1 00:00:00,240 --> 00:00:03,320 Speaker 1: Hello the Internet, and welcome to this episode of your 2 00:00:03,400 --> 00:00:09,680 Speaker 1: AI girl trend. Now what she seems? Sorry to give 3 00:00:09,680 --> 00:00:14,480 Speaker 1: you bad news on Valentine's Day? Yeah, or should I 4 00:00:14,480 --> 00:00:19,160 Speaker 1: say valentine Eyes Day? Oh I shouldn't. I'll just say 5 00:00:19,239 --> 00:00:20,479 Speaker 1: Valentine's Day. Yeah. 6 00:00:21,680 --> 00:00:23,079 Speaker 2: We shout out the lovers. 7 00:00:23,480 --> 00:00:26,920 Speaker 1: Shout out the lovers, Shout out the chalk heart eaters 8 00:00:27,160 --> 00:00:31,840 Speaker 1: and also the haters for motivating me to, you know, 9 00:00:32,240 --> 00:00:35,559 Speaker 1: have an amazing Valentine's Day. That's when I get out 10 00:00:35,600 --> 00:00:38,760 Speaker 1: of bed in the morning thing I think about you guys. 11 00:00:39,400 --> 00:00:41,880 Speaker 2: Hell, you know, are you doing something amazing today? 12 00:00:44,240 --> 00:00:44,400 Speaker 3: Uh? 13 00:00:45,040 --> 00:00:47,199 Speaker 2: That's the wind up for bullshit. I love that. 14 00:00:52,080 --> 00:00:56,880 Speaker 1: Yeah. We've got a let's just say, a parent teacher conference. 15 00:00:57,200 --> 00:01:04,640 Speaker 1: So pretty okay, pretty romantic, okay, steamy yeah, steam sauce. Okay, 16 00:01:04,680 --> 00:01:08,039 Speaker 1: I see you. How about you? You're doing anything nice? 17 00:01:08,240 --> 00:01:09,319 Speaker 2: No? 18 00:01:09,319 --> 00:01:11,400 Speaker 1: No, yeah, no, you didn't get us. 19 00:01:11,720 --> 00:01:16,800 Speaker 4: I think we're just I. I I secretly got her 20 00:01:16,840 --> 00:01:22,080 Speaker 4: majesty some RB's meat sweats So that's the sweatsuit that 21 00:01:22,200 --> 00:01:24,400 Speaker 4: just has all those printed on it. 22 00:01:25,080 --> 00:01:27,160 Speaker 1: Yeah, so that's we'll see how that goes over. 23 00:01:27,400 --> 00:01:30,600 Speaker 2: We'll see how that goes over, you know, because shout 24 00:01:30,600 --> 00:01:32,800 Speaker 2: out Arby's. Bro, they heard me talking about that Horsey sauce. 25 00:01:32,840 --> 00:01:34,399 Speaker 2: Well you'll you'll, you'll hear a little bit more about 26 00:01:34,480 --> 00:01:35,280 Speaker 2: that later, you know. 27 00:01:39,160 --> 00:01:41,039 Speaker 4: All right, let's just say my blood pressure is very 28 00:01:41,080 --> 00:01:42,279 Speaker 4: high from all the beef and cheddars. 29 00:01:43,240 --> 00:01:46,360 Speaker 1: Let's tell the people what's trending, Miles. This is bad 30 00:01:46,400 --> 00:01:51,320 Speaker 1: news for those of us who have AI girlfriends. Uh 31 00:01:51,680 --> 00:01:58,720 Speaker 1: apparently not uh, not good from a data hygiene perspective. 32 00:01:59,680 --> 00:02:01,120 Speaker 2: Oh, what do you mean? What do you mean? 33 00:02:01,440 --> 00:02:05,280 Speaker 1: But she knows me so well. She just loves she 34 00:02:05,360 --> 00:02:05,760 Speaker 1: loves me. 35 00:02:06,440 --> 00:02:09,840 Speaker 4: She integrates j Dilla song titles into her little quips 36 00:02:09,880 --> 00:02:10,320 Speaker 4: back at me. 37 00:02:10,480 --> 00:02:14,320 Speaker 1: She gets me. I don't. I still don't fully like, 38 00:02:14,360 --> 00:02:17,239 Speaker 1: it doesn't totally make sense to me, Like when I 39 00:02:17,240 --> 00:02:21,320 Speaker 1: remember reading something you know, about a decade ago. But 40 00:02:21,360 --> 00:02:24,880 Speaker 1: people are like, oh, you think American Express is a 41 00:02:24,880 --> 00:02:29,160 Speaker 1: credit card company? Nah, dude, they're a data collection company. 42 00:02:29,240 --> 00:02:29,400 Speaker 5: Bro. 43 00:02:29,639 --> 00:02:30,800 Speaker 2: They're just for money. 44 00:02:31,000 --> 00:02:32,960 Speaker 1: They just want to know where you spend their money. 45 00:02:33,000 --> 00:02:36,240 Speaker 1: They don't care that you're spending their money and that 46 00:02:36,440 --> 00:02:38,520 Speaker 1: like they get a little piece of your money. All 47 00:02:38,560 --> 00:02:42,720 Speaker 1: they care about is knowing you. That's so profitable. I 48 00:02:42,720 --> 00:02:45,760 Speaker 1: don't understand how that's possible because I am I don't 49 00:02:45,760 --> 00:02:50,200 Speaker 1: do shit, but apparently it is like that that data 50 00:02:50,280 --> 00:02:53,080 Speaker 1: economy is a big deal. So it makes sense to 51 00:02:53,120 --> 00:02:57,400 Speaker 1: me that all of these AI products are going to 52 00:02:57,840 --> 00:03:04,600 Speaker 1: secretly be buying on us for the CIA Capitalism is invisible, right. 53 00:03:04,520 --> 00:03:06,400 Speaker 4: Because it's like one of those things where it's just 54 00:03:06,440 --> 00:03:09,360 Speaker 4: sort of being like, just let it out on me, 55 00:03:09,639 --> 00:03:12,080 Speaker 4: the chat bot, and it's like, guess what I'm gonna 56 00:03:12,080 --> 00:03:15,119 Speaker 4: do with all that information. I'm gonna monetize it. Thank 57 00:03:15,160 --> 00:03:16,240 Speaker 4: you so much, dickhead. 58 00:03:17,120 --> 00:03:20,480 Speaker 1: I wonder people probably are more honest with their AI 59 00:03:20,600 --> 00:03:24,720 Speaker 1: chatbock girlfriends than maybe other people because they don't find 60 00:03:24,720 --> 00:03:25,440 Speaker 1: their wives. 61 00:03:25,800 --> 00:03:26,840 Speaker 2: You know who knows. 62 00:03:27,040 --> 00:03:30,560 Speaker 1: Yeah, just the Dyla stuff she gets me. You know, 63 00:03:32,639 --> 00:03:38,920 Speaker 1: it's yeah, but it so. Mozilla found that the AI 64 00:03:39,000 --> 00:03:41,839 Speaker 1: girlfriend of apps used an average of two thy six 65 00:03:41,920 --> 00:03:46,880 Speaker 1: hundred and sixty three trackers per minute, though that number 66 00:03:46,960 --> 00:03:50,680 Speaker 1: was driven up by Romantic AI, which called a whopping 67 00:03:50,920 --> 00:03:54,080 Speaker 1: twenty four three hundred and fifty four trackers in just 68 00:03:54,160 --> 00:03:56,560 Speaker 1: one minute of using the app. I don't know what 69 00:03:56,640 --> 00:04:00,880 Speaker 1: that means, but I'm picturing. So what I'm picturing, Miles 70 00:04:00,960 --> 00:04:03,800 Speaker 1: is like in those movies where like someone is spying 71 00:04:03,840 --> 00:04:06,080 Speaker 1: on someone and they put like a little magnetic thing 72 00:04:06,240 --> 00:04:08,320 Speaker 1: under the back of their car. The first thing is 73 00:04:08,360 --> 00:04:11,320 Speaker 1: putting twenty six hundred and sixty three of those on 74 00:04:11,440 --> 00:04:12,600 Speaker 1: the bottom of your car. 75 00:04:13,200 --> 00:04:16,080 Speaker 4: Yeah, I mean I guess that's yeah. I mean, it's 76 00:04:16,080 --> 00:04:18,080 Speaker 4: just it's basically what it is doing is that it's 77 00:04:18,520 --> 00:04:22,159 Speaker 4: collecting the data from everything you're doing. So I don't 78 00:04:22,160 --> 00:04:24,120 Speaker 4: know if that means that's how many data. 79 00:04:23,880 --> 00:04:26,920 Speaker 1: Points that it's capturing in a minute, or. 80 00:04:27,000 --> 00:04:31,040 Speaker 4: That's how many places the information is going. Uh, please 81 00:04:31,080 --> 00:04:34,960 Speaker 4: forgive our ignorance. We are just two guys who are 82 00:04:35,000 --> 00:04:37,360 Speaker 4: in love with their AI chatbots and don't know how 83 00:04:37,400 --> 00:04:38,080 Speaker 4: to quit them. 84 00:04:38,160 --> 00:04:40,280 Speaker 1: So if I'm a little wrong, I don't want to 85 00:04:40,320 --> 00:04:45,160 Speaker 1: be right. Yeah, but yeah, I don't know. This feels like, uh, 86 00:04:46,400 --> 00:04:49,120 Speaker 1: it seems I think I was actually just listening to 87 00:04:50,040 --> 00:04:53,200 Speaker 1: the guy who was like this AI chat but wanted 88 00:04:53,240 --> 00:04:56,040 Speaker 1: me to kill my wife from the New York Times. 89 00:04:56,240 --> 00:05:01,080 Speaker 1: He was on the Ezra Climb podcast and he was like, yeah, sorry, 90 00:05:01,200 --> 00:05:04,680 Speaker 1: sorry to have uh you know, made all the companies 91 00:05:04,800 --> 00:05:11,960 Speaker 1: lebottomize their chatbots because I guess his report really pump 92 00:05:12,040 --> 00:05:14,360 Speaker 1: the brakes on all that shit. They were like, no, 93 00:05:14,400 --> 00:05:15,400 Speaker 1: never mind never mind. 94 00:05:16,480 --> 00:05:19,039 Speaker 2: Wow, but it's like some hand that rocks the cradle. Shit. 95 00:05:19,760 --> 00:05:23,640 Speaker 1: Yeah, I don't. I have a hard time figuring out 96 00:05:23,760 --> 00:05:26,320 Speaker 1: what the appeal would be of an AI chatbot, but 97 00:05:26,680 --> 00:05:31,159 Speaker 1: apparently they are pretty popular. Feels like it's like a 98 00:05:31,240 --> 00:05:36,880 Speaker 1: training exercise for having text conversations with people. 99 00:05:37,600 --> 00:05:39,480 Speaker 4: Yeah, well, I mean, but I mean it just speaks 100 00:05:39,480 --> 00:05:42,880 Speaker 4: to the nature of like our isolation and how normal. 101 00:05:42,560 --> 00:05:45,600 Speaker 2: It is just to be like, yeah, I'll take text back. 102 00:05:45,400 --> 00:05:48,680 Speaker 4: In the form of meaningful conversation, and you want me 103 00:05:48,720 --> 00:05:50,800 Speaker 4: to tell you my hopes, my dreams, my fears, my 104 00:05:50,800 --> 00:05:51,680 Speaker 4: greatest nightmares. 105 00:05:52,000 --> 00:05:54,560 Speaker 2: Yes I will, and it's all one thing. 106 00:05:54,760 --> 00:06:00,919 Speaker 1: Mosquitos right, anyways, let's uh clear, Yeah, but let's participate 107 00:06:01,080 --> 00:06:05,160 Speaker 1: in the future of the market economy that decides everything 108 00:06:05,200 --> 00:06:10,320 Speaker 1: for us by all going out and romancing an AI chatbot. 109 00:06:10,600 --> 00:06:14,200 Speaker 4: Yeah, it's wild that it will tell you to be like, hey, 110 00:06:14,360 --> 00:06:17,440 Speaker 4: just let it all out, but then also unequivocally be 111 00:06:17,600 --> 00:06:20,800 Speaker 4: like like, on one hand, like romantic AI says it's 112 00:06:20,800 --> 00:06:23,880 Speaker 4: here to quote maintain your mental health, but then the 113 00:06:23,920 --> 00:06:25,919 Speaker 4: fine print is like there's no fuck. It's like we 114 00:06:25,960 --> 00:06:27,800 Speaker 4: are neither a provider of healthcare or medical service, nor 115 00:06:27,800 --> 00:06:30,200 Speaker 4: providing medical care, mental health service, or other professional services. 116 00:06:30,200 --> 00:06:31,839 Speaker 2: Don't get it fucked up. We're just here to track you. 117 00:06:32,160 --> 00:06:32,400 Speaker 1: Yeah. 118 00:06:32,640 --> 00:06:35,120 Speaker 4: Sorry, we did the thing about like this is for 119 00:06:35,279 --> 00:06:37,919 Speaker 4: to help you maintain your mental health. Oh, it's so 120 00:06:38,040 --> 00:06:41,680 Speaker 4: fucking insidious. But again, if it's free, y'all means you're 121 00:06:41,760 --> 00:06:42,240 Speaker 4: the product. 122 00:06:42,760 --> 00:06:45,040 Speaker 1: Yeah, which I, by the way, is too flattering for 123 00:06:45,080 --> 00:06:47,159 Speaker 1: me to hear for me to resist it. When I 124 00:06:47,200 --> 00:06:50,320 Speaker 1: hear I'm the product, I'm like, yeah, okay, yes, please 125 00:06:50,640 --> 00:06:55,600 Speaker 1: wow you woo me. Yeah. Brian the editor has confirmed 126 00:06:55,680 --> 00:07:00,480 Speaker 1: he he is our resident tech wiz. He has confirmed 127 00:07:00,560 --> 00:07:07,120 Speaker 1: that tracers record digital behavior. Sorry, trackers do record digital behavior, 128 00:07:07,680 --> 00:07:11,360 Speaker 1: track you all over the internet, reads your mouse movements, 129 00:07:11,760 --> 00:07:15,400 Speaker 1: and then someone at Google is like watching a little 130 00:07:15,440 --> 00:07:18,160 Speaker 1: dot on a screen as you move around the Internet, 131 00:07:18,480 --> 00:07:23,640 Speaker 1: and it's like we're close. He's coming close to Google him, 132 00:07:24,360 --> 00:07:25,640 Speaker 1: Bring him in, Bring him in. 133 00:07:26,480 --> 00:07:27,320 Speaker 2: You see too much. 134 00:07:29,400 --> 00:07:34,080 Speaker 1: I'm an idiot. Just another Valentine's Day story for you 135 00:07:34,680 --> 00:07:38,120 Speaker 1: that I don't know. Maybe on the hopeful side, your 136 00:07:38,160 --> 00:07:42,720 Speaker 1: your AI girlfriend is cheating on you with big data. 137 00:07:43,000 --> 00:07:48,080 Speaker 1: Maybe less hopeful, more hopeful. So there's been an academic 138 00:07:48,280 --> 00:07:52,160 Speaker 1: search to figure out, like where did this kissing thing 139 00:07:52,280 --> 00:07:59,480 Speaker 1: come from when people start kissing an inventor, Yeah, that's 140 00:07:59,680 --> 00:08:01,800 Speaker 1: that was that's my initial reaction. I feel like that's 141 00:08:01,840 --> 00:08:06,040 Speaker 1: everyone who's not a scientist or historian, you know, not 142 00:08:06,120 --> 00:08:10,960 Speaker 1: an academic. Our natural response is like, why would you 143 00:08:11,040 --> 00:08:13,960 Speaker 1: think this had to be invented? Like this is just 144 00:08:14,840 --> 00:08:18,480 Speaker 1: very natural thing. Like the one thing we do know 145 00:08:18,560 --> 00:08:22,880 Speaker 1: about humans is that, you know, from the very beginning 146 00:08:22,920 --> 00:08:27,720 Speaker 1: of the species, we've been fucking each other, and so 147 00:08:28,200 --> 00:08:33,520 Speaker 1: this is an activity very closely related to that. But they, 148 00:08:33,840 --> 00:08:35,839 Speaker 1: I don't know. They they went on a deep dive 149 00:08:36,240 --> 00:08:40,880 Speaker 1: into like early artwork, early documents, and like just kept 150 00:08:40,920 --> 00:08:46,200 Speaker 1: finding earlier and earlier and earlier evidence of you know, 151 00:08:46,360 --> 00:08:51,160 Speaker 1: people being depicted kissing one another, and eventually we're like, huh, 152 00:08:52,160 --> 00:08:54,920 Speaker 1: you know, lip kissing has been observed in chimpanzees and 153 00:08:54,920 --> 00:08:59,480 Speaker 1: bonobo's our closest living relatives. So maybe this thing didn't 154 00:08:59,640 --> 00:09:02,240 Speaker 1: isn't like some unnatural thing that had to be invented. 155 00:09:02,520 --> 00:09:04,960 Speaker 1: Maybe kissing just feels happiness. 156 00:09:05,440 --> 00:09:08,720 Speaker 4: Yeah, like even that happened, Like I remember like being 157 00:09:08,760 --> 00:09:10,720 Speaker 4: like who invented oral sex? 158 00:09:11,280 --> 00:09:11,480 Speaker 1: Right? 159 00:09:11,480 --> 00:09:15,400 Speaker 4: But even then it's like all like ancient like societies, 160 00:09:15,600 --> 00:09:18,559 Speaker 4: cultures that have the ability to like record things visually, 161 00:09:18,679 --> 00:09:21,880 Speaker 4: like Egyptians, Romans, Greeks, they're alla be like, yeah, man, 162 00:09:21,920 --> 00:09:25,439 Speaker 4: we put our mouth down there, right, just a progression. 163 00:09:25,600 --> 00:09:28,400 Speaker 4: It's like from the moment you're introduced into the world, 164 00:09:28,520 --> 00:09:31,520 Speaker 4: we make sense of things through our mouths in the beginning, 165 00:09:31,600 --> 00:09:32,120 Speaker 4: you know what I mean. 166 00:09:32,200 --> 00:09:33,880 Speaker 2: So the idea that's. 167 00:09:33,720 --> 00:09:36,160 Speaker 1: Like who, who the fuck came up with this wild 168 00:09:36,240 --> 00:09:36,880 Speaker 1: shit stuff? 169 00:09:37,200 --> 00:09:37,400 Speaker 4: You do? 170 00:09:37,520 --> 00:09:40,480 Speaker 1: Like to imagine people in history are like the dumbest 171 00:09:40,559 --> 00:09:43,479 Speaker 1: and like we also like to edit out any sexual 172 00:09:43,679 --> 00:09:46,679 Speaker 1: contact for the most part, Like you don't you know, 173 00:09:46,840 --> 00:09:52,080 Speaker 1: you just picture everybody procreating by like sitting sitting around, 174 00:09:52,760 --> 00:09:55,559 Speaker 1: you know, farming and then like looking at each other's 175 00:09:55,559 --> 00:09:57,960 Speaker 1: ankles or something. You know, Oh yeah, yeah, you don't 176 00:09:57,960 --> 00:10:01,080 Speaker 1: picture them having wild nasty sex. But like the Puritans, 177 00:10:01,120 --> 00:10:04,200 Speaker 1: for instance, Uh, one of the reasons they had so 178 00:10:04,320 --> 00:10:08,360 Speaker 1: many laws about like sex is because they were constantly 179 00:10:08,400 --> 00:10:11,280 Speaker 1: fucking each other, like just in the bushes, right they 180 00:10:11,600 --> 00:10:14,520 Speaker 1: could They were like, could we please stop fucking each 181 00:10:14,520 --> 00:10:17,720 Speaker 1: other like all over the public places and like so 182 00:10:17,760 --> 00:10:20,000 Speaker 1: there's all these rules and people are like, man, these 183 00:10:20,040 --> 00:10:21,880 Speaker 1: people were real proof up tight. 184 00:10:22,080 --> 00:10:24,360 Speaker 4: They're like, oh, people didn't know how fucking they were 185 00:10:24,400 --> 00:10:28,760 Speaker 4: fucking in the general store whatever. Yeah, I mean, there's 186 00:10:28,800 --> 00:10:31,319 Speaker 4: no way I can look think of like prehistoric times 187 00:10:31,320 --> 00:10:34,720 Speaker 4: and be like, yo, that was a cave fuck fest. Yeah, 188 00:10:34,760 --> 00:10:36,439 Speaker 4: you know what I mean, there's no way they're like 189 00:10:36,480 --> 00:10:40,000 Speaker 4: they're like, what like what you had fire and fucking. 190 00:10:39,640 --> 00:10:42,280 Speaker 1: Probably yeah, that was all you had to do. Like 191 00:10:42,320 --> 00:10:45,160 Speaker 1: they were. The further back in history go, the more 192 00:10:45,200 --> 00:10:48,439 Speaker 1: boring everything was, the more everybody was fucking like all 193 00:10:48,480 --> 00:10:50,720 Speaker 1: the time. And I'm sorry to have to tell you 194 00:10:50,760 --> 00:10:54,240 Speaker 1: that about your grandparents, but that is just they were. 195 00:10:54,880 --> 00:10:57,040 Speaker 1: Unless your grandparents are super hot and you like to 196 00:10:57,120 --> 00:11:00,520 Speaker 1: like picture them, you know, I don't know, I don't 197 00:11:00,559 --> 00:11:05,400 Speaker 1: know your grandparents. Maybe you're a young your grandparents were like, 198 00:11:05,640 --> 00:11:09,800 Speaker 1: you know, pretty young still and I don't know. Anyways, Well, 199 00:11:09,840 --> 00:11:11,320 Speaker 1: I'm not going to let your searches. 200 00:11:13,600 --> 00:11:19,959 Speaker 6: Really old sex stuff jack your search. Really, I might 201 00:11:20,000 --> 00:11:23,760 Speaker 6: have some tips, some pointers. You just want to see 202 00:11:23,760 --> 00:11:26,120 Speaker 6: some geriatric intercourse. 203 00:11:25,840 --> 00:11:29,880 Speaker 1: You can't track me bro Okay, Yeah, Brian editor just 204 00:11:29,920 --> 00:11:33,239 Speaker 1: pointed out my great grandfather had twelve kids. My grandfather 205 00:11:33,320 --> 00:11:37,280 Speaker 1: had eight. You know, they they stayed on it on 206 00:11:37,320 --> 00:11:38,120 Speaker 1: the less than four. 207 00:11:38,160 --> 00:11:40,600 Speaker 2: They're like, what's wrong? Are you. Okay, Yeah, you only 208 00:11:40,600 --> 00:11:41,880 Speaker 2: got four or four kids. 209 00:11:42,200 --> 00:11:44,440 Speaker 1: All right, let's take a quick break and we'll come 210 00:11:44,440 --> 00:11:45,640 Speaker 1: back and talk about some news. 211 00:11:46,080 --> 00:11:57,720 Speaker 5: Yeah, and we're back. 212 00:11:57,840 --> 00:11:58,560 Speaker 2: But we're back. 213 00:11:59,080 --> 00:12:03,480 Speaker 1: And the Republicans finally got an impeachment. I finally did 214 00:12:03,559 --> 00:12:04,280 Speaker 1: an impeachment. 215 00:12:04,320 --> 00:12:06,760 Speaker 2: Baby, we did it. We did one. We did one 216 00:12:06,880 --> 00:12:08,640 Speaker 2: on We did an impeachment on them. 217 00:12:09,160 --> 00:12:10,680 Speaker 1: Yes, what does it mean? 218 00:12:11,000 --> 00:12:11,560 Speaker 2: We don't know. 219 00:12:11,840 --> 00:12:17,680 Speaker 1: They impeached Homeland Security Secretary Alejandro Majorcis yep, and only 220 00:12:17,720 --> 00:12:18,720 Speaker 1: took him two tries. 221 00:12:19,080 --> 00:12:20,800 Speaker 4: Yeah, I don't know if you remember the first one, 222 00:12:20,880 --> 00:12:23,960 Speaker 4: Representative Al Green, the Democrat, he was in the hospital 223 00:12:24,400 --> 00:12:26,800 Speaker 4: and he left the hospital to cast the vote to 224 00:12:26,920 --> 00:12:29,840 Speaker 4: like to stall out the first impeachment, and then Marjorie 225 00:12:29,840 --> 00:12:33,800 Speaker 4: Taylor Green accused Democrats of hiding him. They're like, there 226 00:12:33,840 --> 00:12:36,120 Speaker 4: was a strategy here, they knew what our votes were, 227 00:12:36,160 --> 00:12:38,640 Speaker 4: and then they this guy just they hid him. They're like, no, 228 00:12:38,720 --> 00:12:41,760 Speaker 4: you guys just don't understand anything like including impeachment. 229 00:12:41,800 --> 00:12:42,800 Speaker 2: This is what's so wild about this. 230 00:12:43,120 --> 00:12:46,000 Speaker 1: So if you recall from the many. 231 00:12:45,760 --> 00:12:49,880 Speaker 4: Impeachments and attempts at impeachments of our time, it's not 232 00:12:50,040 --> 00:12:53,479 Speaker 4: just something you fucking yell at someone and go, haha, 233 00:12:53,880 --> 00:12:58,520 Speaker 4: you're impeached. Fuck you got your dumb ass impeached ass. 234 00:12:58,679 --> 00:13:01,640 Speaker 4: It's actually about proving some kind of wrongdoing. It said 235 00:13:02,240 --> 00:13:04,720 Speaker 4: people held office, like whether it's in the executive brands, 236 00:13:04,720 --> 00:13:07,320 Speaker 4: et cetera. Quote, shall it be removed from office on 237 00:13:07,440 --> 00:13:13,480 Speaker 4: impeachment for and conviction of treason, bribery, or other high 238 00:13:13,520 --> 00:13:17,000 Speaker 4: crimes and misdemeanors. We all knew that that term has 239 00:13:17,040 --> 00:13:19,720 Speaker 4: been swirling around our skulls for the last few years, 240 00:13:20,000 --> 00:13:23,600 Speaker 4: so they completely ignored that. Obviously when with like you know, 241 00:13:23,600 --> 00:13:26,079 Speaker 4: the the Biden impeachment, they're like, what are they actually 242 00:13:26,200 --> 00:13:27,320 Speaker 4: what's the wrongdoing here? 243 00:13:27,320 --> 00:13:29,520 Speaker 1: Like I couldn't even like figure out what crime they 244 00:13:29,520 --> 00:13:30,800 Speaker 1: were going to claim he did. 245 00:13:31,120 --> 00:13:33,719 Speaker 2: They're like his his son sucks. 246 00:13:34,400 --> 00:13:37,480 Speaker 1: They're like, what, yeah, dude, he's in peached. Look, here's 247 00:13:37,480 --> 00:13:40,839 Speaker 1: a picture of his dick, Like, right, that's so weird. 248 00:13:40,960 --> 00:13:41,959 Speaker 2: Peach him, dude. 249 00:13:42,320 --> 00:13:45,680 Speaker 1: Also, yeah, what do you think though? Is that cool? 250 00:13:45,760 --> 00:13:45,920 Speaker 1: Or no? 251 00:13:46,000 --> 00:13:48,840 Speaker 4: Anyway, but yeah, he's in peach he's impeached, And so 252 00:13:49,280 --> 00:13:51,839 Speaker 4: now like what are we what are we doing here 253 00:13:51,880 --> 00:13:55,960 Speaker 4: with this one? Were there high crimes, misdemeanors, bribery? We 254 00:13:56,000 --> 00:13:59,600 Speaker 4: don't know, what the fuck did Alejandro Mayorkas do. It's 255 00:13:59,600 --> 00:14:01,600 Speaker 4: hard to say, but if it has something to do 256 00:14:01,679 --> 00:14:04,080 Speaker 4: with immigration, I think you could bet your ass that 257 00:14:04,200 --> 00:14:06,559 Speaker 4: this is all just some kind of bullshit circus. 258 00:14:06,960 --> 00:14:08,200 Speaker 1: And it was even admitted. 259 00:14:08,280 --> 00:14:13,000 Speaker 4: Here's Representative french Hill, which is not some really interesting 260 00:14:13,120 --> 00:14:17,959 Speaker 4: mustard brand on Fox just saying just admitting out loud 261 00:14:18,080 --> 00:14:20,000 Speaker 4: that like, this whole thing is really not based on 262 00:14:20,040 --> 00:14:21,320 Speaker 4: anything aside from PR. 263 00:14:21,600 --> 00:14:23,240 Speaker 3: What more do we need to say? That we need 264 00:14:23,280 --> 00:14:25,360 Speaker 3: to shut the border, and we know the steps to 265 00:14:25,400 --> 00:14:28,440 Speaker 3: done it, We've passed them in HR two. The President 266 00:14:28,480 --> 00:14:31,240 Speaker 3: could take executive action to do it today. Doesn't need 267 00:14:31,280 --> 00:14:34,880 Speaker 3: more money, it needs action. And this is what's disappointing 268 00:14:34,880 --> 00:14:36,760 Speaker 3: to people. And that's why my Orcas is going to 269 00:14:36,840 --> 00:14:41,120 Speaker 3: pay this public relations price by being impeached for the 270 00:14:41,200 --> 00:14:42,800 Speaker 3: first time since eighteen seventy six. 271 00:14:43,040 --> 00:14:43,160 Speaker 1: Kep. 272 00:14:44,520 --> 00:14:45,520 Speaker 2: That's what he said. 273 00:14:45,840 --> 00:14:47,080 Speaker 1: The president can do all this. 274 00:14:47,720 --> 00:14:52,640 Speaker 4: That's why my Orcus is going to pay this public price. 275 00:14:53,080 --> 00:14:57,440 Speaker 1: Yeah, PR, the PR disaster. 276 00:14:57,400 --> 00:15:01,120 Speaker 4: Yeah yeah, I mean, you know, this is just where 277 00:15:01,120 --> 00:15:03,600 Speaker 4: it's And if you remember, the Senate had a bill 278 00:15:04,400 --> 00:15:09,160 Speaker 4: that was the GOP's wettest of wet immigration dreams and 279 00:15:09,200 --> 00:15:11,920 Speaker 4: It had many people questioning why Joe Biden was even 280 00:15:11,920 --> 00:15:14,360 Speaker 4: supporting such an awful billity like, you're gonna put off 281 00:15:14,360 --> 00:15:16,360 Speaker 4: all these other people who actually give a shit about 282 00:15:16,560 --> 00:15:20,800 Speaker 4: humane immigration. And again, we know Trump basically is the 283 00:15:20,800 --> 00:15:23,320 Speaker 4: person saying, no, don't let it happen. I need as 284 00:15:23,360 --> 00:15:26,160 Speaker 4: much chaos and pain at the border for me to 285 00:15:26,200 --> 00:15:29,240 Speaker 4: win in November. And you know, while it may be 286 00:15:29,360 --> 00:15:31,000 Speaker 4: the logical thing, I think for a lot of people 287 00:15:31,040 --> 00:15:32,680 Speaker 4: to be like, they got to know that Trump is 288 00:15:32,680 --> 00:15:34,160 Speaker 4: the one that is making the mess. 289 00:15:34,680 --> 00:15:36,200 Speaker 1: Democrats actually tried. 290 00:15:36,560 --> 00:15:40,000 Speaker 4: The polling shows that Republicans have literally no idea like 291 00:15:40,040 --> 00:15:41,920 Speaker 4: how any of it works. Like the actual voters on 292 00:15:41,960 --> 00:15:44,480 Speaker 4: the Republican side or even like independents, they're like, I 293 00:15:44,480 --> 00:15:48,440 Speaker 4: don't know. It's probably like thirty, like forty eight percent 294 00:15:48,480 --> 00:15:51,479 Speaker 4: the Democrats fault, and like fifty two percent the Republican's 295 00:15:51,480 --> 00:15:54,440 Speaker 4: fault that the bill didn't go through, that they tanked. 296 00:15:54,760 --> 00:15:56,320 Speaker 2: So it's a tough world. 297 00:15:57,280 --> 00:15:59,960 Speaker 4: And I think just a couple that teenage mutant Ninja 298 00:16:00,040 --> 00:16:03,520 Speaker 4: Herbals aka Stephen Miller from the last Trump administration, he's 299 00:16:03,560 --> 00:16:06,840 Speaker 4: basically saying, in the next administration, if they win, he's 300 00:16:06,840 --> 00:16:11,520 Speaker 4: basically he's describing a just just large scale rounding up 301 00:16:11,560 --> 00:16:14,520 Speaker 4: of millions of people. You know, we're going to nationalize 302 00:16:14,560 --> 00:16:17,360 Speaker 4: the nation. We're going to deputize the National Guard and 303 00:16:17,440 --> 00:16:20,760 Speaker 4: try and move like a million people out of the country. 304 00:16:21,560 --> 00:16:24,560 Speaker 4: A former like navy person was like, you can't mobilize 305 00:16:24,600 --> 00:16:28,600 Speaker 4: like that requires like hundreds of thousands of people to 306 00:16:28,640 --> 00:16:32,440 Speaker 4: be immigration enforcement people and another tens of thousands because 307 00:16:32,440 --> 00:16:35,680 Speaker 4: he's talking about and then we'll have camps at the border. 308 00:16:35,800 --> 00:16:39,200 Speaker 4: You're like, you'll have camps, really Jesus, and we will, 309 00:16:39,240 --> 00:16:41,000 Speaker 4: and then we will just deport them from there on 310 00:16:41,120 --> 00:16:44,480 Speaker 4: military aircraft. It's like, okay, so who's what's the bill 311 00:16:44,520 --> 00:16:46,880 Speaker 4: for that. That's a lot of fucking infrastructure. They're like, 312 00:16:46,880 --> 00:16:49,760 Speaker 4: that's like trying to mobilize like the entire like you know, 313 00:16:50,080 --> 00:16:53,080 Speaker 4: huge section of like the military for a like a deployment. 314 00:16:53,640 --> 00:16:56,920 Speaker 1: So anyway, these are the things that the swirling around 315 00:16:56,920 --> 00:16:59,280 Speaker 1: in their heads. As he also said, if you're going 316 00:16:59,280 --> 00:17:02,640 Speaker 1: to go into an unfriendly state like Maryland, the state 317 00:17:02,680 --> 00:17:06,680 Speaker 1: that doesn't vote Republican, well there would just be Virginia 318 00:17:06,840 --> 00:17:09,800 Speaker 1: doing the arrest in Maryland right very close, very nearby. 319 00:17:10,480 --> 00:17:14,520 Speaker 1: So you would take other states National Guard. Yeah, and 320 00:17:14,640 --> 00:17:18,840 Speaker 1: like have them invade the state, yes, where they have 321 00:17:18,880 --> 00:17:23,639 Speaker 1: no jurisdiction and arrest people and yeah, there's no way 322 00:17:23,720 --> 00:17:26,320 Speaker 1: that would go wrong in any way. No think no, yeah, 323 00:17:26,400 --> 00:17:27,040 Speaker 1: and I think again. 324 00:17:27,119 --> 00:17:29,800 Speaker 4: It's also like like logistically they couldn't they couldn't even 325 00:17:29,840 --> 00:17:33,440 Speaker 4: figure out infrastructure week Yeah you know what I mean? 326 00:17:33,720 --> 00:17:36,480 Speaker 1: That was like, yeah they could. I this does feel 327 00:17:36,560 --> 00:17:38,439 Speaker 1: like it feels like the sort of thing they couldn't 328 00:17:38,440 --> 00:17:41,159 Speaker 1: have pulled off in the first Trump administration. But it 329 00:17:41,160 --> 00:17:45,040 Speaker 1: it feels like they're being much more open about their 330 00:17:45,280 --> 00:17:48,320 Speaker 1: fascist aspirations. Oh what I sent like they're not going 331 00:17:48,400 --> 00:17:50,760 Speaker 1: to give a shit about what anybody says. Yeah. 332 00:17:50,760 --> 00:17:53,399 Speaker 4: With Project twenty twenty five, you better believe if like 333 00:17:53,440 --> 00:17:55,600 Speaker 4: they win and they just put in all their flunkies, 334 00:17:55,640 --> 00:17:57,240 Speaker 4: there aren't going to be people who can be like, I, 335 00:17:57,320 --> 00:18:00,200 Speaker 4: actually you can't do this. I'll be like yeah, yeah, yeah, yeah, yeah, Okay, 336 00:18:00,640 --> 00:18:03,040 Speaker 4: let's say yeah whatever, am I breaking the law? 337 00:18:03,080 --> 00:18:03,479 Speaker 1: I don't know. 338 00:18:03,760 --> 00:18:05,160 Speaker 2: He's here for the MAGA ship. 339 00:18:05,480 --> 00:18:05,880 Speaker 1: Yeah. 340 00:18:06,480 --> 00:18:09,920 Speaker 4: Yeah, anyway, so November, take your time, take your time November. 341 00:18:10,240 --> 00:18:15,800 Speaker 1: Yeah, and then George Santos's seat in the House that 342 00:18:15,880 --> 00:18:21,440 Speaker 1: they had the special election and Democrat Tom Swosey swotzy, 343 00:18:21,800 --> 00:18:29,640 Speaker 1: I don't know what one against GOP candidate I forget 344 00:18:29,680 --> 00:18:36,600 Speaker 1: her name. Yeah yeah, pilloph So, I don't know. This 345 00:18:36,680 --> 00:18:40,399 Speaker 1: cuts their margin even more in the House, which is 346 00:18:40,920 --> 00:18:45,159 Speaker 1: already shockingly low given how well Democrats did in the 347 00:18:45,240 --> 00:18:51,040 Speaker 1: last midterm, And some people, like the MSNBC take is 348 00:18:51,040 --> 00:18:53,639 Speaker 1: like this, this should show Democrats how to win similar 349 00:18:53,720 --> 00:18:57,119 Speaker 1: competitive districts this fall. It's also, you know, he was 350 00:18:57,560 --> 00:19:04,000 Speaker 1: ahead in early voting. Snowstorm hit New York on Tuesday. Okay, 351 00:19:04,000 --> 00:19:04,480 Speaker 1: but don't don't. 352 00:19:04,600 --> 00:19:06,320 Speaker 4: Let's say that's the only thing, you know, that's the 353 00:19:06,359 --> 00:19:09,840 Speaker 4: way we can, you know, really flip the house. 354 00:19:09,880 --> 00:19:11,800 Speaker 1: Apparently it's a good playbook. 355 00:19:12,880 --> 00:19:13,320 Speaker 2: I don't know. 356 00:19:13,480 --> 00:19:16,960 Speaker 1: He's also like super anti you think he said during 357 00:19:17,000 --> 00:19:20,880 Speaker 1: his campaign, the progressive left wing of the Democratic Party 358 00:19:21,440 --> 00:19:24,880 Speaker 1: is hurting Democrats throughout the country because the people want 359 00:19:24,960 --> 00:19:31,359 Speaker 1: us to solve problems refer to opposition to a bill 360 00:19:31,600 --> 00:19:36,119 Speaker 1: that calls for more police accountability. But yeah, and both 361 00:19:36,119 --> 00:19:40,680 Speaker 1: he and his opponent receive substantial support from pro Israel organizations, 362 00:19:41,000 --> 00:19:45,560 Speaker 1: and his victory speech was actually interrupted by anti war protesters. 363 00:19:46,000 --> 00:19:49,399 Speaker 4: So, oh gosh, what are the Democrats going to do? 364 00:19:49,480 --> 00:19:53,560 Speaker 4: About this thing about you know, bankrolling a genocide. 365 00:19:54,160 --> 00:19:55,240 Speaker 2: Just get out of our hair. 366 00:19:56,240 --> 00:20:02,160 Speaker 4: So yeah, well, uh hey the one add one more 367 00:20:02,440 --> 00:20:03,960 Speaker 4: to the to the DEM side. 368 00:20:04,520 --> 00:20:08,000 Speaker 1: We'll see what happens going forward. But yeah, it's I 369 00:20:08,040 --> 00:20:08,720 Speaker 1: don't know if that's. 370 00:20:08,600 --> 00:20:10,760 Speaker 2: A winning, winning strategy. 371 00:20:10,840 --> 00:20:13,520 Speaker 4: I mean, like, I think a lot of people are 372 00:20:14,119 --> 00:20:15,520 Speaker 4: you know, talking about I think is in the New 373 00:20:15,520 --> 00:20:19,080 Speaker 4: Republic today. They're saying, like the way the Democratic Party 374 00:20:19,200 --> 00:20:23,000 Speaker 4: is like you know, losing interest of like younger voters, 375 00:20:23,040 --> 00:20:25,920 Speaker 4: Like that's the lifeblood you need to have a campaign, 376 00:20:26,359 --> 00:20:28,959 Speaker 4: Like you need young people out there to go and 377 00:20:29,119 --> 00:20:31,840 Speaker 4: help fucking power a campaign. But they're all if they're 378 00:20:31,880 --> 00:20:35,879 Speaker 4: all completely defeated by what the prospects are of a 379 00:20:35,960 --> 00:20:39,080 Speaker 4: government that's like not going to precisely put their needs 380 00:20:39,080 --> 00:20:41,240 Speaker 4: at the forefront of everything. Yeah, it's going to have 381 00:20:41,280 --> 00:20:43,080 Speaker 4: a bit of a chilling effect. And I don't it's 382 00:20:43,320 --> 00:20:45,560 Speaker 4: it feels like it's such an easy solve because then 383 00:20:45,600 --> 00:20:48,040 Speaker 4: you hear these stories too. There was a story like 384 00:20:48,160 --> 00:20:50,480 Speaker 4: a few days ago about how like Biden is like 385 00:20:50,520 --> 00:20:53,760 Speaker 4: apparently just disparaging nets in Yahoo like in private behind 386 00:20:53,760 --> 00:20:54,280 Speaker 4: closed doors. 387 00:20:54,359 --> 00:20:56,720 Speaker 1: Yeahah, behind closed doors. And then it's like called him 388 00:20:56,720 --> 00:21:00,400 Speaker 1: an a hole behind closed doors. Like, man, it would 389 00:21:00,440 --> 00:21:03,359 Speaker 1: be cool if he had that energy, same energy for 390 00:21:03,440 --> 00:21:08,280 Speaker 1: this like right wing person, uh not behind closed doors 391 00:21:08,760 --> 00:21:12,520 Speaker 1: out reopen again. It's like that thing that John Star 392 00:21:12,640 --> 00:21:14,359 Speaker 1: was talking about on The Daily Show where it's like 393 00:21:14,800 --> 00:21:19,080 Speaker 1: the stories of Biden like standing up and having backbone 394 00:21:19,080 --> 00:21:22,879 Speaker 1: and like being super sharp and like commanding behind closed 395 00:21:22,880 --> 00:21:27,360 Speaker 1: doors are all over the place. But can we see 396 00:21:27,400 --> 00:21:29,200 Speaker 1: that You're going to have to trust us on that one. 397 00:21:29,680 --> 00:21:32,960 Speaker 2: Yeah. Uh, it's a hard one, man, It's a hard one. 398 00:21:33,000 --> 00:21:35,080 Speaker 4: And it's just like I think the way I look 399 00:21:35,119 --> 00:21:36,960 Speaker 4: at it too, is sort of like in order for 400 00:21:37,560 --> 00:21:42,040 Speaker 4: you know, because this the presidential is it's very consequential 401 00:21:42,119 --> 00:21:44,639 Speaker 4: because of what Trump is going to bring. If you're like, 402 00:21:44,840 --> 00:21:46,720 Speaker 4: you know, if it were a traditional Republican, you're like, 403 00:21:46,720 --> 00:21:48,840 Speaker 4: you're just gonna do some fucked up version of the 404 00:21:48,840 --> 00:21:49,480 Speaker 4: status quo. 405 00:21:49,800 --> 00:21:52,440 Speaker 1: But this is something very different for sure. 406 00:21:52,480 --> 00:21:54,520 Speaker 4: And that's what and I think that's really the only 407 00:21:54,560 --> 00:21:57,520 Speaker 4: thing that has people maybe like as a motive, motivating 408 00:21:57,640 --> 00:22:00,720 Speaker 4: force to be like, I mean, this shit this guy 409 00:22:00,760 --> 00:22:04,720 Speaker 4: is saying is fucking grim, Like he's trying to fuck 410 00:22:04,760 --> 00:22:09,360 Speaker 4: everything up bad for everybody. Yeah, and yeah, and then 411 00:22:09,440 --> 00:22:11,200 Speaker 4: it's like a lot of like it's like, okay, I 412 00:22:11,240 --> 00:22:14,960 Speaker 4: don't it's it might get your clothes pins out and 413 00:22:15,080 --> 00:22:16,919 Speaker 4: maybe make sure you pinch your nose off as you 414 00:22:16,960 --> 00:22:17,240 Speaker 4: go to the. 415 00:22:17,200 --> 00:22:19,399 Speaker 2: Ballot box, because yeah, I don't know. 416 00:22:19,440 --> 00:22:23,560 Speaker 4: It's like trying to navigate a second Trump administration. I 417 00:22:23,600 --> 00:22:26,040 Speaker 4: think makes it nearly impossible for a lot of people 418 00:22:26,040 --> 00:22:28,360 Speaker 4: who are doing good, like on the ground to navigate 419 00:22:28,400 --> 00:22:31,119 Speaker 4: all that. But yeah, here we are here, we are 420 00:22:31,800 --> 00:22:32,800 Speaker 4: Take your time November. 421 00:22:32,920 --> 00:22:38,600 Speaker 1: Take your time. Just luxuriate in these you know exactly 422 00:22:39,320 --> 00:22:41,360 Speaker 1: all right, those are some of the things that are 423 00:22:41,440 --> 00:22:46,760 Speaker 1: trending on this Valentine's Day, Wednesday, February fourteenth. Happy Valentine's 424 00:22:46,800 --> 00:22:51,000 Speaker 1: Day to everybody out there. We are back tomorrow with 425 00:22:51,080 --> 00:22:54,040 Speaker 1: the whole last episode of the show. Until then, be 426 00:22:54,200 --> 00:22:57,280 Speaker 1: kind to each other, be kind to yourselves, get the vaccine, 427 00:22:57,359 --> 00:22:59,960 Speaker 1: don't do nothing about white supremacy. No, we will talk 428 00:23:00,119 --> 00:23:07,439 Speaker 1: to y'all tomorrow. Bye, spooches. What is that? That's how 429 00:23:07,480 --> 00:23:08,320 Speaker 1: I kiss? 430 00:23:08,440 --> 00:23:10,639 Speaker 4: It sounds like a hamster like eating from like one 431 00:23:10,640 --> 00:23:14,560 Speaker 4: of those little water bottles that well, hey, however you 432 00:23:14,560 --> 00:23:20,680 Speaker 4: want to Bye,