1
00:00:02,480 --> 00:00:06,720
Speaker 1: All Zone Media. Oh hello, fancy meeting you here. I'm

2
00:00:06,720 --> 00:00:20,560
Speaker 1: at Zetron and this is better offline. Also in the

3
00:00:20,600 --> 00:00:24,000
Speaker 1: previous episode, I walk through how General Electrics Jack Welch

4
00:00:24,320 --> 00:00:28,920
Speaker 1: created the disgraceful terms of modern capitalism. A corporate mindset

5
00:00:29,040 --> 00:00:31,560
Speaker 1: where thousands of people are laid off the boost revenues

6
00:00:31,560 --> 00:00:33,960
Speaker 1: when a company is making millions or billions of dollars

7
00:00:34,000 --> 00:00:36,520
Speaker 1: in profits, and an era of growth at all costs.

8
00:00:36,560 --> 00:00:40,479
Speaker 1: Corporations that create nothing but shareholder value, run by an

9
00:00:40,640 --> 00:00:44,199
Speaker 1: entire class of managerial pencil pushers that only really care

10
00:00:44,280 --> 00:00:48,519
Speaker 1: about hitting analyst targets. In this episode, I'm going to

11
00:00:48,560 --> 00:00:52,440
Speaker 1: show you how bad that's been, specifically for the tech industry.

12
00:00:53,560 --> 00:00:56,680
Speaker 1: As ever, please check out the episode details for an

13
00:00:57,000 --> 00:00:59,320
Speaker 1: URL that has sources for everything I'm talking about in

14
00:00:59,360 --> 00:01:02,920
Speaker 1: this and future episodes. Sorry to repeat myself on that one,

15
00:01:02,960 --> 00:01:05,399
Speaker 1: but it's really important. You know. I did not just

16
00:01:05,480 --> 00:01:09,800
Speaker 1: make all of this up anyway. A couple weeks back,

17
00:01:10,040 --> 00:01:13,440
Speaker 1: Open ai CTO, Mira Murati spoke for nearly an hour

18
00:01:13,480 --> 00:01:16,959
Speaker 1: at Dartmouth University, where she recently accepted an honorary which,

19
00:01:17,040 --> 00:01:20,399
Speaker 1: by the way, means fake doctorate of Science for and

20
00:01:20,480 --> 00:01:23,959
Speaker 1: I quote, pushing the frontiers of what neural networks can do.

21
00:01:25,360 --> 00:01:28,840
Speaker 1: This is, by the way, very funny. It's very funny indeed,

22
00:01:29,160 --> 00:01:31,920
Speaker 1: because other than when she graduated with her Bachelor of

23
00:01:31,920 --> 00:01:34,640
Speaker 1: Engineering from the Thayer School of Engineering and for one

24
00:01:34,720 --> 00:01:37,760
Speaker 1: year of her career, Mira Murati has only ever been

25
00:01:37,800 --> 00:01:41,479
Speaker 1: a manager, specifically a project manager, somebody who doesn't write

26
00:01:41,520 --> 00:01:44,679
Speaker 1: code or build software, but points at things and says, yeah,

27
00:01:44,720 --> 00:01:48,840
Speaker 1: we should, we should do that. After graduating, Mira Murati

28
00:01:48,960 --> 00:01:51,920
Speaker 1: worked briefly at a French aerospace company called Zodiac as

29
00:01:51,960 --> 00:01:55,720
Speaker 1: an advanced concepts engineer before joining Tesla in twenty thirteen.

30
00:01:55,840 --> 00:01:58,600
Speaker 1: Is a product manager before moving to Leap Motion from

31
00:01:58,640 --> 00:02:01,320
Speaker 1: twenty sixteen to twenty eighteen, where she was the VP

32
00:02:01,400 --> 00:02:04,520
Speaker 1: of Product and Engineering. A deceiving title again does not

33
00:02:04,720 --> 00:02:08,000
Speaker 1: mean she actually wrote code for a company that also

34
00:02:08,440 --> 00:02:11,040
Speaker 1: burned tens of millions of dollars on a gesture based

35
00:02:11,040 --> 00:02:13,640
Speaker 1: control system for a Mac, only to be acquired for

36
00:02:13,639 --> 00:02:16,320
Speaker 1: thirty million dollars in twenty nineteen at about a tenth

37
00:02:16,400 --> 00:02:20,440
Speaker 1: of its all time value. Her role would have undoubtedly

38
00:02:20,480 --> 00:02:24,560
Speaker 1: involved wrangling gang charts, weird product management stuff, just Google

39
00:02:24,600 --> 00:02:27,080
Speaker 1: it and spec sheets rather than lines of code in

40
00:02:27,120 --> 00:02:31,840
Speaker 1: a text editor. After leaving Leap Motion, mir Murti's career

41
00:02:31,880 --> 00:02:35,359
Speaker 1: trajectory accelerated in a way that's kind of hard to explain.

42
00:02:36,280 --> 00:02:38,519
Speaker 1: She moved to open Ai as its Vice president of

43
00:02:38,560 --> 00:02:42,080
Speaker 1: Applied AI in Partnerships, and was promoted to SVP of Research,

44
00:02:42,160 --> 00:02:45,000
Speaker 1: Product and Partnerships in twenty twenty, and then, at some

45
00:02:45,160 --> 00:02:49,120
Speaker 1: indeterminate time in twenty twenty two, became its Chief Technology officer,

46
00:02:49,320 --> 00:02:52,519
Speaker 1: despite having from what I can tell, exactly one academic

47
00:02:52,560 --> 00:02:54,800
Speaker 1: credit to her name in a list of twenty or

48
00:02:54,800 --> 00:02:58,600
Speaker 1: so people. By the way, open ai co founder Ilia Suitskaeva,

49
00:02:58,760 --> 00:03:00,920
Speaker 1: if you're curious, he has overall one hundred, and I

50
00:03:00,960 --> 00:03:03,440
Speaker 1: realized this is the kind of dick measuring stuff might

51
00:03:03,480 --> 00:03:06,880
Speaker 1: not matter, but in this specific case, for the CTO

52
00:03:07,080 --> 00:03:10,760
Speaker 1: of an organization that's about researching how to build AGI,

53
00:03:11,000 --> 00:03:14,399
Speaker 1: you'd think you'd have an academic But don't worry. There's

54
00:03:14,400 --> 00:03:17,960
Speaker 1: many more annoying things about mirror Murti. During her speech,

55
00:03:18,240 --> 00:03:21,480
Speaker 1: she spoke about how artificial intelligence could kill creative jobs,

56
00:03:21,480 --> 00:03:24,000
Speaker 1: and I quote that shouldn't have been there in the

57
00:03:24,040 --> 00:03:27,960
Speaker 1: first place, something you'd only say if you'd never created

58
00:03:28,000 --> 00:03:31,880
Speaker 1: anything in your entire goddamn life putting that aside, and

59
00:03:31,919 --> 00:03:35,600
Speaker 1: trust me, I'll get to it. Murti, much like Sam Altman,

60
00:03:36,120 --> 00:03:39,440
Speaker 1: seems like she's full of shit, rambling in the biggest

61
00:03:39,520 --> 00:03:42,320
Speaker 1: of ways about how the societal impacts of this work

62
00:03:42,320 --> 00:03:44,840
Speaker 1: are not an afterthought and that you kind of have

63
00:03:44,960 --> 00:03:48,720
Speaker 1: to build them alongside the technology. They are real fucking technical.

64
00:03:49,640 --> 00:03:52,680
Speaker 1: The chief technology officer of the most prominent startup in

65
00:03:52,720 --> 00:03:56,600
Speaker 1: America appears to not know that much about technology, to

66
00:03:56,640 --> 00:03:59,240
Speaker 1: the point that a couple months back, she was unable

67
00:03:59,240 --> 00:04:03,040
Speaker 1: to answer whether open AI's generator video product was trained

68
00:04:03,080 --> 00:04:06,600
Speaker 1: on publicly available data, making a face that kind of

69
00:04:06,640 --> 00:04:09,480
Speaker 1: looks like she was doing a vinegar flavored wasp. And

70
00:04:09,520 --> 00:04:11,600
Speaker 1: I've linked to this. You know the face if you've

71
00:04:11,600 --> 00:04:14,600
Speaker 1: looked it up already. It's not a great one. She

72
00:04:14,680 --> 00:04:18,000
Speaker 1: could have been lying, but Maurati rarely demonstrates any kind

73
00:04:18,000 --> 00:04:22,080
Speaker 1: of technical depth, dancing around answers with these vague, weird explanations.

74
00:04:22,279 --> 00:04:24,480
Speaker 1: And if you're wondering why the host didn't push back

75
00:04:24,480 --> 00:04:26,920
Speaker 1: at her at all, it's because the host at Dartmouth,

76
00:04:26,960 --> 00:04:30,080
Speaker 1: by the way, was Jeffrey Blackburn, a career manager at

77
00:04:30,120 --> 00:04:34,960
Speaker 1: Amazona recently joined door dashes, bored. Maurati's a weird one.

78
00:04:35,160 --> 00:04:37,760
Speaker 1: I've watched a lot of her interviews, a lot of them,

79
00:04:38,320 --> 00:04:41,640
Speaker 1: hours of them. They're all so boring. I cannot explain

80
00:04:41,680 --> 00:04:44,440
Speaker 1: how boring they are. But they're not boring because I'm stupid.

81
00:04:44,480 --> 00:04:49,640
Speaker 1: That's another problem. They're boring because they're meandering, they're nonspecific,

82
00:04:50,000 --> 00:04:52,919
Speaker 1: and the people interviewing her are just like, yeah, wow, damn,

83
00:04:52,920 --> 00:04:55,520
Speaker 1: that's crazy. Yeah, so you think AI is good, then

84
00:04:55,560 --> 00:05:00,560
Speaker 1: oh shit, that's the criticism she's got. She never, much

85
00:05:00,680 --> 00:05:03,360
Speaker 1: like mister Raltman, seems to be in front of anyone

86
00:05:03,360 --> 00:05:06,280
Speaker 1: who knows what they're talking about or is capable of

87
00:05:06,320 --> 00:05:10,280
Speaker 1: asking those questions. And yes, the media interviewing these people

88
00:05:10,279 --> 00:05:13,359
Speaker 1: are limited. They have remits about what they can and

89
00:05:13,400 --> 00:05:15,840
Speaker 1: can't say. I don't speak to the exact fundament of it,

90
00:05:15,920 --> 00:05:19,640
Speaker 1: but it isn't great. But it's very goddamn worrying that

91
00:05:19,680 --> 00:05:21,760
Speaker 1: the future of the tech industry is in the hands

92
00:05:21,760 --> 00:05:24,200
Speaker 1: of people who don't seem to know much about tech.

93
00:05:24,880 --> 00:05:27,960
Speaker 1: Open Ai is run by Sam Altman, an unqualified non

94
00:05:27,960 --> 00:05:30,680
Speaker 1: technical founder who has conned his ways to the heights

95
00:05:30,680 --> 00:05:34,400
Speaker 1: of Silicon Valley. Google is run by San darp As Shai,

96
00:05:34,800 --> 00:05:38,680
Speaker 1: an MBA and a former McKinsey management consultant that's overseen

97
00:05:38,720 --> 00:05:41,760
Speaker 1: the destruction of Google's core products, laid off tens of

98
00:05:41,880 --> 00:05:45,640
Speaker 1: thousands of people, and pushed Google to shoehorn generative AI

99
00:05:46,000 --> 00:05:50,360
Speaker 1: into the core search product with disastrous results including telling

100
00:05:50,400 --> 00:05:53,120
Speaker 1: you to put glue on pizza and eat rocks and

101
00:05:53,200 --> 00:05:57,560
Speaker 1: so on and so bloody forth. Microsoft is run by

102
00:05:57,600 --> 00:06:00,599
Speaker 1: sachy in Adela, yet another MBA that has in his

103
00:06:00,720 --> 00:06:04,359
Speaker 1: tenure overseen layoffs of over thirty thousand people and pushed

104
00:06:04,400 --> 00:06:07,680
Speaker 1: his company deep into the deeply unprofitable and unsustainable world

105
00:06:07,720 --> 00:06:11,239
Speaker 1: of generative AI while laying off people from the Xbox group,

106
00:06:11,400 --> 00:06:14,640
Speaker 1: you know, one of the only beloved things Microsoft has left,

107
00:06:14,960 --> 00:06:17,360
Speaker 1: and also wasting a lot of time on the metaverse.

108
00:06:17,680 --> 00:06:21,080
Speaker 1: But I'll get to him. Amazon CEO Andy Jesse, who

109
00:06:21,080 --> 00:06:25,479
Speaker 1: replaced Jeff Bezos. Surprise surprise, he's another NBA and he

110
00:06:25,560 --> 00:06:28,640
Speaker 1: started Amazon as a marketing manager in nineteen ninety seven.

111
00:06:29,200 --> 00:06:31,120
Speaker 1: To his credit, he came up with the idea of

112
00:06:31,160 --> 00:06:34,240
Speaker 1: Amazon Web Services, which is the cloud platform that a

113
00:06:34,360 --> 00:06:36,599
Speaker 1: chunk of the Internet uses. And by the way, ten

114
00:06:36,640 --> 00:06:39,600
Speaker 1: other people also came up with the idea, and then

115
00:06:39,640 --> 00:06:42,920
Speaker 1: he was made CEO of Amazon in twenty twenty one,

116
00:06:43,200 --> 00:06:46,320
Speaker 1: at which point a man called Adam Seleipski was made

117
00:06:46,360 --> 00:06:50,560
Speaker 1: CEO of Amazon Web Services and guess what, he also

118
00:06:50,640 --> 00:06:53,640
Speaker 1: has a Harvard MBA. But then he was replaced in

119
00:06:53,760 --> 00:06:56,680
Speaker 1: March by another guy who also had an MBA, this

120
00:06:56,760 --> 00:07:00,719
Speaker 1: time from Northwestern. It's always these management guys, the most

121
00:07:00,760 --> 00:07:03,640
Speaker 1: technical and one of the most profitable parts of Amazon,

122
00:07:04,200 --> 00:07:07,880
Speaker 1: their cloud storage and processing product. And I'm crushing it

123
00:07:07,920 --> 00:07:10,360
Speaker 1: down for the podcast Calm Down. If you super technical,

124
00:07:11,240 --> 00:07:14,200
Speaker 1: you'd think that would be a tech guy. You think

125
00:07:14,240 --> 00:07:16,120
Speaker 1: that would be someone who actually knew what they were

126
00:07:16,160 --> 00:07:19,360
Speaker 1: got down talking about other than the osmosis of being

127
00:07:19,400 --> 00:07:22,920
Speaker 1: in rooms with people who actually do the work. And

128
00:07:23,080 --> 00:07:25,320
Speaker 1: the reason I'm harping on about this is the founding

129
00:07:25,320 --> 00:07:28,560
Speaker 1: story of Amazon Web Services. Maybe one of the greatest

130
00:07:28,600 --> 00:07:33,000
Speaker 1: lies in texts history. I can find no maybe a

131
00:07:33,000 --> 00:07:36,000
Speaker 1: little specific evidence as to who the actual architect of

132
00:07:36,000 --> 00:07:41,080
Speaker 1: AWS was. Just this hindless muling about how Andy Jasse

133
00:07:41,200 --> 00:07:43,920
Speaker 1: and NBA built one of the most important pieces of

134
00:07:43,960 --> 00:07:49,520
Speaker 1: technological infrastructure of all time. It's just bollocks. And Jesse

135
00:07:49,720 --> 00:07:52,880
Speaker 1: regularly uses the Royal we to talk about how we

136
00:07:53,440 --> 00:07:56,440
Speaker 1: he built Amazon Web Services, despite the fact that he

137
00:07:56,480 --> 00:07:58,640
Speaker 1: didn't build shit. He didn't build anything at all. He

138
00:07:58,680 --> 00:08:03,000
Speaker 1: was a manager, managing managers. Jeff Bezos, who was the CEO,

139
00:08:03,080 --> 00:08:06,160
Speaker 1: who was another manager. It's all managers, all managers doing

140
00:08:06,200 --> 00:08:10,640
Speaker 1: a management centipedeugh And what little I can find suggests

141
00:08:10,680 --> 00:08:13,640
Speaker 1: that much of the actual technical work to build Amazon

142
00:08:13,680 --> 00:08:16,840
Speaker 1: Web Services was done by people like then CTO Alan

143
00:08:17,160 --> 00:08:20,440
Speaker 1: Vermulen and Brewster Kale, who founded a company called Alexa

144
00:08:20,520 --> 00:08:23,280
Speaker 1: Internet that Amazon acquired in nineteen ninety nine. There was

145
00:08:23,320 --> 00:08:27,280
Speaker 1: instrumental to spinning up the services that became Amazon Web Services,

146
00:08:27,400 --> 00:08:29,760
Speaker 1: two names that I've never really read in the many

147
00:08:29,760 --> 00:08:33,160
Speaker 1: many articles crediting Jasse as the architect behind Amazon's most

148
00:08:33,160 --> 00:08:40,520
Speaker 1: profitable service, yet arguably the most Welsh pilled management based

149
00:08:40,640 --> 00:08:44,920
Speaker 1: Silicon Valley staple is Meta, a company dominated by NBA's

150
00:08:45,000 --> 00:08:48,079
Speaker 1: like Sheryl Samdberg. It's first chief operating officer, who has left,

151
00:08:48,800 --> 00:08:51,920
Speaker 1: replaced by a guy called Javier Olivan who also has

152
00:08:51,920 --> 00:08:55,000
Speaker 1: an NBA. Facebook's Chief People Officer Lori Gohler, and the

153
00:08:55,080 --> 00:08:59,040
Speaker 1: chief privacy officer Michael Protty, all NBAS. Yet what makes

154
00:08:59,240 --> 00:09:03,120
Speaker 1: Meta such a Welshian nightmare is its dedication to making

155
00:09:03,160 --> 00:09:05,640
Speaker 1: its products worse in the search of growth, with career

156
00:09:05,679 --> 00:09:09,079
Speaker 1: product managers like CMO Alex Schultz and head of product

157
00:09:09,160 --> 00:09:12,280
Speaker 1: Naomi Glit dominating the company from its earliest days, and

158
00:09:12,320 --> 00:09:16,360
Speaker 1: creating a culture that focused entirely on gaming Facebook's metrics.

159
00:09:16,400 --> 00:09:20,120
Speaker 1: To please Mark Zuckerberg's demand for perpetual ten percent year

160
00:09:20,200 --> 00:09:24,040
Speaker 1: over year growth in core growth metrics, Meta has laid

161
00:09:24,040 --> 00:09:26,199
Speaker 1: off of a thirteen percent of its workforce in the

162
00:09:26,280 --> 00:09:29,560
Speaker 1: last year, over eleven thousand people, despite the fact that

163
00:09:29,600 --> 00:09:32,600
Speaker 1: the company has been profitable for over a decade, even

164
00:09:32,640 --> 00:09:36,960
Speaker 1: while plunging tens of billions of dollars into Zuckerberg's reality

165
00:09:37,040 --> 00:09:41,880
Speaker 1: Labs Metaverse division and authorizing fifty billion dollars in stock buybacks.

166
00:09:42,440 --> 00:09:45,280
Speaker 1: In many ways, Zuckerberg is Welsh perfected the CEO of

167
00:09:45,320 --> 00:09:48,680
Speaker 1: a company that provides a continuously deteriorating service that prints

168
00:09:48,720 --> 00:09:51,800
Speaker 1: money or gaming its metrics, such as no longer reporting

169
00:09:51,800 --> 00:09:54,600
Speaker 1: its monthly active users on earnings to make Wall Street

170
00:09:54,600 --> 00:09:58,360
Speaker 1: believe that it's a quote good company. It doesn't matter

171
00:09:58,640 --> 00:10:01,240
Speaker 1: that Meta has effectively given up on trying to solve

172
00:10:01,320 --> 00:10:04,800
Speaker 1: its massive problems with AI generated spam and scams and

173
00:10:04,840 --> 00:10:07,160
Speaker 1: four h four media reports that Meta has turned its

174
00:10:07,200 --> 00:10:10,600
Speaker 1: back on the experts that helped bolster its content moderation

175
00:10:10,800 --> 00:10:15,760
Speaker 1: services sadly, and this really matters because the markets still

176
00:10:15,800 --> 00:10:18,960
Speaker 1: love Meta, even though they punish the company briefly in

177
00:10:19,040 --> 00:10:22,120
Speaker 1: recent earnings for a and I quote light forecast, where

178
00:10:22,160 --> 00:10:26,480
Speaker 1: it quote raised investor expectations due to its improved financial

179
00:10:26,520 --> 00:10:29,760
Speaker 1: performance in recent quarters, leaving little room for error. According

180
00:10:29,760 --> 00:10:32,560
Speaker 1: to the NBC, a business network that Jack Welch owned

181
00:10:32,600 --> 00:10:35,719
Speaker 1: a large chunk of through his acquisition of NBC as

182
00:10:35,760 --> 00:10:39,040
Speaker 1: part of a deal the General Electric acquired RCA Corp.

183
00:10:39,080 --> 00:10:43,319
Speaker 1: In nineteen eighty five, it all goes back to Welch,

184
00:10:43,640 --> 00:10:46,760
Speaker 1: and it's also important to add that despite all of

185
00:10:46,800 --> 00:10:51,840
Speaker 1: these layoffs and these light forecasts, Meta executives received bonuses

186
00:10:51,880 --> 00:10:54,480
Speaker 1: when they fired thousands of people in twenty twenty three.

187
00:10:55,760 --> 00:10:58,760
Speaker 1: Google isn't much better since san Dar Pashai, a career

188
00:10:58,760 --> 00:11:02,280
Speaker 1: product manager in NBA, came CEO in twenty fifteen. Google's

189
00:11:02,280 --> 00:11:06,320
Speaker 1: culture is soured, giving Android inventor Andy Ruben ninety million

190
00:11:06,360 --> 00:11:09,120
Speaker 1: dollars in twenty eighteen to leave the company after credible

191
00:11:09,120 --> 00:11:13,080
Speaker 1: sexual misconduct claims causing a massive walkout over Google's forced

192
00:11:13,160 --> 00:11:17,120
Speaker 1: arbitration clauses over harassment and discrimination that muzzles victims and

193
00:11:17,160 --> 00:11:20,720
Speaker 1: empowers the fucking assholes to hide behind Google and gives

194
00:11:20,720 --> 00:11:23,960
Speaker 1: Google the ability to hide its failure to police these people.

195
00:11:25,000 --> 00:11:27,199
Speaker 1: This happened in the same year that others walked out

196
00:11:27,240 --> 00:11:30,800
Speaker 1: over Google's work with the Pentagon. Under Peshai, Google has

197
00:11:30,840 --> 00:11:33,320
Speaker 1: been fined billions of dollars by the European Union for

198
00:11:33,360 --> 00:11:36,760
Speaker 1: anti trust violations around its Android operating system, and has

199
00:11:36,800 --> 00:11:39,760
Speaker 1: found itself embroiled in a three year long anti trust

200
00:11:39,760 --> 00:11:42,360
Speaker 1: battle with the US Department of Justice around its anti

201
00:11:42,440 --> 00:11:45,679
Speaker 1: competitive approach to keeping Google Search on top, including paying

202
00:11:45,720 --> 00:11:48,640
Speaker 1: Apple twenty billion dollars in twenty twenty two to the

203
00:11:48,679 --> 00:11:51,760
Speaker 1: be the fault search engine on Safari, their web browser.

204
00:11:53,000 --> 00:11:56,200
Speaker 1: Under Peshai, Google has replaced hard working lifers that built

205
00:11:56,240 --> 00:11:59,120
Speaker 1: the very foundation of the company with contractors and on

206
00:11:59,160 --> 00:12:03,920
Speaker 1: the higher levels scumbags cretins like Prabagar Ragavan and Jerry Dishler,

207
00:12:04,160 --> 00:12:07,920
Speaker 1: the latter of which transparently intimidated the Google Search team

208
00:12:08,160 --> 00:12:11,640
Speaker 1: to increase ad revenue generate by search In emails revealed

209
00:12:11,640 --> 00:12:15,400
Speaker 1: in the trial from March twenty nineteen, you'll be shocked

210
00:12:15,400 --> 00:12:25,120
Speaker 1: by the way to hear that Jerry Dishler has an MBA. Yet,

211
00:12:25,160 --> 00:12:28,200
Speaker 1: as with Meta, and as with all of these companies

212
00:12:28,240 --> 00:12:32,320
Speaker 1: excluding open Ai, which is not public, Google prints money

213
00:12:32,600 --> 00:12:35,400
Speaker 1: knitting over twenty three billion dollars in its first quarter

214
00:12:35,440 --> 00:12:38,319
Speaker 1: twenty twenty four earnings the same ones were announced its

215
00:12:38,320 --> 00:12:42,040
Speaker 1: first dividend, and a seventy billion dollar stock buyback program.

216
00:12:42,240 --> 00:12:45,320
Speaker 1: It doesn't matter that Google Search is incredibly broken as

217
00:12:45,320 --> 00:12:48,120
Speaker 1: a result of Google's constant drive to increase revenue, or

218
00:12:48,120 --> 00:12:50,720
Speaker 1: that Google has decided to generate results on Search using

219
00:12:50,800 --> 00:12:56,120
Speaker 1: unreliable generative AI that generates insane answers. Alphabet Google's holding

220
00:12:56,160 --> 00:12:59,760
Speaker 1: company has seen its stock continually rise since much of

221
00:12:59,760 --> 00:13:03,880
Speaker 1: this year, even after the eating rocks thing. Doesn't that

222
00:13:03,920 --> 00:13:06,679
Speaker 1: fill your veins full of bile? How doesn't it make you?

223
00:13:06,840 --> 00:13:10,280
Speaker 1: It just really really makes me angry. It makes you

224
00:13:10,440 --> 00:13:12,559
Speaker 1: very annoyed. I don't like this. I don't like that

225
00:13:13,240 --> 00:13:15,880
Speaker 1: you and I I guess I'm a podcast that's probably not.

226
00:13:15,960 --> 00:13:18,520
Speaker 1: But regular people like you. You go to a job,

227
00:13:18,559 --> 00:13:20,040
Speaker 1: you do the job. If you do the job badly,

228
00:13:20,080 --> 00:13:23,079
Speaker 1: you get shit canned. Fair enough, That's what happens, right,

229
00:13:23,360 --> 00:13:26,520
Speaker 1: These guys, they get paid through the nose for it,

230
00:13:27,000 --> 00:13:29,280
Speaker 1: they get appreciate it, they get a go get them

231
00:13:29,320 --> 00:13:33,000
Speaker 1: boy for fucking everything up. It's just disgusting. It makes

232
00:13:33,040 --> 00:13:36,800
Speaker 1: me very upset. And as I've said previously, this is

233
00:13:36,840 --> 00:13:40,480
Speaker 1: a special kind of financial nihilism that the market continues

234
00:13:40,520 --> 00:13:43,680
Speaker 1: to reward, one that's poisoned Silicon Valley and elevated men

235
00:13:43,720 --> 00:13:46,760
Speaker 1: and woman like Sam Altman and Mira Murrati the positions

236
00:13:46,760 --> 00:13:48,880
Speaker 1: of power, despite the fact that neither of them actually

237
00:13:48,920 --> 00:13:53,360
Speaker 1: seems to build technology. Altman himself is a CD charlatan,

238
00:13:53,440 --> 00:13:56,240
Speaker 1: one that's growing incredibly powerful in the valley despite not

239
00:13:56,280 --> 00:13:59,080
Speaker 1: really having done anything. And it shouldn't surprise anyone that,

240
00:13:59,160 --> 00:14:02,440
Speaker 1: as I mentioned previ one of Altman's nine recommended books

241
00:14:02,480 --> 00:14:05,160
Speaker 1: is Winning by Jack Welsch, a book where Welch claims

242
00:14:05,160 --> 00:14:09,080
Speaker 1: that Winning companies and meritocracies and lionizes Kenneth Yue of

243
00:14:09,120 --> 00:14:12,400
Speaker 1: three m's Chinese operations for and I quote throwing out

244
00:14:12,400 --> 00:14:15,320
Speaker 1: the phony ritual of annual budgeting and replacing it with

245
00:14:15,360 --> 00:14:19,080
Speaker 1: Sky's The Limit dialogue about Opportunities, claiming that budgeting at

246
00:14:19,080 --> 00:14:21,680
Speaker 1: three M is not about delivering good enough plans and

247
00:14:21,720 --> 00:14:24,120
Speaker 1: being them, but about having the courage and zeal to

248
00:14:24,160 --> 00:14:27,240
Speaker 1: reach for what can be done. And doesn't that sound

249
00:14:27,520 --> 00:14:30,080
Speaker 1: like more fun than budgeting? Yes, that last part is

250
00:14:30,360 --> 00:14:33,040
Speaker 1: a quote, and I imagine he must have been referring

251
00:14:33,040 --> 00:14:35,840
Speaker 1: to three M bribing Chinese government officials and means of

252
00:14:35,880 --> 00:14:38,480
Speaker 1: selling product between twenty fourteen and twenty seventeen, or the

253
00:14:38,560 --> 00:14:40,400
Speaker 1: thousands of people that three MS laid off in the

254
00:14:40,480 --> 00:14:43,880
Speaker 1: last few decades, including in China. Sure that's what he meant.

255
00:14:44,720 --> 00:14:47,560
Speaker 1: Jack Welsh wouldn't have just been talking I have his ass,

256
00:14:47,560 --> 00:14:50,360
Speaker 1: would he? No. Jack Welch is the man that Sam

257
00:14:50,400 --> 00:14:54,400
Speaker 1: Altman lionizes, a sleazy con artist that continually moved around

258
00:14:54,480 --> 00:14:56,960
Speaker 1: data as a means of making General Electric look bigger

259
00:14:56,960 --> 00:14:59,720
Speaker 1: and stronger than it really was. Kind of like how

260
00:14:59,760 --> 00:15:03,440
Speaker 1: Sam Mortmon regularly says things like an I quote that

261
00:15:03,520 --> 00:15:05,720
Speaker 1: we'll be able to ask our computer to solve all

262
00:15:05,760 --> 00:15:08,720
Speaker 1: of physics. Now, this came up on a previous episode

263
00:15:08,720 --> 00:15:10,720
Speaker 1: of the Interview with Nick the man who said he

264
00:15:10,800 --> 00:15:13,160
Speaker 1: of fucking pile drive. You've mentioned AI again. I just

265
00:15:13,200 --> 00:15:15,200
Speaker 1: want to be clear that's actually what Sam Wrtman said.

266
00:15:15,200 --> 00:15:17,440
Speaker 1: He said, you can ask the computer to solve all

267
00:15:17,440 --> 00:15:20,400
Speaker 1: of physics. This kind of proves that he doesn't understand take,

268
00:15:20,440 --> 00:15:22,200
Speaker 1: but it also proves that he might just be really

269
00:15:22,200 --> 00:15:26,440
Speaker 1: goddamn stupid. How do you solve physics? Sam? What are

270
00:15:26,480 --> 00:15:31,640
Speaker 1: you solving? Physics? Isn't the solution, Sam? What do you?

271
00:15:32,120 --> 00:15:34,360
Speaker 1: Maybe you should have stayed in Stanford instead of dropping

272
00:15:34,360 --> 00:15:38,360
Speaker 1: out and becoming a carst Sam Altman is kind of

273
00:15:38,360 --> 00:15:41,280
Speaker 1: in trouble though, because behind the scenes, generative AI it

274
00:15:41,320 --> 00:15:44,080
Speaker 1: isn't moving the needle, with Isabel Busquette of The Wall

275
00:15:44,120 --> 00:15:46,480
Speaker 1: Street Journal reporting that companies are finding getting the full

276
00:15:46,560 --> 00:15:50,840
Speaker 1: value of AI assistance requires heavy lifting, including in her

277
00:15:50,920 --> 00:15:55,480
Speaker 1: article this hilarious quote from Google Cloud chief evangelist Richard Sirota,

278
00:15:55,920 --> 00:15:58,000
Speaker 1: by the way, as a career product manager, where he

279
00:15:58,040 --> 00:16:00,480
Speaker 1: blames those not finding the value in AI for and

280
00:16:00,520 --> 00:16:03,840
Speaker 1: I quote, not having their data house in order, chirping

281
00:16:03,920 --> 00:16:06,040
Speaker 1: that you can't just buy six units of AI and

282
00:16:06,040 --> 00:16:09,080
Speaker 1: then magically change your business. And you know what, I

283
00:16:09,120 --> 00:16:12,280
Speaker 1: actually agree with him, in essence, it isn't generative AI's fault.

284
00:16:12,280 --> 00:16:16,240
Speaker 1: That it isn't adapting to your workflows or fulfilling anything. No,

285
00:16:16,360 --> 00:16:19,360
Speaker 1: it's your faulty, nasty little pig. You didn't do the

286
00:16:19,400 --> 00:16:23,880
Speaker 1: work to make artificial intelligence smart, right, That's your fault.

287
00:16:23,920 --> 00:16:27,480
Speaker 1: Somehow you should feel ashamed. You should apologize to Sam Moltman.

288
00:16:28,080 --> 00:16:31,480
Speaker 1: Just kidding in all seriousness. The commonality between all of

289
00:16:31,520 --> 00:16:34,400
Speaker 1: these people Jack Welch, suned Up a Shai Mirror, Marati,

290
00:16:34,440 --> 00:16:39,400
Speaker 1: Sam Altmanmuk Zuckerberg, and honestly an alarming amount of CEOs

291
00:16:39,440 --> 00:16:41,560
Speaker 1: inside and outside of tech is that they, along with

292
00:16:41,600 --> 00:16:45,680
Speaker 1: their companies, have kind of escaped humanity. They've escaped the

293
00:16:45,720 --> 00:16:48,800
Speaker 1: human condition. They make their companies bigger for the sake

294
00:16:48,840 --> 00:16:51,440
Speaker 1: of making them bigger, making more money, to increase the

295
00:16:51,560 --> 00:16:54,920
Speaker 1: value of the financial instrument attached to the company, Abstracted

296
00:16:54,960 --> 00:16:59,840
Speaker 1: away from purpose or craft or creativity or production. These

297
00:17:00,800 --> 00:17:04,960
Speaker 1: management concerns MBA's product managers. They're not creators of anything

298
00:17:05,040 --> 00:17:09,440
Speaker 1: other than financial occultism, a dark heart. Whether financial value

299
00:17:09,480 --> 00:17:11,840
Speaker 1: of a company is often separated from what it does

300
00:17:11,960 --> 00:17:16,920
Speaker 1: or whether it's good at it. They're parasites meta calls itself.

301
00:17:17,200 --> 00:17:19,720
Speaker 1: It's still calls itself. Go on their website and look

302
00:17:19,960 --> 00:17:23,800
Speaker 1: a social metaverse company that's and I quote committed to

303
00:17:23,920 --> 00:17:27,679
Speaker 1: keeping people safe and making a positive impact. But at

304
00:17:27,760 --> 00:17:31,080
Speaker 1: its core. It's a near monopolistic social data and advertising

305
00:17:31,080 --> 00:17:34,119
Speaker 1: company that's testing the limits of how little connectivity it

306
00:17:34,160 --> 00:17:37,880
Speaker 1: can provide in its core products without sacrificing advertising revenue.

307
00:17:38,480 --> 00:17:41,119
Speaker 1: Mark Zuckerberg has proven he'll do whatever he needs to,

308
00:17:41,280 --> 00:17:45,480
Speaker 1: including letting deadly misinformation spread on Facebook to keep showing

309
00:17:45,480 --> 00:17:48,600
Speaker 1: that meta is growing. One might be forgiven for thinking

310
00:17:48,600 --> 00:17:51,919
Speaker 1: that Mark Zuckerberg is the exception that he isn't a

311
00:17:52,000 --> 00:17:55,160
Speaker 1: management goon disconnected from the processes of writing code. This

312
00:17:55,200 --> 00:17:58,280
Speaker 1: guy coded Facebook right. This guy's a nerd. He's a

313
00:17:58,560 --> 00:18:01,919
Speaker 1: nerd with his keyboard. He types right wrong. Oh he

314
00:18:02,000 --> 00:18:05,639
Speaker 1: stopped coding eighteen fucking years ago, in two thousand and six.

315
00:18:06,600 --> 00:18:09,359
Speaker 1: This is the guy like just every time I think

316
00:18:09,400 --> 00:18:13,680
Speaker 1: I've really nailed how bad it gets? Hey wait a second,

317
00:18:13,720 --> 00:18:15,960
Speaker 1: hold up, wait second, I just thought about starthing for

318
00:18:16,000 --> 00:18:19,080
Speaker 1: a second though. Wasn't Sheryl Sandberg brought in to make

319
00:18:19,800 --> 00:18:23,359
Speaker 1: Facebook a real mature business. Ah fuck? She shared a

320
00:18:23,359 --> 00:18:26,480
Speaker 1: communications coach with goddamn Jack Welch. It all goes back

321
00:18:26,480 --> 00:18:31,000
Speaker 1: to the all right, sorry sorry sorry, Like Welch. Zuckerberg

322
00:18:31,040 --> 00:18:34,320
Speaker 1: has weathered numerous scandals the social network, a movie that

323
00:18:34,359 --> 00:18:37,479
Speaker 1: framed him as a sociopathic thief. A data leaking scandal

324
00:18:37,520 --> 00:18:39,960
Speaker 1: that may or may not have influenced Mark Paul elections,

325
00:18:40,119 --> 00:18:43,960
Speaker 1: a scandal where Facebook deliberately emotionally manipulated seven hundred thousand

326
00:18:44,080 --> 00:18:46,679
Speaker 1: users using the news feed in twenty fourteen. And that

327
00:18:46,840 --> 00:18:48,560
Speaker 1: is real, by the way, there's a link to it.

328
00:18:48,560 --> 00:18:51,560
Speaker 1: It's completely insane. Oh yeah, and a five billion dollar

329
00:18:51,640 --> 00:18:54,520
Speaker 1: FDC fine. And he's come out and scathed all as

330
00:18:54,560 --> 00:18:57,480
Speaker 1: he publicly destroys the company that was once globally beloved

331
00:18:57,800 --> 00:19:02,040
Speaker 1: in the name of endless growth. In fact, much like Welsch,

332
00:19:02,119 --> 00:19:04,159
Speaker 1: was applauded as one of the greatest business minds in

333
00:19:04,200 --> 00:19:07,480
Speaker 1: management for decades as he burned G to the ground. Zuckerberg,

334
00:19:07,520 --> 00:19:09,399
Speaker 1: a man who has taken a once profitable company that

335
00:19:09,440 --> 00:19:12,800
Speaker 1: once benefited society and made it both harmful and shitty

336
00:19:12,840 --> 00:19:15,840
Speaker 1: at providing its services, was named one of Barons's top

337
00:19:16,080 --> 00:19:18,600
Speaker 1: CEOs of twenty twenty four a couple of weeks ago,

338
00:19:18,880 --> 00:19:22,120
Speaker 1: where it credited him with a corporate course correction from

339
00:19:22,119 --> 00:19:25,480
Speaker 1: metaverse to artificial intelligence. Neither of those are making money.

340
00:19:26,320 --> 00:19:28,920
Speaker 1: Much like so many journalists in industry figures failed to

341
00:19:28,920 --> 00:19:31,679
Speaker 1: properly identify Welch, when he was right in their midst.

342
00:19:32,119 --> 00:19:35,320
Speaker 1: Barons failed to call Zuckerberg what he is another con

343
00:19:35,440 --> 00:19:37,840
Speaker 1: artist that took useful software and turned it into a

344
00:19:37,880 --> 00:19:42,040
Speaker 1: data collection firm with a shitty product attached. Zuckerberg is

345
00:19:42,080 --> 00:19:44,240
Speaker 1: trying something that Welsh could have only dreamed of, though

346
00:19:44,680 --> 00:19:47,480
Speaker 1: seeing how little he can actually make to convince the

347
00:19:47,520 --> 00:19:51,199
Speaker 1: markets that matter is valuable. It's almost a little on

348
00:19:51,240 --> 00:19:55,320
Speaker 1: the nose, and it fits, It perfectly fits shareholders. Supremacy

349
00:19:55,359 --> 00:19:58,400
Speaker 1: is the force currently driving the tech ecosystem, and one that,

350
00:19:58,440 --> 00:20:03,280
Speaker 1: as I've noted, and lacks any remaining hypergrowth markets funding

351
00:20:03,320 --> 00:20:06,919
Speaker 1: and proliferating technologies that exist not to provide an innovative,

352
00:20:07,080 --> 00:20:10,680
Speaker 1: useful service, but to create more growth. A phony sense

353
00:20:10,680 --> 00:20:14,159
Speaker 1: of progress that allows companies like Microsoft, Meta, Google, and

354
00:20:14,240 --> 00:20:18,119
Speaker 1: Amazon to create something that looks and smells sort of innovative,

355
00:20:18,320 --> 00:20:21,720
Speaker 1: even if their models are all extremely similar, as they're

356
00:20:21,760 --> 00:20:25,560
Speaker 1: all trained on the same quickly dwindling amount of training data,

357
00:20:25,640 --> 00:20:28,879
Speaker 1: and AI developers don't seem to really care what training

358
00:20:28,960 --> 00:20:31,360
Speaker 1: data they use, or indeed what data source they use

359
00:20:31,400 --> 00:20:34,320
Speaker 1: at all. Look at Google Search, which, as I've mentioned,

360
00:20:34,600 --> 00:20:38,360
Speaker 1: took a Reddit post that made it recommend putting glue

361
00:20:38,400 --> 00:20:40,439
Speaker 1: on a pizza to keep cheese on, or claiming that

362
00:20:40,480 --> 00:20:44,080
Speaker 1: you should eat a rock each every day. It's just

363
00:20:44,119 --> 00:20:48,600
Speaker 1: every time I read this, it's so frustrating, it's so annoying,

364
00:20:49,160 --> 00:20:51,640
Speaker 1: and then putting aside how funny the Google AI search

365
00:20:51,840 --> 00:20:54,520
Speaker 1: was on top of it. These companies are running out

366
00:20:54,520 --> 00:20:57,240
Speaker 1: of data and they very clearly don't care about quality

367
00:20:57,280 --> 00:21:01,880
Speaker 1: at all. They're not doing the work, they're not doing

368
00:21:02,240 --> 00:21:03,879
Speaker 1: the things they need to do to make sure this

369
00:21:04,000 --> 00:21:07,679
Speaker 1: is done right. No, they must have it today. They

370
00:21:07,760 --> 00:21:10,359
Speaker 1: must have it now, even if it's bad, even if

371
00:21:10,400 --> 00:21:13,359
Speaker 1: it burns money. And it's not like the markets are

372
00:21:13,359 --> 00:21:15,840
Speaker 1: actually seeing if the shit does anything or whether it's

373
00:21:15,880 --> 00:21:19,439
Speaker 1: truly revolutionary. They didn't care that. Many tech products have

374
00:21:19,480 --> 00:21:23,320
Speaker 1: got increasingly worse over time as tech executives rewarded again

375
00:21:23,400 --> 00:21:25,920
Speaker 1: and again for pursuing growth overt delivering any kind of

376
00:21:26,000 --> 00:21:30,880
Speaker 1: quality product. Since becoming CEO of Google Sundopieschid has been

377
00:21:30,920 --> 00:21:35,040
Speaker 1: paid over half a billion dollars literally in the last

378
00:21:35,040 --> 00:21:37,760
Speaker 1: three years, by the way, taking home two hundred and

379
00:21:37,800 --> 00:21:40,320
Speaker 1: eighty one million dollars mostly made up of stock in

380
00:21:40,320 --> 00:21:43,560
Speaker 1: twenty nineteen, fateful year that many of you might remember

381
00:21:43,560 --> 00:21:45,440
Speaker 1: from the man who killed Google Search, and then he

382
00:21:45,480 --> 00:21:48,360
Speaker 1: got paid two hundred and twenty six million twenty twenty two,

383
00:21:48,400 --> 00:21:52,720
Speaker 1: a year before Google laid off ten thousand people. Sundupisci's

384
00:21:52,800 --> 00:21:54,760
Speaker 1: job as CEO at Google is not to make sure

385
00:21:54,760 --> 00:21:57,399
Speaker 1: that Google delivers great products such as a quick path

386
00:21:57,440 --> 00:22:00,399
Speaker 1: to an answer using Google Search. No no, no, no, no,

387
00:22:00,359 --> 00:22:03,760
Speaker 1: you fool, you buffoon, you ignoramus. Why would you think that. No,

388
00:22:04,200 --> 00:22:07,560
Speaker 1: Sundai's job is to continually grow the amount of money

389
00:22:07,560 --> 00:22:11,159
Speaker 1: that Google's business units make. I have complete confidence that

390
00:22:11,160 --> 00:22:13,440
Speaker 1: if Sundar Pashai was able to make Google Search worse

391
00:22:13,480 --> 00:22:16,040
Speaker 1: than it already is and maintain double digit year of

392
00:22:16,080 --> 00:22:18,359
Speaker 1: a year revenue growth, he would not only do so,

393
00:22:18,600 --> 00:22:20,439
Speaker 1: but he would do so with a big smile on

394
00:22:20,480 --> 00:22:22,960
Speaker 1: his face and be rewarded with hundreds of billions of

395
00:22:22,960 --> 00:22:27,000
Speaker 1: dollars of stock options, pretty much in perpetuity. Sunda Pashai

396
00:22:27,119 --> 00:22:28,919
Speaker 1: is not judged for what he's done to Google, for

397
00:22:28,960 --> 00:22:31,840
Speaker 1: turning it into this Welshair nightmare, not by the markets,

398
00:22:32,040 --> 00:22:34,280
Speaker 1: not by Nile Patella, the verger, who pretty much gave

399
00:22:34,320 --> 00:22:37,560
Speaker 1: him softballs the whole time, And nobody's punishing him at all,

400
00:22:37,640 --> 00:22:39,640
Speaker 1: or really saying it to his face that he's burning

401
00:22:39,640 --> 00:22:43,000
Speaker 1: a genuine technological innovation that billions of people rely upon.

402
00:22:43,480 --> 00:22:46,560
Speaker 1: And it's a heartbreaking tragedy that's happening in real time,

403
00:22:46,720 --> 00:22:49,399
Speaker 1: one where a bad person makes worse people richer in

404
00:22:49,440 --> 00:22:52,919
Speaker 1: a way that tangibly hurts us all. We're all forced

405
00:22:52,960 --> 00:22:56,040
Speaker 1: to suffer the consequences and mourn the loss of Google

406
00:22:56,080 --> 00:22:58,920
Speaker 1: Search in slow motion, with nobody really wanting to admit

407
00:22:58,960 --> 00:23:01,520
Speaker 1: the obvious that Goo Google intends to bleed this thing

408
00:23:01,560 --> 00:23:05,440
Speaker 1: out until regulation or the markets stop them. And I

409
00:23:05,560 --> 00:23:07,840
Speaker 1: realized it sounded a little bit dramatic describing this as

410
00:23:07,840 --> 00:23:11,000
Speaker 1: a tragedy. Google Search was always a for profit business,

411
00:23:11,000 --> 00:23:14,960
Speaker 1: and advertising would so obviously poison it that founders Brin

412
00:23:15,000 --> 00:23:17,760
Speaker 1: and Page warned about it in the original Google paper,

413
00:23:18,080 --> 00:23:21,640
Speaker 1: saying that they expected that advertising funded search engines would

414
00:23:21,640 --> 00:23:25,439
Speaker 1: be biased towards advertisers and away from needs of customers.

415
00:23:26,400 --> 00:23:30,720
Speaker 1: But Google Search was, for a while something magical. It

416
00:23:30,840 --> 00:23:32,679
Speaker 1: was a thing we all took for granted. And I

417
00:23:32,680 --> 00:23:35,440
Speaker 1: think you're being disingenuous if you pretend that this isn't

418
00:23:35,480 --> 00:23:38,119
Speaker 1: something you cared about or relied upon. And I'd argue

419
00:23:38,119 --> 00:23:40,800
Speaker 1: for the earlier days of Facebook and Instagram to kind

420
00:23:40,800 --> 00:23:45,000
Speaker 1: of fit this bill too. These are, or perhaps were, sadly,

421
00:23:45,400 --> 00:23:48,119
Speaker 1: institutions that helped many people my age and I'm an

422
00:23:48,200 --> 00:23:51,399
Speaker 1: ancient thirty eight years old become who we are today,

423
00:23:51,640 --> 00:23:53,879
Speaker 1: finding the things and the people we needed and the

424
00:23:53,920 --> 00:23:58,600
Speaker 1: connections we otherwise wouldn't have made or sustained. I know,

425
00:23:59,200 --> 00:24:02,359
Speaker 1: at least in my that social networking is how I

426
00:24:02,600 --> 00:24:05,040
Speaker 1: met the world. I was kind of a lonely kid.

427
00:24:05,359 --> 00:24:08,320
Speaker 1: I didn't make friends easily. I never have. Really, I've

428
00:24:08,320 --> 00:24:11,240
Speaker 1: done a lot better thanks to the Internet. Pretty Much

429
00:24:11,280 --> 00:24:14,200
Speaker 1: everything that I found has been through on the Internet,

430
00:24:14,560 --> 00:24:16,880
Speaker 1: much of it from Google Search, much of it from

431
00:24:16,880 --> 00:24:20,960
Speaker 1: social networking from Facebook, from Instagram to extent Twitter to

432
00:24:21,000 --> 00:24:25,760
Speaker 1: a much larger Watching these things get burned sucks And

433
00:24:25,800 --> 00:24:28,359
Speaker 1: I think a problem that some people have with this

434
00:24:28,520 --> 00:24:31,399
Speaker 1: show is that they think I'm just pissy and I

435
00:24:31,440 --> 00:24:33,880
Speaker 1: hate all of this stuff, and I don't. I would

436
00:24:33,960 --> 00:24:35,520
Speaker 1: love it to go back to how it was, or

437
00:24:35,560 --> 00:24:38,920
Speaker 1: maybe how it felt. I wish it was less craven

438
00:24:39,320 --> 00:24:42,800
Speaker 1: of a value exchange. These were companies that made billions

439
00:24:42,840 --> 00:24:45,439
Speaker 1: of dollars in profit by providing a kind of a

440
00:24:45,440 --> 00:24:49,320
Speaker 1: social good, even if it was one where they realized

441
00:24:49,320 --> 00:24:51,080
Speaker 1: they could use it to create a monopoly and then

442
00:24:51,400 --> 00:24:56,119
Speaker 1: rug pull when they needed to for the shareholders. But

443
00:24:56,200 --> 00:24:58,320
Speaker 1: I do mourn the loss of these products, and I

444
00:24:58,359 --> 00:25:01,880
Speaker 1: think many of us. Maybe if I'm wrong, you can

445
00:25:01,920 --> 00:25:05,720
Speaker 1: email me easy at letter E, letter Z at better

446
00:25:05,720 --> 00:25:08,040
Speaker 1: offline dot com if you disagree. By all means, I

447
00:25:08,040 --> 00:25:10,760
Speaker 1: love to hear from you, even the haters one or

448
00:25:10,800 --> 00:25:13,280
Speaker 1: two of you. But in all seriousness, I'm more on

449
00:25:13,359 --> 00:25:17,040
Speaker 1: this stuff. I'm sad about this. I'm pissed off. Not

450
00:25:17,119 --> 00:25:21,560
Speaker 1: because I like being angry, I genuinely don't. I'm sad.

451
00:25:22,000 --> 00:25:25,200
Speaker 1: I'm a broken hearted romantic. I love the tech industry

452
00:25:25,200 --> 00:25:27,159
Speaker 1: and what it used to do. Perhaps I was naive.

453
00:25:27,280 --> 00:25:30,680
Speaker 1: Perhaps now I'm realizing that a lot of that stuff

454
00:25:30,680 --> 00:25:34,000
Speaker 1: that I thought was great wasn't. It wasn't this bad

455
00:25:34,119 --> 00:25:39,880
Speaker 1: wasn't Where Jack Welch destroyed multiple local economies in Massachusetts, Indiana,

456
00:25:39,880 --> 00:25:42,560
Speaker 1: and Pennsylvania by laying off thousands of workers in favor

457
00:25:42,600 --> 00:25:46,520
Speaker 1: of cheaper outsourced options. Sundar Pichai and Mark Zuckerberg have

458
00:25:46,640 --> 00:25:50,480
Speaker 1: realized that shareholder supremacy only means making a product as

459
00:25:50,560 --> 00:25:53,199
Speaker 1: useful as necessary and optimizing it at all times to

460
00:25:53,240 --> 00:25:58,119
Speaker 1: me analyst expectations of revenue. The unique problem that Sundar

461
00:25:58,160 --> 00:26:00,640
Speaker 1: Pishai and the rest of the rock barons currently faces

462
00:26:00,680 --> 00:26:03,720
Speaker 1: that there aren't any hypergrowth markets left, and they've been

463
00:26:03,760 --> 00:26:07,560
Speaker 1: so desperately adapting to that reality since twenty fifteen. And

464
00:26:07,680 --> 00:26:10,080
Speaker 1: now I've said later, but I think twenty fifteen is

465
00:26:10,119 --> 00:26:16,080
Speaker 1: the year so many promises, augmented reality, homo robotics, autonomous cars,

466
00:26:16,080 --> 00:26:20,760
Speaker 1: and even then artificial intelligence writ large never quite materialized

467
00:26:20,800 --> 00:26:24,280
Speaker 1: into these viable business units, making big tech that little

468
00:26:24,320 --> 00:26:28,000
Speaker 1: bit more desperate. I've repeatedly and substantively proven in my

469
00:26:28,040 --> 00:26:31,560
Speaker 1: newsletter and this podcast that both Meta and Google have

470
00:26:31,680 --> 00:26:34,280
Speaker 1: made their products worse in pursuit of growth, and they've

471
00:26:34,280 --> 00:26:37,320
Speaker 1: done so by following a roadmap drawn by Jack Welch,

472
00:26:37,600 --> 00:26:40,480
Speaker 1: a sociopathic scumbag that realized that he could turn General

473
00:26:40,520 --> 00:26:43,480
Speaker 1: Electric into a shambling monstrosity of a company that could

474
00:26:43,480 --> 00:26:46,240
Speaker 1: shape shift into whatever the street needed, even if the

475
00:26:46,240 --> 00:26:50,720
Speaker 1: product sucked. And I believe that this is the same

476
00:26:50,840 --> 00:26:55,080
Speaker 1: financial nihilism that empowers people like Mirror Marati and Sam Altman,

477
00:26:55,760 --> 00:27:00,200
Speaker 1: and also millions more middle managers and absentee CEOs. The

478
00:27:00,320 --> 00:27:02,840
Speaker 1: kind of been writing about and speaking about for the

479
00:27:02,920 --> 00:27:06,439
Speaker 1: last three years. Our economy is run by people that

480
00:27:06,560 --> 00:27:09,640
Speaker 1: have never built anything, running companies that they can taught

481
00:27:09,680 --> 00:27:12,320
Speaker 1: to make a number go up for showlders. They rarely

482
00:27:12,359 --> 00:27:16,399
Speaker 1: meet people like David Zaslav, the CEO of Warner Brothers Discovery,

483
00:27:16,480 --> 00:27:19,600
Speaker 1: who intentionally chose not to release Coyote Versus Acme, a

484
00:27:19,640 --> 00:27:23,280
Speaker 1: fully produced and ready to debut movie featuring Warner Brothers'

485
00:27:23,440 --> 00:27:27,639
Speaker 1: core brands, choosing instead to never release it ever in

486
00:27:27,720 --> 00:27:31,440
Speaker 1: exchange for a cut to its tax bill. Zaslav, a

487
00:27:31,560 --> 00:27:34,199
Speaker 1: CEO of Warner Brothers Discovery, has overseen one of the

488
00:27:34,280 --> 00:27:37,919
Speaker 1: darkest periods in the company's history, including endless cutbacks, and

489
00:27:38,000 --> 00:27:41,360
Speaker 1: through his own mismanagement, caused a five month long strike

490
00:27:41,400 --> 00:27:45,879
Speaker 1: in Hollywood. Zaslav continued to complain even after the strike ended,

491
00:27:46,119 --> 00:27:50,240
Speaker 1: claiming that studios overpaid for the strike to end as

492
00:27:50,280 --> 00:27:52,919
Speaker 1: he earned a fifty million dollar salary for driving his

493
00:27:53,040 --> 00:27:57,200
Speaker 1: company into the ground. Hey hey, just one moment, though,

494
00:27:57,880 --> 00:28:01,960
Speaker 1: where do you think David Zaslav learnt? Do you think

495
00:28:01,960 --> 00:28:05,760
Speaker 1: he learned it by reading books? Or maybe he learned

496
00:28:05,760 --> 00:28:09,120
Speaker 1: his management philosophy a little more directly? Can you guess

497
00:28:09,200 --> 00:28:11,720
Speaker 1: who his close friend was. It was Jack Wells. Jack

498
00:28:11,760 --> 00:28:15,119
Speaker 1: Welch was his. Oh my god, but you know who's

499
00:28:15,119 --> 00:28:26,119
Speaker 1: not horrible our advertisers. During a commencement speech in twenty

500
00:28:26,160 --> 00:28:29,280
Speaker 1: twenty three where David Zaslav was booed by students, he

501
00:28:29,359 --> 00:28:32,640
Speaker 1: told the story of how, sometime after General Electric acquired

502
00:28:32,720 --> 00:28:35,640
Speaker 1: NBC through g's acquisition of RCA in ninety eighty five,

503
00:28:35,840 --> 00:28:38,600
Speaker 1: he sent a handwritten note to Jack Welch telling him

504
00:28:38,640 --> 00:28:42,480
Speaker 1: about himself, David Zaslav, and what he'd been doing he

505
00:28:42,560 --> 00:28:44,960
Speaker 1: was a lawyer, leading to a job running NBC in

506
00:28:45,040 --> 00:28:48,400
Speaker 1: nineteen eighty nine. This story doesn't make a ton of sense,

507
00:28:48,480 --> 00:28:50,840
Speaker 1: by the way, based on any living history of David

508
00:28:50,920 --> 00:28:54,040
Speaker 1: Zaslav's life. He joined NBC three years after the acquisition

509
00:28:54,080 --> 00:28:56,560
Speaker 1: of RCA closed. He claimed he was working for a

510
00:28:56,560 --> 00:29:00,000
Speaker 1: few years in cable news, but everything I found suggests

511
00:29:00,080 --> 00:29:02,760
Speaker 1: that he went straight from school to working at a

512
00:29:02,800 --> 00:29:06,120
Speaker 1: law firm called Lebooth LAMB Libyan McRae according to his

513
00:29:06,160 --> 00:29:09,440
Speaker 1: Warner Brothers profile when he graduated from Boston University in

514
00:29:09,520 --> 00:29:11,360
Speaker 1: ninet eighty five, meaning that he would have had to

515
00:29:11,400 --> 00:29:13,120
Speaker 1: send that note while working at a firm that was

516
00:29:13,160 --> 00:29:17,000
Speaker 1: mostly not working in anything to do with Capernews at all,

517
00:29:17,320 --> 00:29:21,320
Speaker 1: just a liar, just lying. Regardless of whether Zaslav made

518
00:29:21,360 --> 00:29:23,360
Speaker 1: up an entire story about how he got his job,

519
00:29:23,520 --> 00:29:27,360
Speaker 1: he was and is one of Welch's most nasty cronies,

520
00:29:27,400 --> 00:29:31,080
Speaker 1: his most staunch acolytes, telling David Gellis, who wrote The

521
00:29:31,120 --> 00:29:34,680
Speaker 1: Man Who Destroyed Capitalism about Jack Welch, that Jack set

522
00:29:34,720 --> 00:29:37,280
Speaker 1: the path, that he saw the whole world, that he

523
00:29:37,360 --> 00:29:39,760
Speaker 1: was above the whole world, and that what Jack Welch

524
00:29:39,840 --> 00:29:42,480
Speaker 1: created at G became the way that companies now operate,

525
00:29:42,480 --> 00:29:45,080
Speaker 1: which is true. David Zaslav, a man who has caused

526
00:29:45,160 --> 00:29:48,720
Speaker 1: unfathomable damage to the entertainment industry while intentionally choosing not

527
00:29:48,800 --> 00:29:52,200
Speaker 1: to release two different movies, learned to do so from

528
00:29:52,200 --> 00:29:56,600
Speaker 1: the Michael Jordan of corporate destruction, and to Zaslav, Welch

529
00:29:56,760 --> 00:29:59,360
Speaker 1: was like an older brother that would pick people at

530
00:29:59,480 --> 00:30:02,120
Speaker 1: NBC with a hug when things were tough, and that

531
00:30:02,160 --> 00:30:04,080
Speaker 1: there was no better friend. According to an interview with

532
00:30:04,160 --> 00:30:08,920
Speaker 1: CNBC Jesus christ Man, it's like a poorly written drama.

533
00:30:09,600 --> 00:30:12,920
Speaker 1: I hope it ends with a big anvil falling on me. Anyway,

534
00:30:12,960 --> 00:30:15,560
Speaker 1: I realize I'm oscillating between industries and names, but the

535
00:30:15,600 --> 00:30:18,920
Speaker 1: shareholder's supremacy is something that has poisoned almost every part

536
00:30:18,960 --> 00:30:23,160
Speaker 1: of global capitalism. Dedication to the shareholders, in many ways

537
00:30:23,200 --> 00:30:25,640
Speaker 1: is kind of like a religion. It isn't even about

538
00:30:25,680 --> 00:30:29,440
Speaker 1: a shareholder or the shareholder, just moving acids to make

539
00:30:29,440 --> 00:30:32,120
Speaker 1: a number go up and making another number look like

540
00:30:32,160 --> 00:30:36,240
Speaker 1: it might go up in the future. Welch Zaslav, Peshai, Zuckerberg.

541
00:30:36,400 --> 00:30:39,440
Speaker 1: They're all the same kind of monster, one divorced from

542
00:30:39,480 --> 00:30:42,760
Speaker 1: consequence and production and capable of contributing meaningfully to the

543
00:30:42,760 --> 00:30:45,680
Speaker 1: world at large because the market is shown it doesn't

544
00:30:45,720 --> 00:30:49,200
Speaker 1: really care if they do so. Sanda Pashai doesn't use Google,

545
00:30:49,240 --> 00:30:52,400
Speaker 1: and Mark Zuckerberg doesn't use Instagram, Facebook, or threads, at

546
00:30:52,480 --> 00:30:55,560
Speaker 1: least not like a regular person does anyway, much like

547
00:30:55,600 --> 00:30:58,600
Speaker 1: how David Zaslav doesn't watch or care about TVs and

548
00:30:58,640 --> 00:31:02,760
Speaker 1: movies and doesn't even release them sometimes it's crazy. The

549
00:31:02,800 --> 00:31:05,600
Speaker 1: deep sea a nihilism means that they aren't users or

550
00:31:05,640 --> 00:31:09,240
Speaker 1: creators or even active participants in any part of society.

551
00:31:09,800 --> 00:31:11,640
Speaker 1: They're there to move the stuff around so that they

552
00:31:11,640 --> 00:31:14,800
Speaker 1: can keep the number going up. And I believe this

553
00:31:14,840 --> 00:31:17,360
Speaker 1: is all the consequence of Jack Welcher's legacy, where the

554
00:31:17,400 --> 00:31:19,360
Speaker 1: economy has been built on the back of a management

555
00:31:19,400 --> 00:31:23,120
Speaker 1: philosophy that no longer involves managing people or building things.

556
00:31:24,080 --> 00:31:27,800
Speaker 1: The business media and society at large elevates executives like

557
00:31:27,880 --> 00:31:31,000
Speaker 1: Zuckerberg and Peshai as they demolish their products, and they

558
00:31:31,000 --> 00:31:34,520
Speaker 1: are thousands of people because the terms of success are

559
00:31:34,520 --> 00:31:37,880
Speaker 1: no longer about making money by providing a good service

560
00:31:38,000 --> 00:31:41,400
Speaker 1: or a product people like. The markets don't reward steady growth,

561
00:31:41,400 --> 00:31:43,520
Speaker 1: nor that they punish executives for the quality of their

562
00:31:43,560 --> 00:31:47,560
Speaker 1: product because analysts and investors aren't really concerned about the product,

563
00:31:47,680 --> 00:31:50,880
Speaker 1: just the financial output. I don't think their users either.

564
00:31:51,840 --> 00:31:55,360
Speaker 1: At this point, theological rush to boost artificial intelligence makes

565
00:31:55,360 --> 00:31:57,840
Speaker 1: a lot more sense when you have a society and

566
00:31:57,920 --> 00:32:01,040
Speaker 1: economy dominated by people who don't create things or understand

567
00:32:01,040 --> 00:32:04,400
Speaker 1: the things they're selling. People that don't experience or respect

568
00:32:04,480 --> 00:32:07,160
Speaker 1: labor or talk to people. Of course, their natural thought

569
00:32:07,480 --> 00:32:11,040
Speaker 1: will be that any form of creativity or work can

570
00:32:11,120 --> 00:32:14,200
Speaker 1: and should be automated. It isn't about what's good, but

571
00:32:14,760 --> 00:32:17,880
Speaker 1: what's good enough, and artificial intelligence allows them to test

572
00:32:17,920 --> 00:32:21,360
Speaker 1: the boundaries of what enough can mean. Toys, r us

573
00:32:21,440 --> 00:32:24,240
Speaker 1: or at least what remains of it after a leveraged buyout.

574
00:32:24,400 --> 00:32:28,120
Speaker 1: Should feel an abundance of shame for releasing a horrifying

575
00:32:28,200 --> 00:32:31,520
Speaker 1: AI generated orision of Toys of Rus movie full of

576
00:32:31,800 --> 00:32:36,240
Speaker 1: ugly hallucinations and yanky animations. But what it's really trying

577
00:32:36,280 --> 00:32:37,880
Speaker 1: to see is how much it can get away with,

578
00:32:38,080 --> 00:32:41,160
Speaker 1: how shitty something can be without losing customers, or whether

579
00:32:41,200 --> 00:32:43,320
Speaker 1: the potential loss of customers is worth it to save

580
00:32:43,320 --> 00:32:45,840
Speaker 1: the money it would take to actually shoot a goddamn commercial.

581
00:32:47,520 --> 00:32:49,360
Speaker 1: And what's crazy, by the way, and you should watch

582
00:32:49,400 --> 00:32:53,760
Speaker 1: this thing. It's terrible. Is this video looks so bad

583
00:32:53,760 --> 00:32:55,440
Speaker 1: and they put it on the main Toys of US account.

584
00:32:55,440 --> 00:32:57,080
Speaker 1: They don't give a shit. They're trying to see what

585
00:32:57,120 --> 00:32:59,640
Speaker 1: they can get away with. And I think that's a

586
00:32:59,680 --> 00:33:03,480
Speaker 1: big thing theme. When Mirror Murarti said that AI might

587
00:33:03,560 --> 00:33:05,560
Speaker 1: kill creative jobs that shouldn't have been there in the

588
00:33:05,560 --> 00:33:08,360
Speaker 1: first place, it wasn't just the grotesque insult to those

589
00:33:08,600 --> 00:33:12,160
Speaker 1: actually working cret When Mirror Mourati said that AI might

590
00:33:12,280 --> 00:33:14,320
Speaker 1: kill creative jobs that should have never been there in

591
00:33:14,360 --> 00:33:16,880
Speaker 1: the first place, it wasn't just a nasty insult to

592
00:33:16,920 --> 00:33:19,280
Speaker 1: those working in the creative fields. It was also a

593
00:33:19,280 --> 00:33:23,280
Speaker 1: demonstration of an unchained sociopathy and this nasty kind of

594
00:33:23,320 --> 00:33:26,080
Speaker 1: hubris that these tech people have, and the fact that

595
00:33:26,120 --> 00:33:29,480
Speaker 1: she believes that she, a woman of little actual accomplishment

596
00:33:29,520 --> 00:33:32,320
Speaker 1: and talent and the intellectual depth of a puddle on

597
00:33:32,360 --> 00:33:36,160
Speaker 1: a flat sidewalk, is singlely ordained to decide which jobs

598
00:33:36,160 --> 00:33:39,240
Speaker 1: are worthy and which ones should die. Really, it was

599
00:33:39,280 --> 00:33:41,600
Speaker 1: an insult to all of us. It was an expression

600
00:33:41,640 --> 00:33:44,479
Speaker 1: of her belief that consumers don't deserve things created by

601
00:33:44,480 --> 00:33:47,360
Speaker 1: a person who actually gives a shit. You don't deserve

602
00:33:47,400 --> 00:33:49,960
Speaker 1: to watch movies that only exist thanks to the combined

603
00:33:49,960 --> 00:33:54,400
Speaker 1: efforts of illustrators, sound engineers, composers, actors, directors, and countless

604
00:33:54,440 --> 00:33:56,959
Speaker 1: other uncelebrated roles, where each cog in the machine has

605
00:33:56,960 --> 00:33:59,600
Speaker 1: spent years honing their skills until they've reached a level

606
00:33:59,640 --> 00:34:03,560
Speaker 1: of honest mastery. You, yes, you don't deserve to use

607
00:34:03,560 --> 00:34:06,080
Speaker 1: software created by someone who actually thought about the problem

608
00:34:06,120 --> 00:34:08,520
Speaker 1: and at the very least made a best effort to

609
00:34:08,520 --> 00:34:12,960
Speaker 1: write secure, robust code. You don't deserve anything. In their eyes.

610
00:34:13,120 --> 00:34:17,760
Speaker 1: You deserve the minimum viable product. You deserve as little

611
00:34:17,800 --> 00:34:20,480
Speaker 1: as possible so that they can make as much as possible.

612
00:34:21,280 --> 00:34:24,799
Speaker 1: That is what Mirror Murti is saying. No amount of

613
00:34:24,880 --> 00:34:28,480
Speaker 1: two long tweet storms, no amount of vacuous blogs, no

614
00:34:28,560 --> 00:34:31,200
Speaker 1: amount of apologia is going to make up for the

615
00:34:31,280 --> 00:34:36,120
Speaker 1: fact that this is what these people think. They see

616
00:34:36,640 --> 00:34:42,440
Speaker 1: work and creativity as something to be optimized away, and

617
00:34:42,480 --> 00:34:46,839
Speaker 1: it's disgraceful. And even when you get to the more

618
00:34:46,880 --> 00:34:50,000
Speaker 1: workhorse roles, the coding roles, there are still these huge

619
00:34:50,040 --> 00:34:53,400
Speaker 1: problems and they don't care. As pointed out by cybersecurity

620
00:34:53,440 --> 00:34:57,640
Speaker 1: firms nick, Microsoft's get hub copilot tool routinely and unquestionably

621
00:34:57,680 --> 00:35:02,480
Speaker 1: outputs insecure code because, as said ad nauseum in other places,

622
00:35:02,680 --> 00:35:05,680
Speaker 1: it doesn't know anything a human being can look at

623
00:35:05,719 --> 00:35:08,600
Speaker 1: a code based and identify, for example, areas where the

624
00:35:08,600 --> 00:35:11,439
Speaker 1: system doesn't check for SQL injection attacks, which could allow

625
00:35:11,440 --> 00:35:14,320
Speaker 1: an attacker to steal and modify data from a database.

626
00:35:14,760 --> 00:35:18,200
Speaker 1: An AI tool merely guesses what code looks right probabilistically

627
00:35:18,560 --> 00:35:22,840
Speaker 1: given the prompt that was involved. When Murti gleefully brags

628
00:35:22,880 --> 00:35:26,240
Speaker 1: about how AI will eviscerate an unknowable amount of creative jobs,

629
00:35:26,400 --> 00:35:29,600
Speaker 1: which she is personally identified as expendable by the way,

630
00:35:29,840 --> 00:35:32,520
Speaker 1: what she's really saying is that people should be content

631
00:35:32,600 --> 00:35:36,560
Speaker 1: with using shitty broken AI generated software and watching shitty

632
00:35:36,880 --> 00:35:40,239
Speaker 1: broken AI generated films with a number of digits on

633
00:35:40,320 --> 00:35:43,759
Speaker 1: each hand fluctuates wildly that the line on a sisoscope

634
00:35:43,800 --> 00:35:46,520
Speaker 1: and where nothing new is said, but rather a machine

635
00:35:46,600 --> 00:35:50,120
Speaker 1: is regurgitating stuff created by other people solely based on

636
00:35:50,160 --> 00:35:58,440
Speaker 1: a mathematical model of probability. It's insulting, it's disgusting, and

637
00:35:58,520 --> 00:36:00,799
Speaker 1: it sucks. It just objective if he sucks. It's not

638
00:36:00,920 --> 00:36:03,640
Speaker 1: even like this stuff is any good. It's not even

639
00:36:03,880 --> 00:36:07,840
Speaker 1: like the things that it's producing are respectable. Not the

640
00:36:07,920 --> 00:36:11,200
Speaker 1: replacing people is good. But the amount of money they're

641
00:36:11,200 --> 00:36:15,000
Speaker 1: being given, the amount of compute they're using, the amount

642
00:36:15,000 --> 00:36:18,880
Speaker 1: of water they're boiling to make dogshare shows a complete

643
00:36:19,000 --> 00:36:25,080
Speaker 1: contempt for everything, for creativity and labor itself. And generative

644
00:36:25,120 --> 00:36:28,640
Speaker 1: AI is exciting to the disconnected business fucks running our

645
00:36:28,680 --> 00:36:31,479
Speaker 1: economy because it's a way to abstract and outsource even

646
00:36:31,560 --> 00:36:35,399
Speaker 1: more forms of labor. We have spent decades pushing young

647
00:36:35,440 --> 00:36:39,680
Speaker 1: people to get into management without ever teaching anybody about

648
00:36:39,680 --> 00:36:42,680
Speaker 1: what managers are meant to do, creating a class structure

649
00:36:42,680 --> 00:36:45,359
Speaker 1: in organizations where there are those that do things and

650
00:36:45,440 --> 00:36:48,400
Speaker 1: those that take the credit, and the latter are the

651
00:36:48,440 --> 00:36:52,680
Speaker 1: people in charge, disconnected from labor, disconnected from quality, disconnected

652
00:36:52,719 --> 00:36:56,319
Speaker 1: from production, and thus incapable of making informed decisions other

653
00:36:56,400 --> 00:36:58,239
Speaker 1: than what if we moved around this number here and

654
00:36:58,360 --> 00:37:01,520
Speaker 1: what if we start paying these people. The AI bubble

655
00:37:01,560 --> 00:37:04,680
Speaker 1: has been inflated by people excited about the prospect of

656
00:37:04,800 --> 00:37:08,200
Speaker 1: not happening to deal with filthy laborers that do work,

657
00:37:08,440 --> 00:37:11,120
Speaker 1: and they ultimately aspire to make companies with as few

658
00:37:11,160 --> 00:37:14,000
Speaker 1: people as possible, with the CEO making the most money

659
00:37:14,239 --> 00:37:16,480
Speaker 1: because they're the ones that move the numbers around for

660
00:37:16,520 --> 00:37:20,360
Speaker 1: the markets. This also explains where they're so incapable of

661
00:37:20,400 --> 00:37:24,400
Speaker 1: describing what AI is, what it does, and why it's useful.

662
00:37:25,080 --> 00:37:27,520
Speaker 1: It doesn't matter that data centers might end up using

663
00:37:27,560 --> 00:37:30,319
Speaker 1: as much power as India by twenty thirty four, or

664
00:37:30,360 --> 00:37:33,799
Speaker 1: that generator of AI isn't actually that useful. It's a

665
00:37:33,880 --> 00:37:36,160
Speaker 1: chance for them to further disconnect themselves from having to

666
00:37:36,200 --> 00:37:38,560
Speaker 1: pay actual people to do actual work, a thing that

667
00:37:38,600 --> 00:37:42,040
Speaker 1: they themselves consider the product of the underclass. They don't

668
00:37:42,040 --> 00:37:45,239
Speaker 1: care that the output is mediocre, that the product is unprofitable,

669
00:37:45,320 --> 00:37:48,080
Speaker 1: that there's a quickly approaching wall that generative AI can't

670
00:37:48,160 --> 00:37:50,560
Speaker 1: leap over as it runs out of training data, or

671
00:37:50,600 --> 00:37:54,480
Speaker 1: that the transformer based architecture of large language models has

672
00:37:54,520 --> 00:37:58,440
Speaker 1: hard limitations that are impossible to overcome. No, this is

673
00:37:58,480 --> 00:38:00,720
Speaker 1: a shiny new object that they can way of investors

674
00:38:00,760 --> 00:38:03,080
Speaker 1: that already don't know what any of this stuff means,

675
00:38:03,320 --> 00:38:05,520
Speaker 1: one that lets them dream of a world without labor.

676
00:38:06,080 --> 00:38:09,480
Speaker 1: Generative AI wants us to stop researching, or talking or thinking,

677
00:38:09,520 --> 00:38:14,440
Speaker 1: and eventually it will come for your livelihood if it worked.

678
00:38:15,520 --> 00:38:17,680
Speaker 1: But even then, when it doesn't work, it's still taking

679
00:38:18,040 --> 00:38:22,120
Speaker 1: money out of freelancer's mouths. It's replacing good coders with

680
00:38:22,600 --> 00:38:27,279
Speaker 1: shit generated code. There is a poison here, and it's disgusting.

681
00:38:28,080 --> 00:38:31,239
Speaker 1: In some respects. Generative AI is morally worse than Jack

682
00:38:31,239 --> 00:38:35,680
Speaker 1: Welch's odious anti worker philosophy. Whereas Welch saw workers as

683
00:38:35,719 --> 00:38:38,560
Speaker 1: a cost center to be minimized and eliminated where possible,

684
00:38:38,800 --> 00:38:42,200
Speaker 1: generative AI extends that idea to the raw materials necessary

685
00:38:42,320 --> 00:38:45,800
Speaker 1: to build apps like chat GPT, with must of Our Sulliman,

686
00:38:45,880 --> 00:38:48,480
Speaker 1: the CEO of Microsoft AI and the co founder of DeepMind,

687
00:38:48,760 --> 00:38:52,040
Speaker 1: declaring the existence of an unspoken social contract where and

688
00:38:52,120 --> 00:38:56,000
Speaker 1: I quote online content is freeware for building AI models.

689
00:38:57,280 --> 00:38:59,440
Speaker 1: The law I know it tends to regard actual contracts

690
00:38:59,480 --> 00:39:02,920
Speaker 1: more seriously unspoken and let's face it, imaginary contracts. And

691
00:39:02,960 --> 00:39:05,399
Speaker 1: I desperately look forward to the day when Sulliman's ideas

692
00:39:05,440 --> 00:39:07,920
Speaker 1: are tested in court. But I don't fancy these chances.

693
00:39:07,960 --> 00:39:11,600
Speaker 1: And most of you come from my content. You're not

694
00:39:11,640 --> 00:39:14,920
Speaker 1: gonna have words, mate. But that's the thing. In many

695
00:39:14,960 --> 00:39:17,160
Speaker 1: of my newsletters and podcasts, I've argued that the current

696
00:39:17,200 --> 00:39:19,399
Speaker 1: trajectory of the tech industry will lead it to ruin

697
00:39:19,960 --> 00:39:23,319
Speaker 1: the poison of the shareholder supremacy. This nihilistic intention of

698
00:39:23,360 --> 00:39:26,560
Speaker 1: contorting companies, the police, analysts, and investors is one that

699
00:39:26,600 --> 00:39:29,919
Speaker 1: will uniquely punish the tech industry, just like it did

700
00:39:29,960 --> 00:39:35,080
Speaker 1: to General Electric. Google, Microsoft, and Meta have bet their

701
00:39:35,120 --> 00:39:37,560
Speaker 1: futures on generative AI, cramming it into their products with

702
00:39:37,600 --> 00:39:40,600
Speaker 1: little regard for utility, all to show the markets that

703
00:39:40,600 --> 00:39:44,919
Speaker 1: they're futuristic rocket ship growth companies rather than at least

704
00:39:44,920 --> 00:39:47,520
Speaker 1: in matter in Google's case, aging and decaying empires that

705
00:39:47,560 --> 00:39:50,440
Speaker 1: got too big and were corrupted by the forces of

706
00:39:50,560 --> 00:39:54,760
Speaker 1: the MBA management sect. I realized that's master of business

707
00:39:54,800 --> 00:40:00,680
Speaker 1: administration management. This is the force behind everything. This is

708
00:40:00,719 --> 00:40:03,719
Speaker 1: it the dark hand that demanded you return to the

709
00:40:03,760 --> 00:40:06,520
Speaker 1: office in spite of the productivity gains of remote work,

710
00:40:06,840 --> 00:40:09,960
Speaker 1: The weight behind the people destroying the media, the people

711
00:40:10,400 --> 00:40:13,480
Speaker 1: the very same people who lied about cryptocurrency being the

712
00:40:13,520 --> 00:40:16,800
Speaker 1: future of finance, and the people that collapsed multiple banks

713
00:40:17,000 --> 00:40:21,080
Speaker 1: in twenty twenty three. Because risk management, to quote Mark Andresen,

714
00:40:21,640 --> 00:40:25,880
Speaker 1: is considered the enemy. These people will burn the world

715
00:40:25,920 --> 00:40:28,400
Speaker 1: to a crisp in search of a profit, in search

716
00:40:28,400 --> 00:40:31,879
Speaker 1: of eternal growth, in search of the things that will

717
00:40:31,880 --> 00:40:36,600
Speaker 1: make them richer, richer, nastier, disconnected monsters even more capable

718
00:40:36,600 --> 00:40:40,560
Speaker 1: of escaping the drudgery of knowing and doing things. This

719
00:40:40,719 --> 00:40:44,360
Speaker 1: is a dark future where somehow all labor is automated,

720
00:40:44,480 --> 00:40:47,960
Speaker 1: all money flows upwards, and society drained of taxes in

721
00:40:48,040 --> 00:40:51,759
Speaker 1: any kind of social safety net, does something with all

722
00:40:51,760 --> 00:40:53,879
Speaker 1: the children that Elon Musk is saying we need to have.

723
00:40:55,200 --> 00:40:59,760
Speaker 1: The tech industry is dominated now by management consolants, product managers,

724
00:40:59,840 --> 00:41:03,320
Speaker 1: and middle management in general, with people that have written

725
00:41:03,400 --> 00:41:05,719
Speaker 1: few lines of code in their lives holding sway over

726
00:41:05,760 --> 00:41:09,040
Speaker 1: the actual builders, instructing them to create things they don't

727
00:41:09,120 --> 00:41:12,200
Speaker 1: understand as means of improving the bottom line, rather than

728
00:41:12,239 --> 00:41:15,640
Speaker 1: solving an actual need or even addressing the obvious business

729
00:41:15,680 --> 00:41:19,880
Speaker 1: fundamentals like profitability and stability. A few episodes back, when

730
00:41:19,920 --> 00:41:21,600
Speaker 1: I was talking with Nick Siesh, one of the very

731
00:41:21,640 --> 00:41:24,719
Speaker 1: basic things he said was, have you checked your backups?

732
00:41:25,600 --> 00:41:28,840
Speaker 1: This is a problem throughout the valley. We don't maintain

733
00:41:28,920 --> 00:41:32,160
Speaker 1: anything anymore as a society. We have a terrible approach

734
00:41:32,200 --> 00:41:35,280
Speaker 1: to maintenance. We have a terrible approach to business maintenance.

735
00:41:35,600 --> 00:41:38,239
Speaker 1: When you throw sustainability out in the window, you don't

736
00:41:38,239 --> 00:41:42,239
Speaker 1: really check if everything's working well. And I think that

737
00:41:42,239 --> 00:41:44,800
Speaker 1: that's going to be the problem. That and the financial

738
00:41:44,800 --> 00:41:46,759
Speaker 1: precariousness of all of this, That and the fact the

739
00:41:46,760 --> 00:41:49,879
Speaker 1: markets just kind of turn on them when things don't

740
00:41:49,920 --> 00:41:53,480
Speaker 1: work their way, and at some point things have to collapse.

741
00:41:54,440 --> 00:41:57,120
Speaker 1: I'm not saying that every tech company goes belly up,

742
00:41:57,239 --> 00:41:59,400
Speaker 1: but I believe that the generative AI boom is the

743
00:41:59,400 --> 00:42:03,040
Speaker 1: force that creates It's a massive reckoning in this industry.

744
00:42:03,920 --> 00:42:06,319
Speaker 1: It's almost a little too on the nose with the

745
00:42:06,360 --> 00:42:10,080
Speaker 1: wider shareholder supremacy. Generate AI. It's a tool that only

746
00:42:10,080 --> 00:42:12,960
Speaker 1: seems revolutionary to people that haven't written or coded, or

747
00:42:13,080 --> 00:42:16,360
Speaker 1: drawn or sang or created anything in years. The last

748
00:42:16,400 --> 00:42:19,000
Speaker 1: four years have proven that the tech industry is desperate

749
00:42:19,000 --> 00:42:22,760
Speaker 1: for somebody to follow, and follow they have. Mark Zuckerberg

750
00:42:22,800 --> 00:42:25,439
Speaker 1: claimed the metaverse the future in the most flimsy way,

751
00:42:25,600 --> 00:42:28,520
Speaker 1: and the market, along with Microsoft and many other companies agreed.

752
00:42:28,840 --> 00:42:31,880
Speaker 1: Even if the metaverse was barely conceived pipe during by

753
00:42:31,880 --> 00:42:34,360
Speaker 1: a guy who hasn't written code since two thousand and six,

754
00:42:35,280 --> 00:42:37,560
Speaker 1: Generative AI is the next step up a trend with

755
00:42:37,600 --> 00:42:40,520
Speaker 1: a natural product, a superficially impressive do dad that can

756
00:42:40,560 --> 00:42:44,399
Speaker 1: sell cloud compute access and proliferate more software, even if

757
00:42:44,719 --> 00:42:48,200
Speaker 1: the underlying technology is so remarkably unprofitable and unreliable that

758
00:42:48,239 --> 00:42:51,040
Speaker 1: big tech firms are having to calm down their salespeople,

759
00:42:51,080 --> 00:42:54,200
Speaker 1: which happened a few months ago with Amazon, and big

760
00:42:54,239 --> 00:42:57,200
Speaker 1: tech was so desperate for something new to follow, something

761
00:42:57,239 --> 00:42:59,640
Speaker 1: new to do with themselves that would sustain the value's

762
00:42:59,680 --> 00:43:03,839
Speaker 1: thread facade is a crucible of innovation and progress. Rather

763
00:43:03,880 --> 00:43:07,040
Speaker 1: than doing the hard work to actually invest in and

764
00:43:07,160 --> 00:43:11,920
Speaker 1: research and develop important technologies that people like and would

765
00:43:12,040 --> 00:43:15,680
Speaker 1: use and would care about, Sam Altman gave them all

766
00:43:15,800 --> 00:43:18,360
Speaker 1: something to do with themselves, and he packaged it in

767
00:43:18,440 --> 00:43:20,080
Speaker 1: a way that told them how to think about it,

768
00:43:20,160 --> 00:43:24,080
Speaker 1: and of course lie about it. At some point, something

769
00:43:24,200 --> 00:43:27,480
Speaker 1: has to give. The markets are fickle and demanding and

770
00:43:27,600 --> 00:43:32,279
Speaker 1: engineered to demand endless growth and endless returns. GENERATIVAI is

771
00:43:32,360 --> 00:43:35,239
Speaker 1: hitting a wall. I'll go into that in the next episode,

772
00:43:35,440 --> 00:43:38,200
Speaker 1: and any future improvements will be marginal and cost billions

773
00:43:38,239 --> 00:43:41,880
Speaker 1: of dollars to achieve. The transformer based architectures like the

774
00:43:41,960 --> 00:43:45,480
Speaker 1: kind used in open aised GPT models are gigantic maths,

775
00:43:45,520 --> 00:43:48,800
Speaker 1: machines that know nothing and will never, ever, ever ever

776
00:43:48,920 --> 00:43:53,080
Speaker 1: create the artificial general intelligence the conscious tech being that

777
00:43:53,120 --> 00:43:56,840
Speaker 1: Sam Altman has been claiming it will. GENERATIAI does not

778
00:43:56,920 --> 00:44:00,040
Speaker 1: appear to provide the kind of easy business return and

779
00:44:00,080 --> 00:44:02,680
Speaker 1: it's reminiscent of the cloud computing boom and mobile app

780
00:44:02,680 --> 00:44:06,719
Speaker 1: store booms. And once that becomes clear, the markets will

781
00:44:06,719 --> 00:44:10,319
Speaker 1: punish those most deeply invested in quite a painful way,

782
00:44:11,440 --> 00:44:13,680
Speaker 1: and once they do, the real thumb will begin as

783
00:44:13,719 --> 00:44:16,480
Speaker 1: big tech reconciles with the lack of innovation and leadership

784
00:44:16,520 --> 00:44:19,920
Speaker 1: teams stuffed with management consultants, product managers, and sick evans

785
00:44:19,960 --> 00:44:24,600
Speaker 1: that lank any real ideas or expertise that might inform

786
00:44:24,960 --> 00:44:28,360
Speaker 1: what actually might be next, not least because they've sequested

787
00:44:28,400 --> 00:44:31,760
Speaker 1: themselves away from creators and pretty much any normal person

788
00:44:31,840 --> 00:44:35,040
Speaker 1: or anyone who does an actual job. I don't really

789
00:44:35,080 --> 00:44:37,080
Speaker 1: know when this reckoning will happen, though, but I do

790
00:44:37,239 --> 00:44:40,640
Speaker 1: know this. When I started writing this script, it was

791
00:44:40,719 --> 00:44:42,920
Speaker 1: a brief way to connect the past to the present.

792
00:44:43,000 --> 00:44:45,680
Speaker 1: And as with everything I've written, it seems I found

793
00:44:45,680 --> 00:44:47,680
Speaker 1: my argument as I wrote it, searching as I went.

794
00:44:48,400 --> 00:44:50,600
Speaker 1: There's no prompt that could have told a generative AI

795
00:44:50,680 --> 00:44:53,040
Speaker 1: to write what I've written, Nor is there a prompt

796
00:44:53,040 --> 00:44:56,600
Speaker 1: that would let me delightfully enrage myself in a tiny

797
00:44:56,680 --> 00:45:00,040
Speaker 1: sound proof in my garage and all of that. That

798
00:45:00,360 --> 00:45:03,040
Speaker 1: is the magic that creates things like this podcast, things

799
00:45:03,040 --> 00:45:05,320
Speaker 1: like my news there, things like you're writing, you're singing,

800
00:45:05,400 --> 00:45:08,800
Speaker 1: your coding, and everything like that. The process of creation,

801
00:45:09,000 --> 00:45:12,399
Speaker 1: the actual labor of considering what you should do next,

802
00:45:12,480 --> 00:45:15,400
Speaker 1: the mistakes you make, the finding the theories behind the

803
00:45:15,440 --> 00:45:19,280
Speaker 1: decisions you make, is what creates great work. What creates

804
00:45:19,360 --> 00:45:23,839
Speaker 1: great writing, not the probabilistic formulation of whatever you might

805
00:45:23,960 --> 00:45:26,239
Speaker 1: create if you trained on billions of words of other

806
00:45:26,280 --> 00:45:30,040
Speaker 1: people's stuff. It kind of reminds me chat GBT, especially

807
00:45:30,080 --> 00:45:32,480
Speaker 1: reminds me of the kind of writing i'd read in college,

808
00:45:32,880 --> 00:45:35,560
Speaker 1: where it was very much people saying things in the

809
00:45:35,680 --> 00:45:37,880
Speaker 1: order that they thought they should say them. The structures

810
00:45:37,960 --> 00:45:41,120
Speaker 1: like intro, body, conclusion. It was the same words, it

811
00:45:41,160 --> 00:45:43,480
Speaker 1: was the same things. And this was quite a long

812
00:45:43,520 --> 00:45:47,080
Speaker 1: time before chat GBT, and it was because people were

813
00:45:47,080 --> 00:45:49,319
Speaker 1: writing to spec they were doing what they thought they

814
00:45:49,320 --> 00:45:53,000
Speaker 1: should do, rather than writing a lot and coming out

815
00:45:53,000 --> 00:45:54,879
Speaker 1: with something at the end and no offense them. They're

816
00:45:54,880 --> 00:45:57,720
Speaker 1: college students. They should have been told. They shouldn't have been taught. Writing,

817
00:45:57,719 --> 00:46:00,480
Speaker 1: should be taught, talking, should be taught. They there are

818
00:46:00,719 --> 00:46:03,920
Speaker 1: social things that we learn, but we learn through making mistakes.

819
00:46:04,120 --> 00:46:06,319
Speaker 1: I can't code, but those people that I know can

820
00:46:06,520 --> 00:46:08,200
Speaker 1: have messed up so many times to their code. They've

821
00:46:08,200 --> 00:46:11,360
Speaker 1: broken things tons and tons of times. Part of the

822
00:46:11,400 --> 00:46:14,319
Speaker 1: great thing of creation is the destruction that you have

823
00:46:14,400 --> 00:46:17,640
Speaker 1: to go through to get there. I've written about seven

824
00:46:17,719 --> 00:46:20,160
Speaker 1: hundred thousand words in the last four years, and I

825
00:46:20,160 --> 00:46:22,759
Speaker 1: only really became good I'd say in the last two

826
00:46:22,800 --> 00:46:27,680
Speaker 1: hundred thousand, maybe one hundred and fifty thousand. I couldn't

827
00:46:27,680 --> 00:46:30,400
Speaker 1: have got there just by reading that many words. You

828
00:46:30,520 --> 00:46:33,080
Speaker 1: need to put in the time But if you don't

829
00:46:33,080 --> 00:46:35,920
Speaker 1: put time into anything, if you don't create anything, of

830
00:46:35,960 --> 00:46:37,879
Speaker 1: course you don't respect that, And of course you don't

831
00:46:37,880 --> 00:46:41,800
Speaker 1: know what good looks like. But these people, these people

832
00:46:41,800 --> 00:46:45,120
Speaker 1: who are so disconnected, they will demand, as Jack Welch did,

833
00:46:45,200 --> 00:46:47,880
Speaker 1: that we burn whatever we need in pursuit of growth.

834
00:46:48,200 --> 00:46:51,920
Speaker 1: We must divert billions of dollars, exobites of data, endless

835
00:46:51,960 --> 00:46:54,839
Speaker 1: acres of data centers. Also that we could maybe create

836
00:46:54,880 --> 00:46:58,480
Speaker 1: a future they don't understand or care about. It doesn't

837
00:46:58,480 --> 00:47:01,319
Speaker 1: matter if generat if AI actually does anything, just as

838
00:47:01,320 --> 00:47:03,560
Speaker 1: long as they can convince shareholders and an analyst that it

839
00:47:03,600 --> 00:47:07,399
Speaker 1: might one day do so. It's hard to consider any

840
00:47:07,440 --> 00:47:09,279
Speaker 1: of this a grift, because doing so would be it

841
00:47:09,320 --> 00:47:12,160
Speaker 1: to admit how much of the economy is controlled by grifters.

842
00:47:12,880 --> 00:47:14,320
Speaker 1: But you know what, I'm gonna leave you with a

843
00:47:14,400 --> 00:47:16,560
Speaker 1: quote from Nick shi Rash, who I interviewed a few

844
00:47:16,560 --> 00:47:19,000
Speaker 1: episodes ago about it, and this is a quote from

845
00:47:19,000 --> 00:47:21,719
Speaker 1: his excellent blog. I will fucking pile drive you if

846
00:47:21,760 --> 00:47:25,120
Speaker 1: you mention AI again. Not gonna do an Australian accent.

847
00:47:25,160 --> 00:47:31,040
Speaker 1: That's rude. You see, Well, hype is nice. It's only

848
00:47:31,160 --> 00:47:35,319
Speaker 1: nice and small burst for practitioners. We have a few

849
00:47:35,440 --> 00:47:37,839
Speaker 1: key things that a grifter does not have, such as

850
00:47:37,920 --> 00:47:42,680
Speaker 1: job stability, genuine friendships, and souls. What we do not

851
00:47:42,920 --> 00:47:45,920
Speaker 1: have is the ability to trivially switch fields the moment

852
00:47:45,920 --> 00:47:48,440
Speaker 1: the gold rush is over due to the sad fact

853
00:47:48,440 --> 00:47:52,960
Speaker 1: that we've actually needed to study things and build experience. Grifters,

854
00:47:53,000 --> 00:47:54,840
Speaker 1: on the other hand, wield the omni tool that is

855
00:47:54,920 --> 00:47:58,839
Speaker 1: self aggrandizingly called politics. That is to say, it turns

856
00:47:58,880 --> 00:48:01,839
Speaker 1: out that the core competency smiling and promising things that

857
00:48:01,880 --> 00:48:07,560
Speaker 1: you can't actually deliver, is highly transferable. Generative AI is

858
00:48:07,560 --> 00:48:10,440
Speaker 1: an active theft in and of itself, perpetuated by people

859
00:48:10,440 --> 00:48:13,640
Speaker 1: that have stolen innovation in the name of shareholder supremacy,

860
00:48:14,200 --> 00:48:17,279
Speaker 1: creating a degenerative form of innovation that optimizes the tech

861
00:48:17,320 --> 00:48:20,360
Speaker 1: industry to create things that sound cool rather than actually

862
00:48:20,360 --> 00:48:23,799
Speaker 1: do things and help people. And the people perpetuating these

863
00:48:23,840 --> 00:48:29,680
Speaker 1: acts sundarp Isshai, Mark Zuckerberg, Andy Jesse Sachy Nadella, Sam Lman,

864
00:48:29,920 --> 00:48:33,319
Speaker 1: Mirror Marati are all the same kind of charlatan, the

865
00:48:33,440 --> 00:48:36,240
Speaker 1: ultimate manager, one that has created the means to escape

866
00:48:36,239 --> 00:48:39,520
Speaker 1: the workforce and ultimately having to create anything of any kind.

867
00:48:41,160 --> 00:48:45,480
Speaker 1: These people, the crave the ultimate business where it's just

868
00:48:45,560 --> 00:48:48,840
Speaker 1: them and all the money flows up, kind of like

869
00:48:48,880 --> 00:48:52,440
Speaker 1: the final shade from Destiny Too or the Ultimate Sukiyomi

870
00:48:52,440 --> 00:48:55,560
Speaker 1: from Narutau. And I won't spoil the fun Fantasy seven

871
00:48:55,600 --> 00:48:58,880
Speaker 1: Rebirth collection either, But there is this thing in fiction

872
00:48:59,040 --> 00:49:02,000
Speaker 1: about this idea of a final shape, of an ultimate

873
00:49:02,080 --> 00:49:05,080
Speaker 1: dream where everything's locked under one eye, And as crazy

874
00:49:05,120 --> 00:49:07,440
Speaker 1: as that sounds, this really feels like what they want

875
00:49:07,719 --> 00:49:09,879
Speaker 1: as few people as possible to make them as much

876
00:49:09,920 --> 00:49:12,160
Speaker 1: money as possible, and the people who invest in them

877
00:49:12,440 --> 00:49:16,600
Speaker 1: as much money as possible. And it's gross. It's frustrating.

878
00:49:18,080 --> 00:49:19,799
Speaker 1: They could make a tenth of what they do and

879
00:49:19,880 --> 00:49:25,000
Speaker 1: still be so incredibly rich and probably not destroy their companies.

880
00:49:25,200 --> 00:49:28,200
Speaker 1: Google could putter around a two to five percent profitability

881
00:49:28,239 --> 00:49:31,240
Speaker 1: each quarter, it doesn't matter. It would still be fine,

882
00:49:31,960 --> 00:49:35,360
Speaker 1: but the markets don't care. It sucks. It makes me angry,

883
00:49:36,600 --> 00:49:40,080
Speaker 1: and I don't claim to have any answers or truly

884
00:49:40,160 --> 00:49:43,640
Speaker 1: know how to unwind all of this. I don't know

885
00:49:43,960 --> 00:49:46,960
Speaker 1: how to change things other than loudly saying what I

886
00:49:47,000 --> 00:49:48,879
Speaker 1: see in front of my eyes and how it makes

887
00:49:48,880 --> 00:49:51,520
Speaker 1: me feel, and wanting others to at the very least

888
00:49:51,560 --> 00:49:53,920
Speaker 1: have more clarity into the things that are being done

889
00:49:53,960 --> 00:49:56,280
Speaker 1: to them and the ways in which others have twisted

890
00:49:56,280 --> 00:49:58,879
Speaker 1: the system to make more money than anyone's ever had,

891
00:49:59,040 --> 00:50:03,880
Speaker 1: transforming company into these horrifying nihilist engines for growth, anti

892
00:50:03,960 --> 00:50:06,640
Speaker 1: companies that create value by reducing what they contribute to

893
00:50:06,680 --> 00:50:11,040
Speaker 1: the world. But I encourage you not to be nihilistic yourself.

894
00:50:11,400 --> 00:50:14,160
Speaker 1: Do not lose faith in the power of sunlight in

895
00:50:14,239 --> 00:50:18,920
Speaker 1: calling these people what they are. Parasites. Sam Altman is

896
00:50:18,960 --> 00:50:22,920
Speaker 1: a parasite, Sundar Pishai is a parasite, satch Nadella is

897
00:50:22,960 --> 00:50:26,800
Speaker 1: a parasite. Every single one of these people, these people

898
00:50:26,880 --> 00:50:29,440
Speaker 1: who have taken good companies that built good things that

899
00:50:29,480 --> 00:50:31,960
Speaker 1: people like that still made money and made them more

900
00:50:32,000 --> 00:50:35,839
Speaker 1: money while making the things worse, they are parasites, and

901
00:50:35,920 --> 00:50:40,600
Speaker 1: calling them that is necessary. If you Sundar Pishai or

902
00:50:40,640 --> 00:50:43,800
Speaker 1: one of your ilk here's this and are offended, fix

903
00:50:43,880 --> 00:50:47,520
Speaker 1: your goddamn company, make good things again, stop laying people off,

904
00:50:47,560 --> 00:50:50,760
Speaker 1: pay yourself less, and do more for the world. Otherwise

905
00:50:50,760 --> 00:50:53,319
Speaker 1: you are a parasite and you're deliberate in doing so.

906
00:50:54,400 --> 00:50:57,520
Speaker 1: Be clear and concise when speaking about these people. By

907
00:50:57,560 --> 00:51:01,759
Speaker 1: the way, be continually outraged damage they are doing to society.

908
00:51:01,880 --> 00:51:04,760
Speaker 1: And I encourage you all to catalog everything you see.

909
00:51:04,840 --> 00:51:07,239
Speaker 1: And I know posting through it doesn't sound like much,

910
00:51:07,400 --> 00:51:11,480
Speaker 1: but believe me, these people see it. These people know,

911
00:51:11,560 --> 00:51:15,960
Speaker 1: and these people have names. Sam Aortman, Sandra Pishai, Mark Zuckerberg,

912
00:51:16,040 --> 00:51:19,920
Speaker 1: Satya Nadela, Andy Jasse, all of these people diverting the

913
00:51:19,920 --> 00:51:25,040
Speaker 1: world's most talented engineers into an unsustainable, unprofitable boondoggle that

914
00:51:25,120 --> 00:51:28,120
Speaker 1: does nothing that they don't understand. All of them can

915
00:51:28,200 --> 00:51:31,000
Speaker 1: at least be held accountable on record, if not in

916
00:51:31,040 --> 00:51:35,120
Speaker 1: real life. Believe your eyes. You are being given less

917
00:51:35,239 --> 00:51:37,799
Speaker 1: so that others can have more. You are having things

918
00:51:37,840 --> 00:51:40,920
Speaker 1: taken from you by corporations because they must always please

919
00:51:41,080 --> 00:51:45,560
Speaker 1: the nebulous form of the shareholder. As I said, don't

920
00:51:45,560 --> 00:51:49,720
Speaker 1: give into nihilism. Though these people do read all this stuff.

921
00:51:49,760 --> 00:51:53,640
Speaker 1: They are aware of things like this podcast, but they

922
00:51:53,680 --> 00:51:56,280
Speaker 1: also see social media. They see the clouds of people

923
00:51:56,280 --> 00:51:59,160
Speaker 1: talking about how bad Google is now thanks to AI.

924
00:52:00,080 --> 00:52:04,040
Speaker 1: Even before that. Public pressure does work. Loud public pressure

925
00:52:04,080 --> 00:52:07,760
Speaker 1: consist in public pressure, but also Sunda Pishai, Prabagar Ragavan,

926
00:52:08,200 --> 00:52:11,759
Speaker 1: zach In Adela, Sam Altman say the goddamn name. Say

927
00:52:11,760 --> 00:52:15,200
Speaker 1: them repeatedly, loudly everywhere when you don't like something with

928
00:52:15,280 --> 00:52:20,480
Speaker 1: Google mention, Prabagar Ragavan mentioned sundar Pieshai engrave their names

929
00:52:20,520 --> 00:52:24,160
Speaker 1: to their bad acts. When you talk about how shitty

930
00:52:24,200 --> 00:52:29,160
Speaker 1: Facebook is, Mark Zuckerberg, Javier Olivan, Alex Schultz, Naomi gLite,

931
00:52:29,600 --> 00:52:33,480
Speaker 1: put their names by them. Let them not hide behind

932
00:52:33,560 --> 00:52:38,520
Speaker 1: the names of their corporations. Let history show that they

933
00:52:38,640 --> 00:52:42,520
Speaker 1: made so much money while doing so much damage, because

934
00:52:42,560 --> 00:52:45,400
Speaker 1: that is how they've gotten away with it. These people

935
00:52:45,480 --> 00:52:48,520
Speaker 1: have no more worldly concerns. They don't worry about bills,

936
00:52:48,560 --> 00:52:51,000
Speaker 1: they don't worry about the mortgage, they don't worry about

937
00:52:51,000 --> 00:52:55,080
Speaker 1: any of that crap. They don't have real problems. All

938
00:52:55,120 --> 00:52:58,840
Speaker 1: they have is their legacy and their goddamn name. So

939
00:52:59,040 --> 00:53:04,560
Speaker 1: take it from them. Take their name. Say the Cheryl Samberg,

940
00:53:04,719 --> 00:53:08,680
Speaker 1: a McKinsey operator an MBA is the reason that Facebook

941
00:53:08,719 --> 00:53:13,680
Speaker 1: started going downhill. Then Mark Zuckerberg, Javier Oliven, Naomi gLite,

942
00:53:13,800 --> 00:53:18,279
Speaker 1: Alec Schultz, Andrew Bosworth. All these people our why Facebook

943
00:53:18,440 --> 00:53:23,319
Speaker 1: is full of AI generated spam, say Sam Altman, Mirror

944
00:53:23,400 --> 00:53:26,239
Speaker 1: Marathi of open Ai. They are the people that are

945
00:53:26,320 --> 00:53:30,640
Speaker 1: stealing the entire internet to train models most of Varsuliema,

946
00:53:31,320 --> 00:53:35,080
Speaker 1: the Microsoft CEO of AI. Guess what, that guy is

947
00:53:35,120 --> 00:53:37,960
Speaker 1: also stealing your data. He is also training models on it.

948
00:53:38,520 --> 00:53:42,239
Speaker 1: He is the one perpetuating the great theft. As long

949
00:53:42,280 --> 00:53:45,240
Speaker 1: as their names are attached these acts, it'll be scarier

950
00:53:45,280 --> 00:53:48,560
Speaker 1: for them. I can't promise it will stop them. But

951
00:53:48,800 --> 00:53:52,880
Speaker 1: giving them a level of accountability, no matter Howell Thinn,

952
00:53:53,520 --> 00:53:56,680
Speaker 1: is necessary and the first step to fixing things. And

953
00:53:56,840 --> 00:54:00,239
Speaker 1: celebrate companies that make good shit. Celebrate things like the

954
00:54:00,280 --> 00:54:02,200
Speaker 1: steam Deck, one of the best consoles I've ever used.

955
00:54:02,239 --> 00:54:05,040
Speaker 1: I love that thing. So break companies like Anchor great

956
00:54:05,040 --> 00:54:07,680
Speaker 1: battery packs. There are things in tech that are still cool.

957
00:54:07,840 --> 00:54:10,040
Speaker 1: There are things in tech that are still good. You

958
00:54:10,200 --> 00:54:12,160
Speaker 1: just have to look for them, and you're not finding

959
00:54:12,200 --> 00:54:14,040
Speaker 1: them in big tech. And you're not finding them in

960
00:54:14,040 --> 00:54:17,040
Speaker 1: big tech because you are not the customer. You are

961
00:54:17,120 --> 00:54:20,560
Speaker 1: not the person that Mark Zuckerberg, Sam Altman, Sachin at

962
00:54:20,560 --> 00:54:24,280
Speaker 1: Deel or sand Uppishi cares about. No, they care about

963
00:54:24,320 --> 00:54:29,760
Speaker 1: the nebulous form of the shareholder, the markets and analyst targets.

964
00:54:30,719 --> 00:54:42,759
Speaker 1: You deserve better, so give them so much worse. Thank

965
00:54:42,800 --> 00:54:45,520
Speaker 1: you for listening to better Offline. The editor and composer

966
00:54:45,560 --> 00:54:48,359
Speaker 1: of the Better Offline theme song is Matasowski. You can

967
00:54:48,440 --> 00:54:50,799
Speaker 1: check out more of his music and audio projects at

968
00:54:50,840 --> 00:54:54,239
Speaker 1: Matasowski dot com, M A T T O. S O

969
00:54:55,000 --> 00:54:58,800
Speaker 1: w Ski dot com. You can email me an easy

970
00:54:58,840 --> 00:55:01,480
Speaker 1: at Better offline dot com or visit Better Offline dot

971
00:55:01,520 --> 00:55:04,120
Speaker 1: com to find more podcast links and of course, my newsletter.

972
00:55:04,520 --> 00:55:07,040
Speaker 1: I also really recommend you go to chat dot where's

973
00:55:07,040 --> 00:55:09,520
Speaker 1: youreaed dot at to visit the discord, and go to

974
00:55:09,560 --> 00:55:12,960
Speaker 1: our slash Better Offline to check out I'll Reddit. Thank

975
00:55:13,000 --> 00:55:16,400
Speaker 1: you so much for listening. Better Offline is a production

976
00:55:16,480 --> 00:55:19,120
Speaker 1: of cool Zone Media. For more from cool Zone Media,

977
00:55:19,239 --> 00:55:22,400
Speaker 1: visit our website cool Zonemedia dot com, or check us

978
00:55:22,400 --> 00:55:25,400
Speaker 1: out on the iHeartRadio app, Apple Podcasts, or wherever you

979
00:55:25,440 --> 00:55:26,560
Speaker 1: get your podcasts.