WEBVTT - UL NO. 422: To Survive AI, We Must Become Creators 0:00:22.363 --> 0:00:25.633 Welcome to Unsupervised Learning, a security, AI and meaning focused 0:00:25.633 --> 0:00:28.513 podcast that looks at how best to thrive as humans 0:00:28.513 --> 0:00:32.743 in a post AI world. It combines original ideas, analysis, 0:00:32.743 --> 0:00:35.953 and mental models to bring not just the news, but 0:00:35.953 --> 0:00:43.073 why it matters and how to respond. All right. Welcome 0:00:43.073 --> 0:00:45.983 to unsupervised learning. This is Daniel Missler. So we added 0:00:45.983 --> 0:00:48.503 a ton of new patterns to fabric. This week. We 0:00:48.503 --> 0:00:51.653 added crate threat model which basically you pipe in the 0:00:51.653 --> 0:00:54.593 kind of situation that you're worried about in it outputs 0:00:54.593 --> 0:00:57.893 you like a logical threat model. Based on an essay 0:00:57.893 --> 0:01:00.353 that I did a while back. Find a hidden message. 0:01:00.353 --> 0:01:03.173 This thing is so cool. You basically send in any 0:01:03.173 --> 0:01:06.263 essay or article or whatever. You're not sure if you're 0:01:06.263 --> 0:01:08.513 being lied to, if or if the person is being 0:01:08.513 --> 0:01:12.203 disingenuous or whatever, and it'll actually tell you what they 0:01:12.203 --> 0:01:15.323 claim to be trying to say versus what they actually 0:01:15.323 --> 0:01:18.773 are saying. So that's a really cool piece of functionality. 0:01:19.403 --> 0:01:21.203 And I put a bunch of stuff through it. It's 0:01:21.203 --> 0:01:24.143 it's pretty accurate and have it even like fully tweaked 0:01:24.143 --> 0:01:28.223 it yet create Ascii visualization. So this thing will actually 0:01:28.223 --> 0:01:32.813 create a visualization, a very rudimentary Ascii visualization of basically 0:01:32.813 --> 0:01:35.513 any concept. So you can send in like the meaning 0:01:35.513 --> 0:01:39.413 of life or the Dunning-Kruger effect or really sort of 0:01:39.413 --> 0:01:43.283 conceptual things, and it'll just draw a picture for you. 0:01:43.283 --> 0:01:46.013 So you can like explain something to a kid or something. 0:01:46.013 --> 0:01:48.023 So I thought that was pretty cool. You could do 0:01:48.023 --> 0:01:51.053 the same thing with Mark map, which I didn't know 0:01:51.053 --> 0:01:54.263 it was. It's basically like a markdown version of a 0:01:54.263 --> 0:01:57.233 mind map. So you do the same thing. You take 0:01:57.233 --> 0:01:59.363 any concept, you send it into this and it builds 0:01:59.363 --> 0:02:01.823 you a mind map of those things and actually has 0:02:01.823 --> 0:02:05.273 links and everything, and you can actually expand and contract 0:02:05.273 --> 0:02:09.743 the mind map. It's really cool. And same for mermaid visualization. 0:02:09.743 --> 0:02:14.423 This is a JavaScript based, also markdown, but JavaScript. And 0:02:14.423 --> 0:02:16.553 you put it into one of the renderers and you 0:02:16.553 --> 0:02:20.063 could basically see a mind map or a visualization of 0:02:20.063 --> 0:02:22.943 the thing. It's more rich though, than some of the 0:02:22.943 --> 0:02:25.703 other ones, so that was really cool. We also added 0:02:25.703 --> 0:02:31.913 early crew eye integration. So many, many thanks to Jonathan Dunn, 0:02:31.913 --> 0:02:34.673 because he's been working on so many of these pieces 0:02:34.673 --> 0:02:37.913 of client functionality, and we now have our first one working. 0:02:37.913 --> 0:02:42.503 It's like you run fabric agents, trip planner, trip underscore, planner, 0:02:42.503 --> 0:02:46.013 and it will actually run a trip planner for you. 0:02:46.013 --> 0:02:48.113 It'll ask you questions, where are you going? What do 0:02:48.113 --> 0:02:50.213 you want to do while you're there? And it spins 0:02:50.213 --> 0:02:52.523 up a team of agents and actually does that for you. 0:02:52.523 --> 0:02:56.453 So that's now integrated and brand new. Just this morning. 0:02:56.453 --> 0:03:01.433 It's not even in the newsletter yet is local model support. 0:03:01.433 --> 0:03:05.333 So you can now run local model. You actually do 0:03:05.363 --> 0:03:08.843 capital L and then if you do like llama too 0:03:08.843 --> 0:03:11.813 it'll run. You have to install a llama and get 0:03:11.813 --> 0:03:14.573 it running. But that's like one command. And once it's 0:03:14.573 --> 0:03:17.903 done and you have the model actually downloaded, it'll give 0:03:17.903 --> 0:03:19.853 you the result from a local one. So you're not 0:03:19.853 --> 0:03:23.333 even being charged any tokens. And this thing totally works. 0:03:23.333 --> 0:03:26.243 Just got that running in. The documentation is going as well. 0:03:26.243 --> 0:03:29.393 So thanks again to Jonathan Dunn for that work. And 0:03:29.393 --> 0:03:31.943 you want to just yeah, you want to rerun setup 0:03:31.943 --> 0:03:34.703 and restart your shell and then it'll work. All right. 0:03:34.703 --> 0:03:38.183 So my work this week wrote this essay called To 0:03:38.183 --> 0:03:42.173 Survive I we must become creators. Highly recommend this one. 0:03:42.173 --> 0:03:45.233 Especially for anyone who is in school or has a 0:03:45.233 --> 0:03:47.783 loved one in school. It was kind of spawned by 0:03:47.783 --> 0:03:50.843 a post that I saw from somebody on Hacker News. 0:03:50.843 --> 0:03:53.633 In fact, I'm just going to click into this thing. Yeah, 0:03:53.633 --> 0:03:57.293 this post from Hacker News click into that as well. Yeah. 0:03:57.293 --> 0:03:59.603 So they're basically saying I'm about to finish my CSS 0:03:59.603 --> 0:04:02.423 degree in May, and I'm already sick of the tech industry. 0:04:02.423 --> 0:04:04.673 I'm at a loss. I know the job market could 0:04:04.673 --> 0:04:07.823 get better soon, but there's no guarantee that it will. 0:04:07.823 --> 0:04:11.213 And things are looking bad for us with less experience. 0:04:11.213 --> 0:04:15.083 And basically just it's kind of sad. It's kind of 0:04:15.083 --> 0:04:17.723 a real situation that's going on. So I wanted to 0:04:17.723 --> 0:04:20.693 address that, and I think this is the way that 0:04:20.693 --> 0:04:22.973 people should be thinking about it. In my opinion, this 0:04:22.973 --> 0:04:27.713 is just my opinion. But I think that coders and 0:04:27.713 --> 0:04:30.053 lots of people like that are simply not going to 0:04:30.053 --> 0:04:35.063 have jobs, right? And some things will go faster than others. 0:04:35.063 --> 0:04:38.123 But do a quick little walkthrough through here. You want 0:04:38.123 --> 0:04:41.243 to read the whole thing, but basically what is a 0:04:41.243 --> 0:04:45.653 creator versus a worker? So on one hand it's pretty simple, right? 0:04:45.653 --> 0:04:49.013 So its creators come up with new solutions to human problems. 0:04:49.013 --> 0:04:52.013 Workers are the people who execute on building them and 0:04:52.013 --> 0:04:55.043 building those solutions. And then like a corporate setting, it 0:04:55.043 --> 0:04:58.103 would be like creators are the people who determine what 0:04:58.103 --> 0:05:00.293 to build, how to build it, if it's a new thing, 0:05:00.293 --> 0:05:02.093 and then how to sell it in the current market. 0:05:02.093 --> 0:05:05.693 And workers are the people who make that happen. Right now, 0:05:05.693 --> 0:05:08.423 there are situations like we talk about this draw the 0:05:08.423 --> 0:05:11.783 rest of the owl. There are some situations where it's 0:05:11.783 --> 0:05:14.573 not quite clear. If it's if you're doing a creator 0:05:14.573 --> 0:05:18.803 job or an execution job, right? Because if you're making 0:05:18.803 --> 0:05:22.253 something that's never been built, technically you're executing, but you're 0:05:22.253 --> 0:05:25.823 making something that's brand new, you're kind of creating, especially 0:05:25.823 --> 0:05:27.353 if you're doing that and you have your own company, 0:05:27.353 --> 0:05:30.773 you're definitely creating. But the vice versa is also true. 0:05:30.773 --> 0:05:33.383 So it's like if you used to be a creator, 0:05:33.383 --> 0:05:35.903 but now you're creating things that kind of are kind 0:05:35.903 --> 0:05:38.363 of a commodity at this point. Well, now you're more 0:05:38.363 --> 0:05:40.883 of an executor than a creator. So it goes both ways. 0:05:41.183 --> 0:05:43.313 And here's the way to look at it. Basically, I 0:05:43.313 --> 0:05:45.833 say as the amount of creation goes up, the amount 0:05:45.833 --> 0:05:49.433 of execution will balloon massively, but it's going to be 0:05:49.433 --> 0:05:52.703 AI that are actually filling those jobs, right? It's not 0:05:52.703 --> 0:05:55.703 going to be humans that are doing all that execution. 0:05:55.703 --> 0:05:58.523 Once AI comes online is good enough to do a 0:05:58.523 --> 0:06:00.653 lot of this stuff, which I don't think is going 0:06:00.653 --> 0:06:04.823 to be long. Humans are basically hard to train and retrain, 0:06:04.823 --> 0:06:09.953 and human competence is fixed, right? Our IQs are not 0:06:09.953 --> 0:06:11.753 going to go up that fast. I mean, we might 0:06:11.753 --> 0:06:15.413 get some improvement on our IQs from, you know, some 0:06:15.413 --> 0:06:18.983 AI or some enhancements or nutrition. There's lots of different 0:06:18.983 --> 0:06:22.493 things can improve our our IQs as humans, but it's 0:06:22.493 --> 0:06:25.043 not going to go up nearly as fast as AI is. 0:06:25.043 --> 0:06:29.543 And ultimately humans are expensive, sensitive, and need constant replacement. 0:06:29.543 --> 0:06:31.973 And I won't have these problems, right? It's going to 0:06:31.973 --> 0:06:34.433 scale with creation. We can make as many AIS as 0:06:34.433 --> 0:06:37.283 we need to do a particular job. When you upgrade 0:06:37.283 --> 0:06:39.953 an AI, it's pretty easy to roll it out, right? 0:06:39.953 --> 0:06:43.253 And they aren't conscious, they don't get tired, they don't complain, 0:06:43.253 --> 0:06:46.103 they don't go to HR, you know, to start investigation 0:06:46.103 --> 0:06:49.433 and they don't quit. And they're getting smarter at an 0:06:49.433 --> 0:06:53.273 insane rate. So what do you tangibly do? Right. You know, 0:06:53.273 --> 0:06:55.763 what fields do you go into? How do I steer 0:06:55.763 --> 0:06:59.363 my kids towards something or away from something? And should 0:06:59.363 --> 0:07:01.853 I still go to college? So my advice is to 0:07:01.853 --> 0:07:05.873 focus on creation, on ideas, on making new things, focus 0:07:05.873 --> 0:07:07.733 on problems that exist in the world that need to 0:07:07.733 --> 0:07:10.013 be solved, and start thinking about what you could do 0:07:10.013 --> 0:07:14.093 to solve those problems, what you can build that solves 0:07:14.093 --> 0:07:18.803 those problems, right? And basically creating new things to solve 0:07:18.803 --> 0:07:22.523 human problems is like the immortal job skill. It's the 0:07:22.523 --> 0:07:25.613 best job skill that you can have. And then you 0:07:25.613 --> 0:07:29.963 want to think of tech skill and specifically programming in 0:07:29.963 --> 0:07:34.133 AI as the new reading and writing. It's essential. Meaning 0:07:34.133 --> 0:07:36.863 if you're not good at them, then you're probably not 0:07:36.863 --> 0:07:41.523 going to succeed. You're probably going to be like an executor. And. 0:07:42.193 --> 0:07:46.393 Even as a creator who's actually giving these this work 0:07:46.393 --> 0:07:50.563 to eyes, you still need to be decently fluid, fluent 0:07:50.563 --> 0:07:55.063 in programming in AI because they are the language of creation. 0:07:55.063 --> 0:07:57.433 You need to be able to explain yourself to AI, 0:07:57.433 --> 0:08:00.073 and that that largely is going to be in the 0:08:00.073 --> 0:08:04.453 language of like prompting and speaking and thinking and writing. 0:08:04.453 --> 0:08:07.333 And some of that is going to involve programming, right? 0:08:07.513 --> 0:08:09.673 It'll be less and less as time goes on, but 0:08:09.673 --> 0:08:11.713 you should just learn that stuff. The other thing is 0:08:11.713 --> 0:08:13.603 you want to get trained on this stuff, and I 0:08:13.603 --> 0:08:16.093 think you want to get trained in two primary areas. 0:08:16.093 --> 0:08:19.033 And I do think college actually still matters, because it's 0:08:19.033 --> 0:08:21.943 a way of filtering the quality of a person when 0:08:21.943 --> 0:08:24.343 they don't know anything else about you. So I think 0:08:24.343 --> 0:08:26.773 college is still going to matter for a little while longer, 0:08:26.773 --> 0:08:30.163 maybe like a decade or something. But when you do study, 0:08:30.163 --> 0:08:33.283 whether it's in college or self-study, you want to be 0:08:33.283 --> 0:08:36.943 studying two branches simultaneously. One is a hard skill that's 0:08:36.943 --> 0:08:41.353 valuable in the market, like AI or something. AI or 0:08:41.353 --> 0:08:45.313 development or something like that. And number two is training 0:08:45.313 --> 0:08:48.883 on how to think. This one is even more important, 0:08:48.883 --> 0:08:51.133 but you don't want to do it at the expense 0:08:51.133 --> 0:08:52.903 of the first one. You want to have something, a 0:08:52.903 --> 0:08:56.743 hard skill to go along with it. But as time 0:08:56.743 --> 0:09:00.223 goes on, being able to think especially about problems and 0:09:00.223 --> 0:09:08.263 solutions is like the most important thing. So liberal arts, education, philosophy, logic, dialectic, 0:09:08.263 --> 0:09:11.773 all these things become way, way more important. They they 0:09:11.773 --> 0:09:14.563 become the things that separate the creators and like the 0:09:14.563 --> 0:09:18.973 owners and the, the top people from everyone else. So 0:09:18.973 --> 0:09:21.433 you really want to focus on both of those things 0:09:21.433 --> 0:09:23.473 in your education. You don't want to think so much 0:09:23.473 --> 0:09:25.963 about fields or companies. You want to think more about 0:09:25.963 --> 0:09:29.863 problems and problem spaces, right? What are the problems that 0:09:29.863 --> 0:09:32.203 will go away versus what are the problems that are 0:09:32.203 --> 0:09:34.243 going to stay with us all the time? And you 0:09:34.243 --> 0:09:37.543 want to go to where the problems are that interest you, 0:09:37.543 --> 0:09:39.643 and you'd be good at solving. And most of all, 0:09:39.643 --> 0:09:41.323 you want to get out of the mindset of being 0:09:41.323 --> 0:09:43.993 a worker and enter the mindset of being a creator 0:09:43.993 --> 0:09:46.273 or a builder. So you don't want to be the 0:09:46.273 --> 0:09:48.883 person building other people's ideas. You want to be the 0:09:48.883 --> 0:09:52.933 person creating ideas, and in finding the problems and building 0:09:52.933 --> 0:09:55.543 things that solve those problems. And that's the summary there, 0:09:55.543 --> 0:09:58.363 and that's essentially the post. So I didn't think we 0:09:58.363 --> 0:09:59.683 were going to do the whole thing, but that was 0:09:59.683 --> 0:10:03.103 essentially it. All right. So that was that one also 0:10:03.103 --> 0:10:07.663 posted our sponsored interview with BlackBerry. The second one, BlackBerry 0:10:07.663 --> 0:10:13.243 silence with Ismael Valenzuela, and he is the Threat research 0:10:13.243 --> 0:10:17.173 and intelligence VP at BlackBerry silence. And we talked about 0:10:17.173 --> 0:10:19.213 a whole bunch of cool stuff there. So definitely go 0:10:19.213 --> 0:10:22.693 check that one out. Going into security, researchers created a 0:10:22.693 --> 0:10:27.403 worm that exploits generative AI and spreads via prompt injection. 0:10:27.403 --> 0:10:29.713 So there's kind of a and they named it Morris two, 0:10:29.743 --> 0:10:32.593 which I thought was pretty cool. GitHub is now blocking 0:10:32.593 --> 0:10:37.273 commits with secrets and public repos. That's really cool. Biden 0:10:37.273 --> 0:10:40.633 is viewing Chinese connected cars as a national security threat, 0:10:40.633 --> 0:10:43.993 which I'm very happy about. Got to sponsor here. Collide. 0:10:43.993 --> 0:10:48.253 Thank you to collide for sponsoring us. Military's Project Maven 0:10:48.253 --> 0:10:52.393 is now actively using AI to identify and strike targets, 0:10:52.393 --> 0:10:57.163 marking a significant shift from skepticism around doing this to 0:10:57.163 --> 0:10:59.923 actually relying on it. And they've already done this in Yemen, 0:10:59.923 --> 0:11:04.663 the Red sea, Iraq and Syria. Shot spotter who renamed 0:11:04.663 --> 0:11:08.773 themselves probably to get around some PR drama, is now 0:11:08.773 --> 0:11:12.793 called sound Thinking and uses hidden sensors for gunfire detection. 0:11:12.793 --> 0:11:17.473 And it basically reveals exact locations of those sensors. And 0:11:17.473 --> 0:11:21.853 this data was previously unknown. Researchers found over 200 hacking 0:11:21.853 --> 0:11:27.103 services using AI. Things like bots like bad GPT. Cryptocurrency 0:11:27.103 --> 0:11:30.763 enthusiasts are being targeted with Mac malware. A group of hackers, 0:11:30.763 --> 0:11:34.933 including Rizzo my buddy Joseph Thakur, found some vulnerabilities in 0:11:34.933 --> 0:11:37.573 Google's AI and cloud systems, and they got 50 grand 0:11:37.573 --> 0:11:40.903 for that and a new vulnerability in hugging faces Safe 0:11:40.903 --> 0:11:44.923 Tensors conversion service could lead to supply chain attacks in 0:11:44.923 --> 0:11:49.363 AI models. All right. Technology. Yeah. Nvidia's CEO thinks I 0:11:49.363 --> 0:11:52.663 will soon make coding obsolete. Yeah, like we talked about above. 0:11:52.663 --> 0:11:55.003 I think that's true. And we just talked about this 0:11:55.003 --> 0:11:59.473 creators and executors essay here. Waymo is expanding to more 0:11:59.473 --> 0:12:02.203 highways in LA in the Bay area. I can't wait 0:12:02.203 --> 0:12:05.083 till they come to my area. I absolutely loved my 0:12:05.083 --> 0:12:08.533 experience with Waymo and Apple canceled the car project. I 0:12:08.533 --> 0:12:10.753 think everyone knows about this at this point, but they 0:12:10.753 --> 0:12:14.563 moved over 2000 employees to AI initiatives, which I'm super 0:12:14.563 --> 0:12:18.013 excited about. I really cannot wait until this June when 0:12:18.013 --> 0:12:20.593 they do the new announcements. It's going to be. I'm 0:12:20.593 --> 0:12:24.523 so hyped for those announcements. Basically, good AI that's close 0:12:24.523 --> 0:12:26.743 to you and actually on your phone is so much 0:12:26.743 --> 0:12:29.623 better than amazing. I that's stuck in like an IDE 0:12:29.623 --> 0:12:33.913 somewhere in 2023, public tech companies out of 2.4 trillion 0:12:33.913 --> 0:12:37.963 to their market caps. Musk is suing OpenAI, saying that 0:12:37.963 --> 0:12:41.383 they basically got away from their altruistic nature and are just. 0:12:41.493 --> 0:12:43.983 Going after profits, something like that. I'm not sure if 0:12:43.983 --> 0:12:47.073 that's his exact claim, but it's something like that. Basically, 0:12:47.073 --> 0:12:50.793 OpenAI says the New York Times paid someone to hack 0:12:50.793 --> 0:12:55.323 its products to produce content matching the newspaper's articles. This 0:12:55.323 --> 0:12:58.803 is wild. I haven't fully dove into, like, their exact 0:12:58.803 --> 0:13:03.153 claims in the in the lawsuit or whatever they're doing, 0:13:03.153 --> 0:13:07.173 but interesting plot point there. DocuSign has been using customer 0:13:07.173 --> 0:13:10.113 data to train their AI. People are freaking out about it. 0:13:10.113 --> 0:13:12.543 I think this is kind of like the wrong question. 0:13:12.543 --> 0:13:16.413 It's not about if someone is using customer data to 0:13:16.413 --> 0:13:18.993 train their AI. Of course they are. Everyone should be 0:13:18.993 --> 0:13:21.123 doing that. The question is, are you training on like 0:13:21.123 --> 0:13:24.723 personal data, on sensitive data, on privacy related data in 0:13:24.723 --> 0:13:27.483 a way that customers would object to? Customers are not 0:13:27.483 --> 0:13:31.413 going to object to you understanding, like their behavior and stuff. 0:13:31.413 --> 0:13:33.633 It's like it's going to come down to like, are 0:13:33.633 --> 0:13:37.713 you targeting somebody or are you doing something that's unexpected 0:13:37.713 --> 0:13:43.383 and gross that that's the distinction. SpaceX just hit 17mbps 0:13:43.383 --> 0:13:47.223 downloading directly to an Android phone. No. Now, this is 0:13:47.223 --> 0:13:49.683 like a new cell tower, essentially, but it's a cell 0:13:49.683 --> 0:13:53.343 tower that's actually a satellite. 17 megs download to a 0:13:53.343 --> 0:13:57.123 stock Android phone. Wendy's is looking to test dynamic surge 0:13:57.123 --> 0:14:01.173 pricing for food in 2025. Seems a little early to 0:14:01.173 --> 0:14:06.363 announce a strategy that you haven't implemented yet. Like, isn't 0:14:06.363 --> 0:14:10.233 that giving competitors too long to adjust? Yeah, right. What 0:14:10.233 --> 0:14:13.863 do I know about fast food strategy? Though? February and 0:14:13.863 --> 0:14:18.693 January saw a resurgence in tech job cuts. Yes it did. 0:14:18.693 --> 0:14:21.093 They are continuing. I didn't think that was going to happen. 0:14:21.183 --> 0:14:26.163 And the 50 over 90 by Nvidia is going to 0:14:26.163 --> 0:14:30.423 be like 70% faster than the 4090. Makes me sad. 0:14:30.423 --> 0:14:35.913 I got two 4090, but whatever, 192 streaming Multiprocessors and 0:14:35.913 --> 0:14:40.563 24,000 Cuda cores, that is insane. And a new study 0:14:40.563 --> 0:14:44.103 of 13,000 people showed. And this is in the human 0:14:44.103 --> 0:14:48.663 section that long Covid. And going into the human section, 0:14:48.663 --> 0:14:53.013 a new study of 13,000 people showed with long Covid, 0:14:53.043 --> 0:14:56.343 they lost about six IQ points, according to the study. 0:14:56.343 --> 0:15:00.903 Political extremism is now one of America's top concerns. Edging 0:15:00.903 --> 0:15:04.833 out the economy and immigration organ is reversing its drug 0:15:04.833 --> 0:15:10.203 decriminalization policy due to overdose deaths and public concern. I 0:15:10.203 --> 0:15:12.963 feel like 2024 is the year of like, the pendulum 0:15:12.963 --> 0:15:16.563 swinging back against a whole bunch of hyper liberal policies 0:15:16.563 --> 0:15:19.053 and attitudes. I just hope it doesn't swing too far 0:15:19.053 --> 0:15:22.623 and then, you know, then just keeps violent swings of 0:15:22.623 --> 0:15:25.533 the pendulum. It's just no good for anybody. California is 0:15:25.533 --> 0:15:29.373 proposing a bill to ban the homeless encampments near public spaces. 0:15:29.373 --> 0:15:34.023 Florida is experiencing a number of outbreaks of already beaten diseases. Basically, 0:15:34.023 --> 0:15:36.003 you've got people on the left and the right who 0:15:36.003 --> 0:15:39.753 are vaccine skeptics. They're not vaccinating their kids. And we're 0:15:39.753 --> 0:15:43.143 not hitting the numbers for herd immunity that are required 0:15:43.143 --> 0:15:47.073 for herd immunity. And people are getting diseases like the 0:15:47.073 --> 0:15:50.283 measles that that have been, like, already knocked out for 0:15:50.283 --> 0:15:54.213 decades or hundreds of years or whatever. And alcohol related 0:15:54.213 --> 0:15:58.353 deaths in the US jumped by nearly 30%, almost 500 daily. 0:15:58.353 --> 0:16:02.253 And a neurosurgeon is using ultrasound to tackle Alzheimer's and 0:16:02.253 --> 0:16:06.273 addiction with some really exciting results. Had a crazy idea 0:16:06.273 --> 0:16:10.563 in the idea section here. What if AGI powered robots? 0:16:10.563 --> 0:16:14.553 What if we get those before we get autonomous cars? 0:16:14.553 --> 0:16:18.753 What if it's actually easier to do AGI that is 0:16:18.753 --> 0:16:22.863 capable of like evaluating a situation? Maybe not. Maybe. Maybe 0:16:22.863 --> 0:16:27.363 they are the same thing, because the AGI that we 0:16:27.363 --> 0:16:30.903 will have built wouldn't be trained on car stuff, and 0:16:30.903 --> 0:16:34.563 Tesla stuff would still be the best ones anyway. It's 0:16:34.563 --> 0:16:37.293 just a possibility. It random thought. In other words, maybe 0:16:37.293 --> 0:16:40.833 it's easier to put a local GPT six level AI 0:16:40.833 --> 0:16:43.083 in a car and have it learn a whole bunch 0:16:43.083 --> 0:16:47.583 of stuff than to actually try to make the car autonomous. 0:16:47.583 --> 0:16:50.013 I don't know, like I said, it's a random thought 0:16:50.013 --> 0:16:53.973 and Sunday was 30 years with my love two piece 0:16:53.973 --> 0:16:57.813 Combee and Dune two was insanely good. I've already seen 0:16:57.813 --> 0:17:00.243 it twice. Going to see it again. All right. Discovery. 0:17:00.243 --> 0:17:03.273 My buddy Jason Haddix put out a sick episode of 0:17:03.273 --> 0:17:07.623 his newsletter called Executive Offense, and lots of prompt injection 0:17:07.623 --> 0:17:10.413 and other resources about hacking. I definitely want to go 0:17:10.413 --> 0:17:14.133 check that out and subscribe to his newsletter. Do literally anything. 0:17:14.133 --> 0:17:19.353 Great essay here. Caltrans has public data in CCTV, data 0:17:19.353 --> 0:17:24.003 in CSV, Json, text, XML formats. Got a deep dive 0:17:24.003 --> 0:17:27.093 into a git configuration here. How to get nmap to 0:17:27.093 --> 0:17:30.663 detect new services. How did this person decides if your 0:17:30.663 --> 0:17:34.263 website is worth a revisit? The internet feels fake now. 0:17:34.263 --> 0:17:39.423 Tyler Cohen shares his personal strategy around listening to music. 0:17:39.423 --> 0:17:41.753 I didn't agree with it, but I. I actually really 0:17:41.753 --> 0:17:45.923 enjoyed reading it. Apple's releasing Neuromancer as a ten episode 0:17:45.923 --> 0:17:49.553 series on Apple TV+. I definitely agree with somebody who 0:17:49.553 --> 0:17:51.893 said this. I can't remember if it was Scott Galloway, 0:17:51.893 --> 0:17:55.943 but Apple TV is basically basically become the new HBO. 0:17:55.943 --> 0:17:58.523 HBO got knocked out because they're calling it Macs now 0:17:58.523 --> 0:18:03.413 and nobody cares. And so now Apple TV is like fire, 0:18:03.413 --> 0:18:06.413 like it's doing so well, and it's basically become the 0:18:06.413 --> 0:18:09.413 new HBO. It's like if a show comes on to 0:18:09.413 --> 0:18:13.703 Apple TV, it's probably pretty good. Bad therapy argues modern 0:18:13.703 --> 0:18:17.903 therapeutic parenting is failing, leaving kids anxious and unprepared for life. 0:18:17.903 --> 0:18:21.263 Algorithmic thinking. I've ordered this thing. I've got the physical 0:18:21.263 --> 0:18:24.143 copy coming. I read the first one. Absolutely loved it. 0:18:24.143 --> 0:18:26.303 I was working at Apple. I actually remember I was 0:18:26.633 --> 0:18:29.693 talking to someone about it taking a walk, but absolutely 0:18:29.693 --> 0:18:32.123 love this book. And now it's version two or a 0:18:32.123 --> 0:18:34.583 second edition and it's got new chapters. Can't wait to 0:18:34.583 --> 0:18:37.913 read it. It's on the way, and spending ten minutes 0:18:37.913 --> 0:18:40.733 on something is 1% of your day. And I think 0:18:40.733 --> 0:18:44.393 that's assuming, like I forget how many hours, 16 hours 0:18:44.393 --> 0:18:47.363 a week. They have some assumptions in there and the 0:18:47.363 --> 0:18:51.743 recommendation of the week. Ask yourself if you're primarily a nurturer, 0:18:52.133 --> 0:18:55.313 a creator or a worker, because it's my belief that 0:18:55.313 --> 0:18:58.493 creators are nurturers. And this goes back to the essay, um, 0:18:58.493 --> 0:19:02.063 people that help nurtures are basically people that help creators 0:19:02.063 --> 0:19:06.233 or nurtures grow up and and become, uh, fruitful. So 0:19:06.233 --> 0:19:11.303 it's basically parents or nurturers. Um, artists are creators, entrepreneurs 0:19:11.303 --> 0:19:15.953 are creators, therapists are nurturers, etc. and I think that 0:19:15.953 --> 0:19:19.313 creators are nurturers are the roles that will be most 0:19:19.313 --> 0:19:22.223 resilient to AI, and they're also the most human roles 0:19:22.223 --> 0:19:24.893 that they're what we should be doing anyway. We shouldn't 0:19:24.893 --> 0:19:28.973 be like moving paperwork around and tilling fields and all 0:19:28.973 --> 0:19:32.033 this crap. Try to get this is my recommendation. Try 0:19:32.033 --> 0:19:35.663 to get out of the worker mentality. My family is Lutheran, right? 0:19:36.053 --> 0:19:39.203 Hard work. My dad always instilled this into me. Like 0:19:39.203 --> 0:19:41.663 your reputation is based on the work that you do. 0:19:41.663 --> 0:19:44.063 So like I get this and I feel it deeply 0:19:44.063 --> 0:19:49.133 and I think hard work is noble and honorable 100%. 0:19:49.133 --> 0:19:53.453 But we were handed arbitrary jobs just because of the 0:19:53.453 --> 0:19:56.753 the escalation of tech through our lives. Right? When there's 0:19:56.753 --> 0:19:59.213 no clean water, you know, a lot of the work 0:19:59.213 --> 0:20:01.193 is trying to get clean water when there's no food. 0:20:01.193 --> 0:20:02.873 A lot of the work is trying to get food. 0:20:02.873 --> 0:20:05.033 Like all those things get phased out as the tech 0:20:05.033 --> 0:20:07.763 gets better. And that's what we're about to go through. Again, 0:20:07.763 --> 0:20:10.763 an AI is going to be doing most of the 0:20:10.763 --> 0:20:14.063 old worker style jobs better, so we have to start 0:20:14.063 --> 0:20:19.733 planning our migration to a creator and a nurturer style economy. 0:20:19.733 --> 0:20:21.833 And we're all going to be hybrids for for a 0:20:21.833 --> 0:20:24.653 long time, but you want to try to migrate to 0:20:24.653 --> 0:20:26.903 that as soon as possible. And until the people that 0:20:26.903 --> 0:20:28.673 you care about to try to do the same and 0:20:28.673 --> 0:20:31.583 the optimism for the week along those lines, the end 0:20:31.583 --> 0:20:36.613 of labor is to gain leisure. Aristotle. Unsupervised Learning is 0:20:36.613 --> 0:20:39.763 produced and edited by Daniel Miller on a Norman 87 0:20:39.763 --> 0:20:43.843 AI microphone using Hindenburg. Intro and outro music is by 0:20:43.843 --> 0:20:47.053 zombie with the Y, and to get the text and 0:20:47.053 --> 0:20:49.423 links from this episode, sign up for the newsletter version 0:20:49.423 --> 0:20:54.993 of the show at Daniel missler.com/newsletter. We'll see you next time.