1 00:00:00,240 --> 00:00:03,400 Speaker 1: Now here's a highlight from Coast to Coast AM on 2 00:00:03,640 --> 00:00:05,160 Speaker 1: iHeartRadio and. 3 00:00:05,240 --> 00:00:08,360 Speaker 2: Welcome back George Noria Alongo Dala Jndo Rojas. As we 4 00:00:08,440 --> 00:00:11,879 Speaker 2: talk about this new app called Enigma from l Enigma Labs, 5 00:00:11,920 --> 00:00:15,280 Speaker 2: which gives you vital to UFO information. We'll get more 6 00:00:15,320 --> 00:00:18,079 Speaker 2: into that in the moment. Alejandro, you were talking about 7 00:00:18,160 --> 00:00:20,360 Speaker 2: NASA and astronauts. Do you get a lot of reports 8 00:00:20,400 --> 00:00:21,080 Speaker 2: from them? 9 00:00:22,120 --> 00:00:25,959 Speaker 3: We don't, unfortunately, But that is what I was alluding to, 10 00:00:26,239 --> 00:00:29,160 Speaker 3: is that, you know, I'd always ask the NASA press people. 11 00:00:29,160 --> 00:00:31,960 Speaker 3: I said, okay, if I asked the astronaut about UFOs, 12 00:00:32,200 --> 00:00:35,239 Speaker 3: because it's kind of one of my beats, and they 13 00:00:35,280 --> 00:00:38,280 Speaker 3: were always very excited. They were like, please do I'm 14 00:00:38,320 --> 00:00:40,640 Speaker 3: so curious to what they would say. So they were 15 00:00:40,800 --> 00:00:45,599 Speaker 3: always very positive about it, although unfortunately none of them 16 00:00:45,600 --> 00:00:48,160 Speaker 3: told me they had their experience. Scott Kelly did say 17 00:00:48,479 --> 00:00:50,760 Speaker 3: at one point he saw something and he was freaking 18 00:00:50,760 --> 00:00:52,440 Speaker 3: out because he thought, oh my gosh, what is that. 19 00:00:52,720 --> 00:00:56,160 Speaker 4: But then he figured out what it was and he 20 00:00:56,320 --> 00:00:58,760 Speaker 4: was like, you know, we just have those events sometimes. 21 00:01:00,080 --> 00:01:02,080 Speaker 2: Now, what do you do with the information that goes 22 00:01:02,120 --> 00:01:06,119 Speaker 2: into Enigma from the people, How do you analyze it. 23 00:01:06,920 --> 00:01:08,319 Speaker 4: Yeah, so great question. 24 00:01:08,560 --> 00:01:12,520 Speaker 3: So currently we crowdsource the analysis, so a big part 25 00:01:12,680 --> 00:01:15,960 Speaker 3: of Enigma and you can go to Enigma Labs dot io. 26 00:01:16,040 --> 00:01:18,280 Speaker 4: That's the website if you're on the laptop. 27 00:01:18,280 --> 00:01:21,280 Speaker 3: That reminded me because you guys in your advertising remind 28 00:01:21,280 --> 00:01:24,960 Speaker 3: people of the website. But what we do is if 29 00:01:25,000 --> 00:01:27,160 Speaker 3: you go to Enigma Labs dot io, you'll see there's 30 00:01:27,200 --> 00:01:29,959 Speaker 3: comments on all of the sightings and you'll see we've 31 00:01:30,000 --> 00:01:34,680 Speaker 3: created this robust community of people who are very good 32 00:01:34,720 --> 00:01:36,520 Speaker 3: at kind of analyzing and saying, hey, have. 33 00:01:36,520 --> 00:01:37,080 Speaker 4: You thought it is? 34 00:01:37,240 --> 00:01:37,319 Speaker 2: This? 35 00:01:37,560 --> 00:01:40,480 Speaker 3: Is it that we've got. Then the witness is typically 36 00:01:40,800 --> 00:01:43,200 Speaker 3: interfacing with people saying, well, I did think of it, 37 00:01:43,240 --> 00:01:45,600 Speaker 3: but I don't think it's just because of that, or 38 00:01:45,720 --> 00:01:48,440 Speaker 3: we figure out what it is. And there have been 39 00:01:48,600 --> 00:01:51,080 Speaker 3: and that's kind of exciting in itself. There have been 40 00:01:51,400 --> 00:01:55,360 Speaker 3: several things that are novel that people didn't know about 41 00:01:55,480 --> 00:02:01,040 Speaker 3: that we've been able to identify. Most for example, SpaceX, 42 00:02:01,600 --> 00:02:05,720 Speaker 3: not just the satellites themselves, which can do weird things, 43 00:02:05,960 --> 00:02:11,680 Speaker 3: but especially the spacecraft. Even just this week and Texas 44 00:02:11,720 --> 00:02:14,680 Speaker 3: we had this where one of the things that SpaceX 45 00:02:14,680 --> 00:02:17,680 Speaker 3: spacecraft will do in it it'll turn around and slow 46 00:02:17,760 --> 00:02:21,920 Speaker 3: down and it shoots this ginormous kind of halo of 47 00:02:22,720 --> 00:02:26,480 Speaker 3: It looks like kind of this spaceship, something out of 48 00:02:26,520 --> 00:02:29,720 Speaker 3: Star Wars. And people have gotten these videos and you know, 49 00:02:29,800 --> 00:02:32,160 Speaker 3: they don't know what the heck they are. I didn't neither, 50 00:02:32,280 --> 00:02:34,960 Speaker 3: but after doing some research, we were able to figure 51 00:02:34,960 --> 00:02:37,519 Speaker 3: out what it was and then inform people. So it's 52 00:02:37,560 --> 00:02:40,000 Speaker 3: really helpful that way too, because then we all get 53 00:02:40,000 --> 00:02:44,280 Speaker 3: to learn together about these things, and even pilots make mistakes. 54 00:02:44,280 --> 00:02:49,800 Speaker 3: Pilots were reporting these weird objects that were kind of 55 00:02:49,840 --> 00:02:53,320 Speaker 3: going in a circular pattern. They called them racetrack UFOs. 56 00:02:53,360 --> 00:02:57,480 Speaker 3: I got ahold of my buddy Ben Hampson, who works 57 00:02:57,520 --> 00:02:59,560 Speaker 3: with pilots a lot, and he said, yeah, I've been 58 00:02:59,600 --> 00:03:00,400 Speaker 3: getting the too. 59 00:03:01,080 --> 00:03:02,160 Speaker 4: We're researching them. 60 00:03:02,400 --> 00:03:05,840 Speaker 3: We eventually figured out that they were space like satellites. 61 00:03:05,840 --> 00:03:09,200 Speaker 3: They just looked different from aircraft, and a lot of 62 00:03:09,200 --> 00:03:11,960 Speaker 3: pilots were seeing these and thought they were UFOs. They 63 00:03:12,240 --> 00:03:15,120 Speaker 3: went on CNN I think even talking about Hey, we're 64 00:03:15,120 --> 00:03:19,560 Speaker 3: seeing these weird UFOs. They got embarrassed unfortunately, because they 65 00:03:19,600 --> 00:03:21,680 Speaker 3: were like, oh, it turned out to be starlink and 66 00:03:21,680 --> 00:03:24,239 Speaker 3: they were like really embarrassed by it. But I don't 67 00:03:24,240 --> 00:03:26,079 Speaker 3: think they should be, and I tried to say, nobody 68 00:03:26,160 --> 00:03:29,320 Speaker 3: should be. We're all learning together, and that's what's great 69 00:03:29,320 --> 00:03:33,040 Speaker 3: about our community is we're learning to analyze these sightings together, 70 00:03:33,560 --> 00:03:36,600 Speaker 3: so we're educating each other so we get better and 71 00:03:36,680 --> 00:03:39,119 Speaker 3: better videos and we're able to help each other out. 72 00:03:39,200 --> 00:03:42,800 Speaker 3: So currently we're crowd analyzing. In the future, we are 73 00:03:42,880 --> 00:03:47,040 Speaker 3: working on AI tools to be able to identify. In fact, 74 00:03:47,160 --> 00:03:51,160 Speaker 3: we have an AR camera on the app, so you 75 00:03:51,240 --> 00:03:54,840 Speaker 3: can open up the camera feature on the app and 76 00:03:55,400 --> 00:03:58,400 Speaker 3: there is a tab where it'll show you all of 77 00:03:58,400 --> 00:04:04,000 Speaker 3: the planes and astronomical objects and satellites in the sky 78 00:04:04,280 --> 00:04:06,400 Speaker 3: right where you're looking, just like all these apps do, 79 00:04:06,560 --> 00:04:09,160 Speaker 3: like flight radar and all of these others, but we've 80 00:04:09,160 --> 00:04:11,880 Speaker 3: got it all combined and our app. So if you're 81 00:04:11,880 --> 00:04:15,080 Speaker 3: seeing something, you can click to this camera and see, oh, 82 00:04:15,160 --> 00:04:20,800 Speaker 3: that's that's SpaceX or you know, that's that's some astronomical thing. 83 00:04:20,880 --> 00:04:23,240 Speaker 3: But if nothing's there, you know, then you can say, hey, 84 00:04:23,560 --> 00:04:25,040 Speaker 3: you know, I use your app. I checked there were 85 00:04:25,080 --> 00:04:26,760 Speaker 3: no planes or anything that were supposed to be in 86 00:04:26,760 --> 00:04:29,480 Speaker 3: this area where I saw this weird thing. So you know, 87 00:04:29,520 --> 00:04:31,479 Speaker 3: we've got these built in tools to help people with 88 00:04:31,520 --> 00:04:33,760 Speaker 3: the analysis to get better and. 89 00:04:33,839 --> 00:04:35,640 Speaker 4: Better at that and further on. 90 00:04:35,800 --> 00:04:38,520 Speaker 3: You know, we're hoping and we are working on AI 91 00:04:38,920 --> 00:04:41,520 Speaker 3: and teaching AI, so it will be able to do 92 00:04:41,600 --> 00:04:45,039 Speaker 3: recommendations and it probably won't be too long till we 93 00:04:45,120 --> 00:04:48,400 Speaker 3: have this out. It'll say, you know, our AI tool 94 00:04:48,480 --> 00:04:52,320 Speaker 3: says this is likely this and you know the witness 95 00:04:52,360 --> 00:04:54,520 Speaker 3: can take it or leave it, all. 96 00:04:54,440 --> 00:04:57,719 Speaker 2: Right, dear friend, Peter Davenport from the National UFO Reporting 97 00:04:57,800 --> 00:05:01,280 Speaker 2: Center started at all years ago with his reporting network 98 00:05:01,680 --> 00:05:05,160 Speaker 2: which was based primarily on the phone, and then his website. 99 00:05:05,520 --> 00:05:09,880 Speaker 2: You've taken it a step further with Enigma Labs. Congratulations exactly, 100 00:05:10,440 --> 00:05:11,240 Speaker 2: Thank you very much. 101 00:05:11,320 --> 00:05:14,920 Speaker 3: And you know, Peter was a big inspiration we used 102 00:05:14,920 --> 00:05:16,440 Speaker 3: to and I think we still have a picture of 103 00:05:16,520 --> 00:05:19,240 Speaker 3: him up in the office because you're right, you know, 104 00:05:19,320 --> 00:05:22,680 Speaker 3: he's one of the giants two shoulders we stand on, 105 00:05:22,920 --> 00:05:26,440 Speaker 3: and you know we have been in communication with him 106 00:05:26,480 --> 00:05:29,960 Speaker 3: over the time. Interesting enough, speaking of Kevin talking about Madar, 107 00:05:30,360 --> 00:05:32,960 Speaker 3: Peter Davin part thinks my Madar is the way to go. 108 00:05:33,000 --> 00:05:34,559 Speaker 3: I think he's been on your show a few times 109 00:05:34,560 --> 00:05:38,160 Speaker 3: talking about that. But yeah, I agree, and you can 110 00:05:38,200 --> 00:05:39,520 Speaker 3: see his sighting in our app. 111 00:05:39,920 --> 00:05:43,400 Speaker 4: So all of his reports, historical reports. 112 00:05:43,080 --> 00:05:45,359 Speaker 3: A lot of other organizations we've got in the app, 113 00:05:46,520 --> 00:05:50,320 Speaker 3: so people can still see those sightings. But you know, 114 00:05:50,360 --> 00:05:52,320 Speaker 3: we've been collecting a lot on our own that are 115 00:05:52,480 --> 00:05:53,720 Speaker 3: originally given to us. 116 00:05:55,240 --> 00:05:57,760 Speaker 2: How do you vet some of the reports, Alejandro, that 117 00:05:57,839 --> 00:05:58,760 Speaker 2: come through the app? 118 00:05:59,520 --> 00:06:03,080 Speaker 3: Yeah, that's another great question my kind of theory, and 119 00:06:03,320 --> 00:06:07,600 Speaker 3: with most of us were only you know, wanting to 120 00:06:07,960 --> 00:06:14,400 Speaker 3: weed out hoaxes or people trying to trick us or 121 00:06:14,480 --> 00:06:19,160 Speaker 3: being silly or something like that, because at least, you know, 122 00:06:19,279 --> 00:06:24,480 Speaker 3: a lot of the data is still valuable. So for instance, drones, 123 00:06:25,040 --> 00:06:27,359 Speaker 3: we could have just said, you know, let's not you know, 124 00:06:27,400 --> 00:06:28,680 Speaker 3: these are obviously. 125 00:06:28,360 --> 00:06:30,919 Speaker 4: Drones, some of these, let's not approve those. 126 00:06:32,520 --> 00:06:36,000 Speaker 3: But then the drone thing happened last year, and it's 127 00:06:36,040 --> 00:06:37,840 Speaker 3: a good thing that we didn't do that because we 128 00:06:37,839 --> 00:06:40,760 Speaker 3: were able to go through our databases buying you know, 129 00:06:40,920 --> 00:06:43,160 Speaker 3: in those areas tens of thousands of people who had 130 00:06:43,160 --> 00:06:46,960 Speaker 3: reported seeing drones in Jersey, and we were able to 131 00:06:46,960 --> 00:06:50,480 Speaker 3: write up some reports and share that information, which was helpful, 132 00:06:50,520 --> 00:06:52,479 Speaker 3: and you know a lot of the media shared that. 133 00:06:53,880 --> 00:06:56,839 Speaker 3: So you know, it's same with the space X stuff. 134 00:06:56,880 --> 00:06:59,120 Speaker 3: We could say, oh, you know, that's that's a satellite. 135 00:06:59,160 --> 00:07:02,719 Speaker 4: Let's not put that on the app. 136 00:07:02,720 --> 00:07:04,159 Speaker 3: But at the same time, if we don't do that, 137 00:07:04,200 --> 00:07:07,279 Speaker 3: we're not educating people on what the satellites look like 138 00:07:07,560 --> 00:07:10,880 Speaker 3: and stuff like that. So really hoaxes are the only 139 00:07:10,920 --> 00:07:14,520 Speaker 3: thing that we've vet out. Otherwise, you know, we let 140 00:07:14,520 --> 00:07:19,000 Speaker 3: people discuss and come to their own conclusions on each 141 00:07:19,000 --> 00:07:22,320 Speaker 3: of the sidings and you know, share those socially our 142 00:07:22,360 --> 00:07:22,880 Speaker 3: best ones. 143 00:07:22,880 --> 00:07:24,440 Speaker 4: And that's what I do every day. 144 00:07:24,480 --> 00:07:27,520 Speaker 3: I'm looking at these videos every day to pick out 145 00:07:27,520 --> 00:07:30,160 Speaker 3: some of our best ones to share on social media 146 00:07:30,920 --> 00:07:33,160 Speaker 3: or you know, for me to share personally, or to 147 00:07:34,440 --> 00:07:36,440 Speaker 3: me to get to people that to say, hey, this 148 00:07:36,560 --> 00:07:37,120 Speaker 3: is interesting. 149 00:07:37,160 --> 00:07:39,240 Speaker 4: I know you're working on Orange ORBES, maybe. 150 00:07:39,000 --> 00:07:41,880 Speaker 3: You'll find this one interesting to kind of hopefully keep 151 00:07:42,280 --> 00:07:44,680 Speaker 3: some scientific analysis going on out there too. 152 00:07:45,400 --> 00:07:48,280 Speaker 2: Uh, the app is relatively new, so you don't have 153 00:07:48,320 --> 00:07:51,760 Speaker 2: a lot of compelling data to compare with previous reports. 154 00:07:52,240 --> 00:07:55,360 Speaker 2: But could you say if ufour reports are on the 155 00:07:55,480 --> 00:07:56,480 Speaker 2: uptick or not? 156 00:07:57,640 --> 00:08:00,400 Speaker 3: Well, you know, I've been doing this for a really 157 00:08:00,440 --> 00:08:04,160 Speaker 3: long time. In fact, I've been doing data and reports 158 00:08:04,160 --> 00:08:06,400 Speaker 3: on siting reports for a really long time, and I 159 00:08:06,440 --> 00:08:09,920 Speaker 3: think we're pretty far from being able to really be 160 00:08:10,000 --> 00:08:13,760 Speaker 3: able to calculate that sort of thing because we haven't 161 00:08:13,840 --> 00:08:18,920 Speaker 3: had a standard, consistent reporting center. Hopefully, you know, it'd 162 00:08:18,920 --> 00:08:22,040 Speaker 3: be great if our app becomes that, but certainly the 163 00:08:22,080 --> 00:08:26,880 Speaker 3: government isn't doing that. AEROW still isn't taking public reports 164 00:08:27,520 --> 00:08:29,360 Speaker 3: for better or worse. But I think it should be 165 00:08:29,360 --> 00:08:32,560 Speaker 3: someone probably independent of the government, I guess anyway, But 166 00:08:34,240 --> 00:08:36,280 Speaker 3: I don't think we have enough data to say that. 167 00:08:37,080 --> 00:08:41,800 Speaker 3: You know, let's take Davenport for instance. His siting reports 168 00:08:41,840 --> 00:08:44,840 Speaker 3: show a lot of sidings in Washington because that's where 169 00:08:44,840 --> 00:08:49,360 Speaker 3: he was based, So there's more awareness in that that 170 00:08:49,440 --> 00:08:53,040 Speaker 3: area in the north, you know, Western United States, So 171 00:08:53,080 --> 00:08:55,840 Speaker 3: there's skewed the data is a little skewed that way, 172 00:08:56,160 --> 00:08:59,040 Speaker 3: and there's that's an example of how we just haven't 173 00:08:59,080 --> 00:09:02,520 Speaker 3: had a robust kind of international system to be able 174 00:09:02,559 --> 00:09:06,160 Speaker 3: to watch trends over a long period of time, and 175 00:09:06,200 --> 00:09:07,360 Speaker 3: that's something we need. 176 00:09:07,520 --> 00:09:10,000 Speaker 4: That's the big problem everybody was saying it. 177 00:09:10,040 --> 00:09:12,320 Speaker 3: I think NASA and a government were right when they 178 00:09:12,360 --> 00:09:15,199 Speaker 3: said a lot of the problem with this field is. 179 00:09:15,120 --> 00:09:16,720 Speaker 4: That we just don't have enough data. 180 00:09:17,160 --> 00:09:19,319 Speaker 3: Now, of course we don't know what data the government 181 00:09:19,400 --> 00:09:21,760 Speaker 3: actually has, but I don't think we're going to find 182 00:09:21,760 --> 00:09:24,440 Speaker 3: out what data the government actually has, so then it's 183 00:09:24,440 --> 00:09:28,520 Speaker 3: incumbent upon us in the public as citizen scientists or 184 00:09:29,000 --> 00:09:32,360 Speaker 3: you know, to croftsources to do it ourselves. 185 00:09:32,640 --> 00:09:33,600 Speaker 4: And that's what we're doing. 186 00:09:34,600 --> 00:09:37,240 Speaker 2: A couple of things have slowed down from years ago. 187 00:09:38,040 --> 00:09:42,840 Speaker 2: Alien of production cases are slower, crop formations and circles 188 00:09:42,880 --> 00:09:46,560 Speaker 2: are slower, and burned out spots where they used to 189 00:09:46,559 --> 00:09:50,640 Speaker 2: see burned out patches of word like a craft was hovering. 190 00:09:51,800 --> 00:09:51,839 Speaker 4: That. 191 00:09:52,960 --> 00:09:55,120 Speaker 2: We're not getting any reports like that anymore. 192 00:09:55,160 --> 00:09:56,679 Speaker 4: What do you think is going on, Alejandro? 193 00:09:57,360 --> 00:10:00,640 Speaker 3: Yeah, I think that Lee called does UFO nests if 194 00:10:00,679 --> 00:10:02,160 Speaker 3: I remember correctly. 195 00:10:01,760 --> 00:10:02,880 Speaker 4: But yeah, exactly. 196 00:10:04,200 --> 00:10:06,960 Speaker 3: You know, over the years, you do see these trends though, 197 00:10:07,000 --> 00:10:09,880 Speaker 3: you do see these waves. So for example, the seventies 198 00:10:09,880 --> 00:10:13,640 Speaker 3: and the seventies we had cases like Travis Walton or 199 00:10:13,880 --> 00:10:18,720 Speaker 3: Pascagoula fifty right where people but it was this period 200 00:10:18,800 --> 00:10:22,120 Speaker 3: of time where these people were saying they were interfacing 201 00:10:22,160 --> 00:10:25,400 Speaker 3: with these weird looking creatures. But it was only in 202 00:10:25,440 --> 00:10:27,080 Speaker 3: the seventies or a short period of time, and then 203 00:10:27,120 --> 00:10:29,000 Speaker 3: that went away and then it morphed. 204 00:10:29,760 --> 00:10:31,839 Speaker 4: So we have these waves that happen. 205 00:10:31,920 --> 00:10:34,400 Speaker 3: It seems like I think there's a few reasons that 206 00:10:34,440 --> 00:10:37,120 Speaker 3: could be if it's a real phenomena, you know, it 207 00:10:37,160 --> 00:10:40,000 Speaker 3: could be that whatever was creating that phenomena is not 208 00:10:40,120 --> 00:10:40,800 Speaker 3: here anymore. 209 00:10:41,160 --> 00:10:43,680 Speaker 4: You're only here for a certain period of time. 210 00:10:44,120 --> 00:10:47,640 Speaker 3: Some people believe that, you know, maybe there's different civilizations 211 00:10:47,640 --> 00:10:51,720 Speaker 3: coming in different waves, or you know it Also some people, 212 00:10:51,800 --> 00:10:55,839 Speaker 3: the skeptics, would argue that, you know, those events were 213 00:10:55,840 --> 00:10:58,959 Speaker 3: actually influenced by the media or by movies, and that's 214 00:10:59,000 --> 00:11:01,199 Speaker 3: why we had them only in waves. 215 00:11:01,559 --> 00:11:03,600 Speaker 4: So it's hard to say, but you're exactly right. 216 00:11:03,679 --> 00:11:07,800 Speaker 3: I think that, you know, we do have these waves, 217 00:11:08,040 --> 00:11:11,800 Speaker 3: and it is really strange where there'll be times of 218 00:11:11,840 --> 00:11:15,720 Speaker 3: abundance and the two you mentioned, crep circles and abductions. 219 00:11:16,440 --> 00:11:18,720 Speaker 4: It seems like those are waves that come and go. 220 00:11:20,000 --> 00:11:22,360 Speaker 3: That you know, you'll have these kind of periods of 221 00:11:22,360 --> 00:11:24,040 Speaker 3: time where you'll get a lot more of that and 222 00:11:24,040 --> 00:11:26,120 Speaker 3: then it'll kind of subside like it is right now. 223 00:11:26,760 --> 00:11:28,600 Speaker 4: How did you get involved in this alehundra? 224 00:11:28,800 --> 00:11:31,640 Speaker 2: Was there one case, one story that captured your attention? 225 00:11:34,960 --> 00:11:38,959 Speaker 4: Great question. It wasn't necessarily one case. 226 00:11:39,760 --> 00:11:42,760 Speaker 3: So it's kind of funny story because I really it 227 00:11:42,840 --> 00:11:47,360 Speaker 3: was when I was a journalism student I saw that 228 00:11:47,440 --> 00:11:51,440 Speaker 3: there were a lot of credible people talking about this topic, 229 00:11:51,480 --> 00:11:54,000 Speaker 3: and I was, you know, I've always been interested in 230 00:11:54,120 --> 00:11:58,280 Speaker 3: science in space, so I watch all of the specials, 231 00:11:58,320 --> 00:12:02,679 Speaker 3: whether they are back then, you know UFOs or you 232 00:12:02,720 --> 00:12:06,839 Speaker 3: know what the astronauts were up to. I'm watching all 233 00:12:06,880 --> 00:12:09,640 Speaker 3: of these and you know, my friend who got me 234 00:12:09,679 --> 00:12:12,920 Speaker 3: into journalism, her boyfriend was really into UFOs and he 235 00:12:12,960 --> 00:12:14,840 Speaker 3: started telling me these stories and I thought he was 236 00:12:14,880 --> 00:12:15,240 Speaker 3: full of it. 237 00:12:15,280 --> 00:12:17,760 Speaker 4: I thought he was ridiculous, and I got really frustrated. 238 00:12:18,080 --> 00:12:20,120 Speaker 3: But when I looked into it, I was like, you're right, 239 00:12:20,200 --> 00:12:24,440 Speaker 3: why aren't these stories being told, whether they're true or not. 240 00:12:24,600 --> 00:12:28,400 Speaker 3: If these important people are claiming these incredible things, that's 241 00:12:28,440 --> 00:12:33,000 Speaker 3: a news story. So I started writing about it back then, 242 00:12:33,240 --> 00:12:36,360 Speaker 3: so that's like what twenty five years ago or something 243 00:12:36,400 --> 00:12:39,200 Speaker 3: like that. Luckily, I was in Colorado, which was the 244 00:12:39,240 --> 00:12:44,360 Speaker 3: headquarters of Muffan, and eventually, after I read most of 245 00:12:44,400 --> 00:12:46,439 Speaker 3: the books I wanted to read that I could get 246 00:12:46,440 --> 00:12:48,400 Speaker 3: my hands on, I was like, you know, now it's 247 00:12:48,440 --> 00:12:50,320 Speaker 3: time to do some field work and start to talk 248 00:12:50,320 --> 00:12:53,480 Speaker 3: to people. And luckily I got to be part of 249 00:12:53,520 --> 00:12:56,679 Speaker 3: headquarters and very soon after that I was doing you know, 250 00:12:56,760 --> 00:12:58,480 Speaker 3: pr for them and everything else. 251 00:12:58,559 --> 00:13:01,400 Speaker 4: So that's how I got involved. 252 00:13:02,400 --> 00:13:05,560 Speaker 2: Look Magazine when they wrote the Interrupted Journey, the Barney 253 00:13:05,559 --> 00:13:08,000 Speaker 2: and Betty Hill case when I was a kid, that 254 00:13:08,120 --> 00:13:08,920 Speaker 2: got me hooked. 255 00:13:10,640 --> 00:13:12,679 Speaker 4: I can see why great case. 256 00:13:13,600 --> 00:13:15,640 Speaker 2: One of the best. See, we don't have those, but 257 00:13:15,720 --> 00:13:17,079 Speaker 2: we don't have those anymore. 258 00:13:17,880 --> 00:13:21,040 Speaker 4: I know we don't, and that's where I'm hoping that 259 00:13:21,120 --> 00:13:23,480 Speaker 4: for though. You know, with the app. 260 00:13:23,559 --> 00:13:27,800 Speaker 3: This was a really cool when I talked about earlier 261 00:13:27,840 --> 00:13:31,080 Speaker 3: about Texas and there was a SpaceX thing that happened 262 00:13:31,080 --> 00:13:34,200 Speaker 3: where people, you know, the spacecraft turned around and it 263 00:13:34,240 --> 00:13:38,720 Speaker 3: made this big thing. We got dozens of reports of 264 00:13:38,760 --> 00:13:42,360 Speaker 3: that thing over Texas and that got me really excited 265 00:13:42,400 --> 00:13:44,160 Speaker 3: because right now I'm in Arizona. 266 00:13:44,160 --> 00:13:45,679 Speaker 4: I spent a lot of time in Phoenix. 267 00:13:45,720 --> 00:13:48,680 Speaker 3: In fact, I'm looking at a model of the Phoenix 268 00:13:48,760 --> 00:13:51,400 Speaker 3: Lights that I created. It's like three feet it's really big. 269 00:13:51,760 --> 00:13:57,600 Speaker 3: But if the Phoenix Lights had happened today, with the 270 00:13:57,640 --> 00:14:01,320 Speaker 3: proliferation of our app as it is, we would have 271 00:14:01,640 --> 00:14:03,240 Speaker 3: a ton of data. 272 00:14:02,840 --> 00:14:03,480 Speaker 4: On that thing. 273 00:14:03,520 --> 00:14:08,360 Speaker 3: We would have a bunch of videos from different directions. Actually, 274 00:14:08,400 --> 00:14:13,040 Speaker 3: we've already built a triangulation tool to be prepared for. 275 00:14:12,960 --> 00:14:13,880 Speaker 4: An event like this. 276 00:14:14,640 --> 00:14:18,280 Speaker 3: And so I'm really excited that should that happen again, 277 00:14:18,960 --> 00:14:21,640 Speaker 3: which I think it will. You know, I think that 278 00:14:21,800 --> 00:14:24,240 Speaker 3: with our app, we're poised to gather a lot of 279 00:14:24,320 --> 00:14:27,320 Speaker 3: data and figure this thing out. So I'm excited that 280 00:14:27,480 --> 00:14:32,360 Speaker 3: win a big event. You know, Nick Pope says UFOs 281 00:14:32,400 --> 00:14:34,960 Speaker 3: are events led, and I think he's exactly right. You know, 282 00:14:35,200 --> 00:14:38,040 Speaker 3: like you said, it's Benning Barty Hill of Phoenix Lights. 283 00:14:38,360 --> 00:14:41,880 Speaker 3: It's these events that occur that get everybody excited limics 284 00:14:42,000 --> 00:14:44,680 Speaker 3: when it comes to our current kind of fascination with 285 00:14:44,760 --> 00:14:48,840 Speaker 3: this this topic. So events will happen. We just got 286 00:14:48,880 --> 00:14:51,200 Speaker 3: to be ready for it. And now with our app, 287 00:14:51,240 --> 00:14:51,800 Speaker 3: we're ready. 288 00:14:52,240 --> 00:14:55,520 Speaker 1: Listen to more Coast to Coast AM every weeknight at 289 00:14:55,520 --> 00:14:58,480 Speaker 1: one a m. Eastern and go to Coast to coastam 290 00:14:58,520 --> 00:14:59,600 Speaker 1: dot com for more