1
00:00:00,280 --> 00:00:03,680
Speaker 1: Welcome to the Nick, Dick and Paul Show. I am

2
00:00:03,720 --> 00:00:06,640
Speaker 1: one of your hosts, Nick Bilton. I was a journalist

3
00:00:06,720 --> 00:00:08,600
Speaker 1: for twenty years of The New York Times, Amenity Fair,

4
00:00:09,160 --> 00:00:12,600
Speaker 1: read a bunch of books, and now I am one

5
00:00:12,600 --> 00:00:15,360
Speaker 1: of the co hosts of this unbelievable podcast.

6
00:00:15,800 --> 00:00:20,040
Speaker 2: I am Dick Costello, star of Screen and Stage.

7
00:00:21,520 --> 00:00:24,120
Speaker 3: See now I want to meet you. Yeah, it's all change.

8
00:00:24,160 --> 00:00:27,240
Speaker 3: Before I was kind of indifferent. I Paul Kadrowski, investor

9
00:00:27,960 --> 00:00:31,240
Speaker 3: Wall Street Guy years ago, mostly wonder around talking about

10
00:00:31,240 --> 00:00:32,320
Speaker 3: things that I don't know anything about.

11
00:00:32,520 --> 00:00:34,440
Speaker 1: I just want to add to Dick that he was

12
00:00:34,479 --> 00:00:36,479
Speaker 1: also the CEO of Twitter, because we are probably going

13
00:00:36,560 --> 00:00:54,800
Speaker 1: to talk about social media today today's episode at episodes

14
00:00:54,840 --> 00:00:55,080
Speaker 1: about it.

15
00:00:55,120 --> 00:00:56,360
Speaker 2: I don't know if a lot of people, when they

16
00:00:56,360 --> 00:01:00,680
Speaker 2: think about me ago then really include that in the biography.

17
00:01:01,160 --> 00:01:02,600
Speaker 4: I can't imagine why.

18
00:01:03,320 --> 00:01:08,160
Speaker 1: Creighton Barrel he actually yeah, yeah, when I.

19
00:01:08,080 --> 00:01:10,319
Speaker 2: Was when I was when I when I graduated from Michigan.

20
00:01:10,440 --> 00:01:12,800
Speaker 2: So it's because to show you what the college degree

21
00:01:12,840 --> 00:01:14,480
Speaker 2: will get you. No, it was when I was at

22
00:01:14,520 --> 00:01:18,320
Speaker 2: Second City in Chicago. Like you, I had to have

23
00:01:18,400 --> 00:01:20,920
Speaker 2: a general job Twitter.

24
00:01:21,200 --> 00:01:22,080
Speaker 4: But what were you doing there?

25
00:01:22,400 --> 00:01:24,240
Speaker 2: What do you mean, what was I doing there? Was

26
00:01:24,600 --> 00:01:25,360
Speaker 2: selling flatware?

27
00:01:25,440 --> 00:01:26,760
Speaker 4: Oh you were literally flatware?

28
00:01:26,920 --> 00:01:27,640
Speaker 2: Yeah? Literally?

29
00:01:27,760 --> 00:01:28,600
Speaker 4: Oh that's the best.

30
00:01:29,319 --> 00:01:31,560
Speaker 2: Thank you.

31
00:01:31,640 --> 00:01:32,440
Speaker 4: I have good stuff.

32
00:01:32,800 --> 00:01:34,520
Speaker 1: Paul, tell us what we're talking about today.

33
00:01:34,600 --> 00:01:36,200
Speaker 4: I'm building up for sponsorships.

34
00:01:36,240 --> 00:01:43,000
Speaker 2: Okay, answer right there, And that's why we're so excited

35
00:01:43,080 --> 00:01:45,920
Speaker 2: to talk to you for this wreck moment about Bodenova

36
00:01:46,040 --> 00:01:49,760
Speaker 2: flat barrel's the best.

37
00:01:50,880 --> 00:01:54,279
Speaker 3: I saw piece recently that was in New Scientists about

38
00:01:54,320 --> 00:01:57,640
Speaker 3: the best and worst inventions of the last one hundred years,

39
00:01:57,880 --> 00:02:00,480
Speaker 3: and I sent it around to you guys. But I

40
00:02:00,600 --> 00:02:04,400
Speaker 3: just the idea of trying to there's lots of good

41
00:02:04,400 --> 00:02:06,520
Speaker 3: and bad ideas and inventions, but of trying to narrow

42
00:02:06,560 --> 00:02:08,720
Speaker 3: it down to just a couple. It was was interesting,

43
00:02:08,800 --> 00:02:10,600
Speaker 3: and so I sent it around and I thought it

44
00:02:10,639 --> 00:02:12,840
Speaker 3: was worth discussing, Like, for example, one of the worst

45
00:02:12,880 --> 00:02:19,200
Speaker 3: ideas of the door dash, this is like Pavlovian we're

46
00:02:19,200 --> 00:02:19,560
Speaker 3: going to get.

47
00:02:19,600 --> 00:02:20,840
Speaker 2: I want to get back to that, we're going to get.

48
00:02:21,919 --> 00:02:25,120
Speaker 3: So the social media was was an obvious one, was

49
00:02:25,120 --> 00:02:27,120
Speaker 3: one of the on the list. Crypto was on the list.

50
00:02:27,200 --> 00:02:29,560
Speaker 3: Effective altruism, weirdly enough, was on the list, which is

51
00:02:29,800 --> 00:02:31,440
Speaker 3: a weird thing to have as one of the worst

52
00:02:31,440 --> 00:02:34,200
Speaker 3: inventions because a it's not clear it's an invention, and

53
00:02:34,360 --> 00:02:36,120
Speaker 3: most people have no idea what it is anyways. So

54
00:02:36,440 --> 00:02:39,760
Speaker 3: it's my take on respect to these these worst inventions

55
00:02:39,800 --> 00:02:42,320
Speaker 3: is they kind of have to have had an impact

56
00:02:42,440 --> 00:02:45,160
Speaker 3: otherwise it's like, you know, dude in a garage comes

57
00:02:45,200 --> 00:02:47,639
Speaker 3: up with a way to make you know, hairless cats.

58
00:02:47,800 --> 00:02:51,600
Speaker 4: Yeah, I care? Is it that important? Should?

59
00:02:51,800 --> 00:02:52,639
Speaker 2: So I don't.

60
00:02:52,639 --> 00:02:54,680
Speaker 1: I'm not going to start with DoorDash. I do have

61
00:02:54,720 --> 00:02:57,640
Speaker 1: a question, a genuine serious question before us, which is

62
00:02:58,120 --> 00:02:59,600
Speaker 1: and I don't know the answer to this. I have

63
00:02:59,680 --> 00:03:02,600
Speaker 1: lots of opinions. It's not social media, it's the smartphone.

64
00:03:03,720 --> 00:03:06,000
Speaker 3: So it was on going back to the new scientists

65
00:03:06,000 --> 00:03:08,240
Speaker 3: think it was on both their best and worst. It

66
00:03:08,320 --> 00:03:10,240
Speaker 3: was on both of them, which was interesting, right, I

67
00:03:10,280 --> 00:03:12,440
Speaker 3: mean because double edged thing.

68
00:03:13,320 --> 00:03:16,640
Speaker 1: What do you guys think I think it is. I

69
00:03:16,639 --> 00:03:18,960
Speaker 1: would put it in the worst category. I think that

70
00:03:19,880 --> 00:03:23,240
Speaker 1: it doesn't make our It doesn't make us better as people,

71
00:03:23,800 --> 00:03:27,960
Speaker 1: It doesn't make us. All it does is make us

72
00:03:28,000 --> 00:03:30,480
Speaker 1: more insular we walk around. I mean, I was in

73
00:03:30,520 --> 00:03:34,080
Speaker 1: the airport yesterday, two days ago. There wasn't a human

74
00:03:34,120 --> 00:03:35,760
Speaker 1: being not looking at their smartphone.

75
00:03:35,880 --> 00:03:37,960
Speaker 3: Yeah, and I noticed this all the time. One of

76
00:03:38,120 --> 00:03:40,760
Speaker 3: the weirdest phenomenon. If you came forward from thirty years

77
00:03:40,760 --> 00:03:43,000
Speaker 3: ago into an airport, having traveled the last time you

78
00:03:43,000 --> 00:03:45,120
Speaker 3: did was thirty years ago, and you walked thro an airport,

79
00:03:45,120 --> 00:03:47,760
Speaker 3: You're like, what the hell is everyone like a palm reader?

80
00:03:47,800 --> 00:03:49,760
Speaker 3: Why is everyone doing this? Why is everyone staring at

81
00:03:49,760 --> 00:03:51,560
Speaker 3: their hands all over the airport? And of course the

82
00:03:51,560 --> 00:03:55,880
Speaker 3: big changes is smartphones. It's astonishing now. My argument is

83
00:03:56,080 --> 00:03:59,160
Speaker 3: it's actually fantastically important in airports because it operates in

84
00:03:59,200 --> 00:04:01,240
Speaker 3: the same way as like the UN guys with the

85
00:04:01,240 --> 00:04:04,240
Speaker 3: blue helmets. It's like a pacification mechanism. We keep people

86
00:04:04,240 --> 00:04:09,320
Speaker 3: in airports from killing each other. This is my theory.

87
00:04:09,760 --> 00:04:12,920
Speaker 2: That's it. I really really really want to stab that

88
00:04:12,960 --> 00:04:17,680
Speaker 2: guy over there, but on Flappy Birds and I got

89
00:04:17,680 --> 00:04:18,640
Speaker 2: to try to get an eleven.

90
00:04:19,160 --> 00:04:19,800
Speaker 4: I'm not kidding.

91
00:04:19,839 --> 00:04:22,400
Speaker 3: I think it's actually asked well, kind of like a

92
00:04:22,400 --> 00:04:25,200
Speaker 3: better version of the UN where people otherwise are so

93
00:04:25,560 --> 00:04:27,960
Speaker 3: riled up in airports that I just.

94
00:04:27,920 --> 00:04:29,839
Speaker 4: Go back to scrolling Instagram whatever.

95
00:04:29,880 --> 00:04:32,360
Speaker 3: It'll all work out, which turns out to be really

96
00:04:32,360 --> 00:04:35,440
Speaker 3: important whenever people are genuinely bananas, which which is kind

97
00:04:35,440 --> 00:04:36,240
Speaker 3: of the case these days.

98
00:04:36,279 --> 00:04:38,880
Speaker 1: Okay, So, Dick, what's your thought the worst one of

99
00:04:38,880 --> 00:04:41,280
Speaker 1: the worst smart smartphones? Like do you think that they

100
00:04:41,520 --> 00:04:43,760
Speaker 1: do you look at like your kids? Do you look

101
00:04:43,760 --> 00:04:47,320
Speaker 1: at the society day, at the world and the stuff

102
00:04:47,360 --> 00:04:49,880
Speaker 1: we consume, and the fact that people are reading less

103
00:04:49,880 --> 00:04:53,280
Speaker 1: books than ever and they consume shorts And.

104
00:04:52,680 --> 00:04:54,000
Speaker 2: At least you're not leading the witness.

105
00:04:54,040 --> 00:04:59,240
Speaker 3: I mean, come on, that you're approaching this really objectively

106
00:05:00,040 --> 00:05:01,359
Speaker 3: other than all these awful things.

107
00:05:01,600 --> 00:05:03,080
Speaker 1: Let me just ask a question. Let me let me

108
00:05:03,800 --> 00:05:05,760
Speaker 1: which you're not possibly defensible.

109
00:05:06,279 --> 00:05:08,680
Speaker 2: I'm interested in your objective opinion about this.

110
00:05:09,320 --> 00:05:12,960
Speaker 1: Let me ask you a question or such a good gas,

111
00:05:13,640 --> 00:05:17,719
Speaker 1: a real world a better place today? Or or is

112
00:05:17,760 --> 00:05:19,920
Speaker 1: it was it better when people didn't have phones?

113
00:05:20,960 --> 00:05:24,720
Speaker 2: I mean, you sound like you know great Grandpacosta, or

114
00:05:25,000 --> 00:05:26,080
Speaker 2: you know you can.

115
00:05:25,960 --> 00:05:28,480
Speaker 5: Do this all the way back to the wheel, like

116
00:05:28,839 --> 00:05:32,039
Speaker 5: the wheel. You know what, Now no one's gonna walk.

117
00:05:32,040 --> 00:05:36,000
Speaker 5: Anyone walks anywhere. No one walks anymore. They roll things around.

118
00:05:36,400 --> 00:05:39,000
Speaker 5: It was better when we dragged the food up the hill?

119
00:05:42,200 --> 00:05:42,960
Speaker 4: Will not work.

120
00:05:44,160 --> 00:05:47,000
Speaker 1: Okay, let's but there are technologies that are good and

121
00:05:47,000 --> 00:05:48,080
Speaker 1: there are technologies that are bad.

122
00:05:48,120 --> 00:05:50,279
Speaker 4: I don't think that's I don't think that's true either, Yeah,

123
00:05:50,480 --> 00:05:51,320
Speaker 4: go ahead, Okay.

124
00:05:51,360 --> 00:05:54,800
Speaker 3: I mean it's not always true, but generally speaking, it's

125
00:05:54,839 --> 00:05:57,640
Speaker 3: it's how they're used. Lots of technologies can be used

126
00:05:57,680 --> 00:06:01,400
Speaker 3: for malign purposes, they can use for good purposes. It

127
00:06:01,400 --> 00:06:04,960
Speaker 3: doesn't I don't think in general most technologies, with the

128
00:06:04,960 --> 00:06:08,120
Speaker 3: exception of possibly like aerosolized abola or something else.

129
00:06:09,200 --> 00:06:11,560
Speaker 2: Which hard to come up with.

130
00:06:11,520 --> 00:06:15,039
Speaker 3: The possible that there's a good pos But I just

131
00:06:15,120 --> 00:06:17,640
Speaker 3: I don't think it's it's useful to just say that

132
00:06:17,720 --> 00:06:19,400
Speaker 3: everything technology.

133
00:06:19,440 --> 00:06:22,840
Speaker 1: Ah, I'm not saying it's good, it's it's inherently good

134
00:06:22,880 --> 00:06:24,520
Speaker 1: or bad. I think that there I don't think that

135
00:06:24,560 --> 00:06:27,159
Speaker 1: there is a single technology on the planet that is

136
00:06:27,200 --> 00:06:30,520
Speaker 1: either only good and only bad. Cars, for example, they're great,

137
00:06:30,520 --> 00:06:32,640
Speaker 1: one point two million people still die every single year

138
00:06:33,120 --> 00:06:35,400
Speaker 1: every year. Actually, when I was today, there was a

139
00:06:35,480 --> 00:06:39,440
Speaker 1: car that fucking rolled off the cliff and down upon

140
00:06:39,720 --> 00:06:43,840
Speaker 1: Laurel Canyon. And yeah, there was helicopters. And it's crazy. Anyway,

141
00:06:43,920 --> 00:06:48,560
Speaker 1: going back to what we're talking about, smartphones, smartphones no technology.

142
00:06:48,600 --> 00:06:50,800
Speaker 1: So there are technologies that are good and bad and

143
00:06:51,000 --> 00:06:54,160
Speaker 1: so on. However, I would we just agree that wasn't No, No,

144
00:06:54,520 --> 00:06:57,120
Speaker 1: there's like there's some that are more. I believe that

145
00:06:57,120 --> 00:07:00,760
Speaker 1: that that they lean in a direction. And so you

146
00:07:00,760 --> 00:07:04,640
Speaker 1: can say, you know, bio weapons are bad, but the

147
00:07:04,680 --> 00:07:08,039
Speaker 1: same person who invented fertilizer also invented, you know, the

148
00:07:08,080 --> 00:07:12,160
Speaker 1: first biotech weapons. So it's like the thing. But what

149
00:07:12,200 --> 00:07:14,920
Speaker 1: I do believe is that they lean in a direction.

150
00:07:15,120 --> 00:07:17,720
Speaker 1: And no, I think that's and I think social media,

151
00:07:17,800 --> 00:07:21,000
Speaker 1: for example, leans in a much worse direction than a

152
00:07:21,000 --> 00:07:23,000
Speaker 1: positive direction today at least.

153
00:07:23,040 --> 00:07:24,640
Speaker 4: Okay, let's let's stick to smartphone.

154
00:07:24,680 --> 00:07:27,280
Speaker 1: But so I think you're smartphone, Okay, but smartphones. I

155
00:07:27,320 --> 00:07:32,000
Speaker 1: think that everything that we can do with the smartphone

156
00:07:32,880 --> 00:07:35,640
Speaker 1: we could do before the smartphone in a slower capacity.

157
00:07:36,800 --> 00:07:39,440
Speaker 1: Correct or No, Yeah, I.

158
00:07:39,360 --> 00:07:40,559
Speaker 4: Think it's broadly true.

159
00:07:40,560 --> 00:07:42,320
Speaker 3: But that's also goes back to Dick's point about the

160
00:07:42,320 --> 00:07:43,600
Speaker 3: wheel wheel know good.

161
00:07:43,600 --> 00:07:46,120
Speaker 4: Doesn't it doesn't work for bad. I just think that

162
00:07:46,120 --> 00:07:49,800
Speaker 4: that's the wrong. Okay, I'm doing I'm going.

163
00:07:49,760 --> 00:07:52,720
Speaker 1: To push back on you. You have said before, and I

164
00:07:52,760 --> 00:07:55,840
Speaker 1: thought it was a various dude observation that we believe

165
00:07:56,080 --> 00:07:58,920
Speaker 1: that the problem with Silicon Valley and with people that

166
00:07:58,960 --> 00:08:02,440
Speaker 1: make technologies that everyone believes that it is a religious

167
00:08:03,000 --> 00:08:05,560
Speaker 1: right and it's A, it's a and that there's nothing

168
00:08:05,560 --> 00:08:07,600
Speaker 1: that should ever stop it. And you said this when

169
00:08:07,640 --> 00:08:10,320
Speaker 1: AI first came out. I remember this, So then you're

170
00:08:10,440 --> 00:08:12,400
Speaker 1: so what, So what's your point of view?

171
00:08:12,680 --> 00:08:18,320
Speaker 2: I think I'll interject an answer for Paul. I think

172
00:08:18,360 --> 00:08:23,360
Speaker 2: that the challenge is that Silicon Valley always assumes this

173
00:08:23,440 --> 00:08:26,080
Speaker 2: is going to be great. You're gonna love this, This

174
00:08:26,200 --> 00:08:28,640
Speaker 2: is going to solve a lot of problems. I remember

175
00:08:28,640 --> 00:08:31,520
Speaker 2: I had this argument with Reid Hoffman about AI when

176
00:08:31,560 --> 00:08:36,720
Speaker 2: it first came out, and it said, no one's school

177
00:08:36,800 --> 00:08:39,760
Speaker 2: is high school is used now useless, These kids are

178
00:08:39,760 --> 00:08:43,240
Speaker 2: just gonna not learn anything. He's like, no, no, no, it's

179
00:08:43,280 --> 00:08:47,559
Speaker 2: like the calculator. Like it's not like the calculator. It's

180
00:08:47,600 --> 00:08:51,880
Speaker 2: literally like it's so obviously going to be people will

181
00:08:51,920 --> 00:08:54,959
Speaker 2: just stop thinking for themselves and ask Claude or chat

182
00:08:55,040 --> 00:08:57,079
Speaker 2: you bet or Gemini, what should I think about this?

183
00:08:57,200 --> 00:08:57,440
Speaker 4: Yeah?

184
00:08:57,440 --> 00:08:59,960
Speaker 2: And it's for and then here we are. It's happening.

185
00:09:00,360 --> 00:09:06,280
Speaker 2: But literally, every N plus one invention, despite all evidence

186
00:09:06,320 --> 00:09:10,200
Speaker 2: to the contrary from past inventions, is viewed as, oh,

187
00:09:10,280 --> 00:09:11,640
Speaker 2: this is going to be great.

188
00:09:11,679 --> 00:09:12,320
Speaker 4: This is a big one.

189
00:09:12,520 --> 00:09:14,920
Speaker 2: Nonetheless, and have only been great.

190
00:09:15,200 --> 00:09:16,920
Speaker 4: Yeah yeah, yeah, So why would that change.

191
00:09:17,000 --> 00:09:18,680
Speaker 3: And I think some of this has to do with,

192
00:09:18,760 --> 00:09:21,240
Speaker 3: like you know, classic survivor bias, Like we're if you

193
00:09:21,240 --> 00:09:23,080
Speaker 3: think of it like as a multiverse, and in every

194
00:09:23,080 --> 00:09:26,120
Speaker 3: timeline people have been trying technologies. We're in the timeline

195
00:09:26,120 --> 00:09:28,040
Speaker 3: that worked out because if it, if it had killed

196
00:09:28,120 --> 00:09:30,240
Speaker 3: us off, we wouldn't be here having this conversation. So this,

197
00:09:30,559 --> 00:09:34,320
Speaker 3: it creates this bias to believe that every technology eventually

198
00:09:34,640 --> 00:09:36,760
Speaker 3: finds a purpose or even if it starts off and

199
00:09:36,800 --> 00:09:38,440
Speaker 3: it's a little bit uncertain what the use is, it

200
00:09:38,480 --> 00:09:41,520
Speaker 3: sorts itself out. But that's classic survivor bias, right, So

201
00:09:41,600 --> 00:09:44,480
Speaker 3: integue to go back to your original point. That's why

202
00:09:44,559 --> 00:09:47,920
Speaker 3: technologists believe what they believe, because they're all backward looking

203
00:09:48,120 --> 00:09:50,400
Speaker 3: and saying, well, it's always worked out in the past. Yeah,

204
00:09:50,400 --> 00:09:52,080
Speaker 3: but if it hadn't worked out, you wouldn't be here

205
00:09:52,080 --> 00:09:54,800
Speaker 3: having this conversation. That's it's a it's a it's an

206
00:09:54,840 --> 00:09:57,480
Speaker 3: indefensible argument, right, you're arguing on the basis of your

207
00:09:57,520 --> 00:10:00,720
Speaker 3: own presence. Well that's essentially assuming you're trying to prove

208
00:10:00,880 --> 00:10:04,400
Speaker 3: So I don't that whole argument leaves me cold.

209
00:10:04,760 --> 00:10:08,280
Speaker 1: So then the smartphone, Yeah, that both oh.

210
00:10:08,200 --> 00:10:09,840
Speaker 4: I think the smartphone's largely a good invention.

211
00:10:09,920 --> 00:10:12,120
Speaker 3: I think it's one of oh I do, yeah, absolutely,

212
00:10:12,160 --> 00:10:17,080
Speaker 3: And I think it's brought, you know, communications and computation

213
00:10:17,320 --> 00:10:20,120
Speaker 3: and connectivity to people who might not otherwise have access

214
00:10:20,160 --> 00:10:23,319
Speaker 3: through laptops and other things. You see this a lot

215
00:10:23,440 --> 00:10:26,880
Speaker 3: in some emerging economies where people aren't wondering with laptops,

216
00:10:26,880 --> 00:10:28,880
Speaker 3: and yet they're using this to coordinate everything they do

217
00:10:28,960 --> 00:10:30,920
Speaker 3: in terms of business, They're using phones to do all

218
00:10:30,920 --> 00:10:33,880
Speaker 3: those things. It's the same way that in China people

219
00:10:33,920 --> 00:10:36,360
Speaker 3: are like, well, they'll never jump straight ahead to technology

220
00:10:36,360 --> 00:10:38,559
Speaker 3: because they have to build out these giant wireline networks.

221
00:10:38,559 --> 00:10:41,000
Speaker 3: Well no, they leaped straight to wireless, and phones became

222
00:10:41,000 --> 00:10:43,560
Speaker 3: the enabling kind of fabric that let everything happen. So

223
00:10:43,600 --> 00:10:47,800
Speaker 3: I think they're incredibly fraught technologies, but they're wildly important

224
00:10:47,800 --> 00:10:49,840
Speaker 3: and useful and unbalanced. They're probably one of the most

225
00:10:49,840 --> 00:10:51,640
Speaker 3: important inventions of the last hundred years.

226
00:10:52,040 --> 00:10:54,839
Speaker 2: Like most things, I think the smartphone is a great

227
00:10:54,880 --> 00:10:57,480
Speaker 2: invention for me, and I don't want anyone else to

228
00:10:57,480 --> 00:10:58,640
Speaker 2: have one, yeah.

229
00:10:59,280 --> 00:11:02,920
Speaker 3: Exactly, because I I alone, Yeah, I'm capable of I

230
00:11:02,960 --> 00:11:03,760
Speaker 3: really don't.

231
00:11:03,520 --> 00:11:06,200
Speaker 2: Want the guy in seat twenty three B who is

232
00:11:06,240 --> 00:11:09,280
Speaker 2: doing a business deal loudly on his phone to have one, right,

233
00:11:09,280 --> 00:11:11,280
Speaker 2: you know that's there anyway.

234
00:11:11,240 --> 00:11:13,360
Speaker 3: But there was a piece and there's no question. Like

235
00:11:13,760 --> 00:11:16,080
Speaker 3: some of the most bizarre articles in the Wall Street

236
00:11:16,120 --> 00:11:18,480
Speaker 3: Journal lately are about people using smartphones in weird ways.

237
00:11:18,480 --> 00:11:20,640
Speaker 3: Like there was a piece of recently, one of those

238
00:11:20,679 --> 00:11:23,080
Speaker 3: ahead pieces where they have like the funny.

239
00:11:23,120 --> 00:11:23,840
Speaker 4: Drawing to the top.

240
00:11:24,080 --> 00:11:28,440
Speaker 3: It was about how couples are fighting about smartphones because

241
00:11:29,000 --> 00:11:31,920
Speaker 3: their only really alone time is just after they get

242
00:11:31,920 --> 00:11:33,760
Speaker 3: home from work in the car, and they want to

243
00:11:33,800 --> 00:11:36,320
Speaker 3: sit in the car for like ten minutes scrolling Instagram.

244
00:11:36,640 --> 00:11:39,680
Speaker 3: But because they have proximity security with things like ring

245
00:11:39,679 --> 00:11:42,520
Speaker 3: and other things, their spouse knows their home and they're like,

246
00:11:42,880 --> 00:11:44,560
Speaker 3: why aren't you getting out of the car. Well, I

247
00:11:44,640 --> 00:11:46,800
Speaker 3: was just having a little bit of meat time on Instagram,

248
00:11:47,520 --> 00:11:49,320
Speaker 3: and I was like, is this a thing? And so

249
00:11:49,360 --> 00:11:51,160
Speaker 3: I started asking people and it's like, yeah, yeah, I

250
00:11:51,200 --> 00:11:52,599
Speaker 3: do that all the time. I come home and I

251
00:11:52,640 --> 00:11:54,240
Speaker 3: might spend a couple of minutes once I'm parked just

252
00:11:54,240 --> 00:11:56,160
Speaker 3: sort of scrolling the social media feeds and everything else

253
00:11:56,200 --> 00:11:57,760
Speaker 3: and don't go into the house for five or ten minutes.

254
00:11:57,880 --> 00:11:59,400
Speaker 3: Do it when I drop my kid off at school.

255
00:11:59,440 --> 00:12:01,560
Speaker 3: I don't just drop them off and bo bold.

256
00:12:01,800 --> 00:12:03,559
Speaker 4: I'll just sit there and I'll look over to another

257
00:12:03,600 --> 00:12:05,200
Speaker 4: car and there'll be another parent there like this, and

258
00:12:05,240 --> 00:12:08,360
Speaker 4: we're like, you know, thumbs up, we're rocking this thing.

259
00:12:08,400 --> 00:12:12,000
Speaker 4: So this sort of stuff is genuinely bizarre to It's crazy. Yeah,

260
00:12:12,000 --> 00:12:12,439
Speaker 4: it's crazy.

261
00:12:12,640 --> 00:12:14,720
Speaker 2: We're yeah, we're a hop skipping to jump away from

262
00:12:14,920 --> 00:12:17,360
Speaker 2: Has anyone seen Grandpa? I think he's in the garage

263
00:12:17,400 --> 00:12:19,760
Speaker 2: scrolling Instagram. We go out there, he's like, oh, Grandpa,

264
00:12:19,880 --> 00:12:21,440
Speaker 2: we lost Grandpa several days ago.

265
00:12:23,920 --> 00:12:26,440
Speaker 4: It's clearly covered, all right.

266
00:12:26,440 --> 00:12:29,400
Speaker 1: So that's a perfect segue to a new technolog another technology,

267
00:12:29,480 --> 00:12:32,000
Speaker 1: social media. Dick, you're taking this one.

268
00:12:32,880 --> 00:12:36,360
Speaker 2: I mean, I'm going to go back to originally, remember,

269
00:12:36,880 --> 00:12:39,679
Speaker 2: you know, during the Arab Spring, and we used to

270
00:12:39,720 --> 00:12:41,439
Speaker 2: say Twitter like we're the free speech wing of the

271
00:12:41,440 --> 00:12:45,520
Speaker 2: free speech Party, Like you're there's no way to squash

272
00:12:45,920 --> 00:12:48,240
Speaker 2: speech on Twitter. It's one of the reasons people in

273
00:12:48,679 --> 00:12:52,800
Speaker 2: you know, across North Africa were able to rise up

274
00:12:52,840 --> 00:12:54,720
Speaker 2: against the you know, the powers that be because they

275
00:12:54,760 --> 00:12:57,280
Speaker 2: were able to organize, and they were able to organize anonymously,

276
00:12:57,320 --> 00:12:59,439
Speaker 2: because you didn't have to have your real name and

277
00:12:59,480 --> 00:13:01,319
Speaker 2: address in it thing. On Twitter you can have this

278
00:13:01,400 --> 00:13:04,080
Speaker 2: sort of sort of as you know, have pseudonyms. And

279
00:13:04,120 --> 00:13:07,760
Speaker 2: then of course you start to see the millions and

280
00:13:07,800 --> 00:13:11,679
Speaker 2: millions of Russian spambots and fishing. But the first Russian

281
00:13:12,520 --> 00:13:16,160
Speaker 2: influences in interference rather than social media was they were

282
00:13:16,160 --> 00:13:19,480
Speaker 2: just creating millions of accounts for fishing, you know, phishing

283
00:13:19,520 --> 00:13:22,440
Speaker 2: attacks and spam attacks. I remember when I when I

284
00:13:22,520 --> 00:13:26,600
Speaker 2: left in twenty fifteen, it wasn't the coming election we were

285
00:13:26,480 --> 00:13:29,840
Speaker 2: worried about. It was, Man, these you know, spambots that

286
00:13:29,880 --> 00:13:31,640
Speaker 2: are being created in Russia. How were they do?

287
00:13:31,760 --> 00:13:32,840
Speaker 1: What kind of fishing were they doing?

288
00:13:34,040 --> 00:13:35,760
Speaker 2: What do you mean like doing like all the classic

289
00:13:36,200 --> 00:13:41,439
Speaker 2: like hey, you know at replying to people, check this

290
00:13:41,559 --> 00:13:44,160
Speaker 2: off and you know, yeah, all that stuff.

291
00:13:44,200 --> 00:13:45,520
Speaker 1: And then it transitioned into what it.

292
00:13:45,520 --> 00:13:48,720
Speaker 2: Is, transitioned it well, transitioned in interference in the elections

293
00:13:48,760 --> 00:13:50,600
Speaker 2: obviously after I left, but we didn't know it at

294
00:13:50,600 --> 00:13:53,439
Speaker 2: the time, and you know, and then of course all

295
00:13:53,440 --> 00:13:57,760
Speaker 2: the other like just you know, angry like it's now,

296
00:13:58,120 --> 00:14:01,000
Speaker 2: I mean now most of the time you go on there,

297
00:14:01,080 --> 00:14:04,400
Speaker 2: it's either here's this great thing I'm doing that you

298
00:14:04,080 --> 00:14:08,720
Speaker 2: don't You're not getting to do or anger, you know,

299
00:14:09,080 --> 00:14:10,040
Speaker 2: inciting anger.

300
00:14:10,240 --> 00:14:13,400
Speaker 3: Yeah, and that's because anger is you can monetize anger now,

301
00:14:13,400 --> 00:14:16,000
Speaker 3: and I think that's a really important always this idea

302
00:14:16,080 --> 00:14:19,200
Speaker 3: that it's not my line, but the idea of anger entrepreneurs,

303
00:14:19,240 --> 00:14:22,600
Speaker 3: that there are literally angers people who are successfully monetizing

304
00:14:22,640 --> 00:14:24,520
Speaker 3: these very strong negative emotions.

305
00:14:24,520 --> 00:14:26,280
Speaker 1: One of them is the President of the United States.

306
00:14:26,720 --> 00:14:27,480
Speaker 4: There's lots of you.

307
00:14:27,560 --> 00:14:29,320
Speaker 1: No, it's not I'm not it's not I'm not dissing

308
00:14:29,400 --> 00:14:31,400
Speaker 1: him for it. It's literally what he's amazing at.

309
00:14:31,520 --> 00:14:33,400
Speaker 4: But the point is is, like there's lots of he

310
00:14:33,520 --> 00:14:34,600
Speaker 4: was not an early adopter.

311
00:14:35,880 --> 00:14:38,600
Speaker 2: There was plenty. There's plenty of money before him, plenty

312
00:14:38,600 --> 00:14:39,120
Speaker 2: before him.

313
00:14:39,120 --> 00:14:42,840
Speaker 3: And so this idea, though that that was really difficult

314
00:14:42,840 --> 00:14:46,560
Speaker 3: to do at scales, is the important piece of social media,

315
00:14:46,600 --> 00:14:47,600
Speaker 3: like you always had back.

316
00:14:47,680 --> 00:14:49,560
Speaker 2: And it's not one sided either, Like you can be

317
00:14:49,600 --> 00:14:52,920
Speaker 2: an anger entrepreneur on on side of the equation.

318
00:14:52,720 --> 00:14:54,360
Speaker 4: In any political position. Now.

319
00:14:54,520 --> 00:14:58,600
Speaker 3: That's existed back to the nineteenth century newspapers where people

320
00:14:58,640 --> 00:15:01,960
Speaker 3: had their the cultish followings of right leaning, left leaning

321
00:15:02,000 --> 00:15:03,240
Speaker 3: whatever else newspapers.

322
00:15:03,600 --> 00:15:04,280
Speaker 4: So that existed.

323
00:15:04,320 --> 00:15:07,480
Speaker 3: The difference now is there's this flywheel effect where I

324
00:15:07,520 --> 00:15:09,680
Speaker 3: see in real time what works and what doesn't, and

325
00:15:09,720 --> 00:15:14,000
Speaker 3: that becomes self reinforcing, speeds up the process, and from

326
00:15:14,000 --> 00:15:16,800
Speaker 3: my standpoint, you know, as the anger entrepreneur, it's really

327
00:15:16,840 --> 00:15:17,840
Speaker 3: easily monetized.

328
00:15:39,760 --> 00:15:43,440
Speaker 1: Somebody was telling me a story recently about this this

329
00:15:43,640 --> 00:15:50,040
Speaker 1: Israeli research company, about this woman that had become very

330
00:15:50,160 --> 00:15:54,680
Speaker 1: very influential in the Gaza Israel debate, and they had

331
00:15:54,720 --> 00:15:59,200
Speaker 1: gone back to figure out where she became ideological, like

332
00:15:59,400 --> 00:16:03,360
Speaker 1: where all started. And she used to post on Instagram

333
00:16:03,400 --> 00:16:06,160
Speaker 1: pictures of cats and literally that was it was like, Oh,

334
00:16:06,240 --> 00:16:08,600
Speaker 1: here's my cue cat, here's another cute cat. And then

335
00:16:08,640 --> 00:16:11,360
Speaker 1: one day she was really upset about something and she

336
00:16:11,480 --> 00:16:15,120
Speaker 1: posted something like some anti Israel thing and it just exploded.

337
00:16:15,840 --> 00:16:18,720
Speaker 1: Literally like everything before was two or three likes, This

338
00:16:18,880 --> 00:16:21,400
Speaker 1: was sure two hundred thousand and then that was it.

339
00:16:21,520 --> 00:16:23,560
Speaker 1: Everything from there on like that was her, that was

340
00:16:23,720 --> 00:16:25,720
Speaker 1: she had been turned into.

341
00:16:26,200 --> 00:16:27,360
Speaker 4: This wave to the algorithm.

342
00:16:27,440 --> 00:16:32,320
Speaker 2: Yeah right, I guess, Thank goodness, because I hated those cats.

343
00:16:32,960 --> 00:16:35,560
Speaker 2: If she posts another picture, would it be accurate.

344
00:16:35,160 --> 00:16:38,280
Speaker 1: To say that that that social media is a technology

345
00:16:38,320 --> 00:16:39,840
Speaker 1: that started good and ended bad.

346
00:16:41,200 --> 00:16:43,560
Speaker 3: It started with good instincts, This idea back to the

347
00:16:43,600 --> 00:16:46,240
Speaker 3: early days of the Internet, that there's this tim Berners

348
00:16:46,320 --> 00:16:49,320
Speaker 3: Lee and everyone else about how having more people connected

349
00:16:49,520 --> 00:16:51,680
Speaker 3: is a great thing and it's a going to make

350
00:16:51,720 --> 00:16:53,120
Speaker 3: people more aware of what goes on.

351
00:16:53,200 --> 00:16:54,280
Speaker 4: But what really.

352
00:16:54,040 --> 00:16:57,400
Speaker 3: Happens is it goes back to you read like like

353
00:16:57,440 --> 00:17:00,160
Speaker 3: Captain Cook traveling in the South Season, every time you

354
00:17:00,160 --> 00:17:03,000
Speaker 3: had a first encounter with another civilization, it's be like,

355
00:17:03,440 --> 00:17:04,359
Speaker 3: we need to kill those.

356
00:17:04,240 --> 00:17:06,400
Speaker 4: People, right because they're really dangerous.

357
00:17:06,680 --> 00:17:09,560
Speaker 3: Social the Internet and then social media does that at

358
00:17:09,600 --> 00:17:12,560
Speaker 3: scale and in real time. This constant encounter with aliens,

359
00:17:12,560 --> 00:17:14,840
Speaker 3: with people that are like, dude, this guy's nothing like me,

360
00:17:14,920 --> 00:17:18,360
Speaker 3: and this makes me angry. So this is constant first encounters,

361
00:17:18,480 --> 00:17:20,680
Speaker 3: like back to South Sea voyages. And that's the thing

362
00:17:20,720 --> 00:17:24,000
Speaker 3: that I think was the naive bit from Burners, Lee

363
00:17:24,000 --> 00:17:25,480
Speaker 3: and others in the early days of the Internet, the

364
00:17:25,520 --> 00:17:29,760
Speaker 3: idea that this version of first encounters will actually work really,

365
00:17:29,800 --> 00:17:32,600
Speaker 3: really well as all of these tribes start colliding online.

366
00:17:32,640 --> 00:17:35,280
Speaker 3: You know, it's the exact opposite. When tribes encounter each other,

367
00:17:35,359 --> 00:17:37,760
Speaker 3: it is a kind of you know, extinction anger event

368
00:17:37,760 --> 00:17:39,359
Speaker 3: where it's like I want I normally don't want to

369
00:17:39,400 --> 00:17:41,960
Speaker 3: see them, I don't want them to exist amore. That's

370
00:17:42,000 --> 00:17:45,120
Speaker 3: the thing that I think, and that's that has always existed.

371
00:17:45,200 --> 00:17:49,600
Speaker 3: But these technologies, social media in particular, was naively thought

372
00:17:49,640 --> 00:17:51,400
Speaker 3: to not have that problem, and of course the exact

373
00:17:51,440 --> 00:17:53,840
Speaker 3: opposite has been the case. It's created this flywheel of

374
00:17:53,920 --> 00:17:56,800
Speaker 3: first encounter anger and you see that as soon as

375
00:17:56,800 --> 00:17:58,439
Speaker 3: you as soon as you jump on, and then if

376
00:17:58,440 --> 00:18:01,399
Speaker 3: you give the algorithm any signal and say, spend more

377
00:18:01,440 --> 00:18:04,639
Speaker 3: than a second looking at something, it's like, bam, I

378
00:18:05,080 --> 00:18:07,399
Speaker 3: know what. I know what to show you all the time, right,

379
00:18:07,440 --> 00:18:09,439
Speaker 3: And so then of course the whole process continues. So

380
00:18:09,440 --> 00:18:13,520
Speaker 3: it starts off with these genuinely laudable intentions, but it

381
00:18:13,920 --> 00:18:16,600
Speaker 3: misunderstands the nature of how tribes react and how.

382
00:18:16,520 --> 00:18:17,399
Speaker 4: People react to each other.

383
00:18:18,520 --> 00:18:22,800
Speaker 2: At replies on Twitter of all caps wrong? Are the

384
00:18:22,880 --> 00:18:26,680
Speaker 2: disease infested blankets of the twenty first century?

385
00:18:27,840 --> 00:18:28,960
Speaker 4: Is that really a thing to do.

386
00:18:28,920 --> 00:18:32,159
Speaker 1: That he does? He wants My favorite Keith rebart to

387
00:18:32,200 --> 00:18:35,800
Speaker 1: it was was I it was somebody something about real estate,

388
00:18:35,840 --> 00:18:37,920
Speaker 1: and he said, I know more about them in real

389
00:18:38,000 --> 00:18:41,159
Speaker 1: estate than any human being on the planet. And you're wrong.

390
00:18:42,000 --> 00:18:43,800
Speaker 4: That's the best, all right?

391
00:18:43,880 --> 00:18:46,400
Speaker 1: So can I talk about the thing that I think

392
00:18:46,480 --> 00:18:52,920
Speaker 1: is the worst technology ever created in humanstry. Door Dash.

393
00:18:53,320 --> 00:18:57,159
Speaker 3: Other technologies may start war, but I have I have

394
00:18:57,200 --> 00:18:58,159
Speaker 3: an objection.

395
00:18:59,200 --> 00:19:04,639
Speaker 2: Nothing to door Sure, Era sizes the bowl up, but

396
00:19:04,640 --> 00:19:07,119
Speaker 2: but all right, right, let's let's hear it.

397
00:19:07,119 --> 00:19:09,800
Speaker 1: Food deliver to the house. Okay, here's the thing. I

398
00:19:10,160 --> 00:19:12,919
Speaker 1: was years ago in high school. I was a pizza

399
00:19:12,920 --> 00:19:13,480
Speaker 1: delivery driver.

400
00:19:13,640 --> 00:19:15,879
Speaker 2: This is gonna start. Wait, we'll go way back, was

401
00:19:15,920 --> 00:19:16,800
Speaker 2: a Ted speech version.

402
00:19:16,880 --> 00:19:18,840
Speaker 4: I've got a personalized anecdote at the beginning.

403
00:19:19,200 --> 00:19:22,240
Speaker 1: And I and I delivered wings for wings and things, okay,

404
00:19:22,480 --> 00:19:25,080
Speaker 1: and in Florida. And I was very good at my job,

405
00:19:25,080 --> 00:19:26,360
Speaker 1: by the way. I always got it there in under

406
00:19:26,359 --> 00:19:30,159
Speaker 1: thirty minutes. Anyway, they paid us to do this. That

407
00:19:30,240 --> 00:19:32,919
Speaker 1: was our job, right the restaurant, and you call the

408
00:19:32,960 --> 00:19:35,520
Speaker 1: restaurant and you would say whatever. So then along comes

409
00:19:35,520 --> 00:19:37,800
Speaker 1: door Dash, and they're like, hey, we're gonna we're gonna

410
00:19:37,800 --> 00:19:39,439
Speaker 1: make it easier for the restaurant so they don't have

411
00:19:39,440 --> 00:19:43,600
Speaker 1: to pay anyone to go and deliver the food. Right,

412
00:19:44,080 --> 00:19:46,200
Speaker 1: We're gonna make it so the customer has to pay,

413
00:19:46,760 --> 00:19:49,760
Speaker 1: which to me is just the beginning of this. So

414
00:19:49,880 --> 00:19:51,760
Speaker 1: then when you go to door dash, and I've done

415
00:19:51,800 --> 00:19:54,080
Speaker 1: this experience, like, there's a restaurant we go to and

416
00:19:54,119 --> 00:19:56,320
Speaker 1: the kids get pasta, and it's twelve ninety nine for

417
00:19:56,359 --> 00:19:58,919
Speaker 1: some butter pasta. You order it on door dash nineteen

418
00:19:59,000 --> 00:20:02,480
Speaker 1: ninety nine. Okay, they inflate all the prices and then

419
00:20:02,560 --> 00:20:05,560
Speaker 1: on top of that, they add these twenty percent surch

420
00:20:05,640 --> 00:20:07,760
Speaker 1: charges and there's this thing and that thing and blah

421
00:20:07,760 --> 00:20:08,800
Speaker 1: blah blahlah blah.

422
00:20:08,920 --> 00:20:11,880
Speaker 2: So you realize you don't have to use this right, No,

423
00:20:12,080 --> 00:20:12,920
Speaker 2: that's where you're wrong.

424
00:20:13,000 --> 00:20:15,159
Speaker 1: Let me just finish real quick, let me just finish.

425
00:20:15,400 --> 00:20:18,159
Speaker 2: Here's here's no, here's the thing you finish.

426
00:20:18,280 --> 00:20:21,600
Speaker 1: But no, So, so a meal that you would pay

427
00:20:21,720 --> 00:20:24,840
Speaker 1: fifty dollars for before, right, or like a bunch of

428
00:20:24,840 --> 00:20:28,240
Speaker 1: meals is now literally one hundred dollars. You are paying

429
00:20:28,800 --> 00:20:31,879
Speaker 1: double because of all the bullshit fees that they add,

430
00:20:32,359 --> 00:20:35,400
Speaker 1: and you do if you want to have food delivered,

431
00:20:35,600 --> 00:20:39,800
Speaker 1: you have no choice because the restaurants no longer hire people.

432
00:20:40,280 --> 00:20:43,960
Speaker 1: They offset it to us, the customer, and it drives

433
00:20:44,000 --> 00:20:45,920
Speaker 1: me absolutely fucking bonkers.

434
00:20:46,240 --> 00:20:48,640
Speaker 3: So your objection is that they have to stay in business, right,

435
00:20:48,640 --> 00:20:51,480
Speaker 3: that they have the charge higher prices as it's they're

436
00:20:51,480 --> 00:20:54,480
Speaker 3: just their business model. Yeah, their business model is evil.

437
00:20:55,800 --> 00:20:58,080
Speaker 3: What's your feeling about last minute airline bookings? If you

438
00:20:58,119 --> 00:20:59,679
Speaker 3: noticed they raise the prices, if you should look at

439
00:20:59,680 --> 00:21:00,600
Speaker 3: the last is that.

440
00:21:00,520 --> 00:21:03,880
Speaker 1: Evil to No, here's the thing. It's it's evil because

441
00:21:03,960 --> 00:21:05,800
Speaker 1: you It doesn't you don't have a choice.

442
00:21:05,960 --> 00:21:06,760
Speaker 4: You do have a choice.

443
00:21:06,760 --> 00:21:09,200
Speaker 3: You don't if you want to order this, who's making

444
00:21:09,320 --> 00:21:09,800
Speaker 3: you buy it?

445
00:21:12,080 --> 00:21:16,199
Speaker 2: Let's let's imagine a world now in which nick door

446
00:21:16,280 --> 00:21:19,600
Speaker 2: dash app stops working. Oh my god, the kids can't eat.

447
00:21:21,720 --> 00:21:24,119
Speaker 4: Yeah, you don't.

448
00:21:24,280 --> 00:21:24,640
Speaker 2: I tried.

449
00:21:24,920 --> 00:21:26,920
Speaker 1: My point is it's here's my point.

450
00:21:27,359 --> 00:21:29,159
Speaker 2: You don't have to let the whole You don't have

451
00:21:29,160 --> 00:21:30,520
Speaker 2: to know. I believe the.

452
00:21:30,440 --> 00:21:33,080
Speaker 1: Whole point of a technology is to make things easier, right,

453
00:21:33,200 --> 00:21:35,000
Speaker 1: That's what we try. That's why we create these things

454
00:21:35,080 --> 00:21:37,399
Speaker 1: because we're lazy. We want things to be easier. They

455
00:21:37,400 --> 00:21:39,280
Speaker 1: want them better. Quicker, blah blah blah blah blah.

456
00:21:39,280 --> 00:21:43,280
Speaker 2: Amazon, the idea you're lazy complaining about you have to

457
00:21:43,359 --> 00:21:47,679
Speaker 2: use doord so so so is the possible like a

458
00:21:47,680 --> 00:21:48,280
Speaker 2: block away.

459
00:21:48,480 --> 00:21:51,159
Speaker 1: No, it's all these different places all over the Everyone

460
00:21:51,200 --> 00:21:54,040
Speaker 1: I know who agrees with me except for YouTube fuckers.

461
00:21:54,119 --> 00:21:59,959
Speaker 2: Okay, this is my favorite gas lighting move.

462
00:22:00,320 --> 00:22:08,560
Speaker 1: Everyone everyone agrees with me. Except everyone experience. Anyway, I

463
00:22:08,560 --> 00:22:10,680
Speaker 1: would just like to point out that I think it is.

464
00:22:10,760 --> 00:22:14,119
Speaker 1: It is a disgusting company, and they and they screw

465
00:22:14,200 --> 00:22:18,719
Speaker 1: over the customers and it is not okay, it's not.

466
00:22:19,040 --> 00:22:22,440
Speaker 1: You don't need to charge people that much money because

467
00:22:23,000 --> 00:22:25,959
Speaker 1: when you when you come in and you if there

468
00:22:26,000 --> 00:22:27,200
Speaker 1: were I give.

469
00:22:29,920 --> 00:22:30,920
Speaker 4: Are these people who agree with you?

470
00:22:30,960 --> 00:22:33,560
Speaker 1: By the way, I'm just everyone is just like you go.

471
00:22:34,200 --> 00:22:36,000
Speaker 1: I get into this conversation with people all the time.

472
00:22:36,040 --> 00:22:39,360
Speaker 1: By the way, people, you you don't have door Dash

473
00:22:39,440 --> 00:22:40,000
Speaker 1: on your phone.

474
00:22:40,240 --> 00:22:42,520
Speaker 2: I do have door Dash on You said you deleted it.

475
00:22:43,240 --> 00:22:48,480
Speaker 2: You you said you deleted it, you deleted Keep going.

476
00:22:48,480 --> 00:22:50,960
Speaker 1: You use Slice all the time, which incidentally is a

477
00:22:51,040 --> 00:22:54,080
Speaker 1: much nicer company. But anyway, keep going. What's your question?

478
00:22:56,240 --> 00:22:59,880
Speaker 2: I just I don't get where you're saying, like they

479
00:23:00,040 --> 00:23:02,719
Speaker 2: don't have to you don't have to use it, but

480
00:23:02,800 --> 00:23:03,120
Speaker 2: you don't.

481
00:23:03,800 --> 00:23:06,120
Speaker 1: But if you have two choices, you have door Dash

482
00:23:06,160 --> 00:23:08,240
Speaker 1: and you have uber Eats, they both did the same thing.

483
00:23:08,359 --> 00:23:13,400
Speaker 2: Right the other choices you walk to a rostrant. Yeah,

484
00:23:13,400 --> 00:23:13,720
Speaker 2: but you.

485
00:23:15,520 --> 00:23:17,600
Speaker 1: Got the kids and you and your meetings and D

486
00:23:17,760 --> 00:23:21,280
Speaker 1: D D D D yes, okay, that is another choice. However,

487
00:23:22,400 --> 00:23:24,600
Speaker 1: if you want to eat at your local Chinese place

488
00:23:24,640 --> 00:23:28,200
Speaker 1: and it's twelve blocks away and your kids are hungry. Yes,

489
00:23:28,280 --> 00:23:31,199
Speaker 1: it's you have other choices, but you don't. At the

490
00:23:31,200 --> 00:23:33,880
Speaker 1: same time, I think.

491
00:23:33,800 --> 00:23:36,120
Speaker 3: You're redefining the word choice to mean things that doesn't mean.

492
00:23:38,720 --> 00:23:42,080
Speaker 3: This is my This is my takeaway from this. No

493
00:23:42,119 --> 00:23:44,159
Speaker 3: one's forcing you to use it, and your objection is

494
00:23:44,160 --> 00:23:46,239
Speaker 3: that because you like using it, they charge you more

495
00:23:46,280 --> 00:23:47,160
Speaker 3: than you would like to pay.

496
00:23:47,280 --> 00:23:50,119
Speaker 1: Okay, let's let's let's take let's take a different example.

497
00:23:50,200 --> 00:23:51,159
Speaker 1: Let's just imagine.

498
00:23:51,320 --> 00:23:53,960
Speaker 2: Let's take first class seats. Yeah, there's too much money.

499
00:23:54,080 --> 00:23:55,959
Speaker 2: I want to sit in row one.

500
00:23:56,680 --> 00:24:00,440
Speaker 4: Yeah, I like it up there. Why don't charge me

501
00:24:00,480 --> 00:24:00,760
Speaker 4: so much?

502
00:24:00,800 --> 00:24:01,320
Speaker 2: I want to know.

503
00:24:01,760 --> 00:24:02,960
Speaker 4: Yeah, this bugs me.

504
00:24:03,320 --> 00:24:09,080
Speaker 1: If you I'm clearly I'm clearly the minority here. But

505
00:24:09,080 --> 00:24:10,360
Speaker 1: but I just think.

506
00:24:10,160 --> 00:24:12,119
Speaker 2: I'll tell you what is going to be.

507
00:24:12,119 --> 00:24:17,800
Speaker 3: Next week we have another episode that about Davos. This

508
00:24:17,840 --> 00:24:20,560
Speaker 3: is Davos, by the way, This is literally Davos. You've

509
00:24:20,560 --> 00:24:22,360
Speaker 3: got a bunch of people who all feel the same

510
00:24:22,400 --> 00:24:23,879
Speaker 3: way as you do, and you all sit around and

511
00:24:23,880 --> 00:24:26,680
Speaker 3: talk to each other and say yeah, yeah, Not only

512
00:24:26,720 --> 00:24:28,600
Speaker 3: that it's like this, it's also just as bad as

513
00:24:28,600 --> 00:24:31,200
Speaker 3: you thoughts. You're this like echo chamber of reinforcing views

514
00:24:31,200 --> 00:24:32,440
Speaker 3: of the most nonsensical idea.

515
00:24:32,640 --> 00:24:36,240
Speaker 1: But I think it's I think that here's a question. No,

516
00:24:36,359 --> 00:24:40,240
Speaker 1: this is a genuine question. This is no seriously genuine question.

517
00:24:40,720 --> 00:24:44,440
Speaker 1: Does the restaurant benefit from this? No? Does the customer

518
00:24:44,480 --> 00:24:45,040
Speaker 1: beneit from this?

519
00:24:45,359 --> 00:24:45,520
Speaker 2: No?

520
00:24:45,800 --> 00:24:48,080
Speaker 1: The only person that benefits from this is door dash

521
00:24:48,400 --> 00:24:49,520
Speaker 1: because the restaurant.

522
00:24:49,680 --> 00:24:51,720
Speaker 4: I think the word benefit means something. You don't think

523
00:24:51,720 --> 00:24:52,760
Speaker 4: it mean what?

524
00:24:52,760 --> 00:24:54,280
Speaker 1: What does it mean people?

525
00:24:54,280 --> 00:24:56,199
Speaker 4: If it doesn't benefit people, why are they doing it?

526
00:24:56,240 --> 00:24:58,919
Speaker 4: Because they have no choice. They can't come up with

527
00:24:58,960 --> 00:25:00,160
Speaker 4: calories any other way.

528
00:25:00,160 --> 00:25:03,199
Speaker 1: Because the restaurant can't hire someone to We should just

529
00:25:03,240 --> 00:25:05,960
Speaker 1: move on because this is I'm not gonna this argument

530
00:25:06,119 --> 00:25:06,920
Speaker 1: is not landing.

531
00:25:07,680 --> 00:25:10,639
Speaker 4: So all right, No, I think it's interesting, but I

532
00:25:10,640 --> 00:25:12,120
Speaker 4: think it's some kind of weird la thing.

533
00:25:12,200 --> 00:25:14,199
Speaker 1: Just it's not. It's not it's I was in New

534
00:25:14,280 --> 00:25:15,520
Speaker 1: York and then people were talking about it.

535
00:25:15,520 --> 00:25:21,600
Speaker 2: In New York. Everyone was talking, it's you're you're kind

536
00:25:21,600 --> 00:25:26,520
Speaker 2: of making this boiled frog analogy of this stupid pot

537
00:25:26,640 --> 00:25:30,040
Speaker 2: is getting hotter and hotter and it's not benefiting anyone. Well,

538
00:25:30,119 --> 00:25:31,480
Speaker 2: get out of the pot, or.

539
00:25:31,400 --> 00:25:33,520
Speaker 3: They got me addicted to this technology, and and now

540
00:25:33,560 --> 00:25:35,040
Speaker 3: I've discovered they keep raising prices.

541
00:25:35,119 --> 00:25:35,600
Speaker 4: Not like it.

542
00:25:35,720 --> 00:25:38,160
Speaker 1: No, if I could call the restaurant and order from

543
00:25:38,200 --> 00:25:40,840
Speaker 1: them and get it at the price that the restaurant charges,

544
00:25:41,160 --> 00:25:43,520
Speaker 1: and then I can tip the driver, great, I would

545
00:25:43,520 --> 00:25:44,680
Speaker 1: do that. But that's not an option.

546
00:25:44,880 --> 00:25:46,840
Speaker 3: Yeah, but that's because the restaurant doesn't want to be

547
00:25:46,840 --> 00:25:49,920
Speaker 3: in the delivery business. That's that's the real thing you

548
00:25:49,960 --> 00:25:52,280
Speaker 3: should take away from this is restaurants want to be

549
00:25:52,280 --> 00:25:55,760
Speaker 3: in the restaurant business, so they use services to deliver food,

550
00:25:56,040 --> 00:25:59,119
Speaker 3: and those services charge accordingly because people are willing to

551
00:25:59,119 --> 00:25:59,399
Speaker 3: pay it.

552
00:26:00,000 --> 00:26:02,840
Speaker 1: Disagree anyway.

553
00:26:03,760 --> 00:26:07,280
Speaker 3: What are your feelings about gravity? I really don't like gravity.

554
00:26:07,560 --> 00:26:10,160
Speaker 3: I've had a huge nuisance constantly being stuck to the ground.

555
00:26:10,280 --> 00:26:13,480
Speaker 2: Yeah, you take one step and you just go another foot,

556
00:26:14,160 --> 00:26:15,520
Speaker 2: bounding over the right.

557
00:26:15,760 --> 00:26:16,639
Speaker 4: Do I speak to about this?

558
00:26:16,680 --> 00:26:16,960
Speaker 2: Yeah?

559
00:26:17,000 --> 00:26:20,600
Speaker 1: The next bad invention should we do? Bitcoin effective altruism?

560
00:26:20,640 --> 00:26:25,240
Speaker 2: I think the next bad invention is the crypto investor.

561
00:26:28,840 --> 00:26:29,600
Speaker 4: I like that idea.

562
00:26:29,680 --> 00:26:32,120
Speaker 1: Yeah, they're but not crypto itself.

563
00:26:32,480 --> 00:26:36,199
Speaker 2: Crypto itself is innocuous. It's the crypto investor that's gotta go.

564
00:26:36,960 --> 00:26:40,320
Speaker 3: Yeah, the crypto investor is this weird creature where they're

565
00:26:40,359 --> 00:26:42,800
Speaker 3: constantly moving the goalpost. It's like, originally this was going

566
00:26:42,840 --> 00:26:45,359
Speaker 3: to drive transactions. Yeah, it was a store of value,

567
00:26:45,400 --> 00:26:47,240
Speaker 3: and then the world nearly blew up and the value

568
00:26:47,280 --> 00:26:49,760
Speaker 3: of crypto went down. It's like, dude, you don't have

569
00:26:49,800 --> 00:26:51,680
Speaker 3: anything laught. What's the thing that this is supposed to

570
00:26:51,720 --> 00:26:52,159
Speaker 3: be tied to?

571
00:26:52,280 --> 00:26:54,800
Speaker 1: And then everyone started getting their home started getting robbed.

572
00:26:54,840 --> 00:26:58,000
Speaker 1: Did you read the story was it in Bloomberg about

573
00:26:58,040 --> 00:26:58,920
Speaker 1: the guy Meow?

574
00:26:59,400 --> 00:27:00,280
Speaker 4: Oh no, I didn't see that.

575
00:27:00,320 --> 00:27:02,399
Speaker 1: Oh my god, it was crazy. There was this crazy

576
00:27:02,440 --> 00:27:05,720
Speaker 1: story this older couple who had put their retirement into

577
00:27:05,840 --> 00:27:09,560
Speaker 1: crypto and they had like three million bucks and they

578
00:27:09,560 --> 00:27:11,920
Speaker 1: get a they heard this like tapping on the door

579
00:27:11,960 --> 00:27:13,359
Speaker 1: in the middle of the night, was like the glassed

580
00:27:13,440 --> 00:27:16,760
Speaker 1: or all of a sudden the glass smashed, and then

581
00:27:16,760 --> 00:27:19,080
Speaker 1: they were like held hostage. And there's a guy who

582
00:27:19,119 --> 00:27:21,800
Speaker 1: was running this whole ring where he would hire low

583
00:27:21,920 --> 00:27:26,280
Speaker 1: level thugs, thugs to go and like rob people. And

584
00:27:26,359 --> 00:27:27,560
Speaker 1: the guy's name was Meow.

585
00:27:27,840 --> 00:27:28,800
Speaker 4: I didn't catch the name.

586
00:27:28,960 --> 00:27:29,880
Speaker 1: Meaw was a good name.

587
00:27:30,520 --> 00:27:32,400
Speaker 2: No, there's going to be a lot more of that,

588
00:27:32,480 --> 00:27:36,360
Speaker 2: because a lot more you're I mean the coinbase hack,

589
00:27:36,400 --> 00:27:41,399
Speaker 2: I think exposed seventy thousand, seven thousand or seventy thousand names,

590
00:27:41,440 --> 00:27:44,399
Speaker 2: and the names that were distributed to the thought to

591
00:27:44,480 --> 00:27:47,879
Speaker 2: the criminals to me like to we weren't like I

592
00:27:47,960 --> 00:27:51,879
Speaker 2: found seventy thousand random accounts. It's like holders of lots

593
00:27:51,880 --> 00:27:55,600
Speaker 2: of crypto. So people, the bad guys know where who

594
00:27:55,680 --> 00:27:56,840
Speaker 2: has it, how much they have.

595
00:27:57,080 --> 00:27:59,960
Speaker 3: Yeah, And the thing that I find there was a

596
00:28:00,040 --> 00:28:02,520
Speaker 3: big piece just recently about this, I think on Welster

597
00:28:02,520 --> 00:28:06,880
Speaker 3: Return or somewhere, we're talking about the unintended effects of crypto,

598
00:28:07,040 --> 00:28:11,320
Speaker 3: specifically that to fund crypto. One of the accidental or

599
00:28:11,359 --> 00:28:14,440
Speaker 3: sort of intermediary inventions was this idea of stable coins,

600
00:28:14,560 --> 00:28:16,640
Speaker 3: these coins that are tied to the dollar but allow

601
00:28:16,720 --> 00:28:19,119
Speaker 3: you to sort of store with relative liquidity and you

602
00:28:19,119 --> 00:28:20,960
Speaker 3: can go back and forth between crypto and preserve the

603
00:28:20,960 --> 00:28:23,800
Speaker 3: dollar value. And there's a bunch of people out there

604
00:28:23,800 --> 00:28:26,720
Speaker 3: with these stable coins. And the big thing now is

605
00:28:26,720 --> 00:28:29,920
Speaker 3: that stable coins are attracting a significant amount of assets,

606
00:28:29,920 --> 00:28:31,520
Speaker 3: in part because the dollars a week, but a bunch

607
00:28:31,520 --> 00:28:35,680
Speaker 3: of other things. But that's profoundly destabilizing to the existing

608
00:28:35,720 --> 00:28:38,840
Speaker 3: banking system, because we have, in particular with the smaller

609
00:28:38,880 --> 00:28:42,000
Speaker 3: regional US banks, they're very lending dependent. So the way

610
00:28:42,040 --> 00:28:43,760
Speaker 3: that you obviously run a book if you're a lending

611
00:28:43,800 --> 00:28:47,160
Speaker 3: dependent regional bank is you have to have significant deposits,

612
00:28:47,240 --> 00:28:49,560
Speaker 3: because that's how it works. The deposit ratios dictate how

613
00:28:49,640 --> 00:28:51,760
Speaker 3: much lending you can do. But if that money is

614
00:28:51,800 --> 00:28:54,760
Speaker 3: flowing out the door and increasingly going into stable coins,

615
00:28:55,200 --> 00:28:57,200
Speaker 3: it reduces the amount of lending you can do, which

616
00:28:57,280 --> 00:28:59,320
Speaker 3: becomes circular because then you can in returns.

617
00:28:59,560 --> 00:29:01,480
Speaker 4: And so there was a big report out from.

618
00:29:01,400 --> 00:29:03,160
Speaker 3: I don't know, the International Monetary Fund or someone like

619
00:29:03,160 --> 00:29:06,720
Speaker 3: this just in the last week or two talking about

620
00:29:06,720 --> 00:29:11,560
Speaker 3: how stable coins are actually destabilizing for a reason that

621
00:29:11,720 --> 00:29:13,600
Speaker 3: wasn't the reason we thought they were bad. So we're

622
00:29:13,600 --> 00:29:17,920
Speaker 3: in this weird moment where cryptos destabilizing for unexpected.

623
00:29:17,360 --> 00:29:18,800
Speaker 1: Stable coins are destabilizing.

624
00:29:18,800 --> 00:29:19,880
Speaker 4: Stable coins are destabilized.

625
00:29:20,200 --> 00:29:22,200
Speaker 3: We thought that the reason why they were destabilizing was

626
00:29:22,240 --> 00:29:25,720
Speaker 3: because the reserves that these things were holding tether and

627
00:29:25,760 --> 00:29:29,480
Speaker 3: others weren't really We're fairly opaque, so it wasn't obvious

628
00:29:29,480 --> 00:29:32,280
Speaker 3: that they had sufficient reserves to justify the peg against

629
00:29:32,280 --> 00:29:35,800
Speaker 3: the currencies. And then so that was one source of risk, right,

630
00:29:35,840 --> 00:29:37,960
Speaker 3: because then you can have a run the thing doesn't

631
00:29:37,960 --> 00:29:38,720
Speaker 3: have enough reserves.

632
00:29:38,720 --> 00:29:40,360
Speaker 4: But then it turns out that actually.

633
00:29:40,120 --> 00:29:43,800
Speaker 3: Now there's a new reason that they're becoming destabilizing, and

634
00:29:43,840 --> 00:29:46,680
Speaker 3: it's because of this deposit ratio problem.

635
00:29:46,320 --> 00:29:46,920
Speaker 4: In regional bank.

636
00:29:47,000 --> 00:29:48,600
Speaker 3: So I actually think you're going to see a wave

637
00:29:48,680 --> 00:29:52,640
Speaker 3: of regional bank failures as a completely drive by consequence

638
00:29:52,880 --> 00:29:55,240
Speaker 3: of the rise of stable coins that no one predicted,

639
00:29:55,320 --> 00:29:57,560
Speaker 3: or wasn't the original reason that crypto was invented. It

640
00:29:57,600 --> 00:30:00,000
Speaker 3: was actually an intermediary technology, and yet here we are.

641
00:30:00,280 --> 00:30:02,680
Speaker 2: Drive by consequence is a great phrase. I'm going to

642
00:30:02,760 --> 00:30:03,880
Speaker 2: start using that all the time.

643
00:30:04,080 --> 00:30:06,480
Speaker 1: What was the word he used before? I forget it

644
00:30:06,600 --> 00:30:07,160
Speaker 1: was a good word?

645
00:30:08,920 --> 00:30:13,720
Speaker 2: Monoculture forma college uniform of college.

646
00:30:14,560 --> 00:30:20,720
Speaker 1: Wait, are stable coins tie to the value of the

647
00:30:20,800 --> 00:30:21,760
Speaker 1: dollar or do they.

648
00:30:21,840 --> 00:30:22,880
Speaker 4: Know they converted a dollar?

649
00:30:23,000 --> 00:30:26,920
Speaker 1: Yeah, but that's so if the value of the dollar changes,

650
00:30:27,240 --> 00:30:29,560
Speaker 1: does the stable coin or is is pegged to the current.

651
00:30:29,440 --> 00:30:31,360
Speaker 2: Value the dollar? So why would.

652
00:30:31,120 --> 00:30:33,760
Speaker 1: Someone put money into the stable coin versus.

653
00:30:33,640 --> 00:30:36,280
Speaker 3: Well, because hey, they're nervous about what's happening with the dollar,

654
00:30:36,440 --> 00:30:38,800
Speaker 3: so they feel like this is a place to hide.

655
00:30:38,800 --> 00:30:42,880
Speaker 3: But also increasingly because they're paying on deposits. So circle

656
00:30:42,960 --> 00:30:45,160
Speaker 3: and others are now then this is a sort of

657
00:30:45,200 --> 00:30:48,280
Speaker 3: a regulatory hole, but can pay like three and a

658
00:30:48,320 --> 00:30:51,200
Speaker 3: half four percent we're seeing, So that's attracting an inflow

659
00:30:51,240 --> 00:30:53,760
Speaker 3: of assets. And people say, well, it's both protecting making

660
00:30:53,800 --> 00:30:56,000
Speaker 3: it a dollar and paying on my deposit, and so

661
00:30:56,040 --> 00:30:58,040
Speaker 3: why am I not putting money in there? So but

662
00:30:58,200 --> 00:31:01,240
Speaker 3: that money, again is coming from somewhere, so it's sucking

663
00:31:01,280 --> 00:31:03,560
Speaker 3: it out of the regional banks, and the regional banks

664
00:31:03,560 --> 00:31:06,600
Speaker 3: in the US as a result, look increasingly dodgy with

665
00:31:06,640 --> 00:31:08,720
Speaker 3: respect to the assets they have to drive lending. And

666
00:31:08,760 --> 00:31:11,880
Speaker 3: that's obviously bad for the banks, bad for regional economies,

667
00:31:12,360 --> 00:31:14,880
Speaker 3: and all because of you know, these these things, these

668
00:31:14,920 --> 00:31:17,640
Speaker 3: intermediary technologies, this invention called stable coins.

669
00:31:17,760 --> 00:31:20,520
Speaker 2: Do you see Paul came up with a technology that's

670
00:31:20,560 --> 00:31:24,240
Speaker 2: actually causing all sorts of problems. Well, you bitch and

671
00:31:24,320 --> 00:31:27,240
Speaker 2: moan about door dash, which you continue to use.

672
00:31:27,520 --> 00:31:30,000
Speaker 1: I didn't. I use literally lunch today. But that's a

673
00:31:30,000 --> 00:31:32,080
Speaker 1: whole separate host everything I am.

674
00:31:32,240 --> 00:31:34,160
Speaker 3: That's but the thing that I find for me, the

675
00:31:34,200 --> 00:31:37,640
Speaker 3: most interesting bad inventions are ones that have these unintended

676
00:31:37,640 --> 00:31:40,320
Speaker 3: effects that are bad. But in the reverse, the most

677
00:31:40,360 --> 00:31:43,240
Speaker 3: interesting positive inventions are ones where it's like, oh, I

678
00:31:43,320 --> 00:31:45,280
Speaker 3: never expected it would get used for that, right, So

679
00:31:45,320 --> 00:31:48,480
Speaker 3: you find like the idea that in Sub Saharan Africa,

680
00:31:48,480 --> 00:31:52,160
Speaker 3: people who are organizing entire businesses around just mobile mobile phones.

681
00:31:52,320 --> 00:31:54,560
Speaker 3: That's really interesting. We didn't predict that what happened, So

682
00:31:54,600 --> 00:31:57,400
Speaker 3: that's a positive thing that happened from an invention. Is

683
00:31:57,440 --> 00:31:59,960
Speaker 3: probably an idea that this was actually an interesting invention.

684
00:32:00,120 --> 00:32:02,240
Speaker 3: But then on the other side, crypto is one where

685
00:32:02,240 --> 00:32:06,120
Speaker 3: it's all you see are these sort of malign consequences.

686
00:32:05,520 --> 00:32:06,840
Speaker 1: And I think that goes back to what you were

687
00:32:06,840 --> 00:32:09,200
Speaker 1: saying earlier, which I which I've always found the most

688
00:32:09,200 --> 00:32:12,520
Speaker 1: fascinating about technology is that you can't predict what it

689
00:32:12,640 --> 00:32:14,280
Speaker 1: is going to do and how it's going to be used,

690
00:32:14,280 --> 00:32:17,080
Speaker 1: no matter how you try. And in Silicon Valley that's

691
00:32:17,080 --> 00:32:18,400
Speaker 1: always oh, we know it's going to do this, and

692
00:32:18,440 --> 00:32:19,640
Speaker 1: we know it's going to do that, And that's never

693
00:32:19,720 --> 00:32:20,040
Speaker 1: the case.

694
00:32:20,120 --> 00:32:20,320
Speaker 4: Ever.

695
00:32:21,240 --> 00:32:23,560
Speaker 3: No, most technologies, like you see people used to be.

696
00:32:24,080 --> 00:32:26,520
Speaker 3: I'd run into people when I was working on in

697
00:32:26,520 --> 00:32:27,760
Speaker 3: the financial industry who.

698
00:32:27,680 --> 00:32:31,320
Speaker 4: Used Excel for as PowerPoint. I was like, how is

699
00:32:31,320 --> 00:32:32,000
Speaker 4: this even possible?

700
00:32:32,000 --> 00:32:34,360
Speaker 3: They just make gigantic cells, they put fonts, you can

701
00:32:34,440 --> 00:32:35,840
Speaker 3: grow the side of the fund and then like you're

702
00:32:35,920 --> 00:32:37,440
Speaker 3: literally using Excel as PowerPoint.

703
00:32:37,480 --> 00:32:39,720
Speaker 2: Yeah, I just like Excel, but it is better than

704
00:32:39,760 --> 00:32:42,640
Speaker 2: the other way around, trying to use PowerPoint. The math

705
00:32:42,720 --> 00:32:45,880
Speaker 2: is trying to put a pivot table in a PowerPoint.

706
00:32:46,600 --> 00:32:49,320
Speaker 3: But like the most interesting technologies tend to have that

707
00:32:49,320 --> 00:32:53,000
Speaker 3: that attribute that they can use for a lot more

708
00:32:53,080 --> 00:32:55,960
Speaker 3: things than the people who invented them ever anticipated. It's

709
00:32:56,000 --> 00:32:59,640
Speaker 3: just when it comes to these bad inventions social media too,

710
00:33:00,120 --> 00:33:02,000
Speaker 3: to a lesser degree of smoothy crypto or whatever else,

711
00:33:02,000 --> 00:33:04,400
Speaker 3: they often have all of these negative consequences. So it's

712
00:33:04,400 --> 00:33:06,680
Speaker 3: I just think that's a nice way of framing good

713
00:33:06,680 --> 00:33:07,880
Speaker 3: and bad inventions, right.

714
00:33:08,040 --> 00:33:09,640
Speaker 2: The other thing that was on the very good way

715
00:33:09,640 --> 00:33:11,400
Speaker 2: of framing it. That's one of the reasons I think

716
00:33:11,480 --> 00:33:15,120
Speaker 2: the La cruisette is one of the best and technological

717
00:33:15,160 --> 00:33:17,440
Speaker 2: advents of all time because you can cook anything in

718
00:33:17,480 --> 00:33:18,520
Speaker 2: that soccer.

719
00:33:18,360 --> 00:33:22,120
Speaker 1: That's true, and they last forever, and they don't get rusty.

720
00:33:21,880 --> 00:33:24,160
Speaker 2: They're indestructible, and you can just store stuff there.

721
00:33:24,240 --> 00:33:25,560
Speaker 4: Yeah, kids never look.

722
00:33:25,840 --> 00:33:30,040
Speaker 2: Yeah. I use DoorDash to order things and put it.

723
00:33:30,000 --> 00:33:33,880
Speaker 4: In the crosette right as one does. It makes perfect.

724
00:33:56,600 --> 00:34:00,720
Speaker 1: Alternative fuel stick alternative is on the list good or bad?

725
00:34:00,800 --> 00:34:01,160
Speaker 2: I don't know.

726
00:34:01,280 --> 00:34:02,360
Speaker 1: You tell me great.

727
00:34:03,720 --> 00:34:05,600
Speaker 4: It was on the New Scientist list of bad ideas.

728
00:34:05,680 --> 00:34:07,560
Speaker 1: Yeah, yeah, what it was?

729
00:34:07,680 --> 00:34:11,840
Speaker 2: Yeah, New scientists in me and disagreement. It's never happened before.

730
00:34:11,920 --> 00:34:12,920
Speaker 4: It never happened before.

731
00:34:13,239 --> 00:34:15,320
Speaker 2: Me. Wait, how could all turn the fuels be on

732
00:34:15,360 --> 00:34:16,240
Speaker 2: the list of bad.

733
00:34:16,200 --> 00:34:19,800
Speaker 4: Because the energy footprint of producing it? Like, for example,

734
00:34:19,800 --> 00:34:21,040
Speaker 4: somebody is like crossing.

735
00:34:21,719 --> 00:34:26,480
Speaker 2: So it costs, so it takes four gallons of gas

736
00:34:25,280 --> 00:34:30,200
Speaker 2: to one gallon of an alternative fuel. Let's not pick nits.

737
00:34:30,360 --> 00:34:32,640
Speaker 4: That's right. You've got to crack a few eggs to

738
00:34:32,719 --> 00:34:35,360
Speaker 4: make that, to make an energy system.

739
00:34:36,239 --> 00:34:38,520
Speaker 3: No, but I just think that I've got to crack

740
00:34:38,520 --> 00:34:41,000
Speaker 3: a few eggs to make an energy comb That's right.

741
00:34:41,280 --> 00:34:43,640
Speaker 4: That's an old saying. I've heard batch of smee say.

742
00:34:44,320 --> 00:34:46,480
Speaker 2: By the way, can I have an old saying comment?

743
00:34:46,600 --> 00:34:50,160
Speaker 2: Oh go, this is actually great and it's a little

744
00:34:50,160 --> 00:34:52,760
Speaker 2: bit of a non sequitter, but it is an old saying.

745
00:34:53,200 --> 00:34:55,600
Speaker 2: So I was in China trying, you know, we went

746
00:34:55,640 --> 00:35:00,360
Speaker 2: to China and with with Twitter and twenty thirteen to

747
00:35:00,440 --> 00:35:03,279
Speaker 2: try to get you know, fruitlessly, to try to get

748
00:35:03,360 --> 00:35:05,160
Speaker 2: China to you know, hey, you should be why can't

749
00:35:05,200 --> 00:35:08,759
Speaker 2: why can't people in China use Twitter? Within the Great Firewalls?

750
00:35:08,760 --> 00:35:10,280
Speaker 1: Did you meet like the president?

751
00:35:10,640 --> 00:35:13,839
Speaker 2: But I didn't meet the president. I think everyone's a price.

752
00:35:13,920 --> 00:35:17,000
Speaker 2: You think Canada has a president, You think China as

753
00:35:17,000 --> 00:35:17,520
Speaker 2: a president?

754
00:35:17,760 --> 00:35:19,520
Speaker 1: Did you meet the top dog or no?

755
00:35:19,600 --> 00:35:22,000
Speaker 2: I didn't meet Ji. I met some people who are

756
00:35:22,040 --> 00:35:24,240
Speaker 2: like the you know, minister, the head of the Minister

757
00:35:24,320 --> 00:35:29,880
Speaker 2: of the Interior Minister, et cetera, Information Minister, Minston Interior,

758
00:35:29,920 --> 00:35:34,080
Speaker 2: et cetera. And when I would ask, you know, why

759
00:35:34,120 --> 00:35:36,040
Speaker 2: can't you know, why can't you let the people in

760
00:35:36,120 --> 00:35:40,240
Speaker 2: China use Twitter? They were great at They would always say,

761
00:35:40,360 --> 00:35:42,400
Speaker 2: we have an old saying here in China, and they

762
00:35:42,400 --> 00:35:45,520
Speaker 2: would say something to you and he'd be like, it's

763
00:35:45,560 --> 00:35:48,000
Speaker 2: pretty good old saying. And then the people I took

764
00:35:48,040 --> 00:35:50,000
Speaker 2: with me, who are like born raised in Shanghai, after

765
00:35:50,000 --> 00:35:53,640
Speaker 2: the meeting, would always go, there's no such China. You know.

766
00:35:53,800 --> 00:35:56,040
Speaker 2: The saying would be something like, we have an old

767
00:35:56,040 --> 00:35:57,400
Speaker 2: saying in China. If you want to know where the

768
00:35:57,440 --> 00:35:59,719
Speaker 2: car is going, ask the driver. So I would ask you,

769
00:36:00,239 --> 00:36:02,640
Speaker 2: and you know, after the meeting, a couple of engineers

770
00:36:02,640 --> 00:36:05,279
Speaker 2: would be like, China's pretty old country and cars have

771
00:36:05,360 --> 00:36:08,080
Speaker 2: only been around about one hundred years, and that's not

772
00:36:08,120 --> 00:36:10,800
Speaker 2: an old saying in China can possibly fill.

773
00:36:10,600 --> 00:36:12,520
Speaker 1: This, so they just should make them up the whole time.

774
00:36:12,680 --> 00:36:16,279
Speaker 2: They're making up old things. And what are you gonna do?

775
00:36:16,440 --> 00:36:18,040
Speaker 2: Say that's not what do you I don't know.

776
00:36:18,360 --> 00:36:19,960
Speaker 4: This is a huge tourist attraction. You should take a

777
00:36:19,960 --> 00:36:23,239
Speaker 4: picture of it. Yeah, gotcha, Yeah.

778
00:36:22,960 --> 00:36:26,640
Speaker 1: Right, I got you actually used I interviewed you in

779
00:36:26,840 --> 00:36:29,560
Speaker 1: twenty ten, was it on the cover of the business

780
00:36:29,560 --> 00:36:31,480
Speaker 1: section of The York Times? And you actually, I still

781
00:36:31,520 --> 00:36:34,319
Speaker 1: remember this. You had a great saying. You said, I

782
00:36:34,360 --> 00:36:37,200
Speaker 1: asked you a question. You said, it's like the old

783
00:36:37,239 --> 00:36:40,600
Speaker 1: Polish saying not my monkey's not my circus. Yep, it

784
00:36:40,719 --> 00:36:41,320
Speaker 1: was a good one.

785
00:36:41,480 --> 00:36:43,759
Speaker 2: I like that saying it's an actual Polish saying it

786
00:36:43,880 --> 00:36:45,240
Speaker 2: is an actual poles.

787
00:36:45,400 --> 00:36:46,800
Speaker 4: Yeah, my grandparents had that one.

788
00:36:47,120 --> 00:36:50,239
Speaker 2: So it's the better version of play stupid games, win

789
00:36:50,320 --> 00:36:51,120
Speaker 2: stupid prizes.

790
00:36:51,280 --> 00:36:53,480
Speaker 3: Yes, which, which, by the way, wasn't Taylor Swift who

791
00:36:53,520 --> 00:36:55,120
Speaker 3: said that for the first time. I actually I thought

792
00:36:55,160 --> 00:36:56,600
Speaker 3: it was. I got that wrong.

793
00:36:56,800 --> 00:37:03,120
Speaker 2: Anyway, We digress, We digress. I didn't have alternate fuels

794
00:37:03,120 --> 00:37:03,640
Speaker 2: for you do it.

795
00:37:03,800 --> 00:37:06,399
Speaker 4: Let's do it Wikipedia good one.

796
00:37:06,560 --> 00:37:08,879
Speaker 3: I think it's like, hands down, one of the most

797
00:37:08,920 --> 00:37:11,600
Speaker 3: important inventions of last hundred years. There's just no two

798
00:37:11,600 --> 00:37:15,320
Speaker 3: ways around. Unfortunately, it's probably doomed within fine.

799
00:37:15,440 --> 00:37:18,239
Speaker 1: Yeah, because AI is going to completely replace it.

800
00:37:18,239 --> 00:37:20,360
Speaker 3: And that's the problem, right, I mean, it's this notion

801
00:37:20,440 --> 00:37:24,600
Speaker 3: of categorizing human knowledge and having people do it or

802
00:37:24,600 --> 00:37:26,960
Speaker 3: having it i'll say, extracted from people's own knowledge and

803
00:37:26,960 --> 00:37:29,239
Speaker 3: they're doing it on a volunteer basis. Turns out to

804
00:37:29,280 --> 00:37:31,640
Speaker 3: be an incredible invention. But the problem is that you

805
00:37:31,640 --> 00:37:33,640
Speaker 3: can take the humans out of them, out of the loop, right,

806
00:37:33,800 --> 00:37:35,920
Speaker 3: which is what in a sense, large language models do.

807
00:37:36,160 --> 00:37:39,960
Speaker 1: Why do you think that Wikipedia was so successful at

808
00:37:40,040 --> 00:37:44,279
Speaker 1: letting humans do the work and it didn't spiral. I mean,

809
00:37:44,320 --> 00:37:47,160
Speaker 1: there are instances that did spiral into total anarchy, but

810
00:37:47,239 --> 00:37:49,400
Speaker 1: so the largest for the most part, it did not.

811
00:37:50,000 --> 00:37:51,279
Speaker 1: And yet everything else did.

812
00:37:51,640 --> 00:37:53,560
Speaker 3: I think because it was relatively geeky to do the

813
00:37:53,600 --> 00:37:55,000
Speaker 3: things you had to do, editing.

814
00:37:54,760 --> 00:37:57,760
Speaker 2: Things you couldn't just be like, you know, I listened

815
00:37:57,800 --> 00:37:59,759
Speaker 2: to the Joe Rogan podcast and now I'm gonna go

816
00:37:59,840 --> 00:38:02,040
Speaker 2: chack this person would Gipedia and Drake They.

817
00:38:01,920 --> 00:38:04,080
Speaker 4: Had it carefully hidden behind a unix looking thing.

818
00:38:04,160 --> 00:38:07,120
Speaker 2: Yeah, that's right. That turns out to you it turns

819
00:38:07,160 --> 00:38:10,399
Speaker 2: out like command line interface is yeah, going to scare

820
00:38:10,440 --> 00:38:11,200
Speaker 2: a lot of people away.

821
00:38:11,360 --> 00:38:13,040
Speaker 3: Yeah, which and the and the flip side of that

822
00:38:13,160 --> 00:38:15,480
Speaker 3: one of the other you know, I think most important

823
00:38:15,520 --> 00:38:17,880
Speaker 3: inventions that will turn out to have been the Transformer

824
00:38:17,920 --> 00:38:21,480
Speaker 3: model itself. So twenty seventeen, the Google paper attention is

825
00:38:21,520 --> 00:38:24,719
Speaker 3: all you need. Whatever the consequences turned out to be,

826
00:38:24,760 --> 00:38:26,759
Speaker 3: it will be one of those things where weirdly enough,

827
00:38:26,840 --> 00:38:28,440
Speaker 3: like you know, you can't even say, like where were

828
00:38:28,480 --> 00:38:31,520
Speaker 3: reading that happened, because honestly, truth told no idea to

829
00:38:31,640 --> 00:38:33,480
Speaker 3: like two years a year later that it even there

830
00:38:33,480 --> 00:38:36,120
Speaker 3: even was a paper that was saying those kinds of things.

831
00:38:36,239 --> 00:38:39,319
Speaker 3: But nevertheless, in terms of the consequences of it, that's

832
00:38:39,360 --> 00:38:41,120
Speaker 3: going to be one of the most consequential events.

833
00:38:41,200 --> 00:38:44,680
Speaker 2: Of course for sure, right and internal.

834
00:38:44,360 --> 00:38:46,840
Speaker 3: Of course will make Wikipedia much less important invention of

835
00:38:46,840 --> 00:38:47,800
Speaker 3: the last.

836
00:38:47,640 --> 00:38:50,880
Speaker 1: But in your mind it's dick, it's it's one of

837
00:38:50,920 --> 00:38:54,520
Speaker 1: the worst inventions because it will make us extinct or no.

838
00:38:54,640 --> 00:38:57,000
Speaker 2: I think the Transformer paper is one of the great

839
00:38:57,160 --> 00:38:59,240
Speaker 2: It's going to be one of the most widely cited

840
00:38:59,239 --> 00:39:02,920
Speaker 2: and widely used the widely leveraged papers. Ever, I mean,

841
00:39:02,960 --> 00:39:05,120
Speaker 2: I can't think of a I can't think of a

842
00:39:05,200 --> 00:39:11,239
Speaker 2: paper that will be more sore vital to anything that

843
00:39:11,280 --> 00:39:12,640
Speaker 2: happens in the future in the world.

844
00:39:12,800 --> 00:39:15,760
Speaker 1: I I interviewed to the people who wrote the paper.

845
00:39:16,560 --> 00:39:18,160
Speaker 1: I wrote a piece for Vanity Fair a few years

846
00:39:18,160 --> 00:39:20,880
Speaker 1: ago about it and I and I asked them. I

847
00:39:20,920 --> 00:39:23,200
Speaker 1: was like, when you were doing it, did you know

848
00:39:23,280 --> 00:39:24,520
Speaker 1: what you were doing? Like, did you know it was

849
00:39:24,520 --> 00:39:26,200
Speaker 1: going to have this impact? And they were like absolutely no, way,

850
00:39:26,520 --> 00:39:30,439
Speaker 1: Like we were. They were in this little tiny lab

851
00:39:30,480 --> 00:39:32,680
Speaker 1: at Google that no one knew about, no one cared about,

852
00:39:32,880 --> 00:39:37,280
Speaker 1: Sundar didn't even know existed, and they they were trying

853
00:39:37,320 --> 00:39:39,880
Speaker 1: to figure out how to translate language and it was

854
00:39:39,920 --> 00:39:43,160
Speaker 1: a translational and then they realized that it was capable

855
00:39:43,160 --> 00:39:45,880
Speaker 1: of doing these other things. And but I remember I

856
00:39:45,920 --> 00:39:47,640
Speaker 1: was like, well, so when you when you put it out, like,

857
00:39:47,960 --> 00:39:50,800
Speaker 1: was there like a big thing? And they were like no, no, nothing,

858
00:39:50,920 --> 00:39:53,279
Speaker 1: like no one no one at Google, like even their

859
00:39:53,320 --> 00:39:55,080
Speaker 1: own boss was like okay, cool, Like now what's the

860
00:39:55,080 --> 00:39:58,319
Speaker 1: next thing? And and and then cut to two years

861
00:39:58,400 --> 00:39:59,840
Speaker 1: later and the world had changed.

862
00:40:00,200 --> 00:40:03,600
Speaker 3: Yeah, I mean, and there's this the cliched version of

863
00:40:03,640 --> 00:40:06,040
Speaker 3: these stories is that, ah, no one realized how important

864
00:40:06,200 --> 00:40:08,439
Speaker 3: was this thing I'd been doing. I think that's sort

865
00:40:08,440 --> 00:40:10,759
Speaker 3: of true, but its adoption kind of tells you after

866
00:40:10,760 --> 00:40:12,320
Speaker 3: a while that things turned out to be important that

867
00:40:12,360 --> 00:40:14,360
Speaker 3: you didn't realize at the time how important it was

868
00:40:14,400 --> 00:40:16,279
Speaker 3: going to be. Is kind of neither here nor there, right,

869
00:40:16,360 --> 00:40:20,040
Speaker 3: because who knows what people will eventually pick up how

870
00:40:20,040 --> 00:40:22,480
Speaker 3: the invention will you know, diffuse out into the world

871
00:40:22,480 --> 00:40:24,520
Speaker 3: and everything else, just that you invented it. There's lots

872
00:40:24,520 --> 00:40:26,239
Speaker 3: of stuff gets invented never gets picked up.

873
00:40:26,360 --> 00:40:27,880
Speaker 2: Yeah, I think that's what's going to happen with the

874
00:40:27,920 --> 00:40:28,920
Speaker 2: alternative fuels.

875
00:40:29,040 --> 00:40:31,279
Speaker 4: It's a two years turn out.

876
00:40:31,440 --> 00:40:33,399
Speaker 1: The other funny thing about the paper was the guy,

877
00:40:33,480 --> 00:40:34,960
Speaker 1: one of the guys told me he was I said,

878
00:40:35,160 --> 00:40:37,400
Speaker 1: why did you say attentions in the Transformers? And they

879
00:40:37,400 --> 00:40:39,239
Speaker 1: were like, we were watching the movie Transformers and we

880
00:40:39,440 --> 00:40:41,720
Speaker 1: kind of wanted that's part of where it came from.

881
00:40:41,760 --> 00:40:44,600
Speaker 1: Come on, seriously, that's what he said. Unless he lied

882
00:40:44,640 --> 00:40:45,399
Speaker 1: to me.

883
00:40:47,800 --> 00:40:51,919
Speaker 2: Yeah, I don't know about that. That's truly what he said.

884
00:40:51,920 --> 00:40:54,920
Speaker 2: He was that was I'm not disagreeing that it's what

885
00:40:55,000 --> 00:40:58,120
Speaker 2: he said. I'm just saying they probably wasn't watching the

886
00:40:58,160 --> 00:40:59,640
Speaker 2: movie Transformers, while he.

887
00:40:59,680 --> 00:41:03,440
Speaker 3: Wrote, I gave you another invention, another one that I

888
00:41:03,480 --> 00:41:07,000
Speaker 3: really like this Transformers. No, was this idea of the

889
00:41:07,000 --> 00:41:09,719
Speaker 3: electrification of everything, which I think is a really nice

890
00:41:09,719 --> 00:41:13,120
Speaker 3: framing of what's going on right now. That electricity is

891
00:41:13,160 --> 00:41:15,560
Speaker 3: becoming not just the thing that you know, lights your

892
00:41:15,560 --> 00:41:18,840
Speaker 3: house or whatever else, that it's the power substrate underlying

893
00:41:18,880 --> 00:41:22,919
Speaker 3: everything right. It's transportation, it's large language models. It's why

894
00:41:22,920 --> 00:41:25,440
Speaker 3: AI data centers are such a big deal. All of this,

895
00:41:26,000 --> 00:41:27,520
Speaker 3: in a sense, is about at the end of the day,

896
00:41:27,520 --> 00:41:31,439
Speaker 3: it's about trying to power the electrification of everything, which

897
00:41:31,480 --> 00:41:34,560
Speaker 3: is unprecedented because if you go back, you know, two

898
00:41:34,640 --> 00:41:38,120
Speaker 3: hundred years and the prior industry, prior waves of industry revolution,

899
00:41:38,640 --> 00:41:41,840
Speaker 3: it's usually about replacing some of the power with like

900
00:41:42,000 --> 00:41:44,279
Speaker 3: you go from coal to wood or wood to coal,

901
00:41:44,320 --> 00:41:46,200
Speaker 3: depending on where you were, and then you add in

902
00:41:46,239 --> 00:41:47,239
Speaker 3: some other fuel source.

903
00:41:47,280 --> 00:41:48,719
Speaker 4: They all sort of sit on top of each other.

904
00:41:48,719 --> 00:41:52,560
Speaker 3: There's idea that everything is becoming uniformly organized around a

905
00:41:52,560 --> 00:41:54,000
Speaker 3: single way of delivering power.

906
00:41:54,040 --> 00:41:55,720
Speaker 4: Is incredibly interesting, I think.

907
00:41:55,600 --> 00:41:59,280
Speaker 3: And important because electricity has a bunch of interesting attributes,

908
00:41:59,320 --> 00:42:01,239
Speaker 3: not least of which is that you can produce it

909
00:42:01,280 --> 00:42:03,120
Speaker 3: if you want to in relatively clean ways.

910
00:42:03,840 --> 00:42:05,160
Speaker 4: That we aren't the separate problem.

911
00:42:05,200 --> 00:42:07,880
Speaker 2: I was going to say, unfortunately, we've got just the

912
00:42:07,920 --> 00:42:10,040
Speaker 2: sophisticated power grid to handle.

913
00:42:09,760 --> 00:42:11,560
Speaker 4: That that's not going to happen.

914
00:42:11,840 --> 00:42:14,920
Speaker 3: But that idea that everything is becoming in one way

915
00:42:15,000 --> 00:42:17,359
Speaker 3: or another tied to electricity is I just think if

916
00:42:17,800 --> 00:42:20,640
Speaker 3: you look back to the sort of the electrification in

917
00:42:20,640 --> 00:42:23,120
Speaker 3: the United States between like I don't know, nineteen hundred

918
00:42:23,120 --> 00:42:27,080
Speaker 3: and nineteen twenty, that was seen as a relatively narrow

919
00:42:27,120 --> 00:42:31,000
Speaker 3: phenomenon about just providing lights and eventually our conditioning came

920
00:42:31,040 --> 00:42:33,360
Speaker 3: along in other things, but that it would become ubiquitous

921
00:42:33,360 --> 00:42:36,600
Speaker 3: and underneath everything is really should be startling because that

922
00:42:36,640 --> 00:42:37,840
Speaker 3: was never obviously.

923
00:42:37,480 --> 00:42:39,879
Speaker 1: Well, it's startling, but it's also quite terrifying because once

924
00:42:39,960 --> 00:42:42,040
Speaker 1: the power goes out from some sort of.

925
00:42:42,440 --> 00:42:45,400
Speaker 4: Whatever grid based attack.

926
00:42:45,280 --> 00:42:48,759
Speaker 1: We will be dead within the next three weeks, well

927
00:42:48,800 --> 00:42:51,440
Speaker 1: at least if you live in somewhere cold, no where

928
00:42:51,480 --> 00:42:53,360
Speaker 1: are you going to get your antibiotics and your food

929
00:42:53,400 --> 00:42:56,000
Speaker 1: and your fresh water. It's like we would be There's

930
00:42:56,000 --> 00:42:58,759
Speaker 1: a State Department report that predicted ninety five percent of

931
00:42:58,880 --> 00:43:01,560
Speaker 1: America is dead within six months to a year.

932
00:43:01,840 --> 00:43:03,879
Speaker 4: Yeah, like a pulse attack or whatever else.

933
00:43:03,920 --> 00:43:06,480
Speaker 3: No, anything, but the thing that but most technologies it's

934
00:43:06,480 --> 00:43:08,799
Speaker 3: interesting is it creates new attack surfaces, new ways of

935
00:43:08,840 --> 00:43:12,040
Speaker 3: attacking systems in ways that people didn't expect, you know.

936
00:43:12,040 --> 00:43:14,000
Speaker 3: I give the example of stable coins in the context

937
00:43:14,000 --> 00:43:17,360
Speaker 3: of crypto, new attack surface, same thing with electricity and

938
00:43:17,400 --> 00:43:20,279
Speaker 3: everything else. That's what's That's what I think happens all

939
00:43:20,320 --> 00:43:21,920
Speaker 3: the time with these in the same way that like

940
00:43:22,000 --> 00:43:23,960
Speaker 3: I just saw with it this week last week recently,

941
00:43:25,600 --> 00:43:28,000
Speaker 3: was it Sam or Dario one of the two one

942
00:43:28,040 --> 00:43:30,520
Speaker 3: of our two favorite AI CEO was talking about how

943
00:43:30,880 --> 00:43:33,240
Speaker 3: it was Sam who was talking about how they're releasing

944
00:43:33,280 --> 00:43:37,000
Speaker 3: this a new version of codex is it what's the

945
00:43:37,160 --> 00:43:40,560
Speaker 3: what's the quad code for open ai? And his comment

946
00:43:40,840 --> 00:43:44,560
Speaker 3: was that this essentially will radically increase the risk to

947
00:43:44,640 --> 00:43:48,600
Speaker 3: everyone because this thing is so adept at producing, producing

948
00:43:48,719 --> 00:43:52,719
Speaker 3: and curing viruses in terms of like code and everything else.

949
00:43:52,960 --> 00:43:55,000
Speaker 3: And I was like, this is bizarre, this idea that

950
00:43:55,040 --> 00:43:58,640
Speaker 3: we should be rewarding people for technologies that vastly increase

951
00:43:58,719 --> 00:44:01,000
Speaker 3: the attack surface. Right, this is a weird kind of

952
00:44:01,040 --> 00:44:03,839
Speaker 3: invention to be excited about. And it's sort of analogous

953
00:44:03,880 --> 00:44:06,640
Speaker 3: to you know, robber breaks into my house and says,

954
00:44:06,680 --> 00:44:08,239
Speaker 3: you know, you don't don't bust me, like I showed

955
00:44:08,280 --> 00:44:09,640
Speaker 3: you a security flaw in your house.

956
00:44:09,800 --> 00:44:12,520
Speaker 4: Right, No, no, no, no, no, that's not the way this word is. Right.

957
00:44:12,600 --> 00:44:14,879
Speaker 3: So, this is this interesting moment we're at in terms

958
00:44:14,880 --> 00:44:18,440
Speaker 3: of these inventions where it's not just accidental, it's actually

959
00:44:18,520 --> 00:44:21,120
Speaker 3: known at the time that the invention is made that

960
00:44:21,200 --> 00:44:23,680
Speaker 3: it's got these these incredibly.

961
00:44:23,200 --> 00:44:27,680
Speaker 2: Dangerous side intended or known the known bad side effects. Yeah,

962
00:44:27,719 --> 00:44:28,960
Speaker 2: not a drive by side. Right.

963
00:44:29,000 --> 00:44:31,480
Speaker 3: So that's that's unusual at this at this moment in

964
00:44:31,480 --> 00:44:33,239
Speaker 3: inventing things because it's often turns out to be a

965
00:44:33,280 --> 00:44:35,839
Speaker 3: surprise to everybody that's got it when you actually say

966
00:44:35,880 --> 00:44:37,240
Speaker 3: it as part of the launch event.

967
00:44:38,120 --> 00:44:40,239
Speaker 2: That's part of them, it's part of the marketing video.

968
00:44:40,360 --> 00:44:44,160
Speaker 2: Yeah wait, but wait, there's more, just one more thing.

969
00:44:44,400 --> 00:44:45,279
Speaker 4: We could kill us all.

970
00:44:45,440 --> 00:44:49,160
Speaker 1: Do you remember when Microsoft put out their their new

971
00:44:49,320 --> 00:44:52,680
Speaker 1: S one, when they when they did the deal with

972
00:44:52,680 --> 00:44:55,560
Speaker 1: with open Ai. You you sent it to us and

973
00:44:55,320 --> 00:44:58,160
Speaker 1: in the bottom it was like, uh, things that could

974
00:44:58,200 --> 00:45:00,520
Speaker 1: go wrong? It was like could destroy are you human?

975
00:45:02,400 --> 00:45:04,640
Speaker 1: And you were like, there's a problem if you're putting

976
00:45:04,719 --> 00:45:07,760
Speaker 1: out a new technology that is just in a web browser,

977
00:45:07,760 --> 00:45:08,839
Speaker 1: and that's what you have to put in there.

978
00:45:08,920 --> 00:45:10,640
Speaker 3: Yeah, and I mean some of this is obviously just

979
00:45:10,960 --> 00:45:13,920
Speaker 3: loyally cover your ass stuff. But the idea that some

980
00:45:14,000 --> 00:45:16,719
Speaker 3: of these technologies that it's knowable, that they have these

981
00:45:16,800 --> 00:45:18,520
Speaker 3: kinds of things, that's not true. When Nike does a

982
00:45:18,560 --> 00:45:20,480
Speaker 3: new shoe, Yeah, it doesn't have to go in the

983
00:45:20,560 --> 00:45:20,839
Speaker 3: S one.

984
00:45:21,080 --> 00:45:26,360
Speaker 4: Yeah, this may make people never stop running. They should

985
00:45:26,400 --> 00:45:29,919
Speaker 4: be so lucky. That's unusual in this in this current

986
00:45:29,960 --> 00:45:30,719
Speaker 4: wave of technoy Do.

987
00:45:30,719 --> 00:45:34,040
Speaker 1: You think that do you think that fusion is gonna

988
00:45:35,000 --> 00:45:37,240
Speaker 1: become a reality in the not too distant future.

989
00:45:37,760 --> 00:45:39,239
Speaker 4: Every ten years I say it's going to be in

990
00:45:39,280 --> 00:45:40,360
Speaker 4: ten years.

991
00:45:40,640 --> 00:45:42,880
Speaker 2: I find out what is the opposite of the elon

992
00:45:43,000 --> 00:45:45,400
Speaker 2: predictions where every ten years you say it's going to

993
00:45:45,480 --> 00:45:47,879
Speaker 2: be happen next year, one month.

994
00:45:47,960 --> 00:45:49,200
Speaker 4: Oh yeah, it's imminent now.

995
00:45:49,360 --> 00:45:52,120
Speaker 2: So I mean, what was the what was the robotaxi

996
00:45:52,160 --> 00:45:55,560
Speaker 2: prediction At the end of twenty twenty five there'll be

997
00:45:55,600 --> 00:45:57,600
Speaker 2: one million robotex.

998
00:45:57,120 --> 00:46:00,600
Speaker 1: And how many are there? Like twenty seven thirty seven?

999
00:46:01,160 --> 00:46:04,799
Speaker 2: Come on, come on, get stick, get with It is

1000
00:46:04,840 --> 00:46:09,439
Speaker 2: only off by nine hundred ninety nine and sixty three.

1001
00:46:10,160 --> 00:46:13,880
Speaker 3: I mean fusions anyway, fusions are really interesting. Although I

1002
00:46:13,880 --> 00:46:17,680
Speaker 3: will say this, we've probably seen more interesting lad progress

1003
00:46:17,680 --> 00:46:20,160
Speaker 3: in the last four years in the prior twenty five.

1004
00:46:20,480 --> 00:46:23,320
Speaker 3: It's still not at a self sustaining point, so it's

1005
00:46:23,360 --> 00:46:26,640
Speaker 3: not a lot to get excited about, but it's incredible.

1006
00:46:26,160 --> 00:46:28,719
Speaker 4: Progress for where it was at ten years ago.

1007
00:46:28,840 --> 00:46:31,279
Speaker 1: All Right, I'm gonna do one last question for you

1008
00:46:31,320 --> 00:46:33,480
Speaker 1: guys before we wrap this up. Is what is your

1009
00:46:33,560 --> 00:46:35,600
Speaker 1: favorite technology?

1010
00:46:35,680 --> 00:46:44,520
Speaker 2: Dick those lot crousette God. I love that thing. I

1011
00:46:44,600 --> 00:46:45,399
Speaker 2: use it all the time.

1012
00:46:45,440 --> 00:46:47,040
Speaker 4: Probably should color.

1013
00:46:47,040 --> 00:46:49,000
Speaker 2: I wrap it in a blanket and sing to it

1014
00:46:49,040 --> 00:46:49,399
Speaker 2: at Like.

1015
00:46:49,440 --> 00:46:50,480
Speaker 1: What color is yours?

1016
00:46:50,680 --> 00:46:53,359
Speaker 2: I have multiple colors? Which one is your yellow one?

1017
00:46:53,360 --> 00:46:54,120
Speaker 2: In the maroon one?

1018
00:46:54,120 --> 00:46:54,799
Speaker 1: I like the yellow ones.

1019
00:46:54,840 --> 00:46:56,000
Speaker 2: I don't care for the blue one.

1020
00:46:56,239 --> 00:46:57,120
Speaker 1: Nah, I don't like the blue.

1021
00:46:57,200 --> 00:46:59,160
Speaker 2: Shouldn't cook in anything that's bright blue.

1022
00:46:59,239 --> 00:47:01,800
Speaker 1: I don't like the white either, because it gets dirty

1023
00:47:01,840 --> 00:47:02,520
Speaker 1: and you can't clean it.

1024
00:47:02,560 --> 00:47:04,080
Speaker 2: And I've never seen the white one, and I hope

1025
00:47:04,120 --> 00:47:05,839
Speaker 2: never to see the right one.

1026
00:47:07,320 --> 00:47:07,800
Speaker 4: Staining.

1027
00:47:08,360 --> 00:47:10,320
Speaker 1: I like the I have an orange and a yellow

1028
00:47:10,560 --> 00:47:11,359
Speaker 1: or really like the yellow.

1029
00:47:12,440 --> 00:47:13,960
Speaker 4: I have a hunch of people don't actually know what

1030
00:47:14,000 --> 00:47:14,319
Speaker 4: it is.

1031
00:47:14,560 --> 00:47:16,080
Speaker 2: What the look we're talking about.

1032
00:47:16,320 --> 00:47:17,279
Speaker 1: Everyone knows what it is.

1033
00:47:17,320 --> 00:47:19,240
Speaker 4: I don't think so what.

1034
00:47:19,719 --> 00:47:22,440
Speaker 2: It's the baking, it's the next tell them, tell them

1035
00:47:22,480 --> 00:47:22,759
Speaker 2: what the.

1036
00:47:22,960 --> 00:47:28,200
Speaker 1: Made out of iron? And it's a French and cook

1037
00:47:28,840 --> 00:47:30,000
Speaker 1: and cooker.

1038
00:47:30,600 --> 00:47:32,320
Speaker 2: Say it's like it's.

1039
00:47:32,680 --> 00:47:36,000
Speaker 1: It evenly distributes the heat, and it's it's really great

1040
00:47:36,040 --> 00:47:40,160
Speaker 1: for stews and like sauces and and yeah it's it's

1041
00:47:40,200 --> 00:47:41,360
Speaker 1: like a slow cooker, but you put it in the

1042
00:47:41,440 --> 00:47:44,080
Speaker 1: ovena on the stove and it's great. They last for generations.

1043
00:47:44,080 --> 00:47:46,040
Speaker 1: I have one that's probably twenty something years old.

1044
00:47:46,200 --> 00:47:46,520
Speaker 4: Wow.

1045
00:47:46,680 --> 00:47:49,120
Speaker 1: Yeah, I don't know them. Yeah, Okay, you.

1046
00:47:49,440 --> 00:47:51,360
Speaker 2: Don't know what this is. You don't cook, You're not

1047
00:47:51,480 --> 00:47:52,919
Speaker 2: he's not a cooker, you know, you don't cook.

1048
00:47:53,040 --> 00:47:53,680
Speaker 4: I don't even eat.

1049
00:47:53,880 --> 00:47:56,440
Speaker 1: Yeah, all right, Paul, what's yours?

1050
00:47:56,800 --> 00:47:57,319
Speaker 2: I don't know.

1051
00:47:57,560 --> 00:47:59,400
Speaker 3: I mean, I think it really depends on the season.

1052
00:47:59,440 --> 00:48:02,840
Speaker 3: These days, I'm like semi obsessed with these yaktracks things.

1053
00:48:03,160 --> 00:48:03,960
Speaker 1: Yeah, what tracks?

1054
00:48:04,040 --> 00:48:04,680
Speaker 4: Yack tracks?

1055
00:48:04,840 --> 00:48:05,840
Speaker 1: What is a yaktrack?

1056
00:48:05,960 --> 00:48:06,160
Speaker 2: Yeah?

1057
00:48:06,280 --> 00:48:07,000
Speaker 4: Tracks are like.

1058
00:48:07,000 --> 00:48:10,680
Speaker 3: These micro spikes that you are sort of rubberized thing

1059
00:48:10,719 --> 00:48:12,600
Speaker 3: and you wrap them around your shoes, kind of like

1060
00:48:12,640 --> 00:48:14,760
Speaker 3: ballet slippers for people who aren't doing ballet.

1061
00:48:15,000 --> 00:48:17,279
Speaker 2: For getting in through the snow. Yeah yeah, yeah, yeah.

1062
00:48:17,280 --> 00:48:21,000
Speaker 3: And they're absolutely amazing for running on things that aren't pavement,

1063
00:48:21,080 --> 00:48:24,680
Speaker 3: so snow, ice and everything else. They're just ridiculously effective.

1064
00:48:24,680 --> 00:48:27,920
Speaker 3: Like you feel like they're an amazing invention. I was

1065
00:48:28,080 --> 00:48:30,640
Speaker 3: running the other day and I literally had people pointing

1066
00:48:30,640 --> 00:48:34,000
Speaker 3: because they're like, you can't run on that surface. I'm like, yacktracks,

1067
00:48:34,000 --> 00:48:38,319
Speaker 3: baby can run on anything. They're genuinely incredible technique enough

1068
00:48:38,360 --> 00:48:40,200
Speaker 3: to look this up. Well, you don't really use them

1069
00:48:40,200 --> 00:48:40,920
Speaker 3: in LA so much.

1070
00:48:41,880 --> 00:48:43,840
Speaker 4: Well, my favorite slipping on hypodermics.

1071
00:48:43,880 --> 00:48:47,120
Speaker 1: My favorite technology is door dash. I'm a huge fan.

1072
00:48:47,800 --> 00:48:49,279
Speaker 4: Now, what is your favorite technology?

1073
00:48:49,400 --> 00:48:50,160
Speaker 1: I think the camera.

1074
00:48:50,520 --> 00:48:51,239
Speaker 4: Oh yeah, I bet that.

1075
00:48:51,800 --> 00:48:56,200
Speaker 1: I love taking photos and uh and uh specifically black

1076
00:48:56,200 --> 00:48:58,560
Speaker 1: and white. Yeah, I'm a huge fan of like the

1077
00:48:58,600 --> 00:49:02,680
Speaker 1: new mic, the monochrome cameras. I just think it's like

1078
00:49:03,560 --> 00:49:06,800
Speaker 1: you just capture a moment and it's and I don't know,

1079
00:49:06,840 --> 00:49:10,560
Speaker 1: there's something very, very rewarding from the experience. I think

1080
00:49:10,600 --> 00:49:12,759
Speaker 1: it's a perfect example of like a technology and a

1081
00:49:12,800 --> 00:49:15,560
Speaker 1: person and them being required together.

1082
00:49:16,360 --> 00:49:17,920
Speaker 4: Yeah no, no, no, And you're good at it, so

1083
00:49:18,000 --> 00:49:19,440
Speaker 4: I mean you've got an eye for that kind of thing.

1084
00:49:19,520 --> 00:49:21,160
Speaker 1: So what I want to do is learn how to

1085
00:49:21,520 --> 00:49:27,120
Speaker 1: yaktrack while taking photos in order in doordesk huge. Well,

1086
00:49:27,120 --> 00:49:29,839
Speaker 1: that concludes another episode of the Nick, Dick and Poll Show.

1087
00:49:30,000 --> 00:49:33,439
Speaker 1: Tune in next week for us talking about I don't

1088
00:49:33,440 --> 00:49:34,880
Speaker 1: know what we're talking about next week, but it's going

1089
00:49:34,960 --> 00:49:35,840
Speaker 1: to be fucking great.