WEBVTT 1 00:00:00.000 --> 00:00:20.000 Good morning, everyone. Welcome back to the Dry side Dispatch, brought to you by HSI Water. And we've got a little bit different show this morning as our guest this morning was spent the week last week with the NASA on the the Space for Ag NASA tour. And so our guest this morning is Tillery Sims, the creator of the podcast. 2 00:00:20.000 --> 00:00:21.000 The creator of the podcast. 3 00:00:21.000 --> 00:00:23.000 The reason we're all here. 4 00:00:23.000 --> 00:00:24.000 That's right. 5 00:00:24.000 --> 00:00:42.000 But Tillery with the. The space frag tours came in. It's all the, you know, pretty high up people up in NASA that came in and they haven't looked at, at agriculture out here on the high plains. They also, I know they were in Oklahoma and various other places as well. 6 00:00:42.000 --> 00:00:43.000 Yeah. 7 00:00:42.000 --> 00:01:00.000 But you know, they were basically, they come out here to look at stuff in real life, but they are also touting some of the new stuff, new technology that they've got, which if you're in agriculture, interested in agriculture, interested in weather, interested in, you know, existing period, they've got stuff for you. 8 00:01:00.000 --> 00:01:01.000 Yes. 9 00:01:00.000 --> 00:01:06.000 And yes. So start us off on this thing. Let's go down the road and see what they. 10 00:01:06.000 --> 00:02:07.000 Okay, so NASA, NASA Acres is the ag, a strategic ag collaboration with farmers. And so NASA launched a satellite many years ago, recognized that they were catching all this plant data, and they said this is surely good for agriculture. So they created a project called Harvest, NASA Harvest. And it was a global look at agriculture. And it was so successful, they said, okay, now let's, let's do the same thing, but let's do a really deep dive and see what we can provide for US Agriculture. So the. They did a grant. This was a grant program. And the person that won the grant was the co director of Harvest. So she and her crew are out of the University of Maryland. So that's why there were a lot of people there from the University of Maryland. So that group are the NASA Acres group. 11 00:02:07.000 --> 00:02:08.000 Okay. 12 00:02:08.000 --> 00:03:28.000 So Karen St. Germain is the director of the Division of Earth Science. So she has a $21 billion budget. And what she does, everything that looks down on the Earth, that looks down on the Earth, it's under her responsibility. And so she, she came up with this, this idea because she said several years ago, obviously we, what we can do for agriculture is more than we ever anticipated, but I know nothing about it. And so I need to go learn. And so they're really listening Tours is what they're called. And so they've done Ours was this one in Texas was the fourth, I think so. But this was the first time that they'd Ever had one that was very strategically planned. So I knew that they had done these. And so when we went, we first, the first time that we collaborated with them was at Commodity Classic, not this year, but last year. And that's where I met Karen and just said, please, please, please come to Texas. Please come to Texas. We'll, we'll get it all done. We'll make it. It'll be great. You can't imagine how wonderful it'd be. And it's all this cotton and everything. And so she agreed. And then we horse missed because we had the shutdown. 13 00:03:28.000 --> 00:03:29.000 Yep. 14 00:03:29.000 --> 00:04:10.000 So we didn't get good. It was going to be in October of last year, which would have been much better time because we actually had cotton. They could have seen ye and it wouldn't have been 105 degrees before the drought yet. Yeah. So but you know, it was, I would say wildly successful anyway, regardless, so they, she brought her a couple other folks with her. The guy that is the head of the Goddard State Space center was there and Tom, he's such a nice guy. I mean all these people are just like so normal. They're just people that you would just see at Walmart. 15 00:04:10.000 --> 00:04:13.000 You know the Goddard Space. Is that in New Mexico? 16 00:04:13.000 --> 00:04:15.000 Goddard is in Maryland. 17 00:04:15.000 --> 00:04:16.000 In Maryland. Okay. 18 00:04:16.000 --> 00:04:23.000 There is, there's a Haskell Goddard. Haskell in Roswell. I don't know if he was from there or if it's because of White Sands where they launched missiles. 19 00:04:23.000 --> 00:04:24.000 I don't know. I don't know why. 20 00:04:24.000 --> 00:04:25.000 That's why I was asking. 21 00:04:25.000 --> 00:04:52.000 Well, this, when, when Connor Watts and I were up, up there last month. In August. July. In July we got to tour Goddard and we got to see the last. The shuttle that they just launched this last week or a week before was like Sunday after the tour. The Roman. It's called Roman. It has a new name. It's named after really brilliant woman scientist at NASA. First in leadership there. 22 00:04:52.000 --> 00:04:56.000 It wasn't a shuttle, it was a rocket. Right. 23 00:04:56.000 --> 00:04:57.000 It's a, it's a satellite because they. 24 00:04:57.000 --> 00:04:58.000 Okay, it's a satellite. 25 00:04:58.000 --> 00:04:59.000 Yeah, sorry. 26 00:04:59.000 --> 00:05:00.000 Okay. 27 00:04:59.000 --> 00:05:08.000 So anyway, they, I got to see where that was built. So they have this big clean room, three story clean room. 28 00:05:08.000 --> 00:05:09.000 Yeah, yeah. 29 00:05:08.000 --> 00:05:44.000 And then it has like this. I don't even know it. It looks like a massive silver cauldron with a lid. I don't know how else to describe it. But they put it down in there. It's the size of a bus. So they put these satellites down in that thing and they screw it closed and then they Simulate all of the environment of the space to see how they're going to handle up to everything. So it's really amazing. That was crazy. So we learned a lot during that time. Just about like what the satellites, different satellites do and how many we have. And there's a lot. 30 00:05:44.000 --> 00:05:45.000 Yeah. 31 00:05:45.000 --> 00:05:50.000 I keep thinking the more we keep launching, like when are they going to start hitting each other? 32 00:05:50.000 --> 00:06:08.000 So they, they literally have that. I mean, that's, they identify like I think they said, oh, man, I can't remember if it's 59 new like obstacles in space every week. And so they're including. 33 00:06:08.000 --> 00:06:10.000 That includes satellites or just talking about debris. 34 00:06:10.000 --> 00:06:12.000 That includes satellites. Mostly satellites. 35 00:06:12.000 --> 00:06:16.000 Well, it didn't. One SpaceX thing launched like on 100 36 00:06:16.000 --> 00:06:19.000 a time SpaceX low earth orbit. 37 00:06:19.000 --> 00:06:32.000 So they all, they're all, they all have their own orbit. So mostly they won't, mostly they won't collide because there's literally someone there that is like getting notifications about collisions. I mean, they're just, they're constantly like Frogger. 38 00:06:32.000 --> 00:06:33.000 Yeah. 39 00:06:33.000 --> 00:06:51.000 It's crazy. So we got to see all of like everywhere where they're set up for each one ever. It's crazy. There's a lot of, there's a lot of trash up there. I mean, there's a lot of old decommissioned things. And I mean, and it's, it's, I mean, because it's everybody in the world, it's all the countries, 40 00:06:51.000 --> 00:06:52.000 rockets launching them. 41 00:06:52.000 --> 00:07:05.000 Yes, exactly. So I mean it's a. But everything is also based off of like calibrated and everything is based off of NASA, so everything except for China. 42 00:07:05.000 --> 00:07:07.000 They don't want anybody. But they know where they are. 43 00:07:07.000 --> 00:07:32.000 But, oh, China knows. And, and China knows. I mean, their satellite, I would say that like their AG satellite is, is definitely can surpass ours at this point. And, and if we cut our budget with theirs, which they're wanting to do by over half, then they'll be kicking our asses in a. Pardon me, donkey. I meant that as a donkey. They'll be kicking our rears by. 44 00:07:32.000 --> 00:07:33.000 Yeah. 45 00:07:33.000 --> 00:07:40.000 You know what I mean? Because the stuff that they can see, you know, just to be able to say we can see soil moisture levels, 46 00:07:40.000 --> 00:08:02.000 you know, that's the thing about it is that when you look at, you know, like the, over the last couple of weeks, all the crop forecasts are coming out and you're starting to see movement in the grain market. Corn is up and they're expecting it to keep going up. Cotton's from the time that we first talked to Todd Bomb and cotton's up about 20 something. 47 00:08:02.000 --> 00:08:03.000 Was it 90? 48 00:08:03.000 --> 00:08:08.000 It was 90 something cents. This earlier this week 49 00:08:08.000 --> 00:08:16.000 they finally came down and looked west Texas crop and saw that there was basically not. It might be half a million bells instead of 3 million like I've seen. 50 00:08:16.000 --> 00:08:27.000 I mean. Yeah, it's. I'm not even sure it'll be that high. I talked to a guy this, this week that had gone out and done bowl counts and it, you know how you're supposed to do it? 51 00:08:27.000 --> 00:08:28.000 Yeah. 52 00:08:27.000 --> 00:08:30.000 13 foot bowls and it came up to £7. 53 00:08:30.000 --> 00:08:44.000 Yeah, I figured a bunch of it, I think. Who was it? I was talking to a grower. Like maybe you can't. They can't start adjusting it until like September 30th or something like that. There's some date. They can't start adjusting it. 54 00:08:44.000 --> 00:08:45.000 Yeah. 55 00:08:44.000 --> 00:08:47.000 Or it has to be so many days after planning. I don't know. There was some reason. 56 00:08:47.000 --> 00:08:48.000 Yeah. 57 00:08:48.000 --> 00:08:54.000 I went to Midland a couple weeks ago and saw one field being plowed up and that's the first one I've seen. But I expect to see a whole lot more of that. 58 00:08:54.000 --> 00:09:01.000 But anyway. But I was going on that though, with, with all this, the stuff that, that, that NASA Acres can't. What they can already do with it. 59 00:09:01.000 --> 00:09:02.000 Right. 60 00:09:02.000 --> 00:09:20.000 You know, it's, it's interesting that we don't know what every, I mean somebody somewhere in the government has to know, but the fact that that does not trickle down to the US USDA and have an actual solid number of. Hey, you know what? China's crop is X. You know, the water in Brazil is. 61 00:09:20.000 --> 00:09:27.000 Well, and I'll tell you why. Here's here, here's why China is 62 00:09:27.000 --> 00:09:28.000 more. 63 00:09:28.000 --> 00:09:49.000 They, I think that they can gather better data than we can. And it is because it. Everything that they see from remote sensing, they have to confirm that, that they are seeing what they're seeing. So which means that was calibrated really well then. Yeah. So it has to be ground truthed. 64 00:09:49.000 --> 00:09:50.000 Right. 65 00:09:49.000 --> 00:10:14.000 Right. Okay. So if you're in China, like you don't go ask for data, you just go get it. You just go get it belongs to the government. Right. So but if they're saying I think that we're seeing protein, this certain protein in corn. Well, in order for them to actually know for sure that they were, they had to work with the corn growers and corn growers had to like say, here's the protein count on this field and this field and this field. 66 00:10:14.000 --> 00:10:15.000 Yeah. 67 00:10:15.000 --> 00:10:21.000 You know, and so they have to have that. And so until they have that amount of collaboration. We won't ever have that kind of. 68 00:10:21.000 --> 00:10:56.000 Well, I mean, I think that you could get on a. Depending on how broadly you wanted that data, you could, it could be done. But mind, there's reason China would. China. Well, China knows what our crop is like before they come, before the USDA says anything. You know, they don't. Because, you know, the one thing that China. There's one thing. There's two things that they do. They, you know, do things cheap and they do whatever the heck they want. And so, you know, while we have, you know, we'll be bound by. By treaties and, you know, agreements and 69 00:10:56.000 --> 00:10:57.000 stuff like that Bill of Rights. 70 00:10:57.000 --> 00:11:01.000 The bill. Yeah, things like the bill. You know, things like. 71 00:11:01.000 --> 00:11:02.000 Yeah. 72 00:11:01.000 --> 00:11:17.000 You know, they don't like, they don't like it. It's just that they just throw you in jail. Just ask the Uyghurs. But I mean, you know, when you go into that and you have the ability. When you have the ability to do something which we have the ability to do a lot of things that we don't do. 73 00:11:17.000 --> 00:11:18.000 Yes. 74 00:11:18.000 --> 00:11:32.000 Well, on a, on an elementary scale, it would be like, you know, they have all these precipitation, estimated precipitation maps that they put out. And so you, you may see the app and it says, oh, you got one inch of rain and then you go look at your rain gauge and you got a tenth. 75 00:11:32.000 --> 00:11:33.000 Yeah. 76 00:11:32.000 --> 00:11:49.000 Like that's the kind of calibration on a very rudimentary scale that they're trying to do with saying, like, okay, we're looking at infrared discolored. You know, wave is like this, we think. And so we're gonna. And then they go check it and say, okay, well that correlates to 10 protein, weed or whatever. 77 00:11:49.000 --> 00:11:56.000 They also correlate like they also track the movement of the core of the earth because it's all. It's shifting. 78 00:11:56.000 --> 00:11:57.000 Oh yeah. 79 00:11:57.000 --> 00:12:01.000 And so if they don't. That's how they keep GPS is accurate. 80 00:12:01.000 --> 00:12:02.000 Yeah. 81 00:12:02.000 --> 00:12:04.000 Is by tracking that movement. 82 00:12:04.000 --> 00:12:24.000 Yeah. You know, they would forever wouldn't let us get. They wouldn't let us get GPS within like 6 or 8 inches or a foot maybe. I don't remember what it was because they. They in the U. S. Intentionally put, you know, an anti correction or correction device and it would. It scrambled it a little bit. But now they've got it down to. 83 00:12:24.000 --> 00:12:28.000 I think that obviously US Military using different stuff now. 84 00:12:28.000 --> 00:12:29.000 Ah. 85 00:12:29.000 --> 00:12:40.000 I think that their technology passed it far enough that now they're like, okay, you can use this because we're not using that anymore. I Mean, yeah, you know, you see some of the stuff they got, but, I mean, it's. 86 00:12:40.000 --> 00:12:42.000 Well, there's a lot of different. 87 00:12:42.000 --> 00:12:51.000 So what, you know, we've talked a little bit and kind of hit a little bit on what they can do. What can NASA already provide to it. 88 00:12:51.000 --> 00:13:48.000 So what now, what we're looking on. Maybe best to start with, like, what we're looking at doing right now. So the goal was for us to have projects to identify needs with growers here that we could. We could meet. And so what we did was we started out on Sunday night with about 30, 25 or 30 people in the room. And we were supposed to end at like 8, and it was like 10:30 before we left. You know, I mean, like, it was a really good meeting. People really talked about needs and that kind of stuff. And then we did that. We spent then. So that was Sunday. Then we did Monday night, we did Monday. And then Tuesday and Tuesday night we repeated that same conversation because then they had really seen on ground. And that was the thing that. That most of them said was they did not realize how bad it was here. 89 00:13:48.000 --> 00:13:52.000 Yeah, yeah. About the forest water situation. Yes. 90 00:13:52.000 --> 00:13:59.000 Yeah. They're like, no, we had. No, we didn't realize. I mean, we knew. You know, you hear people say it, but you didn't. They didn't realize it until they got here. 91 00:13:59.000 --> 00:14:18.000 It's kind of like if you, you know, we live in it, and so we see little, tiny incremental changes, you know, but we don't see that because they're tiny incremental changes. But now we know it's dry. But, you know, when somebody that hasn't been here for 20 years and you go back and it's terrible there, you're like, well, it's not that bad. 92 00:14:18.000 --> 00:14:27.000 Yeah. But, you know, we were standing and we went to see Barry Evans, and he has a grain sorghum field that's just. I mean, it's just crisp. Yeah, it's like. It's crisp. It's like. 93 00:14:27.000 --> 00:14:28.000 Yeah. 94 00:14:28.000 --> 00:14:52.000 Cooked. Yeah. It's crazy. So what. What came out of that, though, was a conversation about planting dates and how, you know, if you could move the planting date further out, then. So some farmers are planting as late as possible and having some success where they're not dropping the fruit because they're 95 00:14:52.000 --> 00:14:53.000 missing the highest part of the heat. 96 00:14:53.000 --> 00:15:34.000 Right? Yes. And so they're looking at a couple of things. So one is, can you. Can you look at. And help me predict how far I could go? Like, what is our. Like, look at our Freeze. What is the potential? Go as far back as possible and on a specific site to help a farmer say okay, my, the chances of me having a freeze are this percent. And do I. Is that low enough for me to go ahead and plant later than I would normally plant? So. And I, which I think is actually a good idea because you're. I mean it's just staying warmer. 97 00:15:34.000 --> 00:15:48.000 Yeah. I mean, I mean weather has just as a whole, in my opinion has just got to get better. Like they can't even. You can't trust anything really. 24 hours out is about maybe 48. 98 00:15:48.000 --> 00:15:59.000 That's the, that's the other thing. If we cut. So you gotta remember like this year we're seeing all this weird. Like you can't. It's not predictable. How many NOAH stations were closed this year? Well, but they're just not staffed anymore. 99 00:15:59.000 --> 00:16:16.000 But there's, but there's a, there's a, there is a plethora of meteorologists that are looking at NOAA data that is still being collected. Well, and there are people that, that are, that have, they're well educated that are doing this. 100 00:16:16.000 --> 00:16:39.000 Well, I think if there's demand the private sector would take. I mean, you know what you talk about. Who knows what the crop is like, you know who else knows the crop is the people, the commodities traders. They probably have room on some satellite that they least. That has whatever camera and they have proprietary data that they get off that big tour that they do up in the Midwest. You know where they go look at all the corn and stuff and give an estimate on. 101 00:16:39.000 --> 00:16:42.000 I think it's the proactor and that. 102 00:16:42.000 --> 00:16:58.000 And so that gives them. Then they can go back and look at historical data through multiple crop insurance and say, well, hey, this county, we estimated it was going to be this but we're off by. I guarantee you those the people buying the commodities know more about the crop than the usda. 103 00:16:58.000 --> 00:17:08.000 I mean every. Yeah, yeah. And there is, there's a conversation ongoing right now on helping NAS with some of that. 104 00:17:08.000 --> 00:17:14.000 They're bad. You know, I mean farmers are pissed too because it affects the price of corn. Like last year, I mean they was bad. 105 00:17:14.000 --> 00:17:16.000 I mean like they killed the price of corn last year. 106 00:17:16.000 --> 00:17:17.000 Yeah. 107 00:17:17.000 --> 00:17:18.000 On faulty data, on fault. 108 00:17:18.000 --> 00:17:29.000 Yeah. It's just like it's looks like when unemployment numbers come out, you know, like today or the employment number was like a big number. Well, next month it's going to be revised down like when they really know what it was. 109 00:17:29.000 --> 00:17:39.000 Right. Yeah, yeah. I mean it's a, It's A comp. That is a complicated issue because part of it is, you know, they're getting their numbers from that survey. 110 00:17:39.000 --> 00:17:40.000 Yeah. 111 00:17:40.000 --> 00:17:44.000 Yeah. And I don't know anybody that survey has anything. 112 00:17:44.000 --> 00:17:57.000 Part of it last year was they like, changed the acres at the last, like, they revised the acres so they had 100, whatever, 134 bushel of average or whatever. Well, sudden they found like 2 or 3 million more acres. 113 00:17:57.000 --> 00:17:58.000 Yeah. 114 00:17:58.000 --> 00:18:00.000 Or 90 million more bushels, which is 115 00:18:00.000 --> 00:18:04.000 very odd when people have to turn in acreage reports. 116 00:18:04.000 --> 00:18:06.000 Well, a lot of that too is, you know. Yeah. I mean, unless. 117 00:18:06.000 --> 00:18:13.000 I mean, there's nobody out there that's far. Maybe there is some. But nobody's farming some row. Crop. Commodity. Crop. Commodity without having it insured. 118 00:18:13.000 --> 00:18:18.000 It does not on a scale big enough to make. Not enough. Not. 119 00:18:18.000 --> 00:18:29.000 They're. I mean, maybe hay farmers may not do it, but I mean, even they. They probably do it now because you have the. What is it? The drought policies and stuff or rainfall. The policies that you can get piggybacked on. 120 00:18:29.000 --> 00:18:30.000 Yeah. 121 00:18:29.000 --> 00:18:31.000 The forged. The forest thing. 122 00:18:31.000 --> 00:18:32.000 Yeah. 123 00:18:32.000 --> 00:18:48.000 Well, I don't know. I know that the satellites that. That the ones that they have prepared for in the future like that, there will be three that'll be launched specifically for agriculture, which would mean that we would collect data every three days. So the budget would cut it to one. 124 00:18:48.000 --> 00:18:56.000 Like the universe, the whole United States data every three days. Not. So like your place is getting checked every three. 125 00:18:56.000 --> 00:18:57.000 Every three days. 126 00:18:57.000 --> 00:18:58.000 Yeah. 127 00:18:57.000 --> 00:19:04.000 Yeah. So I mean, if you're doing every three days, you could start estimating like when you would want to harvest silage. 128 00:19:04.000 --> 00:19:05.000 Yeah. 129 00:19:05.000 --> 00:19:10.000 Through remote sensing. You can do that right now because it's too, too far apart, too many days apart, you know. 130 00:19:10.000 --> 00:19:11.000 Yeah. 131 00:19:11.000 --> 00:19:23.000 But. But if, if we, if the budget gets cut, which I. I don't know. I'm not sure that it will happen because it didn't happen last year because it just. There were a lot of people that were like, we just can't do this. 132 00:19:23.000 --> 00:19:36.000 I don't think they're going. I don't think that nobody's going to cut anything. I think that's going to be a Democrat windfall in the. In the fall and. Or even they're going to win the House or one of them. They're going to win one of them and then they ain't going to be nothing done for two years. 133 00:19:36.000 --> 00:19:37.000 Yeah. 134 00:19:37.000 --> 00:19:39.000 Which honestly is probably the best thing. 135 00:19:39.000 --> 00:19:42.000 We can all cross our fingers and hope they get nothing done. 136 00:19:42.000 --> 00:20:09.000 All I can say is that, well, I hope they do nothing for more than two years. I mean, if they didn't. But I mean, it's frustrating because you've got, you know, you've got projects like this that you can see a benefit to. I mean, okay, they've got. This is the thing that has always just amazed me from the time, the first time you told me about it, and it's probably been a couple months that they can from space tell you what your soil moisture content is. 137 00:20:09.000 --> 00:20:10.000 Right. 138 00:20:09.000 --> 00:20:12.000 And tell you what your planting moisture looks like. 139 00:20:12.000 --> 00:20:13.000 Yeah. 140 00:20:13.000 --> 00:20:14.000 Everywhere. 141 00:20:13.000 --> 00:20:24.000 Well, and if you think about like, even. Well, now you've got better. Like those in drip soil probes are better. But most soil probes for drip, they're not going to catch that top four inches or so. 142 00:20:24.000 --> 00:20:25.000 Well, I think. 143 00:20:25.000 --> 00:20:28.000 And so if you get. You combine that with remote sensing, you 144 00:20:28.000 --> 00:21:08.000 know, I've played with. We've got. I don't. I don't know how many different types of soil moisture probes me and Andy have dealt, have dealt with, looked into, experimented with, looked at the data from. And I mean, you know, out here. So moisture probe is just basically tells you, hey, don't turn your water off, you know. Yeah, let's drop $10,000 for set to have a piece of data that tells us, an instrument that tells us, hey, it's hot, dry, don't water, don't stop watering, or, hey, look, you got three inches of rain. We don't, you know, so it's. Those information for us is less critical. I mean, from, from where we're standing on. Because irrigation decisions are based upon. Hey, the sun's up. It's. 145 00:21:08.000 --> 00:21:15.000 Well, I could see, I could see where it could work on like, let's say somebody does have fairly adequate drip irrigation on coffee. 146 00:21:15.000 --> 00:21:16.000 Yes. Yeah. 147 00:21:15.000 --> 00:21:45.000 And they're doing, you know, a set. Maybe it takes them two days to get across it or mo. You know, and then. Okay, well then maybe as it gets hotter, it needs to be like, everybody always starts their pivots out on like 10%. Right. It takes a week to make a circle, and then it starts burning up ahead of the water. You're like, okay, I'm gonna turn it up to 12 and a half. And then, and then you look at it and you're like 30%. We're trying to make a circle every day, and you're not ever getting ahead. But maybe there's some way they could do the interval of the water. Well, but as it gets into drought 148 00:21:45.000 --> 00:21:54.000 situation, what I was getting, getting to that was there are places that it does matter, you know, that those that those moisture probes work. You know, they were designed for something. 149 00:21:54.000 --> 00:22:05.000 Well, and the ones that indrip has, they have a. A horizontal tape that the plants grow into. So they're not just taking up moisture, they're taking up a lot more damage. 150 00:22:05.000 --> 00:22:09.000 I want to move somewhere where they have so much water, they have to put tile down to get rid of it. 151 00:22:09.000 --> 00:22:10.000 Can you imagine? Right. 152 00:22:09.000 --> 00:22:11.000 That's what. That's what I wanted. That's where I want. 153 00:22:11.000 --> 00:22:17.000 I read somewhere the other day that infrastructure is like 100 years old. 154 00:22:17.000 --> 00:22:18.000 That's not. I'm telling you right now. 155 00:22:18.000 --> 00:22:23.000 Well, there's stuff that's not. I mean, all that land evidently was a swamp. 156 00:22:23.000 --> 00:22:24.000 Yeah. 157 00:22:23.000 --> 00:22:32.000 That they're doing that tile. I mean, like, they totally changed. But that's where people first settled, I guess, after the colonies was up in that area. 158 00:22:32.000 --> 00:22:54.000 Well, you know, Iowa, there's a. There's a big. There's a big conundrum in our. In Iowa in that the nitrates in their water are astronomically high. I mean, it's. You know, they have. They have the highest cancer rates in the country. Um, but they also have among the highest rates of alcohol consumption, among the highest rates of smoking. 159 00:22:54.000 --> 00:23:01.000 Wisconsin, I think it beats everybody on alcohol. I think I've been doing a lot of deep dives on, like, where the wine market's going and stuff. 160 00:23:01.000 --> 00:23:02.000 Interesting. 161 00:23:01.000 --> 00:23:07.000 Wisconsin. I don't know how they get any work done up there. 162 00:23:07.000 --> 00:23:08.000 I don't know. 163 00:23:08.000 --> 00:23:09.000 Because it's. 164 00:23:08.000 --> 00:23:33.000 It's pretty up there. I've been up there. It is pretty. But one of the things. And. But the other thing that they're. They've got the highest. They got not highest nitrate levels in their water. And they're saying, you know, and they're. Obviously a lot of that is coming from. That is big corn country and they're tiling stuff and so that, you know, you get a shot of Anhydrous on, and then you get six inches of rain and it goes right through that soil profile right to their tile and right. It dumped right into. 165 00:23:33.000 --> 00:23:35.000 Yeah, they'll dump them in the creeks, right? 166 00:23:35.000 --> 00:23:37.000 Yeah, they just dump it right into the tributary. 167 00:23:37.000 --> 00:24:05.000 That's why. I mean, there's a whole dead zone down at the coast from all of that. I mean, it's a thing. But I mean, Kansas is the same way. Kansas has a. I can't remember how many million acres area that is. Their water, groundwater is contaminated by nitrogen. They had to go in and like. But I mean, they're having to haul in water. But like. Because I can't remember. They found out because of. I can't remember what type of cancer it was, but so much of it in this. 168 00:24:05.000 --> 00:24:07.000 Kansas is such an amazing state. I don't know. 169 00:24:07.000 --> 00:24:09.000 I mean, Kansas. I do. 170 00:24:09.000 --> 00:24:11.000 I do, too, because it is. It is. 171 00:24:11.000 --> 00:24:13.000 I've only been in Kansas City. I'm not a fan. 172 00:24:13.000 --> 00:24:45.000 It is like a. It is like. Well, yeah. Well, listen, if you've got a city that's more than 10,000 people, I'm more than likely not that big of a fan, but it's like a bipolar state. It is. I mean, because it's like. It's like Texas is bipolar, too. You know, you got the dry side of Texas, where we are over here, and then you got over there where it, you know, rains. And people, like. People live by the. By the droves. But in Kansas, it's. It seems like it's so compressed because you can get across it, you know, I mean, it doesn't take. You know, I can't drive all day and still be in the same state. 173 00:24:45.000 --> 00:24:46.000 Yeah. 174 00:24:45.000 --> 00:25:23.000 And so you go. You hit western Kansas. And it's really odd because it's like every time I've been. Every time I've been there, which, granted, I have not spent a bunch of time in western Kansas, but it's always seems like it's dry, but their grass will be waist deep. You know, I was. I was there last October, and obviously nothing was growing and they'd harvest this stuff. And I was asking a farmer, I said, well, how was it? He said, well, it's pretty dry this year. We didn't really, you know, get the rains we normally got. And I'm, like, looking at this at the CRP field across from it, and it's literally waist deep, at least in grass and just solid. And I'm not going. How much rain do y' all usually get? Well, you know, there's a beast, and it's gorgeous. 175 00:25:23.000 --> 00:25:26.000 There's a line of latitude that. 176 00:25:26.000 --> 00:25:27.000 Yes. 177 00:25:26.000 --> 00:25:42.000 You can see it on a map, that. Of where it rains and where it. It starts. The demarcation where it doesn't rain as much. And it's like, it's getting really close to the Mississippi River. Like, it keeps moving east. You can see the. The. You know, over the last 30 years, 178 00:25:42.000 --> 00:25:44.000 that's why the tornado alleys moved. 179 00:25:44.000 --> 00:26:10.000 It's moved. Yeah. It's moved east and north. Yeah. I mean, like, way up into past Missouri, up into Iowa. I see these guys that, you know, are like, this is the first hell I ever got, you know, where you at? I'm in southern Indiana or whatever. And it held my. I'm like, we didn't even get rain to even have hail anymore. Hardly. I mean, but when it comes here, you know, it's like the size of the hell here is getting bigger too. Like when it hills it, it's bigger than it used to be too. 180 00:26:10.000 --> 00:26:23.000 Well, and I know when I was in Poland, we were in a city that had flooded like the night before and it held the first time in 100 years there was literally no one there who had ever seen hell before. Now think about how freaky that would be. 181 00:26:23.000 --> 00:26:26.000 Like, it'd be like snow in Miami or something. 182 00:26:26.000 --> 00:26:36.000 Yes. It's just like what? No one had ever even seen it in anyone's lifetime. Had anyone ever seen it. Yeah, you know, I mean that, that's, that's pretty nerve wracking. 183 00:26:36.000 --> 00:26:38.000 Circle back around the NASA a little bit. 184 00:26:38.000 --> 00:26:51.000 So. Yeah. So back to the. So the planning dates. They did this. They did a project with NASA corn growers in Kansas did. And they got the, they got the planning dates moved. 185 00:26:51.000 --> 00:27:03.000 That would, that would be big. That, that would be, that would be a, that would be a, that would be a move that like 99% of the population would not even kind of understand but could potentially be really big. 186 00:27:03.000 --> 00:27:59.000 Oh, I think it'd be super helpful. But I, that's that and you know, because they, they're like, we know exactly how to do it and what needs to be done because they're the ones that did it before. So. Which is Ignacio Campidi, who's the one that's at Purdue and he's the one that really kind of this, he and Ray Flickner in Kansas kind of created this brainchild of the idea of the farmer collaboration with the. On farm research with a researcher that's overseen by NASA. So it's kind of their idea. I've born out of their friendship, you know. So he, he led that effort in Kansas, will lead the effort here as well. And so if anybody wants to participate by that, we'll just need, we need some information from them. We need, you know, yields and dates and that kind of stuff. Planning dates, harvest dates, yields. 187 00:27:59.000 --> 00:28:01.000 Yeah, most of that stuff is, I 188 00:28:01.000 --> 00:28:07.000 mean they have, it exists, it's in the FSA database. Because you have to tell them like what. 189 00:28:07.000 --> 00:28:08.000 Right. 190 00:28:07.000 --> 00:28:09.000 What the plant date was. 191 00:28:09.000 --> 00:28:18.000 And I mean for us, like, I think that we could even just say, you know, call and, and have the FSA office, you know, put it together and we'll come and pick it up. 192 00:28:18.000 --> 00:28:47.000 I mean like, do it even easier than that. Like if you have a file that has all the data in it, just put it AI and like tell it to do it like parse it. I mean, right. Yes, there's that. I know that's huge. A huge file. But as they get compute going up and stuff like, I mean, I'm, I'm using stuff that probably has four, four or five thousand files that it can gl. It can glean from. And surely they have computers that are better than my five year old Mac. 193 00:28:47.000 --> 00:28:49.000 No. To do it on usda. 194 00:28:49.000 --> 00:28:51.000 Yeah, no, usda. 195 00:28:51.000 --> 00:28:52.000 No, they don't. 196 00:28:51.000 --> 00:28:53.000 They're ancient. They spent. 197 00:28:53.000 --> 00:28:55.000 Yeah, I'm talking about NASA. 198 00:28:55.000 --> 00:28:56.000 Oh, absolutely. 199 00:28:56.000 --> 00:29:09.000 Yeah. Because that, that, that data is uploaded to somewhere in usda. So there's a file. Yes. Even if they had to do it county by county and load every county in separately in a different Excel spreadsheet or whatever. 200 00:29:09.000 --> 00:29:10.000 Right. 201 00:29:09.000 --> 00:29:12.000 Yeah, they could still go through and I don't know. 202 00:29:12.000 --> 00:29:56.000 I don't know if they. So this is one thing that I thought was really interesting that, that someone said is like, it's been like, as I had to use the word, destructive, but like this whole, the last, you know, two years, there's just been this huge dismantling of, of a lot of what people would call like sacred cows. You know what I mean? No. No president before has ever touched this department or this for this. So everybody's kind of like on this shaky ground. But what it's also done, they said is it's really given them the freedom to start getting out of their silos and collaborating with other agencies. Instead of having to repeat what they're doing, they can go over and say, hey, we don't really want to. We don't have the capacity to do this, but you do. 203 00:29:56.000 --> 00:29:57.000 Yeah. 204 00:29:56.000 --> 00:30:07.000 And so that's, I think NASA just hasn't been very active with USDA and so, well, NASA we're seeing. 205 00:30:07.000 --> 00:30:11.000 NASA's also never really had any competition and now they do. 206 00:30:11.000 --> 00:31:01.000 Well, you know, that's funny because I asked. So the guy that was, he was the head, the administrator of NASA in the first Trump administration and he was on the tour in Kansas and he works for an aerospace. And I said, well, I don't want to say is, do you see them as a competitor? And he was like, absolutely not. They are. Everyone calibrates their tools from NASA. Like we would not have and could not have the industry that we have if we don't have NASA, it is that important, you know, and so which I Thought was really interesting because I've wondered that same thing too. Like are you competing? But I know what I can remember, it was like $26 billion a year is what that old 1970s Landsat satellite brings in in commercial use. So I mean people are building everything from this. 207 00:31:01.000 --> 00:31:22.000 You know, I think they said the other day, because SpaceX is about to start getting in the phone business. Not making a. Well, they may make a phone. I doubt it. He's on. Elon said he's never gonna make a phone, but just the service part of it. But it's a 600 billion dollar business. Just what we, what you pay for having access to cell towers and stuff like that. 208 00:31:22.000 --> 00:31:23.000 Exactly. 209 00:31:23.000 --> 00:31:31.000 They've already floated, you know, they've. Dr. Oz floated about a week ago. You know, we're in $40 trillion worth of debt. 40 trillion. 210 00:31:31.000 --> 00:31:32.000 Yeah. 211 00:31:32.000 --> 00:31:50.000 So that's why they keep looking at the 10 year and the 30 year note. I mean like it keeps going up, it's bumping up against 5%. Well that's what. But he floated the other day, he's like, you know, if people would just that feel great, would just work one more year than they plan to retire at, it would save us a trillion dollars. 212 00:31:50.000 --> 00:31:51.000 Yeah. 213 00:31:51.000 --> 00:31:55.000 So he's already, they've already floated. They're gonna raise Social Security. 214 00:31:55.000 --> 00:31:56.000 Yeah. 215 00:31:56.000 --> 00:32:07.000 The age that you can take Social Security, that, that's the only, that's the only way to say it, but it's the only way. And the, the. Let me finish real quick. The younger generation is going to be all for that. 216 00:32:07.000 --> 00:32:08.000 Yeah. 217 00:32:07.000 --> 00:32:28.000 They don't realize like we paid into that thing way more than we're ever going to get back out of it. Some people pay all their life and never get anything back because they die early. So it's a, it can be a popular thing that they do because they're gonna do that anyway. But the whole thing, it all goes back to the budget and it all goes back to our debt. 218 00:32:28.000 --> 00:32:29.000 Yes, it is. 219 00:32:29.000 --> 00:32:31.000 And that's why they're looking at cutting stuff. 220 00:32:31.000 --> 00:32:52.000 There's a really great, a conservative economist, I can't remember her name, that did a podcast and they were asking like what is one of the things that we could do? And they were like, if everyone over that made over a certain million dollars a year just didn't take their Social Security. 221 00:32:52.000 --> 00:32:53.000 Yeah. 222 00:32:53.000 --> 00:32:55.000 Now this was a podcast from a year and a half ago. 223 00:32:55.000 --> 00:32:56.000 Yeah. 224 00:32:56.000 --> 00:32:58.000 But she said that that would fix our. 225 00:32:58.000 --> 00:33:02.000 The government should give them back the money they paid in it. 226 00:33:02.000 --> 00:33:03.000 Right. 227 00:33:02.000 --> 00:33:03.000 Or just call it. 228 00:33:03.000 --> 00:33:06.000 She just Says they should just donate it is what she's saying. 229 00:33:06.000 --> 00:33:08.000 If they just said whatever, yeah, here, 230 00:33:08.000 --> 00:33:13.000 we're not going to take it. And they were like, they could start in the, it could start in the legislature. 231 00:33:13.000 --> 00:33:54.000 Well, the other thing that they could do I think they're gonna do is right now, if you make over like a hundred, don't quote me on this, $184,000. You pay Social Security tax up to that, but anything over that, you don't, you don't. So if they made that where it went all the way up to however much money you made, then that would, that would bring in quite a bit of money. Because I mean there, I mean you get, I mean you get two dinks. I mean they're working and making a hundred thousand bucks a year, 150,000 bucks a year, that's $300,000, which I read the other day that really they think a mid, the average middle class income now is somewhere above $200,000 to, you know, when you, when you put it all, it's not in love Texas, but if you. 232 00:33:54.000 --> 00:33:55.000 Yeah. 233 00:33:55.000 --> 00:33:57.000 Average it across the United States. 234 00:33:57.000 --> 00:34:06.000 I mean I've got, I've got two dinks in my family and that's, you know, they're just starting out and they're making as much as my. Almost as much as my wife and I think. 235 00:34:06.000 --> 00:34:08.000 So dinks is double income, no kids. 236 00:34:08.000 --> 00:34:09.000 Yeah. 237 00:34:09.000 --> 00:34:10.000 That's what a dink is. 238 00:34:10.000 --> 00:34:18.000 Yeah. Yeah. But it's, it's, you know, it's, it's funny. It's, you know, you look at, there's a, you know, there's a huge hate fest on boomers. 239 00:34:18.000 --> 00:34:22.000 Yeah. Which is just, that's what I'm saying. It's fair. That's the only thing that they could go to. 240 00:34:22.000 --> 00:34:24.000 That's a two way street, right. 241 00:34:24.000 --> 00:34:54.000 No, it is, but the problem is, is that, is it, that's an easy, they're both, it's an easy thing like as, as the boomers die off and that money goes to Gen X, there's. Gen X. Is this, I think the smallest generation that's left. I think, I think, I think there's less. But it may be because it's because of smaller time. Time horizons is why there's less Gen X people than there are. But they're gonna, it's, it's, that's the only way. I mean if you just look at it from. 242 00:34:54.000 --> 00:35:24.000 But it's, you know, it's funny because you see. Keep seeing headlines like Boomers now control more wealth than any other Generation like. Well, we've had massive inflation which driven the price of everything up. You know, they've also been in the workforce longer than any generation that's still working in the workforce. And so you had more time to raise to have money and to, you know, 30 years ago they might have bought a vacation cottage on, on a lake. They made about a, you know, $75,000 house on LBJ. 243 00:35:24.000 --> 00:35:25.000 You know, now this now. 244 00:35:25.000 --> 00:35:31.000 And it's now worth a million dollars. Well, they didn't sock away anything extra. They didn't. They just. 245 00:35:31.000 --> 00:35:35.000 Well, and their parents go back before that, lived through the depression. 246 00:35:35.000 --> 00:35:36.000 Yeah. 247 00:35:36.000 --> 00:35:41.000 So they were raised on parents that saw everything they had gone. 248 00:35:41.000 --> 00:35:42.000 Yes. 249 00:35:41.000 --> 00:35:48.000 And so there. That still carried over to the boomers and it's a little bit, you know, less from the Gen X because of the stock market. 250 00:35:48.000 --> 00:35:49.000 I'm starting. 251 00:35:49.000 --> 00:35:50.000 I don't know how much because we've 252 00:35:50.000 --> 00:35:53.000 managed to go from NASA and satellites to. 253 00:35:53.000 --> 00:35:55.000 Well, it started with budget cuts. Right? I mean, that's Right. 254 00:35:55.000 --> 00:36:00.000 Yeah. I mean that's, there's always a point that we, we, we never go somewhere without being. 255 00:36:00.000 --> 00:36:04.000 No, I mean that's what start. Yeah, that's what starts. The interesting stuff is when you get off the road. 256 00:36:04.000 --> 00:36:05.000 Yeah. 257 00:36:04.000 --> 00:36:09.000 You stay on the highway. It's not very interesting. You know, it's true. But you get off in the dirt. 258 00:36:09.000 --> 00:36:10.000 Speaking of getting. 259 00:36:10.000 --> 00:36:11.000 This is. 260 00:36:10.000 --> 00:36:13.000 This is completely random. So I was. 261 00:36:13.000 --> 00:36:16.000 Quail. No, it's not, not at all about quail. 262 00:36:16.000 --> 00:36:18.000 It's about Texas country reporter. 263 00:36:18.000 --> 00:36:19.000 Oh. 264 00:36:18.000 --> 00:36:21.000 So I was going on the Instagram. 265 00:36:21.000 --> 00:36:22.000 Yeah, he's up here in the high plains. 266 00:36:22.000 --> 00:36:32.000 Yeah, he's up here in the high plains. Well, the other day he was at some little diner that is on Route 66 and it's like the middle, the almost the exact middle of wherever you 267 00:36:32.000 --> 00:36:34.000 saw the traces of Texas guy. 268 00:36:34.000 --> 00:37:20.000 I think. So anyway, he was there and he said I was just sitting at the counter eating my. Eating lunch and he said I hear this guy talking with a funny accent and I start listening to him and it's a guy from England that was gonna come and it's gonna, was gonna like walk the Route 66 or travel Route 61 something like that. Anyway. And he does in I think Covid hit and so he got canceled. So he's like, well you know what, I'm just gonna do it anyway. And so he got a treadmill in his house and he started walking in on a treadmill in his house and he would research the part of Route 66 he was gonna be on and what was on it. And then he came back over here and he was visiting those things, and he just happened to run into him there. But I thought that was the wildest thing. But that had nothing to do with anything whatsoever. 269 00:37:20.000 --> 00:37:27.000 That was an unpaved county road that you. Not even dirt road that was tracking 270 00:37:27.000 --> 00:37:32.000 BLM land right there that the county commissioner hadn't had to take care of in five years. 271 00:37:32.000 --> 00:37:33.000 Land. 272 00:37:32.000 --> 00:37:35.000 But. So isn't Napa NASA coming out with an app? Don't. 273 00:37:35.000 --> 00:38:01.000 Don't they. Yes, so we released an app. That's. That is one thing that came out of the first meeting that we had in. In Commodity Classic is let's get Nap out. And so farmers that are in the fiat that are participating with the farmer innovation team, they have it right now. Basically, they've been tasked to break it. You know, here, take it. Break it. 274 00:38:01.000 --> 00:38:07.000 Yeah, I'm doing that right now with the deal at work. Like, I did this. Like, don't trust it, but, like, try to break it. Like. 275 00:38:07.000 --> 00:38:23.000 Yes. Yeah, exactly. Yeah. So they're breaking it, and also. They're also saying, here's what we need. So you. You can get it and they'll put your field maps on there and you can get all the information. All the different kinds of information that you want. 276 00:38:23.000 --> 00:38:24.000 Yeah. 277 00:38:24.000 --> 00:38:25.000 So. 278 00:38:24.000 --> 00:38:46.000 And they're. They're saying, can you get. Well, what about this? And so the more they're playing around with it, the more things they're going, hey, can we get this? And could we get this? In fact, I was talking to somebody from one of the groundwater districts this week at the groundwater summit, and they were like, I want. I want stuff like that we need on an app. Like, can we do that? Like, yeah, that's the kind of stuff that's. 279 00:38:46.000 --> 00:38:48.000 You can do anything right now. 280 00:38:48.000 --> 00:38:49.000 Yeah. 281 00:38:48.000 --> 00:38:53.000 If you have somebody that just knows how to. Which is. It's not that hard. 282 00:38:53.000 --> 00:38:54.000 It's amazing. 283 00:38:54.000 --> 00:38:56.000 It really isn't that. It really isn't that. 284 00:38:56.000 --> 00:39:02.000 You just got to be persistent and, you know, like, to get from AI what you need. 285 00:39:02.000 --> 00:39:07.000 It's. You just have to know what the information's there. All you have to ask is the right question. 286 00:39:07.000 --> 00:39:08.000 That's right. 287 00:39:08.000 --> 00:39:13.000 And the show's resident troglodot even used Chat GPT two weeks ago for the first time ever. What? 288 00:39:13.000 --> 00:39:16.000 Show 289 00:39:16.000 --> 00:39:17.000 it out. That's me. 290 00:39:17.000 --> 00:39:22.000 Oh, well, I don't even know what that word is. It sounds pretty awful, though. 291 00:39:22.000 --> 00:39:23.000 I don't either. 292 00:39:23.000 --> 00:39:27.000 It's a guy. Somebody doesn't like technology. Oh, technology. 293 00:39:27.000 --> 00:39:29.000 And again, 294 00:39:29.000 --> 00:39:32.000 I'M just not a. I'm not an again or I'm just not a user. 295 00:39:32.000 --> 00:39:36.000 Well I'll tell you what you be. You'd be if you you struggle man. 296 00:39:36.000 --> 00:39:44.000 If I do something that has to. That I have to use AI for. I've. I've gone on off ramp that I'm not sure I want to get on to. 297 00:39:44.000 --> 00:39:48.000 Well yeah, it's pretty nice honestly but 298 00:39:48.000 --> 00:39:50.000 when is that app supposed. 299 00:39:50.000 --> 00:40:00.000 When is it so it'll go. They're going to release it knock in lock around Thanksgiving sometime. Okay so it's kind of right now we know the name sitting there. I don't think it has a name. 300 00:40:00.000 --> 00:40:05.000 Okay, well check back with us around Thanksgiving. We'll as soon as we know a name. 301 00:40:05.000 --> 00:40:09.000 Well maybe we need to have a naming it contest. I don't know. It's just the NASA. 302 00:40:09.000 --> 00:40:14.000 Hey listen put a dollar in entry into it and we can see if we can. 303 00:40:14.000 --> 00:40:15.000 There you go. 304 00:40:15.000 --> 00:40:19.000 They can get right there. Just everybody in the US has to throw in a dollar and name it. 305 00:40:19.000 --> 00:40:40.000 You know what I've. I've suggested several times and if there's anybody listening that has any influence at Tech, I think this is a great idea. I have suggested. This is really off the topic so I have suggested that they at every game where they have a theme. So like they have veterans theme. 306 00:40:40.000 --> 00:40:41.000 There's a cotton game and there's a. 307 00:40:41.000 --> 00:40:42.000 There's an ag game. 308 00:40:42.000 --> 00:40:43.000 Ag game. Yeah. 309 00:40:43.000 --> 00:41:04.000 That they pick a veteran. So Veterans Day you pick a veterans non profit from Tech and then the opponent they. They pick a veterans non profit from their area and then you have a text a dollar campaign during the football game and if everyone text a single dollar it's like $62,000. 310 00:41:04.000 --> 00:41:06.000 Yeah. Yeah. 311 00:41:06.000 --> 00:41:09.000 And what would who. It would be the skin off anybody's nose. 312 00:41:09.000 --> 00:41:10.000 Yeah. 313 00:41:09.000 --> 00:41:19.000 And how many people are. I mean every student can text a single dollar and you know there'll be people that will text more than that. You can compete and think about what good PR that would be for Tech. 314 00:41:19.000 --> 00:41:20.000 Yeah. 315 00:41:20.000 --> 00:41:27.000 I mean like has anyone ever done this? Probably not. Tech would be the first people to do it. It would be an amazing pr. 316 00:41:27.000 --> 00:41:34.000 You know it didn't happen back in the olden days because they didn't have the money to tax dollars at that time. You know the olden days back in the, in the 90s in the odds. 317 00:41:34.000 --> 00:41:40.000 Well they sure do now. I mean that think about just the people that are there watching that game. They come every week. You know what I mean? 318 00:41:40.000 --> 00:41:41.000 Yeah. 319 00:41:41.000 --> 00:41:51.000 And think about how influential it was when. When Utah came and all the students, like these people just. They gave money to all of our non profits. They spent time. 320 00:41:51.000 --> 00:41:52.000 Right. 321 00:41:51.000 --> 00:41:53.000 The food bank. And they did all these different. 322 00:41:53.000 --> 00:41:58.000 Yeah, that's very different. That's byu, not Utah, you know. 323 00:41:58.000 --> 00:42:01.000 Yeah, yeah. Brigham Young. Yeah, yeah. But they're from Utah. 324 00:42:01.000 --> 00:42:02.000 Yes, they are. They are. 325 00:42:02.000 --> 00:42:04.000 But they're not the only thing. They don't. Yeah. 326 00:42:04.000 --> 00:42:08.000 They don't like each other. And BYU is the one that gave. 327 00:42:08.000 --> 00:42:10.000 Yes, but I mean, it made national news. 328 00:42:10.000 --> 00:42:17.000 Yeah, Well, I think that we did something like. We did something like that and they kind of returned the favor or something. I can't, you know. 329 00:42:17.000 --> 00:42:20.000 No, there was somebody here that was sick. 330 00:42:20.000 --> 00:42:21.000 Well, it was the barber. 331 00:42:21.000 --> 00:42:22.000 Yeah, I think they. 332 00:42:22.000 --> 00:42:26.000 Right. It was the barber's wife that had something happened. Yes, they do that Barber. 333 00:42:26.000 --> 00:42:28.000 I think they do. Everywhere they go. 334 00:42:28.000 --> 00:42:29.000 Yeah, yeah, yeah. 335 00:42:29.000 --> 00:42:30.000 Everywhere they go. 336 00:42:30.000 --> 00:42:32.000 I think they call it love bombing. 337 00:42:32.000 --> 00:42:34.000 Dusty's been. Dusty's been there. 338 00:42:34.000 --> 00:42:35.000 I have been there. 339 00:42:35.000 --> 00:42:38.000 He watched Tech play out there. You got. 340 00:42:38.000 --> 00:43:12.000 I watched Tech be on the field out there. I don't think I saw them actually play, but they were on the field. Yeah. At the same time, they played, like, not very good, which is about par for the course. I go on a road go. Go to a road game thinking, oh, this will be great, and I'm not going. Okay, it's halftime. We've got our free ice cream. Let's go. Yeah, that's the best thing about it. You get that for their. In their visitor section, they have people come. Have people that come through there. I can't remember when. It is early and relatively early in the game and they give you free ice cream from their creamery. And that ice cream is incredible. 341 00:43:12.000 --> 00:43:13.000 Wow. 342 00:43:12.000 --> 00:43:23.000 I mean, it is really ridiculously good. Like, it's. Thank God it comes in a small container because I would not have been able to get out of that place. It was so good. 343 00:43:23.000 --> 00:43:34.000 Wow. I love ice cream, but that's off the topic, too, so. But if you do have an ice cream, if you're an ice cream company, you want to sponsor our show, Blue Bell. 344 00:43:34.000 --> 00:43:36.000 I know the guy that runs the Blue Bell here. 345 00:43:36.000 --> 00:43:38.000 Hey, Blue Bell. We love Blue Bell. 346 00:43:38.000 --> 00:43:41.000 So the app's coming out around Thanksgiving. 347 00:43:41.000 --> 00:44:27.000 App's coming out. And then we. We also are going to look at quantifying how much brush we have, like mesquite and salt cedar, to find out how much water we're losing to those invasive species. And we're going to look at wildfire prevention measures through remote Sensing some things like that. And then we have another project that. This one I'm most excited about is it's strategic row crop to grazing land or dry land conversion. So it be paying to farmers income replacement for turning off their wells. 348 00:44:27.000 --> 00:44:28.000 Yeah. 349 00:44:27.000 --> 00:44:36.000 Leaving infrastructure in place so that if there's drought conditions, you don't have to sell off herds. You know, we can still keep it diversify. 350 00:44:36.000 --> 00:44:39.000 That's not a NASA. NASA program, though. That's something else. 351 00:44:39.000 --> 00:44:57.000 NASA is going to. NASA is going to help us with that program because. Because it would be looking at. You'd be looking at. First of all, you want to quantify and you got to verify how much groundwater was used. And so you can do that. So say a farmer turns in his data for X amount of years. Then they actually can then verify that that's how much water was used. 352 00:44:57.000 --> 00:44:58.000 Okay. 353 00:44:57.000 --> 00:45:12.000 And so they'll kind of be the verifier, certifier type thing. So we're actually going to go to a meeting in a big textile meeting in October to. 354 00:45:12.000 --> 00:45:14.000 When you say we, you're referring to Sarah. Correct. 355 00:45:14.000 --> 00:45:38.000 So. Yes. But we'll be there with like Cotton Trust Protocol. Who was going to partner with us. HSI is going to partner with us. And Sorghum is interested in, you know, being in some type of partnership, which, by the way, Global Sorghum Conference is in Lubbock. Not this week, but the next. It's going to be amazing. And NASA Acres will be there speaking. 356 00:45:38.000 --> 00:45:39.000 Really? 357 00:45:39.000 --> 00:45:41.000 Yep. I think it's Ignacio that's speaking. 358 00:45:41.000 --> 00:45:46.000 So I didn't. I did not realize the Global conference was here. 359 00:45:46.000 --> 00:45:47.000 It's a big deal. 360 00:45:47.000 --> 00:45:52.000 Yeah. Especially for an area that's lost almost all of its grain. Sorghum infrastructure. 361 00:45:52.000 --> 00:45:54.000 Exactly. 362 00:45:54.000 --> 00:45:58.000 Man. That you can think it on. 363 00:45:58.000 --> 00:46:33.000 Well, and that's the whole reason to look at something that's strategic. So like if we said NASA, help us identify, like, what. What wells we should keep, which are our strongest wells to keep. And then you say it's a hypothetical farmer somewhere has two wells that are really great and then surrounded by. And when I say wells, I mean like a circle that has four 14 wells and. Right. You know what I mean? So. But they have. So they. You identify whatever. It's like a section or a quarter section. And then they put, you know, the other into the program. 364 00:46:33.000 --> 00:46:34.000 Yeah. 365 00:46:34.000 --> 00:46:49.000 So then that we want to look and see what's happening at that. At the. At the well that they're using. You know what I mean? We want to keep it. Being able to see, like, is It Is this helping? 366 00:46:49.000 --> 00:46:50.000 Yeah. 367 00:46:49.000 --> 00:47:06.000 To retain some water there and so that they can continue to grow crop there and have water longer there without. How far can you do that without it damaging your infrastructure? Yeah, because once the 20 man cotton Jen's gone, it's gone. 368 00:47:06.000 --> 00:47:07.000 Yeah. 369 00:47:06.000 --> 00:47:15.000 You're not going to get back. But I'm like, to me it's like you're either going to hit a brick wall going 100 miles an hour or going 20. And there's a lot less damage if you're going 20. 370 00:47:15.000 --> 00:47:23.000 Yeah, well. And you know, a lot of the. It's like we had. Good grief. I just. His name was on my tongue. Buster. Gin. 371 00:47:23.000 --> 00:47:24.000 Oh yeah. Dan. 372 00:47:24.000 --> 00:47:46.000 Dan Taylor. We had him on a couple weeks ago and he was talking about how, you know, brown baling has changed Jenning, you know, you don't have to have a gin, you know, that's really close to your farm. We're not dragging cotton trailers or even sending module trucks out for modules. You're going out there and loading a semi load of round bales up and taking half the farm in one, you know, in a go. 373 00:47:46.000 --> 00:47:47.000 Yeah. 374 00:47:46.000 --> 00:48:04.000 And so that's changed a lot of the infrastructure demands that you have to have on it. But it's still, you know, that's still a Infrastructure to me is still the number one limiting factor on what can be grown. What can be grown on diversification 100%. 375 00:48:04.000 --> 00:48:25.000 Well, and I think that's one of the things that makes this project appealing to funders is that they, let's just say it's, you know, a large company that's name might start with a G and they say, you know, we want to help participate. We want to put X million dollars in or something. Well, what they're getting out of it is what you call a water offset credit. So like a carbon credit. 376 00:48:25.000 --> 00:48:26.000 Right. 377 00:48:25.000 --> 00:48:32.000 Because that water is, you know, not going to be used. You know, it's staying there. Yeah, they're turning it off. 378 00:48:32.000 --> 00:48:53.000 I've noticed. Have y' all noticed a significant shift in the way data centers are like approaching stuff? Did you see, you know, they're. They're fixing to build a new water tower for Turkey all of a sudden help their infrastructure. Like they finally realized that. And you got to give a little bit of credit to the state is saying like, okay, hold on a second, let's. You guys are getting taken advantage of. 379 00:48:53.000 --> 00:48:55.000 I never got, never understood how I 380 00:48:55.000 --> 00:49:01.000 think you take advantage. I think you give credit to the people who've been screaming to high heaven about it because they wouldn't have done nothing. 381 00:49:01.000 --> 00:49:10.000 That is true. But the original article that some chick wrote out of the New York Times about how much water was used was way, way high. 382 00:49:10.000 --> 00:49:11.000 Yeah. 383 00:49:11.000 --> 00:49:16.000 Way high. And they just went out like a viral thing. So everybody thinks, oh, I use this. 384 00:49:16.000 --> 00:49:17.000 Yes. 385 00:49:17.000 --> 00:49:22.000 I promise you, the farms that touches that data center use way more water than that. 386 00:49:22.000 --> 00:49:23.000 Well, that's what I'm saying. 387 00:49:23.000 --> 00:49:25.000 And they're going to figure out some other way to cool it. 388 00:49:25.000 --> 00:49:33.000 I mean, there's. That's what I've seen. I'm saying, well, we don't use as much money, as much water as ag. And I'm like, yeah, but you don't eat. You know, I'm not eating a data center. 389 00:49:33.000 --> 00:50:14.000 So, you know, that's officially. I mean, I think this is just like, what they. I think that they didn't all have bad intentions, that I think there are. I think the folks that are coming in and legit already, like, have someone that's gonna be in that data center. They're not just speculating. Those are people that have a better reputation. But the problem is, and I've seen this with so many different, like, brands and retailers is they want to do something for their esg. That's the word. You know, their environmental standing with their investors. 390 00:50:14.000 --> 00:50:15.000 Yeah. 391 00:50:15.000 --> 00:50:51.000 So they. They hire somebody, and bless their hearts, they've graduated from a great school, you know, on the west coast, and they live in a beautiful west coast city, and they have a great idea. And one. One example I've heard is, like, that someone was, like, they hired someone, not even local, to. To build a sculpture that's a. I'm like, I have no idea what it looks like. But apparently people in the town, they put the sculpture on the river as a gift to the town. And, like, the town has a petition to get it removed because everyone hates it. 392 00:50:51.000 --> 00:50:52.000 Yeah. 393 00:50:52.000 --> 00:51:08.000 You know, and they're like, why? Why? We don't want this. You know what I mean? And they're like. Or somebody said, well, we. We did something. You know, we cleaned up a brownfield site. Well, if you've been living in an area where no one cares about brownfield sites, I mean, who cares? 394 00:51:08.000 --> 00:51:09.000 Yeah. 395 00:51:08.000 --> 00:51:15.000 Like, I mean, just to be honest, all of Midland and Odessa is like, pretty much a brownfield side. I mean, just go down to permit basin. 396 00:51:15.000 --> 00:51:16.000 Yeah. 397 00:51:15.000 --> 00:51:49.000 It's like, it's everywhere. You know, it's not something that, like, people are. But people do care if they get a new school. But here's the difference. To me, a new school in 50 years is going to have to be repaired. And it's, it's important to put that investment there. But if you help diversify economy, you know, where you, like now you have a. You totally have a brand new infrastructure for something that you've never had before, then that continues, you know, and you get taxes from that. And it's going to continue to be beneficial. Way after said company that starts with a G leaves. 398 00:51:49.000 --> 00:52:00.000 Well, I heard, and there's a couple things I wanted to get to. One was during the. The lunch that I went to on Tuesday. 399 00:52:00.000 --> 00:52:01.000 Monday. 400 00:52:00.000 --> 00:52:03.000 Was it Monday? 401 00:52:03.000 --> 00:52:04.000 We're up on Monday. 402 00:52:03.000 --> 00:52:27.000 Okay, on Monday I went to one on Monday. I had them come up on Tuesday, couldn't make it to that one. So on Monday I was. My phone doesn't ring very often, but it rang that. And so. And so I was. As I was going out, I was hearing him talking about being able to measure the depth of the aquifer with these satellites. Did I dream that in my head? 403 00:52:27.000 --> 00:52:28.000 I don't think that you can. They can do that. 404 00:52:28.000 --> 00:52:29.000 Okay. 405 00:52:28.000 --> 00:52:30.000 That had to be like ground penetrating. 406 00:52:30.000 --> 00:52:33.000 They were doing. They were doing it. I think they were doing it magnetically, so. 407 00:52:33.000 --> 00:52:39.000 Magnetically. Well, that's how they tell. Well, maybe so. I know that's how they tell if water. Water. 408 00:52:39.000 --> 00:52:41.000 So maybe I did. Maybe I did dream it. 409 00:52:41.000 --> 00:53:32.000 Groundwater. Groundwater use. If that's how they tell. Groundwater. Okay, so there is. If you're ever in dc, you can go and tour NASA headquarters. It's in DC downtown, you know where all the other headquarters stuff are. So they have this like chandelier that's coming down. Like, you know, the entrance is like two stories and it's coming down. This is glass, strips of glass coming down from the ceiling. And it's. It lights up with the name of the satellite. And then all the data that's coming in on all of these little. Looks like strings of light all the way down to the floor. And it is going constantly. One, one will stop. And then two seconds later there's another name. And then all this data is just pouring down like raindrops. 410 00:53:32.000 --> 00:53:38.000 Sounds like the Matrix. That movie, the Matrix where it's just all the green dots and the computers running. 411 00:53:38.000 --> 00:53:57.000 It is totally insane. Insane. And like when I. We think about like AI data centers, like how valuable they are to us. I mean, and I. I don't know, I think a lot about this reminds me kind of the Y2K scare, you know, like everybody was terrified when, you know, we went from 99. All the, all the computers are gonna. 412 00:53:57.000 --> 00:53:59.000 I'M not sure there's this many people. 413 00:53:59.000 --> 00:54:04.000 It reminds me more of the Cold War, like, where it's a. Like, it's kind of like a. 414 00:54:04.000 --> 00:54:06.000 It is an arms race. It definitely is. 415 00:54:06.000 --> 00:54:08.000 Between us and China. 416 00:54:08.000 --> 00:54:09.000 Yes. 417 00:54:08.000 --> 00:54:13.000 And I think that's why. That's why the government's behind it, is because they can see. 418 00:54:13.000 --> 00:54:14.000 Yes. 419 00:54:13.000 --> 00:54:27.000 That. And there's some things that they don't want in here from other countries that they're trying to figure out. But, you know, their AIs, when they test them out, they put them in what's called a sandbox, which is like a deal that kind of keeps them from getting outside of where they're testing them. 420 00:54:27.000 --> 00:54:28.000 Right. 421 00:54:28.000 --> 00:54:43.000 And. And it's pretty scary what those things have tried to do. Like, it's tried to blackmail people because it's found, like, the CEOs texting or something or send the email to some other lady that's not his wife. And. Well, we're going to blackmail you. Don't shut us down. 422 00:54:43.000 --> 00:54:58.000 Well, you know, don't you think that goes to the fact that it's pulling all this data in? And that's what it's pulling in is like, parts of our world there. That's why, like, anthropic is like. Has somebody hired this literally teaching it ethics? 423 00:54:58.000 --> 00:54:59.000 Yeah. 424 00:54:59.000 --> 00:55:00.000 You know. 425 00:55:00.000 --> 00:55:02.000 Well, and who. What ethics do they have to be teaching? 426 00:55:02.000 --> 00:55:05.000 But it's just basic ethics. You know what I mean? Like what. 427 00:55:05.000 --> 00:55:06.000 Yeah, but what's. 428 00:55:05.000 --> 00:55:06.000 In college. 429 00:55:06.000 --> 00:55:07.000 Yeah, it's still. 430 00:55:07.000 --> 00:55:08.000 But it's Socratic. 431 00:55:08.000 --> 00:55:11.000 It is, it is, but it's. It's still. You worry about who's teaching it. 432 00:55:11.000 --> 00:55:12.000 Yeah. Right. 433 00:55:11.000 --> 00:55:13.000 Like, what are you training it to. 434 00:55:13.000 --> 00:55:14.000 Yes. 435 00:55:13.000 --> 00:55:14.000 To do. 436 00:55:14.000 --> 00:55:15.000 To do. 437 00:55:15.000 --> 00:55:31.000 It's, it's, you know, I don't get. I mean, it's, it's amazing what it can do, and it's terrifying what it can do. And, you know, it's. It's here whether we want it or not. But you're going back to arms race stuff. Really. The biggest arms race between us and China is actually energy. It's. 438 00:55:31.000 --> 00:55:33.000 They have way more energy than we, 439 00:55:33.000 --> 00:55:35.000 and they are beating the thunder out of the rest of the world. 440 00:55:35.000 --> 00:55:56.000 Yeah, we'll. We'll get them, though, because there's so much stuff that's wasted. Forget Venezuela. There's so much stuff that's wasted. Gas that's flared off that could be running. It could be running turbines and stuff. I mean, they just did one of the largest geothermal things in Utah. They just started putting it online. They think geothermal will be as big as solar eventually. 441 00:55:56.000 --> 00:55:57.000 Yeah. 442 00:55:56.000 --> 00:56:12.000 I mean, but it's. I mean, yeah, I'm not even talking. I mean, like, just discount solar entirely and don't put another solar panel up in China. And it's going to take decades for us to catch them. But they're putting. They bring in. Was it 30 new coal fire plants a year? 443 00:56:12.000 --> 00:56:15.000 Yeah. They don't have the environmental concern, they just do whatever. 444 00:56:15.000 --> 00:56:19.000 There's a new coal fire plant opening in China basically every other week. 445 00:56:19.000 --> 00:56:20.000 Yeah. 446 00:56:19.000 --> 00:56:22.000 That's why it's so important we unlock nuclear here. 447 00:56:22.000 --> 00:56:23.000 Yeah, yeah, I think so too. 448 00:56:23.000 --> 00:56:35.000 And I mean the. Well, they're building nuclear plants too. I mean, they've built God only knows how many nuclear plants since the last one we opened was, you know, and nuclear has changed so much now. It's, I mean, it's not even the same thing that you have with Chernobyl. 449 00:56:35.000 --> 00:56:52.000 Well, and I think, you know, they're also reclaiming a lot of, like, they've just ruined a lot of their land, you know, so made it where it wasn't farmable. But they've gone back and have been working to reclaim all that because. So I think food independence and energy independence is like, it's going to be 450 00:56:52.000 --> 00:57:02.000 interesting to see what happens with them because their population, their population demographics look bleak in China. I mean, bleak. Like ours don't look great. 451 00:57:02.000 --> 00:57:03.000 Nobody's. 452 00:57:02.000 --> 00:57:05.000 But there's. I mean, it. The only place that. 453 00:57:05.000 --> 00:57:14.000 Well, when I hear people say we're gonna have. We've got all these people to feed. I'm like, that is just. I mean, we're gonna peak like at 2050. Right. 454 00:57:14.000 --> 00:57:15.000 Something. 455 00:57:14.000 --> 00:57:15.000 Our population is. 456 00:57:15.000 --> 00:57:16.000 Yeah. 457 00:57:16.000 --> 00:57:18.000 And then it's like over the cliff. 458 00:57:18.000 --> 00:57:19.000 Yeah. 459 00:57:19.000 --> 00:57:21.000 Decline. You know, there's. 460 00:57:21.000 --> 00:58:10.000 There's several people. People that I've, I've. That I follow and I'm not a genius on it, but there's. They think that China's already hit the tipping point. They've already peaked and are collapsing to the point where it can't become. We can't come back. But one of the things I did want to talk about too was I heard and I did not have time to dig into the details of this because I heard about it about, you know, an hour before I got here. Apparently there has been an executive order where the USDA that feed. The part of the USDA that feeds like prisons and schools and stuff like that. There are. Have been. Has been an executive order to locate to try to buy beef as local as you can to an area to where your. Your area is, and it comes and it goes back into watching to deal with systems. 461 00:58:10.000 --> 00:58:18.000 Well, that would be great. I mean, they should be doing that. They grow a bunch of their stuff, though. It's got to be contractors that heard of a lot. 462 00:58:18.000 --> 00:58:48.000 Some, I don't know, it's HEB or United, but they're doing a deal. There's about. With local beef producers, but I think there's. They said you could get 80 or 85% lean, I want to say, for $4 a pound, or 4.99. What. What is it right now? If it, if you get. I think it's like 8, 7 or 8, but I wonder if that's. That's cheap stuff. But it says. It says they're connecting with local people. But then the US Just import a whole bunch of beef and it has 463 00:58:48.000 --> 00:58:49.000 £3 million of ground beef. 464 00:58:49.000 --> 00:58:51.000 I think that's way more than that, right? 465 00:58:51.000 --> 00:58:53.000 Oh, I think it was a lot. 466 00:58:53.000 --> 00:58:55.000 I thought it was like 25 million. 467 00:58:55.000 --> 00:58:57.000 It was. It was a three. It was either three or 30. 468 00:58:57.000 --> 00:59:02.000 Well, it's 3%, I think. I think, is what it was. I mean, it's not like a huge. 469 00:59:02.000 --> 00:59:10.000 But. But Trump was wanting them to sell it for $5 a paint. I mean, that's like. I mean. I mean, I don't know what they're paying for it. 470 00:59:10.000 --> 00:59:48.000 What I, I have learned is that they. Most of the ground beef that we consume is not US Ground beef. Most of the beef that's grown in the US Is grown for the steaks and roasts and stuff like that. And there's very little waste that they use to put into the ground beef. And most of the ground beef is cattle that come from south and Central America and Australia. It comes as a huge chunk. A surprisingly large amount comes from Australia because their beef is typically not suitable for. What would be for you at the. For the US State market. Yeah. Because they don't raise a whole. They don't raise a whole lot of USDA Prime. 471 00:59:48.000 --> 00:59:49.000 Right. 472 00:59:48.000 --> 00:59:51.000 You know, in the deserts of Austria, Western Australia. 473 00:59:51.000 --> 00:59:52.000 Yeah. 474 00:59:51.000 --> 00:59:53.000 You know, and so. 475 00:59:53.000 --> 01:00:01.000 Well, to me, that's where we have a huge. That's a huge opportunity. I mean, that is a market demand that we're not anywhere near meeting. 476 01:00:01.000 --> 01:00:02.000 No. Yeah. 477 01:00:02.000 --> 01:00:03.000 You know, and so. 478 01:00:03.000 --> 01:00:11.000 And there has been some easing of restrictions on being able to get for a grower, a cattleman to actually be able to sell. 479 01:00:11.000 --> 01:00:21.000 But, you know, the other thing is, I think that we've done a. Probably a disservice to ourselves in trying to explain subsidies to people that it's actually like subsidizing your grocery cost. 480 01:00:21.000 --> 01:00:22.000 Yeah. 481 01:00:22.000 --> 01:00:29.000 Because now it feels like we all think we have the, like we have a constitutional right to cheap groceries. 482 01:00:29.000 --> 01:00:40.000 Yeah. And that's what, I mean, that's what it was designed for. I mean, that's what I was told in multiple different economic. Multiple economics, both ag economics and. 483 01:00:40.000 --> 01:01:07.000 Well, it was designed because we had a ton of. We had too much, we were growing too much. And they had to find a way to do something with it and keep farmers in business. And so they bought it and started giving it away. And they still do. I mean, if you go to the food bank, a lot of the stuff that you load up in those boxes in the food banks are grown, you know, on different farms, beans and rice. And it tells you where they're from. 484 01:01:07.000 --> 01:01:18.000 I don't imagine there's. There's not a whole lot of rice production that I would. Well, there is probably. Well, I know there's a lot of rice production. I just don't know how much of it goes in into that. 485 01:01:18.000 --> 01:01:27.000 Well, every time I've been there, I'm, I'm. I've packed a bag of rice. Now. I haven't worked since COVID but I used to work every. Yeah, twice a week or something packing 486 01:01:27.000 --> 01:01:29.000 beans and rice a week more than me. 487 01:01:29.000 --> 01:01:31.000 That's a great place to go. 488 01:01:31.000 --> 01:01:44.000 So Saint Benedict's. Wait, I'm gonna plug Saint Benedict's because we do that. I'm on the board there and they're, they. We feed. We started feeding like 200 people and now it's gone to like 340 hot meals a day. 489 01:01:44.000 --> 01:01:46.000 A day? I didn't know it was daily. 490 01:01:46.000 --> 01:01:54.000 Yes, daily. Every day of the week. Yeah. Hot meals every day of the week. They have volunteers that do it. It's totally non profit. I mean, it's. 491 01:01:54.000 --> 01:01:55.000 Yeah, it's. 492 01:01:55.000 --> 01:02:18.000 But it's been. It's. It's a really good. It's a ministry. I mean, honestly. But yeah, there's. It's amazing. Like you can tell the numbers. Like when everybody's EBT card gets like filled, we're not as busy. But then like towards the end of the month when the EBT stuff starts running out, we get busy. We might do 400 or something in a day. But yeah, the local people really stepped up and supported that place. So I'll plug. 493 01:02:18.000 --> 01:02:21.000 Say where is is. 494 01:02:21.000 --> 01:02:34.000 It's on Q. North of Park Tower, south of Park Towers apartment though. It used to be really cool. They're real. It's on cue By Orlando. Right across from Orlando. St. Benedict's is right south of it. 495 01:02:34.000 --> 01:02:35.000 Okay. 496 01:02:34.000 --> 01:02:36.000 So I mean we, there's a bus stop right by it. 497 01:02:36.000 --> 01:02:39.000 So we get, you know, people come from all over. 498 01:02:39.000 --> 01:02:46.000 Yeah. I mean there's, you know, there may be a grandmother that has like eight kids that she's taken care of from her for that don't take care of them and. 499 01:02:46.000 --> 01:02:47.000 Right. 500 01:02:47.000 --> 01:02:48.000 It's a good ministry. 501 01:02:48.000 --> 01:02:58.000 Yeah. It is always shocking. Like I, I, people want to go back and listen to the. I did. I've done a two with the chase head at the food bank now. 502 01:02:58.000 --> 01:03:04.000 We should have, yeah, we should have, we should have our ED on here sometime from Saint Benedict's. 503 01:03:04.000 --> 01:03:06.000 Oh, exactly. Let's do it. 504 01:03:06.000 --> 01:03:07.000 Yeah, we should do that. 505 01:03:07.000 --> 01:03:17.000 That's a great idea because I was thinking about having like the United Way director because they're really trying to expand outside of just Lubbock too. But I think it's good for. We just don't realize how many hungry people there are. 506 01:03:17.000 --> 01:03:37.000 Well, but also. Well, I just don't get into that because there's a lot of competition between non profits for money to get to stay, operate and so like some people don't want you to know how many, how much money they have in their bank account when they do canned food drives and like. Yeah, you're like, oh, they're gonna run out. Well, no, they have like millions of dollars in the bank. Like. 507 01:03:37.000 --> 01:03:38.000 Right. 508 01:03:37.000 --> 01:03:41.000 Yeah, fine. I mean we're like month to month. 509 01:03:41.000 --> 01:04:10.000 I did some looking around which, you know, because, you know with, you know, I feel like the government does a lot of things that it would be better served more. The, the more local control we get on it, the better I think it's going to be. You have a lot of variability there and it's very confluent and complex. But anyway. But I was looking at, you know, what can be done with NGOs and you start. There's Pro Publica, I think has got a, they have got a website where you can go and you can look at the financials of an NGO. 510 01:04:10.000 --> 01:04:13.000 Well, NGOs have to release that every. 511 01:04:13.000 --> 01:04:15.000 But not. I don't think a non profit has to do. 512 01:04:15.000 --> 01:04:16.000 Yes. 513 01:04:16.000 --> 01:04:17.000 Yeah, only if they take. 514 01:04:17.000 --> 01:04:21.000 If it's over 50,000 a year, I think then you have to do more than. 515 01:04:21.000 --> 01:04:24.000 I'm pretty sure there's a lot of people that don't know how much money some of these. 516 01:04:24.000 --> 01:04:25.000 That's what I was. 517 01:04:25.000 --> 01:04:27.000 They're not an ngo. They're like. 518 01:04:27.000 --> 01:04:38.000 It was, it was non profits, it was not NGOs. It was. Was nonprofits is what. Yeah, but that NGOs. A lot of. Not all NGOs are non profits, but all nonprofits would be NGO. 519 01:04:38.000 --> 01:04:39.000 It was. 520 01:04:38.000 --> 01:04:46.000 If you take any government money, but it goes. And you can see how much money they brought in, the rate. What brought it up was this. 521 01:04:46.000 --> 01:04:49.000 It's on, it's on the U.S. it 522 01:04:49.000 --> 01:05:20.000 was a non profit hospital in Oregon or Washington state. Something up there. It was. And it served the rural. Rural part of the state. And they fired all of their emergency room staff and replaced them with a physicians group that was on private equity. They contracted it and they're like, well, it's, you know, we're financial headwinds. And the guys said, I pulled up, I went to this thing. So didn't know existed, went, looked at it and they made $104 million. They netted $104 million the year they did this. 523 01:05:20.000 --> 01:05:23.000 Whoa. And so it wasn't a financial move. 524 01:05:23.000 --> 01:05:30.000 No, no. But then you start. But if you can track, you can also think on that thing. You can also see what, you know, how much they pay for director. 525 01:05:30.000 --> 01:05:33.000 Yes. 526 01:05:33.000 --> 01:05:46.000 You know, and I'm gonna throw a curveball because I'm gonna say pheasant forever, not quail. So. But pheasant forever is like, it's like 96%, I think, of what they receive goes back out in. 527 01:05:46.000 --> 01:05:47.000 That's a really high. 528 01:05:47.000 --> 01:05:49.000 And it's an insanely high number. 529 01:05:49.000 --> 01:05:50.000 Yeah. 530 01:05:50.000 --> 01:06:10.000 And it's one of the reasons that you have a lot of turnover down on their biologists and stuff, because they just can't. But yeah, some of these things, it's like completely inverted and they're like 96% of it stays in the director's pockets and the board's pockets. And that's why I'm not calling any name because I don't know any. I just know that the numbers. 531 01:06:10.000 --> 01:06:45.000 Well, that's what. And one of the things as we've talked as we've been raising money for this grassroots conversion, I mean, this grassland conversion thing, which we call rooted returns, because part of it is then you take the beef or whatever protein they're growing and it's water smart. And so if you can, if you can then market that through local restaurants and grocery stores, especially in Lubbock, to consumers to educate them, because how many people live in Lubbock understand what is going to happen to the economy of Lubbock when we hit the brick wall of no irrigation? 532 01:06:45.000 --> 01:06:46.000 Yeah, yeah. 533 01:06:46.000 --> 01:06:47.000 At any mile an hour. 534 01:06:47.000 --> 01:06:55.000 Yeah. At any moment. That People don't understand, like, it's not, it's not half, but it's quite a bit of. Of the income of Lubbock runs off of. 535 01:06:55.000 --> 01:07:23.000 Well, the, you know, that's. When I was outside, I was listening to the podcast up from up in Iowa and they were talking about, you know, getting this out, you know, farmers, you know, and these ranchers are still spending money out. I mean, everybody does. But the farmer dollar turns over in the economy more than any other sector. Let me rephrase that. As of about 15, 20 years ago, the farmer dollar turned around over more times in the economy, in a local economy, than any other dollar that could, that was spent. 536 01:07:23.000 --> 01:07:24.000 Interesting. 537 01:07:23.000 --> 01:08:15.000 So, like, if a dollar came in to, like I say, you get a subsidy, $100, that farmer. And back in the day, the reason was farmers didn't say that. The thing was, you know, farmers don't save anything. Everybody knows they don't save anything. They're going to spend it. And so it goes. And it goes into, you know, the, to the parts store who pays the employee, goes to the grocery store who pays it, you know, and it just, it just, it turns over a lot of times. And I don't know if that number still holds true. And I don't even know where to get it done. Somebody better than me with Claude would have to figure that out. But, you know, that's one of the things that as you push the local, you know, with pushing in local beef demand, you know, because that's the. And like you're talking about on this grazing deals, the infrastructure required to get low local beef is going to have to change. It's going to have to change because, you know, you just look at. 538 01:08:15.000 --> 01:08:17.000 But that's a whole nother restaurant. 539 01:08:17.000 --> 01:09:28.000 You go and you're like, okay, well, I want to serve ribeye steaks. We don't get X number of ribeye steaks out of a cow. Well, if they go in and you have 50 of them, that may be three cows worth. I don't know what it is, but it may be, let's call it two cows worth of ribeyes. But what do you do then with the brisket? You know, is that, you know, that restaurant that serves state, the steakhouse is not necessarily going to get. Not necessarily going to get a brisket and smoke a brisket too, and have all of a sudden become a barbecue joint overnight. You know, that was one of the things that I had never thought about until I was watching Clarkson Farms and he started that pub and his chef was Telling him, here's your problem, you know, you've got X number of cows. Well, this right here is gonna, you know, this is enough meat for this many meals, which is like, you know, say three months or whatever he said. But it's only enough hamburgers for two. So, you know, so you gotta have that whole process in there. And it's not just one thing that, and that's why you got, you wind up with people like Cisco that, you know, that can, that, you know, you go into a restaurant and have a popper in San Francisco and you can have the same popper in Charleston, South Carolina. Because Cisco so. 540 01:09:28.000 --> 01:09:43.000 Well, and which that says like there's a need for both of those. I mean, it's not like I think to say that we have to replace a long supply chain with a short supply chain is wrong. Yeah, we just need to, we. Our long supply chain is solid. 541 01:09:43.000 --> 01:09:44.000 Yeah. 542 01:09:44.000 --> 01:09:46.000 We just need to invest in our shorts. 543 01:09:46.000 --> 01:09:48.000 Yeah. Because you really need them both. 544 01:09:48.000 --> 01:09:50.000 You need both of them and we don't have them. 545 01:09:50.000 --> 01:10:15.000 And it, I mean, it's, to me, it's a natural. And I've heard this. It's not an original thought. I very seldom have original thoughts, but they are, you know, it's a national security issue. Food insecurity, you know, is why you have problems in third world countries most of the time is because they can't get food because poverty and it just follows in through there. 546 01:10:15.000 --> 01:10:21.000 Or if they do get food, it gets withheld by the people that control the country to control the rest of the population. 547 01:10:21.000 --> 01:11:36.000 That's true. Exactly. And you know, so it becomes a, it becomes a deal where, hey, you know, we've got to be able to go in the grocery store and get food or go into a farmer's market and get food. And for the longest time, I mean, this is not a new deal. For the longest time, public policy has been we want to get as efficient so it can be as cheap as possible, which means big. I mean, invariably that's what it means. And which means that you. Consolidation, you might wind up with massive consolidation. I mean, Cisco is, they do their one there. I think they are the largest. There's only three food distribution companies that do the same thing. And it's. I can't remember what the other two are. So I'm, you know, I'm not calling out Cisco, you know, if anybody out there that works for Cisco, I'm not calling you out. I'm just, that's the name I can remember because I've said everybody's seen the truck. But they've gone in and been able to buy up all the local competition, all the regional distributors and move into it. They move in, you know, they can move into an area by four regional distributors and send it there. You've seen the same. We've seen the same thing happen in the three tier alcohol distribution. Yeah, you mean. And you know, you wind up with Southern Glazers and well, which I think 548 01:11:36.000 --> 01:11:45.000 we have laws, you know that should prevent some of those monopolies from happening, you know, because I, I think at one time we understood the damage that they can do. You know. 549 01:11:45.000 --> 01:11:57.000 We do. The problem is that they stop at an oligarchy. Oligarchy. You know, there's four meat packers that control 85% of the US meat market. Four. Well, that's not, that's not technically a monopoly. 550 01:11:57.000 --> 01:12:00.000 Not just the U.S. isn't it global? 551 01:12:00.000 --> 01:12:09.000 I don't know if it's. Well, I just know, I know that at least two of them are owned by global corporations. But. So you got. But it's still four. 552 01:12:09.000 --> 01:12:10.000 Right? 553 01:12:09.000 --> 01:12:19.000 And I know in the US it's like 85%, you know, and they're like, well you know, there's four. So that's not a monopoly. It accomplishes the same deal, you know, so. 554 01:12:19.000 --> 01:12:40.000 So I think that that's like goes back to this feeling that it. Efficiency is the most important thing. Like it has to be efficient and has to make the most money. And you've brought this up before that like corporations are required by law to make the most money they can. That they can. 555 01:12:40.000 --> 01:12:48.000 Thank you. Court case in. I think it was Minnesota back in the 50s, I think. 556 01:12:48.000 --> 01:12:50.000 So it hasn't gone to the Supreme Court. 557 01:12:50.000 --> 01:13:13.000 I don't know that just that was the court that said that said it because a shareholder, the guy that owned the business, wanted to give a bigger chunk of the profits to them to the employees. And the shareholders sued and won and said that he had to. The first step they had to look out for was not his employees. He had to look out. He had a fiduciary duty to the shareholders to make as much money. 558 01:13:13.000 --> 01:13:40.000 On the antithesis of that, you have. Elon's pay package was declared, you know, in Delaware Corporation. They wouldn't, they did. They said no, you can't have that pay package. Even though every shareholder voted and it voted overwhelmingly to give him the pay package. Well then he moved to Texas and that. He got it. He got his pay package. Yeah, but I mean it was, it was a pay package full of Incentives like, hey, if you get us to a trillion dollar company. 559 01:13:40.000 --> 01:13:41.000 Right. 560 01:13:40.000 --> 01:13:45.000 We're gonna. Which in the ultimate scheme of things does make shareholder. 561 01:13:45.000 --> 01:13:46.000 Yeah. 562 01:13:45.000 --> 01:13:51.000 And he said, he said, you know, the largest IPO ever until Anthropic will beat it. 563 01:13:51.000 --> 01:13:52.000 Yeah. 564 01:13:51.000 --> 01:13:56.000 When Anthropic drops theirs, they'll. They'll probably beat it. If I be. They're saying it could be 2 trillion dollar. 565 01:13:56.000 --> 01:13:57.000 Yeah. 566 01:13:56.000 --> 01:13:58.000 Company when it's. When it starts. 567 01:13:58.000 --> 01:14:25.000 But. Yeah. I mean that's. Yeah. And it, I mean, it's, you know, wow. It's. The bigger corporation gets the tougher it is because I mean, even as small as, you know, even as small as looking at a small farm, you know, every decision has got to be viewed through, you know, am I going to get a nickel if I spend this quarter? You know, it's not, it's not a matter of am I going. It's. It's so many decisions in the current marketplace are how can I lose the least amount. 568 01:14:25.000 --> 01:14:31.000 Yeah. That's what I was going to say. If I do this, am I going to lose a nickel or am I going to lose a quarter? I mean, that's the bad thing. 569 01:14:31.000 --> 01:14:53.000 Well, and that's the thing. And I think that like, you know, understanding for. For all of us that, you know, that want to pay for more expensive groceries. But at the same time, I think, I think to me it's worth. And. And also a lot of times these people that are. That are at farmers markets, they can take EBT cards. They can take your. 570 01:14:53.000 --> 01:14:54.000 Yeah. 571 01:14:54.000 --> 01:14:55.000 SNAP benefits and. Which is not. 572 01:14:55.000 --> 01:15:12.000 I just saw that they make $7 made it illegal to use it. I didn't know you could use a EBT card at like Taco. What's it. What's the Taco Bell and KFC and Pizza Hut. You could, you could, you could. You can't. Now I didn't know that you could. 573 01:15:12.000 --> 01:15:24.000 Well, having had one of those before. I've had one of those cards during COVID Yeah. Because Joseph went to. That was not something I could do. The only place that you could get something. So like we used to have single moms that have those. 574 01:15:24.000 --> 01:15:25.000 Yeah. 575 01:15:24.000 --> 01:15:27.000 They could get a frozen pizza from Papa John's, which you could. Absolutely. 576 01:15:27.000 --> 01:15:29.000 I wonder if it's. I wonder if it's do that. 577 01:15:29.000 --> 01:15:30.000 I think it varies by state. 578 01:15:30.000 --> 01:15:33.000 I was gonna say by the state 579 01:15:33.000 --> 01:15:39.000 because I think Florida just changed their law where you could know they couldn't. You couldn't buy vape products and lottery tickets with it. 580 01:15:39.000 --> 01:15:41.000 What. 581 01:15:41.000 --> 01:15:46.000 What I'm like, that was a thing but they just changed the, I mean, 582 01:15:46.000 --> 01:16:19.000 and I don't know, it's hard to know what the actual news is, but I, I think he's right that. So the money goes to the state and then the state decides because like I have a friend now that has three kids, single mom, has, it now has like some kind of pancreas something or another and has not been able to qualify for SNAP benefits. Yeah, she hasn't been able to work for like she was in the hospital and she's just now, I mean, where she might possibly be able to get out and work. 583 01:16:19.000 --> 01:16:20.000 Yeah. 584 01:16:20.000 --> 01:16:31.000 But because she hasn't worked, she doesn't qualify for benefits. That's why she doesn't get benefits now. It's because she hasn't worked. Because you have to have work. There are work requirements for it, right? 585 01:16:31.000 --> 01:16:32.000 Yeah, they're. 586 01:16:31.000 --> 01:16:35.000 Unless you 18 and they're like 18 hours a week. 587 01:16:35.000 --> 01:16:39.000 I think it's so much, so many months out of the, I think quarter or something. 588 01:16:39.000 --> 01:17:26.000 It is, it is, it has to break out to something like 18 hours. And I mean, but there, you know, there's also what makes it tough is, you know, I'm like, like my knee jerk reaction is you should buy, you know, healthy foods. You should buy stuff. You can buy stuff to make a meal for pretty stinking cheap, you know, and you can make that thing stretch. But at the same time though, you do have the single mom with three kids and like, when am I going to cook? I can't, you know, like me when we had the boys at home, I could cook. I could put something into four different containers and in one Sunday afternoon I had it all done. But I, you know, we could have meals planned out going through there. But you know, not everybody has the luxury of being able to go out and buy that. Even go out and buy the stinking Tupperware that it goes into. You know, then when you, you know. 589 01:17:26.000 --> 01:17:36.000 So if you want to know anything about, about food stamps, you can listen to our podcast from Brandon Lips, who was in the first Trump administration. That was his job. He was the. 590 01:17:36.000 --> 01:17:42.000 Okay, so what I was saying is a, is a law was introduced to do that. To take to what? 591 01:17:42.000 --> 01:17:43.000 A federal law. 592 01:17:43.000 --> 01:17:44.000 Yeah. 593 01:17:43.000 --> 01:17:45.000 Where you cannot use SNAP cards. 594 01:17:45.000 --> 01:17:51.000 They couldn't even restaurants, they couldn't even get a rotisserie chicken until like. 595 01:17:51.000 --> 01:18:18.000 So it just says recently. Yeah, it's, it's, it's state level. It's, let's see, it said. I just that here's the people that currently qualify for restaurant meal programs and on SNAP ages, adults age 60 or older, individuals with qualifying disabilities or individuals experience homelessness. That's the three that can qualify for restaurant meal program right now. But it does. It ultimately does go back to the state. 596 01:18:18.000 --> 01:18:30.000 They're elderly. If they're disabled or homeless. Or homeless, then they're saying they might need to eat at a restaurant because they might. Could go get groceries, but they might not have the ability to cook them. 597 01:18:30.000 --> 01:18:31.000 Yeah. 598 01:18:31.000 --> 01:18:33.000 Because they're disabled, they're old or. 599 01:18:33.000 --> 01:18:35.000 Which, I mean. I mean, which makes sense. 600 01:18:35.000 --> 01:18:36.000 Makes some sense. 601 01:18:36.000 --> 01:18:37.000 I mean, you know, let's just go 602 01:18:37.000 --> 01:18:45.000 back also to the fact that it's $7 a day. $7 a day a person. That's the max that you can get. 603 01:18:45.000 --> 01:18:46.000 Yeah. 604 01:18:46.000 --> 01:18:47.000 Well, where are you gonna eat? 605 01:18:47.000 --> 01:18:48.000 I don't know that that's. 606 01:18:48.000 --> 01:18:51.000 You wanna go eat two, three times? I don't know what's gonna be gone. 607 01:18:51.000 --> 01:19:12.000 There was somebody that was on it that got her BMW taken away because she was on Instagram bragging about how she just bought a brand new BMW. And then she was like, I got all this with my food stamp. I mean, there's. There's an amazing amount of wealth. I mean, this person. This person, this person was actually arrested and was actually prosecuted. So it. We know that that was real. 608 01:19:12.000 --> 01:19:26.000 So you should listen to my podcast because this is what I ask Brandon about fraud. And most of it is like organized crime. It's not. It's not the. What do you call her? The welfare queen? It's. 609 01:19:26.000 --> 01:19:28.000 It's organized organized crime. 610 01:19:28.000 --> 01:19:30.000 Organized crime. And a lot of it's international. 611 01:19:30.000 --> 01:19:35.000 Yes. Russia is big in it and the Triads, I believe, are big in it. 612 01:19:35.000 --> 01:19:42.000 I mean, like, why don't we just fix that problem? How can. I mean, we do have like an FBI and all this. Why don't we just fix that problem? 613 01:19:42.000 --> 01:20:01.000 Because it's some random judge from somewhere stops it. I mean, it's just, look, I mean, go way off the deal and go to athletics. Like, LSU wants to have pro quarterbacks play on their team. That has been on the roster this afternoon. Well, they got a local judge to do a temporary restraining order. 614 01:20:01.000 --> 01:20:02.000 Yeah. 615 01:20:01.000 --> 01:20:02.000 Yeah. 616 01:20:02.000 --> 01:20:18.000 Lovell got one for basketball player the other day, which is great because I love him. I'm glad he's back. But I mean, the way that these local judges can, like, do stuff is just beyond me. Well, they can stop stuff nationally. 617 01:20:18.000 --> 01:20:50.000 That's the thing about it, is that the Supreme Court's pushed back on that, but it hasn't each one, you know, the Supreme Court can push back and say, listen, you know, you can't do this. Well, the judge can do that. And it's got to make it to the Supreme Court again before the, you know, the good judge gets slapped down. But I mean, it's, it's wild. I mean, it. There's there for every way that there is someone trying to help someone and get them money in a way that will make their life better. There is four people trying to figure 618 01:20:50.000 --> 01:20:53.000 out how to deal Covid in the PPP program. 619 01:20:53.000 --> 01:20:54.000 Oh, my gosh. 620 01:20:53.000 --> 01:21:03.000 I mean, they haven't even scratched the surface to that yet. If you go back and look at all our problems we're having now with inflation stuff, it started with all the COVID money. Yep. I mean, we all know people that got money that didn't need it. 621 01:21:03.000 --> 01:21:04.000 Yeah. 622 01:21:04.000 --> 01:21:06.000 Their businesses actually flourished during that time. 623 01:21:06.000 --> 01:21:07.000 Yeah. 624 01:21:06.000 --> 01:21:15.000 I've wondered that too, about, like, what will the impact, you know, all of the Trump accounts that are coming out now. I've wondered if we would have. If there would be impacts. 625 01:21:15.000 --> 01:21:17.000 No, because it has to be locked up for. 626 01:21:17.000 --> 01:21:22.000 I know, but I'm saying when it all comes out in 18 years, maybe. 627 01:21:22.000 --> 01:21:25.000 But there's. That gives you. The thing about it is you'll have 628 01:21:25.000 --> 01:21:26.000 the end of their career. 629 01:21:26.000 --> 01:21:27.000 Let's say 18. Let's. 630 01:21:27.000 --> 01:21:28.000 Yeah. 631 01:21:27.000 --> 01:21:35.000 Because. Well, let's say 18 years. You'll have 18 years where that'll be factored into the economy. Whereas with COVID you had. Didn't even have 18 months. 632 01:21:35.000 --> 01:21:38.000 Yeah. They just dump so much in a shorter period of time. 633 01:21:38.000 --> 01:21:56.000 And that's the thing about everybody. I mean, it is a commonly held belief by a large number of economists that, you know, government spending drives inflation. That's just the way it. It works because you dump it in there and there's. And it's like free money. 634 01:21:56.000 --> 01:22:02.000 Yes. To many dollars tasting, chasing too few assets. That's the housing market. 635 01:22:02.000 --> 01:22:03.000 Yeah. 636 01:22:02.000 --> 01:22:19.000 I mean, that's why housing got so high, is that people kept the house they were in, went and bought a house in the mountains or whatever. Yeah. And, you know, but now it's starting to, you know, in area. In areas. It's starting to come back a little bit. But I did see lumber. Lumber actually has come way down in 637 01:22:19.000 --> 01:22:31.000 the last six months, which is, which is interesting. I mean, but we have. I mean, there's a lot of lumber that has been grown in the US for the housing market. And then the meals went away. 638 01:22:31.000 --> 01:22:32.000 Yeah. 639 01:22:31.000 --> 01:22:35.000 And they shut down the mills and moved production to Canada or something like. Something like that. 640 01:22:35.000 --> 01:22:46.000 That's off the table right now. But Canada's not giving us nothing, and we're not giving them anything. I never seen such a ridiculous thing. 641 01:22:46.000 --> 01:22:48.000 It is so in my life. 642 01:22:48.000 --> 01:23:14.000 Well, okay, I. I saw the reason that. Okay. I don't know. I don't know what. Nobody knows the exact details. Right. But the speculation amongst the, you know, talking heads in. In Canada, which. Their news is weird up there because, you know, all their news is from the cbc, the Canadian Broadcasting Company, which is like getting your news from the BBC and them telling you or. 643 01:23:14.000 --> 01:23:17.000 Yeah, I don't know. I mean, I think they're all. That way. They're all bought by somebody. 644 01:23:17.000 --> 01:23:29.000 They're all about. They're all about somebody. But this particular branch happens to be bought by their own government. But anyway, they're saying that the reason he did that, you know, Alberta, is October 19th, I think, is voting to basically leave Canada. 645 01:23:29.000 --> 01:23:34.000 Yeah. And I don't understand. How are they not. So they're under the Crown, right? Like, they're an English. 646 01:23:34.000 --> 01:23:35.000 No. 647 01:23:34.000 --> 01:23:37.000 Well, I thought this. Dude, they're not. 648 01:23:37.000 --> 01:23:43.000 They used to be, but they're in there. But the Crown, I don't think has any control over Canada any longer. Okay. 649 01:23:43.000 --> 01:23:50.000 I thought. I don't know why I thought they did because I thought they just. Like the crown appointed Carney. No. To be the. 650 01:23:50.000 --> 01:23:54.000 I don't know how their politics works because it's a different system and. 651 01:23:54.000 --> 01:23:59.000 But they can. They can they keep states from. Like Alberta from. 652 01:23:59.000 --> 01:24:03.000 Apparently not, because becoming independent will it. 653 01:24:03.000 --> 01:24:05.000 But they have all those. They got all the oil. 654 01:24:05.000 --> 01:24:06.000 Oh, yeah. 655 01:24:05.000 --> 01:24:06.000 And there's. 656 01:24:06.000 --> 01:24:07.000 It's a conservative. 657 01:24:07.000 --> 01:24:27.000 There's only two provinces. And I think there's two provinces in Canada, maybe three that are, you know, because they have equalization payments that each, you know, every. So they know. So some people, some countries, some states or province, they ship the money to Ottawa and Ottawa sends it back. 658 01:24:27.000 --> 01:24:31.000 That's why Robin Hood was out here with, like, the oil districts. 659 01:24:31.000 --> 01:24:35.000 They have equalization payments. And we have an answer. 660 01:24:35.000 --> 01:24:37.000 We do. 661 01:24:37.000 --> 01:25:10.000 Alberta cannot legally leave Canada on its own even if a majority of Albertans vote for independence. The legal framework comes mainly from their supreme court decision in 1998, which was referencing the secession of Quebec and the Federal Clarity Act. The Supreme Court held that a province has no constitutional right to secede unilaterally. However, a sufficiently clear document, democratic vote for independence would create an obligation for the other participants in the confederation to negotiate. 662 01:25:10.000 --> 01:25:13.000 So the whole nation would have to vote in favor of them leaving. 663 01:25:13.000 --> 01:25:19.000 Well, yes, but anyway, what I was going to do is Alberta, Saskatchewan, and I. And I think those the only two 664 01:25:19.000 --> 01:25:20.000 have to amend the constitution. 665 01:25:20.000 --> 01:25:26.000 They are. They are net negative on equals equalization payments. 666 01:25:26.000 --> 01:25:28.000 They give more than. 667 01:25:28.000 --> 01:25:40.000 They give more money than they get. And to the tune of some of them. It's. It's a pretty big dollar amount Canadian dollar. But I mean, it's a dollar amount. Pretty big dollar amount that they get in the other. Other provinces. So. I mean, it's odd, but. 668 01:25:40.000 --> 01:25:41.000 Well, I think cat hair. 669 01:25:41.000 --> 01:25:43.000 It's 128. 670 01:25:43.000 --> 01:25:45.000 128. 671 01:25:45.000 --> 01:25:46.000 We managed to wrap. 672 01:25:46.000 --> 01:25:48.000 We didn't even do a commercial or nothing. 673 01:25:48.000 --> 01:25:52.000 I know. We didn't even finish talking about NASA, by the way. Went to Oklahoma and Kansas and it was great. 674 01:25:52.000 --> 01:25:58.000 Okay, cool. 675 01:25:58.000 --> 01:26:06.000 But we're also doing the fly lake thing and we're doing. We're doing several things, so it was great. If anybody wants to know any more about it, we're gonna have some really great videos follow. 676 01:26:06.000 --> 01:26:08.000 Do we know who we're gonna have on next week for. 677 01:26:08.000 --> 01:26:10.000 Yes, we have. 678 01:26:10.000 --> 01:26:12.000 Is coming back. 679 01:26:12.000 --> 01:26:18.000 He is coming back, but I don't think it's till the 18th. Okay, so the 11th is Catherine. 680 01:26:18.000 --> 01:26:21.000 I'm gonna be sorry, I forgot her last name. By the way. 681 01:26:21.000 --> 01:26:26.000 She is the one that has been doing the research on soil health and produce water. 682 01:26:26.000 --> 01:26:29.000 Oh, I have to listen to that on the road. 683 01:26:29.000 --> 01:26:36.000 It's gonna be good. Yep. On the 11th. So next week. And I think Todd's coming on the 18th, so. 684 01:26:36.000 --> 01:26:47.000 Okay, then we've got. Well, I'm still efforting the fire guy, but every time, every time I get close to getting him, he gets sent somewhere else to fight another fire. 685 01:26:47.000 --> 01:26:50.000 So that's because we keep having too many fires. 686 01:26:50.000 --> 01:26:57.000 Tell you what, we got a lot of brush to burn, but you could open a whole nother can of worm. We could talk another half an hour on that. But anyway, we won't. 687 01:26:57.000 --> 01:27:00.000 So we'll see y' all next week. 688 01:27:00.000 --> 01:27:02.000 On the dry side, dispatch. 689 01:27:02.000 --> 01:27:03.000 On the dry side, dispatch. 690 01:27:03.000 --> 01:27:04.000 Yes, I water.