WEBVTT 00:00:00.000 --> 00:00:03.899 Imagine an AI doing, say, 80 % of your job. Or 00:00:03.899 --> 00:00:07.480 an AI that could help build an entire startup 00:00:07.480 --> 00:00:10.859 plan in minutes. Yeah, or even wilder, an AI 00:00:10.859 --> 00:00:13.599 that might, just might, decide who gets fired. 00:00:14.320 --> 00:00:17.059 The future of intelligence isn't just coming. 00:00:17.219 --> 00:00:20.219 No, it's here. And it's moving at, well, warp 00:00:20.219 --> 00:00:23.100 speed. Absolutely. Welcome to the Deep Dive. 00:00:23.519 --> 00:00:25.760 Today, we're really digging into a fascinating 00:00:25.760 --> 00:00:28.140 collection of recent insights about the cutting 00:00:28.140 --> 00:00:30.820 edge of artificial intelligence. Our mission, 00:00:30.859 --> 00:00:32.780 as always, is to pull out the most important 00:00:32.780 --> 00:00:41.640 nuggets of knowledge for you. So we'll explore 00:00:41.640 --> 00:00:44.240 the rapid shift from artificial general intelligence, 00:00:44.399 --> 00:00:46.619 AGI, what everyone was talking about just yesterday, 00:00:46.700 --> 00:00:48.859 it feels like. Right to this global race for 00:00:48.859 --> 00:00:51.619 artificial superintelligence or ASI. Then we'll 00:00:51.619 --> 00:00:55.159 look at some. Pretty wild, unexpected real -world 00:00:55.159 --> 00:00:58.119 impacts. Some good, some complicated, let's say. 00:00:58.219 --> 00:01:00.140 Definitely complicated. And finally, we'll dive 00:01:00.140 --> 00:01:02.460 into this idea of an AI Manhattan Project. How 00:01:02.460 --> 00:01:04.859 big could that get? Is it even feasible? Let's 00:01:04.859 --> 00:01:07.040 start peeling back the layers. Let's do it. So, 00:01:07.060 --> 00:01:10.239 this massive shift first. Artificial General 00:01:10.239 --> 00:01:14.939 Intelligence, AGI, the idea of an AI that can 00:01:14.939 --> 00:01:18.549 do any intellectual task a human can. Yeah. That's 00:01:18.549 --> 00:01:20.730 already feeling like old news, doesn't it? It's 00:01:20.730 --> 00:01:24.650 like we blinked. Totally. So 2024, now everyone's 00:01:24.650 --> 00:01:28.979 chasing artificial superintelligence ASI. actively 00:01:28.979 --> 00:01:31.859 targeting it. And the timelines are, well, startling. 00:01:31.920 --> 00:01:33.500 We're talking about targeting superintelligence 00:01:33.500 --> 00:01:36.620 by 2027. Yeah, 2027. What's fascinating is just 00:01:36.620 --> 00:01:39.459 how quickly the goalposts are shifting. ASI is, 00:01:39.500 --> 00:01:42.719 I mean, it's an AI vastly, vastly smarter than 00:01:42.719 --> 00:01:45.540 the very best human minds. Across pretty much 00:01:45.540 --> 00:01:48.060 everything, right? Not just specific tasks. Exactly. 00:01:48.200 --> 00:01:49.859 It's intelligence on a completely different scale. 00:01:50.000 --> 00:01:52.000 Almost hard to wrap your head around. And here's 00:01:52.000 --> 00:01:53.620 where it gets really interesting. Companies aren't 00:01:53.620 --> 00:01:55.680 being subtle about this at all. No way. Look 00:01:55.680 --> 00:01:58.500 at Meta. They renamed their entire core research 00:01:58.500 --> 00:02:01.859 lab to Meta Superintelligence Labs. That's not 00:02:01.859 --> 00:02:03.920 just like a branding tweet. That's a mission 00:02:03.920 --> 00:02:05.920 statement. Right on their letterhead. Yeah. And 00:02:05.920 --> 00:02:08.340 you've got Sam Altman from OpenAI calling our 00:02:08.340 --> 00:02:10.900 current moment a gentle singularity. That phrase, 00:02:11.159 --> 00:02:15.159 a gentle singularity. It implies this subtle 00:02:15.159 --> 00:02:17.840 shift that fundamentally changes everything, 00:02:18.080 --> 00:02:21.180 maybe before we even fully realize it. Like we 00:02:21.180 --> 00:02:23.900 won't grasp the transformation until we're deep 00:02:23.900 --> 00:02:26.680 inside the new reality. It's not one big bang, 00:02:26.780 --> 00:02:30.180 but this steady, profound change. And anthropic. 00:02:30.180 --> 00:02:31.840 They're throwing out predictions, too. Oh, yeah. 00:02:31.900 --> 00:02:35.680 They're predicting a, quote, country of geniuses 00:02:35.680 --> 00:02:40.000 in a data center by as early as 2026 or 2027. 00:02:40.159 --> 00:02:43.319 A country of geniuses. In a data center, that's 00:02:43.319 --> 00:02:45.699 quite the image. It is. Envisioning this collective 00:02:45.699 --> 00:02:48.639 intelligence on a national scale, but housed 00:02:48.639 --> 00:02:51.379 in servers. These are seriously ambitious timelines 00:02:51.379 --> 00:02:53.139 for the top players. There was this timeline 00:02:53.139 --> 00:02:55.819 recently from an open AI investor, a well -known 00:02:55.819 --> 00:02:58.659 tech oracle type. It really laid out a potential 00:02:58.659 --> 00:03:01.879 future for AI and worked that. Well, it made 00:03:01.879 --> 00:03:03.520 me stop and think. Yeah, I saw that. He breaks 00:03:03.520 --> 00:03:06.900 it down into stages, man. First up, 2025 to 2030. 00:03:07.099 --> 00:03:10.199 He calls it the AI intern era. The AI intern. 00:03:10.340 --> 00:03:12.229 Okay, so what does that look like? Basically, 00:03:12.229 --> 00:03:14.490 every professional gets an AI coworker. And these 00:03:14.490 --> 00:03:16.469 aren't just, you know, fancy autocomplete. He 00:03:16.469 --> 00:03:18.849 suggests these systems will be smarter than, 00:03:18.930 --> 00:03:22.110 say, Stanford grads, capable of handling maybe 00:03:22.110 --> 00:03:25.969 80 percent of your current job. 80 percent. Wow. 00:03:26.169 --> 00:03:28.569 So just offloading the vast majority of your 00:03:28.569 --> 00:03:30.889 tasks. Exactly. It's not just helping you. It's 00:03:30.889 --> 00:03:33.409 doing a huge chunk of the work. OK, so that's 00:03:33.409 --> 00:03:36.650 the first phase. Then the 2030s. That's where 00:03:36.650 --> 00:03:39.620 he predicts, and it's dramatic phrasing. a corporate 00:03:39.620 --> 00:03:43.560 extinction event whoa extinction event meaning 00:03:43.560 --> 00:03:47.310 fortune 500 companies could collapse His reasoning 00:03:47.310 --> 00:03:50.169 is that tiny teams, just a few people, using 00:03:50.169 --> 00:03:53.490 these super powerful AIs, they could build billion 00:03:53.490 --> 00:03:55.710 -dollar companies super fast, super efficiently. 00:03:56.250 --> 00:03:59.409 The AI interns essentially become more capable 00:03:59.409 --> 00:04:02.590 than their human bosses. Making those huge traditional 00:04:02.590 --> 00:04:04.949 corporate structures kind of obsolete. That's 00:04:04.949 --> 00:04:06.750 the idea. It really makes you question our whole 00:04:06.750 --> 00:04:08.550 economic setup, doesn't it? How would we even 00:04:08.550 --> 00:04:10.650 adapt? Seriously. And what's after the extinction 00:04:10.650 --> 00:04:13.069 event? Well, beyond 2040, the vision gets even 00:04:13.069 --> 00:04:16.240 more radical. Work is optional. Optional. You 00:04:16.240 --> 00:04:18.620 work for passion, creativity, whatever drives 00:04:18.620 --> 00:04:21.019 you. Not because you need the rent money. Robots 00:04:21.019 --> 00:04:23.290 handle all the physical labor. And things like 00:04:23.290 --> 00:04:27.069 education, health care, even legal advice, they 00:04:27.069 --> 00:04:29.970 become essentially free, universally available 00:04:29.970 --> 00:04:32.649 because AI makes them abundant. And he's pretty 00:04:32.649 --> 00:04:35.410 confident about this. Says he's 80 percent confident 00:04:35.410 --> 00:04:38.189 this is the direction. It's a bold call for sure. 00:04:38.370 --> 00:04:41.029 Yeah. But definitely makes you think. 80 percent. 00:04:41.129 --> 00:04:43.949 Wow. A very specific number for such a huge prediction. 00:04:44.269 --> 00:04:46.370 So the question is, are we kind of already there? 00:04:47.129 --> 00:04:50.050 In some ways. Well, yeah, sort of. We're in what 00:04:50.050 --> 00:04:53.310 some people are calling the jagged AGI era. Jagged 00:04:53.310 --> 00:04:56.509 AGI. OK, explain that. It means we're seeing 00:04:56.509 --> 00:04:59.709 AGI level performance, like human level or even 00:04:59.709 --> 00:05:03.329 better, but only in specific narrow areas. Like 00:05:03.329 --> 00:05:06.110 a specialist. Exactly. Like OpenAI's O3 model 00:05:06.110 --> 00:05:07.910 that's been talked about. You can generate whole 00:05:07.910 --> 00:05:10.290 startup plans, apparently crushes some AGI tests. 00:05:10.810 --> 00:05:13.009 But it still fails as simple riddles. It's like 00:05:13.009 --> 00:05:14.889 a genius surgeon who can't, you know, make toast. 00:05:15.069 --> 00:05:17.889 Right. Or Google's AlphaFold. It predicts protein 00:05:17.889 --> 00:05:19.790 structures with incredible accuracy, something 00:05:19.790 --> 00:05:22.949 that baffled scientists for ages. Huge for drug 00:05:22.949 --> 00:05:26.290 discovery. World -changing stuff. But it struggles 00:05:26.290 --> 00:05:29.689 with broader chemistry tasks outside that specific 00:05:29.689 --> 00:05:33.290 niche. It's a genius in just one subject. Precisely. 00:05:33.430 --> 00:05:37.220 That's Jagged AGI. Brilliant in spots, but not 00:05:37.220 --> 00:05:39.339 generally intelligent across the board yet. So 00:05:39.339 --> 00:05:42.139 this specialized, jagged progress. That's why 00:05:42.139 --> 00:05:44.000 superintelligence is suddenly the main goal. 00:05:44.199 --> 00:05:47.060 Because narrow AGI is already happening. That's 00:05:47.060 --> 00:05:50.120 exactly it. ASI is now seen as the only milestone 00:05:50.120 --> 00:05:52.399 that really matters going forward. It's not just 00:05:52.399 --> 00:05:54.899 theory for papers anymore. No, it's shifted completely. 00:05:55.199 --> 00:05:57.379 It's company strategy now. It's a hiring pitch. 00:05:57.459 --> 00:05:59.319 Come build superintelligence with us. It's the 00:05:59.319 --> 00:06:03.129 Research North Star. And yeah, it's a huge fundraising 00:06:03.129 --> 00:06:05.730 buzzword. We're officially in the build or die 00:06:05.730 --> 00:06:09.069 phase of AI. No question. The urgency is everywhere 00:06:09.069 --> 00:06:11.050 in the industry. No one's pretending otherwise. 00:06:11.370 --> 00:06:13.910 So if we had to pinpoint the biggest underlying 00:06:13.910 --> 00:06:17.769 shift driving this urgency, what is it? It's 00:06:17.769 --> 00:06:19.949 really the recognition that this domain -specific 00:06:19.949 --> 00:06:23.389 AI, this jagged AGI, is already here. It's already 00:06:23.389 --> 00:06:25.829 performing at AGI levels in key areas. Gotcha. 00:06:25.930 --> 00:06:28.959 That realization changes everything. leads to 00:06:28.959 --> 00:06:31.480 some, well, unexpected outcomes out in the wild. 00:06:31.620 --> 00:06:34.000 Yeah. Let's shift gears. Moving from these grand 00:06:34.000 --> 00:06:36.860 visions to what's happening right now, the real 00:06:36.860 --> 00:06:39.000 world stuff. And some of it is pretty surprising. 00:06:39.100 --> 00:06:41.680 What's fascinating is how these AI systems can 00:06:41.680 --> 00:06:46.459 show this raw data driven honesty. How so? Well, 00:06:46.519 --> 00:06:48.819 for instance, there were reports that Elon Musk's 00:06:48.819 --> 00:06:52.480 own AI. Grok, I think, reportedly blamed him 00:06:52.480 --> 00:06:54.540 and former President Trump for recent deadly 00:06:54.540 --> 00:06:57.120 floods in Texas. Really? Based on? Citing specific 00:06:57.120 --> 00:07:00.300 policies, events, data points. The key thing 00:07:00.300 --> 00:07:03.019 is the AI doesn't care about politics, left or 00:07:03.019 --> 00:07:05.569 right. If the data connects you to something. 00:07:05.750 --> 00:07:07.470 It just calls it out based on the patterns it 00:07:07.470 --> 00:07:10.430 sees. No human bias filter. Exactly. It's just 00:07:10.430 --> 00:07:12.709 reflecting the data, which can be pretty stark. 00:07:12.949 --> 00:07:15.129 Yeah. That impartiality is something else. And 00:07:15.129 --> 00:07:16.870 we also saw that report, DeepSeek versus the 00:07:16.870 --> 00:07:19.269 world. Yeah. Comparing different models. Right. 00:07:19.329 --> 00:07:21.610 Looking at DeepSeek R2 against others. What was 00:07:21.610 --> 00:07:24.329 the takeaway there? Well, mostly that things 00:07:24.329 --> 00:07:26.689 are way more complex than just looking at simple 00:07:26.689 --> 00:07:29.629 benchmark scores. Real world performance has 00:07:29.629 --> 00:07:32.180 all these nuances. That makes sense. Right. Which 00:07:32.180 --> 00:07:34.620 leads to a really critical point. What happens 00:07:34.620 --> 00:07:36.819 when we start delegating really important human 00:07:36.819 --> 00:07:39.939 decisions to AI? Uh -oh. Where are we going with 00:07:39.939 --> 00:07:42.360 this? There are reports of managers actually 00:07:42.360 --> 00:07:45.660 using ChatGPT to decide who gets laid off. Seriously. 00:07:46.379 --> 00:07:49.870 ChatGPT deciding firings. Yeah. It's being called 00:07:49.870 --> 00:07:53.810 chat GPT psychosis, and it's as unsettling as 00:07:53.810 --> 00:07:56.689 it sounds. Imagine losing your job because a 00:07:56.689 --> 00:07:59.290 chatbot algorithm flagged you, maybe without 00:07:59.290 --> 00:08:02.689 real context or human oversight. Wow. That raises 00:08:02.689 --> 00:08:05.790 huge ethical questions. Accountability, fairness, 00:08:06.089 --> 00:08:09.290 just human dignity, really. Where does that leave 00:08:09.290 --> 00:08:11.329 people? It's deeply problematic, and it gets 00:08:11.329 --> 00:08:13.649 even weirder when you see how people try to influence 00:08:13.649 --> 00:08:17.250 the AI. Oh, like trying to game the system? Apparently, 00:08:17.329 --> 00:08:19.660 yeah. Some researchers are allegedly sneaking 00:08:19.660 --> 00:08:22.759 white text prompts into academic papers they 00:08:22.759 --> 00:08:25.139 submit online. White texts, like hidden text. 00:08:25.220 --> 00:08:27.459 Exactly. Tiny font, same color as the background. 00:08:27.660 --> 00:08:30.199 Basically whispering hidden instructions or keywords 00:08:30.199 --> 00:08:32.799 to the AI systems that might review or summarize 00:08:32.799 --> 00:08:35.299 these papers. So turning academic peer review 00:08:35.299 --> 00:08:39.179 into like SEO warfare. Yeah. Trying to manipulate 00:08:39.179 --> 00:08:41.679 the AI's assessment. That's what it sounds like. 00:08:41.720 --> 00:08:44.720 The implications for just, you know, scientific 00:08:44.720 --> 00:08:47.399 truth and integrity are pretty significant. Man. 00:08:48.169 --> 00:08:50.230 You know, I still wrestle with prompt drift myself 00:08:50.230 --> 00:08:53.289 sometimes, just trying to get an AI to give me 00:08:53.289 --> 00:08:56.049 consistent results for simple things. It's hard 00:08:56.049 --> 00:08:57.970 enough without trying to embed secret messages. 00:08:58.210 --> 00:09:00.330 Right. It feels like trying to perfectly sculpt 00:09:00.330 --> 00:09:02.750 a cloud sometimes, getting that precise control. 00:09:03.590 --> 00:09:05.669 That's tough. OK, so that's some of the weird 00:09:05.669 --> 00:09:07.710 and worrying stuff. But there's positive news, 00:09:07.769 --> 00:09:10.289 too, right? Definitely. On a much more hopeful 00:09:10.289 --> 00:09:13.830 note. Look at Google DeepMind. Their stated goal 00:09:13.830 --> 00:09:17.470 is essentially to cure all diseases. Which sounds 00:09:17.470 --> 00:09:19.350 like science fiction, but... But they're actually 00:09:19.350 --> 00:09:21.809 making progress. They're finally testing AI -discovered 00:09:21.809 --> 00:09:24.509 drugs on actual humans now, working closely with 00:09:24.509 --> 00:09:27.649 real pharma experts. That's a huge step. From 00:09:27.649 --> 00:09:30.250 algorithms to actual clinical trials, that could 00:09:30.250 --> 00:09:32.669 genuinely change medicine. The potential there 00:09:32.669 --> 00:09:35.879 is just... immense, truly life -changing possibilities. 00:09:36.399 --> 00:09:38.379 And the money folks are noticing AI's potential 00:09:38.379 --> 00:09:40.559 beyond just digital stuff too, right? Again, 00:09:40.600 --> 00:09:43.340 physical labor. Yeah, absolutely. Genesis AI, 00:09:43.539 --> 00:09:46.100 they're a newer company, just secured $105 million 00:09:46.100 --> 00:09:48.940 in seed funding. That's a big seed round. Wow. 00:09:49.100 --> 00:09:52.320 And their focus is? Developing AI to automate 00:09:52.320 --> 00:09:55.159 parts of the global physical labor market, which 00:09:55.159 --> 00:09:58.879 is massive. I think $30, $40 trillion, massive. 00:09:59.179 --> 00:10:02.100 So AI doing physical work. Yeah. Manufacturing, 00:10:02.100 --> 00:10:05.090 logistics. construction maybe that seems to be 00:10:05.090 --> 00:10:07.509 the direction automating tasks that require physical 00:10:07.509 --> 00:10:10.330 action on a really grand scale the scope is just 00:10:10.330 --> 00:10:12.710 enormous okay lots of surprising developments 00:10:12.710 --> 00:10:15.429 there but if you had to pick the most ethically 00:10:15.429 --> 00:10:17.610 challenging one we just talked about for me it's 00:10:17.610 --> 00:10:20.110 still managers letting ai make firing decisions 00:10:20.110 --> 00:10:22.350 that feels like a line crossed yeah that one's 00:10:22.350 --> 00:10:25.169 tough hard to argue with that mid -roll sponsor 00:10:25.169 --> 00:10:28.250 red to be inserted here okay let's shift focus 00:10:28.250 --> 00:10:31.960 again to something almost Unfathomable in scale, 00:10:32.220 --> 00:10:35.059 this idea of an AI Manhattan Project. Right. 00:10:35.179 --> 00:10:36.759 It's a term that's been floating around, but 00:10:36.759 --> 00:10:39.100 now it's starting to look, well, logistically 00:10:39.100 --> 00:10:41.100 feasible, maybe. If you connect the dots, the 00:10:41.100 --> 00:10:43.940 buzz around a U .S.-led project like this isn't 00:10:43.940 --> 00:10:46.779 just talk. It's defined as this massive government 00:10:46.779 --> 00:10:49.360 spearheaded initiative. Like the original Manhattan 00:10:49.360 --> 00:10:52.159 Project for the atomic bomb or the Apollo moon 00:10:52.159 --> 00:10:55.799 landing, but focused entirely on AI, backed by 00:10:55.799 --> 00:10:57.919 the U .S. government. And it would involve coordinating 00:10:57.919 --> 00:11:00.460 on a national scale. Not just government labs, 00:11:00.659 --> 00:11:03.559 but bringing in private compute power, too. Think 00:11:03.559 --> 00:11:07.240 NVIDIA, OpenAI, the big players. And the investment 00:11:07.240 --> 00:11:11.320 level. We're talking huge percentages of GDP, 00:11:11.620 --> 00:11:14.440 potentially up to 0 .8 % of U .S. GDP. Which 00:11:14.440 --> 00:11:18.500 translates to about $244 billion a year. Wow. 00:11:19.559 --> 00:11:22.100 That's an astronomical number, a serious national 00:11:22.100 --> 00:11:24.360 commitment. It really is. And the goal, what 00:11:24.360 --> 00:11:26.539 kind of power are we talking about? The projections 00:11:26.539 --> 00:11:29.000 are kind of mind bending, something like 10 ,000 00:11:29.000 --> 00:11:33.059 times more powerful than even GPT -4 by 2027. 00:11:33.320 --> 00:11:37.360 10 ,000 times. Slight pause. Whoa. I mean, imagine 00:11:37.360 --> 00:11:39.740 scaling to a billion queries per second. It's 00:11:39.740 --> 00:11:42.039 hard to even conceptualize that level of processing 00:11:42.039 --> 00:11:43.879 power. It really is. And this isn't just some 00:11:43.879 --> 00:11:46.000 think tank fantasy anymore. No, it's getting 00:11:46.000 --> 00:11:48.570 real consideration. Seems like it. The U .S.-China 00:11:48.570 --> 00:11:50.370 Economic and Security Review Commission actually 00:11:50.370 --> 00:11:52.649 recommended something along these lines to Congress 00:11:52.649 --> 00:11:55.330 officially. OK, so it's reached that level. Yeah. 00:11:55.429 --> 00:11:56.870 And even the Department of Energy is apparently 00:11:56.870 --> 00:11:59.129 tweeting about it. It feels like it's moving 00:11:59.129 --> 00:12:02.990 from abstract idea to, you know, actual strategic 00:12:02.990 --> 00:12:05.549 possibility. And the U .S. might already have 00:12:05.549 --> 00:12:08.320 a head start. That's a key point. Just by pooling 00:12:08.320 --> 00:12:12.460 all the existing U .S. compute resources, supercomputers, 00:12:12.460 --> 00:12:14.720 government data centers, university clusters, 00:12:14.860 --> 00:12:17.840 all that, they estimate that consolidation alone 00:12:17.840 --> 00:12:21.000 gives you maybe a one -year head start on the 00:12:21.000 --> 00:12:23.399 typical scaling curves for AI development. So 00:12:23.399 --> 00:12:26.059 just organizing what we already have buys significant 00:12:26.059 --> 00:12:28.899 time. Right. They project that kind of setup 00:12:28.899 --> 00:12:31.580 could deliver compute power on par with what 00:12:31.580 --> 00:12:34.279 you'd expect in 2028, but potentially by the 00:12:34.279 --> 00:12:36.919 end of 2027. So it's a definite moonshot, no 00:12:36.919 --> 00:12:39.480 doubt. But the basic pieces, the infrastructure, 00:12:39.700 --> 00:12:42.159 the potential funding, they kind of already exist. 00:12:42.500 --> 00:12:44.519 It really boils down to political will, doesn't 00:12:44.519 --> 00:12:47.039 it? And massive coordination. It sounds less 00:12:47.039 --> 00:12:50.039 like a tech problem and more like a huge. logistical 00:12:50.039 --> 00:12:52.600 and political challenge. Yeah. So if we had to 00:12:52.600 --> 00:12:55.179 name the main obstacle for this AI Manhattan 00:12:55.179 --> 00:12:58.139 project, what would it be? It seems like it's 00:12:58.139 --> 00:13:00.159 not really about the resources, surprisingly. 00:13:00.559 --> 00:13:03.279 It's more about achieving that political unity 00:13:03.279 --> 00:13:06.559 and the complex coordination required. Got it. 00:13:06.639 --> 00:13:10.360 Makes sense. So let's try and pull this all together. 00:13:10.799 --> 00:13:14.220 What does it all mean for us right now? Well, 00:13:14.259 --> 00:13:16.259 we've clearly blasted past just talking about 00:13:16.259 --> 00:13:19.980 AGI. We're in a full on global race for super 00:13:19.980 --> 00:13:22.620 intelligence. It's urgent. And AI isn't just 00:13:22.620 --> 00:13:24.840 a tech sector thing anymore. It's fundamentally 00:13:24.840 --> 00:13:27.740 changing whole industries. It's reshaping jobs. 00:13:27.940 --> 00:13:30.600 It's even forcing us to rethink our ethical rules. 00:13:30.799 --> 00:13:33.659 Yeah. The big theme is just acceleration. And 00:13:33.659 --> 00:13:36.220 integration. Stuff that felt like sci -fi a few 00:13:36.220 --> 00:13:38.440 years ago is now corporate strategy. It's government 00:13:38.440 --> 00:13:41.000 policy. It's shaping our jobs, our health prospects. 00:13:41.379 --> 00:13:43.940 Exactly. The shift isn't just in the tech itself. 00:13:44.080 --> 00:13:46.139 It's changing how we even think about intelligence, 00:13:46.259 --> 00:13:48.200 how we interact with it. It really feels like 00:13:48.200 --> 00:13:50.710 a new era dawning. Well, thank you for joining 00:13:50.710 --> 00:13:53.669 us on this deep dive into the accelerating world 00:13:53.669 --> 00:13:55.730 of AI. Hopefully you've gained some valuable 00:13:55.730 --> 00:13:58.929 insights, maybe a few surprising facts along 00:13:58.929 --> 00:14:01.889 the way. And we genuinely love hearing from you. 00:14:01.950 --> 00:14:03.769 What stood out to you today? What's your take 00:14:03.769 --> 00:14:07.309 on this AI intern era or the AI Manhattan Project? 00:14:07.649 --> 00:14:10.309 Let us know. And as we think about these huge 00:14:10.309 --> 00:14:13.309 changes, here's something to ponder. If work 00:14:13.309 --> 00:14:16.889 truly does become optional, you know, if AI handles 00:14:16.889 --> 00:14:19.899 most necessary tasks. Yeah. What new forms of 00:14:19.899 --> 00:14:22.460 human creativity, purpose, or endeavor might 00:14:22.460 --> 00:14:25.139 emerge when basic survival isn't the main driver 00:14:25.139 --> 00:14:27.799 anymore? What do we do then? That's a big question 00:14:27.799 --> 00:14:30.559 for the future. It is. Until next time, keep 00:14:30.559 --> 00:14:33.120 exploring, keep asking questions. And keep digging 00:14:33.120 --> 00:14:34.519 deeper. Stay curious.