> 00:05:31,240 Speaker 1: and we have an amazing team. We have um you know, 104 00:05:31,279 --> 00:05:34,440 Speaker 1: we have the Harvard Blockchain Professor on our board as 105 00:05:34,480 --> 00:05:37,000 Speaker 1: well with Jeffrey and I and Dale is one of 106 00:05:37,000 --> 00:05:38,839 Speaker 1: the founders. So you know, we've done a lot of work. 107 00:05:38,839 --> 00:05:40,240 Speaker 1: At this point, we've been working on this for two 108 00:05:40,279 --> 00:05:44,400 Speaker 1: and a half years. We're trying to create something that 109 00:05:44,520 --> 00:05:46,920 Speaker 1: is going to be a gift back to the industry 110 00:05:46,960 --> 00:05:49,800 Speaker 1: that producers of data will be able to own their 111 00:05:49,839 --> 00:05:53,800 Speaker 1: own data, but also to showcase it and advance our research. 112 00:05:53,920 --> 00:05:56,880 Speaker 1: Like all the medical doctors here, the hope is that 113 00:05:56,920 --> 00:06:00,440 Speaker 1: we can start to showcase all of this people can 114 00:06:00,480 --> 00:06:03,119 Speaker 1: own their own data in a decentralized way and also 115 00:06:03,200 --> 00:06:07,360 Speaker 1: prepare us technologically for Web three and the things that 116 00:06:07,400 --> 00:06:09,320 Speaker 1: are coming up along the line. So it's it's a 117 00:06:09,360 --> 00:06:13,040 Speaker 1: deep it's a deep conversation. So there's so many different 118 00:06:13,400 --> 00:06:15,599 Speaker 1: levels of where we can go down, Like right everything 119 00:06:15,600 --> 00:06:16,919 Speaker 1: you just said, I'm I can go down there, So 120 00:06:17,000 --> 00:06:18,240 Speaker 1: we can go down to that one. I can't wait 121 00:06:18,279 --> 00:06:20,400 Speaker 1: to talk to Jeff Hamilton's about the director and Dale 122 00:06:20,440 --> 00:06:22,440 Speaker 1: now he puts his hands in something mouth. It's just 123 00:06:22,520 --> 00:06:25,479 Speaker 1: so crazy to think of how it's still all going 124 00:06:25,520 --> 00:06:28,240 Speaker 1: in the same direction of moving it forward in different 125 00:06:28,279 --> 00:06:32,280 Speaker 1: areas that there's just so many elements of where this 126 00:06:32,360 --> 00:06:34,159 Speaker 1: is going and what you guys are doing by putting 127 00:06:34,200 --> 00:06:37,280 Speaker 1: all those minds together. Does it get confusing sometimes? Where 128 00:06:37,600 --> 00:06:42,200 Speaker 1: or does everybody come to the same direction going well, no, no, no, 129 00:06:42,279 --> 00:06:44,080 Speaker 1: and somebody go, but what about this and what about that? 130 00:06:44,120 --> 00:06:47,760 Speaker 1: Does everybody just keep in putting and is there conflicts 131 00:06:47,800 --> 00:06:51,400 Speaker 1: sometimes because of different opinions. I feel like generally the 132 00:06:51,440 --> 00:06:53,920 Speaker 1: people that we've brought into it's an open group. So 133 00:06:54,000 --> 00:06:57,839 Speaker 1: I will say that we're open to the whole cannabis community. 134 00:06:57,839 --> 00:07:00,760 Speaker 1: If people want to join us and move the vision forward, 135 00:07:01,160 --> 00:07:03,719 Speaker 1: we are open. We have open calls, and then we 136 00:07:03,760 --> 00:07:07,240 Speaker 1: also are running pilots to showcase the proof of concept. 137 00:07:07,880 --> 00:07:10,880 Speaker 1: So I feel like we're all pretty aligned the people 138 00:07:10,880 --> 00:07:13,240 Speaker 1: who want, you know, have good ethics and want to 139 00:07:13,280 --> 00:07:15,000 Speaker 1: move forward. We're going to be at some point here 140 00:07:15,040 --> 00:07:17,840 Speaker 1: after the release of our next pilot, we're going to 141 00:07:17,880 --> 00:07:22,080 Speaker 1: be doing some sort of pledge essentially to pledge them 142 00:07:22,480 --> 00:07:25,840 Speaker 1: with some sort of contract. Companies could come and pledge 143 00:07:25,960 --> 00:07:29,960 Speaker 1: their allegiance to kind of like the Ethical Data Alliance. Um, 144 00:07:30,480 --> 00:07:32,320 Speaker 1: I'm sorry to catch off. Do you feel like that 145 00:07:32,400 --> 00:07:36,120 Speaker 1: there's gonna be you know, it's like it's a race though, 146 00:07:36,160 --> 00:07:38,360 Speaker 1: because there's so many people that probably already feel that 147 00:07:38,360 --> 00:07:42,800 Speaker 1: they own this, these strains or the cultivars um. They 148 00:07:42,800 --> 00:07:46,920 Speaker 1: already own the rights to the to to in in 149 00:07:46,920 --> 00:07:49,200 Speaker 1: in so many different facets. So now that there's a 150 00:07:49,240 --> 00:07:51,880 Speaker 1: new blockchain and they may or may not be aware 151 00:07:51,960 --> 00:07:55,640 Speaker 1: of how to you know, process that data and actually 152 00:07:55,640 --> 00:07:59,120 Speaker 1: claim it. Um, that there's gonna be a weird of 153 00:07:59,800 --> 00:08:03,920 Speaker 1: you know, I guess fight for that claims something like 154 00:08:04,080 --> 00:08:05,960 Speaker 1: you know what I mean. Like this, there's the guy 155 00:08:06,000 --> 00:08:08,640 Speaker 1: that maybe like in you know, northern California that's like 156 00:08:08,680 --> 00:08:11,680 Speaker 1: owned you know, the original white Widow strain or the 157 00:08:11,760 --> 00:08:14,360 Speaker 1: birthday cake right and then and he may not be 158 00:08:14,400 --> 00:08:18,240 Speaker 1: his hip to you know, this convention or that one. 159 00:08:18,360 --> 00:08:22,000 Speaker 1: And then you know, tomorrow it gets you know documented 160 00:08:22,040 --> 00:08:24,200 Speaker 1: as he's this guy's the new owner and he's going, 161 00:08:24,240 --> 00:08:26,080 Speaker 1: wait a minute, ude, I've owned this thing for like 162 00:08:26,120 --> 00:08:28,360 Speaker 1: the last hundred years, Like how could someone just take 163 00:08:28,440 --> 00:08:31,400 Speaker 1: this from me? Like gelato from Scherbinsky. Yeah, and it's 164 00:08:31,400 --> 00:08:33,320 Speaker 1: just like, how do you how do you you know, 165 00:08:33,440 --> 00:08:36,679 Speaker 1: I guess shuffle through that as you know, as professionals 166 00:08:36,720 --> 00:08:38,960 Speaker 1: in the industry, and how do we you know? I 167 00:08:39,000 --> 00:08:41,079 Speaker 1: guess is there layment terms to make that makes sense? 168 00:08:41,080 --> 00:08:44,240 Speaker 1: Because yeah, I know, how do you make that make sense? Question? 169 00:08:44,320 --> 00:08:46,760 Speaker 1: Because if I like, let's just use Scherbinsky for that matter, 170 00:08:46,840 --> 00:08:51,080 Speaker 1: or Sherbinsky has been claimed to come up with the 171 00:08:51,120 --> 00:08:55,120 Speaker 1: Scherbinsky model where all those things that he came up with, 172 00:08:55,679 --> 00:08:58,960 Speaker 1: what using that exact analogy that Blue Gay, which I 173 00:08:59,000 --> 00:09:01,160 Speaker 1: love because we could use a real company out there, 174 00:09:01,240 --> 00:09:03,320 Speaker 1: and I probably could have articulated a way better, but 175 00:09:03,400 --> 00:09:05,040 Speaker 1: I just kind of know, I felt it. I get it, 176 00:09:05,840 --> 00:09:07,400 Speaker 1: So I'm gonna try to help that. So you guys 177 00:09:07,559 --> 00:09:09,880 Speaker 1: understand that, right, I speak Blue very well, and I 178 00:09:09,920 --> 00:09:11,679 Speaker 1: thought to me, how about this Blue? I thought it 179 00:09:11,679 --> 00:09:14,000 Speaker 1: was all said, but I want to use a real person, 180 00:09:14,120 --> 00:09:19,480 Speaker 1: meaning Gelato and Sharbinsky. It is to us that Sharbinski 181 00:09:19,640 --> 00:09:23,960 Speaker 1: made gelato cannabis. Can you guys prove that? Or can 182 00:09:24,000 --> 00:09:26,720 Speaker 1: he prove that if someone else goes into mark it 183 00:09:26,800 --> 00:09:31,080 Speaker 1: just registers in. I'm not the technology guy here, so 184 00:09:31,320 --> 00:09:36,400 Speaker 1: um uh, the way that this is actually implemented. Maybe 185 00:09:36,600 --> 00:09:39,520 Speaker 1: the details may be different, but here's the principle. The 186 00:09:39,559 --> 00:09:43,200 Speaker 1: principle is anybody who has data about something they developed 187 00:09:43,280 --> 00:09:45,920 Speaker 1: or something they're working with is free to put their data, 188 00:09:46,000 --> 00:09:49,679 Speaker 1: make their data available on the on EDEN, which can 189 00:09:49,760 --> 00:09:53,320 Speaker 1: include whatever. It can include your evidence of when you 190 00:09:53,360 --> 00:09:56,319 Speaker 1: started working with this, however strong or week that evidence is. 191 00:09:56,640 --> 00:09:59,040 Speaker 1: You can put in as much as you want. It's 192 00:09:59,080 --> 00:10:04,199 Speaker 1: not necessarily Uh, it's not the place of EDEN or 193 00:10:04,240 --> 00:10:07,880 Speaker 1: eader to decide how valid those data are or how 194 00:10:07,960 --> 00:10:11,920 Speaker 1: how just put that in, put it on the blockchain. 195 00:10:11,960 --> 00:10:15,800 Speaker 1: It's immutable. Other people put their things in, and I 196 00:10:15,800 --> 00:10:18,720 Speaker 1: think it settles out. The facts settle out. Now. What's 197 00:10:18,800 --> 00:10:20,920 Speaker 1: what matters though, is that as this goes into the 198 00:10:20,960 --> 00:10:23,200 Speaker 1: supply chain, what what's this. One of the things that 199 00:10:23,240 --> 00:10:25,520 Speaker 1: this can do is it can connect a source. So 200 00:10:25,840 --> 00:10:29,280 Speaker 1: in a particular season, somebody's growing a particular strain or cultivar, 201 00:10:29,840 --> 00:10:32,679 Speaker 1: and then that that is so this person bred it. 202 00:10:32,679 --> 00:10:36,040 Speaker 1: It went from them to the nursery, to a cultivator, 203 00:10:36,600 --> 00:10:41,880 Speaker 1: to UH manufacturer, to a distributor to a patient, and 204 00:10:41,920 --> 00:10:44,520 Speaker 1: then the patient can even put in if they want to, 205 00:10:44,600 --> 00:10:47,400 Speaker 1: they can put in their own DNA information and their 206 00:10:47,440 --> 00:10:50,760 Speaker 1: outcomes and they can say, Wow, this thing did this 207 00:10:51,080 --> 00:10:54,680 Speaker 1: for me, and that's great. But if it's one data point, 208 00:10:54,679 --> 00:10:56,400 Speaker 1: it doesn't tell you a lot. As soon though, as 209 00:10:56,440 --> 00:11:00,280 Speaker 1: you aggregate or whatever makes all of this stuff available, uh, 210 00:11:00,360 --> 00:11:02,920 Speaker 1: then you can really start to tease out the effects 211 00:11:03,040 --> 00:11:06,360 Speaker 1: and you can correlate them with Okay, this mode of cultivation, 212 00:11:06,800 --> 00:11:10,200 Speaker 1: this genotype of the of the plant, and this genotype 213 00:11:10,200 --> 00:11:12,200 Speaker 1: of the patient. This is this is going to be 214 00:11:12,240 --> 00:11:14,920 Speaker 1: a real revolution and personalized medicine and it's just all 215 00:11:14,920 --> 00:11:16,439 Speaker 1: going to be at a data spot where we can 216 00:11:16,480 --> 00:11:18,079 Speaker 1: look it all up. I mean, is that how it's 217 00:11:18,080 --> 00:11:21,560 Speaker 1: going to be? You could actually, if I'm not mistaken, 218 00:11:21,559 --> 00:11:23,640 Speaker 1: you can now put it in yourself. So this isn't 219 00:11:23,679 --> 00:11:28,080 Speaker 1: about ownership. This is about educational and learning how to actually, 220 00:11:28,600 --> 00:11:31,640 Speaker 1: um know what strain what cultivar is going to help 221 00:11:31,679 --> 00:11:34,360 Speaker 1: me for my elements. It's a little more complicate, can 222 00:11:34,400 --> 00:11:37,520 Speaker 1: I can ideal? So basically, so we all know that 223 00:11:37,559 --> 00:11:40,959 Speaker 1: we were required in the regulated market to use the 224 00:11:41,000 --> 00:11:44,760 Speaker 1: cannabis tracking systems or seed to sail tracking systems, but 225 00:11:45,320 --> 00:11:48,839 Speaker 1: essentially what we've been working to create, there's missing elements 226 00:11:49,000 --> 00:11:51,200 Speaker 1: in that as it is right now, so there's no 227 00:11:51,240 --> 00:11:55,280 Speaker 1: way to story tell the complete vision from like you know, 228 00:11:55,360 --> 00:11:58,320 Speaker 1: the breeding, the history of the breeding. Even so where 229 00:11:58,320 --> 00:12:01,640 Speaker 1: did you know, for instance, where did Scherbinsky come up 230 00:12:01,720 --> 00:12:04,360 Speaker 1: with that? What did he pull down? There's no storytelling 231 00:12:04,640 --> 00:12:08,280 Speaker 1: and so basically the blockchain enables us to have and 232 00:12:08,320 --> 00:12:11,839 Speaker 1: what we're doing with the EDEN protocol and EDEN platform 233 00:12:12,040 --> 00:12:16,160 Speaker 1: is to create a storytelling application through blockchain, because cannabis 234 00:12:16,240 --> 00:12:19,520 Speaker 1: has one of the most complicated supply chains of anything 235 00:12:19,559 --> 00:12:21,840 Speaker 1: else that we work with. So you have the historical 236 00:12:22,520 --> 00:12:25,200 Speaker 1: data of when somebody bred something and they could you know, 237 00:12:25,400 --> 00:12:28,760 Speaker 1: do their best to stamp those things. There's genomic data 238 00:12:28,800 --> 00:12:31,160 Speaker 1: when people are working with molecular breeding, not that all 239 00:12:31,200 --> 00:12:34,440 Speaker 1: breeders do that. And then from there, as Dale was 240 00:12:34,480 --> 00:12:37,000 Speaker 1: saying that, you know, there's usually there's a seed or 241 00:12:37,240 --> 00:12:41,200 Speaker 1: there's a genetics provider. Then there's a nursery application. Sometimes 242 00:12:41,200 --> 00:12:45,920 Speaker 1: there's two nursery applications, like TC plus a nursery application, 243 00:12:46,240 --> 00:12:48,760 Speaker 1: and then from there it goes to the producer every 244 00:12:48,760 --> 00:12:51,400 Speaker 1: single one of these things and there and then at 245 00:12:51,480 --> 00:12:55,320 Speaker 1: the point of nursery there could be you know, pathogen 246 00:12:55,400 --> 00:12:58,839 Speaker 1: testing that could be third party certified also, and then 247 00:12:58,920 --> 00:13:03,840 Speaker 1: from there there's so much producer cultivation data that can 248 00:13:03,880 --> 00:13:06,679 Speaker 1: come through. It's pretty infinite if you have not observed, 249 00:13:06,960 --> 00:13:11,160 Speaker 1: and that really impacts the you know, the the chemotype 250 00:13:11,160 --> 00:13:14,320 Speaker 1: and the chemical makeup of the plant. So there's so 251 00:13:14,360 --> 00:13:20,280 Speaker 1: many and everything. Yeah, exactly whether farm data, bioregional data, indoor, outdoor, 252 00:13:20,320 --> 00:13:22,840 Speaker 1: and this is way more extensive and and not that 253 00:13:22,880 --> 00:13:26,360 Speaker 1: doesn't even include the you know that there is also 254 00:13:26,520 --> 00:13:29,560 Speaker 1: the CTS data that comes through that, and then beyond 255 00:13:29,679 --> 00:13:34,920 Speaker 1: there there's um, you know, labs test results, third party certifications. 256 00:13:34,960 --> 00:13:38,040 Speaker 1: There's third party certifications for you know, say like Sun 257 00:13:38,080 --> 00:13:41,240 Speaker 1: and Earth certification, organic certification. We don't we can't be 258 00:13:41,320 --> 00:13:45,080 Speaker 1: technically certified organic. But there's so many different point data 259 00:13:45,120 --> 00:13:49,400 Speaker 1: points along the chain that um from. Then then it 260 00:13:49,440 --> 00:13:51,960 Speaker 1: could go to processing, that product could go to processing, 261 00:13:51,960 --> 00:13:54,959 Speaker 1: which creates a whole another set of data. There's harvest data, 262 00:13:55,400 --> 00:13:58,400 Speaker 1: and then I'm not done yet, So there's not just 263 00:13:59,760 --> 00:14:02,120 Speaker 1: it's well, but it keeps going all the way. And 264 00:14:02,120 --> 00:14:04,440 Speaker 1: the missing link at this point is we don't have 265 00:14:04,600 --> 00:14:07,520 Speaker 1: that end the ability for the end consumer data to 266 00:14:07,600 --> 00:14:10,280 Speaker 1: plug back in with the whole supply chain. And then 267 00:14:10,320 --> 00:14:14,160 Speaker 1: also this authentication of the genetics because we at this 268 00:14:14,240 --> 00:14:16,960 Speaker 1: point we really don't. I mean, there are I like 269 00:14:17,040 --> 00:14:19,360 Speaker 1: to use the example of wedding cake, because there really are. 270 00:14:19,440 --> 00:14:22,600 Speaker 1: I know that I've grown five very different distinct things. 271 00:14:22,640 --> 00:14:25,400 Speaker 1: And when you start to actually blueprint this stuff to 272 00:14:25,520 --> 00:14:29,120 Speaker 1: prove provenance of genetics, which you know, I do believe, 273 00:14:29,160 --> 00:14:32,880 Speaker 1: like there are some really fantastic um i P things 274 00:14:32,960 --> 00:14:36,400 Speaker 1: that can integrate into this as well, and creating smart 275 00:14:36,480 --> 00:14:38,360 Speaker 1: contracts like this is so deep and now with the 276 00:14:38,360 --> 00:14:40,560 Speaker 1: whole n f T thing, you know, this is a 277 00:14:40,680 --> 00:14:43,920 Speaker 1: very deep thing. But I think what we're realizing is 278 00:14:43,960 --> 00:14:46,800 Speaker 1: that we don't have that like CTS is not and 279 00:14:47,040 --> 00:14:49,520 Speaker 1: it's not we don't know. We don't know the origin 280 00:14:49,680 --> 00:14:52,480 Speaker 1: of things in our space, and cannabis is a perfect 281 00:14:52,480 --> 00:14:56,480 Speaker 1: example to train our markets to understand and technology is 282 00:14:56,520 --> 00:14:59,080 Speaker 1: the tool to do that. And then also within that 283 00:14:59,160 --> 00:15:03,040 Speaker 1: there's multiple different people trying to prove providence and having 284 00:15:03,280 --> 00:15:07,000 Speaker 1: patents or other things on on different cultivars and variety. 285 00:15:07,120 --> 00:15:10,560 Speaker 1: So it's a very deep, deep storytelling and people could 286 00:15:10,640 --> 00:15:13,560 Speaker 1: share as much or as little of the data that 287 00:15:13,600 --> 00:15:18,040 Speaker 1: they want to. And as a board member, I thought 288 00:15:18,080 --> 00:15:19,800 Speaker 1: you made you created the whole thing up yourself, and 289 00:15:19,840 --> 00:15:24,920 Speaker 1: you just grab these two baboons to help you. It's 290 00:15:24,960 --> 00:15:27,160 Speaker 1: Cannabis Talk. What when we come back, We're talking to 291 00:15:27,200 --> 00:15:29,920 Speaker 1: more of these guys. Ethical Data Alliance. Check out the 292 00:15:29,960 --> 00:15:33,040 Speaker 1: website Ethical Data dot net. That's E T H I 293 00:15:33,160 --> 00:15:35,360 Speaker 1: C A L D A t A dot n et. 294 00:15:35,640 --> 00:15:37,160 Speaker 1: We'll be right back. It's gonna be stalk one on. 295 00:15:37,200 --> 00:15:39,440 Speaker 1: Watch stay with us. We'll be right back with Cannabis 296 00:15:39,520 --> 00:15:55,280 Speaker 1: Talk one oh one. Welcome back to Cannabis Talk one 297 00:15:55,280 --> 00:15:58,640 Speaker 1: oh one. Folks has the widest selection of cannabinoids. They 298 00:15:58,640 --> 00:16:01,640 Speaker 1: carry products with all the cannabinoids that you've heard of 299 00:16:02,120 --> 00:16:04,440 Speaker 1: and some that you even haven't. Now we're talking to 300 00:16:04,480 --> 00:16:07,160 Speaker 1: these amazing people here once again. The website is Ethical 301 00:16:07,240 --> 00:16:11,560 Speaker 1: Data dot nets and everything you guys are describing is 302 00:16:11,600 --> 00:16:15,680 Speaker 1: just so much information that's needed out there. But yet 303 00:16:15,800 --> 00:16:19,320 Speaker 1: I feel like it's still gonna always change and evolve, 304 00:16:19,840 --> 00:16:22,520 Speaker 1: and it's nothing that could be a quote unquote certain 305 00:16:22,560 --> 00:16:27,560 Speaker 1: protocol that we can make now because it's still gonna change. Correct, Well, no, 306 00:16:27,640 --> 00:16:29,720 Speaker 1: I mean, wouldn't it still evolved as we're not going 307 00:16:29,800 --> 00:16:31,960 Speaker 1: to even see what we don't even know yet as 308 00:16:31,960 --> 00:16:35,960 Speaker 1: a plant is still providing more and more um things 309 00:16:35,960 --> 00:16:38,320 Speaker 1: that we don't even know right, so therefore it's going 310 00:16:38,360 --> 00:16:40,640 Speaker 1: to change. I would imagine me looking at this from 311 00:16:40,640 --> 00:16:44,080 Speaker 1: a my standpoint, going, Okay, we create the standard right now, 312 00:16:44,560 --> 00:16:47,200 Speaker 1: but then we find out that the plant creates something 313 00:16:47,240 --> 00:16:50,080 Speaker 1: new that therefore now that stander changes. Well, that's why 314 00:16:50,120 --> 00:16:51,920 Speaker 1: being here at Ken Matt, I just gotta say, like, 315 00:16:52,040 --> 00:16:54,760 Speaker 1: it's you know, anybody who's truly on this path, it's 316 00:16:54,800 --> 00:16:58,800 Speaker 1: the razor edge, cutting edge science piece that you know. 317 00:16:58,880 --> 00:17:00,960 Speaker 1: I think that's why we're here can Med. Right, this 318 00:17:01,040 --> 00:17:03,480 Speaker 1: is like hearing all the scientists go back and forth 319 00:17:03,520 --> 00:17:06,000 Speaker 1: and hearing Dale argue with the doctor about you know, 320 00:17:06,480 --> 00:17:11,720 Speaker 1: strange and you know what a great debate deal where 321 00:17:11,720 --> 00:17:13,520 Speaker 1: I went home and talked about I went to go home, 322 00:17:13,640 --> 00:17:15,639 Speaker 1: went to my room and came and talked about it, 323 00:17:15,640 --> 00:17:18,320 Speaker 1: like it was so intriguing to me. Like hearing you 324 00:17:18,359 --> 00:17:21,320 Speaker 1: guys literally have a great debate about that was what 325 00:17:21,359 --> 00:17:24,119 Speaker 1: I love about Canada. Like there's the debates I'm in. 326 00:17:24,760 --> 00:17:27,160 Speaker 1: We're in the corner over here, and this other lady 327 00:17:27,240 --> 00:17:29,840 Speaker 1: said something to other lady and was like, oh, thank 328 00:17:29,840 --> 00:17:32,200 Speaker 1: you for schooling me on that. That was so well versed, 329 00:17:32,320 --> 00:17:35,199 Speaker 1: bo Boa, and I heard it. I can't repeat it 330 00:17:35,200 --> 00:17:38,040 Speaker 1: because it was just so well said. But the other 331 00:17:38,160 --> 00:17:41,200 Speaker 1: scientists looked at the other doctor and said, well, thank 332 00:17:41,240 --> 00:17:43,200 Speaker 1: you for schooling me on that. That was really well said. 333 00:17:43,200 --> 00:17:45,320 Speaker 1: And that's the type of soaking up knowledge that you 334 00:17:45,359 --> 00:17:48,480 Speaker 1: sit around can med and here because it's from a 335 00:17:48,520 --> 00:17:51,160 Speaker 1: different level rather than oh, let's just smoke or let's 336 00:17:51,200 --> 00:17:53,280 Speaker 1: just talk about I call it fast food like a 337 00:17:53,280 --> 00:17:55,199 Speaker 1: lot of us. You know, we we we get so 338 00:17:55,280 --> 00:17:57,639 Speaker 1: much fast food in this industry, so it's hard to 339 00:17:57,680 --> 00:18:00,840 Speaker 1: really take in and and and not get fattened. Right, 340 00:18:01,040 --> 00:18:04,000 Speaker 1: So you know, so you know, there's good, really good 341 00:18:04,000 --> 00:18:07,320 Speaker 1: dining here, and you can have some conversations with people 342 00:18:07,320 --> 00:18:09,159 Speaker 1: that are just like on the next level. And I 343 00:18:09,160 --> 00:18:11,480 Speaker 1: think what you guys are doing, and you're gonna have 344 00:18:11,520 --> 00:18:14,080 Speaker 1: to forgive us because you guys are moving faster than us. 345 00:18:14,119 --> 00:18:17,359 Speaker 1: And and we've heard so many things on this show. Um, 346 00:18:17,440 --> 00:18:20,280 Speaker 1: but what you're telling us right now and again, and 347 00:18:20,400 --> 00:18:23,160 Speaker 1: there's so many more ways. But if I'm not mistaken, 348 00:18:23,240 --> 00:18:25,560 Speaker 1: is that the data that people start to input on 349 00:18:25,600 --> 00:18:30,080 Speaker 1: your guys site, right, we'll start to give people more 350 00:18:30,160 --> 00:18:33,080 Speaker 1: and more data on the plant and they can identify 351 00:18:33,240 --> 00:18:36,199 Speaker 1: what this plant will do per strain per cult of 352 00:18:36,240 --> 00:18:39,720 Speaker 1: our poor whatever it is. And from from the weather 353 00:18:39,760 --> 00:18:42,520 Speaker 1: that the conditions they had, down to the soils they use, 354 00:18:42,640 --> 00:18:46,439 Speaker 1: down to the um you know, uh turpine, you know, 355 00:18:46,520 --> 00:18:49,560 Speaker 1: profiles or whatever that's out there. And and as you 356 00:18:49,600 --> 00:18:53,479 Speaker 1: start putting that in, it's almost you know, for me, 357 00:18:53,520 --> 00:18:55,240 Speaker 1: I feel like it's almost a person that puts the 358 00:18:55,280 --> 00:18:58,959 Speaker 1: most data in winds or is it the combination of 359 00:18:59,000 --> 00:19:01,439 Speaker 1: all the people putting in all the data that wins 360 00:19:01,480 --> 00:19:03,760 Speaker 1: because now there's so much information about it. It's like 361 00:19:03,880 --> 00:19:07,080 Speaker 1: the dictionary. We're building the dictionary. Are you guys building 362 00:19:07,080 --> 00:19:10,119 Speaker 1: a dictionary? I mean, I think we're building a storehouse 363 00:19:10,160 --> 00:19:12,879 Speaker 1: of great information. But there's really I used a word 364 00:19:13,080 --> 00:19:16,200 Speaker 1: really incorrectly a minute ago when I said aggregation. Because 365 00:19:16,920 --> 00:19:20,359 Speaker 1: you know the entities like Google and Facebook, they aggregate 366 00:19:20,480 --> 00:19:22,560 Speaker 1: data and they own it and it can be abused. 367 00:19:23,359 --> 00:19:25,520 Speaker 1: The goal here is not really to aggregate the data, 368 00:19:25,520 --> 00:19:28,080 Speaker 1: but to make it accessible. Even though each person whose 369 00:19:28,119 --> 00:19:31,040 Speaker 1: data it is still has control. They can take it 370 00:19:31,080 --> 00:19:33,080 Speaker 1: down at any time, they can make it make its 371 00:19:33,200 --> 00:19:38,400 Speaker 1: access conditional and then edited. And so it's essentially a 372 00:19:38,400 --> 00:19:41,040 Speaker 1: collection of information that someone can access if they want 373 00:19:41,040 --> 00:19:44,800 Speaker 1: to learn something. And um and as more people put 374 00:19:44,800 --> 00:19:46,920 Speaker 1: more information, it will be more, it will be worth more. Now, 375 00:19:46,920 --> 00:19:49,160 Speaker 1: what motivates them to do that is as they put 376 00:19:49,160 --> 00:19:51,480 Speaker 1: their information and they get some sort of a token 377 00:19:51,920 --> 00:19:55,000 Speaker 1: for that, and when they're when there's value associated with 378 00:19:55,040 --> 00:19:58,600 Speaker 1: their information, their token gets value. They actually get paid. 379 00:19:58,600 --> 00:20:01,600 Speaker 1: Instead of some giant any like Google or Facebook. Up 380 00:20:01,840 --> 00:20:05,359 Speaker 1: here we go. Now you're talking to everybody. I can 381 00:20:05,440 --> 00:20:08,520 Speaker 1: get paid to keep talking to keep going, like it 382 00:20:08,640 --> 00:20:11,080 Speaker 1: makes sense? How do I make money on this side? Now? 383 00:20:11,160 --> 00:20:16,920 Speaker 1: I want to start data? Is that is the new 384 00:20:16,960 --> 00:20:20,160 Speaker 1: gold right where it's gold already cannabis data and where 385 00:20:20,200 --> 00:20:22,640 Speaker 1: the data producers being able to own that own data. 386 00:20:22,680 --> 00:20:24,199 Speaker 1: But we do we kind of just give it up 387 00:20:24,200 --> 00:20:27,560 Speaker 1: in this centralized fashion. And if we can understand how 388 00:20:27,560 --> 00:20:31,400 Speaker 1: we can advance science and actually that this data could 389 00:20:31,400 --> 00:20:34,600 Speaker 1: actually end up benefiting the end consumer in such a 390 00:20:34,640 --> 00:20:37,760 Speaker 1: massive way, and then all the people along the supply chain, 391 00:20:38,480 --> 00:20:40,879 Speaker 1: because we really we were still learning, like you said earlier, 392 00:20:40,880 --> 00:20:43,399 Speaker 1: like it's going to change all the time with this plant, 393 00:20:43,440 --> 00:20:47,040 Speaker 1: and we're still learning on a regular basis. And I 394 00:20:47,080 --> 00:20:50,000 Speaker 1: think a really important thing to recognize is that you know, 395 00:20:50,119 --> 00:20:53,000 Speaker 1: I could grow the same cultivar in Oregon you know, 396 00:20:53,040 --> 00:20:55,119 Speaker 1: I've worked with EBB and Flow for years Ebb and 397 00:20:55,160 --> 00:20:57,720 Speaker 1: Flow farm, and we could grow a cultivar and it 398 00:20:57,720 --> 00:21:00,240 Speaker 1: would be different if every one of us um totally 399 00:21:00,240 --> 00:21:03,760 Speaker 1: different threw the same exact cut of the same cultivar. 400 00:21:03,920 --> 00:21:07,440 Speaker 1: It's going to have slight variations based on what we do. 401 00:21:07,560 --> 00:21:09,719 Speaker 1: And we're still trying to understand these things. I mean, 402 00:21:09,720 --> 00:21:12,879 Speaker 1: the science here, we don't even understand all of the 403 00:21:12,880 --> 00:21:16,040 Speaker 1: different compounds that are in the plant. We're just learning 404 00:21:16,040 --> 00:21:17,600 Speaker 1: in the past couple of days things that are in 405 00:21:17,640 --> 00:21:20,280 Speaker 1: the least that we still don't even know. To think 406 00:21:20,280 --> 00:21:22,119 Speaker 1: that we still don't know that, that's just powerful for 407 00:21:22,160 --> 00:21:23,919 Speaker 1: me to be honest with like to think about how 408 00:21:24,000 --> 00:21:25,359 Speaker 1: long this plan has been around, To think of how 409 00:21:25,359 --> 00:21:27,919 Speaker 1: many brilliant people are around here that's study this on 410 00:21:27,960 --> 00:21:32,080 Speaker 1: a daily basis and have organizations with a bunch of 411 00:21:32,080 --> 00:21:34,720 Speaker 1: people doing the same thing, and we've yet to find 412 00:21:34,720 --> 00:21:37,640 Speaker 1: out everything about this plant. Well, let's post prohibition has 413 00:21:38,040 --> 00:21:41,480 Speaker 1: we're coming out of prohibition era thinking and so hope 414 00:21:41,520 --> 00:21:43,800 Speaker 1: hopefully with the work that we're doing with the Ethical 415 00:21:43,880 --> 00:21:47,480 Speaker 1: Data Alliance and the companies that we are all affiliated with, 416 00:21:48,000 --> 00:21:51,320 Speaker 1: that we can start to help advance the science and 417 00:21:51,400 --> 00:21:54,640 Speaker 1: move things forward because at this point and also verify 418 00:21:54,760 --> 00:21:57,560 Speaker 1: because people can say a law of stuff and and 419 00:21:57,560 --> 00:21:59,840 Speaker 1: in cannabis, we we are required by law to do 420 00:22:00,000 --> 00:22:04,119 Speaker 1: certain testing, but I think there's deeper layers of you know, 421 00:22:04,160 --> 00:22:07,240 Speaker 1: we're missing our origin stories where you know, these people 422 00:22:07,280 --> 00:22:11,159 Speaker 1: have for years protected a lot of these cultivars and genetics, 423 00:22:11,200 --> 00:22:13,800 Speaker 1: and so I think it's our duty. I mean, that's 424 00:22:13,800 --> 00:22:15,679 Speaker 1: part of my passion with this and the reason that 425 00:22:15,800 --> 00:22:18,919 Speaker 1: I have been so dedicated to this nonprofit work is 426 00:22:18,960 --> 00:22:21,920 Speaker 1: because somebody's got to speak for the plants. Somebody's got 427 00:22:21,920 --> 00:22:24,679 Speaker 1: to speak for the breeders that have worked for you know, 428 00:22:24,960 --> 00:22:28,040 Speaker 1: decades and decades to preserve these things, not let alone 429 00:22:28,119 --> 00:22:31,960 Speaker 1: the indigenous cultures that have protected these things for thousands 430 00:22:32,000 --> 00:22:34,879 Speaker 1: of years that we're not necessarily giving. We're not able to. 431 00:22:34,920 --> 00:22:37,360 Speaker 1: But my my personal hope is at some point we're 432 00:22:37,400 --> 00:22:39,520 Speaker 1: able to tip back to some of those communities. And 433 00:22:39,560 --> 00:22:42,160 Speaker 1: I will say to the Ethical Data Alliance is not 434 00:22:42,280 --> 00:22:46,840 Speaker 1: just about cannabis. It's also about other biological substances, so 435 00:22:46,960 --> 00:22:49,680 Speaker 1: not other botanical plants. The hope is that maybe as 436 00:22:49,760 --> 00:22:52,679 Speaker 1: some of the amazing professors here have and doctors have 437 00:22:52,760 --> 00:22:54,680 Speaker 1: spoken in the past couple of days, there's this hope 438 00:22:54,720 --> 00:22:57,080 Speaker 1: that where cannabis is going to help bring all of 439 00:22:57,119 --> 00:23:00,480 Speaker 1: these other things into the limelight and really help humanity 440 00:23:00,520 --> 00:23:04,160 Speaker 1: in the future, and the psilocybin for instance, but also 441 00:23:04,240 --> 00:23:06,680 Speaker 1: there's a ton of other things that we're just we're 442 00:23:06,720 --> 00:23:09,720 Speaker 1: still studying, and also to protect those things along the 443 00:23:09,720 --> 00:23:13,080 Speaker 1: way is a big, very very important a verse of 444 00:23:13,080 --> 00:23:15,159 Speaker 1: you know, I love it. It's awesome. It's just everything 445 00:23:15,200 --> 00:23:17,560 Speaker 1: you're saying is what you guys are doing. And when 446 00:23:17,600 --> 00:23:19,080 Speaker 1: we come back to I want to talk to you Dale, 447 00:23:19,080 --> 00:23:20,600 Speaker 1: because we haven't heard too much from you as you're 448 00:23:20,600 --> 00:23:23,120 Speaker 1: the legal adviser and what company you're with. For those 449 00:23:23,160 --> 00:23:25,159 Speaker 1: who don't know Jeff Hamilton's we talked to him and 450 00:23:25,200 --> 00:23:27,400 Speaker 1: the other podcast a while back. We'll get exactly what 451 00:23:27,680 --> 00:23:29,760 Speaker 1: his company does on this podcast, but you have heard 452 00:23:29,760 --> 00:23:32,080 Speaker 1: from him and know from his staff what they were 453 00:23:32,119 --> 00:23:35,160 Speaker 1: doing and which is amazing stuff. Jeff like that. That's 454 00:23:35,680 --> 00:23:38,960 Speaker 1: you know, just just Dale. I mean Dale, Jeff, We're 455 00:23:38,960 --> 00:23:42,280 Speaker 1: gonna come back with Jeff let me which those words. Yeah, 456 00:23:42,520 --> 00:23:44,000 Speaker 1: I was like I was living here, like I think 457 00:23:44,200 --> 00:23:47,240 Speaker 1: I messed up that whole thing. Yeah, Jeff Hamilton, we 458 00:23:47,280 --> 00:23:48,960 Speaker 1: want to come back with you. You're the director we 459 00:23:49,000 --> 00:23:51,080 Speaker 1: did hear from Dale was the one that we did here. 460 00:23:51,160 --> 00:23:52,919 Speaker 1: Dale hasn't been here to see and he didn't want 461 00:23:52,960 --> 00:23:55,360 Speaker 1: to come on yesterday, so you wouldn't spoil it for him. 462 00:23:55,480 --> 00:23:57,320 Speaker 1: But now, but now we're gonna come back for him 463 00:23:57,359 --> 00:23:58,880 Speaker 1: and talk to him to the we can't a little. 464 00:23:58,880 --> 00:24:00,639 Speaker 1: It'skind of talk one on one. Right back after the 465 00:24:00,680 --> 00:24:03,600 Speaker 1: jo we'll be right back with Cannabis Talk one oh one. 466 00:24:17,640 --> 00:24:20,720 Speaker 1: Welcome back to Cannabis Talk one oh one. What time 467 00:24:20,800 --> 00:24:24,360 Speaker 1: is it? That's right, Folks think higher with Dime Industries. 468 00:24:24,400 --> 00:24:28,120 Speaker 1: Find him in California, Arizona and Oklahoma. Dime Industry has 469 00:24:28,119 --> 00:24:30,880 Speaker 1: been a leading trusted source of clean and potent medicine 470 00:24:31,080 --> 00:24:33,760 Speaker 1: using state of the yard hardware including premium food grade 471 00:24:33,760 --> 00:24:37,439 Speaker 1: stainless steel, glass, ceramic plates, and enhanced battery life. The 472 00:24:37,520 --> 00:24:40,840 Speaker 1: one thousand milligram cartridges are amazing. Check out the website 473 00:24:40,880 --> 00:24:44,320 Speaker 1: diamon industry dot com or on Instagram Dime dot Industry. 474 00:24:44,560 --> 00:24:46,840 Speaker 1: Now we're still here live at cam d All these 475 00:24:46,920 --> 00:24:50,399 Speaker 1: wonderful people were just messing up names or I was 476 00:24:50,440 --> 00:24:51,920 Speaker 1: blue not you. I don't want to tell you under 477 00:24:51,920 --> 00:24:54,520 Speaker 1: the bust of me, so definitely messing up Jeff Hamilton's 478 00:24:54,560 --> 00:24:56,240 Speaker 1: and Dale Hunt. Dale was the guy that we did 479 00:24:56,280 --> 00:24:58,359 Speaker 1: have on the the day, but a legal advisor and 480 00:24:58,400 --> 00:25:00,760 Speaker 1: a CEO and all this great things. Eff Hamilton's is 481 00:25:00,800 --> 00:25:02,840 Speaker 1: somebody that we've heard little words from so far. The 482 00:25:02,880 --> 00:25:06,000 Speaker 1: director of Ethical Data Alliance, Jeff, what is the company 483 00:25:06,000 --> 00:25:08,800 Speaker 1: that you're with and how do you work with this company? 484 00:25:08,800 --> 00:25:13,040 Speaker 1: Because you're either probably a breeder or grower, supply chain operator, researcher, 485 00:25:13,080 --> 00:25:17,560 Speaker 1: genetics doctor, lawyer, software developer, writer, advocate. What do you do? Brother, 486 00:25:17,800 --> 00:25:22,199 Speaker 1: I'm a lawyer, another layer, another lawyer, another one and 487 00:25:22,240 --> 00:25:27,520 Speaker 1: what got you in towards this? So so what the 488 00:25:27,600 --> 00:25:31,040 Speaker 1: Ethical Data Alliance does is I mean, it's going to 489 00:25:31,119 --> 00:25:34,080 Speaker 1: be incredible um and it's going to be incredible for 490 00:25:34,359 --> 00:25:38,320 Speaker 1: health outcomes. And so in the last segment we were 491 00:25:38,320 --> 00:25:41,119 Speaker 1: talking about you know, if the volume of data is 492 00:25:41,160 --> 00:25:45,480 Speaker 1: what makes this successful or what makes user successful, but 493 00:25:45,520 --> 00:25:48,639 Speaker 1: I would argue it's the quality of the data. And 494 00:25:48,680 --> 00:25:52,159 Speaker 1: so when you think about how people use the plant, 495 00:25:52,680 --> 00:25:55,520 Speaker 1: we know very little, but it doesn't take that much 496 00:25:55,560 --> 00:25:59,359 Speaker 1: to get data that's going to meaningfully improve people's lives. 497 00:25:59,520 --> 00:26:03,440 Speaker 1: So love that we think about you go to dispensary, 498 00:26:03,640 --> 00:26:06,159 Speaker 1: you buy your jar of cannabis, you go home, you 499 00:26:06,200 --> 00:26:09,440 Speaker 1: consumer it. But what if you go to the dispensary 500 00:26:09,560 --> 00:26:11,919 Speaker 1: you get your Darve cannabis and it's you get this 501 00:26:12,000 --> 00:26:16,119 Speaker 1: coupon off your next purchase. If you fell out of survey, 502 00:26:16,119 --> 00:26:18,399 Speaker 1: how does this make you feel? Doesn't make you feel 503 00:26:18,720 --> 00:26:21,159 Speaker 1: didn't make you hungry, didn't make you feel energized. Did 504 00:26:21,160 --> 00:26:23,840 Speaker 1: it make you feel tired, didn't give you the munchies? 505 00:26:23,960 --> 00:26:25,600 Speaker 1: Did it help you with your back pain? Did it 506 00:26:25,680 --> 00:26:28,320 Speaker 1: help you sleep? And then all of a sudden, you 507 00:26:28,320 --> 00:26:32,280 Speaker 1: can participate the cost of off your next purchase throughout 508 00:26:32,320 --> 00:26:35,320 Speaker 1: the supply chain. So people are contributing. People are paying 509 00:26:35,440 --> 00:26:38,919 Speaker 1: for data that improves people's lives. So all of a sudden, 510 00:26:39,119 --> 00:26:43,600 Speaker 1: you are a breeder and you developed the strain. You 511 00:26:43,640 --> 00:26:46,520 Speaker 1: didn't know it, but it's being used in the market 512 00:26:46,560 --> 00:26:50,440 Speaker 1: to treat back pain. And you could say, with specificity, 513 00:26:50,560 --> 00:26:54,200 Speaker 1: we had five hundred surveys. Three people said it helped 514 00:26:54,240 --> 00:26:57,000 Speaker 1: me treat my back paint. You with a breeder, just 515 00:26:57,040 --> 00:27:01,400 Speaker 1: have your bag of seeds in your trader. But all 516 00:27:01,440 --> 00:27:03,960 Speaker 1: of a sudden, you have a product with a therapeutic use, 517 00:27:04,000 --> 00:27:06,080 Speaker 1: not that you can do a clinical trial, because that's 518 00:27:06,119 --> 00:27:09,000 Speaker 1: a you know, another level of scrutiny. But the fact 519 00:27:09,000 --> 00:27:13,320 Speaker 1: that you can use data to create value for your 520 00:27:13,320 --> 00:27:16,160 Speaker 1: products to improve people's lives. And it's just a matter 521 00:27:16,359 --> 00:27:18,560 Speaker 1: of how that data talks to each other and how 522 00:27:18,600 --> 00:27:22,280 Speaker 1: people will supply chain use it. UM. But the marketing value, 523 00:27:22,359 --> 00:27:25,520 Speaker 1: the beneficial value, the therapeutic value, it's there. It's just 524 00:27:25,640 --> 00:27:28,520 Speaker 1: a matter of capturing people's data in a way that's appropriate, 525 00:27:28,560 --> 00:27:31,480 Speaker 1: that's fair, that's ethical, which is almost which is which 526 00:27:31,520 --> 00:27:35,119 Speaker 1: is priceless. I mean actually right, having the ability to 527 00:27:35,160 --> 00:27:37,960 Speaker 1: get this data from so many different people and then 528 00:27:39,119 --> 00:27:41,400 Speaker 1: that's verified, I guess you know, and once you start 529 00:27:41,440 --> 00:27:44,040 Speaker 1: having it, you know, you know what your product is, 530 00:27:44,240 --> 00:27:46,280 Speaker 1: you know what can help people. I mean, this is 531 00:27:46,320 --> 00:27:48,879 Speaker 1: something that is highly needed. Are you guys the only 532 00:27:48,960 --> 00:27:52,680 Speaker 1: one doing this right now? I mean so I think 533 00:27:52,720 --> 00:27:54,840 Speaker 1: that there, I mean, there are other projects. I think 534 00:27:54,840 --> 00:27:57,840 Speaker 1: there's what we're doing is more comprehensive. It's open. Anyone 535 00:27:57,880 --> 00:28:00,800 Speaker 1: can plug in UM. Like I know that I personally 536 00:28:00,840 --> 00:28:04,439 Speaker 1: have a company that's plugging into this system UM. And 537 00:28:04,480 --> 00:28:06,840 Speaker 1: so I think that the way that we're doing it 538 00:28:06,960 --> 00:28:09,959 Speaker 1: and the openness with which this whole entire process has 539 00:28:10,000 --> 00:28:12,960 Speaker 1: been conducted. There's calls on Tuesday mornings, people are for 540 00:28:13,000 --> 00:28:17,120 Speaker 1: you to join, there's a slack channel. It's just we're 541 00:28:17,119 --> 00:28:19,639 Speaker 1: trying to do We're trying to do this right, starting 542 00:28:19,640 --> 00:28:22,639 Speaker 1: from scratch. Wow, were you doing it right? And Jeff, 543 00:28:22,680 --> 00:28:24,679 Speaker 1: what made you go or what kind of lawyer are you? 544 00:28:25,240 --> 00:28:27,919 Speaker 1: So I'm I'm a partner for Lebron and Martel in 545 00:28:27,920 --> 00:28:32,080 Speaker 1: San Francisco. UM, I do cannabis transactional work. You and 546 00:28:32,359 --> 00:28:36,399 Speaker 1: you live in the city. I live in Oakland. UM. Yeah, well, 547 00:28:36,520 --> 00:28:38,280 Speaker 1: now I've been working from home for the last couple 548 00:28:38,320 --> 00:28:41,960 Speaker 1: of years, and I also founded a company called Canopy Right, 549 00:28:42,160 --> 00:28:47,880 Speaker 1: which is decentralized botanical registry for cannabis plants that allows 550 00:28:47,920 --> 00:28:52,640 Speaker 1: people to license. UM there's their cultivars based on transaction 551 00:28:52,840 --> 00:28:57,400 Speaker 1: or based on track and trace data. So UM, I 552 00:28:57,440 --> 00:29:01,960 Speaker 1: can talk about that more. I'm so curious what is that? 553 00:29:02,400 --> 00:29:07,720 Speaker 1: So if you think about how the regulated market works, UM, 554 00:29:07,800 --> 00:29:10,000 Speaker 1: you have the breeders who develop their strains, and then 555 00:29:10,000 --> 00:29:13,800 Speaker 1: you have the cultivators who grow those strains. UM. But 556 00:29:14,160 --> 00:29:17,680 Speaker 1: the problem with the industry is that it's really hard 557 00:29:17,760 --> 00:29:20,160 Speaker 1: to track what a cultivar is. So you're talking about 558 00:29:20,200 --> 00:29:25,120 Speaker 1: Chabinski's earlier. You know what is gelato? And so my 559 00:29:25,200 --> 00:29:28,800 Speaker 1: experience working as a in the in the legal field 560 00:29:28,960 --> 00:29:32,320 Speaker 1: is that these problems come up all of the time. Um, 561 00:29:32,320 --> 00:29:36,280 Speaker 1: they're very complicated and um, but what you can you 562 00:29:36,320 --> 00:29:39,520 Speaker 1: can simplify it by saying, this is what my cultivar is, 563 00:29:39,600 --> 00:29:42,840 Speaker 1: and you define it, um in a way that allows 564 00:29:42,920 --> 00:29:46,560 Speaker 1: other people to to grow it and at scale and 565 00:29:46,600 --> 00:29:50,280 Speaker 1: get paid for it. So what we're doing is we're saying, 566 00:29:50,640 --> 00:29:53,920 Speaker 1: if if you want to register a cultivar, you take 567 00:29:53,960 --> 00:29:56,320 Speaker 1: a cutting, a fresh leaf material, you stick it in 568 00:29:56,360 --> 00:29:58,800 Speaker 1: an evidence bag, just a Tampa revenue package with a 569 00:29:58,880 --> 00:30:02,640 Speaker 1: QR code so that um, there's no identifying information, and 570 00:30:02,760 --> 00:30:05,320 Speaker 1: you take your you seal your evidence bag and you 571 00:30:05,360 --> 00:30:08,640 Speaker 1: stick your sample and your freezer and all of a sudden, 572 00:30:08,800 --> 00:30:11,440 Speaker 1: what is a cultivar? Well, it's a It's an embodiment 573 00:30:11,480 --> 00:30:14,160 Speaker 1: of a physical plant that's living in my freezer. Now, 574 00:30:14,760 --> 00:30:17,480 Speaker 1: if you think about how the regulated market works, you 575 00:30:17,560 --> 00:30:21,440 Speaker 1: have to put a tag on every single flowering plant 576 00:30:21,520 --> 00:30:24,480 Speaker 1: in the market. So if you know what a cannabis 577 00:30:24,480 --> 00:30:27,240 Speaker 1: strain is because it's in your freezer, and you put 578 00:30:27,280 --> 00:30:30,360 Speaker 1: as much data into your profile as you want. You 579 00:30:30,360 --> 00:30:32,959 Speaker 1: could put in your testing data, you can put in 580 00:30:33,040 --> 00:30:36,480 Speaker 1: your stories, you can put in anecdotal evidence, um. But 581 00:30:36,560 --> 00:30:39,120 Speaker 1: you know that in the regulated market you have to 582 00:30:39,160 --> 00:30:41,880 Speaker 1: put a tag on every single plant. So if you 583 00:30:41,920 --> 00:30:45,040 Speaker 1: think of a cannabis breeder as an artist and a 584 00:30:45,040 --> 00:30:48,479 Speaker 1: cannabis strain as a song, and a cannabis plant as 585 00:30:48,520 --> 00:30:50,680 Speaker 1: the equivalent of a play of a song, exactly, you 586 00:30:50,720 --> 00:30:55,360 Speaker 1: can create a copyright like system. So when somebody grows 587 00:30:55,520 --> 00:30:59,960 Speaker 1: a plant of your strain um and it the tag 588 00:31:00,000 --> 00:31:02,040 Speaker 1: bags that are on the planet entered into the track 589 00:31:02,080 --> 00:31:05,240 Speaker 1: and trade system automatically, you can you can send invoices 590 00:31:05,640 --> 00:31:08,080 Speaker 1: and so you can create a system that works like 591 00:31:08,200 --> 00:31:11,760 Speaker 1: music streaming, but for licensing cannabis stains. And so that's 592 00:31:11,800 --> 00:31:16,960 Speaker 1: what we built, or we're building right now. So I 593 00:31:16,960 --> 00:31:23,840 Speaker 1: love Jeff where you come up with that like the 594 00:31:23,880 --> 00:31:26,320 Speaker 1: poor man's copyright, Like we'd send it, you know, we'd 595 00:31:26,360 --> 00:31:29,480 Speaker 1: send ourselves something in the mail, right so that and 596 00:31:29,520 --> 00:31:32,320 Speaker 1: we'd have our songs and you know, they're just in 597 00:31:32,400 --> 00:31:34,520 Speaker 1: case we're in the studio with this guy and he 598 00:31:34,600 --> 00:31:37,000 Speaker 1: decides to use the song and it happens all the time. 599 00:31:37,040 --> 00:31:38,680 Speaker 1: It's like, dude, that's my hook. I'm like, what do 600 00:31:38,680 --> 00:31:40,400 Speaker 1: you mean, Like I I wrote that ship, I was 601 00:31:40,400 --> 00:31:42,840 Speaker 1: in the studio and just like no, But now Snoop 602 00:31:42,880 --> 00:31:44,880 Speaker 1: Dogg has it and he's you know, using it, and 603 00:31:44,920 --> 00:31:46,920 Speaker 1: you're like, wait a minute, he was there the dad, 604 00:31:47,040 --> 00:31:49,360 Speaker 1: you know. And you can't really approve that unless you 605 00:31:49,440 --> 00:31:51,880 Speaker 1: had that, you know, set back before the day they 606 00:31:51,920 --> 00:31:55,120 Speaker 1: recorded it. But if you have medicinal genomics and you 607 00:31:55,200 --> 00:31:58,040 Speaker 1: have a sample in your freezer and somebody rips you off, 608 00:31:58,200 --> 00:32:01,960 Speaker 1: you can open bag and freezer, that's timestamp. You can 609 00:32:02,000 --> 00:32:08,400 Speaker 1: send it for testing and you can sort of prove it. Yeah, 610 00:32:08,440 --> 00:32:12,120 Speaker 1: and so so, because in the regulated market you have 611 00:32:12,200 --> 00:32:14,200 Speaker 1: to you have to tag everything. You have these like 612 00:32:14,840 --> 00:32:20,800 Speaker 1: incredible inventory control requirements. The same system that makes music 613 00:32:20,840 --> 00:32:23,600 Speaker 1: streaming work, Like this is just a different application of 614 00:32:23,680 --> 00:32:26,200 Speaker 1: the same concept, but for data that you're already tracking 615 00:32:26,240 --> 00:32:28,360 Speaker 1: anyway because you have to because the state makes you. 616 00:32:28,760 --> 00:32:30,680 Speaker 1: I love that your brain and whoever helped you come 617 00:32:30,760 --> 00:32:33,040 Speaker 1: up with this came up with something like that. Help 618 00:32:33,360 --> 00:32:36,960 Speaker 1: did you deny? You got so many random things like dude, 619 00:32:36,960 --> 00:32:39,800 Speaker 1: where do you come from? Deal that you're you're sitting 620 00:32:41,160 --> 00:32:42,880 Speaker 1: let me see this, Like when Dale came in and 621 00:32:42,920 --> 00:32:45,760 Speaker 1: he you know, and and he was he yesterday he 622 00:32:45,760 --> 00:32:49,520 Speaker 1: gave me with a shameless blug, the shameless blug you 623 00:32:49,560 --> 00:32:52,120 Speaker 1: put in yesterday, I thought to myself, I said, well, 624 00:32:52,480 --> 00:32:55,719 Speaker 1: you know, she shouldn't even have to do that because 625 00:32:55,760 --> 00:32:58,200 Speaker 1: everybody in this freaking the audience shouldn't know exactly who 626 00:32:58,200 --> 00:33:00,800 Speaker 1: this man is. And that's in the and and that's 627 00:33:00,800 --> 00:33:02,520 Speaker 1: what I think we're gonna help. We'll help bridge a 628 00:33:02,520 --> 00:33:04,280 Speaker 1: lot of those guests for you, because I think we 629 00:33:04,360 --> 00:33:07,479 Speaker 1: touched so many people. And it's funny because I think 630 00:33:07,520 --> 00:33:09,720 Speaker 1: there's there's a million other people that are thinking just 631 00:33:09,800 --> 00:33:12,600 Speaker 1: like you guys that probably listened to our show, and 632 00:33:12,640 --> 00:33:15,080 Speaker 1: then there's a ton of other people that can care less. 633 00:33:16,000 --> 00:33:18,320 Speaker 1: But it's the orchestration of all of us that create 634 00:33:18,480 --> 00:33:22,160 Speaker 1: the actual, the actual, real song and dance. So uh 635 00:33:22,240 --> 00:33:24,360 Speaker 1: continue that, I think finding those who want to move 636 00:33:24,360 --> 00:33:27,160 Speaker 1: and dance. Yeah, We're gonna help find more people because 637 00:33:27,200 --> 00:33:32,360 Speaker 1: what you guys are doing. Every dude, I'm sitting here 638 00:33:32,440 --> 00:33:36,160 Speaker 1: for everybody like, how did you pull that out? And 639 00:33:36,200 --> 00:33:39,640 Speaker 1: then yesterday with Dale, huh, like you guys are just 640 00:33:39,800 --> 00:33:43,880 Speaker 1: pushing the envelope and pushing it. And Dale, you have 641 00:33:44,080 --> 00:33:46,560 Speaker 1: this company you have your hand in that company. You're 642 00:33:46,600 --> 00:33:50,920 Speaker 1: a director here, a legal advisor. They're a board member here. Dale. 643 00:33:50,960 --> 00:33:55,560 Speaker 1: You're doing so much, dude, I'm so impressed, impressed and 644 00:33:55,640 --> 00:33:59,040 Speaker 1: in awe, and I want you to say a little 645 00:33:59,080 --> 00:34:01,200 Speaker 1: more about what you do and and forgive me that 646 00:34:01,240 --> 00:34:02,720 Speaker 1: I don't have in my notes right now in front 647 00:34:02,720 --> 00:34:04,120 Speaker 1: of me. The company that we just talked about that 648 00:34:04,200 --> 00:34:07,480 Speaker 1: you own yesterday? What was that one? Thank you? I 649 00:34:07,480 --> 00:34:09,440 Speaker 1: sat Breeders something I knew with something Breeders. I seen 650 00:34:09,440 --> 00:34:11,960 Speaker 1: the breeders here. Breeders Best is your colvery, that's you're 651 00:34:11,960 --> 00:34:14,440 Speaker 1: the CEO of. And then what else are you a 652 00:34:14,480 --> 00:34:16,480 Speaker 1: part of? Like you just said two things right now, 653 00:34:16,480 --> 00:34:18,360 Speaker 1: you're a part of this one, the Ethical Data Alliance, 654 00:34:18,560 --> 00:34:20,719 Speaker 1: And now Jeff just mentioned something else that you're part of. 655 00:34:21,560 --> 00:34:24,600 Speaker 1: What else are you a part of? Well? I found 656 00:34:24,920 --> 00:34:27,520 Speaker 1: a law firm called Plant and Planet Law Firm. That's 657 00:34:27,560 --> 00:34:30,440 Speaker 1: my day job. Where's that It's in San Diego, but 658 00:34:30,480 --> 00:34:33,239 Speaker 1: we're all over the place. In fact, this is the 659 00:34:33,320 --> 00:34:35,600 Speaker 1: last leg on a three thousand mile road trip that 660 00:34:35,640 --> 00:34:38,400 Speaker 1: I began a couple of weeks ago. I was visiting 661 00:34:38,760 --> 00:34:42,200 Speaker 1: um farms and breeders and meetings of groups like that 662 00:34:42,560 --> 00:34:45,319 Speaker 1: for the last couple of weeks and dropping off a 663 00:34:45,320 --> 00:34:48,000 Speaker 1: little tequila here and there, picking up some flour here 664 00:34:48,000 --> 00:34:50,640 Speaker 1: and there. So, um, this is what I love. This 665 00:34:50,680 --> 00:34:53,360 Speaker 1: is my passion. Before I did this, I was a 666 00:34:53,400 --> 00:34:57,560 Speaker 1: partner in a big a few big law firms, and um, 667 00:34:57,600 --> 00:34:59,960 Speaker 1: I kind of had to clear most of those idea 668 00:35:00,040 --> 00:35:01,960 Speaker 1: as I had with my partners because if you're a 669 00:35:02,000 --> 00:35:04,000 Speaker 1: partner in a law firm, you don't really have any 670 00:35:04,040 --> 00:35:07,160 Speaker 1: bosses except all your other partners or your boss. So 671 00:35:07,760 --> 00:35:09,440 Speaker 1: the reason I started my own law firm is I 672 00:35:09,440 --> 00:35:11,719 Speaker 1: wanted to be free to do stuff like this. And 673 00:35:11,840 --> 00:35:15,400 Speaker 1: so nobody's checking my billable hours except my accountant, you know. 674 00:35:15,400 --> 00:35:19,439 Speaker 1: Always nobody's checking to see what I'm doing with my time. 675 00:35:19,600 --> 00:35:21,640 Speaker 1: It's just me. It's just me and can I afford 676 00:35:21,640 --> 00:35:24,319 Speaker 1: to do it? And I'm just chasing my passions. That's 677 00:35:24,360 --> 00:35:26,680 Speaker 1: so awesome that guys like you, and there's so many 678 00:35:26,719 --> 00:35:28,640 Speaker 1: of them out there that have that passion for this, 679 00:35:28,719 --> 00:35:30,719 Speaker 1: and I think there's a lot of them have very 680 00:35:30,760 --> 00:35:34,240 Speaker 1: successful careers and then decide I'm gonna put this passion 681 00:35:34,280 --> 00:35:37,560 Speaker 1: back into cannabis, which are then helping so many other people. 682 00:35:37,880 --> 00:35:40,799 Speaker 1: And as you go towards that cultivar. What is that 683 00:35:40,880 --> 00:35:44,279 Speaker 1: love for that plant that makes you go extremely I 684 00:35:44,280 --> 00:35:48,680 Speaker 1: feel like you're helping the cultivars. Well, I can tell 685 00:35:48,680 --> 00:35:54,000 Speaker 1: that cannabis is the richest source of of useful medicinal 686 00:35:54,080 --> 00:35:57,680 Speaker 1: chemicals of any plant that we know. Um. I learned 687 00:35:57,680 --> 00:35:59,759 Speaker 1: a lot of that from my friend Ethan whom you 688 00:35:59,760 --> 00:36:05,160 Speaker 1: guys stirred. Almost gotten a fistfight with Ethan Russo not really, 689 00:36:05,200 --> 00:36:13,000 Speaker 1: but anyway, UM I can see that the plant really 690 00:36:13,040 --> 00:36:17,200 Speaker 1: is going to revolutionize medicine. That the legalization of cannabis 691 00:36:17,280 --> 00:36:21,000 Speaker 1: coincides with so much that we're learning about human genomics, 692 00:36:21,280 --> 00:36:23,399 Speaker 1: and that we can correlate what the plant can do 693 00:36:23,520 --> 00:36:26,359 Speaker 1: with what each different person's genetic makeup is. And we're 694 00:36:26,360 --> 00:36:29,440 Speaker 1: gonna be able to dial in some really great personalized medicines. 695 00:36:29,760 --> 00:36:33,520 Speaker 1: And we're gonna be getting away from, uh from at 696 00:36:33,560 --> 00:36:36,919 Speaker 1: least in many cases, from pharmaceutical drugs that I think 697 00:36:37,320 --> 00:36:39,319 Speaker 1: they bring a lot of side effects between because they're 698 00:36:39,320 --> 00:36:41,600 Speaker 1: trying to do all a lot of things, a lot 699 00:36:41,640 --> 00:36:45,840 Speaker 1: of yeah bring a strong effect with one single molecule, 700 00:36:46,280 --> 00:36:49,040 Speaker 1: and when you have plant medicines that have that combine 701 00:36:49,040 --> 00:36:51,120 Speaker 1: a lot of things, you have room for synergy and 702 00:36:51,160 --> 00:36:54,480 Speaker 1: that's um. So that matters to me a lot. And 703 00:36:54,480 --> 00:36:56,560 Speaker 1: then the other thing that I think, the other passion 704 00:36:56,560 --> 00:36:58,840 Speaker 1: that drives me is just having gotten to know a 705 00:36:58,840 --> 00:37:02,040 Speaker 1: lot of old school leaders and seeing their their passion 706 00:37:02,040 --> 00:37:04,719 Speaker 1: and their dedication and how much they struggled to have 707 00:37:04,760 --> 00:37:07,239 Speaker 1: to even keep make ends meet because of all the 708 00:37:07,280 --> 00:37:10,799 Speaker 1: regulations and taxes and all the everything. That I just 709 00:37:11,840 --> 00:37:14,520 Speaker 1: my favorite thing is is hanging out with them, visiting 710 00:37:14,560 --> 00:37:16,680 Speaker 1: them and helping them. That's that's my passion. Are you 711 00:37:16,719 --> 00:37:21,359 Speaker 1: familiar with Dave Branfred? Oh? Yeah, Dave's out there by you, right. Yeah. 712 00:37:21,719 --> 00:37:23,319 Speaker 1: Dave called me the other day when I was on 713 00:37:23,320 --> 00:37:25,600 Speaker 1: my road trip and he saw an Instagram post and 714 00:37:25,600 --> 00:37:27,800 Speaker 1: he said, yeah, we gotta do this in San Diego. 715 00:37:27,800 --> 00:37:29,319 Speaker 1: Why are you going a little bitwhere else? So we're 716 00:37:29,360 --> 00:37:32,680 Speaker 1: gonna do something like that in San Diego. So Dave, 717 00:37:32,840 --> 00:37:36,600 Speaker 1: Dave actually uh did the IP for Cannabis Talk one 718 00:37:36,600 --> 00:37:38,520 Speaker 1: on one. So he got us to Cannabis Talk and 719 00:37:38,600 --> 00:37:40,880 Speaker 1: Cannabis Talk one on one and the and all the 720 00:37:41,200 --> 00:37:43,279 Speaker 1: fun stuff. And it took a long time because the 721 00:37:43,280 --> 00:37:45,960 Speaker 1: words cannabis and talk are so broad, you know, so 722 00:37:45,960 --> 00:37:48,040 Speaker 1: it's like you're trying to do you know, cannabis talk. 723 00:37:48,120 --> 00:37:50,640 Speaker 1: You can't own them. I'm like, yes, I can, and 724 00:37:50,640 --> 00:37:52,399 Speaker 1: and then he is, He's like, it's gonna be a fight, 725 00:37:52,440 --> 00:37:56,719 Speaker 1: and I'm like, I'm fighter. So now I you know, 726 00:37:56,800 --> 00:37:59,839 Speaker 1: we owned the rights to it, but it took some time. 727 00:38:00,040 --> 00:38:02,080 Speaker 1: A very very good friend, and I was just hoping 728 00:38:02,120 --> 00:38:03,960 Speaker 1: that I can maybe make the introduction for you too, 729 00:38:03,960 --> 00:38:07,359 Speaker 1: because you're both attorneys and San Diego boys. Yeah, and 730 00:38:07,360 --> 00:38:09,880 Speaker 1: for whatever reason, I you know, we're always surrounded by 731 00:38:09,880 --> 00:38:11,920 Speaker 1: a ton of attorneys. There's the Pop Brothers at law. 732 00:38:11,960 --> 00:38:14,920 Speaker 1: There's David Branton. I mean, there's this, there's there's so 733 00:38:14,960 --> 00:38:17,839 Speaker 1: many different attorneys that end up being an e and yeah, 734 00:38:17,840 --> 00:38:19,920 Speaker 1: there's a there's a ton of them and and um 735 00:38:20,200 --> 00:38:23,839 Speaker 1: and so we've sent seemed to for some reason, um 736 00:38:24,280 --> 00:38:26,760 Speaker 1: end up working really well with you guys. That's Jeff Hamilton, 737 00:38:26,800 --> 00:38:29,320 Speaker 1: guy who's just come up with great things with another 738 00:38:29,320 --> 00:38:31,800 Speaker 1: great lawyer at open Jeff has been on the show 739 00:38:31,800 --> 00:38:35,200 Speaker 1: many times, apparently thousand times. She's the first one I 740 00:38:35,280 --> 00:38:38,040 Speaker 1: aspired to be on the show many times. Yeah, clearly 741 00:38:38,880 --> 00:38:40,640 Speaker 1: I'm gonna come to Oakland just to hang out with 742 00:38:40,680 --> 00:38:45,680 Speaker 1: you on Grape Street, just to go kick. How long 743 00:38:45,719 --> 00:38:51,839 Speaker 1: have you been there in northern California your whole life? Really? Uh? Yeah, 744 00:38:52,040 --> 00:38:57,319 Speaker 1: I lived two miles. I went to Yale. Oh well, 745 00:38:57,400 --> 00:38:59,200 Speaker 1: Joe used to have a show out there. I'm born 746 00:38:59,320 --> 00:39:01,040 Speaker 1: rights to San Jose so and I used to work 747 00:39:01,040 --> 00:39:03,680 Speaker 1: at Hot Night seven seven and the Wild and then 748 00:39:03,760 --> 00:39:05,520 Speaker 1: one of seven seven that show called the Doghouse from 749 00:39:05,640 --> 00:39:08,160 Speaker 1: show called the Doghouse. I'm Big Joe for the Doghouse, 750 00:39:08,680 --> 00:39:10,640 Speaker 1: Elvis and JV and Big jar I probably went to 751 00:39:10,640 --> 00:39:12,399 Speaker 1: your school when you're a kid and fucking passed out 752 00:39:12,400 --> 00:39:14,759 Speaker 1: stickers to you or something. But yeah, I hold you 753 00:39:16,360 --> 00:39:18,600 Speaker 1: definitely what isn't at your school because you're younger than me? 754 00:39:19,560 --> 00:39:22,839 Speaker 1: But yeah, fifty But yeah, so back and I left 755 00:39:22,920 --> 00:39:27,600 Speaker 1: the Bay Area in or something I got. I got 756 00:39:27,719 --> 00:39:30,960 Speaker 1: drafted by you. You've got a personal invite to come back. 757 00:39:31,640 --> 00:39:33,839 Speaker 1: Thank you, brother. I should go there sometimes. Anything else 758 00:39:33,840 --> 00:39:36,240 Speaker 1: we're missing that we're not talking about Ethical Data Alliance 759 00:39:36,239 --> 00:39:39,920 Speaker 1: once again, Ethical Data Alliance dot Net go there, And 760 00:39:39,920 --> 00:39:42,520 Speaker 1: it's so key because everything that these guys are saying 761 00:39:42,520 --> 00:39:48,920 Speaker 1: in GAL is user driven, meaning Ethical Data dot Net 762 00:39:49,080 --> 00:39:52,759 Speaker 1: is only gonna be as successful as as many users 763 00:39:52,880 --> 00:39:55,800 Speaker 1: use it, because then we can gather that data in 764 00:39:55,880 --> 00:39:59,040 Speaker 1: my right guys and utilize this to benefit everyone as 765 00:39:59,040 --> 00:40:01,640 Speaker 1: a society. Yeah. And the other thing people can do 766 00:40:01,719 --> 00:40:04,000 Speaker 1: is they can go to the website and they can donate. 767 00:40:04,080 --> 00:40:07,399 Speaker 1: Because this is a nonprofit, we're all donating our time 768 00:40:07,400 --> 00:40:09,480 Speaker 1: and we have been for a long time. We've got 769 00:40:09,640 --> 00:40:13,200 Speaker 1: people deeply committed to this. But um, we only have 770 00:40:13,280 --> 00:40:15,359 Speaker 1: one person who's getting any pay from this. He's our 771 00:40:15,400 --> 00:40:18,560 Speaker 1: executive director. He throws so much passion and energy into it. 772 00:40:18,960 --> 00:40:21,440 Speaker 1: But we could really use some donations. We're also raising 773 00:40:21,480 --> 00:40:24,960 Speaker 1: some attempting to get some grants and things. But um, 774 00:40:25,160 --> 00:40:27,239 Speaker 1: in addition all the time that that a lot of 775 00:40:27,440 --> 00:40:30,440 Speaker 1: people really donate to this, we would love to get 776 00:40:30,480 --> 00:40:32,400 Speaker 1: some cash in the door to sure. Yeah, just a 777 00:40:32,960 --> 00:40:35,440 Speaker 1: small contributions go really a long way. We only have 778 00:40:35,520 --> 00:40:38,560 Speaker 1: one person that's full time staff and everyone else is 779 00:40:38,560 --> 00:40:42,080 Speaker 1: a volunteer. And it's really your money goes into the development, 780 00:40:42,120 --> 00:40:44,759 Speaker 1: it goes into one person to just ran the ship, 781 00:40:44,880 --> 00:40:48,840 Speaker 1: and it's it's it's very leanly staffed and efficiently operated. 782 00:40:49,200 --> 00:40:52,040 Speaker 1: I'd like to to to get involved more with you guys. Um, 783 00:40:52,160 --> 00:40:54,800 Speaker 1: so you know, for for us, we could definitely donate 784 00:40:54,840 --> 00:40:57,279 Speaker 1: time money, energy, all those things. And I think that 785 00:40:57,920 --> 00:41:00,279 Speaker 1: it's important that we do um is. So it's two 786 00:41:00,360 --> 00:41:02,239 Speaker 1: little things. So if you're listening down at home, and 787 00:41:02,520 --> 00:41:04,480 Speaker 1: you know, reach out where where can they actually go 788 00:41:04,560 --> 00:41:09,680 Speaker 1: donate again Ethical Data dot net And there's a button. Yeah, 789 00:41:10,000 --> 00:41:11,800 Speaker 1: and and and make sure you hit that button because 790 00:41:11,880 --> 00:41:13,719 Speaker 1: it's it's super important, like I said, if you care 791 00:41:13,719 --> 00:41:15,719 Speaker 1: about this plan or if you've been affected by it 792 00:41:15,760 --> 00:41:18,799 Speaker 1: in any way to the community, because you contribute, give back. 793 00:41:18,840 --> 00:41:20,680 Speaker 1: And like you said, even if it's a small or 794 00:41:20,800 --> 00:41:24,239 Speaker 1: large contribution, it's just something that you or you know 795 00:41:24,320 --> 00:41:26,719 Speaker 1: you can and and probably should do. So thank you 796 00:41:26,719 --> 00:41:28,960 Speaker 1: guys so much for joining us. Appreciate you guys being 797 00:41:29,000 --> 00:41:30,920 Speaker 1: here man and make should you guys go check that out. 798 00:41:30,960 --> 00:41:33,600 Speaker 1: Remember this everybody out there. If nobody else loves you, 799 00:41:33,760 --> 00:41:36,520 Speaker 1: we do. Thank you for listening to Cannabis Talk one 800 00:41:36,520 --> 00:41:39,320 Speaker 1: oh one on the I Heart Radio app, Apple Podcasts 801 00:41:39,560 --> 00:41:41,359 Speaker 1: or wherever you get your podcasts.