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 --> 00:00:59,572 S1: like five shells open right now and they're all in 12 00:00:59,572 --> 00:01:03,932 S1: separate repositories. And like, not many of them are actually 13 00:01:03,932 --> 00:01:06,612 S1: building anything related to like a web app or web 14 00:01:06,612 --> 00:01:08,852 S1: coding or any of that. Um, a lot of them 15 00:01:08,852 --> 00:01:12,331 S1: are like, organize this, clean this up, you know, go 16 00:01:12,332 --> 00:01:15,212 S1: get this content, um, fix all the links on my 17 00:01:15,212 --> 00:01:18,542 S1: website or whatever. It's like It's a whole bunch of 18 00:01:18,542 --> 00:01:21,742 S1: stuff that would have taken hours and hours of manual work, 19 00:01:21,742 --> 00:01:24,021 S1: and that's why I hadn't done it yet. And so 20 00:01:24,021 --> 00:01:25,622 S1: now this thing is just like, yeah, tell me what 21 00:01:25,661 --> 00:01:27,581 S1: to do. It's like, okay, cool, I'll write a script 22 00:01:27,581 --> 00:01:30,741 S1: to do that here. I just fixed your entire blog. Okay. 23 00:01:30,822 --> 00:01:34,502 S1: It fixed my entire blog for content going back to 1999. 24 00:01:35,382 --> 00:01:40,822 S1: Hundreds and thousands, thousands of articles, thousands of pieces with 25 00:01:40,822 --> 00:01:45,862 S1: broken links. It migrated all of my images to a 26 00:01:45,902 --> 00:01:49,702 S1: new system. Um, I cleaned up all my cloud or 27 00:01:49,822 --> 00:01:54,382 S1: all my, uh, Cloudflare. Um, basically how everything was being 28 00:01:54,382 --> 00:01:57,062 S1: handled before I was doing a bunch of stuff, um, 29 00:01:57,462 --> 00:02:00,982 S1: with S3 and CloudFront, and I moved everything to be 30 00:02:00,982 --> 00:02:05,942 S1: Cloudflare now, um, I migrated all my images to use 31 00:02:05,942 --> 00:02:08,862 S1: that instead. And they're all located at slash images. This 32 00:02:08,862 --> 00:02:11,382 S1: is all stuff I was like piecing away at manually 33 00:02:12,062 --> 00:02:14,582 S1: and sort of like as I came upon the problem, 34 00:02:14,582 --> 00:02:18,061 S1: I would go and fix it, but to it was 35 00:02:18,062 --> 00:02:20,142 S1: daunting to think about even trying to do this right. 36 00:02:20,182 --> 00:02:22,022 S1: So I mean, it's the type of thing you hire 37 00:02:22,022 --> 00:02:23,702 S1: somebody and they go and do it and it's going 38 00:02:23,702 --> 00:02:26,182 S1: to be done really, really poorly. If I would have 39 00:02:26,181 --> 00:02:28,742 S1: paid someone to do this, first of all, it would 40 00:02:28,742 --> 00:02:31,942 S1: have cost me thousands of dollars. Second of all, they 41 00:02:31,942 --> 00:02:34,942 S1: would have messed a whole bunch of stuff up. So 42 00:02:34,982 --> 00:02:38,422 S1: it's like I can't even express how useful and powerful 43 00:02:38,422 --> 00:02:40,702 S1: this is. And I'm paying for Max, which is like 44 00:02:40,702 --> 00:02:45,181 S1: 200 bucks a month. But like, if this was $2,000 45 00:02:45,181 --> 00:02:49,142 S1: a month, I have like five times over, made my money. 46 00:02:49,942 --> 00:02:53,462 S1: And that's just from like last weekend, right? I mean, 47 00:02:53,662 --> 00:02:55,901 S1: or like up to up to now, which is like Wednesday. 48 00:02:55,942 --> 00:02:59,502 S1: So I'm telling you, this is like the most excited I've, 49 00:02:59,542 --> 00:03:02,221 S1: I've been about this whole AI thing, and I don't 50 00:03:02,222 --> 00:03:05,302 S1: even see it as I actually like. I'm starting to, like, 51 00:03:05,341 --> 00:03:08,302 S1: just not even care about that. What I'm caring about 52 00:03:08,621 --> 00:03:12,341 S1: is this agent thing and not like AI agents, but 53 00:03:12,382 --> 00:03:16,192 S1: the concept of handing ending work to something that understands 54 00:03:16,192 --> 00:03:19,392 S1: what you're trying to do. Okay, here's another good example. 55 00:03:19,392 --> 00:03:24,231 S1: I have content on the site from so many different 56 00:03:24,712 --> 00:03:28,912 S1: previous platforms, right? Because I've been blogging since 1999, which 57 00:03:28,912 --> 00:03:34,072 S1: means I've got just grossness, just nastiness, like weird embeds 58 00:03:34,072 --> 00:03:37,472 S1: and weird linking strategies like my images were being called 59 00:03:37,472 --> 00:03:41,552 S1: in five different ways. Do they have forward slashes or not? Like, 60 00:03:41,552 --> 00:03:43,552 S1: all of this stuff was a messed up. I went 61 00:03:43,552 --> 00:03:47,192 S1: and told this thing, here's the canonical way to do things. 62 00:03:47,472 --> 00:03:50,392 S1: Here's what a post is supposed to look like, right? 63 00:03:50,432 --> 00:03:52,792 S1: When when I send you a URL. And by the way, 64 00:03:52,792 --> 00:03:55,392 S1: I don't have to give it like specifics. I'm just like, hey, 65 00:03:55,552 --> 00:03:57,472 S1: there's a I have a post called The End of Work. 66 00:03:57,912 --> 00:04:00,232 S1: It's really messed up. Go and fix it. It goes 67 00:04:00,232 --> 00:04:02,432 S1: and checks all the 20 things that I need it 68 00:04:02,432 --> 00:04:05,072 S1: to do for it to be normalized, for it to 69 00:04:05,072 --> 00:04:07,552 S1: be a canonical post, it's like, okay, cool, I did 70 00:04:07,552 --> 00:04:10,272 S1: that and I pushed it. Anything else? Oh, and by 71 00:04:10,272 --> 00:04:13,272 S1: the way, I tested it and it works, I can't 72 00:04:13,272 --> 00:04:18,232 S1: express to you how insane that is. It is completely, 73 00:04:18,752 --> 00:04:24,232 S1: completely spectacular. I mean, this is a type of work. 74 00:04:24,232 --> 00:04:27,192 S1: Like I said, if I hired someone who is super 75 00:04:27,192 --> 00:04:31,952 S1: smart and super awesome, like a super hard core developer, 76 00:04:31,952 --> 00:04:33,752 S1: and I said, I want you to do these 20 77 00:04:33,752 --> 00:04:37,032 S1: things to this post. And by the way, some of 78 00:04:37,032 --> 00:04:42,912 S1: these posts are like a thousand words, 2000 words, 3000 words, 79 00:04:42,912 --> 00:04:46,632 S1: 5000 words. I mean, I've got posts that are 17,000 words, 80 00:04:46,672 --> 00:04:50,912 S1: 9000 words, 10,000 words. We're talking about small books here, okay. 81 00:04:51,752 --> 00:04:53,952 S1: And you hand that to a human and you're like, hey, 82 00:04:53,992 --> 00:04:56,112 S1: go through all this text. And by the way, it's 83 00:04:56,112 --> 00:04:59,551 S1: done differently for every single post, okay? Every single post. 84 00:04:59,592 --> 00:05:02,991 S1: It's broken in different ways. And I tell it a 85 00:05:02,992 --> 00:05:05,632 S1: canonical way to do it. It literally comes back in 86 00:05:05,672 --> 00:05:07,272 S1: 2 or 3 minutes and it's like, yeah, I fixed 87 00:05:07,272 --> 00:05:11,631 S1: all that. And I'm, I'm so I've got cloud code 88 00:05:11,632 --> 00:05:13,352 S1: over here working and then I have cursor. I have 89 00:05:13,351 --> 00:05:15,512 S1: the same project open in cursor. So I can actually 90 00:05:15,512 --> 00:05:17,792 S1: go in and do manual edits. More importantly I can 91 00:05:17,791 --> 00:05:20,832 S1: see what it's actually doing, what what Claude is actually doing. 92 00:05:21,072 --> 00:05:23,431 S1: And sometimes I could use the cursor agent if I want, 93 00:05:23,472 --> 00:05:27,152 S1: but generally I'm using it for transparency. And just like, 94 00:05:27,472 --> 00:05:30,672 S1: you know, manually accepting things if it's crazy or whatever. 95 00:05:30,992 --> 00:05:33,632 S1: Plus I have my vim bindings active inside of cursor, 96 00:05:33,632 --> 00:05:36,472 S1: so I could actually just go right using air quotes 97 00:05:36,512 --> 00:05:40,152 S1: vim inside of cursor and it doesn't feel crazy. I 98 00:05:40,152 --> 00:05:42,671 S1: don't have auto save enabled though, someone can figure that out. 99 00:05:43,112 --> 00:05:46,912 S1: But anyway, it's just been. I've been getting so much done, 100 00:05:46,912 --> 00:05:49,192 S1: so many projects that are just like and I've got 101 00:05:49,592 --> 00:05:53,512 S1: 1520 more that are popping into my mind. Like, I 102 00:05:53,512 --> 00:05:57,072 S1: literally have seven terminals open right now doing cool projects. 103 00:05:57,072 --> 00:05:59,231 S1: I'm about to go do cool stuff, like I'm doing 104 00:05:59,231 --> 00:06:02,592 S1: some physical stuff with some friends. We're going to, um, 105 00:06:03,072 --> 00:06:06,392 S1: celebrate Dustin's life tonight, so I'm really looking forward to that. 106 00:06:06,992 --> 00:06:10,561 S1: And all these other cool things, like I'm doing a 107 00:06:10,562 --> 00:06:13,522 S1: cool project, I'm traveling or doing whatever. Right now I 108 00:06:13,562 --> 00:06:16,882 S1: am thinking, when can I get back to coding? Um, 109 00:06:16,882 --> 00:06:19,282 S1: I've recently been messing around with Diablo for a little bit. 110 00:06:19,322 --> 00:06:21,762 S1: Diablo four is my favorite video game, or Diablo in 111 00:06:21,762 --> 00:06:24,922 S1: general is like probably my favorite video game, and I'm 112 00:06:24,922 --> 00:06:27,002 S1: pretty excited about what's going on in there. I could 113 00:06:27,002 --> 00:06:28,782 S1: go and just, you know, have some fun for two 114 00:06:28,782 --> 00:06:33,522 S1: hours or whatever. It is. Nothing compared to these five 115 00:06:33,562 --> 00:06:36,722 S1: terminal windows that are calling me. I literally play around 116 00:06:36,722 --> 00:06:39,802 S1: with this stuff and build stuff and fix stuff and create. 117 00:06:39,842 --> 00:06:42,122 S1: Net new things. The next one I'm about to do 118 00:06:42,242 --> 00:06:46,282 S1: is substrate. It's going to be insane. But I start 119 00:06:46,322 --> 00:06:48,522 S1: on this. I look up at the clock and I'm like, 120 00:06:48,562 --> 00:06:51,882 S1: oh well, I need to stand up. I need to eat. 121 00:06:51,882 --> 00:06:55,801 S1: I haven't eaten in six hours. Also, it's going to 122 00:06:55,802 --> 00:06:59,202 S1: be breakfast and that's 3 p.m. breakfast or whatever. Like, 123 00:06:59,202 --> 00:07:03,282 S1: I have never been this excited and focused that I 124 00:07:03,282 --> 00:07:06,682 S1: can remember on anything. Now you combine that with the 125 00:07:06,682 --> 00:07:11,252 S1: fact that This thing's getting better, right? Just imagine, Claude 126 00:07:11,252 --> 00:07:13,772 S1: code a bit better. Imagine Claude code. But I can 127 00:07:13,812 --> 00:07:17,172 S1: send it content from my voice, right? I mean, and 128 00:07:17,172 --> 00:07:18,772 S1: this is where this is all going that I've been 129 00:07:18,772 --> 00:07:21,812 S1: talking about forever, right? We already know where it's going. 130 00:07:21,812 --> 00:07:23,292 S1: We already know how this is all going to be 131 00:07:23,292 --> 00:07:26,972 S1: stitched up. And we're messing with the individual pieces here. Um, 132 00:07:26,972 --> 00:07:29,172 S1: one of these projects is called Chi. It's actually my 133 00:07:29,172 --> 00:07:32,532 S1: digital assistant. So that when I'm actually teaching the meta 134 00:07:32,532 --> 00:07:36,812 S1: tools of how to do, you know, skills and tools 135 00:07:36,812 --> 00:07:39,372 S1: and tasks that I'm just going to have to do, 136 00:07:39,732 --> 00:07:42,932 S1: you know, universally going forward. So a good example of 137 00:07:42,932 --> 00:07:48,132 S1: this is, um, I recently taught Chi how to draw 138 00:07:48,172 --> 00:07:53,052 S1: animations using Grant Sanderson's stuff. So he's the guy who does, uh, 139 00:07:53,372 --> 00:07:58,172 S1: three blue, one brown or three brown, one blue. So animations, math, 140 00:07:58,172 --> 00:08:00,812 S1: animations of whatever. Well, now I can send it a 141 00:08:00,812 --> 00:08:02,972 S1: prompt and say animate this. So I sent it a 142 00:08:02,972 --> 00:08:06,772 S1: prompt of the solar system and it drew it. it 143 00:08:06,812 --> 00:08:08,772 S1: drew it and it animated it, and it opened it 144 00:08:08,772 --> 00:08:10,612 S1: up and showed it to me. And I'm like, this 145 00:08:10,612 --> 00:08:13,052 S1: is absolutely insane. I've got another one, which is like 146 00:08:13,052 --> 00:08:15,412 S1: a knowledge map. So I'm going to be able to 147 00:08:15,412 --> 00:08:18,892 S1: take other projects. My blogs are sitting right next to 148 00:08:18,932 --> 00:08:26,172 S1: it in a directory, all markdown files, all normalizing canonicalized now. Right. So, 149 00:08:26,892 --> 00:08:30,412 S1: so they're canonicalized. So they have all tags in them. 150 00:08:30,732 --> 00:08:33,772 S1: They're all marked up. They're all clean. So I could 151 00:08:33,772 --> 00:08:37,092 S1: just be like, hey, pull the pull the knowledge from this. 152 00:08:38,012 --> 00:08:40,692 S1: And you know, map that in this new graphing function 153 00:08:40,732 --> 00:08:45,132 S1: because I've got this graphing knowledge map and I'm teaching 154 00:08:45,172 --> 00:08:47,572 S1: Chi right now how to use this library, how to 155 00:08:47,612 --> 00:08:50,531 S1: use this GitHub project to do this with any knowledge 156 00:08:50,532 --> 00:08:52,771 S1: that I give it. Right. So it's just like these 157 00:08:52,772 --> 00:08:55,972 S1: small universal tools which are getting so good they just 158 00:08:55,972 --> 00:09:00,531 S1: become skills that it has. So collecting data, collecting data 159 00:09:00,532 --> 00:09:06,222 S1: from sources, um, rating the quality of a source. right? 160 00:09:06,462 --> 00:09:09,901 S1: Because when I'm doing like these collections and I'm making 161 00:09:09,902 --> 00:09:12,062 S1: graphs based on them and, you know, if I want 162 00:09:12,102 --> 00:09:13,582 S1: to publish them or whatever, I need to be able 163 00:09:13,582 --> 00:09:16,262 S1: to point and say, look, this came from here, this 164 00:09:16,261 --> 00:09:20,182 S1: came from CDC, this came from so-and-so French agency that 165 00:09:20,182 --> 00:09:22,982 S1: puts out data or whatever. Um, you got to be 166 00:09:22,982 --> 00:09:25,422 S1: able to show your work. Otherwise it's just pretty graphs, right? 167 00:09:25,462 --> 00:09:28,742 S1: So all of that is just becomes core components built 168 00:09:28,742 --> 00:09:35,342 S1: into this thing. All right. So yeah, that very exciting stuff. 169 00:09:35,381 --> 00:09:40,782 S1: The other side of this is I'm basically manic about that, right. 170 00:09:40,822 --> 00:09:44,982 S1: I'm manic about that. And I'm morose about the way 171 00:09:44,982 --> 00:09:48,182 S1: I see this affecting humanity, because the way I see this, 172 00:09:48,182 --> 00:09:50,022 S1: I wrote a post a long time ago, maybe like 173 00:09:50,062 --> 00:09:54,342 S1: 2017 or something called, uh, The Bifurcation or something like that. 174 00:09:54,782 --> 00:09:57,622 S1: And it's like the separation of people. And I don't know, 175 00:09:57,662 --> 00:09:59,942 S1: it was somewhat readers and non-readers. It was talking about 176 00:09:59,942 --> 00:10:04,742 S1: just like how some people just can't get enough And 177 00:10:04,742 --> 00:10:07,102 S1: they're crazy ambitious and they're always trying to learn things 178 00:10:07,102 --> 00:10:10,782 S1: or whatever. And the rest of the masses are just like, yeah, 179 00:10:10,822 --> 00:10:12,742 S1: haven't read a book since high school, and I hated 180 00:10:12,742 --> 00:10:15,502 S1: it then, you know, haven't read a book since college, 181 00:10:15,502 --> 00:10:18,702 S1: and I hated it then. So it's like they've never 182 00:10:18,702 --> 00:10:24,022 S1: really read or studied for fun. And I'm telling you, 183 00:10:24,022 --> 00:10:28,982 S1: people like that are unbelievably screwed, right? If you do 184 00:10:28,982 --> 00:10:31,222 S1: not have learning as, like part of your core DNA 185 00:10:31,222 --> 00:10:35,502 S1: right now, you you are just absolutely screwed. And it's 186 00:10:35,502 --> 00:10:38,182 S1: not like it's 5050. It's not like it's half and 187 00:10:38,182 --> 00:10:41,822 S1: half or like 60% or hardcore learners and 40% aren't. 188 00:10:42,502 --> 00:10:47,542 S1: It's more like 10% or 5% are. Or maybe it's 2%. 189 00:10:47,542 --> 00:10:50,901 S1: Maybe it's 1%. Right. But this is the group, whatever 190 00:10:50,902 --> 00:10:54,622 S1: that small percentage is that sees all these tools, right. 191 00:10:54,662 --> 00:10:57,582 S1: And like I'm in these communities with like, uh, all 192 00:10:57,582 --> 00:10:59,502 S1: my friends are doing this, I'm watching other people do 193 00:10:59,502 --> 00:11:03,592 S1: it on online or whatever. It's like This community is 194 00:11:03,592 --> 00:11:06,272 S1: so excited right now. They're just building stuff all the time, 195 00:11:06,272 --> 00:11:10,432 S1: just like I am. So in one world and I 196 00:11:10,472 --> 00:11:11,992 S1: live in the Bay area, so it's like I'm living 197 00:11:11,992 --> 00:11:14,992 S1: inside this world as well. It's like one world. It's like, 198 00:11:14,992 --> 00:11:17,631 S1: oh my God, can you believe this is possible? And 199 00:11:17,631 --> 00:11:21,152 S1: it's just like constant shock on our faces. And then 200 00:11:21,152 --> 00:11:23,512 S1: there's this other world of like, I. What are you 201 00:11:23,511 --> 00:11:25,992 S1: talking about? Isn't that ChatGPT? Yeah, I use it sometimes. 202 00:11:26,192 --> 00:11:28,552 S1: I don't know, but it hallucinates a lot, so you 203 00:11:28,552 --> 00:11:33,631 S1: can't really trust it. And I'm like, well, that person's screwed. 204 00:11:34,272 --> 00:11:37,631 S1: It's like a completely different universe that we live in, 205 00:11:37,832 --> 00:11:42,712 S1: completely different universe. And what I'm trying to figure out 206 00:11:42,712 --> 00:11:45,672 S1: is like, what can you say? How can we get 207 00:11:45,672 --> 00:11:48,992 S1: more people into that world? How can we convince more 208 00:11:48,992 --> 00:11:53,472 S1: people that this is a critical skill? Right. And it's 209 00:11:53,472 --> 00:11:56,352 S1: hard because if they're already not readers, if they're already 210 00:11:56,352 --> 00:11:58,712 S1: not into the whole learning thing, then like giving them 211 00:11:58,712 --> 00:12:01,392 S1: a better tool for learning is going to be difficult, 212 00:12:01,392 --> 00:12:04,352 S1: but we've got to find a way. I don't want 213 00:12:04,392 --> 00:12:06,872 S1: to just give up on these people and just be like, well, 214 00:12:07,312 --> 00:12:09,392 S1: I guess they're screwed and just kind of move on 215 00:12:09,392 --> 00:12:11,352 S1: and be like, well, it sure is fun to build 216 00:12:11,352 --> 00:12:14,712 S1: with cloud code. That's what makes me morose. So I 217 00:12:14,712 --> 00:12:20,952 S1: basically oscillate between. This is the saddest thing ever because 218 00:12:20,992 --> 00:12:22,832 S1: I look around at all these jobs, all these people 219 00:12:22,832 --> 00:12:25,632 S1: who have jobs, who think AI is ChatGPT and they 220 00:12:25,631 --> 00:12:28,872 S1: use it once a month, you know, for 15 minutes. 221 00:12:28,872 --> 00:12:33,032 S1: And I'm like, the economy is going to crash. This 222 00:12:33,032 --> 00:12:35,992 S1: is what I'm honestly thinking about. This. This economy is 223 00:12:36,312 --> 00:12:42,712 S1: going to have a massive, massive disruption because these folks 224 00:12:42,712 --> 00:12:45,592 S1: here who who don't think of AI in this way, 225 00:12:46,392 --> 00:12:49,152 S1: they're going to get fired. They're just going to get fired. 226 00:12:49,152 --> 00:12:52,152 S1: They're going to get replaced either by a smart person 227 00:12:52,152 --> 00:12:54,312 S1: who could do nine jobs all at once because they 228 00:12:54,312 --> 00:12:58,112 S1: understand AI a little bit, but then eventually just by 229 00:12:58,112 --> 00:13:00,962 S1: AI itself. right? And who knows the timelines and all 230 00:13:00,962 --> 00:13:04,042 S1: that stuff. You. You saw the debate. That could be tomorrow. 231 00:13:04,082 --> 00:13:06,482 S1: It could be in four years from now. Who actually knows? 232 00:13:06,482 --> 00:13:10,242 S1: It actually doesn't matter, right? Don't even care about that. 233 00:13:10,522 --> 00:13:14,322 S1: What matters is, you know, the direction stochastically. You. You 234 00:13:14,362 --> 00:13:18,442 S1: know this for certain, right? And there is another caveat here, 235 00:13:18,442 --> 00:13:22,202 S1: which is legislation. But what could the legislation possibly look like? 236 00:13:22,202 --> 00:13:26,842 S1: They're like, you can't fire your human workers anymore. Well, 237 00:13:26,881 --> 00:13:29,242 S1: that just that just tells like all the workers like 238 00:13:29,242 --> 00:13:30,962 S1: you could do whatever and they can't fire you like 239 00:13:31,002 --> 00:13:33,922 S1: it's some crazy union stuff. And I don't think it'll 240 00:13:33,962 --> 00:13:37,362 S1: be that extreme, although there is some extreme stuff happening 241 00:13:37,362 --> 00:13:40,202 S1: in New York City, so who knows, maybe something like 242 00:13:40,202 --> 00:13:43,082 S1: that will happen. That could definitely slow things down. Uh, 243 00:13:43,082 --> 00:13:46,282 S1: big sort of terrorist events, I think that are like 244 00:13:46,761 --> 00:13:51,041 S1: planned or assisted, planned by AI, that cause major disruption, 245 00:13:51,042 --> 00:13:55,122 S1: that could cause some legislation. But other than that I 246 00:13:55,162 --> 00:14:00,242 S1: just see kind of normal. Non. I would say non 247 00:14:00,242 --> 00:14:03,962 S1: crazy people about AI. People who aren't crazy. Forget AI, 248 00:14:04,202 --> 00:14:07,602 S1: not crazy about learning, not crazy about building, not crazy 249 00:14:07,602 --> 00:14:14,322 S1: about progressing and evolving that mentality because the tech doesn't 250 00:14:14,322 --> 00:14:16,401 S1: really matter, right? We've we've always had people that were 251 00:14:16,402 --> 00:14:18,762 S1: like that and weren't like that. Right? And previously the 252 00:14:18,761 --> 00:14:23,242 S1: tech was like reading and computers. Right. And you know, 253 00:14:23,282 --> 00:14:27,722 S1: tech in that sense. Um, and obviously people who are 254 00:14:27,722 --> 00:14:30,762 S1: fluent with computers and really good readers and, you know, 255 00:14:30,802 --> 00:14:33,842 S1: could write well and all that, they have a massive advantage. 256 00:14:34,042 --> 00:14:37,482 S1: This is just taking that same advantage with a different 257 00:14:37,522 --> 00:14:42,042 S1: tech and magnifying it by a thousand. That's what this 258 00:14:42,042 --> 00:14:46,602 S1: is right now. And it's really hard to watch when 259 00:14:46,602 --> 00:14:50,882 S1: you think about what is likely to happen to most people. Um, 260 00:14:50,882 --> 00:14:53,082 S1: and then I'm like, okay, what am I going to 261 00:14:53,082 --> 00:14:55,442 S1: do to get myself out of this mindset? And I'm like, well, 262 00:14:56,412 --> 00:14:59,372 S1: I've got to help build. I got to help with government. 263 00:14:59,372 --> 00:15:02,492 S1: I've got to help get somebody elected who's actually, uh, 264 00:15:02,492 --> 00:15:06,652 S1: you know, centrist and actually cares about poor people. And, um, 265 00:15:06,652 --> 00:15:09,452 S1: isn't going to break the economy and move us towards communism, um, 266 00:15:09,452 --> 00:15:12,332 S1: or go extreme right or extreme left. Like, how do 267 00:15:12,332 --> 00:15:15,132 S1: how do we do this? All these, all these powers, 268 00:15:15,132 --> 00:15:18,292 S1: all these tools that we have? Can I use something 269 00:15:18,292 --> 00:15:23,852 S1: like substrate to build a platform that is democratic, it's transparent. 270 00:15:23,892 --> 00:15:31,572 S1: It uncovers, um, corruption. It provides, you know, an auditable 271 00:15:31,932 --> 00:15:35,972 S1: government for ourselves where we feel like we're more involved. Um, 272 00:15:36,132 --> 00:15:39,452 S1: how can we bring this technology to be personal tutors 273 00:15:39,452 --> 00:15:42,132 S1: for everyone, for billions of people on the planet, as 274 00:15:42,132 --> 00:15:46,332 S1: opposed to only the, um, you know, the most academically 275 00:15:46,332 --> 00:15:49,532 S1: focused cultures having it? Why can't we give it to everyone? Right. 276 00:15:49,572 --> 00:15:56,052 S1: So I'm thinking about like. Basically, what are projects that 277 00:15:56,052 --> 00:15:59,212 S1: I could do that can maybe help solve some of 278 00:15:59,212 --> 00:16:02,732 S1: this problem for people who are going to be left behind. 279 00:16:02,932 --> 00:16:06,452 S1: And right now that's largely substrate. So I'm working really 280 00:16:06,452 --> 00:16:08,532 S1: hard on that. That's going to be like my main 281 00:16:08,532 --> 00:16:10,612 S1: thing for the next couple of weeks, trying to get 282 00:16:10,612 --> 00:16:12,492 S1: that spun up with a lot more data, a lot 283 00:16:12,492 --> 00:16:16,892 S1: more ideas. Um, maybe a whole site around it. Um, 284 00:16:16,892 --> 00:16:21,252 S1: domain and stuff like that. But the concept here is like, 285 00:16:22,532 --> 00:16:23,932 S1: I don't want to be sad about it. I don't 286 00:16:23,932 --> 00:16:30,612 S1: want to just, you know, have an apathetic attitude toward it. Um, 287 00:16:30,612 --> 00:16:32,372 S1: I definitely am not going to have, like, an elitist 288 00:16:32,372 --> 00:16:34,972 S1: attitude towards it of like, well, we're just special and 289 00:16:34,972 --> 00:16:38,172 S1: they're just not special and that therefore we deserve with 290 00:16:38,172 --> 00:16:40,852 S1: a D word, right? We deserve all these things because 291 00:16:40,852 --> 00:16:42,412 S1: people just don't want to read books and they don't 292 00:16:42,412 --> 00:16:44,812 S1: want to play with AI. That's a shitty attitude to 293 00:16:44,812 --> 00:16:47,732 S1: have too. Um, as is the attitude of like, well, 294 00:16:47,732 --> 00:16:49,612 S1: there's nothing I could do to help them, right? So 295 00:16:49,612 --> 00:16:52,932 S1: it seems like the only third rail there is. Fucking 296 00:16:52,972 --> 00:16:57,462 S1: try to do something. And and before, you know, you 297 00:16:57,502 --> 00:16:59,582 S1: kind of have an excuse. Well, what can you do? 298 00:16:59,622 --> 00:17:02,782 S1: I can't possibly research all that. I can't possibly find 299 00:17:03,062 --> 00:17:05,821 S1: all the different donors who are giving money to these politicians. 300 00:17:05,822 --> 00:17:11,102 S1: I can't possibly build an entire government transparency platform. Well, yeah, 301 00:17:11,582 --> 00:17:14,782 S1: now you can. Now, there's no excuse to not being 302 00:17:14,782 --> 00:17:17,462 S1: part of the solution. So that's the mindset I have 303 00:17:17,462 --> 00:17:20,902 S1: right now. And, uh, anyone who wants to help, please 304 00:17:20,902 --> 00:17:25,941 S1: reach out. I really, um, would love some ideas on this, uh, 305 00:17:25,942 --> 00:17:30,141 S1: ways to take threshold, not threshold, uh, substrate, uh, along 306 00:17:30,142 --> 00:17:36,222 S1: these lines and, uh. Yeah. All right, next one here. Um, 307 00:17:37,102 --> 00:17:40,742 S1: Marcus posted a YouTube video, and he did an intro 308 00:17:40,862 --> 00:17:43,462 S1: of the video, just like I did, where he basically 309 00:17:43,462 --> 00:17:46,022 S1: laid out how he doesn't believe in AI. He, uh, 310 00:17:46,061 --> 00:17:49,422 S1: basically completely opposite views to me, uh, which I thought 311 00:17:49,422 --> 00:17:50,862 S1: was cool. I thought it was a cool intro. And 312 00:17:50,862 --> 00:17:53,502 S1: I got the link there. Project Hail Mary. One of 313 00:17:53,502 --> 00:17:56,702 S1: the coolest books we've read in UL. Book club has 314 00:17:56,702 --> 00:17:59,182 S1: a trailer out and the trailer is out and you 315 00:17:59,182 --> 00:18:00,742 S1: got to go check it out. It looks really good. 316 00:18:00,742 --> 00:18:03,302 S1: It looks like they've they've done it. Well, it felt 317 00:18:03,302 --> 00:18:04,782 S1: like the book when I was looking at the trailer, 318 00:18:04,782 --> 00:18:07,182 S1: so that's a good sign. The big question is what 319 00:18:07,182 --> 00:18:10,902 S1: is um, you know, the the alien going to look like, uh. 320 00:18:10,902 --> 00:18:14,422 S1: So I can't wait to see that, but it looks promising. Network. 321 00:18:14,462 --> 00:18:16,662 S1: Chuck did a whole video on Telos and his process 322 00:18:16,662 --> 00:18:21,622 S1: of trying to go through the, um, the whole Telos exercise, 323 00:18:21,622 --> 00:18:24,422 S1: and it was really good. And it was also the 324 00:18:24,422 --> 00:18:28,062 S1: honesty and the vulnerability that Chuck shared in this was really, 325 00:18:28,061 --> 00:18:33,782 S1: really endearing and really, really, um, I just loved it. And, uh, 326 00:18:33,821 --> 00:18:36,342 S1: hats off to him to, to put himself out there 327 00:18:36,342 --> 00:18:39,901 S1: like that and, uh, continue doing the good stuff that 328 00:18:39,902 --> 00:18:44,462 S1: he's doing. All right. Cybersecurity. US agencies warn Iran that 329 00:18:44,502 --> 00:18:50,302 S1: hackers may target critical infrastructure during Mideast tensions. So Ccsa, FBI, NSA, 330 00:18:50,302 --> 00:18:52,872 S1: say everyone's basically saying that this is likely to happen, 331 00:18:52,872 --> 00:19:00,392 S1: especially around USA slash Israeli operations or companies. DOJ says 332 00:19:00,392 --> 00:19:09,232 S1: that in 2018 Sinaloa, Sinaloa, Sinaloa cartel, um, hacker used 333 00:19:09,272 --> 00:19:13,832 S1: FBI officials phone to track their movements and identify informants. 334 00:19:14,192 --> 00:19:19,552 S1: And those informants were then intimidated and or killed. Uh, Switzerland. 335 00:19:19,552 --> 00:19:22,151 S1: Government data is stolen in a ransomware attack. A whole 336 00:19:22,152 --> 00:19:27,911 S1: bunch of it. 1.3TB of government data now available free. Uh, 337 00:19:27,912 --> 00:19:31,432 S1: Google fixed a fourth Chrome zero day. Uh, persona is 338 00:19:31,432 --> 00:19:34,752 S1: a really cool technology. It's, um, this is actually a company, 339 00:19:34,752 --> 00:19:36,952 S1: so I'm not sure how they made it in here, but, um, 340 00:19:37,632 --> 00:19:41,192 S1: 75 million blocked attempts means there are probably way more 341 00:19:41,232 --> 00:19:45,792 S1: getting through to other systems. And, uh, yeah, they basically 342 00:19:45,792 --> 00:19:49,472 S1: try to counter, uh, I fraudsters. So it's basically a 343 00:19:49,472 --> 00:19:53,392 S1: whole bunch of AI to counter, um, you know, corruptions 344 00:19:53,392 --> 00:19:55,952 S1: and fakes and fraud and stuff like that. So a 345 00:19:55,992 --> 00:19:59,032 S1: really cool, uh, company not involved with them, but would 346 00:19:59,032 --> 00:20:03,032 S1: love to be, uh, Chinese hackers hit Canadian telecom using 347 00:20:03,032 --> 00:20:07,032 S1: 16 month old unpatched Cisco flaw. US House has banned 348 00:20:07,071 --> 00:20:10,712 S1: WhatsApp because they don't like the data handling practices of 349 00:20:10,712 --> 00:20:15,792 S1: meta and AT&T. Finally rolls out SIM swap lock, which, uh, 350 00:20:15,832 --> 00:20:19,472 S1: they've not had in previously. Uh, Verizon and a bunch 351 00:20:19,472 --> 00:20:21,232 S1: of other companies have had it, but, uh, took a 352 00:20:21,272 --> 00:20:25,192 S1: while for AT&T to get it. National security. China's mosquito 353 00:20:25,192 --> 00:20:28,392 S1: sized spy drone. So small you might not not even 354 00:20:28,392 --> 00:20:31,712 S1: notice it flying around your house. And it's got tiny 355 00:20:31,752 --> 00:20:35,712 S1: cameras and microphones. Holy crap. This is where I tell 356 00:20:35,712 --> 00:20:40,952 S1: you to read Kill Decision by Daniel Suarez. As per requirement, 357 00:20:42,392 --> 00:20:45,232 S1: AI cloud code gets hooks, so now you can auto 358 00:20:45,232 --> 00:20:49,561 S1: execute functions from your AI I conversations. Metta creates a 359 00:20:49,561 --> 00:20:52,082 S1: new super intelligence lab and they hired a whole bunch 360 00:20:52,242 --> 00:20:55,841 S1: of OpenAI people. It's kind of funny. It's like Sam 361 00:20:55,882 --> 00:20:59,802 S1: taunted Zuckerberg. And he's like, yeah, they didn't hire any 362 00:20:59,802 --> 00:21:03,442 S1: of our people. And a week later, Zuck is like, oh, really? 363 00:21:03,762 --> 00:21:06,482 S1: And hires like five or something or more of, like, 364 00:21:06,482 --> 00:21:08,842 S1: their best people or really good people anyway. I don't 365 00:21:08,882 --> 00:21:11,562 S1: know how how good they rank, but really good people 366 00:21:11,561 --> 00:21:14,321 S1: spends like billions of dollars, I think literally billions of 367 00:21:14,321 --> 00:21:17,682 S1: dollars on this. And now everyone's like, hey, maybe meta 368 00:21:17,682 --> 00:21:20,561 S1: is the place to work. So yeah, don't, uh, don't 369 00:21:20,602 --> 00:21:24,442 S1: taunt Mark Zuckerberg. That's my lesson. Marc Benioff says that 370 00:21:24,442 --> 00:21:27,882 S1: AI now does half of the work at Salesforce. He's 371 00:21:27,882 --> 00:21:31,361 S1: got some cool stats here, but again, he's selling an 372 00:21:31,362 --> 00:21:34,282 S1: AI product, so I don't know. You got to, uh 373 00:21:34,321 --> 00:21:37,642 S1: you got to weigh that in. Google brings AI search 374 00:21:37,642 --> 00:21:41,282 S1: to YouTube. So they're basically doing a lot of summaries 375 00:21:41,282 --> 00:21:43,202 S1: of videos. And I think this is heading in the 376 00:21:43,202 --> 00:21:47,002 S1: direction I've been talking about where I actually makes the 377 00:21:47,842 --> 00:21:52,082 S1: version of the content for you, right? The actual future 378 00:21:52,082 --> 00:21:54,642 S1: is that your own personal Da will do this for you. 379 00:21:54,762 --> 00:21:59,482 S1: So basically it'll see this YouTube video of whoever pop up. 380 00:21:59,722 --> 00:22:02,682 S1: It'll go read the video, watch the video, whatever it does, 381 00:22:03,242 --> 00:22:06,682 S1: and it knows what you're doing at the time. Okay. 382 00:22:06,722 --> 00:22:08,561 S1: If you're on a bicycle ride, if you're on a hike, 383 00:22:08,561 --> 00:22:11,922 S1: if you're on a whatever, you're driving and it's like 384 00:22:11,922 --> 00:22:13,802 S1: you can't pay attention to the screen or whatever for 385 00:22:13,802 --> 00:22:16,602 S1: whatever reason, or maybe you don't even like to watch video, 386 00:22:16,642 --> 00:22:19,321 S1: it'll give it to you in audio version, but more importantly, 387 00:22:19,321 --> 00:22:22,641 S1: it cut it up. It re-edited it for you in 388 00:22:22,642 --> 00:22:25,122 S1: the way that you like it. Right? So it made 389 00:22:25,122 --> 00:22:28,081 S1: a complete net new video. It might have deepfaked the 390 00:22:28,082 --> 00:22:30,802 S1: actual original creator, but it might have just put your 391 00:22:30,802 --> 00:22:33,082 S1: favorite person on there. Maybe it was Taylor Swift or 392 00:22:33,122 --> 00:22:38,242 S1: Richard Feynman who actually gives you the content. So dynamic 393 00:22:38,762 --> 00:22:42,202 S1: custom content. That's what we're going to see from AI. 394 00:22:42,362 --> 00:22:45,492 S1: And this is just like an intermediary step of that. 395 00:22:45,492 --> 00:22:49,492 S1: It is Google providing the I summary of the content, 396 00:22:49,492 --> 00:22:52,572 S1: which also came from Google. But you see where it's going. 397 00:22:52,852 --> 00:22:55,452 S1: And I think creators need to be very concerned about 398 00:22:55,452 --> 00:22:58,012 S1: this and be thinking about the future, because it could 399 00:22:58,012 --> 00:23:02,772 S1: be that raw content is not really the thing anymore. 400 00:23:02,811 --> 00:23:08,371 S1: Raw content just becomes literally raw material. And here's the 401 00:23:08,372 --> 00:23:15,932 S1: problem can raw content ever compete with someone's personal digital 402 00:23:15,932 --> 00:23:19,611 S1: assistant who knows them better than anybody in the entire universe, 403 00:23:20,012 --> 00:23:23,891 S1: who is also an expert in creating content? Can the 404 00:23:23,892 --> 00:23:28,972 S1: original source make a video better than that? All knowing, 405 00:23:29,132 --> 00:23:33,292 S1: super smart, super creative AI can make for their favorite person? 406 00:23:34,052 --> 00:23:36,611 S1: I think the answer is probably no. Now there are 407 00:23:36,612 --> 00:23:37,972 S1: going to be a whole bunch of exceptions to this, 408 00:23:37,972 --> 00:23:40,252 S1: and it's not going to happen overnight, right? So these 409 00:23:40,252 --> 00:23:45,052 S1: things aren't emergencies. They take time. But so one example 410 00:23:45,052 --> 00:23:48,332 S1: is like, you're a celebrity. Okay. If there's a celebrity, 411 00:23:48,532 --> 00:23:50,172 S1: you like the way they talk. You like the way 412 00:23:50,172 --> 00:23:54,331 S1: they look. You like their jokes. Well, maybe that doesn't 413 00:23:54,332 --> 00:23:58,452 S1: get deepfaked, because maybe the deepfake doesn't copy that perfectly right. 414 00:23:58,492 --> 00:24:01,331 S1: Or maybe it's just human. You just like to watch 415 00:24:01,332 --> 00:24:04,532 S1: humans do their thing, right? We see this in chess, 416 00:24:04,972 --> 00:24:07,852 S1: and chess is more fun and more popular than it's 417 00:24:07,852 --> 00:24:12,012 S1: ever been right now. Because people have real, actual stories, right? Um, 418 00:24:12,972 --> 00:24:19,171 S1: Ganesh like, uh, winning and Ganesh losing and, uh, you know, uh, 419 00:24:19,172 --> 00:24:21,931 S1: Magnus winning and losing. Like, I care about that. I 420 00:24:21,972 --> 00:24:24,372 S1: care about that. I care about the Botez sisters who 421 00:24:24,372 --> 00:24:27,532 S1: are grinding, and I care about, um, the younger one, Andrea, 422 00:24:27,571 --> 00:24:31,492 S1: because she's doing, um, techno on the side, and she's 423 00:24:31,492 --> 00:24:34,932 S1: doing modeling, and she's a chess influencer, and she's hella 424 00:24:34,932 --> 00:24:37,732 S1: smart like her sister. And so they're content creators, but 425 00:24:37,732 --> 00:24:39,892 S1: they're also doing chess, and they love chess and they're, 426 00:24:39,932 --> 00:24:41,942 S1: I don't know, I think they're stuck at around 19 427 00:24:41,942 --> 00:24:46,502 S1: or 2100 somewhere around there. And then you've got Gautham, who? 428 00:24:46,542 --> 00:24:48,942 S1: I really like him. He does the best, like overviews 429 00:24:48,942 --> 00:24:52,302 S1: of chess. Um, he's a really good narrator. And he's 430 00:24:52,342 --> 00:24:57,821 S1: on a mission to get to Grandmaster. Right, I love that. 431 00:24:57,821 --> 00:25:00,182 S1: I love that everyone makes some fun of him because 432 00:25:00,182 --> 00:25:03,382 S1: he's not great. I think he's like, is he like, 2000, 433 00:25:03,382 --> 00:25:07,982 S1: 2200 something or no, 2200 is Grandmaster, I think, or 2400. Anyway, 434 00:25:08,022 --> 00:25:10,742 S1: he's a lot of people think he'll never get there. 435 00:25:10,742 --> 00:25:13,022 S1: But he started having wins, right? I think he had 436 00:25:13,022 --> 00:25:15,982 S1: a win over Magnus, uh, kind of on accident or whatever. 437 00:25:16,782 --> 00:25:19,101 S1: Or he just. He played a really good game, and 438 00:25:19,142 --> 00:25:22,182 S1: Magnus played a bad game, whatever it was. But, um, 439 00:25:22,582 --> 00:25:25,422 S1: that is a human story. Here's a guy who probably 440 00:25:25,422 --> 00:25:28,302 S1: you're not expecting to be a grandmaster, and he might 441 00:25:28,302 --> 00:25:30,302 S1: get there, and he gives you updates on it. So 442 00:25:30,302 --> 00:25:33,462 S1: you're pulling from for him, right? So the question is, 443 00:25:34,542 --> 00:25:37,942 S1: will those sorts of stories, those sorts of human aspects 444 00:25:38,182 --> 00:25:41,061 S1: protect against this? I think it will. There's no question 445 00:25:41,061 --> 00:25:44,902 S1: it will. The question is how much? Versus like an 446 00:25:44,902 --> 00:25:48,302 S1: AI influencer. Maybe it's an AI influencer who's actually giving 447 00:25:48,302 --> 00:25:51,062 S1: your stuff. Maybe that's the avatar for your actual Da. 448 00:25:51,622 --> 00:25:54,262 S1: And he or she is like the most attractive person 449 00:25:54,262 --> 00:25:57,022 S1: in the world, and they could change their outfits or 450 00:25:57,022 --> 00:26:00,502 S1: whatever to put on a school uniform like Richard Feynman, 451 00:26:00,542 --> 00:26:03,702 S1: you know, teaching at university with like the university hat 452 00:26:03,702 --> 00:26:06,022 S1: or whatever, and just be like, yeah, here's how this 453 00:26:06,022 --> 00:26:08,422 S1: physical thing works and, you know, teach you physics or 454 00:26:08,422 --> 00:26:11,782 S1: teach you math or whatever. Um, but the threat to 455 00:26:11,821 --> 00:26:16,582 S1: content creators is like, I'm making all this content. Only 456 00:26:16,622 --> 00:26:20,742 S1: AI is consuming the content people don't. You know, very 457 00:26:20,742 --> 00:26:25,302 S1: few actual humans are consuming my content because there are 458 00:26:25,302 --> 00:26:28,861 S1: millions of other people, hundreds of millions of other people 459 00:26:28,862 --> 00:26:33,702 S1: creating content and billions of other agents creating content. So 460 00:26:33,702 --> 00:26:40,792 S1: it's a giant content creating marketplace. Um, and for regular consumers. 461 00:26:40,952 --> 00:26:43,391 S1: Keep in mind our bandwidth is limited as humans to 462 00:26:43,432 --> 00:26:47,672 S1: consume content, right? So even if we wanted to, we 463 00:26:47,672 --> 00:26:50,072 S1: can't follow all all the cool people that we want to. 464 00:26:50,152 --> 00:26:52,792 S1: I mean, I got friends whose newsletters I don't even read. 465 00:26:52,792 --> 00:26:54,272 S1: I know for a fact a lot of my friends 466 00:26:54,272 --> 00:26:57,152 S1: don't read my newsletter. They're just too busy. Why? Because 467 00:26:57,152 --> 00:27:01,831 S1: they're content creators, right? And I'll read, um, many of 468 00:27:01,872 --> 00:27:04,552 S1: their newsletters, like, once a month. Right. But I'm not 469 00:27:04,552 --> 00:27:06,632 S1: reading it all the time, and they're damn sure not 470 00:27:06,632 --> 00:27:09,232 S1: reading mine all the time. Right? We catch a little 471 00:27:09,232 --> 00:27:11,032 S1: piece from each other and we're like, hey, great, great 472 00:27:11,032 --> 00:27:13,071 S1: job with that. It's like, hey, did you see this one? No, 473 00:27:13,071 --> 00:27:15,432 S1: I didn't see that one. Sorry. Right. We don't even 474 00:27:15,432 --> 00:27:17,631 S1: have the time. We don't have the time. Now imagine 475 00:27:17,632 --> 00:27:20,351 S1: when there's ten times more content, a thousand times more content, 476 00:27:20,352 --> 00:27:23,832 S1: a million times more content. The only thing that's consuming 477 00:27:23,832 --> 00:27:29,272 S1: that content is I working for somebody. And that somebody 478 00:27:29,912 --> 00:27:32,792 S1: in many cases is going to be the digital assistant 479 00:27:32,832 --> 00:27:36,032 S1: of somebody else, right? And then they'll just dynamically create 480 00:27:36,032 --> 00:27:41,512 S1: the content for them. All right. Grammarly acquires superhuman. That 481 00:27:41,512 --> 00:27:45,591 S1: was supposed to be bolded. I hate formatting mistakes. Um, 482 00:27:45,632 --> 00:27:49,152 S1: that was my bad. Um. All right. Anthropic turns Claude 483 00:27:49,152 --> 00:27:51,472 S1: into a no code app. Okay. So basically, anthropic is 484 00:27:51,472 --> 00:27:55,032 S1: now competing directly with, um, like V0 and all the 485 00:27:55,032 --> 00:27:58,631 S1: other app makers. So everyone's everyone's converging on the same space. 486 00:27:58,952 --> 00:28:02,472 S1: My content or my, uh, comment? There was almost no castle. 487 00:28:03,071 --> 00:28:08,992 S1: Where's the moat? No. Where's the castle? Let's see here. Yeah. Technology. 488 00:28:08,992 --> 00:28:12,912 S1: Cloudflare now blocks AI crawlers by default. They are doing 489 00:28:12,912 --> 00:28:16,831 S1: this crazy model. They're going to start charging AI crawlers 490 00:28:17,272 --> 00:28:19,312 S1: to consume content. So this is the type of thing 491 00:28:19,311 --> 00:28:23,552 S1: that could potentially economically disrupt this whole, this whole meta 492 00:28:23,552 --> 00:28:27,752 S1: that I was just talking about. Right. Um, and that's why, 493 00:28:27,912 --> 00:28:29,591 S1: you know, you got to watch yourself with predictions. You 494 00:28:29,592 --> 00:28:31,632 S1: don't know how the economy, you don't know how society 495 00:28:31,632 --> 00:28:34,552 S1: is going to adjust. Um, maybe there becomes this thing 496 00:28:34,552 --> 00:28:38,842 S1: where it's like. maybe we're able to make an economy 497 00:28:39,122 --> 00:28:42,602 S1: where the raw content has value. I find that hard 498 00:28:42,602 --> 00:28:47,802 S1: to believe, but, um, I think it will happen to 499 00:28:47,842 --> 00:28:51,202 S1: some degree. Okay. There will be sectors where where it 500 00:28:51,202 --> 00:28:54,202 S1: does happen or a degree to which it does happen. 501 00:28:54,242 --> 00:28:56,122 S1: Like anything that's a good idea is going to happen 502 00:28:56,122 --> 00:28:57,842 S1: a little bit. The question is what's going to be 503 00:28:57,842 --> 00:29:02,362 S1: the dominant model. I don't unfortunately, you know, and I 504 00:29:02,402 --> 00:29:04,762 S1: create content as well as one of the things that 505 00:29:04,762 --> 00:29:09,562 S1: I do. Um, I don't I don't see a crazy 506 00:29:09,602 --> 00:29:13,082 S1: good future for, you know, billions of people are going 507 00:29:13,122 --> 00:29:15,482 S1: to be watching this YouTube video that I put out. 508 00:29:15,882 --> 00:29:17,282 S1: It's not going to be that. It's going to be 509 00:29:17,322 --> 00:29:20,202 S1: I watching that video I put out. And hopefully here's 510 00:29:20,202 --> 00:29:22,522 S1: the only thing I can hope for. The only thing 511 00:29:22,522 --> 00:29:28,082 S1: I can hope for is the Da. There. Da attributes 512 00:29:28,082 --> 00:29:32,082 S1: it to me and you know, shows a picture of me, 513 00:29:32,082 --> 00:29:33,962 S1: or shows a piece of content that I wrote or 514 00:29:34,002 --> 00:29:36,442 S1: says something cool about it and it's like or says, hey, 515 00:29:36,442 --> 00:29:39,202 S1: this is the seventh thing that I've shown you, you know, 516 00:29:39,242 --> 00:29:42,921 S1: from Clint Gibler this week. Um, you know. Oh, and 517 00:29:42,922 --> 00:29:45,722 S1: also he lives nearby. You should go get a coffee. 518 00:29:46,202 --> 00:29:48,962 S1: That's the type of thing that hopefully is going to happen, right? 519 00:29:49,002 --> 00:29:52,202 S1: You should talk to Clint, because Clint is also talking 520 00:29:52,202 --> 00:29:53,762 S1: about a lot of the same stuff you're talking about. 521 00:29:53,802 --> 00:29:56,962 S1: I'm like, oh, really? And my da, my da, whose 522 00:29:56,962 --> 00:29:59,042 S1: name is Chi, by the way, Chi is like, yeah, actually, 523 00:29:59,042 --> 00:30:00,402 S1: a lot of the stuff I've been showing you, like 524 00:30:00,442 --> 00:30:02,242 S1: a lot of those videos that I made for you, 525 00:30:02,442 --> 00:30:06,322 S1: those actually came from Clint's videos. And I'm like, okay, well, 526 00:30:06,322 --> 00:30:09,162 S1: in the future, you know, put like a Clint, you know, 527 00:30:09,202 --> 00:30:12,282 S1: watermark on it or something. And Chi is like, okay. Yeah, sure. 528 00:30:12,282 --> 00:30:14,162 S1: My bad. Yeah, I'll make sure I do that. So 529 00:30:14,162 --> 00:30:19,562 S1: hopefully there's something like that dynamic that happens. All right. Uh, 530 00:30:19,562 --> 00:30:24,082 S1: meta adds another gigawatt of renewable power to feed its 531 00:30:24,082 --> 00:30:30,002 S1: data centers. So it's buying. Um, okay. Solar. Wind. Geothermal. 532 00:30:30,442 --> 00:30:33,412 S1: I thought I also had in here. Your. Yeah, they're 533 00:30:33,412 --> 00:30:38,212 S1: also doing nuclear stuff as well. They're buying nuclear stuff. Um, 534 00:30:38,212 --> 00:30:41,532 S1: maybe that was a previous story. Um, all right. Humans, 535 00:30:41,532 --> 00:30:45,532 S1: scientists finally pinpoint what wiped out America's bees, and it 536 00:30:45,532 --> 00:30:49,292 S1: wasn't pesticides. I'm going to leave that as a mystery 537 00:30:49,292 --> 00:30:53,532 S1: for you to go. Click noise ruins sleep quality even 538 00:30:53,532 --> 00:30:57,692 S1: when you think you're sleeping through it. I've recently moved 539 00:30:57,692 --> 00:31:04,372 S1: to full earbuds. Um, not Apple ones like actual, um, in-ear, 540 00:31:04,932 --> 00:31:08,892 S1: you know, non-electronic earbuds. And I got a new sleep mask. Oh, 541 00:31:08,932 --> 00:31:11,332 S1: I'm about to do a wirecutter episode for for members, 542 00:31:11,332 --> 00:31:13,492 S1: by the way. So it's going to be like, because 543 00:31:13,532 --> 00:31:15,692 S1: I'm super crazy when it comes to all this, uh, 544 00:31:15,772 --> 00:31:18,572 S1: like the best pens, the best shoes, the best, you know, 545 00:31:18,732 --> 00:31:20,691 S1: covers for your pillows or whatever. So I'm about to 546 00:31:20,692 --> 00:31:23,012 S1: do that. Um, I don't know, I should call it 547 00:31:23,092 --> 00:31:26,452 S1: Wirecutter probably get sued, though. Maybe I'll call it something else. 548 00:31:26,492 --> 00:31:33,492 S1: UL Wirecutter I don't know. Um, anyway, I mask massively 549 00:31:33,492 --> 00:31:36,692 S1: upgraded my eye mask, so it's better than the ms1 550 00:31:36,692 --> 00:31:39,972 S1: that I've been using and it's just fantastic. Um. Highly 551 00:31:39,972 --> 00:31:43,931 S1: recommend eye mask and earplugs. I do have to have 552 00:31:43,972 --> 00:31:46,812 S1: very strong locks on the doors, because I don't like 553 00:31:46,812 --> 00:31:49,572 S1: the idea of of not being able to hear people 554 00:31:49,572 --> 00:31:53,692 S1: sneak up on me. That's the army for you. Luckin 555 00:31:53,692 --> 00:31:57,412 S1: coffee opens up first US stores after beating Starbucks in China. 556 00:31:57,412 --> 00:32:00,212 S1: They just opened up the first two US locations and 557 00:32:00,212 --> 00:32:03,692 S1: they're in New York City. This is basically the BYD 558 00:32:03,732 --> 00:32:06,772 S1: of coffee. Um, so naturally, I want to go there, 559 00:32:06,772 --> 00:32:08,732 S1: and I wanted to check it out. I want to 560 00:32:08,732 --> 00:32:10,972 S1: sit in the chairs. I want to look at people there. 561 00:32:11,132 --> 00:32:12,972 S1: I want to just see the vibe. I want to, 562 00:32:13,012 --> 00:32:16,132 S1: you know, knock my knuckles on the table and the 563 00:32:16,132 --> 00:32:18,332 S1: chairs and just, like, see what they're doing different. I 564 00:32:18,332 --> 00:32:21,052 S1: want to see, like, how their employees interact with people. 565 00:32:21,492 --> 00:32:25,132 S1: I'm like, fascinated by this whole concept of like, when 566 00:32:25,132 --> 00:32:28,332 S1: one chain wins out over another, what did they do better? 567 00:32:28,372 --> 00:32:33,262 S1: You know, in and out, Chick fil A. Stuff like that. Uh, 568 00:32:33,382 --> 00:32:36,822 S1: staff at the Louvre shut down the museum to protest 569 00:32:36,822 --> 00:32:41,102 S1: unmanageable tourist crowds. Uh, I've been once, and it was 570 00:32:41,102 --> 00:32:44,782 S1: a hellscape. It was an absolute hellscape of people who 571 00:32:44,782 --> 00:32:48,262 S1: cared nothing about art whatsoever. They were crammed in like 572 00:32:48,582 --> 00:32:55,502 S1: insects and nothing but iPhones everywhere. And it was, I 573 00:32:55,502 --> 00:32:57,742 S1: don't know, it was kind of the opposite of art. 574 00:32:57,742 --> 00:33:01,102 S1: It was the worst art experience I've ever had was 575 00:33:01,102 --> 00:33:05,142 S1: at the Louvre. That's what I'll say about that. The 576 00:33:05,142 --> 00:33:09,862 S1: dollar just had its worst first half since 1973, and 577 00:33:09,862 --> 00:33:11,862 S1: stocks are doing better than ever. But the dollar is 578 00:33:11,862 --> 00:33:16,742 S1: falling and Trump threatens to investigate Musk's companies through Doge. 579 00:33:16,862 --> 00:33:20,262 S1: He also. I didn't see the actual, um, quote. So 580 00:33:20,262 --> 00:33:23,742 S1: I don't know, like what level of grumpiness it was. But, uh, 581 00:33:23,902 --> 00:33:29,382 S1: he also somehow alluded to deporting Ellen. And the whole 582 00:33:29,382 --> 00:33:32,302 S1: reason for this is because Ellen is now proposing a 583 00:33:32,302 --> 00:33:36,342 S1: third political party, because he is so morally upset with 584 00:33:36,342 --> 00:33:40,502 S1: the waste and the budget. Um, I actually had a debate. 585 00:33:40,542 --> 00:33:45,982 S1: A public debate, uh, on LinkedIn with Marcus. Uh, we 586 00:33:45,982 --> 00:33:48,382 S1: made two bets, and I believe I have now won 587 00:33:48,382 --> 00:33:53,022 S1: both bets. Uh, so the first bet that we made was, um, 588 00:33:54,182 --> 00:33:57,142 S1: he thought Tesla's stock was going to drop below, like, 589 00:33:57,182 --> 00:34:00,902 S1: $300 or $200. I forgot what the number was by 590 00:34:00,902 --> 00:34:04,142 S1: a certain date, and, um, or it would not get 591 00:34:04,142 --> 00:34:06,222 S1: above a certain amount. I forget what it was. Well, 592 00:34:06,222 --> 00:34:08,702 S1: it immediately went to like 400 something and it's now 593 00:34:09,102 --> 00:34:12,062 S1: very high. It's like 300 something, I don't know. Um, 594 00:34:12,342 --> 00:34:14,262 S1: but I think I already won that one. And then 595 00:34:14,262 --> 00:34:18,062 S1: what I told him is that, uh, Musk would break 596 00:34:18,062 --> 00:34:22,142 S1: from Trump because of some moral issue, because of some 597 00:34:22,142 --> 00:34:27,112 S1: principle issue. And that happened, uh, that happened. And the 598 00:34:27,112 --> 00:34:30,512 S1: issue wasn't like, you know, child labor or something. It 599 00:34:30,512 --> 00:34:35,752 S1: was balancing the budget and reducing the debt. And it 600 00:34:35,752 --> 00:34:38,712 S1: turns out all that stuff that Ellen was saying about 601 00:34:38,752 --> 00:34:44,872 S1: Doge saving money. Ellen was not joking. He was serious. 602 00:34:44,872 --> 00:34:47,392 S1: He thought he was actually doing good. So he goes 603 00:34:47,392 --> 00:34:50,152 S1: over there and does all this stuff. And by the way, 604 00:34:50,152 --> 00:34:54,232 S1: a lot of it was really, really bad. Really bad. Um, 605 00:34:54,352 --> 00:34:56,512 S1: I forget the name of the one organization that just 606 00:34:56,512 --> 00:34:58,832 S1: should not have been messed with the way that it was. 607 00:34:58,952 --> 00:35:01,472 S1: And like hundreds of thousands of people have died because 608 00:35:01,472 --> 00:35:04,232 S1: of it. It's or are going to because of it. 609 00:35:04,232 --> 00:35:07,912 S1: And it's like not all good is what I'm saying there. 610 00:35:07,912 --> 00:35:12,472 S1: But the point is he thought he was doing good, um, 611 00:35:13,032 --> 00:35:15,632 S1: and was actually trying. It was not like some charade 612 00:35:15,632 --> 00:35:20,352 S1: or whatever. So he leaves Doge kind of gets kicked 613 00:35:20,352 --> 00:35:23,672 S1: out of the whole establishment, and then they're like, hey, 614 00:35:23,712 --> 00:35:28,032 S1: big beautiful Bill, let's raise the debt by trillions of dollars. 615 00:35:28,352 --> 00:35:34,792 S1: Let's not cut anything. Basically, multiples of like damage. Way 616 00:35:34,792 --> 00:35:38,352 S1: more than any possible good that Doge has done. And 617 00:35:38,352 --> 00:35:42,472 S1: so Elon is absolutely freaking out. That's why he called 618 00:35:42,472 --> 00:35:45,392 S1: him a pedophile in front of hundreds of millions of people. 619 00:35:45,392 --> 00:35:47,152 S1: And it's now why he says he's going to raise 620 00:35:47,152 --> 00:35:51,192 S1: a completely different party called the American Party. So all 621 00:35:51,192 --> 00:35:56,872 S1: that to say is, um, I think, um, I think 622 00:35:56,872 --> 00:36:00,872 S1: I won both of those, um, ideas. Stanford professor made 623 00:36:00,872 --> 00:36:05,592 S1: up that famous chess grandmasters burn 6000 calories. Claim. So 624 00:36:05,592 --> 00:36:09,512 S1: the reason I put this in ideas is because I 625 00:36:09,552 --> 00:36:15,472 S1: find it very interesting that. I learned stuff in the 626 00:36:15,472 --> 00:36:18,312 S1: 80s and the 90s and the 2000 and the tens. 627 00:36:18,712 --> 00:36:21,072 S1: We're still in the 20s. So all those decades I 628 00:36:21,112 --> 00:36:24,522 S1: learned things. How many of those things were just straight false. 629 00:36:24,522 --> 00:36:30,682 S1: For example, the marshmallow test. How much fundamental? How much 630 00:36:30,682 --> 00:36:33,962 S1: did the belief that that was real lead to mental 631 00:36:33,962 --> 00:36:37,682 S1: models in my brain that are now broken? Um, it's 632 00:36:37,682 --> 00:36:40,802 S1: possible that that particular case didn't actually have those, but 633 00:36:40,842 --> 00:36:43,922 S1: what other things do I still believe are true because 634 00:36:43,922 --> 00:36:46,642 S1: of some crap study that came out that turns out 635 00:36:46,642 --> 00:36:53,242 S1: is not replicable. Replicable? I think the answer is probably large. 636 00:36:53,242 --> 00:36:55,522 S1: Hopefully from all my reading and stuff like that, it's 637 00:36:55,562 --> 00:36:57,202 S1: like cleaned up some of it or most of it, 638 00:36:57,202 --> 00:36:59,722 S1: or maybe it's all gone. Who knows? But I guarantee you, 639 00:36:59,722 --> 00:37:02,882 S1: I've still got some dumb beliefs that some teacher told 640 00:37:02,882 --> 00:37:06,522 S1: me or my parents told me in the 80s. You know, 641 00:37:06,762 --> 00:37:09,762 S1: the food groups, I mean, stuff like that, right? There's 642 00:37:09,762 --> 00:37:12,082 S1: just got to be a million of these things. And, like, 643 00:37:12,082 --> 00:37:14,082 S1: I just hate the idea that, like, the foundation of 644 00:37:14,082 --> 00:37:18,522 S1: the house is, like, got, like, termites or something, or like, 645 00:37:18,802 --> 00:37:22,042 S1: I don't know, nanobots eating, uh, eating away the, uh. 646 00:37:23,522 --> 00:37:27,402 S1: the the undergirding. Uh, I don't like it. And it's 647 00:37:27,442 --> 00:37:31,362 S1: worth a question of, like, for all of us, you know, 648 00:37:31,402 --> 00:37:34,962 S1: where is that? Where is that rot? Taste is the 649 00:37:34,962 --> 00:37:37,402 S1: new intelligence. This one should have had a fire mark 650 00:37:37,402 --> 00:37:39,762 S1: next to it. This thing is so good. It's all 651 00:37:39,762 --> 00:37:42,202 S1: about Rick Rubin talking about his book. Uh, but it's 652 00:37:42,202 --> 00:37:45,522 S1: a really good full length, uh, essay. Uh, go check 653 00:37:45,522 --> 00:37:49,482 S1: it out. Joan Westenberg deleted her entire second brain. Love 654 00:37:49,482 --> 00:37:52,602 S1: the idea here where basically. So she had like, this 655 00:37:52,602 --> 00:37:57,762 S1: super elaborate, awesome second brain in obsidian. And she basically decided, 656 00:37:57,802 --> 00:38:02,762 S1: you know what? Nah. Nope. Um, I'm spending too much 657 00:38:02,762 --> 00:38:06,362 S1: time optimizing this thing. It's taken away the focus of, like, 658 00:38:06,402 --> 00:38:09,202 S1: actually being good in my own brain and has put 659 00:38:09,202 --> 00:38:11,442 S1: all my effort at being good in the second brain. 660 00:38:12,122 --> 00:38:15,522 S1: So the movement is basically first brain, and she just 661 00:38:15,522 --> 00:38:19,042 S1: trashed the entire thing. I think it's a really interesting 662 00:38:19,082 --> 00:38:22,692 S1: thing to like, not overoptimize. AI is a good example. 663 00:38:22,732 --> 00:38:27,612 S1: Don't overoptimize on AI. It's really anything. Exercise, you know work. 664 00:38:27,652 --> 00:38:30,132 S1: Don't work too much because in your personal relationships it's 665 00:38:30,132 --> 00:38:32,252 S1: like anything that's a good thing can be a bad 666 00:38:32,252 --> 00:38:34,212 S1: thing if done too much. It's like the most cliche 667 00:38:34,292 --> 00:38:38,852 S1: thing in the world and absolutely worth repeating or remembering. 668 00:38:39,812 --> 00:38:44,012 S1: Schizophrenia may be the evolutionary price. I love articles like 669 00:38:44,012 --> 00:38:45,652 S1: this that are like, hey, you know that thing you 670 00:38:45,652 --> 00:38:49,252 S1: think is bad? That could be a necessary piece of 671 00:38:49,252 --> 00:38:52,452 S1: exhaust that comes after a thing that you think is good. 672 00:38:52,452 --> 00:38:58,452 S1: In this case, they're saying ingenuity, creativity, new ideas. You know, 673 00:38:58,612 --> 00:39:02,932 S1: Einstein type stuff where, oh, maybe it's just space is curved. 674 00:39:02,972 --> 00:39:09,452 S1: You know, maybe that requires that something like schizophrenia exists. 675 00:39:11,532 --> 00:39:16,292 S1: Discovery how to use markdown. Been book uses AI to 676 00:39:16,492 --> 00:39:22,932 S1: turn coffee bag photos into detailed brew logs. Mhm. Proxy 677 00:39:22,932 --> 00:39:27,252 S1: cloud code requests through Cloudflare. Aging related inflammation isn't universal. 678 00:39:27,292 --> 00:39:29,892 S1: The developer built an AI dungeon master that runs in 679 00:39:29,932 --> 00:39:33,452 S1: the terminal. This thing is really cool. Um. James Webb 680 00:39:33,492 --> 00:39:37,932 S1: takes first directional exoplanet photo. Local LM notepad on a 681 00:39:37,972 --> 00:39:41,132 S1: USB stick. This thing is so cool. Uh, Joseph and 682 00:39:41,132 --> 00:39:43,892 S1: I have been talking about this. Joseph mentioned it to 683 00:39:43,932 --> 00:39:46,612 S1: me first. He's like, hey, you know, how do we have, like, 684 00:39:46,652 --> 00:39:49,612 S1: a local thing of knowledge? You know, worse came to worst. 685 00:39:50,452 --> 00:39:52,012 S1: I want to be able to ask this thing, you know, 686 00:39:52,012 --> 00:39:54,572 S1: how to restart society or something. Like, what's a small 687 00:39:54,572 --> 00:39:56,452 S1: version we could do? Well, here's one. It's on the 688 00:39:56,452 --> 00:40:04,052 S1: USB stick and custom voice agent tutorial. And the recommendation 689 00:40:04,052 --> 00:40:06,572 S1: of the week. Go play with cloud code, but don't 690 00:40:06,572 --> 00:40:08,972 S1: think of it as vibe coding, or even don't even 691 00:40:08,972 --> 00:40:11,452 S1: think about it as coding at all. Instead, make a 692 00:40:11,452 --> 00:40:13,812 S1: list of all the different research or study or technical 693 00:40:13,812 --> 00:40:16,252 S1: or whatever types of projects you plan on doing, and 694 00:40:16,252 --> 00:40:18,022 S1: have it help you do those. So here are here's 695 00:40:18,022 --> 00:40:21,302 S1: some ideas. Fixing file names on thousands of files, organizing 696 00:40:21,302 --> 00:40:25,902 S1: a file structure. Renaming photos. Fixing broken links on a website. 697 00:40:26,022 --> 00:40:30,022 S1: Keep in mind you can actually rename photos based on 698 00:40:30,022 --> 00:40:32,422 S1: what's in the photo, right? And you could do this 699 00:40:32,422 --> 00:40:33,902 S1: with open source. You don't even have to use the 700 00:40:33,902 --> 00:40:37,742 S1: cloud for this. So you could just like reorganize photos 701 00:40:38,422 --> 00:40:40,982 S1: into a file structure based on the content of the photos. 702 00:40:41,022 --> 00:40:44,062 S1: Like you could do anything with this thing. Fix broken 703 00:40:44,062 --> 00:40:46,502 S1: links on a website, build a flashcard system for learning 704 00:40:46,502 --> 00:40:50,102 S1: a new language or whatever like the list goes on. Basically, 705 00:40:50,102 --> 00:40:52,062 S1: if it involves a computer, you could probably help you 706 00:40:52,062 --> 00:40:54,422 S1: do it and think of all the giant projects that 707 00:40:54,422 --> 00:40:56,742 S1: would have taken you like 100 people or like a 708 00:40:56,742 --> 00:40:59,422 S1: company to do it properly, and you might now be 709 00:40:59,462 --> 00:41:02,542 S1: able to do them just by yourself. And the aphorism 710 00:41:02,542 --> 00:41:05,542 S1: of the week. It is amazing how complete is the 711 00:41:05,542 --> 00:41:09,502 S1: delusion that beauty is goodness. It is amazing how complete 712 00:41:09,502 --> 00:41:14,062 S1: is the delusion that beauty is goodness. Leo Tolstoy.