1
00:00:02,480 --> 00:00:03,560
Speaker 1: Also media.

2
00:00:05,519 --> 00:00:08,320
Speaker 2: Hello and welcome to this week's Better Offline. I'm your

3
00:00:08,360 --> 00:00:23,479
Speaker 2: host ed Zetron. Subscribe to the newsletter, buy one of

4
00:00:23,480 --> 00:00:26,480
Speaker 2: our beautiful new fuck Data Center t shirts and join

5
00:00:26,560 --> 00:00:29,200
Speaker 2: me and welcoming the wonderful and incredible Steve Burke of

6
00:00:29,280 --> 00:00:31,800
Speaker 2: Gamers Nextus, who joins us today to talk about how

7
00:00:31,840 --> 00:00:32,839
Speaker 2: great everything is.

8
00:00:33,840 --> 00:00:35,880
Speaker 1: I didn't know there was a fuck Data Center shirt.

9
00:00:36,040 --> 00:00:38,000
Speaker 2: Yeah, man, we got fuck datas that. You've got this

10
00:00:38,159 --> 00:00:40,199
Speaker 2: shirt with like a skull, whether you is so that

11
00:00:40,240 --> 00:00:42,280
Speaker 2: you can wear it out you're not technically swearing.

12
00:00:44,080 --> 00:00:46,760
Speaker 1: Yeah, I might buy one. We have the we have

13
00:00:46,840 --> 00:00:50,280
Speaker 1: the new micro slop shirt. Oh yeah, between the two

14
00:00:50,320 --> 00:00:53,720
Speaker 1: of us, as we're making the world the better plays

15
00:00:53,760 --> 00:00:54,840
Speaker 1: just like Silicon Valley.

16
00:00:55,320 --> 00:00:58,040
Speaker 2: Yeah, I'm just worried that, like someone's gonna be walking

17
00:00:58,080 --> 00:01:00,440
Speaker 2: around and do something wearing one of mine. But you

18
00:01:00,440 --> 00:01:04,160
Speaker 2: know it's not my not my fault. Yeah, it's so

19
00:01:04,200 --> 00:01:07,200
Speaker 2: this this year's GtC was It kind of reminded me

20
00:01:07,240 --> 00:01:10,080
Speaker 2: of this year's CES in the sense that it felt

21
00:01:10,160 --> 00:01:12,959
Speaker 2: like a couple doing stuff to pretend that they were

22
00:01:13,000 --> 00:01:15,959
Speaker 2: doing well, like being like, yeah, you know, we're great,

23
00:01:16,000 --> 00:01:18,520
Speaker 2: we're going We're going to Puerto Rico going on vacation,

24
00:01:18,640 --> 00:01:21,200
Speaker 2: We're feeling great, we love each other, we're only in

25
00:01:21,240 --> 00:01:24,200
Speaker 2: couples counseling three times a week. It was so weird.

26
00:01:25,360 --> 00:01:30,480
Speaker 1: Yeah, it was. I gotta say the DLSS appearance, the

27
00:01:30,520 --> 00:01:34,400
Speaker 1: gaming appearance, I wasn't expecting just because.

28
00:01:34,680 --> 00:01:37,679
Speaker 2: What happened there, what happened, Well, why was everyone upset?

29
00:01:37,800 --> 00:01:39,759
Speaker 2: This part just completely passed me by.

30
00:01:40,080 --> 00:01:43,080
Speaker 1: I So DLSS is a gaming thing, and one thing

31
00:01:43,080 --> 00:01:45,559
Speaker 1: I wonder is that there's a huge amount of backlash

32
00:01:45,600 --> 00:01:49,080
Speaker 1: towards it from just everybody. I mean, it's like one

33
00:01:49,080 --> 00:01:52,000
Speaker 1: of the most hated dance I've ever seen it now,

34
00:01:52,080 --> 00:01:53,880
Speaker 1: so I'll get into what it is. But what I

35
00:01:53,880 --> 00:01:57,280
Speaker 1: thought was interesting was, uh, I don't know, just like

36
00:01:57,400 --> 00:02:01,840
Speaker 1: Jensen's reaction afterward, where they had multiple statements and reactions,

37
00:02:01,840 --> 00:02:05,480
Speaker 1: and I almost wonder, if you're Jensen, if if you

38
00:02:05,560 --> 00:02:09,120
Speaker 1: look at that and you're like, okay, fuck gamers, like.

39
00:02:09,880 --> 00:02:12,720
Speaker 2: I mean that kind of already doing that already.

40
00:02:12,480 --> 00:02:14,720
Speaker 1: They are, But I think I mean in like a

41
00:02:14,840 --> 00:02:19,079
Speaker 1: more direct less of a shrewd business decision and more

42
00:02:19,080 --> 00:02:21,120
Speaker 1: of a no, seriously.

43
00:02:20,760 --> 00:02:23,520
Speaker 2: No we have we actually don't. Yeah, we're just saying

44
00:02:23,520 --> 00:02:24,120
Speaker 2: it out loud.

45
00:02:24,160 --> 00:02:28,920
Speaker 1: Now, yeah, so yeah, it's it's basically a filter. It's

46
00:02:28,960 --> 00:02:31,160
Speaker 1: an AI slop filter more or less. They said it's

47
00:02:31,160 --> 00:02:34,560
Speaker 1: not a filter, and then they put out multiple different

48
00:02:34,560 --> 00:02:37,280
Speaker 1: public statements that are like paragraphs long when you read

49
00:02:37,320 --> 00:02:39,799
Speaker 1: all of them, and they they say it's not a filter,

50
00:02:39,880 --> 00:02:41,919
Speaker 1: and then they proceed to describe a filter.

51
00:02:42,600 --> 00:02:45,840
Speaker 2: So, but isn't the LSS generally good and that it

52
00:02:45,919 --> 00:02:47,960
Speaker 2: adds frames like that's a good thing.

53
00:02:48,320 --> 00:02:52,960
Speaker 1: DLSS has has some things it's done pretty well over time.

54
00:02:53,000 --> 00:02:57,200
Speaker 1: So it starts as basically an upscaler, and then it

55
00:02:57,360 --> 00:03:00,080
Speaker 1: progressed to where there's been times where DLSS can be

56
00:03:00,080 --> 00:03:03,760
Speaker 1: better than native while improving the performance just because of

57
00:03:03,800 --> 00:03:07,320
Speaker 1: the way games render. Right, Yeah, different things. So, I

58
00:03:07,320 --> 00:03:11,720
Speaker 1: mean there's certain types of for example, fence posts or

59
00:03:11,840 --> 00:03:14,400
Speaker 1: grates or things that have a lot of repeating patterns

60
00:03:14,480 --> 00:03:17,040
Speaker 1: straight lines. Sometimes you have trouble with that at low resolution.

61
00:03:17,120 --> 00:03:20,079
Speaker 1: So DLSS to an upscale and sometimes even repair these

62
00:03:20,120 --> 00:03:24,000
Speaker 1: things they rendered in a way that's just not good.

63
00:03:24,760 --> 00:03:31,000
Speaker 1: But they've now attached this this basically Instagram twenty nineteen

64
00:03:31,880 --> 00:03:36,440
Speaker 1: face filter to DLSS and kind of tarnets the name

65
00:03:36,480 --> 00:03:40,520
Speaker 1: of something totally unrelated. It looks like they're trying to say, look,

66
00:03:40,640 --> 00:03:44,680
Speaker 1: AI it has uses, please kill the bubble.

67
00:03:45,120 --> 00:03:48,960
Speaker 2: And so it seems like it's not just like adding frames,

68
00:03:49,040 --> 00:03:52,080
Speaker 2: it's attempting to fill in details. It's almost like yasifying

69
00:03:52,240 --> 00:03:54,720
Speaker 2: and yes, this is really horrible.

70
00:03:55,240 --> 00:04:00,880
Speaker 1: Yeah it so it basically what it's doing. So they

71
00:04:00,920 --> 00:04:04,720
Speaker 1: originally said that it changes it uses color and some

72
00:04:04,840 --> 00:04:08,960
Speaker 1: vectors on the screen to then improve things by using

73
00:04:09,040 --> 00:04:13,480
Speaker 1: AI generation to do whatever it is they think is

74
00:04:13,480 --> 00:04:17,200
Speaker 1: improving it. What they're actually doing, yeah, they're changing the

75
00:04:17,320 --> 00:04:19,680
Speaker 1: entire feel of the game. And I mean you know

76
00:04:19,760 --> 00:04:24,360
Speaker 1: this where AI generated images, especially when you ask them

77
00:04:24,360 --> 00:04:29,400
Speaker 1: to be photorealistic, they all pretty much look the same, right, like, yeah, yeah,

78
00:04:29,480 --> 00:04:33,640
Speaker 1: there's no style, there's no character to it. And whether

79
00:04:33,720 --> 00:04:35,400
Speaker 1: or not it's useful for people, I don't even care.

80
00:04:35,680 --> 00:04:39,360
Speaker 1: I think what most people cared about was you're stripping

81
00:04:39,400 --> 00:04:43,039
Speaker 1: all of the character out of the artwork. And the

82
00:04:43,160 --> 00:04:45,440
Speaker 1: you know, part of the art for video games is

83
00:04:45,480 --> 00:04:48,320
Speaker 1: you have to work within these strict confines to make

84
00:04:48,360 --> 00:04:51,200
Speaker 1: it regnerable. Yeah, and they strip it out and they

85
00:04:51,200 --> 00:04:53,240
Speaker 1: replace it with something that just looks like the same

86
00:04:53,240 --> 00:04:58,320
Speaker 1: slop everywhere. And Video's initial defense was well, but the

87
00:04:58,440 --> 00:05:02,760
Speaker 1: artists can control it. And I think the answer to

88
00:05:02,800 --> 00:05:06,520
Speaker 1: that is, I find it very unlikely that the artists

89
00:05:06,600 --> 00:05:09,400
Speaker 1: make these decisions. I think this is probably an executive

90
00:05:09,440 --> 00:05:12,719
Speaker 1: level corporate decision of we're gonna partner with Nvidia to

91
00:05:12,839 --> 00:05:15,160
Speaker 1: use this thing, and if you're an.

92
00:05:15,120 --> 00:05:19,919
Speaker 2: Artist, fire artist, so yeah, yeah, like yeah yeah. And

93
00:05:20,000 --> 00:05:22,160
Speaker 2: also wouldn't it add a bunch of work to an

94
00:05:22,240 --> 00:05:25,320
Speaker 2: artist anyway, because you'd have to tweak this completely separate

95
00:05:25,360 --> 00:05:28,960
Speaker 2: thing that also is not consistent and is generative.

96
00:05:29,279 --> 00:05:33,839
Speaker 1: Yeah, and I mean it. They didn't even show any

97
00:05:33,920 --> 00:05:36,520
Speaker 1: like actual motion other than one game, and it looked awful.

98
00:05:37,040 --> 00:05:42,080
Speaker 1: And I think it's likely that the face details slightly change,

99
00:05:42,200 --> 00:05:45,719
Speaker 1: you know, from scene to scene, because it's some form

100
00:05:45,760 --> 00:05:49,040
Speaker 1: of generative, so it's it's not going to be perfectly consistent.

101
00:05:49,160 --> 00:05:52,479
Speaker 1: So anyway, they're they're trying to shove AI slop into

102
00:05:53,240 --> 00:05:55,960
Speaker 1: real time rendering for games now in a way that

103
00:05:56,880 --> 00:05:59,479
Speaker 1: I will say I was, I guess proud of the

104
00:05:59,480 --> 00:06:04,840
Speaker 1: gaming can unity to see. The amount of pushback was unbelievable,

105
00:06:04,960 --> 00:06:09,719
Speaker 1: Like these large companies have done far more corrupt, terrible

106
00:06:09,760 --> 00:06:13,599
Speaker 1: things in the real world with governments and data centers whatever,

107
00:06:14,480 --> 00:06:16,719
Speaker 1: and this got more pushback than that stuff.

108
00:06:17,160 --> 00:06:20,480
Speaker 2: Yeah, I think everyone's just kind of fucking tired of

109
00:06:20,560 --> 00:06:24,960
Speaker 2: Nvidia at this point, because it it isn't really clear

110
00:06:25,000 --> 00:06:28,360
Speaker 2: what Invidia is doing other than selling more stuff, and

111
00:06:28,400 --> 00:06:31,120
Speaker 2: it isn't clear who is actually using that stuff. I mean,

112
00:06:32,640 --> 00:06:35,560
Speaker 2: I just the the indignity of watching a company with

113
00:06:36,040 --> 00:06:38,920
Speaker 2: like a three four trillion dollar market cap talking about

114
00:06:38,960 --> 00:06:44,200
Speaker 2: open claw. Truly, like, to this day, I cannot get

115
00:06:44,200 --> 00:06:46,040
Speaker 2: a straight answer as to why you should use an

116
00:06:46,040 --> 00:06:46,640
Speaker 2: open claw.

117
00:06:47,560 --> 00:06:51,760
Speaker 1: I liked his uh in their pregame for GtC where

118
00:06:53,560 --> 00:06:55,880
Speaker 1: he made the comments to the other I don't know

119
00:06:55,920 --> 00:06:59,960
Speaker 1: the podcasters about I think AI is going to make

120
00:07:00,080 --> 00:07:02,600
Speaker 1: us all busier. Isn't it making you busier? Ha ha?

121
00:07:03,240 --> 00:07:05,719
Speaker 2: What do you do all day? Jensen? Jensen, You're not

122
00:07:05,800 --> 00:07:08,799
Speaker 2: that busy. I refuse to believe any of these people

123
00:07:08,800 --> 00:07:10,800
Speaker 2: are busy at all. In fact, I think that they're

124
00:07:10,800 --> 00:07:13,280
Speaker 2: just kind of fucking sitting around coming up with new

125
00:07:13,320 --> 00:07:16,440
Speaker 2: ideas of stuff they can say at GtC, and then

126
00:07:16,440 --> 00:07:17,840
Speaker 2: they go to sleep for three months.

127
00:07:18,080 --> 00:07:21,120
Speaker 1: Yeah, because I'm not even sure. It's just not even

128
00:07:21,120 --> 00:07:23,960
Speaker 1: a good I don't know, it's it's not news that

129
00:07:24,040 --> 00:07:28,239
Speaker 1: these executives are toned aff obviously been disconnected from reality,

130
00:07:28,280 --> 00:07:30,840
Speaker 1: but it is a very disconnected from reality thing to

131
00:07:30,880 --> 00:07:35,160
Speaker 1: say to make the cell of AI is going to

132
00:07:35,200 --> 00:07:38,200
Speaker 1: reduce the workforce for the executives, and then also say

133
00:07:38,240 --> 00:07:41,640
Speaker 1: that it's making people busier. And it's just like these,

134
00:07:42,040 --> 00:07:44,120
Speaker 1: this isn't the cell you think it is.

135
00:07:44,760 --> 00:07:47,920
Speaker 2: Also, these aren't thoughts that connect together. If you say

136
00:07:47,960 --> 00:07:52,520
Speaker 2: them both in a sentence, you sound insane. I just this.

137
00:07:53,000 --> 00:07:55,800
Speaker 2: I'm sure you haven't really explored open claw march. I

138
00:07:55,960 --> 00:07:58,720
Speaker 2: certainly haven't wanted to. But it appears to just be

139
00:07:58,880 --> 00:08:01,160
Speaker 2: what if I turned over my compute to a large

140
00:08:01,240 --> 00:08:06,080
Speaker 2: language model and nothing really changed. That's long and short

141
00:08:06,080 --> 00:08:08,560
Speaker 2: of it. So, which is what makes it so insane

142
00:08:08,560 --> 00:08:10,960
Speaker 2: that in videos, Look, GtC used to be a place

143
00:08:11,000 --> 00:08:17,640
Speaker 2: they announced hardware and new technology, not hey guys, the

144
00:08:17,720 --> 00:08:20,480
Speaker 2: latest open source thing you're gonna forget about in six

145
00:08:20,560 --> 00:08:23,920
Speaker 2: months that is now the most important thing in videos stack.

146
00:08:25,000 --> 00:08:28,320
Speaker 1: It's it's really weird because we've covered on video for

147
00:08:28,360 --> 00:08:32,959
Speaker 1: so long that I've met a lot of the engineers there. Yeah,

148
00:08:33,000 --> 00:08:37,920
Speaker 1: and the people who are running these AI departments now

149
00:08:38,480 --> 00:08:41,160
Speaker 1: are at hardware and software levels are people that I

150
00:08:41,200 --> 00:08:44,800
Speaker 1: worked with on the gaming side, you know, anywhere from

151
00:08:44,880 --> 00:08:48,199
Speaker 1: fifteen years ago until even more recently, like three years ago,

152
00:08:48,640 --> 00:08:52,960
Speaker 1: and it's a little sad for me seeing these people

153
00:08:53,000 --> 00:08:56,960
Speaker 1: move over to purely AI in these big important roles,

154
00:08:57,679 --> 00:09:01,240
Speaker 1: and it's just like, I don't know, they're smart people,

155
00:09:01,440 --> 00:09:05,240
Speaker 1: and I have nothing I respect about their work anymore

156
00:09:05,280 --> 00:09:08,920
Speaker 1: for the most part because of the just I think,

157
00:09:09,160 --> 00:09:13,160
Speaker 1: sort of feckless rollout and widespread damage that it's causing.

158
00:09:13,360 --> 00:09:16,040
Speaker 1: And it's just it's interesting where you see on video

159
00:09:16,080 --> 00:09:18,720
Speaker 1: moving their pieces around like a chess board, where they're going, Okay,

160
00:09:18,720 --> 00:09:22,280
Speaker 1: this guy is really good at this specific type of research.

161
00:09:22,640 --> 00:09:24,319
Speaker 1: Let's strip him out of the thing that he's been

162
00:09:24,360 --> 00:09:26,920
Speaker 1: doing really well for ten years in gaming or whatever

163
00:09:27,160 --> 00:09:30,880
Speaker 1: and put them into AI, you know, and then outcomes

164
00:09:31,520 --> 00:09:33,680
Speaker 1: like the DLS.

165
00:09:33,800 --> 00:09:39,679
Speaker 2: Nemo Claw, Nemo Claw, Nemo Claw. This leaked to like

166
00:09:39,960 --> 00:09:42,360
Speaker 2: four months ago. No one knew what the fuck this was,

167
00:09:43,080 --> 00:09:46,640
Speaker 2: Like they the guy who made open claw sold hisself

168
00:09:46,679 --> 00:09:49,920
Speaker 2: to open AI. Cool for him, I guess, And now

169
00:09:49,960 --> 00:09:53,240
Speaker 2: this is like, now this is the most important thing

170
00:09:53,240 --> 00:09:57,200
Speaker 2: to do in video now, Like what's It's just it's

171
00:09:57,200 --> 00:10:00,240
Speaker 2: so strange. It's it's just very strange. They did it song.

172
00:10:00,280 --> 00:10:02,800
Speaker 2: At the end of GtC as well, they had a

173
00:10:02,880 --> 00:10:06,280
Speaker 2: song a horrible altar I saw, take him. I was

174
00:10:06,320 --> 00:10:10,600
Speaker 2: a disgrace to journalism. Sorry Tay, who was like, not

175
00:10:10,640 --> 00:10:12,520
Speaker 2: gonna lie, it's just kind of a banger.

176
00:10:13,240 --> 00:10:15,520
Speaker 1: Maybe go to the song as a banner.

177
00:10:15,480 --> 00:10:19,000
Speaker 2: Yeah, banger. Yes, he did go to the doctor. That's

178
00:10:19,200 --> 00:10:21,480
Speaker 2: my first thought is like, you need to go to

179
00:10:21,480 --> 00:10:24,120
Speaker 2: the doctor. Man, you have like I said, to hear

180
00:10:24,160 --> 00:10:26,280
Speaker 2: it and it was not good. But I heard it

181
00:10:26,320 --> 00:10:27,480
Speaker 2: and it made me angry.

182
00:10:28,080 --> 00:10:34,640
Speaker 1: Yeah, yeah, I was thinking about this when AI music

183
00:10:34,679 --> 00:10:38,600
Speaker 1: covers first started to really propagate on YouTube. And yeah,

184
00:10:38,600 --> 00:10:41,320
Speaker 1: I remember the first one I ran into. It was

185
00:10:41,400 --> 00:10:50,679
Speaker 1: like Slipknot reimagined as soul like blues. Yeah, and I did. Actually,

186
00:10:50,760 --> 00:10:52,280
Speaker 1: that was the first one I saw. I listened to

187
00:10:52,320 --> 00:10:55,240
Speaker 1: it and I was like, damn, this is like not bad.

188
00:10:55,440 --> 00:10:57,880
Speaker 1: And it was only you know, thirty seconds into it

189
00:10:57,880 --> 00:11:03,240
Speaker 1: where you realize the horrors of music and entertainment. The

190
00:11:03,400 --> 00:11:06,200
Speaker 1: entire currency of it is attention, and you only have

191
00:11:06,240 --> 00:11:09,160
Speaker 1: so much time you can give to listening to music

192
00:11:09,280 --> 00:11:12,960
Speaker 1: in a day. And for each of these AI songs

193
00:11:12,960 --> 00:11:15,480
Speaker 1: that someone's going to listen to, and even worse for

194
00:11:15,720 --> 00:11:19,240
Speaker 1: the real artists. If people start liking them, that's one

195
00:11:19,320 --> 00:11:22,880
Speaker 1: less real artist who may already be like just a

196
00:11:23,000 --> 00:11:28,280
Speaker 1: starving artist archetype who doesn't get that view or that listen.

197
00:11:29,280 --> 00:11:31,520
Speaker 2: Yeah, and I've heard some of those AI thinks, and

198
00:11:31,559 --> 00:11:35,240
Speaker 2: it's always like the first ten to twenty seconds you're like, okay,

199
00:11:35,280 --> 00:11:38,640
Speaker 2: this is and then nothing changes. It's just very repetitious.

200
00:11:38,960 --> 00:11:40,720
Speaker 2: But you're right, it only exists as a kind of

201
00:11:40,760 --> 00:11:43,719
Speaker 2: phishing law to get people in just kind of hear

202
00:11:43,760 --> 00:11:49,040
Speaker 2: in the background. It's just patently evil. It's just wafting

203
00:11:49,120 --> 00:11:52,400
Speaker 2: evil at the moment, and even by the standards of

204
00:11:52,440 --> 00:11:55,719
Speaker 2: regular software, it's not really clear what any of these

205
00:11:55,720 --> 00:11:59,080
Speaker 2: companies are doing anymore. Like I GtC, I don't know

206
00:11:59,120 --> 00:12:01,360
Speaker 2: if i'd describe it as exciting, but it felt like

207
00:12:01,400 --> 00:12:04,120
Speaker 2: they were selling real things every year. Yeah, and now

208
00:12:04,120 --> 00:12:07,960
Speaker 2: it's just you want an open claw. Oh, actually, I

209
00:12:08,000 --> 00:12:11,560
Speaker 2: forgot my favorite part. So Jensen went on the all

210
00:12:11,600 --> 00:12:15,760
Speaker 2: in podcast, you know, the classic guys we don't think

211
00:12:15,800 --> 00:12:18,960
Speaker 2: of anything happening too, and he went on and he

212
00:12:19,040 --> 00:12:22,040
Speaker 2: was like, what, so, what should happen now is that

213
00:12:22,240 --> 00:12:25,679
Speaker 2: you should give engineers when they join your company two

214
00:12:25,800 --> 00:12:28,000
Speaker 2: hundred and fifty thousand dollars worth of tokens a year

215
00:12:29,640 --> 00:12:33,520
Speaker 2: and that's part of their compackage. It's like, oh, I'm sure,

216
00:12:33,559 --> 00:12:35,640
Speaker 2: I'm sure he would love that. I'm sure he would

217
00:12:35,640 --> 00:12:38,920
Speaker 2: love that. I'm sure. Like so much of the so

218
00:12:39,040 --> 00:12:41,000
Speaker 2: much of this is just Jensen going out there and

219
00:12:41,000 --> 00:12:43,520
Speaker 2: being like, it'd be really good if you use my stuff.

220
00:12:43,640 --> 00:12:46,920
Speaker 1: That's not even camp though, right, Like, but isn't it

221
00:12:46,920 --> 00:12:48,640
Speaker 1: for work? It's literally just budget.

222
00:12:49,320 --> 00:12:53,000
Speaker 2: Yeah, it's it's it's your compensation so that you can

223
00:12:53,000 --> 00:12:57,800
Speaker 2: do your job. Like, it's just it's really weird. It

224
00:12:57,800 --> 00:13:00,520
Speaker 2: it's really weird. The more of these we see, the

225
00:13:00,520 --> 00:13:03,160
Speaker 2: weirder it gets, Like it says on the website. Now

226
00:13:03,240 --> 00:13:08,720
Speaker 2: and video is opening in the Agentic Frontier with Sorry,

227
00:13:08,760 --> 00:13:11,760
Speaker 2: and Vidia launches Veros CPU's purpose built for Agentic. Ai'm

228
00:13:11,800 --> 00:13:15,320
Speaker 2: not sure that that's really true considering GPUs run it. Yeah,

229
00:13:15,520 --> 00:13:18,679
Speaker 2: large language models and something about Vera Rubin and Agentic

230
00:13:18,720 --> 00:13:22,000
Speaker 2: as well. It's just it feels like mad lips at

231
00:13:22,000 --> 00:13:22,360
Speaker 2: this point.

232
00:13:22,440 --> 00:13:26,240
Speaker 1: I mean together going to old gtcs, like some of

233
00:13:26,240 --> 00:13:30,960
Speaker 1: the really early ones and announcements, the exciting announcements where

234
00:13:31,040 --> 00:13:33,640
Speaker 1: you know they'd have the shield like handheld gaming device,

235
00:13:33,760 --> 00:13:35,960
Speaker 1: or they'd have the Shield TV if you prefer that.

236
00:13:37,000 --> 00:13:40,160
Speaker 1: They sometimes some GPUs, sometimes it would be Quadro or

237
00:13:40,600 --> 00:13:45,199
Speaker 1: or professional class have a fun gaming class. Yeah, and

238
00:13:45,200 --> 00:13:47,480
Speaker 1: it was pretty interesting and they had servers too a

239
00:13:47,520 --> 00:13:49,520
Speaker 1: lot of the time, and they were also interested in

240
00:13:49,600 --> 00:13:53,000
Speaker 1: It wasn't pitched the same way. But the biggest thing

241
00:13:53,040 --> 00:13:55,040
Speaker 1: about it, and I actually really did like the show,

242
00:13:55,679 --> 00:13:58,000
Speaker 1: was there are a lot of panels where you could

243
00:13:58,000 --> 00:14:01,080
Speaker 1: do really technical discussions, and they still have those, but

244
00:14:02,000 --> 00:14:05,760
Speaker 1: it's just completely transformed into now it's the AI Show

245
00:14:05,800 --> 00:14:07,920
Speaker 1: and there's like almost nothing else there. So we don't

246
00:14:07,960 --> 00:14:12,400
Speaker 1: even bother going anymore. Total company shift. I mean they

247
00:14:12,400 --> 00:14:15,360
Speaker 1: are they're really all in on this. I speaking of

248
00:14:15,600 --> 00:14:17,640
Speaker 1: things that Jensen though has studies all in on. I

249
00:14:17,679 --> 00:14:19,280
Speaker 1: don't know if you even want to get into this one,

250
00:14:19,320 --> 00:14:21,960
Speaker 1: but he made the comment in the in the all

251
00:14:22,000 --> 00:14:26,640
Speaker 1: in I think it was podcast about AI uses in

252
00:14:26,680 --> 00:14:29,800
Speaker 1: the Middle East given the current situation.

253
00:14:29,920 --> 00:14:33,680
Speaker 2: Oh god, what what do you what? Why is Jensen Jensen?

254
00:14:33,720 --> 00:14:36,640
Speaker 2: You run a you run a GPU company? Come on, man.

255
00:14:37,320 --> 00:14:40,880
Speaker 1: He said that he believes there's a paraphrase and he

256
00:14:40,920 --> 00:14:44,800
Speaker 1: believes there's a reason for the war with Iran and

257
00:14:45,840 --> 00:14:49,040
Speaker 1: talked about potentially use cases in the Middle East, and

258
00:14:49,120 --> 00:14:51,320
Speaker 1: I don't really he said. He did say I'm one

259
00:14:51,360 --> 00:14:53,640
Speaker 1: hundred percent in on that when he was talking about

260
00:14:53,640 --> 00:14:56,440
Speaker 1: the subject, which is just like, how did we get

261
00:14:56,440 --> 00:15:01,320
Speaker 1: from You're on stage talking about like doom and quake

262
00:15:01,760 --> 00:15:05,400
Speaker 1: and making jokes about crisis. You know, they like judging

263
00:15:06,080 --> 00:15:10,600
Speaker 1: the reasons for various wars. I don't know. You just

264
00:15:10,680 --> 00:15:14,040
Speaker 1: you wonder like they've been angling for this military industrial

265
00:15:14,280 --> 00:15:16,040
Speaker 1: side for a while now, and that to me, it

266
00:15:16,080 --> 00:15:17,760
Speaker 1: seems kind of like more of a signal to the

267
00:15:17,840 --> 00:15:20,960
Speaker 1: US government than anything. I'm like, hey, we want to

268
00:15:20,960 --> 00:15:22,840
Speaker 1: sell you stuff, But I just.

269
00:15:23,120 --> 00:15:25,960
Speaker 2: I think it just feels that it's kind of my

270
00:15:26,000 --> 00:15:27,680
Speaker 2: thing to say. But it's the end of the hypergrowth

271
00:15:27,720 --> 00:15:30,360
Speaker 2: era in the sense that it's just everyone going like, oh,

272
00:15:30,440 --> 00:15:32,880
Speaker 2: what do you you want to do war with the GPUs.

273
00:15:32,960 --> 00:15:35,360
Speaker 2: I guess you want to, Yeah, what do you think

274
00:15:35,400 --> 00:15:37,440
Speaker 2: if the do you want to blow stuff up? It's

275
00:15:37,440 --> 00:15:39,360
Speaker 2: not really what we do well, I mean, actually I

276
00:15:39,400 --> 00:15:43,160
Speaker 2: take that back. Doesn't in video also already involve itself

277
00:15:43,480 --> 00:15:46,600
Speaker 2: with what's it called the robot platform.

278
00:15:47,600 --> 00:15:50,800
Speaker 1: They're definitely involved with Palette here, which is involved in war.

279
00:15:52,320 --> 00:15:56,440
Speaker 2: It's not Isaac, there's they have a specific Jetson Oh ye,

280
00:15:56,600 --> 00:16:00,560
Speaker 2: jets Jetson's already involved in I can't say specific leagues

281
00:16:00,640 --> 00:16:02,840
Speaker 2: truly done, but I swear to god I heard it

282
00:16:02,880 --> 00:16:05,360
Speaker 2: was involved in some sort of war related censors that

283
00:16:05,400 --> 00:16:06,080
Speaker 2: I'm not.

284
00:16:05,840 --> 00:16:09,160
Speaker 1: Sure if I should I shouldn't say it, but yeah,

285
00:16:09,280 --> 00:16:13,760
Speaker 1: Jadson's we have photographs of things that they are in

286
00:16:13,960 --> 00:16:20,960
Speaker 1: that have been used in uh in Ukraine. So I

287
00:16:21,000 --> 00:16:22,520
Speaker 1: don't know if I couldn't say any more of that.

288
00:16:22,520 --> 00:16:24,960
Speaker 1: That was a conversation with some congress people earlier.

289
00:16:25,440 --> 00:16:28,440
Speaker 2: Yeah, that's the thing though, It's like they talk about

290
00:16:28,520 --> 00:16:30,960
Speaker 2: the Nemo klor and they talk about doing war stuff,

291
00:16:30,960 --> 00:16:32,920
Speaker 2: and they talk about all these things when the only

292
00:16:33,480 --> 00:16:36,160
Speaker 2: ninety percent of their revenues from these fucking GPUs. It's

293
00:16:36,200 --> 00:16:39,600
Speaker 2: not even it's not even a case of like, oh,

294
00:16:39,640 --> 00:16:42,800
Speaker 2: they're making like fifty percent of revenue all pretty much

295
00:16:42,800 --> 00:16:45,680
Speaker 2: all of their revenue comes from the GPUs. And just

296
00:16:45,720 --> 00:16:48,840
Speaker 2: before we got on, I have I've been trying to

297
00:16:48,880 --> 00:16:51,600
Speaker 2: answer a question of how many data centers have actually

298
00:16:51,680 --> 00:16:54,440
Speaker 2: been built in the last year. It is a very

299
00:16:54,440 --> 00:16:58,520
Speaker 2: difficult question, but from what I can tell based on

300
00:16:59,040 --> 00:17:02,479
Speaker 2: like there's like four or five gigawats might have gone online,

301
00:17:02,720 --> 00:17:06,919
Speaker 2: which means we're running at about it takes about a

302
00:17:07,119 --> 00:17:11,760
Speaker 2: year may to install like half a year's worth of

303
00:17:11,800 --> 00:17:16,200
Speaker 2: GPU seales. Oh wow, Okay, it's it's really I don't

304
00:17:16,240 --> 00:17:19,719
Speaker 2: think people realize how slow this is. But I just

305
00:17:19,760 --> 00:17:22,560
Speaker 2: can't work out at this point why anyone's buying these

306
00:17:22,560 --> 00:17:26,280
Speaker 2: GPUs anymore. Like it's just just as if they stop

307
00:17:26,359 --> 00:17:28,920
Speaker 2: doing it, it's not the bus from speed their company

308
00:17:28,960 --> 00:17:29,560
Speaker 2: or shut down.

309
00:17:29,560 --> 00:17:32,200
Speaker 1: Like yeah, I mean it might be like that. There

310
00:17:32,280 --> 00:17:35,720
Speaker 1: might be a chain reaction, you know, of just.

311
00:17:37,040 --> 00:17:41,360
Speaker 2: It's just so bizarre because Metaverse was killed last week.

312
00:17:41,400 --> 00:17:43,600
Speaker 2: They killed it. They shot it with a gun. Horizon

313
00:17:43,680 --> 00:17:46,199
Speaker 2: Worlds will no longer you can. But then they were like, oh,

314
00:17:46,240 --> 00:17:48,240
Speaker 2: we're going to keep it running kind of, but it's

315
00:17:48,280 --> 00:17:49,119
Speaker 2: not clear what that.

316
00:17:49,240 --> 00:17:50,639
Speaker 1: Was stupid the beginning.

317
00:17:50,680 --> 00:17:52,520
Speaker 2: It's so it's so cool, it's just.

318
00:17:52,440 --> 00:17:55,000
Speaker 1: A shitty video game, Like it's not even you could

319
00:17:55,040 --> 00:17:57,240
Speaker 1: literally just play a video game and it would be

320
00:17:57,040 --> 00:17:57,520
Speaker 1: the better.

321
00:17:58,160 --> 00:18:00,560
Speaker 2: It's just But the great thing is they no longer

322
00:18:00,600 --> 00:18:03,440
Speaker 2: bringing it to Horizon Worlds to VR, but they are

323
00:18:03,480 --> 00:18:06,200
Speaker 2: also bringing it back for an indeterminate amount of time

324
00:18:07,000 --> 00:18:10,000
Speaker 2: I I just I don't think the tech industry knows

325
00:18:10,040 --> 00:18:11,919
Speaker 2: what it's doing ever anymore. I think that they just

326
00:18:12,000 --> 00:18:13,960
Speaker 2: wake up one then they're like, what what do we

327
00:18:14,320 --> 00:18:17,080
Speaker 2: What do we do today? What we do? We fucking what?

328
00:18:17,320 --> 00:18:19,439
Speaker 2: We buy? More? GPUs that? What do you like?

329
00:18:19,520 --> 00:18:19,600
Speaker 3: That?

330
00:18:32,280 --> 00:18:35,160
Speaker 1: It's validation seeking, right, It's almost like the whole industry

331
00:18:35,200 --> 00:18:39,880
Speaker 1: is seeking validation. And I think some of that may

332
00:18:40,400 --> 00:18:43,360
Speaker 1: mirror what we saw happen to Intel for for multiple

333
00:18:43,359 --> 00:18:48,879
Speaker 1: CEOs running where it's uh, they eventually moved from engineering

334
00:18:49,000 --> 00:18:55,680
Speaker 1: focused CEOs to accounting focused CEOs and marketing in one instance,

335
00:18:55,920 --> 00:18:57,560
Speaker 1: you know, and that didn't work out very well for them.

336
00:18:57,840 --> 00:19:01,560
Speaker 1: And I don't know, I wonder if maybe there's just

337
00:19:01,640 --> 00:19:05,439
Speaker 1: so much money in everything now that it's become a

338
00:19:05,480 --> 00:19:09,040
Speaker 1: game about and it's like cost engineering or it's stock

339
00:19:09,280 --> 00:19:14,000
Speaker 1: engineering or whatever rather than engineering engineering. I think maybe

340
00:19:14,000 --> 00:19:16,239
Speaker 1: that's some of where we're seeing that well.

341
00:19:16,280 --> 00:19:19,280
Speaker 2: I think we're came out just before we we got

342
00:19:19,320 --> 00:19:22,359
Speaker 2: on as well. We're finally getting Enron shit though, because

343
00:19:22,400 --> 00:19:24,439
Speaker 2: open ai is trying to offer they're trying to do

344
00:19:24,520 --> 00:19:30,040
Speaker 2: this spurious joint venture thing with private equity firms and

345
00:19:30,080 --> 00:19:32,439
Speaker 2: they're like, well, what we'll do is we'll raise money

346
00:19:32,680 --> 00:19:35,280
Speaker 2: and then the private equity firm will pay us in

347
00:19:35,400 --> 00:19:41,440
Speaker 2: advance to install chat GPT across their portfolio companies. Right,

348
00:19:41,680 --> 00:19:45,720
Speaker 2: and as part of this deal, open Ai is guaranteeing

349
00:19:45,720 --> 00:19:50,120
Speaker 2: a minimum minimum return of seventeen point five percent. Now

350
00:19:50,359 --> 00:19:53,480
Speaker 2: do you maybe think that's a good question? And also

351
00:19:54,080 --> 00:19:59,640
Speaker 2: a seventeen zero point five percent return on what I've

352
00:19:59,680 --> 00:20:02,080
Speaker 2: read the routter's opticle four or five times, like kind

353
00:20:02,080 --> 00:20:05,439
Speaker 2: of work it out? I just this whole thing feels

354
00:20:05,480 --> 00:20:08,160
Speaker 2: like an exploitation of ignorance. It's just like how many

355
00:20:08,320 --> 00:20:11,280
Speaker 2: reports actually read the emails they get or when they

356
00:20:11,280 --> 00:20:13,800
Speaker 2: write up a story, how hard do they think about it?

357
00:20:13,960 --> 00:20:17,600
Speaker 1: I had I had a reporter from another from a

358
00:20:17,640 --> 00:20:23,639
Speaker 1: business focused publication email and asked to talk about and

359
00:20:23,840 --> 00:20:28,120
Speaker 1: video And basically the reporter was interested in learning from

360
00:20:28,119 --> 00:20:31,080
Speaker 1: our perspective, why is it that gamers and why is

361
00:20:31,119 --> 00:20:35,360
Speaker 1: it that consumers are so mad at nvideo? And the

362
00:20:35,440 --> 00:20:42,560
Speaker 1: first question that was asked of me was, uh, did

363
00:20:42,760 --> 00:20:45,920
Speaker 1: when did gamers for like, did did gamers notice or

364
00:20:45,920 --> 00:20:48,600
Speaker 1: were they happy about Nvidia stock going up? When it

365
00:20:48,640 --> 00:20:50,560
Speaker 1: started to go up? And I had to start It's

366
00:20:50,600 --> 00:20:54,440
Speaker 1: like let's start from scratch. The consumers ten years ago

367
00:20:54,480 --> 00:20:57,560
Speaker 1: weren't paying attention to Nvidio stock. You know, they wanted

368
00:20:57,560 --> 00:21:00,679
Speaker 1: to buy gps to play video games. Like people weren't.

369
00:21:01,320 --> 00:21:03,800
Speaker 1: You weren't interested in the GPU for the stock price.

370
00:21:03,960 --> 00:21:06,440
Speaker 2: I don't get stock when you buy a graphics card.

371
00:21:06,840 --> 00:21:08,360
Speaker 2: You don't get that.

372
00:21:07,880 --> 00:21:09,760
Speaker 1: That is a good idea. Though, maybe that's how you

373
00:21:09,840 --> 00:21:10,480
Speaker 1: can do next.

374
00:21:11,160 --> 00:21:13,720
Speaker 2: Yeah, and they're just like, that's how they do stock buybacks.

375
00:21:13,760 --> 00:21:15,800
Speaker 2: But each time they sell a GPU, they buy back.

376
00:21:16,480 --> 00:21:18,600
Speaker 2: It's just I love it. But that's I actually think

377
00:21:18,640 --> 00:21:21,920
Speaker 2: that that question is really indicative of the media problem

378
00:21:21,920 --> 00:21:24,640
Speaker 2: with in video, where it's just like, oh, in video, right,

379
00:21:24,800 --> 00:21:27,080
Speaker 2: so every single person who's ever used in video cares

380
00:21:27,080 --> 00:21:31,200
Speaker 2: about the stock, right, That's that's not true, Like most

381
00:21:31,240 --> 00:21:33,399
Speaker 2: people should not think about the stock market.

382
00:21:33,480 --> 00:21:36,960
Speaker 1: I would say the I mean, for sure, I don't

383
00:21:37,000 --> 00:21:40,960
Speaker 1: know exactly, but at least going back to the earlier

384
00:21:41,040 --> 00:21:43,480
Speaker 1: days for end video, I can't say their stock price

385
00:21:43,520 --> 00:21:47,719
Speaker 1: ever really came up in any discussions like in technical news,

386
00:21:47,800 --> 00:21:51,000
Speaker 1: Like it definitely came up in news in general, but

387
00:21:51,440 --> 00:21:53,760
Speaker 1: in our space, you know, it never came up.

388
00:21:53,800 --> 00:21:55,800
Speaker 2: Why would it come up? Why would it come up.

389
00:21:55,960 --> 00:21:59,320
Speaker 2: You are you are covering hardware, You cover hardware. Why

390
00:21:59,320 --> 00:22:00,399
Speaker 2: would the stock come up?

391
00:22:00,560 --> 00:22:00,800
Speaker 1: Yeah?

392
00:22:01,320 --> 00:22:05,240
Speaker 2: Why? Why? And I think it's also because, and I

393
00:22:05,240 --> 00:22:07,359
Speaker 2: mean this with no offense to the reporters that listen,

394
00:22:07,520 --> 00:22:09,840
Speaker 2: I'm sorry, but these people did not know who in

395
00:22:09,920 --> 00:22:12,040
Speaker 2: video was four years ago. They had no idea. They

396
00:22:12,320 --> 00:22:14,440
Speaker 2: did not they had no idea. They were not thinking

397
00:22:14,480 --> 00:22:17,040
Speaker 2: about in video they had they did not think about.

398
00:22:17,200 --> 00:22:19,679
Speaker 2: It's kind of like how a much larger version of

399
00:22:19,720 --> 00:22:23,760
Speaker 2: how I think. I now see seventy five different guys

400
00:22:23,760 --> 00:22:26,160
Speaker 2: who are now an expert on the straight off Umus

401
00:22:27,359 --> 00:22:31,600
Speaker 2: despite learning what it was around two weeks ago. Like

402
00:22:31,840 --> 00:22:33,960
Speaker 2: it's that I'm now, Oh, look at the straight and

403
00:22:34,320 --> 00:22:36,800
Speaker 2: did you see the venture capitalist whose solution to it

404
00:22:36,840 --> 00:22:41,200
Speaker 2: was to just build a big road. It's just there's

405
00:22:41,280 --> 00:22:44,760
Speaker 2: this little like blob, like the kind of the the

406
00:22:44,840 --> 00:22:45,720
Speaker 2: tip of it to.

407
00:22:45,800 --> 00:22:47,520
Speaker 1: See understand how health?

408
00:22:47,680 --> 00:22:52,240
Speaker 2: No, No, it's fine. You just draw a giant road

409
00:22:52,320 --> 00:22:54,920
Speaker 2: from like the coast of Iman to the coast of

410
00:22:56,000 --> 00:22:58,840
Speaker 2: the UAE and you also this just.

411
00:22:58,720 --> 00:23:01,760
Speaker 1: Then, structure infrastructure is famously quick to build.

412
00:23:01,880 --> 00:23:05,919
Speaker 2: Exactly, especially during a massive assault from a large a

413
00:23:06,000 --> 00:23:09,400
Speaker 2: nation the size of Alaska. Yeah, but on top of that,

414
00:23:10,280 --> 00:23:14,400
Speaker 2: I assume he has some way around the giant rocks

415
00:23:14,800 --> 00:23:17,840
Speaker 2: either side, and also a way for the boats to

416
00:23:17,880 --> 00:23:21,040
Speaker 2: get in. It's just that easy. But I genuinely think

417
00:23:21,080 --> 00:23:23,160
Speaker 2: that that's the era though, because people are like, yeah,

418
00:23:23,200 --> 00:23:26,040
Speaker 2: you know, there's like two hundred and forty gigawatts of

419
00:23:26,640 --> 00:23:30,240
Speaker 2: data center's being built right now, and it's great. Actually

420
00:23:30,280 --> 00:23:33,960
Speaker 2: there's only about five gigawatts in America that's actually under construction.

421
00:23:34,840 --> 00:23:37,480
Speaker 1: But you know, easy because if you look at maps

422
00:23:37,520 --> 00:23:40,920
Speaker 1: of like announced or planned or hopeful data centers, there's

423
00:23:40,960 --> 00:23:42,240
Speaker 1: thousands of them in the US.

424
00:23:42,280 --> 00:23:45,520
Speaker 2: Yes, you know, yeah there's oh god, I had it.

425
00:23:45,560 --> 00:23:46,919
Speaker 2: I was just working on it before it came on.

426
00:23:47,000 --> 00:23:49,800
Speaker 2: But it's something like there's two hundred and forty gigawatts,

427
00:23:49,920 --> 00:23:56,199
Speaker 2: but let's see. Yet, it's very very very strange that,

428
00:23:56,520 --> 00:23:58,840
Speaker 2: you know, yeah, there's about five gigawats that are actually

429
00:23:58,880 --> 00:24:02,560
Speaker 2: under construction, despite like sixty or seventy that's allegedly meant.

430
00:24:02,640 --> 00:24:05,199
Speaker 2: There's meant to be like thirteen to fourteen gigawats that

431
00:24:06,280 --> 00:24:09,840
Speaker 2: actually there's meant to be I think fourteen that comes

432
00:24:09,840 --> 00:24:13,359
Speaker 2: on this year. Hmm. From yeah, Sideline, Sorry, I'm gonna

433
00:24:13,359 --> 00:24:14,919
Speaker 2: get it. Right this tunge because I actually found it

434
00:24:14,960 --> 00:24:17,840
Speaker 2: in my notes. I'm sorry everyone. Sixteen gigawats of capacity

435
00:24:17,920 --> 00:24:19,800
Speaker 2: was slated to come online in twenty twenty six across

436
00:24:19,800 --> 00:24:22,399
Speaker 2: one hundred and forty projects, but only five gigawats is

437
00:24:22,400 --> 00:24:27,000
Speaker 2: currently under construction. And that's under construction. That's under construct,

438
00:24:27,040 --> 00:24:29,960
Speaker 2: that's just being built. It doesn't mean they're actually going

439
00:24:30,000 --> 00:24:34,000
Speaker 2: to be built. And the only reason this is happening

440
00:24:34,280 --> 00:24:36,680
Speaker 2: is so that we can keep in video inflated.

441
00:24:37,480 --> 00:24:41,720
Speaker 1: I people still I don't know who they're pulling the

442
00:24:41,720 --> 00:24:45,840
Speaker 1: wool over the eyes of these days, but we always

443
00:24:45,880 --> 00:24:49,120
Speaker 1: reading the following this news of some of the ones

444
00:24:49,160 --> 00:24:52,119
Speaker 1: that were canceled, and you know, from pushback from the

445
00:24:52,160 --> 00:24:56,320
Speaker 1: community and town council hearings and stuff, and it's interested

446
00:24:56,320 --> 00:24:58,600
Speaker 1: in reading the comments where if they're even humans these days,

447
00:24:58,600 --> 00:25:02,240
Speaker 1: I don't know anymore, but so the comments being about, uh,

448
00:25:03,119 --> 00:25:05,840
Speaker 1: why are people proud about turning away jobs? And it's

449
00:25:05,880 --> 00:25:08,240
Speaker 1: just like, do you know how many jobs this like

450
00:25:08,720 --> 00:25:13,000
Speaker 1: million square foot facility would create because it's not a lot.

451
00:25:13,480 --> 00:25:18,520
Speaker 2: And on top of that, even the jobs supposedly created

452
00:25:18,920 --> 00:25:22,520
Speaker 2: by building them, they're all flown in like yeah, they're

453
00:25:22,680 --> 00:25:25,200
Speaker 2: they're not local. It's not like you get local builders.

454
00:25:25,200 --> 00:25:29,199
Speaker 2: Well it's start things well, Stargate ampline. They've just flown

455
00:25:29,240 --> 00:25:32,280
Speaker 2: in people to just move in to town. So I

456
00:25:32,280 --> 00:25:34,760
Speaker 2: guess like that helps the economy, and then when it

457
00:25:34,840 --> 00:25:37,720
Speaker 2: turns on, which it never will, they'll be like seventy jobs.

458
00:25:38,119 --> 00:25:39,600
Speaker 1: I mean that's the same, right, It's like it's the

459
00:25:39,600 --> 00:25:43,399
Speaker 1: one it turns on where Okay, you get this transient burst, great,

460
00:25:43,560 --> 00:25:47,439
Speaker 1: but this isn't It's not like you're I think the

461
00:25:47,480 --> 00:25:52,080
Speaker 1: branding of data centers as AI factories, which is insane

462
00:25:52,119 --> 00:25:56,679
Speaker 1: by the way, but I think the branding of it

463
00:25:56,680 --> 00:25:59,200
Speaker 1: it's like blue collar washing or something. It's like they

464
00:25:59,280 --> 00:26:04,440
Speaker 1: they they're trying to make it sound like a I

465
00:26:04,480 --> 00:26:07,240
Speaker 1: don't know, like like the grit and the hard work

466
00:26:07,280 --> 00:26:10,520
Speaker 1: and like the manpower you get out of a traditional factory.

467
00:26:10,680 --> 00:26:14,240
Speaker 1: Except it's a bunch of computers in a room, yeah,

468
00:26:14,280 --> 00:26:17,280
Speaker 1: you know, and there's like fifteen guys in the on

469
00:26:17,359 --> 00:26:19,600
Speaker 1: the floor who are just keeping them turned on, which

470
00:26:19,680 --> 00:26:22,080
Speaker 1: is a real job and can be an important job.

471
00:26:22,280 --> 00:26:24,240
Speaker 1: But it's not a factory.

472
00:26:24,680 --> 00:26:28,000
Speaker 2: Yes, it's not like bringing thousands of factory jobs from

473
00:26:28,040 --> 00:26:31,240
Speaker 2: the bygone era, Like we're not doing like we're not

474
00:26:31,320 --> 00:26:34,440
Speaker 2: going to repeal NAFTA, so we're not actually going to

475
00:26:34,480 --> 00:26:38,119
Speaker 2: fix the problem here. But my favorite, my most favorite

476
00:26:38,240 --> 00:26:41,679
Speaker 2: of all recent data centers are not being built story

477
00:26:41,840 --> 00:26:45,360
Speaker 2: is from Sachin Kati, who is head of Infrastructure Open AI,

478
00:26:45,880 --> 00:26:49,040
Speaker 2: March sixth, twenty twenty six. Construction is underware our site

479
00:26:49,040 --> 00:26:52,440
Speaker 2: in Port Washington, Wisconsin. And there is just a single

480
00:26:52,480 --> 00:26:53,359
Speaker 2: steel beam.

481
00:26:54,040 --> 00:26:57,240
Speaker 1: That was just one beam. I saw your tweet that

482
00:26:57,359 --> 00:27:01,520
Speaker 1: was like probably my favorite tweet a lot time, just.

483
00:27:01,440 --> 00:27:04,520
Speaker 2: The single just and at this rate, great, this will

484
00:27:04,560 --> 00:27:06,600
Speaker 2: be done in like twenty twenty nine.

485
00:27:08,160 --> 00:27:11,160
Speaker 1: Maybe the beam was almost entirely in the ground.

486
00:27:11,720 --> 00:27:14,800
Speaker 2: Yes, And it's like there's still there's like four guys,

487
00:27:14,840 --> 00:27:17,680
Speaker 2: like three guys that sitting kind of standing around it

488
00:27:17,800 --> 00:27:21,240
Speaker 2: like poking it, and one guy walking towards it. It's

489
00:27:21,320 --> 00:27:24,520
Speaker 2: just it's just really what's great? But they only do

490
00:27:24,600 --> 00:27:26,679
Speaker 2: this because none No, I don't think I know I

491
00:27:26,720 --> 00:27:30,159
Speaker 2: sound conspiratorial, but it's like the mainstream media just doesn't

492
00:27:30,160 --> 00:27:33,880
Speaker 2: say anything. Like to naturally move into my favorite story,

493
00:27:34,119 --> 00:27:38,320
Speaker 2: super Micro, Yes with a Wale Lear who so to

494
00:27:38,400 --> 00:27:41,720
Speaker 2: explain for the listeners. Super Micro is an AI server company.

495
00:27:42,240 --> 00:27:45,600
Speaker 2: They two years ago had a massive accounting scandal where

496
00:27:45,600 --> 00:27:48,760
Speaker 2: a bunch of people resigned. I forget exactly what happened

497
00:27:48,760 --> 00:27:50,760
Speaker 2: in the scandal, but like they had to restay earnings,

498
00:27:50,760 --> 00:27:53,280
Speaker 2: they had to delay earnings. But then things got back

499
00:27:53,280 --> 00:27:57,600
Speaker 2: on track late twenty twenty four, twenty twenty, Sorry it's

500
00:27:57,600 --> 00:28:00,919
Speaker 2: twenty eighteen when the scandal was. But twenty twenty four,

501
00:28:01,000 --> 00:28:03,200
Speaker 2: twenty five, they got back on track. They were selling

502
00:28:03,240 --> 00:28:06,200
Speaker 2: GPUs to Crusoe, they were selling GPUs to core Wave,

503
00:28:06,520 --> 00:28:09,960
Speaker 2: and then very recently there the Apartment of Justice arrested

504
00:28:10,040 --> 00:28:14,800
Speaker 2: three different guys, including co founder Wally yet Lao, for

505
00:28:15,440 --> 00:28:18,040
Speaker 2: shipping like hundreds of millions of dollars of GPUs to

506
00:28:18,119 --> 00:28:24,320
Speaker 2: China and like changing the serial numbers using a hairdryer. Yeah,

507
00:28:24,320 --> 00:28:25,920
Speaker 2: which I fucking love it.

508
00:28:26,000 --> 00:28:28,680
Speaker 1: They're removing the serial numbers and the stickers and then

509
00:28:28,760 --> 00:28:32,119
Speaker 1: using a middle in logistics company to basically repackage and

510
00:28:32,160 --> 00:28:32,920
Speaker 1: forward them.

511
00:28:33,520 --> 00:28:38,360
Speaker 2: And this story, this story has just kind of disappeared already. Yeah,

512
00:28:39,160 --> 00:28:42,120
Speaker 2: there was a picture where Jensen Hwang is standing next

513
00:28:42,160 --> 00:28:45,880
Speaker 2: to co founder Charles Lang of super Micro, just stanning.

514
00:28:45,560 --> 00:28:49,280
Speaker 1: My personal opinion and this is an opinion, but okay,

515
00:28:49,480 --> 00:28:53,040
Speaker 1: my opinion is that there is no way that Nvideo

516
00:28:53,080 --> 00:28:56,240
Speaker 1: couldn't have known this was happening. Yeah, I just think

517
00:28:56,560 --> 00:29:00,080
Speaker 1: it's like actually impossible that they were not aware of

518
00:29:00,200 --> 00:29:01,120
Speaker 1: GPU smuggling.

519
00:29:01,200 --> 00:29:04,840
Speaker 2: But wouldn't they don't these GPUs have some mechanism of

520
00:29:04,880 --> 00:29:05,480
Speaker 2: phoning home?

521
00:29:05,680 --> 00:29:07,719
Speaker 1: Oh for sure they can be. They can be identified

522
00:29:07,760 --> 00:29:10,400
Speaker 1: through the internet one hundred percent. I mean, yeah, they have.

523
00:29:10,680 --> 00:29:15,000
Speaker 1: The firmware has identifying information in it for the GPUs.

524
00:29:15,800 --> 00:29:19,200
Speaker 1: You don't need the serial number on the sticker to

525
00:29:19,480 --> 00:29:21,200
Speaker 1: know what it is. You know, you don't have to

526
00:29:21,200 --> 00:29:23,800
Speaker 1: physically see it to know what it is. And so yeah,

527
00:29:23,880 --> 00:29:26,000
Speaker 1: if this is like connecting to some kind of server

528
00:29:26,160 --> 00:29:29,720
Speaker 1: somewhere or whatever it may be doing, if in any

529
00:29:29,760 --> 00:29:31,880
Speaker 1: way that's linked back to end Video, they would know

530
00:29:31,920 --> 00:29:35,680
Speaker 1: about it. If there's ever a service request, I would

531
00:29:35,720 --> 00:29:38,160
Speaker 1: assume at some point someone figures out and maybe it's

532
00:29:38,200 --> 00:29:43,040
Speaker 1: a okay, well kind of you know, blind eye approach,

533
00:29:43,160 --> 00:29:47,800
Speaker 1: But it's just there's I don't know. I really think

534
00:29:47,840 --> 00:29:51,840
Speaker 1: there's no way that they were ignorant to this because,

535
00:29:52,040 --> 00:29:54,200
Speaker 1: to quote one of the guys we spoke with when

536
00:29:54,200 --> 00:29:57,160
Speaker 1: we did the Black Market GPU Smuggling documentary last year,

537
00:29:58,400 --> 00:30:01,200
Speaker 1: the professor of a in Hong Kong. We spoke with.

538
00:30:01,480 --> 00:30:03,400
Speaker 1: I asked him, I was like, do you think Nyvidyo knows?

539
00:30:03,480 --> 00:30:06,200
Speaker 1: And yeah. His reaction was, well, how could they not?

540
00:30:06,680 --> 00:30:08,960
Speaker 1: These are very expensive jeep us. You would think you

541
00:30:08,960 --> 00:30:11,720
Speaker 1: would track them all extremely carefully.

542
00:30:12,600 --> 00:30:15,360
Speaker 2: Yeah, I just And also it's the co founder of

543
00:30:15,400 --> 00:30:18,440
Speaker 2: super Micro. And just to be clear, Wally Lear, the

544
00:30:18,520 --> 00:30:22,960
Speaker 2: co founder, resigned in twenty eighteen, rejoined as a consultant

545
00:30:23,040 --> 00:30:25,160
Speaker 2: a few years later, and then was just added back

546
00:30:25,200 --> 00:30:28,160
Speaker 2: to the board. Yeah, and now he is in jail.

547
00:30:28,880 --> 00:30:31,440
Speaker 2: And you're telling me that Charles Lang had no idea,

548
00:30:31,840 --> 00:30:35,560
Speaker 2: no idea, what, no one an inventor, where where they

549
00:30:35,560 --> 00:30:38,560
Speaker 2: think they were going? But this is like, this is

550
00:30:38,720 --> 00:30:43,800
Speaker 2: yet another story that is just ignored. And I'm trying

551
00:30:43,800 --> 00:30:46,560
Speaker 2: to work out if it is a journalistic competence issue

552
00:30:47,120 --> 00:30:50,400
Speaker 2: or whether it's just a don't don't fuck without out

553
00:30:50,440 --> 00:30:51,560
Speaker 2: Disneyland problem.

554
00:30:51,680 --> 00:30:55,640
Speaker 1: I think there's yeah much there there. So, first of all,

555
00:30:55,720 --> 00:30:58,400
Speaker 1: Land Video has a lot of money in different media publications,

556
00:30:58,440 --> 00:31:01,320
Speaker 1: and then also the ones that are how do you mean, yeah,

557
00:31:01,320 --> 00:31:05,080
Speaker 1: in the media publications that are involved in like stock coverage,

558
00:31:05,120 --> 00:31:07,680
Speaker 1: they're all going to be biased towards protecting en Video

559
00:31:07,680 --> 00:31:11,040
Speaker 1: In someway or another for the most part. But secondly,

560
00:31:11,080 --> 00:31:14,920
Speaker 1: also I do think there's probably an issue of what

561
00:31:15,120 --> 00:31:20,080
Speaker 1: a super micro for a lot of the reporters. And yeah, I.

562
00:31:20,120 --> 00:31:24,800
Speaker 2: Just there's a picture of Wallie lear was at he

563
00:31:24,880 --> 00:31:27,280
Speaker 2: was actually at GtC. There's a picture of him with

564
00:31:27,320 --> 00:31:30,280
Speaker 2: an ice luge. There's a picture of him standing three

565
00:31:30,280 --> 00:31:35,000
Speaker 2: people over from Jensen Huang. There's you can like Lambda,

566
00:31:35,080 --> 00:31:39,280
Speaker 2: an AI compute company. He was. He was commenting on

567
00:31:39,320 --> 00:31:43,040
Speaker 2: their LinkedIn very recently, being like super congress all. He's

568
00:31:43,160 --> 00:31:47,160
Speaker 2: like clearly a dorky old man because he's like super congratulations,

569
00:31:47,200 --> 00:31:50,120
Speaker 2: super great. I kind of I kind of love that,

570
00:31:50,200 --> 00:31:52,400
Speaker 2: and I kind of loved the text he sent where

571
00:31:52,400 --> 00:31:54,440
Speaker 2: somebody basically said you're going to jail and he just

572
00:31:54,440 --> 00:31:57,680
Speaker 2: was spotted with three crying. Honestly, it was.

573
00:31:57,720 --> 00:31:58,720
Speaker 1: Sad, but it was fine.

574
00:31:58,880 --> 00:32:03,200
Speaker 2: Could be if I would do the same thing, I

575
00:32:03,200 --> 00:32:05,640
Speaker 2: would be responding the same way if I was going

576
00:32:05,680 --> 00:32:09,280
Speaker 2: to jail for like the most obvious crime. But it's

577
00:32:09,360 --> 00:32:13,800
Speaker 2: so weird, like this super micro is the backbone of

578
00:32:13,840 --> 00:32:14,640
Speaker 2: coal Wave like that.

579
00:32:15,440 --> 00:32:20,000
Speaker 1: Also wonder if so some behind the scenes is after

580
00:32:20,040 --> 00:32:23,760
Speaker 1: our black Market documentary last year, I went to Washington

581
00:32:23,840 --> 00:32:28,240
Speaker 1: d C. And met with a number of congressional staff

582
00:32:28,280 --> 00:32:33,560
Speaker 1: on one of the committees there, and it was they

583
00:32:35,000 --> 00:32:37,240
Speaker 1: One of the things they told me was that they

584
00:32:37,280 --> 00:32:40,680
Speaker 1: had some stuff in the works. There was some talk about,

585
00:32:40,680 --> 00:32:44,280
Speaker 1: you know, maybe testifying or something, but they had stuff

586
00:32:44,320 --> 00:32:46,680
Speaker 1: in the works and they were hoping they would materialize

587
00:32:46,720 --> 00:32:48,840
Speaker 1: earlier this year. I didn't know what that was at

588
00:32:48,840 --> 00:32:51,080
Speaker 1: the time, but I know they said it was related

589
00:32:51,120 --> 00:32:53,080
Speaker 1: to the GP smuggling. They had a bunch of questions

590
00:32:53,120 --> 00:32:56,680
Speaker 1: about it and how it works and whatever, and I

591
00:32:56,720 --> 00:32:59,360
Speaker 1: think this is probably what they were working on. I

592
00:32:59,360 --> 00:33:02,400
Speaker 1: think it was probably only the super Micro keys, I guess.

593
00:33:02,480 --> 00:33:05,600
Speaker 2: But just the fact that super Micro is just walking around,

594
00:33:05,640 --> 00:33:08,720
Speaker 2: still doing business and they weren't named in the indictment.

595
00:33:09,280 --> 00:33:11,920
Speaker 1: Yeah, it's they weren't a defendant, right, it.

596
00:33:11,920 --> 00:33:15,840
Speaker 2: Was the three ye Yeah, And it's just I don't

597
00:33:15,880 --> 00:33:18,800
Speaker 2: know that doesn't see it doesn't seem very likely that

598
00:33:18,840 --> 00:33:22,440
Speaker 2: nobody knew. But you know, it was just a few

599
00:33:22,480 --> 00:33:26,480
Speaker 2: bad apples, right, just the co founder of the company. Yeah,

600
00:33:26,600 --> 00:33:30,400
Speaker 2: just one guy. Couldn't be I just feel like by

601
00:33:30,400 --> 00:33:31,880
Speaker 2: the end of this, we're going to have a few

602
00:33:31,880 --> 00:33:35,840
Speaker 2: of those. I don't think you've got everything that you

603
00:33:35,840 --> 00:33:38,600
Speaker 2: could possibly want from a scam For a scammer, you've

604
00:33:38,640 --> 00:33:41,440
Speaker 2: got a vague technology that could do everything but doesn't

605
00:33:41,480 --> 00:33:44,160
Speaker 2: really have to do anything, and a shit ton of construction.

606
00:33:44,760 --> 00:33:48,160
Speaker 1: Just an absolute awes funny point on the construction, it's

607
00:33:48,200 --> 00:33:49,800
Speaker 1: it's easy to hide money there.

608
00:33:49,680 --> 00:33:54,000
Speaker 2: And just also let money just like marinate. The one

609
00:33:54,080 --> 00:33:57,440
Speaker 2: thing that I can't find any way of like structuring

610
00:33:57,480 --> 00:33:59,760
Speaker 2: this into an argument I could point out with data,

611
00:33:59,800 --> 00:34:02,640
Speaker 2: but well, I've never seen a building project come in

612
00:34:02,720 --> 00:34:06,800
Speaker 2: under budget, not once in my life. And you're telling

613
00:34:06,880 --> 00:34:11,400
Speaker 2: me none of these companies need follow on funding. Yeah, none.

614
00:34:12,719 --> 00:34:17,160
Speaker 1: I think the I think the construction alone is I

615
00:34:17,160 --> 00:34:20,560
Speaker 1: don't know, it's it's all part of this interesting like

616
00:34:20,600 --> 00:34:25,120
Speaker 1: the meme that's gone around of buying gps that don't

617
00:34:25,120 --> 00:34:27,600
Speaker 1: exist yet to put in data centers that aren't built,

618
00:34:27,680 --> 00:34:31,720
Speaker 1: you know, or it's yeah, the amount of promise, especially

619
00:34:31,800 --> 00:34:37,720
Speaker 1: open AI versus actualized is there's a huge disparity there.

620
00:34:38,520 --> 00:34:41,240
Speaker 2: My favorite thing is them claiming that the more compute

621
00:34:41,239 --> 00:34:44,560
Speaker 2: they get, the more revenue they make, because that doesn't

622
00:34:44,600 --> 00:34:45,399
Speaker 2: make sense at all.

623
00:34:45,640 --> 00:34:47,840
Speaker 1: I mean, Jensen said that in one of the interviews

624
00:34:47,840 --> 00:34:49,560
Speaker 1: where I think he went as high as ten x.

625
00:34:49,600 --> 00:34:51,920
Speaker 1: He was like, if they had ten x were and

626
00:34:51,960 --> 00:34:54,240
Speaker 1: they would have ten x the revenues, Like, I don't

627
00:34:54,239 --> 00:34:54,719
Speaker 1: think so.

628
00:35:08,040 --> 00:35:12,280
Speaker 2: Well. The thing with that I always say is where

629
00:35:12,360 --> 00:35:14,960
Speaker 2: is the current state of affairs if that's the case, Like,

630
00:35:15,680 --> 00:35:19,200
Speaker 2: where are the people that cannot do something because there's

631
00:35:19,200 --> 00:35:22,360
Speaker 2: not enough compute? What is the thing being held back?

632
00:35:22,600 --> 00:35:24,920
Speaker 2: Who is holding it back? Like are they sitting there

633
00:35:24,920 --> 00:35:28,760
Speaker 2: and they're saying when this comes online, X bazillion dollars

634
00:35:28,800 --> 00:35:31,840
Speaker 2: will slosh out of it, Like what is the what

635
00:35:32,040 --> 00:35:34,480
Speaker 2: is not well? Like what's going on?

636
00:35:34,640 --> 00:35:37,520
Speaker 1: In the previous CNBC interview, I think it was where

637
00:35:37,680 --> 00:35:41,439
Speaker 1: Altman and Juan are with Brockman, who is a dollar

638
00:35:41,520 --> 00:35:44,359
Speaker 1: store Jensen, Juan with his leather jackets. They were talking

639
00:35:44,400 --> 00:35:47,360
Speaker 1: about that one hundred billion dollar investment back at the time,

640
00:35:47,760 --> 00:35:53,759
Speaker 1: and Altman, to answer your question, his angle for the

641
00:35:53,800 --> 00:35:58,800
Speaker 1: CNBC or whoever was audience was if you could choose,

642
00:35:58,840 --> 00:36:03,279
Speaker 1: if you could choose between free education for everybody or

643
00:36:03,960 --> 00:36:06,440
Speaker 1: curing cancer, And he pitched it as that those are

644
00:36:06,480 --> 00:36:09,080
Speaker 1: your choices, but if they only had more compute, they

645
00:36:09,120 --> 00:36:09,520
Speaker 1: could do.

646
00:36:09,520 --> 00:36:15,000
Speaker 2: Both right as opposed to neither right, correct as opposed

647
00:36:15,040 --> 00:36:20,080
Speaker 2: to nothing of the sort. Happening at all anywhere.

648
00:36:20,239 --> 00:36:22,960
Speaker 1: But I do like that. That's it's I don't like

649
00:36:23,080 --> 00:36:28,840
Speaker 1: the examples he chose. They're just so intentionally manipulative. I

650
00:36:28,960 --> 00:36:31,840
Speaker 1: think you know where it's like, well, you could you

651
00:36:31,840 --> 00:36:35,360
Speaker 1: could choose from preventing puppies from being kicked or from

652
00:36:35,400 --> 00:36:37,880
Speaker 1: preventing cats from being homeless, just.

653
00:36:37,800 --> 00:36:42,319
Speaker 2: Like you can only crush one animal. Like it's just

654
00:36:42,880 --> 00:36:45,160
Speaker 2: very It's also the kind of thing that you come

655
00:36:45,239 --> 00:36:47,359
Speaker 2: up with if you do not do any work, if

656
00:36:47,360 --> 00:36:49,440
Speaker 2: you don't really know what happens in the real world,

657
00:36:49,480 --> 00:36:54,000
Speaker 2: You're like, fuck, do yeah, what if education was free

658
00:36:54,480 --> 00:36:58,640
Speaker 2: or what if cancer note no happen? Do you like this? Like?

659
00:36:58,880 --> 00:37:01,080
Speaker 1: And of course CNBC is like, yep, can I have

660
00:37:01,120 --> 00:37:01,640
Speaker 1: money now?

661
00:37:01,800 --> 00:37:04,160
Speaker 2: Yeah? This is good? And that one hundred billion is

662
00:37:04,280 --> 00:37:07,400
Speaker 2: very real that that's enough. This is the thing maybe

663
00:37:07,400 --> 00:37:10,640
Speaker 2: conspiracy theorists right all along in the sense that it's like, yeah,

664
00:37:10,719 --> 00:37:14,160
Speaker 2: there was a point last year where in video an

665
00:37:14,160 --> 00:37:16,680
Speaker 2: open ai light one hundred billion dollar deal never happened.

666
00:37:16,920 --> 00:37:20,240
Speaker 2: AMD and the open ai Light as well, just nobody

667
00:37:20,480 --> 00:37:23,480
Speaker 2: talked about their guidance didn't change for a MD. They

668
00:37:23,600 --> 00:37:26,040
Speaker 2: do not appear to have sold a single chip to

669
00:37:26,440 --> 00:37:31,799
Speaker 2: open Ai Broadcom still nothing like three quarters in we

670
00:37:31,840 --> 00:37:33,919
Speaker 2: don't have a single sale. What the fuck.

671
00:37:34,440 --> 00:37:37,359
Speaker 1: Johnson was really defensive about that one. When the Taiwanese

672
00:37:37,480 --> 00:37:41,080
Speaker 1: media asked, oh yeah, yeah, oh he there was never

673
00:37:41,080 --> 00:37:41,760
Speaker 1: any commitment.

674
00:37:41,840 --> 00:37:44,319
Speaker 2: He said, there's never got any commitment from any of

675
00:37:44,360 --> 00:37:48,439
Speaker 2: these things, though. I just I think and I think

676
00:37:48,480 --> 00:37:50,359
Speaker 2: at some point we're just going to find out that

677
00:37:50,440 --> 00:37:54,200
Speaker 2: nothing happened, like I just did, nothing actually moved to anyone,

678
00:37:54,239 --> 00:37:57,000
Speaker 2: Like we still haven't heard of in Vidia has sent

679
00:37:57,040 --> 00:38:00,479
Speaker 2: a dime to open Ai. Soft Bank has to raise

680
00:38:00,520 --> 00:38:04,880
Speaker 2: forty billion dollars to send thirty billion dollars to open Aye. Yeah,

681
00:38:05,200 --> 00:38:06,279
Speaker 2: that hasn't happened yet.

682
00:38:06,400 --> 00:38:10,000
Speaker 1: You see the game. So there's a game that came

683
00:38:10,000 --> 00:38:12,200
Speaker 1: out this past week called Crimson Desert, and.

684
00:38:12,800 --> 00:38:14,480
Speaker 2: I've been meaning to play it, but I hear it's

685
00:38:14,480 --> 00:38:14,879
Speaker 2: some mess.

686
00:38:15,320 --> 00:38:17,160
Speaker 1: Yeah, it is a It is a bit of a mess,

687
00:38:17,239 --> 00:38:21,400
Speaker 1: I think. But the interesting thing was they had a

688
00:38:21,400 --> 00:38:24,000
Speaker 1: bit of an unexpected scandal where amongst all the other

689
00:38:24,080 --> 00:38:29,799
Speaker 1: various problems like blocking Intel from working, they had some

690
00:38:29,960 --> 00:38:33,640
Speaker 1: users noticed that there was very clearly AI generated art

691
00:38:33,920 --> 00:38:36,840
Speaker 1: in the Yeah hell yeah, yeah. So it's like you

692
00:38:36,880 --> 00:38:39,160
Speaker 1: walk into the whatever the tavern and on the wall

693
00:38:39,200 --> 00:38:41,360
Speaker 1: there's a painting handing and if you get close to

694
00:38:41,400 --> 00:38:43,839
Speaker 1: it you can see it's like the early several years

695
00:38:43,840 --> 00:38:48,960
Speaker 1: ago generative AI art. That's just fairy obvious, and so

696
00:38:49,200 --> 00:38:51,560
Speaker 1: on Steam, you're supposed to disclose if there's AI art

697
00:38:51,640 --> 00:38:54,000
Speaker 1: or assets in the game. They didn't do that. They're

698
00:38:54,040 --> 00:38:55,680
Speaker 1: too big, so they're not gonna be punished for it.

699
00:38:55,960 --> 00:38:59,920
Speaker 1: But they put out a statement apologizing saying these replace holders.

700
00:39:00,000 --> 00:39:01,839
Speaker 1: They're supposed to be replaced. We're going back through and

701
00:39:01,840 --> 00:39:09,280
Speaker 1: removing them all whatever. And the Mike Evara, who's currently

702
00:39:09,360 --> 00:39:12,600
Speaker 1: the CEO of Prize Picks and previously was president of

703
00:39:12,600 --> 00:39:18,080
Speaker 1: Blizzard and previously was also a VP of Microsoft Windows,

704
00:39:19,080 --> 00:39:23,239
Speaker 1: he tweeted out asking why the studio was apologizing and

705
00:39:23,280 --> 00:39:25,480
Speaker 1: basically saying this is going to be in everything, so

706
00:39:25,560 --> 00:39:31,200
Speaker 1: you shouldn't apologize. And it's just it's crazy to me

707
00:39:31,520 --> 00:39:35,840
Speaker 1: where the approach to a lot of the AI stuff.

708
00:39:35,840 --> 00:39:39,319
Speaker 1: It feels so like this is inevitable, is what you're

709
00:39:39,360 --> 00:39:41,719
Speaker 1: being told by the suits and the vps and the CEOs.

710
00:39:42,120 --> 00:39:44,560
Speaker 1: I don't think they realize that. That's the part a

711
00:39:44,560 --> 00:39:47,719
Speaker 1: lot of people don't like, is the part where it's

712
00:39:48,640 --> 00:39:51,600
Speaker 1: being forced and you're told this is inevitable. Get used

713
00:39:51,600 --> 00:39:51,960
Speaker 1: to it.

714
00:39:52,520 --> 00:39:54,439
Speaker 2: Yeah, it doesn't have to be good or you don't

715
00:39:54,480 --> 00:39:56,359
Speaker 2: have to like it, but you're going to have it

716
00:39:56,440 --> 00:39:59,200
Speaker 2: because of us. We're gonna make you have it and

717
00:39:59,520 --> 00:40:02,279
Speaker 2: that'll be good. Well it won't be good, but you'll

718
00:40:02,280 --> 00:40:05,799
Speaker 2: have it, and we will. Ostensibly something will change. Like

719
00:40:06,200 --> 00:40:08,680
Speaker 2: they're not even making I don't even think they're saving

720
00:40:08,719 --> 00:40:10,640
Speaker 2: money doing this stuff. For if they are, it's the

721
00:40:11,120 --> 00:40:15,440
Speaker 2: it's like very it's just firing three people, which is

722
00:40:15,480 --> 00:40:18,520
Speaker 2: a lot for the people being fired, and their work

723
00:40:18,520 --> 00:40:21,120
Speaker 2: would make the game better. But it's just a fucking

724
00:40:21,160 --> 00:40:23,759
Speaker 2: excel spreadsy edge, right like it's for the for the

725
00:40:23,840 --> 00:40:27,560
Speaker 2: larger companies. I mean, it's just so I think that

726
00:40:27,640 --> 00:40:29,680
Speaker 2: this is also a mask off moment for so many

727
00:40:29,719 --> 00:40:31,920
Speaker 2: of these companies. It's the ones that just don't give

728
00:40:31,960 --> 00:40:35,320
Speaker 2: a rap fuck about anyone who just they don't make stuff,

729
00:40:35,360 --> 00:40:38,399
Speaker 2: they don't contribute things. They just like, yeah, you know, man,

730
00:40:39,000 --> 00:40:42,319
Speaker 2: you know the thing. You're like, it's gonna suck shit

731
00:40:42,400 --> 00:40:46,120
Speaker 2: and we're gonna save like eight eight dollars.

732
00:40:46,680 --> 00:40:49,640
Speaker 1: Yeah. No, it definitely enables drift in, right, Like the

733
00:40:49,680 --> 00:40:55,120
Speaker 1: whole it's like you said earlier, you have the just

734
00:40:55,200 --> 00:40:58,000
Speaker 1: the entire premise of the way the technology is set

735
00:40:58,080 --> 00:41:00,800
Speaker 1: up and pitched and the lack of understand and technically

736
00:41:00,840 --> 00:41:03,400
Speaker 1: for a lot of like media and coverage, it just

737
00:41:03,600 --> 00:41:06,080
Speaker 1: it's set up where people can grift. And I think

738
00:41:06,080 --> 00:41:08,879
Speaker 1: you saw that with crypto too, where there's a lot

739
00:41:08,920 --> 00:41:12,520
Speaker 1: of blockchain, you know, is the big word everyone's thrown

740
00:41:12,560 --> 00:41:15,799
Speaker 1: around suddenly all these people on TV who had no

741
00:41:15,840 --> 00:41:19,279
Speaker 1: idea what that meant, but same type of thing, and

742
00:41:19,360 --> 00:41:23,279
Speaker 1: it's I don't know the situation's right where maybe there's

743
00:41:23,280 --> 00:41:27,279
Speaker 1: some real use cases for sure, but it's pretty easy

744
00:41:27,320 --> 00:41:29,200
Speaker 1: to scam people right now.

745
00:41:29,200 --> 00:41:33,160
Speaker 2: I just I also think that it's just showing how

746
00:41:33,160 --> 00:41:35,360
Speaker 2: many dunces there are, how many people that don't actually

747
00:41:35,360 --> 00:41:38,360
Speaker 2: want to learn anything. I mean, even the coding side.

748
00:41:38,680 --> 00:41:40,799
Speaker 2: The little code I've learned so far has just made

749
00:41:40,800 --> 00:41:43,560
Speaker 2: me aware that there are lots of engineers who don't

750
00:41:43,600 --> 00:41:45,360
Speaker 2: read any of the code that comes out and they're like,

751
00:41:45,440 --> 00:41:48,120
Speaker 2: it'll be fine, shit work fine.

752
00:41:48,320 --> 00:41:53,160
Speaker 1: I think I had someone really pushing me to try

753
00:41:53,520 --> 00:41:56,959
Speaker 1: claude where he's basically like no, no, like you don't

754
00:41:57,000 --> 00:41:59,320
Speaker 1: the other ones. Because I've I've tested a few of

755
00:41:59,320 --> 00:42:02,120
Speaker 1: the LM's and I'm not too impressed, but he was like,

756
00:42:02,160 --> 00:42:05,360
Speaker 1: this one, this is the one, you know, that's unbelievable

757
00:42:05,400 --> 00:42:09,200
Speaker 1: how good it is. And I guess my use case

758
00:42:09,360 --> 00:42:11,600
Speaker 1: wasn't maybe the right fit or something.

759
00:42:13,920 --> 00:42:21,080
Speaker 2: Yeah, it's just like.

760
00:42:19,520 --> 00:42:21,880
Speaker 1: Like I tried it, and the thing I tried it

761
00:42:21,920 --> 00:42:28,160
Speaker 1: for was I wanted to make a template for Adobe

762
00:42:28,160 --> 00:42:32,560
Speaker 1: in Design, which I've never used, and you can go

763
00:42:32,719 --> 00:42:35,360
Speaker 1: buy and download a template and whatever, but I wanted

764
00:42:35,360 --> 00:42:37,760
Speaker 1: like a specific one made in the way I wanted

765
00:42:37,760 --> 00:42:41,080
Speaker 1: to use it. And because in Design can accept code

766
00:42:41,120 --> 00:42:43,279
Speaker 1: I might be XML, I don't remember, but it's got

767
00:42:43,280 --> 00:42:45,320
Speaker 1: some kind of code it can accept, I thought, Okay,

768
00:42:45,320 --> 00:42:47,200
Speaker 1: this should be able to write the code. It's not.

769
00:42:47,320 --> 00:42:49,960
Speaker 1: It's not a design I'm asking for. It's code, and

770
00:42:50,000 --> 00:42:51,719
Speaker 1: then I should be able to shove it into in

771
00:42:51,760 --> 00:42:54,920
Speaker 1: Design and have a template. And I experimented with it

772
00:42:54,960 --> 00:42:58,000
Speaker 1: for probably I got like really obsessed with when I'm

773
00:42:58,000 --> 00:43:01,840
Speaker 1: trying to make software work. I spent like eight hours

774
00:43:01,840 --> 00:43:04,960
Speaker 1: on it. Jeeuz it did this the same thing as

775
00:43:05,000 --> 00:43:08,799
Speaker 1: chat GVT, where you know it gives you code. It

776
00:43:08,840 --> 00:43:11,359
Speaker 1: didn't work. I feedback the error to it, and it's like, oh,

777
00:43:11,480 --> 00:43:13,680
Speaker 1: I see what went wrong. It was this, and then

778
00:43:13,680 --> 00:43:15,440
Speaker 1: it sends you more code and it doesn't work, and

779
00:43:15,520 --> 00:43:17,520
Speaker 1: before you know, you've blown through all your tokens for

780
00:43:17,560 --> 00:43:20,080
Speaker 1: the day, right, which seems like a great way to

781
00:43:20,080 --> 00:43:23,480
Speaker 1: make more money. And I ended up after that experiment,

782
00:43:24,280 --> 00:43:27,319
Speaker 1: I was like, let me just do this the old

783
00:43:27,360 --> 00:43:30,439
Speaker 1: fashioned way, and I watched like three tutorials and within

784
00:43:30,480 --> 00:43:31,960
Speaker 1: two and a half hours I had done what I

785
00:43:31,960 --> 00:43:32,680
Speaker 1: wanted myself.

786
00:43:32,920 --> 00:43:35,120
Speaker 2: You know, the model did not provide you with the

787
00:43:35,120 --> 00:43:35,720
Speaker 2: thing you needed.

788
00:43:36,200 --> 00:43:39,440
Speaker 1: It did not. And not only that, but there was

789
00:43:39,480 --> 00:43:43,680
Speaker 1: a moment there where I was starting to feel that

790
00:43:43,680 --> 00:43:46,040
Speaker 1: that disconnect with that like psychosis I think some people

791
00:43:46,040 --> 00:43:47,719
Speaker 1: get as they use these tools more and more and

792
00:43:47,840 --> 00:43:52,239
Speaker 1: rely on them, where it starts to feel like, well,

793
00:43:52,280 --> 00:43:54,560
Speaker 1: I can't do this and this thing doesn't help in me.

794
00:43:54,680 --> 00:43:57,200
Speaker 1: So there's that temptation of like I'll just give up,

795
00:43:57,760 --> 00:43:59,960
Speaker 1: But then you know, you try to do it yourself

796
00:44:00,040 --> 00:44:02,719
Speaker 1: for like five minutes, like, oh, this isn't that bad

797
00:44:02,840 --> 00:44:05,000
Speaker 1: to learn new software. You know, I can handle this,

798
00:44:05,600 --> 00:44:09,400
Speaker 1: And I just worry the people who get really reliant

799
00:44:09,440 --> 00:44:12,359
Speaker 1: on this stuff. I don't know, it seems not good.

800
00:44:13,000 --> 00:44:15,759
Speaker 2: Well that's the thing though, whenever I've because I have

801
00:44:16,239 --> 00:44:18,840
Speaker 2: the times have experimented with like Claude and chat GPT,

802
00:44:19,120 --> 00:44:21,640
Speaker 2: I've always thrown it stuff where I'm like, I've already

803
00:44:21,640 --> 00:44:25,400
Speaker 2: finished a model, I've already finished at a paraff what

804
00:44:25,400 --> 00:44:27,920
Speaker 2: do you think? And it will say something. I'll be like, okay,

805
00:44:27,920 --> 00:44:29,760
Speaker 2: but what about this, and I'll just make up something.

806
00:44:30,920 --> 00:44:33,440
Speaker 2: It's like, actually, there were eighty gigawatts added in the

807
00:44:33,520 --> 00:44:35,200
Speaker 2: last quarter, what do you think about that? I'll be like, oh,

808
00:44:35,239 --> 00:44:35,800
Speaker 2: my mistake.

809
00:44:37,040 --> 00:44:38,400
Speaker 1: It's just like you're gaslighting.

810
00:44:38,560 --> 00:44:41,320
Speaker 2: Now, I'm gaslighting you, like I am abusing the model.

811
00:44:41,640 --> 00:44:42,319
Speaker 2: But that's the thing.

812
00:44:42,560 --> 00:44:44,680
Speaker 1: You better be careful. That's gonna come back to you

813
00:44:44,719 --> 00:44:45,080
Speaker 1: one day.

814
00:44:45,360 --> 00:44:51,040
Speaker 2: Yeah, well, well Rococo's modern basilisk. Yeah. It's just it's

815
00:44:51,120 --> 00:44:53,680
Speaker 2: just like the fact that they can just have their

816
00:44:53,680 --> 00:44:58,160
Speaker 2: wrong twisted immediately makes them useless, because the whole point

817
00:44:58,160 --> 00:45:00,480
Speaker 2: of artificial intelligence is it's meant to be in intelligent

818
00:45:00,680 --> 00:45:05,520
Speaker 2: and kind of support you when you're like, not agree

819
00:45:05,560 --> 00:45:07,239
Speaker 2: with you when you're wrong, but be like, hey, you're

820
00:45:07,280 --> 00:45:11,080
Speaker 2: wrong here. But it's just very weird as well that

821
00:45:11,200 --> 00:45:13,600
Speaker 2: every time I hear a story it's like yours, where

822
00:45:13,600 --> 00:45:15,759
Speaker 2: it's like, yeah, I wanted it to do stuff, but

823
00:45:15,840 --> 00:45:19,160
Speaker 2: it didn't. And do you talk to someone who's a

824
00:45:19,200 --> 00:45:21,600
Speaker 2: booster and they go, well, what you should have done?

825
00:45:21,680 --> 00:45:24,799
Speaker 2: It's like, so, so you're just gonna just let's start

826
00:45:24,840 --> 00:45:27,600
Speaker 2: from the point of this thing doesn't work and you

827
00:45:27,680 --> 00:45:29,440
Speaker 2: have to find a way to make it work. Well,

828
00:45:29,480 --> 00:45:31,520
Speaker 2: it does work, you're just not using it right. Well

829
00:45:31,560 --> 00:45:34,799
Speaker 2: why not? Yeah, well how did you prompt it? How

830
00:45:34,840 --> 00:45:37,959
Speaker 2: did you exactly? But the thing is, you can hold

831
00:45:38,000 --> 00:45:40,680
Speaker 2: something wrong. There's no way to use these right. It's

832
00:45:40,800 --> 00:45:44,240
Speaker 2: just how how much can they gaslight you into believing

833
00:45:44,239 --> 00:45:46,200
Speaker 2: that you're deficient and that you should say I think

834
00:45:46,880 --> 00:45:47,839
Speaker 2: it work.

835
00:45:48,000 --> 00:45:50,600
Speaker 1: It just seems like, at least for the task I

836
00:45:50,640 --> 00:45:54,840
Speaker 1: was doing, the amount of time required to babystep it

837
00:45:55,160 --> 00:46:00,520
Speaker 1: through the process is so much greater than just learning

838
00:46:00,560 --> 00:46:01,240
Speaker 1: something new.

839
00:46:01,760 --> 00:46:04,560
Speaker 2: Actually, I also don't know about you, but when I

840
00:46:04,640 --> 00:46:08,960
Speaker 2: don't understand something, the more I don't understand it, the

841
00:46:09,000 --> 00:46:12,439
Speaker 2: more worried I get, Like, I don't I can't sacrifice

842
00:46:12,440 --> 00:46:14,680
Speaker 2: myself to a machine. I'll be like I will straight

843
00:46:14,760 --> 00:46:16,839
Speaker 2: up just think like I don't get this this. I'm

844
00:46:16,840 --> 00:46:19,960
Speaker 2: worried that I'm going to learn something wrong because I'm

845
00:46:19,960 --> 00:46:22,280
Speaker 2: looking at this and it seems to be trying to

846
00:46:22,560 --> 00:46:25,000
Speaker 2: gas me up when I do not understand what I'm talking. Well,

847
00:46:25,000 --> 00:46:27,480
Speaker 2: I'm just like, I don't fucking know what you're talking about. Brother.

848
00:46:29,120 --> 00:46:31,960
Speaker 1: You had a great quote when we met up when

849
00:46:31,960 --> 00:46:36,040
Speaker 1: you came down here, and I've actually said it to

850
00:46:36,719 --> 00:46:38,880
Speaker 1: writers on the team for training. But you know, one

851
00:46:38,880 --> 00:46:40,600
Speaker 1: of the things I made a comment about how I

852
00:46:40,600 --> 00:46:42,239
Speaker 1: needed to do a bunch of fact checking that day

853
00:46:42,320 --> 00:46:47,080
Speaker 1: or something, and you made a comment about how you

854
00:46:47,960 --> 00:46:50,440
Speaker 1: always double check your facts and if you want it

855
00:46:50,440 --> 00:46:52,000
Speaker 1: to be right, you check it a third time.

856
00:46:52,560 --> 00:46:53,480
Speaker 2: Yeah, which is brilliant.

857
00:46:54,040 --> 00:46:56,239
Speaker 1: I think if you add AI to that, you know,

858
00:46:56,360 --> 00:46:58,239
Speaker 1: it's like it's kind of that same feeling where it's

859
00:46:58,239 --> 00:47:01,640
Speaker 1: like if anything comes out of an llm uh, the

860
00:47:01,680 --> 00:47:06,200
Speaker 1: amount of anxiety I have mm hmmm, yep is not

861
00:47:06,280 --> 00:47:08,520
Speaker 1: even worth whatever the answer is.

862
00:47:09,520 --> 00:47:13,120
Speaker 2: And also, I so a while ago I had access

863
00:47:13,160 --> 00:47:17,239
Speaker 2: to like a much bigger, more financial focused one and

864
00:47:17,280 --> 00:47:19,520
Speaker 2: I used it to like look up a bunch of stuff,

865
00:47:19,560 --> 00:47:22,360
Speaker 2: like do a report on this. Three or four of

866
00:47:22,360 --> 00:47:26,359
Speaker 2: the links were for were just dead. One of them

867
00:47:26,400 --> 00:47:29,040
Speaker 2: referred to something that just was an irrelevant link. I

868
00:47:29,080 --> 00:47:31,160
Speaker 2: did look something up on Claude once and it gave

869
00:47:31,200 --> 00:47:37,160
Speaker 2: me two different citations from Grokipedia. Are you you're not

870
00:47:37,200 --> 00:47:42,400
Speaker 2: familiar with Grokipedia. I just well, that's the special groc

871
00:47:43,160 --> 00:47:47,759
Speaker 2: Wikipedia that okay at xtually everything app.

872
00:47:48,120 --> 00:47:50,880
Speaker 1: Ah, they have their own Wikipedia.

873
00:47:50,600 --> 00:47:54,319
Speaker 2: Yep, and that's what Claude is citing from. There's the

874
00:47:54,440 --> 00:47:58,440
Speaker 2: basic Wikipedia. It's so good. It's just I do think

875
00:47:58,480 --> 00:48:00,520
Speaker 2: that there is also a degree here where AI is

876
00:48:00,680 --> 00:48:03,279
Speaker 2: just a test of how much you're how willing you

877
00:48:03,320 --> 00:48:05,640
Speaker 2: are to just be like, yeah, I get it. I

878
00:48:05,640 --> 00:48:08,239
Speaker 2: guess like just quickly you can wave off something and

879
00:48:08,320 --> 00:48:11,800
Speaker 2: be like I have yes, fine, I guess I'll mostly

880
00:48:11,800 --> 00:48:14,920
Speaker 2: get it. This sounded good enough for me.

881
00:48:15,080 --> 00:48:20,640
Speaker 1: The best use cases have still been for browsing Chinese Internet,

882
00:48:20,760 --> 00:48:26,040
Speaker 1: or browsing the Internet generally in another language, and specifically

883
00:48:26,040 --> 00:48:31,160
Speaker 1: it's for like when I've needed sources and research. So

884
00:48:31,239 --> 00:48:32,840
Speaker 1: for the I don't know if I gave this example

885
00:48:32,840 --> 00:48:34,880
Speaker 1: on your show before, but the one that came up

886
00:48:34,920 --> 00:48:38,640
Speaker 1: previously was for the d ram Cartel Piece and for

887
00:48:38,680 --> 00:48:41,720
Speaker 1: the Rise of Chinese Chinese Memory. We were looking at

888
00:48:41,840 --> 00:48:44,480
Speaker 1: a bunch of different filings for these companies in China.

889
00:48:45,239 --> 00:48:46,800
Speaker 1: I wasn't one hundred percent sure if they had like

890
00:48:46,800 --> 00:48:50,400
Speaker 1: an SEC equivalent or something like that. And so using

891
00:48:51,280 --> 00:48:52,680
Speaker 1: I don't know if I use I think I used

892
00:48:52,840 --> 00:48:55,719
Speaker 1: GPT to try that. But using GPT or whatever it

893
00:48:55,760 --> 00:49:00,520
Speaker 1: was at the time, it was useful for providing phrases

894
00:49:00,560 --> 00:49:03,360
Speaker 1: where it's it's like, okay, here's the Chinese characters of

895
00:49:03,400 --> 00:49:06,920
Speaker 1: what you should search for. And the reason Google Translate

896
00:49:07,000 --> 00:49:08,560
Speaker 1: wasn't good enough on its own for that is because

897
00:49:08,600 --> 00:49:11,920
Speaker 1: I didn't know the colloquialisms of what might they call

898
00:49:12,000 --> 00:49:14,080
Speaker 1: these different things that I know exist in the US,

899
00:49:14,120 --> 00:49:15,840
Speaker 1: but I don't know if they exist there, you know,

900
00:49:15,840 --> 00:49:17,319
Speaker 1: And then I can take that and I can put

901
00:49:17,320 --> 00:49:20,600
Speaker 1: it into Google Translate, which is a dumb translator that's

902
00:49:20,640 --> 00:49:22,480
Speaker 1: just word for word, and just make sure it makes

903
00:49:22,520 --> 00:49:25,719
Speaker 1: any sense and that it was useful for. But so

904
00:49:25,880 --> 00:49:29,640
Speaker 1: far that's pretty much the only, you know, the only

905
00:49:29,719 --> 00:49:31,040
Speaker 1: use case I've I've had.

906
00:49:31,560 --> 00:49:34,959
Speaker 2: Yeah, and it's also it's the classic thing of maybe

907
00:49:34,960 --> 00:49:38,000
Speaker 2: your own device model could do that. Yeah, I think

908
00:49:38,000 --> 00:49:41,520
Speaker 2: that eventually that will be the case. And it's just

909
00:49:43,040 --> 00:49:46,000
Speaker 2: is that really enough to substantiate nearly two hundred billion

910
00:49:46,040 --> 00:49:49,040
Speaker 2: dollars worth of GPU and networking sales from Vidia a year.

911
00:49:49,160 --> 00:49:51,240
Speaker 2: No dollars.

912
00:49:51,640 --> 00:49:55,360
Speaker 1: Yeah, it's it's not enough to be worth the destruction

913
00:49:55,520 --> 00:50:00,120
Speaker 1: of consumer hardware, you know. And that was constantly, like

914
00:50:00,160 --> 00:50:02,399
Speaker 1: every time I try to poke at these things every

915
00:50:02,400 --> 00:50:04,320
Speaker 1: now and then so that i'm at I want to

916
00:50:04,320 --> 00:50:07,439
Speaker 1: make sure if I'm criticizing them, I've at least used

917
00:50:07,480 --> 00:50:08,240
Speaker 1: them the same.

918
00:50:08,480 --> 00:50:13,680
Speaker 2: Yeah, yeah, but it still feels bad. It's just and

919
00:50:13,760 --> 00:50:16,920
Speaker 2: then you even then just having my Twitter feed up

920
00:50:16,960 --> 00:50:20,440
Speaker 2: while we're talking, random ship pops up, such as SaaS CEOs.

921
00:50:20,480 --> 00:50:24,000
Speaker 2: If your CFO hasn't used Lauter Excel by now, you

922
00:50:24,120 --> 00:50:26,760
Speaker 2: need a new CFO. Only the curious will survive. Shut

923
00:50:26,800 --> 00:50:29,400
Speaker 2: the fuck up. Just shut the fuck up, Like what

924
00:50:29,560 --> 00:50:33,040
Speaker 2: are you talking about? Why? Why? What do you mean?

925
00:50:33,280 --> 00:50:36,440
Speaker 1: That's so I feel like that's so dangerous, specifically for

926
00:50:36,680 --> 00:50:42,080
Speaker 1: just responding with why feed all of your companies financial

927
00:50:42,160 --> 00:50:43,759
Speaker 1: information to the cell?

928
00:50:44,719 --> 00:50:47,520
Speaker 2: Also all what do you think? Like, what do you

929
00:50:47,560 --> 00:50:50,520
Speaker 2: think a CFO does? Oh, they just they build models,

930
00:50:50,560 --> 00:50:50,919
Speaker 2: I guess.

931
00:50:51,000 --> 00:50:51,200
Speaker 3: Yeah.

932
00:50:51,280 --> 00:50:53,680
Speaker 2: Well, the good idea for financial modeling is when you

933
00:50:53,840 --> 00:50:57,600
Speaker 2: distance yourself from everything as far as but ideally you're

934
00:50:57,640 --> 00:51:00,399
Speaker 2: so abstracted from the problem that you don't eat really

935
00:51:00,520 --> 00:51:04,000
Speaker 2: understand it anymore. As we're finding out isn't a problem anywhere.

936
00:51:04,560 --> 00:51:08,680
Speaker 2: It's just insane. It's I feel like we live in

937
00:51:08,800 --> 00:51:10,919
Speaker 2: a truly insane period.

938
00:51:11,160 --> 00:51:15,040
Speaker 1: And it's bad. I mean, the consumer space is just

939
00:51:15,200 --> 00:51:19,680
Speaker 1: like last time I talked to you, similar topic, but

940
00:51:21,080 --> 00:51:24,000
Speaker 1: more of the companies in the industry, computer industry that

941
00:51:24,160 --> 00:51:29,280
Speaker 1: don't sell silicon products, you know, cases, cooler as, accessories, whatever, motherboards,

942
00:51:30,920 --> 00:51:33,279
Speaker 1: we've had more of them now contacts basically saying hey,

943
00:51:33,320 --> 00:51:35,800
Speaker 1: we're in big trouble and they want to talk to

944
00:51:35,920 --> 00:51:38,160
Speaker 1: us about it for a video. But it's just when

945
00:51:38,200 --> 00:51:39,560
Speaker 1: I say big trouble, I mean a lot of these

946
00:51:39,600 --> 00:51:44,360
Speaker 1: companies are down like fifty plus percent from expectations, and

947
00:51:45,239 --> 00:51:48,840
Speaker 1: that's because you can't build a computer as a consumer

948
00:51:48,960 --> 00:51:52,320
Speaker 1: if you can't afford like five six hundred dollars minimum

949
00:51:52,600 --> 00:51:56,000
Speaker 1: for basic memory now because of the data center demand

950
00:51:56,080 --> 00:51:56,320
Speaker 1: for it.

951
00:51:57,080 --> 00:51:59,080
Speaker 2: How does any of this turnaround?

952
00:51:59,120 --> 00:51:59,279
Speaker 3: Though?

953
00:52:00,120 --> 00:52:03,960
Speaker 2: How quickly? Is there any possibility that when the bubble

954
00:52:04,040 --> 00:52:07,600
Speaker 2: busts anything returns to normal within gaming like you've seen

955
00:52:07,680 --> 00:52:10,000
Speaker 2: I'm sure you've seen aras where they've oversold memory in

956
00:52:10,080 --> 00:52:10,480
Speaker 2: the past.

957
00:52:10,760 --> 00:52:14,960
Speaker 1: Yeah, not like this though, Yeah, I've never seen it

958
00:52:15,080 --> 00:52:18,480
Speaker 1: like this. Memory is a really unique industry because of

959
00:52:18,560 --> 00:52:23,520
Speaker 1: how it's been corrupt for forty years. And when I

960
00:52:23,560 --> 00:52:28,960
Speaker 1: say maybe, well, yeah, So, like the Department of Justice

961
00:52:30,200 --> 00:52:36,600
Speaker 1: under the Bush administration w busted the memory makers for

962
00:52:37,080 --> 00:52:39,680
Speaker 1: what they called a cartel, and by definition that's what

963
00:52:39,760 --> 00:52:44,320
Speaker 1: it was, price fixing cartel. And this has been happening

964
00:52:44,440 --> 00:52:47,839
Speaker 1: like at least once a decade where in the late

965
00:52:47,960 --> 00:52:51,000
Speaker 1: nineties early two thousands, the memory suppliers all got together

966
00:52:51,760 --> 00:52:56,880
Speaker 1: and would agree on price ceilings and floors. So when

967
00:52:56,920 --> 00:52:59,839
Speaker 1: they go and sell memory to Dell or Apple or HP,

968
00:53:01,120 --> 00:53:03,880
Speaker 1: they've already spoken to their competitors and agreed, we're not

969
00:53:03,960 --> 00:53:05,200
Speaker 1: going to go below this price.

970
00:53:06,080 --> 00:53:06,360
Speaker 2: Cool.

971
00:53:07,040 --> 00:53:10,560
Speaker 1: Yeah, and this has happened multiple times for that industry.

972
00:53:11,040 --> 00:53:11,600
Speaker 2: Very cool.

973
00:53:12,320 --> 00:53:14,560
Speaker 1: And you know what my favorite part of the story,

974
00:53:15,000 --> 00:53:17,400
Speaker 1: and I didn't know this untill we did our report recently,

975
00:53:18,000 --> 00:53:22,759
Speaker 1: was so there were there were several people that are

976
00:53:22,800 --> 00:53:25,080
Speaker 1: like over one hundred people involved, I remember correctly, And

977
00:53:25,560 --> 00:53:28,720
Speaker 1: if you look up the people who were charged with crime,

978
00:53:28,960 --> 00:53:33,320
Speaker 1: including fined and even sentenced to prison for that for

979
00:53:33,400 --> 00:53:36,800
Speaker 1: a price fixing cartel. If you look up what happened

980
00:53:36,800 --> 00:53:40,160
Speaker 1: to them after a lot of them got promoted. Yep,

981
00:53:40,239 --> 00:53:44,640
Speaker 1: one of them, his reward was to become CEO Jesus

982
00:53:44,719 --> 00:53:46,840
Speaker 1: what company Samsung Europe?

983
00:53:47,760 --> 00:53:49,880
Speaker 2: Very well, didn't someone from Samsung WANs to go to

984
00:53:50,000 --> 00:53:52,000
Speaker 2: jail a few times? Like I swear to God like

985
00:53:52,080 --> 00:53:56,440
Speaker 2: people from few times. Yeah, It's just it really does

986
00:53:56,520 --> 00:53:58,440
Speaker 2: feel that by the end of this someone else is

987
00:53:58,480 --> 00:53:59,120
Speaker 2: going to jail.

988
00:54:00,160 --> 00:54:03,120
Speaker 1: There's just somewhat and they'll get out and they'll be promoted.

989
00:54:03,360 --> 00:54:06,840
Speaker 2: Yeah. Well, the question is if it's clammy Sam Mortman

990
00:54:06,880 --> 00:54:08,840
Speaker 2: though that I don't think they're gonna I don't know.

991
00:54:09,239 --> 00:54:10,840
Speaker 2: I hear people being like someone was going to go

992
00:54:10,880 --> 00:54:12,520
Speaker 2: to jail. I don't know if I buy it. But

993
00:54:12,640 --> 00:54:15,840
Speaker 2: this private equity thing with the minimum returns maybe just

994
00:54:15,920 --> 00:54:18,000
Speaker 2: to a classic Ponzi I hope.

995
00:54:18,040 --> 00:54:22,920
Speaker 1: So yeah, classic Ponzi at least has some some history

996
00:54:22,960 --> 00:54:27,320
Speaker 1: of meaningful busts and sentences, right, So, I don't know.

997
00:54:27,560 --> 00:54:29,319
Speaker 1: But a lot of the white collar stuff, I feel

998
00:54:29,360 --> 00:54:31,360
Speaker 1: like a lot of the time it's kind of a

999
00:54:31,600 --> 00:54:34,440
Speaker 1: whatever you get. Like in the price fixing cartel, most

1000
00:54:34,480 --> 00:54:36,200
Speaker 1: of them got seven or eight months max.

1001
00:54:36,840 --> 00:54:42,400
Speaker 2: So I just America doesn't really have antitrust anymore, otherwise

1002
00:54:43,160 --> 00:54:46,600
Speaker 2: this would be I don't know. All all of this

1003
00:54:46,800 --> 00:54:49,160
Speaker 2: just feels like it's going to set back consumer hardware

1004
00:54:49,200 --> 00:54:50,520
Speaker 2: for a decade at this point.

1005
00:54:50,680 --> 00:54:52,880
Speaker 1: Oh yeah, yeah. And it's not just gaming either, like

1006
00:54:52,920 --> 00:54:56,560
Speaker 1: I think that's just what we specialize in. But yeah,

1007
00:54:56,640 --> 00:55:02,080
Speaker 1: it's it's more it's becoming increasingly viable I think for

1008
00:55:02,160 --> 00:55:05,279
Speaker 1: people on the surface to rent their computer or rent

1009
00:55:05,360 --> 00:55:07,239
Speaker 1: access to a computer in the cloud, and that's a

1010
00:55:07,360 --> 00:55:07,879
Speaker 1: bad thing.

1011
00:55:08,800 --> 00:55:12,040
Speaker 2: We don't want that. Is that really a likely outcome?

1012
00:55:13,239 --> 00:55:16,920
Speaker 1: I mean, the low end is drying up, and so

1013
00:55:17,120 --> 00:55:21,400
Speaker 1: if you can't really afford the cheapest, let's just keep

1014
00:55:21,440 --> 00:55:26,000
Speaker 1: it a gaming computer anymore. Your best option might be

1015
00:55:26,080 --> 00:55:30,239
Speaker 1: to go rent server access from Nvidia and use one

1016
00:55:30,320 --> 00:55:34,040
Speaker 1: of their thousand dollars GPUs for twenty dollars a month.

1017
00:55:34,880 --> 00:55:39,520
Speaker 2: God, what a fucking bleak, What a bleak environment. I

1018
00:55:39,719 --> 00:55:42,520
Speaker 2: just hope it. I hope it works out more that

1019
00:55:42,719 --> 00:55:45,919
Speaker 2: just these companies lose shit tons of money. I don't

1020
00:55:45,960 --> 00:55:48,480
Speaker 2: know if they because surely the memory prices would come down,

1021
00:55:48,520 --> 00:55:51,879
Speaker 2: in storage prices would come down as well, I would think, so, yeah,

1022
00:55:51,880 --> 00:55:54,240
Speaker 2: I would think. So. I think I have one involved

1023
00:55:54,280 --> 00:55:56,600
Speaker 2: with this should should suffer in ways I can't say

1024
00:55:56,640 --> 00:55:59,759
Speaker 2: on the show due to legal reasons, you know, just

1025
00:55:59,840 --> 00:56:01,520
Speaker 2: the thoughts that I have in sign in my head.

1026
00:56:03,000 --> 00:56:04,799
Speaker 2: All right, Steve, we're gonna wrap it there. You got

1027
00:56:04,840 --> 00:56:05,799
Speaker 2: anything you want to hype?

1028
00:56:06,800 --> 00:56:08,960
Speaker 1: Nah? I mean we've got a Yeah, I guess I'll

1029
00:56:08,960 --> 00:56:12,040
Speaker 1: throw one out there. We've got a big another documentary

1030
00:56:12,040 --> 00:56:15,200
Speaker 1: we're working on right now, but it's gonna be on

1031
00:56:15,600 --> 00:56:19,080
Speaker 1: the war on Huawei. So we went and dug through

1032
00:56:19,080 --> 00:56:22,120
Speaker 1: all of Huawei's history. It's pretty interesting and then interesting. Yeah,

1033
00:56:22,360 --> 00:56:25,760
Speaker 1: and that should be over an hour long and lots

1034
00:56:25,800 --> 00:56:31,120
Speaker 1: of They're a wild company and it's very politically intertwined

1035
00:56:31,160 --> 00:56:34,120
Speaker 1: with the US and China. So that'll be our next

1036
00:56:34,120 --> 00:56:34,480
Speaker 1: big one.

1037
00:56:34,880 --> 00:56:36,960
Speaker 2: Should be fun. And yeah, you know where to find me.

1038
00:56:37,040 --> 00:56:38,560
Speaker 2: The links will be in the show notes. Thank you

1039
00:56:38,760 --> 00:56:40,680
Speaker 2: as ever for listening to Better Offline. There will be

1040
00:56:40,719 --> 00:56:42,920
Speaker 2: a monologue this week. Love you all, goodbye.

1041
00:56:51,600 --> 00:56:53,960
Speaker 4: Thank you for listening to Better Offline. The editor and

1042
00:56:54,040 --> 00:56:56,800
Speaker 4: composer of the Better off Line theme song is Metosowski.

1043
00:56:57,160 --> 00:56:58,920
Speaker 4: You can check out more of his music and audio

1044
00:56:59,000 --> 00:57:02,759
Speaker 4: projects to selsk dot com, M A T T O

1045
00:57:03,040 --> 00:57:07,160
Speaker 4: s O W s KI dot com. You can email

1046
00:57:07,200 --> 00:57:09,640
Speaker 4: me at easy at better offline dot com or visit

1047
00:57:09,680 --> 00:57:12,000
Speaker 4: better Offline dot com to find more podcast links, and

1048
00:57:12,080 --> 00:57:15,160
Speaker 4: of course my newsletter. I also really recommend you go

1049
00:57:15,239 --> 00:57:17,800
Speaker 4: to chat dot where's youreaed dot at to visit the discord,

1050
00:57:18,120 --> 00:57:19,360
Speaker 4: and go to our slash.

1051
00:57:19,120 --> 00:57:22,200
Speaker 2: Better Offline to check out our reddit. Thank you so

1052
00:57:22,360 --> 00:57:23,080
Speaker 2: much for listening.

1053
00:57:23,960 --> 00:57:26,600
Speaker 3: Better Offline is a production of cool Zone Media. For

1054
00:57:26,760 --> 00:57:29,920
Speaker 3: more from cool Zone Media, visit our website cool Zonemedia

1055
00:57:29,960 --> 00:57:32,800
Speaker 3: dot com, or check us out on the iHeartRadio app,

1056
00:57:32,880 --> 00:57:35,280
Speaker 3: Apple Podcasts, or wherever you get your podcasts.