1 00:00:00,050 --> 00:00:03,470 S1: Whether you're starting or scaling your company's security program, demonstrating 2 00:00:03,500 --> 00:00:07,010 S1: top notch security practices and establishing trust is more important 3 00:00:07,010 --> 00:00:12,139 S1: than ever. Vanta automates compliance for Soc2, ISO 27,001 and more, 4 00:00:12,140 --> 00:00:16,100 S1: saving you time and money while helping you build customer trust. Plus, 5 00:00:16,100 --> 00:00:20,360 S1: you can streamline security reviews by automating questionnaires and demonstrating 6 00:00:20,360 --> 00:00:24,079 S1: your security posture with a customer facing trust center, all 7 00:00:24,079 --> 00:00:28,640 S1: powered by advanced AI. Over 7000 global companies like Atlassian, 8 00:00:28,640 --> 00:00:31,780 S1: Flow Health and Quora use Vanta to manage risk and 9 00:00:31,780 --> 00:00:35,770 S1: prove security in real time. Get $1,000 off Vanta when 10 00:00:35,770 --> 00:00:42,190 S1: you go to Vanta comm slash unsupervised. That's vanta.com/supervised for 11 00:00:42,190 --> 00:00:47,290 S1: $1,000 off. Welcome to Unsupervised Learning, a security, AI, and 12 00:00:47,290 --> 00:00:50,019 S1: meaning focused podcast that looks at how best to thrive 13 00:00:50,020 --> 00:00:54,310 S1: as humans in a post AI world. It combines original ideas, 14 00:00:54,310 --> 00:00:57,820 S1: analysis and mental models to bring not just the news, 15 00:00:57,820 --> 00:01:05,319 S1: but why it matters and how to respond. All right, 16 00:01:05,319 --> 00:01:08,350 S1: welcome to unsupervised learning. This is Daniel Miessler. Okay. Leigh 17 00:01:08,380 --> 00:01:13,000 S1: Honeywell had probably the best or coolest little quote here about, uh, 18 00:01:13,000 --> 00:01:17,470 S1: the CrowdStrike incident. Any sufficiently bad software update is indistinguishable 19 00:01:17,470 --> 00:01:20,340 S1: from a cyberattack. Love that. Had a wonderful couple of 20 00:01:20,340 --> 00:01:24,179 S1: days celebrating my buddy Jason's birthday, and it's actually coming 21 00:01:24,180 --> 00:01:27,090 S1: up on the 27th and mine is on the 26th, 22 00:01:27,090 --> 00:01:29,730 S1: so it's a little bit in the future. But we 23 00:01:29,730 --> 00:01:32,040 S1: celebrated last weekend and it was super fun. Did a 24 00:01:32,040 --> 00:01:34,590 S1: presentation for a UN group on the future of AI 25 00:01:34,590 --> 00:01:38,429 S1: and employability, and that should be coming out soon to YouTube. 26 00:01:38,430 --> 00:01:41,910 S1: So look for that soon. Doing another UL dinner in Vegas. 27 00:01:41,910 --> 00:01:44,100 S1: This is going to be cool. Mad props to all 28 00:01:44,100 --> 00:01:46,590 S1: the people who had to hustle and grind this weekend 29 00:01:46,590 --> 00:01:49,770 S1: as a result of Blue Friday, and let's get into it. 30 00:01:49,770 --> 00:01:51,870 S1: So I've been mostly heads down on the class, so 31 00:01:51,870 --> 00:01:56,730 S1: I haven't written any new essays. Security, CrowdStrike. Outage I 32 00:01:56,730 --> 00:02:00,180 S1: think we all know the deal at this point. Banks, airlines, hospitals, 33 00:02:00,180 --> 00:02:05,250 S1: media companies. It was probably the largest IT outage. I 34 00:02:05,250 --> 00:02:08,140 S1: think it's probably up for debate and people are probably 35 00:02:08,139 --> 00:02:10,450 S1: still talking about it. So I'm trying to come up 36 00:02:10,450 --> 00:02:12,700 S1: with that. Lessons learned here. But perhaps the biggest one 37 00:02:12,700 --> 00:02:16,750 S1: is around PR. So at first the CEO came out 38 00:02:16,750 --> 00:02:20,800 S1: and basically said something like, don't worry, this isn't a 39 00:02:20,800 --> 00:02:25,119 S1: security problem, and that's not the way to go because 40 00:02:25,120 --> 00:02:27,910 S1: the internet's basically down as a result of you. So 41 00:02:27,910 --> 00:02:29,980 S1: I don't think that was the right stance to take. 42 00:02:29,980 --> 00:02:33,079 S1: He did much better later on. I think his subsequent 43 00:02:33,080 --> 00:02:36,980 S1: posts were much better, and where he eventually landed was great. But, um, 44 00:02:36,980 --> 00:02:39,110 S1: I like what my buddy Chris Hoff said about it, 45 00:02:39,110 --> 00:02:42,020 S1: which was, uh, this was not a security attack against 46 00:02:42,020 --> 00:02:45,170 S1: CrowdStrike or its customers, but an outage caused by a 47 00:02:45,169 --> 00:02:49,070 S1: bad software update. And this was just he was proposing 48 00:02:49,070 --> 00:02:53,299 S1: a possible option to to what was actually said. And 49 00:02:53,300 --> 00:02:56,100 S1: I like this take by Chris. And Chris has been 50 00:02:56,100 --> 00:02:59,580 S1: a CISO, uh, through some pretty rough times. So he 51 00:02:59,580 --> 00:03:02,250 S1: knows the deal. And another thought I had is that 52 00:03:02,250 --> 00:03:05,970 S1: this would be probably much less likely to happen if, say, 53 00:03:05,970 --> 00:03:10,170 S1: everything was Microsoft, right? If the EDR was just part 54 00:03:10,169 --> 00:03:14,370 S1: of Microsoft. Kind of similar to the way that defender 55 00:03:14,370 --> 00:03:16,919 S1: is getting so good that it's almost as good as 56 00:03:16,919 --> 00:03:19,850 S1: any third party option. And I think this is the 57 00:03:19,850 --> 00:03:23,930 S1: natural flow, right? You start off with a cool app idea. 58 00:03:23,930 --> 00:03:27,620 S1: It eventually becomes like a big company, and eventually that 59 00:03:27,620 --> 00:03:29,750 S1: moves into the platform. And you see that with all 60 00:03:29,750 --> 00:03:34,520 S1: sorts of things like location services, antivirus and stuff like that. 61 00:03:34,520 --> 00:03:37,100 S1: So I think that's likely to just happen with EDR 62 00:03:37,100 --> 00:03:40,280 S1: as well. And the whole point is, maybe Microsoft would 63 00:03:40,280 --> 00:03:43,660 S1: have handled that better or avoided it if the testing 64 00:03:43,660 --> 00:03:46,960 S1: and everything like that was more deeply integrated with the 65 00:03:46,960 --> 00:03:49,450 S1: OS itself, because they are the OS and they are 66 00:03:49,450 --> 00:03:52,840 S1: the other one. Now with this, you actually get a 67 00:03:52,840 --> 00:03:57,400 S1: different problem, which is more eggs in fewer baskets, right? 68 00:03:57,400 --> 00:04:00,910 S1: So there's a trade off there. But I feel like 69 00:04:00,910 --> 00:04:03,970 S1: this is the natural trend to basically have everything that's 70 00:04:03,970 --> 00:04:06,760 S1: awesome eventually end up in the platform itself. Got a 71 00:04:06,760 --> 00:04:10,300 S1: new threat actor called Crystal Ray using open source tool 72 00:04:10,300 --> 00:04:15,760 S1: called SSH snake to move laterally across networks, exfiltrate credentials 73 00:04:15,760 --> 00:04:19,420 S1: and deploy crypto mining software. GitHub has warned developers about 74 00:04:19,420 --> 00:04:24,700 S1: a social engineering campaign by Lazarus, which is North Korean group, 75 00:04:24,700 --> 00:04:29,740 S1: and they're targeting developers in cryptocurrency gambling and cybersecurity. And 76 00:04:29,740 --> 00:04:31,750 S1: essentially what they do is kind of what happened with 77 00:04:31,750 --> 00:04:35,280 S1: the Linux attack recently. They gained trust over time, and 78 00:04:35,279 --> 00:04:38,279 S1: then they start submitting malware once you trust them to 79 00:04:38,279 --> 00:04:42,300 S1: submit things. Special thanks to sponsor dropzone. And I wrote 80 00:04:42,300 --> 00:04:45,270 S1: this copy myself here, which I'm not going to read here, 81 00:04:45,270 --> 00:04:49,409 S1: but definitely check out dropzone dot I and check out 82 00:04:49,410 --> 00:04:52,200 S1: a demo there. So not only are they sponsoring here, 83 00:04:52,200 --> 00:04:55,440 S1: but I'm actually an advisor for them as well. That's 84 00:04:55,440 --> 00:04:58,099 S1: how much I believe in their stuff. Palmer Luckey, the 85 00:04:58,100 --> 00:05:01,040 S1: guy who created Oculus, is now making AI weapons for 86 00:05:01,040 --> 00:05:05,330 S1: Ukraine through his company Anduril think it's Anduril that looks 87 00:05:05,330 --> 00:05:07,489 S1: like a Lord of the rings or some kind of 88 00:05:07,490 --> 00:05:12,170 S1: fantasy thing. See if this identifies it. Open source? Nope. 89 00:05:12,170 --> 00:05:14,870 S1: Can't identify it. All right. Yeah. So he started Anduril 90 00:05:14,900 --> 00:05:18,260 S1: to build AI driven weapons like drones and submarines, but 91 00:05:18,260 --> 00:05:22,000 S1: they're now being used by the Pentagon and sent to Ukraine. 92 00:05:22,029 --> 00:05:25,510 S1: China is installing massive amounts of solar and wind energy, 93 00:05:25,510 --> 00:05:31,240 S1: adding ten gigawatts of wind and solar capacity every two weeks, 94 00:05:31,510 --> 00:05:36,070 S1: which is like building five large nuclear plants every week. 95 00:05:36,070 --> 00:05:39,370 S1: And this really, really makes me mad because I, the 96 00:05:39,370 --> 00:05:41,740 S1: US needs to be doing this. Every time I fly. 97 00:05:41,740 --> 00:05:45,219 S1: I fly over wide open country that is getting hit 98 00:05:45,220 --> 00:05:48,700 S1: by the sun. And it's windy down there and it's like, oh, 99 00:05:48,700 --> 00:05:51,339 S1: we don't have enough jobs for people and we don't 100 00:05:51,339 --> 00:05:54,010 S1: have enough energy, and we have way too much open 101 00:05:54,010 --> 00:05:57,219 S1: land being hit by the sun and wind. Why can 102 00:05:57,220 --> 00:06:00,430 S1: we not do this, especially when we know that AI 103 00:06:00,430 --> 00:06:02,740 S1: is going to need all this energy and we just 104 00:06:02,740 --> 00:06:04,989 S1: we need to put people to work and we need 105 00:06:04,990 --> 00:06:08,409 S1: the energy, and we have the wide open space and 106 00:06:08,410 --> 00:06:11,370 S1: we need to build more housing. So it's like this 107 00:06:11,370 --> 00:06:16,740 S1: is the perfect opportunity for a massive, like FDR type event, 108 00:06:16,740 --> 00:06:21,300 S1: which hopefully the next president gets on this because yeah, 109 00:06:21,300 --> 00:06:24,810 S1: I do not like the idea of China having all 110 00:06:24,810 --> 00:06:27,510 S1: this extra energy to do whatever with and us not 111 00:06:27,510 --> 00:06:30,839 S1: having it. Iran and China are increasing their foreign influence efforts, 112 00:06:30,839 --> 00:06:35,089 S1: using social media to stoke discord and promote anti-U.S. narratives. 113 00:06:35,089 --> 00:06:36,920 S1: And this is coming out of Google. They blocked over 114 00:06:36,920 --> 00:06:42,020 S1: 10,000 instances of Chinese influence activity in Q1 alone, thanks 115 00:06:42,020 --> 00:06:45,110 S1: to Nudge Security for sponsoring the US Department of Justice, 116 00:06:45,110 --> 00:06:49,310 S1: seize two domains and search nearly 1000 social media accounts 117 00:06:49,310 --> 00:06:54,740 S1: used by Russian actors to spread pro-Kremlin disinformation. Cloudflare says 118 00:06:54,740 --> 00:06:58,360 S1: nearly 7% of all internet traffic is malicious, with DDoS 119 00:06:58,360 --> 00:07:03,400 S1: attacks making up over 37% of all mitigated traffic. And 120 00:07:03,400 --> 00:07:06,339 S1: UK police arrested a 17 year old suspect of being 121 00:07:06,339 --> 00:07:10,030 S1: part of the scattered spider hacking group involved in the 122 00:07:10,030 --> 00:07:15,190 S1: 2023 MGM resorts ransomware attack, also known as this is 123 00:07:15,190 --> 00:07:19,480 S1: the person responsible or the group responsible for making Defcon 124 00:07:19,480 --> 00:07:23,180 S1: way farther north this year. It's now in the convention center, 125 00:07:23,270 --> 00:07:25,940 S1: pretty far north of the city, which it looks like 126 00:07:25,940 --> 00:07:29,090 S1: it's going to be pretty cool, especially for the different villages, 127 00:07:29,090 --> 00:07:31,250 S1: because all the villages are going to be together. Looking 128 00:07:31,250 --> 00:07:35,630 S1: forward to that real time video transcription with timestamps. Whisper 129 00:07:35,630 --> 00:07:41,060 S1: Diarization Diarization. Yeah, that's right, Beijing support has seen China 130 00:07:41,060 --> 00:07:43,760 S1: make up ground in the AI race, but it still 131 00:07:43,760 --> 00:07:47,700 S1: has handcuffed a bunch of AI Companies with really tight 132 00:07:47,700 --> 00:07:51,480 S1: restrictions and a lot of these are just purely political. 133 00:07:51,480 --> 00:07:54,720 S1: So they're basically saying this is going to be good 134 00:07:54,720 --> 00:07:58,590 S1: for control and bad for speed. So I think unless 135 00:07:58,590 --> 00:08:01,530 S1: they steal some sort of pinnacle AI tech, which they 136 00:08:01,530 --> 00:08:04,650 S1: probably are going to, as per Leopold and as per 137 00:08:04,650 --> 00:08:07,200 S1: a lot of people talking about this, I think ultimately, 138 00:08:07,200 --> 00:08:11,430 S1: if that doesn't happen, this closed nature of their approach 139 00:08:11,430 --> 00:08:14,520 S1: to AI is going to hurt them, especially relative to 140 00:08:14,520 --> 00:08:16,860 S1: the US, which is just running with scissors, which you 141 00:08:16,860 --> 00:08:20,940 S1: can see because, um, meta just released llama three, uh, 142 00:08:20,940 --> 00:08:23,880 S1: 405 B today and is basically giving it out to 143 00:08:23,880 --> 00:08:26,280 S1: the world. And by the way, it's not fully open source, 144 00:08:26,280 --> 00:08:30,480 S1: but it's much more open source than other pinnacle models. 145 00:08:30,480 --> 00:08:34,380 S1: But anyway, that stuff is coming out quickly. And so 146 00:08:34,380 --> 00:08:37,820 S1: the US is innovating very, very fast. And you can't 147 00:08:37,820 --> 00:08:39,920 S1: do that when you're China. And you have to be 148 00:08:39,920 --> 00:08:42,470 S1: very careful what you put in the model. Because if 149 00:08:42,470 --> 00:08:46,130 S1: you train the model on open knowledge, the model is 150 00:08:46,130 --> 00:08:49,040 S1: going to figure out how reality actually is. And China 151 00:08:49,040 --> 00:08:51,830 S1: doesn't want to present the world as it actually is. 152 00:08:51,830 --> 00:08:54,830 S1: They want to present the filtered version of the world, 153 00:08:54,830 --> 00:08:58,160 S1: which means they have to do so much more protection and, 154 00:08:58,160 --> 00:09:03,130 S1: you know, post-training tricks or, um, nuking the knowledge inside 155 00:09:03,130 --> 00:09:07,120 S1: of the, the training data to not have the real 156 00:09:07,120 --> 00:09:09,280 S1: knowledge of the world. That's another way to do it, 157 00:09:09,280 --> 00:09:11,770 S1: to train the model and have it just be worse. 158 00:09:11,770 --> 00:09:14,560 S1: It'll just be worse. It'll be a worse representation of 159 00:09:14,559 --> 00:09:18,640 S1: actual reality. It'll be like, yeah, Tiananmen never happened or whatever. So, 160 00:09:18,640 --> 00:09:22,720 S1: you know, they're not oppressive. The US is bad. You know, 161 00:09:22,720 --> 00:09:25,679 S1: they are the true free society or whatever kind of 162 00:09:25,679 --> 00:09:28,349 S1: garbage they want to, you know, put in there. But 163 00:09:28,350 --> 00:09:32,189 S1: that's extra work for them. That's extra friction for them, 164 00:09:32,190 --> 00:09:35,219 S1: that's going to slow them down. And so that's one thing. 165 00:09:35,220 --> 00:09:37,260 S1: It's going to be slower. The second thing is the 166 00:09:37,260 --> 00:09:39,270 S1: people who want to go fast, who are in China. 167 00:09:39,270 --> 00:09:41,070 S1: So they're super smart and they want to go fast 168 00:09:41,070 --> 00:09:44,430 S1: and they're more like Western oriented. They're just going to leave. 169 00:09:44,429 --> 00:09:46,890 S1: They're going to go go to the US, to Canada, 170 00:09:46,890 --> 00:09:49,340 S1: to EU. Not all of them, of course, but a 171 00:09:49,340 --> 00:09:52,670 S1: lot of them. So ultimately this makes you slower as 172 00:09:52,670 --> 00:09:56,179 S1: China the country. And it also produces more brain drain 173 00:09:56,179 --> 00:09:58,670 S1: because people don't want to be there. Kaiser Permanente is 174 00:09:58,670 --> 00:10:02,030 S1: using AI, wearables and other tech to bring health care 175 00:10:02,030 --> 00:10:05,689 S1: directly to patients. Very AI forward approach from them, which 176 00:10:05,690 --> 00:10:08,090 S1: I really appreciate. It's all in the implementation, of course, 177 00:10:08,090 --> 00:10:10,520 S1: so we'll see how that goes. But I like the 178 00:10:10,520 --> 00:10:14,120 S1: open mind. Sam Altman revealed that OpenAI's Voice Alpha mode 179 00:10:14,120 --> 00:10:17,300 S1: release is coming later this month, and llama three one 180 00:10:17,300 --> 00:10:19,910 S1: just came out today, so you know they really need 181 00:10:19,910 --> 00:10:22,220 S1: to speed that up. And I love what my buddy 182 00:10:22,220 --> 00:10:25,490 S1: Matthew Berman said about this. He's a YouTube AI guy 183 00:10:25,490 --> 00:10:30,050 S1: and he says, let's denormalize companies demoing products earlier than 184 00:10:30,050 --> 00:10:33,860 S1: three months before release. So Microsoft Recall did this. Apple 185 00:10:33,860 --> 00:10:37,720 S1: intelligence did this definitely, because it's not coming out until 186 00:10:37,720 --> 00:10:43,120 S1: like after September, maybe even not until beginning of 2025. 187 00:10:43,120 --> 00:10:47,080 S1: And OpenAI did this big demo on Sora and GPT 188 00:10:47,080 --> 00:10:49,840 S1: for voice, and it's still not out yet. And that 189 00:10:49,840 --> 00:10:51,910 S1: was a long time ago. I mean, that was ancient 190 00:10:51,910 --> 00:10:54,490 S1: history at this point. So yeah, three months, I think 191 00:10:54,490 --> 00:10:56,410 S1: is like the max. You should do that. Don't even 192 00:10:56,410 --> 00:10:59,140 S1: talk about it if it's not coming out. Andre Karpathy 193 00:10:59,140 --> 00:11:03,930 S1: is launching Eureka Labs to create AI teaching assistants for education. 194 00:11:03,929 --> 00:11:06,240 S1: And yeah, this is going to be really cool. They're 195 00:11:06,240 --> 00:11:10,110 S1: basically going to have AI teachers, which is just fantastic. 196 00:11:10,110 --> 00:11:13,410 S1: Google has launched Project Oscar, open source platform that enables 197 00:11:13,410 --> 00:11:16,949 S1: development teams to create AI agents that monitor issues, manage 198 00:11:16,950 --> 00:11:20,640 S1: bugs and handle various aspects of the software lifecycle. Omega's 199 00:11:20,640 --> 00:11:24,300 S1: AI will map how Olympic athletes win. They're using AI 200 00:11:24,320 --> 00:11:28,580 S1: to map how Olympic athletes win by analyzing their full performance, 201 00:11:28,580 --> 00:11:31,970 S1: not just start and finish times. That includes motion sensors 202 00:11:31,970 --> 00:11:35,150 S1: on athletes clothing to capture every detail of their movements. 203 00:11:35,150 --> 00:11:39,229 S1: Compelling us is thinking about new trade restrictions that can 204 00:11:39,230 --> 00:11:44,210 S1: stop Nvidia from selling its HG, H20, AI GPUs to China, 205 00:11:44,210 --> 00:11:46,699 S1: and people are worried. Investors are worried that it could 206 00:11:46,700 --> 00:11:50,720 S1: cost Nvidia like $12 billion in revenue because, you know, 207 00:11:50,720 --> 00:11:52,640 S1: China is big and they buy a lot of stuff 208 00:11:52,640 --> 00:11:55,490 S1: if they're allowed to. But I don't think that'll ultimately 209 00:11:55,490 --> 00:11:58,699 S1: matter for that long. So not too worried. As an 210 00:11:58,700 --> 00:12:03,920 S1: Nvidia stockholder, Beijing scientists have developed the world's smallest and 211 00:12:03,920 --> 00:12:11,330 S1: lightest solar powered drone just 4.21g with a 200 millimeter wingspan. 212 00:12:11,330 --> 00:12:14,740 S1: I want one of these. They can fly nonstop during 213 00:12:14,740 --> 00:12:18,849 S1: the day because the motor is lighter and more efficient, 214 00:12:18,850 --> 00:12:22,630 S1: and because the thing is so light itself, the actual 215 00:12:22,630 --> 00:12:24,970 S1: craft is so light itself. I would love to mess 216 00:12:24,970 --> 00:12:30,670 S1: with that. A Florida yeah, it's usually either Florida man. Yeah, 217 00:12:30,670 --> 00:12:35,229 S1: a Florida man. It's it's either a Florida man or DNS. 218 00:12:35,260 --> 00:12:39,780 S1: They're responsible for all problems. Uh, this person got arrested 219 00:12:39,780 --> 00:12:43,380 S1: for shooting down a Walmart delivery drone claiming it was 220 00:12:43,380 --> 00:12:46,650 S1: spying on him. Typical of Florida men, shooting at drones 221 00:12:46,650 --> 00:12:49,140 S1: is treated as a felony, similar to firing at a 222 00:12:49,140 --> 00:12:53,790 S1: passenger aircraft. That's probably because the bullets keep going and 223 00:12:53,790 --> 00:12:57,120 S1: might hit other things in the air. Unlikely, but turns 224 00:12:57,120 --> 00:13:00,329 S1: out they they don't launch off into orbit or move 225 00:13:00,330 --> 00:13:03,199 S1: towards the sun. They just fall down, potentially on people's 226 00:13:03,200 --> 00:13:06,020 S1: heads or their pets or whatever. Waymo wants to bring 227 00:13:06,020 --> 00:13:09,920 S1: robotaxis to SFO. They already have approval in the city, 228 00:13:09,920 --> 00:13:12,890 S1: but they need separate approval for the airport. And Microsoft 229 00:13:12,890 --> 00:13:16,310 S1: is laid off. Their Dei team, probably one of them. 230 00:13:16,309 --> 00:13:19,880 S1: I assume there's many, many, but laid off its Dei 231 00:13:19,910 --> 00:13:23,270 S1: team saying it's no longer business critical. I'm not sure 232 00:13:23,270 --> 00:13:26,630 S1: if this no longer business critical is an actual quote 233 00:13:26,630 --> 00:13:30,560 S1: from Microsoft leadership. It must be because this article, which 234 00:13:30,559 --> 00:13:35,900 S1: is a Business Insider article, probably quoted that correctly. But okay. 235 00:13:35,900 --> 00:13:39,710 S1: I mean, I think the overall sentiment is worth noting, 236 00:13:39,710 --> 00:13:41,810 S1: which is a lot of people are doing this. A 237 00:13:41,809 --> 00:13:45,230 S1: lot of people are rolling back Dei as like a 238 00:13:45,230 --> 00:13:49,370 S1: prime directive and realizing it should be about merit, which 239 00:13:49,370 --> 00:13:51,940 S1: I think is a good thing. I just don't want 240 00:13:51,940 --> 00:13:55,570 S1: them to go back to just hiring people that look 241 00:13:55,570 --> 00:13:58,870 S1: like you and sound like you, and respond to questions 242 00:13:58,870 --> 00:14:01,719 S1: like you, because then you get rid of diversity, which 243 00:14:01,720 --> 00:14:06,100 S1: is actually bad because you end up with like these, 244 00:14:06,130 --> 00:14:08,650 S1: these blinders. And you have to make sure that your 245 00:14:08,650 --> 00:14:13,209 S1: meritocracy is has a wide enough top of filter, right, 246 00:14:13,210 --> 00:14:15,209 S1: top of funnel. So you want to make sure you're 247 00:14:15,210 --> 00:14:19,440 S1: getting everyone there into this meritocracy filter and not just 248 00:14:19,440 --> 00:14:22,920 S1: looking for certain types of people because you think they, um, 249 00:14:22,920 --> 00:14:25,650 S1: they come out of the bottom of the filter more often. Right? 250 00:14:25,650 --> 00:14:30,150 S1: So I think the concept of Dei is 100% correct, 251 00:14:30,150 --> 00:14:34,260 S1: and we need to 100% keep doing it. The implementation 252 00:14:34,260 --> 00:14:36,960 S1: that we've done over the last few years has been bad, 253 00:14:36,960 --> 00:14:40,610 S1: and it's good to see that rolling back. Andreessen Horowitz 254 00:14:40,610 --> 00:14:43,460 S1: argues that bad government policies are now the biggest threat 255 00:14:43,460 --> 00:14:46,400 S1: to tech startups, which they call little tech. And they 256 00:14:46,400 --> 00:14:49,940 S1: basically launched a manifesto about little tech. And I did 257 00:14:49,940 --> 00:14:52,670 S1: an analysis of it in fabric. Probably should have included that. 258 00:14:52,670 --> 00:14:57,500 S1: But it's basically pro startup stuff that's bottom line, which 259 00:14:57,500 --> 00:15:00,530 S1: makes sense because they're a VC. Essentially, Google is shutting 260 00:15:00,530 --> 00:15:04,580 S1: down its URL shortening service. so any links created with 261 00:15:04,580 --> 00:15:07,040 S1: it will stop working. If you have any important links 262 00:15:07,040 --> 00:15:09,620 S1: using the service, you want to migrate them. I'm pretty 263 00:15:09,620 --> 00:15:12,980 S1: sure Google will soon sell YouTube to like Johnson and 264 00:15:12,980 --> 00:15:16,160 S1: Johnson and Gmail to Luxottica, and then go full speed 265 00:15:16,160 --> 00:15:20,720 S1: into the what the f are we doing business? Whatever 266 00:15:20,720 --> 00:15:25,100 S1: business that is, it's the single most perplexing company like 267 00:15:25,100 --> 00:15:27,460 S1: I've ever seen. They were first on j'en ai. They 268 00:15:27,460 --> 00:15:30,970 S1: wrote the paper for Transformers, and now they're completely lapped 269 00:15:30,970 --> 00:15:34,600 S1: by not just OpenAI, but anthropic as well. And now 270 00:15:34,600 --> 00:15:39,520 S1: they're being lapped by meta, by meta in an open 271 00:15:39,520 --> 00:15:42,280 S1: source model. How are you like fifth place when you 272 00:15:42,280 --> 00:15:44,590 S1: have all the people and all the money and you 273 00:15:44,590 --> 00:15:47,740 S1: actually invented the tech? They're like the opposite of Cloudflare, 274 00:15:47,740 --> 00:15:51,010 S1: which does small things really well that add up over 275 00:15:51,010 --> 00:15:54,910 S1: time because Google is like slowly dismantling everything. It's getting 276 00:15:54,910 --> 00:15:56,680 S1: rid of all the best things that it has. The 277 00:15:56,680 --> 00:16:00,070 S1: main thing Google is growing is the Google graveyard. Such 278 00:16:00,070 --> 00:16:03,610 S1: a colossal waste of money and talent. And these failures 279 00:16:03,610 --> 00:16:06,340 S1: should be studied for centuries as an example of what 280 00:16:06,340 --> 00:16:10,270 S1: happens when you don't lead with UX focused product management. 281 00:16:10,270 --> 00:16:13,900 S1: Product management, like being in charge, like thinking about the 282 00:16:13,900 --> 00:16:17,220 S1: customer and the total package and the total experience of 283 00:16:17,220 --> 00:16:20,160 S1: this product or service that you're launching, as opposed to 284 00:16:20,190 --> 00:16:23,610 S1: throw shit at the wall. Focused engineering and engineering is 285 00:16:23,610 --> 00:16:26,820 S1: in charge of product. It makes no sense whatsoever. Like 286 00:16:26,820 --> 00:16:30,600 S1: like it is the most inefficient, like large organization I 287 00:16:30,600 --> 00:16:33,600 S1: can imagine that I've ever seen. All right, and Google rant, 288 00:16:33,600 --> 00:16:36,690 S1: I need a section just for Google rant. Humans. Iran 289 00:16:36,690 --> 00:16:40,010 S1: backed Houthi rebels said they were behind a drone attack 290 00:16:40,010 --> 00:16:44,060 S1: on Tel Aviv, killed one person and injured several others. 291 00:16:44,090 --> 00:16:47,720 S1: USA household income distribution by state. A Reddit user shared 292 00:16:47,720 --> 00:16:51,620 S1: a detailed visualization of household income distribution across different states 293 00:16:51,620 --> 00:16:55,040 S1: in the US. New meta analysis shows that tooth brushing 294 00:16:55,040 --> 00:16:58,880 S1: can tooth brushing. Not heard it like that kind of verb. 295 00:16:58,880 --> 00:17:02,690 S1: Is that tooth brushing? It's a gerund. Anyway, brushing your 296 00:17:02,690 --> 00:17:07,690 S1: teeth can significantly reduce hospital acquired pneumonia in ICU patients. 297 00:17:07,690 --> 00:17:12,070 S1: Simple intervention could lead to 17,000 fewer deaths each year. 298 00:17:12,070 --> 00:17:14,770 S1: This is a this is a big thing I've realized recently. Um, 299 00:17:15,010 --> 00:17:18,250 S1: or just gotten the religion on, which is all the 300 00:17:18,250 --> 00:17:22,060 S1: bacteria like in your teeth and gums, that's related to 301 00:17:22,060 --> 00:17:25,360 S1: inflammation in the body. It's also related to the heart 302 00:17:25,359 --> 00:17:28,980 S1: being in really bad shape. So, uh, really important that 303 00:17:28,980 --> 00:17:32,490 S1: you kind of treat that infection in your mouth or 304 00:17:32,490 --> 00:17:35,550 S1: the potential for infection in your mouth, like having a 305 00:17:35,550 --> 00:17:38,189 S1: disease throughout your entire body. And they're talking about it 306 00:17:38,190 --> 00:17:41,400 S1: going into the the brain as well, and just being 307 00:17:41,400 --> 00:17:45,900 S1: this state of disease in your body and really, really 308 00:17:45,900 --> 00:17:49,350 S1: focused on the mouth. So I've upped my game around 309 00:17:49,350 --> 00:17:53,070 S1: that significantly as a result. That was probably like a 310 00:17:53,070 --> 00:17:56,250 S1: year ago or whatever. Young adulthood is no longer one 311 00:17:56,250 --> 00:17:59,969 S1: of life's happiest times. Research shows that young adulthood is 312 00:17:59,970 --> 00:18:02,490 S1: now one of the most unhappy times in life, with 313 00:18:02,490 --> 00:18:07,560 S1: a significant rise in despair among people, especially women from 314 00:18:07,560 --> 00:18:10,980 S1: 18 to 25. And if you've been following my stuff, 315 00:18:10,980 --> 00:18:13,590 S1: I have lots of reasons for that which we will 316 00:18:13,590 --> 00:18:16,970 S1: not go into most of Gen Z is using TikTok 317 00:18:16,970 --> 00:18:21,950 S1: for health advice. 56% are using TikTok for wellness, diet 318 00:18:21,950 --> 00:18:25,550 S1: and fitness, 34% are relying on it as their main 319 00:18:25,550 --> 00:18:29,780 S1: source of health information. About a third ask HN, which 320 00:18:29,780 --> 00:18:33,740 S1: is Hacker News every day, feels like prison. A mid-thirties 321 00:18:33,770 --> 00:18:35,750 S1: guy in tech feels trapped in a 9 to 5 322 00:18:35,750 --> 00:18:38,540 S1: job he no longer cares about, and is struggling to 323 00:18:38,540 --> 00:18:41,600 S1: build a business on the side. This is the reason 324 00:18:41,600 --> 00:18:44,810 S1: I do unsupervised learning. This is the mission of unsupervised 325 00:18:44,810 --> 00:18:49,460 S1: learning is giving people mental models and frames and ways 326 00:18:49,460 --> 00:18:54,590 S1: to think about the world, and actual methodologies for getting 327 00:18:54,590 --> 00:18:58,460 S1: true meaning in their lives. This problem right here is 328 00:18:58,460 --> 00:19:01,310 S1: pretty much the whole game, and the way I plays 329 00:19:01,310 --> 00:19:04,010 S1: into that is I think AI is going to make 330 00:19:04,010 --> 00:19:06,990 S1: it worse as it removes jobs before we have the 331 00:19:06,990 --> 00:19:09,899 S1: ability to have it increase jobs. There's going to be 332 00:19:09,900 --> 00:19:13,140 S1: that that, uh, chasm in the middle. When that happens, 333 00:19:13,140 --> 00:19:16,350 S1: when the jobs come away, this meaning crisis is going 334 00:19:16,350 --> 00:19:19,530 S1: to get way worse. And that's what we are here for. 335 00:19:19,560 --> 00:19:21,690 S1: All right. Got a cool button here. Read the full 336 00:19:21,690 --> 00:19:25,590 S1: newsletter online. Appreciate the team doing that. Ideas. Sam Altman 337 00:19:25,619 --> 00:19:30,030 S1: is simultaneously building AGI and doing big studies on UBI. 338 00:19:30,060 --> 00:19:33,090 S1: Super obvious what he's doing, in fact. Oh, this is 339 00:19:33,090 --> 00:19:35,400 S1: kind of hot off the press here, because I just 340 00:19:35,400 --> 00:19:38,250 S1: did this analysis with fabric, and I saw a tweet 341 00:19:38,250 --> 00:19:42,150 S1: thread about this as well, the UBI study that came out. 342 00:19:42,150 --> 00:19:44,910 S1: This is not in the newsletter. This just happened this morning. 343 00:19:44,910 --> 00:19:48,510 S1: This UBI study that OpenAI put out, which was funded 344 00:19:48,510 --> 00:19:52,439 S1: by essentially Altman. It turns out at least one of 345 00:19:52,440 --> 00:19:54,890 S1: the interpretations and some of the manual work that I 346 00:19:54,890 --> 00:19:58,520 S1: just did doing AI analysis on the results, it did 347 00:19:58,520 --> 00:20:01,010 S1: not increase a lot of the things that they were 348 00:20:01,010 --> 00:20:04,730 S1: hoping their spinning it as a very positive outcome, and 349 00:20:04,730 --> 00:20:08,720 S1: I'm sure they said there is some minor positive outcomes, 350 00:20:08,720 --> 00:20:11,510 S1: but in general it did not encourage people to be 351 00:20:11,510 --> 00:20:14,330 S1: more ambitious. It did not encourage people to go and 352 00:20:14,330 --> 00:20:17,810 S1: get more work. It didn't do that. So it looks 353 00:20:17,810 --> 00:20:20,440 S1: a bit bad now. I think we need to do 354 00:20:20,440 --> 00:20:24,430 S1: more analysis to say for sure that UBI is not 355 00:20:24,430 --> 00:20:27,070 S1: going to massively help, um, or it's not going to 356 00:20:27,070 --> 00:20:31,750 S1: help people be more ambitious or more creative or more productive, 357 00:20:31,750 --> 00:20:34,240 S1: which which I think is the hope. The hope is 358 00:20:34,240 --> 00:20:37,480 S1: that or the idea here is that ambitious people are 359 00:20:37,480 --> 00:20:39,940 S1: lucky people who have the time and energy to go 360 00:20:39,940 --> 00:20:42,750 S1: and be ambitious, and that when you look at people 361 00:20:42,750 --> 00:20:46,619 S1: who are struggling and they're not ambitious, it's likely because 362 00:20:46,619 --> 00:20:49,050 S1: they have too many jobs, you know, they got too 363 00:20:49,050 --> 00:20:51,540 S1: much drama in their lives. There's too much going on. 364 00:20:51,540 --> 00:20:53,910 S1: And if that were to not be the case, if 365 00:20:53,910 --> 00:20:56,700 S1: they were, we were able to reduce their stress. They 366 00:20:56,700 --> 00:20:59,580 S1: would become just like the go getters and just like 367 00:20:59,580 --> 00:21:04,800 S1: the ambitious and smart people. And this study, being so large, 368 00:21:04,800 --> 00:21:07,800 S1: has the ability to undo that narrative a bit and 369 00:21:07,800 --> 00:21:10,949 S1: basically say that there's a chance here we need to 370 00:21:10,950 --> 00:21:14,160 S1: do full analysis of this, but there's a chance here 371 00:21:14,160 --> 00:21:17,879 S1: that what it uncovers is that no ambitious people have 372 00:21:17,880 --> 00:21:21,630 S1: something else. They have this ambition and drive that lets 373 00:21:21,630 --> 00:21:26,429 S1: them thrive almost despite whatever is going on. So if 374 00:21:26,430 --> 00:21:28,169 S1: they have lots of burdens on them, they're going to 375 00:21:28,170 --> 00:21:31,070 S1: find a way through. Unless they're overwhelming, of course, But 376 00:21:31,070 --> 00:21:34,100 S1: given the same amount of burden, people with this attribute 377 00:21:34,100 --> 00:21:37,729 S1: of like drive and self-discipline and ambition, they're just going 378 00:21:37,730 --> 00:21:39,290 S1: to crush it. They're going to find a way to 379 00:21:39,290 --> 00:21:42,170 S1: crush it. And the whole narrative for this UBI thing 380 00:21:42,170 --> 00:21:45,410 S1: was that, no, everyone has that. And I think I'm 381 00:21:45,410 --> 00:21:48,200 S1: old enough at this point to realize, no, not everyone 382 00:21:48,200 --> 00:21:52,010 S1: has special beans or special magic. It really is a 383 00:21:52,010 --> 00:21:55,540 S1: small portion of, you know, society who is in the 384 00:21:55,540 --> 00:21:58,780 S1: top 10% of a given thing. Um, I mean, just 385 00:21:58,780 --> 00:22:03,040 S1: by the numbers, like only 10% can be in the 10%, right? 386 00:22:03,040 --> 00:22:06,580 S1: So I think first we need to confirm that that 387 00:22:06,580 --> 00:22:08,890 S1: this is what it's saying. But even if it is 388 00:22:08,890 --> 00:22:11,889 S1: saying the worst possible thing, which is no, this doesn't 389 00:22:11,890 --> 00:22:15,670 S1: actually make people more ambitious. It doesn't really matter. We 390 00:22:15,670 --> 00:22:18,190 S1: still have to keep looking for the thing that is 391 00:22:18,190 --> 00:22:20,640 S1: the ambition. We still have to find the source of 392 00:22:20,640 --> 00:22:23,820 S1: this thing that is so valuable to us, which is 393 00:22:23,820 --> 00:22:28,260 S1: people who are driven and ambitious. Now, if it's genetic, well, 394 00:22:28,260 --> 00:22:31,979 S1: then I don't care, right? We're not we're not going 395 00:22:31,980 --> 00:22:35,430 S1: to be changing genetics, right. Any time soon anyway. So 396 00:22:35,430 --> 00:22:38,189 S1: it's like, I don't care if we find that there's 397 00:22:38,190 --> 00:22:41,670 S1: more ambition in this group or less ambition in that group, 398 00:22:41,670 --> 00:22:45,270 S1: because those numbers are likely to be so tiny compared 399 00:22:45,270 --> 00:22:47,489 S1: to what we can control. You know, even if they 400 00:22:47,490 --> 00:22:49,680 S1: exist and they might not even exist. It might be 401 00:22:49,680 --> 00:22:52,679 S1: all environment. But I mean, this is a three year study. 402 00:22:52,680 --> 00:22:56,010 S1: This doesn't control, like what went into their their upbringing 403 00:22:56,010 --> 00:22:58,950 S1: and their childhood and everything. Um, because if you look 404 00:22:58,950 --> 00:23:03,060 S1: at cultures where they have this really, really strong drive 405 00:23:03,060 --> 00:23:06,540 S1: and ambition and everything, it's part of their actual culture. 406 00:23:06,750 --> 00:23:08,780 S1: This is like they pop out of the womb and 407 00:23:08,780 --> 00:23:11,900 S1: it's like, pick your college, right? You were told from 408 00:23:11,900 --> 00:23:15,230 S1: a very early age that you must be producing. It's 409 00:23:15,230 --> 00:23:18,470 S1: your responsibility to give back to community. All your, you know, 410 00:23:18,470 --> 00:23:21,740 S1: family members are looking up to you. You know you 411 00:23:21,740 --> 00:23:26,240 S1: owe us, you owe society quality outputs, and you must 412 00:23:26,240 --> 00:23:30,350 S1: work hard to create those that cultural influence and power, 413 00:23:30,350 --> 00:23:32,560 S1: plus all the peers that come with it. Plus then 414 00:23:32,560 --> 00:23:34,929 S1: you go to nice colleges and they all believe the 415 00:23:34,930 --> 00:23:38,619 S1: same thing. That entire mechanism is what we need to 416 00:23:38,619 --> 00:23:41,500 S1: give to the entire world. Okay, that that is the 417 00:23:41,500 --> 00:23:45,460 S1: thing that I believe is creating ambitious people. So you 418 00:23:45,460 --> 00:23:48,430 S1: do a three year study on UBI, you find out 419 00:23:48,430 --> 00:23:52,750 S1: that doesn't make people into those people. Fine, fine. Something 420 00:23:52,750 --> 00:23:56,850 S1: is and I believe it's that entire culture as a package. 421 00:23:56,850 --> 00:23:59,879 S1: And that's the thing that we need to give to everyone. 422 00:23:59,880 --> 00:24:02,909 S1: That's our responsibility. And if the world were more like that, 423 00:24:02,910 --> 00:24:06,600 S1: the world would be better. First of all, that automatically 424 00:24:06,600 --> 00:24:09,210 S1: fixes crime. If you're trying to build things and doing 425 00:24:09,210 --> 00:24:14,459 S1: things and you're busy, that automatically fixes literacy crime, like 426 00:24:14,460 --> 00:24:18,179 S1: so many different things that are a problem. So I 427 00:24:18,180 --> 00:24:20,970 S1: just I don't see this as too negative. I see 428 00:24:20,970 --> 00:24:23,699 S1: it as a little bit negative, but positive in the 429 00:24:23,700 --> 00:24:27,540 S1: sense that it's going to uncover the real issues, which 430 00:24:27,540 --> 00:24:34,170 S1: is how to propagate successful mental models and frames, um, 431 00:24:34,170 --> 00:24:37,710 S1: in a wider scope across wider groups of people across 432 00:24:37,710 --> 00:24:41,129 S1: the entire planet. And I think that's the problem we 433 00:24:41,130 --> 00:24:45,170 S1: need to focus on and move towards solving. Okay, some 434 00:24:45,440 --> 00:24:49,010 S1: standalone ideas here. And I just put the tweets in 435 00:24:49,010 --> 00:24:52,369 S1: here because basically when I have ideas I, I um, 436 00:24:52,490 --> 00:24:56,210 S1: post them on X and then come back to them 437 00:24:56,450 --> 00:24:59,930 S1: to distill into the idea section here. So first one, 438 00:24:59,930 --> 00:25:05,119 S1: what if cannabis? Cannabis, not cannabis is soma from the 439 00:25:05,119 --> 00:25:08,929 S1: Brave New world. So it makes people comfortable with mediocrity, 440 00:25:08,930 --> 00:25:12,460 S1: makes people more accepting of whatever they're handed, and makes 441 00:25:12,460 --> 00:25:16,150 S1: people less likely to change their situation. And legalization is 442 00:25:16,150 --> 00:25:20,470 S1: actually happening coincident with the rise of AI, which is 443 00:25:20,470 --> 00:25:23,080 S1: pretty cool. And I don't actually think that's a conspiracy. 444 00:25:23,200 --> 00:25:25,390 S1: Just to keep in mind, I think they're just both 445 00:25:25,390 --> 00:25:28,180 S1: happening at the same time. Conspiracy culture. Speaking of that 446 00:25:28,180 --> 00:25:31,450 S1: is getting stupid at this point. Um, yeah, bad thing happens. 447 00:25:31,450 --> 00:25:34,359 S1: It must be deep state. Um, Biden pulls out of 448 00:25:34,359 --> 00:25:38,379 S1: the race. Must be deep state. I saw a reply 449 00:25:38,380 --> 00:25:41,530 S1: to my my post here. Somebody said the number of 450 00:25:41,530 --> 00:25:44,770 S1: people believing the world is like that, where they see 451 00:25:44,800 --> 00:25:48,340 S1: deep state and everything is inversely proportional to the number 452 00:25:48,340 --> 00:25:51,970 S1: of people who have worked in a very large organization. 453 00:25:51,970 --> 00:25:54,640 S1: And I think that is so smart, because when you 454 00:25:54,640 --> 00:25:57,070 S1: work in these very large organizations or in the government 455 00:25:57,070 --> 00:26:02,399 S1: or whatever, you just see constant stupidity, just constant stupidity 456 00:26:02,400 --> 00:26:06,150 S1: performed by really smart people. And the fact that they're 457 00:26:06,150 --> 00:26:09,210 S1: in these large groups with lots of bureaucracy just makes 458 00:26:09,210 --> 00:26:12,689 S1: the whole thing stupid and inefficient. So you see enough 459 00:26:12,690 --> 00:26:15,869 S1: of that. And then when you see a botched Secret 460 00:26:15,869 --> 00:26:20,219 S1: Service thing or whatever, you're like, yeah, the world is stupid. 461 00:26:20,220 --> 00:26:23,659 S1: People are stupid. Like, where's I'm surprised anything works, right? 462 00:26:23,660 --> 00:26:26,600 S1: That's the eventual attitude you get after you work at 463 00:26:26,600 --> 00:26:29,750 S1: enough of these large organizations. And this one here, I'm 464 00:26:29,750 --> 00:26:32,240 S1: going to save, because this one is like, I'm going 465 00:26:32,240 --> 00:26:36,530 S1: to do a whole essay and video on this one. Essentially, 466 00:26:36,530 --> 00:26:41,179 S1: it is the use of AI for security on a 467 00:26:41,180 --> 00:26:44,240 S1: whole bunch of intractable problems. And I believe this is 468 00:26:44,240 --> 00:26:46,159 S1: the future of AI and security, which is why I'm 469 00:26:46,160 --> 00:26:47,929 S1: going to turn it into its own thing. And the 470 00:26:47,930 --> 00:26:50,330 S1: future of security and risk management is to have them 471 00:26:50,330 --> 00:26:53,540 S1: disappear into SOPs. This one, I'm also going to break 472 00:26:53,540 --> 00:26:56,840 S1: out into a separate thing and got someone posted here. 473 00:26:56,869 --> 00:26:59,930 S1: A great tribe of Silicon Valley is making a bid 474 00:26:59,930 --> 00:27:03,379 S1: to take over the US. Vance is Thiel's man. Musk 475 00:27:03,380 --> 00:27:06,350 S1: and Andreessen Horowitz are backing him. He will be the 476 00:27:06,350 --> 00:27:09,890 S1: nominee in four years as an admin, steered by Thiel 477 00:27:09,890 --> 00:27:13,180 S1: and Musk. Right when AGI is due and Starship goes 478 00:27:13,180 --> 00:27:17,260 S1: to Mars. Incredible timeline. And basically I just said, hmm, interesting. 479 00:27:17,290 --> 00:27:21,879 S1: I'll be watching this closely. I love looking at movements 480 00:27:21,880 --> 00:27:27,100 S1: like this. Like, what is Silicon Valley thinking? What are 481 00:27:27,100 --> 00:27:30,280 S1: the top tier people? What are their political views? Are 482 00:27:30,280 --> 00:27:34,209 S1: they ambitious? Are they pessimistic? Are they optimistic? What are 483 00:27:34,210 --> 00:27:36,690 S1: they doing? What are they thinking? Who are they backing? 484 00:27:36,690 --> 00:27:40,050 S1: What are their arguments? I want to know all this stuff. 485 00:27:40,050 --> 00:27:42,600 S1: And I've got a buddy who is so good at 486 00:27:42,600 --> 00:27:45,270 S1: tracking this stuff and just knows everything about this. And 487 00:27:45,270 --> 00:27:49,380 S1: I go walking with him, um, very often and have 488 00:27:49,380 --> 00:27:52,379 S1: dinner and just get into these great discussions about, like, 489 00:27:52,380 --> 00:27:56,430 S1: all these different zeitgeists happening. And it's just it's just fantastic. 490 00:27:56,430 --> 00:27:58,320 S1: And it doesn't mean I have to agree with any 491 00:27:58,320 --> 00:28:01,280 S1: of them. But hopefully if I capture enough of them 492 00:28:01,280 --> 00:28:04,340 S1: and I understand them enough, it helps me triangulate and 493 00:28:04,340 --> 00:28:07,610 S1: build my own view. All right. Discovery lemma new recon 494 00:28:07,609 --> 00:28:11,120 S1: security tool that runs via Lambda in your browser. Responder 495 00:28:11,119 --> 00:28:16,640 S1: honeypot for responder tricks attackers into revealing their presence. Exo 496 00:28:16,640 --> 00:28:20,330 S1: run your own AI cluster at home on everyday devices. 497 00:28:20,330 --> 00:28:23,920 S1: Why aren't we using SSH for everything? By Shaso. Grey 498 00:28:23,920 --> 00:28:27,820 S1: Swan AI specializes in AI safety and security tools to 499 00:28:27,820 --> 00:28:32,950 S1: assess and safeguard AI deployments. And Costco's Apocalypse bucket. They're 500 00:28:32,950 --> 00:28:36,220 S1: selling a 25 year shelf life emergency food kit called 501 00:28:36,220 --> 00:28:41,770 S1: the Apocalypse Bucket for $80. Includes 150 freeze dried and 502 00:28:41,770 --> 00:28:46,660 S1: dehydrated meal servings ranging from teriyaki rice to apple cinnamon cereal. 503 00:28:46,660 --> 00:28:49,450 S1: I bought three of these just in case things get 504 00:28:49,450 --> 00:28:53,170 S1: crazy end of this year and into next year. Plus 505 00:28:53,170 --> 00:28:56,170 S1: I'm in California. Lots of earthquakes and we're waiting for 506 00:28:56,170 --> 00:28:59,200 S1: the big one. All right, recommendation of the week. Don't 507 00:28:59,200 --> 00:29:03,460 S1: ask what someone's politics are because that's likely just to 508 00:29:03,460 --> 00:29:06,790 S1: get gross. They'll just respond with a bunch of emotional things. 509 00:29:06,790 --> 00:29:09,400 S1: They will trigger you emotionally and it will be a 510 00:29:09,400 --> 00:29:13,620 S1: complete mess. Instead, ask them what their ideal world looks like, 511 00:29:13,620 --> 00:29:17,010 S1: including questions like these. Are there multiple religions? Are there 512 00:29:17,010 --> 00:29:20,790 S1: multiple ethnic groups? Are people free to love whoever they want? 513 00:29:20,820 --> 00:29:22,920 S1: Do we all live together? What are the most famous 514 00:29:22,920 --> 00:29:25,530 S1: people in the world? Who gets paid the most? Who 515 00:29:25,530 --> 00:29:28,200 S1: gets paid the least? What happens to someone if they're 516 00:29:28,200 --> 00:29:31,350 S1: truly disabled and they cannot work? What happens to someone 517 00:29:31,350 --> 00:29:34,260 S1: if they're too lazy to work? What happens to someone 518 00:29:34,260 --> 00:29:37,070 S1: who is addicted to drugs? I think many of our 519 00:29:37,070 --> 00:29:40,850 S1: disagreements are about how and not what. Because I know 520 00:29:40,850 --> 00:29:44,120 S1: a lot of people who support Trump, for example, who 521 00:29:44,120 --> 00:29:47,479 S1: would say, yeah, you can absolutely be gay. Yeah, you 522 00:29:47,480 --> 00:29:52,190 S1: can absolutely be transgender. No problem. Love to everyone. Yes, 523 00:29:52,190 --> 00:29:55,730 S1: there absolutely can be other religions. Yes, all the ethnic 524 00:29:55,730 --> 00:29:59,030 S1: groups should live together. Yes, there should be a safety net. 525 00:29:59,030 --> 00:30:03,970 S1: I literally know multiple Trump supporters who voted for Trump twice, 526 00:30:03,970 --> 00:30:06,760 S1: who believe all four of these. You can be gay, 527 00:30:06,760 --> 00:30:10,270 S1: you can be transgender, you can be other religions. We 528 00:30:10,270 --> 00:30:12,910 S1: should all live together. We should all get along, and 529 00:30:12,910 --> 00:30:15,940 S1: there should be a social safety net. Okay, so if 530 00:30:15,940 --> 00:30:17,590 S1: you're on the left and you hear someone on the 531 00:30:17,590 --> 00:30:19,630 S1: right say those things, or you're on the right and 532 00:30:19,630 --> 00:30:21,940 S1: you hear the left say, you know some other stuff, 533 00:30:21,940 --> 00:30:25,750 S1: this is an opportunity for a real conversation. Both sides 534 00:30:25,750 --> 00:30:29,739 S1: should describe what they view as an ideal version of 535 00:30:29,740 --> 00:30:32,350 S1: the world. And I would argue to you that if 536 00:30:32,350 --> 00:30:36,040 S1: you both start with that, it's going to look very similar. 537 00:30:36,040 --> 00:30:40,780 S1: I think roughly the center 80 or 70% of the 538 00:30:40,780 --> 00:30:43,870 S1: country is going to build that model, and it's mostly 539 00:30:43,870 --> 00:30:46,420 S1: going to look the same, and it's mostly going to 540 00:30:46,420 --> 00:30:49,480 S1: include those 4 or 5 things that I just mentioned. 541 00:30:49,480 --> 00:30:52,870 S1: So if you had a smart moderator in between, you 542 00:30:52,870 --> 00:30:55,000 S1: could look at these two people and be like, okay, 543 00:30:55,000 --> 00:30:57,250 S1: let me get this straight. You think there should be 544 00:30:57,250 --> 00:31:02,320 S1: multiple ethnic groups and religions and gender identities, and we 545 00:31:02,320 --> 00:31:05,500 S1: should all work together and all live together and be 546 00:31:05,500 --> 00:31:07,900 S1: happy together and not infringe on each other. Is that 547 00:31:07,900 --> 00:31:10,690 S1: is that correct? And both of them say yes. Do 548 00:31:10,690 --> 00:31:12,880 S1: you realize how much progress that is? Do you realize 549 00:31:12,880 --> 00:31:16,190 S1: how much we need that conversation to take place right now, 550 00:31:16,190 --> 00:31:19,850 S1: in the middle of 2024, going into this crazy election cycle? 551 00:31:19,850 --> 00:31:22,430 S1: We absolutely need that. So that's where you should start 552 00:31:22,430 --> 00:31:25,490 S1: the conversation. Don't start with like, hey, what are your politics? 553 00:31:25,490 --> 00:31:27,770 S1: Because they're they're going to go to an emotional hot 554 00:31:27,770 --> 00:31:30,110 S1: button that's going to trigger both of you. Instead, talk 555 00:31:30,110 --> 00:31:32,570 S1: about the ideal. And when you realize you agree on 556 00:31:32,570 --> 00:31:35,600 S1: the ideal, now we have a how problem okay, now 557 00:31:35,600 --> 00:31:39,430 S1: we have a transition problem. Cool. That's much more tractable 558 00:31:39,430 --> 00:31:43,270 S1: and much more discussable than disagreeing on where we're supposed 559 00:31:43,270 --> 00:31:46,030 S1: to go. All right. In the aphorism of the week, 560 00:31:46,030 --> 00:31:49,990 S1: silence is a fence around wisdom. Silence is a fence 561 00:31:49,990 --> 00:31:55,480 S1: around wisdom. German proverb unsupervised learning is produced and edited 562 00:31:55,480 --> 00:31:59,920 S1: by Daniel Miller on a Neumann U87 AI microphone using Hindenburg. 563 00:32:00,400 --> 00:32:03,220 S1: Intro and outro music is by Zomby with the Y, 564 00:32:03,940 --> 00:32:06,190 S1: and to get the text and links from this episode, 565 00:32:06,190 --> 00:32:08,470 S1: sign up for the newsletter version of the show at 566 00:32:08,470 --> 00:32:13,180 S1: Daniel miessler.com/newsletter. We'll see you next time.