1 00:00:19,252 --> 00:00:22,052 S1: All right. Welcome to episode 47. This is Daniel Miessler. 2 00:00:23,092 --> 00:00:25,772 S1: All right. Lots of updates. I've been the most creative, 3 00:00:25,772 --> 00:00:29,812 S1: productive I've ever been in my life in this last week, 4 00:00:30,292 --> 00:00:32,612 S1: and I think it probably has to do with a 5 00:00:32,612 --> 00:00:37,012 S1: combination of cloud code and cursor. And I would say 6 00:00:37,012 --> 00:00:41,251 S1: specifically cloud code, because I am now using it to 7 00:00:41,292 --> 00:00:44,052 S1: do way more things than just coding. I'm basically using 8 00:00:44,052 --> 00:00:48,492 S1: it as like basically it's like I'm a CEO of 9 00:00:49,252 --> 00:00:54,091 S1: multiple companies and I could give work to like 100 10 00:00:54,092 --> 00:00:56,651 S1: workers at all these different companies. So basically I've got 11 00:00:56,692 --> 00:00:59,372 S1: like five shells open right now and they are all 12 00:00:59,372 --> 00:01:03,572 S1: in separate repositories. And like not many of them are 13 00:01:03,612 --> 00:01:06,172 S1: actually building anything related to like a web app or 14 00:01:06,292 --> 00:01:08,692 S1: web coding or any of that. Um, a lot of 15 00:01:08,692 --> 00:01:12,132 S1: them are like, organize this, clean this up, you know, 16 00:01:12,172 --> 00:01:15,092 S1: go get this content, um, fix all the links on 17 00:01:15,092 --> 00:01:18,422 S1: my website or whatever. It's like, It's a whole bunch 18 00:01:18,422 --> 00:01:20,902 S1: of stuff that would have taken hours and hours of 19 00:01:20,902 --> 00:01:23,342 S1: manual work, and that's why I hadn't done it yet. 20 00:01:23,702 --> 00:01:25,422 S1: And so now this thing is just like, yeah, tell 21 00:01:25,422 --> 00:01:27,262 S1: me what to do. It's like, okay, cool, I'll write 22 00:01:27,262 --> 00:01:29,101 S1: a script to do that here. I just fixed your 23 00:01:29,102 --> 00:01:32,982 S1: entire blog. Okay. It fixed my entire blog for content 24 00:01:32,982 --> 00:01:39,022 S1: going back to 1999. Hundreds. No. Thousands. Thousands of articles. 25 00:01:39,062 --> 00:01:43,461 S1: Thousands of pieces with broken links. It migrated all of 26 00:01:43,462 --> 00:01:48,302 S1: my images to a new system. Um, I cleaned up 27 00:01:48,302 --> 00:01:53,622 S1: all my cloud or all my, uh, Cloudflare. Um, basically 28 00:01:53,622 --> 00:01:55,462 S1: how everything was being handled before I was doing a 29 00:01:55,462 --> 00:02:00,142 S1: bunch of stuff, um, with S3 and CloudFront, and I 30 00:02:00,142 --> 00:02:04,662 S1: moved everything to be Cloudflare now, um, I migrated all my, uh, 31 00:02:04,822 --> 00:02:07,582 S1: images to use that instead. And they're all located at 32 00:02:07,582 --> 00:02:10,182 S1: slash images. This is all stuff I was like, piecing 33 00:02:10,182 --> 00:02:13,742 S1: away at manually and sort of like as I came 34 00:02:13,742 --> 00:02:16,582 S1: upon the problem, I would go and fix it, but 35 00:02:17,062 --> 00:02:19,502 S1: to me it was daunting to think about even trying 36 00:02:19,502 --> 00:02:21,222 S1: to do this right. So, I mean, it's the type 37 00:02:21,222 --> 00:02:23,102 S1: of thing you hire somebody and they go and do 38 00:02:23,102 --> 00:02:25,382 S1: it and it's going to be done really, really poorly. 39 00:02:25,702 --> 00:02:28,302 S1: If I would have paid someone to do this, first 40 00:02:28,302 --> 00:02:30,382 S1: of all, it would have cost me thousands of dollars. 41 00:02:31,022 --> 00:02:32,822 S1: Second of all, they would have messed a whole bunch 42 00:02:32,822 --> 00:02:36,982 S1: of stuff up. So it's like I can't even express 43 00:02:36,982 --> 00:02:40,341 S1: how useful and powerful this is. And I'm paying for Max, 44 00:02:40,341 --> 00:02:43,901 S1: which is like 200 bucks a month. But like, if 45 00:02:43,901 --> 00:02:48,302 S1: this was $2,000 a month, I have like five times over, 46 00:02:48,302 --> 00:02:52,982 S1: made my money. And that's just from like last weekend, right? 47 00:02:53,022 --> 00:02:55,061 S1: I mean, or like up to up to now, which 48 00:02:55,062 --> 00:02:57,942 S1: is like Wednesday. So I'm telling you, this is like 49 00:02:57,982 --> 00:03:01,342 S1: the most excited I've, I've been about this whole AI thing, 50 00:03:01,742 --> 00:03:03,982 S1: and I don't even see it as I actually like. 51 00:03:04,142 --> 00:03:06,862 S1: I'm starting to, like, just not even care about that. 52 00:03:06,901 --> 00:03:10,982 S1: What I'm caring about is this agent, uh, thing and 53 00:03:10,982 --> 00:03:14,221 S1: not like AI agents, but the concept of handing work 54 00:03:14,702 --> 00:03:18,072 S1: to something that understands what you're trying to do. Okay, 55 00:03:18,112 --> 00:03:21,512 S1: here's another good example. I have content on the site 56 00:03:22,151 --> 00:03:26,992 S1: from so many different previous platforms, right? Because I've been 57 00:03:26,992 --> 00:03:32,712 S1: blogging since 1999, which means I've got just grossness, just nastiness, 58 00:03:32,752 --> 00:03:36,832 S1: like weird embeds and weird linking strategies like my images 59 00:03:36,832 --> 00:03:40,112 S1: were being called in five different ways. Do they have 60 00:03:40,152 --> 00:03:42,352 S1: forward slashes or not? Like, all of this stuff was 61 00:03:42,392 --> 00:03:45,712 S1: messed up. I went and told this thing, here's the 62 00:03:45,712 --> 00:03:48,552 S1: canonical way to do things. Here's what a post is 63 00:03:48,552 --> 00:03:51,672 S1: supposed to look like, right? When when I send you 64 00:03:51,672 --> 00:03:53,352 S1: a URL. And by the way, I don't have to 65 00:03:53,352 --> 00:03:55,912 S1: give it like specifics. I'm just like, hey, there's a 66 00:03:55,912 --> 00:03:58,152 S1: I have a post called The End of Work. It's 67 00:03:58,152 --> 00:04:00,432 S1: really messed up. Go and fix it. It goes and 68 00:04:00,432 --> 00:04:02,512 S1: checks all the 20 things that I need it to 69 00:04:02,552 --> 00:04:05,232 S1: do for it to be normalized, for it to be 70 00:04:05,232 --> 00:04:07,672 S1: a canonical post. It's like, okay, cool, I did that 71 00:04:07,672 --> 00:04:10,432 S1: and I pushed it. Anything else? Oh, and by the way, 72 00:04:10,432 --> 00:04:13,792 S1: I tested it and it works. I can't express to 73 00:04:13,792 --> 00:04:20,392 S1: you how Insane. That is, it is completely, completely spectacular. 74 00:04:20,432 --> 00:04:25,032 S1: I mean, this is a type of work. Like I said, 75 00:04:25,432 --> 00:04:28,472 S1: if I hired someone who is super smart and super awesome, 76 00:04:29,312 --> 00:04:32,432 S1: like a super hard core developer, and I said, I 77 00:04:32,432 --> 00:04:35,832 S1: want you to do these 20 things to this post. 78 00:04:36,312 --> 00:04:38,072 S1: And by the way, some of these posts are like 79 00:04:39,832 --> 00:04:44,032 S1: a thousand words, 2000 words, 3000, 5000 words. I mean, 80 00:04:44,072 --> 00:04:48,231 S1: I've got posts that are 17,000 words, 9000 words, 10,000 words. 81 00:04:48,231 --> 00:04:52,272 S1: We're talking about small books here, okay. And you hand 82 00:04:52,272 --> 00:04:54,472 S1: that to a human and you're like, hey, go through 83 00:04:54,472 --> 00:04:56,832 S1: all this text. And by the way, it's done differently 84 00:04:56,832 --> 00:05:00,472 S1: for every single post, okay? Every single post. It's broken 85 00:05:00,472 --> 00:05:03,552 S1: in different ways, and I tell it a canonical way 86 00:05:03,552 --> 00:05:06,012 S1: to do it. It literally comes back in 2 or 87 00:05:06,012 --> 00:05:07,792 S1: 3 minutes and it's like, yeah, I fixed all that. 88 00:05:08,752 --> 00:05:11,912 S1: And I'm, I'm so I've got cloud code over here 89 00:05:11,912 --> 00:05:13,551 S1: working and then I have cursor, I have the same 90 00:05:13,552 --> 00:05:15,842 S1: project open in cursor. So I can actually go in 91 00:05:15,842 --> 00:05:18,122 S1: and do manual edits. More importantly, I can see what 92 00:05:18,122 --> 00:05:21,282 S1: it's actually doing, what what Claude is actually doing. And 93 00:05:21,282 --> 00:05:23,442 S1: sometimes I could use the cursor agent if I want, 94 00:05:23,481 --> 00:05:27,162 S1: but generally I'm using it for transparency. And just like, 95 00:05:27,481 --> 00:05:30,642 S1: you know, manually accepting things if it's crazy or whatever. 96 00:05:31,002 --> 00:05:33,642 S1: Plus I have my vim bindings active inside of cursor, 97 00:05:33,642 --> 00:05:36,481 S1: so I could actually just go right using air quotes 98 00:05:36,481 --> 00:05:40,162 S1: vim inside of cursor and it doesn't feel crazy. I 99 00:05:40,162 --> 00:05:42,681 S1: don't have auto save enabled though, someone can figure that out. 100 00:05:43,122 --> 00:05:46,842 S1: But anyway, it's just been. I've been getting so much done, 101 00:05:46,842 --> 00:05:49,202 S1: so many projects that are just like. And I've got 102 00:05:49,601 --> 00:05:53,482 S1: 1520 more that are popping into my mind. Like, I 103 00:05:53,481 --> 00:05:57,082 S1: literally have seven terminals open right now doing cool projects. 104 00:05:57,082 --> 00:05:59,241 S1: I'm about to go do cool stuff, like I'm doing 105 00:05:59,242 --> 00:06:02,601 S1: some physical stuff with some friends. We're going to, um, 106 00:06:03,082 --> 00:06:06,442 S1: celebrate Dustin's life tonight, so I'm really looking forward to that. 107 00:06:07,002 --> 00:06:10,442 S1: And all these other cool things, like I'm doing a 108 00:06:10,442 --> 00:06:13,522 S1: cool project, I'm traveling or doing whatever. Right now I 109 00:06:13,562 --> 00:06:17,092 S1: am thinking, when can I get back to coding? I 110 00:06:17,132 --> 00:06:19,332 S1: recently been messing around with Diablo for a little bit. 111 00:06:19,332 --> 00:06:22,372 S1: Diablo four is my favorite video game, or Diablo in general, 112 00:06:22,372 --> 00:06:25,492 S1: is probably my favorite video game, and I'm pretty excited 113 00:06:25,492 --> 00:06:27,571 S1: about what's going on in there. I could go and just, 114 00:06:27,612 --> 00:06:29,572 S1: you know, have some fun for two hours or whatever. 115 00:06:30,252 --> 00:06:34,332 S1: It is. Nothing compared to these five terminal windows that 116 00:06:34,332 --> 00:06:37,291 S1: are calling me. I literally play around with this stuff 117 00:06:37,291 --> 00:06:40,772 S1: and build stuff and fix stuff and create. Net new things. 118 00:06:40,772 --> 00:06:43,532 S1: The next one I'm about to do is substrate. It's 119 00:06:43,532 --> 00:06:46,892 S1: going to be insane. But I start on this. I 120 00:06:46,932 --> 00:06:49,772 S1: look up at the clock and I'm like, oh well, 121 00:06:49,772 --> 00:06:52,012 S1: I need to stand up. I need to eat. I 122 00:06:52,052 --> 00:06:55,931 S1: haven't eaten in six hours. Also, it's going to be 123 00:06:55,932 --> 00:06:59,372 S1: breakfast and that's 3 p.m. breakfast or whatever. Like, I 124 00:06:59,412 --> 00:07:03,452 S1: have never been this excited and focused that I can 125 00:07:03,452 --> 00:07:06,972 S1: remember on anything. Now, you combine that with the fact 126 00:07:06,972 --> 00:07:11,212 S1: that this thing is getting better, right? Just imagine Cloud 127 00:07:11,212 --> 00:07:13,732 S1: Code a bit better. Imagine cloud code, but I can 128 00:07:13,852 --> 00:07:17,252 S1: send it content from my voice, right? I mean, and 129 00:07:17,252 --> 00:07:18,852 S1: this is where this is all going that I've been 130 00:07:18,852 --> 00:07:21,812 S1: talking about forever, right? We already know where it's going. 131 00:07:21,812 --> 00:07:23,292 S1: We already know how this is all going to be 132 00:07:23,292 --> 00:07:26,932 S1: stitched up, and we're messing with the individual pieces here. Um, 133 00:07:26,932 --> 00:07:29,172 S1: one of these projects is called Chi. It's actually my 134 00:07:29,172 --> 00:07:32,532 S1: digital assistant. So that when I'm actually teaching the meta 135 00:07:32,532 --> 00:07:36,812 S1: tools of how to do, you know, skills and tools 136 00:07:36,812 --> 00:07:39,372 S1: and tasks that I'm just going to have to do, 137 00:07:39,732 --> 00:07:42,892 S1: you know, universally going forward. So a good example of 138 00:07:42,892 --> 00:07:48,092 S1: this is, um, I recently taught Chi how to draw 139 00:07:48,132 --> 00:07:53,052 S1: animations using Grant Sanderson's stuff. So he's the guy who does, uh, 140 00:07:53,372 --> 00:07:58,172 S1: three blue, one brown or three brown, one blue. So animations, math, 141 00:07:58,172 --> 00:08:00,812 S1: animations of whatever. Well, now I can send it a 142 00:08:00,812 --> 00:08:02,972 S1: prompt and say animate this. So I sent it a 143 00:08:02,972 --> 00:08:06,732 S1: prompt of the solar system and it drew it. It 144 00:08:06,772 --> 00:08:08,652 S1: drew it and it animated it, and it opened it 145 00:08:08,652 --> 00:08:10,572 S1: up and showed it to me. And I'm like, this 146 00:08:10,572 --> 00:08:13,012 S1: is absolutely insane. I've got another one, which is like 147 00:08:13,142 --> 00:08:15,542 S1: a knowledge map. So I'm going to be able to 148 00:08:15,542 --> 00:08:18,942 S1: take other projects. My blogs are sitting right next to 149 00:08:18,982 --> 00:08:26,182 S1: it in a directory, all markdown files, all normalizing canonicalized now. Right. So, 150 00:08:26,902 --> 00:08:30,382 S1: so they're canonicalized. So they have all tags in them. 151 00:08:30,702 --> 00:08:33,782 S1: They're all marked up. They're all clean. So I could 152 00:08:33,782 --> 00:08:37,062 S1: just be like, hey, pull the pull the knowledge from this. 153 00:08:38,022 --> 00:08:40,662 S1: And you know, map that in this new graphing function 154 00:08:40,742 --> 00:08:45,182 S1: because I've got this graphing knowledge map and I'm teaching 155 00:08:45,222 --> 00:08:47,582 S1: Chi right now how to use this library, how to 156 00:08:47,622 --> 00:08:50,541 S1: use this GitHub project to do this with any knowledge 157 00:08:50,542 --> 00:08:52,702 S1: that I give it. Right. So it's just like these 158 00:08:52,702 --> 00:08:55,982 S1: small universal tools which are getting so good they just 159 00:08:55,982 --> 00:09:00,541 S1: become skills that it has. So collecting data, collecting data 160 00:09:00,542 --> 00:09:06,102 S1: from sources, um, rating the quality of a source. Right. 161 00:09:06,422 --> 00:09:09,822 S1: Because when I'm doing like these collections and I'm making 162 00:09:09,822 --> 00:09:12,021 S1: graphs based on them and, you know, if I want 163 00:09:12,062 --> 00:09:13,702 S1: to publish them or whatever, I need to be able 164 00:09:13,702 --> 00:09:16,302 S1: to point and say, look, this came from here, this 165 00:09:16,302 --> 00:09:20,222 S1: came from CDC, this came from so-and-so French agency that 166 00:09:20,222 --> 00:09:22,902 S1: puts out data or whatever. Um, but you got to 167 00:09:22,902 --> 00:09:25,422 S1: be able to show your work. Otherwise it's just pretty graphs, right? 168 00:09:25,462 --> 00:09:28,982 S1: So all of that just becomes core components built into 169 00:09:28,982 --> 00:09:35,342 S1: this thing. All right. So yeah, that very exciting stuff. 170 00:09:35,381 --> 00:09:40,782 S1: The other side of this is I'm basically manic about that, right? 171 00:09:40,822 --> 00:09:44,982 S1: I'm manic about that. And I'm morose about the way 172 00:09:44,982 --> 00:09:48,182 S1: I see this affecting humanity, because the way I see this, 173 00:09:48,182 --> 00:09:50,022 S1: I wrote a post a long time ago, maybe like 174 00:09:50,062 --> 00:09:54,342 S1: 2017 or something called, uh, The Bifurcation or something like that. 175 00:09:54,782 --> 00:09:56,942 S1: And it's like the separation of people. And it was, 176 00:09:57,062 --> 00:09:59,742 S1: I don't know, somewhat readers and non-readers I was talking 177 00:09:59,742 --> 00:10:03,622 S1: about just like how some people just can't get enough 178 00:10:04,342 --> 00:10:06,742 S1: and they're crazy ambitious and they're always trying to learn 179 00:10:06,782 --> 00:10:09,582 S1: things or whatever. And the rest of the masses are 180 00:10:09,582 --> 00:10:12,312 S1: just like, yeah, haven't read a book since high school, 181 00:10:12,312 --> 00:10:14,832 S1: and I hated it then, you know, haven't read a 182 00:10:14,832 --> 00:10:17,832 S1: book since college and I hated it then. So it's 183 00:10:17,832 --> 00:10:23,192 S1: like they've never really read or studied for fun. And 184 00:10:23,232 --> 00:10:28,352 S1: I'm telling you, people like that are unbelievably screwed, right? 185 00:10:28,392 --> 00:10:30,432 S1: If you do not have learning as, like part of 186 00:10:30,432 --> 00:10:34,552 S1: your core DNA right now, you you are just absolutely screwed. 187 00:10:34,952 --> 00:10:37,512 S1: And it's not like it's 50 over 50. It's not 188 00:10:37,511 --> 00:10:40,312 S1: like it's half and half or like 60% or hardcore 189 00:10:40,352 --> 00:10:45,432 S1: learners and 40% art. It's more like 10% or 5% are. 190 00:10:46,631 --> 00:10:49,952 S1: Or maybe it's 2%, maybe it's 1%. Right? But this 191 00:10:49,952 --> 00:10:53,112 S1: is the group, whatever that small percentage is that sees 192 00:10:53,112 --> 00:10:56,432 S1: all these tools. Right. And like I'm in these communities 193 00:10:56,432 --> 00:10:58,671 S1: with like, uh, all my friends are doing this, I'm 194 00:10:58,672 --> 00:11:01,472 S1: watching other people do it on online or whatever. It's like, 195 00:11:02,232 --> 00:11:05,312 S1: this community is so excited right now. They're just building 196 00:11:05,312 --> 00:11:08,791 S1: stuff all the time, just like I am. So in 197 00:11:08,792 --> 00:11:11,352 S1: one world and I live in the Bay area, so 198 00:11:11,352 --> 00:11:13,112 S1: it's like I'm living inside of this world as well. 199 00:11:13,112 --> 00:11:15,872 S1: It's like one world. It's like, oh my God, can 200 00:11:15,872 --> 00:11:19,272 S1: you believe this is possible? And it's just like constant 201 00:11:19,272 --> 00:11:22,032 S1: shock on our faces. And then there's this other world 202 00:11:22,032 --> 00:11:24,992 S1: of like, I. What are you talking about? Isn't that ChatGPT? Yeah, 203 00:11:24,992 --> 00:11:27,671 S1: I use it sometimes. I don't know, but it hallucinates 204 00:11:27,712 --> 00:11:31,832 S1: a lot. So you can't really trust it. And I'm like, well, 205 00:11:32,511 --> 00:11:36,952 S1: that person's screwed. It's like a completely different universe that 206 00:11:36,952 --> 00:11:42,232 S1: we live in. Completely different universe. And what I'm trying 207 00:11:42,232 --> 00:11:45,112 S1: to figure out is like, what can you say? How 208 00:11:45,112 --> 00:11:48,072 S1: can we get more people into that world? How can 209 00:11:48,072 --> 00:11:52,312 S1: we convince more people that this is a critical skill? Right? 210 00:11:52,832 --> 00:11:55,752 S1: And it's hard because if they're already not readers, if 211 00:11:55,752 --> 00:11:58,192 S1: they're already not into the whole learning thing, then like 212 00:11:58,192 --> 00:12:00,792 S1: giving them a better tool for learning is going to 213 00:12:00,792 --> 00:12:03,911 S1: be difficult. But we've got to find a way. I 214 00:12:03,992 --> 00:12:05,911 S1: don't want to just give up on these people and 215 00:12:05,912 --> 00:12:08,872 S1: just be like, well, I guess they're screwed and just 216 00:12:08,872 --> 00:12:10,202 S1: kind of move on and be like, well, it well, 217 00:12:10,202 --> 00:12:13,242 S1: it sure is fun to build with cloud code. That's 218 00:12:13,242 --> 00:12:18,922 S1: what makes me morose. So I basically oscillate between. This 219 00:12:18,922 --> 00:12:21,802 S1: is the saddest thing ever because I look around at 220 00:12:21,802 --> 00:12:23,602 S1: all these jobs, all these people who have jobs, who 221 00:12:23,602 --> 00:12:26,642 S1: think AI is ChatGPT and they use it once a month, 222 00:12:27,522 --> 00:12:31,402 S1: you know, for 15 minutes. And I'm like, the economy 223 00:12:31,402 --> 00:12:34,602 S1: is going to crash. This is what I'm honestly thinking about. This. 224 00:12:34,602 --> 00:12:39,602 S1: This economy is going to have a massive, massive disruption 225 00:12:39,602 --> 00:12:45,002 S1: because these folks here who who don't think of AI 226 00:12:45,002 --> 00:12:48,602 S1: in this way, they're going to get fired. They're just 227 00:12:48,602 --> 00:12:51,002 S1: going to get fired. They're going to get replaced either 228 00:12:51,002 --> 00:12:53,401 S1: by a smart person who could do nine jobs all 229 00:12:53,402 --> 00:12:56,882 S1: at once because they understand AI a little bit, but 230 00:12:56,881 --> 00:13:00,122 S1: then eventually just by AI itself. Right. And who knows 231 00:13:00,122 --> 00:13:02,482 S1: the timelines and all that stuff. You you saw the debate. 232 00:13:03,002 --> 00:13:05,042 S1: That could be tomorrow. It could be in four years 233 00:13:05,042 --> 00:13:08,962 S1: from now. Who actually knows? It actually doesn't matter, right? 234 00:13:09,082 --> 00:13:11,651 S1: Don't even care about that. What matters is, you know, 235 00:13:11,652 --> 00:13:16,492 S1: the direction stochastically. You. You know this for certain, right? 236 00:13:16,892 --> 00:13:20,292 S1: And there is another caveat here, which is legislation. But 237 00:13:20,332 --> 00:13:23,092 S1: what could the legislation possibly look like? They're like, you 238 00:13:23,092 --> 00:13:27,771 S1: can't fire your human workers anymore. Well, that just that 239 00:13:27,772 --> 00:13:29,612 S1: just tells like all the workers like you could do 240 00:13:29,612 --> 00:13:31,891 S1: whatever and they can't fire you. Like it's some crazy 241 00:13:31,892 --> 00:13:35,292 S1: union stuff. And I don't think it'll be that extreme, 242 00:13:35,492 --> 00:13:38,172 S1: although there is some extreme stuff happening in New York City, 243 00:13:38,172 --> 00:13:41,092 S1: so who knows, maybe something like that will happen. That 244 00:13:41,092 --> 00:13:44,732 S1: could definitely slow things down. Uh, big sort of terrorist events, 245 00:13:44,732 --> 00:13:49,651 S1: I think, that are like planned or assisted, planned by AI, 246 00:13:49,692 --> 00:13:53,292 S1: that cause major disruption, that could cause some legislation. But 247 00:13:53,332 --> 00:13:58,051 S1: other than that, I just see kind of normal non 248 00:13:59,131 --> 00:14:02,932 S1: I would say non-crazy people about AI, people who aren't 249 00:14:03,332 --> 00:14:07,012 S1: forget AI, not crazy about learning, not crazy about building, 250 00:14:07,011 --> 00:14:13,892 S1: not crazy about Progressing and evolving that mentality because the 251 00:14:13,892 --> 00:14:16,092 S1: tech doesn't really matter, right? We've we've always had people 252 00:14:16,092 --> 00:14:18,212 S1: that were like that and weren't like that. Right. And 253 00:14:18,212 --> 00:14:22,692 S1: previously the tech was like reading and computers. Right. And 254 00:14:22,972 --> 00:14:27,372 S1: you know, tech in that sense. Um, and obviously people 255 00:14:27,372 --> 00:14:30,492 S1: who are fluent with computers and really good readers and, 256 00:14:30,532 --> 00:14:32,732 S1: you know, could write well and all that, they have 257 00:14:32,732 --> 00:14:36,172 S1: a massive advantage. This is just taking that same advantage 258 00:14:36,692 --> 00:14:40,132 S1: with a different tech and magnifying it by a thousand. 259 00:14:41,292 --> 00:14:44,732 S1: That's what this is right now. And it's really hard 260 00:14:44,732 --> 00:14:48,332 S1: to watch when you think about what is likely to 261 00:14:48,332 --> 00:14:52,412 S1: happen to most people. Um, and then I'm like, okay, 262 00:14:52,412 --> 00:14:53,892 S1: what am I going to do to get myself out 263 00:14:53,892 --> 00:14:57,172 S1: of this mindset? And I'm like, well, I've got to 264 00:14:57,532 --> 00:14:59,652 S1: help build. I got to help with government. I've got 265 00:14:59,652 --> 00:15:02,732 S1: to help get someone elected who's actually, uh, you know, 266 00:15:02,772 --> 00:15:06,892 S1: centrist and actually cares about poor people and, um, isn't 267 00:15:06,892 --> 00:15:09,182 S1: going to break the economy and move us towards communism, 268 00:15:09,502 --> 00:15:12,342 S1: or go extreme right or extreme left. Like how do 269 00:15:12,342 --> 00:15:15,142 S1: how do we do this? All these, all these powers, 270 00:15:15,142 --> 00:15:18,302 S1: all these tools that we have? Can I use something 271 00:15:18,302 --> 00:15:23,902 S1: like substrate to build a platform that is democratic, it's transparent. 272 00:15:23,902 --> 00:15:31,542 S1: It uncovers, um, corruption. It provides, you know, an auditable 273 00:15:31,942 --> 00:15:35,982 S1: government for ourselves where we feel like we're more involved. Um, 274 00:15:36,102 --> 00:15:39,302 S1: how can we bring this technology to be personal tutors 275 00:15:39,462 --> 00:15:42,142 S1: for everyone, for billions of people on the planet, as 276 00:15:42,142 --> 00:15:46,342 S1: opposed to only the, um, you know, the most academically 277 00:15:46,342 --> 00:15:49,542 S1: focused cultures having it? Why can't we give it to everyone? Right. 278 00:15:49,582 --> 00:15:55,942 S1: So I'm thinking about like. Basically, what are projects that 279 00:15:55,942 --> 00:15:59,142 S1: I could do that can maybe help solve some of 280 00:15:59,142 --> 00:16:02,702 S1: this problem for people who are going to be left behind. 281 00:16:02,902 --> 00:16:06,462 S1: And right now that's largely substrate. So I'm working really 282 00:16:06,462 --> 00:16:08,622 S1: hard on that. That's going to be like my main 283 00:16:08,622 --> 00:16:10,542 S1: thing for the next couple of weeks is trying to 284 00:16:10,542 --> 00:16:12,302 S1: get that spun up with a lot more data, a 285 00:16:12,342 --> 00:16:16,902 S1: lot more ideas. Um, maybe a whole site around it. Um, 286 00:16:16,902 --> 00:16:21,262 S1: domain and stuff like that. But the concept here is like, 287 00:16:22,502 --> 00:16:23,942 S1: I don't want to be sad about it. I don't 288 00:16:23,942 --> 00:16:30,622 S1: want to just, you know, have an apathetic attitude toward it. Um, 289 00:16:30,622 --> 00:16:32,382 S1: I definitely am not going to have, like, an elitist 290 00:16:32,382 --> 00:16:34,942 S1: attitude towards it of like, well, we're just special and 291 00:16:34,942 --> 00:16:38,262 S1: they're just not special and therefore we deserve with a 292 00:16:38,302 --> 00:16:41,102 S1: D word, right? We deserve all these things because people 293 00:16:41,102 --> 00:16:42,582 S1: just don't want to read books and they don't want 294 00:16:42,582 --> 00:16:46,062 S1: to play with AI. That's a shitty attitude to have to, um, 295 00:16:46,102 --> 00:16:48,222 S1: as is the attitude of like, well, there's nothing I 296 00:16:48,222 --> 00:16:50,102 S1: could do to help them, right? So it seems like 297 00:16:50,102 --> 00:16:53,422 S1: the only third rail there is fucking try to do 298 00:16:53,422 --> 00:16:57,822 S1: something and and before, you know, you kind of have 299 00:16:57,822 --> 00:17:00,462 S1: an excuse. Well, what can you do? I can't possibly 300 00:17:00,462 --> 00:17:03,742 S1: research all that. I can't possibly find all the different 301 00:17:03,742 --> 00:17:06,182 S1: donors who are giving money to these politicians. I can't 302 00:17:06,182 --> 00:17:11,872 S1: possibly build an entire government transparency platform. Well, yeah, now 303 00:17:11,872 --> 00:17:14,912 S1: you can. Now there's no excuse to not being part 304 00:17:14,912 --> 00:17:19,392 S1: of the solution. So that's the mindset I have right now. And, uh, 305 00:17:19,432 --> 00:17:22,631 S1: anyone who wants to help, please reach out. I really 306 00:17:24,152 --> 00:17:27,512 S1: would love some ideas on this. Uh, ways to take threshold, 307 00:17:27,552 --> 00:17:33,112 S1: not threshold, uh, substrate, uh, along these lines and, uh. Yeah. 308 00:17:34,192 --> 00:17:39,591 S1: All right. Next one here. Um, Marcus posted a YouTube video, 309 00:17:39,592 --> 00:17:42,032 S1: and he did an intro of the video, just like 310 00:17:42,032 --> 00:17:44,512 S1: I did, where he basically laid out how he doesn't 311 00:17:44,512 --> 00:17:48,952 S1: believe in AI. He, uh, basically completely opposite views to me, uh, 312 00:17:48,952 --> 00:17:50,192 S1: which I thought was cool. I thought it was a 313 00:17:50,192 --> 00:17:53,112 S1: cool intro. And I got the link there. Project Hail Mary. 314 00:17:53,152 --> 00:17:55,192 S1: One of the coolest books we've read in UL. Book 315 00:17:55,192 --> 00:17:58,792 S1: club has a trailer out and the trailer is out 316 00:17:58,792 --> 00:18:00,272 S1: and you got to go check it out. It looks 317 00:18:00,272 --> 00:18:02,512 S1: really good. It looks like they've they've done it well. 318 00:18:02,792 --> 00:18:04,431 S1: It felt like a book when I was looking at 319 00:18:04,432 --> 00:18:07,002 S1: the trailer, so that's a good sign. The big question is, 320 00:18:07,042 --> 00:18:10,081 S1: what is, um, you know, the the alien going to 321 00:18:10,082 --> 00:18:12,242 S1: look like. Uh, so I can't wait to see that, 322 00:18:12,242 --> 00:18:15,282 S1: but it looks promising. Network. Chuck did a whole video 323 00:18:15,282 --> 00:18:18,242 S1: on Telos and his process of trying to go through 324 00:18:18,282 --> 00:18:22,602 S1: the the whole Telos exercise, and it was really good. 325 00:18:22,602 --> 00:18:25,722 S1: And it was also the honesty and the vulnerability that 326 00:18:25,722 --> 00:18:31,562 S1: Chuck shared in this was really, really endearing and really, really, um, 327 00:18:31,802 --> 00:18:34,962 S1: I just loved it. And, uh, hats off to him to, 328 00:18:35,402 --> 00:18:39,082 S1: to put himself out there like that and, uh, continue 329 00:18:39,082 --> 00:18:42,442 S1: doing the good stuff that he's doing. All right. Cybersecurity 330 00:18:42,482 --> 00:18:46,601 S1: US agencies warn Iran that hackers may target critical infrastructure 331 00:18:46,602 --> 00:18:51,442 S1: during Mideast tensions. So FBI, NSA, everyone's basically saying that 332 00:18:51,442 --> 00:18:56,602 S1: this is likely to happen, especially around USA slash Israeli, uh, 333 00:18:56,602 --> 00:19:05,322 S1: operations or companies. DOJ says that in 2018 Sinaloa Sinaloa 334 00:19:05,882 --> 00:19:11,882 S1: Sinaloa cartel hacker used FBI officials phone to track their 335 00:19:11,882 --> 00:19:16,482 S1: movements and identify informants, and those informants were then intimidated 336 00:19:16,482 --> 00:19:21,121 S1: and or killed. Switzerland. Government data is stolen in a 337 00:19:21,122 --> 00:19:24,841 S1: ransomware attack. A whole bunch of it. 1.3TB of government 338 00:19:24,842 --> 00:19:30,042 S1: data now available. Free. Google fixed the fourth Chrome zero day. 339 00:19:30,802 --> 00:19:33,962 S1: Persona is a really cool technology. It's, um. This is 340 00:19:34,002 --> 00:19:35,722 S1: actually a company, so I'm not sure how they made 341 00:19:35,722 --> 00:19:40,082 S1: it in here, but, um, 75 million blocked attempts means 342 00:19:40,082 --> 00:19:44,882 S1: there are probably way more getting through to other systems. And, uh, yeah, 343 00:19:44,882 --> 00:19:49,002 S1: they basically try to counter, uh, I fraudsters. So it's 344 00:19:49,002 --> 00:19:52,641 S1: basically a whole bunch of AI to counter, um, you know, 345 00:19:52,682 --> 00:19:55,762 S1: corruptions and fakes and fraud and stuff like that. So 346 00:19:55,762 --> 00:19:58,802 S1: a really cool, uh, company not involved with them, but 347 00:19:58,842 --> 00:20:02,362 S1: would love to be, uh, Chinese hackers hit Canadian telecom 348 00:20:02,682 --> 00:20:06,812 S1: using 16 month old unpatched Cisco flaw. US House has 349 00:20:06,892 --> 00:20:10,571 S1: banned WhatsApp because they don't like the data handling practices 350 00:20:10,571 --> 00:20:15,772 S1: of meta and AT&T. Finally rolls out SIM swap lock, which, uh, 351 00:20:15,852 --> 00:20:19,331 S1: they have not had in previously. Uh, Verizon and a 352 00:20:19,332 --> 00:20:21,172 S1: bunch of other companies have had it, but, uh, took 353 00:20:21,172 --> 00:20:24,652 S1: a while for AT&T to get it. National security. China's 354 00:20:24,652 --> 00:20:28,172 S1: mosquito sized spy drone. So small you might not not 355 00:20:28,172 --> 00:20:31,252 S1: even notice it flying around your house. And it's got 356 00:20:31,292 --> 00:20:35,532 S1: tiny cameras and microphones. Holy crap. This is where I 357 00:20:35,532 --> 00:20:39,652 S1: tell you to read Kill Decision by Daniel Suarez. As 358 00:20:39,652 --> 00:20:44,732 S1: per requirement, AI cloud code gets hooks. So now you 359 00:20:44,732 --> 00:20:49,332 S1: can auto execute functions from your AI conversations. Meta creates 360 00:20:49,372 --> 00:20:52,052 S1: a new superintelligence lab and they hired a whole bunch 361 00:20:52,212 --> 00:20:57,972 S1: of OpenAI people. It's kind of funny. It's like Sam taunted, uh, Zuckerberg. 362 00:20:58,372 --> 00:21:00,492 S1: And he's like, yeah, they didn't hire any of our people. 363 00:21:01,132 --> 00:21:03,972 S1: And a week later, Zuck is like, oh, really? And 364 00:21:03,972 --> 00:21:06,772 S1: hires like five or something or more of like their 365 00:21:06,772 --> 00:21:09,092 S1: best people or really good people anyway. I don't know 366 00:21:09,252 --> 00:21:12,212 S1: how good they rank, but really good people spends like 367 00:21:12,212 --> 00:21:15,131 S1: billions of dollars, I think literally billions of dollars on this. 368 00:21:15,852 --> 00:21:18,092 S1: And now everyone's like, hey, maybe meta is the place 369 00:21:18,092 --> 00:21:21,812 S1: to work. So yeah, don't, uh, don't taunt Mark Zuckerberg. 370 00:21:21,811 --> 00:21:25,331 S1: That's my lesson. Marc Benioff says that AI now does 371 00:21:25,332 --> 00:21:28,332 S1: half of the work at Salesforce. He's got some cool 372 00:21:28,332 --> 00:21:32,412 S1: stats here, but again, he's selling an AI product. So 373 00:21:32,811 --> 00:21:34,892 S1: I don't know. You got to you got to weigh 374 00:21:34,892 --> 00:21:39,772 S1: that in. Google brings AI search to YouTube. So they're 375 00:21:39,772 --> 00:21:42,411 S1: basically doing a lot of summaries of videos. And I 376 00:21:42,412 --> 00:21:44,252 S1: think this is heading in the direction I've been talking about, 377 00:21:44,252 --> 00:21:48,851 S1: where I actually makes the deal version of the content 378 00:21:49,132 --> 00:21:52,932 S1: for you. Right. The actual future is that your own 379 00:21:52,932 --> 00:21:56,212 S1: personal Da would do this for you. So basically it'll 380 00:21:56,252 --> 00:22:00,172 S1: see this YouTube video of whoever pop up, it'll go 381 00:22:00,172 --> 00:22:03,862 S1: read the video, watch the video, whatever it does. And 382 00:22:04,582 --> 00:22:06,901 S1: it knows what you're doing at the time. Okay. If 383 00:22:06,902 --> 00:22:08,582 S1: you're on a bicycle ride, if you're on a hike, 384 00:22:08,622 --> 00:22:11,942 S1: if you're on a whatever, you're driving and it's like 385 00:22:11,942 --> 00:22:13,862 S1: you can't pay attention to the screen or whatever for 386 00:22:13,862 --> 00:22:16,622 S1: whatever reason, or maybe you don't even like to watch video, 387 00:22:16,662 --> 00:22:19,341 S1: it'll give it to you an audio version, but more importantly, 388 00:22:19,342 --> 00:22:22,621 S1: it cut it up. It re-edited it for you in 389 00:22:22,622 --> 00:22:25,142 S1: the way that you like it. Right? So it made 390 00:22:25,142 --> 00:22:28,102 S1: a complete net new video. It might have deepfaked the 391 00:22:28,102 --> 00:22:30,821 S1: actual original creator, but it might have just put your 392 00:22:30,821 --> 00:22:33,142 S1: favorite person on there. Maybe it was Taylor Swift or 393 00:22:33,142 --> 00:22:38,182 S1: Richard Feynman who actually gives you the content. So dynamic 394 00:22:38,742 --> 00:22:42,181 S1: custom content. That's what we're going to see from AI. 395 00:22:42,382 --> 00:22:45,462 S1: And this is just like an intermediary step of that. 396 00:22:45,462 --> 00:22:49,462 S1: It is Google providing the AI summary of the content, 397 00:22:49,462 --> 00:22:52,542 S1: which also came from Google. But you see where it's going. 398 00:22:52,821 --> 00:22:55,462 S1: And I think creators need to be very concerned about 399 00:22:55,462 --> 00:22:58,022 S1: this and be thinking about the future, because it could 400 00:22:58,022 --> 00:23:02,782 S1: be that raw content is not really the thing anymore. 401 00:23:02,902 --> 00:23:08,422 S1: Raw content just becomes literally raw material. And here's the 402 00:23:08,422 --> 00:23:15,901 S1: problem can raw content ever compete with someone's personal digital 403 00:23:15,902 --> 00:23:19,621 S1: assistant who knows them better than anybody in the entire universe, 404 00:23:20,022 --> 00:23:23,861 S1: who is also an expert in creating content? Can the 405 00:23:23,862 --> 00:23:28,902 S1: original source make a video better than that? All knowing, 406 00:23:29,102 --> 00:23:33,302 S1: super smart, super creative AI can make for their favorite person? 407 00:23:34,022 --> 00:23:36,581 S1: I think the answer is probably no. Now there are 408 00:23:36,582 --> 00:23:37,982 S1: going to be a whole bunch of exceptions to this, 409 00:23:37,982 --> 00:23:40,222 S1: and it's not going to happen overnight, right? So these 410 00:23:40,222 --> 00:23:44,982 S1: things aren't emergencies. They take time. But so one example 411 00:23:44,982 --> 00:23:48,302 S1: is like you're a celebrity, okay. If there's a celebrity, 412 00:23:48,502 --> 00:23:50,142 S1: you like the way they talk, you like the way 413 00:23:50,142 --> 00:23:54,302 S1: they look. You like their jokes. Well, maybe that doesn't 414 00:23:54,302 --> 00:23:58,462 S1: get deepfaked because maybe the deepfake doesn't copy that perfectly right. 415 00:23:58,502 --> 00:24:01,341 S1: Or maybe it's just human. You just like to watch 416 00:24:01,342 --> 00:24:04,552 S1: humans do their thing right? We see this in chess, 417 00:24:04,992 --> 00:24:07,912 S1: and chess is more fun and more popular than it's 418 00:24:07,912 --> 00:24:12,272 S1: ever been right now because people have real, actual stories, right? Um, 419 00:24:12,952 --> 00:24:19,151 S1: Ganesh like, uh, winning and Ganesh losing and, uh, you know, uh, 420 00:24:19,152 --> 00:24:21,912 S1: Magnus winning and losing. Like, I care about that. I 421 00:24:21,952 --> 00:24:24,392 S1: care about that. I care about the Botez sisters who 422 00:24:24,392 --> 00:24:27,472 S1: are grinding, and I care about, um, the younger one, Andrea, 423 00:24:27,552 --> 00:24:31,432 S1: because she's doing, um, techno on the side, and she's 424 00:24:31,432 --> 00:24:35,112 S1: doing modeling, and she's a chess influencer, and she's hella smart, 425 00:24:35,112 --> 00:24:37,752 S1: like her sister. And so there are content creators, but 426 00:24:37,752 --> 00:24:39,872 S1: they're also doing chess, and they love chess. And they're, 427 00:24:39,912 --> 00:24:41,872 S1: I don't know, I think they're stuck at around 19 428 00:24:41,872 --> 00:24:46,512 S1: or 2100 somewhere around there. And then you've got Gotham, who? 429 00:24:46,512 --> 00:24:48,912 S1: I really like him. He does the best like overviews 430 00:24:48,912 --> 00:24:52,311 S1: of chess. Um, he's a really good narrator, and he's 431 00:24:52,352 --> 00:24:57,832 S1: on a mission to get to Grandmaster, right? I love that. 432 00:24:57,832 --> 00:25:00,352 S1: I love that everyone makes fun of him because he's 433 00:25:00,352 --> 00:25:03,442 S1: not great. I think he's like, is he like 2000, 434 00:25:03,482 --> 00:25:08,042 S1: 2200 something or no, 2200 is Grandmaster, I think, or 2400. Anyway, 435 00:25:08,082 --> 00:25:10,762 S1: he's a lot of people think he'll never get there. 436 00:25:10,762 --> 00:25:13,042 S1: But he started having wins, right? I think he had 437 00:25:13,042 --> 00:25:15,962 S1: a win over Magnus, uh, kind of on accident or whatever. 438 00:25:16,762 --> 00:25:19,121 S1: Or he just. He played a really good game, and 439 00:25:19,162 --> 00:25:22,162 S1: Magnus played a bad game, whatever it was. But, um, 440 00:25:22,602 --> 00:25:25,402 S1: that is a human story. Here's a guy who probably 441 00:25:25,402 --> 00:25:28,321 S1: you're not expecting to be a grandmaster, and he might 442 00:25:28,321 --> 00:25:30,322 S1: get there, and he gives you updates on it. So 443 00:25:30,321 --> 00:25:33,482 S1: you're pulling from for him, right? So the question is, 444 00:25:34,561 --> 00:25:37,962 S1: will those sorts of stories, those sorts of human aspects 445 00:25:38,162 --> 00:25:40,922 S1: protect against this? I think it will. There's no question. 446 00:25:40,922 --> 00:25:44,882 S1: It will. The question is how much versus like an 447 00:25:44,882 --> 00:25:48,282 S1: AI influencer, maybe it's an AI influencer who's actually giving 448 00:25:48,282 --> 00:25:50,962 S1: your stuff. Maybe that's the avatar for your actual Da. 449 00:25:51,602 --> 00:25:54,242 S1: And he or she is like the most attractive person 450 00:25:54,242 --> 00:25:57,002 S1: in the world, and they could change their outfits or 451 00:25:57,002 --> 00:26:00,522 S1: whatever to put on a school uniform like Richard Feynman, 452 00:26:00,561 --> 00:26:04,522 S1: you know, teaching at university with the university hat or whatever, 453 00:26:04,682 --> 00:26:06,682 S1: and just be like, yeah, here's how this physical thing 454 00:26:06,682 --> 00:26:08,722 S1: works and, you know, teach you physics or teach you 455 00:26:08,722 --> 00:26:12,682 S1: math or whatever. Um, but the threat to content creators 456 00:26:12,682 --> 00:26:17,042 S1: is like, I'm making all this content only I is 457 00:26:17,042 --> 00:26:21,522 S1: consuming the content. People don't, you know, very few actual 458 00:26:21,522 --> 00:26:25,802 S1: humans are consuming my content because there are millions of 459 00:26:25,802 --> 00:26:29,802 S1: other people, hundreds of millions of other people creating content 460 00:26:30,321 --> 00:26:33,962 S1: and billions of other agents creating content. So it's a 461 00:26:33,962 --> 00:26:41,042 S1: giant content creating marketplace. Um, and for regular consumers, keep 462 00:26:41,042 --> 00:26:44,602 S1: in mind, our bandwidth is limited as humans to consume content, right? 463 00:26:44,722 --> 00:26:48,642 S1: So even if we wanted to, we can't follow all 464 00:26:48,682 --> 00:26:50,482 S1: all the cool people that we want to. I mean, 465 00:26:50,482 --> 00:26:52,881 S1: I got friends whose newsletters I don't even read. I 466 00:26:52,922 --> 00:26:54,522 S1: know for a fact a lot of my friends don't 467 00:26:54,522 --> 00:26:57,362 S1: read my newsletter. They're just too busy. Why? Because they're 468 00:26:57,362 --> 00:27:02,652 S1: content creators, right? And I'll read, um, many of their newsletters, 469 00:27:02,652 --> 00:27:05,012 S1: like once a month, right? But I'm not reading it 470 00:27:05,012 --> 00:27:07,172 S1: all the time. And they're damn sure not reading mine 471 00:27:07,172 --> 00:27:09,612 S1: all the time. Right? We catch a little piece from 472 00:27:09,612 --> 00:27:11,811 S1: each other and we're like, hey, great, great job with that. 473 00:27:11,852 --> 00:27:13,172 S1: It's like, hey, did you see this one? No, I 474 00:27:13,172 --> 00:27:15,612 S1: didn't see that one. Sorry. Right. We don't even have 475 00:27:15,612 --> 00:27:17,772 S1: the time. We don't have the time. Now imagine when 476 00:27:17,772 --> 00:27:20,372 S1: there's ten times more content, a thousand times more content, 477 00:27:20,372 --> 00:27:23,812 S1: a million times more content. The only thing that's consuming 478 00:27:23,811 --> 00:27:29,252 S1: that content is I working for somebody. And that somebody 479 00:27:29,892 --> 00:27:32,772 S1: in many cases is going to be the digital assistant 480 00:27:32,811 --> 00:27:36,012 S1: of somebody else, right? And then they'll just dynamically create 481 00:27:36,012 --> 00:27:41,492 S1: the content for them. All right. Grammarly acquires superhuman. That 482 00:27:41,492 --> 00:27:45,571 S1: was supposed to be bolded. I hate formatting mistakes. Um, 483 00:27:45,612 --> 00:27:49,172 S1: that was my bad. Um, all right. Anthropic turns Claude 484 00:27:49,172 --> 00:27:51,492 S1: into a no code app. Okay, so basically anthropic is 485 00:27:51,492 --> 00:27:55,052 S1: now competing directly with, um, like V0 and all the 486 00:27:55,052 --> 00:27:58,612 S1: other app makers. So everyone's everyone's converging on the same space, 487 00:27:58,972 --> 00:28:02,492 S1: my content or my comment. There was almost no castle. 488 00:28:03,132 --> 00:28:09,012 S1: Where's the moat? No. Where's the castle? Let's see here. Yeah. Technology. 489 00:28:09,012 --> 00:28:12,892 S1: Cloudflare now blocks AI crawlers by default. They are doing 490 00:28:12,892 --> 00:28:16,811 S1: this crazy model. They're going to start charging AI crawlers 491 00:28:17,252 --> 00:28:19,292 S1: to consume content. So this is the type of thing 492 00:28:19,292 --> 00:28:23,532 S1: that could potentially economically disrupt this whole this whole meta 493 00:28:23,532 --> 00:28:27,732 S1: that I was just talking about. Right. Um, and that's why, 494 00:28:27,892 --> 00:28:29,611 S1: you know, you got to watch yourself with predictions. You 495 00:28:29,612 --> 00:28:31,612 S1: don't know how the economy, you don't know how society 496 00:28:31,612 --> 00:28:34,532 S1: is going to adjust. Um, maybe there becomes this thing 497 00:28:34,532 --> 00:28:38,812 S1: where it's like, maybe we're able to make an economy 498 00:28:39,132 --> 00:28:42,572 S1: where the raw content has value. I find that hard 499 00:28:42,572 --> 00:28:47,812 S1: to believe, but, um, I think it will happen to 500 00:28:47,852 --> 00:28:51,171 S1: some degree. Okay. There will be sectors where where it 501 00:28:51,172 --> 00:28:54,212 S1: does happen or a degree to which it does happen. 502 00:28:54,252 --> 00:28:56,132 S1: Like anything that's a good idea is going to happen 503 00:28:56,132 --> 00:28:57,852 S1: a little bit. The question is what's going to be 504 00:28:57,852 --> 00:29:02,422 S1: the dominant model. I don't unfortunately, you know, and I 505 00:29:02,462 --> 00:29:04,822 S1: create content as well as one of the things that 506 00:29:04,822 --> 00:29:09,542 S1: I do, um, I don't I don't see a crazy 507 00:29:09,582 --> 00:29:13,102 S1: good future for, you know, billions of people are going 508 00:29:13,142 --> 00:29:15,502 S1: to be watching this YouTube video that I put out. 509 00:29:15,862 --> 00:29:17,302 S1: It's not going to be that. It's going to be 510 00:29:17,342 --> 00:29:20,142 S1: I watching that video I put out. And hopefully here's 511 00:29:20,142 --> 00:29:22,542 S1: the only thing I can hope for. The only thing 512 00:29:22,542 --> 00:29:28,062 S1: I can hope for is the Da. Their Da attributes 513 00:29:28,062 --> 00:29:32,102 S1: it to me and you know, shows a picture of me, 514 00:29:32,102 --> 00:29:33,902 S1: or shows a piece of content that I wrote or 515 00:29:33,942 --> 00:29:36,342 S1: says something cool about it and it's like or says, hey, 516 00:29:36,342 --> 00:29:39,182 S1: this is the seventh thing that I've shown you, you know, 517 00:29:39,222 --> 00:29:43,222 S1: from Clint Gibler this week, um, you know. Oh, and also, 518 00:29:43,262 --> 00:29:46,662 S1: he lives nearby. You should go get a coffee. That's 519 00:29:46,662 --> 00:29:48,982 S1: the type of thing that hopefully is going to happen, right? 520 00:29:48,982 --> 00:29:52,182 S1: You should talk to Clint, because Clint is also talking 521 00:29:52,182 --> 00:29:53,782 S1: about a lot of the same stuff you're talking about. 522 00:29:53,822 --> 00:29:56,942 S1: I'm like, oh, really? And my da, my da, whose 523 00:29:56,942 --> 00:29:59,072 S1: name is Chi, by the way. Chi is like, yeah, actually, 524 00:29:59,072 --> 00:30:00,472 S1: a lot of the stuff I've been showing you, like 525 00:30:00,512 --> 00:30:02,432 S1: a lot of those videos that I made for you, 526 00:30:02,472 --> 00:30:06,352 S1: those actually came from Clint's videos. And I'm like, okay, well, 527 00:30:06,352 --> 00:30:09,152 S1: in the future, you know, put like a Clint, you know, 528 00:30:09,192 --> 00:30:12,272 S1: watermark on it or something. And he's like, okay. Yeah, sure. 529 00:30:12,272 --> 00:30:14,152 S1: My bad. Yeah, I'll make sure I do that. So 530 00:30:14,152 --> 00:30:19,552 S1: hopefully there's something like that dynamic that happens. All right. Uh, 531 00:30:19,552 --> 00:30:24,632 S1: meta adds another gigawatt of renewable power to feed its datacenters. 532 00:30:24,632 --> 00:30:30,952 S1: So it's buying, um, okay. Solar, wind, geothermal. I thought 533 00:30:30,952 --> 00:30:35,152 S1: I also had in here. Yeah. They're also, um, doing 534 00:30:35,152 --> 00:30:38,352 S1: nuclear stuff as well. They're buying nuclear stuff. Um, maybe 535 00:30:38,352 --> 00:30:42,032 S1: that was a previous story. Um, all right, humans, scientists 536 00:30:42,032 --> 00:30:46,872 S1: finally pinpoint what wiped out America's bees, and it wasn't pesticides. 537 00:30:46,912 --> 00:30:49,552 S1: I'm going to leave that as a mystery for you 538 00:30:49,552 --> 00:30:53,792 S1: to go. Click noise ruins sleep quality even when you 539 00:30:53,792 --> 00:31:01,352 S1: think you're sleeping through it. I've recently moved to full earbuds. Um, 540 00:31:01,352 --> 00:31:07,272 S1: not Apple ones like actual, um, in-ear, you know, non-electronic earbuds. 541 00:31:07,392 --> 00:31:09,272 S1: And I got a new sleep mask. Oh, I'm about 542 00:31:09,272 --> 00:31:11,872 S1: to do a wirecutter episode for for members, by the way. 543 00:31:12,112 --> 00:31:14,272 S1: So it's going to be like, because I'm super crazy 544 00:31:14,272 --> 00:31:16,592 S1: when it comes to all this, uh, like the best pens, 545 00:31:16,592 --> 00:31:19,472 S1: the best shoes, the best, you know, covers for your 546 00:31:19,472 --> 00:31:21,952 S1: pillows or whatever. So I'm about to do that. Um, 547 00:31:21,992 --> 00:31:24,552 S1: I don't know. I should call it Wirecutter probably get sued, though. 548 00:31:25,192 --> 00:31:29,952 S1: Maybe I'll call it something else. UL wirecutter. I don't know. Um, anyway, 549 00:31:30,952 --> 00:31:35,592 S1: I mask massively upgraded my eye mask, so it's better 550 00:31:35,592 --> 00:31:39,632 S1: than the ms1 that I've been using, and it's just fantastic. Um. 551 00:31:39,672 --> 00:31:43,592 S1: Highly recommend. Eye mask and earplugs. I do have to 552 00:31:43,592 --> 00:31:46,592 S1: have very strong locks on the doors, because I don't 553 00:31:46,592 --> 00:31:49,312 S1: like the idea of of not being able to hear 554 00:31:49,312 --> 00:31:51,912 S1: people sneak up on me. That's the army for you. 555 00:31:53,112 --> 00:31:57,042 S1: Luckin coffee opens up first US stores after beating Starbucks 556 00:31:57,042 --> 00:31:59,602 S1: in China. They just opened up the first two US 557 00:31:59,602 --> 00:32:03,002 S1: locations and they're in New York City. This is basically 558 00:32:03,002 --> 00:32:06,522 S1: the BYD of coffee. Um, so naturally I want to 559 00:32:06,522 --> 00:32:08,442 S1: go there and I wanted to check it out. I 560 00:32:08,442 --> 00:32:10,042 S1: want to sit in the chairs. I want to look 561 00:32:10,042 --> 00:32:12,442 S1: at people there. I want to just see the vibe. 562 00:32:12,442 --> 00:32:15,362 S1: I want to, you know, knock my knuckles on the 563 00:32:15,362 --> 00:32:17,602 S1: table and the chairs and just, like, see what they're 564 00:32:17,602 --> 00:32:20,002 S1: doing different. I want to see, like, how their employees 565 00:32:20,002 --> 00:32:23,562 S1: interact with people. I'm like, fascinated by this whole concept 566 00:32:23,562 --> 00:32:27,362 S1: of like, when one chain wins out over another, what 567 00:32:27,362 --> 00:32:29,882 S1: did they do better? You know, in and out, chick 568 00:32:29,882 --> 00:32:34,562 S1: fil A, stuff like that. Uh, staff at the Louvre 569 00:32:35,122 --> 00:32:39,442 S1: shut down the museum to protest unmanageable tourist crowds. Uh, 570 00:32:39,482 --> 00:32:43,002 S1: I've been once, and it was a hellscape. It was 571 00:32:43,002 --> 00:32:46,722 S1: an absolute hellscape of people who cared nothing about art whatsoever. 572 00:32:47,162 --> 00:32:52,242 S1: They were crammed in like insects and nothing but iPhones everywhere. 573 00:32:53,642 --> 00:32:56,842 S1: And it was, I don't know, it was kind of 574 00:32:56,882 --> 00:33:00,402 S1: the opposite of art. It was the worst art experience 575 00:33:00,402 --> 00:33:03,762 S1: I've ever had was at the Louvre. That's what I'll 576 00:33:03,762 --> 00:33:06,482 S1: say about that. The dollar just had its worst first 577 00:33:06,482 --> 00:33:11,002 S1: half since 1973, and stocks are doing better than ever. 578 00:33:11,002 --> 00:33:14,682 S1: But the dollar is falling and Trump threatens to investigate 579 00:33:14,682 --> 00:33:18,522 S1: Musk's companies through Doge. He also. I didn't see the 580 00:33:18,522 --> 00:33:21,882 S1: actual quote. So I don't know like what level of 581 00:33:21,922 --> 00:33:26,802 S1: grumpiness it was. But, uh, he also somehow alluded to 582 00:33:26,842 --> 00:33:30,482 S1: deporting Elon. And the whole reason for this is because 583 00:33:30,522 --> 00:33:34,202 S1: Elon is now proposing a third political party, because he 584 00:33:34,202 --> 00:33:39,282 S1: is so morally upset with the waste and the budget. Um, 585 00:33:39,442 --> 00:33:43,362 S1: I actually had a debate, a public debate, uh, on 586 00:33:43,362 --> 00:33:47,442 S1: LinkedIn with Marcus. Uh, we made two bets, and I 587 00:33:47,442 --> 00:33:50,442 S1: believe I've now won both bets. Uh, so the first 588 00:33:50,442 --> 00:33:55,452 S1: bet that we made was, um, he thought Tesla's Tesla 589 00:33:55,492 --> 00:33:59,012 S1: stock was going to drop below like $300 or $200. 590 00:33:59,012 --> 00:34:01,732 S1: I forgot what the number was by a certain date 591 00:34:02,092 --> 00:34:05,052 S1: and um, or it would not get above a certain amount. 592 00:34:05,052 --> 00:34:06,932 S1: I forget what it was. Well, it immediately went to 593 00:34:06,972 --> 00:34:10,011 S1: like 400 something and it's now very high. It's like 594 00:34:10,012 --> 00:34:12,932 S1: 300 something, I don't know. Um, but I think I 595 00:34:12,932 --> 00:34:15,051 S1: already won that one. And then what I told him 596 00:34:15,052 --> 00:34:20,172 S1: is that, uh, Musk would break from Trump because of 597 00:34:20,172 --> 00:34:25,852 S1: some moral issue, because of some principle issue. And that happened, uh, 598 00:34:25,852 --> 00:34:29,412 S1: that happened. And the issue wasn't like, you know, child 599 00:34:29,412 --> 00:34:33,812 S1: labor or something. It was balancing the budget and reducing 600 00:34:33,812 --> 00:34:37,492 S1: the debt. And it turns out all that stuff that 601 00:34:37,532 --> 00:34:43,012 S1: Elon was saying about Doge saving money, Elon was not joking. 602 00:34:43,412 --> 00:34:46,532 S1: He was serious. He thought he was actually doing good. 603 00:34:46,892 --> 00:34:49,332 S1: So he goes over there and does all this stuff. 604 00:34:49,612 --> 00:34:51,332 S1: And by the way, a lot of it was really, 605 00:34:51,372 --> 00:34:55,292 S1: really bad. Really bad. Um, I forget the name of 606 00:34:55,292 --> 00:34:57,492 S1: the one organization that just should not have been messed 607 00:34:57,492 --> 00:35:00,132 S1: with the way that it was. And like hundreds of 608 00:35:00,132 --> 00:35:02,972 S1: thousands of people have died because of it. It's or 609 00:35:03,012 --> 00:35:06,532 S1: are going to because of it. And it's like not 610 00:35:06,532 --> 00:35:09,212 S1: all good is what I'm saying there. But the point 611 00:35:09,212 --> 00:35:13,532 S1: is he thought he was doing good. Um, and was 612 00:35:13,532 --> 00:35:16,332 S1: actually trying. It was not like some charade or whatever. 613 00:35:16,572 --> 00:35:20,652 S1: So he leaves Doge kind of gets kicked out of 614 00:35:20,652 --> 00:35:24,852 S1: the whole establishment, and then they're like, hey, big beautiful Bill, 615 00:35:25,012 --> 00:35:28,892 S1: let's raise the debt by trillions of dollars. Let's not 616 00:35:28,892 --> 00:35:35,212 S1: cut anything. Basically multiples of like damage, way more than 617 00:35:35,212 --> 00:35:39,412 S1: any possible good that Doge has done. And so Elon 618 00:35:39,772 --> 00:35:42,772 S1: is absolutely freaking out. That's why he called him a 619 00:35:42,772 --> 00:35:45,572 S1: pedophile in front of hundreds of millions of people. And 620 00:35:45,572 --> 00:35:47,212 S1: it's now why he says he's going to raise a 621 00:35:47,212 --> 00:35:51,332 S1: completely different party called the American Party. So all that 622 00:35:51,332 --> 00:35:57,062 S1: to say is, um, I think, um, I think I 623 00:35:57,062 --> 00:36:01,302 S1: want both of those, um, ideas. Stanford professor made up 624 00:36:01,302 --> 00:36:05,742 S1: that famous chess grandmasters burn 6000 calories. Claim. So the 625 00:36:05,742 --> 00:36:09,782 S1: reason I put this in ideas is because I find 626 00:36:09,782 --> 00:36:15,822 S1: it very interesting that. I learned stuff in the 80s 627 00:36:15,822 --> 00:36:18,862 S1: and the 90s and the 2000 and the tens. We're 628 00:36:18,862 --> 00:36:21,862 S1: still in the 20s. So all those decades I learned things. 629 00:36:22,342 --> 00:36:25,382 S1: How many of those things were just straight? False? For example, 630 00:36:25,382 --> 00:36:31,102 S1: the marshmallow test, how much fundamental? How much did the 631 00:36:31,102 --> 00:36:34,542 S1: belief that that was real lead to mental models in 632 00:36:34,542 --> 00:36:38,182 S1: my brain that are now broken? Um, it's possible that 633 00:36:38,182 --> 00:36:41,302 S1: that particular case didn't actually have those, but what other 634 00:36:41,302 --> 00:36:44,342 S1: things do I still believe are true because of some 635 00:36:44,342 --> 00:36:50,062 S1: crap study that came out that turns out is not replicable. Replicable? 636 00:36:51,822 --> 00:36:54,352 S1: I think the answer is probably large. Hopefully from all 637 00:36:54,352 --> 00:36:56,312 S1: my reading and stuff like that, it's like cleaned up 638 00:36:56,312 --> 00:36:57,712 S1: some of it or most of it, or maybe it's 639 00:36:57,712 --> 00:37:00,112 S1: all gone. Who knows? But I guarantee you, I've still 640 00:37:00,112 --> 00:37:03,112 S1: got some dumb beliefs that some teacher told me or 641 00:37:03,112 --> 00:37:06,912 S1: my parents told me in the 80s. You know, the 642 00:37:06,912 --> 00:37:09,912 S1: food groups, I mean, stuff like that, right? There's just 643 00:37:09,912 --> 00:37:12,072 S1: got to be a million of these things. And, like, 644 00:37:12,072 --> 00:37:14,152 S1: I just hate the idea that, like, the foundation of 645 00:37:14,152 --> 00:37:18,512 S1: the house is, like, got, like, termites or something, or like, 646 00:37:18,792 --> 00:37:21,992 S1: I don't know, nanobots eating, uh, eaten away the, uh, 647 00:37:23,512 --> 00:37:27,432 S1: the the undergirding. Uh, I don't like it. And it's 648 00:37:27,432 --> 00:37:31,352 S1: worth a question of, like, for all of us, you know. 649 00:37:31,392 --> 00:37:34,952 S1: Where is that? Where is that rot? Taste is the 650 00:37:34,952 --> 00:37:37,392 S1: new intelligence. This one should have had a fire mark 651 00:37:37,392 --> 00:37:39,752 S1: next to it. This thing is so good. So how 652 00:37:39,752 --> 00:37:42,232 S1: about Rick Rubin talking about his book? Uh, but it's 653 00:37:42,232 --> 00:37:45,952 S1: a really good full length essay. Uh, go check it out. 654 00:37:46,872 --> 00:37:49,912 S1: Joan Westenberg deleted her entire second brain. Love the idea 655 00:37:49,952 --> 00:37:53,832 S1: here where basically. So she had like, this the super elaborate, 656 00:37:53,832 --> 00:37:57,952 S1: awesome second brain in obsidian. And she basically decided, you 657 00:37:57,952 --> 00:38:03,112 S1: know what? Nah. Nope. Um, I'm spending too much time 658 00:38:03,152 --> 00:38:06,352 S1: optimizing this thing. It's taking away the focus of, like, 659 00:38:06,392 --> 00:38:09,192 S1: actually being good in my own brain and has put 660 00:38:09,192 --> 00:38:11,472 S1: all my effort at being good in the second brain. 661 00:38:12,112 --> 00:38:15,512 S1: So the movement is basically first brain, and she just 662 00:38:15,512 --> 00:38:19,072 S1: trashed the entire thing. I think it's a really interesting 663 00:38:19,112 --> 00:38:22,632 S1: thing to like, not overoptimize. AI is a good example. 664 00:38:22,672 --> 00:38:27,552 S1: Don't overoptimize on AI. It's really anything. Exercise. You know work. 665 00:38:27,592 --> 00:38:30,072 S1: Don't work too much because then your personal relationships, it's 666 00:38:30,072 --> 00:38:32,232 S1: like anything that's a good thing can be a bad 667 00:38:32,232 --> 00:38:34,232 S1: thing if done too much. It's like the most cliche 668 00:38:34,272 --> 00:38:38,872 S1: thing in the world and absolutely worth repeating or remembering. 669 00:38:39,832 --> 00:38:44,032 S1: Schizophrenia may be the evolutionary price. I love articles like 670 00:38:44,032 --> 00:38:45,632 S1: this that are like, hey, you know that thing you 671 00:38:45,632 --> 00:38:49,232 S1: think is bad? That could be a necessary piece of 672 00:38:49,232 --> 00:38:52,442 S1: exhaust that comes after a thing that you think is good. 673 00:38:52,482 --> 00:38:58,522 S1: In this case, they're saying ingenuity, creativity, new ideas. You know, 674 00:38:58,642 --> 00:39:02,922 S1: Einstein type stuff where, oh, maybe it's just space is curved. 675 00:39:02,962 --> 00:39:12,282 S1: You know, maybe that requires that something like schizophrenia exists. Discovery. 676 00:39:12,682 --> 00:39:16,802 S1: How to use markdown. Been book uses AI to turn 677 00:39:16,802 --> 00:39:23,202 S1: coffee bag photos into detailed brew logs. Hmm. Proxy cloud 678 00:39:23,202 --> 00:39:27,442 S1: code requests through Cloudflare. Aging related inflammation isn't universal. The 679 00:39:27,442 --> 00:39:30,322 S1: developer built an AI Dungeon Master that runs in the terminal. 680 00:39:30,362 --> 00:39:34,202 S1: This thing is really cool. Um. James Webb takes first 681 00:39:34,202 --> 00:39:38,722 S1: directional exoplanet photo local LM notepad on a USB stick. 682 00:39:38,722 --> 00:39:41,802 S1: This thing is so cool. Uh, Joseph and I have 683 00:39:41,802 --> 00:39:44,722 S1: been talking about this. Joseph mentioned it to me first. 684 00:39:44,762 --> 00:39:46,602 S1: He's like, hey, you know, how do we have, like, 685 00:39:46,642 --> 00:39:49,642 S1: a local thing of knowledge? You know, worst came to worst. 686 00:39:50,482 --> 00:39:52,122 S1: I want to be able to ask this thing, you know, 687 00:39:52,122 --> 00:39:54,642 S1: how to restart society or something like what's a small 688 00:39:54,642 --> 00:39:56,482 S1: version we could do? Well, here's one that's on the 689 00:39:56,482 --> 00:40:06,002 S1: USB stick and custom voice agent tutorial. Okay, this is 690 00:40:06,002 --> 00:40:07,802 S1: the end of the standard edition of the podcast, which 691 00:40:07,802 --> 00:40:10,002 S1: includes just the news items for the week to get 692 00:40:10,002 --> 00:40:12,082 S1: the rest of the episode, which includes much more of 693 00:40:12,082 --> 00:40:15,362 S1: my analysis, the ideas section, and the weekly member essay. 694 00:40:15,362 --> 00:40:18,082 S1: Please consider becoming a member. As a member, you get 695 00:40:18,122 --> 00:40:20,842 S1: access to all sorts of stuff, most importantly, access to 696 00:40:20,882 --> 00:40:24,042 S1: our extraordinary community of over a thousand brilliant and kind 697 00:40:24,082 --> 00:40:28,482 S1: people in industries like cybersecurity, AI, and the humanities. You 698 00:40:28,482 --> 00:40:31,122 S1: also get access to the UL Book Club, dedicated member 699 00:40:31,122 --> 00:40:34,162 S1: content and events, and lots more. Plus, you'll get a 700 00:40:34,162 --> 00:40:36,442 S1: dedicated podcast feed that you can put into your client 701 00:40:36,442 --> 00:40:38,962 S1: that gets you the full member edition of the podcast 702 00:40:39,002 --> 00:40:41,002 S1: that basically doesn't have this in it, and just goes 703 00:40:41,002 --> 00:40:43,522 S1: all the way through with all the different sections. So 704 00:40:43,562 --> 00:40:45,362 S1: to become a member and get all that, just head 705 00:40:45,362 --> 00:40:50,042 S1: over to Daniel Store.com upgrade. That's Daniel Miessler upgrade and 706 00:40:50,042 --> 00:40:50,962 S1: we'll see you next time.