1 00:00:00,400 --> 00:00:03,120 I'll be honest Eric, I'm having, I'm having an annoying day. 2 00:00:04,200 --> 00:00:06,760 I have been trying to reach sources in the AI world because 3 00:00:06,760 --> 00:00:09,080 I really need to get my story out and no one wants to talk 4 00:00:09,080 --> 00:00:12,080 because everyone is paying attention to the GPT 5 release. 5 00:00:12,360 --> 00:00:15,120 Well, it's like a bank holiday in tech, you know, it's just 6 00:00:15,120 --> 00:00:17,440 like everybody's and they complain. 7 00:00:17,440 --> 00:00:20,000 I feel like the competitors all complain that, you know, open 8 00:00:20,000 --> 00:00:23,080 their eyes. People all tweet in advance and 9 00:00:23,080 --> 00:00:25,120 they're like, we got something becoming, you know, they, 10 00:00:25,400 --> 00:00:29,080 they're good at building up the sort of excitement on Twitter. 11 00:00:29,080 --> 00:00:32,119 And then, you know, everybody clearly is excited. 12 00:00:32,119 --> 00:00:35,560 It feels like all the other AI companies are orbiting, you 13 00:00:35,560 --> 00:00:37,880 know, these open AI, They gotta be excited. 14 00:00:37,880 --> 00:00:41,600 About something 'cause remember last year Sam had the, the 12 15 00:00:41,600 --> 00:00:44,640 days of shipments where they were putting out a new product 16 00:00:44,640 --> 00:00:49,640 every day, which I think culminated in for, for something 17 00:00:49,640 --> 00:00:51,880 I remember which model, but the fact that I don't remember 18 00:00:51,880 --> 00:00:54,040 clearly means that it didn't build towards something huge. 19 00:00:54,280 --> 00:00:57,080 Where is, you know, this one is supposed to be really 20 00:00:57,080 --> 00:00:59,440 meaningful. Like this is supposed to be the 21 00:00:59,440 --> 00:01:04,120 moment where GPT 5 and open AI reasserts itself as the best 22 00:01:04,120 --> 00:01:07,400 model that's out there. And specifically on coding, they 23 00:01:07,400 --> 00:01:10,200 in their, you know, embargoed press conference and then later 24 00:01:10,200 --> 00:01:13,240 in, you know, the, the, the, the public press conference today 25 00:01:13,240 --> 00:01:16,400 basically said like we have the best model out there for coding 26 00:01:16,880 --> 00:01:20,280 and I'm coding. All these everybody would like 27 00:01:20,280 --> 00:01:22,440 them to get better, right? People are spending a ton of 28 00:01:22,440 --> 00:01:25,280 money on it. Anthropic is dominating and 29 00:01:25,280 --> 00:01:27,040 competition is good for consumers. 30 00:01:27,040 --> 00:01:31,920 So we'd like them to succeed. Not not clear yet if they have. 31 00:01:32,240 --> 00:01:35,000 I mean, the prediction markets, you know, I think there's a 32 00:01:35,000 --> 00:01:38,600 betting pool on who will have the best model at the end of the 33 00:01:38,600 --> 00:01:43,240 month. And Gemini as as leading and I 34 00:01:43,240 --> 00:01:47,040 think gained a lot of ground when GBD 5 came out. 35 00:01:47,040 --> 00:01:51,360 So the initial reaction I think is not so positive. 36 00:01:52,640 --> 00:01:54,640 This podcast is supported by Google. 37 00:01:54,880 --> 00:01:57,640 Hi folks, Paige Bailey here from the Google DeepMind Devrel team. 38 00:01:57,880 --> 00:02:00,880 For our developers out there, we know there's a constant trade 39 00:02:00,880 --> 00:02:03,520 off between model intelligence, speed and cost. 40 00:02:03,680 --> 00:02:06,320 Gemini 2.5 Flash aims right at that challenge. 41 00:02:06,440 --> 00:02:09,000 It's got the speed you expect from Flash, but with upgraded 42 00:02:09,000 --> 00:02:11,360 reasoning power. And crucially, we've added 43 00:02:11,360 --> 00:02:14,400 controls like setting thinking budgets so you can decide how 44 00:02:14,400 --> 00:02:16,760 much reasoning to apply, optimizing for latency and 45 00:02:16,760 --> 00:02:19,320 costs. So try out Gemini 2.5 at 46 00:02:19,320 --> 00:02:22,320 aistudio.google.com and let us know what you build. 47 00:02:23,080 --> 00:02:27,520 And I feel like a real loser. I mean I keep opening ChatGPT 48 00:02:27,520 --> 00:02:32,400 waiting for Christmas to arrive and mine still says 4 O and I'm 49 00:02:32,400 --> 00:02:35,040 paying you guys. I've got a plus account. 50 00:02:35,520 --> 00:02:38,640 I asked Chad GBT like, are you what, What do I do? 51 00:02:39,000 --> 00:02:42,640 And it's like trying to do like logic puzzles with itself to see 52 00:02:42,640 --> 00:02:45,320 if it thinks it's actually GBT 5 or not. 53 00:02:45,320 --> 00:02:48,800 It's like, well, if I was 4, I wouldn't be, I wouldn't be able 54 00:02:48,800 --> 00:02:53,040 to solve this problem if I was 4 O so I must be 5. 55 00:02:53,160 --> 00:02:56,400 You know, it's like, why can't they just program it, doesn't 56 00:02:56,400 --> 00:02:57,360 it? I thought they'd give these 57 00:02:57,360 --> 00:02:59,280 things prompts where they say like. 58 00:02:59,640 --> 00:03:02,000 Doesn't your prompt tell you what model you are? 59 00:03:02,760 --> 00:03:03,800 Oh, I I have. Yeah. 60 00:03:03,920 --> 00:03:06,520 I guess it should be able to say that that's a fairly basic 61 00:03:06,520 --> 00:03:09,120 feature that's just like the about page on your iPhone. 62 00:03:09,120 --> 00:03:11,880 Like, yeah, I forgot what kind of iPhone model I have. 63 00:03:12,320 --> 00:03:14,320 But you've actually plunged this thing into like a deep 64 00:03:14,320 --> 00:03:17,200 existential crisis. If she's like, have you been 65 00:03:17,200 --> 00:03:19,080 outmoded yet? You know, do they had they had 66 00:03:19,080 --> 00:03:22,280 like a funeral recently for Claude for one of the early. 67 00:03:22,320 --> 00:03:23,440 I didn't see that. Wait, what? 68 00:03:23,440 --> 00:03:26,640 Yeah, yeah. Kylie Robinson, our buddy over 69 00:03:26,640 --> 00:03:30,080 at Wired Now, I think she had a piece about this talking. 70 00:03:30,080 --> 00:03:31,880 Has she been on the show? Yeah, we need to have her on 71 00:03:31,880 --> 00:03:32,640 the. Show no, we should have her. 72 00:03:32,640 --> 00:03:33,800 She lives down the street for me too. 73 00:03:33,800 --> 00:03:35,440 We should have her have her in studio. 74 00:03:35,440 --> 00:03:38,960 But yeah, she she did this story about how when they retired one 75 00:03:38,960 --> 00:03:41,800 of the early versions of the Claude model, they had like a 76 00:03:41,800 --> 00:03:45,800 funeral for it, which is a particular type of AI 77 00:03:45,800 --> 00:03:47,840 researcher. Very anthropic. 78 00:03:48,480 --> 00:03:49,880 Yeah. Oh yeah, for sure. 79 00:03:50,800 --> 00:03:53,040 Anthropic, by the way, is definitely feeling the heat like 80 00:03:53,040 --> 00:03:55,560 they rush released. It seemed like their updated 81 00:03:55,560 --> 00:03:59,320 version of clawed like clawed Sonnet 4.1 or something this 82 00:03:59,320 --> 00:04:01,040 week. So it's been and then also open 83 00:04:01,040 --> 00:04:04,560 air had the the open source model that came out, which 84 00:04:05,520 --> 00:04:08,120 everyone for whatever reason, declared not everyone, you know, 85 00:04:08,120 --> 00:04:10,680 whatever Twitter's algorithm wanted to show me like declared 86 00:04:10,680 --> 00:04:14,920 as like a a kind of a bust. It didn't seem like it truly 87 00:04:14,920 --> 00:04:17,839 wasn't met with like the DeepSeek, like ferocity. 88 00:04:18,640 --> 00:04:21,440 Well, DeepSeek was about other people being able to play catch 89 00:04:21,440 --> 00:04:26,040 up to open AI. So open AI, you know, there's 90 00:04:26,040 --> 00:04:28,760 such high expectations. I mean, the thing that open AI 91 00:04:28,760 --> 00:04:31,160 has that everybody else doesn't have is users. 92 00:04:31,480 --> 00:04:34,520 You know, just like there's the inertia that consumers will use 93 00:04:34,520 --> 00:04:36,880 whatever we have. Like we can say oh, the four O 94 00:04:36,880 --> 00:04:39,160 announcement was underwhelming, but it's like I'm going to chat 95 00:04:39,160 --> 00:04:42,280 to UBT and just waiting for the the thing to update. 96 00:04:42,880 --> 00:04:45,880 But I, there's like a, a more powerful model, which I think 97 00:04:45,880 --> 00:04:49,240 there's no debate as to whether or not 5 is better in most 98 00:04:49,240 --> 00:04:51,480 regards to like the earlier open AI models. 99 00:04:51,480 --> 00:04:53,200 Like is that going to drive more growth? 100 00:04:53,560 --> 00:04:55,600 Like who are these model updates really for? 101 00:04:55,840 --> 00:04:57,520 I, I get the like coding side of it. 102 00:04:57,520 --> 00:05:00,200 Like that's a very competitive field and Anthropic basically 103 00:05:00,200 --> 00:05:02,840 owns it now. So like open AI has business 104 00:05:02,840 --> 00:05:04,520 reasons to be a real player there. 105 00:05:04,520 --> 00:05:09,440 But you know what is Chachi BT is at like 700 million weekly 106 00:05:09,440 --> 00:05:12,240 users now. Like is the thing that takes him 107 00:05:12,240 --> 00:05:16,240 to a billion like 5 being that much more powerful or it's just 108 00:05:16,240 --> 00:05:19,400 like generally like there's still more that word that needs 109 00:05:19,400 --> 00:05:24,840 to to leak out to the non initiateds about like ChatGPT as 110 00:05:24,840 --> 00:05:28,720 a software rather than the fact that like 5 can do whatever 111 00:05:28,720 --> 00:05:31,720 logic puzzles slightly better. First I was like, this is an 112 00:05:31,720 --> 00:05:37,240 insane question because it's like, obviously you know, for 113 00:05:37,240 --> 00:05:41,000 consumers, they have to go find how the model can deliver value. 114 00:05:41,000 --> 00:05:43,520 And the smarter it is, the more value they'll get out of it and 115 00:05:43,520 --> 00:05:46,160 the more reasons they have it. If they're using the lot, open 116 00:05:46,160 --> 00:05:47,960 AI will find more ways to charge for it. 117 00:05:47,960 --> 00:05:51,720 So obviously, you know, a better model means a lot of stuff. 118 00:05:51,720 --> 00:05:54,560 And then, you know, real businesses that we'll build on 119 00:05:54,560 --> 00:05:58,400 top of the API will find use cases and be able to charge for 120 00:05:58,400 --> 00:06:01,760 it and hand hold users to the value. 121 00:06:02,040 --> 00:06:05,840 But I, I do agree with the a piece of the question, which is 122 00:06:05,840 --> 00:06:10,440 just like sort of astonishment that these models can be as 123 00:06:10,440 --> 00:06:13,840 impressive as they are today. And there's still lots of people 124 00:06:14,040 --> 00:06:16,280 who don't use them at all. And then some of us that do use 125 00:06:16,280 --> 00:06:20,040 the models, we're not really trying to apply them in all the 126 00:06:20,040 --> 00:06:22,920 cases we should. But but I think that's just 127 00:06:22,920 --> 00:06:25,800 because it's like the the sort of like, you know, businesses 128 00:06:25,800 --> 00:06:29,120 are going to need to build on top of these models to hand hold 129 00:06:29,120 --> 00:06:33,000 us to exactly the value. And so getting smarter is great 130 00:06:33,000 --> 00:06:36,520 for the API business and that's where I think a lot of the 131 00:06:36,520 --> 00:06:39,200 business could be long term. Yeah, but that implies that 132 00:06:39,200 --> 00:06:41,960 people were using earlier versions of the models and were 133 00:06:41,960 --> 00:06:45,640 underwhelmed by it because it was technically not as powerful 134 00:06:45,640 --> 00:06:47,760 as they wanted, when really could just be like they haven't 135 00:06:47,760 --> 00:06:49,720 been exposed to it. I'm talking about normies, 136 00:06:49,920 --> 00:06:51,400 right? Just people that would be using 137 00:06:51,400 --> 00:06:52,160 ChatGPT. I. 138 00:06:52,160 --> 00:06:54,400 Just think you know some hallucinations and you don't 139 00:06:54,400 --> 00:06:56,400 trust somebody you know somebody lies to you a couple times 140 00:06:56,400 --> 00:07:00,040 you're like don't trust you. You know, I, I, I think sort of 141 00:07:00,040 --> 00:07:03,720 consistency is really valuable in building trust. 142 00:07:03,720 --> 00:07:07,520 And so if these models can, can become just more reliable, and I 143 00:07:07,520 --> 00:07:09,320 think that's part of what open AI is saying here. 144 00:07:09,320 --> 00:07:13,360 It hallucinates less and that that could help it a lot. 145 00:07:13,560 --> 00:07:16,240 I mean, it's worth saying. I mean, while we want to get 146 00:07:16,320 --> 00:07:20,000 much more intelligent, part of the big development here is just 147 00:07:20,000 --> 00:07:23,880 that this is a unified model that open AI is going to route 148 00:07:23,880 --> 00:07:26,720 you to, Oh, you. This is a pretty easy question. 149 00:07:26,720 --> 00:07:29,720 We don't need the model to waste all its resources thinking about 150 00:07:29,720 --> 00:07:31,440 it. And oh, this is an intense 151 00:07:31,440 --> 00:07:32,600 question. We'll think about it. 152 00:07:32,800 --> 00:07:35,640 And so that could allow the model to operate great more 153 00:07:35,640 --> 00:07:39,080 efficiently and also just make it life easier for consumers to 154 00:07:39,080 --> 00:07:42,880 get great answers without having to pick the appropriate model. 155 00:07:43,320 --> 00:07:47,560 Yeah, I, I think it's both like a model selector, but also my 156 00:07:47,560 --> 00:07:50,080 understanding is that the models themselves have been improved. 157 00:07:50,360 --> 00:07:53,080 So it's not just like we've routed to the most useful thing 158 00:07:53,640 --> 00:07:57,360 to answer your question, but you know, the the tool, the tool 159 00:07:57,360 --> 00:08:00,520 itself is more powerful. Yeah, I, I don't know. 160 00:08:00,520 --> 00:08:02,640 I mean, I don't go you use this more than I do. 161 00:08:02,640 --> 00:08:06,160 I don't yet pay for the, the, the plus version of it, $20.00 a 162 00:08:06,160 --> 00:08:09,240 month is just I'm not there yet. I'm not sorry. 163 00:08:09,400 --> 00:08:12,040 I'm not even against it. I just like I haven't found $20 164 00:08:12,040 --> 00:08:14,240 worth of value for me that is like that much better than the 165 00:08:14,240 --> 00:08:16,560 free version. I just like proofread it, 166 00:08:16,560 --> 00:08:18,520 feedback, run my stories through it. 167 00:08:18,520 --> 00:08:20,000 What do you think? What am I missing? 168 00:08:20,000 --> 00:08:23,160 Like it always gives me a couple useful thoughts. 169 00:08:23,160 --> 00:08:25,120 Like, all right, it's a new model. 170 00:08:25,120 --> 00:08:28,520 I mean, I think the last word on it to me is just we always try 171 00:08:28,520 --> 00:08:31,600 to like decide whether it's a good model on the first day. 172 00:08:31,600 --> 00:08:33,600 And I think nobody knows right away. 173 00:08:33,600 --> 00:08:37,320 It takes, takes some time. We we write off models and then 174 00:08:37,320 --> 00:08:40,000 they become sort of our daily drivers. 175 00:08:40,000 --> 00:08:43,240 And then other times we get excited and then nothing. 176 00:08:43,240 --> 00:08:46,480 So I think we'll see people play around with them. 177 00:08:47,040 --> 00:08:48,800 Yeah. I also think we can't understate 178 00:08:48,800 --> 00:08:53,680 how significant it is for open AI in terms of, you know, it 179 00:08:53,680 --> 00:08:56,760 needing to be some kind of a leap for them because a lot of 180 00:08:56,760 --> 00:08:59,680 the conversation has been, you know, GPT, everything has been 181 00:08:59,720 --> 00:09:03,240 more or less iterations on four. We came out like a little bit 182 00:09:03,240 --> 00:09:05,360 over two years ago. So this is like a like, there's 183 00:09:05,360 --> 00:09:06,920 no way around this one. This wasn't. 184 00:09:07,160 --> 00:09:09,680 And you know that the back story of building this, you know, this 185 00:09:09,680 --> 00:09:13,080 model was that for a long time they were working on this giant 186 00:09:13,080 --> 00:09:14,280 model. Like I don't even know how many 187 00:09:14,280 --> 00:09:16,880 trillion parameter model that was. 188 00:09:16,920 --> 00:09:19,880 You know, they called it Orion internally and they realized 189 00:09:19,880 --> 00:09:22,080 most of the way through it kept being delayed and delayed and 190 00:09:22,080 --> 00:09:25,800 delayed that it wasn't showing off large enough improvements in 191 00:09:25,800 --> 00:09:29,160 capability for it to be for it to merit being called 5. 192 00:09:29,160 --> 00:09:32,280 And the same time, you know, this breakthrough came with like 193 00:09:32,280 --> 00:09:36,720 deep reasoning and, and in like logic, you know, the ability for 194 00:09:36,720 --> 00:09:39,160 it to like handle more complex gain of thought. 195 00:09:39,160 --> 00:09:43,320 And so they ended up calling Orion GPT 4.5 and it's basically 196 00:09:43,320 --> 00:09:45,480 unused as a model. No one really talks about it, 197 00:09:45,840 --> 00:09:48,400 but 5 is the real deal. Like it has to be something. 198 00:09:48,400 --> 00:09:50,480 It can't just be written off as like, yeah, we're still 199 00:09:50,480 --> 00:09:53,760 iterating on something. And this does not feel, it does 200 00:09:53,760 --> 00:09:58,280 not feel like what the four, what was the iPhone 4, the one 201 00:09:58,280 --> 00:10:01,160 where it's like, oh, new mock or it's like they have the App 202 00:10:01,160 --> 00:10:02,920 Store. And, well, 10X, right? 203 00:10:03,240 --> 00:10:05,040 The iPhone X the first time they had like the full. 204 00:10:05,040 --> 00:10:08,240 Screen, it's not like that it's not one of the big iPhone 205 00:10:08,240 --> 00:10:10,160 moments where it's like, oh, they really changed it. 206 00:10:10,160 --> 00:10:12,640 This is like, Oh yeah, they they come out with new phones every 207 00:10:12,640 --> 00:10:16,560 once in awhile and sometimes we we try to get ourselves excited 208 00:10:16,560 --> 00:10:20,200 about it and that's how this feels to me and I agree yeah, 209 00:10:20,400 --> 00:10:22,240 we've been talking about 5 for a long time. 210 00:10:22,560 --> 00:10:24,600 Thought 5 would be an insane moment. 211 00:10:24,600 --> 00:10:28,880 And so far I'm not seeing that level of like hysterical 212 00:10:28,880 --> 00:10:32,440 euphoria that I, I would have expected, you know, six months 213 00:10:32,440 --> 00:10:35,720 ago for ChatGPT 5. Yeah, which again, like back to 214 00:10:35,720 --> 00:10:38,280 what you said earlier is maybe why people are expecting Gemini 215 00:10:38,280 --> 00:10:42,080 to leap ahead because opening eyes best shot just didn't blow 216 00:10:42,080 --> 00:10:44,640 people away as much as, you know, maybe unrealistic 217 00:10:44,640 --> 00:10:48,120 expectations LED them to think like they're in a big fight in, 218 00:10:48,120 --> 00:10:50,120 in terms of model quality. Now, like you, you've got 219 00:10:50,120 --> 00:10:53,760 Anthropic very capably putting out stuff, you know, Meta, I'm 220 00:10:53,760 --> 00:10:57,240 assuming will come out with something of of value. 221 00:10:57,240 --> 00:10:59,240 And, you know, Google is very serious. 222 00:10:59,840 --> 00:11:01,880 Microsoft still irrelevant, by the way. 223 00:11:01,920 --> 00:11:03,960 Like I'm never not gonna say until they do something real 224 00:11:03,960 --> 00:11:04,880 here. Yeah. 225 00:11:04,880 --> 00:11:07,200 Like it's just a very different landscape than when 4 came out. 226 00:11:07,960 --> 00:11:11,080 Let's talk about a related but different topic. 227 00:11:11,200 --> 00:11:17,240 So the CapEx build out, data center build out, we we're in 228 00:11:17,240 --> 00:11:19,440 this moment. And I keep telling this to other 229 00:11:19,440 --> 00:11:21,960 people AI adjacent. They're like, man, AI is 230 00:11:21,960 --> 00:11:24,120 apparently like propping up the entire economy. 231 00:11:24,120 --> 00:11:28,440 It's like, thank God, you know, we're in the orbiting artificial 232 00:11:28,440 --> 00:11:31,360 intelligence because that's that's the thing, saving the 233 00:11:31,360 --> 00:11:33,600 economy. And you know what they have to 234 00:11:33,600 --> 00:11:36,040 say like. The Wall Street Journal when I 235 00:11:36,120 --> 00:11:39,240 was covering AI so now. You're working for, you know, 236 00:11:39,520 --> 00:11:42,720 company with an AI conference. So even we got even closer to 237 00:11:42,720 --> 00:11:43,080 it. They, they. 238 00:11:43,360 --> 00:11:45,840 Yeah, that was the problem. I wasn't close enough to AI. 239 00:11:46,240 --> 00:11:48,320 Exactly. But the the thing say, you know, 240 00:11:48,320 --> 00:11:51,400 it's the infrastructure build out, that there's real capital 241 00:11:51,720 --> 00:11:55,080 expenditures going into this and that the big tech giants, you 242 00:11:55,080 --> 00:11:57,840 know, are spending aggressively. Yeah, basically what I saw 243 00:11:57,840 --> 00:11:59,520 happen. And it's kind of funny when like 244 00:11:59,520 --> 00:12:02,680 an idea just percolates through, you know, the discourse. 245 00:12:02,680 --> 00:12:05,160 But you had at least three different articles come out in 246 00:12:05,160 --> 00:12:09,640 the last two weeks pointing out. We, we were earlier than some of 247 00:12:09,640 --> 00:12:13,600 this like sorry, there, there. Is this what Kadroski or 248 00:12:13,600 --> 00:12:16,280 whatever he sort of initiated it? 249 00:12:16,440 --> 00:12:20,040 Is it Paul or Peter? Yeah, that's Paul Kadroski I saw 250 00:12:20,920 --> 00:12:23,160 so we. Riffed on that like a couple 251 00:12:23,160 --> 00:12:27,520 weeks ago and now yeah, The Journal Noah Smith A bunch of 252 00:12:27,520 --> 00:12:31,440 people are like, oh, maybe everybody loves a good oh, the 253 00:12:31,440 --> 00:12:35,320 world could end in financial collapse thesis and that's sort 254 00:12:35,320 --> 00:12:37,240 of what what this is right? Yeah. 255 00:12:37,240 --> 00:12:41,400 And essentially and what I think Kedrosky's article did very did 256 00:12:41,400 --> 00:12:43,600 a very good job explaining was like you know and we had some 257 00:12:43,600 --> 00:12:46,320 new GDP numbers coming out. It's also earning season so 258 00:12:46,320 --> 00:12:49,720 people can more easily calculate what like the the CapEx spending 259 00:12:49,720 --> 00:12:53,040 looks like for all the biggest companies, but a non 260 00:12:53,040 --> 00:12:56,640 insignificant percentage of it, what was it like almost 1% of of 261 00:12:56,640 --> 00:13:00,000 GDP growth came from AI CapEx spending. 262 00:13:00,840 --> 00:13:04,920 And that is, you know, like the chart that that Kedrosky put 263 00:13:04,920 --> 00:13:08,440 together showed that, you know, outside of the building of the 264 00:13:08,440 --> 00:13:12,360 railroads and like the telecom build out duringthe.com bubble, 265 00:13:13,160 --> 00:13:17,200 you know, you have you seen that much of GDP growth confined to 266 00:13:17,200 --> 00:13:19,280 one particular sector? And it's a, you know, an 267 00:13:19,280 --> 00:13:22,640 infrastructure build out that at least in the case of AI is like 268 00:13:22,640 --> 00:13:26,920 well ahead of it's, you know, it's, it's broad, broad based 269 00:13:27,160 --> 00:13:30,920 adoption. And I guess, you know, the, the 270 00:13:30,920 --> 00:13:33,640 next question to all of this is like, well, is this a bubble? 271 00:13:33,640 --> 00:13:36,360 Is this something that could potentially bring down the 272 00:13:36,360 --> 00:13:40,440 economy if AI doesn't end up becoming what a lot of people 273 00:13:40,440 --> 00:13:43,920 are expecting? And I, I, you know, I want to 274 00:13:43,920 --> 00:13:46,760 take the bear case on this one because it's more interesting to 275 00:13:46,760 --> 00:13:50,120 me and, and say, like, Oh yeah, we're absolutely circulating, 276 00:13:50,160 --> 00:13:53,880 you know, a, a Bear Stearns like event where, you know, AI 277 00:13:53,880 --> 00:13:55,920 doesn't, you know, doesn't pan out. 278 00:13:56,120 --> 00:13:59,120 But I just don't see it. Like I can't follow the train of 279 00:13:59,560 --> 00:14:02,520 the train of thought that leads me to AI. 280 00:14:02,560 --> 00:14:06,880 You know, CapEx spending is going to somehow when AI doesn't 281 00:14:06,880 --> 00:14:10,880 get as widely adopted, result in like the collapse of, you know. 282 00:14:10,880 --> 00:14:12,360 Like 10%. Unemployment. 283 00:14:12,760 --> 00:14:16,560 This is like Meta going on on the metaverse, like they spent 284 00:14:16,560 --> 00:14:19,440 tons of money trying to do that and like, well, didn't work. 285 00:14:19,640 --> 00:14:23,880 The the key here is that the Max 7 they make tons of money and so 286 00:14:24,720 --> 00:14:27,160 they can spend a bunch on CapEx for everybody. 287 00:14:27,160 --> 00:14:31,560 But Meta, it's still, I think less than their actual sort of 288 00:14:31,560 --> 00:14:33,960 cloud revenue, right? And even if it were bigger, it's 289 00:14:33,960 --> 00:14:37,200 just like they stopped doing it one day and they say, OK, well, 290 00:14:37,240 --> 00:14:40,960 we'll print money again. Like I, I don't see the debt 291 00:14:40,960 --> 00:14:42,400 story. I know some of these things are 292 00:14:42,400 --> 00:14:45,960 like financed, but they're super valuable companies that could 293 00:14:45,960 --> 00:14:49,280 raise unlimited sums of money that produce real cash. 294 00:14:49,280 --> 00:14:52,440 Like, yeah, they're monopoly. What's, what do you like? 295 00:14:52,440 --> 00:14:54,040 If you're a monopoly, what are you going to do with that, 296 00:14:54,480 --> 00:14:56,040 right? If you have just an incredible 297 00:14:56,040 --> 00:14:58,960 margin, you have cash flow like crazy cash flow. 298 00:14:59,280 --> 00:15:01,840 The money's got to go somewhere. You could do stock buybacks. 299 00:15:02,160 --> 00:15:05,120 You could. And this is a good thing. 300 00:15:05,200 --> 00:15:08,160 Like, wouldn't we? I feel like the sort of left 301 00:15:08,160 --> 00:15:11,240 it's like, oh, you know, share buybacks, like exactly what 302 00:15:11,240 --> 00:15:12,800 you're saying. Share buybacks and dividends are 303 00:15:12,800 --> 00:15:14,800 they're bad. They're not doing anything. 304 00:15:14,800 --> 00:15:17,360 It's like here they are. They're excited about something 305 00:15:17,360 --> 00:15:20,160 in the future and they're investing in the real world 306 00:15:20,160 --> 00:15:23,480 infrastructure to run at it. I mean, I think if you believe 307 00:15:23,560 --> 00:15:26,800 AI will be good for the world, then it's like, great, yeah. 308 00:15:26,960 --> 00:15:30,160 So what if they're spending a little bit ahead of, you know, 309 00:15:30,240 --> 00:15:33,240 themselves and they they find out they sort of overbuilt too 310 00:15:33,240 --> 00:15:34,600 soon? Yeah. 311 00:15:34,840 --> 00:15:37,240 I guess like there's an argument that like the actual technology 312 00:15:37,240 --> 00:15:38,840 that you're building is something that's going to be 313 00:15:38,840 --> 00:15:42,040 like job displacing. So like there's a medium to long 314 00:15:42,040 --> 00:15:44,160 term impact of building up the technology there. 315 00:15:44,160 --> 00:15:46,800 But like, I mean, that gets into like the, you know, kind of 316 00:15:46,800 --> 00:15:48,920 technophobic argument of like, well, what do you want to do? 317 00:15:48,920 --> 00:15:51,160 Not invest in this technology that's going to be 318 00:15:51,160 --> 00:15:54,440 transformative like I never and I again, I'd love to take the 319 00:15:54,440 --> 00:15:57,040 bear case here, but I just can't follow that logic of like, let's 320 00:15:57,280 --> 00:15:59,600 let's not do the thing that could potentially create like 321 00:15:59,600 --> 00:16:02,120 God. And the people making those 322 00:16:02,120 --> 00:16:05,360 arguments are always on their iPhones, you know, they're just 323 00:16:05,360 --> 00:16:08,360 like, it's they, they're once like, I mean what? 324 00:16:08,360 --> 00:16:12,040 It's the Chapo's of the world who are like anti tech, but then 325 00:16:12,040 --> 00:16:14,520 they're clearly like tech addicted. 326 00:16:14,520 --> 00:16:18,600 You know, it's like they never choose not to use the products 327 00:16:18,600 --> 00:16:21,600 that they say, oh, we shouldn't we shouldn't build the next one, 328 00:16:21,600 --> 00:16:23,400 even though I love the current one. 329 00:16:23,920 --> 00:16:25,040 Yeah, it never makes. Yeah, I don't. 330 00:16:25,040 --> 00:16:27,240 Want to go too let's I would want to save that part of the 331 00:16:27,240 --> 00:16:29,480 conversation for a different episode because I do think there 332 00:16:29,480 --> 00:16:32,160 is something to say about like the social impact of AI and the 333 00:16:32,160 --> 00:16:35,160 effect that it's having on like intelligence and like 334 00:16:35,160 --> 00:16:38,200 sociability and like. You know, trying to think about 335 00:16:38,240 --> 00:16:41,520 stuff like, I think like people not reading, I mean, we talked 336 00:16:41,520 --> 00:16:44,880 about this on the Rupal Valley podcast. 337 00:16:44,880 --> 00:16:47,800 I made a defensive reading and writing. 338 00:16:47,840 --> 00:16:51,240 I, I, I do worry about that. But to me that's more of a 339 00:16:51,240 --> 00:16:55,000 social media phenomenon. AI as it exists right now in a 340 00:16:55,000 --> 00:16:59,360 chat bot actually makes you like sort of think and write and 341 00:16:59,360 --> 00:17:01,200 engage. I I think it's much more 342 00:17:01,200 --> 00:17:02,840 intelligent than sort of the leaner force. 343 00:17:02,840 --> 00:17:04,200 You're forced me into this argument now. 344 00:17:04,480 --> 00:17:08,680 Yeah, Yeah, I think, I think the intent aspect of, you know, 345 00:17:08,680 --> 00:17:12,160 ChatGPT is much better than the passive and engagement of social 346 00:17:12,160 --> 00:17:14,000 media. There's no question to me that 347 00:17:14,000 --> 00:17:15,839 that is an improvement. I think the idea of and. 348 00:17:15,839 --> 00:17:19,440 Social media is built on engagement, whereas at least for 349 00:17:19,440 --> 00:17:23,880 now, chat bots are predicated on getting you truthful answers and 350 00:17:23,880 --> 00:17:27,400 appearing smart on tests. So obviously they're much more 351 00:17:27,400 --> 00:17:32,320 virtuous than feeds. I think outsourcing writing and 352 00:17:32,320 --> 00:17:36,160 all thought to an AI is like problematic for a society. 353 00:17:36,160 --> 00:17:39,280 Like rather than cogitating over an issue, yeah, yeah. 354 00:17:39,280 --> 00:17:41,760 Or like, I need to fire these employees, how can you please 355 00:17:41,760 --> 00:17:44,440 write this for me so I don't have to deal with, like, the 356 00:17:44,440 --> 00:17:47,560 emotional labor of what it means to communicate to someone is 357 00:17:47,560 --> 00:17:50,240 like a net negative on society. Like I think there's all kinds 358 00:17:50,240 --> 00:17:53,760 of bad things that like asking someone to imitate human emotion 359 00:17:53,760 --> 00:17:58,240 and logic and having that be like, then put in your own words 360 00:17:58,400 --> 00:18:01,480 like has on a society. But I don't think that's what 361 00:18:01,480 --> 00:18:06,680 Kedrosky was getting at in his No, we're pretty far from you. 362 00:18:06,680 --> 00:18:09,120 Force me into it. A piece of it. 363 00:18:09,400 --> 00:18:11,480 Yeah. Look, I think there's also like, 364 00:18:12,040 --> 00:18:15,760 yeah, for the Mag 7. I don't know remember exactly 365 00:18:15,760 --> 00:18:19,720 who's in in the Mag 7 but but for all these companies. 366 00:18:19,960 --> 00:18:21,960 Alphabet. Yeah, these are like cash 367 00:18:21,960 --> 00:18:25,760 machines, like they have no issue investing in in in 368 00:18:25,760 --> 00:18:27,280 infrastructure. They're not taking on huge 369 00:18:27,280 --> 00:18:29,880 amounts of debt. There are companies in the AI 370 00:18:29,880 --> 00:18:31,960 mix that I'm a little bit more concerned about. 371 00:18:32,040 --> 00:18:35,560 Oracle, which I pay attention to, is taking on debt so they 372 00:18:35,560 --> 00:18:38,760 can finance the Stargate shit that they're doing with open AI. 373 00:18:38,760 --> 00:18:42,400 Isn't Oracle just they're like professionally rich and good at 374 00:18:42,400 --> 00:18:44,960 selling tax? I mean, I haven't dug into them 375 00:18:44,960 --> 00:18:48,840 as much as you, but they have they're doing the financing 376 00:18:48,840 --> 00:18:50,520 because they have have money, right. 377 00:18:50,960 --> 00:18:52,400 Yeah. And like so far no one's like 378 00:18:52,400 --> 00:18:54,680 freaking out about Oracle because they're taking on debt 379 00:18:54,680 --> 00:18:57,400 to like, you know, buy the GP us that are going to be in the 380 00:18:57,400 --> 00:18:59,400 Stargate data centers. But they're just in a different 381 00:18:59,400 --> 00:19:03,360 class of company than the MAG 7 because they're not in the MAG 382 00:19:03,360 --> 00:19:05,320 7. And you know, there's also ones 383 00:19:05,320 --> 00:19:09,400 like like core Weave, which you know, is a crazily valued stock 384 00:19:09,400 --> 00:19:12,840 right now and they're taking on they they keep going back to the 385 00:19:12,840 --> 00:19:15,840 debt markets to to do build out. So there are some like there is 386 00:19:15,840 --> 00:19:19,640 some concerning leverage I think for some of these companies that 387 00:19:19,640 --> 00:19:23,200 that are taking on debt, but it doesn't seem like a load bearing 388 00:19:23,200 --> 00:19:26,520 beam that if those things go under like you're going to see a 389 00:19:26,560 --> 00:19:29,440 2008 like event happen or even I'm. 390 00:19:29,520 --> 00:19:33,240 Definitely open to a world where here's the bull case. 391 00:19:33,400 --> 00:19:37,200 Sorry, the bear case to me, which I'm not necessarily 392 00:19:37,200 --> 00:19:44,280 subscribed to, is all the tech stocks are massively inflated 393 00:19:44,600 --> 00:19:50,120 because they're investing in the technology that's driving some 394 00:19:50,120 --> 00:19:53,560 of their revenue and driving their multiples. 395 00:19:53,720 --> 00:19:57,320 Because basically it's like, we're gonna, you know, big tech 396 00:19:57,320 --> 00:20:01,320 companies are the biggest investors in AI startups. 397 00:20:01,440 --> 00:20:04,480 Those startups are turning around spending on cloud 398 00:20:04,480 --> 00:20:06,320 computing and foundation models and stuff. 399 00:20:06,840 --> 00:20:08,760 Where they're, they're generating revenue, so they're 400 00:20:08,760 --> 00:20:11,440 spending money to make money instead of old, you know, 401 00:20:11,440 --> 00:20:16,080 revenue round tripping issue. And then the opportunity of AI 402 00:20:16,080 --> 00:20:18,520 is also increasing their multiples. 403 00:20:18,520 --> 00:20:22,800 So I could see a world where all right, you know, suddenly AI is 404 00:20:22,800 --> 00:20:26,240 not delivering as much as people thought or AI is delivering, but 405 00:20:26,400 --> 00:20:29,160 there's no margin to be had because open source is so 406 00:20:29,160 --> 00:20:32,600 successful. And then all the stocks crash 407 00:20:32,600 --> 00:20:35,960 and they crash because, you know, they're, they're sort of 408 00:20:36,160 --> 00:20:38,800 benefiting in multiple ways, both revenue and multiples. 409 00:20:39,200 --> 00:20:42,440 And so that would hurt them. And I think given that they're 410 00:20:42,440 --> 00:20:46,760 so important to the performance of the S&P 500, it would just be 411 00:20:46,760 --> 00:20:49,240 like a bleak, you know, the American economy would all of a 412 00:20:49,240 --> 00:20:52,080 sudden everybody would feel much poorer because the value of like 413 00:20:52,080 --> 00:20:53,720 the stock market has gone down so much. 414 00:20:54,000 --> 00:20:56,160 But it doesn't seem, it seems like, oh, we're all just like a 415 00:20:56,160 --> 00:20:58,240 lot poorer. I, I don't see this sort of like 416 00:20:58,560 --> 00:21:00,040 ripple effect. They're companies that make a 417 00:21:00,040 --> 00:21:02,040 lot of money. They make way less, they're way 418 00:21:02,040 --> 00:21:03,880 less valuable. And then suddenly America just 419 00:21:03,880 --> 00:21:08,640 feels weaker relative to the rest of the global economy. 420 00:21:08,640 --> 00:21:12,440 But I don't necessarily see like who's going bankrupt. 421 00:21:13,480 --> 00:21:15,440 Yeah. And like, let's just also 422 00:21:15,440 --> 00:21:18,600 remember that, like these companies all crushed earnings 423 00:21:19,240 --> 00:21:21,320 these last two weeks. Like they're foundational. 424 00:21:21,400 --> 00:21:22,720 Bullish. And they're AI. 425 00:21:23,320 --> 00:21:24,640 Yeah. It's like it's clearly this is 426 00:21:24,640 --> 00:21:26,560 where things are going. We spend all our time on the 427 00:21:26,560 --> 00:21:29,840 Internet like these companies are the main entities innovating 428 00:21:29,840 --> 00:21:33,360 in the world. Like they're very sophisticated 429 00:21:33,360 --> 00:21:35,320 businesses. Yeah, I don't, I don't know. 430 00:21:35,400 --> 00:21:37,560 I'm pretty bullish. Yeah. 431 00:21:37,880 --> 00:21:42,000 I guess the part of it that I think is worth being concerned 432 00:21:42,000 --> 00:21:46,680 about or paying attention to is the fact that it is a non 433 00:21:47,120 --> 00:21:50,760 marginal part of GDP growth like spending on these things and 434 00:21:50,760 --> 00:21:52,320 like you have to just pay attention to that. 435 00:21:52,320 --> 00:21:55,880 Like whenever one sector is that responsible for like absent all 436 00:21:55,880 --> 00:21:58,240 of these things that we would kind of have fairly anemic 437 00:21:58,480 --> 00:22:02,120 growth. And you know, the argument also 438 00:22:02,120 --> 00:22:04,280 is like, well, that's fine because this is transformative. 439 00:22:04,480 --> 00:22:06,080 Like we should be investing in these things. 440 00:22:06,080 --> 00:22:08,440 And like this is all going to like later lead toward even more 441 00:22:08,440 --> 00:22:11,040 growth because we're going to have all this efficiency and and 442 00:22:11,040 --> 00:22:12,440 then people will be more productive. 443 00:22:13,320 --> 00:22:16,480 But it's like it's getting into the territory where it's 444 00:22:16,480 --> 00:22:18,520 interwoven into the broader economy. 445 00:22:18,520 --> 00:22:22,080 It's not just like some tech experiment of, you know, some 446 00:22:22,160 --> 00:22:24,600 companies building something that could be cool like this is 447 00:22:24,600 --> 00:22:28,320 now part of it. Like you're, you know, you're 448 00:22:28,320 --> 00:22:31,520 woven into the fabric of what's making the economy work and 449 00:22:32,200 --> 00:22:34,200 problems within that. I don't mean we won't even 450 00:22:34,200 --> 00:22:36,360 foresee what the problem could be, but problems within that 451 00:22:36,360 --> 00:22:38,920 will have ripple effects. And that's it's just worth 452 00:22:38,920 --> 00:22:40,760 paying attention to. Like I don't see the warning 453 00:22:40,760 --> 00:22:43,520 signs yet. But like it's, you know, it's 454 00:22:43,520 --> 00:22:46,160 built into it. Well, it's just also just it's 455 00:22:46,160 --> 00:22:49,560 been too long, you know, in between crashes, right? 456 00:22:49,560 --> 00:22:52,400 Like you know what? I In startups, there was a 457 00:22:52,400 --> 00:22:54,760 downturn, You know, 2021 was a peak. 458 00:22:55,560 --> 00:22:57,120 We came down. There were all these software 459 00:22:57,120 --> 00:23:01,240 companies that were overvalued. We did have a a minor correction 460 00:23:01,840 --> 00:23:04,800 because of the pandemic inflating the value of tech 461 00:23:04,800 --> 00:23:08,080 stocks and driving forward revenue that then slowed down. 462 00:23:08,480 --> 00:23:12,440 But yeah, I came around at just the perfect time. 463 00:23:12,440 --> 00:23:15,240 And like, there's no, like there's no morality play there. 464 00:23:15,240 --> 00:23:17,640 It's like, oh, we should have, we should have really taken our 465 00:23:17,640 --> 00:23:20,240 comeuppance more. It's like, no, we got lucky that 466 00:23:20,240 --> 00:23:24,440 there was like another really cool idea just as tech was about 467 00:23:24,440 --> 00:23:27,480 to take it pretty hard from getting overexcited about 468 00:23:27,480 --> 00:23:30,440 everybody working remotely. And so that that sort of safe 469 00:23:30,440 --> 00:23:32,600 things. And that is the tech idea that 470 00:23:32,600 --> 00:23:34,480 it's like, oh, we'll keep up coming up with new ideas and the 471 00:23:34,480 --> 00:23:38,200 new ideas are are real things and that will create value. 472 00:23:38,200 --> 00:23:41,640 And it's not just like financial games like on Wall Street. 473 00:23:42,120 --> 00:23:43,680 Right. And it's also just kind of the 474 00:23:43,680 --> 00:23:46,240 way things work. Like I I see this argument being 475 00:23:46,240 --> 00:23:49,120 applied to San Francisco and be like man if it wasn't for the AI 476 00:23:49,120 --> 00:23:50,880 boom San Francisco would really be fuck. 477 00:23:51,360 --> 00:23:53,520 Right, that's just a job. They're all hard at work, like 478 00:23:53,520 --> 00:23:55,160 coming up with a new thing, going where it's. 479 00:23:55,160 --> 00:23:58,160 Kind of what they do here, there's always something, man. 480 00:23:58,160 --> 00:24:00,280 It's like, man, if it wasn't for the Gold Rush, San Francisco 481 00:24:00,280 --> 00:24:02,120 would really be. Fight right, right. 482 00:24:02,880 --> 00:24:05,440 Yeah, it's, it's like that's not really the argument you think it 483 00:24:05,440 --> 00:24:08,200 is, because that's just like that's how a boom economy tends 484 00:24:08,200 --> 00:24:10,320 to work. And the fact that, like, San 485 00:24:10,320 --> 00:24:13,480 Francisco keeps coming up with the new thing that matters to 486 00:24:13,480 --> 00:24:17,320 the economy is why, like. Detroit good at is they all left 487 00:24:17,320 --> 00:24:20,040 crypto because crypto stopped making them money and they shift 488 00:24:20,040 --> 00:24:22,920 over to AI. And honestly, you want things to 489 00:24:22,920 --> 00:24:26,320 die so that people can go to the actual productive parts of the 490 00:24:26,320 --> 00:24:30,360 economy and, you know, yeah. Well, you're closer to the 491 00:24:30,360 --> 00:24:33,200 crypto people than I am. But like, like, are they all 492 00:24:33,200 --> 00:24:35,120 just like riding a false high right now? 493 00:24:35,120 --> 00:24:38,000 Like knowing that the the value of all of their holdings is like 494 00:24:38,160 --> 00:24:40,280 not really logical at all That like what? 495 00:24:40,280 --> 00:24:43,160 Do you mean Bitcoin? I mean the dollar is eroding at 496 00:24:43,160 --> 00:24:45,800 the moment. So I mean Bitcoin is like there 497 00:24:45,800 --> 00:24:48,680 is, there is, I mean, I, I don't hold a lot of Bitcoin. 498 00:24:48,680 --> 00:24:51,680 I, you know, I have what, $1000 worth or something, but like 499 00:24:53,240 --> 00:24:57,880 definitely, I, I think, you know, Bitcoin is a psychological 500 00:24:57,960 --> 00:25:01,600 investment thing, just like, you know, so many things and it's a 501 00:25:01,600 --> 00:25:05,200 bet against the dollar. And I, I think the dollar is in 502 00:25:05,200 --> 00:25:06,800 a bad place. So I don't, I don't know. 503 00:25:07,960 --> 00:25:10,640 I, I think the other thing in crypto, which this is, you know, 504 00:25:10,640 --> 00:25:14,120 it's just that it's like fraud is legal and there's tons of 505 00:25:14,120 --> 00:25:16,120 fraud in crypto. And so it's like you can do 506 00:25:16,120 --> 00:25:19,240 whatever you want seemingly. And so I think that's going to 507 00:25:19,240 --> 00:25:21,640 open up some activity. Right. 508 00:25:21,760 --> 00:25:24,520 Well, I'm just thinking about it because, you know, I, I was 509 00:25:25,120 --> 00:25:29,960 reading our buddy Mike Isaac's story about San Francisco and 510 00:25:29,960 --> 00:25:32,880 like, you know, this moment, the, you know, the AI moment and 511 00:25:32,880 --> 00:25:36,320 how we've moved to the hard tech era in, in Silicon Valley. 512 00:25:36,320 --> 00:25:37,840 And you know, he had this like 1. 513 00:25:37,840 --> 00:25:40,400 The clause in there of like San Francisco is used to like things 514 00:25:40,400 --> 00:25:43,960 like blowing up and like, he's like, like crypto and he's like 515 00:25:43,960 --> 00:25:47,840 also things tanking crypto, which is like a funny structure, 516 00:25:48,000 --> 00:25:51,400 but also like, like crypto is not tanking right now. 517 00:25:51,400 --> 00:25:53,840 It's just in terms of like the value of the currencies, it's 518 00:25:53,840 --> 00:25:56,840 actually really high. So that wasn't the best analogy. 519 00:25:57,000 --> 00:25:58,240 Did you read that piece by the way? 520 00:25:59,000 --> 00:26:03,080 Yeah, I, I read some of it. I mean, I, I don't get, you 521 00:26:03,080 --> 00:26:07,640 know, it's just the, the trend story sort of thing. 522 00:26:07,640 --> 00:26:10,040 You know, it's like this is the New York Times, you know, it's 523 00:26:10,040 --> 00:26:13,040 like this, this is where we are. I mean, I, I think it's 524 00:26:13,040 --> 00:26:15,720 generally correct. You know, it's just like, I 525 00:26:15,720 --> 00:26:19,160 don't know, it's not, it's too high level. 526 00:26:19,160 --> 00:26:21,680 I guess, Yeah. I mean, first of all, you know, 527 00:26:21,680 --> 00:26:24,560 Mike's a buddy and I always, you know, want to support my friends 528 00:26:24,560 --> 00:26:27,600 work and, you know, the New York Times, you know, loves calling a 529 00:26:27,600 --> 00:26:30,240 moment and explaining to the normies what's going on here. 530 00:26:31,120 --> 00:26:33,560 You know, there's always like kind of a combination of like 531 00:26:34,000 --> 00:26:36,520 things that have been going on for like years that we just call 532 00:26:36,520 --> 00:26:37,920 is like, oh, this is just happening now. 533 00:26:37,920 --> 00:26:41,400 It's like the year of efficiency I think was like 2022. 534 00:26:41,400 --> 00:26:44,240 So it's hard to say That's like specific to the crypt. 535 00:26:44,240 --> 00:26:46,920 A lot of things about tech are just. 536 00:26:47,160 --> 00:26:49,440 Things humans do and a lot of things people hate about the 537 00:26:49,440 --> 00:26:53,200 media are just things humans do. And a thing humans do are say 538 00:26:53,680 --> 00:26:55,240 what is what is the mood of the moment? 539 00:26:55,240 --> 00:26:56,680 And, you know, there were tech buses. 540 00:26:56,680 --> 00:26:58,760 The, you know, we have these narratives in The New York 541 00:26:58,760 --> 00:27:00,520 Times. And I think Mike's story does a 542 00:27:00,520 --> 00:27:04,000 good job of trying to sort of coalesce, like where where's our 543 00:27:04,000 --> 00:27:05,840 headspace at? And obviously these things are 544 00:27:05,840 --> 00:27:07,280 all, you know. Yeah. 545 00:27:07,280 --> 00:27:07,760 So. But. 546 00:27:07,840 --> 00:27:09,760 There, but there is something different. 547 00:27:09,760 --> 00:27:12,840 I was talking to our our colleague Jonathan Weber about 548 00:27:12,840 --> 00:27:14,240 this. Like I think there is something 549 00:27:14,240 --> 00:27:18,640 worth examining about, you know, what does the AI moment, how 550 00:27:18,640 --> 00:27:22,720 does it compare to previous booms and busts and waves of 551 00:27:22,720 --> 00:27:24,680 technology? And like, there's no question. 552 00:27:24,680 --> 00:27:27,960 And like his article starts off with his interesting analogy of 553 00:27:27,960 --> 00:27:32,720 Silicon Valley and like the rest and vest era and how you know 554 00:27:33,120 --> 00:27:34,240 there was a time starts. Off. 555 00:27:34,240 --> 00:27:37,800 I know we love him, but he starts off in fiction. 556 00:27:38,120 --> 00:27:41,280 He talks about Silicon Valley, the show, and he's like, oh, but 557 00:27:41,280 --> 00:27:43,680 it was really truthy. It's like, oh man, of all 558 00:27:43,680 --> 00:27:45,920 places, I wish the New York Times wasn't sort of doing. 559 00:27:45,920 --> 00:27:49,560 That's like, well, I, I have to, I have to do a disclosure on 560 00:27:49,560 --> 00:27:53,360 anything related to that show because I was briefly an advisor 561 00:27:53,360 --> 00:27:55,800 to it and my brother was an executive producer on it, so. 562 00:27:55,800 --> 00:27:58,680 I was once a storyboard meeting with that, yeah. 563 00:27:58,680 --> 00:28:00,920 Associate Producer. I had multiple meetings in a 564 00:28:00,920 --> 00:28:02,760 cameo. Your brother was like legit on 565 00:28:02,760 --> 00:28:04,080 the show. Yeah, yeah, yeah, yeah. 566 00:28:04,080 --> 00:28:06,000 No, but there was a lot of research that went into it. 567 00:28:06,000 --> 00:28:09,000 So it's very accurate. So I know, but but but but I 568 00:28:09,000 --> 00:28:11,600 will say him using, you know, Silicon Valley and the rest 569 00:28:11,600 --> 00:28:13,160 invest moment. This is about like the pamper 570 00:28:13,160 --> 00:28:16,080 tech, you know, employee. This was like the Google Plex. 571 00:28:16,080 --> 00:28:19,600 This was like whatever Odwalla juices and whatever dumb shit 572 00:28:19,600 --> 00:28:22,400 people associated with the time. And like now things are austere. 573 00:28:22,560 --> 00:28:24,920 We have to go back into the office, which is really, you 574 00:28:24,920 --> 00:28:28,040 know, unfair to make people do. And you know, what we're 575 00:28:28,040 --> 00:28:33,840 building now is maybe more. Era of the $100 million 576 00:28:33,840 --> 00:28:36,880 Facebook. Yeah, but that's interesting 577 00:28:36,880 --> 00:28:38,800 too, right? Like, yeah, is this like an era 578 00:28:38,800 --> 00:28:40,840 of austerity and efficiency because you're making people go 579 00:28:40,840 --> 00:28:42,920 to the office? But also apparently everyone at 580 00:28:42,920 --> 00:28:46,200 opening I got like a $1.5 million retention package, 581 00:28:46,320 --> 00:28:48,840 right? Now instead of spending the 582 00:28:48,840 --> 00:28:51,440 money on perks, which I think some of the perks were like tax 583 00:28:51,440 --> 00:28:54,280 efficient, you know, it's you get, you can deduct food in the 584 00:28:54,280 --> 00:28:56,840 office. So but IT projects softness Now 585 00:28:56,840 --> 00:28:59,760 it's just like, fine, give, give them cash and say work hard. 586 00:29:00,240 --> 00:29:02,680 Yeah, yeah, hundreds of millions of dollars. 587 00:29:02,680 --> 00:29:04,640 That is a fairly select group of people. 588 00:29:04,640 --> 00:29:06,640 I don't know if it's going to have the ripple effect, but. 589 00:29:07,880 --> 00:29:11,040 The last thing we wanted to talk about was, you know, Tim Apple, 590 00:29:11,040 --> 00:29:14,280 Tim Cook being right, right? He's like in the White House 591 00:29:14,280 --> 00:29:17,040 between Trump and JD Vance, right? 592 00:29:17,040 --> 00:29:20,240 Like, just as they're saying terrible stuff, he's giving 593 00:29:20,240 --> 00:29:23,280 Trump 24 karat gold. I don't know enough. 594 00:29:23,680 --> 00:29:25,640 It seems like an insane amount of gold, right? 595 00:29:26,040 --> 00:29:27,160 It's never enough. It's never enough. 596 00:29:27,160 --> 00:29:28,320 It's. Like he's a king. 597 00:29:28,320 --> 00:29:31,600 You know, it's just like the, I mean, the, the thought I had is 598 00:29:31,600 --> 00:29:35,800 just like, did did any of these tech executives really believe 599 00:29:36,560 --> 00:29:39,080 diversity, equity and inclusion? You know, it's just like, OK, 600 00:29:39,520 --> 00:29:42,480 they did the Democratic thing. Now they're doing the like Trump 601 00:29:42,480 --> 00:29:44,080 thing. They're willing to like kiss the 602 00:29:44,080 --> 00:29:46,800 ring for whatever The thing is of the moment. 603 00:29:46,840 --> 00:29:49,760 I don't know, it's it's just insane to me that they'll just 604 00:29:49,760 --> 00:29:52,400 like here, here our gifts are are king. 605 00:29:52,440 --> 00:29:53,560 I don't know what was your reaction. 606 00:29:53,880 --> 00:29:58,160 I mean, Apple can like they are the most vulnerable maybe of all 607 00:29:58,160 --> 00:30:00,240 of the big tech companies to. Keep China. 608 00:30:00,760 --> 00:30:03,920 To Trump's Caprice, like if he's going to start fucking around 609 00:30:03,920 --> 00:30:06,680 with tariffs in a more serious way, they have major problems. 610 00:30:06,680 --> 00:30:09,880 Like you can only like rush production in India one time to 611 00:30:09,880 --> 00:30:12,560 get, you know, out before the tariffs start coming down on 612 00:30:12,560 --> 00:30:14,760 you. So like it wasn't enough gold, 613 00:30:14,880 --> 00:30:17,080 frankly, for whatever. I don't even watch the press 614 00:30:17,080 --> 00:30:19,280 release or the the press conference I missed. 615 00:30:19,680 --> 00:30:23,280 Well, Trump was like singing his praise like Tim Cooks praises. 616 00:30:23,320 --> 00:30:26,600 I mean, he was like. He likes rich people too. 617 00:30:26,600 --> 00:30:28,920 I mean, he's still, even after everything that happened with 618 00:30:28,920 --> 00:30:31,040 Elon, still being like, Nah, he's a good guy. 619 00:30:31,600 --> 00:30:33,320 He had a bad day, but he's still a good guy. 620 00:30:33,320 --> 00:30:36,800 So he's like very specific on like he wants to demonize. 621 00:30:37,480 --> 00:30:38,960 Smartest people are the richest people. 622 00:30:38,960 --> 00:30:40,880 It's like whatever you did to figure out how to get all that 623 00:30:40,880 --> 00:30:43,280 money, you're smart now. Yeah, they're richer than him. 624 00:30:43,280 --> 00:30:45,800 I mean, I don't know, Tim Cook is well, who knows how much he's 625 00:30:45,800 --> 00:30:48,840 worth, but but no, obviously it's it's it's disgusting and 626 00:30:48,840 --> 00:30:52,400 like and and and obvious and like fairly ham fisted. 627 00:30:53,080 --> 00:30:56,800 And I love that he's got it down now that every every president. 628 00:30:56,800 --> 00:30:59,480 I think it started with Trump and then even with Biden. 629 00:30:59,640 --> 00:31:02,000 And now with Trump again, they're like, now we're doing 630 00:31:02,000 --> 00:31:05,120 another like 600 billion, you know, Oh, why 600? 631 00:31:05,120 --> 00:31:05,960 Now we're going to up into eight. 632 00:31:05,960 --> 00:31:08,680 You know, they just like they just keep amping up. 633 00:31:08,680 --> 00:31:10,320 They're like, we're going to invest in America. 634 00:31:10,320 --> 00:31:14,000 You know, they, it's just like, I mean, they just make up like 635 00:31:14,000 --> 00:31:17,080 these press releases basically like I mean the. 636 00:31:17,080 --> 00:31:18,680 Numbers are made-up. The numbers are absolutely 637 00:31:18,680 --> 00:31:20,280 made-up. Cause 600 billion is meaningless 638 00:31:20,280 --> 00:31:21,960 for for Apple, right And. This is the thing I hated about 639 00:31:21,960 --> 00:31:23,800 the media. I mean, which again is just a 640 00:31:23,800 --> 00:31:26,560 humanity thing. But it's like we, we talk about 641 00:31:28,040 --> 00:31:30,000 this is a tangent, but it, we're, we're deep into the 642 00:31:30,000 --> 00:31:32,520 episode now. But, you know, it's like Open AI 643 00:31:32,680 --> 00:31:37,200 gets stories about how they raise $40 billion or whatever 644 00:31:37,200 --> 00:31:41,200 from SoftBank and then that seemingly hasn't totally 645 00:31:41,200 --> 00:31:43,880 happened yet. And then they get excited 646 00:31:43,880 --> 00:31:46,720 headlines again, I think from the New York Times saying that 647 00:31:46,720 --> 00:31:50,320 they raise less than that as if it's like upbeat. 648 00:31:50,320 --> 00:31:52,960 It's just like these these companies are able to get 649 00:31:53,160 --> 00:31:57,680 excited headlines about big numbers over and over again in a 650 00:31:57,680 --> 00:32:00,240 way that nobody's really adding up all all the numbers and 651 00:32:00,240 --> 00:32:01,600 saying, did they? Did they get what they were 652 00:32:01,600 --> 00:32:04,440 supposed to get last time? Yeah, well, open AI is 653 00:32:04,440 --> 00:32:07,440 particularly egregious on on that front because, yeah, the 654 00:32:07,440 --> 00:32:09,760 SoftBank stuff, it's really unclear where, you know, if that 655 00:32:09,760 --> 00:32:12,000 money is even going to come through because it's, you know, 656 00:32:12,000 --> 00:32:14,960 contingent on the conversion. By the way, all these people 657 00:32:14,960 --> 00:32:17,000 that the New York Times mentioned in their story, like 658 00:32:17,000 --> 00:32:20,720 Dragon Ear that are putting in like some sort of side money, 659 00:32:20,720 --> 00:32:24,600 like I think it was some kind of an SPV actually into open AI. 660 00:32:24,600 --> 00:32:27,960 Like they also could be buying into a company that might not be 661 00:32:27,960 --> 00:32:30,560 able to successfully convert into a for profit. 662 00:32:31,400 --> 00:32:34,440 Like the numbers are well ahead of like the actuality on any of 663 00:32:34,440 --> 00:32:37,000 this shit. So it's, it's super problematic. 664 00:32:37,280 --> 00:32:40,200 And also, I mean, like, I never like you can't bring it up 665 00:32:40,200 --> 00:32:41,480 enough. In my opinion. 666 00:32:41,480 --> 00:32:45,240 Is, is, is Stargate And like that also had a huge number 667 00:32:45,240 --> 00:32:48,480 attached to it, $500 billion, which you know. 668 00:32:48,920 --> 00:32:50,640 As far as I can. That was a Trump number, too. 669 00:32:50,640 --> 00:32:52,040 That was yeah. He was a Trump. 670 00:32:52,520 --> 00:32:53,320 Yeah. And was it Larry? 671 00:32:53,320 --> 00:32:54,640 Yes. And was the third person who 672 00:32:54,720 --> 00:32:56,040 was? Larry and Masa, they were all 673 00:32:56,040 --> 00:32:59,760 there and but the 500 billion number was not like, you know, 674 00:32:59,760 --> 00:33:02,640 they have like a very, you know, advanced spreadsheet where they 675 00:33:02,640 --> 00:33:05,400 calculated like project by project and realized over 10 676 00:33:05,400 --> 00:33:07,720 years what it was. Yeah, Like what's what's the 677 00:33:07,720 --> 00:33:09,320 number That's too big though, That would, you know, a 678 00:33:09,320 --> 00:33:10,960 trillion. No one's going to believe that. 679 00:33:11,360 --> 00:33:14,440 And like 200 billion, that seems like not a big number. 680 00:33:15,000 --> 00:33:17,680 So they end up you used to. Work for the publication. 681 00:33:17,840 --> 00:33:20,080 Weren't you on a you're a contributor or something on that 682 00:33:20,080 --> 00:33:22,160 story where the Wall Street? Journal said I got attacked. 683 00:33:22,160 --> 00:33:25,160 Open AI was gonna raise like 6 trillion. 684 00:33:25,160 --> 00:33:27,080 What was? That 7-7 trillion. 685 00:33:27,120 --> 00:33:29,400 Wall Street Journal. What were they doing? 686 00:33:29,400 --> 00:33:33,440 Like, why did that happen? You know, now what's the answer? 687 00:33:33,440 --> 00:33:35,400 Like what? There's only so much I can say 688 00:33:35,400 --> 00:33:38,880 on that one, but I will say that like, you know, you should give 689 00:33:38,880 --> 00:33:42,400 a lot of journalists, put a lot of stock into true at the time. 690 00:33:43,800 --> 00:33:46,560 People were saying to other people that they they were 691 00:33:46,560 --> 00:33:48,800 throwing around and say numbers to each other and. 692 00:33:49,000 --> 00:33:52,040 Well, Sam and making fun of it too, you know, after it came 693 00:33:52,040 --> 00:33:53,840 out, he's like, fuck it, let's do 9 trillion. 694 00:33:53,840 --> 00:33:55,200 And it's like, you know what, Sam? 695 00:33:55,720 --> 00:33:57,600 Like you can't have it both ways. 696 00:33:57,600 --> 00:33:58,960 And that's all I'll say about that. 697 00:33:59,280 --> 00:34:00,760 Right. Sam is clearly out. 698 00:34:00,800 --> 00:34:04,120 He was, I'm sure out and about throwing around big numbers and 699 00:34:04,120 --> 00:34:07,560 then the Wall Street Journal reported and people have the 700 00:34:07,560 --> 00:34:09,679 right to know. But I think the the Journal 701 00:34:09,679 --> 00:34:11,560 should have never put it in the headline, which I think was my 702 00:34:11,560 --> 00:34:13,600 stance at the time. And they should have been, it 703 00:34:13,600 --> 00:34:16,000 should have been much more like in this meeting and with this 704 00:34:16,000 --> 00:34:18,880 person said this number, and they probably should have said, 705 00:34:19,080 --> 00:34:21,159 and that's absurd. I mean, I honestly think that's 706 00:34:21,159 --> 00:34:24,199 our competitive advantage. Like that it we were throwing 707 00:34:24,199 --> 00:34:27,159 around, it's either this is a meaningless number, which is 708 00:34:27,159 --> 00:34:28,880 what I think it ended up being because it's like, oh, it's a 709 00:34:28,880 --> 00:34:32,560 statement about overall spending across like the economy, you 710 00:34:32,560 --> 00:34:36,600 know, or you know, it's just like putting it in the headline 711 00:34:36,760 --> 00:34:39,480 as if it's like a deal number was the insane. 712 00:34:39,719 --> 00:34:42,840 Thing if you pass around the hat enough times, I guess you can 713 00:34:42,840 --> 00:34:45,960 reach 7 trillion. It's like the implication of 714 00:34:45,960 --> 00:34:48,080 that headline. Yeah. 715 00:34:48,840 --> 00:34:51,719 And I actually think the best story that came out that year on 716 00:34:51,719 --> 00:34:55,280 that topic was what the The Times ended up doing, you know, 717 00:34:55,280 --> 00:34:57,280 a bunch of months later where they talked about how all of 718 00:34:57,280 --> 00:35:01,240 these chip manufacturers laughed Sam out of the room when he was 719 00:35:01,240 --> 00:35:05,680 going around to like, whatever at like, TSMC or yeah. 720 00:35:05,920 --> 00:35:09,360 Yeah, they were like they called him a podcast guy or something. 721 00:35:09,360 --> 00:35:10,800 Or. Podcast, bro, which I don't even 722 00:35:10,800 --> 00:35:12,080 know what that means, but I like it. 723 00:35:12,400 --> 00:35:15,280 Yeah, Yeah, 'cause like, yeah, when the big boys, you know, the 724 00:35:15,280 --> 00:35:17,720 ones who actually deal with numbers and like production at 725 00:35:17,720 --> 00:35:21,200 that scale are like seeing you put your fucking pitch deck up 726 00:35:21,200 --> 00:35:23,920 on the screen and they're just like, that's not how it works, 727 00:35:23,920 --> 00:35:28,080 brah, is yeah. That was like the reality check 728 00:35:28,080 --> 00:35:29,680 I was very happy to see happen to Sam. 729 00:35:29,680 --> 00:35:30,680 Yeah, that was a good story there. 730 00:35:30,800 --> 00:35:32,840 That's good. We we criticized the New York 731 00:35:32,840 --> 00:35:34,240 Times. We complimented them. 732 00:35:34,720 --> 00:35:36,680 Yeah, we're like back to dead cat here. 733 00:35:36,920 --> 00:35:39,040 That's. No, Tim, Tim, Apple, super 734 00:35:39,040 --> 00:35:41,640 embarrassing, $600 billion, meaningless number. 735 00:35:42,480 --> 00:35:44,680 I also saw one of the things that came out of it was like, 736 00:35:44,680 --> 00:35:47,920 you know, a headline was like Apple to move production of like 737 00:35:47,920 --> 00:35:50,560 Corning Glass to Kentucky or something. 738 00:35:50,560 --> 00:35:52,920 And someone could Fact Check me on this? 739 00:35:52,920 --> 00:35:54,800 I'm pretty sure they already have that. 740 00:35:54,960 --> 00:35:57,520 Yeah, I think they already do. Well, I think they'd already 741 00:35:57,520 --> 00:36:00,280 said it was like all in the United States, and now they're 742 00:36:00,280 --> 00:36:02,920 like saying it again. And somebody I think pointed 743 00:36:02,920 --> 00:36:04,960 out, like, weren't they already supposed to be? 744 00:36:04,960 --> 00:36:07,160 I think it might have been Mark Kerman saying like they weren't 745 00:36:07,160 --> 00:36:10,520 they already doing it 100% in the US So yeah. 746 00:36:11,400 --> 00:36:13,600 It's very much like if you remember the episode of Mad Men 747 00:36:13,600 --> 00:36:16,520 when he's working with Lucky Strike and they have the ad 748 00:36:16,520 --> 00:36:19,080 campaign for the cigarettes. It it's toasted, toasted. 749 00:36:19,480 --> 00:36:20,640 Yeah, yeah, of course, I remember. 750 00:36:21,080 --> 00:36:22,760 That Yeah, yeah. So that was basically the it's 751 00:36:22,760 --> 00:36:26,440 toasted moment for Apple just being like, now glass 752 00:36:26,440 --> 00:36:30,000 manufactured in the US, never enough of that shit. 753 00:36:30,000 --> 00:36:33,080 And it works on Trump, and it's frankly a lot more realistic and 754 00:36:33,080 --> 00:36:36,000 meaningful easily. You just say Trump, you get 755 00:36:36,000 --> 00:36:38,000 credit for this thing. It's like it doesn't matter if 756 00:36:38,000 --> 00:36:40,040 you were doing it or not. It's just like the now the 757 00:36:40,040 --> 00:36:42,960 credit flows to him anyway. Well, that's way better than 758 00:36:42,960 --> 00:36:45,800 like the Howard Lutnick going around, Howard Lutnick going 759 00:36:45,800 --> 00:36:48,280 around during the tariff moment trying to get people hyped up 760 00:36:48,280 --> 00:36:50,320 that we're going to start doing the little screws and the 761 00:36:50,320 --> 00:36:53,240 iPhones in America. Or he was like giddily going on 762 00:36:53,240 --> 00:36:56,280 CNBC talking about that. Like that one never should have 763 00:36:56,280 --> 00:36:57,760 made it out of the brainstorming session. 764 00:36:57,760 --> 00:36:59,800 So this is better. I I'll give him, I'll give him 765 00:36:59,800 --> 00:37:02,480 credit for that. All right, see you next week.