1
00:00:02,840 --> 00:00:03,560
Speaker 1: Zone Media.

2
00:00:04,400 --> 00:00:07,560
Speaker 2: Hello, and welcome to Better Offline. I'm your host ed Zetron.

3
00:00:19,760 --> 00:00:22,320
Speaker 2: The tech industry has craved a messiah since the death

4
00:00:22,360 --> 00:00:26,079
Speaker 2: of Steve Jobson twenty eleven, but in Open Ay's CEO

5
00:00:26,200 --> 00:00:28,840
Speaker 2: Sam Mortmon, I think they've discovered more of a false profit,

6
00:00:29,160 --> 00:00:32,360
Speaker 2: a seedy little grifter that uses his remarkable ability to

7
00:00:32,400 --> 00:00:37,160
Speaker 2: impress and manipulate people, specifically in Silicon Valley, to mask

8
00:00:37,200 --> 00:00:40,920
Speaker 2: a total lack of technical and business acumen. I realized

9
00:00:40,920 --> 00:00:44,000
Speaker 2: this sounds a little dramatic and definitely a little inflammatory,

10
00:00:44,040 --> 00:00:47,360
Speaker 2: but the air around Sam Mortman has for years been

11
00:00:47,640 --> 00:00:51,200
Speaker 2: that he's somehow a magical, special creature, a man who

12
00:00:51,240 --> 00:00:54,200
Speaker 2: and I quote is wise beyond his years and was

13
00:00:54,280 --> 00:00:57,080
Speaker 2: so at the tender age of nineteen and who to

14
00:00:57,200 --> 00:01:01,680
Speaker 2: quote startup incubator why Combinators Paul Gray could be parachuted

15
00:01:01,720 --> 00:01:04,399
Speaker 2: into an island full of cannibals and come back in

16
00:01:04,480 --> 00:01:07,760
Speaker 2: five years and be king. In the next two episodes,

17
00:01:08,000 --> 00:01:12,320
Speaker 2: I'm going to dig into Sam Moultman's really specious success story,

18
00:01:12,600 --> 00:01:14,160
Speaker 2: and it's one that was built on the back of

19
00:01:14,240 --> 00:01:16,759
Speaker 2: being in the right place at the right time, definitely

20
00:01:16,800 --> 00:01:21,920
Speaker 2: dodging accountability and responsibility and basically every job he's ever had,

21
00:01:22,040 --> 00:01:24,720
Speaker 2: including by the way, the two that he was fired

22
00:01:24,760 --> 00:01:27,800
Speaker 2: from and the feiled startup he had. And I believe

23
00:01:27,840 --> 00:01:30,920
Speaker 2: he's used his political powers leverage to scare away anyone

24
00:01:30,920 --> 00:01:33,759
Speaker 2: who's going to ask any nasty questions or of course,

25
00:01:34,080 --> 00:01:38,280
Speaker 2: dare to stand against him. In a stunning in depth

26
00:01:38,319 --> 00:01:41,600
Speaker 2: piece by Ellen Hewett of Bloomberg, Sam Altman is repeatedly

27
00:01:41,640 --> 00:01:45,400
Speaker 2: framed by his contemporaries as some sort of genius, without

28
00:01:45,440 --> 00:01:49,520
Speaker 2: anyone ever asking why or explaining why, Rather than there's

29
00:01:49,560 --> 00:01:55,080
Speaker 2: this vague sense of intellectual and philosophical superiority with why

30
00:01:55,120 --> 00:01:58,440
Speaker 2: Combinator founder John Cougan claiming that Altman had and I

31
00:01:58,600 --> 00:02:02,560
Speaker 2: quote an uncanny ability to listen intently and diagnose problems,

32
00:02:02,960 --> 00:02:05,240
Speaker 2: and that he was and this is a real quote.

33
00:02:05,280 --> 00:02:09,560
Speaker 2: I'm not kidding the Michael Jordan of listening. Sit with

34
00:02:09,600 --> 00:02:15,840
Speaker 2: that for a moment, Just sit with that. These laughable

35
00:02:15,840 --> 00:02:19,120
Speaker 2: and completely stupid accolades aside, there doesn't actually appear to

36
00:02:19,160 --> 00:02:21,200
Speaker 2: be a single story that I can find of some

37
00:02:21,360 --> 00:02:25,480
Speaker 2: genius moment of clarity ushered in by Sam Altman. There

38
00:02:25,520 --> 00:02:29,240
Speaker 2: are none of these fantastical situations where his remarkable mind

39
00:02:29,280 --> 00:02:32,760
Speaker 2: brilliantly delivers the exact solution to a problem or some

40
00:02:32,800 --> 00:02:37,920
Speaker 2: sort of concrete accomplishment that required these descriptive, pre natural

41
00:02:38,040 --> 00:02:40,800
Speaker 2: levels of vision and clarity. No, I just found this

42
00:02:40,919 --> 00:02:44,400
Speaker 2: torrent of platitudes about this man who always gets what

43
00:02:44,480 --> 00:02:46,960
Speaker 2: he wants, which is, by the way, another quote from

44
00:02:47,000 --> 00:02:50,280
Speaker 2: Ellen Hewitt's story. And he just appears to be this

45
00:02:50,360 --> 00:02:54,440
Speaker 2: unstoppably pushy young man that excelled not necessarily at building things,

46
00:02:54,520 --> 00:02:58,520
Speaker 2: because he really has not built any great companies, nor

47
00:02:58,600 --> 00:03:02,320
Speaker 2: have they done any great things. It's mostly about and

48
00:03:02,320 --> 00:03:05,880
Speaker 2: I quote Allan Hugh again, sam Orman, bending the world

49
00:03:05,960 --> 00:03:10,280
Speaker 2: to his will. If this all sounds familiar, by the way,

50
00:03:10,280 --> 00:03:14,160
Speaker 2: it's because I've really said this before. Many CEOs, especially

51
00:03:14,200 --> 00:03:17,760
Speaker 2: in take, had this amazing ability to make these bold proclamations,

52
00:03:17,800 --> 00:03:20,800
Speaker 2: and that had people pretty much accept them at face value,

53
00:03:21,080 --> 00:03:23,960
Speaker 2: even by the media that's meant to hold them to account.

54
00:03:24,120 --> 00:03:27,280
Speaker 2: With the earliest days of Facebook's metaverse pivot, probably the

55
00:03:27,280 --> 00:03:29,720
Speaker 2: best example I can give you, I really encourage you

56
00:03:29,800 --> 00:03:31,320
Speaker 2: to go back to the rock Com bubble and the

57
00:03:31,360 --> 00:03:35,080
Speaker 2: Facebook episodes to look into it. But even by Mark

58
00:03:35,200 --> 00:03:39,800
Speaker 2: Zuckerbian standards, Zuckerberbian now we'll get to that later. Sam

59
00:03:39,880 --> 00:03:44,560
Speaker 2: Altman exists in his own pantheon of bullshit. There are many, many,

60
00:03:44,640 --> 00:03:47,680
Speaker 2: many examples of him saying open AI, or I should

61
00:03:47,720 --> 00:03:51,200
Speaker 2: be more specific, AI broadly will do something it cannot

62
00:03:51,240 --> 00:03:54,360
Speaker 2: and likely will not do, such as think for itself

63
00:03:54,480 --> 00:03:58,320
Speaker 2: or be that super smart companion I keep quoting, and

64
00:03:59,080 --> 00:04:02,120
Speaker 2: the fourth estate just kind of accepts it without any pushback.

65
00:04:02,880 --> 00:04:06,240
Speaker 2: And this is really Sam Mortman's history being in the

66
00:04:06,320 --> 00:04:09,480
Speaker 2: right place, saying the right thing, and even when the

67
00:04:09,520 --> 00:04:13,640
Speaker 2: thing in question is kind of hollow, people saying, wow, oh,

68
00:04:13,720 --> 00:04:17,800
Speaker 2: this boy is so smart, and there's just no limit.

69
00:04:18,200 --> 00:04:21,400
Speaker 2: It seems to this phenomenon. When Sam Mortman says something

70
00:04:21,480 --> 00:04:25,520
Speaker 2: or does something genuinely truly insane, like how he wants

71
00:04:25,520 --> 00:04:28,960
Speaker 2: to raise seven trillion dollars for futuristic chips, which is

72
00:04:29,040 --> 00:04:32,159
Speaker 2: by the way, they combined GDP of Germany and France,

73
00:04:32,920 --> 00:04:35,480
Speaker 2: or that he needs one hundred billion dollars from Microsoft

74
00:04:35,480 --> 00:04:40,080
Speaker 2: to build a supercomputer for the future of AI, people

75
00:04:40,160 --> 00:04:43,279
Speaker 2: just say, yeah, sounds about right, Yes, classic Sam Mortman's

76
00:04:43,240 --> 00:04:46,159
Speaker 2: stuff is just the smart bloke going. The response is

77
00:04:46,279 --> 00:04:49,679
Speaker 2: never to dismiss it and say this is absolutely bloody

78
00:04:49,720 --> 00:04:52,560
Speaker 2: stupid but to actually discuss it with a level of

79
00:04:52,640 --> 00:04:56,040
Speaker 2: seriousness that just is not warranted for anyone, let alone

80
00:04:56,120 --> 00:05:00,760
Speaker 2: Sam Ortman. And that might be Aortmand's real skill collopsia,

81
00:05:01,320 --> 00:05:04,599
Speaker 2: the appearance of things being more beautiful than they really are,

82
00:05:04,839 --> 00:05:08,000
Speaker 2: hiding the weakness of his arguments, and indeed generative AI

83
00:05:08,080 --> 00:05:11,600
Speaker 2: writ large and beguiling those around him with this nasty

84
00:05:11,680 --> 00:05:14,120
Speaker 2: instinctial ability to tell them exactly what they want to hear,

85
00:05:14,200 --> 00:05:17,480
Speaker 2: giving them the words to tell other people in his name,

86
00:05:17,839 --> 00:05:20,120
Speaker 2: to get in exactly the room he needs to be

87
00:05:20,160 --> 00:05:22,640
Speaker 2: in exactly the right time to connect with exactly the

88
00:05:22,720 --> 00:05:26,680
Speaker 2: right people, or without ever having to actually do anything

89
00:05:26,760 --> 00:05:30,719
Speaker 2: or create anything. Despite the fact that his location based

90
00:05:30,720 --> 00:05:33,800
Speaker 2: social network looped failed to get any traction or build

91
00:05:34,040 --> 00:05:36,800
Speaker 2: any meaningful product, it appears it allowed him to get

92
00:05:36,800 --> 00:05:41,320
Speaker 2: in the Dora famed Silicon Valley Incubator, y Combinator, and Dazzle.

93
00:05:41,360 --> 00:05:46,200
Speaker 2: Poor Graham It's creator who, for reasons I cannot understand,

94
00:05:46,240 --> 00:05:49,560
Speaker 2: I've read so much of poor Graham's stuff now, Paul

95
00:05:49,560 --> 00:05:52,560
Speaker 2: Graham became convinced that Sam Worton was the future, and

96
00:05:52,640 --> 00:05:55,760
Speaker 2: in turn helped Sam Morton get in on these huge

97
00:05:55,880 --> 00:05:59,400
Speaker 2: VC deals in companies like Stripe and Airbnb, making him

98
00:05:59,520 --> 00:06:03,200
Speaker 2: hundreds of millions of dollars. This is, by the way,

99
00:06:03,760 --> 00:06:06,599
Speaker 2: a very Silicon valley problem and a problem with the

100
00:06:06,640 --> 00:06:09,120
Speaker 2: vallee writ large, and a precursor to the growth that

101
00:06:09,200 --> 00:06:12,360
Speaker 2: all costs rot economy that I talk about seemingly every minute.

102
00:06:12,720 --> 00:06:15,520
Speaker 2: When you strip away Sam Morton's ability to convince people

103
00:06:15,520 --> 00:06:18,400
Speaker 2: that he's smart, he doesn't appear to have done anything.

104
00:06:18,440 --> 00:06:21,160
Speaker 2: He's done very, very little. He was a college dropout

105
00:06:21,200 --> 00:06:25,200
Speaker 2: with a failing then failed startup, one where employees tried

106
00:06:25,240 --> 00:06:29,200
Speaker 2: to get him fired twice because he kept diverting resources

107
00:06:29,240 --> 00:06:32,560
Speaker 2: to other places and focusing on his own personal products

108
00:06:32,760 --> 00:06:34,960
Speaker 2: and projects. And the reason they sound so flushed that

109
00:06:35,120 --> 00:06:40,080
Speaker 2: is this is Sam Altman's entire existence. In a podcast

110
00:06:40,120 --> 00:06:43,679
Speaker 2: discovered by Ellen Hewett Bloomberg, Twitch co founder Emmitt Sheer

111
00:06:43,839 --> 00:06:47,040
Speaker 2: appeared from Mortman's y combinator cohort the first one and

112
00:06:47,160 --> 00:06:51,520
Speaker 2: briefly his replacement at CEO of OpenAI, described his surprise

113
00:06:51,600 --> 00:06:53,719
Speaker 2: that Sam Morton was able to close deals with boost

114
00:06:53,800 --> 00:06:59,200
Speaker 2: Mobile without any actual product yet because Altmand fit a template.

115
00:06:59,400 --> 00:07:02,120
Speaker 2: He resembled a kind of guy that got things done.

116
00:07:02,400 --> 00:07:05,479
Speaker 2: Powerful people in Silicon Valley have fallen over themselves to

117
00:07:05,560 --> 00:07:08,279
Speaker 2: give him the opportunities that made him look like a

118
00:07:08,360 --> 00:07:11,440
Speaker 2: king maker. And at some point, the funny thing is

119
00:07:11,480 --> 00:07:13,840
Speaker 2: in the Valley is when you get to the prominence

120
00:07:13,880 --> 00:07:16,000
Speaker 2: where people just feel like you should be in on

121
00:07:16,080 --> 00:07:20,280
Speaker 2: these things, you are. That's why all these guys all

122
00:07:20,360 --> 00:07:22,520
Speaker 2: kind of look and act the same and all get

123
00:07:22,560 --> 00:07:28,160
Speaker 2: in on the same things. And honestly, I think the

124
00:07:28,240 --> 00:07:32,000
Speaker 2: truth might be a little grimmar. Almond was, from a

125
00:07:32,040 --> 00:07:35,440
Speaker 2: relatively early age chosen by Silicon Valley to be their

126
00:07:35,480 --> 00:07:38,760
Speaker 2: next messiah, which allowed him to wield this incredible power

127
00:07:39,040 --> 00:07:42,920
Speaker 2: over the startup ecosystem without really ever meaningfully contributing to it.

128
00:07:43,520 --> 00:07:45,880
Speaker 2: His ascent to the apex of the Valley and the

129
00:07:45,880 --> 00:07:49,480
Speaker 2: budding flowers of a sam Ortman colt, which we see

130
00:07:49,520 --> 00:07:54,559
Speaker 2: today everywhere, feels random and arbitrary, without any real force

131
00:07:54,640 --> 00:08:00,720
Speaker 2: behind it. Aw there's one thing, though, Sam Boulman, he's

132
00:08:00,720 --> 00:08:04,400
Speaker 2: a master manipulator. He's incredibly adept at saying things that

133
00:08:04,600 --> 00:08:08,240
Speaker 2: sound profound, like your rate of learning should always be high,

134
00:08:08,240 --> 00:08:10,040
Speaker 2: and yes that's a quote, as are the rest of these,

135
00:08:10,360 --> 00:08:12,760
Speaker 2: and that each unit of work you do should generate

136
00:08:12,800 --> 00:08:15,520
Speaker 2: more and more results while also knowing that the self

137
00:08:15,560 --> 00:08:18,440
Speaker 2: reinforcing prophecies of the tech industry are what makes someone

138
00:08:18,520 --> 00:08:23,400
Speaker 2: rich and powerful, rather than achievements or founder great companies

139
00:08:23,520 --> 00:08:27,560
Speaker 2: or doing things for people. In essence, his whole vacuous

140
00:08:27,600 --> 00:08:30,560
Speaker 2: platitude buffet, the kind that can be cut into ten

141
00:08:30,600 --> 00:08:34,600
Speaker 2: second clips for TikTok and YouTube and Twitter. They're really

142
00:08:34,679 --> 00:08:38,719
Speaker 2: good ways to feel intelligent when people already want you

143
00:08:38,840 --> 00:08:45,120
Speaker 2: to be, and they're just really useful for tricking extremely

144
00:08:45,200 --> 00:08:51,160
Speaker 2: disconnected and credulous morons. People that don't really participate in

145
00:08:51,240 --> 00:08:54,920
Speaker 2: the grandest scheme of building software and hardware, people like

146
00:08:55,000 --> 00:08:58,880
Speaker 2: Read Hoffman of LinkedIn, of Brian Cheski of Airbnb. People

147
00:08:58,880 --> 00:09:02,160
Speaker 2: that aren't coders or builders or anything. They're just people

148
00:09:02,200 --> 00:09:06,480
Speaker 2: that vaguely fell into success. Perhaps they built useful companies,

149
00:09:06,480 --> 00:09:08,440
Speaker 2: but they didn't really make the companies, and they didn't

150
00:09:08,480 --> 00:09:12,079
Speaker 2: really do the work. Sam Altman is really good at

151
00:09:12,080 --> 00:09:15,280
Speaker 2: saying the things that reinforce their biases, and in the

152
00:09:15,360 --> 00:09:20,960
Speaker 2: process kind of helps them disguise their nepotism and his

153
00:09:21,120 --> 00:09:24,800
Speaker 2: real superpower, which is, by the way, another form of nepotism.

154
00:09:25,440 --> 00:09:28,480
Speaker 2: Sam Moorman didn't find the startups that made him so

155
00:09:28,720 --> 00:09:31,880
Speaker 2: rich and wealthy and influential. He was being shown them

156
00:09:31,880 --> 00:09:35,440
Speaker 2: by other powerful people that wanted him in on these

157
00:09:35,480 --> 00:09:37,839
Speaker 2: deals so that he could give them a vice based

158
00:09:37,920 --> 00:09:41,520
Speaker 2: on the career of specious management bullshit. And because the

159
00:09:41,600 --> 00:09:44,439
Speaker 2: valley liked how he looked and how he acted, how

160
00:09:44,440 --> 00:09:47,120
Speaker 2: he talked, the things he resembled, the things they were

161
00:09:47,160 --> 00:09:50,880
Speaker 2: reminded of when they heard Sam Mormon speak. And it's

162
00:09:50,880 --> 00:09:53,160
Speaker 2: funny because a lot of these people, the Paul Graham's

163
00:09:53,160 --> 00:09:56,560
Speaker 2: of the world especially, they're big time meritocratic people. They

164
00:09:56,640 --> 00:09:59,679
Speaker 2: love the meritocracy. Yet when you look deeper, the people

165
00:10:00,080 --> 00:10:04,079
Speaker 2: seeding and not actually building the things. Ilia Suitzkaeva over

166
00:10:04,200 --> 00:10:07,840
Speaker 2: Open Ai. He is the actual technolog Jesus, He's the

167
00:10:07,880 --> 00:10:10,280
Speaker 2: actual guy that and by the way, no longer Open

168
00:10:10,320 --> 00:10:14,040
Speaker 2: Ai the kind of deserves this. But Sam Alton's the

169
00:10:14,040 --> 00:10:16,600
Speaker 2: one that got invited in early to stripe and Airbnb

170
00:10:16,720 --> 00:10:19,319
Speaker 2: and all these things. And as I'll get into, kind

171
00:10:19,320 --> 00:10:22,640
Speaker 2: of rat fucked his way around a bit. And nowhere

172
00:10:22,720 --> 00:10:26,319
Speaker 2: is this more obvious than in Hydrozene Capital, Aortman's venture

173
00:10:26,360 --> 00:10:28,680
Speaker 2: capital fund that he created with the five million dollars

174
00:10:28,760 --> 00:10:31,880
Speaker 2: he got from selling looped his failed startup by the

175
00:10:31,880 --> 00:10:36,240
Speaker 2: way and backing of course from Peter Teel, Hydrozene invested

176
00:10:36,320 --> 00:10:39,760
Speaker 2: seventy five percent of its funding in y Combinator companies

177
00:10:39,800 --> 00:10:43,440
Speaker 2: including Reddit and instacar, even after Sam Mortman became the

178
00:10:43,480 --> 00:10:47,280
Speaker 2: president of y Combinator, which is weird because the other

179
00:10:47,360 --> 00:10:50,000
Speaker 2: partners at y Combinate, like Gary Tann, they were forbidden

180
00:10:50,040 --> 00:10:52,880
Speaker 2: from managing their own investment funds at the time, according

181
00:10:52,920 --> 00:10:55,839
Speaker 2: to reporting from the Wall Street Journal. But I guess

182
00:10:55,840 --> 00:10:59,800
Speaker 2: Sam Moltman just felt right. It's cool that he gets

183
00:10:59,880 --> 00:11:02,840
Speaker 2: rid right, not to say Gary Tann hasn't, but the

184
00:11:02,880 --> 00:11:06,200
Speaker 2: other people just didn't seem to get these opportunities for

185
00:11:06,240 --> 00:11:11,760
Speaker 2: some reason, could be anything. And he became head of

186
00:11:11,880 --> 00:11:14,720
Speaker 2: why Combinated, by the way, despite being one of the

187
00:11:14,960 --> 00:11:17,439
Speaker 2: he was looped was one of the first companies in

188
00:11:17,679 --> 00:11:20,440
Speaker 2: y Combinator, and they to explain how this works. Why

189
00:11:20,480 --> 00:11:23,280
Speaker 2: Combinate would invest a little in a few early stage

190
00:11:23,280 --> 00:11:26,160
Speaker 2: startups and much larger number these days, and the first

191
00:11:26,200 --> 00:11:28,880
Speaker 2: cohort was one that included Sam Altman's Looped and he

192
00:11:28,960 --> 00:11:32,680
Speaker 2: was made president of y Combinator. Despite the fact that

193
00:11:32,800 --> 00:11:35,480
Speaker 2: luped was terrible. It didn't have a good product, They

194
00:11:35,520 --> 00:11:38,960
Speaker 2: couldn't sell it. He retasked engineers at one point to

195
00:11:39,040 --> 00:11:41,800
Speaker 2: work on a dating app somewhere else. Sam Alton was

196
00:11:41,840 --> 00:11:47,320
Speaker 2: a terrible CEO, But you know what, he's capable of

197
00:11:47,360 --> 00:11:50,679
Speaker 2: saying stupid shit like and I quote, competitors are one

198
00:11:50,720 --> 00:11:53,080
Speaker 2: of the last monsters that haunt your dreams to New

199
00:11:53,160 --> 00:11:56,760
Speaker 2: York Magazine shortly before predicting that there was absolutely no

200
00:11:56,840 --> 00:12:01,120
Speaker 2: reason to believe that we would not have a computer

201
00:12:01,200 --> 00:12:03,960
Speaker 2: by twenty twenty nine that could replicate his brain. You

202
00:12:04,040 --> 00:12:08,480
Speaker 2: know what, though, putting that aside, I do think Sam

203
00:12:08,480 --> 00:12:10,760
Speaker 2: Mormon's right on that one, though, in the sense that

204
00:12:10,840 --> 00:12:14,839
Speaker 2: chat GPT kind of seems capable of producing this kind

205
00:12:14,840 --> 00:12:20,439
Speaker 2: of nonsense too. But again, because Sam Mortman's the affable, friendly,

206
00:12:20,559 --> 00:12:23,560
Speaker 2: amicable white guy who's known by the right people. He

207
00:12:23,679 --> 00:12:27,640
Speaker 2: keeps going, he keeps on trucking, And I think that

208
00:12:27,720 --> 00:12:30,880
Speaker 2: Sam Moltman is on some level, he's a monument to

209
00:12:30,920 --> 00:12:32,480
Speaker 2: the roight at the core of the valley, and he's

210
00:12:32,520 --> 00:12:35,440
Speaker 2: a product of this growing distance between the tech industry

211
00:12:35,600 --> 00:12:40,120
Speaker 2: and actually creating things of value. While why Combinator founder

212
00:12:40,200 --> 00:12:43,480
Speaker 2: Paul Graham may be a decorated and successful computer scientist,

213
00:12:43,600 --> 00:12:45,640
Speaker 2: by the time he made Sam Mortman, president of y

214
00:12:45,679 --> 00:12:48,400
Speaker 2: Combinator in twenty fourteen, he was already more than a

215
00:12:48,440 --> 00:12:51,760
Speaker 2: decade removed from selling his software startup via web to Yahoo.

216
00:12:52,559 --> 00:12:55,599
Speaker 2: As he drifted further away from actually building things on

217
00:12:55,679 --> 00:12:59,520
Speaker 2: the computer, so too did Paul Graham's essays drift away

218
00:12:59,559 --> 00:13:04,480
Speaker 2: from the piosophical measures of software development towards a far

219
00:13:05,080 --> 00:13:08,160
Speaker 2: darker management philosophy, one where he admitted in a blog

220
00:13:08,200 --> 00:13:11,000
Speaker 2: from two thousand and three that intelligence itself is not

221
00:13:11,040 --> 00:13:14,040
Speaker 2: a factor in popularity because smart kids don't want to

222
00:13:14,080 --> 00:13:18,280
Speaker 2: be popular, and that popularity is much more about alliances

223
00:13:18,600 --> 00:13:23,520
Speaker 2: and doing things that bring you closer to other popular people. Humm,

224
00:13:24,400 --> 00:13:27,920
Speaker 2: maybe he did like Sam Wultman for real reasons then. Anyway,

225
00:13:28,400 --> 00:13:31,280
Speaker 2: two years before he made Samultman president, Paul Graham would

226
00:13:31,280 --> 00:13:34,480
Speaker 2: publish a piece called Startup Equal Growth, claiming that growth

227
00:13:34,600 --> 00:13:37,160
Speaker 2: drives everything in this world, and that growth makes the

228
00:13:37,200 --> 00:13:41,240
Speaker 2: successful companies so valuable that the expected value is high

229
00:13:41,320 --> 00:13:44,560
Speaker 2: even though the risk is two. A statement that could

230
00:13:44,640 --> 00:13:46,840
Speaker 2: only make sense if you believed that there will always

231
00:13:46,880 --> 00:13:49,959
Speaker 2: be hyper growth companies, and indeed that the opportunities for

232
00:13:49,960 --> 00:13:55,120
Speaker 2: those high growth companies would keep emerging, say for the

233
00:13:55,160 --> 00:13:59,120
Speaker 2: next forever and these people ever thought about it. It's so

234
00:13:59,320 --> 00:14:04,240
Speaker 2: strange to read this stuff, to go back even five years,

235
00:14:04,240 --> 00:14:08,800
Speaker 2: but especially ten and reading these things and reading these

236
00:14:08,800 --> 00:14:11,719
Speaker 2: people talking about how dogged Sam Morton is and how

237
00:14:11,760 --> 00:14:14,360
Speaker 2: great he is at this, and then reading their other philosophies,

238
00:14:14,400 --> 00:14:18,520
Speaker 2: and it's all stuff like, well, you see, uh, intelligence

239
00:14:18,520 --> 00:14:21,000
Speaker 2: comes from the mind and building businesses. It's all about

240
00:14:21,000 --> 00:14:25,200
Speaker 2: growth and business. And you read them and you're like, huh,

241
00:14:25,600 --> 00:14:28,400
Speaker 2: these people smart or stupid. I can't tell. They're using

242
00:14:28,480 --> 00:14:33,520
Speaker 2: smart people language, but they seem kind of stupid. Maybe

243
00:14:33,520 --> 00:14:36,760
Speaker 2: that's also the problem. Maybe the problem's just a little simpler.

244
00:14:37,520 --> 00:14:41,960
Speaker 2: While Sam Morton's a spacious opportunist and very much a manipulator,

245
00:14:43,240 --> 00:14:46,040
Speaker 2: the time he entered Silicon Valley was this period where

246
00:14:46,520 --> 00:14:48,800
Speaker 2: pretty much all you needed to do was sound smart

247
00:14:49,200 --> 00:14:52,880
Speaker 2: and be in the right rooms. Companies were being created

248
00:14:53,160 --> 00:14:56,280
Speaker 2: that could enter these giant markets and just dominate because

249
00:14:56,320 --> 00:15:01,360
Speaker 2: all they really needed was money and enough handshakes. Oltman

250
00:15:01,480 --> 00:15:04,840
Speaker 2: is adept at using connections to make new connections, in

251
00:15:04,880 --> 00:15:07,840
Speaker 2: finding new ways to make others owe him favors, in

252
00:15:07,960 --> 00:15:10,840
Speaker 2: saying the right thing at the right time when he

253
00:15:10,920 --> 00:15:13,400
Speaker 2: knew that nobody would think about it too hard, something

254
00:15:13,440 --> 00:15:16,840
Speaker 2: he continues to this day. Ortmand was early on Stripe

255
00:15:16,840 --> 00:15:20,560
Speaker 2: and read it in Airbnb, all seemingly brilliant moments of

256
00:15:20,640 --> 00:15:23,040
Speaker 2: investment in the life of a man who has had

257
00:15:23,200 --> 00:15:25,600
Speaker 2: many things handed to him, who knew how to look

258
00:15:25,680 --> 00:15:27,800
Speaker 2: and sound to get put in the room and to

259
00:15:27,840 --> 00:15:31,680
Speaker 2: get the capital to make his next move. It's easy

260
00:15:31,840 --> 00:15:35,320
Speaker 2: to conflay investment returns with intellectual capital, even though the

261
00:15:35,360 --> 00:15:38,480
Speaker 2: truth is that people just liked Sam Wultman enough to

262
00:15:38,480 --> 00:15:40,520
Speaker 2: give him the opportunity to be rich, and he took it.

263
00:15:40,840 --> 00:15:43,080
Speaker 2: And he had the ability to hand them money too.

264
00:15:43,600 --> 00:15:45,560
Speaker 2: In two thousand and nine, when he put fifteen thousand

265
00:15:45,600 --> 00:15:47,240
Speaker 2: dollars into Stripe, which I'll get to it a bit,

266
00:15:47,720 --> 00:15:49,640
Speaker 2: he had fifteen grand he could pull out in the

267
00:15:49,640 --> 00:15:52,040
Speaker 2: middle of founding a start up. He was working on

268
00:15:52,080 --> 00:15:55,040
Speaker 2: Loop for years at this point. Where did he get

269
00:15:55,040 --> 00:15:57,800
Speaker 2: the fifteen grand? I didn't have fifteen grands sitting around then,

270
00:15:57,920 --> 00:16:01,160
Speaker 2: Jesus Christ, he didn't like. This is the thing. No

271
00:16:01,200 --> 00:16:04,120
Speaker 2: one digs deeper into these things. No one asks where

272
00:16:04,120 --> 00:16:07,360
Speaker 2: the privilege truly comes from, and when that happens, guys

273
00:16:07,440 --> 00:16:11,960
Speaker 2: like this get popular. Now, look, those who might defend

274
00:16:12,000 --> 00:16:14,440
Speaker 2: Sam Altman might suggest that he may not have been

275
00:16:14,440 --> 00:16:17,600
Speaker 2: a creator, but he gave his time and his energy

276
00:16:17,640 --> 00:16:20,360
Speaker 2: to those he backed. Maybe he was a value creator.

277
00:16:20,800 --> 00:16:25,680
Speaker 2: Right wrong. According to the Washington Post, sam Aulman's time

278
00:16:25,680 --> 00:16:28,480
Speaker 2: at y Combinat ere it ended because he developed a

279
00:16:28,520 --> 00:16:33,320
Speaker 2: reputation for favoring personal priorities over official duties and for

280
00:16:33,360 --> 00:16:36,800
Speaker 2: an absenteeism that rankled his peers and some of the

281
00:16:36,840 --> 00:16:40,680
Speaker 2: startups he was supposed to nurture, much as he had,

282
00:16:40,760 --> 00:16:43,800
Speaker 2: as I've mentioned, once diverted engineers at lut to work

283
00:16:43,840 --> 00:16:46,760
Speaker 2: on a dating app instead of working on the company

284
00:16:46,800 --> 00:16:51,320
Speaker 2: he was running. To give Sam Altman credit, he really

285
00:16:51,440 --> 00:16:55,480
Speaker 2: is able to talk for hours without saying anything. Just

286
00:16:55,600 --> 00:16:58,440
Speaker 2: ask LinkedIn, co founder of Reied Hoffman, an investor in

287
00:16:58,480 --> 00:17:01,840
Speaker 2: open Ai and early of Sam Mortman, and a man

288
00:17:01,880 --> 00:17:04,280
Speaker 2: who was critical to getting Sam Mortman returned to the

289
00:17:04,320 --> 00:17:07,920
Speaker 2: helm of open Ai when he was fired, who also

290
00:17:08,040 --> 00:17:10,639
Speaker 2: let Sam Mortan ramble for over an hour on his

291
00:17:10,720 --> 00:17:13,680
Speaker 2: podcast Masters of Scale with all one, at one point

292
00:17:13,760 --> 00:17:16,639
Speaker 2: saying that he was and I quote, he was in

293
00:17:16,680 --> 00:17:20,200
Speaker 2: a developing world country shortly after the iPhone came out,

294
00:17:20,359 --> 00:17:24,560
Speaker 2: and despite their poverty, everyone had smartphones. Now, I just

295
00:17:24,600 --> 00:17:27,159
Speaker 2: want to be clear. This is so obviously, completely and

296
00:17:27,280 --> 00:17:32,320
Speaker 2: utterly stupidly false. It made me genuinely angry. Why because

297
00:17:32,800 --> 00:17:35,560
Speaker 2: what so the iPhone comes out? So the rollout of

298
00:17:35,600 --> 00:17:39,000
Speaker 2: smartphones in other countries has been incredibly useful, it's been great.

299
00:17:39,320 --> 00:17:41,879
Speaker 2: It didn't happen in a goddamn year. Sam, you lying

300
00:17:41,920 --> 00:17:45,200
Speaker 2: sack of shit. I'm sorry. I just really hate this stuff.

301
00:17:46,280 --> 00:17:49,360
Speaker 2: I really hate that these people who can go around

302
00:17:49,400 --> 00:17:52,840
Speaker 2: getting money seemingly at will just go on each other's

303
00:17:52,880 --> 00:17:56,920
Speaker 2: podcasts and jack off and wank about this nonsense, who

304
00:17:57,040 --> 00:18:02,760
Speaker 2: say these patently obviously fake things. He probably saying his

305
00:18:02,840 --> 00:18:04,760
Speaker 2: defense by the way, Oh it's four years later, which

306
00:18:04,840 --> 00:18:07,800
Speaker 2: might have made sense. It's always vague with this goddamn guy.

307
00:18:08,080 --> 00:18:11,280
Speaker 2: It's always vague with these goddamn guys. And it's just

308
00:18:11,400 --> 00:18:16,399
Speaker 2: so offensive because regular people do not get these opportunities.

309
00:18:17,000 --> 00:18:19,840
Speaker 2: Regular people don't get put in these rooms. People that

310
00:18:19,920 --> 00:18:23,959
Speaker 2: are undoubtedly smarter and more accomplished and harder working than

311
00:18:24,040 --> 00:18:27,240
Speaker 2: Sam Aortman. But because Sam Altman fits the template, he's

312
00:18:27,280 --> 00:18:29,600
Speaker 2: allowed to go and he's allowed to be rich one

313
00:18:29,680 --> 00:18:33,960
Speaker 2: hundred times over. And it really shouldn't come as a

314
00:18:33,960 --> 00:18:37,640
Speaker 2: surprise that Reid Hoffman of LinkedIn, investor in open ai

315
00:18:37,800 --> 00:18:41,640
Speaker 2: and so much has such affection for Aortman. After all,

316
00:18:41,800 --> 00:18:45,440
Speaker 2: he's the founder of LinkedIn, which is basically the one

317
00:18:45,480 --> 00:18:47,560
Speaker 2: place that you know you can go to read six

318
00:18:47,640 --> 00:18:52,399
Speaker 2: hundred words that mean nothing, these massive, cringe worthy paragraphs

319
00:18:52,880 --> 00:18:56,000
Speaker 2: broken into a Staccato's style that hurts the brain and

320
00:18:56,040 --> 00:18:58,840
Speaker 2: the mind, but makes people who don't really know why

321
00:18:58,880 --> 00:19:01,640
Speaker 2: they're doing their job care about what they're doing very

322
00:19:01,680 --> 00:19:04,719
Speaker 2: happy because it makes it all feel far more important

323
00:19:04,960 --> 00:19:09,240
Speaker 2: than it really is. Moving on through Aortmand's power structures.

324
00:19:09,400 --> 00:19:13,080
Speaker 2: Another of his close friends is Airbnb CEO Brian Chesky,

325
00:19:13,480 --> 00:19:16,280
Speaker 2: who helped, by the way, also get Sam Altman put

326
00:19:16,320 --> 00:19:19,720
Speaker 2: back in open AI, and he's helped Altmand pedal these

327
00:19:19,840 --> 00:19:23,960
Speaker 2: vague rubbish promises about artificial intelligence, at one point, with

328
00:19:24,040 --> 00:19:27,240
Speaker 2: Cheske calling it bigger than the Internet, mobile and cloud

329
00:19:27,280 --> 00:19:31,120
Speaker 2: combined and saying that AI will, by the way, non

330
00:19:31,160 --> 00:19:35,359
Speaker 2: specifically change Airbnb, which is a company that has and

331
00:19:35,400 --> 00:19:38,439
Speaker 2: this is what kills me as well, only got worse

332
00:19:38,480 --> 00:19:41,520
Speaker 2: over time. I think Airbnb really crested about four or

333
00:19:41,520 --> 00:19:44,000
Speaker 2: five years ago, and then it just became the same.

334
00:19:44,040 --> 00:19:47,200
Speaker 2: But worse over time, put my gravances to the side,

335
00:19:49,560 --> 00:19:51,480
Speaker 2: and as you can kind of tell what I'm getting

336
00:19:51,520 --> 00:19:55,359
Speaker 2: at here, Aortmand's used his political maneuver and to become

337
00:19:55,560 --> 00:19:58,840
Speaker 2: super rich. And he's grown, according to the Wall Street Journal,

338
00:19:58,920 --> 00:20:01,760
Speaker 2: a portfolio of more them four hundred companies worth nearly

339
00:20:01,880 --> 00:20:06,000
Speaker 2: three billion dollars. Now what's really worrying is that he's

340
00:20:06,080 --> 00:20:09,879
Speaker 2: partially funded it with hundreds of millions of dollars of

341
00:20:10,040 --> 00:20:15,640
Speaker 2: debt of loans from JP Morgan Chase. Now almost anyone

342
00:20:15,640 --> 00:20:18,520
Speaker 2: can see why this is insane borrowing money from a

343
00:20:18,560 --> 00:20:21,280
Speaker 2: bank and putting it into an industry where the majority

344
00:20:21,320 --> 00:20:27,080
Speaker 2: of companies fail. It's just completely bonkers. I don't understand

345
00:20:27,119 --> 00:20:29,159
Speaker 2: what's going on. Well, I mean I do, which is

346
00:20:29,880 --> 00:20:32,840
Speaker 2: the rich reinforce the rich, and they put money with

347
00:20:33,040 --> 00:20:38,160
Speaker 2: people who don't necessarily qualify for it and aren't necessarily

348
00:20:38,280 --> 00:20:41,120
Speaker 2: smart or good at stuff or have done things. But

349
00:20:41,119 --> 00:20:44,040
Speaker 2: because they're in the right company, it works for them.

350
00:20:44,359 --> 00:20:46,960
Speaker 2: Like a regular person. They can barely get a mortgage,

351
00:20:47,000 --> 00:20:50,040
Speaker 2: let alone. What's likely I'm guessing by the way a

352
00:20:50,080 --> 00:20:53,240
Speaker 2: low interest rate loan to sink hundreds of millions of

353
00:20:53,280 --> 00:20:57,560
Speaker 2: dollars into companies like Helion, which is a nuclear fusion

354
00:20:57,640 --> 00:21:00,320
Speaker 2: company that Sam Moultman put three hundred and seventy five

355
00:21:00,320 --> 00:21:03,880
Speaker 2: million dollars into in twenty twenty one. He serves as

356
00:21:03,920 --> 00:21:07,159
Speaker 2: both the chairman of Helion's board and potentially one of

357
00:21:07,160 --> 00:21:10,159
Speaker 2: its largest customers because open ai is now and just

358
00:21:10,200 --> 00:21:14,560
Speaker 2: announced a deal with Helion, and I quote Matthew Konnittzer

359
00:21:14,840 --> 00:21:18,760
Speaker 2: from the Register here to get access to Helion's not

360
00:21:18,840 --> 00:21:24,879
Speaker 2: yet possible nuclear fusion driven electricity generators. Just it's so

361
00:21:25,040 --> 00:21:27,560
Speaker 2: cool that that, and tons of people reported that without

362
00:21:28,440 --> 00:21:32,359
Speaker 2: Matt's necessary bile there. I love the Register because they're

363
00:21:32,520 --> 00:21:34,639
Speaker 2: willing to say stuff like this nuclear fusion has not

364
00:21:34,720 --> 00:21:38,080
Speaker 2: happened yet. That's that's a sci fi thing that he

365
00:21:38,119 --> 00:21:40,720
Speaker 2: has put all that money into. Nevertheless, plenty of people

366
00:21:40,800 --> 00:21:43,720
Speaker 2: credulously accepted this, and like Sam odd Man, aw they're

367
00:21:43,760 --> 00:21:47,040
Speaker 2: doing a deal open ai, open ai and nuclear Fusion.

368
00:21:47,440 --> 00:21:50,119
Speaker 2: Just to be clear, there's no deal there the nuclear fusion.

369
00:21:50,280 --> 00:21:54,000
Speaker 2: Oh my god. The Wall Street Journal also reported the

370
00:21:54,040 --> 00:21:56,920
Speaker 2: open Ai is happily cutting multiple deals with other things

371
00:21:56,920 --> 00:22:00,240
Speaker 2: that Sam Altman's invested in, including Reddit, which Ortmann owns

372
00:22:00,359 --> 00:22:02,760
Speaker 2: hundreds of millions of dollars were stuck in thanks to

373
00:22:02,760 --> 00:22:05,680
Speaker 2: an investment from hydro Seen Capital when he worked a

374
00:22:05,840 --> 00:22:09,720
Speaker 2: y combat are, along with AI device companies Limitless and Humane,

375
00:22:09,880 --> 00:22:13,040
Speaker 2: the latter of which Ortmand owns a fifteen percent stake in.

376
00:22:13,160 --> 00:22:17,800
Speaker 2: According to the Journal, it's just obvious, naked self dealing,

377
00:22:17,800 --> 00:22:21,040
Speaker 2: the kind of stuff that should be something that disqualifies you,

378
00:22:21,119 --> 00:22:25,560
Speaker 2: that gets critiqued further than of course the journal, and

379
00:22:25,920 --> 00:22:27,879
Speaker 2: I'm not seeing it. I'm not seeing enough of it

380
00:22:27,960 --> 00:22:31,560
Speaker 2: at least, But I wanted to dig further into this

381
00:22:31,720 --> 00:22:35,119
Speaker 2: investment portfolio, so I sat down with Ton Datan of

382
00:22:35,160 --> 00:22:37,240
Speaker 2: the Wall Street Journal to kind of go through it.

383
00:22:47,160 --> 00:22:49,720
Speaker 2: So in your story, you were talking about how Sam

384
00:22:49,800 --> 00:22:53,119
Speaker 2: Ortman had this massive credit line I think from JP Morgan.

385
00:22:53,600 --> 00:22:57,040
Speaker 2: Is this standard for investment? Have you seen this before?

386
00:22:57,880 --> 00:23:00,600
Speaker 1: No, It's incredibly not standard. And in the course of

387
00:23:00,640 --> 00:23:02,800
Speaker 1: reporting out this story with my colleagues, we talk to

388
00:23:03,359 --> 00:23:06,919
Speaker 1: a lot of venture capitalists and investors, other kinds of

389
00:23:06,920 --> 00:23:12,080
Speaker 1: investors and founders in the tech industry, and they either

390
00:23:12,119 --> 00:23:14,000
Speaker 1: had never heard of something like this before or found

391
00:23:14,040 --> 00:23:17,280
Speaker 1: it to be so incredibly risky, not just investing in

392
00:23:17,320 --> 00:23:21,040
Speaker 1: startups off of credit, but using as collateral your holdings

393
00:23:21,119 --> 00:23:24,200
Speaker 1: in privately held tech companies. Both of those things together

394
00:23:24,280 --> 00:23:27,040
Speaker 1: are like not you do not see that very often

395
00:23:27,040 --> 00:23:28,240
Speaker 1: in the tech industry.

396
00:23:28,680 --> 00:23:31,439
Speaker 2: And why don't you? Just to be clear, why is

397
00:23:31,480 --> 00:23:33,160
Speaker 2: this usually a bad idea?

398
00:23:33,520 --> 00:23:35,879
Speaker 1: Because it's incredibly risky. I mean, if you think about

399
00:23:35,920 --> 00:23:39,959
Speaker 1: an investment in a startup, what percentage of startups not

400
00:23:40,040 --> 00:23:43,080
Speaker 1: only don't get acquired or go public, but straight up

401
00:23:43,160 --> 00:23:46,040
Speaker 1: fail will go to zero? The numbers I don't want

402
00:23:46,080 --> 00:23:48,639
Speaker 1: to quote a specific one, but it's like the majority.

403
00:23:49,240 --> 00:23:51,119
Speaker 1: And that's kind of the way the venture capital system

404
00:23:51,160 --> 00:23:54,080
Speaker 1: works is that you invest in a bunch of unprofitable

405
00:23:54,280 --> 00:23:58,000
Speaker 1: or zero profit, zero revenue companies, hoping that a few

406
00:23:58,000 --> 00:24:00,520
Speaker 1: home runs or Grand Slams or whatever is enough to

407
00:24:01,040 --> 00:24:04,480
Speaker 1: justify your entire fund. But if you were to use

408
00:24:04,520 --> 00:24:06,920
Speaker 1: those holdings in those kinds of companies in which a

409
00:24:07,000 --> 00:24:10,320
Speaker 1: huge majority of them go under, and then a huge

410
00:24:10,320 --> 00:24:12,479
Speaker 1: majority of them do go under, and suddenly you are

411
00:24:12,520 --> 00:24:16,080
Speaker 1: having to use as collateral holdings in a company that

412
00:24:16,200 --> 00:24:19,119
Speaker 1: is worth zero, you're in big trouble. So yes, it

413
00:24:19,200 --> 00:24:20,800
Speaker 1: is not done very commonly.

414
00:24:21,119 --> 00:24:25,879
Speaker 2: Very strange, and it seems the strange financial relationships that

415
00:24:25,960 --> 00:24:30,320
Speaker 2: kind of Oltman's modus operandi. So tell me about Hydrozine.

416
00:24:31,240 --> 00:24:35,040
Speaker 1: Sure. Hydrozine was a fund that Sam started around the

417
00:24:35,080 --> 00:24:40,119
Speaker 1: time that he joined y Combinator, the accelerator incubator in

418
00:24:40,200 --> 00:24:43,480
Speaker 1: Silicon Valley, and he got some funding from Peter Teel

419
00:24:43,600 --> 00:24:45,880
Speaker 1: for it, and basically it was a way for him

420
00:24:45,880 --> 00:24:48,800
Speaker 1: to invest in other y Combinator startups. So it was

421
00:24:49,160 --> 00:24:52,280
Speaker 1: largely using outside money, but it was like just an

422
00:24:52,320 --> 00:24:55,400
Speaker 1: access line to capital that he could put into these

423
00:24:55,440 --> 00:24:57,200
Speaker 1: seed stage investments in startups.

424
00:24:58,680 --> 00:25:02,480
Speaker 2: As I've mentioned previously, since leaving White Company, Altman's investment

425
00:25:02,520 --> 00:25:05,880
Speaker 2: portfolio was balloon to hundreds of start ups with billions

426
00:25:05,920 --> 00:25:11,800
Speaker 2: of dollars. How many of these companies have you seen

427
00:25:12,000 --> 00:25:15,800
Speaker 2: have a direct relationship with open Ai that's he's invested in.

428
00:25:16,800 --> 00:25:18,600
Speaker 1: Well, in the story, we laid out a couple of

429
00:25:18,960 --> 00:25:22,159
Speaker 1: clear overlaps between you know, open Ai as a business

430
00:25:22,240 --> 00:25:25,359
Speaker 1: and companies that he's invested in. Like the most obvious

431
00:25:25,480 --> 00:25:27,879
Speaker 1: one that we that we brought up, I shouldn't say obvious,

432
00:25:27,920 --> 00:25:29,440
Speaker 1: but the most like apparent one of this kind of

433
00:25:29,520 --> 00:25:34,880
Speaker 1: overlap was Helion, which is this nuclear fusion energy startup

434
00:25:34,920 --> 00:25:37,960
Speaker 1: that he's put hundreds of millions of dollars into and

435
00:25:38,520 --> 00:25:41,359
Speaker 1: they worked out a deal, as we broken in the story,

436
00:25:42,080 --> 00:25:45,439
Speaker 1: for Helion to provide be the energy provider for future

437
00:25:45,480 --> 00:25:49,080
Speaker 1: open ai data centers. So these data centers, when they're

438
00:25:49,119 --> 00:25:52,000
Speaker 1: built and I guess when nuclear fusion exists, you know,

439
00:25:52,040 --> 00:25:55,200
Speaker 1: would be powered by clean nuclear fusion energy. And so

440
00:25:55,280 --> 00:25:57,680
Speaker 1: that's something in which Sam obviously as one of the

441
00:25:57,760 --> 00:26:01,240
Speaker 1: largest by far the largest investor, and he leon, you know,

442
00:26:01,359 --> 00:26:03,640
Speaker 1: there's there's there's an overlap there between that and open

443
00:26:03,680 --> 00:26:07,160
Speaker 1: AI's business. And then the other one that also kind

444
00:26:07,160 --> 00:26:10,639
Speaker 1: of stoock out to us was Reddit, where he is

445
00:26:10,840 --> 00:26:14,040
Speaker 1: one of the largest outside shareholders in the company. And

446
00:26:15,359 --> 00:26:18,480
Speaker 1: open ai announced a licensing deal with Reddit a couple

447
00:26:18,520 --> 00:26:22,159
Speaker 1: of weeks ago, and you know, Reddit stock popped on

448
00:26:22,359 --> 00:26:25,879
Speaker 1: announcement of this deal, and Sam, as a major shareholder,

449
00:26:25,920 --> 00:26:28,880
Speaker 1: saw his net worth increase, you know, within the course

450
00:26:28,920 --> 00:26:30,040
Speaker 1: of a day. I mean, that's kind of how it

451
00:26:30,080 --> 00:26:33,920
Speaker 1: goes when you hold stock. But you know, notably on

452
00:26:33,960 --> 00:26:34,960
Speaker 1: announcement of this deal.

453
00:26:36,400 --> 00:26:39,359
Speaker 2: Surely any future deals between open ai and Reddit would

454
00:26:39,400 --> 00:26:41,920
Speaker 2: mean that Sam Oapman would be there must be some

455
00:26:42,160 --> 00:26:45,560
Speaker 2: kind of insided trading. How is that possibly legal?

456
00:26:46,800 --> 00:26:48,280
Speaker 1: I mean, I don't know, I don't want to get

457
00:26:48,320 --> 00:26:52,760
Speaker 1: into what what's legal or isn't legal. I thought questionable. Yeah,

458
00:26:52,840 --> 00:26:55,119
Speaker 1: I guess what was interesting to me and to the

459
00:26:55,240 --> 00:26:58,960
Speaker 1: other reporters about the way that Reddit and open ai

460
00:26:59,080 --> 00:27:02,240
Speaker 1: announced this license deal was they didn't say that Sam

461
00:27:02,400 --> 00:27:06,240
Speaker 1: recused himself from the conversations between Reddit and open Ai.

462
00:27:06,720 --> 00:27:09,520
Speaker 1: They said something to the effect of this deal was

463
00:27:09,840 --> 00:27:11,800
Speaker 1: spearheaded or the person who was in charge of this

464
00:27:11,920 --> 00:27:15,480
Speaker 1: deal was open Ai COO. And I don't know what

465
00:27:15,640 --> 00:27:17,600
Speaker 1: to make of that. I feel like the language of

466
00:27:17,640 --> 00:27:19,760
Speaker 1: Sam recused himself would have been easy enough to do,

467
00:27:20,359 --> 00:27:22,359
Speaker 1: but they didn't do it. They chose not to do it.

468
00:27:23,440 --> 00:27:26,280
Speaker 2: So if it was like saying Brad Lightcap took the deal,

469
00:27:26,720 --> 00:27:29,200
Speaker 2: that doesn't feel like a disconnection from Sam Oltman.

470
00:27:29,800 --> 00:27:32,280
Speaker 1: Yeah, and it isn't regardless even if he wasn't involved.

471
00:27:32,400 --> 00:27:34,720
Speaker 1: And you know, you could make a fair argument that

472
00:27:34,880 --> 00:27:38,840
Speaker 1: like open ai probably should be licensing data from all

473
00:27:38,920 --> 00:27:41,359
Speaker 1: of these you know, providers, because that's what they're using

474
00:27:41,520 --> 00:27:44,639
Speaker 1: to train their models. But the fact is they didn't.

475
00:27:45,920 --> 00:27:48,560
Speaker 1: Sam didn't recuse himself, And you know, whether it's his

476
00:27:48,720 --> 00:27:50,480
Speaker 1: fault or not, or this was intentional or not, the

477
00:27:50,520 --> 00:27:53,119
Speaker 1: fact of the matter is he owns a sizeable like

478
00:27:53,280 --> 00:27:56,960
Speaker 1: disclosed percentage of Reddit through various holdings, and like those

479
00:27:57,520 --> 00:27:59,520
Speaker 1: you know, those shares went up on announcement of the deal.

480
00:28:00,720 --> 00:28:03,840
Speaker 2: So with Helion, back to the nuclear energy startup, have

481
00:28:03,920 --> 00:28:05,280
Speaker 2: they actually built anything yet?

482
00:28:05,560 --> 00:28:05,600
Speaker 1: No?

483
00:28:06,320 --> 00:28:08,040
Speaker 2: No, I mean it's so strange.

484
00:28:08,200 --> 00:28:10,679
Speaker 1: I don't want to discount anything that Helion does because

485
00:28:11,000 --> 00:28:14,440
Speaker 1: you know, who wouldn't want nuclear energy to exist? Right? Like,

486
00:28:14,560 --> 00:28:17,359
Speaker 1: that's that's obviously a great boon for humanity to have

487
00:28:18,080 --> 00:28:20,800
Speaker 1: nuclear fusion. You mean yeah, sorry, so nuclear fusion, yes,

488
00:28:21,520 --> 00:28:24,120
Speaker 1: like that would be a major technological breakthrough. That would

489
00:28:24,520 --> 00:28:26,320
Speaker 1: be a you know, a sea change in how you

490
00:28:26,400 --> 00:28:29,119
Speaker 1: know we derive energy from the grid and whatever. But

491
00:28:30,440 --> 00:28:33,160
Speaker 1: you know, aside from a couple of announcements in terms

492
00:28:33,240 --> 00:28:38,840
Speaker 1: of partnerships or future purchase agreements between Helion and Microsoft

493
00:28:39,320 --> 00:28:41,320
Speaker 1: and and you know the thing that we reported Helion

494
00:28:41,400 --> 00:28:44,400
Speaker 1: and open AI, this is not like they have not

495
00:28:44,560 --> 00:28:47,240
Speaker 1: achieved it yet. These guys are not out there selling

496
00:28:47,680 --> 00:28:50,880
Speaker 1: you know, nuclear fusion energy to the mass public.

497
00:28:51,720 --> 00:28:54,040
Speaker 2: Well, I think what gets me that Sam Won puts

498
00:28:54,040 --> 00:28:56,560
Speaker 2: three hundred and seventy five million dollars into this company.

499
00:28:56,640 --> 00:28:58,600
Speaker 2: He got them into y combine or if I remember

500
00:28:58,640 --> 00:29:01,880
Speaker 2: from you reporting he being embedded with them. Now there

501
00:29:01,960 --> 00:29:04,640
Speaker 2: is this deal between Helia and a company that is

502
00:29:04,720 --> 00:29:08,480
Speaker 2: yet to build something and open Ai that they will

503
00:29:08,560 --> 00:29:12,320
Speaker 2: theoretically do something in the future. It just feels like,

504
00:29:13,480 --> 00:29:15,880
Speaker 2: I know we're not talking in legalities here, but it

505
00:29:16,000 --> 00:29:19,960
Speaker 2: feels like there is just so much self dealing here.

506
00:29:20,120 --> 00:29:22,440
Speaker 2: It feels like he has been self Oltman has been

507
00:29:22,480 --> 00:29:23,480
Speaker 2: self dealing for years.

508
00:29:24,720 --> 00:29:27,520
Speaker 1: Yeah, I mean, I guess to make the argument that

509
00:29:28,640 --> 00:29:31,520
Speaker 1: Sam or open AI or other people in that circle

510
00:29:31,520 --> 00:29:34,680
Speaker 1: would make is like Sam is a prolific investor. He's

511
00:29:34,680 --> 00:29:37,040
Speaker 1: been doing this for as long as he's been in tech.

512
00:29:38,160 --> 00:29:40,040
Speaker 1: They say he's kind of slowed down quite a bit.

513
00:29:40,360 --> 00:29:43,680
Speaker 1: You know, maybe numbers would show a different story, but regardless,

514
00:29:43,800 --> 00:29:45,680
Speaker 1: he you know, this is a thing that he does.

515
00:29:45,840 --> 00:29:48,120
Speaker 1: And like, if you are going to be running, you know,

516
00:29:48,320 --> 00:29:52,160
Speaker 1: the most consequential tech company at the moment or startup

517
00:29:52,160 --> 00:29:54,280
Speaker 1: at the moment and open AI, there's just bound to

518
00:29:54,320 --> 00:29:58,680
Speaker 1: be overlap between a vast investment empire and an open AI.

519
00:29:58,880 --> 00:30:01,320
Speaker 1: So that's like the argument to the contrary, you know,

520
00:30:01,440 --> 00:30:04,880
Speaker 1: self dealing. I guess that's in the interpretation of the reader.

521
00:30:06,080 --> 00:30:10,160
Speaker 2: Yeah, I think what it is is that it doesn't

522
00:30:10,320 --> 00:30:14,200
Speaker 2: feel like this would be tolerated in any other industry,

523
00:30:15,240 --> 00:30:18,480
Speaker 2: like if you put politicians own stock, for example. I

524
00:30:18,560 --> 00:30:22,880
Speaker 2: realized it's not an industry, and they are heavily criticized

525
00:30:22,880 --> 00:30:25,360
Speaker 2: for it. But it almost feels like perhaps you can

526
00:30:25,400 --> 00:30:27,960
Speaker 2: speak to this. It feels like Sam Wilton gets reported

527
00:30:28,040 --> 00:30:32,480
Speaker 2: on differently than many entrepreneurs and many investors. And I

528
00:30:32,600 --> 00:30:34,240
Speaker 2: really do put the journal to the side here. I

529
00:30:34,280 --> 00:30:36,200
Speaker 2: think the journal in the Washington Post done a very

530
00:30:36,200 --> 00:30:38,720
Speaker 2: good job scrutinizing it, but it feels writ large like

531
00:30:38,760 --> 00:30:42,520
Speaker 2: he's given a much rosier and easier ride than most.

532
00:30:43,600 --> 00:30:45,680
Speaker 1: It's hard to know with Sam, right, I mean, he's

533
00:30:45,720 --> 00:30:48,520
Speaker 1: such a figure at this point, which is kind of

534
00:30:48,560 --> 00:30:51,000
Speaker 1: funny to me because like I've been reporting on tech

535
00:30:51,120 --> 00:30:54,680
Speaker 1: for let's say ten years or so, and Sam's always

536
00:30:54,720 --> 00:30:57,800
Speaker 1: kind of been around. He's just this person that we

537
00:30:57,920 --> 00:31:00,840
Speaker 1: all kind of knew as reporters because of you know,

538
00:31:01,320 --> 00:31:04,880
Speaker 1: his role at y Combinator and showing up at Sun

539
00:31:05,000 --> 00:31:09,040
Speaker 1: Valley almost every year, and you know, now open Ay

540
00:31:09,200 --> 00:31:12,040
Speaker 1: being this big deal that it is. He's this figure

541
00:31:12,080 --> 00:31:14,440
Speaker 1: that everyone kind of has dealt with at certain points

542
00:31:14,480 --> 00:31:18,440
Speaker 1: as a tech reporter, and there's just so many opinions

543
00:31:18,480 --> 00:31:21,000
Speaker 1: on him. I mean, you know, I think there are people,

544
00:31:21,120 --> 00:31:23,800
Speaker 1: maybe like you, who see him as this nefarious character,

545
00:31:23,920 --> 00:31:27,600
Speaker 1: self dealing, someone who isn't really above board. But you know,

546
00:31:27,720 --> 00:31:30,080
Speaker 1: you report a story like this and you talk to

547
00:31:30,200 --> 00:31:33,959
Speaker 1: founders and some venture capitalists and they love him. They

548
00:31:34,000 --> 00:31:37,640
Speaker 1: think he's, you know, a great investor, a brilliant business person,

549
00:31:37,720 --> 00:31:41,000
Speaker 1: has incredible insights, and you know, is this also kind

550
00:31:41,000 --> 00:31:44,640
Speaker 1: of futuristic thinker, who's who's kind of in that Elon

551
00:31:44,760 --> 00:31:48,960
Speaker 1: musk vein thinking ten twenty years down the road and

552
00:31:49,600 --> 00:31:51,880
Speaker 1: at a scale at the trillions of dollars level that

553
00:31:52,120 --> 00:31:56,440
Speaker 1: they find very you know, alluring and exciting. And so,

554
00:31:57,480 --> 00:31:59,480
Speaker 1: you know, I it's always hard to know when you

555
00:31:59,560 --> 00:32:01,320
Speaker 1: do these sort of story is like what you're going

556
00:32:01,400 --> 00:32:03,040
Speaker 1: to get in the course of reporting, because you can

557
00:32:03,080 --> 00:32:05,400
Speaker 1: talk to a certain group of people who think he's

558
00:32:05,800 --> 00:32:08,000
Speaker 1: borderline criminal and to be clear, I'm not saying that,

559
00:32:08,120 --> 00:32:08,480
Speaker 1: but there are.

560
00:32:08,400 --> 00:32:11,680
Speaker 2: People yeah yeah, just citing someone yeah yeah, and and.

561
00:32:11,880 --> 00:32:14,920
Speaker 1: People who think he's the you know, nikolay Tesla of

562
00:32:14,960 --> 00:32:16,560
Speaker 1: our time. What are you gonna do?

563
00:32:17,680 --> 00:32:21,800
Speaker 2: So here's my thing with that, is he that successful

564
00:32:21,840 --> 00:32:27,080
Speaker 2: a businessman though, Like he's a very clearly a successful investor.

565
00:32:28,320 --> 00:32:32,160
Speaker 2: But as a businessman, the company he's been attempted, fired from, looped,

566
00:32:32,480 --> 00:32:36,520
Speaker 2: fired from Y Combinator, fired from open Ai. He seems

567
00:32:36,600 --> 00:32:41,040
Speaker 2: like a very effective politician and a very good deal maker.

568
00:32:41,760 --> 00:32:43,760
Speaker 2: But I wonder how much of this, because you say

569
00:32:43,760 --> 00:32:46,600
Speaker 2: he's slown down. I wonder how much of his success

570
00:32:46,680 --> 00:32:49,280
Speaker 2: can be attributed to the fact that he just was

571
00:32:49,480 --> 00:32:52,560
Speaker 2: inside of Y Combinator and had the money to play

572
00:32:53,040 --> 00:32:58,360
Speaker 2: at the time. Because yeah, you've been around long, so

573
00:32:58,880 --> 00:32:59,280
Speaker 2: go ahead.

574
00:32:59,600 --> 00:33:02,920
Speaker 1: Yeah, I know, looks it's a fair point, and I think, like, look,

575
00:33:02,960 --> 00:33:05,280
Speaker 1: the numbers probably speak for themselves in terms of his

576
00:33:05,400 --> 00:33:08,600
Speaker 1: net worth, right, you know, you can stack the deck

577
00:33:08,640 --> 00:33:11,120
Speaker 1: however you want in Silicon Valley to say someone is

578
00:33:11,200 --> 00:33:12,680
Speaker 1: or isn't a good investor.

579
00:33:12,440 --> 00:33:14,960
Speaker 2: Like when you have deal flow, when you have really

580
00:33:15,040 --> 00:33:16,280
Speaker 2: is a school board situation.

581
00:33:16,760 --> 00:33:18,480
Speaker 1: Yeah, well no, but I'm saying, like, you can have

582
00:33:18,640 --> 00:33:22,280
Speaker 1: access to early stage startups better than other people, and

583
00:33:22,360 --> 00:33:25,400
Speaker 1: you're just gonna be getting first looks at Uber and Stripe. No,

584
00:33:25,480 --> 00:33:27,320
Speaker 1: he's not an Uber. I'm just giving an example, yea,

585
00:33:27,480 --> 00:33:31,240
Speaker 1: like you you know Stripe, Yeah, yeah, or Stripe or Airbnb,

586
00:33:31,360 --> 00:33:33,600
Speaker 1: which he is in. Like if you're in that inner

587
00:33:33,680 --> 00:33:36,000
Speaker 1: circle of people who see these companies on the way up,

588
00:33:36,080 --> 00:33:38,160
Speaker 1: and like, you know, I don't think it takes a

589
00:33:38,240 --> 00:33:40,959
Speaker 1: brain genius to look at something like Uber and be like, oh, well,

590
00:33:41,000 --> 00:33:43,040
Speaker 1: I bet that's probably going to be a pretty big

591
00:33:43,160 --> 00:33:45,600
Speaker 1: deal one day, so I'd like to invest in that.

592
00:33:46,880 --> 00:33:50,360
Speaker 1: But you know, I think to his credit, maybe his

593
00:33:50,760 --> 00:33:54,080
Speaker 1: investment in Stripe was an incredibly risky one for him personally.

594
00:33:54,160 --> 00:33:56,560
Speaker 1: I think it was like fifteen thousand dollars or something,

595
00:33:57,160 --> 00:33:59,120
Speaker 1: and you know, he probably didn't have a ton in

596
00:33:59,160 --> 00:34:00,680
Speaker 1: his bank account at the time, so that was a

597
00:34:00,760 --> 00:34:04,320
Speaker 1: pretty When when was that early early days, I mean

598
00:34:04,400 --> 00:34:07,560
Speaker 1: they were they were in It was in two thousand

599
00:34:07,560 --> 00:34:11,919
Speaker 1: and nine, actually, Paul Grant so before he sold Looped. Yeah, yeah,

600
00:34:12,120 --> 00:34:13,680
Speaker 1: I think it was around the same time.

601
00:34:14,600 --> 00:34:17,080
Speaker 2: Because that's what I'm saying, there's not really much of

602
00:34:17,120 --> 00:34:18,640
Speaker 2: a risk if he hadn't, But I feel like he

603
00:34:18,719 --> 00:34:21,920
Speaker 2: sold Loop later because that. But nevertheless, it.

604
00:34:21,960 --> 00:34:23,400
Speaker 1: Is fair enough. I don't know Sam would have been

605
00:34:23,400 --> 00:34:26,080
Speaker 1: out on the streets, you know if if this, if

606
00:34:26,120 --> 00:34:29,200
Speaker 1: this investment hadn't turned out. But you know, in a

607
00:34:29,280 --> 00:34:32,160
Speaker 1: world of investment where people get congratulated for you know,

608
00:34:32,280 --> 00:34:34,640
Speaker 1: going all in on something or you know, being willing

609
00:34:34,719 --> 00:34:41,040
Speaker 1: to bet it all on an unprofitable, you know, unproven startup.

610
00:34:41,280 --> 00:34:43,879
Speaker 1: You know, people give Sam a lot of credit. But yeah,

611
00:34:43,920 --> 00:34:46,000
Speaker 1: I don't know. I think you bring up a good question,

612
00:34:46,160 --> 00:34:49,320
Speaker 1: which is like if you have access to an Airbnb

613
00:34:50,000 --> 00:34:53,239
Speaker 1: in the earliest days, or or a Reddit or even

614
00:34:53,280 --> 00:34:56,000
Speaker 1: a company that like Rippling, which I don't know if

615
00:34:56,080 --> 00:34:58,120
Speaker 1: your you know, listeners know about. But it's this very

616
00:34:58,200 --> 00:35:02,880
Speaker 1: successful now hrs art up that Sam has has invested

617
00:35:02,880 --> 00:35:03,640
Speaker 1: in and also.

618
00:35:03,400 --> 00:35:07,480
Speaker 2: An offshoot of Gusto when it's complicated.

619
00:35:08,040 --> 00:35:10,560
Speaker 1: Yeah, yeah, basically I don't know how interesting this is,

620
00:35:10,600 --> 00:35:13,040
Speaker 1: but whatever, you know. There was a kind of a

621
00:35:13,080 --> 00:35:15,280
Speaker 1: big scandal a bunch of years back with this company

622
00:35:15,360 --> 00:35:23,640
Speaker 1: called Zenefitz, which was accused of shirking regulatory requirements for

623
00:35:24,920 --> 00:35:27,920
Speaker 1: training its workers on anyway, it was a big scandal

624
00:35:27,920 --> 00:35:29,360
Speaker 1: a couple of years ago, and the CEO of that

625
00:35:29,560 --> 00:35:32,239
Speaker 1: was was pushed out very publicly, later replaced by David

626
00:35:32,280 --> 00:35:35,960
Speaker 1: Sachs for what it's worth, and he went on to

627
00:35:36,000 --> 00:35:38,719
Speaker 1: start this other company that was basically a direct competitor

628
00:35:38,760 --> 00:35:41,080
Speaker 1: to that, and it's called rippling, and it's done really

629
00:35:41,120 --> 00:35:43,520
Speaker 1: well in terms of building up its valuation. And Sam

630
00:35:43,640 --> 00:35:46,160
Speaker 1: is one of their earliest investors. And I think you

631
00:35:46,239 --> 00:35:49,480
Speaker 1: know part of his Conrad Parker. Conrad is the guy's name. Yeah,

632
00:35:49,880 --> 00:35:52,160
Speaker 1: And anyway, Sam has made a bunch of money from that,

633
00:35:52,360 --> 00:35:54,600
Speaker 1: or at least you know his his investment is valuable

634
00:35:54,680 --> 00:35:57,920
Speaker 1: from that. And my point is basically like when you

635
00:35:58,040 --> 00:35:59,719
Speaker 1: when you're in this inner circle, you have access to

636
00:35:59,800 --> 00:36:02,759
Speaker 1: these companies and you can make these investments. Whether you

637
00:36:02,840 --> 00:36:07,120
Speaker 1: know he is like standard Deviation is a better business

638
00:36:07,200 --> 00:36:10,359
Speaker 1: person than anyone else in tech, I don't know. It's

639
00:36:10,400 --> 00:36:12,120
Speaker 1: not for me to say, but you know he is

640
00:36:12,400 --> 00:36:14,720
Speaker 1: on paper, you know his his holdings are worth billions.

641
00:36:14,800 --> 00:36:16,680
Speaker 1: So I guess you got to give him something for that.

642
00:36:18,120 --> 00:36:20,880
Speaker 2: So you mentioned in the story that Hydrozene, Sam Altman's

643
00:36:20,920 --> 00:36:23,959
Speaker 2: firm bought a portion of startup shares owned by Paul

644
00:36:24,000 --> 00:36:29,080
Speaker 2: Graham versus y Combinator. Would those have been Paul Graham

645
00:36:29,160 --> 00:36:31,920
Speaker 2: basically doing the same like he might have been investing

646
00:36:31,960 --> 00:36:34,520
Speaker 2: in these companies too, or is this just early days

647
00:36:34,600 --> 00:36:35,680
Speaker 2: why Combinator shares?

648
00:36:36,239 --> 00:36:38,200
Speaker 1: These were shares that were owned by Paul Graham, As

649
00:36:38,239 --> 00:36:41,560
Speaker 1: we reported, and so it was probably a transaction for

650
00:36:41,680 --> 00:36:43,840
Speaker 1: him to kind of take some money off of the

651
00:36:43,920 --> 00:36:47,040
Speaker 1: table and offload them to Hydrazine so he could be

652
00:36:47,160 --> 00:36:49,839
Speaker 1: I guess a little bit more liquid. But yeah, these

653
00:36:49,880 --> 00:36:51,480
Speaker 1: were these were Paul Graham shares that you know ended

654
00:36:51,560 --> 00:36:53,120
Speaker 1: up being bought up by the Hydrozene Fund.

655
00:36:54,480 --> 00:36:58,319
Speaker 2: It's interesting because there's so it feels like Altman at

656
00:36:58,400 --> 00:37:01,399
Speaker 2: times doesn't have a focus though, because he's done all

657
00:37:01,480 --> 00:37:04,520
Speaker 2: of these investments, and you within the reporting, within the

658
00:37:04,600 --> 00:37:07,880
Speaker 2: Washington Posts reporting as well, there's this idea of him

659
00:37:07,920 --> 00:37:12,200
Speaker 2: being absent, absent from y Combinator, absent from looped at

660
00:37:12,239 --> 00:37:16,200
Speaker 2: one point, retasking engineers to work on a dating app separately.

661
00:37:17,640 --> 00:37:21,240
Speaker 2: It almost feels it almost feels hard to tell whether

662
00:37:21,920 --> 00:37:25,320
Speaker 2: Autman is focused on anything other than just the number

663
00:37:25,400 --> 00:37:29,880
Speaker 2: going up. But here here is the real problem. I

664
00:37:30,000 --> 00:37:33,239
Speaker 2: see what happens if and we mentioned this earlier, these

665
00:37:33,280 --> 00:37:36,400
Speaker 2: startups go to zero and he has this these massive

666
00:37:36,480 --> 00:37:37,240
Speaker 2: credit lines.

667
00:37:38,080 --> 00:37:41,399
Speaker 1: Yeah, I mean it feels like a house of cards. Yeah.

668
00:37:41,600 --> 00:37:45,800
Speaker 1: I think, you know, these people tend to be okay

669
00:37:45,920 --> 00:37:48,200
Speaker 1: in the end, I find so, you know, I don't

670
00:37:48,200 --> 00:37:50,040
Speaker 1: know how many people are really all that worried about

671
00:37:50,400 --> 00:37:52,520
Speaker 1: you know, Sam's credit line and stuff, and you know,

672
00:37:52,560 --> 00:37:55,320
Speaker 1: obviously when interest rates go up, these things tend to

673
00:37:55,360 --> 00:37:57,239
Speaker 1: be a lot riskier than they were going into it.

674
00:37:58,360 --> 00:37:59,960
Speaker 1: You know, I can't go into all of the details there,

675
00:38:00,239 --> 00:38:04,040
Speaker 1: but yeah, there's a reason why using you know, privately

676
00:38:04,080 --> 00:38:05,960
Speaker 1: held shares or private you know, you know shares and

677
00:38:06,000 --> 00:38:09,600
Speaker 1: privately held companies as collateral is not commonly done. I

678
00:38:09,680 --> 00:38:11,239
Speaker 1: mean I talked to someone in the course of this

679
00:38:11,320 --> 00:38:14,840
Speaker 1: story who was like shocked that someone would do that

680
00:38:14,920 --> 00:38:18,120
Speaker 1: kind of thing. But you know, again, to this Silicon

681
00:38:18,200 --> 00:38:21,279
Speaker 1: Valley mindset in which risk, you know, quote unquote risk

682
00:38:21,760 --> 00:38:24,719
Speaker 1: is really promoted and celebrated around here, that kind of

683
00:38:24,800 --> 00:38:28,080
Speaker 1: thing is seen as like an example of how aggressive

684
00:38:28,160 --> 00:38:30,239
Speaker 1: and cool Sam is that he's willing to kind of

685
00:38:30,560 --> 00:38:32,400
Speaker 1: take a risk on something like that in order to

686
00:38:32,640 --> 00:38:35,520
Speaker 1: put more money into well, I guess you could. Some

687
00:38:35,560 --> 00:38:37,319
Speaker 1: people would say, put more money into the ecosystem. Other

688
00:38:37,320 --> 00:38:39,879
Speaker 1: people would be like, give himself more examples to get rich.

689
00:38:41,080 --> 00:38:44,439
Speaker 2: Yeah, and it's it doesn't. Actually, this is a question.

690
00:38:45,440 --> 00:38:47,760
Speaker 2: Did you see a lot of it was the general

691
00:38:47,800 --> 00:38:50,759
Speaker 2: pattern of what you've seen a lot of smaller investments

692
00:38:51,200 --> 00:38:54,560
Speaker 2: across a lot of companies or big fat ones generally

693
00:38:54,640 --> 00:38:56,600
Speaker 2: like the three hundred and seventy five million in Helium.

694
00:38:57,360 --> 00:38:59,959
Speaker 1: That one is a standout, the three seventy five million

695
00:39:00,000 --> 00:39:04,240
Speaker 1: and Helion. But you know, again without going too specific

696
00:39:04,280 --> 00:39:06,160
Speaker 1: into the numbers because we didn't put them in the story,

697
00:39:06,280 --> 00:39:08,120
Speaker 1: but you know some of them are in the you know,

698
00:39:08,239 --> 00:39:10,759
Speaker 1: millions and tens of millions. You know, whether that's all

699
00:39:10,800 --> 00:39:13,960
Speaker 1: his personal money or money that's raised through you know,

700
00:39:14,080 --> 00:39:17,160
Speaker 1: various LP funds that are you know, in which there's

701
00:39:17,400 --> 00:39:20,880
Speaker 1: capital put in by LPs. Can get a bit complicated,

702
00:39:21,360 --> 00:39:24,240
Speaker 1: but no, this isn't you know, one of those angel

703
00:39:24,320 --> 00:39:26,880
Speaker 1: investors who's putting ten thousand dollars in a bunch of

704
00:39:26,920 --> 00:39:29,960
Speaker 1: different companies. I mean when he really believes in a

705
00:39:30,040 --> 00:39:32,080
Speaker 1: startup or he really thinks they're going to go somewhere.

706
00:39:32,880 --> 00:39:35,120
Speaker 1: The number is in the millions and tens of millions.

707
00:39:36,640 --> 00:39:40,440
Speaker 2: So slightly different tack here. Yeah, everyone is saying the

708
00:39:40,560 --> 00:39:43,960
Speaker 2: open AI is the future, that chat GPT will be

709
00:39:44,000 --> 00:39:46,680
Speaker 2: in everything. You've been reporting on the enterprise for a

710
00:39:46,760 --> 00:39:49,520
Speaker 2: long time. Do you think that's actually the case. Do

711
00:39:49,600 --> 00:39:52,160
Speaker 2: you think that this company is really I know they're

712
00:39:52,200 --> 00:39:54,480
Speaker 2: making billions of revenue, but do you think they're ever

713
00:39:54,560 --> 00:39:57,400
Speaker 2: gonna go into the green? Do you think this is

714
00:39:57,480 --> 00:39:57,879
Speaker 2: for real?

715
00:39:59,080 --> 00:40:02,840
Speaker 1: I I don't know. I mean, I guess i'd actually

716
00:40:02,880 --> 00:40:05,360
Speaker 1: maybe even push that back to you, because you know,

717
00:40:05,400 --> 00:40:08,520
Speaker 1: you're someone who's you know, been around tech and you

718
00:40:08,600 --> 00:40:11,680
Speaker 1: know reporters and and I mean, like it's it's incredibly

719
00:40:11,800 --> 00:40:15,400
Speaker 1: hypey right now. Like of my time, you know, covering

720
00:40:15,480 --> 00:40:18,920
Speaker 1: this industry, I've never really seen the level of how

721
00:40:19,000 --> 00:40:21,480
Speaker 1: you know you you you know. Crypto obviously was an

722
00:40:21,960 --> 00:40:24,960
Speaker 1: interesting moment in terms of there are people who believe

723
00:40:25,040 --> 00:40:28,400
Speaker 1: that the entire financial system was about to be transformed

724
00:40:28,440 --> 00:40:31,120
Speaker 1: because of these you know, the blockchain, and you know,

725
00:40:31,200 --> 00:40:34,480
Speaker 1: there was the on demand era, you know cloud. I

726
00:40:34,520 --> 00:40:36,400
Speaker 1: didn't really cover tech at the time, and you know

727
00:40:36,480 --> 00:40:38,560
Speaker 1: that sort of proved out to really be in a

728
00:40:38,680 --> 00:40:43,399
Speaker 1: very specific way transformative. I don't know with this one.

729
00:40:43,520 --> 00:40:45,839
Speaker 1: I mean, I think the technology as it stands right

730
00:40:45,840 --> 00:40:50,320
Speaker 1: now is very problematic in terms of its shortcomings. I

731
00:40:50,400 --> 00:40:54,000
Speaker 1: think hallucinations are a major issue, Uh, if it's going

732
00:40:54,040 --> 00:40:56,480
Speaker 1: to be as valuable as search, which is like the

733
00:40:56,560 --> 00:40:59,040
Speaker 1: most successful product you know, tech has probably ever put out.

734
00:41:00,600 --> 00:41:03,920
Speaker 1: And the other issue is the cost of training and

735
00:41:04,000 --> 00:41:07,520
Speaker 1: deploying these models is tremendous. I mean, like you said,

736
00:41:07,600 --> 00:41:09,520
Speaker 1: like I cover the enterprise, so part of my bead

737
00:41:09,600 --> 00:41:12,480
Speaker 1: is writing about the cloud and data centers. I mean,

738
00:41:12,600 --> 00:41:14,840
Speaker 1: to me, one of the biggest things that's going on

739
00:41:15,000 --> 00:41:17,320
Speaker 1: right now is this multi billion dollar build out of

740
00:41:17,400 --> 00:41:21,480
Speaker 1: data centers that's happening at an unprecedented level across not

741
00:41:21,600 --> 00:41:23,879
Speaker 1: even the country, but the world in order for there

742
00:41:23,960 --> 00:41:28,000
Speaker 1: to be enough you know, AI warehouses, data centers you know,

743
00:41:28,080 --> 00:41:32,800
Speaker 1: outfitted with Nvidia chips to train and inference, you know,

744
00:41:32,880 --> 00:41:36,080
Speaker 1: deploy all of these models. That's crazy, I mean, because

745
00:41:36,120 --> 00:41:38,439
Speaker 1: that is all done in advance that they're being enough

746
00:41:38,480 --> 00:41:42,600
Speaker 1: demand to justify these investments, right. I mean, like this

747
00:41:42,800 --> 00:41:45,239
Speaker 1: is all because you know, for a huge portion of

748
00:41:45,320 --> 00:41:48,360
Speaker 1: last year, there was more demand than supply when it

749
00:41:48,400 --> 00:41:52,040
Speaker 1: came to compute, and so all of these tech companies

750
00:41:53,600 --> 00:41:56,440
Speaker 1: started saying, well, we need to build out in advance

751
00:41:56,520 --> 00:41:59,360
Speaker 1: of you know, this demand being unending and increasing. And

752
00:41:59,480 --> 00:42:01,800
Speaker 1: it's like, well, well, okay, that's fine for now, but

753
00:42:01,960 --> 00:42:04,360
Speaker 1: if in the future it doesn't, If you know, this

754
00:42:04,440 --> 00:42:06,919
Speaker 1: turns out to have been a fad, or the years

755
00:42:06,960 --> 00:42:09,480
Speaker 1: that it takes for this to be a widely a

756
00:42:09,560 --> 00:42:15,160
Speaker 1: widely use technology is way longer than it is. You know,

757
00:42:15,280 --> 00:42:18,640
Speaker 1: it could be one of the bigger boondoggles I think

758
00:42:18,719 --> 00:42:20,799
Speaker 1: we've seen in tech, you know, like all these data

759
00:42:20,840 --> 00:42:23,080
Speaker 1: centers that were built out that lay unused because there's

760
00:42:23,120 --> 00:42:25,879
Speaker 1: not enough people wanting to use chat ept or any

761
00:42:25,880 --> 00:42:27,520
Speaker 1: of the kind of similar similar products.

762
00:42:27,640 --> 00:42:29,799
Speaker 2: Is that happening now or is that something you fear

763
00:42:29,880 --> 00:42:30,440
Speaker 2: for the future.

764
00:42:31,000 --> 00:42:33,160
Speaker 1: More for the future, you know, I think the demand

765
00:42:33,280 --> 00:42:35,480
Speaker 1: is still fairly high right now. And if you talk

766
00:42:35,600 --> 00:42:38,040
Speaker 1: to startups like a I startups, they'll say it's still

767
00:42:38,080 --> 00:42:41,560
Speaker 1: hard for us to get access to GPU clusters, for

768
00:42:41,680 --> 00:42:45,000
Speaker 1: us to train models or you know, things like, you know,

769
00:42:45,239 --> 00:42:47,680
Speaker 1: the technology we want to deploy is still much slower

770
00:42:47,719 --> 00:42:51,719
Speaker 1: than we want because there isn't enough compute. But yeah,

771
00:42:51,800 --> 00:42:53,759
Speaker 1: Jerry is still out. Sorry, I know that's a really

772
00:42:53,840 --> 00:42:54,759
Speaker 1: lame phrase, but like.

773
00:42:55,800 --> 00:43:00,120
Speaker 2: For real, that's good though, because what happens if the

774
00:43:00,160 --> 00:43:03,879
Speaker 2: demand never arrives? Though? Does this stuff get repurposed? Does

775
00:43:03,920 --> 00:43:06,319
Speaker 2: it get sold off? Well?

776
00:43:06,360 --> 00:43:08,480
Speaker 1: I think you actually saw a kind of interesting thing

777
00:43:08,560 --> 00:43:12,080
Speaker 1: happening with crypto, which I actually wrote a story about

778
00:43:12,080 --> 00:43:14,959
Speaker 1: that with with berber Jen, my colleague on this story.

779
00:43:15,040 --> 00:43:16,600
Speaker 1: Who you know, who was who was you know, the

780
00:43:16,680 --> 00:43:19,520
Speaker 1: lead on this Sam Altman piece about you know, with

781
00:43:19,640 --> 00:43:22,840
Speaker 1: crypto mining, there were a lot of companies at the

782
00:43:22,920 --> 00:43:26,160
Speaker 1: height of and specifically ethereum mining that were building up

783
00:43:26,280 --> 00:43:30,120
Speaker 1: these rigs, these these mining rigs that were had GPUs

784
00:43:30,160 --> 00:43:33,799
Speaker 1: at the heart of them that were necessary when people

785
00:43:33,840 --> 00:43:35,960
Speaker 1: thought that was going to be profitable basically.

786
00:43:35,719 --> 00:43:38,760
Speaker 2: Like it wasn't. Coal Weave, which is as a listener,

787
00:43:38,840 --> 00:43:42,240
Speaker 2: is a huge student typo, multi billion dollar GP provider.

788
00:43:42,480 --> 00:43:43,400
Speaker 2: They previously crypto.

789
00:43:43,640 --> 00:43:46,839
Speaker 1: Yeah, one hundred percent. They're a fascinating company. I love

790
00:43:46,920 --> 00:43:49,759
Speaker 1: core Weave because, yes, this was a company that is

791
00:43:49,800 --> 00:43:53,719
Speaker 1: started up by people in finance basically like traders, like

792
00:43:53,920 --> 00:43:56,319
Speaker 1: energy traders. I shouldn't actually don't know if it was energy,

793
00:43:56,360 --> 00:43:58,520
Speaker 1: but but people with like a very financial background who

794
00:43:58,600 --> 00:44:01,760
Speaker 1: realized like this amazing arbitrage that was happening in crypto

795
00:44:01,920 --> 00:44:04,759
Speaker 1: and ethereum mining, which was that like the like the

796
00:44:04,880 --> 00:44:09,400
Speaker 1: value of mining when theoreum prices were high, is greater

797
00:44:09,520 --> 00:44:13,440
Speaker 1: than the electricity it takes to consume to do the mining.

798
00:44:13,520 --> 00:44:15,640
Speaker 1: And so when that was at its peak, they were,

799
00:44:16,160 --> 00:44:18,640
Speaker 1: you know, they were doing pretty well, and then they

800
00:44:18,680 --> 00:44:20,640
Speaker 1: read the writing on the wall that you know, ethereum

801
00:44:20,680 --> 00:44:23,680
Speaker 1: mining was probably gonna decrease in value, and they made

802
00:44:23,719 --> 00:44:26,200
Speaker 1: an early switch to like retrofit all of their mining

803
00:44:26,320 --> 00:44:30,040
Speaker 1: rigs into AI compute. And that was before chat GPT

804
00:44:30,280 --> 00:44:34,040
Speaker 1: and you know, open ai became a household name. But anyway,

805
00:44:34,200 --> 00:44:38,200
Speaker 1: I bring up that whole story because what a lot

806
00:44:38,239 --> 00:44:41,400
Speaker 1: of ethereum miners started to realize when there was this

807
00:44:41,600 --> 00:44:44,320
Speaker 1: kind of shift in the nature of ethereum mining that

808
00:44:44,400 --> 00:44:47,920
Speaker 1: basically meant they didn't need GPUs, like these very powerful

809
00:44:48,000 --> 00:44:50,200
Speaker 1: GPU rigs to do the mining is they were stuck

810
00:44:50,320 --> 00:44:54,239
Speaker 1: with these kind of useless machines. And so a lot

811
00:44:54,320 --> 00:44:56,800
Speaker 1: of them have tried to like jump over into AI

812
00:44:57,360 --> 00:45:02,239
Speaker 1: compute and providing you know, training and inferencing. And so

813
00:45:02,680 --> 00:45:04,880
Speaker 1: it was an interesting example of like one trend jumping

814
00:45:04,960 --> 00:45:08,359
Speaker 1: into another. And so I don't know what that could

815
00:45:08,440 --> 00:45:10,960
Speaker 1: mean because the theory of mining is just not even

816
00:45:11,000 --> 00:45:13,960
Speaker 1: close to the scale that we're talking at here with AI,

817
00:45:14,880 --> 00:45:18,640
Speaker 1: but you know, tech seems to find a way. I

818
00:45:18,719 --> 00:45:21,080
Speaker 1: don't know, I don't have a good answer for it,

819
00:45:21,200 --> 00:45:25,560
Speaker 1: but it would be a crazy outcome, honestly, if you know,

820
00:45:25,800 --> 00:45:28,480
Speaker 1: we're talking thirty billion dollars a year of investment in

821
00:45:28,560 --> 00:45:32,760
Speaker 1: infrastructure from a single company alone in building up data centers,

822
00:45:32,800 --> 00:45:35,000
Speaker 1: So if that ended up not being necessary, yeah, I

823
00:45:35,000 --> 00:45:36,279
Speaker 1: don't I don't know what to do with those things.

824
00:45:37,440 --> 00:45:41,279
Speaker 2: Yeah, it feels like what I would worry about is

825
00:45:41,480 --> 00:45:47,480
Speaker 2: the physical GPU equivalent of twenty twenty two, where you

826
00:45:47,600 --> 00:45:49,680
Speaker 2: had all these companies in twenty twenty one who hired

827
00:45:49,760 --> 00:45:54,480
Speaker 2: everyone everywhere and then they went, oh crap, better fire them.

828
00:45:55,160 --> 00:45:58,359
Speaker 2: But it almost feels like it could cause I think

829
00:45:58,520 --> 00:46:01,279
Speaker 2: Nvidia feels like they would be or a MD to

830
00:46:01,360 --> 00:46:04,120
Speaker 2: an extent Micron, I guess, but would be most at

831
00:46:04,200 --> 00:46:07,840
Speaker 2: risk from this because if there's just thousands, tens of thousands,

832
00:46:07,920 --> 00:46:09,960
Speaker 2: hundreds of thousands of black Wells or what have you

833
00:46:10,280 --> 00:46:13,720
Speaker 2: sitting around unused, it feels like it could be catastrophic.

834
00:46:15,200 --> 00:46:17,560
Speaker 1: Yeah, I mean, at least in videas selling stuff, like

835
00:46:17,600 --> 00:46:20,279
Speaker 1: at least they're pushing product, you know, like, at least

836
00:46:20,320 --> 00:46:23,399
Speaker 1: they're manufacturing or designing things that are manufactured and selling

837
00:46:23,440 --> 00:46:25,239
Speaker 1: to the people who are paying cash for them. So

838
00:46:25,800 --> 00:46:28,279
Speaker 1: that's that's better than some crypto or sorry, that's better

839
00:46:28,360 --> 00:46:31,239
Speaker 1: than some AI companies that it's really just on like

840
00:46:31,640 --> 00:46:34,799
Speaker 1: on hype and a hope and a prayer, but yeah,

841
00:46:34,840 --> 00:46:36,960
Speaker 1: I mean, like, as we're recording this in video is

842
00:46:37,120 --> 00:46:39,680
Speaker 1: in and around a three trillion dollar company. It's more

843
00:46:39,800 --> 00:46:43,920
Speaker 1: valuable than Apple. I mean that's just crazy. Yeah, there's

844
00:46:43,960 --> 00:46:46,120
Speaker 1: a lot going on in terms of the expectation of

845
00:46:46,200 --> 00:46:48,200
Speaker 1: this sort of not stopping anytime soon.

846
00:46:49,680 --> 00:46:51,560
Speaker 2: Do you think the AI boom is a bubble?

847
00:46:52,120 --> 00:46:54,480
Speaker 1: Oh yeah, one hundred percent. Like I don't even think

848
00:46:54,480 --> 00:46:59,200
Speaker 1: that's a controversial statement, Like I think Sam go ahead. Yeah, no,

849
00:46:59,280 --> 00:47:01,839
Speaker 1: I think Sam would even agree. And like most people

850
00:47:01,880 --> 00:47:03,360
Speaker 1: that I talk to in a I think it's a

851
00:47:03,400 --> 00:47:07,960
Speaker 1: bubble because look, the nature of that doesn't mean that

852
00:47:08,000 --> 00:47:10,200
Speaker 1: everything's going to go to zero and that you know,

853
00:47:10,360 --> 00:47:12,480
Speaker 1: like the huge run up and value that we've seen

854
00:47:12,520 --> 00:47:16,680
Speaker 1: with Microsoft and in Nvidia is gonna all, you know,

855
00:47:17,760 --> 00:47:21,160
Speaker 1: disintegrate if it takes a lot longer or it doesn't

856
00:47:21,200 --> 00:47:24,120
Speaker 1: even catch on with AI. But yeah, I mean you're

857
00:47:24,160 --> 00:47:26,799
Speaker 1: seeing money. And my colleague Berber wrote actually a good

858
00:47:26,840 --> 00:47:28,319
Speaker 1: story about this a couple of weeks ago. I mean,

859
00:47:28,320 --> 00:47:32,640
Speaker 1: you're seeing startups that have no you know, no revenue

860
00:47:32,800 --> 00:47:37,000
Speaker 1: really or not even a product raising at valuations in

861
00:47:37,040 --> 00:47:39,680
Speaker 1: the billions. I mean that's the very definition of a bubble.

862
00:47:39,840 --> 00:47:41,560
Speaker 1: So yeah, I don't. I don't even feel like I'm

863
00:47:41,600 --> 00:47:42,719
Speaker 1: going out on a limb saying that.

864
00:47:43,920 --> 00:47:45,759
Speaker 2: So I will push back on that, not to say

865
00:47:45,760 --> 00:47:48,319
Speaker 2: you're not going like I believe you are, because if

866
00:47:48,360 --> 00:47:51,239
Speaker 2: you look around and this is rap on this one.

867
00:47:51,280 --> 00:47:55,200
Speaker 2: I think it feels like AI is humored on a

868
00:47:55,320 --> 00:47:59,040
Speaker 2: level in the media right now. The I have literally

869
00:47:59,120 --> 00:48:01,880
Speaker 2: only seen since on the metaverse, where it was just

870
00:48:02,040 --> 00:48:04,919
Speaker 2: this concept, not saying AI is useless generally if AI

871
00:48:05,080 --> 00:48:09,680
Speaker 2: has uses, But it feels like everybody is giving Sunda Pshai,

872
00:48:09,960 --> 00:48:12,400
Speaker 2: for example, the benefit of the doubt about Google Search,

873
00:48:12,880 --> 00:48:14,279
Speaker 2: or at least they were until it told you to

874
00:48:14,320 --> 00:48:17,160
Speaker 2: eat rocks, but especially with chat GPT, they're just kind

875
00:48:17,160 --> 00:48:18,800
Speaker 2: of assuming these things will happen.

876
00:48:19,480 --> 00:48:20,360
Speaker 1: And I don't know what it is.

877
00:48:20,440 --> 00:48:24,160
Speaker 2: It feels almost like the why do you think people

878
00:48:24,200 --> 00:48:26,560
Speaker 2: are giving it so much space and believing that it

879
00:48:26,640 --> 00:48:27,759
Speaker 2: will grow exponentially?

880
00:48:29,600 --> 00:48:31,080
Speaker 1: Why? Actually I have to have two answers to that.

881
00:48:31,320 --> 00:48:33,759
Speaker 1: I mean, one is like you are surrounded as a

882
00:48:33,840 --> 00:48:36,480
Speaker 1: reporter by your sources. The people that you talk to

883
00:48:36,640 --> 00:48:39,400
Speaker 1: day in day out, who you know try to let

884
00:48:39,440 --> 00:48:41,160
Speaker 1: you know what's going on in the space. Are people

885
00:48:41,360 --> 00:48:44,360
Speaker 1: that a lot of the times are big believers in

886
00:48:44,920 --> 00:48:47,040
Speaker 1: any new trend in technology, and so it's kind of

887
00:48:47,080 --> 00:48:49,960
Speaker 1: easy as a reporter to hear about this stuff and

888
00:48:50,719 --> 00:48:53,680
Speaker 1: want to at least explain it to readers. Not necessarily

889
00:48:53,760 --> 00:48:55,520
Speaker 1: be part of the hype. I mean, that's not our job,

890
00:48:55,680 --> 00:48:58,680
Speaker 1: but at least say, like, well, this is why Anthropic

891
00:48:58,840 --> 00:49:01,799
Speaker 1: is getting billions of dollars of investments, or obviously open

892
00:49:01,840 --> 00:49:06,200
Speaker 1: Ai or anything like that. I think if I had

893
00:49:06,239 --> 00:49:08,480
Speaker 1: to just personally guess on a lot of this stuff,

894
00:49:08,760 --> 00:49:11,200
Speaker 1: you know, it's been a bit slow in terms of

895
00:49:11,880 --> 00:49:15,680
Speaker 1: transformational technologies in a while. I mean, honestly, you could

896
00:49:15,719 --> 00:49:19,680
Speaker 1: maybe look back to probably the iPhone as the last

897
00:49:19,719 --> 00:49:23,000
Speaker 1: thing that like fundamentally upended the way we live our lives,

898
00:49:23,960 --> 00:49:25,600
Speaker 1: you know, in the enterprise. I guess you could look

899
00:49:25,600 --> 00:49:27,800
Speaker 1: to the cloud, although most people don't care about that,

900
00:49:29,840 --> 00:49:32,319
Speaker 1: but you know, with AI and you know these kind

901
00:49:32,320 --> 00:49:35,800
Speaker 1: of seemingly magical interactions that you've had with chat, GPT

902
00:49:36,120 --> 00:49:39,600
Speaker 1: or it can you know, write poems and you know,

903
00:49:39,719 --> 00:49:43,320
Speaker 1: create images and and you know Sora and the video

904
00:49:43,400 --> 00:49:45,160
Speaker 1: stuff and you know whatever you want to call that.

905
00:49:45,760 --> 00:49:49,400
Speaker 1: You know, her like demonstration from open Ai, like it

906
00:49:49,760 --> 00:49:53,600
Speaker 1: it demos very well. It sounds like the kind of

907
00:49:53,680 --> 00:49:58,359
Speaker 1: promise of AI of creating something that approximates human intelligence.

908
00:49:58,480 --> 00:49:59,880
Speaker 2: Right, so you can fill in the gaps.

909
00:50:00,719 --> 00:50:03,360
Speaker 1: Yeah, it's just like it feels like the future. You know,

910
00:50:03,400 --> 00:50:05,000
Speaker 1: I'm not at all saying that it is, but like

911
00:50:05,520 --> 00:50:08,160
Speaker 1: in terms of like other technological trends that we've seen

912
00:50:08,800 --> 00:50:12,000
Speaker 1: in the last decade or so, like this one comes

913
00:50:12,040 --> 00:50:15,160
Speaker 1: closer to science fiction than anything I've seen. I'm not

914
00:50:15,239 --> 00:50:17,840
Speaker 1: saying it is, but like it looks like it on paper,

915
00:50:17,880 --> 00:50:20,080
Speaker 1: And so it's a lot easier, I think, to get

916
00:50:20,160 --> 00:50:21,839
Speaker 1: caught up in the hype than you may have been

917
00:50:21,920 --> 00:50:24,200
Speaker 1: in like I don't know, Uber for X or like

918
00:50:24,320 --> 00:50:25,680
Speaker 1: instant delivery or something.

919
00:50:38,400 --> 00:50:40,799
Speaker 2: The Wall Street Journal also reports the Open AI has

920
00:50:40,880 --> 00:50:44,640
Speaker 2: established and I quote, a strengthened conflicts policy and a

921
00:50:44,920 --> 00:50:49,000
Speaker 2: new independent audit committee that reviews potential conflicts, which the

922
00:50:49,120 --> 00:50:52,680
Speaker 2: journal also note says yet to disclose any details about

923
00:50:53,120 --> 00:50:56,400
Speaker 2: what those policies might be. It's also important to remember

924
00:50:56,440 --> 00:50:59,279
Speaker 2: that when Samultman returned to Open AI, he appointed a

925
00:50:59,360 --> 00:51:02,040
Speaker 2: new board of direct is made up of this avengers

926
00:51:02,080 --> 00:51:05,839
Speaker 2: of capitalism. I've called them before, people like Fidjisimos, CEO

927
00:51:05,920 --> 00:51:08,759
Speaker 2: of Instacart, which is a company that Sam Mormon invested in,

928
00:51:09,840 --> 00:51:13,080
Speaker 2: to a board that also already included Dan Adam DeAngelo

929
00:51:13,960 --> 00:51:17,520
Speaker 2: of Cora, which is another company that Sam Mortman invested in.

930
00:51:18,640 --> 00:51:21,399
Speaker 2: Oh oh, sorry, sorry, I forgot. There's one other guy

931
00:51:21,520 --> 00:51:24,360
Speaker 2: that Sam Ortman added back to the board when he

932
00:51:24,440 --> 00:51:27,239
Speaker 2: became CEO. He's a guy you might know. He's called

933
00:51:27,320 --> 00:51:31,759
Speaker 2: Sam Altman. It's so good watching all this happen. It's

934
00:51:31,840 --> 00:51:35,520
Speaker 2: so fun. It's so great watching all of this naked

935
00:51:36,800 --> 00:51:40,719
Speaker 2: self dealing, corrupt nonsense happen, and everyone's just like, this

936
00:51:40,840 --> 00:51:43,920
Speaker 2: guy is the future. Sam Mortman's the man. And I

937
00:51:44,000 --> 00:51:46,880
Speaker 2: think the frustrating part of watching the Sam Mortman story

938
00:51:47,000 --> 00:51:50,160
Speaker 2: unfold is that at no point anybody appears to interrogated

939
00:51:50,680 --> 00:51:53,480
Speaker 2: who this person was and whether they might be fit

940
00:51:53,560 --> 00:51:56,719
Speaker 2: to task. There are credible allegations of abuse from his

941
00:51:56,800 --> 00:52:01,839
Speaker 2: sister Annie Altman. There are real things happening here, business things,

942
00:52:01,920 --> 00:52:05,480
Speaker 2: social things, horrible things, and no one's god dwn doing anything.

943
00:52:05,960 --> 00:52:08,799
Speaker 2: And maybe that's it. Maybe Ortmand's skill isn't so much

944
00:52:08,920 --> 00:52:13,040
Speaker 2: creating things or any real legacy, but it's just a

945
00:52:13,120 --> 00:52:15,560
Speaker 2: result of the momentum one gets when you've made enough

946
00:52:15,680 --> 00:52:19,719
Speaker 2: money for people and enough money yourself that people no

947
00:52:19,880 --> 00:52:23,000
Speaker 2: longer bother to check and would rather just find convenient

948
00:52:23,080 --> 00:52:27,239
Speaker 2: platitudes and stories about the clever things you've said, rather

949
00:52:27,360 --> 00:52:30,960
Speaker 2: than think about it for too long, because maybe the

950
00:52:31,040 --> 00:52:35,320
Speaker 2: truth's just a little disgusting. And the problem with someone

951
00:52:35,440 --> 00:52:37,600
Speaker 2: like Sam Orman is that they'll eventually get to the

952
00:52:37,640 --> 00:52:40,480
Speaker 2: point where they can do real damage. I don't know,

953
00:52:41,080 --> 00:52:44,440
Speaker 2: like today, like becoming the figurehead for the entirety of

954
00:52:44,480 --> 00:52:48,600
Speaker 2: Silicon Valley and the entire artificial intelligence boom and the

955
00:52:48,719 --> 00:52:54,880
Speaker 2: CEO of its largest player. Aortman is a marketer at best,

956
00:52:55,360 --> 00:52:58,560
Speaker 2: kind of a management consultant, but let's be honest, history

957
00:52:58,600 --> 00:53:00,360
Speaker 2: shows he doesn't really manage it anything.

958
00:53:01,280 --> 00:53:01,400
Speaker 1: Now.

959
00:53:01,440 --> 00:53:03,800
Speaker 2: I think he's the Michael Jordan of bullshit, the Michael

960
00:53:03,880 --> 00:53:07,080
Speaker 2: Jordan of empty promises, except he's never had a situation

961
00:53:07,280 --> 00:53:10,040
Speaker 2: before where these promises were actually connected to something he

962
00:53:10,239 --> 00:53:14,400
Speaker 2: was responsible for. And what's scary is, like I said,

963
00:53:14,719 --> 00:53:18,200
Speaker 2: this guy is the CEO of Open AI, and he

964
00:53:18,280 --> 00:53:21,960
Speaker 2: has made all of these promises for everyone in artificial intelligence,

965
00:53:22,280 --> 00:53:27,000
Speaker 2: even those not making generative AI. So everyone is putting

966
00:53:27,080 --> 00:53:30,520
Speaker 2: the expectations of Sam Altman, who is building and by

967
00:53:30,680 --> 00:53:32,960
Speaker 2: which I mean having other people build a technology that

968
00:53:33,040 --> 00:53:35,680
Speaker 2: doesn't do the things he's promising on the entirety of

969
00:53:35,840 --> 00:53:39,160
Speaker 2: the AI industry, so that the people buying AI who

970
00:53:39,160 --> 00:53:40,680
Speaker 2: don't really know what they're talking about go and use

971
00:53:40,719 --> 00:53:43,200
Speaker 2: generative AI and then they say, wait, this doesn't do

972
00:53:43,320 --> 00:53:47,279
Speaker 2: the thing. Do you not see the problem here? Do

973
00:53:47,400 --> 00:53:51,160
Speaker 2: you not see that Sam Altman is leading tech to ruin.

974
00:53:52,560 --> 00:53:56,680
Speaker 2: He's promising these things that generative AI cannot do. He

975
00:53:56,880 --> 00:54:00,400
Speaker 2: is making these statements that are boosting stocks that are

976
00:54:00,800 --> 00:54:05,840
Speaker 2: honest to god impressive here tricking fortune one hundred CEOs

977
00:54:05,880 --> 00:54:08,600
Speaker 2: into investing money in take that will not do what

978
00:54:08,840 --> 00:54:13,600
Speaker 2: it says. And when the ruination begins, it's going to

979
00:54:13,680 --> 00:54:16,680
Speaker 2: be terrible for the valley. Funding will be even harder

980
00:54:16,719 --> 00:54:21,040
Speaker 2: to get. And in the next episode, I'm gonna explore

981
00:54:21,080 --> 00:54:23,759
Speaker 2: Sam a little bit more and I'm gonna really look

982
00:54:23,800 --> 00:54:27,120
Speaker 2: at what happens to an industry when they so doggedly

983
00:54:27,280 --> 00:54:31,520
Speaker 2: follow and support and appreciate such an obvious false prophet.

984
00:54:39,600 --> 00:54:41,960
Speaker 2: Thank you for listening to Better Offline. The editor and

985
00:54:42,040 --> 00:54:45,200
Speaker 2: composer of the Better Offline theme song is Matasowski. You

986
00:54:45,239 --> 00:54:47,440
Speaker 2: can check out more of his music and audio projects

987
00:54:47,640 --> 00:54:51,080
Speaker 2: at Matasowski dot com, M A T T O S

988
00:54:51,239 --> 00:54:55,239
Speaker 2: O W s ki dot com. You can email me

989
00:54:55,320 --> 00:54:57,919
Speaker 2: at easy at better offline dot com or visit better

990
00:54:57,960 --> 00:55:00,160
Speaker 2: offline dot com to find more podcast links and of

991
00:55:00,200 --> 00:55:03,279
Speaker 2: course my newsletter. I also really recommend you go to

992
00:55:03,360 --> 00:55:05,800
Speaker 2: chat dot Where's youread dot at to visit the discord,

993
00:55:06,120 --> 00:55:08,359
Speaker 2: and go to our slash Better Offline to check out

994
00:55:08,440 --> 00:55:12,760
Speaker 2: I'll Reddit. Thank you so much for listening. Better Offline

995
00:55:12,880 --> 00:55:15,040
Speaker 2: is a production of cool Zone Media. For more from

996
00:55:15,120 --> 00:55:18,359
Speaker 2: cool Zone Media, visit our website cool Zonemedia dot com,

997
00:55:18,880 --> 00:55:21,719
Speaker 2: or check us out on the iHeartRadio app, Apple Podcasts,

998
00:55:21,840 --> 00:55:23,280
Speaker 2: or wherever you get your podcasts.