WEBVTT - UL NO. 434: Can You Articulate Yourself in 50 Words? 0:00:01.129 --> 0:00:04.490 Welcome to Unsupervised Learning, a security, AI and meaning focused 0:00:04.490 --> 0:00:07.370 podcast that looks at how best to thrive as humans 0:00:07.370 --> 0:00:11.570 in a post AI world. It combines original ideas, analysis, 0:00:11.570 --> 0:00:14.810 and mental models to bring not just the news, but 0:00:14.810 --> 0:00:21.980 why it matters and how to respond. All right. Welcome 0:00:21.980 --> 0:00:25.100 to unsupervised learning. This is Daniel Meisler. This episode is. 0:00:25.100 --> 0:00:30.710 Can you articulate yourself in 50 words? Let's jump in here. Yeah. 0:00:30.710 --> 0:00:33.140 One of the most important things for surviving AI is 0:00:33.140 --> 0:00:36.560 being able to articulate what you do, or even better, 0:00:36.560 --> 0:00:39.290 who you are. So I was at a party with 0:00:39.290 --> 0:00:42.410 a bunch of like, high net worth people, like muckety 0:00:42.409 --> 0:00:45.290 mucks like important people. And somebody asked me, I was 0:00:45.290 --> 0:00:48.290 at RSA, so people have asked me this like 20 0:00:48.290 --> 0:00:50.360 times over the course of the week. They asked me 0:00:50.360 --> 0:00:52.190 what I did and I told them I built AI 0:00:52.190 --> 0:00:55.850 stuff and they just looked at me like, oh, you're 0:00:55.850 --> 0:00:58.790 an asshole. Basically, like I was trying to be cool. 0:00:58.790 --> 0:01:01.430 And it's like, I am seriously not trying to be cool. 0:01:01.430 --> 0:01:04.490 I'm trying to say a small amount, which maybe spawns 0:01:04.490 --> 0:01:07.399 a conversation if they're like, oh yeah, really? What kind 0:01:07.400 --> 0:01:09.350 of AI or something? But I don't want to go 0:01:09.350 --> 0:01:11.690 into some sales pitch of like, oh, I'm building AI 0:01:11.690 --> 0:01:13.760 that blah blah, blah blah does this. But it was 0:01:13.760 --> 0:01:16.850 just like not landing. It didn't land for me. It 0:01:16.850 --> 0:01:19.250 didn't land for them. It just wasn't good. So I 0:01:19.250 --> 0:01:22.790 think I'm basically going to answer differently from now on. 0:01:22.790 --> 0:01:25.460 I'm going to start with the problems. So I'm basically 0:01:25.459 --> 0:01:28.009 worried about two problems people having a lack of meaning 0:01:28.010 --> 0:01:32.240 in their lives and AI making that worse when their 0:01:32.240 --> 0:01:34.700 jobs go away. So what I do is I use 0:01:34.700 --> 0:01:37.460 AI to build products and services that help people and 0:01:37.459 --> 0:01:41.360 companies create a version of themselves that will not just survive, 0:01:41.390 --> 0:01:45.620 but will thrive after AI is everywhere. And I could 0:01:45.620 --> 0:01:48.080 say that in multiple different ways, but it starts with 0:01:48.080 --> 0:01:51.110 I'm worried about two problems, so I'm building these things 0:01:51.110 --> 0:01:53.780 to solve them. So that's basically like my new spiel. 0:01:53.780 --> 0:01:56.450 And I like this for a few different reasons. One, 0:01:56.450 --> 0:01:59.960 it starts with the problems. Two, it highlights that I'm building. 0:01:59.960 --> 0:02:03.260 It mentions AI, which is good to mention, and it 0:02:03.470 --> 0:02:06.680 is actually what I'm doing, and it puts meaning as 0:02:06.680 --> 0:02:09.380 the most important piece even above AI. So I like 0:02:09.380 --> 0:02:12.080 it for all these different reasons. But I think the 0:02:12.080 --> 0:02:16.880 most screwed people right now are those who don't know themselves, right? 0:02:16.880 --> 0:02:19.640 They don't know what they're about, they don't have a 0:02:19.639 --> 0:02:22.520 purpose they can't articulate, like why they get up in 0:02:22.520 --> 0:02:25.130 the morning and what they're driving towards, or why they 0:02:25.130 --> 0:02:27.980 do the job that they're doing other than, well, I 0:02:27.980 --> 0:02:31.190 it's just the job I have or whatever. So my 0:02:31.190 --> 0:02:35.060 recommendation know yourself and be able to articulate that thing. 0:02:35.060 --> 0:02:39.890 So I ran this through the create five sentence summary 0:02:39.889 --> 0:02:43.130 fabric pattern. And it ended up with this helping people 0:02:43.130 --> 0:02:47.600 find meaning in the AI era. Empowering human potential with AI, 0:02:47.630 --> 0:02:52.880 AI for human flourishing, meaningful AI solutions, and AI powered meaning. 0:02:52.880 --> 0:02:56.000 Not too bad. So my work network Chuck, my buddy 0:02:56.000 --> 0:03:00.530 Chuck here just posted the most amazing video about fabric. 0:03:00.530 --> 0:03:04.640 It was just absolutely, insanely good. I've been waiting for 0:03:04.639 --> 0:03:06.380 this thing to drop for a couple of months now, 0:03:06.380 --> 0:03:11.329 and so he basically captures this spirit of the project 0:03:11.330 --> 0:03:15.260 in such a fantastic way. He just really gets the 0:03:15.260 --> 0:03:18.080 concept of it how it's human. First, he mentions it 0:03:18.080 --> 0:03:21.980 multiple times, he pulls multiple quotes out. He's got us 0:03:21.980 --> 0:03:25.579 talking about it in an interactive way there. It's just 0:03:25.580 --> 0:03:28.400 unbelievably good. And it's a pretty long video. And he 0:03:28.400 --> 0:03:32.419 walks through all sorts of use cases. Highly recommend that one. Security. 0:03:32.419 --> 0:03:34.549 Looks like we're going to have a cyber force similar 0:03:34.550 --> 0:03:38.150 to the Space Force. Chinese linked hackers are using things 0:03:38.150 --> 0:03:42.020 called orbs, which are basically these hop networks that they 0:03:42.020 --> 0:03:44.960 can bounce through for hiding, spying, and a bunch of 0:03:44.960 --> 0:03:50.420 other shenanigans. Fixed problems instead of doing risk measurement theatre. 0:03:50.420 --> 0:03:53.270 I came up with that title, but Andy Ellis wrote 0:03:53.270 --> 0:03:58.130 this piece. Quite cool. This piece actually. Short. Sweet. Yeah. 0:03:58.160 --> 0:04:01.490 Really good. Highly recommend it. Run some AI against it 0:04:01.490 --> 0:04:04.010 if you don't want to read that. But yeah, really good. 0:04:04.130 --> 0:04:10.610 Got a bug cloud? No, a cloud related bug. Linguistic lumberjack. 0:04:10.640 --> 0:04:14.930 Pretty cool alliteration there. Issue with Fluentbit. And basically it's 0:04:14.930 --> 0:04:18.590 got 3 billion downloads and it's yeah all sorts of systems. 0:04:18.589 --> 0:04:23.120 So another supply chain issue American criminal records exposed 70 0:04:23.120 --> 0:04:28.580 million rows of American criminal record in a database somewhere. 0:04:28.850 --> 0:04:33.740 So Russia evidently launched some sort of space weapon capable 0:04:33.740 --> 0:04:36.470 of attacking satellites. And they're saying that it's close to 0:04:36.470 --> 0:04:39.830 a particular one, same orbit as a US government satellite 0:04:39.830 --> 0:04:42.740 posing a direct threat. And of course, Russian said Russia 0:04:42.740 --> 0:04:45.710 said fake news. Not true, which I believe. And why 0:04:45.710 --> 0:04:48.500 wouldn't you believe him? Like why would they lie? That's 0:04:48.500 --> 0:04:52.820 the thing. I breaks into a tech giant. So X-Force 0:04:52.820 --> 0:04:56.300 from IBM, they've been around forever. They've been around like 0:04:56.300 --> 0:04:58.729 they were around when I got started, I think. And 0:04:58.730 --> 0:05:00.919 they got a new AI hacking platform, and they use 0:05:00.920 --> 0:05:04.430 it to attack some major tech manufacturers network, and they 0:05:04.430 --> 0:05:07.310 got in around eight hours. Question is, how much human 0:05:07.310 --> 0:05:10.460 involvement was there or was it like completely automated? That 0:05:10.460 --> 0:05:13.520 would be impressive. They haven't released this tool yet, but 0:05:13.520 --> 0:05:16.400 eager to hear more about it. Tesla's can still be hacked. 0:05:16.400 --> 0:05:20.549 I believe these were model threes, but. A buddy, Malwaretech 0:05:20.550 --> 0:05:24.839 Marcus Hutchins did a demo of this on his TikTok. 0:05:24.870 --> 0:05:27.599 Pretty easy to get into these cars still, even though 0:05:27.600 --> 0:05:30.210 they switched to wideband to try to get around this, 0:05:30.210 --> 0:05:33.060 I believe. But yeah, it still works. Not sure if 0:05:33.060 --> 0:05:37.050 it works on model wise. Preliminary report on the Baltimore 0:05:37.050 --> 0:05:42.540 Bridge looks like unexpected structural weaknesses. So not cyber like 0:05:42.540 --> 0:05:46.830 so many people said immediately. Core issue with Wi-Fi with 0:05:46.830 --> 0:05:51.090 lack of Ssid authentication during beaconing. Okay, got a US 0:05:51.089 --> 0:05:54.060 woman and four others charged in a scheme using fake 0:05:54.060 --> 0:05:57.450 IT jobs to get lots of money into North Korea's 0:05:57.450 --> 0:06:03.060 nuclear program. 60 identities and 300 companies US companies. Insane. 0:06:03.330 --> 0:06:07.050 NYPD is rolling out drones to respond to 911 calls. 0:06:07.080 --> 0:06:09.660 I am happy about this, but only because I like 0:06:09.660 --> 0:06:14.190 sci fi technology. You. The EU passed its AI act, 0:06:14.190 --> 0:06:16.650 and I've got a summary here. I'm not going to 0:06:16.650 --> 0:06:19.800 read all ten of these points, but the fines up 0:06:19.800 --> 0:06:22.919 to 7% of worldwide turnover, that's a pretty hefty fine. 0:06:23.040 --> 0:06:27.870 Probably not going to be ignored as much as other regulation. Oh, 0:06:27.870 --> 0:06:30.330 the other key point, because I read a whole bunch 0:06:30.330 --> 0:06:34.380 of this thing, was that they tried to support innovation, 0:06:34.380 --> 0:06:37.380 so they didn't go like crazy Europe on it with 0:06:37.380 --> 0:06:41.310 like just more and more regulation. They actually have a 0:06:41.310 --> 0:06:44.700 regulation in here that says you can't impose other regulation. 0:06:44.700 --> 0:06:48.000 So they wanted to avoid this getting out of control, 0:06:48.000 --> 0:06:50.969 which I thought was smart of them. And when your 0:06:50.970 --> 0:06:55.050 AI sounds too much like Scarlett Johansson. So I have 0:06:55.050 --> 0:06:58.920 opinions on this. So basically Sam tweeted out her, okay, 0:06:58.920 --> 0:07:01.080 so it was pretty obvious that they wanted this thing 0:07:01.110 --> 0:07:03.419 to sound like the movie, right? So they reached out 0:07:03.420 --> 0:07:06.690 to a voice actress who sounded like Scarlett, and then 0:07:06.690 --> 0:07:10.920 they reached out to actual Scarlett Johansson. Real Scarlett Johansson 0:07:10.920 --> 0:07:12.630 said no. So they're like, okay, we're going to go 0:07:12.630 --> 0:07:14.700 with the other one. They already I don't know if 0:07:14.700 --> 0:07:17.070 they had tweeted out her before or after that, but 0:07:17.070 --> 0:07:19.920 it was obviously they were going in that direction. I 0:07:19.920 --> 0:07:22.410 don't think this is horribly malicious. Like if you've ever 0:07:22.410 --> 0:07:24.630 worked inside of one of these companies, especially at like 0:07:24.630 --> 0:07:28.200 the leadership level, there is mass chaos. You might have 0:07:28.200 --> 0:07:30.660 marketing talking about something. You might have someone on your 0:07:30.660 --> 0:07:34.530 leadership team who, like, was approved to say something. But 0:07:34.530 --> 0:07:37.170 they said the thing that was different than the actual message. 0:07:37.170 --> 0:07:40.470 There could be miscommunication here. So yeah, I don't think 0:07:40.470 --> 0:07:44.100 it's malicious, but somebody was bringing up. Look, it's not 0:07:44.100 --> 0:07:48.060 Scarlett Johansson. You can hire somebody who sounds like somebody else, 0:07:48.060 --> 0:07:50.280 no big deal. And I had a tweet somewhere. It 0:07:50.280 --> 0:07:54.090 was like, you're not allowed to deepfake people using real humans. 0:07:54.090 --> 0:07:57.540 That's still a deepfake. Not technically. It's not technically a 0:07:57.540 --> 0:07:59.880 deepfake because it's not AI. It's a real person. But 0:07:59.880 --> 0:08:02.400 the point is to copy someone else. And I'm sure 0:08:02.400 --> 0:08:05.400 there's precedent for this all over the place. Already on 0:08:05.400 --> 0:08:08.280 the books. It's like if I hire somebody who looks 0:08:08.280 --> 0:08:13.620 exactly like whoever, um, the Rock, Dwayne Johnson or whatever, 0:08:13.620 --> 0:08:17.640 and I'm like, yeah, I'm claiming to be him or no, 0:08:17.640 --> 0:08:20.550 I just call the app the Stone, and it's like 0:08:20.550 --> 0:08:22.710 the Rock's voice, but it's like, no, I didn't know 0:08:22.710 --> 0:08:24.690 it was the Rock, and I. What are you talking about? 0:08:24.690 --> 0:08:26.550 I don't even know who the rock is. But you 0:08:26.550 --> 0:08:28.650 hire a person who sounds just like him, and the 0:08:28.650 --> 0:08:31.860 app is called the Stone. Then you tweet out, rocks 0:08:31.860 --> 0:08:34.950 are cool, that come on, there's got to be a 0:08:34.950 --> 0:08:37.650 precedent for that. So they're going to get smashed if 0:08:37.650 --> 0:08:40.800 that does go to court. I wish it just wouldn't. Right? 0:08:40.800 --> 0:08:43.890 I mean, I'm trying to look at positives here. Like 0:08:43.890 --> 0:08:46.830 Sam is trying to do a cool thing. Okay. It's 0:08:46.830 --> 0:08:50.010 like her is awesome, I love her. I've got a 0:08:50.010 --> 0:08:53.250 video about this where I'm like, hey, look, you could 0:08:53.250 --> 0:08:57.630 talk to Samantha from the movie her and I'm breaking down, 0:08:57.630 --> 0:08:59.729 like how you can use that with Siri and Shortcuts 0:08:59.730 --> 0:09:03.420 and everything. So it's like so obvious and it's so cool. 0:09:03.420 --> 0:09:06.210 And it's also cool for Scarlett to be able to say, yeah, 0:09:06.210 --> 0:09:09.809 you know what? Not me. Can't do that. So anyway, 0:09:09.809 --> 0:09:12.480 it's a legal issue. I'm not sure what the actual 0:09:12.480 --> 0:09:16.140 precedent says, but yeah, hiring someone who sounds just like 0:09:16.140 --> 0:09:19.949 Scarlett and pretending it didn't happen, that's not the game. 0:09:20.130 --> 0:09:23.069 Looks like Apple tried to get all of TSMC's two 0:09:23.070 --> 0:09:30.420 nanometer chips stock skyrocketing 262%, $26 billion. They're about to 0:09:30.420 --> 0:09:34.109 be worth more than Apple, which is ridiculous. And I 0:09:34.110 --> 0:09:37.590 think Scott Galloway was quoting some stats of like, it's 0:09:37.590 --> 0:09:40.110 Nvidia at this point is worth more than like the 0:09:40.110 --> 0:09:44.819 economy of Germany or something. Just ridiculous numbers. And I 0:09:44.820 --> 0:09:47.340 think we're just starting with AI, so I don't see 0:09:47.340 --> 0:09:51.240 how someone's going to catch up before, who knows how 0:09:51.240 --> 0:09:53.280 high Nvidia is going to go, but I feel like 0:09:53.280 --> 0:09:55.560 they got a massive lead and everyone's going to be 0:09:55.559 --> 0:09:58.800 trying to get in. AI is just starting. People are 0:09:58.800 --> 0:10:02.880 talking about plateaus. I think they're absolutely insane. So yeah, 0:10:02.880 --> 0:10:06.480 exciting times. Looks like we found some lithium in the US. 0:10:06.750 --> 0:10:11.610 Massive untapped lithium source Microsoft is reimagining windows with a 0:10:11.610 --> 0:10:15.900 deep dive into AI, introducing copilot NPCs that blend cutting 0:10:15.900 --> 0:10:19.800 edge AI features directly into the operating system. People are saying, hey, 0:10:19.800 --> 0:10:24.179 nobody wants this. Well, yeah, they actually do. Once everyone 0:10:24.179 --> 0:10:28.350 has the ability to remember everything they've done on their computer, 0:10:28.350 --> 0:10:30.840 remember every screen, and they could just talk to their 0:10:30.840 --> 0:10:33.930 computer and be like, hey, where was that one email? Hey, 0:10:33.929 --> 0:10:36.900 am I missing a thing? Hey, keep me up to date. Hey, 0:10:36.900 --> 0:10:38.940 make a list of this. Hey, send a list of 0:10:38.940 --> 0:10:41.939 this to all my friends. Hey, show me the most 0:10:41.940 --> 0:10:45.060 important things I should be taking a look at. Hey, 0:10:45.059 --> 0:10:49.110 reprioritize my work. Hey, rewrite this document for me. And 0:10:49.110 --> 0:10:51.959 when I say rewrite this document for me, it knows 0:10:51.960 --> 0:10:54.570 that I'm looking at the screen and it knows what 0:10:54.570 --> 0:10:57.510 document I'm looking at. So it just rewrites it and 0:10:57.510 --> 0:10:59.910 it's like, ah, not so much. Make it less formal. 0:10:59.910 --> 0:11:03.630 Boom rewrites it less formal. Okay, send it out to 0:11:03.630 --> 0:11:06.930 all my directs or whatever. Boom sends it out. Once 0:11:06.929 --> 0:11:09.270 you're interacting with a computer like that and you have 0:11:09.270 --> 0:11:12.180 all of your history available, this is like I said 0:11:12.179 --> 0:11:15.540 in my AI prediction video, everyone's going to want this, 0:11:15.540 --> 0:11:18.930 and they're going to demand it. And what it requires 0:11:18.950 --> 0:11:22.820 is everything being recorded all the time, all your screens, 0:11:22.820 --> 0:11:26.960 all your conversations. Trust me, it's happening. It's going to happen. 0:11:26.960 --> 0:11:29.089 There's nothing that's going to stop that. There's nothing's going 0:11:29.090 --> 0:11:33.020 to slow it down. It is too powerful and too awesome. Now, 0:11:33.020 --> 0:11:38.569 will there be security issues? Oh yes. So many security issues. 0:11:38.570 --> 0:11:41.420 And they will be horrible because it will be your 0:11:41.420 --> 0:11:45.679 whole entire soul getting compromised when that stuff gets leaked. Right. 0:11:45.679 --> 0:11:48.200 It's every text message that came through everything. A little 0:11:48.200 --> 0:11:51.470 pop pop up, someone sent you a dirty joke or whatever, 0:11:51.470 --> 0:11:54.470 or you sent somebody else a dirty joke that's also recorded. 0:11:54.470 --> 0:11:57.770 That's also captured by AI. That's somewhere. Now it's in 0:11:57.770 --> 0:12:01.400 some law document somewhere. Because guess what? Lawyers get access 0:12:01.400 --> 0:12:03.860 to that and everything. I mean, it's going to be 0:12:03.860 --> 0:12:07.190 crazy world we're about to move into. But I tell you, 0:12:07.190 --> 0:12:09.589 the downsides are not going to slow it down in 0:12:09.590 --> 0:12:13.219 the slightest because the upsides are going to be so powerful. 0:12:13.490 --> 0:12:17.330 Mapping AI's inner universe. This is really cool. Anthropic released 0:12:17.330 --> 0:12:22.430 a paper on sonnet, which is their medium level model, 0:12:22.429 --> 0:12:26.569 and basically showed how it thought essentially basically a lot 0:12:26.570 --> 0:12:30.350 more transparency for AI, which has been traditionally opaque with 0:12:30.350 --> 0:12:35.060 neural nets. China released a chatbot called Ask President XI, 0:12:35.420 --> 0:12:39.679 and it allows citizens to ask Prachi how to be 0:12:39.679 --> 0:12:43.339 better socialists. Fantastic. I bet that's flying off the shelf. 0:12:43.580 --> 0:12:47.449 Astronomers are preparing to use AI to tackle 300PB of 0:12:47.450 --> 0:12:51.110 data annually. Yeah. Watch this guy. Find some stuff. Make 0:12:51.110 --> 0:12:54.980 sure rocks don't hit us. Windows 11 Powertoys allows you 0:12:54.980 --> 0:12:59.870 to transform AI transform clipboard content into different formats or 0:12:59.870 --> 0:13:04.670 languages with a simple shortcut. Love it and it uses OpenAI. Cool. 0:13:04.670 --> 0:13:08.750 No problem. Microservices might be all the rage, but this 0:13:08.750 --> 0:13:13.339 thing basically says use modules instead of microservices. Interesting. X 0:13:13.340 --> 0:13:15.830 is getting rid of public likes, so you can't get 0:13:15.830 --> 0:13:20.120 in trouble for liking somebody who's controversial. You'll still be 0:13:20.120 --> 0:13:22.010 able to see when someone likes your stuff, and you'll 0:13:22.010 --> 0:13:24.260 still be able to see your own likes, but you 0:13:24.260 --> 0:13:27.290 won't be able to see other people's. You won't be 0:13:27.290 --> 0:13:30.350 able to see someone who you hate and see a 0:13:30.350 --> 0:13:33.079 third person who liked their stuff. That's what you won't 0:13:33.080 --> 0:13:36.050 be able to see. And Elon basically thinks that this 0:13:36.050 --> 0:13:38.599 is going to increase the number of likes. And I 0:13:38.600 --> 0:13:41.750 think he's probably right about that. Focusing on fundamentals over 0:13:41.750 --> 0:13:45.620 frameworks could be the secret sauce for long lasting tech skills. 0:13:45.620 --> 0:13:48.080 Agree with this. This was a good essay. Shows you 0:13:48.080 --> 0:13:52.459 how to use ghidra for crafting gdb scripts that trace 0:13:52.460 --> 0:13:58.430 function calls helping with vulnerability, hunting D3 in-depth guides. Love 0:13:58.429 --> 0:14:03.740 me some D3. Really powerful library experts JS simplifies creating 0:14:03.740 --> 0:14:07.970 multi-agent AI systems. Starting to get pretty turned off by 0:14:08.030 --> 0:14:11.270 AI agent systems. Honestly, I'm heading down the path of 0:14:11.270 --> 0:14:13.400 just building all my own stuff, and that's what I'm 0:14:13.400 --> 0:14:16.730 doing with substrate. So getting away from the agent frameworks, 0:14:16.730 --> 0:14:20.450 I think just a lot of really cool stuff in 0:14:20.450 --> 0:14:24.410 demos and not usable in production. That's what I'm finding. 0:14:24.410 --> 0:14:27.980 And I think everyone's finding that who's actually building user 0:14:27.980 --> 0:14:33.590 persona generator prompts simulates user interviews to create detailed user personas, 0:14:33.830 --> 0:14:38.600 saving you from conducting dozens of real interviews. Yeah, wait 0:14:38.630 --> 0:14:43.010 till you see what AI is going to hiring. Oh yeah, 0:14:43.010 --> 0:14:45.560 that's what we're about to talk about. Job seekers are 0:14:45.560 --> 0:14:49.760 struggling to find work and employers can't seem to fill positions. Paradox. 0:14:49.760 --> 0:14:53.240 It is not a mystery. The problem is hiring managers 0:14:53.240 --> 0:14:55.640 need people ready to do the job and they don't 0:14:55.640 --> 0:14:58.370 want to train anyone. This is why degrees are mattering less, 0:14:58.370 --> 0:15:01.190 and why somebody with an active tech blog or YouTube 0:15:01.190 --> 0:15:04.820 channel who's actually building stuff and doing the thing can 0:15:04.820 --> 0:15:07.580 get hired with no credentials over someone with a degree 0:15:07.580 --> 0:15:11.390 in computer science, or two degrees, or a master's degree 0:15:11.390 --> 0:15:15.080 or a PhD. The ability to actually do the thing 0:15:15.080 --> 0:15:18.770 is all that matters now. Expect to see AI services soon. 0:15:19.240 --> 0:15:22.900 Now look at a person's social media blog, YouTube, whatever, 0:15:22.900 --> 0:15:26.710 and then do an interactive interview with them and give 0:15:26.710 --> 0:15:29.830 a score of how likely they are to do a 0:15:29.830 --> 0:15:32.710 good job at this job. This will cut through all 0:15:32.710 --> 0:15:35.320 the credentials, all the fluff, all sorts of other BS 0:15:35.320 --> 0:15:38.260 and get at the real thing. The value of traditional 0:15:38.260 --> 0:15:42.940 education will drastically fall because of this. Like pay attention 0:15:42.940 --> 0:15:47.110 to this. The value of traditional education will drastically fall 0:15:47.110 --> 0:15:50.980 as a result of this, because degrees won't significantly raise 0:15:50.980 --> 0:15:55.780 these scores for most people. This is something this controversial point. 0:15:55.780 --> 0:15:58.360 I used to think that it was all about expose 0:15:58.360 --> 0:16:00.700 people to the training and they will get better, and 0:16:00.700 --> 0:16:03.400 you just need better training. If they're not moving, you 0:16:03.400 --> 0:16:07.120 give them better training. Turns out that's not it. It's 0:16:07.120 --> 0:16:10.780 actually something inside the person that if they are that 0:16:10.780 --> 0:16:14.560 person who's going to be awesome, it doesn't take much 0:16:14.560 --> 0:16:20.320 to prompt them or to stimulate them into their curiosity, 0:16:20.320 --> 0:16:24.700 which just makes them a voracious reader and learner and studier. 0:16:24.700 --> 0:16:26.440 And all of a sudden, boom, they shoot out of 0:16:26.440 --> 0:16:28.960 the thing. That's why the help desk is so good 0:16:28.960 --> 0:16:33.370 at finding talent, because it's a wide filter. There's so 0:16:33.370 --> 0:16:36.160 many people on Help Desk, but there's somebody on help 0:16:36.160 --> 0:16:40.270 desk who, the moment they sat on the tier one floor, 0:16:40.300 --> 0:16:44.680 they immediately like started answering all the questions for everyone else. Boom! 0:16:44.680 --> 0:16:47.530 They become tier two, boom. They become tier three. And 0:16:47.530 --> 0:16:50.410 before long, if they have the right networking or whatever, 0:16:50.410 --> 0:16:52.990 they go into networking, they go into sysadmin, or they 0:16:52.990 --> 0:16:56.110 go into programming or they go into security or something, 0:16:56.110 --> 0:16:59.950 and they shoot off and they become a star. And 0:16:59.950 --> 0:17:03.460 an experienced person could have seen them at tier one 0:17:03.460 --> 0:17:05.980 in tech and just been like, oh, that's a star 0:17:05.980 --> 0:17:10.700 right there. First of that is that there are people 0:17:10.700 --> 0:17:14.119 who come in with two degrees, go to tier one, 0:17:14.119 --> 0:17:17.990 you send them to Harvard, the best training, the best everything, 0:17:17.990 --> 0:17:21.530 and they can't even move into tier two. They're there 0:17:21.530 --> 0:17:24.140 for six years. And when they see a problem that 0:17:24.140 --> 0:17:26.659 they've seen a million times, they call their manager or 0:17:26.660 --> 0:17:28.970 they ask the person next to them, and that is 0:17:28.970 --> 0:17:32.150 a function of them versus the other person. Now. And 0:17:32.150 --> 0:17:35.149 there's lots of people in between what this is going 0:17:35.150 --> 0:17:38.480 to do. And this is here's two extremes here. Lots 0:17:38.480 --> 0:17:43.550 of education, little ability to do the thing practically and 0:17:43.550 --> 0:17:48.649 technically versus somebody who doesn't have much training at all. Right. 0:17:48.680 --> 0:17:52.460 No exposure to the stuff, no networking, no connections. And 0:17:52.460 --> 0:17:55.520 they're just voracious. They just what? Oh, how do you 0:17:55.520 --> 0:17:57.380 do that? Whoa whoa whoa whoa. And they just jump 0:17:57.380 --> 0:17:59.930 into it and jump all over it. And they learn 0:17:59.930 --> 0:18:02.570 the stuff instantly and they're like, oh, you can just 0:18:02.570 --> 0:18:06.050 code that. Oh, well, what's the name of that Python? Oh, okay. 0:18:06.050 --> 0:18:08.689 I guess I'll go learn Python. They come back, they're like, hey, 0:18:08.690 --> 0:18:11.240 I wrote a program to do that. It's like, when 0:18:11.240 --> 0:18:13.610 did you learn Python? Oh, I didn't, I just looked on. 0:18:13.609 --> 0:18:16.010 I watched a couple of YouTube videos. I wrote a program. 0:18:16.010 --> 0:18:18.439 Some people are like that and some people are the 0:18:18.440 --> 0:18:22.609 opposite of that. This is what I is good at. 0:18:22.609 --> 0:18:24.890 It's going to be able to tell you the difference 0:18:24.890 --> 0:18:27.680 between those. So guess what? You're going to be able 0:18:27.680 --> 0:18:34.340 to filter through tens, hundreds, thousands, tens of thousands of resumes, 0:18:34.340 --> 0:18:38.090 find people like that, send them into an additional filter, 0:18:38.090 --> 0:18:41.090 which is like a live interview with like an AI 0:18:41.090 --> 0:18:44.930 avatar or whatever. It runs them through scenarios, sees how 0:18:44.930 --> 0:18:48.080 curious they are. It's going to find the magic sauce, 0:18:48.080 --> 0:18:50.390 the same magic sauce that I'm talking about right now. 0:18:50.390 --> 0:18:53.510 The AI is going to find that magic sauce. It's 0:18:53.510 --> 0:18:55.340 going to give them a score, and they're going to 0:18:55.340 --> 0:18:57.560 shoot to the top. And guess what? Everyone's going to 0:18:57.560 --> 0:19:02.120 go hire those people. Nobody wants to hire a new person. 0:19:02.119 --> 0:19:05.210 Nobody wants to train new people. This is why there 0:19:05.210 --> 0:19:08.090 is the gap in hiring. This is why so many 0:19:08.090 --> 0:19:10.130 people are getting out of college, can't find a job. 0:19:10.130 --> 0:19:13.399 It's because they're like, hey, look, I've got my degrees. 0:19:13.670 --> 0:19:15.710 Can't wait to do my training so you can teach 0:19:15.710 --> 0:19:18.080 me how to do my job. And the hiring manager 0:19:18.080 --> 0:19:20.870 is like, yeah, so about that, we're busy. We don't 0:19:20.869 --> 0:19:25.370 have time to train anybody, so we won't be hiring you. 0:19:25.400 --> 0:19:28.940 We will be hiring Caleb, who is a 15 year 0:19:28.940 --> 0:19:32.929 old who is doing this job already and has been 0:19:32.930 --> 0:19:36.080 for three years in between playing video games. And that's 0:19:36.080 --> 0:19:37.610 who we're going to hire instead of you with your 0:19:37.609 --> 0:19:43.639 master's degrees. So it'll filter for drive, curiosity, obsession, and 0:19:43.640 --> 0:19:47.420 proof of work like actual builders and coders and people 0:19:47.420 --> 0:19:50.450 who raise insightful questions that are curious. This is going 0:19:50.450 --> 0:19:54.110 to spawn a completely new type of education dedicated to 0:19:54.109 --> 0:19:58.220 making more people like the stars that I'm talking about, 0:19:58.220 --> 0:20:00.590 because a lot of the people who are dull in 0:20:00.590 --> 0:20:02.990 this way that I'm talking about, they were just let 0:20:02.990 --> 0:20:07.520 down by their maybe it's genetic, maybe they're just not 0:20:07.520 --> 0:20:11.090 as smart. Of course, there are smarter, less smart people, 0:20:11.090 --> 0:20:14.150 but I think a lot of this is cultural where 0:20:14.150 --> 0:20:18.080 you have they were just not given curiosity as a 0:20:18.080 --> 0:20:21.110 thing as they were growing up. And this is another 0:20:21.109 --> 0:20:25.160 opportunity for AI to change that education and not teach them. Oh, 0:20:25.160 --> 0:20:27.950 it's about what you can remember and instead teach them. 0:20:27.950 --> 0:20:31.190 It's about what you find interesting, right? Get that curiosity 0:20:31.190 --> 0:20:34.670 into them early, then expose them to modules of training 0:20:34.670 --> 0:20:38.359 instead of stupid curricula. Tough times for new grads. Okay, 0:20:38.359 --> 0:20:41.419 same point. Yeah, see above. And of course this is 0:20:41.420 --> 0:20:44.060 not the only factor, but yeah, hitting a wall with 0:20:44.060 --> 0:20:49.520 entry level hiring projected to drop by 5.8% in 24. Yeah, 0:20:49.520 --> 0:20:53.389 wait till you see 25 and 26 and 27. It's 0:20:53.390 --> 0:20:57.050 going to get nastier. Software engineer positions on indeed have 0:20:57.050 --> 0:21:02.780 plummeted 30% from pre-pandemic levels. Even with all this stuff considered, 0:21:02.780 --> 0:21:05.689 I still don't understand that number. That's ridiculous. That's got 0:21:05.690 --> 0:21:08.239 to be some macroeconomic stuff. I'll have to talk to 0:21:08.240 --> 0:21:11.000 Mike about that. I don't know all the inputs coming in. 0:21:11.000 --> 0:21:14.359 I think the thing I'm describing is one of those inputs, 0:21:14.359 --> 0:21:16.880 but I don't know how that accounts for 30%. So 0:21:16.880 --> 0:21:22.430 obviously multifactorial is college overrated? Nearly 30% of Americans are 0:21:22.430 --> 0:21:25.910 questioning the value of college, according to a recent Pew poll. 0:21:25.910 --> 0:21:32.990 Once again, see above. Job hopping not just flaky, but strategic. Yeah, yeah, 0:21:32.990 --> 0:21:34.699 I wrote this here. You're wondering why I say I 0:21:34.700 --> 0:21:38.540 wrote this. I helps with this sometimes. Write some of 0:21:38.540 --> 0:21:43.010 these sentences. Some portion of this could be I written 0:21:43.010 --> 0:21:45.980 a lot of these I write myself or I have 0:21:45.980 --> 0:21:48.110 to go and edit them just because I don't like 0:21:48.109 --> 0:21:50.690 what the AI writes. So I have to do it myself. 0:21:50.690 --> 0:21:53.180 Like I had to write this whole thing. I think 0:21:53.180 --> 0:21:55.489 not because they're flaky, but because they're in search of 0:21:55.490 --> 0:21:58.580 a culture that matches their drive. Sticking it out in 0:21:58.580 --> 0:22:01.730 a toxic work environment can dole a high performance edge. 0:22:01.730 --> 0:22:05.870 I think that might be I right there. Can't actually remember. 0:22:05.869 --> 0:22:08.810 My AI is getting so good that. A it actually 0:22:08.810 --> 0:22:14.209 copies me pretty well. I definitely write everything in the blue. 100% yeah. 0:22:14.210 --> 0:22:18.200 So here's my main point for truly top performers. It's 0:22:18.200 --> 0:22:21.080 not bad to see them jump every 3 to 4 years. 0:22:21.080 --> 0:22:24.560 Hiring managers know they get bored quickly and that they 0:22:24.560 --> 0:22:28.100 can probably solve a bunch of problems, and then they 0:22:28.100 --> 0:22:29.899 just leave because they want to solve a new challenge. 0:22:29.900 --> 0:22:32.030 And plus they got a little bit of their stock payout. 0:22:32.450 --> 0:22:35.419 I know tons of people like this, like star programmers, 0:22:35.420 --> 0:22:38.149 and they just bounce around and nobody really cares because 0:22:38.150 --> 0:22:40.040 they're just happy to have them when they show up. 0:22:40.340 --> 0:22:44.450 It doesn't work for the whatever. 30 years ago IBM employee, 0:22:44.450 --> 0:22:47.630 they'll be like, oh, you left after seven years, why 0:22:47.630 --> 0:22:50.119 are your pants on fire or whatever? All right. So 0:22:50.119 --> 0:22:52.969 now they're saying avoiding the sun might actually be a 0:22:52.970 --> 0:22:56.389 risk factor. Yeah. So get too much sun. You'll die. 0:22:56.390 --> 0:22:59.690 Don't get enough sun. You'll die. Punchline. You'll die. I 0:22:59.690 --> 0:23:02.840 definitely believe this. I think there's value to this whole like, 0:23:02.840 --> 0:23:07.610 get sun touch grass thing grounding. Get in touch with nature, whatever. Yeah, 0:23:07.609 --> 0:23:11.929 definitely true for me, anecdotally and possibly anecdotally as well. 0:23:11.930 --> 0:23:14.420 I think we need more science on this. More people 0:23:14.420 --> 0:23:17.420 are doing marijuana than drinking now. I guess we could 0:23:17.420 --> 0:23:19.910 take that as a win. That drinking is down because 0:23:19.910 --> 0:23:23.390 Uberman said alcohol is poison. He also went pretty hard 0:23:23.390 --> 0:23:27.710 on cannabis as far as I can remember. Psychedelics as painkillers. Yeah, 0:23:27.710 --> 0:23:30.920 this is getting a lot of press. One third of 0:23:30.920 --> 0:23:35.570 Amazon warehouse workers are on food stamps or Medicaid. That 0:23:35.570 --> 0:23:38.690 is not a good number one file to rule them all. 0:23:38.690 --> 0:23:44.900 One massive, sprawling text file I am in favor of. Text. 0:23:44.900 --> 0:23:49.040 Text is my favorite. I love large files, broken down, 0:23:49.040 --> 0:23:53.900 markdown bullets. Super clear, easy to read. I love this 0:23:53.900 --> 0:23:57.170 whole vibe, and I'm using it for fabric and managing 0:23:57.170 --> 0:24:01.010 my own internal context and everything. US Justice Department is 0:24:01.010 --> 0:24:05.840 gearing up to dismantle the Live Nation Ticketmaster giant. Hallelujah! 0:24:05.840 --> 0:24:10.220 So overdue. And thank you for Taylor Swift, because I 0:24:10.220 --> 0:24:12.740 think she had something to do with this. California is 0:24:12.740 --> 0:24:16.909 getting over a quarter of its energy from sun soared. 0:24:16.910 --> 0:24:19.609 Finding is not what you think. An argument from one 0:24:19.609 --> 0:24:23.150 expert claiming everything we know about sword fighting is bad. 0:24:23.330 --> 0:24:26.450 It's my favorite Paul Graham essay. Great work happens by 0:24:26.450 --> 0:24:32.180 focusing consistently on something you're genuinely interested in. I love 0:24:32.180 --> 0:24:36.590 this sentence. When you pause to take stock, you're surprised 0:24:36.590 --> 0:24:39.590 how far you've come. Paul Graham is one of my 0:24:39.590 --> 0:24:43.550 favorite essayists ever, and this is one of my favorite ones. 0:24:43.550 --> 0:24:45.590 I think it's called Great Work or How to Do 0:24:45.590 --> 0:24:47.570 Great Work is the name of the essay should have 0:24:47.570 --> 0:24:50.239 linked it here. This rhymes with a realization I've been 0:24:50.240 --> 0:24:52.879 having lately that the best leaders and founders have something 0:24:52.880 --> 0:24:55.220 in common, which is like we were talking about before, 0:24:55.220 --> 0:24:58.760 actually obsession. It's not that they're disciplined, or they might be, 0:24:58.760 --> 0:25:01.550 and they probably are, but they just might be obsessed, 0:25:01.550 --> 0:25:04.610 which tends to look a lot like discipline because they 0:25:04.609 --> 0:25:08.720 both produce consistent effort in a uniform direction. I find 0:25:08.720 --> 0:25:12.200 myself increasingly looking for people who are obsessed with things, 0:25:12.200 --> 0:25:15.709 life and idea, whatever. They can't stop thinking about it. 0:25:15.710 --> 0:25:18.680 And the million different ideas they have tend to revolve 0:25:18.680 --> 0:25:22.070 around that same concept. It's one that my buddy Joel 0:25:22.070 --> 0:25:25.399 Paris sent me the link to. This is cool. Nostalgia 0:25:25.400 --> 0:25:27.260 tends to peak at a single age, and I think 0:25:27.260 --> 0:25:30.350 this is either Pew or Gallup. I mix the two up, 0:25:30.350 --> 0:25:33.290 but if you draw the line, it's somewhere like right here, 0:25:33.290 --> 0:25:37.550 and that's around 15. Yeah, 15 years old, 18 years 0:25:37.550 --> 0:25:40.910 old or whatever. And guess what? The most close knit 0:25:40.910 --> 0:25:44.450 community is the most moral society, the least political division, 0:25:44.450 --> 0:25:48.740 the happiest families, the most reliable news reporting. It all 0:25:48.740 --> 0:25:53.480 happens when you're 18 years old. So regardless of your age, 0:25:53.480 --> 0:25:56.899 whenever you were 18, that's when you think the Golden 0:25:56.900 --> 0:26:02.389 Age was brilliant. Data visualization recommendation of the week. Become 0:26:02.390 --> 0:26:05.990 able to articulate who you are and what you're about 0:26:05.990 --> 0:26:09.379 in 25 to 50 words. And the aphorism of the 0:26:09.380 --> 0:26:14.030 week fall seven times. Stand up eight, fall seven times. 0:26:14.030 --> 0:26:19.590 Stand up eight. Japanese proverb. Unsupervised Learning is produced and 0:26:19.590 --> 0:26:23.130 edited by Daniel Meisler on a Neumann U87 AI microphone 0:26:23.130 --> 0:26:27.119 using Hindenburg. Intro and outro music is by zombie with 0:26:27.119 --> 0:26:29.940 the why and to get the text and links from 0:26:29.940 --> 0:26:32.070 this episode, sign up for the newsletter version of the 0:26:32.070 --> 0:26:37.610 show at Daniel meisler.com/newsletter. We'll see you next time.