WEBVTT 00:00:00.000 --> 00:00:02.580 You know, we spend so much of our time debating 00:00:02.580 --> 00:00:06.620 premium AI tools. We argue over which $20 subscription 00:00:06.620 --> 00:00:10.480 is technically superior, but we kind of miss 00:00:10.480 --> 00:00:13.140 the bigger picture sometimes. Right, yeah. Like 00:00:13.140 --> 00:00:17.120 the fact that by April 2026, a completely free 00:00:17.120 --> 00:00:21.420 AI model quietly approached one billion downloads. 00:00:21.739 --> 00:00:24.539 One billion. That is just a massive number. It 00:00:24.539 --> 00:00:27.039 really makes you realize that a massive, free, 00:00:27.559 --> 00:00:31.350 almost Android -like AI ecosystem. has quietly 00:00:31.350 --> 00:00:34.369 taken over. It absolutely has. And it's completely 00:00:34.369 --> 00:00:36.750 shifting the developer space. Welcome to the 00:00:36.750 --> 00:00:38.609 deep dive, everyone. I'm really looking forward 00:00:38.609 --> 00:00:41.390 to this one. Today, our mission is unpacking 00:00:41.390 --> 00:00:44.170 the Alibaba Quinn ecosystem. Yeah, and from the 00:00:44.170 --> 00:00:45.950 sources we've looked at, this is not just another 00:00:45.950 --> 00:00:48.210 browser chatbot. No, not at all. It's a seven 00:00:48.210 --> 00:00:50.729 -tool suite. It functions way less like a simple 00:00:50.729 --> 00:00:53.789 app and much more like a lightweight AI operating 00:00:53.789 --> 00:00:55.850 system. Exactly. It's a fundamental shift. It 00:00:55.850 --> 00:00:58.810 connects your local file system directly to cloud 00:00:58.810 --> 00:01:00.689 -based coding environments. I have to admit, 00:01:00.750 --> 00:01:03.070 I still wrestle with subscription fatigue myself. 00:01:03.210 --> 00:01:05.730 Oh, I think we all do, right? Yeah. You pay for 00:01:05.730 --> 00:01:08.370 a premium text model, then you need an image 00:01:08.370 --> 00:01:11.530 generator, then a coding assistant. It adds up 00:01:11.530 --> 00:01:15.829 so fast. There's just a real friction there. 00:01:15.930 --> 00:01:18.310 It becomes a heavy tax on the user. And well, 00:01:18.450 --> 00:01:20.709 that's exactly the vulnerability Alibaba is targeting 00:01:20.709 --> 00:01:23.170 here. They're just bypassing that $20 gateway 00:01:23.170 --> 00:01:25.510 entirely. They are. They're keeping their core 00:01:25.510 --> 00:01:28.969 frontier models free under an Apache 2 .0 open 00:01:28.969 --> 00:01:31.370 source license. It's a fascinating strategy. 00:01:31.469 --> 00:01:33.409 I mean, it really mirrors what Google did with 00:01:33.409 --> 00:01:35.530 Android in the early smartphone days. Oh, that's 00:01:35.530 --> 00:01:37.790 a perfect analogy. Google didn't try to sell 00:01:37.790 --> 00:01:39.530 the operating system. Right. They gave it away 00:01:39.530 --> 00:01:41.629 to hardware makers for free. They just wanted 00:01:41.629 --> 00:01:43.790 to control the ecosystem. Because they knew the 00:01:43.790 --> 00:01:46.109 monetization would naturally follow later. And 00:01:46.109 --> 00:01:48.010 it's working incredibly well for Quinn right 00:01:48.010 --> 00:01:51.310 now. Yeah, they've passed 200 million monthly 00:01:51.310 --> 00:01:54.750 active users. Over half of all open source model 00:01:54.750 --> 00:01:57.109 downloads are Quinn models now. People just care 00:01:57.109 --> 00:01:59.129 less about a tiny coding benchmark. They care 00:01:59.129 --> 00:02:01.109 about practical workflows they can actually use 00:02:01.109 --> 00:02:03.310 daily. Which is a great segue into where this 00:02:03.310 --> 00:02:06.170 actually starts. We usually think of AI as a 00:02:06.170 --> 00:02:08.370 remote brain on a server. Right, trapped in a 00:02:08.370 --> 00:02:11.889 browser tab. Exactly. But Quinn Desktop shifts 00:02:11.889 --> 00:02:14.509 the model directly onto your local machine. It 00:02:14.509 --> 00:02:16.889 basically takes over your actual desktop environment. 00:02:17.150 --> 00:02:18.909 Yeah, and the mechanism behind this is called 00:02:18.909 --> 00:02:21.490 MCP. It's been making a lot of waves recently. 00:02:21.930 --> 00:02:25.069 That stands for Model Context Protocol. Let me 00:02:25.069 --> 00:02:26.669 make sure I'm wrapping my head around this. If 00:02:26.669 --> 00:02:30.729 I had to define it, MCP is a bridge letting AI 00:02:30.729 --> 00:02:33.849 use your actual computer tools directly. That 00:02:33.849 --> 00:02:36.669 is exactly right. Normally, an AI is totally 00:02:36.669 --> 00:02:38.930 blind to your actual machine. It can't read your 00:02:38.930 --> 00:02:41.250 files. It doesn't know what apps are open. And 00:02:41.250 --> 00:02:43.169 it definitely can't click any buttons. It's like 00:02:43.169 --> 00:02:46.150 a brain in a jar. It has profound thoughts, but 00:02:46.150 --> 00:02:48.669 no hands to interact with the world. I love that 00:02:48.669 --> 00:02:52.069 metaphor, yes. MCP gives the AI hands. It lets 00:02:52.069 --> 00:02:55.030 Quen scan your local folders, rename documents, 00:02:55.189 --> 00:02:58.129 and use system utilities. Whoa. I mean, imagine 00:02:58.129 --> 00:03:00.889 an AI organizing your chaotic downloads folder 00:03:00.889 --> 00:03:04.729 automatically. Just scanning randomly named PDFs, 00:03:04.889 --> 00:03:06.689 renaming them and sorting them while you grab 00:03:06.689 --> 00:03:08.949 a coffee. It is a profound level of automation 00:03:08.949 --> 00:03:11.330 for daily productivity. But historically, setting 00:03:11.330 --> 00:03:13.969 up MCP has been a nightmare, right? Oh, completely. 00:03:14.210 --> 00:03:16.639 You had to act like a systems engineer. Editing 00:03:16.639 --> 00:03:19.400 complex JSON files, installing node servers. 00:03:19.419 --> 00:03:22.460 Adjusting with path variables. Yeah, it's intimidating. 00:03:22.900 --> 00:03:26.020 So does setting of MCP require running complicated 00:03:26.020 --> 00:03:28.680 local servers? No. The app handles everything 00:03:28.680 --> 00:03:31.740 internally with simple toggle switches. Two -sex 00:03:31.740 --> 00:03:34.259 silence. So the app handles it all with simple 00:03:34.259 --> 00:03:36.520 toggles. That's brilliant. Yeah. You just open 00:03:36.520 --> 00:03:39.159 the Quinn desktop settings, click the MCP tab, 00:03:39.479 --> 00:03:41.479 and just flip a switch for reconfigured tools. 00:03:41.710 --> 00:03:43.530 They're just abstracting away all that command 00:03:43.530 --> 00:03:46.629 line terror, making it a native OS feature. So 00:03:46.629 --> 00:03:48.590 once your local environment is organized, the 00:03:48.590 --> 00:03:51.310 next hurdle is building actual workflows. Right, 00:03:51.310 --> 00:03:53.710 moving from organizing files to creating entirely 00:03:53.710 --> 00:03:55.849 new applications in the browser. And that brings 00:03:55.849 --> 00:03:59.110 us to Quen Studio. This is where things get really 00:03:59.110 --> 00:04:01.810 creative. Yeah, Quen Studio has this feature 00:04:01.810 --> 00:04:04.849 called Artifacts. It's powered by their Quen 00:04:04.849 --> 00:04:07.770 3 .6 Plus model. I looked into how artifacts 00:04:07.770 --> 00:04:09.689 work, and the mechanics are just fascinating. 00:04:09.750 --> 00:04:12.110 It's not just spitting out text code. No, the 00:04:12.110 --> 00:04:14.819 model is actually writing front -end code. usually 00:04:14.819 --> 00:04:17.839 React components. And then the browser instantly 00:04:17.839 --> 00:04:20.959 renders that code in an isolated iframe right 00:04:20.959 --> 00:04:23.199 next to your chat. You literally go from a text 00:04:23.199 --> 00:04:25.899 prompt to a fully interactive user interface 00:04:25.899 --> 00:04:29.060 in seconds. It totally removes the barrier to 00:04:29.060 --> 00:04:31.360 entry for software creation. Let's ground this 00:04:31.360 --> 00:04:33.939 with a specific example from the sources, the 00:04:33.939 --> 00:04:37.079 Fit Menu AI app. Oh yeah, the meal planning app. 00:04:37.100 --> 00:04:39.759 If I have zero coding experience, how do I build 00:04:39.759 --> 00:04:42.259 that? It's as simple as chatting. You tell Q 00:04:42.259 --> 00:04:45.240 you want a meal planning app. You ask for input 00:04:45.240 --> 00:04:47.939 fields for a grocery budget, cooking times, and 00:04:47.939 --> 00:04:49.980 dietary restrictions. And because of that rendering 00:04:49.980 --> 00:04:53.160 engine, it instantly builds a working UI. You 00:04:53.160 --> 00:04:55.500 can type your budget in, select vegan from a 00:04:55.500 --> 00:04:58.560 dropdown, and hit generate. And it outputs a 00:04:58.560 --> 00:05:00.980 structured weekly meal plan and a shopping list. 00:05:01.290 --> 00:05:03.670 It feels like having a senior developer sitting 00:05:03.670 --> 00:05:05.769 right over your shoulder. It's incredible for 00:05:05.769 --> 00:05:08.089 lightweight internal workflows, like spinning 00:05:08.089 --> 00:05:10.750 up a custom invoice calculator or a team social 00:05:10.750 --> 00:05:13.410 media calendar. Exactly. You ask for a grid layout, 00:05:13.490 --> 00:05:16.689 and it just builds it. But we should define the 00:05:16.689 --> 00:05:18.430 boundaries here, too. I'm glad you brought that 00:05:18.430 --> 00:05:20.509 up. There's a lot of hype in the no -code space. 00:05:21.009 --> 00:05:23.910 Tools like Cursor or Replet are changing professional 00:05:23.910 --> 00:05:27.500 software. Can this replace platforms like Cursor 00:05:27.500 --> 00:05:30.819 for complex production -level projects? No. It's 00:05:30.819 --> 00:05:34.060 strictly best for quick prototypes and lightweight 00:05:34.060 --> 00:05:37.019 personal apps. Beat. So it's really just for 00:05:37.019 --> 00:05:39.540 quick prototypes, not production. Exactly. That's 00:05:39.540 --> 00:05:42.279 a crucial distinction. Cursor is built for heavy 00:05:42.279 --> 00:05:45.800 lifting. complex backends, secure user authentication, 00:05:46.420 --> 00:05:49.600 large databases. QuinnStudio is entirely client 00:05:49.600 --> 00:05:51.800 -side. It doesn't have a secure backend database 00:05:51.800 --> 00:05:54.079 attached out of the box. Right. If you're building 00:05:54.079 --> 00:05:56.180 the next Airbnb, you need a full development 00:05:56.180 --> 00:05:58.600 environment. But for a personal budget tracker, 00:05:58.959 --> 00:06:01.939 QuinnStudio is unmatched. And it keeps you in 00:06:01.939 --> 00:06:04.819 that free ecosystem. We'll take a quick break 00:06:04.819 --> 00:06:07.389 here. sponsor. All right, we are back. So before 00:06:07.389 --> 00:06:09.230 the break, we covered logical app building and 00:06:09.230 --> 00:06:10.790 local file management. But if you're building 00:06:10.790 --> 00:06:13.250 an interface, you eventually need assets, images, 00:06:13.470 --> 00:06:15.870 video. Usually that breaks your workflow. You 00:06:15.870 --> 00:06:18.290 have to open a new tab for mid -journey, log 00:06:18.290 --> 00:06:21.110 into Runway, juggle more subscriptions. Context 00:06:21.110 --> 00:06:24.490 switching just destroys human productivity. But 00:06:24.490 --> 00:06:27.750 with Quen, visual generation happens inside that 00:06:27.750 --> 00:06:30.970 exact same unified chat interface. Let's talk 00:06:30.970 --> 00:06:33.490 about the image model first. The sources give 00:06:33.490 --> 00:06:36.230 a very specific example here. You can prompt 00:06:36.230 --> 00:06:39.290 it for a photorealistic lion sitting next to 00:06:39.290 --> 00:06:41.829 a laptop on a wooden desk. With natural sunlight 00:06:41.829 --> 00:06:44.629 filtering through a window. And it generates 00:06:44.629 --> 00:06:48.209 it instantly with really striking realism. But 00:06:48.209 --> 00:06:50.389 what's really interesting is the model's limitations. 00:06:50.509 --> 00:06:52.850 They reveal how it was actually built. Yeah, 00:06:52.990 --> 00:06:55.209 especially when it comes to rendering text inside 00:06:55.209 --> 00:06:57.649 those images. Right. If you ask it to render 00:06:57.649 --> 00:07:00.230 English text on that laptop screen, it does it 00:07:00.230 --> 00:07:02.810 beautifully. Same with complex Chinese characters. 00:07:03.029 --> 00:07:05.230 But if you try to render text in languages like 00:07:05.230 --> 00:07:07.819 Spanish, It totally falls apart. It hallucinates 00:07:07.819 --> 00:07:10.199 strange layouts and spelling errors. Why does 00:07:10.199 --> 00:07:12.319 that happen mechanically? I mean, functionally, 00:07:12.560 --> 00:07:15.300 Spanish uses the same Latin alphabet as English. 00:07:15.439 --> 00:07:17.560 It comes down to the training data. The data 00:07:17.560 --> 00:07:20.579 set was heavily weighted toward massive English 00:07:20.579 --> 00:07:23.620 and Mandarin text corpuses. And diffusion models 00:07:23.620 --> 00:07:25.740 don't actually understand letters. They learn 00:07:25.740 --> 00:07:28.870 visual geometric patterns. Exactly. The model 00:07:28.870 --> 00:07:31.269 simply hasn't seen enough visual examples of 00:07:31.269 --> 00:07:33.990 Spanish text patterns to accurately reconstruct 00:07:33.990 --> 00:07:36.129 them. That makes perfect sense. It's about statistical 00:07:36.129 --> 00:07:39.110 probability, not linguistic understanding. Yeah, 00:07:39.529 --> 00:07:42.050 but even with that limit, the editing workflow 00:07:42.050 --> 00:07:44.819 is incredibly smooth. You don't need Photoshop 00:07:44.819 --> 00:07:47.100 layers. You can just upload a selfie and use 00:07:47.100 --> 00:07:49.899 natural language. You type, add that photorealistic 00:07:49.899 --> 00:07:52.100 lion sitting next to me. And it ensures your 00:07:52.100 --> 00:07:54.740 phone stays visible in your hand, matches the 00:07:54.740 --> 00:07:56.639 ambient lighting. So it doesn't look like a cheap 00:07:56.639 --> 00:07:59.540 sticker, it just blends perfectly. And then Quinn 00:07:59.540 --> 00:08:03.100 takes it a step further with One 2 .7, their 00:08:03.100 --> 00:08:05.430 video generation model. This is where things 00:08:05.430 --> 00:08:07.889 get computationally heavy. You take that edited 00:08:07.889 --> 00:08:10.990 selfie and directly in the chat, ask the AI to 00:08:10.990 --> 00:08:13.269 convert it into a five second video. You can 00:08:13.269 --> 00:08:15.589 even specify a 1080p resolution rendering at 00:08:15.589 --> 00:08:18.689 30 frames per second. Under the hood, this uses 00:08:18.689 --> 00:08:21.540 latent video diffusion. It takes the spatial 00:08:21.540 --> 00:08:24.079 data and adds a temporal dimension, predicting 00:08:24.079 --> 00:08:27.240 pixel shifts frame by frame. It's complex, so 00:08:27.240 --> 00:08:29.180 it takes about three to five minutes to render. 00:08:29.579 --> 00:08:31.680 But the output is a clip where you're smiling 00:08:31.680 --> 00:08:34.039 naturally and the lion subtly moves its head. 00:08:34.159 --> 00:08:36.539 And it's completely free, which is wild given 00:08:36.539 --> 00:08:39.919 the server costs for video generation. It's fantastic 00:08:39.919 --> 00:08:42.240 for short social clips. But again, we have to 00:08:42.240 --> 00:08:43.940 be honest about the boundaries here compared 00:08:43.940 --> 00:08:47.509 to paid tools like Kling or Runway. Right. Did 00:08:47.509 --> 00:08:50.190 these videos handle multi -character scenes or 00:08:50.190 --> 00:08:53.450 complex camera movements well? No, it is definitely 00:08:53.450 --> 00:08:56.389 best for simple motion and short social clips. 00:08:56.720 --> 00:08:59.600 Two -sec silence. Got it. Best for simple motion 00:08:59.600 --> 00:09:02.419 and social clips. Yeah. If you ask for a cinematic 00:09:02.419 --> 00:09:04.940 camera pan, the temporal consistency breaks down. 00:09:05.220 --> 00:09:07.419 The background morphs. Or if two characters are 00:09:07.419 --> 00:09:09.580 shaking hands, the pixels just meld together 00:09:09.580 --> 00:09:12.200 into a messy hallucination. It's not rendering 00:09:12.200 --> 00:09:15.019 a Hollywood short film. Exactly. But zooming 00:09:15.019 --> 00:09:17.779 out, you have a workflow from text prompt to 00:09:17.779 --> 00:09:21.860 image to video animation all in one free chat 00:09:21.860 --> 00:09:24.629 window. It's a robust creative suite. But let's 00:09:24.629 --> 00:09:26.889 pivot back to power users and developers. Right. 00:09:27.049 --> 00:09:29.330 What if you need to execute logical operations 00:09:29.330 --> 00:09:32.350 securely? That brings us to Quencode and Quencoder. 00:09:32.809 --> 00:09:35.629 This is where it becomes a serious utility. Quencode 00:09:35.629 --> 00:09:39.029 is a terminal AI agent, and Quencoder is a fully 00:09:39.029 --> 00:09:42.529 integrated cloud -based coding workspace. With 00:09:42.529 --> 00:09:44.929 the terminal agent, you don't even need to grant 00:09:44.929 --> 00:09:46.830 it terminal access on your physical machine. 00:09:47.159 --> 00:09:49.620 Which is a massive security risk anyway. Oh yeah, 00:09:49.879 --> 00:09:52.419 you do not want an AI hallucinating a command 00:09:52.419 --> 00:09:55.039 that formats your hard drive. Absolutely not. 00:09:55.279 --> 00:09:57.620 Everything runs securely in an isolated browser 00:09:57.620 --> 00:10:00.259 environment. The source gives a great Python 00:10:00.259 --> 00:10:02.500 script example. You can ask the agent to scan 00:10:02.500 --> 00:10:05.419 an entire project folder. look at nested files, 00:10:05.899 --> 00:10:07.940 and generate a markdown summary. And it writes 00:10:07.940 --> 00:10:11.039 the script, executes it in that sandbox, catalogs 00:10:11.039 --> 00:10:13.820 the file sizes, maps the directory, and outputs 00:10:13.820 --> 00:10:16.379 the summary instantly. You review it without 00:10:16.379 --> 00:10:18.679 ever opening a local terminal. And this workflow 00:10:18.679 --> 00:10:21.000 is supercharged by their open router integration. 00:10:21.620 --> 00:10:24.379 OpenRouter has been everywhere in dev docs lately, 00:10:24.639 --> 00:10:26.620 but how does that integration actually work in 00:10:26.620 --> 00:10:29.720 practice? It's basically a unified API aggregator. 00:10:29.899 --> 00:10:32.100 Instead of making 50 accounts for different models, 00:10:32.500 --> 00:10:34.899 OpenRouter gives you one interface. And it connects 00:10:34.899 --> 00:10:38.320 to dozens of free open weights models. Precisely. 00:10:38.399 --> 00:10:41.000 So when Quencoder integrates with it, you route 00:10:41.000 --> 00:10:45.039 your code execution through free endpoints, bypassing 00:10:45.039 --> 00:10:48.299 expensive, patriotic APIs. Cloud code is powerful. 00:10:48.519 --> 00:10:51.460 but requires a paid sub and you hit limits fast. 00:10:52.000 --> 00:10:54.460 Quencoder provides a zero cost starting point 00:10:54.460 --> 00:10:56.559 for real development. You can connect it directly 00:10:56.559 --> 00:10:58.720 to your GitHub repos and just start iterating. 00:10:59.120 --> 00:11:02.960 That brings us to the final and maybe most philosophically 00:11:02.960 --> 00:11:05.480 interesting piece of this ecosystem. Vocal deployment. 00:11:05.899 --> 00:11:08.759 Everything so far relies on the cloud. But what 00:11:08.759 --> 00:11:11.279 if you are dealing with sensitive intellectual 00:11:11.279 --> 00:11:14.059 property or personal financial data? You want 00:11:14.059 --> 00:11:16.200 to take the model completely offline. And that's 00:11:16.200 --> 00:11:18.559 where tools like a llama come in. You literally 00:11:18.559 --> 00:11:20.720 download the actual neural network weights onto 00:11:20.720 --> 00:11:23.240 your hardware. The AI lives entirely on your 00:11:23.240 --> 00:11:25.700 silicon. Your data never lose your device, no 00:11:25.700 --> 00:11:28.840 processing cues, zero API fees. Historically, 00:11:28.940 --> 00:11:31.200 the challenge was hardware constraints. You needed 00:11:31.200 --> 00:11:34.299 a massive, expensive graphics card. Right. But 00:11:34.299 --> 00:11:37.480 these Quinn models stale down beautifully. They 00:11:37.480 --> 00:11:40.320 offer highly compressed versions with under one 00:11:40.320 --> 00:11:43.559 billion parameters, using a process called quantization. 00:11:43.720 --> 00:11:47.059 Yeah. If we define quantization simply, it's 00:11:47.059 --> 00:11:49.100 shrinking the model's memory footprint so it 00:11:49.100 --> 00:11:51.779 fits on normal devices. It's like taking a massive, 00:11:52.019 --> 00:11:55.000 uncompressed WAV audio file and converting it 00:11:55.000 --> 00:11:58.299 to an MP3. You lose microscopic fidelity, but 00:11:58.299 --> 00:12:01.370 it fits on an old iPod. It converts high -precision 00:12:01.370 --> 00:12:04.750 floating point numbers into smaller 4 -bit integers, 00:12:05.330 --> 00:12:08.289 which reduces RAM requirements by, like, 75%. 00:12:08.289 --> 00:12:10.850 That small size means you can run these models 00:12:10.850 --> 00:12:13.149 on low -power devices. Like, why would someone 00:12:13.149 --> 00:12:15.490 choose to run an AI model locally on an iPhone? 00:12:15.690 --> 00:12:18.730 You get total privacy and zero reliance on cloud 00:12:18.730 --> 00:12:21.350 servers or the internet. Beat. Total privacy 00:12:21.350 --> 00:12:23.730 and zero reliance on the cloud. That is huge. 00:12:23.870 --> 00:12:26.250 It's all about ultimate control and data sovereignty. 00:12:26.590 --> 00:12:28.970 Nobody is harvesting your personal journal entries 00:12:28.970 --> 00:12:30.830 or health data for training. And if you're on 00:12:30.830 --> 00:12:33.669 a plane without Wi -Fi, your AI still works perfectly. 00:12:34.210 --> 00:12:37.110 It's true digital independence. Let's pull all 00:12:37.110 --> 00:12:39.549 these threads together, because the big idea 00:12:39.549 --> 00:12:42.929 here is profound. It really is. The true value 00:12:42.929 --> 00:12:45.870 of the Alibaba Quinn ecosystem isn't about beating 00:12:45.870 --> 00:12:49.029 open AI on every single esoteric technical benchmark. 00:12:49.529 --> 00:12:51.830 No, it's about providing a highly practical, 00:12:52.370 --> 00:12:56.039 frictionless workflow. an end -to -end free ecosystem 00:12:56.039 --> 00:12:58.720 for the tasks people actually do every day. It 00:12:58.720 --> 00:13:01.259 is the ultimate gap filler. We all hit our free 00:13:01.259 --> 00:13:04.139 tier limits. We hit the paywall, get frustrated, 00:13:04.600 --> 00:13:07.059 but don't want another $20 subscription. Quinn 00:13:07.059 --> 00:13:09.519 steps into that exact moment perfectly. You get 00:13:09.519 --> 00:13:13.440 desktop file control via MCP, no -code app building 00:13:13.440 --> 00:13:16.299 with artifacts, creative image and video generation, 00:13:16.639 --> 00:13:19.000 and secure local coding environments. If you're 00:13:19.000 --> 00:13:20.980 listening and wondering where to start, our sources 00:13:20.980 --> 00:13:23.460 provide a clear guide. Pick the specific tool 00:13:23.460 --> 00:13:25.759 that solves a problem you have today. Use the 00:13:25.759 --> 00:13:28.399 desktop app for your chaotic files. Try Quinn 00:13:28.399 --> 00:13:30.899 Studio for a quick budget tracker. Jump into 00:13:30.899 --> 00:13:34.519 WAN 2 .7 for a quick b -roll clip or download 00:13:34.519 --> 00:13:37.419 Alama if you need strict privacy. Pick just one 00:13:37.419 --> 00:13:39.120 and try it today. It costs nothing but a few 00:13:39.120 --> 00:13:41.019 minutes. And I think it will completely change 00:13:41.019 --> 00:13:43.539 how you view the necessity of these premium AI 00:13:43.539 --> 00:13:45.879 tools. It really shifts the landscape beneath 00:13:45.879 --> 00:13:48.419 our feet. It does. Yeah. And it leaves us with 00:13:48.419 --> 00:13:50.809 a very provocative thought to chew on. Right. 00:13:50.909 --> 00:13:53.470 If an entire ecosystem complete with desktop 00:13:53.470 --> 00:13:56.110 agents, no code builders, video generators, and 00:13:56.110 --> 00:13:59.129 coding assistants becomes a standard free public 00:13:59.129 --> 00:14:02.090 utility, like a basic operating system, what 00:14:02.090 --> 00:14:05.610 happens to the future of the $20 a month AI subscription 00:14:05.610 --> 00:14:08.710 model? It is a massive existential question that 00:14:08.710 --> 00:14:11.169 every major AI company has to answer very soon. 00:14:11.309 --> 00:14:13.269 It certainly is. Thank you for joining us on 00:14:13.269 --> 00:14:15.529 this deep dive. Keep exploring, keep questioning 00:14:15.529 --> 00:14:17.730 the tools you use, and we will see you next time.