WEBVTT 00:00:00.000 --> 00:00:02.620 What if you could build a powerful app? Not by 00:00:02.620 --> 00:00:05.740 writing a single line of code, but just by describing 00:00:05.740 --> 00:00:08.800 your idea. The future of creation might just 00:00:08.800 --> 00:00:12.900 be clarity, not syntax. Welcome, welcome back 00:00:12.900 --> 00:00:16.160 everyone to another deep dive. Today, we're plunging 00:00:16.160 --> 00:00:19.899 headfirst into the accelerating pace of AI advancements. 00:00:20.320 --> 00:00:22.559 it's a really fascinating landscape right now 00:00:22.559 --> 00:00:24.839 absolutely today we're unpacking a whole stack 00:00:24.839 --> 00:00:27.339 of fresh insights really from the frontier of 00:00:27.339 --> 00:00:29.719 artificial intelligence we're going to explore 00:00:29.719 --> 00:00:31.940 breakthrough tools letting non -coders build 00:00:31.940 --> 00:00:35.280 full applications which is huge yeah we'll dive 00:00:35.280 --> 00:00:37.799 into some frankly surprising ai achievements 00:00:37.799 --> 00:00:40.659 and the intense rivalries driving them forward 00:00:40.659 --> 00:00:43.320 and then we'll get a glimpse into a future where 00:00:43.320 --> 00:00:46.570 ai might even sort of predict our thoughts. It's 00:00:46.570 --> 00:00:48.229 going to be quite a journey today. Okay, let's 00:00:48.229 --> 00:00:50.229 get into it. Starting with something that honestly 00:00:50.229 --> 00:00:52.549 feels like a major shift in how software gets 00:00:52.549 --> 00:00:56.090 made. Vercel, a name many web devs know, they 00:00:56.090 --> 00:00:59.030 just rebranded their AI builder from v0 .dev 00:00:59.030 --> 00:01:02.469 to v0 .app. Right. And their claim is, well, 00:01:02.549 --> 00:01:05.209 incredibly bold. They're saying Vercel just killed 00:01:05.209 --> 00:01:08.109 the I can't code excuse forever. That is a huge 00:01:08.109 --> 00:01:10.680 statement, isn't it? I mean, what does vzero 00:01:10.680 --> 00:01:13.959 .app actually do to back that up? How's it different 00:01:13.959 --> 00:01:16.299 from earlier attempts at these prompt -to -code 00:01:16.299 --> 00:01:17.819 tools? They often felt like they needed a lot 00:01:17.819 --> 00:01:20.299 of babysitting. It really is a complete mindset 00:01:20.299 --> 00:01:23.579 shift, I think. With the older versions or, you 00:01:23.579 --> 00:01:26.000 know, lots of other tools, you'd prompt something 00:01:26.000 --> 00:01:28.859 like, build me a dashboard for my podcast analytics. 00:01:29.140 --> 00:01:30.980 Right. Okay. And then you'd get into this long 00:01:30.980 --> 00:01:33.000 back and forth, tweaking the layout, refining 00:01:33.000 --> 00:01:35.620 the logic, adjusting the design, figuring out 00:01:35.620 --> 00:01:38.680 data flows. It was a lot of manual work, a lot 00:01:38.680 --> 00:01:41.799 of specific instructions. Right. Iterative. Exactly. 00:01:42.060 --> 00:01:45.079 But vZero .app, it... aims to change that whole 00:01:45.079 --> 00:01:48.420 process. The vision is you prompt once, clearly 00:01:48.420 --> 00:01:50.840 defining your idea, and it's designed to give 00:01:50.840 --> 00:01:52.980 you a full working app. A full app. Yeah, the 00:01:52.980 --> 00:01:55.079 front end, the back end, the actual copy, even 00:01:55.079 --> 00:01:57.319 the underlying logic. It's meant to be a complete 00:01:57.319 --> 00:02:00.180 solution right out of the box. So, okay, it's 00:02:00.180 --> 00:02:02.620 not just spitting out a code snippet or a basic 00:02:02.620 --> 00:02:05.200 wireframe. It's the whole system. How does it 00:02:05.200 --> 00:02:07.359 actually manage all that complexity automatically? 00:02:07.719 --> 00:02:09.509 What's happening under the hood there? Okay, 00:02:09.550 --> 00:02:10.750 this is where it gets really interesting. It 00:02:10.750 --> 00:02:12.689 plans your request like an autonomous agent. 00:02:12.830 --> 00:02:14.810 Now, when we say autonomous agent, think of it 00:02:14.810 --> 00:02:17.349 like a smart system that can take initiative, 00:02:17.530 --> 00:02:21.849 right? It performs tasks without you needing 00:02:21.849 --> 00:02:25.590 to give constant step -by -step prompts. It doesn't 00:02:25.590 --> 00:02:27.789 just wait. It actually thinks ahead, figures 00:02:27.789 --> 00:02:30.330 out how to fulfill your request. It actively 00:02:30.330 --> 00:02:33.030 searches the web for info, gives you citations 00:02:33.030 --> 00:02:35.930 too. It can read your existing files, look at 00:02:35.930 --> 00:02:38.330 live websites to understand design patterns or 00:02:38.330 --> 00:02:41.949 data structures. It can even generate design 00:02:41.949 --> 00:02:44.449 inspiration with screenshots. If it hits errors, 00:02:44.650 --> 00:02:46.969 it often fixes them on its own. Automatically. 00:02:47.150 --> 00:02:49.069 Yeah, automatically. And it integrates with other 00:02:49.069 --> 00:02:50.750 tools you might be using, creating this smooth 00:02:50.750 --> 00:02:53.620 end -to -end flow, all without you coding. That 00:02:53.620 --> 00:02:57.060 sounds incredibly powerful, almost mind -bending 00:02:57.060 --> 00:02:58.960 in scope. How are they handling the business 00:02:58.960 --> 00:03:01.060 side? Because compute costs for this kind of 00:03:01.060 --> 00:03:04.099 AI, they can get massive, right? That's a great 00:03:04.099 --> 00:03:06.060 question. What's fascinating is their business 00:03:06.060 --> 00:03:09.219 model. Instead of charging per app or per user, 00:03:09.400 --> 00:03:13.240 they use token pricing. And they sell those tokens 00:03:13.240 --> 00:03:16.370 essentially at cost. At cost. Pretty much. Tokens, 00:03:16.370 --> 00:03:18.430 you know, they're like the basic units AI models 00:03:18.430 --> 00:03:21.090 process. Vercel treats them like a raw resource. 00:03:21.409 --> 00:03:23.949 This approach helps them avoid that compute cost 00:03:23.949 --> 00:03:27.169 collapse problem that some other AI dev tools 00:03:27.169 --> 00:03:30.110 have run into where running the AI just becomes 00:03:30.110 --> 00:03:32.199 too expensive. It's a smart way to scale and 00:03:32.199 --> 00:03:34.219 keep it accessible. Okay, that makes sense. So 00:03:34.219 --> 00:03:36.300 pulling back, what does this mean for the bigger 00:03:36.300 --> 00:03:39.020 picture? If this tech really works as advertised, 00:03:39.479 --> 00:03:44.020 who benefits most? Does this truly democratize 00:03:44.020 --> 00:03:47.139 building complex software for non -coders? Yeah, 00:03:47.180 --> 00:03:49.460 I think the big idea here is that app building 00:03:49.460 --> 00:03:52.099 now belongs more to the people who understand 00:03:52.099 --> 00:03:53.919 the problem, not just the folks who can write 00:03:53.919 --> 00:03:56.659 the code. Right. Your only job is clarity. not 00:03:56.659 --> 00:03:59.860 syntax. It totally shifts the focus from technical 00:03:59.860 --> 00:04:02.280 skill to just having a clear vision and defining 00:04:02.280 --> 00:04:04.900 the problem well. So yes, it significantly lowers 00:04:04.900 --> 00:04:06.900 that technical barrier, empowering people with 00:04:06.900 --> 00:04:09.159 great ideas. So just to clarify then, does this 00:04:09.159 --> 00:04:11.699 really mean pretty much anyone can build complex 00:04:11.699 --> 00:04:14.500 software now without needing coding experience? 00:04:15.060 --> 00:04:17.680 Well, it massively simplifies the process, focusing 00:04:17.680 --> 00:04:20.339 effort on the core idea, less on the code itself. 00:04:20.579 --> 00:04:23.660 Okay. Moving on, the AI world is just constantly 00:04:23.660 --> 00:04:25.720 buzzing, isn't it? This past week, no exception. 00:04:25.800 --> 00:04:29.079 We saw some incredible milestones and, yeah, 00:04:29.160 --> 00:04:31.360 a fair bit of competitive drama, too. Absolutely. 00:04:31.579 --> 00:04:34.740 Let's start with something pretty amazing. OpenAI's 00:04:34.740 --> 00:04:37.779 reasoning model. And get this, it wasn't even 00:04:37.779 --> 00:04:40.759 specifically fine -tuned for coding. It ranked 00:04:40.759 --> 00:04:44.800 an astonishing sixth globally at the 2025 International 00:04:44.800 --> 00:04:49.339 Olympiad in Informatics. Sixth. Against top student 00:04:49.339 --> 00:04:52.740 coders. Exactly. The IOI. That's this huge global 00:04:52.740 --> 00:04:55.019 competition for the best high school programmers. 00:04:55.279 --> 00:04:58.259 Whoa. I mean, imagine a model not even explicitly 00:04:58.259 --> 00:05:00.860 trained for coding ranking sixth globally against 00:05:00.860 --> 00:05:03.420 human prodigies. It's just it's a mind bending 00:05:03.420 --> 00:05:06.160 leap in general AI ability. That really shows 00:05:06.160 --> 00:05:08.199 some deep reasoning power. Totally impressive 00:05:08.199 --> 00:05:10.519 foundational reasoning. That is remarkable for 00:05:10.519 --> 00:05:12.920 a non -specialized model. And speaking of open 00:05:12.920 --> 00:05:15.680 AI, they also just put out a new GPT -5 prompting 00:05:15.680 --> 00:05:17.889 guide. I hear it's packed with best practices, 00:05:17.949 --> 00:05:19.670 you know, to really unlock what the model can 00:05:19.670 --> 00:05:22.009 do, which I imagine is helpful for anyone trying 00:05:22.009 --> 00:05:23.670 to get the most out of these tools. You know, 00:05:23.689 --> 00:05:25.730 I still wrestle with prompt drift myself sometimes, 00:05:25.810 --> 00:05:27.829 so guides like that sound incredibly practical. 00:05:28.069 --> 00:05:30.470 Oh, yeah, definitely helpful. And the competition 00:05:30.470 --> 00:05:32.810 is heating up everywhere, even in government. 00:05:33.129 --> 00:05:36.670 Just a week after OpenAI announced that $1 a 00:05:36.670 --> 00:05:39.329 year chat GPT enterprise deal, but just for the 00:05:39.329 --> 00:05:41.550 U .S. executive branch. Right, I saw that. Well, 00:05:41.649 --> 00:05:44.519 Claude made a counter move. Now, Claude is available 00:05:44.519 --> 00:05:46.600 to all three branches of government for just 00:05:46.600 --> 00:05:50.379 $1 a year. Ah, interesting play. Broader reach. 00:05:50.720 --> 00:05:53.660 Exactly. A clear grab for wider adoption within 00:05:53.660 --> 00:05:55.579 the federal government. And Claude's also improving 00:05:55.579 --> 00:05:58.040 its own features, right, with a new memory function. 00:05:58.459 --> 00:06:01.319 Yeah, that's a big one. It can now remember and 00:06:01.319 --> 00:06:04.259 reference your past chats, handle much longer 00:06:04.259 --> 00:06:07.420 prompts, and unlike ChatGPT's auto -profile thing, 00:06:07.579 --> 00:06:10.660 you explicitly tell Claude when to remember something 00:06:10.660 --> 00:06:13.759 for later. So user -triggered memory, that gives 00:06:13.759 --> 00:06:15.620 you more control. Definitely. More predictable 00:06:15.620 --> 00:06:17.540 interactions if that's what you want. But the 00:06:17.540 --> 00:06:20.240 drama doesn't stop there, of course. Elon Musk's 00:06:20.240 --> 00:06:23.500 XAI is reportedly suing Apple. They're alleging 00:06:23.500 --> 00:06:26.199 Apple rigged App Store rankings to favor chat 00:06:26.199 --> 00:06:29.220 GPT and blocked Grok AI. Always something with 00:06:29.220 --> 00:06:31.660 Musk and AI companies. And then you've got Sam 00:06:31.660 --> 00:06:34.959 Altman from OpenAI. He's working on Merge Labs 00:06:34.959 --> 00:06:38.540 now. It's a new brain interface startup. Brain 00:06:38.540 --> 00:06:41.620 interface, like Neuralink. Looks like a direct 00:06:41.620 --> 00:06:44.220 challenge to Musk's Neuralink, yeah. Pushing 00:06:44.220 --> 00:06:46.819 competition beyond just software right into, 00:06:46.959 --> 00:06:49.600 well, the human mind interface. That's a whole 00:06:49.600 --> 00:06:52.379 other level of rivalry. Wow. And other news. 00:06:52.620 --> 00:06:55.980 Well, Character AI, that platform with like 18 00:06:55.980 --> 00:06:59.459 million AI chatbot personalities. Yeah, I've 00:06:59.459 --> 00:07:01.379 heard of them. They just raised $150 million, 00:07:01.699 --> 00:07:04.420 hitting a billion -dollar valuation. That's despite 00:07:04.420 --> 00:07:06.860 facing various legal challenges. So personality 00:07:06.860 --> 00:07:09.300 -driven chatbots are still a huge growth area. 00:07:09.639 --> 00:07:12.120 Okay, so looking at all this, the breakthroughs, 00:07:12.120 --> 00:07:14.740 the government deals, the lawsuits, the new ventures, 00:07:14.800 --> 00:07:16.480 what's the biggest takeaway here? What's the 00:07:16.480 --> 00:07:19.220 core theme? It's just clear. AI innovation is 00:07:19.220 --> 00:07:21.579 accelerating like crazy across so many different 00:07:21.579 --> 00:07:24.540 fronts, sparking really intense competition everywhere. 00:07:24.800 --> 00:07:27.519 Moving along then. The sheer number of new AI 00:07:27.519 --> 00:07:29.920 tools hitting the market every day is just staggering. 00:07:30.079 --> 00:07:31.819 It feels like a constant stream of innovation 00:07:31.819 --> 00:07:35.180 making complex stuff simpler. It really is. Here 00:07:35.180 --> 00:07:37.519 are just a few of the new empowered AI tools 00:07:37.519 --> 00:07:40.949 that caught our eye. Shows how fast AI is getting 00:07:40.949 --> 00:07:44.949 into specific everyday tasks. Like for content 00:07:44.949 --> 00:07:47.110 creators, there's Social Rails. It makes content 00:07:47.110 --> 00:07:49.329 and schedules it to nine social platforms automatically. 00:07:49.670 --> 00:07:53.009 Nine platforms, wow. Then there's Nextpost. Generates 00:07:53.009 --> 00:07:55.889 social posts in seconds. Optimizes the tone for 00:07:55.889 --> 00:07:58.389 your brand voice. Handy. For workflow automation, 00:07:58.910 --> 00:08:02.629 N8NGini sounds incredible. Turns ideas into workflows 00:08:02.629 --> 00:08:05.930 from just a three -word prompt. Three words, 00:08:06.189 --> 00:08:10.199 seriously? Yeah. And for visuals, SVGenius. Create 00:08:10.199 --> 00:08:12.879 stunning animations from text descriptions. These 00:08:12.879 --> 00:08:15.160 aren't just toys. They're like hyper -specialized 00:08:15.160 --> 00:08:18.139 tools changing how specific jobs get done. It 00:08:18.139 --> 00:08:20.379 really is about making the complex almost trivially 00:08:20.379 --> 00:08:22.740 simple sometimes. And then we have the AI quick 00:08:22.740 --> 00:08:25.279 hits. These are often smaller updates, but they're 00:08:25.279 --> 00:08:27.160 really key signals for where things are headed 00:08:27.160 --> 00:08:30.480 for us, the everyday users. Like GPT -5 now offers 00:08:30.480 --> 00:08:33.460 new modes, auto, fast, or thinking. Right, more 00:08:33.460 --> 00:08:36.000 control. Exactly. More control over how it processes 00:08:36.000 --> 00:08:38.399 info. Big deal for efficiency, depending on what 00:08:38.399 --> 00:08:41.009 you're doing. And CloudSignit 4 just massively 00:08:41.009 --> 00:08:44.029 boosted its context window, supporting one million 00:08:44.029 --> 00:08:46.669 tokens now. One million tokens. Explain context 00:08:46.669 --> 00:08:49.269 window again quickly. Sure. Think of it as the 00:08:49.269 --> 00:08:52.029 AI's short -term memory, how much info it can 00:08:52.029 --> 00:08:55.029 hold and consider at once. A million tokens is 00:08:55.029 --> 00:08:57.149 a five -fold increase. It means you can feed 00:08:57.149 --> 00:09:00.289 it, like the entire Harry Potter series, or hours 00:09:00.289 --> 00:09:02.450 of meeting transcripts, and it can analyze it 00:09:02.450 --> 00:09:04.759 all together without losing track. That is a 00:09:04.759 --> 00:09:07.019 huge leap in comprehension. Okay, what else? 00:09:07.179 --> 00:09:09.519 Well, YouTube's testing a new AI age verification 00:09:09.519 --> 00:09:12.820 system in the U .S., shows AI moving into safety 00:09:12.820 --> 00:09:15.730 and compliance roles on big platforms. Important 00:09:15.730 --> 00:09:18.590 stuff. And a really big one. Apple's adding GPT 00:09:18.590 --> 00:09:22.710 -5 to iOS 26 and Mac OS Talo 26 next month. Advanced 00:09:22.710 --> 00:09:24.570 AI baked right into our phones and computers. 00:09:24.809 --> 00:09:26.250 That's going to be interesting to see how it 00:09:26.250 --> 00:09:27.929 integrates. Definitely. Plus that interesting 00:09:27.929 --> 00:09:30.870 rumor about Perplexity, the AI search engine, 00:09:30.970 --> 00:09:34.830 offering to buy Google's Chrome Browner for $34 00:09:34.830 --> 00:09:39.490 .5 billion. $34 billion for Chrome. Yeah. Shows 00:09:39.490 --> 00:09:41.490 the ambition and the sheer amount of money swirling 00:09:41.490 --> 00:09:43.769 around trying to redefine how we even get information 00:09:43.769 --> 00:09:47.320 online. How are all these quick hits, these daily 00:09:47.320 --> 00:09:50.019 updates, shaping the immediate future for us 00:09:50.019 --> 00:09:52.299 as users? I think they just show this incredibly 00:09:52.299 --> 00:09:56.200 rapid integration into everyday tech, plus massive 00:09:56.200 --> 00:09:58.740 new capabilities becoming available almost constantly. 00:09:58.940 --> 00:10:01.279 Welcome back to the Deep Dive. Our final segment 00:10:01.279 --> 00:10:03.679 today looks at something really captivating from 00:10:03.679 --> 00:10:05.799 what we call the AI chart, where we spotlight 00:10:05.799 --> 00:10:08.879 research hinting at future possibilities. And 00:10:08.879 --> 00:10:13.570 this week, it's Meta's new AI model, Tribe. It's 00:10:13.570 --> 00:10:15.730 making waves because it can apparently predict 00:10:15.730 --> 00:10:18.210 how you'll react to content without scanning 00:10:18.210 --> 00:10:20.129 your brain. Yeah, this is fascinating stuff. 00:10:20.509 --> 00:10:24.110 Tribe won first place in the Algonauts 2025 Brain 00:10:24.110 --> 00:10:26.950 Modeling Challenge. That's a top competition 00:10:26.950 --> 00:10:29.690 for neuroscience and AI trying to build better 00:10:29.690 --> 00:10:31.889 models of the brain and its main achievement. 00:10:31.950 --> 00:10:34.490 It can predict brain activity while someone watches 00:10:34.490 --> 00:10:36.870 a movie without needing a scanner on their head. 00:10:37.200 --> 00:10:39.620 It's a big step in understanding how we process 00:10:39.620 --> 00:10:41.860 information. Okay, wait. If it's not scanning 00:10:41.860 --> 00:10:43.559 your brain, how is it doing this? What's the 00:10:43.559 --> 00:10:46.480 input it's using? So Tribe looks at three main 00:10:46.480 --> 00:10:49.019 things from films and shows. The visual data, 00:10:49.159 --> 00:10:51.620 the video itself, what's happening. The auditory 00:10:51.620 --> 00:10:54.940 input, the soundtrack, music, sound effects, 00:10:55.259 --> 00:10:57.960 ambient noise. Gotcha. And the language, the 00:10:57.960 --> 00:11:00.500 dialogue, any text on screen. It combines all 00:11:00.500 --> 00:11:02.740 three of these senses to predict brain activity. 00:11:03.179 --> 00:11:05.279 And how did it learn to do that so well? Must 00:11:05.279 --> 00:11:07.419 have been a lot of data. Oh, yeah, exactly. It 00:11:07.419 --> 00:11:09.600 was trained on data from people who watched over 00:11:09.600 --> 00:11:12.879 80 hours of different content. From that, it 00:11:12.879 --> 00:11:15.000 learned to simulate brain activity across about 00:11:15.000 --> 00:11:17.759 1 ,000 different brain regions just by analyzing 00:11:17.759 --> 00:11:21.220 the media. 1 ,000 regions. Yeah. And the accuracy 00:11:21.220 --> 00:11:24.320 is apparently wild. It beats models that only 00:11:24.320 --> 00:11:27.299 use one sense, like just visual or just audio, 00:11:27.399 --> 00:11:30.789 by about 30%. especially in those key brain areas 00:11:30.789 --> 00:11:33.049 for higher level thinking and emotional response. 00:11:33.250 --> 00:11:36.309 This is, yeah, truly mind bending. So what's 00:11:36.309 --> 00:11:38.950 the real implication here? It's not reading thoughts, 00:11:39.070 --> 00:11:41.629 you said, but it knows what content will make 00:11:41.629 --> 00:11:44.049 you react. Right. It means it could potentially 00:11:44.049 --> 00:11:46.450 see what kind of content will grab your focus 00:11:46.450 --> 00:11:48.629 or make you laugh or make you keep scrolling 00:11:48.629 --> 00:11:51.289 before you even realize you're reacting. So it 00:11:51.289 --> 00:11:53.629 knows what works on our brains before our brain 00:11:53.629 --> 00:11:56.529 even fully processes it. Kind of. It knows what's 00:11:56.529 --> 00:11:59.580 likely to work. based on learned patterns. It's 00:11:59.580 --> 00:12:01.700 crucial to remember it's not reading your mind 00:12:01.700 --> 00:12:04.679 yet, but it knows what your mind will probably 00:12:04.679 --> 00:12:07.620 do next based on the input. It's predicting engagement 00:12:07.620 --> 00:12:10.019 patterns. Okay, so what are the biggest implications 00:12:10.019 --> 00:12:12.460 then of being able to predict brain activity 00:12:12.460 --> 00:12:15.539 just from the content itself? Well, it could 00:12:15.539 --> 00:12:17.639 fundamentally revolutionize how content gets 00:12:17.639 --> 00:12:20.559 made and how digital experiences become hyper 00:12:20.559 --> 00:12:22.840 -personalized for you. Okay, so let's connect 00:12:22.840 --> 00:12:25.220 the dots here. We talked about Vercel democratizing 00:12:25.220 --> 00:12:27.700 app building. Right, focusing on the idea, not 00:12:27.700 --> 00:12:30.600 the code. Then OpenAI's leap in core reasoning, 00:12:30.840 --> 00:12:33.480 Claude's memory and context. Pushing the boundaries 00:12:33.480 --> 00:12:36.340 of AI intelligence itself, fueling that intense 00:12:36.340 --> 00:12:39.340 competition. And now Meta's tribe, starting to 00:12:39.340 --> 00:12:42.120 predict brain activity from media. A clear theme 00:12:42.120 --> 00:12:45.200 is emerging, isn't it? AI is rapidly democratizing 00:12:45.200 --> 00:12:47.519 creation, letting people focus on the what, not 00:12:47.519 --> 00:12:49.740 the how. Absolutely. And it's a pushing core 00:12:49.740 --> 00:12:52.200 intelligence forward while fueling massive innovation 00:12:52.200 --> 00:12:55.419 and rivalry. And perhaps most profoundly, as 00:12:55.419 --> 00:12:57.460 you said, it's starting to understand human cognition 00:12:57.460 --> 00:12:59.940 on a really deep level, like with tribe. The 00:12:59.940 --> 00:13:02.759 whole shift seems to be towards more intuitive, 00:13:02.980 --> 00:13:05.799 more human -like interactions with AI. Exactly. 00:13:05.879 --> 00:13:08.299 And what that means for you, for all of us, is 00:13:08.299 --> 00:13:10.500 that clarity of thought, being able to clearly 00:13:10.500 --> 00:13:13.840 define a problem or an idea that becomes way 00:13:13.840 --> 00:13:16.259 more valuable than just technical skill or knowing 00:13:16.259 --> 00:13:19.340 syntax. The machines handle more how, leaving 00:13:19.340 --> 00:13:22.259 us to master the what's. So here's a thought 00:13:22.259 --> 00:13:25.419 to leave you with. If AI is increasingly handling 00:13:25.419 --> 00:13:27.960 the how and maybe even starting to predict the 00:13:27.960 --> 00:13:30.799 what of our interactions, what does this actually 00:13:30.799 --> 00:13:33.980 mean for human creativity, for genuine ingenuity 00:13:33.980 --> 00:13:36.179 going forward? Something to ponder, perhaps, 00:13:36.340 --> 00:13:38.700 as these tools become even more woven into our 00:13:38.700 --> 00:13:41.399 lives. A truly thought -provoking question indeed. 00:13:41.580 --> 00:13:43.460 Thanks, everyone, for joining us on this deep 00:13:43.460 --> 00:13:45.639 dive today. Yeah, thanks for listening. We encourage 00:13:45.639 --> 00:13:47.759 you to keep asking questions, keep exploring 00:13:47.759 --> 00:13:50.240 these fascinating topics, and keep digging deeper. 00:13:50.399 --> 00:13:52.299 Until the next deep dive, stay curious.