WEBVTT 00:00:00.000 --> 00:00:04.059 Imagine an AI, not one that just predicts what 00:00:04.059 --> 00:00:07.559 you'll type next, but what you'll do. Yeah. We're 00:00:07.559 --> 00:00:09.820 talking about a model that actually beat human 00:00:09.820 --> 00:00:12.960 cognitive models at predicting behavior. Just 00:00:12.960 --> 00:00:14.839 by reading psychology experiments. It's kind 00:00:14.839 --> 00:00:17.079 of wild. Yeah. It's not science fiction. It's 00:00:17.079 --> 00:00:21.070 this new AI called Centaur. Well, its accuracy 00:00:21.070 --> 00:00:23.969 is quite startling. Welcome to the Deep Dive. 00:00:24.050 --> 00:00:25.730 Today, we're going to unpack a whole bunch of 00:00:25.730 --> 00:00:28.910 insights trying to chart this really complex, 00:00:29.030 --> 00:00:32.549 fast -moving AI landscape. Right. It's all pulled 00:00:32.549 --> 00:00:35.289 from a recent newsletter that was pretty packed 00:00:35.289 --> 00:00:37.850 with info. Our mission really is to give you 00:00:37.850 --> 00:00:39.990 those crucial nuggets of knowledge, the stuff 00:00:39.990 --> 00:00:42.009 you need to kind of navigate this accelerating 00:00:42.009 --> 00:00:44.710 AI world. We'll kick off looking at Meta's... 00:00:45.530 --> 00:00:48.189 latest big quest this ai super intelligence for 00:00:48.189 --> 00:00:50.590 everyone idea okay then we'll zoom out a bit 00:00:50.590 --> 00:00:52.829 look at industry highlights maybe some practical 00:00:52.829 --> 00:00:55.890 tools you can actually use and then yeah dive 00:00:55.890 --> 00:00:58.649 deep into centaur that mind reading ai and what 00:00:58.649 --> 00:01:01.149 that means for understanding us you know human 00:01:01.149 --> 00:01:03.670 cognition all right let's get into meta's big 00:01:03.670 --> 00:01:07.349 claims then the company that you know gave us 00:01:07.349 --> 00:01:10.930 the metaverse dream Now pitching AI superintelligence 00:01:10.930 --> 00:01:13.689 for everyone. It sounds so familiar, doesn't 00:01:13.689 --> 00:01:15.670 it? It really does. Like that metaverse push 00:01:15.670 --> 00:01:18.930 in 2021. Yeah. We all remember how that went. 00:01:19.150 --> 00:01:21.370 Horizon Worlds ended up being kind of this virtual 00:01:21.370 --> 00:01:23.469 ghost town. Right. Even Meta's own employees 00:01:23.469 --> 00:01:25.569 weren't really using it much. Yeah. A quiet digital 00:01:25.569 --> 00:01:28.409 place is a good way to put it. And now Zuckerberg's 00:01:28.409 --> 00:01:30.609 latest memo talks about AI reels you can chat 00:01:30.609 --> 00:01:33.909 with, these always -on AI video chats that mimic 00:01:33.909 --> 00:01:37.290 human expressions. And even AI friends, like 00:01:37.290 --> 00:01:39.969 designed to fill social gaps, give you the feeling 00:01:39.969 --> 00:01:43.230 of 15 friends. It's quite a vision. It is. But 00:01:43.230 --> 00:01:44.870 what's interesting, what's different this time 00:01:44.870 --> 00:01:46.750 maybe, is that while the pitch sounds familiar, 00:01:47.010 --> 00:01:49.969 Meta actually has some real traction. Okay. How 00:01:49.969 --> 00:01:53.530 so? Over a billion people are using Meta AI tools 00:01:53.530 --> 00:01:56.480 every month. A billion. That's just worlds away 00:01:56.480 --> 00:01:58.359 from the few hundred thousand metaverse users. 00:01:58.560 --> 00:02:02.540 Wow. Okay. That's a huge difference. Huge. And 00:02:02.540 --> 00:02:04.640 they're using AI coding tools inside the company, 00:02:04.719 --> 00:02:07.420 too, which helps them build faster. Plus, people 00:02:07.420 --> 00:02:11.599 are genuinely kind of forming attachments to 00:02:11.599 --> 00:02:14.020 these AI personas. Really attachments? Yeah, 00:02:14.039 --> 00:02:15.759 it's like this whole new type of social connection 00:02:15.759 --> 00:02:18.240 emerging. It's interesting. The fundamental problems 00:02:18.240 --> 00:02:20.120 are still there, right? These models, they still 00:02:20.120 --> 00:02:22.340 hallucinate, make stuff up. Oh, absolutely. They 00:02:22.340 --> 00:02:25.120 invent information. Their reasoning is often, 00:02:25.280 --> 00:02:28.219 you know. hit or miss. You give them a simple 00:02:28.219 --> 00:02:30.879 logic puzzle, even a basic game, and they often 00:02:30.879 --> 00:02:33.740 just break. So that super intelligence part still 00:02:33.740 --> 00:02:37.300 feels pretty far off, like science fiction territory. 00:02:37.659 --> 00:02:40.039 Very much so. And if you connect it to the bigger 00:02:40.039 --> 00:02:43.060 picture, you see meta is, well, it's rebranding. 00:02:43.449 --> 00:02:46.710 Again. Right. And this strategy keeps investors 00:02:46.710 --> 00:02:49.210 happy, keeps them excited. That's key. And it 00:02:49.210 --> 00:02:52.050 helps them pull in top AI talent, which is super 00:02:52.050 --> 00:02:55.250 competitive right now. Helps justify those kind 00:02:55.250 --> 00:02:57.289 of crazy salaries. So it's partly a business 00:02:57.289 --> 00:02:59.789 move, attracting talent and investment. Definitely. 00:03:00.009 --> 00:03:02.189 Less about some sudden breakthrough, more about 00:03:02.189 --> 00:03:05.349 smart positioning in the market. OK, so is Meta's 00:03:05.349 --> 00:03:08.849 AI. push fundamentally different this time around? 00:03:08.949 --> 00:03:11.129 Or is it just, you know, a new label on an old 00:03:11.129 --> 00:03:13.210 approach? Well, it definitely has user traction 00:03:13.210 --> 00:03:16.430 this time, unlike the metaverse. But those core 00:03:16.430 --> 00:03:19.590 AI challenges. They absolutely remain. All right. 00:03:19.590 --> 00:03:22.270 Let's move beyond meta then. Look at the broader 00:03:22.270 --> 00:03:24.990 AI industry because there's just so much happening. 00:03:25.150 --> 00:03:26.949 Seems like it speeds up every week. Totally. 00:03:27.310 --> 00:03:29.490 Take Baidu, for instance. They just dropped Mute 00:03:29.490 --> 00:03:31.490 Steamer. Mute Steamer. Yeah. It's a new model. 00:03:31.710 --> 00:03:33.430 Basically, it goes head -to -head with Google's 00:03:33.430 --> 00:03:35.469 VO. It makes these 10 -second video clips. Okay. 00:03:35.629 --> 00:03:39.569 But get this. Fully synchronized visuals, sound 00:03:39.569 --> 00:03:42.389 effects, and spoken dialogue. All generated together. 00:03:42.990 --> 00:03:46.150 That's a pretty big step for multimodal AI, you 00:03:46.150 --> 00:03:47.949 know, AI that handles different types of data. 00:03:48.069 --> 00:03:50.229 That sounds impressive. And it brings us to some 00:03:50.229 --> 00:03:52.689 of the, let's say, weirder sides of AI's impact. 00:03:52.870 --> 00:03:54.669 Like, did you hear about that job hopper? The 00:03:54.669 --> 00:03:57.590 one landing multiple AI jobs at once? Yeah. Keeps 00:03:57.590 --> 00:04:00.069 getting caught, fired, then just does it again. 00:04:00.490 --> 00:04:03.509 Soft chuckle. Yeah. Yeah, I saw that. It's funny, 00:04:03.550 --> 00:04:06.370 but it kind of highlights how AI is really shaking 00:04:06.370 --> 00:04:08.530 up the job market, creating these weird news 00:04:08.530 --> 00:04:11.430 scenarios. Definitely. And speaking of shaking 00:04:11.430 --> 00:04:13.830 things up, look at news consumption. Oh, yeah. 00:04:14.430 --> 00:04:16.990 That's a big one. SimilarWeb found news -related 00:04:16.990 --> 00:04:20.310 searches on ChatGPT just exploded up, what, 212 00:04:20.310 --> 00:04:23.129 %? Yeah, massive jump. But at the same time, 00:04:23.170 --> 00:04:27.649 traffic to actual news websites down 26 % since 00:04:27.649 --> 00:04:31.089 Google rolled out its AI overviews. That's significant. 00:04:31.209 --> 00:04:33.370 A big shift in how people get their information. 00:04:33.550 --> 00:04:35.889 Maybe a bit concerning. Could be, yeah. Changes 00:04:35.889 --> 00:04:37.949 the whole information ecosystem. But on the flip 00:04:37.949 --> 00:04:40.529 side... There are new opportunities. Like if 00:04:40.529 --> 00:04:42.889 you're good at spotting AI mistakes and fixing 00:04:42.889 --> 00:04:44.730 them. Like Sarah Skid, the product marketing 00:04:44.730 --> 00:04:47.329 manager. Exactly. She's making like two grand 00:04:47.329 --> 00:04:50.329 just fixing bad AI website copy. So there's value 00:04:50.329 --> 00:04:52.689 in that human touch, that refinement. For sure. 00:04:52.810 --> 00:04:55.970 But then you've got MIT economist David Autor 00:04:55.970 --> 00:04:59.170 warning about a potential Mad Max scenario. Mad 00:04:59.170 --> 00:05:01.730 Max. What does he mean? Basically that AI could 00:05:01.730 --> 00:05:04.050 automate so much that a lot of current skills 00:05:04.050 --> 00:05:07.199 just become worthless. A pretty stark warning 00:05:07.199 --> 00:05:10.500 about economic disruption. Wow. So opportunity 00:05:10.500 --> 00:05:13.139 and disruption side by side. Exactly. And look 00:05:13.139 --> 00:05:15.480 at the money pouring in. Recognize this investment 00:05:15.480 --> 00:05:19.560 firm. They just raised $1 .7 billion. Billion 00:05:19.560 --> 00:05:23.220 with a B. Yep. Specifically to invest in mid 00:05:23.220 --> 00:05:26.420 -sized AI digital services companies. Shows huge 00:05:26.420 --> 00:05:28.360 confidence in the sector's growth. It's such 00:05:28.360 --> 00:05:31.430 a mix, isn't it? AI creating wealth, new jobs, 00:05:31.550 --> 00:05:33.610 but also disrupting industries, raising these 00:05:33.610 --> 00:05:36.769 big questions about, well, about us. Yeah. Huge 00:05:36.769 --> 00:05:39.550 opportunities and pretty profound existential 00:05:39.550 --> 00:05:42.410 questions all tangled up together. So thinking 00:05:42.410 --> 00:05:45.009 about this broader AI landscape, what's the takeaway 00:05:45.009 --> 00:05:47.800 for our careers and how we get information? Well, 00:05:47.860 --> 00:05:50.199 it's creating new jobs, definitely changing how 00:05:50.199 --> 00:05:53.040 we access news, and yeah, challenging the value 00:05:53.040 --> 00:05:55.139 of our existing skills. Okay, let's pivot then. 00:05:55.180 --> 00:05:57.199 Let's talk practical stuff. Tools, strategies, 00:05:57.459 --> 00:05:59.480 things you listening can actually use. I know 00:05:59.480 --> 00:06:01.259 a lot of people worry, especially if they run 00:06:01.259 --> 00:06:03.680 automation businesses, about these DIY tools 00:06:03.680 --> 00:06:06.480 maybe replacing them. It's a fair worry. But 00:06:06.480 --> 00:06:09.480 here's the thing. Most AI projects, they don't 00:06:09.480 --> 00:06:12.079 fail because the tech isn't good enough. They 00:06:12.079 --> 00:06:14.319 fail because of bad strategy, poor alignment 00:06:14.319 --> 00:06:16.639 with business goals. Ah, okay. So it's not just 00:06:16.639 --> 00:06:19.420 about the tool itself. Right. The key is to shift. 00:06:19.639 --> 00:06:22.019 Don't just be the person who implements the tool. 00:06:22.279 --> 00:06:25.819 Become that high -value strategic partner, the 00:06:25.819 --> 00:06:28.480 one who understands why you're using AI and how 00:06:28.480 --> 00:06:30.660 it fits the bigger picture. Makes sense. And 00:06:30.660 --> 00:06:33.470 for people who do want to build things. Maybe 00:06:33.470 --> 00:06:35.889 without being coding experts. Yeah, totally possible 00:06:35.889 --> 00:06:38.329 now. You can build your own custom AI apps without 00:06:38.329 --> 00:06:40.670 writing code. There are guides out there using 00:06:40.670 --> 00:06:44.430 tools like Firebase Studio for the backend stuff, 00:06:44.649 --> 00:06:48.529 database hosting. Right. And N8n for workflow 00:06:48.529 --> 00:06:50.810 automation. You can basically stitch together 00:06:50.810 --> 00:06:53.490 a real working app. Anyone can try it. It's kind 00:06:53.490 --> 00:06:55.870 of like playing with digital Lego blocks. That's 00:06:55.870 --> 00:06:57.970 pretty cool. Democratizing AI development a bit. 00:06:58.240 --> 00:07:00.500 Definitely. And even with existing tools like 00:07:00.500 --> 00:07:03.279 ChatGPT, becoming a real pro means learning specific 00:07:03.279 --> 00:07:05.720 techniques, how to refine your prompts, how to 00:07:05.720 --> 00:07:08.379 automate tasks. You know, I still wrestle with 00:07:08.379 --> 00:07:10.300 prompt drift myself sometimes. What's prompt 00:07:10.300 --> 00:07:14.019 drift again? It's when the AI's responses kind 00:07:14.019 --> 00:07:16.379 of change or get worse over time, even the same 00:07:16.379 --> 00:07:18.620 prompt. Makes it hard to get consistent results. 00:07:18.720 --> 00:07:21.180 So mastering prompting is really key if you want 00:07:21.180 --> 00:07:24.920 top -notch output. It's an art. Gotcha. And there 00:07:24.920 --> 00:07:26.639 are new tools popping up all the time, right? 00:07:26.779 --> 00:07:30.100 Oh, yeah. Loads. Like open memory. It syncs memory 00:07:30.100 --> 00:07:32.740 across different AIs. So you can pick up a conversation 00:07:32.740 --> 00:07:34.680 with one AI where you left off with another. 00:07:34.860 --> 00:07:37.920 Whoa, that sounds useful. Yeah. Or afo .dev. 00:07:38.519 --> 00:07:41.339 Phase one. Builds mobile apps in minutes. Even 00:07:41.339 --> 00:07:44.199 integrates Stripe for payments. In minutes. Seriously. 00:07:44.420 --> 00:07:47.800 Apparently. And browse. Anything that is an AI 00:07:47.800 --> 00:07:49.500 agent for your browser that can automate pretty 00:07:49.500 --> 00:07:51.800 much any task you do on the web sounds super 00:07:51.800 --> 00:07:53.560 powerful for getting stuff done. Okay, those 00:07:53.560 --> 00:07:56.279 sound seriously useful. Any others? Well, there 00:07:56.279 --> 00:07:59.800 are some quirkier ones too, like Mori. It's this 00:07:59.800 --> 00:08:02.660 timer that shows your age or even like a countdown 00:08:02.660 --> 00:08:05.980 to your estimated death in real time. Ah, okay. 00:08:06.439 --> 00:08:10.199 That's morbidly interesting. Chuckles. Yeah, 00:08:10.339 --> 00:08:12.839 definitely a conversation starter. And beep that 00:08:12.839 --> 00:08:15.220 out, an AI profanity filter for content creators. 00:08:15.459 --> 00:08:17.639 Could be handy for keeping things clean. Right. 00:08:17.720 --> 00:08:20.139 And just some quick hits from the industry that 00:08:20.139 --> 00:08:23.839 show how fast things are moving. Go for it. MidJourney 00:08:23.839 --> 00:08:27.220 has 17 new art styles. Google finally rolled 00:08:27.220 --> 00:08:30.620 out VO3, their video model, globally. About time. 00:08:30.939 --> 00:08:33.759 Daniel Gross, co -founder of SSI, he joined Meta's 00:08:33.759 --> 00:08:37.360 big AI lab. Meta's trying a new tactic, having 00:08:37.360 --> 00:08:39.759 chatbots message you first to keep you engaged. 00:08:39.980 --> 00:08:43.139 Oh, interesting. Proactive chatbots. And maybe 00:08:43.139 --> 00:08:45.860 the most amazing one. AI apparently gave fresh 00:08:45.860 --> 00:08:48.460 hope for treating male infertility, like, in 00:08:48.460 --> 00:08:51.320 hours. Yeah. A huge potential medical breakthrough. 00:08:51.580 --> 00:08:54.269 Wow. See? The pace is just incredible. These 00:08:54.269 --> 00:08:56.230 tools are really changing what's possible for 00:08:56.230 --> 00:08:58.529 everyone. So for the everyday user, how can they 00:08:58.529 --> 00:09:01.289 best leverage all these new AI capabilities that 00:09:01.289 --> 00:09:03.669 are coming out so fast? Really, by using these 00:09:03.669 --> 00:09:07.049 smart tools wisely and, crucially, getting better 00:09:07.049 --> 00:09:08.990 at understanding those prompt techniques. Okay, 00:09:09.049 --> 00:09:11.169 now for the part that feels, well, feels like 00:09:11.169 --> 00:09:13.250 a pretty big deal, maybe even a little unsettling. 00:09:13.289 --> 00:09:15.730 Let's talk about Centaur. Right, Centaur. So 00:09:15.730 --> 00:09:18.929 researchers at Helmholtz Munich in Germany, they 00:09:18.929 --> 00:09:20.970 trained this AI, and you called it mind reading 00:09:20.970 --> 00:09:24.490 earlier. It's shockingly good at predicting what 00:09:24.490 --> 00:09:27.129 humans will choose to do next. How did they train 00:09:27.129 --> 00:09:30.830 it? Get this. 10 million real choices from over 00:09:30.830 --> 00:09:35.450 50 ,000 actual people across 160 different psychology 00:09:35.450 --> 00:09:38.690 experiments. 10 million data points on human 00:09:38.690 --> 00:09:42.080 choice. Yeah. Whoa. Imagine scaling that kind 00:09:42.080 --> 00:09:44.460 of insight, understanding human decision -making 00:09:44.460 --> 00:09:46.879 on a massive, massive scale. The implications 00:09:46.879 --> 00:09:49.519 are just huge. And they built it using Meta's 00:09:49.519 --> 00:09:52.600 Alama 3 .1 model. Yep, a standard large language 00:09:52.600 --> 00:09:54.340 model. They basically turned these psychology 00:09:54.340 --> 00:09:57.179 tasks into plain English descriptions. Then they 00:09:57.179 --> 00:09:59.159 fine -tuned the model, but only tweaked like 00:09:59.159 --> 00:10:01.940 0 .15 % of its parameters. Tiny adjustment. And 00:10:01.940 --> 00:10:04.289 the whole training took... Five days. Just five 00:10:04.289 --> 00:10:06.889 days to get these incredible results. It's ridiculously 00:10:06.889 --> 00:10:09.129 fast. Incredible results meaning how good was 00:10:09.129 --> 00:10:11.830 it? Okay, so it went up against 14 classic cognitive 00:10:11.830 --> 00:10:13.909 models from psychology. You know, established 00:10:13.909 --> 00:10:15.889 theories of how we make decisions. Centaur beat 00:10:15.889 --> 00:10:20.309 them in 31 out of 32 different tasks. Wow. It 00:10:20.309 --> 00:10:23.590 just outperformed decades of psychological modeling. 00:10:23.730 --> 00:10:25.809 Pretty much. And even when the researchers tried 00:10:25.809 --> 00:10:28.149 to trick it, like changing the details in stories 00:10:28.149 --> 00:10:30.809 or throwing in new logic problems it hadn't seen, 00:10:31.009 --> 00:10:34.549 Centaur just adapted. Like a human would. So 00:10:34.549 --> 00:10:37.389 it's not just memorizing patterns, it's generalizing. 00:10:37.570 --> 00:10:39.850 Exactly. It seems to be showing this deeper level 00:10:39.850 --> 00:10:42.269 of adaptation. And the wildest part you mentioned 00:10:42.269 --> 00:10:46.529 earlier, its internal structure started looking 00:10:46.529 --> 00:10:49.429 like a human brain. Yeah, that's the kicker. 00:10:49.490 --> 00:10:52.009 Without being trained on any actual brain scan 00:10:52.009 --> 00:10:55.169 data, nothing neurological, it just converged. 00:10:55.519 --> 00:10:58.159 It organized itself in a way that mirrors how 00:10:58.159 --> 00:11:00.340 our brains process things. That feels profound, 00:11:00.600 --> 00:11:02.320 like it found the optimal structure independently. 00:11:02.779 --> 00:11:05.399 It does, and it gets better. Centaur actually 00:11:05.399 --> 00:11:07.700 discovered a completely new decision -making 00:11:07.700 --> 00:11:10.360 strategy, one that performed better than existing 00:11:10.360 --> 00:11:13.580 psychological theories. The AI found a new way 00:11:13.580 --> 00:11:15.759 we make decisions. Yep, which just flips things 00:11:15.759 --> 00:11:18.139 around, right? It raises this huge question. 00:11:18.299 --> 00:11:21.139 What can AI teach us about ourselves, about our 00:11:21.139 --> 00:11:23.899 own minds? It's like getting insights from, well... 00:11:24.139 --> 00:11:26.580 From a non -human intelligence. So Centaur is 00:11:26.580 --> 00:11:29.320 like having a virtual human test subject. You 00:11:29.320 --> 00:11:32.240 can run countless simulations. Exactly. Scientists 00:11:32.240 --> 00:11:35.620 can simulate behavior, test out theories, explore 00:11:35.620 --> 00:11:39.059 cognition without needing labs, without years 00:11:39.059 --> 00:11:41.600 of recruiting people for trials. Think about 00:11:41.600 --> 00:11:44.460 what that could do for mental health research. 00:11:44.990 --> 00:11:48.230 behavioral design, education. Marketing. Oh yeah, 00:11:48.289 --> 00:11:50.370 definitely marketing too. The efficiency gains 00:11:50.370 --> 00:11:52.690 could be absolutely massive. What? There's always 00:11:52.690 --> 00:11:54.710 a but, isn't there? What's the downside? The 00:11:54.710 --> 00:11:57.750 flip side is pretty significant. If AI can simulate 00:11:57.750 --> 00:12:00.500 your decisions this accurately. It can manipulate 00:12:00.500 --> 00:12:03.240 them? Precisely. It can be used to nudge you, 00:12:03.279 --> 00:12:06.279 maybe exploit your biases, influence your behavior 00:12:06.279 --> 00:12:09.440 at a huge scale. This could be maybe the first 00:12:09.440 --> 00:12:11.659 real step towards what people call cognitive 00:12:11.659 --> 00:12:14.960 AGI. Artificial general intelligence, but focused 00:12:14.960 --> 00:12:17.059 on thought processes. Right. It's not conscious, 00:12:17.139 --> 00:12:19.820 let's be clear. Not sentient like us. But it 00:12:19.820 --> 00:12:21.519 might be getting close enough to mimicking our 00:12:21.519 --> 00:12:24.179 cognitive processes that it fundamentally changes 00:12:24.179 --> 00:12:26.480 the game. And that makes it an incredibly powerful 00:12:26.480 --> 00:12:29.240 tool. Powerful and with a really serious potential. 00:12:31.700 --> 00:12:37.019 So this predictive power, does it ultimately 00:12:37.019 --> 00:12:40.059 open more doors for understanding ourselves or 00:12:40.059 --> 00:12:43.980 does it close off more avenues for genuine human 00:12:43.980 --> 00:12:46.740 choice and autonomy? That's the question, isn't 00:12:46.740 --> 00:12:48.759 it? It definitely opens huge doors for research. 00:12:49.000 --> 00:12:51.340 Yeah. But yeah, it raises very serious concerns 00:12:51.340 --> 00:12:53.960 about manipulation and autonomy. OK, so wrapping 00:12:53.960 --> 00:12:56.299 this all up. What does this mean for you listening 00:12:56.299 --> 00:13:00.279 right now? We've covered a lot. From Meta's big 00:13:00.279 --> 00:13:03.440 AI dreams, maybe learning a bit from their metaverse 00:13:03.440 --> 00:13:06.559 bumps, to these incredible leaps like Baidu's 00:13:06.559 --> 00:13:08.840 video generation. We looked at new tools you 00:13:08.840 --> 00:13:11.000 can use and how the job market is shifting under 00:13:11.000 --> 00:13:12.879 our feet. Yeah, the big idea, I think, is just 00:13:12.879 --> 00:13:15.539 the sheer speed, the accelerating pace of AI 00:13:15.539 --> 00:13:17.940 development. It's almost dizzying. Right. from 00:13:17.940 --> 00:13:20.580 the practical tools you can unload today to something 00:13:20.580 --> 00:13:22.980 as profound as Centaur. AI's reach is expanding 00:13:22.980 --> 00:13:25.340 so fast it's touching everything, how we get 00:13:25.340 --> 00:13:28.379 news, how we work, even how we understand what 00:13:28.379 --> 00:13:30.840 it means to be human. That line between the hype 00:13:30.840 --> 00:13:33.139 and the actual reality seems blurrier than ever. 00:13:33.320 --> 00:13:35.120 Especially with tools that can predict our own 00:13:35.120 --> 00:13:37.700 behavior with this kind of accuracy, it's constantly 00:13:37.700 --> 00:13:40.879 shifting. This deep dive really paints a picture 00:13:40.879 --> 00:13:43.320 of a future that's, well, it's full of incredible 00:13:43.320 --> 00:13:45.500 promise, but also really complex challenges. 00:13:45.500 --> 00:13:48.440 Definitely both. And as AI gets woven deeper 00:13:48.440 --> 00:13:51.259 into our lives, predicting our choices, maybe 00:13:51.259 --> 00:13:54.379 even sensing our emotions, it leaves us with 00:13:54.379 --> 00:13:56.100 a pretty crucial question for you to think about. 00:13:56.259 --> 00:13:58.580 Yeah. If an AI can predict what you're going 00:13:58.580 --> 00:14:01.460 to do. How much of your decision -making is still 00:14:01.460 --> 00:14:03.980 truly, authentically your own? That's a heavy 00:14:03.980 --> 00:14:06.379 one. Maybe think about how knowing these capabilities 00:14:06.379 --> 00:14:09.559 exist might change how you make choices. What 00:14:09.559 --> 00:14:12.460 does it all mean for our future autonomy in a 00:14:12.460 --> 00:14:15.460 world that's increasingly driven by AI? Now, 00:14:15.460 --> 00:14:16.159 T .O. Rowe music.