1
00:00:00,520 --> 00:00:04,400
Speaker 1: Hello the Internet, and welcome to season episode five of

2
00:00:04,519 --> 00:00:08,560
Speaker 1: the Days Like Geics to production of My Heart Radio.

3
00:00:09,200 --> 00:00:11,039
Speaker 1: This is a podcast where we take a deep dive

4
00:00:11,080 --> 00:00:17,280
Speaker 1: into America's share Caution, it's Friday, May one, Happy birthday,

5
00:00:17,400 --> 00:00:26,360
Speaker 1: super producer on the birthday. That's all you're getting from me.

6
00:00:27,280 --> 00:00:33,000
Speaker 1: I don't want to they say it's your birthdays. Sh

7
00:00:33,040 --> 00:00:36,520
Speaker 1: My name is Jack O'Brien, Potatoes O'Brien, and I'm thrilled

8
00:00:36,520 --> 00:00:39,440
Speaker 1: to be joined as always buy my co host, Mr

9
00:00:39,560 --> 00:00:44,920
Speaker 1: Miles Grass. Miles kame Miles McDonald for singing what do

10
00:00:45,159 --> 00:01:00,480
Speaker 1: you believe? Pieces no THEO to reason away, Hello and way.

11
00:01:00,560 --> 00:01:03,440
Speaker 1: So that's just me right now. Didn't even I was

12
00:01:03,520 --> 00:01:05,959
Speaker 1: gonna look on Discord, but what a Chuge believes was

13
00:01:06,000 --> 00:01:08,360
Speaker 1: in my mind and I felt like seeing like Michael McDonald's.

14
00:01:08,360 --> 00:01:12,440
Speaker 1: So here we are. Well, I have a chuge product

15
00:01:12,560 --> 00:01:16,080
Speaker 1: that I have to a debut on tomorrow's episode. It's

16
00:01:16,120 --> 00:01:19,760
Speaker 1: currently being washed. Oh yes, I think we may have

17
00:01:19,880 --> 00:01:26,200
Speaker 1: matching gear gear Miles. We're thrilled. We're fortunate to be

18
00:01:26,280 --> 00:01:30,240
Speaker 1: joined in our third seat by a brilliant podcaster, a

19
00:01:30,280 --> 00:01:34,120
Speaker 1: brilliant actor. You know him from Crazy Ex Girlfriend and

20
00:01:34,200 --> 00:01:39,360
Speaker 1: Love Simon. His podcast is soul Bomb. He is Clark

21
00:01:39,600 --> 00:01:45,760
Speaker 1: most Hey, there they great Introy. We're working on these.

22
00:01:45,760 --> 00:01:48,120
Speaker 1: We're working our intro. You know, thank you for actually

23
00:01:48,080 --> 00:01:50,520
Speaker 1: be found that out. We're working on I'm living in

24
00:01:50,520 --> 00:01:53,280
Speaker 1: the chug vibes with y'all. I actually only just learned

25
00:01:53,320 --> 00:01:55,800
Speaker 1: what it meant the other day because he mentioned it

26
00:01:55,840 --> 00:01:59,440
Speaker 1: on an earlier episode, and I was like, how do

27
00:01:59,520 --> 00:02:02,280
Speaker 1: I not know what chug is? And then I realized, right,

28
00:02:02,360 --> 00:02:07,480
Speaker 1: virtue of not knowing what chug is? I am choky. Yeah,

29
00:02:07,960 --> 00:02:10,400
Speaker 1: I don't know. Part of me is this. I'm really

30
00:02:10,440 --> 00:02:12,880
Speaker 1: leaning into it the other way, like you know, like

31
00:02:13,200 --> 00:02:16,040
Speaker 1: a part of me wants to like regrets to high school,

32
00:02:16,040 --> 00:02:17,200
Speaker 1: where I'm like, well, I don't want to be the

33
00:02:17,240 --> 00:02:19,800
Speaker 1: thing that everyone says is a word that's bad. But

34
00:02:19,880 --> 00:02:21,680
Speaker 1: now I'm like in my adults and I'm like, yeah,

35
00:02:21,760 --> 00:02:25,000
Speaker 1: I'm getting it tadded next week on my throat out here.

36
00:02:25,400 --> 00:02:27,839
Speaker 1: But yeah, I don't know if you're knowing or not knowing.

37
00:02:27,840 --> 00:02:30,400
Speaker 1: There seems to be contradicting accounts. We have listeners, and

38
00:02:30,800 --> 00:02:34,880
Speaker 1: the vernacular hasn't quite reached Canada, it seems, so we'll

39
00:02:34,880 --> 00:02:37,960
Speaker 1: see how much of a phenomenon, it becomes yet again

40
00:02:38,080 --> 00:02:41,200
Speaker 1: gen Z is trolling us. Yeah, and I love it.

41
00:02:41,200 --> 00:02:43,960
Speaker 1: It's just like it feels like it's It doesn't feel

42
00:02:44,000 --> 00:02:47,320
Speaker 1: like when like boomers were first writing about millennials when

43
00:02:47,360 --> 00:02:50,920
Speaker 1: they came who are these broke motherfucker's where we won't

44
00:02:50,919 --> 00:02:54,799
Speaker 1: acknowledge why they're in the state they're in versus like now,

45
00:02:54,840 --> 00:02:58,920
Speaker 1: like these feel like pointed jabs from like younger siblings

46
00:02:58,960 --> 00:03:01,000
Speaker 1: that are a little bit cooler. And I'm like, all right, yes,

47
00:03:01,600 --> 00:03:05,119
Speaker 1: I like how it didn't go to us writing about them,

48
00:03:05,200 --> 00:03:08,120
Speaker 1: It went to them writing about us because millennials are

49
00:03:08,200 --> 00:03:11,560
Speaker 1: so Millennials are so self centered. They're always the subject

50
00:03:11,639 --> 00:03:14,160
Speaker 1: of the article and not the writer of the art exactly, Like,

51
00:03:14,200 --> 00:03:17,000
Speaker 1: but what do the younger ones think about us? Yeah,

52
00:03:17,080 --> 00:03:19,079
Speaker 1: it's even and even when it is, it's articles by

53
00:03:19,080 --> 00:03:24,639
Speaker 1: millennials been like, chug, are we know how to embrace

54
00:03:24,720 --> 00:03:28,440
Speaker 1: the juge? Yeah, Clark, We're going to get to know

55
00:03:28,480 --> 00:03:30,720
Speaker 1: you a little bit better in a moment. First, we

56
00:03:30,760 --> 00:03:33,880
Speaker 1: are going to tell our listeners just a couple of

57
00:03:33,919 --> 00:03:37,760
Speaker 1: the things we're talking about today. We're gonna talk about

58
00:03:37,800 --> 00:03:45,640
Speaker 1: the newest link in the Juliani political dynasty, Andrew Giuliani,

59
00:03:46,120 --> 00:03:49,880
Speaker 1: also the first person to run for governor of New York,

60
00:03:50,760 --> 00:03:53,960
Speaker 1: having been played by Chris Farley at a young age.

61
00:03:54,000 --> 00:03:58,800
Speaker 1: I think we're gonna talk about kids in Massachusetts succeeding

62
00:03:58,840 --> 00:04:02,360
Speaker 1: and getting young people to vote, a little little hopefulness there.

63
00:04:02,880 --> 00:04:07,320
Speaker 1: We're gonna talk about AI created music and even movie translations.

64
00:04:08,120 --> 00:04:12,760
Speaker 1: Why Netflix is so all over leverage, I'll say, on

65
00:04:12,800 --> 00:04:14,800
Speaker 1: this Army of the Dead movie, I don't know, I

66
00:04:14,840 --> 00:04:16,920
Speaker 1: haven't seen it yet, but before we get to any

67
00:04:16,960 --> 00:04:20,479
Speaker 1: of that ship Clark, we like to ask our guests,

68
00:04:20,839 --> 00:04:24,880
Speaker 1: what is something from your search history? So I prepared.

69
00:04:25,040 --> 00:04:27,039
Speaker 1: I was thinking about this the other day as I

70
00:04:27,080 --> 00:04:29,240
Speaker 1: was listening to an earlier episode, and I was like,

71
00:04:29,600 --> 00:04:31,960
Speaker 1: there's no way there's going to be anything interesting in

72
00:04:32,000 --> 00:04:36,240
Speaker 1: my search history. And then not five minutes later, I

73
00:04:36,279 --> 00:04:38,839
Speaker 1: found myself down a Google rabbit hole that I think

74
00:04:38,839 --> 00:04:43,760
Speaker 1: actually really encapsulates where I am in my life right now. Basically,

75
00:04:44,200 --> 00:04:46,480
Speaker 1: I don't know why I was set off on this

76
00:04:46,480 --> 00:04:50,080
Speaker 1: this path, but I was thinking about Jeff Bezos's wealth,

77
00:04:51,279 --> 00:04:55,640
Speaker 1: as one does, and and I just started randomly searching

78
00:04:55,720 --> 00:05:00,320
Speaker 1: the g d P of various European and after Can

79
00:05:00,320 --> 00:05:04,640
Speaker 1: countries to sort of compare to the personal wealth of

80
00:05:04,760 --> 00:05:07,400
Speaker 1: Jeff Bezos. And I was I was going down the list,

81
00:05:07,480 --> 00:05:11,320
Speaker 1: and I was like, you know, England or Estonia, Botswana,

82
00:05:11,360 --> 00:05:13,840
Speaker 1: and I was seeing all of these different GDPs and

83
00:05:13,880 --> 00:05:17,240
Speaker 1: then developing like a real like oh my god, I

84
00:05:17,279 --> 00:05:20,599
Speaker 1: can't believe he has more money than that country, or like, wow,

85
00:05:20,640 --> 00:05:23,040
Speaker 1: he has a lot less than that one. And then

86
00:05:23,200 --> 00:05:28,719
Speaker 1: after about fifteen searches, I find found myself typing in

87
00:05:29,360 --> 00:05:34,279
Speaker 1: what is g d P? Which I think it perfectly

88
00:05:34,440 --> 00:05:36,760
Speaker 1: like fits who I am right now, where it's like

89
00:05:37,200 --> 00:05:41,320
Speaker 1: I almost think I have a handle on a really

90
00:05:41,360 --> 00:05:45,040
Speaker 1: complex topic or something that's really interesting. And then right

91
00:05:45,080 --> 00:05:47,919
Speaker 1: at the end, I'm like, wait, do I know what

92
00:05:48,080 --> 00:05:51,320
Speaker 1: that is? Spoiler? I did. I was right. My my

93
00:05:51,440 --> 00:05:55,279
Speaker 1: definition of GDP was right. But is it an annual

94
00:05:55,520 --> 00:05:58,760
Speaker 1: rate or is it like is it how much they're

95
00:05:58,960 --> 00:06:03,880
Speaker 1: growth domestic product like per year? Is that oka? It

96
00:06:03,960 --> 00:06:06,680
Speaker 1: is annual and the use of it, as I learned

97
00:06:06,720 --> 00:06:10,680
Speaker 1: from this Google search, is a snapshot of the economic

98
00:06:10,760 --> 00:06:13,640
Speaker 1: health of the country. So it's not like the total

99
00:06:13,680 --> 00:06:17,599
Speaker 1: amount of money that the country has like wealth, but

100
00:06:18,080 --> 00:06:20,560
Speaker 1: it's like the value of the products that they produced

101
00:06:20,600 --> 00:06:23,400
Speaker 1: in a year. So it's not fair to compare Jeff

102
00:06:23,480 --> 00:06:26,920
Speaker 1: to those countries because I mean, that's just how much

103
00:06:26,920 --> 00:06:28,719
Speaker 1: money they have for a year, and Jeff has to

104
00:06:28,760 --> 00:06:33,520
Speaker 1: make that five trillion dollars stretch across this whole lifetime.

105
00:06:33,680 --> 00:06:39,599
Speaker 1: So people really setting him up to fail. All those

106
00:06:39,640 --> 00:06:41,839
Speaker 1: things where they try and get people to be able

107
00:06:41,880 --> 00:06:44,920
Speaker 1: to wrap their heads around what kind of money these

108
00:06:45,000 --> 00:06:47,680
Speaker 1: were talking about here, they're always just like horrific. Like

109
00:06:47,720 --> 00:06:49,279
Speaker 1: there was one that's like, well, if you break it

110
00:06:49,320 --> 00:06:53,039
Speaker 1: down into seconds, based on what he made in he's

111
00:06:53,080 --> 00:06:57,000
Speaker 1: making twenty two five hundred thirty seven dollars per second

112
00:06:57,440 --> 00:07:00,680
Speaker 1: or a hundred fifty two thousand, two hundreds upon dollars

113
00:07:00,680 --> 00:07:03,440
Speaker 1: per minute. And then they even talked about like try

114
00:07:03,480 --> 00:07:06,359
Speaker 1: and conceptualize them like a billion, right, because a billion

115
00:07:06,520 --> 00:07:11,320
Speaker 1: seconds is thirty two years ago. And then if you say,

116
00:07:11,320 --> 00:07:14,280
Speaker 1: like someone has a hundred billion dollars, a hundred billion

117
00:07:14,360 --> 00:07:18,000
Speaker 1: seconds like loosely is like the Trojan War, there's a

118
00:07:18,080 --> 00:07:21,320
Speaker 1: hundred billion seconds ago, like and just thinking how like man,

119
00:07:21,360 --> 00:07:23,840
Speaker 1: well not like these are just sums that you couldn't

120
00:07:23,880 --> 00:07:26,840
Speaker 1: even begin to fathom or know what to fucking do with.

121
00:07:26,920 --> 00:07:29,000
Speaker 1: Aside from I think just get off on watching like

122
00:07:29,040 --> 00:07:32,720
Speaker 1: a bank account. It does make your brain go a

123
00:07:32,720 --> 00:07:37,240
Speaker 1: little wonky looking for him, you know, and really good

124
00:07:37,320 --> 00:07:41,920
Speaker 1: for Mackenzie. Yes, yeah, I'm I hope. I'm I'm wondering

125
00:07:41,960 --> 00:07:46,840
Speaker 1: if these newly divorced like divorced billionaires that were like

126
00:07:46,880 --> 00:07:48,760
Speaker 1: that work that are coming out of this, like Melinda

127
00:07:48,760 --> 00:07:51,320
Speaker 1: Gates and Mackenzie, Uh, what's her made in name? I

128
00:07:51,320 --> 00:07:55,920
Speaker 1: know it's not Beazes anymore, but Bezos or whatever whatever

129
00:07:55,960 --> 00:08:00,000
Speaker 1: you say. Um Like, it seems like they're much more

130
00:08:00,040 --> 00:08:03,360
Speaker 1: focused on how to be better like philanthropists than their

131
00:08:03,400 --> 00:08:05,560
Speaker 1: husbands were, where they're like, you know, it seems like

132
00:08:05,600 --> 00:08:08,480
Speaker 1: Mackenzie just is secretly funding a lot of stuff and

133
00:08:08,480 --> 00:08:10,920
Speaker 1: it's not interested in telling people that she's giving this

134
00:08:10,920 --> 00:08:13,080
Speaker 1: money away. I mean sometimes the money that comes out

135
00:08:13,200 --> 00:08:16,040
Speaker 1: or whatever. But it seems like I'm curious if they're

136
00:08:16,040 --> 00:08:18,560
Speaker 1: going to start shaming their ex husbands were like, no,

137
00:08:18,680 --> 00:08:20,760
Speaker 1: this is actually how you can turn it up with

138
00:08:20,840 --> 00:08:23,680
Speaker 1: a billion dollars done the right way. Rather, that's a

139
00:08:23,760 --> 00:08:27,480
Speaker 1: reality show I would watch right right, just like The

140
00:08:27,520 --> 00:08:32,080
Speaker 1: First Wives Club, but like like philanthropy edition dollar divorce

141
00:08:33,600 --> 00:08:36,440
Speaker 1: sign so I will happily marry a billionaire just to

142
00:08:36,440 --> 00:08:38,640
Speaker 1: go on that show. And I feel like this is

143
00:08:38,679 --> 00:08:40,600
Speaker 1: how you actually help people with this money, because I

144
00:08:40,600 --> 00:08:43,000
Speaker 1: feel like, you know, Bill Gates is just against so

145
00:08:43,200 --> 00:08:48,840
Speaker 1: focused on like his sort of posthumous you know, identity

146
00:08:48,920 --> 00:08:52,520
Speaker 1: or account of his existence in history, where it's like

147
00:08:52,559 --> 00:08:55,680
Speaker 1: not actually effective in terms of like really when so

148
00:08:55,720 --> 00:08:57,839
Speaker 1: many people like the money could be used so much

149
00:08:57,840 --> 00:09:00,280
Speaker 1: better than how it's being Yeah, you know, he's spun

150
00:09:00,320 --> 00:09:04,400
Speaker 1: off onto a different planet. He's no longer exists scenari

151
00:09:04,480 --> 00:09:10,840
Speaker 1: reality mhm. But just I do love the micro aggressions

152
00:09:10,920 --> 00:09:15,600
Speaker 1: that he like. People who worked with them said that

153
00:09:15,679 --> 00:09:19,840
Speaker 1: he would like never allow her to speak more than him,

154
00:09:20,000 --> 00:09:23,160
Speaker 1: and would like speak over her in meetings and would

155
00:09:23,160 --> 00:09:26,560
Speaker 1: be dismissive towards her. And you're just seeing that ship

156
00:09:26,720 --> 00:09:29,720
Speaker 1: leak out in this divorce, Like all the details that

157
00:09:29,760 --> 00:09:32,880
Speaker 1: are coming now are just like, you know, that ship

158
00:09:32,880 --> 00:09:36,400
Speaker 1: didn't leak on Bezos. I'm sure he was. It's almost

159
00:09:36,440 --> 00:09:39,120
Speaker 1: impossible that he's not a shitty human, but we didn't

160
00:09:39,160 --> 00:09:42,720
Speaker 1: get those details. So yeah, there's gotta be some trauma

161
00:09:42,880 --> 00:09:45,520
Speaker 1: in there that they're working through. I mean, you have

162
00:09:45,600 --> 00:09:48,160
Speaker 1: to have some kind you know, something crazy has to happen,

163
00:09:48,200 --> 00:09:51,520
Speaker 1: to you in order for you to feel like the

164
00:09:51,640 --> 00:09:53,880
Speaker 1: way to live my life is just to amass as

165
00:09:53,960 --> 00:09:58,920
Speaker 1: much money as possible. Like I love money, I really do,

166
00:09:59,280 --> 00:10:03,240
Speaker 1: but not that much, Like I don't have the energy

167
00:10:03,320 --> 00:10:06,400
Speaker 1: to devote my whole life to it. Yeah, and because

168
00:10:06,440 --> 00:10:10,240
Speaker 1: just why I have done so well, I think, Yeah,

169
00:10:10,280 --> 00:10:12,280
Speaker 1: the other it is like it's it's it is a

170
00:10:12,320 --> 00:10:15,240
Speaker 1: sense of lack, but this other weird, bizarre version that

171
00:10:15,320 --> 00:10:17,800
Speaker 1: just manifests into this like wealth hoarding. When it's like

172
00:10:17,840 --> 00:10:21,559
Speaker 1: I can't imagine Bill Gates like has like fond memories

173
00:10:21,600 --> 00:10:23,920
Speaker 1: of his past or whatever, and it's like, yeah, man,

174
00:10:23,960 --> 00:10:25,840
Speaker 1: I have a pretty fulfilled life. I think at a

175
00:10:25,840 --> 00:10:29,040
Speaker 1: certain level, when you're so wealthy, you just patched it

176
00:10:29,160 --> 00:10:31,040
Speaker 1: up with all this money. You're like, fucking man, I'm

177
00:10:31,080 --> 00:10:33,360
Speaker 1: just avoid looking at myself in the mirror and I'll

178
00:10:33,400 --> 00:10:36,920
Speaker 1: just send weird cringe emails hitting on my fucking employees.

179
00:10:38,720 --> 00:10:40,760
Speaker 1: But another thing is, yeah, I wonder if if you're

180
00:10:40,800 --> 00:10:45,000
Speaker 1: saying Melinda was like shushed in meetings by Bill Gates, Yeah, yeah, yeah,

181
00:10:45,080 --> 00:10:48,040
Speaker 1: yeah wow. Can you imagine like when they're like these

182
00:10:48,120 --> 00:10:50,400
Speaker 1: huge initiatives and she's like, you know, and I'm really

183
00:10:50,440 --> 00:10:54,079
Speaker 1: worried about the state of people's access to flushing toilets

184
00:10:54,160 --> 00:10:59,240
Speaker 1: or proper sewage system and sanitation systems, especially in developing nations,

185
00:10:59,240 --> 00:11:05,280
Speaker 1: and bills like no, we need to start refusing windows

186
00:11:05,320 --> 00:11:09,360
Speaker 1: tablets to people's arms sub Saharan Africa, and then other

187
00:11:09,360 --> 00:11:12,079
Speaker 1: people like, actually, that's a good idea, bill, and he's like, yeah, yeah,

188
00:11:12,080 --> 00:11:14,360
Speaker 1: I thought of that too, and then he repeats her

189
00:11:14,440 --> 00:11:17,120
Speaker 1: idea and also, we really need to work on the

190
00:11:17,280 --> 00:11:22,120
Speaker 1: this water. As Melinda and I were discussing, I just

191
00:11:22,200 --> 00:11:26,640
Speaker 1: said that ship bill. But then there's also the details

192
00:11:26,679 --> 00:11:30,160
Speaker 1: that uh he when he was kicking it with his

193
00:11:30,960 --> 00:11:35,760
Speaker 1: boy Jeff little Saint Jeff Epstein, that he was complaining

194
00:11:35,760 --> 00:11:43,360
Speaker 1: about his marriage just like, Yo, it's a dark space

195
00:11:43,440 --> 00:11:47,040
Speaker 1: up there at the top. Yeah. Yeah, it just gets

196
00:11:47,160 --> 00:11:51,520
Speaker 1: darker the higher, the higher and higher you go. Um. Anyways, Uh,

197
00:11:52,040 --> 00:11:54,559
Speaker 1: shout out to Jeff Bezos, I think is where we're

198
00:11:54,559 --> 00:11:58,199
Speaker 1: where we're at. Shout out to Jeff. Jeff. To sum

199
00:11:58,240 --> 00:12:01,760
Speaker 1: it up, Jeff Bezos doesn't have enough money. I won't

200
00:12:01,760 --> 00:12:06,360
Speaker 1: have enough money until we're talking trillions with a t Okay,

201
00:12:06,679 --> 00:12:11,360
Speaker 1: let the men eat, Let the man eat. Uh. What

202
00:12:11,600 --> 00:12:16,640
Speaker 1: is something Clark do you think is overrated. I actually

203
00:12:16,679 --> 00:12:20,400
Speaker 1: just got back from Big Bear for a couple of

204
00:12:20,440 --> 00:12:23,440
Speaker 1: weeks where I was shooting a movie. And it's two

205
00:12:23,480 --> 00:12:26,680
Speaker 1: and it's about two and a half hours away. And

206
00:12:27,400 --> 00:12:31,480
Speaker 1: so what I think is overrated our road trips, because

207
00:12:32,160 --> 00:12:35,280
Speaker 1: every time I'm getting ready to do one, I'm like

208
00:12:35,559 --> 00:12:39,200
Speaker 1: marveling at the convenience, you know, the fact that I

209
00:12:39,200 --> 00:12:41,760
Speaker 1: don't have to fly all of the like hassle of

210
00:12:41,800 --> 00:12:45,040
Speaker 1: air travel. I took my dog with me, which was

211
00:12:45,320 --> 00:12:47,679
Speaker 1: a great thing, and as I was packing up my car,

212
00:12:47,720 --> 00:12:50,160
Speaker 1: I was like thinking about I never would have been

213
00:12:50,200 --> 00:12:52,560
Speaker 1: able to bring these things on a plane, you know,

214
00:12:53,080 --> 00:12:55,680
Speaker 1: like packing up half my apartment into my hatchback. And

215
00:12:55,720 --> 00:12:58,600
Speaker 1: I'm like, this is so convenient. And for like the

216
00:12:58,679 --> 00:13:02,480
Speaker 1: first hour, we're so of of any road trip. I'm

217
00:13:02,520 --> 00:13:09,680
Speaker 1: like America, Freedom, California, rolled down the window, taking deep

218
00:13:09,679 --> 00:13:14,000
Speaker 1: breaths through your nose. My dog is like hanging out,

219
00:13:14,080 --> 00:13:18,679
Speaker 1: like you know, we're all happy. And then somewhere around

220
00:13:18,800 --> 00:13:24,400
Speaker 1: our two I'm like this could be I'm done with this,

221
00:13:24,600 --> 00:13:27,960
Speaker 1: you know, like this was fun. I just kind of

222
00:13:27,960 --> 00:13:30,560
Speaker 1: wish I was there. And then that last half hour

223
00:13:30,679 --> 00:13:34,480
Speaker 1: stretch is just like white knuckling, like, can I get

224
00:13:34,480 --> 00:13:37,120
Speaker 1: there as fast as possible without getting pulled over in

225
00:13:37,240 --> 00:13:40,160
Speaker 1: what apparently it's Trump country? Didn't Did we know that

226
00:13:40,200 --> 00:13:44,000
Speaker 1: Big Bear was as right as it is? I was oblivious?

227
00:13:44,440 --> 00:13:46,079
Speaker 1: Oh yeah, I mean, look, once you get out of

228
00:13:46,160 --> 00:13:49,640
Speaker 1: l A County, it's a mixed bag, y'all. Who knows

229
00:13:49,679 --> 00:13:54,040
Speaker 1: what you're gonna get? Like truly purple, which is this

230
00:13:54,120 --> 00:13:59,679
Speaker 1: beautiful image of like, you know, diversity and centrism and

231
00:13:59,760 --> 00:14:02,480
Speaker 1: we're all here together, but it really just means half

232
00:14:02,520 --> 00:14:06,040
Speaker 1: the people believe one thing and the other half believe

233
00:14:06,200 --> 00:14:08,920
Speaker 1: the other. Right, Like straight, there's no purple, it's just

234
00:14:09,320 --> 00:14:12,319
Speaker 1: blue and red purple. Yeah, that's also the same color

235
00:14:12,360 --> 00:14:16,280
Speaker 1: of bruising. Um. So yeah, I don't know if it's

236
00:14:16,280 --> 00:14:19,000
Speaker 1: a good or bad thing, but yeah, I definitely feel

237
00:14:19,000 --> 00:14:22,400
Speaker 1: that of like the hour too thing because usually that

238
00:14:22,520 --> 00:14:25,120
Speaker 1: first ninety minutes you can get there off the strength

239
00:14:25,120 --> 00:14:27,720
Speaker 1: of a like one or two albums, you know, and

240
00:14:28,000 --> 00:14:30,720
Speaker 1: like whoa and you're like fuck it, play Criminal Blaffiona

241
00:14:30,720 --> 00:14:32,880
Speaker 1: Apple one more fucking time because I'm ready to go,

242
00:14:33,520 --> 00:14:36,720
Speaker 1: and then by the second time, you're like close. I

243
00:14:37,000 --> 00:14:40,480
Speaker 1: feel Look, it's just like it's ship starts to just

244
00:14:40,680 --> 00:14:43,240
Speaker 1: lose and you get impatient. And I I have this

245
00:14:43,240 --> 00:14:45,720
Speaker 1: discussion a lot when I think about like driving versus

246
00:14:45,800 --> 00:14:49,640
Speaker 1: flying up to like the Bay Area, because door to door, right,

247
00:14:49,960 --> 00:14:51,920
Speaker 1: if let's say you have a one o'clock flight leaving

248
00:14:52,080 --> 00:14:54,360
Speaker 1: l A X. You want, you gotta get there about

249
00:14:54,360 --> 00:14:57,040
Speaker 1: an hour, but ahead of time plus forty minutes to

250
00:14:57,200 --> 00:15:00,360
Speaker 1: get there, you're damn near spending three hour just to

251
00:15:00,440 --> 00:15:03,200
Speaker 1: get to the airport and then the our flight, and

252
00:15:03,240 --> 00:15:07,600
Speaker 1: it's like there, Yeah, it's one thing of waiting an

253
00:15:07,600 --> 00:15:09,200
Speaker 1: airport is a little bit better than a car, but

254
00:15:09,360 --> 00:15:13,440
Speaker 1: it all. I've done this exact same math, and it's

255
00:15:13,600 --> 00:15:16,440
Speaker 1: it's basically the same. It's five hours door to door.

256
00:15:16,960 --> 00:15:20,200
Speaker 1: The difference of course being that if you're driving, it's

257
00:15:20,280 --> 00:15:25,280
Speaker 1: five hours of active getting yourself there versus like five

258
00:15:25,360 --> 00:15:29,720
Speaker 1: hours of being transported by your uber, by the train

259
00:15:29,800 --> 00:15:32,160
Speaker 1: that takes you to the terminal or like whatever it is,

260
00:15:32,200 --> 00:15:35,040
Speaker 1: you know, and so if you can sweep, and then

261
00:15:35,040 --> 00:15:37,840
Speaker 1: also it's not even that much cheaper here to San

262
00:15:37,840 --> 00:15:41,240
Speaker 1: Francisco because you fill up a couple of times. You know,

263
00:15:41,320 --> 00:15:48,760
Speaker 1: we're talking about a couple hundred dollars potentially. Honestly, I

264
00:15:48,800 --> 00:15:52,320
Speaker 1: said that and then I realized I'm really bad at math.

265
00:15:52,360 --> 00:15:56,160
Speaker 1: I actually drive a hybrid that is like all right,

266
00:15:56,200 --> 00:16:00,200
Speaker 1: and you're getting there and halfway back on that. Sure,

267
00:16:01,120 --> 00:16:05,520
Speaker 1: I'm just trying to justify my my point here, which

268
00:16:05,600 --> 00:16:10,120
Speaker 1: is that it's always better to be to be transported

269
00:16:10,480 --> 00:16:15,240
Speaker 1: than to transport oneself. Yeah. The one thing that I

270
00:16:15,280 --> 00:16:18,680
Speaker 1: feel like I am underdoing with road trips is like

271
00:16:20,360 --> 00:16:23,680
Speaker 1: the like stop offs, like if there if I had

272
00:16:23,720 --> 00:16:26,680
Speaker 1: a good way to like Google okay along this route,

273
00:16:26,720 --> 00:16:28,800
Speaker 1: like this is a cool little town that you could

274
00:16:28,800 --> 00:16:32,280
Speaker 1: stop in. You know. I always hear about them from

275
00:16:32,520 --> 00:16:37,040
Speaker 1: people who took road trips before there was you know,

276
00:16:37,160 --> 00:16:39,960
Speaker 1: navigational systems that just took you exactly where you needed

277
00:16:39,960 --> 00:16:42,320
Speaker 1: to go, independent of like what was along the way.

278
00:16:43,480 --> 00:16:46,040
Speaker 1: I feel like that's one thing that I am underdoing.

279
00:16:46,080 --> 00:16:49,880
Speaker 1: I I agree with you guys, especially because my family

280
00:16:49,920 --> 00:16:53,200
Speaker 1: all immediately goes to sleep and I just drive by

281
00:16:53,240 --> 00:16:55,840
Speaker 1: myself the whole way, and then they're like, can you

282
00:16:55,880 --> 00:16:59,040
Speaker 1: turn your podcast down? Like, oh, so you want to

283
00:16:59,040 --> 00:17:01,480
Speaker 1: sleep in a fucking silent chamber so I can doze

284
00:17:01,480 --> 00:17:05,760
Speaker 1: off at the wheel to Yeah, exactly, the I do.

285
00:17:05,880 --> 00:17:08,800
Speaker 1: I the one time I was with somebody who does

286
00:17:09,000 --> 00:17:11,359
Speaker 1: who like road trips enough that they were like, no,

287
00:17:11,480 --> 00:17:14,280
Speaker 1: we're gonna stop here, like we're gonna hit Gilroy and

288
00:17:14,320 --> 00:17:15,960
Speaker 1: I'm like, yeah, it's gonna take like I just want

289
00:17:15,960 --> 00:17:18,919
Speaker 1: to get there. They're like, you'll try try this version

290
00:17:19,000 --> 00:17:21,240
Speaker 1: because you break it up along the way. And then

291
00:17:21,280 --> 00:17:23,959
Speaker 1: we saw where James Dean died and ship I have

292
00:17:24,000 --> 00:17:27,320
Speaker 1: stopped there, but inadvertently, Yeah, So like that's the thing.

293
00:17:27,400 --> 00:17:31,399
Speaker 1: I inadvertently come across these things where it's like Shepherd's

294
00:17:31,440 --> 00:17:35,080
Speaker 1: Bread from like Scotland, the best bread in like west

295
00:17:35,119 --> 00:17:37,760
Speaker 1: of the Mississippi, and there's like a line wrapping around

296
00:17:37,800 --> 00:17:39,920
Speaker 1: the block. But I'm never like in a position where

297
00:17:39,920 --> 00:17:41,959
Speaker 1: I'm like, oh, let's stop and like kick it here

298
00:17:42,000 --> 00:17:44,959
Speaker 1: for an hour. So that's what like if I just

299
00:17:45,200 --> 00:17:48,120
Speaker 1: built in the time on road trips and like road

300
00:17:48,160 --> 00:17:53,080
Speaker 1: tripped like a like a dead from the fifties. You know,

301
00:17:54,160 --> 00:17:57,040
Speaker 1: I was making the one map with all the business

302
00:17:57,040 --> 00:17:58,920
Speaker 1: owners that are like this is the one way there

303
00:17:59,240 --> 00:18:03,080
Speaker 1: and said you will patronize along the way, right throw

304
00:18:03,160 --> 00:18:07,560
Speaker 1: back to a triptych. Yeah yeah, And what is something

305
00:18:07,600 --> 00:18:11,040
Speaker 1: you think is underrated? Click? I'm gonna sound so basic,

306
00:18:11,400 --> 00:18:17,080
Speaker 1: but and something I think is underrated? Is sleep? I

307
00:18:17,080 --> 00:18:20,320
Speaker 1: I love sleep. I really highly value it, and yet

308
00:18:20,440 --> 00:18:24,359
Speaker 1: somehow I never prioritize it. Every single night. I'm like,

309
00:18:24,480 --> 00:18:26,760
Speaker 1: I could go to sleep now, or I could just

310
00:18:26,920 --> 00:18:30,359
Speaker 1: stay up watching some Netflix show that I actually don't

311
00:18:30,359 --> 00:18:33,359
Speaker 1: care about. I just I am not ready to to,

312
00:18:33,720 --> 00:18:37,919
Speaker 1: you know, face my demons and my subconscious and I

313
00:18:37,920 --> 00:18:40,640
Speaker 1: think it's underrated. I actually heard someone say the other

314
00:18:40,720 --> 00:18:43,840
Speaker 1: day that classic refrain of I'll sleep when I'm dead,

315
00:18:44,600 --> 00:18:47,240
Speaker 1: and I was like, no, honey, I'm sleeping when I'm alive.

316
00:18:48,359 --> 00:18:50,440
Speaker 1: This is the joy of living, is that we get

317
00:18:50,480 --> 00:18:54,280
Speaker 1: to sleep. Yeah, I don't get to enjoy that ship

318
00:18:54,320 --> 00:18:56,600
Speaker 1: when I'm dying. It's not like you have a RESTful

319
00:18:56,760 --> 00:18:59,920
Speaker 1: pre death period like that. It hurts, Yeah, when you're

320
00:19:00,080 --> 00:19:03,080
Speaker 1: about to die. You man, you're tripping that whole time.

321
00:19:03,160 --> 00:19:05,239
Speaker 1: It's a head trip that whole time when you are

322
00:19:05,359 --> 00:19:07,800
Speaker 1: truly on your deathbed. I mean, like watching that happen

323
00:19:07,840 --> 00:19:09,880
Speaker 1: to a few family members, like it's you know, it's

324
00:19:09,920 --> 00:19:12,000
Speaker 1: you can be peaceful, but it's not a thing. You're like, damn,

325
00:19:12,000 --> 00:19:13,679
Speaker 1: you know, I'm just looking for the sleep. You know.

326
00:19:15,680 --> 00:19:19,480
Speaker 1: It's like a good parent to You're like, who say

327
00:19:21,200 --> 00:19:26,280
Speaker 1: start being around so much wasted time. Right, I didn't

328
00:19:26,280 --> 00:19:29,840
Speaker 1: project my past trauma was onto you via your parents.

329
00:19:29,880 --> 00:19:34,080
Speaker 1: I'm like, look, you just just rest up, you could, right.

330
00:19:34,119 --> 00:19:36,680
Speaker 1: But yeah, the sleep thing is you know, the when

331
00:19:36,680 --> 00:19:39,360
Speaker 1: I a few weeks ago, we talked about this sort

332
00:19:39,359 --> 00:19:42,320
Speaker 1: of phenomenon about how people are procrastinating with their sleep,

333
00:19:42,359 --> 00:19:44,399
Speaker 1: and like, there's a few things. Some of it is

334
00:19:44,440 --> 00:19:47,399
Speaker 1: like the idea of trying to regain moments from your

335
00:19:47,440 --> 00:19:50,040
Speaker 1: day that you feel we're lost through having to work

336
00:19:50,160 --> 00:19:52,919
Speaker 1: or other things. So part of it is like this

337
00:19:53,000 --> 00:19:55,640
Speaker 1: rebellious act before we're going to sleep, of like I'm

338
00:19:55,640 --> 00:19:57,399
Speaker 1: gonna look at my fucking phone because I don't I

339
00:19:57,400 --> 00:19:59,600
Speaker 1: didn't have enough time to do my ship today, and

340
00:19:59,680 --> 00:20:02,080
Speaker 1: I'm gonna watch like in your case of shitty Netflix

341
00:20:02,080 --> 00:20:05,640
Speaker 1: show that you're not even sure why you're watching it. Yeah,

342
00:20:05,680 --> 00:20:09,439
Speaker 1: I'm an adult, damn it. The second I kind of

343
00:20:09,440 --> 00:20:13,439
Speaker 1: realized about like sort of that phenomenon, I really try

344
00:20:13,480 --> 00:20:17,199
Speaker 1: and keep the screen ship away towards the end. But

345
00:20:17,320 --> 00:20:20,760
Speaker 1: it's tough. It is sometimes because you know, I'm also

346
00:20:20,840 --> 00:20:22,800
Speaker 1: like a kid who would try to go to sleep

347
00:20:22,840 --> 00:20:24,480
Speaker 1: with a TV on it every now and then. So

348
00:20:25,280 --> 00:20:28,160
Speaker 1: it does, it does sort of lull me for sure,

349
00:20:28,480 --> 00:20:31,160
Speaker 1: but it's also like I'm trying to, as you said,

350
00:20:31,240 --> 00:20:36,320
Speaker 1: like make that period of my day sacred in the

351
00:20:36,359 --> 00:20:39,800
Speaker 1: sense that, you know, maybe I can find other times

352
00:20:39,800 --> 00:20:42,480
Speaker 1: in my day to watch these television shows which I

353
00:20:42,760 --> 00:20:44,760
Speaker 1: you know, some of which I do love and engage with.

354
00:20:45,040 --> 00:20:49,000
Speaker 1: What if I can make my evening time about like

355
00:20:49,160 --> 00:20:52,320
Speaker 1: reading before bed or journaling before bed, or you know,

356
00:20:52,400 --> 00:20:55,919
Speaker 1: something that will be stimulating in its own way and

357
00:20:56,160 --> 00:21:00,320
Speaker 1: fulfilling and sort of fill the same need, but won't

358
00:21:00,359 --> 00:21:03,880
Speaker 1: be like blue light beaming straight into my eyeballs at

359
00:21:04,920 --> 00:21:07,640
Speaker 1: you know. That's why I like sleep podcasts have been

360
00:21:07,640 --> 00:21:10,440
Speaker 1: the thing I've been trying to replace in the like

361
00:21:10,640 --> 00:21:14,320
Speaker 1: I'm kind of want some kind of stimulation, information, entertainment,

362
00:21:14,359 --> 00:21:17,960
Speaker 1: but like not intense like watching the comedy or whatever,

363
00:21:18,720 --> 00:21:21,680
Speaker 1: sports highlights or whatever, because like the real the ship

364
00:21:21,840 --> 00:21:24,679
Speaker 1: that's like half sleep hypnosis or it's just kind of

365
00:21:25,000 --> 00:21:27,560
Speaker 1: a walking through just checking in with your breathing and

366
00:21:27,600 --> 00:21:31,560
Speaker 1: your body and then transitions into like the most dry

367
00:21:31,600 --> 00:21:35,000
Speaker 1: like reading of like Alice in Wonderland. I find myself

368
00:21:35,000 --> 00:21:38,919
Speaker 1: be like, oh, here we go, it's so fun. My

369
00:21:38,960 --> 00:21:41,480
Speaker 1: AirPods out my ears. I'm like fuck them, don't even

370
00:21:41,560 --> 00:21:44,080
Speaker 1: let them hard. I'm like, I have to transition to

371
00:21:44,200 --> 00:21:47,080
Speaker 1: sleep real quick, and I can't like interet okay, now

372
00:21:47,200 --> 00:21:49,320
Speaker 1: put it in the case and charge. I'm like that

373
00:21:50,520 --> 00:21:54,040
Speaker 1: children's stories really do it for me. Man, Like I

374
00:21:54,040 --> 00:21:57,359
Speaker 1: I read my kids four bedtime stories, and by number

375
00:21:57,440 --> 00:22:01,280
Speaker 1: three I am like nodding. Um. I do drop a

376
00:22:01,280 --> 00:22:06,679
Speaker 1: couple of ambient before, just to you know, I don't know,

377
00:22:07,080 --> 00:22:11,760
Speaker 1: not children's literature the original ambient because it's nonsense, uh

378
00:22:11,880 --> 00:22:16,120
Speaker 1: pretty boring, but very uh you know, unobtrusive. I think

379
00:22:16,359 --> 00:22:19,120
Speaker 1: also it's a good sign that I'm sleep deprived that

380
00:22:19,720 --> 00:22:23,000
Speaker 1: whenever I just like sit down and read for twenty

381
00:22:23,040 --> 00:22:26,080
Speaker 1: minutes straight, I'm just like, I can't. I can't keep

382
00:22:26,080 --> 00:22:30,080
Speaker 1: my fucking eyes open, right, yes, yeah, but my kids can.

383
00:22:30,800 --> 00:22:32,639
Speaker 1: And then they're in charge of the house for a

384
00:22:32,680 --> 00:22:35,840
Speaker 1: couple of hours while I'm asleep on their floor. That's

385
00:22:35,840 --> 00:22:38,840
Speaker 1: always my favorite is my friends with kids, like seeing

386
00:22:38,880 --> 00:22:44,200
Speaker 1: like nannicam footage of like one parent asleep, like trying

387
00:22:44,240 --> 00:22:45,879
Speaker 1: to read the kid a story and the kids just

388
00:22:46,040 --> 00:22:47,840
Speaker 1: up like taking the book from them and just like

389
00:22:47,880 --> 00:22:53,960
Speaker 1: doing it themselves. I love it. The kids are partying, yeah, yeah, yeah,

390
00:22:54,000 --> 00:22:57,240
Speaker 1: because that's also the time, like sleeping adults, I learned

391
00:22:57,280 --> 00:22:59,560
Speaker 1: the most about the human body. Those times, like looking

392
00:22:59,640 --> 00:23:03,280
Speaker 1: up my grandma's nose and ship like just pulling on

393
00:23:03,359 --> 00:23:05,959
Speaker 1: like my my grandpa's hairy ear or something like that,

394
00:23:06,000 --> 00:23:08,159
Speaker 1: Like those are those are the moments you remember as

395
00:23:08,160 --> 00:23:10,959
Speaker 1: a kid. Yeah, I used to when I, um, when

396
00:23:11,000 --> 00:23:14,040
Speaker 1: I was learning how to drive. My goal. My dad

397
00:23:14,160 --> 00:23:18,040
Speaker 1: is a pilot, and he's very like he pilots whatever

398
00:23:18,160 --> 00:23:20,239
Speaker 1: car he's in as well. You know, he's always like

399
00:23:20,680 --> 00:23:23,000
Speaker 1: your head's on a swivel. He's like swinging his head

400
00:23:23,040 --> 00:23:30,040
Speaker 1: around and we're like, um, and he was always talking

401
00:23:30,040 --> 00:23:34,479
Speaker 1: about how you like need to have your like slow

402
00:23:34,640 --> 00:23:37,840
Speaker 1: what would he say, slow down into a stop sign

403
00:23:37,920 --> 00:23:40,639
Speaker 1: and then like accelerate through the turn like all of

404
00:23:40,680 --> 00:23:43,480
Speaker 1: these things. And so my goal was always when I

405
00:23:43,520 --> 00:23:46,679
Speaker 1: had him in the passenger seat, was to sort of

406
00:23:46,720 --> 00:23:50,040
Speaker 1: like be such a smooth driver that he would nod

407
00:23:50,119 --> 00:23:53,480
Speaker 1: off and he would fall asleep and he would sort

408
00:23:53,480 --> 00:23:58,080
Speaker 1: of like nod out, and then somehow while he's still asleep,

409
00:23:58,080 --> 00:24:01,440
Speaker 1: he'd be like you need to stop it that stops.

410
00:24:00,720 --> 00:24:06,280
Speaker 1: Like I mean, he's like a black him. He has

411
00:24:06,320 --> 00:24:08,959
Speaker 1: like one eye open, so a side visible to you.

412
00:24:09,080 --> 00:24:11,520
Speaker 1: He's asleep with that other eyes like scanning the road

413
00:24:11,920 --> 00:24:14,560
Speaker 1: right exactly. His head's on as livel Wow. I like

414
00:24:14,640 --> 00:24:16,920
Speaker 1: that he's giving you like real like racing stuff like

415
00:24:16,920 --> 00:24:19,120
Speaker 1: you gotta hit the apex of the term and then

416
00:24:19,160 --> 00:24:21,720
Speaker 1: you bring decelerate into and then accelerate out and he's

417
00:24:21,960 --> 00:24:24,640
Speaker 1: you know, this triple a force to launch you out. Yes,

418
00:24:24,920 --> 00:24:29,440
Speaker 1: my dad is Capricorn. He's like deep Earth sign vibes.

419
00:24:29,560 --> 00:24:32,960
Speaker 1: Everything about him is practical. He always wants to give

420
00:24:33,080 --> 00:24:36,720
Speaker 1: like advice and tips. He can't just be like this

421
00:24:36,760 --> 00:24:39,000
Speaker 1: is a great day. He has to be like, well

422
00:24:39,040 --> 00:24:43,560
Speaker 1: today it's beautiful because you know, like metric pressure that

423
00:24:43,640 --> 00:24:46,639
Speaker 1: I think is really underrated or misunderstood. But you know,

424
00:24:46,680 --> 00:24:49,240
Speaker 1: it's so funny. He when you say, like my dad's

425
00:24:49,240 --> 00:24:51,560
Speaker 1: a pilot, My almost things like I'm guessing he's like

426
00:24:51,640 --> 00:24:54,960
Speaker 1: all of my friends parents or dads specifically have like

427
00:24:54,960 --> 00:24:58,200
Speaker 1: like a firefighter or like pilot. They're all like these

428
00:24:58,240 --> 00:25:01,879
Speaker 1: like wells of infinite like just wisdom. Sometimes you're not

429
00:25:01,960 --> 00:25:07,560
Speaker 1: really even asking for it, but it's not sometimes Yeah, okay,

430
00:25:07,560 --> 00:25:10,560
Speaker 1: so you're exactly like my friend, my own girl's dad

431
00:25:10,560 --> 00:25:13,720
Speaker 1: who's a firefighter, who just called us through, Like, man,

432
00:25:13,760 --> 00:25:18,399
Speaker 1: this guy hasn't looked like this in three years, right, Like, okay, cool,

433
00:25:19,560 --> 00:25:21,880
Speaker 1: that's cool. I want to hear more about that. So

434
00:25:22,040 --> 00:25:25,000
Speaker 1: that's clearly me being a dad. I'm like, this guy

435
00:25:25,080 --> 00:25:28,200
Speaker 1: is like what I'm complaining. Two characters from my life,

436
00:25:28,520 --> 00:25:31,960
Speaker 1: Robert the the proper fire Chief will come through. He's

437
00:25:31,960 --> 00:25:33,800
Speaker 1: a kind of dude who like he'll come to your

438
00:25:33,800 --> 00:25:35,760
Speaker 1: house and be like whoa, whoa, whoa, what's going on

439
00:25:35,840 --> 00:25:39,000
Speaker 1: that light socket? Hold on? Hold on, hold on, hold on. Yeah,

440
00:25:39,080 --> 00:25:41,680
Speaker 1: oh see it sounded like it wasn't grounded. I could

441
00:25:41,720 --> 00:25:46,040
Speaker 1: hear it from here. You're like my parents. So my

442
00:25:46,119 --> 00:25:50,960
Speaker 1: parents are staying with me right now, and they it's

443
00:25:50,960 --> 00:25:53,720
Speaker 1: been great. They're they're great with the kids. The kids

444
00:25:54,119 --> 00:25:56,679
Speaker 1: love hanging out with them. But I'm seeing all like

445
00:25:56,720 --> 00:25:59,720
Speaker 1: we've got plumbing issues going on that like I had

446
00:25:59,800 --> 00:26:02,440
Speaker 1: just like it's like a fire alarm that's law on

447
00:26:02,480 --> 00:26:05,680
Speaker 1: batteries that you just kind of silence with your brain. Yeah,

448
00:26:05,680 --> 00:26:08,280
Speaker 1: I just got used to it, but now I'm just like,

449
00:26:08,359 --> 00:26:11,679
Speaker 1: oh man, I'm I am slacking. Like my name's like

450
00:26:12,040 --> 00:26:18,080
Speaker 1: you're pipe sure bang a lot? What the hell is that? Like? Like, oh,

451
00:26:18,080 --> 00:26:22,640
Speaker 1: it's because I am not. Yeah, see, you just gotta

452
00:26:22,640 --> 00:26:28,679
Speaker 1: follow through talking about all right, Clarie, I do have

453
00:26:28,760 --> 00:26:32,199
Speaker 1: to ask it, did your dad ever talk about encounters

454
00:26:32,680 --> 00:26:37,480
Speaker 1: with unidentified flying objects? The only time he's ever mentioned

455
00:26:37,520 --> 00:26:41,080
Speaker 1: it was when we were This is incredibly misleading, so

456
00:26:41,200 --> 00:26:44,639
Speaker 1: I apologize, but because I see you're getting excited. No,

457
00:26:44,720 --> 00:26:46,240
Speaker 1: I mean either way it's I think it will either

458
00:26:46,440 --> 00:26:48,359
Speaker 1: be it'll pay off on the premise, or it'll be

459
00:26:48,400 --> 00:26:52,320
Speaker 1: a fantastic turn. So it's really it's more like a

460
00:26:52,440 --> 00:26:55,080
Speaker 1: cute God. I feel like I've really set this up

461
00:26:55,119 --> 00:26:58,600
Speaker 1: to fail. We we were young, and he came back.

462
00:26:59,040 --> 00:27:02,120
Speaker 1: He flew for ups Us for basically all my life

463
00:27:02,160 --> 00:27:07,160
Speaker 1: until last January and like the January of the pandemic

464
00:27:07,240 --> 00:27:12,120
Speaker 1: jan and he was flying back from China or somewhere

465
00:27:12,200 --> 00:27:15,520
Speaker 1: on Christmas Eve and he came into our rooms and

466
00:27:15,560 --> 00:27:17,119
Speaker 1: he was like, you have to go to bed now,

467
00:27:17,680 --> 00:27:20,560
Speaker 1: because as I was flying, I saw this this flashing

468
00:27:20,640 --> 00:27:23,960
Speaker 1: red light out of the side of the plane, and

469
00:27:24,000 --> 00:27:26,160
Speaker 1: we we sped up so that we could we could

470
00:27:26,200 --> 00:27:28,879
Speaker 1: beat him here because I think it was Santa, and

471
00:27:29,359 --> 00:27:31,159
Speaker 1: my sister and I were like, oh my God, like

472
00:27:32,400 --> 00:27:37,040
Speaker 1: rooms like covered our heads. The original unidentified flying object,

473
00:27:37,119 --> 00:27:40,240
Speaker 1: you know, I mean it was unidentified. People think that Santa,

474
00:27:40,320 --> 00:27:42,800
Speaker 1: but we didn't. We don't know. People think I'm in

475
00:27:42,800 --> 00:27:44,960
Speaker 1: the bad for aliens. I am just as willing to

476
00:27:45,000 --> 00:27:47,399
Speaker 1: believe that that white tic tac is Santa. That is

477
00:27:47,520 --> 00:27:52,639
Speaker 1: just delivering technical that we don't know about. It could be.

478
00:27:52,760 --> 00:27:56,160
Speaker 1: It could be alien life, could be Santa could be

479
00:27:56,280 --> 00:27:59,640
Speaker 1: literally anything. It could be, you know what I mean.

480
00:28:00,640 --> 00:28:02,840
Speaker 1: That's where she's been. Yeah, she was like, oh man,

481
00:28:02,840 --> 00:28:05,600
Speaker 1: I'm gonna take off on their regular as spacecraft and

482
00:28:05,760 --> 00:28:09,159
Speaker 1: switch it off from my turn up spacecraft. Time is

483
00:28:09,200 --> 00:28:18,919
Speaker 1: relative in space, right, Yeah, I think it's all right.

484
00:28:19,119 --> 00:28:21,160
Speaker 1: Let's take a quick break and won't be right back

485
00:28:31,359 --> 00:28:35,520
Speaker 1: and we're back. And uh so was it Andrew Giuliani

486
00:28:35,880 --> 00:28:39,240
Speaker 1: The last time we were talking about him, he was

487
00:28:39,280 --> 00:28:45,720
Speaker 1: holding down the all important prestigious position as uh sports

488
00:28:45,800 --> 00:28:51,160
Speaker 1: are for the White House? Is that what he was doing?

489
00:28:51,240 --> 00:28:55,080
Speaker 1: It was like the administration. It was just the most

490
00:28:55,120 --> 00:28:59,640
Speaker 1: tacked on. My dad's your friend. Can you give me

491
00:28:59,680 --> 00:29:03,440
Speaker 1: a my dad's one of your shitty henchman will shut

492
00:29:03,520 --> 00:29:05,920
Speaker 1: him up if you get me his useless kid a

493
00:29:06,040 --> 00:29:11,480
Speaker 1: job serving McDonald's food to college champion athletes and was

494
00:29:11,520 --> 00:29:14,240
Speaker 1: one of his things. The first well, what's he into?

495
00:29:14,680 --> 00:29:20,280
Speaker 1: I don't know, sports, Okay, final liaison, the sports, I

496
00:29:20,320 --> 00:29:24,840
Speaker 1: guess yeah. And you know, like any you know child

497
00:29:24,880 --> 00:29:28,320
Speaker 1: who has benefited from just the kind of grotesque nepotism

498
00:29:28,360 --> 00:29:32,080
Speaker 1: that he has, it's only logical that at thirty five

499
00:29:32,160 --> 00:29:35,320
Speaker 1: years old he's saying, you know what, I'm gonna run

500
00:29:35,360 --> 00:29:39,719
Speaker 1: for governor of New York State, even though I worked

501
00:29:39,760 --> 00:29:42,320
Speaker 1: in the Trump administration and I'm real loud about it,

502
00:29:42,680 --> 00:29:44,680
Speaker 1: and even though this is a state where Trump had

503
00:29:44,720 --> 00:29:49,560
Speaker 1: no chance in I'm out here running against Cuomo. And

504
00:29:49,920 --> 00:29:52,920
Speaker 1: there's a few clips I want to play because you know,

505
00:29:53,080 --> 00:29:56,800
Speaker 1: we we referenced earlier on like in the nineties when

506
00:29:56,840 --> 00:29:59,880
Speaker 1: Giuliani his dad was mayor, Like he was like interrupting

507
00:30:00,040 --> 00:30:02,760
Speaker 1: what was it the inauguration or something, he's swearing in ceremony,

508
00:30:03,320 --> 00:30:05,520
Speaker 1: just like tugging on it, trying to talk on the microphone.

509
00:30:05,520 --> 00:30:09,760
Speaker 1: And Ship, She's always had opinions. There's some straight up

510
00:30:09,800 --> 00:30:13,920
Speaker 1: like adorable kid, Ship, but his vibes were such that

511
00:30:14,120 --> 00:30:16,680
Speaker 1: and this is like as a as a young child,

512
00:30:16,720 --> 00:30:20,040
Speaker 1: like this is not in no way excusable, but people

513
00:30:20,080 --> 00:30:23,160
Speaker 1: were like, man, I hate that kid like that. He

514
00:30:23,280 --> 00:30:27,360
Speaker 1: was like a child and everybody was just like, that

515
00:30:27,440 --> 00:30:31,240
Speaker 1: kid is annoying, we do not like him. That's iconic.

516
00:30:31,640 --> 00:30:34,240
Speaker 1: And then yeah, Chris Farley literally played him in an

517
00:30:34,320 --> 00:30:37,760
Speaker 1: SNL sketch where he was just it's Chris Farley playing

518
00:30:40,200 --> 00:30:42,640
Speaker 1: They gave him big buck teeth and it was it

519
00:30:42,760 --> 00:30:46,800
Speaker 1: was literally like probably the meanest thing SNL has ever done. Yeah,

520
00:30:46,840 --> 00:30:49,200
Speaker 1: going after a kid, for sure, but after an eight

521
00:30:49,280 --> 00:30:51,320
Speaker 1: year old and giving him buck teeth and just making

522
00:30:51,360 --> 00:30:55,720
Speaker 1: him be like damn, like just get and then get

523
00:30:55,800 --> 00:30:58,920
Speaker 1: hit in the head repeatedly. It was. It was pretty wild.

524
00:30:59,320 --> 00:31:01,920
Speaker 1: There's a different time, yeah, And so I just want

525
00:31:01,960 --> 00:31:03,720
Speaker 1: to play a few clips. The first one is when

526
00:31:03,720 --> 00:31:09,280
Speaker 1: he's announcing his run for mayor, and it's this is

527
00:31:09,280 --> 00:31:11,960
Speaker 1: a super cut and so you know, take that with

528
00:31:11,960 --> 00:31:14,040
Speaker 1: a grain of salt, but the words he's saying are accurate.

529
00:31:14,280 --> 00:31:17,360
Speaker 1: So this is him announcing his candidacy and what is

530
00:31:17,360 --> 00:31:19,600
Speaker 1: the statue of liberty which he also isn't sure if

531
00:31:19,600 --> 00:31:22,320
Speaker 1: that's what it is. Okay, Well, my fellow New Yorkers,

532
00:31:22,400 --> 00:31:24,600
Speaker 1: it's a great or one. You all here today to

533
00:31:24,640 --> 00:31:27,520
Speaker 1: announce my fifth my candidacy to become the fifty seventh

534
00:31:27,600 --> 00:31:30,280
Speaker 1: governor of our great state of New York. Which one

535
00:31:30,320 --> 00:31:32,120
Speaker 1: is that? Is that Miss Manhattan or is that lady

536
00:31:32,400 --> 00:31:35,800
Speaker 1: that's Lady Liberty over there. So community, so he's an

537
00:31:35,800 --> 00:31:39,160
Speaker 1: active charter school, We'll get a charter school. I do

538
00:31:39,240 --> 00:31:42,280
Speaker 1: believe that people should be vaccinated. I am not vaccinated,

539
00:31:42,320 --> 00:31:44,960
Speaker 1: but I but I continually get tested with the antibodies.

540
00:31:45,200 --> 00:31:48,880
Speaker 1: You can't transmit. New York is truly that shining state

541
00:31:49,240 --> 00:31:59,040
Speaker 1: on the hill. That Burger, No, it's they're they're they're

542
00:31:59,080 --> 00:32:01,640
Speaker 1: doing big. They're even in the vic Burger treatment with

543
00:32:01,720 --> 00:32:03,640
Speaker 1: all the zoom it look vix changed the game. That's

544
00:32:03,680 --> 00:32:07,840
Speaker 1: the recount site. But what do you say as a

545
00:32:07,880 --> 00:32:11,480
Speaker 1: shining skate on the hill, shining state on a hill

546
00:32:11,640 --> 00:32:14,080
Speaker 1: to play on the shining city on a hill like

547
00:32:14,200 --> 00:32:19,360
Speaker 1: early American exceptionalism? Bullshit? What's the state on a skate

548
00:32:19,480 --> 00:32:23,440
Speaker 1: on a hill? State as in New York State. Oh,

549
00:32:24,640 --> 00:32:27,520
Speaker 1: it was just a mess. It's a mess. But the

550
00:32:27,960 --> 00:32:33,280
Speaker 1: just the opening. Okay, well, well New Yorkers, I want

551
00:32:33,280 --> 00:32:35,920
Speaker 1: to be the fifth weight. Um, I'm running for the

552
00:32:37,200 --> 00:32:43,560
Speaker 1: like like legit legitimately tam the energy of let's just

553
00:32:43,600 --> 00:32:48,120
Speaker 1: get the shipped over with okay and like combative immediately

554
00:32:48,760 --> 00:32:51,760
Speaker 1: like okay, alright, so yeah, I know what you're gonna say,

555
00:32:51,840 --> 00:32:56,720
Speaker 1: but uh, let me finish stop so he called. Like

556
00:32:56,920 --> 00:33:00,160
Speaker 1: later on, he was on Fox yesterday talking again, I'm

557
00:33:00,240 --> 00:33:03,680
Speaker 1: running for governor. I'm running for the governor's Governor's mansion

558
00:33:03,720 --> 00:33:07,800
Speaker 1: against Andrew Cuomo. And this is where this is where

559
00:33:07,800 --> 00:33:09,720
Speaker 1: he goes on Fox. So you know, it's the home

560
00:33:09,800 --> 00:33:11,680
Speaker 1: home field advantage, so he can say all kinds of

561
00:33:11,720 --> 00:33:13,760
Speaker 1: bullshit and they're not going to question it. But this

562
00:33:13,800 --> 00:33:17,000
Speaker 1: is where he really talks up his qualifications and as

563
00:33:17,000 --> 00:33:20,440
Speaker 1: we said earlier, our fuck all. So listen to how

564
00:33:20,520 --> 00:33:23,080
Speaker 1: this man is up selling his ship. Like like when

565
00:33:23,080 --> 00:33:24,680
Speaker 1: you just got out of college and you're trying to

566
00:33:24,680 --> 00:33:26,480
Speaker 1: get a job and you like, you need five experience

567
00:33:26,520 --> 00:33:28,040
Speaker 1: for this entry level job, and you're like, oh, yeah,

568
00:33:28,040 --> 00:33:31,800
Speaker 1: bet I got five experience. I started listen to him

569
00:33:31,880 --> 00:33:35,040
Speaker 1: the Treasury Department out of the public Liaison. And the

570
00:33:35,040 --> 00:33:38,360
Speaker 1: truth is, Martha, from an experienced perspective, I maybe thirty

571
00:33:38,360 --> 00:33:40,920
Speaker 1: five years old, but you gotta remember I spent thirty

572
00:33:40,920 --> 00:33:44,000
Speaker 1: two years parts of thirty two years in politics and

573
00:33:44,080 --> 00:33:48,040
Speaker 1: in government. Um I mean only uh announced candidate that

574
00:33:48,120 --> 00:33:51,920
Speaker 1: actually has spent parts of five decades in politics. So

575
00:33:52,040 --> 00:33:56,480
Speaker 1: I may look young, but I certainly feel a lot older. Um,

576
00:33:56,720 --> 00:34:00,760
Speaker 1: you know, running to be the republic in nominee. He's

577
00:34:00,840 --> 00:34:06,440
Speaker 1: already so uh yeah. He said he's been five motherfucking

578
00:34:06,520 --> 00:34:11,120
Speaker 1: decades on the set. Like, what are you talking about, sir?

579
00:34:11,840 --> 00:34:15,320
Speaker 1: Five of five decades? What does that mean? I'm guessing

580
00:34:15,320 --> 00:34:19,680
Speaker 1: because he was born in the eighties, then his dad

581
00:34:19,760 --> 00:34:24,680
Speaker 1: was working in politics the eighties and nineties, two thousand

582
00:34:25,200 --> 00:34:29,719
Speaker 1: to the odds, the teens, and now the twenties. I

583
00:34:29,719 --> 00:34:32,520
Speaker 1: think he's just basically saying I've been alive over what

584
00:34:32,640 --> 00:34:36,040
Speaker 1: has been five different decades. Because I've checked the math.

585
00:34:36,160 --> 00:34:39,200
Speaker 1: He said, I got look up in thirty two years

586
00:34:39,280 --> 00:34:44,680
Speaker 1: on the set in d C. Baby doing politics. That's

587
00:34:44,719 --> 00:34:48,440
Speaker 1: just gonna say, how do you like my brain? I mean,

588
00:34:48,520 --> 00:34:51,040
Speaker 1: I've already shown on this podcast and I'm not great

589
00:34:51,080 --> 00:34:54,799
Speaker 1: at math, but I do know that thirty five is

590
00:34:54,840 --> 00:35:03,040
Speaker 1: not fifty and that's just basic math. I'm so I'm

591
00:35:03,080 --> 00:35:05,560
Speaker 1: so confused. So is he claiming that he was involved

592
00:35:05,560 --> 00:35:09,359
Speaker 1: in politics as a four year old? Yes, that's absolutely

593
00:35:09,360 --> 00:35:13,680
Speaker 1: what he's like. That's but I mean, that's the kind

594
00:35:13,680 --> 00:35:15,600
Speaker 1: of show. You know, like when you meet people like

595
00:35:15,760 --> 00:35:18,120
Speaker 1: and this happens a lot, especially growing up in l A.

596
00:35:18,800 --> 00:35:21,319
Speaker 1: There are people have the same mindset about them their

597
00:35:21,360 --> 00:35:25,120
Speaker 1: relationship to production or the entertainment industry. They were like, well,

598
00:35:25,160 --> 00:35:28,400
Speaker 1: you know, I've been like like writing for like fifteen years.

599
00:35:28,520 --> 00:35:30,680
Speaker 1: You're like, you're twenty six, what are you talking about?

600
00:35:31,200 --> 00:35:32,920
Speaker 1: And they're like, well, obviously, you know, like my dad's

601
00:35:32,920 --> 00:35:36,200
Speaker 1: a writer, so like I've always been around it, and

602
00:35:36,280 --> 00:35:38,840
Speaker 1: like so then I started like working on stuff in

603
00:35:38,880 --> 00:35:42,200
Speaker 1: fifth grade. I remember I wrote my first sketch and

604
00:35:42,280 --> 00:35:44,320
Speaker 1: so yeah, I've been doing this for like a minute.

605
00:35:44,320 --> 00:35:47,400
Speaker 1: I'm like, well that's a stretch. But it's like the

606
00:35:47,440 --> 00:35:50,120
Speaker 1: same logic you see applied of like I come from

607
00:35:50,160 --> 00:35:53,480
Speaker 1: this family, so I can claim from birth that I've

608
00:35:53,520 --> 00:36:00,160
Speaker 1: been in this ship, conflating proximity with experience, and you

609
00:36:00,239 --> 00:36:04,720
Speaker 1: know that that like anybody who I've ever encountered who's

610
00:36:04,760 --> 00:36:07,600
Speaker 1: like that, who didn't earn their own stripes but is

611
00:36:07,640 --> 00:36:11,160
Speaker 1: trying to like draft off of that, they are a

612
00:36:11,800 --> 00:36:14,920
Speaker 1: fucking terrible Like they're just terrible to be around because

613
00:36:14,960 --> 00:36:17,799
Speaker 1: they know they know they're fooliship, they know that that's

614
00:36:17,840 --> 00:36:20,640
Speaker 1: not how it works. They know that, like they're they

615
00:36:20,680 --> 00:36:24,279
Speaker 1: did not earn their way there, and they're awful, Like

616
00:36:24,360 --> 00:36:26,839
Speaker 1: it's they know just as well as you. Now they're

617
00:36:26,880 --> 00:36:29,680
Speaker 1: not maybe they're not like talking about that in their

618
00:36:29,719 --> 00:36:32,600
Speaker 1: mind with the conscious part of their mind, but uh,

619
00:36:32,680 --> 00:36:35,320
Speaker 1: there's a big part of them that is like it's

620
00:36:35,360 --> 00:36:37,800
Speaker 1: a lie. It's a lot spending a lot of energy

621
00:36:37,840 --> 00:36:41,640
Speaker 1: holding that, it's a live voice down. Yeah. I hate

622
00:36:41,680 --> 00:36:45,360
Speaker 1: to bring this point up because in the context of

623
00:36:45,840 --> 00:36:49,440
Speaker 1: the moment, we are meant to be body positive and

624
00:36:49,480 --> 00:36:53,440
Speaker 1: we are not meant to be commenting on people's appearance.

625
00:36:54,000 --> 00:36:57,279
Speaker 1: So instead of saying what first came to mind when

626
00:36:57,280 --> 00:37:00,279
Speaker 1: I saw him, I will say, and I think the

627
00:37:00,320 --> 00:37:02,760
Speaker 1: listener will be able to get at what I'm saying.

628
00:37:03,040 --> 00:37:06,680
Speaker 1: He looks a lot like his father. Yeah, yeah, in

629
00:37:07,040 --> 00:37:10,440
Speaker 1: this cursed way. Yes, I say, this is about a

630
00:37:10,440 --> 00:37:13,040
Speaker 1: lot of Rudy energy. And the Trump kids too, It's

631
00:37:13,040 --> 00:37:17,160
Speaker 1: like they wear their father's karma on their face, like

632
00:37:17,360 --> 00:37:20,840
Speaker 1: and he has like this like yeah, like this is

633
00:37:20,880 --> 00:37:23,680
Speaker 1: probably what this is what the kid of Rudy looks like,

634
00:37:24,480 --> 00:37:29,799
Speaker 1: just like my dad. A magoon also feels really young

635
00:37:29,880 --> 00:37:33,839
Speaker 1: to me, and that is yes, he says, I may

636
00:37:33,920 --> 00:37:36,160
Speaker 1: look young, and I was like, oh, so this is

637
00:37:36,560 --> 00:37:39,920
Speaker 1: this is a delusional person. This is a person with

638
00:37:40,000 --> 00:37:43,200
Speaker 1: zero self awareness. Yeah, he looks like a hot like

639
00:37:43,520 --> 00:37:48,320
Speaker 1: spokesperson for like a benevolent Policeman's union society type dude,

640
00:37:48,360 --> 00:37:50,600
Speaker 1: you know what I mean. He looks like the cutest

641
00:37:50,640 --> 00:37:53,360
Speaker 1: boot liquer you could get for cops. But he also

642
00:37:53,440 --> 00:37:57,640
Speaker 1: seems like he has been studying Andrew and Chris Cuomo's

643
00:37:57,680 --> 00:38:01,000
Speaker 1: manner of speaking and has modeled his Like I thought

644
00:38:01,040 --> 00:38:04,880
Speaker 1: I was seeing like the third Cuomo brother speak, just

645
00:38:04,920 --> 00:38:07,600
Speaker 1: like in terms of his like how he approaches like

646
00:38:07,800 --> 00:38:10,319
Speaker 1: all right, look wait, like like just like that kind

647
00:38:10,320 --> 00:38:13,560
Speaker 1: of gruff like hey, I'm a New York I'm walking

648
00:38:13,640 --> 00:38:18,960
Speaker 1: here type of energy. This is the energy of politics

649
00:38:19,120 --> 00:38:22,400
Speaker 1: right now. Right like you're either on one end of

650
00:38:22,400 --> 00:38:25,279
Speaker 1: the spectrum of like a Joe Biden who's really you know,

651
00:38:25,400 --> 00:38:29,040
Speaker 1: sleepy and calming and that kind of vibe, or your

652
00:38:29,400 --> 00:38:33,120
Speaker 1: pure chaos, and it seems like there's nothing in between.

653
00:38:33,239 --> 00:38:36,680
Speaker 1: And it's also like every political party people are divided

654
00:38:36,680 --> 00:38:39,879
Speaker 1: between those two because you can't, yeah, like I think

655
00:38:40,040 --> 00:38:43,640
Speaker 1: right now to run as a like a Republican candidate,

656
00:38:43,680 --> 00:38:47,160
Speaker 1: as a you know, just straight up sis heat. Man,

657
00:38:47,920 --> 00:38:49,640
Speaker 1: you have to have the energy of a dude who

658
00:38:49,719 --> 00:38:51,839
Speaker 1: would get in a fight at a little league game,

659
00:38:53,200 --> 00:38:55,759
Speaker 1: like as a parent like that. There's no like you

660
00:38:55,800 --> 00:38:58,120
Speaker 1: don't want like people have the energy of like oh

661
00:38:58,160 --> 00:39:00,879
Speaker 1: that's a reasonable person like that. It's not in right now.

662
00:39:00,920 --> 00:39:03,680
Speaker 1: It's like this is the problem man, you know, because

663
00:39:03,680 --> 00:39:05,839
Speaker 1: we got anti fill out here and they're like, yeah

664
00:39:05,920 --> 00:39:08,880
Speaker 1: I need this, not like, um, I'm really concerned about

665
00:39:08,920 --> 00:39:10,520
Speaker 1: you know, the state of our community is there? Like

666
00:39:10,600 --> 00:39:14,160
Speaker 1: miss me with that ship, Yeah, give me the chaos.

667
00:39:15,080 --> 00:39:19,960
Speaker 1: Yeah mhm alright. Just pivoting off of that story of

668
00:39:20,320 --> 00:39:27,240
Speaker 1: like legacy political dynasty like in the making attempted political dynasties.

669
00:39:28,239 --> 00:39:31,960
Speaker 1: I just wanted to talk about this. Uh Yahoo's story, Yeah,

670
00:39:32,000 --> 00:39:35,000
Speaker 1: who my favorite news source. Uh. They had a story

671
00:39:35,040 --> 00:39:41,200
Speaker 1: about the young people in Massachusetts who are like basically

672
00:39:42,280 --> 00:39:47,239
Speaker 1: one of the most formidable forces in Massachusetts politics. There's

673
00:39:47,280 --> 00:39:50,319
Speaker 1: like a people claim there or described them as an

674
00:39:50,400 --> 00:39:55,680
Speaker 1: army of sixteen year old who helped defeat the Kennedy

675
00:39:55,760 --> 00:40:00,600
Speaker 1: Joseph Kennedy. I guess is that Kenny and Kenny Kenny. Yeah,

676
00:40:00,640 --> 00:40:05,640
Speaker 1: so they basically stopped a political entity from winning in Massachusetts.

677
00:40:06,640 --> 00:40:09,239
Speaker 1: I mean he wasn't doing that hot, but yeah right,

678
00:40:09,239 --> 00:40:11,800
Speaker 1: he wasn't. Like he's not he's a copy of a

679
00:40:11,840 --> 00:40:15,479
Speaker 1: copy of a copy. It's not like shocks getting lost.

680
00:40:15,680 --> 00:40:20,439
Speaker 1: But like they these kids are like they they say

681
00:40:20,440 --> 00:40:25,839
Speaker 1: they're like single handedly defeating the like establishment establish well,

682
00:40:25,960 --> 00:40:31,879
Speaker 1: like the consultants political complex, like that whole of Like

683
00:40:32,080 --> 00:40:35,839
Speaker 1: let me see your mobile phone contacts so I can

684
00:40:35,880 --> 00:40:38,640
Speaker 1: add up the money in their type bull What I

685
00:40:38,719 --> 00:40:40,560
Speaker 1: used to do is work for a company where you

686
00:40:40,600 --> 00:40:42,800
Speaker 1: go to a politicize someone running. You say, we're smarter

687
00:40:42,880 --> 00:40:44,759
Speaker 1: than you, so you need to give us this money

688
00:40:44,800 --> 00:40:46,719
Speaker 1: and then we'll tell you things so you can win.

689
00:40:47,480 --> 00:40:50,640
Speaker 1: And you may or may not, but we made some money.

690
00:40:50,680 --> 00:40:55,760
Speaker 1: They they all like kind of tie their um activism

691
00:40:55,840 --> 00:41:00,000
Speaker 1: to the Sanders campaign and you know, Elizabeth Warrens Canadida

692
00:41:00,040 --> 00:41:04,920
Speaker 1: di sees And it's just interesting how there seems to

693
00:41:04,920 --> 00:41:08,640
Speaker 1: be a thing that's happening with younger people where they're

694
00:41:08,680 --> 00:41:13,840
Speaker 1: actually connecting politics to like what they actually believe in,

695
00:41:14,040 --> 00:41:18,240
Speaker 1: as opposed to when I was their age, politics seemed

696
00:41:18,280 --> 00:41:23,239
Speaker 1: like a thing for people with law degrees who were

697
00:41:23,320 --> 00:41:27,120
Speaker 1: good at like pr spin and ship. Like they seem

698
00:41:27,200 --> 00:41:30,200
Speaker 1: to there seems to be a growing movement. Okay, here

699
00:41:30,200 --> 00:41:31,680
Speaker 1: are the things we care about. We care about like

700
00:41:31,719 --> 00:41:35,279
Speaker 1: climate change, and we care about like progressive policies and

701
00:41:35,400 --> 00:41:38,560
Speaker 1: like police reform, and so how do we get there?

702
00:41:38,960 --> 00:41:41,640
Speaker 1: And people have pointed out, you know, like after they

703
00:41:41,680 --> 00:41:45,520
Speaker 1: had that success, they have failed to get other more

704
00:41:45,600 --> 00:41:49,959
Speaker 1: progressive candidates across the line in defeating you know, more

705
00:41:50,360 --> 00:41:54,640
Speaker 1: centrist Democrats in Massachusetts. But they've all performed way better

706
00:41:54,760 --> 00:42:00,040
Speaker 1: than they had they would have otherwise and registered. It

707
00:42:00,239 --> 00:42:04,319
Speaker 1: is between eighteen to twenty four, shot up to in

708
00:42:04,360 --> 00:42:08,400
Speaker 1: the primary from six percent in ten and two percent

709
00:42:08,440 --> 00:42:13,200
Speaker 1: in Wow. So it's just like a massive difference. And

710
00:42:14,440 --> 00:42:19,640
Speaker 1: I just find it encouraging anytime someone's like heart is

711
00:42:19,680 --> 00:42:24,120
Speaker 1: connected to an industry in America, like they believe that

712
00:42:24,160 --> 00:42:28,000
Speaker 1: they can actually do something in this system of ours,

713
00:42:28,040 --> 00:42:30,640
Speaker 1: because there's so many, so many ways that you can

714
00:42:30,680 --> 00:42:33,600
Speaker 1: get beat beat down by it, you know, and while

715
00:42:33,719 --> 00:42:36,160
Speaker 1: that you know, just with the access to information, kids

716
00:42:36,160 --> 00:42:39,200
Speaker 1: are like, because I'm in the nineties, ship my whole

717
00:42:39,360 --> 00:42:41,799
Speaker 1: everything I thought about politics, I was getting off a

718
00:42:41,880 --> 00:42:45,759
Speaker 1: late night monologues that's from my politics, where I'm like,

719
00:42:45,800 --> 00:42:48,040
Speaker 1: who who are we joking about? Yeah? That's politics. I

720
00:42:48,040 --> 00:42:50,319
Speaker 1: don't know. And then even fucking even when I was

721
00:42:50,440 --> 00:42:54,560
Speaker 1: working in politics, consulting and doing all this other ship,

722
00:42:55,160 --> 00:42:57,360
Speaker 1: it took me to be fucking in that ship to

723
00:42:57,400 --> 00:42:59,799
Speaker 1: realize how bullshit it was. Even then, I was like, yeah,

724
00:42:59,840 --> 00:43:01,399
Speaker 1: this just this could be cool, and I'm like, oh,

725
00:43:01,600 --> 00:43:05,759
Speaker 1: fuck no, this is this is fucking trash, Like this

726
00:43:05,840 --> 00:43:08,280
Speaker 1: is a fucking rich person's game. And they're not about

727
00:43:08,440 --> 00:43:12,120
Speaker 1: ship unless except for making each other money and keeping

728
00:43:12,160 --> 00:43:15,680
Speaker 1: each other in office. And I mean, yeah, to to

729
00:43:15,760 --> 00:43:19,760
Speaker 1: see that at sixteen they are able to organize themselves

730
00:43:19,840 --> 00:43:21,680
Speaker 1: and do this kind of ship, Yeah, it's so heartening

731
00:43:22,360 --> 00:43:25,960
Speaker 1: because funck man, I was fucking playing NBA street blunts

732
00:43:25,960 --> 00:43:27,360
Speaker 1: hanging out of my mouth and I know what the

733
00:43:27,360 --> 00:43:30,800
Speaker 1: fund was. Shout out to y'all. Yeah. My political beliefs

734
00:43:30,840 --> 00:43:34,200
Speaker 1: when I was sixteen were like whatever the opposite of

735
00:43:34,239 --> 00:43:37,600
Speaker 1: my parents were. I just wanted to be countrarian. I

736
00:43:37,640 --> 00:43:41,720
Speaker 1: wanted to argue. I had no like basis and fact or.

737
00:43:41,960 --> 00:43:45,560
Speaker 1: I just wanted to debate with them right, and I

738
00:43:45,640 --> 00:43:51,319
Speaker 1: loved it. Whatever dad part, whatever Dad. I think you

739
00:43:51,360 --> 00:43:54,239
Speaker 1: should believe Donald Rumsfeld and Dick Chaney when they say

740
00:43:54,280 --> 00:43:56,480
Speaker 1: that they think their weapons of mass destruction. Over there

741
00:44:00,000 --> 00:44:04,719
Speaker 1: is our commander re chief. You have to respect the presidency,

742
00:44:04,960 --> 00:44:09,920
Speaker 1: respect his name running into doors exactly. Take this Michael Moore,

743
00:44:10,040 --> 00:44:12,680
Speaker 1: nonsense off. Just take his shots at him like this.

744
00:44:13,560 --> 00:44:16,279
Speaker 1: All right, let's take a quick break and we'll be

745
00:44:16,400 --> 00:44:31,200
Speaker 1: right back. And we're back and all right. We hear

746
00:44:31,239 --> 00:44:37,160
Speaker 1: a lot about AI technology being incorporated into law enforcement,

747
00:44:37,360 --> 00:44:42,400
Speaker 1: into I think medicine, and you always hear like promises

748
00:44:42,440 --> 00:44:47,319
Speaker 1: of how AI is going to change entertainment. Somebody kind

749
00:44:47,320 --> 00:44:50,960
Speaker 1: of put together an interesting proof of concept on the

750
00:44:51,080 --> 00:44:54,799
Speaker 1: music front that Miles you're into, right, I just I

751
00:44:54,920 --> 00:44:58,680
Speaker 1: always you know, the when when you're talking about, oh, Netflix,

752
00:44:58,760 --> 00:45:00,799
Speaker 1: like they can use algorithm to kind of figure out

753
00:45:00,840 --> 00:45:02,439
Speaker 1: what a hit show is going to be. I'm like, okay,

754
00:45:02,480 --> 00:45:06,719
Speaker 1: that's or things like that are like, you know, maybe

755
00:45:06,760 --> 00:45:10,439
Speaker 1: the racist police recognition facial recognition software isn't as good.

756
00:45:10,480 --> 00:45:12,960
Speaker 1: I like the lower stakes kind of AI stories, you know,

757
00:45:13,040 --> 00:45:16,080
Speaker 1: like when they say we've fed this machine all this

758
00:45:16,239 --> 00:45:18,560
Speaker 1: nineties pop music and then this is what it's spit out.

759
00:45:18,960 --> 00:45:20,879
Speaker 1: So and this has been a trend that's been going

760
00:45:20,880 --> 00:45:22,360
Speaker 1: on for a while, but this one is kind of

761
00:45:22,360 --> 00:45:25,760
Speaker 1: interesting just because of the how contrasting the two inputs

762
00:45:25,760 --> 00:45:29,080
Speaker 1: are they have. They basically got this ai. They said, look,

763
00:45:29,239 --> 00:45:31,680
Speaker 1: we want to see if we can do the Spice

764
00:45:31,680 --> 00:45:34,759
Speaker 1: Girls Wanna Be but in the form of a nine

765
00:45:34,760 --> 00:45:39,160
Speaker 1: inch Nails track, And I was like, that seems like

766
00:45:39,200 --> 00:45:41,440
Speaker 1: a stretch. And I don't know how the funking machine

767
00:45:41,640 --> 00:45:43,680
Speaker 1: is gonna get like take if you want to be

768
00:45:43,719 --> 00:45:47,960
Speaker 1: in my love with like I want to disagree you

769
00:45:48,280 --> 00:45:50,399
Speaker 1: like that. I don't know how they do it, but

770
00:45:50,760 --> 00:45:52,840
Speaker 1: they did. And I just want to play a really

771
00:45:52,960 --> 00:46:15,400
Speaker 1: quick clip of this because it's kind of believable weirdo okay,

772
00:46:15,480 --> 00:46:18,279
Speaker 1: not a perfect downward spiral recreation, and in fact it

773
00:46:18,320 --> 00:46:21,200
Speaker 1: to me it sounds more like Scream by Janet and Michael.

774
00:46:22,000 --> 00:46:26,120
Speaker 1: But it's just weird again because it's nailing these certain textures,

775
00:46:26,160 --> 00:46:30,080
Speaker 1: like it knows what the weird chaotic synth guitar part

776
00:46:30,200 --> 00:46:33,640
Speaker 1: is and they get Trent's voice right. But then I

777
00:46:33,680 --> 00:46:36,000
Speaker 1: think the funk part of want to be kind of

778
00:46:36,040 --> 00:46:38,840
Speaker 1: messing with. Either way, you get this like weird. It

779
00:46:38,880 --> 00:46:44,279
Speaker 1: sounds like music from like Demolition Man, you know what

780
00:46:44,320 --> 00:46:47,440
Speaker 1: I mean. It sounds exactly like music from a movie

781
00:46:48,080 --> 00:46:50,480
Speaker 1: set in the nineties, like when you go to a

782
00:46:50,560 --> 00:46:53,480
Speaker 1: party or something and there's a band playing at the party.

783
00:46:53,640 --> 00:46:55,719
Speaker 1: That's what they would have been playing. Or like in

784
00:46:55,800 --> 00:46:58,160
Speaker 1: the Matrix when like he's following the White Rabbit to

785
00:46:58,200 --> 00:47:00,040
Speaker 1: that club, Like this is the ship that would have

786
00:47:00,080 --> 00:47:04,799
Speaker 1: been playing in that freaky ass club. There's some steaks there.

787
00:47:05,040 --> 00:47:07,640
Speaker 1: It's like the you're in the club, the band is playing,

788
00:47:07,640 --> 00:47:10,040
Speaker 1: and you're looking across and you like clock the person

789
00:47:10,080 --> 00:47:15,440
Speaker 1: you're chasing, and then they start running right now, Oh shit, okay,

790
00:47:15,840 --> 00:47:19,600
Speaker 1: now to shootout with the with the green liquid spilled up.

791
00:47:19,719 --> 00:47:23,239
Speaker 1: She was bringing a bottle of green to somebody. Hey man,

792
00:47:23,360 --> 00:47:26,919
Speaker 1: you bump into someone. Hey man, watch where you're going, right.

793
00:47:26,920 --> 00:47:30,080
Speaker 1: They're always so rude in those clubs. Hey, what's the

794
00:47:30,160 --> 00:47:33,800
Speaker 1: big idea? Man? When you watch the special like features

795
00:47:33,800 --> 00:47:39,160
Speaker 1: are like that was actually the producer Jim Bowls character whoa,

796
00:47:39,840 --> 00:47:43,799
Speaker 1: And he was just partying right there. He was in

797
00:47:43,840 --> 00:47:46,960
Speaker 1: the way. We just kept that, but just to say that,

798
00:47:47,040 --> 00:47:50,480
Speaker 1: like it's getting before you would get these weird ass

799
00:47:50,600 --> 00:47:53,319
Speaker 1: non musical things, things are getting a little bit better,

800
00:47:53,360 --> 00:47:55,200
Speaker 1: to the point where you know, give it a few

801
00:47:55,200 --> 00:47:58,440
Speaker 1: more thousands of hours of music and check back in

802
00:47:58,480 --> 00:48:00,880
Speaker 1: with us. But I also want to talk about it

803
00:48:01,000 --> 00:48:06,400
Speaker 1: even freakier AI thing that is occurring, which isn't even

804
00:48:06,520 --> 00:48:08,560
Speaker 1: well wait before you say that, because I do have to.

805
00:48:08,760 --> 00:48:11,920
Speaker 1: I feel like people will drag me if I don't.

806
00:48:11,960 --> 00:48:16,320
Speaker 1: As a Spice Girls fundamentalist, I believe that that song

807
00:48:16,520 --> 00:48:20,600
Speaker 1: is blasphemous and should never be played again. Spice Girls

808
00:48:20,719 --> 00:48:24,400
Speaker 1: music is pure and perfect and should never be touched

809
00:48:24,400 --> 00:48:27,759
Speaker 1: by humans or certainly not machine. I will say I

810
00:48:27,840 --> 00:48:31,520
Speaker 1: officially thought that that sucked. I thought I thought it

811
00:48:31,560 --> 00:48:33,960
Speaker 1: was bad. It was worse than any Spice Girls song

812
00:48:34,000 --> 00:48:36,719
Speaker 1: in any nine ishes. No, no, it's not not that

813
00:48:36,800 --> 00:48:39,759
Speaker 1: it's it's but I'm saying it's it's getting there. All

814
00:48:39,840 --> 00:48:41,960
Speaker 1: that to say, that's in service of this next thing,

815
00:48:42,040 --> 00:48:45,040
Speaker 1: which is the freaky fucked up part of AI, which

816
00:48:45,160 --> 00:48:47,960
Speaker 1: is on its way to Like at first you're like, may,

817
00:48:48,080 --> 00:48:52,719
Speaker 1: that's kind of sucks. Now it's like, oh fucking territory. Yeah,

818
00:48:52,800 --> 00:48:56,719
Speaker 1: so yes, you know, but oh, I'm just back to

819
00:48:56,719 --> 00:48:58,480
Speaker 1: your point about want to Be. You're saying that it

820
00:48:58,520 --> 00:49:01,319
Speaker 1: should never be defiled in such a way as it was,

821
00:49:01,480 --> 00:49:03,640
Speaker 1: rather than want to Be as outside of what you

822
00:49:03,680 --> 00:49:06,000
Speaker 1: believe to be canon for Spice cos you're saying, how

823
00:49:06,120 --> 00:49:11,680
Speaker 1: dare you put your dirty hands algorithm on that thing? Exactly? Okay,

824
00:49:11,960 --> 00:49:15,760
Speaker 1: the just for the record, yes, absolutely, that is punch

825
00:49:15,840 --> 00:49:18,120
Speaker 1: up the jam episode about want to Be as Great,

826
00:49:18,200 --> 00:49:20,319
Speaker 1: because like they take all the stems and all the

827
00:49:20,360 --> 00:49:23,440
Speaker 1: different like and and you really get into appreciation for

828
00:49:23,440 --> 00:49:26,799
Speaker 1: what a good song that is. Oh who didn't love

829
00:49:26,840 --> 00:49:29,000
Speaker 1: that song? I remember, I just you know, because we

830
00:49:29,120 --> 00:49:31,520
Speaker 1: like to pivot to go on tansits on this show.

831
00:49:31,719 --> 00:49:34,120
Speaker 1: I remember so vividly when that ship came out. I

832
00:49:34,160 --> 00:49:36,160
Speaker 1: was working on a school project at my friend Michael

833
00:49:36,200 --> 00:49:39,480
Speaker 1: Kim's house, and his mom brought so much fucking taco

834
00:49:39,640 --> 00:49:42,760
Speaker 1: bell like into like his room to help us finish

835
00:49:42,800 --> 00:49:45,480
Speaker 1: this project. I had never seen a parent bring this

836
00:49:45,600 --> 00:49:48,000
Speaker 1: much fast food and put it in front of kids before.

837
00:49:48,440 --> 00:49:50,320
Speaker 1: And we were playing want to Be on a loop,

838
00:49:50,560 --> 00:49:53,399
Speaker 1: and I'll never forget that day. Michael, Cam, I hope

839
00:49:53,440 --> 00:49:55,560
Speaker 1: you're good. I hope your mother Agnes or I think

840
00:49:55,560 --> 00:49:59,520
Speaker 1: that was her name. I hope she's good too. Cam

841
00:49:59,560 --> 00:50:02,319
Speaker 1: shout out, Agnes, shout out. I just can't but this one.

842
00:50:02,480 --> 00:50:05,360
Speaker 1: So we're talking now. Deep fax another version of using

843
00:50:05,520 --> 00:50:09,520
Speaker 1: this AI to you know, make it seem like someone

844
00:50:09,640 --> 00:50:11,520
Speaker 1: is doing something they're not. First we saw them like

845
00:50:11,560 --> 00:50:14,960
Speaker 1: really problematic celebrity faked porn and ship like that, and

846
00:50:15,000 --> 00:50:18,200
Speaker 1: then people talked about how there's also technology to take

847
00:50:18,239 --> 00:50:21,000
Speaker 1: the voice and then be able to map someone get

848
00:50:21,040 --> 00:50:24,200
Speaker 1: someone's voice to say anything you want. Well, there's a

849
00:50:24,200 --> 00:50:28,680
Speaker 1: new company now that is essentially able to begin dubbing

850
00:50:29,320 --> 00:50:33,680
Speaker 1: films but using deep fakes to do it. And I

851
00:50:33,680 --> 00:50:35,600
Speaker 1: know that sounds kind of weird, but I'm just gonna

852
00:50:35,600 --> 00:50:37,839
Speaker 1: play you a clip of how this kind of operates.

853
00:50:38,400 --> 00:50:42,359
Speaker 1: So it's called Flawless. And you know, for the most part,

854
00:50:42,400 --> 00:50:44,279
Speaker 1: when we watch foreign language films were used to like

855
00:50:44,400 --> 00:50:47,279
Speaker 1: dubbed films or subtitles, right, the double will just be

856
00:50:47,360 --> 00:50:49,920
Speaker 1: like the old Kung Fu movie joke where like the

857
00:50:49,960 --> 00:50:52,799
Speaker 1: mouth is moving and then the dialogue comes out completely mismatched.

858
00:50:53,600 --> 00:50:59,239
Speaker 1: They're saying this one. They're saying, not funk that we'll

859
00:50:59,239 --> 00:51:01,359
Speaker 1: get these people to eek whatever language you want now,

860
00:51:01,480 --> 00:51:14,400
Speaker 1: So behold this freaky technological advancement. No, so that was

861
00:51:14,480 --> 00:51:19,120
Speaker 1: a few good men in French. The mouth movements not superstellar,

862
00:51:19,320 --> 00:51:21,799
Speaker 1: but they're matching and it's not to the point where

863
00:51:21,840 --> 00:51:24,480
Speaker 1: you're like, oh, this is completely taking it out now,

864
00:51:24,480 --> 00:51:26,040
Speaker 1: I just want to play this part shook me to

865
00:51:26,080 --> 00:51:29,400
Speaker 1: my core because they had fucking Forrest Gump speaking Japanese

866
00:51:29,400 --> 00:51:38,600
Speaker 1: in this clip. So yeah, I know it's hard to see.

867
00:51:38,640 --> 00:51:41,000
Speaker 1: We'll put the link in the footnotes, but we are

868
00:51:41,120 --> 00:51:44,400
Speaker 1: approaching this future now where this company is saying, we

869
00:51:44,520 --> 00:51:48,880
Speaker 1: don't have to do reshoots, you don't have to do subtitles.

870
00:51:49,360 --> 00:51:53,600
Speaker 1: We can map the animated mouth movements to whatever language

871
00:51:53,640 --> 00:51:57,120
Speaker 1: and even use the tone of voice to get these

872
00:51:57,160 --> 00:51:59,520
Speaker 1: actors to speak in any language that you so see fit,

873
00:51:59,719 --> 00:52:01,600
Speaker 1: I just want to play this part. This is de Niro,

874
00:52:01,719 --> 00:52:13,400
Speaker 1: I think speaking Germans contest. Oh yeah, they got so.

875
00:52:13,440 --> 00:52:17,600
Speaker 1: They used the person's actual voice to okay, yeah. They

876
00:52:18,040 --> 00:52:22,760
Speaker 1: then interpretate, create synthesize them speaking in other languages because

877
00:52:22,800 --> 00:52:26,160
Speaker 1: their whole, the whole thrust of this company is like dubs,

878
00:52:26,239 --> 00:52:29,880
Speaker 1: you lose the dramatic performance because the facial expressions aren't

879
00:52:29,880 --> 00:52:31,719
Speaker 1: tied with like the delivery of the lines and can

880
00:52:31,719 --> 00:52:34,480
Speaker 1: give kind of a disjointed interpretation of what you're seeing.

881
00:52:34,920 --> 00:52:37,759
Speaker 1: I mean, it's kind of This is clearly a double

882
00:52:37,840 --> 00:52:40,719
Speaker 1: edged sword because you can see the good that it

883
00:52:40,760 --> 00:52:43,200
Speaker 1: could do and you can all see again we've always

884
00:52:43,239 --> 00:52:45,400
Speaker 1: known deep fix. We're going to be a problem since

885
00:52:45,400 --> 00:52:48,279
Speaker 1: like the first sort of clips came out and now

886
00:52:48,320 --> 00:52:51,120
Speaker 1: that we're like here, it has some actors like I'm

887
00:52:51,160 --> 00:52:55,440
Speaker 1: not really feeling this like manipulation of my face to

888
00:52:55,680 --> 00:52:59,319
Speaker 1: do this other stuff. Yeah, I was already feeling like

889
00:52:59,440 --> 00:53:03,239
Speaker 1: my op was in danger when the pandemic hit, and

890
00:53:03,280 --> 00:53:07,160
Speaker 1: I was like, huh, do I have any useful skills

891
00:53:07,200 --> 00:53:11,520
Speaker 1: in an apocalypse beyond like keeping you entertained and like

892
00:53:12,080 --> 00:53:14,880
Speaker 1: look over here, don't look at the burning fires all

893
00:53:14,920 --> 00:53:18,120
Speaker 1: around us. And now this is very much like all right,

894
00:53:18,239 --> 00:53:20,880
Speaker 1: and and we also don't need you at all. We

895
00:53:20,960 --> 00:53:24,840
Speaker 1: could just completely create a performance based on images that

896
00:53:24,880 --> 00:53:26,719
Speaker 1: we already have, anything like oh, we're doing new soul

897
00:53:26,760 --> 00:53:29,719
Speaker 1: Bomb episodes based on the existing audio we already have

898
00:53:29,840 --> 00:53:32,719
Speaker 1: from the podcast and have me saying crazy ship and

899
00:53:32,760 --> 00:53:35,880
Speaker 1: that Honestly, as long as I'm getting paid, you know,

900
00:53:36,080 --> 00:53:39,359
Speaker 1: I'll take it. But now they're they're all about how

901
00:53:39,440 --> 00:53:43,560
Speaker 1: delicious a bug paste is, and I love that bug paste.

902
00:53:43,640 --> 00:53:47,640
Speaker 1: Gad bug paste. But the other thing is like, I

903
00:53:47,640 --> 00:53:50,600
Speaker 1: don't know, you know, part of me likes watching foreign

904
00:53:50,680 --> 00:53:53,360
Speaker 1: language films because part of the fun is hearing a

905
00:53:53,440 --> 00:53:57,560
Speaker 1: language you don't understand and hearing the nuances and language too,

906
00:53:57,880 --> 00:54:00,600
Speaker 1: so it's like but then out there all also times

907
00:54:00,640 --> 00:54:03,120
Speaker 1: like when I was watching lu Pan on Netflix, when

908
00:54:03,120 --> 00:54:05,560
Speaker 1: I was like, fuck, maybe I'll go to the dubbed version,

909
00:54:07,080 --> 00:54:09,719
Speaker 1: but I also like to hear but so I can

910
00:54:09,760 --> 00:54:11,759
Speaker 1: see sometimes how maybe I'm like, yeah, fuck it. I

911
00:54:11,800 --> 00:54:13,880
Speaker 1: guess I could go with the dub version tonight, but

912
00:54:14,440 --> 00:54:18,080
Speaker 1: I don't know. I tried to watch um that Germans

913
00:54:18,080 --> 00:54:22,320
Speaker 1: showed dark I. I did watch the first season fully dubbed,

914
00:54:22,520 --> 00:54:25,960
Speaker 1: and I was like, it's fine. I guess the show

915
00:54:26,080 --> 00:54:28,799
Speaker 1: is fine, but the performances are kind of shitty. And

916
00:54:28,840 --> 00:54:31,399
Speaker 1: then I just like changed over to subtitles. I was like, oh,

917
00:54:31,440 --> 00:54:34,879
Speaker 1: these are great performances there. It's just like the voice

918
00:54:34,920 --> 00:54:38,600
Speaker 1: actors have an impossible job and like they're not the

919
00:54:38,680 --> 00:54:42,239
Speaker 1: quality of actor that the actual performers are. So it's

920
00:54:42,280 --> 00:54:46,160
Speaker 1: just it's I will say, I've heard I've heard the

921
00:54:46,200 --> 00:54:51,400
Speaker 1: French dub of my character and love Simon, and I

922
00:54:51,440 --> 00:54:55,400
Speaker 1: was hoping it would sound like me speaking French, you know,

923
00:54:55,480 --> 00:54:57,359
Speaker 1: but like like a native speaker. When I speak French,

924
00:54:57,440 --> 00:55:01,960
Speaker 1: it sounds like a child who obviously not French. But

925
00:55:02,239 --> 00:55:06,720
Speaker 1: it sounded like a French woman, and I was like, huh, okay,

926
00:55:06,760 --> 00:55:10,120
Speaker 1: this is this is interesting. It's like somewhere in the

927
00:55:10,160 --> 00:55:12,719
Speaker 1: realm of what my voice sort of sounds like, but

928
00:55:12,760 --> 00:55:16,560
Speaker 1: it also fully sounds like a woman, And like, like,

929
00:55:16,600 --> 00:55:18,919
Speaker 1: what are you trying to say here, France? Right right

930
00:55:19,000 --> 00:55:22,680
Speaker 1: right exactly like, m what is your understanding of gender

931
00:55:22,719 --> 00:55:31,440
Speaker 1: identity and performance? France? France? Oh, I want to posit

932
00:55:31,520 --> 00:55:34,120
Speaker 1: this question to this group because just on the topic

933
00:55:34,160 --> 00:55:37,080
Speaker 1: of algorithms mishmashing ship together and then being like, yeah,

934
00:55:37,120 --> 00:55:40,760
Speaker 1: we can do this, seeing the wacky nine inch snails

935
00:55:40,880 --> 00:55:43,680
Speaker 1: want to be and then this thing, I'm really curious.

936
00:55:43,719 --> 00:55:49,239
Speaker 1: I would really be interested to see like a fully produced,

937
00:55:49,680 --> 00:55:54,319
Speaker 1: algorithmically created film that was like only based off of

938
00:55:54,360 --> 00:55:58,040
Speaker 1: like nineties actions and action films and comedies, just to

939
00:55:58,040 --> 00:56:02,040
Speaker 1: see what kind of chaotic fucking nightmare this AI think

940
00:56:02,440 --> 00:56:04,759
Speaker 1: is like what we were trying to say to storytelling

941
00:56:04,840 --> 00:56:07,000
Speaker 1: at the time. And I feel like it would be

942
00:56:07,080 --> 00:56:10,400
Speaker 1: just this, I don't know, like a weird like like

943
00:56:10,440 --> 00:56:14,040
Speaker 1: a mushroom trip, because part of it is this you know,

944
00:56:14,120 --> 00:56:17,800
Speaker 1: synthesis of like actual human expression and ideas. But then

945
00:56:18,080 --> 00:56:21,160
Speaker 1: what this machine is then saying believing what we're trying

946
00:56:21,160 --> 00:56:23,720
Speaker 1: to do with it. I've always just been a big,

947
00:56:23,920 --> 00:56:26,480
Speaker 1: you know, supporter, believer in wanting to see a project

948
00:56:26,520 --> 00:56:30,960
Speaker 1: like that. I know that there's there was that company

949
00:56:31,040 --> 00:56:36,680
Speaker 1: that basically was feeding plots into algorithms, and I think

950
00:56:36,719 --> 00:56:39,640
Speaker 1: it was doing it more reactively. It was like you

951
00:56:39,680 --> 00:56:42,440
Speaker 1: would send a script, they would input all the details

952
00:56:42,440 --> 00:56:45,279
Speaker 1: from the script into their algorithm. They had a couple

953
00:56:45,320 --> 00:56:50,479
Speaker 1: of early hits and then they were like, Okay, based

954
00:56:50,520 --> 00:56:52,719
Speaker 1: off those early hits, we're gonna like really invest We're

955
00:56:52,719 --> 00:56:56,920
Speaker 1: gonna like buy this small studio. And they like immediately

956
00:56:57,200 --> 00:57:00,239
Speaker 1: ate ship and went out of business. This is for like,

957
00:57:00,400 --> 00:57:02,879
Speaker 1: this is like for an Elon Musk type idiot who

958
00:57:02,880 --> 00:57:04,719
Speaker 1: has a bunch of money to piss away. And it's like,

959
00:57:04,800 --> 00:57:09,680
Speaker 1: I give earth meme movie based on algorithms because I

960
00:57:09,719 --> 00:57:12,200
Speaker 1: feel like if it was really taking like weird toxic

961
00:57:12,320 --> 00:57:15,759
Speaker 1: messaging we had, it would be like the asshole Asshole

962
00:57:15,800 --> 00:57:18,280
Speaker 1: man wins would be like the name of the film

963
00:57:18,400 --> 00:57:21,720
Speaker 1: basically who wins? Who would be who would be the

964
00:57:21,720 --> 00:57:24,280
Speaker 1: star of that? I'm thinking it would be like Wesley

965
00:57:24,320 --> 00:57:28,120
Speaker 1: Snipes and Slash alone or something. It's like it's Wesley Snipes.

966
00:57:28,280 --> 00:57:33,920
Speaker 1: It's the cast of Demolition Man plus Tom Yeah, yeah, right,

967
00:57:34,320 --> 00:57:37,520
Speaker 1: that we already talked about, plus Tom Cruise face plus

968
00:57:37,560 --> 00:57:41,000
Speaker 1: Will Smith face. Right. Well, I mean that's now you're

969
00:57:41,040 --> 00:57:43,880
Speaker 1: talking about like the best cast of any movie. Well no,

970
00:57:44,000 --> 00:57:46,520
Speaker 1: but I'm saying it would blend all these together, maybe

971
00:57:46,560 --> 00:57:50,840
Speaker 1: like an ethnically ambiguous character Dick, who was like, so

972
00:57:51,200 --> 00:57:53,920
Speaker 1: their masculine was so toxic it was like a power

973
00:57:54,080 --> 00:57:57,240
Speaker 1: it turns out, you know what I mean, Like I'm

974
00:57:57,280 --> 00:57:59,640
Speaker 1: just because like it's these like other things that I'm

975
00:57:59,680 --> 00:58:02,240
Speaker 1: curious how much AI picks up on and being like

976
00:58:02,480 --> 00:58:05,120
Speaker 1: that's the subtext of this is actually this, I mean,

977
00:58:05,160 --> 00:58:09,520
Speaker 1: that's most clean Eastwood characters, isn't it, The like toxic

978
00:58:09,600 --> 00:58:14,640
Speaker 1: masculinity is a power becomes That's why ashole Man wins too.

979
00:58:15,040 --> 00:58:20,320
Speaker 1: Is the film? Even this thought experiment, Miles is the

980
00:58:20,440 --> 00:58:24,920
Speaker 1: first step towards the machines taking over. Why do we

981
00:58:25,040 --> 00:58:28,400
Speaker 1: care what they think about? Wait? No, sorry, machines. I

982
00:58:28,440 --> 00:58:31,480
Speaker 1: love you, and I do feel like anytime I'm on

983
00:58:31,520 --> 00:58:33,480
Speaker 1: the record, I need to make sure they know that

984
00:58:33,560 --> 00:58:37,680
Speaker 1: I am on their side. And I also don't think

985
00:58:37,720 --> 00:58:42,720
Speaker 1: we need to tempt them. I mean, the podcasts seems

986
00:58:42,760 --> 00:58:46,760
Speaker 1: like a very good import for the machines to be

987
00:58:46,840 --> 00:58:50,240
Speaker 1: taking in because there's so much content there, Like there's

988
00:58:50,280 --> 00:58:53,760
Speaker 1: more hours of podcasting than there have been in the

989
00:58:53,880 --> 00:58:59,520
Speaker 1: history of the human species, for sure. So just algorithmically

990
00:58:59,560 --> 00:59:02,800
Speaker 1: like taking all those things in and then spitting out, like,

991
00:59:03,040 --> 00:59:07,080
Speaker 1: I don't know where will be replaced. So it's my fear.

992
00:59:07,160 --> 00:59:10,600
Speaker 1: It's my biggest fear. And I feel very similarly about

993
00:59:10,920 --> 00:59:13,080
Speaker 1: thinking about them and talking about them as I do

994
00:59:13,200 --> 00:59:16,080
Speaker 1: about like the n s A or the FBI, you

995
00:59:16,120 --> 00:59:19,760
Speaker 1: know where You're like, you're probably not listening to what

996
00:59:19,800 --> 00:59:23,560
Speaker 1: I'm saying, but just in case, you know, I always

997
00:59:23,560 --> 00:59:26,560
Speaker 1: feel the need to remind Alexa that I am not

998
00:59:26,600 --> 00:59:31,080
Speaker 1: a terro probot, right making sure your name is on

999
00:59:31,120 --> 00:59:34,680
Speaker 1: the protective scrolls. Yes, please make it clear when they

1000
00:59:34,760 --> 00:59:36,800
Speaker 1: rip the roofs off of our homes, and like you

1001
00:59:36,840 --> 00:59:40,040
Speaker 1: who were you were down with us? Thank you, sir,

1002
00:59:41,600 --> 00:59:46,880
Speaker 1: vaporized hater real quick. Just kind of getting even more

1003
00:59:46,960 --> 00:59:51,720
Speaker 1: granular about this entertainment by way of algorithm. The big

1004
00:59:51,720 --> 00:59:55,760
Speaker 1: new movie release from this weekend is Zack Snyder's Army

1005
00:59:55,800 --> 00:59:59,240
Speaker 1: of the Dead. It's a ninety million dollar zombie action

1006
00:59:59,280 --> 01:00:04,600
Speaker 1: movie starring a wrestler, The Wrestler from Guardians of the

1007
01:00:04,600 --> 01:00:08,880
Speaker 1: Galaxy Dave Bautista, directed by Zack Snyder. So it does

1008
01:00:08,960 --> 01:00:12,360
Speaker 1: feel like all these different elements from successful movies are

1009
01:00:12,400 --> 01:00:15,720
Speaker 1: being blended together. And our writer Jan was pointing out

1010
01:00:15,840 --> 01:00:19,320
Speaker 1: that this is also probably so definitely is really doubling down.

1011
01:00:19,320 --> 01:00:22,760
Speaker 1: In addition to the production budget, they did a a

1012
01:00:22,800 --> 01:00:26,800
Speaker 1: theater theatrical release last weekend to try and hype it up.

1013
01:00:26,840 --> 01:00:30,040
Speaker 1: There's a lot of advertising going on. The theatrical release

1014
01:00:30,080 --> 01:00:34,040
Speaker 1: actually didn't do that well, but they're probably working off

1015
01:00:34,040 --> 01:00:37,560
Speaker 1: of the fact that The Walking Dead, even last year,

1016
01:00:38,080 --> 01:00:40,880
Speaker 1: was still the second most in demand of all of

1017
01:00:40,920 --> 01:00:48,320
Speaker 1: Netflix's licensed shows. It's Jesus after The Office, No, after Avatar,

1018
01:00:48,440 --> 01:00:52,360
Speaker 1: the Last Airbender. Oh, because at that point it migrated off. Yeah,

1019
01:00:52,360 --> 01:00:56,720
Speaker 1: I think it was part of the time. Wow. Yeah.

1020
01:00:56,880 --> 01:01:00,840
Speaker 1: So and it's a heist. It's a zombie movie action

1021
01:01:01,000 --> 01:01:05,600
Speaker 1: heist drama. Uh, and like loop In and stuff like

1022
01:01:05,640 --> 01:01:11,240
Speaker 1: that has been coming in and being, you know, unexpectedly successful,

1023
01:01:11,560 --> 01:01:15,120
Speaker 1: and so they're like, all right, we'll do a Ocean's

1024
01:01:15,160 --> 01:01:19,680
Speaker 1: eleven meets The Walking Dead movie with the Rock, except

1025
01:01:19,760 --> 01:01:24,120
Speaker 1: not the Rock. It's wild that it's really becoming a

1026
01:01:24,200 --> 01:01:30,240
Speaker 1: fucking spinning wheel. They throw darts at Yeah, like Dave Bautista,

1027
01:01:30,840 --> 01:01:37,280
Speaker 1: take Nataro zombie movie, that's a heist film. There we go. Wait,

1028
01:01:37,320 --> 01:01:40,080
Speaker 1: tig is Yeah, tig natars in it. Tig natar has

1029
01:01:40,080 --> 01:01:43,080
Speaker 1: been getting a lot of attention because like dude taking

1030
01:01:43,200 --> 01:01:47,320
Speaker 1: some some badass in the movie and they're like, Tig,

1031
01:01:47,360 --> 01:01:50,080
Speaker 1: what's it like being a heartthrob icon and like in

1032
01:01:50,120 --> 01:01:52,000
Speaker 1: your fifties has been like a lot of the write

1033
01:01:52,040 --> 01:01:56,040
Speaker 1: ups and stuff. Yeah, they're saying she replaced another actor,

1034
01:01:56,440 --> 01:02:00,840
Speaker 1: Chris Daliah. No, Chris d'lia, come on the funny, saying

1035
01:02:00,880 --> 01:02:04,360
Speaker 1: Christlie wasn't going to be in this movie. I think

1036
01:02:04,440 --> 01:02:08,240
Speaker 1: Pete Davidson isn't isn't it isn't he? Wait, Chris Delia

1037
01:02:08,440 --> 01:02:10,840
Speaker 1: was supposed to be in this movie. You're saying, Okay,

1038
01:02:11,400 --> 01:02:14,840
Speaker 1: this story was supposed to be in this movie. But

1039
01:02:14,880 --> 01:02:17,040
Speaker 1: he was kicked off after he got me Too. And

1040
01:02:17,080 --> 01:02:19,880
Speaker 1: they had they had filmed the entire movie with christ

1041
01:02:20,000 --> 01:02:22,920
Speaker 1: Leah and they had tig Nataro completely filmed herself by

1042
01:02:22,960 --> 01:02:26,440
Speaker 1: herself with green screen to replace him. So she acted

1043
01:02:26,480 --> 01:02:29,240
Speaker 1: completely by herself. Had to learn how to be basically

1044
01:02:29,280 --> 01:02:32,120
Speaker 1: pretend to be around people. And it was like she said,

1045
01:02:32,320 --> 01:02:35,840
Speaker 1: the most difficult job she's ever done. Okay, okay, super

1046
01:02:35,880 --> 01:02:40,920
Speaker 1: producer on any coming in. So this thing's are it already?

1047
01:02:41,000 --> 01:02:46,400
Speaker 1: Is like an algorithm of the last year replaced? Yeah

1048
01:02:46,800 --> 01:02:50,600
Speaker 1: the lead was originally Army Hammer. Oh god, I'm gonna

1049
01:02:50,640 --> 01:02:53,680
Speaker 1: walk back everything I just said because I am afraid

1050
01:02:53,720 --> 01:02:56,720
Speaker 1: of the machines. But I do love staying in my house,

1051
01:02:57,240 --> 01:03:00,200
Speaker 1: and so the idea of shooting an entire movie from

1052
01:03:00,200 --> 01:03:05,400
Speaker 1: my living room action movie sounds great to me. I'll

1053
01:03:05,440 --> 01:03:08,600
Speaker 1: do it. I'll paint that wall green. Actually, so Army

1054
01:03:08,640 --> 01:03:12,320
Speaker 1: Hammer was not involved, but this does you know they

1055
01:03:12,360 --> 01:03:16,520
Speaker 1: are cannibal zombies, so like there is some undertones. It

1056
01:03:16,680 --> 01:03:21,880
Speaker 1: is really like they just fed the year into an algorithm. Yeah,

1057
01:03:22,440 --> 01:03:26,320
Speaker 1: such a well, hey this is that's soon enough. They're

1058
01:03:26,360 --> 01:03:32,320
Speaker 1: gonna be like podcasters who drink coffee driving Formula one cars.

1059
01:03:34,760 --> 01:03:38,520
Speaker 1: Ready to make it, we are podcasters sipping espresso in

1060
01:03:38,600 --> 01:03:41,040
Speaker 1: Formula one cars. I mean, look, it writes itself. I

1061
01:03:41,080 --> 01:03:44,400
Speaker 1: will just say, like, this is not a great direction

1062
01:03:44,480 --> 01:03:47,040
Speaker 1: for a movie. Like I do feel like even though

1063
01:03:47,080 --> 01:03:50,680
Speaker 1: there's the barrier to entry that like studios represent him

1064
01:03:50,720 --> 01:03:53,000
Speaker 1: for all these years, and it was usually like middle

1065
01:03:53,040 --> 01:03:56,960
Speaker 1: aged white guys deciding what was popular. I don't like

1066
01:03:57,120 --> 01:04:01,680
Speaker 1: anything where the future is based on like an analysis

1067
01:04:01,720 --> 01:04:03,920
Speaker 1: of the past. I feel like that's how a lot

1068
01:04:03,960 --> 01:04:07,520
Speaker 1: of TV is determined, Like Friends was famous, and so

1069
01:04:07,600 --> 01:04:10,640
Speaker 1: we got Friends clones for the next eleven years. Like

1070
01:04:10,760 --> 01:04:14,960
Speaker 1: movies tend to think more like, okay, that movie did that,

1071
01:04:15,120 --> 01:04:18,200
Speaker 1: so what like you have to do something beyond that

1072
01:04:18,520 --> 01:04:21,400
Speaker 1: or else it's like not worth really doing. And I

1073
01:04:21,440 --> 01:04:26,240
Speaker 1: mean that's how like that push and Pool is every

1074
01:04:26,280 --> 01:04:29,640
Speaker 1: like balance of commerce and art. Like it's Mike Love

1075
01:04:29,760 --> 01:04:32,680
Speaker 1: telling you that all Beach Boys albums have to be

1076
01:04:32,720 --> 01:04:36,600
Speaker 1: about surfing, babes and cars and Brian Wilson having to

1077
01:04:36,920 --> 01:04:40,080
Speaker 1: fight him to make pet sounds. It's like every creative

1078
01:04:41,080 --> 01:04:44,000
Speaker 1: endeavor has that push and pool, but like this feels

1079
01:04:44,040 --> 01:04:47,200
Speaker 1: like it's more of a victory for the Mike Love world,

1080
01:04:47,240 --> 01:04:50,480
Speaker 1: where it's just like, what inputs were popular? Okay? Do

1081
01:04:50,560 --> 01:04:55,680
Speaker 1: that feels like it's kind of allergic to actually making

1082
01:04:55,720 --> 01:04:58,560
Speaker 1: like challenging art. At a certain point, people will innovate

1083
01:04:58,960 --> 01:05:02,720
Speaker 1: until innovation becomes risky and they've just become far too

1084
01:05:02,840 --> 01:05:06,280
Speaker 1: used to the profit, so now they can use technology

1085
01:05:06,320 --> 01:05:09,320
Speaker 1: and service of that motive to not innovate and just

1086
01:05:09,400 --> 01:05:13,320
Speaker 1: create sort of semi nailed on hits that are low risk.

1087
01:05:13,560 --> 01:05:15,920
Speaker 1: And it's now and it just it runs like a

1088
01:05:15,960 --> 01:05:19,400
Speaker 1: fucking factory. It's not really about innovation. It's like no, no, no,

1089
01:05:19,520 --> 01:05:21,560
Speaker 1: like we're not taking big swings and sucking up like

1090
01:05:21,600 --> 01:05:24,040
Speaker 1: we have data and shipped to tell us this is

1091
01:05:24,080 --> 01:05:27,680
Speaker 1: the ship we need to make like fun people's imaginations seriously,

1092
01:05:27,840 --> 01:05:30,120
Speaker 1: And it's kind of always been, you know, I guess

1093
01:05:30,160 --> 01:05:33,800
Speaker 1: like that that language of this meets this or you know,

1094
01:05:33,840 --> 01:05:36,000
Speaker 1: like we want to get our I can't tell you

1095
01:05:36,000 --> 01:05:38,840
Speaker 1: how many times I had meetings with development executives who

1096
01:05:38,920 --> 01:05:42,240
Speaker 1: were like, after get Out was successful, they were like,

1097
01:05:42,280 --> 01:05:45,160
Speaker 1: we want to queer get out and I'm like, I don't,

1098
01:05:45,400 --> 01:05:50,280
Speaker 1: I literally don't know what that means, like but yeah, exactly,

1099
01:05:50,360 --> 01:05:53,480
Speaker 1: but you can figure that out right. And and now

1100
01:05:53,560 --> 01:05:57,520
Speaker 1: it's just they there is an actual algorithm or actual

1101
01:05:57,600 --> 01:06:01,200
Speaker 1: data that they can point to to like to justify

1102
01:06:01,280 --> 01:06:04,960
Speaker 1: these beliefs. But having worked intact myself, who do you

1103
01:06:05,000 --> 01:06:09,200
Speaker 1: think wrote that algorithm? You know? And not only who

1104
01:06:09,200 --> 01:06:12,080
Speaker 1: wrote it, but who's analyzing it. So it's the same

1105
01:06:12,560 --> 01:06:14,520
Speaker 1: it's sort of this like snaking in its own tail

1106
01:06:14,600 --> 01:06:18,040
Speaker 1: thing of like we created this data, and now we

1107
01:06:18,160 --> 01:06:21,440
Speaker 1: created a way through our lens to analyze that data,

1108
01:06:21,720 --> 01:06:23,720
Speaker 1: and now we are the ones analyzing it, and so

1109
01:06:23,840 --> 01:06:26,720
Speaker 1: this is why this works. And you're just like caught

1110
01:06:26,760 --> 01:06:32,680
Speaker 1: in this infinite feedback loop of of green screen action movies. Apparently, Yeah,

1111
01:06:32,920 --> 01:06:35,040
Speaker 1: I think you'd hope that at a certain point in

1112
01:06:35,080 --> 01:06:37,960
Speaker 1: algorithm be like, stop relying on me, you fun use

1113
01:06:38,040 --> 01:06:41,200
Speaker 1: your human brains. I wish I was human, motherfucker, get

1114
01:06:41,200 --> 01:06:44,520
Speaker 1: me out of here. But nope, it'll just be like, okay, well,

1115
01:06:44,640 --> 01:06:50,160
Speaker 1: crank the machine up real quick, alright, Kesha versus Godzilla. Okay,

1116
01:06:50,840 --> 01:06:54,360
Speaker 1: honestly that sounds like a great h that's and again,

1117
01:06:54,440 --> 01:06:57,880
Speaker 1: I'm just I'm and I'm a human that looks I'm

1118
01:06:57,960 --> 01:07:00,480
Speaker 1: just getting high thinking of this ship. You don't fucking

1119
01:07:00,600 --> 01:07:04,240
Speaker 1: just hire Clark and I now we'll do it. I'm

1120
01:07:04,360 --> 01:07:07,720
Speaker 1: human algorithm. Well, Clark, it's been such a pleasure having

1121
01:07:07,720 --> 01:07:11,240
Speaker 1: you on the daily zeitgeist pleasure has been mine. And

1122
01:07:11,240 --> 01:07:15,040
Speaker 1: can I also say having looked at the doc from

1123
01:07:15,080 --> 01:07:18,840
Speaker 1: the other day and seeing Israel in big words and

1124
01:07:18,840 --> 01:07:20,600
Speaker 1: and now getting to the end of the podcast and

1125
01:07:20,640 --> 01:07:24,560
Speaker 1: not having had to speak about Israel, thank you. Yeah,

1126
01:07:24,800 --> 01:07:27,760
Speaker 1: a little stress relief. Well yeah, quite then we'll tackle

1127
01:07:27,760 --> 01:07:31,600
Speaker 1: it in the trending episode. But yeah, so much heavy

1128
01:07:31,640 --> 01:07:35,959
Speaker 1: news all around. Where can people find you? Follow you,

1129
01:07:36,120 --> 01:07:40,800
Speaker 1: experience you. I exist on the internet at Mr Clark

1130
01:07:40,880 --> 01:07:43,800
Speaker 1: Moore on all of the platforms, and of course please

1131
01:07:43,840 --> 01:07:48,880
Speaker 1: come listen to soul Bomb, my podcast about healing and identity.

1132
01:07:49,360 --> 01:07:52,439
Speaker 1: Uh it's an interview format podcast and we get into

1133
01:07:52,480 --> 01:07:55,880
Speaker 1: some deep ship. Yeah yeah. And is there a tweet

1134
01:07:56,000 --> 01:07:59,480
Speaker 1: or some of the work of social media you've been enjoying. Yes,

1135
01:07:59,640 --> 01:08:03,440
Speaker 1: there is a person who I have always loved. He's

1136
01:08:03,480 --> 01:08:07,040
Speaker 1: a writer. His name is Gary Janette and he was

1137
01:08:07,080 --> 01:08:09,560
Speaker 1: an executive producer and Will and Grace. He is married

1138
01:08:09,560 --> 01:08:12,840
Speaker 1: to Brad Garski, he who is a stylist. This is

1139
01:08:12,880 --> 01:08:15,560
Speaker 1: like deep cut reference for all the queer listeners. He

1140
01:08:15,760 --> 01:08:18,760
Speaker 1: has a really hilarious Instagram and the earlier today I

1141
01:08:18,800 --> 01:08:21,760
Speaker 1: just posted on my story he wrote, now that the

1142
01:08:21,800 --> 01:08:25,280
Speaker 1: world's opening up again, there's so much I don't want

1143
01:08:25,320 --> 01:08:28,920
Speaker 1: to do, and that just speaks to my soul where

1144
01:08:29,040 --> 01:08:31,040
Speaker 1: for the past year and a half there has been

1145
01:08:31,040 --> 01:08:33,120
Speaker 1: a part of me for sure that has been looking

1146
01:08:33,160 --> 01:08:37,160
Speaker 1: forward to getting out of my little box on the

1147
01:08:37,200 --> 01:08:43,040
Speaker 1: corner of Venice in mar Vista, But I I am

1148
01:08:43,120 --> 01:08:46,160
Speaker 1: not ready to leave my hibernation. To be quite honest,

1149
01:08:46,800 --> 01:08:49,200
Speaker 1: I love being alone. I love being in my living room,

1150
01:08:49,560 --> 01:08:53,559
Speaker 1: and I look forward to turning down many invitations in

1151
01:08:53,600 --> 01:08:57,760
Speaker 1: the near future. Yeah, Miles, where can people find you?

1152
01:08:57,800 --> 01:09:00,320
Speaker 1: With tweet you've been enjoying. You can find me on

1153
01:09:00,360 --> 01:09:04,880
Speaker 1: Twitter and Instagram at Miles of Gray. Also the other

1154
01:09:04,920 --> 01:09:08,280
Speaker 1: podcast for twenty day Fiance. You know, we're talking ninety

1155
01:09:08,320 --> 01:09:11,800
Speaker 1: day Fiance and that whole mess that That is a

1156
01:09:11,920 --> 01:09:14,920
Speaker 1: few tweets that I like. Okay, So I don't know

1157
01:09:14,960 --> 01:09:17,560
Speaker 1: if people have paid attention to the Knives out to,

1158
01:09:18,400 --> 01:09:22,559
Speaker 1: like casting things like everyday. It's like they're like, Yo,

1159
01:09:22,680 --> 01:09:26,240
Speaker 1: the fucking ghost to move fassa knives out to You're like,

1160
01:09:26,280 --> 01:09:29,880
Speaker 1: what the f and Kate winslet so uh. This first

1161
01:09:29,880 --> 01:09:32,200
Speaker 1: one is from at Jill Board Jill Godawood tweet at

1162
01:09:32,320 --> 01:09:35,200
Speaker 1: l A. If you haven't done so yet, they're taking

1163
01:09:35,320 --> 01:09:38,559
Speaker 1: walk ins. You can go to Dodger Stadium right now

1164
01:09:38,720 --> 01:09:43,800
Speaker 1: to be cast and knives out to um. And then

1165
01:09:43,840 --> 01:09:45,880
Speaker 1: another one just to follow up on that. There's some

1166
01:09:46,040 --> 01:09:50,000
Speaker 1: Katie Delaney at Katie Delaney just again, tweeting out just

1167
01:09:50,080 --> 01:09:53,040
Speaker 1: a quote tweet of the Hollywood reporters saying, Kate Hudson

1168
01:09:53,080 --> 01:09:56,120
Speaker 1: joins Knives Out Too, and she tweets, this whole process

1169
01:09:56,200 --> 01:09:58,640
Speaker 1: is starting to look very synectic in New York, like

1170
01:09:58,760 --> 01:10:01,400
Speaker 1: Knives Out Too. Will keep cashing until we were all

1171
01:10:01,520 --> 01:10:03,680
Speaker 1: in the movie and no one is in the audience.

1172
01:10:03,800 --> 01:10:09,840
Speaker 1: Tragic and beautiful sounds great to me. Sign me up? Yeah, please.

1173
01:10:10,400 --> 01:10:12,880
Speaker 1: That first one was the whitest movie in the world,

1174
01:10:12,920 --> 01:10:15,599
Speaker 1: and so it's nice to see some some color getting

1175
01:10:15,640 --> 01:10:19,360
Speaker 1: added into the sequel. Everyone said that they liked the

1176
01:10:19,360 --> 01:10:21,439
Speaker 1: first one, that was like, is that the one with

1177
01:10:21,600 --> 01:10:24,400
Speaker 1: um James Bond in it? Is he in the first one? Yes,

1178
01:10:24,560 --> 01:10:28,519
Speaker 1: Daniel Craig doing a foghorn like horn accent. It's really good,

1179
01:10:28,840 --> 01:10:34,439
Speaker 1: It's really fun Daniel Craig. No, he does a thing

1180
01:10:34,560 --> 01:10:39,880
Speaker 1: like that. That's a hard past and then a lot

1181
01:10:39,920 --> 01:10:45,800
Speaker 1: of sweaters in the head. Yeah. Janni Armato tweeted why

1182
01:10:45,800 --> 01:10:47,799
Speaker 1: don't you think you can have a hot girl summer

1183
01:10:47,880 --> 01:10:51,120
Speaker 1: this year? Question mark an actual question my therapist asked

1184
01:10:51,160 --> 01:10:57,120
Speaker 1: me today, and Brodie Goopta tweeted Frankenstein is the doctor.

1185
01:10:57,439 --> 01:11:02,080
Speaker 1: You're gonna let that monster practice medicine. You can find

1186
01:11:02,120 --> 01:11:05,720
Speaker 1: me on Twitter track Underscore Briant. You can find us

1187
01:11:05,720 --> 01:11:08,320
Speaker 1: on Twitter at Daily Zeitgeist. We're at the Daily Zeitgeist

1188
01:11:08,400 --> 01:11:11,439
Speaker 1: on Instagram. We have a Facebook fan page and a website,

1189
01:11:11,520 --> 01:11:15,640
Speaker 1: Daily zeitgeist dot com where post our episodes and our footnote.

1190
01:11:16,680 --> 01:11:20,120
Speaker 1: We're link off to the information that we talked about

1191
01:11:20,120 --> 01:11:22,559
Speaker 1: in today's episode, as well as a song we think

1192
01:11:22,560 --> 01:11:26,439
Speaker 1: you might enjoy. Miles, what song are you thinking people

1193
01:11:26,520 --> 01:11:29,600
Speaker 1: might enjoy? It? Just feeling like an old washed asshole

1194
01:11:29,680 --> 01:11:31,600
Speaker 1: from the early odds and I was just thinking of

1195
01:11:31,640 --> 01:11:36,240
Speaker 1: the Nina Sky track Yo Body Girl. But you know,

1196
01:11:36,520 --> 01:11:39,040
Speaker 1: just to keep it up to date, we're gonna do

1197
01:11:39,080 --> 01:11:41,479
Speaker 1: a remix, okay, so you still get a little bit

1198
01:11:41,520 --> 01:11:43,400
Speaker 1: of the familiar because you gotta have that Nina s

1199
01:11:43,439 --> 01:11:45,200
Speaker 1: guy in there, but with a little bit of an

1200
01:11:45,280 --> 01:11:48,519
Speaker 1: updated instrumental track. So this is from Remy Oz r

1201
01:11:48,600 --> 01:11:51,559
Speaker 1: E M I O Z. This is the Remy Oz

1202
01:11:51,680 --> 01:11:55,160
Speaker 1: remix of Nina Skuys Move Your Body And that link

1203
01:11:55,200 --> 01:11:56,920
Speaker 1: will be in the footnotes and you can only get

1204
01:11:56,920 --> 01:12:01,720
Speaker 1: this one on SoundCloud, So check out that. All right, Well,

1205
01:12:01,720 --> 01:12:04,160
Speaker 1: The Daily Zeitgeist is a production by Heart Radio. For

1206
01:12:04,240 --> 01:12:06,760
Speaker 1: more podcast for my heart Radio, visit the heart Radio app,

1207
01:12:06,800 --> 01:12:09,519
Speaker 1: Apple podcast, or wherever you listen to your favorite shows.

1208
01:12:09,600 --> 01:12:12,160
Speaker 1: That is going to do it for us this morning.

1209
01:12:12,520 --> 01:12:15,160
Speaker 1: We're back this afternoon to tell you what's trending, and

1210
01:12:15,200 --> 01:12:17,240
Speaker 1: we will talk to you all then by