1
00:00:01,760 --> 00:00:02,880
Speaker 1: Also media.

2
00:00:04,160 --> 00:00:18,759
Speaker 2: We're still here, We're still in Las Vegas. I'm still

3
00:00:18,760 --> 00:00:21,040
Speaker 2: at Tron and this is still better offline. This is

4
00:00:21,079 --> 00:00:24,440
Speaker 2: the second episode of Day five, our last two parter,

5
00:00:25,079 --> 00:00:28,280
Speaker 2: and I was trying to think of something like glib

6
00:00:28,320 --> 00:00:31,319
Speaker 2: and kind of sardonic to say, but I'm just gonna

7
00:00:31,360 --> 00:00:33,280
Speaker 2: be honest. I've had one of the best weeks of

8
00:00:33,280 --> 00:00:36,279
Speaker 2: my life. I've just been really enjoying myself. We've had

9
00:00:36,320 --> 00:00:40,040
Speaker 2: so many really, really great guests. I've got David j

10
00:00:40,240 --> 00:00:45,240
Speaker 2: Roth of course from Defecta Hello, and edwardso Jr. Hello,

11
00:00:45,440 --> 00:00:49,760
Speaker 2: And Carl Schernard of the Las Vegas Sun, and all

12
00:00:49,800 --> 00:00:52,199
Speaker 2: week has just been awesome. People. Kyle, I talked over you.

13
00:00:52,320 --> 00:00:57,480
Speaker 2: I apologize just saying hello. Yeah, that's enough. So Kyle

14
00:00:57,640 --> 00:01:01,520
Speaker 2: your Ed's show, Okay, getting ahead of you. No, So

15
00:01:01,560 --> 00:01:03,800
Speaker 2: you're a general assignment reporter. Yeah, So what have you

16
00:01:03,840 --> 00:01:04,759
Speaker 2: been covering at the show?

17
00:01:05,240 --> 00:01:07,000
Speaker 3: Well, it's pretty unique for me because, you know, a

18
00:01:07,000 --> 00:01:08,840
Speaker 3: lot of the media that comes here is from you know,

19
00:01:09,280 --> 00:01:11,640
Speaker 3: across the country, across the world looking at whatever new

20
00:01:11,680 --> 00:01:14,160
Speaker 3: text coming and I get to cover from a local

21
00:01:14,200 --> 00:01:17,600
Speaker 3: angle and how it affects Vegas and fifically, you know

22
00:01:17,680 --> 00:01:19,920
Speaker 3: what shown here could be implemented in the city in

23
00:01:20,000 --> 00:01:20,959
Speaker 3: the next couple of years.

24
00:01:21,080 --> 00:01:22,759
Speaker 2: So can you talk a little bit about that. I'm

25
00:01:22,760 --> 00:01:27,080
Speaker 2: a local. Yeah, I'm out in Green Valley, Henderson. Well

26
00:01:27,120 --> 00:01:29,760
Speaker 2: then no, it's still less Vegas no ate true way.

27
00:01:30,000 --> 00:01:32,560
Speaker 3: Yeah, so yeah, I was. I was talking to a

28
00:01:32,720 --> 00:01:35,039
Speaker 3: couple of different companies this week. One of them was

29
00:01:35,319 --> 00:01:39,240
Speaker 3: Autonomous Hotel, which is they call it the first AI

30
00:01:39,400 --> 00:01:40,119
Speaker 3: powered hotel.

31
00:01:40,120 --> 00:01:41,679
Speaker 2: Okay, can you define any of that?

32
00:01:42,840 --> 00:01:43,200
Speaker 4: Yeah?

33
00:01:43,240 --> 00:01:46,160
Speaker 3: So, a lot of what that means is collecting a

34
00:01:46,200 --> 00:01:49,800
Speaker 3: lot of user data and then using that to personalize

35
00:01:49,960 --> 00:01:52,400
Speaker 3: kind of the experience of It's also it's a hotel

36
00:01:52,440 --> 00:01:55,680
Speaker 3: slash apartment, so there's gonna be some split between there.

37
00:01:55,680 --> 00:01:58,040
Speaker 3: But for the hotel, it's you know, like remembering your

38
00:01:58,080 --> 00:02:02,480
Speaker 3: coffee order, what direction like your windows, and then when

39
00:02:02,520 --> 00:02:05,200
Speaker 3: you come direction I like that, No, like if you

40
00:02:05,240 --> 00:02:06,680
Speaker 3: like it facing south or west or north?

41
00:02:06,760 --> 00:02:08,880
Speaker 2: Oh, sorry for your Okay, that makes most sense for

42
00:02:08,919 --> 00:02:12,399
Speaker 2: a second. But being like brutalized by CS long enough

43
00:02:12,400 --> 00:02:14,760
Speaker 2: that I'm just like, okay, man, they got moving windows.

44
00:02:14,800 --> 00:02:18,640
Speaker 3: Now, No, the windows I'm I've been I wasn't told this,

45
00:02:18,680 --> 00:02:19,919
Speaker 3: but I'm pretty sure they're stationary.

46
00:02:20,560 --> 00:02:22,400
Speaker 4: Uh, saying somewhere else.

47
00:02:23,200 --> 00:02:25,639
Speaker 3: So, yeah, there's there's a lot of premig just data

48
00:02:25,639 --> 00:02:28,320
Speaker 3: scraping from the week they were I asked about, you know,

49
00:02:28,400 --> 00:02:30,760
Speaker 3: data privacy and stuff like that. Uh, and they were

50
00:02:30,800 --> 00:02:33,480
Speaker 3: all about, you know, whatever data they collect, is the

51
00:02:33,600 --> 00:02:34,639
Speaker 3: user giving it to them?

52
00:02:34,680 --> 00:02:39,720
Speaker 1: And did they sell it? I imagine no, they said they were.

53
00:02:39,960 --> 00:02:42,800
Speaker 5: Well, really more regifting in this scenario.

54
00:02:43,560 --> 00:02:46,520
Speaker 3: No, they said, you know, they they're put a lot

55
00:02:46,560 --> 00:02:49,480
Speaker 3: of emphasis on keeping that data very secure. You know,

56
00:02:49,560 --> 00:02:51,240
Speaker 3: I was talking with the culinary Union.

57
00:02:51,280 --> 00:02:53,480
Speaker 2: No, no, but sorry I had to push back. Yeah, yeah,

58
00:02:53,520 --> 00:02:59,520
Speaker 2: secure is not the same as not sharing it. So yeah,

59
00:02:59,639 --> 00:03:05,280
Speaker 2: have they been remotely giving on I mean, if the

60
00:03:05,320 --> 00:03:07,639
Speaker 2: answer is you don't know, yeah, I'm not sure. No. No,

61
00:03:07,680 --> 00:03:09,400
Speaker 2: but this is not a failing on you. This is

62
00:03:09,440 --> 00:03:12,280
Speaker 2: them being like, thank god, thank god, we don't have

63
00:03:12,320 --> 00:03:14,239
Speaker 2: to say. The thing is, which is we are selling

64
00:03:14,280 --> 00:03:18,680
Speaker 2: this to the points guy and airlines and hotels, because

65
00:03:18,840 --> 00:03:22,359
Speaker 2: that's the thing. These hotels around here are like data warehouse.

66
00:03:22,440 --> 00:03:24,680
Speaker 2: Oh yeah, the amount of shit they collect on you

67
00:03:24,800 --> 00:03:27,560
Speaker 2: is crazy, not just through them. I actually, this is

68
00:03:27,560 --> 00:03:31,040
Speaker 2: a question do you know anything about data collection practices here?

69
00:03:31,080 --> 00:03:33,120
Speaker 2: And this is I don't either, So if you.

70
00:03:33,080 --> 00:03:35,680
Speaker 3: Don't, I'm not super familiar with it. I mean, surveillance

71
00:03:35,720 --> 00:03:39,640
Speaker 3: is nothing new in Las Vegas. You know, it's not

72
00:03:40,520 --> 00:03:45,480
Speaker 3: rare to find hotels working with the government. That's pretty normal.

73
00:03:46,040 --> 00:03:47,280
Speaker 2: In what ways they work together.

74
00:03:47,840 --> 00:03:52,600
Speaker 3: Oh, you know FBI, if they're looking for something I'm not.

75
00:03:52,680 --> 00:03:53,840
Speaker 1: I honestly don't know these.

76
00:03:54,360 --> 00:03:57,680
Speaker 2: If there's even because I love living here, but I'm

77
00:03:57,720 --> 00:04:02,120
Speaker 2: also a weird, greasy freak and I understand what Vegas is,

78
00:04:02,160 --> 00:04:03,640
Speaker 2: which is you walk in here if you're not being

79
00:04:03,640 --> 00:04:05,360
Speaker 2: to Vegas, so you haven't spent a lot of time here.

80
00:04:05,600 --> 00:04:09,000
Speaker 2: There are cameras everywhere, Yeah, everywhere you go. Not in

81
00:04:09,040 --> 00:04:12,559
Speaker 2: the rooms, I think, but in the hallways, in the casinos,

82
00:04:12,600 --> 00:04:16,159
Speaker 2: and there are You may think that the scariest place

83
00:04:16,279 --> 00:04:19,719
Speaker 2: cameras can look at you is a bank. It's actually

84
00:04:19,760 --> 00:04:23,160
Speaker 2: a casino. They are they are watching and you can

85
00:04:23,160 --> 00:04:26,599
Speaker 2: make the glip to ooh the iron sky. No for real, though,

86
00:04:26,760 --> 00:04:29,560
Speaker 2: it's one of the safest places to be, yeah, because

87
00:04:30,560 --> 00:04:32,919
Speaker 2: they are watching you, and they're watching you because you

88
00:04:32,960 --> 00:04:35,400
Speaker 2: could do stuff with their money, which is not good.

89
00:04:35,600 --> 00:04:38,960
Speaker 2: But anyway, continue, So you've seen this this AI powered hotel, Yeah,

90
00:04:39,000 --> 00:04:39,839
Speaker 2: and it's it's.

91
00:04:39,720 --> 00:04:41,520
Speaker 1: Opening next couple months.

92
00:04:41,800 --> 00:04:42,960
Speaker 2: Which one is? Where is it?

93
00:04:43,160 --> 00:04:45,680
Speaker 3: It's actually by Allegiant. It's like, I think, like a

94
00:04:45,800 --> 00:04:47,920
Speaker 3: mile away from Legion. It's not on this trail.

95
00:04:47,960 --> 00:04:49,479
Speaker 2: Oh, so it's one of the closer places.

96
00:04:49,560 --> 00:04:53,160
Speaker 1: Oh whit? Yeah, walk into Legions fun.

97
00:04:53,720 --> 00:04:56,720
Speaker 2: I have season tickets. Man, I want to die.

98
00:04:56,880 --> 00:04:57,520
Speaker 5: Can you walk it?

99
00:04:58,480 --> 00:05:01,120
Speaker 3: You can walk from the MGM. Yeah, I it's not

100
00:05:01,160 --> 00:05:04,000
Speaker 3: delan know anymore. It's w but I usually just park

101
00:05:04,000 --> 00:05:08,279
Speaker 3: there and walk. Yeah, it's I went to the Syracuse game.

102
00:05:08,360 --> 00:05:12,160
Speaker 6: So yeah, this is a question that I've always sort

103
00:05:12,160 --> 00:05:14,279
Speaker 6: of struggled with here as a and you know, in

104
00:05:14,320 --> 00:05:15,880
Speaker 6: Los Angeles as well, any of the sort of as

105
00:05:15,920 --> 00:05:17,880
Speaker 6: a New York person that like I like the idea

106
00:05:17,880 --> 00:05:20,440
Speaker 6: of being able to either take mass transit or walk

107
00:05:20,560 --> 00:05:23,640
Speaker 6: to a thing, and yet like Las Vegas isn't big enough,

108
00:05:23,680 --> 00:05:25,640
Speaker 6: like theoretically, like your phone will tell you that's a

109
00:05:25,680 --> 00:05:28,320
Speaker 6: forty five minute walk, and yet I feel like most

110
00:05:28,320 --> 00:05:29,760
Speaker 6: of that is just fully impractical.

111
00:05:29,880 --> 00:05:30,080
Speaker 4: Yeah.

112
00:05:30,120 --> 00:05:32,120
Speaker 2: I mean I wasn't that bad to get too though.

113
00:05:32,200 --> 00:05:36,520
Speaker 1: I was talking with Oh god, what's the CTA not CEO?

114
00:05:36,560 --> 00:05:39,320
Speaker 2: The other guy, Oh I do not know, don't want.

115
00:05:39,480 --> 00:05:42,080
Speaker 3: I was talking to him and He was like, you know,

116
00:05:42,120 --> 00:05:44,000
Speaker 3: I was asking for a bit of advice on ceas

117
00:05:44,040 --> 00:05:46,240
Speaker 3: and he's like, every walk is longer than you think

118
00:05:46,240 --> 00:05:46,400
Speaker 3: of this.

119
00:05:46,640 --> 00:05:48,360
Speaker 2: That's actually great conference advice.

120
00:05:48,680 --> 00:05:48,880
Speaker 4: Yeah.

121
00:05:48,920 --> 00:05:52,719
Speaker 2: So, but I'm still kind of confused this AI hotel.

122
00:05:54,520 --> 00:05:58,040
Speaker 2: What else does it do other than allegedly remember my preferences?

123
00:05:58,040 --> 00:06:01,400
Speaker 2: Because I have an idea you could have some sort

124
00:06:01,400 --> 00:06:05,800
Speaker 2: of data base of sort, like a place for datar data,

125
00:06:05,920 --> 00:06:08,120
Speaker 2: and you could put the data in that base and

126
00:06:08,160 --> 00:06:11,520
Speaker 2: then you could simply remember which way my thing. What

127
00:06:11,680 --> 00:06:13,599
Speaker 2: does what does AI do with this bit?

128
00:06:13,760 --> 00:06:16,320
Speaker 1: So a lot of it's with their app. So they

129
00:06:16,320 --> 00:06:16,800
Speaker 1: have this thing.

130
00:06:16,960 --> 00:06:17,800
Speaker 2: Oh it's key.

131
00:06:17,880 --> 00:06:24,160
Speaker 3: It's called k ee where they and they described it

132
00:06:24,240 --> 00:06:25,800
Speaker 3: as I have it here at twenty four to seven

133
00:06:25,839 --> 00:06:27,040
Speaker 3: butler and the poll of your hands.

134
00:06:28,480 --> 00:06:31,000
Speaker 5: Sure, so it's just a lot of the requests that.

135
00:06:30,960 --> 00:06:33,080
Speaker 3: You'd be making, not really having to go through a human,

136
00:06:33,160 --> 00:06:35,240
Speaker 3: just saying it into your phone right room.

137
00:06:35,560 --> 00:06:38,080
Speaker 2: This doesn't add functionality to the hotel, surely because the

138
00:06:38,120 --> 00:06:39,320
Speaker 2: butler brings you things.

139
00:06:40,360 --> 00:06:43,640
Speaker 3: Yeah, so a lot of the functionalities I guess just

140
00:06:43,920 --> 00:06:47,200
Speaker 3: having to avoid humans. I mean I asked them about that, like, hey,

141
00:06:47,200 --> 00:06:49,320
Speaker 3: how many humans are going to be working here and

142
00:06:49,360 --> 00:06:50,920
Speaker 3: it's around thirty.

143
00:06:51,560 --> 00:06:54,040
Speaker 1: Which is a hotel, which is not a lot. I mean,

144
00:06:54,080 --> 00:06:56,480
Speaker 1: there's we've that's that's what they told me. I want

145
00:06:56,720 --> 00:06:57,160
Speaker 1: for myself.

146
00:06:57,160 --> 00:06:58,040
Speaker 2: This isn't your company.

147
00:06:58,040 --> 00:06:58,440
Speaker 5: Don't worry.

148
00:06:58,440 --> 00:07:00,000
Speaker 2: I'm not mad at you.

149
00:06:59,839 --> 00:07:00,919
Speaker 5: But there's like a.

150
00:07:01,000 --> 00:07:02,880
Speaker 4: Full time and part time employees.

151
00:07:03,040 --> 00:07:04,080
Speaker 1: That's what That's what they say.

152
00:07:04,160 --> 00:07:06,520
Speaker 3: At a big like Las Vegas three hundred rooms, it's

153
00:07:06,560 --> 00:07:07,000
Speaker 3: not that big.

154
00:07:07,040 --> 00:07:08,279
Speaker 5: That's still pretty big.

155
00:07:08,880 --> 00:07:12,280
Speaker 3: Yeah, like that's ten rooms, but a lot of the

156
00:07:12,440 --> 00:07:14,880
Speaker 3: also is apartments and you don't need as many stuff.

157
00:07:14,960 --> 00:07:17,440
Speaker 6: It is funny that that's like basically where the the

158
00:07:17,440 --> 00:07:20,360
Speaker 6: AI thing. It goes from being like it's like a

159
00:07:20,600 --> 00:07:22,840
Speaker 6: you know, an application on your phone. It's like that,

160
00:07:22,920 --> 00:07:24,760
Speaker 6: but it's AI to suddenly like you get to the

161
00:07:24,880 --> 00:07:27,320
Speaker 6: where the actual rubber meat throat on all of this stuff,

162
00:07:27,320 --> 00:07:28,000
Speaker 6: which is fewer.

163
00:07:28,160 --> 00:07:30,920
Speaker 5: I am going to stay there and I am.

164
00:07:30,800 --> 00:07:33,720
Speaker 2: Going to do an episode, okay, and I'm going to

165
00:07:33,760 --> 00:07:34,640
Speaker 2: have a piss fit.

166
00:07:34,880 --> 00:07:36,120
Speaker 4: You're going to disappear.

167
00:07:37,800 --> 00:07:41,520
Speaker 2: Well, I will be disassociating, like that's the That's so

168
00:07:43,440 --> 00:07:46,880
Speaker 2: it's just frustrating because it's like theoretically an AI hotel

169
00:07:47,360 --> 00:07:50,200
Speaker 2: could well in the sense that if they were to

170
00:07:50,240 --> 00:07:52,440
Speaker 2: find use of preferences that they could just kind of

171
00:07:52,480 --> 00:07:54,680
Speaker 2: move around them. I'm not talking about generative A. I'm

172
00:07:54,680 --> 00:07:58,680
Speaker 2: talking about theoretically algorithms that are capable of knowing a

173
00:07:58,840 --> 00:08:02,240
Speaker 2: user's preference, but only in a much larger hotel system,

174
00:08:02,360 --> 00:08:04,040
Speaker 2: like I don't know Marriott.

175
00:08:04,200 --> 00:08:06,840
Speaker 3: Yeah, well, it's interesting you say that, because I asked

176
00:08:06,880 --> 00:08:08,520
Speaker 3: them about that. I asked, you know, is there any

177
00:08:08,560 --> 00:08:12,240
Speaker 3: interest from hotels in the area, and they said, you know,

178
00:08:12,320 --> 00:08:15,000
Speaker 3: currently we're trying to get everything up and running and

179
00:08:15,040 --> 00:08:17,680
Speaker 3: ready to go, but that there was a lot of

180
00:08:17,760 --> 00:08:20,040
Speaker 3: interest from other hotels and kind of the system you're making.

181
00:08:20,200 --> 00:08:23,080
Speaker 3: And right after I got my interview, I saw someone

182
00:08:23,160 --> 00:08:25,360
Speaker 3: from a Vegas hotel repsent it from a Vegas hotel

183
00:08:25,600 --> 00:08:26,480
Speaker 3: come by and talk.

184
00:08:26,520 --> 00:08:29,200
Speaker 2: Because this isn't entirely out of the Roman possibility for

185
00:08:29,800 --> 00:08:33,200
Speaker 2: thinking about Marriott, for example, they have I don't know

186
00:08:33,200 --> 00:08:36,160
Speaker 2: why I'm talking up like a publicly traded hotel phone,

187
00:08:36,160 --> 00:08:39,120
Speaker 2: but like Marriott's pretty decent, like you can put your

188
00:08:39,200 --> 00:08:41,200
Speaker 2: shit into it. And the frustration I have with the

189
00:08:41,240 --> 00:08:44,200
Speaker 2: AI part is that, yeah, I've specified what kind of

190
00:08:44,240 --> 00:08:47,840
Speaker 2: hotel pillow even very different from a hotel that I

191
00:08:48,000 --> 00:08:50,480
Speaker 2: like in a hotel stay. I'm just not sure what

192
00:08:50,559 --> 00:08:53,120
Speaker 2: else this does other than what they've is suggesting, which

193
00:08:53,160 --> 00:08:55,880
Speaker 2: is what if we just had less people.

194
00:08:56,240 --> 00:08:57,800
Speaker 6: Well, it's the same thing as the stuff that we

195
00:08:57,800 --> 00:09:01,160
Speaker 6: were talking about yesterday with the like smart homes. There's

196
00:09:01,200 --> 00:09:03,360
Speaker 6: a lot of that with AI related stuff, and it

197
00:09:03,400 --> 00:09:07,200
Speaker 6: seems like some of it it's like a a degree

198
00:09:07,320 --> 00:09:10,280
Speaker 6: of convenience that like doesn't just verge upon but like

199
00:09:10,760 --> 00:09:15,080
Speaker 6: goes fully into infantilization or just like i mean, which

200
00:09:15,120 --> 00:09:17,240
Speaker 6: is the place where you get infent That's more of

201
00:09:17,280 --> 00:09:19,400
Speaker 6: what you'd in some ways, like it makes more sense

202
00:09:19,440 --> 00:09:20,880
Speaker 6: for the Isn't that what a hotel's for?

203
00:09:22,160 --> 00:09:22,400
Speaker 2: Right now?

204
00:09:22,480 --> 00:09:25,400
Speaker 5: You're like you're removing variables from the equation that Like.

205
00:09:25,520 --> 00:09:27,760
Speaker 2: It also feels like there are very obvious a I

206
00:09:27,800 --> 00:09:30,600
Speaker 2: thinks a hotel could do, such as making check in quicker,

207
00:09:30,920 --> 00:09:33,200
Speaker 2: making sure you check in with that, making sure no

208
00:09:33,280 --> 00:09:35,880
Speaker 2: but making sure the cleaning is done based on when

209
00:09:36,080 --> 00:09:38,840
Speaker 2: Like I don't know, I'm I ain't no tech doer,

210
00:09:39,040 --> 00:09:42,600
Speaker 2: but I don't know if I had an algorithm that

211
00:09:42,679 --> 00:09:45,680
Speaker 2: would say, and I'm sure Vegas has these where it's like, okay,

212
00:09:45,720 --> 00:09:48,839
Speaker 2: we have a hotel of X size and why number

213
00:09:48,880 --> 00:09:51,079
Speaker 2: of people come in on a Friday, so we can

214
00:09:51,120 --> 00:09:53,080
Speaker 2: say that we need this much, but we have this

215
00:09:53,120 --> 00:09:53,640
Speaker 2: one person.

216
00:09:54,040 --> 00:09:54,640
Speaker 5: It definitely has that.

217
00:09:54,880 --> 00:09:58,280
Speaker 3: Yeah, so this isn't that, No, this is about what

218
00:09:58,400 --> 00:10:01,920
Speaker 3: the experience for the and I mean to be fair,

219
00:10:02,280 --> 00:10:04,199
Speaker 3: A lot of hotels, and I talked to professor, I

220
00:10:04,240 --> 00:10:05,800
Speaker 3: talked a lot of people about this. A lot of

221
00:10:05,840 --> 00:10:09,320
Speaker 3: hotels have just a billion different legacy systems running every

222
00:10:09,320 --> 00:10:10,119
Speaker 3: single function.

223
00:10:09,920 --> 00:10:11,960
Speaker 2: Which feels like the things to upgrade rather than this,

224
00:10:12,360 --> 00:10:13,959
Speaker 2: which is and this is that's kind of the point

225
00:10:14,000 --> 00:10:14,640
Speaker 2: they're trying to do.

226
00:10:14,880 --> 00:10:18,000
Speaker 3: It's one completely integrated system for the entire hotel.

227
00:10:18,120 --> 00:10:19,400
Speaker 1: You know, everything is.

228
00:10:19,440 --> 00:10:24,800
Speaker 2: Content's gonna have so much fucking trouble selling that. So yeah, sorry,

229
00:10:24,920 --> 00:10:27,800
Speaker 2: just there's no way. It's why we have airlines on

230
00:10:28,120 --> 00:10:33,520
Speaker 2: nineties computers. Like you think the Grotzi system of Venetian. Yeah,

231
00:10:33,600 --> 00:10:36,760
Speaker 2: people know I use the Venetian a lot. They do

232
00:10:36,800 --> 00:10:39,640
Speaker 2: you think they're going to upgrade an entire multifested system.

233
00:10:39,640 --> 00:10:41,520
Speaker 2: It seems like an unreal that's physician.

234
00:10:41,600 --> 00:10:43,319
Speaker 1: Yeah, when I was talking to a professor from you

235
00:10:43,400 --> 00:10:44,679
Speaker 1: and LV, great guy.

236
00:10:45,720 --> 00:10:50,200
Speaker 2: You're a real journalist. Also very clear here, like's.

237
00:10:49,200 --> 00:10:51,319
Speaker 3: Great I'm trying to be very very accurate my wording.

238
00:10:53,360 --> 00:10:54,640
Speaker 3: One thing he told me is that that's one of

239
00:10:54,679 --> 00:10:58,360
Speaker 3: the main reasons. I mean, hospitality is Vegas kind of unique,

240
00:10:58,360 --> 00:11:00,599
Speaker 3: but hospitality as industry is not for being on the

241
00:11:00,600 --> 00:11:06,040
Speaker 3: cunning edge. It's known for kind of not the way

242
00:11:06,040 --> 00:11:08,199
Speaker 3: of say, being very stubborn and not really changing it.

243
00:11:08,240 --> 00:11:10,439
Speaker 3: And one of the reasons they're kind of stubborn and

244
00:11:10,880 --> 00:11:13,199
Speaker 3: don't really adapt to the times as quick is because

245
00:11:13,240 --> 00:11:15,720
Speaker 3: of that. Because there's a million systems interacting with each other,

246
00:11:16,040 --> 00:11:19,640
Speaker 3: and when you change one, oh god, that took down everything.

247
00:11:19,679 --> 00:11:22,560
Speaker 2: It's an equilibrium thing. You can't just mess with one

248
00:11:22,600 --> 00:11:23,439
Speaker 2: part of a hotel.

249
00:11:23,559 --> 00:11:26,400
Speaker 3: And that's kind of why, like for a new hotel,

250
00:11:27,040 --> 00:11:29,760
Speaker 3: for them, it's like, Okay, let's not make a billion

251
00:11:29,800 --> 00:11:31,680
Speaker 3: systems and then have to integrate them all later.

252
00:11:31,920 --> 00:11:33,040
Speaker 1: Let's just get it at the outset.

253
00:11:33,160 --> 00:11:36,680
Speaker 2: They can't be the first windows of hotels though they cannot.

254
00:11:37,000 --> 00:11:39,440
Speaker 3: Yeah, I'm not sure if there's other companies having that,

255
00:11:39,440 --> 00:11:40,800
Speaker 3: but they were emphasizing that Witell.

256
00:11:40,840 --> 00:11:43,280
Speaker 2: I'm just imagining startups will do that. So what else

257
00:11:43,320 --> 00:11:44,840
Speaker 2: have you seen moving off of hotels?

258
00:11:44,920 --> 00:11:47,520
Speaker 3: Yeah, I mean I think one of the most interesting

259
00:11:47,520 --> 00:11:49,800
Speaker 3: things I saw was from this company Sorensen, which I

260
00:11:49,800 --> 00:11:53,840
Speaker 3: believe is based in Utah. They're at West and so

261
00:11:54,400 --> 00:11:56,040
Speaker 3: we were talking earlier about this being kind of like

262
00:11:56,080 --> 00:11:57,679
Speaker 3: a decent use of AI, like there are.

263
00:11:57,640 --> 00:11:59,719
Speaker 5: Still good uses of an no I would love to hear.

264
00:12:00,240 --> 00:12:03,400
Speaker 3: And so it's a real time translator that works for

265
00:12:03,720 --> 00:12:07,640
Speaker 3: specifically for like longer form presentations in a city like

266
00:12:07,720 --> 00:12:08,360
Speaker 3: Las Vegas.

267
00:12:08,679 --> 00:12:09,840
Speaker 1: That's obviously very important.

268
00:12:10,120 --> 00:12:14,199
Speaker 3: You know, we have a convention authority, and the way

269
00:12:14,240 --> 00:12:15,920
Speaker 3: it works is that once it's set up by the event,

270
00:12:16,320 --> 00:12:18,760
Speaker 3: all you do is scan a QR code and then

271
00:12:18,800 --> 00:12:21,240
Speaker 3: you can have a real time translation of whoever speaking

272
00:12:21,240 --> 00:12:23,560
Speaker 3: at the front on your phone in I think it's

273
00:12:23,600 --> 00:12:26,400
Speaker 3: twenty five languages. And one of the cooler parts about

274
00:12:26,400 --> 00:12:28,400
Speaker 3: it is that they also trained it with different dialects.

275
00:12:29,240 --> 00:12:31,920
Speaker 2: Okay, I was gonna say, so is this generative AI?

276
00:12:32,840 --> 00:12:35,960
Speaker 1: It's a lot of training training data, Jobert.

277
00:12:36,240 --> 00:12:37,480
Speaker 2: Is it a generative model?

278
00:12:37,520 --> 00:12:37,680
Speaker 5: Is it?

279
00:12:37,720 --> 00:12:38,760
Speaker 2: And you a technology?

280
00:12:38,800 --> 00:12:38,960
Speaker 4: Is it?

281
00:12:38,960 --> 00:12:39,320
Speaker 2: Basically?

282
00:12:39,320 --> 00:12:41,439
Speaker 1: I believe it's a generative model, right.

283
00:12:41,360 --> 00:12:43,839
Speaker 2: So my one concern with that, and I'm glad that

284
00:12:43,880 --> 00:12:49,640
Speaker 2: you mentioned dialects is everyone that I've talked to about

285
00:12:49,679 --> 00:12:53,240
Speaker 2: I can't speak any other languages. I can barely speak English.

286
00:12:53,440 --> 00:12:56,680
Speaker 2: I thus have no experience with it. But everyone I

287
00:12:56,679 --> 00:13:00,200
Speaker 2: talked to is like, there are these subtleties. Yeah, it

288
00:13:00,240 --> 00:13:02,720
Speaker 2: sounds like so how with extra dialects.

289
00:13:02,800 --> 00:13:05,840
Speaker 1: So it's like all good things.

290
00:13:05,840 --> 00:13:07,720
Speaker 3: It's a very human solution to that, where they just

291
00:13:07,800 --> 00:13:10,400
Speaker 3: have a lot of really trained people that you know,

292
00:13:10,440 --> 00:13:13,760
Speaker 3: pretty consistently are checking the models to make sure that

293
00:13:13,800 --> 00:13:16,319
Speaker 3: they're they're working. It's it's not They don't just set

294
00:13:16,360 --> 00:13:17,719
Speaker 3: it to the side. They were really big on this.

295
00:13:17,840 --> 00:13:19,400
Speaker 3: They don't just set to the side and hope it

296
00:13:19,440 --> 00:13:21,880
Speaker 3: works that. They are pretty consistently checking it with a

297
00:13:22,520 --> 00:13:24,160
Speaker 3: group of trained professionals.

298
00:13:24,320 --> 00:13:25,960
Speaker 2: One of the reasons I love having you here is

299
00:13:26,480 --> 00:13:28,920
Speaker 2: being able to respond with this, which is Vegas is

300
00:13:29,000 --> 00:13:32,200
Speaker 2: quite intolerant of bullshit. Weird for this place. It's the

301
00:13:32,559 --> 00:13:35,200
Speaker 2: you can bring whatever you want to see, yes, but

302
00:13:35,240 --> 00:13:37,800
Speaker 2: it's like, oh, you want to sell to our beautiful casinos,

303
00:13:37,800 --> 00:13:39,600
Speaker 2: with our beautiful slot machines that bring us off.

304
00:13:40,720 --> 00:13:42,400
Speaker 5: We love our money.

305
00:13:42,400 --> 00:13:45,840
Speaker 2: Thank you, thank you. You understand we love our slots.

306
00:13:45,960 --> 00:13:49,000
Speaker 2: Why we don't spend we don't have state income tax.

307
00:13:49,480 --> 00:13:52,080
Speaker 2: Our beautiful slot machines. We love them, folks. But it's

308
00:13:52,120 --> 00:13:55,400
Speaker 2: like Vegas is quite intolerant of just shit that don't work,

309
00:13:55,640 --> 00:13:58,440
Speaker 2: because ship that don't work is extremely unprofitable.

310
00:13:58,679 --> 00:13:59,400
Speaker 1: Yeah, and a lot.

311
00:13:59,760 --> 00:14:02,680
Speaker 3: When you're working in the hospitality industry, your main job

312
00:14:02,840 --> 00:14:03,920
Speaker 3: is to keep people happy.

313
00:14:04,280 --> 00:14:05,000
Speaker 1: And when you.

314
00:14:04,960 --> 00:14:06,680
Speaker 2: Want Vegas people are babies.

315
00:14:08,520 --> 00:14:11,520
Speaker 3: And when you are running into tech issues and this

316
00:14:11,760 --> 00:14:14,000
Speaker 3: was again this professor. He's giving me all my lines.

317
00:14:15,080 --> 00:14:16,079
Speaker 2: What was the professor's name.

318
00:14:16,080 --> 00:14:16,880
Speaker 1: Oh, let me get it out.

319
00:14:17,360 --> 00:14:18,360
Speaker 5: Don't worry about no, no, no, no.

320
00:14:19,200 --> 00:14:24,000
Speaker 2: Look, this show can be quite cynical and hitty, and

321
00:14:24,040 --> 00:14:26,400
Speaker 2: I say words that people don't like, and they get

322
00:14:26,440 --> 00:14:28,640
Speaker 2: upset with me, and they email me every day and

323
00:14:28,680 --> 00:14:29,280
Speaker 2: they say.

324
00:14:29,280 --> 00:14:30,200
Speaker 4: Ed, I hope you die.

325
00:14:30,360 --> 00:14:32,800
Speaker 2: And I imagine the cyber trucking you ed. I imagine

326
00:14:32,840 --> 00:14:35,360
Speaker 2: the Ford f one fifty ed, I sort of a

327
00:14:35,400 --> 00:14:37,880
Speaker 2: Ford f one fifty rapped or hang you you bounced

328
00:14:37,920 --> 00:14:40,160
Speaker 2: and you you went in so much.

329
00:14:41,600 --> 00:14:43,280
Speaker 1: His name is a met or dem.

330
00:14:43,320 --> 00:14:46,880
Speaker 3: He is a resorts sorry, the chair of Unovis Resorts

331
00:14:46,880 --> 00:14:48,280
Speaker 3: Gaming and Golf Management department.

332
00:14:48,520 --> 00:14:53,160
Speaker 2: And I imagine a prius anyway. But that's the thing.

333
00:14:53,640 --> 00:14:56,320
Speaker 2: I want these people on here because there is a

334
00:14:56,440 --> 00:14:59,239
Speaker 2: thing I love about Vegas, where there is a dishonest

335
00:14:59,280 --> 00:15:01,840
Speaker 2: on this day. It's just you can't just fling shit

336
00:15:01,920 --> 00:15:05,720
Speaker 2: here because it's a very working class city. It's a

337
00:15:05,800 --> 00:15:08,960
Speaker 2: very it's a pragmatic city in many, many different ways.

338
00:15:09,200 --> 00:15:11,320
Speaker 2: So it's kind of like, I'm more willing to humor

339
00:15:11,360 --> 00:15:13,960
Speaker 2: the idea that they would have this translation thing. Yeah,

340
00:15:14,160 --> 00:15:18,080
Speaker 2: just because putting aside all my feelings, Vegas would simply

341
00:15:18,080 --> 00:15:20,040
Speaker 2: be like, n this fucking sucks. It's going to get

342
00:15:20,080 --> 00:15:22,200
Speaker 2: between the customer and the slums.

343
00:15:22,320 --> 00:15:23,880
Speaker 3: But I mean, when you're running a com I mean

344
00:15:24,000 --> 00:15:27,320
Speaker 3: especially comments like ces having real time translation when I

345
00:15:27,760 --> 00:15:29,840
Speaker 3: think every panels in English.

346
00:15:29,640 --> 00:15:33,480
Speaker 2: Yeah, Anglo well, anglers, anglophote.

347
00:15:33,000 --> 00:15:36,560
Speaker 3: Anglo centric when you know, I'm talking people and there's

348
00:15:36,560 --> 00:15:41,600
Speaker 3: a billion languages here, and you mentioned working class. Another

349
00:15:41,600 --> 00:15:43,640
Speaker 3: part of this is for at story I'm publishing later.

350
00:15:45,160 --> 00:15:47,400
Speaker 3: I talked to the Culinary union about their tech protection.

351
00:15:47,920 --> 00:15:48,840
Speaker 2: Cool. What did they say?

352
00:15:48,920 --> 00:15:50,960
Speaker 1: So they have they've.

353
00:15:50,720 --> 00:15:54,000
Speaker 3: Been working since twenty eighteen, probably longer actually, but they've

354
00:15:54,000 --> 00:15:58,800
Speaker 3: got protection since twenty eighteen, specifically regarding tech replacing workers

355
00:15:59,760 --> 00:16:03,560
Speaker 3: with that. When tech gets introduced to that would affect

356
00:16:03,600 --> 00:16:06,600
Speaker 3: someone's job, they have to and they negotiated this. They

357
00:16:06,600 --> 00:16:09,840
Speaker 3: get a six month notice and part of that there's

358
00:16:09,880 --> 00:16:11,400
Speaker 3: there's kind of two things that come out of that.

359
00:16:11,840 --> 00:16:14,840
Speaker 3: One that gives them time to kind of work out

360
00:16:14,880 --> 00:16:19,080
Speaker 3: the kinks. One example type of a George the Treasury

361
00:16:19,120 --> 00:16:24,240
Speaker 3: Secretary Treasurer Secretary told me, was there was this new

362
00:16:24,480 --> 00:16:29,000
Speaker 3: system for housekeepers that basically was sending them all across

363
00:16:29,000 --> 00:16:31,520
Speaker 3: different zones, all across different floors, and they're like, hey,

364
00:16:31,560 --> 00:16:32,960
Speaker 3: this is you're gonna.

365
00:16:32,800 --> 00:16:33,920
Speaker 1: Break the backs of the workers here.

366
00:16:34,040 --> 00:16:36,560
Speaker 3: Yeah, And so with that time they were able to

367
00:16:36,560 --> 00:16:38,720
Speaker 3: get a fix, no problem. And what it also does

368
00:16:38,760 --> 00:16:41,360
Speaker 3: that if a job gets eliminated or if a position

369
00:16:41,400 --> 00:16:47,360
Speaker 3: is eliminated that like Vegas has a there's plenty of jobs,

370
00:16:48,520 --> 00:16:52,160
Speaker 3: so especially in the hospitality industry. So it gives people

371
00:16:52,200 --> 00:16:56,840
Speaker 3: the time to find somewhere else within you know, the industry,

372
00:16:56,920 --> 00:16:59,040
Speaker 3: stay with the union and you know, keep their pension.

373
00:17:00,800 --> 00:17:03,480
Speaker 3: And there's also a pretty decent severance package if your

374
00:17:03,560 --> 00:17:05,520
Speaker 3: job is eliminated from the attack.

375
00:17:05,720 --> 00:17:07,960
Speaker 2: So fucking cool working union man.

376
00:17:08,119 --> 00:17:10,200
Speaker 5: No, I simply accept no substitute thing.

377
00:17:10,320 --> 00:17:12,360
Speaker 2: Like I live here in people like edge. You live

378
00:17:12,520 --> 00:17:15,439
Speaker 2: in a vending machine and that's why I like it.

379
00:17:15,480 --> 00:17:20,320
Speaker 2: But also there are actual really strong unions. Yeah, there's

380
00:17:20,320 --> 00:17:24,000
Speaker 2: a strike. I've been covering it Virgin. Yeah yeah, so

381
00:17:24,520 --> 00:17:26,760
Speaker 2: what's the strike? I care way more about that than

382
00:17:26,800 --> 00:17:27,000
Speaker 2: the do.

383
00:17:27,280 --> 00:17:29,359
Speaker 3: Oh yeah yeah yeah, So they've been on strike for

384
00:17:29,400 --> 00:17:31,760
Speaker 3: a little bit. Now regarding which who is this is?

385
00:17:31,800 --> 00:17:35,000
Speaker 3: This is Virgin Hotels, right with the culinary union. The

386
00:17:35,080 --> 00:17:38,879
Speaker 3: latest proposal, and this was from a little bit ago,

387
00:17:39,320 --> 00:17:41,840
Speaker 3: was well, the original proposal I believe was no raise

388
00:17:41,960 --> 00:17:43,800
Speaker 3: for the first couple of years of the contract, and

389
00:17:43,840 --> 00:17:47,320
Speaker 3: this was from Virgin from Virgin, and then the secondary proposal,

390
00:17:47,359 --> 00:17:49,520
Speaker 3: at least the secondary proposal I heard about his journalist

391
00:17:50,720 --> 00:17:54,360
Speaker 3: was a consistent thirty cent per hour race per year, wasn't.

392
00:17:54,160 --> 00:17:56,439
Speaker 2: The argument from Virgin They couldn't afford anything?

393
00:17:56,640 --> 00:17:56,880
Speaker 1: Yeah?

394
00:17:56,880 --> 00:17:58,119
Speaker 2: And how true was that?

395
00:17:59,560 --> 00:18:04,600
Speaker 3: So it's hard because their private company, Yeah, so kind of.

396
00:18:05,000 --> 00:18:08,280
Speaker 3: So they used to have their casino run by Mohegan,

397
00:18:08,960 --> 00:18:14,760
Speaker 3: which you can look like the tribe, right, so like

398
00:18:14,840 --> 00:18:17,360
Speaker 3: you you can look at that data and their casino

399
00:18:17,520 --> 00:18:19,760
Speaker 3: or I think it was the only one that was

400
00:18:20,119 --> 00:18:24,480
Speaker 3: I think losing money, which isn't great. So again they

401
00:18:24,480 --> 00:18:28,280
Speaker 3: do have a point, like Virgin is not a super

402
00:18:28,400 --> 00:18:31,880
Speaker 3: successful hotel when it comes to its casino. But what

403
00:18:31,920 --> 00:18:33,919
Speaker 3: they what the union keys pointing at is all you know,

404
00:18:34,040 --> 00:18:37,280
Speaker 3: these giant corporations, a lot of them are. There's what

405
00:18:37,400 --> 00:18:40,440
Speaker 3: it's the Leuna pension fund, one of them in Canada

406
00:18:40,720 --> 00:18:44,480
Speaker 3: that owns the owns the hotel part of the ownership group.

407
00:18:45,119 --> 00:18:47,600
Speaker 3: And then there's another company called fen Gate. So you know,

408
00:18:48,560 --> 00:18:51,320
Speaker 3: the company points to you know, we're an offstra property.

409
00:18:51,440 --> 00:18:55,600
Speaker 3: We can't give you strip pay. And the union's pointing

410
00:18:55,640 --> 00:18:58,080
Speaker 3: at their management saying, you definitely have the money. If

411
00:18:58,119 --> 00:19:00,880
Speaker 3: you want to invest in Vegas, you have to invest

412
00:19:00,880 --> 00:19:08,040
Speaker 3: in the workers, and they've consistently said go back to Canada.

413
00:19:08,280 --> 00:19:10,600
Speaker 2: Yes. So I just want to be clear, Kyle can't

414
00:19:10,600 --> 00:19:12,960
Speaker 2: say this and is no way offering any opinion on

415
00:19:13,040 --> 00:19:16,600
Speaker 2: what I'm going to say, which is solidarity. Now, fuck

416
00:19:16,640 --> 00:19:19,960
Speaker 2: you virgin. Now moving on, what else have you seen

417
00:19:20,160 --> 00:19:22,920
Speaker 2: the Vegas related while you've been here?

418
00:19:23,119 --> 00:19:24,040
Speaker 1: Yeah, So the other.

419
00:19:24,440 --> 00:19:27,679
Speaker 3: Major Vegas company I was looking at was a robotic

420
00:19:27,720 --> 00:19:28,800
Speaker 3: company that's been here for a while.

421
00:19:28,840 --> 00:19:29,600
Speaker 1: That's rich tech.

422
00:19:29,840 --> 00:19:31,000
Speaker 2: Okay, tell me about them.

423
00:19:31,240 --> 00:19:33,439
Speaker 3: So they work on a couple different things. So you

424
00:19:33,520 --> 00:19:37,400
Speaker 3: have like this atom it's called Adam. It's a bartender robot.

425
00:19:38,240 --> 00:19:41,440
Speaker 3: And when I was at the booth for cees. It

426
00:19:41,520 --> 00:19:42,640
Speaker 3: was kind of interesting because I.

427
00:19:42,600 --> 00:19:47,040
Speaker 1: Didn't see demos of the robot making drinks.

428
00:19:47,000 --> 00:19:48,160
Speaker 2: But it was a bartender.

429
00:19:48,240 --> 00:19:50,000
Speaker 3: Yeah, it's like a bartender robot, so it has two arms,

430
00:19:50,000 --> 00:19:55,239
Speaker 3: you can do everything. And the thing that surprised me

431
00:19:55,359 --> 00:19:57,119
Speaker 3: was like the main thing that brought people over to

432
00:19:57,119 --> 00:19:59,600
Speaker 3: the booth was when the robot was dancing to Apa

433
00:19:59,680 --> 00:20:01,840
Speaker 3: Tu by Bruno Mars and I think.

434
00:20:02,160 --> 00:20:07,280
Speaker 2: Familiar to a song since two thousand and seven your views.

435
00:20:07,359 --> 00:20:10,000
Speaker 6: It is funny that they had the robot partender not

436
00:20:10,040 --> 00:20:11,320
Speaker 6: making drinks, but it was like.

437
00:20:11,359 --> 00:20:12,800
Speaker 1: It might have been at some point when I was there,

438
00:20:12,800 --> 00:20:13,200
Speaker 1: it wasn't.

439
00:20:13,240 --> 00:20:18,679
Speaker 6: It was consoling another robot, right, better than.

440
00:20:22,840 --> 00:20:27,000
Speaker 3: Go back to so But the the thing, it was

441
00:20:27,040 --> 00:20:28,960
Speaker 3: interesting because it was drawing a crowd by its little

442
00:20:29,000 --> 00:20:31,320
Speaker 3: dance with the music. And I was talking to someone

443
00:20:31,320 --> 00:20:35,240
Speaker 3: with the company and they were like, you know, the.

444
00:20:34,119 --> 00:20:36,040
Speaker 1: The show of it, the spectacles.

445
00:20:36,040 --> 00:20:37,600
Speaker 3: I asked like, you know, at what point do we

446
00:20:37,640 --> 00:20:40,359
Speaker 3: get past a spectacle and into just being there?

447
00:20:40,640 --> 00:20:42,880
Speaker 1: And he's like, spectacles part.

448
00:20:42,680 --> 00:20:48,800
Speaker 2: Of the cell. This is Vegas quiet, spectacles part of

449
00:20:48,840 --> 00:20:49,080
Speaker 2: the cell.

450
00:20:49,160 --> 00:20:51,480
Speaker 5: Yeah, that's also CS too though, right, like it seems

451
00:20:51,480 --> 00:20:52,480
Speaker 5: like the Vegas.

452
00:20:52,200 --> 00:20:52,879
Speaker 2: Is honest about it.

453
00:20:53,000 --> 00:20:56,480
Speaker 5: Yeah, yeah uh.

454
00:20:56,480 --> 00:20:59,000
Speaker 3: And then they had another system that was a lot

455
00:20:59,040 --> 00:21:02,080
Speaker 3: more utilitar. And you also, by the way, can find

456
00:21:02,119 --> 00:21:04,879
Speaker 3: some of their robots at all the Boyd Gaming or

457
00:21:04,960 --> 00:21:05,400
Speaker 3: not all of them.

458
00:21:05,400 --> 00:21:06,720
Speaker 2: But what are the Boyd Gaming for?

459
00:21:07,720 --> 00:21:10,840
Speaker 6: That's like the Awe strip, that Sam's Town and those ones. Yeah,

460
00:21:10,880 --> 00:21:12,880
Speaker 6: somebody was telling me about there was the it's.

461
00:21:12,680 --> 00:21:16,000
Speaker 3: At the Orleans Alante. I might be pronouncing that wrong. Sorry,

462
00:21:16,040 --> 00:21:16,560
Speaker 3: I'm new here.

463
00:21:17,000 --> 00:21:18,520
Speaker 1: And sun Coast cool.

464
00:21:19,040 --> 00:21:22,640
Speaker 3: So they'll have like delivery robots like delivering food and

465
00:21:22,680 --> 00:21:27,280
Speaker 3: then this other robots Skylark and that's more like getting

466
00:21:27,280 --> 00:21:30,800
Speaker 3: a robot to clean floors and make deliveries and stuff

467
00:21:30,840 --> 00:21:34,240
Speaker 3: like that. And so, I mean, you know, like all things,

468
00:21:34,320 --> 00:21:37,440
Speaker 3: the main one of the main things preventing it from

469
00:21:37,480 --> 00:21:40,760
Speaker 3: mass adoption is price. What was it they used to

470
00:21:40,800 --> 00:21:43,639
Speaker 3: have a lot of the robots used to be like

471
00:21:43,720 --> 00:21:45,119
Speaker 3: you just it's like I think it was like one

472
00:21:45,200 --> 00:21:48,560
Speaker 3: hundred and eight thousand dollars, But now they're working off

473
00:21:48,560 --> 00:21:50,159
Speaker 3: more of like a subscription model.

474
00:21:51,160 --> 00:21:53,240
Speaker 5: Baby much of that maybe.

475
00:21:55,080 --> 00:21:56,000
Speaker 2: Do exactly.

476
00:21:56,359 --> 00:21:59,399
Speaker 3: So you have the bartender robot, which is I have

477
00:21:59,440 --> 00:22:03,919
Speaker 3: the price can it tend bar clean, I mean, like

478
00:22:04,000 --> 00:22:06,399
Speaker 3: actually drinks reliably.

479
00:22:06,880 --> 00:22:09,040
Speaker 2: How does it accept the drink order?

480
00:22:09,520 --> 00:22:11,520
Speaker 5: Yeah, I'm sure aware of how drinks.

481
00:22:11,560 --> 00:22:12,040
Speaker 1: I'm not sure.

482
00:22:12,200 --> 00:22:16,320
Speaker 4: I know the drink make a little hand motion, but

483
00:22:16,440 --> 00:22:19,760
Speaker 4: he also probably does. It also come with like an inventory.

484
00:22:19,160 --> 00:22:23,800
Speaker 3: System, Like I'm not sure exactly how its inventory system works,

485
00:22:23,800 --> 00:22:25,880
Speaker 3: but i know for like Tipsy Robot, which is kind

486
00:22:25,880 --> 00:22:28,400
Speaker 3: of like the other that's actually at the Phenician.

487
00:22:28,480 --> 00:22:30,800
Speaker 6: Yeah, there's one downstairs and that has like f.

488
00:22:32,080 --> 00:22:34,600
Speaker 3: That's like a the point of sales system where you

489
00:22:34,640 --> 00:22:36,520
Speaker 3: just kind of like tap on a tablet and it

490
00:22:36,560 --> 00:22:38,920
Speaker 3: gives you the drink. So I imagine it will be

491
00:22:38,960 --> 00:22:41,960
Speaker 3: something similar to that. I'm not positive, but I imagine

492
00:22:42,000 --> 00:22:43,200
Speaker 3: its probably a similar system.

493
00:22:43,000 --> 00:22:46,280
Speaker 4: To robot because it feels like it probably it's probably

494
00:22:46,840 --> 00:22:48,840
Speaker 4: not too hard for them to be like, okay, as

495
00:22:48,880 --> 00:22:52,520
Speaker 4: long as we catalog and keep every single drink in

496
00:22:52,560 --> 00:22:56,280
Speaker 4: a certain place, and maybe if you like make a

497
00:22:56,320 --> 00:22:59,520
Speaker 4: request that's outside the bounds of the inventory, then it says.

498
00:22:59,320 --> 00:23:00,879
Speaker 5: Do you mean Yeah.

499
00:23:02,040 --> 00:23:05,000
Speaker 2: I feel bad about these though, because there are two

500
00:23:05,040 --> 00:23:07,719
Speaker 2: cities that have my heart, New York and Las Vegas,

501
00:23:07,720 --> 00:23:10,240
Speaker 2: Like it was my favorite. I got here in a

502
00:23:10,280 --> 00:23:12,199
Speaker 2: weird way, and I will probably leave here in a

503
00:23:12,200 --> 00:23:17,359
Speaker 2: weird way. But the thing is, the bartenders here are fascinating,

504
00:23:17,880 --> 00:23:20,040
Speaker 2: that's fun to talk to. I don't want to rope

505
00:23:20,080 --> 00:23:22,040
Speaker 2: at replacing them, because first of all, I don't believe

506
00:23:22,160 --> 00:23:25,639
Speaker 2: Robert will do his good job. But also that was

507
00:23:25,680 --> 00:23:28,399
Speaker 2: not me coughing for any ironic reasons. I really was

508
00:23:28,480 --> 00:23:31,840
Speaker 2: just coughing. The bartender's here rock. But also, like the

509
00:23:31,920 --> 00:23:37,240
Speaker 2: accumulated experience of witnessing Vegas is what makes a bartender

510
00:23:37,320 --> 00:23:42,280
Speaker 2: masks all about people watching, yeah, but also people experiencing Yeah.

511
00:23:42,680 --> 00:23:44,200
Speaker 6: This kind of comes back to another one of the

512
00:23:44,440 --> 00:23:46,400
Speaker 6: things that we kind of keep bumping up against with

513
00:23:46,880 --> 00:23:49,560
Speaker 6: going down there is this idea that somehow the important

514
00:23:49,600 --> 00:23:52,040
Speaker 6: thing I understand it from a business perspective, but from

515
00:23:52,160 --> 00:23:54,399
Speaker 6: any other perspective, the idea that you want to remove

516
00:23:54,920 --> 00:23:58,240
Speaker 6: human interaction from every process and every transaction.

517
00:23:58,600 --> 00:24:00,959
Speaker 1: The thing I I keep saying this.

518
00:24:01,000 --> 00:24:06,600
Speaker 3: I asked them about that, and both this company and

519
00:24:07,640 --> 00:24:09,840
Speaker 3: I think Atomics also to this. They don't want to

520
00:24:10,760 --> 00:24:14,760
Speaker 3: replace humans. They want them to like work alongside them.

521
00:24:14,680 --> 00:24:15,840
Speaker 4: They want to augment them.

522
00:24:16,359 --> 00:24:19,000
Speaker 1: The phrase, the phrase I was told was coba.

523
00:24:20,200 --> 00:24:24,880
Speaker 5: That parallel, So it's cobot.

524
00:24:24,480 --> 00:24:26,760
Speaker 3: So instead of it being a robot replacing you, it's

525
00:24:26,800 --> 00:24:27,919
Speaker 3: one you work with.

526
00:24:29,240 --> 00:24:33,800
Speaker 2: That is loathsome Well, I don't like the idea of like,

527
00:24:34,440 --> 00:24:38,000
Speaker 2: unless the robot is like doing annoying things, you don't.

528
00:24:37,840 --> 00:24:39,159
Speaker 4: Want a robot understudy.

529
00:24:40,320 --> 00:24:40,760
Speaker 2: Yeah, what if?

530
00:24:41,280 --> 00:24:42,800
Speaker 6: What if it just what if it just sat on

531
00:24:42,800 --> 00:24:44,399
Speaker 6: your arm and looked at you and blinked?

532
00:24:44,440 --> 00:24:46,400
Speaker 5: Sometimes?

533
00:24:46,720 --> 00:24:47,720
Speaker 1: Was that the pet?

534
00:24:48,200 --> 00:24:49,960
Speaker 5: Yeah, we've heard.

535
00:24:49,760 --> 00:24:52,640
Speaker 6: Good things weirdly like previous episodes, but yeah, they're kind

536
00:24:52,640 --> 00:24:52,879
Speaker 6: of like.

537
00:24:52,920 --> 00:24:56,320
Speaker 5: Look, I don't I was not initially that into the idea, but.

538
00:24:56,280 --> 00:24:59,000
Speaker 1: It's very it's very large eyes like I have my

539
00:24:59,080 --> 00:24:59,800
Speaker 1: cat and I love my.

540
00:24:59,800 --> 00:25:04,480
Speaker 6: Yeah, a lot of people are living things. But yeah,

541
00:25:04,520 --> 00:25:06,320
Speaker 6: that the cobot thing.

542
00:25:06,560 --> 00:25:09,320
Speaker 2: I just Also, it sounds like something said by someone

543
00:25:09,359 --> 00:25:11,159
Speaker 2: who has not worked a job in a while.

544
00:25:11,400 --> 00:25:13,360
Speaker 6: It also sounds like the hyper loop shit where it's

545
00:25:13,359 --> 00:25:16,160
Speaker 6: basically it takes two people to get two people into

546
00:25:16,200 --> 00:25:18,400
Speaker 6: a car that then takes them someplace.

547
00:25:18,040 --> 00:25:18,480
Speaker 5: But it's not.

548
00:25:18,880 --> 00:25:20,760
Speaker 3: And then you had the pro public of story that

549
00:25:20,800 --> 00:25:23,720
Speaker 3: came out this week about which was about what about

550
00:25:23,760 --> 00:25:24,840
Speaker 3: him to do something bad?

551
00:25:25,040 --> 00:25:28,000
Speaker 5: This don't tell me if you did something I want to.

552
00:25:27,960 --> 00:25:31,920
Speaker 1: Do something against I mean no me.

553
00:25:31,640 --> 00:25:34,919
Speaker 6: Oh yes, I got when I went over to the

554
00:25:35,000 --> 00:25:38,600
Speaker 6: convention center yesterday, and it was fully the dumbest shit

555
00:25:38,600 --> 00:25:39,560
Speaker 6: I've ever done in my life.

556
00:25:39,600 --> 00:25:41,040
Speaker 5: I really loved it. I thought it was amazing.

557
00:25:41,080 --> 00:25:42,600
Speaker 1: Yeah, I need to give this a proper read.

558
00:25:42,600 --> 00:25:45,359
Speaker 3: But pro Public published a piece of car Elon's Elon

559
00:25:45,440 --> 00:25:47,800
Speaker 3: Musk Boring Company is tunneling beneath Las Vegas with a

560
00:25:47,840 --> 00:25:48,680
Speaker 3: little oversight.

561
00:25:48,920 --> 00:25:51,520
Speaker 5: Oh really, Well, I'm sure they're probably doing a good job.

562
00:25:51,920 --> 00:25:54,600
Speaker 2: That's the weird thing, though, It's like this city seemed

563
00:25:54,640 --> 00:25:57,560
Speaker 2: more resistant to that kind of stuff. Are they just

564
00:25:57,640 --> 00:26:00,160
Speaker 2: letting him dig tunnels because it gets the money?

565
00:26:00,359 --> 00:26:03,720
Speaker 3: Well, I mean it's I have not covered the enough

566
00:26:03,760 --> 00:26:04,280
Speaker 3: to answer that.

567
00:26:04,280 --> 00:26:06,479
Speaker 2: That's fine, No, sorry, I must be clear. I'm not

568
00:26:06,520 --> 00:26:09,000
Speaker 2: holding you to account here. You didn't do the reporting.

569
00:26:09,040 --> 00:26:11,480
Speaker 2: But it's just like it feels like such an aberration

570
00:26:11,680 --> 00:26:15,840
Speaker 2: because one of the things that destroys people about Vegas

571
00:26:15,960 --> 00:26:18,879
Speaker 2: is that everything is convenient at all times. Everything is

572
00:26:18,880 --> 00:26:22,000
Speaker 2: fifteen minutes exactly, thank god. Damn. It's so good that

573
00:26:22,640 --> 00:26:27,679
Speaker 2: real resident here which is five months, three years baby,

574
00:26:27,720 --> 00:26:30,720
Speaker 2: and you know it better than anyone. And it's like, wow,

575
00:26:30,800 --> 00:26:33,560
Speaker 2: I can have diet coke whenever I need to The

576
00:26:33,640 --> 00:26:35,800
Speaker 2: problem is there are people who have other kinds of

577
00:26:35,800 --> 00:26:38,440
Speaker 2: coke they can get in fifteen minutes, and then they do.

578
00:26:38,920 --> 00:26:42,360
Speaker 2: Then there are other proclivities they can fuel in fifteen minutes.

579
00:26:42,440 --> 00:26:44,320
Speaker 6: Is this what they mean by fifteen minute cities when

580
00:26:44,359 --> 00:26:50,440
Speaker 6: you hear that phrase, Yes, yes, I start a place.

581
00:26:50,560 --> 00:26:53,040
Speaker 3: It's a fifteen minute city run by cars.

582
00:26:53,600 --> 00:26:55,399
Speaker 5: Yeah. Actually that's really weird.

583
00:26:55,640 --> 00:26:58,119
Speaker 2: I'm so glad you're on the last episode. This is

584
00:26:58,280 --> 00:27:03,040
Speaker 2: valuable information about Vegas. The thing is the result of

585
00:27:03,119 --> 00:27:07,760
Speaker 2: every proclivity Jesus Christ being available at all times, is

586
00:27:07,760 --> 00:27:10,280
Speaker 2: that Vegas is just like no, man, I understand, you

587
00:27:10,400 --> 00:27:12,240
Speaker 2: got this new tech and you're very horny and you

588
00:27:12,359 --> 00:27:15,480
Speaker 2: raised all this money, like very exciting. However, you're between

589
00:27:15,560 --> 00:27:18,640
Speaker 2: the beautiful slot machines and our beautiful customers, who are

590
00:27:18,680 --> 00:27:22,320
Speaker 2: anyone who is here, and they ain't going to PRIM.

591
00:27:22,359 --> 00:27:25,080
Speaker 1: So ye had a pretty bad believe they are pretty

592
00:27:25,080 --> 00:27:25,440
Speaker 1: bad gaming.

593
00:27:26,240 --> 00:27:28,400
Speaker 2: And by the way, if they ever find a way

594
00:27:28,440 --> 00:27:32,040
Speaker 2: to get people quicker to PRIM one hundred billion dollar industry,

595
00:27:32,080 --> 00:27:34,960
Speaker 2: I'm just giving people like that. Primm is a city

596
00:27:35,040 --> 00:27:37,040
Speaker 2: that is far further than it looks.

597
00:27:37,040 --> 00:27:40,400
Speaker 6: Oh it's Nevada. You guys, did one of those that's cool.

598
00:27:40,640 --> 00:27:44,520
Speaker 2: No, yes, in the sense that there is a strange

599
00:27:44,520 --> 00:27:49,760
Speaker 2: authority with money that has created the city.

600
00:27:49,800 --> 00:27:50,600
Speaker 5: He's ambitious.

601
00:27:50,880 --> 00:27:54,000
Speaker 2: It's a strange, but I don't have enough prim exp

602
00:27:55,440 --> 00:27:56,600
Speaker 2: some shrooms.

603
00:27:56,160 --> 00:28:03,240
Speaker 4: And going to Robert, Let's find Silica Valley's Eldorado.

604
00:28:03,640 --> 00:28:07,840
Speaker 2: But the launcher point is that Vegas is intolerant of things,

605
00:28:07,880 --> 00:28:11,200
Speaker 2: not because of good or bad, but because of efficiency.

606
00:28:11,280 --> 00:28:12,560
Speaker 5: Oh yeah, it's all bad efficiency.

607
00:28:12,920 --> 00:28:16,840
Speaker 2: And that's the weird thing. Cus exists in this very

608
00:28:16,880 --> 00:28:20,880
Speaker 2: inefficient way here and it's just Vegas is like, I'll take.

609
00:28:20,680 --> 00:28:22,760
Speaker 3: A little well yeah, I mean it's it might be

610
00:28:22,840 --> 00:28:25,800
Speaker 3: inefficient for the tech industry, but it's a great money

611
00:28:25,800 --> 00:28:29,640
Speaker 3: maker for the city, which.

612
00:28:29,440 --> 00:28:31,920
Speaker 2: Is a great description in Vegas. I mean, this may

613
00:28:31,960 --> 00:28:33,200
Speaker 2: destroy you, but it.

614
00:28:33,119 --> 00:28:36,040
Speaker 3: May you know, it might not be great for you know,

615
00:28:36,240 --> 00:28:40,160
Speaker 3: there's AI being put into everything all that stuff, but

616
00:28:40,480 --> 00:28:43,000
Speaker 3: I mean, look, it's a very large conference that the

617
00:28:43,040 --> 00:28:45,479
Speaker 3: city makes good money off of. And we just had

618
00:28:45,480 --> 00:28:48,480
Speaker 3: a recent F one report or at recent November gaming

619
00:28:48,520 --> 00:28:52,240
Speaker 3: revenue report and F one not performing the way people

620
00:28:52,280 --> 00:28:55,280
Speaker 3: want it to. So I mean these conventions are in

621
00:28:55,680 --> 00:28:57,840
Speaker 3: I mean, they keep the city afloat, especially I mean

622
00:28:58,200 --> 00:29:01,120
Speaker 3: when people couldn't travel here in twenty twenty. I mean

623
00:29:01,160 --> 00:29:04,040
Speaker 3: I wasn't here about it. I wash then you know strange.

624
00:29:04,200 --> 00:29:06,320
Speaker 3: I mean it was also the depression here was it

625
00:29:06,360 --> 00:29:06,920
Speaker 3: was terrible.

626
00:29:07,760 --> 00:29:09,880
Speaker 2: Like this is a working class city, and when you

627
00:29:09,880 --> 00:29:12,600
Speaker 2: think about c s a lot of engineers and such,

628
00:29:13,080 --> 00:29:16,480
Speaker 2: Vegas is a place which is very working class. And

629
00:29:16,560 --> 00:29:19,120
Speaker 2: the effects of these conferences are quite pronounced.

630
00:29:19,200 --> 00:29:21,720
Speaker 1: Yeah, and it's important, it's important for the city.

631
00:29:21,640 --> 00:29:26,080
Speaker 2: So very meaningful. Ending for a third of the episode

632
00:29:26,080 --> 00:29:28,920
Speaker 2: that mister David rothwork and people find you.

633
00:29:29,120 --> 00:29:32,320
Speaker 6: Defector dot com the website and I do the distraction

634
00:29:32,400 --> 00:29:33,120
Speaker 6: podcast there.

635
00:29:33,280 --> 00:29:36,080
Speaker 2: Well you're on okay, Well just move past that. You

636
00:29:36,160 --> 00:29:37,160
Speaker 2: messed up the order there.

637
00:29:37,200 --> 00:29:38,080
Speaker 5: Oh I did. I'm sorry.

638
00:29:38,160 --> 00:29:39,360
Speaker 2: No, no, no, no, it's gone.

639
00:29:39,360 --> 00:29:41,880
Speaker 5: I don't get any second shot at this working people

640
00:29:42,200 --> 00:29:42,560
Speaker 5: take it over.

641
00:29:43,560 --> 00:29:45,080
Speaker 1: I am still do it.

642
00:29:45,080 --> 00:29:46,080
Speaker 2: Another cut it.

643
00:29:48,240 --> 00:29:50,120
Speaker 1: I'm still on X believe it or not.

644
00:29:50,200 --> 00:29:52,080
Speaker 2: I told the Everything app.

645
00:29:52,200 --> 00:29:54,680
Speaker 6: Yeah, I'm on there too, but I only only for banking.

646
00:29:57,440 --> 00:29:58,880
Speaker 6: Don't use it for social network.

647
00:29:58,920 --> 00:29:59,280
Speaker 2: I use it.

648
00:29:59,440 --> 00:30:01,800
Speaker 1: I put my cat scans in there. Ye see what

649
00:30:01,800 --> 00:30:02,840
Speaker 1: Crock tells me about it.

650
00:30:02,840 --> 00:30:03,720
Speaker 3: It's like, l.

651
00:30:05,320 --> 00:30:06,080
Speaker 5: You have disease.

652
00:30:07,000 --> 00:30:11,800
Speaker 6: Your discs are very cheeky, you get the elon butt

653
00:30:11,800 --> 00:30:15,840
Speaker 6: head last when it uploads successful, you're like, cool, it's

654
00:30:15,880 --> 00:30:19,920
Speaker 6: processing way, Kyle, where could people actually find you?

655
00:30:20,080 --> 00:30:22,640
Speaker 1: Kyle Underscore Schnard C H O U I N A

656
00:30:22,720 --> 00:30:22,920
Speaker 1: R D.

657
00:30:23,440 --> 00:30:25,520
Speaker 3: And then the Las Vegas Sun dot com or just

658
00:30:25,600 --> 00:30:28,440
Speaker 3: Las Vegas Sun dot com, edam Gwaiso Junior.

659
00:30:28,960 --> 00:30:34,880
Speaker 4: I am on uh Twitter and blue Sky the Foreign

660
00:30:35,000 --> 00:30:39,040
Speaker 4: Agent Registry of the shack up in I won't say

661
00:30:39,040 --> 00:30:44,080
Speaker 4: it for which country, we can guess. For my newsletter

662
00:30:44,360 --> 00:30:47,920
Speaker 4: it's uh the tech Bubble dot substack dot com. And

663
00:30:47,960 --> 00:30:50,920
Speaker 4: for my podcast this Machine Kills.

664
00:30:52,360 --> 00:30:54,840
Speaker 2: You can find me at Where's your Head dot at

665
00:30:54,880 --> 00:30:58,400
Speaker 2: for my newsletter and the podcast is called Better Offline.

666
00:30:59,240 --> 00:31:01,760
Speaker 2: And you're thinking this seems way too honest for it.

667
00:31:01,880 --> 00:31:04,240
Speaker 2: What's he gonna do to me next? And the answer

668
00:31:04,360 --> 00:31:07,000
Speaker 2: is nothing. This is a clean break. We're about to

669
00:31:07,040 --> 00:31:10,000
Speaker 2: go to some advertisements and you're gonna listen to them

670
00:31:10,040 --> 00:31:14,040
Speaker 2: intently or else you are committing crimes against me. And

671
00:31:14,080 --> 00:31:16,160
Speaker 2: I know you love the crimes you do on this show.

672
00:31:16,200 --> 00:31:18,720
Speaker 2: You love to fill up the reddit something that will

673
00:31:18,760 --> 00:31:22,720
Speaker 2: be called Exhibit A through Z and I regret the

674
00:31:22,840 --> 00:31:25,320
Speaker 2: crime jokes, but I'm not gonna stop them anyway. The

675
00:31:25,360 --> 00:31:28,920
Speaker 2: following ads very legitimate companies or podcasts. You're gonna listen

676
00:31:28,960 --> 00:31:31,880
Speaker 2: to them, download them, and I won't feel any pain

677
00:31:32,560 --> 00:31:46,320
Speaker 2: by their products. And we're back. So we have replaced

678
00:31:46,400 --> 00:31:51,680
Speaker 2: David Roth using science with gear Davis. You are here

679
00:31:51,720 --> 00:31:53,880
Speaker 2: from it could happen here. I am a cool Zone

680
00:31:53,920 --> 00:31:56,800
Speaker 2: Media product. We're colleagues. How are you doing.

681
00:31:57,080 --> 00:32:00,560
Speaker 5: I'm so tired. I've watched so many steps this week.

682
00:32:00,720 --> 00:32:03,360
Speaker 2: I feel like I have new energy. That's the problem.

683
00:32:03,360 --> 00:32:05,479
Speaker 2: I'm going into the last day with more energy than

684
00:32:05,520 --> 00:32:06,400
Speaker 2: I have when I arrived.

685
00:32:06,600 --> 00:32:09,120
Speaker 5: That's that's that's another Cees miracle.

686
00:32:09,520 --> 00:32:12,760
Speaker 2: It's it's beautiful. Kyle Shanad from the Las Vegas Sun

687
00:32:12,840 --> 00:32:17,280
Speaker 2: either and of course Edward and Guiso Junior. Hellow, that's

688
00:32:17,320 --> 00:32:22,560
Speaker 2: really bad. Yeah, Kyle, you were at the same panel.

689
00:32:22,760 --> 00:32:25,080
Speaker 2: Tell me about this panel.

690
00:32:25,760 --> 00:32:27,800
Speaker 5: So it was this panel done by a number of

691
00:32:27,880 --> 00:32:31,840
Speaker 5: tech companies. Adobe had a spokesperson there as well as

692
00:32:32,000 --> 00:32:36,840
Speaker 5: one of the DHS Science and Technology at representatives. It

693
00:32:36,880 --> 00:32:41,920
Speaker 5: was ostensibly about like deep fakes, AI generated like information

694
00:32:42,720 --> 00:32:46,640
Speaker 5: UH and disinformation and misinformation. And I've been to a

695
00:32:46,680 --> 00:32:48,920
Speaker 5: lot of these panels over the years. I went to

696
00:32:48,960 --> 00:32:51,560
Speaker 5: one last year at ce YES put on by Deloitte.

697
00:32:51,840 --> 00:32:54,800
Speaker 5: That was that was actually okay. And then I went

698
00:32:54,800 --> 00:32:58,760
Speaker 5: to a few at them at the r NC earlier last.

699
00:32:58,600 --> 00:33:01,320
Speaker 2: Year, and that's the Republican National Convention.

700
00:33:01,440 --> 00:33:04,800
Speaker 5: Correct, correct, So you know it's a good good, uh

701
00:33:05,000 --> 00:33:07,600
Speaker 5: good panel for journalists to go to speaking of speaking

702
00:33:07,640 --> 00:33:12,120
Speaker 5: of disinformation. But yeah, I I uh, this was on

703
00:33:12,240 --> 00:33:16,040
Speaker 5: Thursday that we were we we walked into the LVCC,

704
00:33:16,720 --> 00:33:20,040
Speaker 5: went to this panel and it was uh one one

705
00:33:20,040 --> 00:33:21,600
Speaker 5: person in front of me did fall asleep?

706
00:33:22,480 --> 00:33:23,680
Speaker 1: Yeah, I thought it was.

707
00:33:23,920 --> 00:33:24,960
Speaker 2: What was the panel about?

708
00:33:25,000 --> 00:33:28,160
Speaker 3: Also, it was about U misinformation, disinformation and deep fakes.

709
00:33:28,640 --> 00:33:28,720
Speaker 7: Uh.

710
00:33:28,840 --> 00:33:31,880
Speaker 3: And I think if you didn't know much about it,

711
00:33:31,880 --> 00:33:34,880
Speaker 3: it probably could be a little shuffle. But for I

712
00:33:34,920 --> 00:33:36,960
Speaker 3: think as audience, maybe not as much.

713
00:33:37,720 --> 00:33:39,320
Speaker 5: Yeah, yeah, I mean it was. It was talking about

714
00:33:39,360 --> 00:33:42,920
Speaker 5: you know, various various tools to identify, uh, like AI

715
00:33:43,040 --> 00:33:47,640
Speaker 5: generated or or or deep faked like information or or

716
00:33:47,680 --> 00:33:50,560
Speaker 5: you know like you know, pictures, videos, and you know

717
00:33:50,560 --> 00:33:52,680
Speaker 5: how a whole bunch of the previous like visual tactics.

718
00:33:52,760 --> 00:33:54,520
Speaker 5: Right a few years ago, it's pretty easy to spawn

719
00:33:54,560 --> 00:33:59,520
Speaker 5: a AI image. It's maybe slightly harder now. It depends

720
00:33:59,520 --> 00:34:01,920
Speaker 5: on the model. But how you know, how with with

721
00:34:01,920 --> 00:34:04,240
Speaker 5: with how fast that kind of that is developing, especially

722
00:34:04,240 --> 00:34:07,760
Speaker 5: for stills. It's it's it's going beyond like visual detection.

723
00:34:07,840 --> 00:34:10,879
Speaker 5: You have to actually create tools to detect this, and

724
00:34:11,000 --> 00:34:14,560
Speaker 5: those tools can also be prone to false positives and

725
00:34:14,920 --> 00:34:19,000
Speaker 5: false negatives. And so there's this another technology that a

726
00:34:19,000 --> 00:34:21,440
Speaker 5: whole bunch of companies like a Microsoft making a big

727
00:34:21,480 --> 00:34:23,520
Speaker 5: push for it as well as well as Adobe. It's

728
00:34:23,600 --> 00:34:26,719
Speaker 5: kind of like a build in systems for when you

729
00:34:26,760 --> 00:34:30,560
Speaker 5: generate AI content that that like clearly identifies it as

730
00:34:30,600 --> 00:34:34,359
Speaker 5: such in the metadata. And that that's something I heard

731
00:34:34,640 --> 00:34:36,520
Speaker 5: a lot about last year, and they talked about it here.

732
00:34:36,560 --> 00:34:37,800
Speaker 5: I think they called it providence.

733
00:34:38,480 --> 00:34:40,359
Speaker 1: Providence was the word of the day.

734
00:34:40,600 --> 00:34:42,560
Speaker 5: Yes, that was the That was the word that they

735
00:34:42,600 --> 00:34:45,680
Speaker 5: that they used was these uh, these providence systems as

736
00:34:45,719 --> 00:34:48,880
Speaker 5: opposed to like, uh detection systems, which is like you know,

737
00:34:49,000 --> 00:34:52,640
Speaker 5: like like post post post talk, you know, we we

738
00:34:52,640 --> 00:34:56,600
Speaker 5: will use we will use that against you know, AI

739
00:34:56,920 --> 00:35:00,359
Speaker 5: or suspected AI content. Uh that was you know, maybe

740
00:35:00,400 --> 00:35:02,680
Speaker 5: not generated with this built in information.

741
00:35:03,920 --> 00:35:04,160
Speaker 8: Yeah.

742
00:35:04,480 --> 00:35:09,799
Speaker 2: So how was the panel though? Was it useful? Like

743
00:35:10,200 --> 00:35:14,400
Speaker 2: did it make profound statements or was this more cslop.

744
00:35:13,760 --> 00:35:17,080
Speaker 3: I mean I wouldn't call it c yes slop because

745
00:35:17,080 --> 00:35:19,239
Speaker 3: there's the oh yeah, the ones where you just sit

746
00:35:19,280 --> 00:35:21,080
Speaker 3: there for half an hour and go like a, well

747
00:35:21,800 --> 00:35:25,359
Speaker 3: that was half an hour I could be doing something else. Yeah,

748
00:35:25,400 --> 00:35:28,920
Speaker 3: I mean it was good for you know, learning the basics.

749
00:35:29,000 --> 00:35:31,120
Speaker 3: And they talked about, you know how like you mentioned,

750
00:35:31,200 --> 00:35:33,280
Speaker 3: it was a lot easier to detect things a while ago.

751
00:35:33,960 --> 00:35:35,560
Speaker 3: One thing I wish they and this is not your

752
00:35:35,560 --> 00:35:37,120
Speaker 3: reallyid question, but one thing I wish they did talk

753
00:35:37,160 --> 00:35:41,840
Speaker 3: about was just how text based a lot of this

754
00:35:42,640 --> 00:35:47,640
Speaker 3: AI misinformation, Like it's a lot of the misinformation that

755
00:35:47,680 --> 00:35:48,520
Speaker 3: gets published.

756
00:35:48,560 --> 00:35:51,719
Speaker 1: I mean, if you go on X be everything.

757
00:35:51,400 --> 00:35:55,120
Speaker 2: App as I do for my Bankking of course.

758
00:35:56,000 --> 00:35:57,799
Speaker 3: I mean I I go into I can't even read

759
00:35:57,800 --> 00:35:59,719
Speaker 3: the comments anymore because I have to scroll through a

760
00:35:59,719 --> 00:36:01,759
Speaker 3: billion in blue checks, and so many of them are

761
00:36:01,840 --> 00:36:07,319
Speaker 3: just like uh, obviously AI generated based off analyzing the

762
00:36:07,320 --> 00:36:10,280
Speaker 3: image and then writing the most basic comment possible.

763
00:36:10,920 --> 00:36:13,480
Speaker 1: So I wish there was a little more focus on that, if.

764
00:36:13,120 --> 00:36:15,400
Speaker 5: You want to no, sure, I mean like that is

765
00:36:15,640 --> 00:36:17,680
Speaker 5: that is a massive section of it. And this is

766
00:36:17,719 --> 00:36:21,440
Speaker 5: something even I asked a question about at the Republican

767
00:36:21,480 --> 00:36:24,040
Speaker 5: National Convention at Microsoft panel being like you have all

768
00:36:24,040 --> 00:36:25,920
Speaker 5: these tools for like AI images, right, you know, images

769
00:36:25,960 --> 00:36:29,440
Speaker 5: of politicians and in debaucherous acts, you know, all all

770
00:36:29,440 --> 00:36:33,720
Speaker 5: these sorts of things. But they also advertised like AI's

771
00:36:33,719 --> 00:36:37,759
Speaker 5: ability to make specifically like like a specific like a

772
00:36:38,320 --> 00:36:43,200
Speaker 5: user uh user specific political like press releases basically like

773
00:36:43,400 --> 00:36:45,600
Speaker 5: like you know, like a campaign can send an email

774
00:36:45,840 --> 00:36:48,560
Speaker 5: like based on like a voter's profile that can be

775
00:36:48,640 --> 00:36:54,400
Speaker 5: tailored using AI to specific voters and like that what

776
00:36:54,960 --> 00:36:55,960
Speaker 5: could go wrong with that?

777
00:36:56,800 --> 00:36:59,680
Speaker 2: And also do you mean creating data to specifically push

778
00:36:59,760 --> 00:37:00,840
Speaker 2: vote in one direction?

779
00:37:00,920 --> 00:37:02,279
Speaker 5: Well yeah, yes, but like but you know, like you

780
00:37:03,239 --> 00:37:05,520
Speaker 5: if you're working for a campaign and you want to

781
00:37:05,520 --> 00:37:09,080
Speaker 5: target specific voters, you can analyze their social media presence,

782
00:37:09,120 --> 00:37:11,319
Speaker 5: you know, whatever kind of information about them is in

783
00:37:11,400 --> 00:37:14,040
Speaker 5: certain data seats that can be bought and and make

784
00:37:14,120 --> 00:37:17,600
Speaker 5: you know, an AI written press release specifically for them.

785
00:37:17,800 --> 00:37:19,520
Speaker 5: And this is something I also like asked questions about,

786
00:37:19,560 --> 00:37:22,759
Speaker 5: like you're talking about you know these like uh these

787
00:37:22,840 --> 00:37:27,120
Speaker 5: AI AI metadata watermarks for images, but what about for text?

788
00:37:27,239 --> 00:37:28,719
Speaker 5: Like how will I be able to know if an

789
00:37:28,760 --> 00:37:31,000
Speaker 5: email I'm getting from a politician was written by a

790
00:37:31,000 --> 00:37:34,120
Speaker 5: person or written by a robot They're like, well you can't.

791
00:37:34,960 --> 00:37:37,200
Speaker 5: We simply aren't gonna worry about that.

792
00:37:37,560 --> 00:37:41,480
Speaker 3: And like, I mean I walked up to y'all afterwards,

793
00:37:41,480 --> 00:37:43,200
Speaker 3: and I was like, I guess the lesson is that

794
00:37:43,239 --> 00:37:43,960
Speaker 3: we're all screwed.

795
00:37:44,120 --> 00:37:46,120
Speaker 1: Yeah, we all, we all are screwed. I mean that

796
00:37:46,200 --> 00:37:47,080
Speaker 1: was the main takeaway.

797
00:37:47,120 --> 00:37:50,320
Speaker 5: That was what the DHS was saying, which I was like, maybe,

798
00:37:50,320 --> 00:37:53,839
Speaker 5: oh god, that was the main takeaway I had.

799
00:37:53,920 --> 00:37:55,719
Speaker 3: Was everyone pretty much saying like this is going to

800
00:37:55,719 --> 00:37:58,480
Speaker 3: get worse, and it's an arms and like all the

801
00:37:58,520 --> 00:37:59,200
Speaker 3: stuff is an.

802
00:37:59,120 --> 00:38:01,680
Speaker 5: Arms and it is and like you know, they they

803
00:38:01,760 --> 00:38:04,279
Speaker 5: gestured towards you know, quote unquote bad guys or like

804
00:38:04,320 --> 00:38:08,040
Speaker 5: you know, foreign state actors specifically Iran, does you know

805
00:38:08,320 --> 00:38:11,960
Speaker 5: a lot of work on this? Russia? But and you know,

806
00:38:12,000 --> 00:38:14,200
Speaker 5: I think in some ways to focus on those two

807
00:38:14,600 --> 00:38:17,680
Speaker 5: might be kind of lifted as the new is the

808
00:38:17,680 --> 00:38:20,560
Speaker 5: new administration focuses more on China, but specifically for like

809
00:38:20,840 --> 00:38:25,200
Speaker 5: for like just disformation using AI tools. Iran and Russia.

810
00:38:25,239 --> 00:38:27,120
Speaker 5: Like the past year has been like the main players

811
00:38:27,200 --> 00:38:29,040
Speaker 5: targeting US voters.

812
00:38:29,719 --> 00:38:31,920
Speaker 2: It is so wild. We just have I'm this is

813
00:38:31,920 --> 00:38:34,520
Speaker 2: a real dumb guy statement. Do we just have other

814
00:38:34,560 --> 00:38:37,680
Speaker 2: countries who are just fucking with the US citizen tree

815
00:38:37,680 --> 00:38:39,719
Speaker 2: and it's just like a thing that happens.

816
00:38:39,760 --> 00:38:41,759
Speaker 5: Oh yeah, it's a huge it's like a it's a

817
00:38:42,000 --> 00:38:43,040
Speaker 5: it's a huge project.

818
00:38:43,080 --> 00:38:44,360
Speaker 2: Disidered an act of war.

819
00:38:45,920 --> 00:38:47,719
Speaker 5: Yeah, I mean it's it's it's an extension of like

820
00:38:47,760 --> 00:38:49,480
Speaker 5: Cold War stuff, right, like it's.

821
00:38:49,400 --> 00:38:51,520
Speaker 2: So we just have wars that are like not really

822
00:38:52,280 --> 00:38:55,319
Speaker 2: yeah yeah, yeah, pretty much. I mean, I mean, I'm

823
00:38:55,320 --> 00:38:59,400
Speaker 2: also describing how colonial Britain work by paying people not

824
00:38:59,440 --> 00:39:01,879
Speaker 2: to like teach people to write. So I realized I'm

825
00:39:01,920 --> 00:39:08,160
Speaker 2: like the Bill Belichick of But it's just very frustrating

826
00:39:08,400 --> 00:39:10,440
Speaker 2: to hear this stuff and not really know what to

827
00:39:10,600 --> 00:39:12,760
Speaker 2: do about it because it could happen here. Does amazing

828
00:39:12,760 --> 00:39:15,960
Speaker 2: welk on disinformation for something as like a person?

829
00:39:16,120 --> 00:39:20,400
Speaker 5: Okay no, but no, no, okay, you know, it is

830
00:39:20,400 --> 00:39:23,040
Speaker 5: a huge problem and there really isn't much to do

831
00:39:23,160 --> 00:39:26,600
Speaker 5: realistic like we have tried to make fact checking work

832
00:39:26,640 --> 00:39:29,120
Speaker 5: the past few years, and I don't think Americans are

833
00:39:29,200 --> 00:39:34,360
Speaker 5: that much better at identifying false or genuine information. Like

834
00:39:34,440 --> 00:39:37,200
Speaker 5: fact checking has kind of failed as a as like

835
00:39:37,239 --> 00:39:39,000
Speaker 5: a large as a large project.

836
00:39:39,680 --> 00:39:42,920
Speaker 2: I almost feel like what they actually need is vibe checkers.

837
00:39:43,719 --> 00:39:47,000
Speaker 2: I mean, they need someone, but it's why do I

838
00:39:47,080 --> 00:39:49,600
Speaker 2: feel bad looking at this? What I'm saying is everyone

839
00:39:49,600 --> 00:39:50,280
Speaker 2: needs therapy.

840
00:39:50,480 --> 00:39:54,000
Speaker 4: Jesus Christ, astrologers and estate.

841
00:39:54,480 --> 00:39:56,440
Speaker 5: State mandated therapy is the solution here.

842
00:39:56,640 --> 00:40:01,359
Speaker 2: Yeah, definitely a state mandated vibe checker. Is this real?

843
00:40:02,440 --> 00:40:06,399
Speaker 5: I would apply to be checker? What do you think

844
00:40:06,440 --> 00:40:09,200
Speaker 5: about this? It's not.

845
00:40:11,360 --> 00:40:11,520
Speaker 9: Big.

846
00:40:13,320 --> 00:40:15,399
Speaker 10: Don't read the end of Jiu Jitsu Kaise and it's

847
00:40:15,400 --> 00:40:19,360
Speaker 10: a very disappointing manga, very unfair. The end of Demons

848
00:40:19,400 --> 00:40:26,080
Speaker 10: LA have far better seven similar, terrible ending. It took

849
00:40:26,080 --> 00:40:27,920
Speaker 10: out the US superhero.

850
00:40:28,120 --> 00:40:30,759
Speaker 4: Joe's bizarre adventure is holding up?

851
00:40:31,400 --> 00:40:34,280
Speaker 5: It was normal. I didn't know. Look, think you were weaves.

852
00:40:34,320 --> 00:40:38,960
Speaker 5: That is interesting. I am I appreciate other cultures. Oh,

853
00:40:39,000 --> 00:40:39,879
Speaker 5: I don't give a ship.

854
00:40:39,960 --> 00:40:40,919
Speaker 2: I'm a huge weave.

855
00:40:41,120 --> 00:40:41,960
Speaker 5: Do you know what I'm wearing?

856
00:40:43,000 --> 00:40:45,319
Speaker 2: I was wondering if that was a reference. You look

857
00:40:45,400 --> 00:40:48,400
Speaker 2: like you might explain this one gap because I don't know.

858
00:40:48,840 --> 00:40:49,759
Speaker 5: I don't guess.

859
00:40:49,920 --> 00:40:53,000
Speaker 2: No, like Anti Anti was it that one?

860
00:40:53,320 --> 00:40:55,600
Speaker 1: No, there's no chainsaw man right, No?

861
00:40:55,600 --> 00:40:57,240
Speaker 5: No, Oh, I thought you were one of those agents.

862
00:40:57,360 --> 00:41:00,319
Speaker 2: It's one of the club ones or in high school, yes,

863
00:41:02,280 --> 00:41:05,640
Speaker 2: host club one yes, just to be clear, is the

864
00:41:05,640 --> 00:41:08,440
Speaker 2: best dressed of any of us and also fucking rocking

865
00:41:08,520 --> 00:41:12,759
Speaker 2: like an actual Manger related outfit and nailing it.

866
00:41:13,080 --> 00:41:14,799
Speaker 5: I spent a lot of money on this as you

867
00:41:14,800 --> 00:41:17,560
Speaker 5: should have looks great. I I I found. I found

868
00:41:17,600 --> 00:41:20,560
Speaker 5: a very nice blue blazer that I defaced by putting

869
00:41:20,600 --> 00:41:21,600
Speaker 5: on the orange patch.

870
00:41:23,480 --> 00:41:26,000
Speaker 4: This is good. This good. I've been admiring your fits.

871
00:41:26,040 --> 00:41:28,280
Speaker 4: I feel like back home. I'm usually I'm usually dressed

872
00:41:28,520 --> 00:41:30,439
Speaker 4: the best dress and dressed best.

873
00:41:32,320 --> 00:41:33,520
Speaker 5: Your pants are fantastic.

874
00:41:33,600 --> 00:41:34,279
Speaker 4: I appreciate it.

875
00:41:34,320 --> 00:41:36,719
Speaker 2: I appreciate it, but no one's saying anything about me.

876
00:41:38,200 --> 00:41:41,560
Speaker 4: Good personally. I think you should have gone with the

877
00:41:41,600 --> 00:41:42,520
Speaker 4: aviator shades.

878
00:41:42,640 --> 00:41:48,480
Speaker 5: I think you should have gone with the shade I

879
00:41:48,480 --> 00:41:52,879
Speaker 5: would love. But I was talking about this with with

880
00:41:52,920 --> 00:41:55,640
Speaker 5: my boss Robert Evans last night. We should bring the

881
00:41:55,680 --> 00:41:58,120
Speaker 5: men's wear a guy here one year. I have him

882
00:41:58,200 --> 00:41:59,200
Speaker 5: walk around.

883
00:41:58,880 --> 00:42:06,560
Speaker 2: Ceyes, you have anticipated. He's also not cheap, No, he

884
00:42:06,680 --> 00:42:07,200
Speaker 2: wants no.

885
00:42:07,840 --> 00:42:09,760
Speaker 5: Derek guy is legend.

886
00:42:09,840 --> 00:42:12,080
Speaker 2: I love him, and he also knows what he's worth

887
00:42:12,160 --> 00:42:14,840
Speaker 2: and should he should It's a pro labor podcast.

888
00:42:14,920 --> 00:42:18,319
Speaker 5: Is that his name Derek Derek, which is so fucking.

889
00:42:18,040 --> 00:42:20,600
Speaker 2: Funny to be like the menswear guy, and your second

890
00:42:20,680 --> 00:42:21,640
Speaker 2: name is guy.

891
00:42:21,920 --> 00:42:26,120
Speaker 5: Very very cool. I would I would love for him

892
00:42:26,120 --> 00:42:29,359
Speaker 5: to walk around the show floor. I think it could

893
00:42:29,360 --> 00:42:30,440
Speaker 5: do some real psychicama.

894
00:42:30,800 --> 00:42:32,879
Speaker 4: It doesn't rate my fing. I never want him to

895
00:42:33,120 --> 00:42:34,920
Speaker 4: put his I have so on on me.

896
00:42:36,520 --> 00:42:40,279
Speaker 2: I say this with my not quite parasocial but here's

897
00:42:40,320 --> 00:42:42,600
Speaker 2: my Derek Guy's story. So I lost a lot of

898
00:42:42,600 --> 00:42:45,160
Speaker 2: weight this year. And this is not a me trying

899
00:42:45,160 --> 00:42:47,839
Speaker 2: to actually conjure up people saying anything. I'm fine. What

900
00:42:47,880 --> 00:42:50,080
Speaker 2: I'm saying is I lost all the weight and I

901
00:42:50,080 --> 00:42:51,960
Speaker 2: bought a bunch of clothes and I took a picture

902
00:42:52,000 --> 00:42:54,880
Speaker 2: and I'm like, I still feel like shit. So I

903
00:42:55,000 --> 00:42:58,400
Speaker 2: emailed Derek Guy, as one normally does in tears, and

904
00:42:58,440 --> 00:43:00,919
Speaker 2: I was like, why do I feel bad still? Because

905
00:43:00,960 --> 00:43:02,760
Speaker 2: I was like, you know what, if he doesn't respond,

906
00:43:02,760 --> 00:43:05,359
Speaker 2: he doesn't respond, but if he does, he can help

907
00:43:05,440 --> 00:43:07,400
Speaker 2: me deal with something like an emotional thing where I'm like,

908
00:43:07,440 --> 00:43:09,319
Speaker 2: I feel better about my body, but I don't like

909
00:43:09,320 --> 00:43:10,840
Speaker 2: what's on it. And he was like, you have no

910
00:43:10,960 --> 00:43:13,600
Speaker 2: aesthetic and he explained the concept of aesthetics. One of you.

911
00:43:13,640 --> 00:43:17,480
Speaker 4: Responded, yeah, there, he's like the chump ski fashion.

912
00:43:21,520 --> 00:43:21,839
Speaker 5: For the.

913
00:43:23,400 --> 00:43:26,440
Speaker 2: He's still responding, well, this is kind of what I

914
00:43:26,480 --> 00:43:29,719
Speaker 2: was addressing with Gare, which is he isn't there to

915
00:43:29,840 --> 00:43:32,759
Speaker 2: eighty six people. He's there to try and explain what

916
00:43:32,800 --> 00:43:34,920
Speaker 2: looks and feels good. And he talks about clothing his

917
00:43:34,960 --> 00:43:37,200
Speaker 2: social language. And he said, you have no aesthetic. You're

918
00:43:37,200 --> 00:43:41,480
Speaker 2: wearing like trainers with like a threadbelt. My shit was busted.

919
00:43:41,480 --> 00:43:44,040
Speaker 2: I look terrible because of the clothes, not because of me.

920
00:43:45,080 --> 00:43:48,720
Speaker 2: I would actually love him to do that, but also

921
00:43:48,920 --> 00:43:52,280
Speaker 2: walk around being like, this ship looks fucking good because

922
00:43:52,280 --> 00:43:55,680
Speaker 2: I feel like and with this show, especially if you're

923
00:43:55,840 --> 00:43:59,840
Speaker 2: just a hater, were loving nothing, you're just vacuous.

924
00:44:00,280 --> 00:44:05,440
Speaker 5: Occasionally you see a very well dressed Asian businessman fucking rocks,

925
00:44:05,480 --> 00:44:07,800
Speaker 5: and then you see a lot of a lot of Asian,

926
00:44:08,280 --> 00:44:10,720
Speaker 5: a lot of Asian businessmen in very ill fitting suits.

927
00:44:10,719 --> 00:44:13,560
Speaker 5: But occasionally you'll see one guy who has that ship on.

928
00:44:14,040 --> 00:44:16,160
Speaker 4: Yes, I did see someone who had that ship on

929
00:44:16,239 --> 00:44:18,759
Speaker 4: and they were like looking at other people's fits. Would

930
00:44:18,800 --> 00:44:20,080
Speaker 4: discuss That's.

931
00:44:20,560 --> 00:44:23,840
Speaker 2: What I've been doing all week, baby fashion ped.

932
00:44:24,840 --> 00:44:26,640
Speaker 4: I really I should have gone up to him and

933
00:44:26,680 --> 00:44:27,279
Speaker 4: talked to him.

934
00:44:27,440 --> 00:44:32,560
Speaker 2: Yeah, you have notes about the convention, rapp, Why this

935
00:44:32,600 --> 00:44:35,400
Speaker 2: is my actual job. Okay, yeah, I forgot why we

936
00:44:35,520 --> 00:44:40,000
Speaker 2: have we just you know, yeah, at the YAP index

937
00:44:40,280 --> 00:44:44,040
Speaker 2: is over five thousand right now, Japanese, can please bring

938
00:44:44,120 --> 00:44:45,719
Speaker 2: us back to why we're actually well?

939
00:44:45,800 --> 00:44:48,680
Speaker 5: So, I guess one thing I was spending almost all

940
00:44:48,680 --> 00:44:52,520
Speaker 5: of yesterday doing, as we've been intundated with these AI products,

941
00:44:52,960 --> 00:44:55,920
Speaker 5: is is learning about all of the AI products targeting

942
00:44:55,920 --> 00:45:00,400
Speaker 5: your offspring, your kids who are being raised now with

943
00:45:00,480 --> 00:45:03,240
Speaker 5: AI the same way my generation was raised with social media.

944
00:45:03,400 --> 00:45:04,280
Speaker 2: Nice son of mine.

945
00:45:04,520 --> 00:45:06,719
Speaker 4: This is like cocoa melon ship where it's like put

946
00:45:06,760 --> 00:45:08,520
Speaker 4: this in front of your kid, or it's like the vice,

947
00:45:08,719 --> 00:45:11,240
Speaker 4: like consumer products for the anxious parent.

948
00:45:11,880 --> 00:45:14,000
Speaker 5: You know, both these things kind of these these things

949
00:45:14,080 --> 00:45:17,360
Speaker 5: canna kind of overlap. The first thing I did yesterday

950
00:45:17,400 --> 00:45:21,239
Speaker 5: morning was a TENDED panel called Raising AI Kids Responsibly.

951
00:45:21,760 --> 00:45:25,319
Speaker 5: Great title because this could either mean you're making an

952
00:45:25,320 --> 00:45:28,880
Speaker 5: AI child that you get to raise, or it's about

953
00:45:28,880 --> 00:45:30,880
Speaker 5: how do you raise kids in the world at AI?

954
00:45:31,080 --> 00:45:33,480
Speaker 5: And now it was the latter. I kind of wanted

955
00:45:33,480 --> 00:45:34,000
Speaker 5: the former.

956
00:45:34,719 --> 00:45:36,920
Speaker 2: I hate all of it.

957
00:45:36,920 --> 00:45:40,200
Speaker 5: It was bad, Uh it was. It was in some

958
00:45:40,239 --> 00:45:42,440
Speaker 5: ways it was bad and you know, a little bit cringe.

959
00:45:43,000 --> 00:45:45,399
Speaker 5: But there's also some interesting you know stuff set here.

960
00:45:46,000 --> 00:45:48,520
Speaker 5: There was two products that were that were displayed. One

961
00:45:48,520 --> 00:45:52,080
Speaker 5: of them was from this company called ready Land, I

962
00:45:52,080 --> 00:45:55,640
Speaker 5: believe partners with Amazon. It's basically like it's an AI

963
00:45:55,760 --> 00:45:59,359
Speaker 5: story book that interacts with an Alexa machine. Now, one

964
00:45:59,360 --> 00:46:01,680
Speaker 5: thing about them that I think is actually really good.

965
00:46:02,600 --> 00:46:05,720
Speaker 5: They don't they don't generate any new AI content. It's

966
00:46:05,760 --> 00:46:08,640
Speaker 5: just using AI to stitch together basically kind of a

967
00:46:08,719 --> 00:46:11,680
Speaker 5: choose your own adventure book, but for kids to to

968
00:46:11,760 --> 00:46:14,440
Speaker 5: have like a physical book that they read with with

969
00:46:14,520 --> 00:46:16,880
Speaker 5: the Alexa machine that then can make them like toxic

970
00:46:17,120 --> 00:46:19,759
Speaker 5: characters change the story in different directions. But all the

971
00:46:19,800 --> 00:46:22,120
Speaker 5: content is pre baked. It just it just gets it

972
00:46:22,160 --> 00:46:23,520
Speaker 5: just gets assembled in different ways.

973
00:46:23,560 --> 00:46:24,240
Speaker 2: Just one idea.

974
00:46:25,160 --> 00:46:27,839
Speaker 7: As the father of a son, the son of a mother,

975
00:46:28,280 --> 00:46:32,799
Speaker 7: a brother of a sister, you can do this thing

976
00:46:33,360 --> 00:46:35,600
Speaker 7: when you're reading to your child where you can think

977
00:46:35,640 --> 00:46:36,279
Speaker 7: of something else.

978
00:46:36,320 --> 00:46:39,560
Speaker 5: I understand, And this is what my parents did to

979
00:46:39,600 --> 00:46:42,160
Speaker 5: me and macination. This is what I was thinking about.

980
00:46:42,400 --> 00:46:43,880
Speaker 5: Like in the panel, I'm like, yes, this is this

981
00:46:43,960 --> 00:46:45,600
Speaker 5: is cool. You know, it's safer than a whole bunch

982
00:46:45,600 --> 00:46:48,680
Speaker 5: of the other other stuff I'm seeing. But how this

983
00:46:48,760 --> 00:46:56,120
Speaker 5: kind of steals away the joy of reading to your kids.

984
00:46:56,120 --> 00:46:58,520
Speaker 4: When my little brother is growing up, you just don't

985
00:46:58,600 --> 00:47:00,680
Speaker 4: realize how bad shit child is.

986
00:47:01,760 --> 00:47:04,480
Speaker 2: So I avoid talking about my son in general. I

987
00:47:04,480 --> 00:47:06,520
Speaker 2: won't name him because I believe he should have his

988
00:47:06,560 --> 00:47:11,400
Speaker 2: own destiny. But one of the most wonderful parts of

989
00:47:11,440 --> 00:47:14,520
Speaker 2: being a father is having my son come and talk

990
00:47:14,600 --> 00:47:16,920
Speaker 2: to me about something he just thought up, and it

991
00:47:16,960 --> 00:47:19,920
Speaker 2: will be something Minecraft related, and he will explain something

992
00:47:19,920 --> 00:47:23,480
Speaker 2: I did not know about Minecraft, and you will, like,

993
00:47:24,760 --> 00:47:27,359
Speaker 2: he will explain something in such detail that I've never

994
00:47:27,440 --> 00:47:30,040
Speaker 2: even considered in my life, and it's something quite simple.

995
00:47:30,680 --> 00:47:32,680
Speaker 2: But it's because he's been allowed to go off in

996
00:47:32,760 --> 00:47:35,280
Speaker 2: these directions with no prompting, with no.

997
00:47:35,920 --> 00:47:39,160
Speaker 5: Yeah, no totally, I mean my bit, Yeah, it's beautiful.

998
00:47:39,320 --> 00:47:42,440
Speaker 2: Yeah, And it's like the idea of depriving children of

999
00:47:42,520 --> 00:47:43,359
Speaker 2: this makes me so.

1000
00:47:43,520 --> 00:47:45,960
Speaker 5: Fucking actually, especially when it's targeting like five year olds,

1001
00:47:46,000 --> 00:47:48,279
Speaker 5: which is like where it gets more upsetting to me.

1002
00:47:49,280 --> 00:47:53,160
Speaker 2: And taking the fucking parenting thing of having an imagination

1003
00:47:53,239 --> 00:47:56,840
Speaker 2: about what your child could be is so fucking sickening.

1004
00:47:56,840 --> 00:47:59,960
Speaker 5: I'm getting angry this is now. Unfortunately, like I actually

1005
00:48:00,080 --> 00:48:03,839
Speaker 5: felt relatively better about this product. So it's basically kind

1006
00:48:03,840 --> 00:48:05,440
Speaker 5: of just like it's kind of it's kind of just

1007
00:48:05,480 --> 00:48:07,320
Speaker 5: a visual It's kind of it's kind of just like

1008
00:48:07,360 --> 00:48:10,400
Speaker 5: a visual novel, you know, like like those uh like

1009
00:48:10,400 --> 00:48:12,120
Speaker 5: those visual novel games. But you have much you have

1010
00:48:12,200 --> 00:48:15,080
Speaker 5: physical books you're reading now. Compared to the other product

1011
00:48:15,360 --> 00:48:19,640
Speaker 5: called Poe the AI Teddy Bear, which I also saw,

1012
00:48:22,200 --> 00:48:23,920
Speaker 5: so much worse is it? It is what it sounds like.

1013
00:48:24,000 --> 00:48:25,879
Speaker 5: It's a teddy bear that comes with an app where

1014
00:48:25,880 --> 00:48:28,040
Speaker 5: you can put in certain like parameters for like I

1015
00:48:28,080 --> 00:48:31,040
Speaker 5: want the story starring this character with this archetype of

1016
00:48:31,040 --> 00:48:34,400
Speaker 5: civillain in this setting, and it'll generate an AI story

1017
00:48:34,520 --> 00:48:38,760
Speaker 5: for your child, generating new content. So unlike unlike story

1018
00:48:38,880 --> 00:48:43,680
Speaker 5: Land or unlike unlike ready Land, Poe the AI Bear

1019
00:48:43,760 --> 00:48:48,200
Speaker 5: is actually is actually generating live content, unreviewed by unreviewed

1020
00:48:48,239 --> 00:48:50,840
Speaker 5: by moderator. It's just straight to your child. It's fifty

1021
00:48:50,880 --> 00:48:53,279
Speaker 5: dollars on Amazon. You can order this thing right now

1022
00:48:53,280 --> 00:48:53,920
Speaker 5: and talk to it.

1023
00:48:54,719 --> 00:48:58,239
Speaker 2: He putting my tongue in my cheek. When did I

1024
00:48:58,280 --> 00:48:59,520
Speaker 2: do when I'm pissed off about?

1025
00:48:59,600 --> 00:49:04,279
Speaker 5: Side is gonna hang out? You're low key tweaking right,

1026
00:49:05,680 --> 00:49:12,279
Speaker 5: I'm like names places he did talk about. He's like,

1027
00:49:12,320 --> 00:49:16,360
Speaker 5: you know, like chat GPT does does have guardrails for content.

1028
00:49:16,480 --> 00:49:21,279
Speaker 5: But but those guardrails you know, don't always reliably work,

1029
00:49:21,480 --> 00:49:24,600
Speaker 5: but they're better than nothing, and and and content moderation

1030
00:49:24,880 --> 00:49:27,160
Speaker 5: is an issue that we're working on. I'm like, yeah,

1031
00:49:27,200 --> 00:49:31,360
Speaker 5: but your product is hit the market like you are selling, we're.

1032
00:49:31,160 --> 00:49:32,840
Speaker 1: Working on moderation. Isn't a great answer?

1033
00:49:33,000 --> 00:49:36,319
Speaker 5: No, not a good answer. And this is something like

1034
00:49:36,400 --> 00:49:39,439
Speaker 5: even even the other guy with like the AI storybook mentioned,

1035
00:49:39,480 --> 00:49:41,560
Speaker 5: He's like, it's pretty easy to make like your AI

1036
00:49:41,920 --> 00:49:45,799
Speaker 5: kids toy not say swear words or even even even

1037
00:49:45,920 --> 00:49:48,080
Speaker 5: like you talk about like sex or drugs. But one

1038
00:49:48,120 --> 00:49:50,000
Speaker 5: thing that's even harder to moderate. It's like what if

1039
00:49:50,040 --> 00:49:53,200
Speaker 5: it's what if it says like inaccurate or or actually

1040
00:49:53,239 --> 00:49:55,799
Speaker 5: like like like a like dangerous information, you know, like

1041
00:49:55,880 --> 00:49:57,520
Speaker 5: what if it's what if it goes in a really

1042
00:49:57,520 --> 00:49:59,920
Speaker 5: weird direction and starts like and starts like talking about

1043
00:49:59,560 --> 00:50:03,560
Speaker 5: he son so that generally exactly general exactly models.

1044
00:50:03,600 --> 00:50:06,680
Speaker 2: They don't even understand how the training data truly interacts

1045
00:50:06,719 --> 00:50:09,520
Speaker 2: with the system totally, they don't know how this shit

1046
00:50:09,719 --> 00:50:13,680
Speaker 2: truly works. The only useful thing in quantum computing related

1047
00:50:13,719 --> 00:50:15,400
Speaker 2: to AI right now is the fact that they can

1048
00:50:15,440 --> 00:50:18,839
Speaker 2: actually have models that can discern what the training data does.

1049
00:50:19,200 --> 00:50:22,960
Speaker 2: So the idea of my child interacting with all of

1050
00:50:23,000 --> 00:50:26,960
Speaker 2: these I realize now like nothing actually makes me angry

1051
00:50:27,000 --> 00:50:29,880
Speaker 2: other than harms to my child, at which point I

1052
00:50:30,000 --> 00:50:32,200
Speaker 2: might actually go falling down mode.

1053
00:50:32,800 --> 00:50:34,239
Speaker 5: So it's such a good movie too.

1054
00:50:34,320 --> 00:50:35,239
Speaker 2: It's such a great movie.

1055
00:50:35,280 --> 00:50:36,759
Speaker 5: That's a good movie.

1056
00:50:37,320 --> 00:50:37,560
Speaker 4: Now.

1057
00:50:38,040 --> 00:50:39,680
Speaker 5: The other the last part of the last thing about

1058
00:50:39,680 --> 00:50:41,839
Speaker 5: this panel is that it was it actually opened with

1059
00:50:41,880 --> 00:50:47,799
Speaker 5: this person from the company Ido Ido Play Lab Partnerships,

1060
00:50:47,960 --> 00:50:50,560
Speaker 5: who was the first company to partner with Sesame Workshop

1061
00:50:50,640 --> 00:50:52,400
Speaker 5: to make to make apps for kids. So I'm like,

1062
00:50:52,520 --> 00:50:55,400
Speaker 5: this is interesting, Like Sesmei Workshop usually I consider I

1063
00:50:55,440 --> 00:50:58,560
Speaker 5: consider being like pretty pretty thoughtful in how they produce

1064
00:50:58,840 --> 00:51:01,000
Speaker 5: media for kids, and like, if they're choosing to partner

1065
00:51:01,040 --> 00:51:02,960
Speaker 5: with this company, maybe I'll listen to what they say.

1066
00:51:03,040 --> 00:51:05,799
Speaker 5: And they didn't have anything to sell. They just had

1067
00:51:05,880 --> 00:51:09,360
Speaker 5: data that they've been collecting on how gen Z thinks

1068
00:51:09,360 --> 00:51:12,720
Speaker 5: about AI. This thing's becoming increasingly invasive in our lives,

1069
00:51:12,760 --> 00:51:15,080
Speaker 5: Like how do we think about it and what do

1070
00:51:15,120 --> 00:51:17,920
Speaker 5: we really want out of it? And some of the

1071
00:51:17,920 --> 00:51:20,360
Speaker 5: way this lady presented stuff was a little bit odd.

1072
00:51:20,360 --> 00:51:21,919
Speaker 5: She kind of presented all of all of the data

1073
00:51:21,960 --> 00:51:24,880
Speaker 5: findings as like shocking surprises, which I think may have

1074
00:51:24,880 --> 00:51:26,440
Speaker 5: been tailored for the CEES audience.

1075
00:51:26,640 --> 00:51:30,280
Speaker 2: Sure, so I feel like more attention to the details

1076
00:51:30,360 --> 00:51:30,959
Speaker 2: isn't bad.

1077
00:51:31,280 --> 00:51:34,360
Speaker 5: Sure, and like this is this is what she said

1078
00:51:34,440 --> 00:51:37,719
Speaker 5: her uh, her data like showed and and you can

1079
00:51:37,800 --> 00:51:39,120
Speaker 5: you can look you can look this stuff up on

1080
00:51:39,160 --> 00:51:42,520
Speaker 5: their website. The main question she asked is what if

1081
00:51:42,640 --> 00:51:47,279
Speaker 5: the tech savvy generation gen Z isn't buying what we're

1082
00:51:47,320 --> 00:51:48,160
Speaker 5: selling anymore?

1083
00:51:48,680 --> 00:51:51,919
Speaker 2: Fucking hell, imagine the customer does the thing you're building.

1084
00:51:52,080 --> 00:51:54,240
Speaker 5: Uh, she said, Like, you know, gen Z is typically

1085
00:51:54,280 --> 00:51:57,359
Speaker 5: seen as early as like early adopters, early users, and

1086
00:51:57,520 --> 00:52:00,200
Speaker 5: they usually are, but they also come with the most

1087
00:52:00,239 --> 00:52:03,440
Speaker 5: amount of informed opinions about how badly the tech feels,

1088
00:52:03,480 --> 00:52:06,040
Speaker 5: how cringing it is to use, and how it affects

1089
00:52:06,080 --> 00:52:07,160
Speaker 5: their sense of humanity.

1090
00:52:07,239 --> 00:52:08,719
Speaker 1: So so the issue is that they know what's up.

1091
00:52:09,040 --> 00:52:11,920
Speaker 5: They know what's up, which was you know, if you're

1092
00:52:11,960 --> 00:52:14,920
Speaker 5: in businesses is like as either a hurdle to overcome

1093
00:52:16,200 --> 00:52:18,600
Speaker 5: or some insights to help you, you know, maybe maybe

1094
00:52:18,640 --> 00:52:22,239
Speaker 5: pivot or change in a completely different direction. She identified

1095
00:52:22,320 --> 00:52:24,839
Speaker 5: like the key areas of tension around AI for gen

1096
00:52:24,960 --> 00:52:27,200
Speaker 5: Z is one creative expression.

1097
00:52:27,640 --> 00:52:27,759
Speaker 2: Uh.

1098
00:52:27,800 --> 00:52:30,319
Speaker 5: You know, it's its ability to you know, have us

1099
00:52:30,480 --> 00:52:33,640
Speaker 5: feel proud of the art that we make and how

1100
00:52:33,719 --> 00:52:36,440
Speaker 5: it affects human relationships. And she she brought up a

1101
00:52:36,440 --> 00:52:39,920
Speaker 5: few questions or like examples of of the types of

1102
00:52:39,920 --> 00:52:43,279
Speaker 5: stuff that she's that she's like you know, asking asking people, uh,

1103
00:52:43,560 --> 00:52:46,359
Speaker 5: as a part of this data collections, Like let's say

1104
00:52:46,360 --> 00:52:48,600
Speaker 5: you've let's say let's say you've had a friend breakup?

1105
00:52:49,360 --> 00:52:52,520
Speaker 5: Would you rather an AI tool kind of like like

1106
00:52:52,520 --> 00:52:55,680
Speaker 5: like counsel you through that process, you know, like like

1107
00:52:55,719 --> 00:52:58,399
Speaker 5: you know, like bounce ideas off and try to try

1108
00:52:58,440 --> 00:53:00,680
Speaker 5: to like move on or figure out like what happened?

1109
00:53:01,640 --> 00:53:04,719
Speaker 5: Or do you want like a temporary friend replacement? Do

1110
00:53:05,040 --> 00:53:07,360
Speaker 5: you want the AI to become a friend for you instead?

1111
00:53:07,520 --> 00:53:10,000
Speaker 5: Would you rather would you rather that be your friend

1112
00:53:10,280 --> 00:53:13,520
Speaker 5: for the time being? And like no, we we actually

1113
00:53:13,560 --> 00:53:16,279
Speaker 5: don't want AI friends. That's that's not what we want.

1114
00:53:16,400 --> 00:53:18,080
Speaker 5: Which is a lot of stuff at Yes, this year,

1115
00:53:18,080 --> 00:53:21,680
Speaker 5: it feels so much of AI this year is like

1116
00:53:21,760 --> 00:53:25,880
Speaker 5: it is like about replacing human friendship, so to preserve

1117
00:53:26,160 --> 00:53:27,000
Speaker 5: human friendship.

1118
00:53:27,080 --> 00:53:30,319
Speaker 2: Right, Sorry, it's fucked up because the idea of tech

1119
00:53:30,360 --> 00:53:32,640
Speaker 2: at least ten years ago was they would bring us

1120
00:53:32,680 --> 00:53:39,239
Speaker 2: closer together and would allow for deeper connections. Now it's like, buddy, like,

1121
00:53:39,480 --> 00:53:42,360
Speaker 2: yeah about that, you want to connect with the computer.

1122
00:53:42,920 --> 00:53:44,920
Speaker 4: I mean, this is what happens when I mean all

1123
00:53:44,920 --> 00:53:47,080
Speaker 4: these you know, this is what happens when everyone starts

1124
00:53:47,080 --> 00:53:48,920
Speaker 4: reading Marcus Aurelius a little too closely.

1125
00:53:49,280 --> 00:53:53,840
Speaker 2: So true, I don't know that reference. I am an idiot.

1126
00:53:53,920 --> 00:53:58,400
Speaker 2: People need to stop quoting books to me.

1127
00:53:59,640 --> 00:54:01,720
Speaker 4: I think that you don't know.

1128
00:54:04,719 --> 00:54:09,640
Speaker 2: Yes, yes, ed, Yes, Actually, Russell Croche will say that

1129
00:54:09,840 --> 00:54:11,960
Speaker 2: one of the funniest things on Twitter, which is he

1130
00:54:12,040 --> 00:54:16,000
Speaker 2: responded to one of the CNN reports I believe at

1131
00:54:16,000 --> 00:54:18,520
Speaker 2: the time and he was just like blocked blogger, which

1132
00:54:18,560 --> 00:54:20,520
Speaker 2: is one of the funniest things to say. Anyway, let's

1133
00:54:20,719 --> 00:54:22,960
Speaker 2: just ignore my forty.

1134
00:54:23,280 --> 00:54:25,480
Speaker 5: But this was the same thing that she was talking about.

1135
00:54:25,520 --> 00:54:27,799
Speaker 5: It is like, you know this thing where that what

1136
00:54:27,840 --> 00:54:30,719
Speaker 5: we're all seeing is like these air products designed to

1137
00:54:30,840 --> 00:54:35,279
Speaker 5: replace the role of human friendship. And another thing she

1138
00:54:35,280 --> 00:54:38,799
Speaker 5: presented as like this like surprising the problem of meeting people. No, no,

1139
00:54:38,840 --> 00:54:42,120
Speaker 5: it's it's it's it's it's it's actually helping you like

1140
00:54:42,320 --> 00:54:44,799
Speaker 5: overcome the fact that you like lost a friend. It's

1141
00:54:44,800 --> 00:54:46,480
Speaker 5: trying to be like, hey, it's okay. If you lost

1142
00:54:46,480 --> 00:54:51,080
Speaker 5: a friend, this AI can be your friend instead. Yeah, yes, I.

1143
00:54:50,960 --> 00:54:54,239
Speaker 3: Mean the solution to like this loneliness epidemic, especially young

1144
00:54:54,280 --> 00:54:57,200
Speaker 3: people are going through. I can't imagine is more robots,

1145
00:54:57,360 --> 00:54:57,560
Speaker 3: you know.

1146
00:54:57,719 --> 00:55:01,719
Speaker 5: And yeah, one thing I keep thinking that's driving alienation.

1147
00:55:01,920 --> 00:55:04,600
Speaker 4: One of these guys who did who does? Like these

1148
00:55:04,600 --> 00:55:09,719
Speaker 4: companion bought chat bought sites. I think character AI, you're like, oh, okay, well,

1149
00:55:09,719 --> 00:55:12,680
Speaker 4: you know, you seem in interviews to be earnest about

1150
00:55:12,680 --> 00:55:15,480
Speaker 4: like people are lonely. Maybe we can't replace, but we

1151
00:55:15,520 --> 00:55:17,880
Speaker 4: can offer a salve that helps people get back to

1152
00:55:17,920 --> 00:55:20,640
Speaker 4: the point where they have human friendships. Again, what does

1153
00:55:20,680 --> 00:55:23,560
Speaker 4: he believe about people? And it's just like let's hang

1154
00:55:23,640 --> 00:55:27,040
Speaker 4: homeless people and you know, let's murder the poor like

1155
00:55:27,080 --> 00:55:29,880
Speaker 4: these like this sort of it's not a coincidence that

1156
00:55:30,000 --> 00:55:33,320
Speaker 4: someone building that sort of firm has such deeply pathology.

1157
00:55:33,440 --> 00:55:34,279
Speaker 4: It's so such the.

1158
00:55:34,320 --> 00:55:37,120
Speaker 2: Top as well, because the idea of an AI you

1159
00:55:37,120 --> 00:55:40,840
Speaker 2: can bounce ideas off of, is not inherently a rib idea.

1160
00:55:40,960 --> 00:55:43,240
Speaker 2: We sit there, we think about shit, and the idea

1161
00:55:43,280 --> 00:55:45,879
Speaker 2: of having a log of it. I general a great

1162
00:55:45,920 --> 00:55:48,440
Speaker 2: deal and I think many people listening to this, dude,

1163
00:55:48,480 --> 00:55:50,880
Speaker 2: there's an idea of looking at this, but are like, yeah,

1164
00:55:51,080 --> 00:55:53,759
Speaker 2: what if your journal was a person.

1165
00:55:53,800 --> 00:55:55,319
Speaker 5: Can help it gets worse?

1166
00:55:55,480 --> 00:55:56,560
Speaker 1: Oh yeah.

1167
00:55:56,640 --> 00:55:58,680
Speaker 5: The next thing that choose as an example is like,

1168
00:55:59,040 --> 00:56:01,960
Speaker 5: what if there's an AI that's trained on your preferences

1169
00:56:02,000 --> 00:56:04,799
Speaker 5: to train on your dating preferences what you like aesthetically

1170
00:56:05,239 --> 00:56:08,200
Speaker 5: and what if that could instead go on your first

1171
00:56:08,239 --> 00:56:11,160
Speaker 5: dates for you? What what? What if?

1172
00:56:12,600 --> 00:56:14,120
Speaker 1: What if this is literally a black mirrors?

1173
00:56:14,360 --> 00:56:17,440
Speaker 5: What what if this could like handle like icebreaker questions

1174
00:56:17,480 --> 00:56:21,000
Speaker 5: and like and like get over like hard life experiences

1175
00:56:20,800 --> 00:56:21,440
Speaker 5: easier for you.

1176
00:56:21,800 --> 00:56:25,839
Speaker 4: One of my favorite little perverse things was there once

1177
00:56:25,880 --> 00:56:28,200
Speaker 4: said one time said he doesn't like sex. What he

1178
00:56:28,239 --> 00:56:32,040
Speaker 4: would like he's just a Slovenian philosopher psychoanalytics.

1179
00:56:32,120 --> 00:56:36,000
Speaker 1: That's a lot he's you know, he means, yeah, yeah, exactly.

1180
00:56:36,480 --> 00:56:38,840
Speaker 4: And he was talking about how the ideal sexual encounter

1181
00:56:38,880 --> 00:56:42,239
Speaker 4: for him is two people taking their sex toys and

1182
00:56:42,280 --> 00:56:44,000
Speaker 4: those sex toys playing with each other.

1183
00:56:44,000 --> 00:56:47,560
Speaker 5: Exactly, and this is this is exactly what that's disgusting,

1184
00:56:47,719 --> 00:56:49,200
Speaker 5: and the ideal, the.

1185
00:56:50,760 --> 00:56:53,920
Speaker 2: Ideal perversion, the pure perversion of that is two people

1186
00:56:54,120 --> 00:56:56,560
Speaker 2: using those sex toys together to get each other off.

1187
00:56:56,640 --> 00:56:58,680
Speaker 5: No, that's great, that's wonderful.

1188
00:56:58,719 --> 00:57:03,440
Speaker 4: Good perversions pro sex podcast Christ the the the one

1189
00:57:03,440 --> 00:57:05,120
Speaker 4: where you send an avatar.

1190
00:57:04,760 --> 00:57:10,400
Speaker 5: That different, completely autonomous from from you and evil. And

1191
00:57:11,400 --> 00:57:14,480
Speaker 5: it was like this is this is why what she

1192
00:57:14,600 --> 00:57:16,760
Speaker 5: was saying was so odd because like she presented this

1193
00:57:16,800 --> 00:57:20,720
Speaker 5: as like a surprising revelation that that gen Z would

1194
00:57:20,800 --> 00:57:23,880
Speaker 5: rather live life themselves than have an AI live your

1195
00:57:23,920 --> 00:57:27,880
Speaker 5: life for you, and like like that was what she

1196
00:57:27,960 --> 00:57:29,880
Speaker 5: was trying to say, but it was so odd having

1197
00:57:29,880 --> 00:57:33,040
Speaker 5: that presented like some like surprising like exclusive fact that

1198
00:57:33,080 --> 00:57:35,400
Speaker 5: you can only get through like data research and and

1199
00:57:35,400 --> 00:57:38,280
Speaker 5: and she she talked about like there is like gen

1200
00:57:38,360 --> 00:57:41,280
Speaker 5: Z sees value in having like bad dates and like

1201
00:57:41,720 --> 00:57:44,400
Speaker 5: and like and like actually and actually like and actually

1202
00:57:44,400 --> 00:57:48,120
Speaker 5: like overcoming like challenges in life and like that's that's

1203
00:57:48,120 --> 00:57:50,600
Speaker 5: actually a core part of being human and we don't

1204
00:57:50,600 --> 00:57:54,560
Speaker 5: want that process like uh, like like smoothed over with

1205
00:57:54,760 --> 00:57:58,240
Speaker 5: like tech can't solve the hardship of life. The hardship

1206
00:57:58,320 --> 00:58:00,640
Speaker 5: is part of life. That's what makes life work living and.

1207
00:58:00,640 --> 00:58:03,040
Speaker 2: Like, yeah, how old are you?

1208
00:58:03,120 --> 00:58:04,800
Speaker 5: I'm in my early twenties.

1209
00:58:05,160 --> 00:58:09,240
Speaker 2: Sorry, I didn't want to get so gen Z. Yeah, Yeah,

1210
00:58:09,280 --> 00:58:11,600
Speaker 2: how do you feel about these assumptions?

1211
00:58:13,040 --> 00:58:15,360
Speaker 5: I mean, like again like this is these are questions

1212
00:58:15,400 --> 00:58:18,280
Speaker 5: that she's like that she's imposing to like you know,

1213
00:58:18,560 --> 00:58:21,600
Speaker 5: focused groups of of of like Jami, but like but

1214
00:58:23,200 --> 00:58:25,240
Speaker 5: they're really pandering, They're they're there.

1215
00:58:25,560 --> 00:58:26,400
Speaker 2: Is it accurate?

1216
00:58:26,840 --> 00:58:29,560
Speaker 5: Well no, because they assume such a base level of

1217
00:58:29,600 --> 00:58:32,760
Speaker 5: stupidity that they're like kind of offensively like even like

1218
00:58:32,840 --> 00:58:35,000
Speaker 5: framed the fact that I would be like would you

1219
00:58:35,120 --> 00:58:36,720
Speaker 5: rather have an AI go on dates for you?

1220
00:58:36,840 --> 00:58:36,960
Speaker 4: Like?

1221
00:58:37,360 --> 00:58:39,760
Speaker 5: Why why would you ever ask me that? That's that?

1222
00:58:39,760 --> 00:58:40,920
Speaker 5: That's fucking stupid?

1223
00:58:41,040 --> 00:58:44,880
Speaker 2: Some of the fun parts about romance. Wow, set the

1224
00:58:44,880 --> 00:58:48,520
Speaker 2: word correctly. They're always saying this about me with how

1225
00:58:48,560 --> 00:58:53,200
Speaker 2: words go? Is fucking up about exact of yourself that

1226
00:58:53,240 --> 00:58:55,520
Speaker 2: get banged off someone and you feel that you learn

1227
00:58:55,560 --> 00:58:56,840
Speaker 2: about yourself exactly.

1228
00:58:57,000 --> 00:58:58,600
Speaker 5: And that's and that's what she was saying, is like

1229
00:58:59,480 --> 00:59:01,760
Speaker 5: that's act atually what people want. People don't people don't

1230
00:59:01,760 --> 00:59:05,200
Speaker 5: actually want AI telling to to like live your life,

1231
00:59:05,360 --> 00:59:07,760
Speaker 5: you shouldn't take and and and and she and she

1232
00:59:07,760 --> 00:59:10,920
Speaker 5: she specifically provided to push back against this idea in

1233
00:59:10,920 --> 00:59:13,720
Speaker 5: in the in the tech industry, where like the smoothest

1234
00:59:13,720 --> 00:59:17,919
Speaker 5: possible path is the best one, right, you you want

1235
00:59:18,080 --> 00:59:21,680
Speaker 5: you want, you want to like optimize every part of life,

1236
00:59:21,680 --> 00:59:24,760
Speaker 5: and like what if that optimization actually isn't the point?

1237
00:59:25,080 --> 00:59:27,120
Speaker 5: What what if this like idea in the in the

1238
00:59:27,120 --> 00:59:29,400
Speaker 5: tech industry that we have to optimize and smooth over

1239
00:59:29,520 --> 00:59:34,080
Speaker 5: every hardship misses the entire point of living. And you

1240
00:59:34,120 --> 00:59:37,200
Speaker 5: have all these tech bros being like, oh yeah, huh,

1241
00:59:37,280 --> 00:59:40,720
Speaker 5: I guess so maybe maybe we shouldn't smooth over all

1242
00:59:40,760 --> 00:59:41,400
Speaker 5: the problems.

1243
00:59:41,440 --> 00:59:43,240
Speaker 3: It's like a it's a very maybe I'm getting this

1244
00:59:43,280 --> 00:59:45,960
Speaker 3: reference wrong. It's a very like Patrick Baateman Bateman like

1245
00:59:46,000 --> 00:59:49,280
Speaker 3: things of like I am optimizing everything to the tea

1246
00:59:49,840 --> 00:59:52,240
Speaker 3: and I will you keep it, keep it going?

1247
00:59:52,480 --> 00:59:54,560
Speaker 4: I mean no specifically in his in the book, you

1248
00:59:54,600 --> 00:59:57,200
Speaker 4: know that is like the sort of train of thought

1249
00:59:57,240 --> 01:00:01,160
Speaker 4: he has. This he's like kind of imp empty, engaging

1250
01:00:01,200 --> 01:00:08,480
Speaker 4: with life at the very superficial, craving something else.

1251
01:00:08,840 --> 01:00:11,360
Speaker 5: Like the final point she had is like and again

1252
01:00:11,400 --> 01:00:12,920
Speaker 5: this is all it's all kind of panderings, like you're

1253
01:00:12,960 --> 01:00:14,920
Speaker 5: saying like you're saying, like gen Z, but like this

1254
01:00:14,960 --> 01:00:17,080
Speaker 5: is like acrossing a lot of people, like but she said,

1255
01:00:17,120 --> 01:00:20,760
Speaker 5: like gen Z doesn't trust AI to understand the nuance

1256
01:00:20,840 --> 01:00:27,120
Speaker 5: of their lives and minial of course, but yes, like

1257
01:00:27,760 --> 01:00:29,400
Speaker 5: it was not a panel because on one hand you

1258
01:00:29,440 --> 01:00:32,080
Speaker 5: have these like like AI toys for kids, and then

1259
01:00:32,160 --> 01:00:34,720
Speaker 5: you have this woman with this company that works as

1260
01:00:34,760 --> 01:00:37,960
Speaker 5: sess to me and she's like, yeah, actually gen Z

1261
01:00:38,040 --> 01:00:42,000
Speaker 5: doesn't want AI to run their lives, and you're like, yeah,

1262
01:00:41,880 --> 01:00:43,040
Speaker 5: who could have thought.

1263
01:00:44,240 --> 01:00:49,240
Speaker 2: So, as we approach the final second of the thirds

1264
01:00:49,280 --> 01:00:52,800
Speaker 2: of Better Offline, Yeah, where can people find you?

1265
01:00:53,360 --> 01:00:57,120
Speaker 5: Well? I am I am on X the the Everything

1266
01:00:57,320 --> 01:01:00,360
Speaker 5: at Hungry bow Tie as well as Blue Sky at

1267
01:01:00,400 --> 01:01:04,880
Speaker 5: Hungry boy Tie, at Hungrybowtie dot Social and it could

1268
01:01:04,960 --> 01:01:07,800
Speaker 5: happen here and the podcast with me Robert Evans and

1269
01:01:07,800 --> 01:01:10,600
Speaker 5: a few of our other colleagues where recover sometimes tech

1270
01:01:10,720 --> 01:01:14,920
Speaker 5: but you know, politics, culture, just disinformation, all that kind

1271
01:01:14,920 --> 01:01:17,480
Speaker 5: of fun stuff that greases the wheels of our society.

1272
01:01:17,760 --> 01:01:22,600
Speaker 2: Yummy, Kyle, I can be found on X the Everything

1273
01:01:22,640 --> 01:01:25,000
Speaker 2: app I've Got.

1274
01:01:24,880 --> 01:01:28,880
Speaker 3: Kyle Underscore Schnard and then my my writing's on Las Vegas.

1275
01:01:28,560 --> 01:01:29,320
Speaker 1: On dot com.

1276
01:01:29,360 --> 01:01:31,560
Speaker 2: Oh yeah, and Edward Guaso Junia.

1277
01:01:31,680 --> 01:01:33,840
Speaker 4: You can I in the real world. I live at

1278
01:01:33,880 --> 01:01:38,200
Speaker 4: sixteen hundred Pencils in the Avenue Northwest in Washington, d

1279
01:01:38,320 --> 01:01:40,440
Speaker 4: C s code two zero five zero zero.

1280
01:01:40,600 --> 01:01:41,480
Speaker 5: That's a nice neighborhood.

1281
01:01:41,560 --> 01:01:44,520
Speaker 4: It's it's kind of nice. It's got a great view

1282
01:01:44,520 --> 01:01:45,040
Speaker 4: of everything.

1283
01:01:45,200 --> 01:01:45,480
Speaker 5: Nice.

1284
01:01:47,160 --> 01:01:50,400
Speaker 4: What else? I'm at a big black Jacobin on Twitter

1285
01:01:50,480 --> 01:01:54,800
Speaker 4: and Blue Sky and This Machine Kills is my podcast,

1286
01:01:55,200 --> 01:01:58,400
Speaker 4: and the Tech Bubble dot Substack dot com is my newsletter.

1287
01:01:58,920 --> 01:02:02,080
Speaker 2: You are approaching the final third of the final two

1288
01:02:02,120 --> 01:02:04,680
Speaker 2: part episode of the Consumer Electronics Show, and I just

1289
01:02:04,720 --> 01:02:07,360
Speaker 2: want to say something to you, which I'll elongate at

1290
01:02:07,360 --> 01:02:10,040
Speaker 2: the end of this. I'm so grateful for you giving

1291
01:02:10,080 --> 01:02:13,320
Speaker 2: me your patients. With this, I will say, I need

1292
01:02:13,360 --> 01:02:16,160
Speaker 2: you to listen to the ad. I don't know actually

1293
01:02:16,160 --> 01:02:19,800
Speaker 2: what happens after I'm done talking. I never do. Frankly,

1294
01:02:19,840 --> 01:02:22,400
Speaker 2: I barely understand what I'm doing when I am talking.

1295
01:02:22,480 --> 01:02:27,000
Speaker 2: Because Madisowski over here heals Jesus Christ. I can't even say,

1296
01:02:27,040 --> 01:02:31,000
Speaker 2: here's we're keeping it. Madisowski hears me mess up my name,

1297
01:02:31,080 --> 01:02:33,040
Speaker 2: mess up the name of companies, or just mess up

1298
01:02:33,080 --> 01:02:36,440
Speaker 2: a word. But you know, I keep reading because podcasting

1299
01:02:36,480 --> 01:02:38,200
Speaker 2: is in my blood and that's who I am, and

1300
01:02:38,200 --> 01:02:41,960
Speaker 2: that's my identity. It's very normal and healthy. Please listen

1301
01:02:42,040 --> 01:02:44,720
Speaker 2: to the ads, Please download the podcast, plead buy the product.

1302
01:02:44,760 --> 01:02:47,000
Speaker 2: If they don't give me another contract, it's going to

1303
01:02:47,040 --> 01:02:49,600
Speaker 2: be very bad and my therapist is going to be mad.

1304
01:03:05,440 --> 01:03:08,280
Speaker 2: So we enter the end of the truly unified end

1305
01:03:08,280 --> 01:03:11,400
Speaker 2: of the Better Offline podcast. This incredible week, and I'm

1306
01:03:11,400 --> 01:03:14,880
Speaker 2: not even gonna do any like sardonic shit. I'm just

1307
01:03:14,960 --> 01:03:17,520
Speaker 2: so happy. I'm surrounded by people who are super game

1308
01:03:17,640 --> 01:03:20,880
Speaker 2: to make podcasts too. Like I'm like genuinely like near

1309
01:03:20,960 --> 01:03:23,280
Speaker 2: tears of how happy I am with everyone being game

1310
01:03:23,320 --> 01:03:25,960
Speaker 2: for this. Everyone has been so amazing, all the journalists

1311
01:03:26,000 --> 01:03:28,200
Speaker 2: who have joined us. It's just been the best fucking

1312
01:03:28,240 --> 01:03:32,240
Speaker 2: week of a week that is generally quite depressing. Also

1313
01:03:32,680 --> 01:03:36,120
Speaker 2: feels like a good point to admit two things. One,

1314
01:03:36,400 --> 01:03:41,080
Speaker 2: I watched Neogenesis Evangelian and I was a teenager, and

1315
01:03:41,160 --> 01:03:44,600
Speaker 2: I did not understand the subtext. Oh yeah, so the

1316
01:03:44,640 --> 01:03:47,400
Speaker 2: whole time for most of my life was watching this

1317
01:03:47,480 --> 01:03:50,800
Speaker 2: show and being like, Danny's robots are fucking cool, and

1318
01:03:50,840 --> 01:03:54,480
Speaker 2: then like some weird shit happened. I guess I'm like, okay,

1319
01:03:54,480 --> 01:03:57,240
Speaker 2: but okay, the robot's back. Okay, there's like some stuff

1320
01:03:57,240 --> 01:04:00,000
Speaker 2: from space and there's a big head kind of fucking weird,

1321
01:04:00,080 --> 01:04:02,800
Speaker 2: I guess anyway. Welcome to Better Offline. I'm Ed Zichron.

1322
01:04:03,000 --> 01:04:06,440
Speaker 2: We are joined by everyone. We're joined by Robert Evans

1323
01:04:06,480 --> 01:04:09,680
Speaker 2: of cool Zone Media. That's right, all right, David J. Roth,

1324
01:04:09,720 --> 01:04:12,520
Speaker 2: who is gonna have to grab the mic? Hello of

1325
01:04:12,600 --> 01:04:16,640
Speaker 2: defector Edward Nguiso Junior, of course, will now have another mic.

1326
01:04:19,040 --> 01:04:22,520
Speaker 2: Kyle Shanard of the Las Vegas Sun, Hello, and Gaed

1327
01:04:22,640 --> 01:04:25,240
Speaker 2: Davis of it could happen here, Cool Zone Media and

1328
01:04:25,280 --> 01:04:26,480
Speaker 2: Associated Properties.

1329
01:04:26,760 --> 01:04:27,800
Speaker 5: Hello, Hello, Hello.

1330
01:04:28,400 --> 01:04:30,440
Speaker 2: We're at the end of CES. We have one more

1331
01:04:30,480 --> 01:04:32,800
Speaker 2: positive masculine e day coming after this, but this is

1332
01:04:32,880 --> 01:04:36,520
Speaker 2: really the close out, as all of us just slop

1333
01:04:36,560 --> 01:04:41,640
Speaker 2: ourselves into the remaining quarters of this convention center. I

1334
01:04:41,680 --> 01:04:43,560
Speaker 2: could not have had more fun if I tried, But

1335
01:04:43,600 --> 01:04:46,360
Speaker 2: next year I'll try. Robert, how has the show been?

1336
01:04:46,400 --> 01:04:47,840
Speaker 2: How would you summarize the show?

1337
01:04:47,880 --> 01:04:48,400
Speaker 5: It was great?

1338
01:04:48,400 --> 01:04:52,400
Speaker 8: I mean, obviously AI is here to stay. This is

1339
01:04:52,440 --> 01:04:57,920
Speaker 8: the worst it's ever gonna be. Everything's thank you, only

1340
01:04:57,960 --> 01:05:01,080
Speaker 8: gonna get better and thank God. You know, there's this

1341
01:05:01,120 --> 01:05:03,640
Speaker 8: little kid that I helped take care of and it

1342
01:05:03,680 --> 01:05:05,720
Speaker 8: takes a lot of time, as you know, as a father,

1343
01:05:05,920 --> 01:05:07,680
Speaker 8: ed a lot of time and a lot of effort

1344
01:05:07,840 --> 01:05:10,440
Speaker 8: to raise a child, and I'm just excited that TCL

1345
01:05:10,560 --> 01:05:12,560
Speaker 8: has a solution to that problem.

1346
01:05:13,000 --> 01:05:13,360
Speaker 5: We can do.

1347
01:05:13,480 --> 01:05:15,400
Speaker 8: It's what I've always dreamed, which is that you keep

1348
01:05:15,440 --> 01:05:17,760
Speaker 8: like a hamster like feeder and a water like you

1349
01:05:17,840 --> 01:05:19,760
Speaker 8: just took up a hose to the room and you

1350
01:05:19,840 --> 01:05:22,080
Speaker 8: lock the child in with a robot until they're eighteen

1351
01:05:22,160 --> 01:05:24,480
Speaker 8: or twenty like the room exactly.

1352
01:05:24,560 --> 01:05:25,400
Speaker 5: Yeah, it's perfect.

1353
01:05:25,680 --> 01:05:27,000
Speaker 8: You know, as long as you get like one of

1354
01:05:27,040 --> 01:05:29,800
Speaker 8: those lights that gives you some sun kind of effect,

1355
01:05:29,880 --> 01:05:32,840
Speaker 8: you know, they won't die probably, like and that's ideal.

1356
01:05:33,440 --> 01:05:34,680
Speaker 5: Have you introduced this product?

1357
01:05:35,360 --> 01:05:38,880
Speaker 2: I I'll introduced Oh wait, no, no, we have not

1358
01:05:39,560 --> 01:05:41,520
Speaker 2: just into the disparagement.

1359
01:05:44,040 --> 01:05:44,640
Speaker 5: No, I'll move on.

1360
01:05:45,040 --> 01:05:46,880
Speaker 6: No, I mean this is in the we had talked

1361
01:05:46,920 --> 01:05:49,600
Speaker 6: about how like cute little guys are part of the

1362
01:05:49,920 --> 01:05:54,800
Speaker 6: like that again about me, it's but that like this,

1363
01:05:55,000 --> 01:05:57,800
Speaker 6: the TCL is the most I looked at this also,

1364
01:05:57,840 --> 01:06:00,240
Speaker 6: and they have like a whole little video of like

1365
01:06:00,360 --> 01:06:04,240
Speaker 6: a towheaded child interacting with this thing. Yes, and his parents,

1366
01:06:04,600 --> 01:06:06,440
Speaker 6: the kid's parents are kind of like standing off to

1367
01:06:06,520 --> 01:06:09,280
Speaker 6: the side being like super listen, do you want to

1368
01:06:09,360 --> 01:06:10,880
Speaker 6: like go to the movies or whatever?

1369
01:06:11,360 --> 01:06:12,439
Speaker 5: But it's the most.

1370
01:06:12,720 --> 01:06:15,360
Speaker 6: It's probably the cutest of the cute little guys, but

1371
01:06:15,440 --> 01:06:18,360
Speaker 6: then also easily the most sinister, the most evil. Yeah,

1372
01:06:18,400 --> 01:06:19,240
Speaker 6: it's the most sinister.

1373
01:06:19,840 --> 01:06:21,480
Speaker 5: Well, and you stray towheaded.

1374
01:06:21,960 --> 01:06:24,280
Speaker 8: I didn't disagree with with Garrison, So I'm wondering how

1375
01:06:24,320 --> 01:06:26,479
Speaker 8: you thought, because I felt like they cast that child

1376
01:06:26,520 --> 01:06:30,480
Speaker 8: because it looked like he had leukemia definitely.

1377
01:06:31,480 --> 01:06:33,520
Speaker 5: Well, I don't want to say anything bad about the kid, right,

1378
01:06:34,280 --> 01:06:37,960
Speaker 5: I don't know. Yeah, yeah, yes he did.

1379
01:06:38,040 --> 01:06:38,160
Speaker 2: Well.

1380
01:06:38,520 --> 01:06:40,960
Speaker 6: What he looked like was honestly the scenario you described,

1381
01:06:40,960 --> 01:06:43,080
Speaker 6: which is basically like we're growing a child the way

1382
01:06:43,120 --> 01:06:44,280
Speaker 6: that people grow mushrooms.

1383
01:06:44,360 --> 01:06:48,280
Speaker 5: Yes, in their house. Yes, it looks like.

1384
01:06:53,920 --> 01:06:56,680
Speaker 8: Yeah, huge bags under his eyes. Never seen the kiss

1385
01:06:56,800 --> 01:06:58,040
Speaker 8: of the sun or his mom.

1386
01:06:58,120 --> 01:07:00,880
Speaker 4: You do not know what vitamin sees is, little boy,

1387
01:07:00,960 --> 01:07:03,680
Speaker 4: But don't worry or d d well.

1388
01:07:03,920 --> 01:07:06,440
Speaker 6: Pfirst robot specifically for children that look the way the

1389
01:07:06,520 --> 01:07:10,560
Speaker 6: actor Brad Doroff looks right now, designed for that.

1390
01:07:10,760 --> 01:07:11,840
Speaker 5: I don't know who that is.

1391
01:07:12,480 --> 01:07:15,680
Speaker 2: I am the host of this fucking thing. You need

1392
01:07:15,720 --> 01:07:19,280
Speaker 2: to Okay, so we've also got Phil our bartender. We

1393
01:07:19,320 --> 01:07:24,160
Speaker 2: should talk in Hello. Thank you Phil, very good. That's enough,

1394
01:07:25,360 --> 01:07:28,240
Speaker 2: thank you. I really don't know how to direct this

1395
01:07:28,360 --> 01:07:32,280
Speaker 2: at this point because I invited like seven people into camp. Okay,

1396
01:07:32,440 --> 01:07:35,400
Speaker 2: well with us, let's start on an easy point. We'll

1397
01:07:35,480 --> 01:07:38,200
Speaker 2: just go around has everyone feeling at this point of

1398
01:07:38,280 --> 01:07:41,760
Speaker 2: CS we are at the end. Let's start with Gare

1399
01:07:41,920 --> 01:07:47,080
Speaker 2: because you are probably the like second least likely to

1400
01:07:47,200 --> 01:07:51,640
Speaker 2: say something legally actionable, and I realized that it is.

1401
01:07:51,640 --> 01:07:55,960
Speaker 5: Now a challenge. You haven't had all the conversations I've

1402
01:07:56,040 --> 01:07:59,880
Speaker 5: had with care. What am I doing?

1403
01:08:01,200 --> 01:08:01,520
Speaker 4: I don't know.

1404
01:08:01,600 --> 01:08:04,439
Speaker 5: I feel fine. It gets I was able to find

1405
01:08:04,520 --> 01:08:07,360
Speaker 5: some cool stuff despite having to sort through lots of slop.

1406
01:08:07,960 --> 01:08:10,480
Speaker 5: There's always one or two gems at cees that makes

1407
01:08:10,600 --> 01:08:12,360
Speaker 5: kind of all like that that makes all of this

1408
01:08:12,440 --> 01:08:15,120
Speaker 5: slop sorting worth it. So I was happy to find

1409
01:08:15,160 --> 01:08:17,400
Speaker 5: a few of those in Eureka Park. I also had

1410
01:08:17,479 --> 01:08:22,240
Speaker 5: my my family no, absolutely not, we're not We're not

1411
01:08:22,280 --> 01:08:25,040
Speaker 5: gonna do free publicity. Agreed, that's my job and it

1412
01:08:25,160 --> 01:08:26,520
Speaker 5: costs money anyway.

1413
01:08:27,560 --> 01:08:27,800
Speaker 2: But no.

1414
01:08:27,920 --> 01:08:29,599
Speaker 5: I was also able to have a little bit of fun.

1415
01:08:29,680 --> 01:08:31,320
Speaker 5: As soon as I realized that this show is just

1416
01:08:31,360 --> 01:08:35,080
Speaker 5: gonna be last year's show again, I kind of relaxed myself,

1417
01:08:35,200 --> 01:08:37,320
Speaker 5: being like I can just kind of do what I

1418
01:08:37,720 --> 01:08:41,200
Speaker 5: can kind of just like funk off. So I talked

1419
01:08:41,240 --> 01:08:48,400
Speaker 5: to a flying car company. It was real. I was

1420
01:08:48,439 --> 01:08:51,080
Speaker 5: waiting to interview someone and instead one of their like

1421
01:08:51,160 --> 01:08:52,880
Speaker 5: pr guys walk up to me is like, hey, can

1422
01:08:52,920 --> 01:08:56,120
Speaker 5: we interview you about your thoughts on this flying car.

1423
01:08:56,200 --> 01:09:01,479
Speaker 5: I'm like absolutely, I wish that happened to me, like

1424
01:09:01,600 --> 01:09:03,280
Speaker 5: I would just thought I will kill my It was.

1425
01:09:03,360 --> 01:09:07,680
Speaker 5: It was every the phrase ces miracle gets used a lot.

1426
01:09:08,120 --> 01:09:10,320
Speaker 5: That really was what did you do it?

1427
01:09:10,439 --> 01:09:10,599
Speaker 2: Though?

1428
01:09:10,680 --> 01:09:13,479
Speaker 5: Oh I did hell and so I talked a lot

1429
01:09:13,520 --> 01:09:16,400
Speaker 5: about like my concerns around safety for these flying cars.

1430
01:09:16,680 --> 01:09:19,000
Speaker 5: I I predicted it has twenty minutes in the air.

1431
01:09:19,080 --> 01:09:20,760
Speaker 5: It was actually it was a huge drone and I

1432
01:09:20,800 --> 01:09:21,599
Speaker 5: got exactly right.

1433
01:09:21,720 --> 01:09:21,880
Speaker 2: It was.

1434
01:09:22,000 --> 01:09:22,840
Speaker 4: It was a.

1435
01:09:24,360 --> 01:09:26,840
Speaker 5: Twenty minutes up in the air. It launches from something

1436
01:09:27,120 --> 01:09:29,080
Speaker 5: something that looks like a cyber truck. It launches, it

1437
01:09:29,160 --> 01:09:31,760
Speaker 5: launches out of the classic and it launches out of

1438
01:09:31,880 --> 01:09:34,120
Speaker 5: like the trunk of the cyber truck. You can get

1439
01:09:34,160 --> 01:09:36,519
Speaker 5: twenty minutes in the air and then you're gonna crash

1440
01:09:36,760 --> 01:09:39,400
Speaker 5: or which is my god, you will have some kind

1441
01:09:39,439 --> 01:09:41,720
Speaker 5: of AI assisted landing, And like I asked them, like yeah,

1442
01:09:42,200 --> 01:09:44,640
Speaker 5: so I'm crashing what's your plan for that? Like, like,

1443
01:09:44,720 --> 01:09:46,240
Speaker 5: what if you're in a populated area and you're like

1444
01:09:46,439 --> 01:09:50,000
Speaker 5: and they said, no, well, we'll have guard rail software

1445
01:09:50,040 --> 01:09:53,479
Speaker 5: to make sure it doesn't land in populated areas of

1446
01:09:53,600 --> 01:09:56,439
Speaker 5: like we have some of the papers from Night Capital.

1447
01:09:56,560 --> 01:10:00,120
Speaker 5: I'm launching this thing right in the middle of midtown Manhattan. Oh,

1448
01:10:00,479 --> 01:10:03,320
Speaker 5: I'm gonna do hover for twenty minutes, And which brings

1449
01:10:03,320 --> 01:10:05,240
Speaker 5: me to the second thing that they asked me about

1450
01:10:05,360 --> 01:10:08,240
Speaker 5: was like, like, what's you know, what's maybe some of

1451
01:10:08,320 --> 01:10:10,320
Speaker 5: your concerns or like, what's the first thing you think of?

1452
01:10:10,400 --> 01:10:14,840
Speaker 5: I'm like, well, a few weeks ago, a few weeks ago,

1453
01:10:15,200 --> 01:10:19,559
Speaker 5: a Deloitte consultant drove a car into like into fifteen

1454
01:10:19,600 --> 01:10:23,760
Speaker 5: people in a in a terrorist attack. Like same day,

1455
01:10:24,040 --> 01:10:26,960
Speaker 5: someone used a cyber truck to make a bomb. What

1456
01:10:27,080 --> 01:10:29,720
Speaker 5: if some rich guy loses his mind and flies this

1457
01:10:29,760 --> 01:10:33,000
Speaker 5: thing into a building and they did not like that?

1458
01:10:34,400 --> 01:10:34,599
Speaker 2: Why.

1459
01:10:36,520 --> 01:10:39,080
Speaker 5: I don't know what kind of PR trading these guys had.

1460
01:10:40,479 --> 01:10:42,000
Speaker 5: I don't know if they were prepared to this.

1461
01:10:42,040 --> 01:10:43,680
Speaker 6: Is like good enough PR training that they were Like

1462
01:10:44,040 --> 01:10:46,599
Speaker 6: this person seems nice, Let's ask them what they think.

1463
01:10:46,840 --> 01:10:49,639
Speaker 2: Turning to my turn to my class, like just killed

1464
01:10:49,640 --> 01:10:52,120
Speaker 2: you killed, like just gun in your mind, just don't.

1465
01:10:52,240 --> 01:10:54,679
Speaker 2: Don't also diet, like it's the best way you could

1466
01:10:54,680 --> 01:10:55,200
Speaker 2: go about this.

1467
01:10:55,439 --> 01:10:57,920
Speaker 8: But you would get into commercial aviation and not have

1468
01:10:58,000 --> 01:11:00,479
Speaker 8: an answer. The nine to eleven question is is just.

1469
01:11:02,120 --> 01:11:04,880
Speaker 5: That's in the past, so I was able to relax

1470
01:11:05,000 --> 01:11:07,280
Speaker 5: and have fun, you know, with moments like that, you

1471
01:11:07,360 --> 01:11:10,320
Speaker 5: had fun, you know, once it became clear, it was

1472
01:11:10,439 --> 01:11:12,560
Speaker 5: just like, you know, like AI software was like the

1473
01:11:12,640 --> 01:11:14,479
Speaker 5: king of this year once again, a whole bunch of

1474
01:11:14,760 --> 01:11:16,720
Speaker 5: things that used to be like, you know, actually kind

1475
01:11:16,720 --> 01:11:20,360
Speaker 5: of like all of the like university projects in Eureka Park,

1476
01:11:20,400 --> 01:11:23,559
Speaker 5: which sometimes has like a really cool new thing. Right now,

1477
01:11:23,640 --> 01:11:25,960
Speaker 5: all of that creativity is being is just being channeled

1478
01:11:26,000 --> 01:11:29,080
Speaker 5: into AI software, and that's in some ways disappointing to

1479
01:11:29,120 --> 01:11:31,800
Speaker 5: see some of the Some of the software is like good,

1480
01:11:31,960 --> 01:11:35,120
Speaker 5: like it works, it can solve problems, but it's also

1481
01:11:35,320 --> 01:11:37,240
Speaker 5: again like it's it's it's part of the slop. There's

1482
01:11:37,240 --> 01:11:38,559
Speaker 5: also a lot of slop software.

1483
01:11:38,960 --> 01:11:41,200
Speaker 2: I feel like we're in the slop society. I feel

1484
01:11:41,200 --> 01:11:44,080
Speaker 2: like we're at this point where everyone here, I think,

1485
01:11:44,360 --> 01:11:49,200
Speaker 2: is experiencing some form of mental damage from being here

1486
01:11:49,320 --> 01:11:53,599
Speaker 2: too long. Oh yeah, but also the thing, to be clear,

1487
01:11:53,880 --> 01:11:56,519
Speaker 2: definitely least the one commonality I have with Robert, which

1488
01:11:56,600 --> 01:11:59,360
Speaker 2: is Robert is the only person I've seen exhibit the

1489
01:11:59,400 --> 01:12:02,360
Speaker 2: same thing of like the Jokers feel where you're just

1490
01:12:02,479 --> 01:12:04,599
Speaker 2: like You're like it gets worse and I get better.

1491
01:12:06,080 --> 01:12:08,439
Speaker 2: I'm just fucking suffering, and like the more I suffer,

1492
01:12:08,520 --> 01:12:10,800
Speaker 2: the stronger I get, and the more intrigued.

1493
01:12:10,360 --> 01:12:11,720
Speaker 5: I get with the more pain I get.

1494
01:12:11,800 --> 01:12:13,439
Speaker 6: He's also the only person that I saw that I

1495
01:12:13,520 --> 01:12:17,439
Speaker 6: recognized on the floor of the South Hall of the

1496
01:12:17,520 --> 01:12:20,479
Speaker 6: Conventions that are where it was just like cell phone cases,

1497
01:12:20,880 --> 01:12:23,760
Speaker 6: like not technology, but just like Chinese stuff designed to

1498
01:12:23,800 --> 01:12:24,679
Speaker 6: be sold on Amazon.

1499
01:12:24,760 --> 01:12:26,120
Speaker 2: That's where Robert his best was.

1500
01:12:26,280 --> 01:12:27,960
Speaker 5: And he was he was like locked in.

1501
01:12:28,120 --> 01:12:29,640
Speaker 6: I was like hey, and he got like some of

1502
01:12:29,680 --> 01:12:31,080
Speaker 6: the way past me was like, do you fucking need

1503
01:12:31,160 --> 01:12:37,280
Speaker 6: something or whatever, like, oh man, it's from yesterday.

1504
01:12:38,200 --> 01:12:40,040
Speaker 5: Table that we were at. Oh my god.

1505
01:12:40,600 --> 01:12:43,639
Speaker 8: In my defense, there were really huge cell phones there,

1506
01:12:43,840 --> 01:12:46,400
Speaker 8: like massive, like it literally and inho and a half.

1507
01:12:46,320 --> 01:12:47,559
Speaker 5: Thick rugged cell phones.

1508
01:12:47,600 --> 01:12:49,479
Speaker 8: Okay, And to look at them, I had to touch them.

1509
01:12:49,720 --> 01:12:51,960
Speaker 8: We're not reporting on them, I have nothing to say

1510
01:12:52,040 --> 01:12:52,479
Speaker 8: about them.

1511
01:12:52,520 --> 01:12:53,479
Speaker 5: I had to feel them.

1512
01:12:53,600 --> 01:12:56,679
Speaker 2: Are we establishing that Rubbert Evans accidentally Big Times people,

1513
01:12:56,800 --> 01:12:57,519
Speaker 2: is that what we're saying.

1514
01:12:57,840 --> 01:12:59,280
Speaker 5: I did not feel big Times. I was just like,

1515
01:12:59,400 --> 01:13:02,599
Speaker 5: damn this guy, I will.

1516
01:13:02,439 --> 01:13:05,560
Speaker 2: Give the most derisive view of I did not know

1517
01:13:05,640 --> 01:13:08,920
Speaker 2: who Robert Evans was before August twenty twenty three, a

1518
01:13:09,080 --> 01:13:12,400
Speaker 2: fact I am regularly reminded of by everyone else. They

1519
01:13:12,520 --> 01:13:15,280
Speaker 2: mentioned Robert Evans too, Oh my god, the behind the

1520
01:13:15,400 --> 01:13:18,560
Speaker 2: Bastards guy, and I was like, Eh, this is a

1521
01:13:18,640 --> 01:13:21,160
Speaker 2: fucking guy with the weird avatar. Oh you want to

1522
01:13:21,160 --> 01:13:22,080
Speaker 2: do podcasts, but the.

1523
01:13:23,560 --> 01:13:25,680
Speaker 5: Fucking ass what you're gonna do about it?

1524
01:13:25,840 --> 01:13:28,599
Speaker 2: Mayah need money? It turns out I already a corporation.

1525
01:13:28,760 --> 01:13:31,479
Speaker 2: Thank you, no negative statements right now, all of you.

1526
01:13:31,600 --> 01:13:35,160
Speaker 2: I actually need this. But nevertheless, it is really fun

1527
01:13:35,240 --> 01:13:37,840
Speaker 2: being here with Robert because Robert again is one of

1528
01:13:37,880 --> 01:13:40,439
Speaker 2: the only people who experiences CS in the way I do,

1529
01:13:40,560 --> 01:13:44,080
Speaker 2: which is the Metallica song Frantic, where you're just like,

1530
01:13:44,439 --> 01:13:46,960
Speaker 2: it's not great but you're here, Oh yeah, and it

1531
01:13:47,120 --> 01:13:49,599
Speaker 2: kind of bangs, but not for the reasons everyone else

1532
01:13:49,720 --> 01:13:53,400
Speaker 2: feels totally sat anger fans line up all three of us.

1533
01:13:54,000 --> 01:13:56,559
Speaker 2: But it's also really fun being here this time because

1534
01:13:56,640 --> 01:13:59,360
Speaker 2: last year I was but a babe and very nervous.

1535
01:13:59,439 --> 01:14:02,280
Speaker 2: Now I'm just like, oh no, you wade into it

1536
01:14:02,400 --> 01:14:04,680
Speaker 2: with like your pants off, like you're just like I

1537
01:14:04,800 --> 01:14:06,000
Speaker 2: will see everything.

1538
01:14:06,560 --> 01:14:08,760
Speaker 8: And speaking of Metallica, I heard a pretty good Master

1539
01:14:08,880 --> 01:14:11,200
Speaker 8: of Puppets cover at the MGM Grand in the top

1540
01:14:11,320 --> 01:14:13,479
Speaker 8: three covers of Master of Puppets I've heard on that

1541
01:14:13,600 --> 01:14:15,799
Speaker 8: exact same stage at the MGM Grand.

1542
01:14:16,040 --> 01:14:17,439
Speaker 2: No longer interested in the text.

1543
01:14:17,479 --> 01:14:21,240
Speaker 5: So where was this? It was right near the ski ball.

1544
01:14:21,920 --> 01:14:25,559
Speaker 2: Okay, well I know where we're going. Dinner is canceled, fellas,

1545
01:14:26,360 --> 01:14:29,920
Speaker 2: That's where I'm going. But it is interesting because talking

1546
01:14:29,960 --> 01:14:32,519
Speaker 2: to the various reporters here about CS and why we

1547
01:14:32,640 --> 01:14:35,000
Speaker 2: do this, and no one can answer that question. But

1548
01:14:35,120 --> 01:14:39,200
Speaker 2: the way, it's just like I we're all fucking here

1549
01:14:39,320 --> 01:14:43,000
Speaker 2: every January. But it has been interesting. Gang one of

1550
01:14:43,000 --> 01:14:45,599
Speaker 2: four reports, like Kylin ging it could happen here, Robin,

1551
01:14:45,680 --> 01:14:49,720
Speaker 2: gare gang ed and Dave in like truly like I

1552
01:14:49,760 --> 01:14:53,360
Speaker 2: don't want to say objective, but like fresh looks. And

1553
01:14:53,439 --> 01:14:55,360
Speaker 2: then Robert and Gare of course, who are very much

1554
01:14:55,479 --> 01:14:59,680
Speaker 2: used to Robert is a separate creature. I mean that

1555
01:14:59,800 --> 01:15:02,240
Speaker 2: with more love than I could ever put into my voice.

1556
01:15:02,800 --> 01:15:05,320
Speaker 2: But it's interesting to get this few and then bring

1557
01:15:05,439 --> 01:15:08,840
Speaker 2: reports in and talk and they're like, yeah, well we're

1558
01:15:08,960 --> 01:15:13,200
Speaker 2: here and we saw stuff. But there's also an ephemera

1559
01:15:13,320 --> 01:15:16,120
Speaker 2: that is kind of hard to cover an objective journalism.

1560
01:15:16,200 --> 01:15:17,000
Speaker 5: Kyle totally.

1561
01:15:17,479 --> 01:15:22,360
Speaker 3: Yeah, it's I thought that my main takeaway from the

1562
01:15:22,360 --> 01:15:24,760
Speaker 3: week was the politics of it.

1563
01:15:25,800 --> 01:15:28,759
Speaker 1: I mean from I was at Panasonic's.

1564
01:15:29,720 --> 01:15:32,559
Speaker 3: Keynote and immediately you had people from the Consumer Tech

1565
01:15:32,800 --> 01:15:37,519
Speaker 3: Association talking about tariffs. I mean I walked by people

1566
01:15:37,800 --> 01:15:40,240
Speaker 3: wearing Department of Government efficiency shirts.

1567
01:15:41,200 --> 01:15:43,400
Speaker 1: Really yeah, which was really interesting.

1568
01:15:43,520 --> 01:15:44,720
Speaker 2: Did you hit them? No?

1569
01:15:44,960 --> 01:15:45,320
Speaker 1: Right, did not.

1570
01:15:46,960 --> 01:15:49,840
Speaker 2: I'll take care of it. No, no, don't crime so bad.

1571
01:15:50,920 --> 01:15:53,400
Speaker 3: But yeah, I mean, tariffs were just such a thing.

1572
01:15:53,680 --> 01:15:55,360
Speaker 3: I think a scene in articles I wrote about it.

1573
01:15:56,400 --> 01:15:58,400
Speaker 3: They were just kind of looming over the entire event,

1574
01:15:58,520 --> 01:16:02,400
Speaker 3: and it seems like, i mean, Trump coming in pretty

1575
01:16:02,520 --> 01:16:05,679
Speaker 3: pretty soon. It is just kind of hanging over everyone's

1576
01:16:05,680 --> 01:16:07,559
Speaker 3: heads on top of all the tech. So I mean,

1577
01:16:07,840 --> 01:16:10,400
Speaker 3: is that what, Who's Who's Donald Trump?

1578
01:16:10,560 --> 01:16:10,800
Speaker 5: Trump?

1579
01:16:11,360 --> 01:16:18,639
Speaker 2: No? Sorry, I'm drinking a bit. Yeah, I mean I'm

1580
01:16:18,680 --> 01:16:20,240
Speaker 2: trying to think of the political feeling.

1581
01:16:20,439 --> 01:16:22,320
Speaker 3: Yeah, there's there's a political feeling there, and at the

1582
01:16:22,439 --> 01:16:26,040
Speaker 3: same time, CES is happening. You're seeing this shift from

1583
01:16:26,080 --> 01:16:31,200
Speaker 3: meta that's just just I mean, especially on their their

1584
01:16:31,240 --> 01:16:34,680
Speaker 3: new policies regarding comments about trans and and just other

1585
01:16:34,800 --> 01:16:35,280
Speaker 3: vegan people.

1586
01:16:36,680 --> 01:16:39,599
Speaker 5: Yeah, what was it, something like you're allowed to say

1587
01:16:39,760 --> 01:16:40,320
Speaker 5: don't repeat.

1588
01:16:40,880 --> 01:16:41,519
Speaker 1: Yeah, no I'm not.

1589
01:16:42,040 --> 01:16:44,640
Speaker 2: But it's basically you can just insult trans people, you

1590
01:16:44,720 --> 01:16:47,320
Speaker 2: can sell get without any issue, Jewish people.

1591
01:16:47,400 --> 01:16:50,360
Speaker 5: You can refer to women as property too, and you

1592
01:16:50,439 --> 01:16:53,320
Speaker 5: can actually I really like, I mean at this point,

1593
01:16:53,400 --> 01:16:55,320
Speaker 5: I'm just like you could say, well, I think it

1594
01:16:55,400 --> 01:16:57,720
Speaker 5: actually is worth mentioning, like specifically, like the types of

1595
01:16:57,840 --> 01:17:00,400
Speaker 5: like insults around like mental illness that you're now allowed

1596
01:17:00,439 --> 01:17:03,640
Speaker 5: to call to like call queer people but not call

1597
01:17:03,760 --> 01:17:06,759
Speaker 5: other types of people. Actually is worth actually is worth mentioning.

1598
01:17:06,920 --> 01:17:10,040
Speaker 5: Like it's a it's a huge change.

1599
01:17:10,520 --> 01:17:14,000
Speaker 2: It's just an interesting show because it desperately wants to

1600
01:17:14,080 --> 01:17:18,400
Speaker 2: be a political, a moral totally bereft of these feelings,

1601
01:17:18,479 --> 01:17:21,160
Speaker 2: but it still shows it in the things they show,

1602
01:17:21,200 --> 01:17:25,080
Speaker 2: the collection of data, the kind of surveillance aspect. And

1603
01:17:25,240 --> 01:17:27,519
Speaker 2: it sucks because it feels like this show could be

1604
01:17:27,640 --> 01:17:30,920
Speaker 2: better because on the fringes of the conversations we've had

1605
01:17:30,960 --> 01:17:34,640
Speaker 2: of like, yeah, everyone's creating solutions for problems that they

1606
01:17:34,720 --> 01:17:37,719
Speaker 2: haven't even come up with yet. You get these things,

1607
01:17:38,360 --> 01:17:43,479
Speaker 2: the skin care product, the caine for blind people that

1608
01:17:43,600 --> 01:17:46,240
Speaker 2: can tell you what's coming up, really useful things, the

1609
01:17:46,360 --> 01:17:50,040
Speaker 2: translation stuff exactly, like yeah, like actual translation for a conference,

1610
01:17:50,080 --> 01:17:51,920
Speaker 2: so you could go to a conference in Taiwan and

1611
01:17:52,000 --> 01:17:55,040
Speaker 2: actually computext one of the most important conferences in the world.

1612
01:17:55,280 --> 01:17:59,439
Speaker 5: Really some really impressive like tech to assist people who

1613
01:18:00,080 --> 01:18:03,040
Speaker 5: are disabled. Yeah, I thought accessibility tech was like my

1614
01:18:03,120 --> 01:18:05,400
Speaker 5: main Hi. Yeah, a lot of good That's what Eureka

1615
01:18:05,560 --> 01:18:06,400
Speaker 5: was best at show.

1616
01:18:06,520 --> 01:18:07,759
Speaker 2: Yeah, it's weird that Eureka.

1617
01:18:07,880 --> 01:18:11,320
Speaker 8: The Poisonville actually had some good shit in it for that,

1618
01:18:11,600 --> 01:18:14,760
Speaker 8: and it had I would say the one like consistent

1619
01:18:15,360 --> 01:18:18,040
Speaker 8: like form factor for consumer tech that seems to be

1620
01:18:18,120 --> 01:18:20,000
Speaker 8: getting a lot better every year, and that reminds me

1621
01:18:20,080 --> 01:18:23,120
Speaker 8: of like how phones and tablets felt ten years ago.

1622
01:18:23,479 --> 01:18:26,880
Speaker 8: Is glasses tell me like they're getting smaller, they're getting

1623
01:18:26,920 --> 01:18:30,639
Speaker 8: more capable. I'm seeing like glasses that are designed for navigation,

1624
01:18:30,840 --> 01:18:33,120
Speaker 8: that are designed for recording. I did see to what

1625
01:18:33,160 --> 01:18:35,439
Speaker 8: you were saying about politics. A lot of glasses with

1626
01:18:35,680 --> 01:18:38,960
Speaker 8: that were specifically marketed based on their ability to aid

1627
01:18:39,040 --> 01:18:41,519
Speaker 8: TikTok that I'm like in a week that might not be.

1628
01:18:41,560 --> 01:18:44,400
Speaker 5: Such a good business. Well, yeah, yeah, I had a

1629
01:18:44,479 --> 01:18:49,120
Speaker 5: full conversation with someone speaking Chinese. Yeah yeah, yeah, absolutely

1630
01:18:49,560 --> 01:18:50,040
Speaker 5: the same.

1631
01:18:49,960 --> 01:18:53,000
Speaker 2: King That is objectively very cool.

1632
01:18:53,080 --> 01:18:53,519
Speaker 5: It's great.

1633
01:18:53,800 --> 01:18:56,280
Speaker 2: And was it a conversation with Nuance like it was?

1634
01:18:56,760 --> 01:18:59,439
Speaker 5: Yeah, more than I'd have been able to do, you

1635
01:18:59,520 --> 01:19:03,599
Speaker 5: know on my before we talked about making specific specific

1636
01:19:03,640 --> 01:19:07,840
Speaker 5: dinner plans, what we do for work a real coper too.

1637
01:19:08,479 --> 01:19:10,920
Speaker 2: This is the thing that I I and I've said

1638
01:19:10,960 --> 01:19:14,200
Speaker 2: this many times in episodes. I'm not anti tech. I

1639
01:19:14,360 --> 01:19:16,719
Speaker 2: wish tech was able to do the thing they promised,

1640
01:19:16,760 --> 01:19:19,559
Speaker 2: but I love technology. The only reason I know literally

1641
01:19:19,760 --> 01:19:24,080
Speaker 2: every person I'm looking at in this room is through posting.

1642
01:19:25,560 --> 01:19:27,719
Speaker 2: And I'm not even kidding. And this is the sickening

1643
01:19:27,800 --> 01:19:30,240
Speaker 2: thing that upsets my father. No, my dad's very proud.

1644
01:19:30,560 --> 01:19:34,640
Speaker 2: My therapist kind of like my multiple lawyers. Anyway, the

1645
01:19:34,720 --> 01:19:37,160
Speaker 2: idea that one can do that, but the internet and

1646
01:19:37,360 --> 01:19:40,439
Speaker 2: tech is fully capable of making these wonderful connections like genuine.

1647
01:19:40,479 --> 01:19:42,680
Speaker 2: I laugh about the Robert Evans think he found me

1648
01:19:42,760 --> 01:19:45,280
Speaker 2: through a podcast called Western KOBOOKI with my friend Caleb

1649
01:19:45,320 --> 01:19:48,200
Speaker 2: Wilson June and other people who are wonderful Alex as well,

1650
01:19:48,280 --> 01:19:50,760
Speaker 2: like the great podcasts and these all digital things, tech

1651
01:19:50,880 --> 01:19:53,599
Speaker 2: is fully capable. As much as I can be cynical

1652
01:19:53,680 --> 01:19:56,200
Speaker 2: and angry about this stuff, the reason I'm fucking angry

1653
01:19:56,320 --> 01:19:59,559
Speaker 2: is it's fully capable of helping people. And we've all

1654
01:19:59,640 --> 01:20:00,439
Speaker 2: experien that.

1655
01:20:01,080 --> 01:20:03,040
Speaker 6: That was the bit that I sort of was struck

1656
01:20:03,080 --> 01:20:05,080
Speaker 6: by again as like sort of somebody who hasn't covered

1657
01:20:05,080 --> 01:20:07,680
Speaker 6: this stuff as much and has had sort of, you know,

1658
01:20:07,720 --> 01:20:10,599
Speaker 6: the same sort of experience like a normal middle aged

1659
01:20:10,680 --> 01:20:13,840
Speaker 6: person's experience of tech. I was blown away by the

1660
01:20:13,920 --> 01:20:16,720
Speaker 6: capacities of the things that were there. I mean, like

1661
01:20:16,920 --> 01:20:18,560
Speaker 6: I didn't realize that it was like you could have

1662
01:20:18,640 --> 01:20:20,479
Speaker 6: a conversation with someone speaking in other language.

1663
01:20:20,479 --> 01:20:22,080
Speaker 5: Like I didn't see anything that that cool.

1664
01:20:22,560 --> 01:20:24,800
Speaker 6: But the accessibility tech stuff for me too, Like I

1665
01:20:24,840 --> 01:20:29,000
Speaker 6: found not just really impressive but really like heartening to

1666
01:20:29,080 --> 01:20:31,400
Speaker 6: see that. The bit that was strange and we obviously,

1667
01:20:31,560 --> 01:20:33,519
Speaker 6: like we have talked about this in previous episodes and

1668
01:20:33,560 --> 01:20:38,800
Speaker 6: stuff is the sort of contortions that are required in

1669
01:20:39,000 --> 01:20:42,479
Speaker 6: order to make that marketable in a way that like

1670
01:20:42,600 --> 01:20:45,360
Speaker 6: it's not like it's not a niche market to be

1671
01:20:45,720 --> 01:20:48,000
Speaker 6: like an old person or to be disabled like one

1672
01:20:48,040 --> 01:20:51,000
Speaker 6: way or another. That's like most people will experience that

1673
01:20:51,080 --> 01:20:53,360
Speaker 6: at some point in there. Yeah, and yet like the

1674
01:20:53,439 --> 01:20:55,040
Speaker 6: way that you have to sort of this is something

1675
01:20:55,080 --> 01:20:57,599
Speaker 6: that really struck me from yesterday that we talked about,

1676
01:20:57,680 --> 01:20:59,280
Speaker 6: you know enough that I probably shouldn't be bring it

1677
01:20:59,360 --> 01:21:02,000
Speaker 6: back up again that like you still have to come

1678
01:21:02,080 --> 01:21:04,160
Speaker 6: up with some sort of like industrial application to it,

1679
01:21:04,360 --> 01:21:06,160
Speaker 6: or you have to say AI or you have to

1680
01:21:06,240 --> 01:21:07,600
Speaker 6: do this stuff that in order to get people to

1681
01:21:07,680 --> 01:21:10,800
Speaker 6: invest in this stuff, which is expensive to develop and

1682
01:21:10,920 --> 01:21:13,680
Speaker 6: expensive to produce, you have to say the words that

1683
01:21:13,840 --> 01:21:14,439
Speaker 6: the money.

1684
01:21:14,280 --> 01:21:15,439
Speaker 5: People want to hear.

1685
01:21:15,720 --> 01:21:17,720
Speaker 6: The mod which is also like another of the sort

1686
01:21:17,720 --> 01:21:20,600
Speaker 6: of political aspects here that you've got this like in

1687
01:21:20,720 --> 01:21:23,400
Speaker 6: some ways many in many ways like a sort of

1688
01:21:25,920 --> 01:21:27,640
Speaker 6: tempted not to use this word, but I will say

1689
01:21:27,680 --> 01:21:30,880
Speaker 6: that it is like a good hearted intention. It feels like,

1690
01:21:31,000 --> 01:21:33,360
Speaker 6: especially with the disability attech, that is like actually aimed

1691
01:21:33,400 --> 01:21:37,000
Speaker 6: at using this new human capability to make people's lives better.

1692
01:21:37,360 --> 01:21:39,080
Speaker 6: And yet you still have to fucking pitch it the

1693
01:21:39,160 --> 01:21:41,160
Speaker 6: sociopaths if you want to get the thing made.

1694
01:21:41,280 --> 01:21:44,320
Speaker 2: And I say this is someone who runs a fairly

1695
01:21:44,400 --> 01:21:47,360
Speaker 2: successful podcast. I have fifty one thousand subscribers. I have

1696
01:21:47,400 --> 01:21:50,200
Speaker 2: a successful be off them. I've had emails about this.

1697
01:21:50,439 --> 01:21:53,759
Speaker 2: I have dyspraxia, which is a coordination disability. It limits

1698
01:21:53,800 --> 01:21:56,760
Speaker 2: my I'm wearing zip up boots, which look I'll bang in,

1699
01:21:57,360 --> 01:22:00,280
Speaker 2: but I can't tie my shoes. And this is an

1700
01:22:00,280 --> 01:22:03,599
Speaker 2: embarrassing thing about my life. I fucking hate tying things.

1701
01:22:03,720 --> 01:22:05,479
Speaker 2: I physically can't do it. And you explain it to

1702
01:22:05,479 --> 01:22:08,160
Speaker 2: people and they laugh, which is really good with something

1703
01:22:08,200 --> 01:22:11,160
Speaker 2: that you're very upset about that people love to be

1704
01:22:11,280 --> 01:22:14,479
Speaker 2: laughed at for that. I don't think people realize the

1705
01:22:14,600 --> 01:22:19,040
Speaker 2: capacity for technology to bridge the gap between your own bodies.

1706
01:22:20,000 --> 01:22:22,240
Speaker 2: I don't want to say failure, but inability to fully

1707
01:22:22,280 --> 01:22:25,959
Speaker 2: complete an action. And I think people are myself included

1708
01:22:26,200 --> 01:22:30,559
Speaker 2: at times exactly, but technology is one of the greatest

1709
01:22:32,080 --> 01:22:35,240
Speaker 2: What was that you said again, Jesus Christ, assistive aid

1710
01:22:35,520 --> 01:22:40,680
Speaker 2: Thank you assistive aids. And I nearly fucked it up again. Nevertheless,

1711
01:22:41,080 --> 01:22:43,920
Speaker 2: technology for me is a person has been something that's

1712
01:22:43,920 --> 01:22:46,040
Speaker 2: allowed me to bridge with so many of you. I

1713
01:22:46,120 --> 01:22:49,120
Speaker 2: will tear up on the fucking show people. I love

1714
01:22:49,320 --> 01:22:51,720
Speaker 2: people that I've been able to experience through their own

1715
01:22:51,720 --> 01:22:56,360
Speaker 2: writing and connections to them. But most of CS isn't

1716
01:22:56,520 --> 01:23:00,640
Speaker 2: fucking this. It's about bridging gaps between my people and

1717
01:23:00,760 --> 01:23:03,360
Speaker 2: money people to another money person so they can sell

1718
01:23:03,479 --> 01:23:04,479
Speaker 2: nothing to nobody.

1719
01:23:05,080 --> 01:23:05,400
Speaker 5: Totally.

1720
01:23:05,520 --> 01:23:07,240
Speaker 8: Yeah, I mean that's one of the things that's disheartening

1721
01:23:07,320 --> 01:23:10,519
Speaker 8: is I was at like the Samsung booth, which is massive.

1722
01:23:10,600 --> 01:23:13,280
Speaker 8: You know, it's the size of a very large house,

1723
01:23:13,400 --> 01:23:17,080
Speaker 8: like a mansion, and every square foot is tens of

1724
01:23:17,160 --> 01:23:19,120
Speaker 8: thousands or hundreds of thousands of dollars in terms of

1725
01:23:19,160 --> 01:23:20,720
Speaker 8: what the cost to rent it and the cost to

1726
01:23:20,880 --> 01:23:23,559
Speaker 8: Like these displays they've got are very advanced. A lot

1727
01:23:23,640 --> 01:23:26,880
Speaker 8: of effort is just going into making the presentation as

1728
01:23:26,880 --> 01:23:29,559
Speaker 8: advanced as possible. And what I'm saying on display there

1729
01:23:29,640 --> 01:23:31,240
Speaker 8: is like, well, we've got a fridge that lets you

1730
01:23:31,280 --> 01:23:33,559
Speaker 8: know when your milk is off, and at the cost

1731
01:23:33,640 --> 01:23:35,360
Speaker 8: of you can never ever have a guy over to

1732
01:23:35,439 --> 01:23:37,400
Speaker 8: repair your fridge, never, never again.

1733
01:23:38,920 --> 01:23:41,840
Speaker 5: And you compare that too and Eureka Park.

1734
01:23:41,880 --> 01:23:43,519
Speaker 8: Today we saw a company who had a small booth

1735
01:23:43,600 --> 01:23:45,559
Speaker 8: that was maybe like four feet wide five feet wide

1736
01:23:45,640 --> 01:23:50,080
Speaker 8: called Knaki in a qi that their attempt was to

1737
01:23:50,240 --> 01:23:53,880
Speaker 8: develop like a way to allow people to control computers

1738
01:23:53,960 --> 01:23:57,040
Speaker 8: and interface with their machine with their phone in a

1739
01:23:57,080 --> 01:23:59,800
Speaker 8: way that is similar to how neuralink works, but without

1740
01:23:59,800 --> 01:24:00,799
Speaker 8: any sort of surgery.

1741
01:24:00,840 --> 01:24:02,400
Speaker 5: So it's an earpiece you wear in your head.

1742
01:24:03,280 --> 01:24:06,800
Speaker 2: Oh yeah, we kind of made fun of this, but

1743
01:24:06,920 --> 01:24:08,240
Speaker 2: if this is real, awesome.

1744
01:24:08,479 --> 01:24:12,080
Speaker 5: It seemed to like we like the use case.

1745
01:24:12,960 --> 01:24:15,080
Speaker 4: We like the use case for people who are not

1746
01:24:15,160 --> 01:24:18,360
Speaker 4: able bodied. But what happened when we came up to

1747
01:24:18,400 --> 01:24:20,479
Speaker 4: the booth, The first pitch we got was for retail,

1748
01:24:21,080 --> 01:24:27,120
Speaker 4: and then the interest in it was like, Noah, what's

1749
01:24:27,200 --> 01:24:30,400
Speaker 4: real is you can use this if you are someone

1750
01:24:30,439 --> 01:24:32,920
Speaker 4: who's not really able to use your arms or to

1751
01:24:33,000 --> 01:24:35,200
Speaker 4: move the rest of your body. You can slightly tilt

1752
01:24:35,240 --> 01:24:37,800
Speaker 4: it and that makes more sense than like being able

1753
01:24:37,840 --> 01:24:41,439
Speaker 4: to do a sort of like a retail cashier U

1754
01:24:41,640 --> 01:24:44,080
Speaker 4: secondary labor productivity aim.

1755
01:24:44,280 --> 01:24:46,719
Speaker 8: Yeah, I mean there was a because, like my mind

1756
01:24:46,840 --> 01:24:49,680
Speaker 8: was very much geared towards quadriplegics, but not just but

1757
01:24:49,760 --> 01:24:52,200
Speaker 8: the other because it won't work if you have as

1758
01:24:52,240 --> 01:24:55,280
Speaker 8: long as you have that muscular control like above your neck,

1759
01:24:55,439 --> 01:24:58,000
Speaker 8: like it will work because it reads micro gestures of

1760
01:24:58,120 --> 01:25:01,720
Speaker 8: your face and them the live demo they did, you

1761
01:25:01,760 --> 01:25:03,680
Speaker 8: could see the signal coming into the phone when he

1762
01:25:03,680 --> 01:25:05,679
Speaker 8: would make micro gestures and it would like it would

1763
01:25:05,800 --> 01:25:08,080
Speaker 8: you know, control the phone. So it's it seems like

1764
01:25:08,120 --> 01:25:09,800
Speaker 8: it works. I can also see I can't see like

1765
01:25:09,880 --> 01:25:12,599
Speaker 8: a retail app for like you've got your smart glasses

1766
01:25:12,640 --> 01:25:13,760
Speaker 8: while you're biking.

1767
01:25:13,640 --> 01:25:16,120
Speaker 2: Fucking works because we talked about it, it seemed to.

1768
01:25:16,600 --> 01:25:18,479
Speaker 5: But it's like, but it seemed I don't have the

1769
01:25:18,520 --> 01:25:20,880
Speaker 5: ability to like sound though they did.

1770
01:25:20,760 --> 01:25:23,719
Speaker 4: A conceptual yeah that so this is the thing because

1771
01:25:23,720 --> 01:25:25,519
Speaker 4: I think also there were three or four of them

1772
01:25:25,720 --> 01:25:26,240
Speaker 4: where it's.

1773
01:25:26,160 --> 01:25:28,680
Speaker 5: Like, yeah, there were there were variations.

1774
01:25:28,720 --> 01:25:30,800
Speaker 8: There was the one that was like almost like a

1775
01:25:31,120 --> 01:25:33,240
Speaker 8: retainer that you put in and it gave you the

1776
01:25:33,320 --> 01:25:35,120
Speaker 8: same It was a similar sort of idea.

1777
01:25:35,800 --> 01:25:38,360
Speaker 5: Yeah you use your sorry sorry, yeah you used your

1778
01:25:38,400 --> 01:25:38,760
Speaker 5: tongue for it.

1779
01:25:38,840 --> 01:25:40,439
Speaker 6: We were struck by that because it was a guy

1780
01:25:40,560 --> 01:25:43,000
Speaker 6: standing completely still with no expression on his face and

1781
01:25:43,040 --> 01:25:45,120
Speaker 6: a bunch of people standing around him recording them on

1782
01:25:45,200 --> 01:25:48,719
Speaker 6: their phones like this is like you've entered the daw Da.

1783
01:25:48,800 --> 01:25:50,720
Speaker 5: Section of the here Eureka Park.

1784
01:25:50,800 --> 01:25:54,080
Speaker 8: But but all of those booths together were like a

1785
01:25:54,200 --> 01:25:56,719
Speaker 8: tenth of Samsung's booth, and all of them were people

1786
01:25:57,040 --> 01:26:00,720
Speaker 8: utilizing significant ingenuity to attempt to solve problems For real

1787
01:26:00,840 --> 01:26:03,960
Speaker 8: human beings who were suffering as opposed to the Samsung booth,

1788
01:26:04,000 --> 01:26:08,160
Speaker 8: which was this massive edifice of capital attempting to solve

1789
01:26:08,200 --> 01:26:10,080
Speaker 8: the problem of like, well, what if your milk goes bad?

1790
01:26:10,760 --> 01:26:12,280
Speaker 4: Yeah, I know, and you know, and that's the thing

1791
01:26:12,320 --> 01:26:18,439
Speaker 4: I think also, you know, to this like inventive stuff

1792
01:26:18,560 --> 01:26:20,360
Speaker 4: was the most interesting of a few friends when you're

1793
01:26:20,800 --> 01:26:23,320
Speaker 4: degenerative diseases and like the you know, some of the

1794
01:26:23,360 --> 01:26:26,280
Speaker 4: stuff that gets made and offered to be able to

1795
01:26:26,280 --> 01:26:29,840
Speaker 4: give finer control over tasks that you need to do,

1796
01:26:31,000 --> 01:26:32,880
Speaker 4: especially when you have sudden jumpson what you're you know,

1797
01:26:33,040 --> 01:26:35,880
Speaker 4: you're able to do or not do very impressive. But

1798
01:26:35,960 --> 01:26:38,360
Speaker 4: then like kind of similar to what you were just saying,

1799
01:26:38,760 --> 01:26:41,759
Speaker 4: sometimes you actually you literally can't get that made unless

1800
01:26:41,800 --> 01:26:45,120
Speaker 4: you have to clonjure up some sort of secondary application,

1801
01:26:46,040 --> 01:26:49,040
Speaker 4: which is a shame and a problem with how tech

1802
01:26:49,080 --> 01:26:51,520
Speaker 4: innovation proceeds, right, because.

1803
01:26:51,280 --> 01:26:53,680
Speaker 2: You must show growth. You must be like this is

1804
01:26:53,800 --> 01:26:54,920
Speaker 2: how this is going.

1805
01:26:54,760 --> 01:26:58,000
Speaker 4: To tell There should be no reason why you have

1806
01:26:58,200 --> 01:27:03,320
Speaker 4: to consider anything other than that mediate and and an

1807
01:27:03,520 --> 01:27:06,200
Speaker 4: urgent use case, which is like someone losing the ability

1808
01:27:06,320 --> 01:27:09,200
Speaker 4: to communicate with the outside of regulatory avoidance.

1809
01:27:10,120 --> 01:27:14,240
Speaker 9: So from the earlier conversation we've had several times regarding

1810
01:27:14,600 --> 01:27:20,559
Speaker 9: regulatory power and authorized medical devices. So all of these

1811
01:27:20,600 --> 01:27:25,920
Speaker 9: products I have, I've sounded negative where you're trying to

1812
01:27:26,000 --> 01:27:31,280
Speaker 9: skirt and avoid these requirements. However, the agencies that certify

1813
01:27:31,439 --> 01:27:34,920
Speaker 9: them to want to help people. They want people to

1814
01:27:35,040 --> 01:27:37,800
Speaker 9: go through this process. So these are the things that

1815
01:27:38,160 --> 01:27:42,400
Speaker 9: the FDA loves to see. And it's hopeful.

1816
01:27:43,400 --> 01:27:46,479
Speaker 1: Yeah, I mean the I guess you talking about capital.

1817
01:27:46,560 --> 01:27:48,760
Speaker 3: I mean, the main worry is that if there's no

1818
01:27:49,120 --> 01:27:53,320
Speaker 3: growth opportunity for a product, then there's no investment, and

1819
01:27:53,640 --> 01:27:56,320
Speaker 3: and that's just it just kills products that have a

1820
01:27:56,800 --> 01:27:58,559
Speaker 3: one you know, use purpose.

1821
01:27:59,320 --> 01:28:01,320
Speaker 1: Uh and there that's all there is to it, because

1822
01:28:01,320 --> 01:28:02,479
Speaker 1: that's all there needs to be to it.

1823
01:28:03,320 --> 01:28:05,200
Speaker 3: And I think that's one thing that struck me as well,

1824
01:28:05,240 --> 01:28:08,000
Speaker 3: is everything needs to have beld and whistles that aren't

1825
01:28:08,439 --> 01:28:09,240
Speaker 3: usually necessary.

1826
01:28:09,600 --> 01:28:11,599
Speaker 2: So one of the themes I've discussed on this show

1827
01:28:11,720 --> 01:28:13,960
Speaker 2: is the rock economy, the idea that everything has growth

1828
01:28:14,120 --> 01:28:15,880
Speaker 2: or costs. And some of you, at the very beginning

1829
01:28:15,920 --> 01:28:19,559
Speaker 2: with very unfair, you're saying that he's just angry at nothing.

1830
01:28:20,240 --> 01:28:21,360
Speaker 2: I'm angry at everything.

1831
01:28:21,600 --> 01:28:23,519
Speaker 5: I love that when you do you Donald Trump voice.

1832
01:28:23,560 --> 01:28:27,759
Speaker 5: I can tell now I turn my head, but it's.

1833
01:28:29,120 --> 01:28:32,720
Speaker 2: I hope it's been obvious how pernicious this problem is

1834
01:28:32,840 --> 01:28:36,960
Speaker 2: because there are companies doing really useful things, and I

1835
01:28:37,040 --> 01:28:40,040
Speaker 2: talk about my dyspraxia because I don't know whatever platform

1836
01:28:40,080 --> 01:28:42,240
Speaker 2: I have. I want people to realize, if you fucking

1837
01:28:42,360 --> 01:28:44,200
Speaker 2: have this and someone makes fun of you, give me

1838
01:28:44,280 --> 01:28:48,799
Speaker 2: their email. I will personally make them regret being online.

1839
01:28:48,880 --> 01:28:50,920
Speaker 2: This is a personal thing. I was bullied, I will

1840
01:28:50,960 --> 01:28:54,920
Speaker 2: bully back, very unfair to them. But the point is

1841
01:28:55,200 --> 01:28:58,320
Speaker 2: there are real solutions, the real problems, real things being

1842
01:28:58,439 --> 01:29:01,280
Speaker 2: fixed today by companies that actually raising money. And then

1843
01:29:01,320 --> 01:29:05,559
Speaker 2: you've got the Samsung milk simulate that uses generative AI

1844
01:29:05,720 --> 01:29:08,160
Speaker 2: to assume when your milk won't go bad, as opposed

1845
01:29:08,200 --> 01:29:10,120
Speaker 2: to look into the fucking top and it'll bandar you

1846
01:29:10,200 --> 01:29:12,640
Speaker 2: a little bit, and the Bailey bought the Wooks and

1847
01:29:13,120 --> 01:29:14,880
Speaker 2: your milk has expired.

1848
01:29:15,720 --> 01:29:18,000
Speaker 8: I did see a product that I would say was

1849
01:29:18,080 --> 01:29:20,360
Speaker 8: my best in show in terms of products that you

1850
01:29:20,479 --> 01:29:22,680
Speaker 8: see an ad for in the first three minutes of

1851
01:29:22,720 --> 01:29:25,439
Speaker 8: a zombie movie and then it causes the outbreak and

1852
01:29:25,560 --> 01:29:28,120
Speaker 8: like that's the end of the world scenario, and it

1853
01:29:28,280 --> 01:29:35,400
Speaker 8: was called Vera Doxo. It's a product that generates a

1854
01:29:35,600 --> 01:29:41,680
Speaker 8: miss noise sweeps over your fruits and vegetables to stop.

1855
01:29:41,479 --> 01:29:47,040
Speaker 5: The most spoilt using plasma plasma. And here's the thing

1856
01:29:47,320 --> 01:29:48,160
Speaker 5: they explained this to me.

1857
01:29:48,200 --> 01:29:50,040
Speaker 8: They said, it extends the shelf life of like you

1858
01:29:50,120 --> 01:29:52,160
Speaker 8: can put this little box up and it'll it'll get

1859
01:29:52,240 --> 01:29:54,680
Speaker 8: the missed over groceries in your kitchen, or you can

1860
01:29:54,800 --> 01:29:57,120
Speaker 8: use it in like a in a grocery store to

1861
01:29:57,120 --> 01:29:58,599
Speaker 8: get all of the great and it'll extend the shelf

1862
01:29:58,640 --> 01:30:00,760
Speaker 8: life by thirty three percent. And that's a real thing

1863
01:30:01,120 --> 01:30:04,120
Speaker 8: that's massive, right, Like this, I have no ability to

1864
01:30:04,200 --> 01:30:06,760
Speaker 8: vet this based on what I know from Like I'm

1865
01:30:07,040 --> 01:30:08,479
Speaker 8: like absolutely no ability to bet.

1866
01:30:08,560 --> 01:30:11,360
Speaker 5: I'm gonna hat that missed I'm not I'm gonna huff

1867
01:30:11,400 --> 01:30:12,040
Speaker 5: that I did.

1868
01:30:12,160 --> 01:30:15,599
Speaker 8: Buddy, didn't get high, so tasteless as far as I'm

1869
01:30:15,760 --> 01:30:16,920
Speaker 8: so quick question anyone.

1870
01:30:17,000 --> 01:30:19,200
Speaker 6: It's like, if that's a shelf life of your vegetables

1871
01:30:19,320 --> 01:30:23,760
Speaker 6: leaves you glowing, youthful, ye, and then also like there's

1872
01:30:23,800 --> 01:30:27,400
Speaker 6: like a seventy percent chance you grow tail. Hey hey, hey,

1873
01:30:27,560 --> 01:30:32,640
Speaker 6: whoam Yeah you're trying to not sell Some people are

1874
01:30:33,200 --> 01:30:35,800
Speaker 6: that that's like the most innocuous, like that actually sounds good,

1875
01:30:35,840 --> 01:30:37,760
Speaker 6: like it's similar to something you would see and they just.

1876
01:30:37,880 --> 01:30:41,640
Speaker 5: Called it like like doom slayer, like but it's for

1877
01:30:41,760 --> 01:30:44,719
Speaker 5: your cucumbers, like we just we thought it sounded cool, volunteer.

1878
01:30:48,160 --> 01:30:52,200
Speaker 2: But also two things, Well, let's just focus on one,

1879
01:30:52,240 --> 01:30:56,639
Speaker 2: which is what the fuck does the miss what's made?

1880
01:30:57,720 --> 01:30:59,840
Speaker 8: The way they explained it is that it's a my

1881
01:31:00,240 --> 01:31:03,679
Speaker 8: and it kills before you actually get like molds starting

1882
01:31:03,720 --> 01:31:05,639
Speaker 8: to form. It kills them, so it extends a period

1883
01:31:05,680 --> 01:31:08,960
Speaker 8: of time the molds. It's so far just the mold,

1884
01:31:09,040 --> 01:31:10,960
Speaker 8: it's said. Because I asked if it was dangerous and

1885
01:31:11,120 --> 01:31:15,320
Speaker 8: they said no, I have no ability to visit the

1886
01:31:15,400 --> 01:31:17,880
Speaker 8: vera Ox people at this moment. I'm not trying to

1887
01:31:17,920 --> 01:31:21,120
Speaker 8: shit on that. Maybe this will massively improve the world, Okay,

1888
01:31:21,200 --> 01:31:24,280
Speaker 8: it just seemed like a product that caused the apocalypse,

1889
01:31:24,439 --> 01:31:26,920
Speaker 8: Like okay, that was when somebody said we.

1890
01:31:27,080 --> 01:31:30,920
Speaker 5: Make it agent vera Dux. This is like, oh, you're

1891
01:31:30,960 --> 01:31:32,320
Speaker 5: going to kill everyone I love.

1892
01:31:32,439 --> 01:31:36,839
Speaker 4: Okay, great, taking a wet market that's spread from a bag.

1893
01:31:38,040 --> 01:31:41,160
Speaker 2: So many nine inch nails fans here like a year

1894
01:31:41,360 --> 01:31:44,240
Speaker 2: zero I'm thinking of this is the big hand from

1895
01:31:44,240 --> 01:31:44,840
Speaker 2: the year zero.

1896
01:31:45,400 --> 01:31:47,880
Speaker 8: Yeah again, this scene right now could be the start

1897
01:31:47,960 --> 01:31:49,479
Speaker 8: of the Apocalypse movie, you know.

1898
01:31:49,600 --> 01:31:52,320
Speaker 5: Okay, one of us who's alive in three weeks like

1899
01:31:52,439 --> 01:31:54,439
Speaker 5: it is thinking back to this as they're fighting off

1900
01:31:54,520 --> 01:31:59,080
Speaker 5: viad ox. Use again to complain about the end of.

1901
01:31:59,560 --> 01:32:03,200
Speaker 2: Jiu Jitsu Kaisen, the manga, I'm going to just really

1902
01:32:03,280 --> 01:32:04,240
Speaker 2: put this in them.

1903
01:32:05,400 --> 01:32:07,320
Speaker 4: How did you want Jujitsu Kien to end?

1904
01:32:07,720 --> 01:32:12,439
Speaker 5: Okay, welcome? Did you want to get again? What you

1905
01:32:12,479 --> 01:32:13,639
Speaker 5: want going to take a break?

1906
01:32:13,920 --> 01:32:17,679
Speaker 2: Well, first of all, the people of the Jiu Jitsu

1907
01:32:17,960 --> 01:32:20,840
Speaker 2: High School thing, they do very unfair to mister Ryan

1908
01:32:20,920 --> 01:32:24,880
Speaker 2: and Suker All. They spend a lot of time building

1909
01:32:24,960 --> 01:32:28,479
Speaker 2: up abilities that do not manifest into an interest in

1910
01:32:28,920 --> 01:32:32,840
Speaker 2: these real people are these and I'm being very you

1911
01:32:33,000 --> 01:32:39,000
Speaker 2: made this podcast happen. Consequent the ending of Jiu Jitsu

1912
01:32:39,160 --> 01:32:42,120
Speaker 2: Kaisen involves a bit where Ryan mister Ryan and Sukiner

1913
01:32:43,040 --> 01:32:46,920
Speaker 2: mister Sto Go Joe. He's very unfairly treated. They show

1914
01:32:47,160 --> 01:32:49,760
Speaker 2: him winning a battle and then at the end of

1915
01:32:49,800 --> 01:32:55,559
Speaker 2: the battle he's dead. He's treated so unfair, and then

1916
01:32:55,640 --> 01:32:59,120
Speaker 2: it's just a simple dream sequence, which is very unfair.

1917
01:32:58,800 --> 01:33:05,000
Speaker 5: For Rigged, unfair for mister Ran and seeking now I'm thinking. Now,

1918
01:33:05,040 --> 01:33:15,040
Speaker 5: I'm thinking I have a different trumpet person. I am

1919
01:33:15,200 --> 01:33:17,280
Speaker 5: so sorry, I can see.

1920
01:33:18,360 --> 01:33:21,000
Speaker 2: I'm sorry that this is how David Roth feels about

1921
01:33:21,000 --> 01:33:25,240
Speaker 2: the Mets. So I'll move us back to the podcast

1922
01:33:25,400 --> 01:33:27,479
Speaker 2: as we wrap this bad Boy up.

1923
01:33:28,720 --> 01:33:32,439
Speaker 5: I have no ability to vet it based on the conversation.

1924
01:33:32,040 --> 01:33:35,680
Speaker 2: I have you never will. I genuinely want to thank

1925
01:33:35,720 --> 01:33:39,080
Speaker 2: everyone else in this room because we're doing another episode tomorrow.

1926
01:33:39,120 --> 01:33:42,439
Speaker 2: But this show has been conceptually one of the more

1927
01:33:42,520 --> 01:33:45,000
Speaker 2: insane things I have done, and I must give real

1928
01:33:45,120 --> 01:33:48,519
Speaker 2: credit to Sophie Lichtman, who is one of the hardest

1929
01:33:48,560 --> 01:33:52,080
Speaker 2: working and also most patient people in history.

1930
01:33:52,800 --> 01:33:56,720
Speaker 5: Oh yeah, and so oh yeah, she.

1931
01:33:56,960 --> 01:34:01,720
Speaker 2: Is the only person who can really move Robert oh yeah,

1932
01:34:01,760 --> 01:34:05,040
Speaker 2: who is one of the comment single most talented people

1933
01:34:05,080 --> 01:34:08,439
Speaker 2: I've met in my fucking life. And my comment there

1934
01:34:08,479 --> 01:34:11,800
Speaker 2: we go. And Robert turned to me a year ago

1935
01:34:12,000 --> 01:34:15,240
Speaker 2: and said, you seem to be more pissed off at

1936
01:34:15,280 --> 01:34:18,639
Speaker 2: these people than anyone And he was wrong, only because

1937
01:34:18,680 --> 01:34:21,559
Speaker 2: I was yet to get pissed off enough. Robert has

1938
01:34:21,640 --> 01:34:25,160
Speaker 2: been insanely supported of me in a creative means that

1939
01:34:25,240 --> 01:34:28,439
Speaker 2: no one else has, and honestly, everyone in this room

1940
01:34:28,520 --> 01:34:30,720
Speaker 2: has Geb turned to me and said, you seem to

1941
01:34:30,880 --> 01:34:35,920
Speaker 2: just be a series of grievances, and Gare was completely correct.

1942
01:34:36,640 --> 01:34:39,439
Speaker 5: It has been so fun hearing you get progressively more

1943
01:34:39,640 --> 01:34:43,400
Speaker 5: angry over the course of a year. It's it's been

1944
01:34:43,439 --> 01:34:45,840
Speaker 5: a real treasure and I mean it sincerely.

1945
01:34:46,040 --> 01:34:48,200
Speaker 2: I say this as someone who is a pair of yours.

1946
01:34:48,680 --> 01:34:51,280
Speaker 2: The work you make seems to get better every episode,

1947
01:34:51,280 --> 01:34:52,760
Speaker 2: and you're incredible at it. Thank you so much.

1948
01:34:52,760 --> 01:34:54,880
Speaker 8: You're getting none of this, Robert, You're just very good around.

1949
01:34:54,960 --> 01:34:57,920
Speaker 8: I say this as someone who is profiting off of you.

1950
01:34:58,000 --> 01:34:58,839
Speaker 8: Are you in a stanton?

1951
01:34:59,120 --> 01:35:01,400
Speaker 5: Should we should we make what that is like just

1952
01:35:01,479 --> 01:35:04,200
Speaker 5: hard medication. I'm just I'm just worried, dude.

1953
01:35:04,280 --> 01:35:06,840
Speaker 2: I am like the healthiest I've ever been, Like my

1954
01:35:06,960 --> 01:35:09,320
Speaker 2: v O two Max is like doing well, like and

1955
01:35:09,479 --> 01:35:11,400
Speaker 2: my dog just really happy. They don't know what I

1956
01:35:11,479 --> 01:35:12,639
Speaker 2: did ever since.

1957
01:35:12,439 --> 01:35:20,240
Speaker 5: I got a via dox. And that's another Cees miracle,

1958
01:35:21,400 --> 01:35:25,479
Speaker 5: which which leads which leads me to the which leads

1959
01:35:25,479 --> 01:35:27,760
Speaker 5: me to the last thing that I'll say is the

1960
01:35:28,000 --> 01:35:31,400
Speaker 5: first thing we all said on episode one is this

1961
01:35:31,560 --> 01:35:34,519
Speaker 5: feels like the Cees from last year, and we're not

1962
01:35:34,560 --> 01:35:38,040
Speaker 5: the only ones to think true last night, I was

1963
01:35:38,240 --> 01:35:41,559
Speaker 5: at the chandelier in the Cosmo. That is the place.

1964
01:35:41,720 --> 01:35:43,720
Speaker 5: Now we can write off the drinks and thank you.

1965
01:35:43,840 --> 01:35:46,960
Speaker 5: There we go and Robert I was sitting at the

1966
01:35:47,000 --> 01:35:49,120
Speaker 5: bar and Robert was upstairs waiting for a table and

1967
01:35:49,479 --> 01:35:53,280
Speaker 5: we got a table. Hard to do, and I said,

1968
01:35:53,640 --> 01:35:56,920
Speaker 5: it's another Cees miracle. There's a There was two people

1969
01:35:56,920 --> 01:36:00,160
Speaker 5: sitting next to me who turned was like, what's see, yes,

1970
01:36:00,280 --> 01:36:03,360
Speaker 5: or there was two people sitting next to me who

1971
01:36:03,520 --> 01:36:06,920
Speaker 5: turned and said, what Cees are you going to? This

1972
01:36:07,120 --> 01:36:11,760
Speaker 5: is this has been terrible and I I had a great,

1973
01:36:12,000 --> 01:36:16,200
Speaker 5: if if brief conversation with these people who were two exhibitors.

1974
01:36:16,439 --> 01:36:18,560
Speaker 5: Now I was a bad journalist, I was, I was

1975
01:36:18,600 --> 01:36:22,320
Speaker 5: too drunk. I did not I did not learn which

1976
01:36:22,360 --> 01:36:25,200
Speaker 5: company they were from. But there were two people who

1977
01:36:25,240 --> 01:36:28,680
Speaker 5: were exhibiting a CES and like, this feels just like

1978
01:36:28,760 --> 01:36:31,800
Speaker 5: last year's Cees. I was like, yes, this is what

1979
01:36:31,920 --> 01:36:34,000
Speaker 5: me and all my friends have been saying, like it is.

1980
01:36:34,640 --> 01:36:36,880
Speaker 5: It has been so disappointing. And it's not just us,

1981
01:36:37,080 --> 01:36:40,400
Speaker 5: like you know, somewhat tech critical journalists. It's people who

1982
01:36:40,479 --> 01:36:44,040
Speaker 5: actually like go to Cees to present who are saying

1983
01:36:44,080 --> 01:36:46,640
Speaker 5: the exact same thing. Like, yeah, this is this is

1984
01:36:46,760 --> 01:36:50,920
Speaker 5: last year's CES, but worse because there's nothing new. Yeah,

1985
01:36:50,920 --> 01:36:54,640
Speaker 5: and and this is like I did not feed them this.

1986
01:36:55,080 --> 01:36:57,519
Speaker 5: They turned to me and said this like unprompted, and

1987
01:36:57,560 --> 01:37:00,680
Speaker 5: they're like, what kind of miracles are you seeing? Like no, no, no, no,

1988
01:37:00,800 --> 01:37:02,640
Speaker 5: no no, that was sarcastic.

1989
01:37:03,960 --> 01:37:06,439
Speaker 8: It's remarkable to see. And David, I'm gonn guess yournees

1990
01:37:06,439 --> 01:37:09,680
Speaker 8: are about as bad as mine. But starting out in

1991
01:37:09,720 --> 01:37:13,000
Speaker 8: twenty ten, like right after kind of the iPad came out,

1992
01:37:13,280 --> 01:37:15,320
Speaker 8: there was so much excitement every year of like I'd

1993
01:37:15,360 --> 01:37:17,400
Speaker 8: never seen a thing that could do this. Every year,

1994
01:37:17,439 --> 01:37:19,280
Speaker 8: I'd never seen a thing that could do like and

1995
01:37:19,320 --> 01:37:21,280
Speaker 8: I would that would be every like room I walked

1996
01:37:21,280 --> 01:37:23,160
Speaker 8: into every like thirty minutes, I would see a thing

1997
01:37:23,240 --> 01:37:25,640
Speaker 8: that was like I didn't know technology could do that

1998
01:37:25,760 --> 01:37:26,840
Speaker 8: until this exact second.

1999
01:37:27,479 --> 01:37:29,920
Speaker 5: And that's just not CS anymore.

2000
01:37:31,439 --> 01:37:33,280
Speaker 6: Yeah, I mean it's like even as like a soft

2001
01:37:33,320 --> 01:37:35,040
Speaker 6: touch you can be impressed by, like a cool new

2002
01:37:35,080 --> 01:37:37,720
Speaker 6: TV screen. It's not the first TV screen, you know,

2003
01:37:37,880 --> 01:37:41,000
Speaker 6: not to brag, but there is like, yeah, there's certainly

2004
01:37:41,080 --> 01:37:43,040
Speaker 6: that sense. It's interesting that like the people that are

2005
01:37:43,120 --> 01:37:45,519
Speaker 6: showing here were also kind of like what am I doing?

2006
01:37:45,680 --> 01:37:46,880
Speaker 5: Like, I feel what am I doing here?

2007
01:37:47,400 --> 01:37:50,920
Speaker 2: Yeah? I think the and what batt Roughline has tried

2008
01:37:50,960 --> 01:37:54,280
Speaker 2: to do with this entire show is CS is a

2009
01:37:54,320 --> 01:37:56,680
Speaker 2: combination of people who don't want to be here and

2010
01:37:56,800 --> 01:37:58,080
Speaker 2: do want to be here, And a lot of the

2011
01:37:58,080 --> 01:37:59,400
Speaker 2: people that want to be here are the people that

2012
01:37:59,439 --> 01:38:02,200
Speaker 2: already live here to sell services to those who are visiting.

2013
01:38:03,160 --> 01:38:07,280
Speaker 2: But the fundamental problem with CES is that the show

2014
01:38:07,360 --> 01:38:10,400
Speaker 2: itself doesn't seem to be serving the use case of

2015
01:38:10,560 --> 01:38:13,720
Speaker 2: making things happen in the future. It's like, how can

2016
01:38:13,760 --> 01:38:18,200
Speaker 2: we make the present continue for longer? Yes? And the

2017
01:38:18,320 --> 01:38:20,240
Speaker 2: thing is something I've tried to do with this, and

2018
01:38:20,320 --> 01:38:23,960
Speaker 2: I should be clear about what this is. Everything you're

2019
01:38:24,000 --> 01:38:26,120
Speaker 2: hearing this week is something I came up with about

2020
01:38:26,760 --> 01:38:29,719
Speaker 2: five weeks ago. I wanted to do this. I booked

2021
01:38:29,760 --> 01:38:33,120
Speaker 2: this months ago, Robert then booked much later. It could

2022
01:38:33,160 --> 01:38:35,240
Speaker 2: happen here, and Robert, please get it.

2023
01:38:35,400 --> 01:38:38,840
Speaker 5: I was hungover at all. He is.

2024
01:38:38,880 --> 01:38:43,240
Speaker 2: Actually, Sophie is so much stronger willed, and that's very true,

2025
01:38:43,360 --> 01:38:47,080
Speaker 2: willing to respond. But Robert has been an incredible mentor.

2026
01:38:47,120 --> 01:38:49,240
Speaker 2: And I'm going to be sentimental and you're just gonna

2027
01:38:49,280 --> 01:38:51,320
Speaker 2: have to fucking suck it up. All Right, We're an

2028
01:38:51,720 --> 01:38:54,800
Speaker 2: award nominated podcast. I can do whatever the hell I want.

2029
01:38:55,400 --> 01:38:59,200
Speaker 2: But what I think this show needs going forward is

2030
01:38:59,320 --> 01:39:02,080
Speaker 2: more independent voices. And it means bringing in people like

2031
01:39:02,200 --> 01:39:05,479
Speaker 2: Kyle from Las Vegas Suck and allowing them to speak

2032
01:39:05,640 --> 01:39:08,320
Speaker 2: because it isn't so much. The problem these journalists can't

2033
01:39:08,320 --> 01:39:10,920
Speaker 2: say what they want is that formats demand things in

2034
01:39:11,080 --> 01:39:14,120
Speaker 2: certain ways, and the way to talk about tech is

2035
01:39:14,240 --> 01:39:17,680
Speaker 2: no longer as flat as and the product exists or

2036
01:39:18,000 --> 01:39:22,680
Speaker 2: tech company sucks. I can do both, but the thing

2037
01:39:22,840 --> 01:39:26,719
Speaker 2: is having these different voices, having these people talk about

2038
01:39:26,760 --> 01:39:30,120
Speaker 2: their experience of CS is on some level an explanation

2039
01:39:30,240 --> 01:39:32,519
Speaker 2: of how the tech industry feels. They're in this thing

2040
01:39:32,560 --> 01:39:36,560
Speaker 2: where you have this dichotomy between this vast millieaure of

2041
01:39:36,680 --> 01:39:39,320
Speaker 2: different things that are like, hey, what if this happened,

2042
01:39:40,040 --> 01:39:43,120
Speaker 2: you'd then give me money. What would that be? Like, Well,

2043
01:39:43,160 --> 01:39:45,240
Speaker 2: I'd have the money, and then you'd have the product

2044
01:39:45,360 --> 01:39:47,479
Speaker 2: and did something good happen?

2045
01:39:47,960 --> 01:39:48,120
Speaker 6: Oh?

2046
01:39:48,200 --> 01:39:50,360
Speaker 2: I don't care. And then you have these people like

2047
01:39:50,520 --> 01:39:55,360
Speaker 2: I'm gonna fucking solve people with eye twitches, people with

2048
01:39:55,560 --> 01:39:57,680
Speaker 2: twitching in their eye, which turns out to be a

2049
01:39:57,800 --> 01:40:01,599
Speaker 2: huge industry of people who are genuinely fucking suffering people

2050
01:40:01,680 --> 01:40:05,040
Speaker 2: with way bigger problems, like mobility problems, having that problem

2051
01:40:05,160 --> 01:40:07,240
Speaker 2: solved in real time. But the people that get talked

2052
01:40:07,240 --> 01:40:10,840
Speaker 2: about I have the most massive television, and no, I

2053
01:40:10,920 --> 01:40:11,880
Speaker 2: actually take that back.

2054
01:40:12,880 --> 01:40:14,080
Speaker 5: It's not even the big TV.

2055
01:40:14,320 --> 01:40:16,360
Speaker 2: I want a larger TV. I want like a two

2056
01:40:16,479 --> 01:40:19,800
Speaker 2: hundred and fifty inch fucker. I want to watch the

2057
01:40:20,000 --> 01:40:20,960
Speaker 2: Raiders lose.

2058
01:40:22,439 --> 01:40:23,240
Speaker 5: Well that was so.

2059
01:40:23,560 --> 01:40:25,360
Speaker 8: I had a moment at the Samsung with and they

2060
01:40:25,360 --> 01:40:27,160
Speaker 8: were showing off one of those transparent TVs and there

2061
01:40:27,200 --> 01:40:29,320
Speaker 8: was a lady who's hold another one another one.

2062
01:40:29,400 --> 01:40:32,160
Speaker 5: Well, I'm probably the same was No, that was LG.

2063
01:40:32,360 --> 01:40:34,160
Speaker 2: Last year it was LG.

2064
01:40:34,280 --> 01:40:36,640
Speaker 5: Yeah, I think it was LG. Yeah, yeah, I it

2065
01:40:36,720 --> 01:40:37,439
Speaker 5: all blurs together.

2066
01:40:37,520 --> 01:40:39,760
Speaker 8: There was a lady behind a transparent TV whose whole

2067
01:40:39,840 --> 01:40:42,240
Speaker 8: job was when the TV went transparent, to waverhand behind it,

2068
01:40:42,320 --> 01:40:42,760
Speaker 8: and I was like.

2069
01:40:42,840 --> 01:40:43,720
Speaker 5: That's that's your job.

2070
01:40:44,960 --> 01:40:48,479
Speaker 8: And it was this recognition as they're like walking as

2071
01:40:48,520 --> 01:40:50,679
Speaker 8: we Garrison and I sat through a guy who played

2072
01:40:50,720 --> 01:40:52,920
Speaker 8: us Ai generated Scot and tried to convince this that

2073
01:40:53,000 --> 01:40:58,919
Speaker 8: we did we know a lot. They needed musicians, even great.

2074
01:41:00,439 --> 01:41:01,880
Speaker 5: I would know No.

2075
01:41:02,280 --> 01:41:06,800
Speaker 8: The next time someone played that is a situation it was.

2076
01:41:07,040 --> 01:41:10,680
Speaker 8: It is very much a following down situation, yes, but

2077
01:41:10,840 --> 01:41:13,759
Speaker 8: the realization that, like there is a chunk of guys

2078
01:41:14,320 --> 01:41:17,400
Speaker 8: running big tech who will see holding your hand behind

2079
01:41:17,400 --> 01:41:20,040
Speaker 8: the transparent TV is a thing that human beings should do,

2080
01:41:20,600 --> 01:41:24,400
Speaker 8: but not making music, and like that that upsets me.

2081
01:41:25,720 --> 01:41:32,000
Speaker 2: It's just it's frustrating because entering into this and the

2082
01:41:32,160 --> 01:41:35,240
Speaker 2: format that I created in a Google dog three weeks ago,

2083
01:41:35,280 --> 01:41:39,200
Speaker 2: and some of some people even read it. Uh. The

2084
01:41:39,320 --> 01:41:42,720
Speaker 2: goal was to try and pull out how the show

2085
01:41:42,760 --> 01:41:45,400
Speaker 2: affects people and indeed the implications of this show do.

2086
01:41:46,479 --> 01:41:48,920
Speaker 2: I'm now going to return to the sentimental bit I

2087
01:41:49,040 --> 01:41:51,960
Speaker 2: was diverted by. I want to thank every single fucking

2088
01:41:52,000 --> 01:41:54,519
Speaker 2: person who listened to this but also joined me on this.

2089
01:41:55,479 --> 01:42:00,040
Speaker 2: Gare Davis one of these single insanely young and in

2090
01:42:00,120 --> 01:42:04,320
Speaker 2: a non specific way, I realize the single most talented

2091
01:42:04,400 --> 01:42:08,160
Speaker 2: person to come into anything associated with tech, insanely young,

2092
01:42:08,240 --> 01:42:12,080
Speaker 2: but also is insanely presient and aware of the social

2093
01:42:12,240 --> 01:42:15,800
Speaker 2: issues but also the context of basically everything they look at.

2094
01:42:16,439 --> 01:42:22,599
Speaker 2: Robert Evans the single most focused but disorganized person I've

2095
01:42:22,640 --> 01:42:25,800
Speaker 2: ever met, but also someone who cares so deeply and

2096
01:42:26,080 --> 01:42:31,360
Speaker 2: has such an innate talent at finding talent and empowering

2097
01:42:31,439 --> 01:42:34,240
Speaker 2: those voices. Without Robert Evans, I would not have done this,

2098
01:42:34,400 --> 01:42:36,680
Speaker 2: and I did try and like wave him off when

2099
01:42:36,720 --> 01:42:38,800
Speaker 2: he offered the podcast to me, I was like, yeah, mate,

2100
01:42:38,880 --> 01:42:41,640
Speaker 2: show you a fucking budget down even is in the

2101
01:42:41,720 --> 01:42:44,320
Speaker 2: actual jack off gesture in front of the computer. Robert

2102
01:42:44,479 --> 01:42:47,240
Speaker 2: and Sophie Lichtman, who will never get enough compliments and

2103
01:42:47,320 --> 01:42:50,560
Speaker 2: by the way, universal law with better offline. If you

2104
01:42:50,600 --> 01:42:54,240
Speaker 2: don't love Sophie, I will fucking kill you, not literally,

2105
01:42:54,360 --> 01:42:58,880
Speaker 2: but I will think about it very fucking aggressively. Robert

2106
01:42:59,120 --> 01:43:02,200
Speaker 2: has actually have faith in me that most people haven't,

2107
01:43:02,280 --> 01:43:04,680
Speaker 2: and the result is a fucking successful tech podcast that

2108
01:43:04,800 --> 01:43:07,320
Speaker 2: does things more successfully than most of the tech podcasts

2109
01:43:07,400 --> 01:43:12,760
Speaker 2: out there. Otherwise, Robert supports Gare, who has been so

2110
01:43:13,000 --> 01:43:15,600
Speaker 2: incredible and will do better work than I will ever do.

2111
01:43:16,320 --> 01:43:18,560
Speaker 2: But you know what, that's what doing good ship is

2112
01:43:18,720 --> 01:43:20,280
Speaker 2: knowing the people who do things well.

2113
01:43:20,560 --> 01:43:22,679
Speaker 8: What I've been really excited about this year is getting

2114
01:43:22,720 --> 01:43:25,960
Speaker 8: to meet David and Edward and now getting this is

2115
01:43:25,960 --> 01:43:27,400
Speaker 8: the first time we're in a room together.

2116
01:43:27,240 --> 01:43:28,519
Speaker 1: But it's not we talked yesterday.

2117
01:43:28,680 --> 01:43:32,360
Speaker 5: Oh Ship, I was so drunk, So sorry Kyle during

2118
01:43:32,400 --> 01:43:35,920
Speaker 5: the panel, During the panel the disinformation, Oh no, no,

2119
01:43:36,040 --> 01:43:36,240
Speaker 5: I was.

2120
01:43:36,320 --> 01:43:42,160
Speaker 8: I was just just high on mushrooms. Oh okay, and

2121
01:43:42,360 --> 01:43:43,880
Speaker 8: I've got some creative still in my part.

2122
01:43:44,520 --> 01:43:44,920
Speaker 4: I'm okay.

2123
01:43:45,640 --> 01:43:54,439
Speaker 2: I was trying to do like a sincere moment. Now

2124
01:43:54,560 --> 01:43:56,200
Speaker 2: let Robert finish his fucking thing.

2125
01:43:56,320 --> 01:43:58,360
Speaker 8: I was just saying, like, it's been very exciting to

2126
01:43:58,439 --> 01:44:00,439
Speaker 8: get to meet these folks, some of whom I had

2127
01:44:00,520 --> 01:44:02,160
Speaker 8: been reading for a while, or some of Moore. I'm

2128
01:44:02,160 --> 01:44:04,320
Speaker 8: excited to start reading and get to like make these

2129
01:44:04,360 --> 01:44:07,639
Speaker 8: connections because in a cees that is so anti human.

2130
01:44:07,720 --> 01:44:09,439
Speaker 8: It's nice to make connections to people.

2131
01:44:09,760 --> 01:44:13,600
Speaker 2: And I'm about to harpoon you with sincerity. Robert and

2132
01:44:13,760 --> 01:44:16,560
Speaker 2: Sophie have been the single and geare as well have

2133
01:44:16,720 --> 01:44:20,720
Speaker 2: been the most single supportive creatives I've ever fucking worked

2134
01:44:20,760 --> 01:44:24,160
Speaker 2: with my in life. I have had issues with believing

2135
01:44:24,200 --> 01:44:26,439
Speaker 2: in myself and believing what I can do. I have talent, whatever,

2136
01:44:26,560 --> 01:44:28,519
Speaker 2: Like who fucking cares? Email me? You're mad were you're

2137
01:44:28,520 --> 01:44:32,559
Speaker 2: listening to this little pig? But the thing is these

2138
01:44:32,640 --> 01:44:35,519
Speaker 2: people beyond when even a year ago, I didn't think

2139
01:44:35,560 --> 01:44:37,280
Speaker 2: I could fucking do this, And now look at me.

2140
01:44:37,320 --> 01:44:43,120
Speaker 2: I'm a fucking ultra ponce and it rocks. And I

2141
01:44:43,200 --> 01:44:45,640
Speaker 2: believe what cool Zone Media does is the future of

2142
01:44:46,240 --> 01:44:49,920
Speaker 2: fucking creativity. The idea that a big corporation can give

2143
01:44:50,000 --> 01:44:52,439
Speaker 2: someone multiple seasons to work out their audience and work

2144
01:44:52,479 --> 01:44:54,560
Speaker 2: out what they're building. You look at it behind the

2145
01:44:54,600 --> 01:44:59,320
Speaker 2: bustards could happen here, sixteenth minute politics, cool people who

2146
01:44:59,360 --> 01:45:02,200
Speaker 2: did cool stuf. There is so much cool shit that

2147
01:45:02,320 --> 01:45:04,320
Speaker 2: comes out of the idea of damn, what if you

2148
01:45:04,439 --> 01:45:08,879
Speaker 2: give people more time to build something than seven minutes?

2149
01:45:09,840 --> 01:45:12,639
Speaker 2: What if you didn't rush them to make something good? Better?

2150
01:45:12,640 --> 01:45:15,479
Speaker 2: Offline at the beginning was fucking rough, but we worked

2151
01:45:15,520 --> 01:45:17,920
Speaker 2: it out and you people seem to like it, and

2152
01:45:18,000 --> 01:45:19,920
Speaker 2: the people in this room are fucking adored. But don't

2153
01:45:19,920 --> 01:45:23,439
Speaker 2: We're not done. Phil Broughton over there feel brought in

2154
01:45:23,520 --> 01:45:26,759
Speaker 2: health physicist East picked me up two or three times,

2155
01:45:27,320 --> 01:45:29,920
Speaker 2: and I've been like shaping my pants, not literally, I've

2156
01:45:29,960 --> 01:45:31,960
Speaker 2: never shipped my pants around you. Let's not talk about

2157
01:45:32,000 --> 01:45:34,680
Speaker 2: that further. But the truth is Phil has been here

2158
01:45:34,720 --> 01:45:40,320
Speaker 2: for multiple CS's tending bar, grabbed the Mikey motherfucker tending

2159
01:45:40,360 --> 01:45:42,439
Speaker 2: bar for people and utimately doing the thing of asking

2160
01:45:42,520 --> 01:45:45,920
Speaker 2: them why they are here. I think that is the

2161
01:45:46,000 --> 01:45:48,960
Speaker 2: most valuable thing you can do in the consumer electronics show,

2162
01:45:49,040 --> 01:45:52,760
Speaker 2: asking people the reason they are there and finding out

2163
01:45:52,880 --> 01:45:55,360
Speaker 2: what it is they actually fucking cared about. And you

2164
01:45:55,479 --> 01:45:58,479
Speaker 2: do that so well while also serving various bourbons. And

2165
01:45:58,560 --> 01:46:01,639
Speaker 2: I was even like a man he replaced them.

2166
01:46:01,840 --> 01:46:04,680
Speaker 9: And I like this one, by the way, one of

2167
01:46:04,720 --> 01:46:07,960
Speaker 9: my that would be a part of Premium uh cass

2168
01:46:08,040 --> 01:46:12,400
Speaker 9: prank Thryer. That was a goddamn journey that made fury

2169
01:46:12,520 --> 01:46:14,040
Speaker 9: for weeks finding it film.

2170
01:46:14,720 --> 01:46:17,560
Speaker 2: I love you, I love all of you, seriously. Thank you.

2171
01:46:18,160 --> 01:46:20,680
Speaker 9: One of the things that made me happy is for

2172
01:46:20,840 --> 01:46:23,479
Speaker 9: everyone that I picked up at an elevator. By the

2173
01:46:23,560 --> 01:46:25,840
Speaker 9: time we'd hit the twenty eighth floor, I knew what

2174
01:46:25,920 --> 01:46:26,600
Speaker 9: I was serving you.

2175
01:46:27,120 --> 01:46:30,600
Speaker 2: Thank you so much, ma'am. David Roth. David Roth is

2176
01:46:30,680 --> 01:46:31,519
Speaker 2: someone I brought here.

2177
01:46:32,200 --> 01:46:35,639
Speaker 5: No take the fucking mic. You grab the goddamn mike.

2178
01:46:35,680 --> 01:46:37,280
Speaker 2: I will shove it in you out. We all know

2179
01:46:37,439 --> 01:46:43,960
Speaker 2: how good I am ed, which is why it's necessary

2180
01:46:44,000 --> 01:46:48,240
Speaker 2: to remind people. David Roth is the is actually my

2181
01:46:48,320 --> 01:46:52,240
Speaker 2: favorite writer, and he is one of the single most

2182
01:46:52,280 --> 01:46:55,720
Speaker 2: empathetic people who understands why people enjoy stuff, and his

2183
01:46:55,840 --> 01:46:59,320
Speaker 2: sports writing and cultural writing is genuinely influential over everything

2184
01:46:59,360 --> 01:47:02,160
Speaker 2: I've ever done. And I'm absolutely going self indulgent. There's

2185
01:47:02,160 --> 01:47:04,200
Speaker 2: nothing a single fucking person in this room could do it.

2186
01:47:04,240 --> 01:47:07,559
Speaker 2: Mattasowski is just sitting there being like, yeah, vacuuming up.

2187
01:47:07,920 --> 01:47:11,200
Speaker 2: But David Roth being here is like watching the movies

2188
01:47:11,280 --> 01:47:15,080
Speaker 2: with eBAM and it's genuinely I'm getting a little emotional.

2189
01:47:15,600 --> 01:47:18,960
Speaker 5: But thank you, David, and thanks for having me. For real,

2190
01:47:19,120 --> 01:47:20,000
Speaker 5: I feel the same.

2191
01:47:20,400 --> 01:47:24,960
Speaker 2: Edward Graso Junior. You are an undiscovered talent and anyone

2192
01:47:25,080 --> 01:47:26,880
Speaker 2: fortunate enough to listen to this should now they should

2193
01:47:26,960 --> 01:47:31,439
Speaker 2: hire you immediately because when you finally take off, when

2194
01:47:31,439 --> 01:47:33,920
Speaker 2: you finally get big enough, you are the single most

2195
01:47:34,000 --> 01:47:35,280
Speaker 2: capable grab the microphone.

2196
01:47:35,320 --> 01:47:37,400
Speaker 4: Motherfucker, hello, I said, when I get my gun.

2197
01:47:40,400 --> 01:47:42,519
Speaker 2: Okay, let's walk back to the guy.

2198
01:47:43,760 --> 01:47:46,479
Speaker 4: Okay, let's cut that out on the words, my.

2199
01:47:47,680 --> 01:47:49,400
Speaker 5: Matt, this is still keep it in.

2200
01:47:49,560 --> 01:47:51,559
Speaker 2: But just to be clear, the gun was a metaphor

2201
01:47:51,760 --> 01:47:53,919
Speaker 2: right for my potential.

2202
01:47:58,880 --> 01:48:01,960
Speaker 5: I'm really trying. Sorry, no more, no more.

2203
01:48:03,360 --> 01:48:08,720
Speaker 2: I know You're not done, ed there are there really

2204
01:48:08,800 --> 01:48:10,519
Speaker 2: isn't not the right that it can do the kind

2205
01:48:10,560 --> 01:48:13,439
Speaker 2: of labor reporting you do and the understanding of the

2206
01:48:13,479 --> 01:48:15,720
Speaker 2: human experience that you can do. You are just at

2207
01:48:15,720 --> 01:48:18,920
Speaker 2: the beginning, and I can't wait to bring you back

2208
01:48:18,960 --> 01:48:21,639
Speaker 2: on this show and have you do more. I love

2209
01:48:21,680 --> 01:48:24,920
Speaker 2: all of you so much. But also, your potential is barey.

2210
01:48:25,080 --> 01:48:27,439
Speaker 2: You are, your potential is barely getting started. Is some

2211
01:48:27,640 --> 01:48:29,360
Speaker 2: ship you'd see on a CS banner.

2212
01:48:29,400 --> 01:48:31,559
Speaker 5: Though, this is the worst.

2213
01:48:33,920 --> 01:48:35,120
Speaker 4: This is the worst I'll ever be.

2214
01:48:36,640 --> 01:48:37,120
Speaker 5: That's right.

2215
01:48:37,760 --> 01:48:40,120
Speaker 2: That's right, brother, That's why I put on a hinge

2216
01:48:43,000 --> 01:48:46,519
Speaker 2: that I actually might put that on hinge. Any any

2217
01:48:46,640 --> 01:48:49,040
Speaker 2: singles want to email me like, that's what's.

2218
01:48:48,840 --> 01:48:51,200
Speaker 5: On, darling. I know I've vomited in your car, but

2219
01:48:51,320 --> 01:48:53,559
Speaker 5: let me assure you this is the worst I'm ever

2220
01:48:53,720 --> 01:48:54,080
Speaker 5: gonna be.

2221
01:48:57,280 --> 01:49:01,960
Speaker 2: Oh my god, you may think I just meant you,

2222
01:49:02,040 --> 01:49:05,519
Speaker 2: so that's true. You came on this show completely, You

2223
01:49:05,560 --> 01:49:08,320
Speaker 2: were actually well prepared. You had a laptop out, which

2224
01:49:08,400 --> 01:49:12,160
Speaker 2: fucking rocks. You actually like took this seriously much like

2225
01:49:12,320 --> 01:49:14,320
Speaker 2: I did with my laptop. Glad that I don't have

2226
01:49:14,520 --> 01:49:19,040
Speaker 2: in the preparation I definitely did. Here's the thing. On

2227
01:49:19,120 --> 01:49:22,040
Speaker 2: an instinctual level, when your first thought is labor, that

2228
01:49:22,160 --> 01:49:25,360
Speaker 2: says a lot about you as a person. It's incredible

2229
01:49:26,040 --> 01:49:28,840
Speaker 2: that you immediately jumped to the hospitality workers in this

2230
01:49:28,960 --> 01:49:32,519
Speaker 2: city that are before by the various conferences, and you thought,

2231
01:49:32,560 --> 01:49:34,560
Speaker 2: how the fuck does this affect them? Because when it

2232
01:49:34,600 --> 01:49:37,200
Speaker 2: comes to better offline and what this fucking show actually means,

2233
01:49:37,439 --> 01:49:40,320
Speaker 2: it's what the actual effects of technology are on people.

2234
01:49:41,280 --> 01:49:43,360
Speaker 2: So thank you for joining us, of course, and please

2235
01:49:43,439 --> 01:49:44,960
Speaker 2: keep doing your shit. You're going to be back on

2236
01:49:45,080 --> 01:49:47,280
Speaker 2: because we live in the same city we do, and

2237
01:49:47,400 --> 01:49:48,400
Speaker 2: I will be finding you.

2238
01:49:48,840 --> 01:49:53,400
Speaker 8: God, no, God, somebody more actionable threats in these episodes

2239
01:49:53,439 --> 01:49:54,280
Speaker 8: than I'd expected.

2240
01:49:54,720 --> 01:49:56,280
Speaker 2: That's not a threat, it's a promise.

2241
01:49:56,920 --> 01:49:57,479
Speaker 5: Oh, thank you.

2242
01:49:59,560 --> 01:50:03,760
Speaker 2: I would thank me, And then of course to Mattiasowski.

2243
01:50:04,560 --> 01:50:08,000
Speaker 2: Manisowski is our producer, and he is the silent party

2244
01:50:08,240 --> 01:50:11,559
Speaker 2: who has been sitting here patiently the entire show, working

2245
01:50:11,640 --> 01:50:14,080
Speaker 2: through texting me time signals. When I text him I

2246
01:50:14,200 --> 01:50:18,800
Speaker 2: have BURBD. He edits that out because it's happened three times.

2247
01:50:18,840 --> 01:50:23,760
Speaker 2: I believe Matt. I and I bring up Matt Hughes here,

2248
01:50:23,880 --> 01:50:27,000
Speaker 2: my word editor, who has been so patient with him.

2249
01:50:27,040 --> 01:50:29,559
Speaker 2: Megan wernstromo over at Penguin, who has also been patient

2250
01:50:29,600 --> 01:50:33,320
Speaker 2: reading the dross. I assume she says it's good. But

2251
01:50:33,640 --> 01:50:37,320
Speaker 2: back to Mattisowski. Matt has been here since the beginning

2252
01:50:37,320 --> 01:50:39,840
Speaker 2: when I was really not fucking confident about this show

2253
01:50:39,840 --> 01:50:43,439
Speaker 2: and I was genuinely experiencing like real anxiety and worry.

2254
01:50:44,120 --> 01:50:47,800
Speaker 2: Matt encouraged me, work with me and edited. Matt. Love

2255
01:50:47,800 --> 01:50:50,280
Speaker 2: you man, Thank you so much for your hard work

2256
01:50:50,520 --> 01:50:52,879
Speaker 2: this entire week. Could you come over to the microphone

2257
01:50:52,920 --> 01:50:56,880
Speaker 2: and just say hello, Hello. Mattisowski is a protected party.

2258
01:50:56,880 --> 01:51:00,360
Speaker 2: If you ever wrong Mattisowski, I will destroy you, actually

2259
01:51:00,360 --> 01:51:02,360
Speaker 2: everyone in this room. But really, like, if you fuck

2260
01:51:02,400 --> 01:51:05,000
Speaker 2: with Mattasowski, I will actually fucking peck out your eyes

2261
01:51:05,040 --> 01:51:08,080
Speaker 2: like a podcast voice, like a big bird if you

2262
01:51:08,120 --> 01:51:12,479
Speaker 2: play Final Fantasy fifteen, specifically the zoo Bird, very big bird.

2263
01:51:13,920 --> 01:51:17,440
Speaker 2: You've been listening to the better off line CS experience.

2264
01:51:18,880 --> 01:51:21,759
Speaker 2: I am so grateful that you've been here, and tomorrow

2265
01:51:21,800 --> 01:51:23,720
Speaker 2: you'll get a final wrap up episode. But this is

2266
01:51:23,800 --> 01:51:28,479
Speaker 2: really like the rap night. I am actually really grateful

2267
01:51:28,520 --> 01:51:30,800
Speaker 2: for everyone who came in. Everyone's really fucking showed up

2268
01:51:30,840 --> 01:51:32,800
Speaker 2: and just had an incredible show for a show that

2269
01:51:32,920 --> 01:51:37,479
Speaker 2: is so regularly so fucking miserable and so lifeless about

2270
01:51:37,880 --> 01:51:40,439
Speaker 2: people that people are imagining rather than real people. And

2271
01:51:40,520 --> 01:51:43,880
Speaker 2: everyone's been here and just shown an incredible fucking show.

2272
01:51:43,920 --> 01:51:47,519
Speaker 2: I'm so grateful to everyone for being here. Thank you,

2273
01:51:48,200 --> 01:51:52,000
Speaker 2: and I'm now going to pass the microphone around, starting

2274
01:51:52,080 --> 01:51:55,160
Speaker 2: with Zai, who's been here, Zi please join us? Thank

2275
01:51:55,240 --> 01:51:59,840
Speaker 2: you for hi. Hello, You've been wonderful taking photos. Thank you.

2276
01:52:00,160 --> 01:52:02,360
Speaker 2: And then we'll now go to Robert Evans. Thank you, Robert.

2277
01:52:02,760 --> 01:52:04,800
Speaker 8: I just want everyone to know that you know as

2278
01:52:04,840 --> 01:52:08,400
Speaker 8: the verver a ox miss takes your loved ones. Ed

2279
01:52:08,680 --> 01:52:09,439
Speaker 8: Ed cares about you.

2280
01:52:10,360 --> 01:52:10,639
Speaker 4: Phil.

2281
01:52:13,120 --> 01:52:15,120
Speaker 9: I want to thank everyone. It's been a pleasure to

2282
01:52:15,200 --> 01:52:18,879
Speaker 9: be here and to serve, to serve and be of service.

2283
01:52:19,320 --> 01:52:22,080
Speaker 5: David Roff, thanks very much. It's a good time and

2284
01:52:22,439 --> 01:52:23,960
Speaker 5: I feel like I learned a lot.

2285
01:52:24,840 --> 01:52:26,000
Speaker 2: Mister Wrongways.

2286
01:52:27,360 --> 01:52:29,160
Speaker 4: Had a great time, and I'm not going to make

2287
01:52:29,200 --> 01:52:31,000
Speaker 4: any more legally actionable threats.

2288
01:52:31,560 --> 01:52:31,920
Speaker 2: Thanks.

2289
01:52:35,320 --> 01:52:38,240
Speaker 5: Yeah, Coon, you can just say yeah, this was This

2290
01:52:38,400 --> 01:52:39,559
Speaker 5: was my first ES.

2291
01:52:39,640 --> 01:52:43,599
Speaker 3: Ever, and I really enjoyed figuring out what was real

2292
01:52:43,680 --> 01:52:46,559
Speaker 3: and what wasn't and support local journalism.

2293
01:52:47,040 --> 01:52:49,840
Speaker 5: Yeah well, and thank you Ed for putting this whole

2294
01:52:49,840 --> 01:52:53,000
Speaker 5: space together. This has been a fantastic escape away from

2295
01:52:53,000 --> 01:52:57,080
Speaker 5: the show floor. I spent five hours in the Venetian today.

2296
01:52:57,200 --> 01:53:02,360
Speaker 5: Coming up here was a wonderful reprieve and you really,

2297
01:53:02,439 --> 01:53:04,639
Speaker 5: you really put this all together. So thank you so much,

2298
01:53:04,760 --> 01:53:07,760
Speaker 5: and your hard work over the last year on Better

2299
01:53:07,800 --> 01:53:12,320
Speaker 5: Offline has been has been lovely, has been lovely to watch.

2300
01:53:12,720 --> 01:53:14,880
Speaker 5: Thank you so much, and thank you so much for

2301
01:53:15,000 --> 01:53:17,880
Speaker 5: your listeners. If you've got to this point, I I'm

2302
01:53:17,960 --> 01:53:21,600
Speaker 5: so sorry, but also thank you for your patience. I

2303
01:53:21,720 --> 01:53:27,040
Speaker 5: hope I've successfully encapsulated ces. I've given you the various

2304
01:53:27,160 --> 01:53:30,040
Speaker 5: joketor positions of the show. Tomorrow you'll have a wonderful

2305
01:53:30,080 --> 01:53:34,559
Speaker 5: positive masculinity day. As the remaining crew me Mattasowski, Phil Broughton,

2306
01:53:34,600 --> 01:53:38,240
Speaker 5: and Edon Guaiso Junior kind of like smooth.

2307
01:53:37,880 --> 01:53:42,160
Speaker 2: Ourselves out, real smooth like. But today's the last day

2308
01:53:42,200 --> 01:53:46,320
Speaker 2: of the show. Email me easy or ease ed. If

2309
01:53:46,360 --> 01:53:49,599
Speaker 2: you're one of those people at Better Offline dot com,

2310
01:53:50,600 --> 01:53:53,240
Speaker 2: please let me know what you thought. A lot of

2311
01:53:53,320 --> 01:53:56,080
Speaker 2: you have emailed like we had we didn't have enough

2312
01:53:56,120 --> 01:53:58,080
Speaker 2: woman on this We next year we're going to fucking

2313
01:53:58,120 --> 01:54:01,040
Speaker 2: correct that. We luckily got victorious Charisa Belle and of

2314
01:54:01,120 --> 01:54:03,560
Speaker 2: course Sheerlyn Lowe, who really balanced that out. We'll do

2315
01:54:03,600 --> 01:54:06,800
Speaker 2: a better job last last time. Wow, the concept of

2316
01:54:06,920 --> 01:54:10,720
Speaker 2: time is fucked up. Nevertheless, we'll do a better job

2317
01:54:10,800 --> 01:54:13,200
Speaker 2: next year. And I love your feedback and I actually

2318
01:54:13,240 --> 01:54:15,479
Speaker 2: read all the emails. Will I respond to them. It

2319
01:54:15,640 --> 01:54:20,000
Speaker 2: gets increasingly harder each each week, which is a good sign,

2320
01:54:20,040 --> 01:54:24,479
Speaker 2: I guess. Either way, I'm very grateful for all of you.

2321
01:54:24,640 --> 01:54:27,000
Speaker 2: A lot of people have given a lot of people

2322
01:54:27,280 --> 01:54:31,639
Speaker 2: given me faith, given my given their faith Jesus Christ

2323
01:54:32,520 --> 01:54:34,520
Speaker 2: in the show in the last year, It's only going

2324
01:54:34,600 --> 01:54:36,680
Speaker 2: to get better. But next c Yes is going to

2325
01:54:36,720 --> 01:54:42,160
Speaker 2: be weirder. Geah has ideas, I have ideas, and it's

2326
01:54:42,640 --> 01:54:45,520
Speaker 2: just going to be sharper. It's just going to be weirder.

2327
01:54:46,160 --> 01:54:48,440
Speaker 2: You have another episode, There's going to be more Viera

2328
01:54:48,480 --> 01:54:50,840
Speaker 2: Nax too. Palpatine will be back.

2329
01:54:51,000 --> 01:54:52,920
Speaker 1: Cees twenty twenty four, Part three.

2330
01:54:53,200 --> 01:54:55,440
Speaker 2: I'm actually going to try and contact the e mcdummot.

2331
01:54:55,440 --> 01:54:58,600
Speaker 2: But anyway, thank you so much for listening. I know

2332
01:54:58,680 --> 01:55:02,280
Speaker 2: it's a lot of audio and and I I'm really

2333
01:55:02,400 --> 01:55:05,839
Speaker 2: grateful for everyone who contacts I love everyone who listens.

2334
01:55:06,360 --> 01:55:09,440
Speaker 2: I genuinely mes so grateful. I am not really good

2335
01:55:09,480 --> 01:55:12,480
Speaker 2: at hiding any of like the me in this and

2336
01:55:12,560 --> 01:55:15,320
Speaker 2: a lot of podcasts are very performative. I've phil can

2337
01:55:15,400 --> 01:55:17,960
Speaker 2: speak to this more than anyone I'm not really good

2338
01:55:18,000 --> 01:55:23,960
Speaker 2: at like pretending there is no off switch. I genuinely

2339
01:55:24,040 --> 01:55:33,800
Speaker 2: love you all. Thank you for listening. Thank you for

2340
01:55:33,880 --> 01:55:36,520
Speaker 2: listening to Better Offline. The editor and composer of the

2341
01:55:36,600 --> 01:55:39,640
Speaker 2: Better Offline theme song is Matasowski. You can check out

2342
01:55:39,680 --> 01:55:42,880
Speaker 2: more of his music and audio projects at Mattasowski dot com,

2343
01:55:43,520 --> 01:55:46,839
Speaker 2: m A T T O S O W s ki

2344
01:55:47,240 --> 01:55:50,120
Speaker 2: dot com. You can email me at easy at Better

2345
01:55:50,160 --> 01:55:52,600
Speaker 2: Offline dot com or visit Better Offline dot com to

2346
01:55:52,640 --> 01:55:55,400
Speaker 2: find more podcast links and of course my newsletter. I

2347
01:55:55,520 --> 01:55:58,240
Speaker 2: also really recommend you go to chat dot where's youreaed

2348
01:55:58,320 --> 01:56:00,520
Speaker 2: dot at to visit the discord, and go to our

2349
01:56:00,640 --> 01:56:03,880
Speaker 2: slash Better Offline to check out I'll Reddit. Thank you

2350
01:56:04,000 --> 01:56:04,920
Speaker 2: so much for listening.

2351
01:56:05,800 --> 01:56:08,240
Speaker 1: Better Offline is a production of cool Zone Media.

2352
01:56:08,440 --> 01:56:11,760
Speaker 2: For more from cool Zone Media, visit our website Coolzonemedia

2353
01:56:11,840 --> 01:56:14,640
Speaker 2: dot com, or check us out on the iHeartRadio app,

2354
01:56:14,720 --> 01:56:17,120
Speaker 2: Apple Podcasts, or wherever you get your podcasts.