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أحنا اللى الدنيا بتتهد وترقص على خطوتنا ومادام غنينا مافيش حد ع الأرض يسكتنا 💃🏻💃🏻💃🏻💃🏻💃🏻 حبايبي ده تيزر من اغنية #يا_ليالي من اول الاغاني اللي نفذناها بتقنية الذكاء الاصطناعي مع المخرج الكبير #وليد_ناصيف ويارب تعجبكم و استنوها قريبا ضمن البوم #مفيش_ممنوع قريباً على قناتي على اليوتيوب وكل المنصات الموسيقية... show more
106,747 次观看 • 2 年前 •via X (Twitter)
10 条评论
رائعة👌❤️❤️❤️
سويًا، أعمال وأفكار وفن وتحديات، مشبعة بحب واحترام ونجاحات وثقة لا تُضاهى. قصة فنية وأخلاقية أعتز بها و بكل إنجاز حققناه. لطيفة ليست مجرد اسم، بل هي رمز للقوة والجمال والإبداع و الفن و الشغف والتفاني الذي يلامس القلوب ويُلهِم الأرواح. #مفيش_ممنوع
واو 😍🤯🤯🤯🤯👏👏👏👏👏
الاغنية واو.بالتوفيق لطيفتنا الحلوة بالجزائر صراحة بيحبوك كتير ولكي ذكريات انتي ونجوى كرم من اقوى الفنانات العربيات بالجزائر #مفيش_ممنوع #نجوى_كرم_تعا_نقعد_سو الصيفية رح تولع بين لطيفة ونجوى كرم ببقى اليسا اللي اتراجعت والبومها مر مرور الكرام..ربما لانها دخلت دوامة التكرار
الابلوم المنتظر بالتوفيق
اغنيتي من الآن 💗
واووو انا ليبي حبيت الاغنية على نااااار حلو التغير واللحن والكلمات برافوووووو لطيفة كل الدعم ليك ❤️🇱🇾
حماس 🔥
woow 😍🔥
منتظرين يا ملكه
![✨ I made a 100% AI video of a single night in 🇩🇪 Berlin's underground techno scene Doing an AI shoot is very much like a real life shoot, you have to prepare locations, settings, outfits and models, you can do the same: 1) First I generated photos with the [ 🇩🇪 Berlin nightlife ] photo pack on they're all non-existing AI people except me and my gf 2) Then I put the pics I liked in Kling AI to make them into 10 second videos (with Professional Mode), soon I'll have API access and it'll be one-click inside Photo AI to turn a photo into a 10-sec video, it then takes about 5 minutes to make a video. It's not always great, especially dancing is hard to get right! 3) Then I wanted to have a German narrator talking about Berlin's techno nights in a poetic way like a documentary, so I asked ChatGPT 4o: "write in the style of a cult German novelist about the Berlin techno scene" I then copied that text into Eleven Labs and selected a German AI voice 4) I then collected all the videos, the music and the audio narrator and edited them together in Final Cut Pro adding music from HÖR and adding audio effects 5) Then I added English captions with CapCut Time to make it: 3 hours for 1 minute of video I hope you like it! My dream is to have this entire pipeline in Photo AI at some point. Connecting to Kling AI's video API is the first step to that. Imagine just writing a prompt and you end up with a video like this without all the work Credits: Music: Asquith - Let Me (Rave Mix) [ASQ004] Barbax - Si Vis Pacem Para Bellum (Original Mix) Mixed by Ellen Allien @ HÖR Video: 100% AI characters and video by Photo AI Edited by me Narrator voice: 100% written by ChatGPT 4o 100% narrated by Eleven Labs AI voice](https://image.24vids.com/tw-1836017413650829587/ext_tw_video_thumb/1836016292328865792/pu/img/pZMR0VCR6sYaD8Vj.jpg)
![someone is going to make millions with this in 2026 99% of people think this is a real human (or they fail to notice it’s an ai-generated video) but this video is completely ai-generated, including the background music. let me teach you how to create this in a few minutes follow this workflow step by step: first, create the base image of your ai influencer using nb pro. this is currently the best tool for character consistency i used a json prompt to generate the base image then i turn it into video (i will share the exact json prompt with you in this thread) now, to generate the video paste this prompt into google veo using the “frame to video” option “a man in his 40s sits on a 1980s living room couch, looking directly at the camera with a serious expression. he gestures naturally with one hand as he speaks in vintage tv broadcast aesthetic: "today is october 12th, 1985. what i'm about to tell you will sound impossible... but mark my words, these three predictions will come true. no background music, no sound effects” next, i gave it a chunk of script, i only changed the script dialogue each time and kept the rest of the prompt exactly the same using this method, you also get a little consintent voiceover here is the format for you to use: [character description] + [visual style] + [dialogue of your script for under 8 seconds] for example, for the next part dialogue; [A man in his 40s sits on a 1980s living room couch, looking directly at the camera with a serious expression. He gestures naturally with one hand as he speaks in Vintage TV broadcast aesthetic: "but mark my words, these three predictions will come true... ONE: You will carry a device no bigger than a playing card that holds ten thousand songs" ] rest things i adjusted in the editing, now how to clone the audio for these several clips we just generated? i got the best audio from the very first clip i generated using veo 3 but here is the trick: - export that clip to a video editor - detach the audio of it - duplicate it to make it 10+ seconds long - clone the voice over using elevenlabs (go to 11Labs-> click on voices-> click on "create or clone a voice" button in the top right side) (i named mine “1985 ai influencer” inside 11labs) then, finally export all your video clips into your video editor detach the audios of all clips, and export it to 11Labs to clone it with that "1985 AI Influencer" voice once you dubbed it, import it back to your editor that’s it. there are endless use cases where you can use such an ai influencer like this to promote your biz: - skincare - weight loss & nutrition - psychology and mental health - marketing and sales - predictions (like this video) - making money & career growth - dating, parenting, and so on… there are a few people already started using such ai influencers, you are just behind them, you can find their pages on instagram don't be lazy, create one such an ai influencer for your targeted biz 2026 is going to be yours](https://image.24vids.com/tw-2000200740137288169/amplify_video_thumb/2000197743109865472/img/sRF-I3pLFErUysD_.jpg)
![$TSLA 🇰🇷 [I hope the wide release of FSD V14 Lite will begin in Korea soon!] Yesterday I installed the second update of FSD V14 Lite (version 2026.20.7.5), and I drove with it this morning. The FSD V14 Lite that is currently running in Korea is overall excellent. This version newly added features like: • Ability to disable the brake confirm • FSD statistics (also viewable in the app) • FSD Streaks These make it much more intuitive to feel that my Tesla truly has “autonomy.” With just one touch, it takes me from point A to point B. There are still occasional moments where I need to intervene, but most of the time it drives very smoothly and stably. It’s truly amazing that a car from 4, 5, or even 7 years ago can gain new intelligence simply through software updates. I’ve driven more than 3,500km with V14 Lite.. sometimes it still feels like a dream. Tesla’s autonomy is that captivating. Here’s another example of how well FSD V14 Lite works in Korea. I even uploaded it to my YouTube channel: I drove my Model 3 from Seoul to Busan(415 km) with zero interventions. I also went back and forth between Seoul and Jeonju, from Jeonju to Daejeon, and from Daejeon to Geumwang — and in most of those trips, I didn’t need to intervene at all. In Korea, Model 3/Y(Fremont-built) owners generally have a very high level of understanding of Tesla and a strong passion for new technologies like FSD. Many of us, including myself, would make excellent testers, and we would safely and enjoyably experience autonomy. FSD V14 Lite still has some areas for improvement in Korea — such as bus lane recognition, speed camera recognition, and more conservative highway driving — but we are now confident that this software is good enough for us to fully accept and enjoy it. Thank you for creating such an amazing piece of software. The efforts of the Tesla AI team are truly remarkable. I hope this great build will be a big help to HW3 owners. Many owners around the world — in the US, China, Australia, Europe, and elsewhere — are waiting for it! I’ll keep cheering you on. Thank you so much!😀Ashok Elluswamy Tesla AI](https://image.24vids.com/tw-2085614416221905285/amplify_video_thumb/2085566115611328512/img/aUJDF_Hwt6kRkds0.jpg)
![Just in $AMD Anush "Speed is the moat"|ROCm🎙️ In the race to define the future of AI, what's the one advantage that truly lasts? It's not proprietary tech, argues Anush Elangovan Elangovan, VP of AI Software at AMD , but the sustainable speed of innovation. He explains why AMD is rejecting the "walled garden" model for its open source ROCm stack, betting that an open community flywheel is the key to victory. Listen to understand how this open strategy is designed to out-innovate closed systems by empowering developers to solve everything from frontier-model challenges to the mundane, everyday problems that define the "last mile" of AI. AMD ROCm Software: Part 1 Transcript [00:00:00] Andrew Zigler: Joining me is Anush Elangovan, VP of AI software at AMD. And when people talk about AI compute, the conversation often stops at hardware specs, but it's more than just physical chips that win the game. It's also the software ecosystems supporting them. [00:00:18] Andrew Zigler: The prevailing strategy in the industry has been to build something like a walled garden. You know, something closed, proprietary locks, developers in. But AMD is betting on an entirely different play, open source acceleration, and with rock, their open source AI software stack. AMD is building not just hardware parity, but an innovation flywheel that's powered by the community with interoperability and the freedom to scale without all of that pesky lockin. [00:00:48] Andrew Zigler: And in this world, speed is your moat and how fast you can innovate while your platform remains open, flexible, and standardize across all of its applications. That's what we're gonna explore [00:01:00] today. So Anush, I'm really excited to have you here. Welcome to Dev Interrupted. [00:01:04] Anush Elangovan: Thanks for having me. Uh, super excited to chat about it. [00:01:07] Andrew Zigler: Amazing. Well, let's go ahead and dive right in with kind of what I laid it out with in the beginning, the idea of the moat and it being about speed. I wanna unpack that a bit because that came from you when you and I first spoke. And I, and I want to know, you know, how do you define speed inside of AMD beyond just things like hardware, benchmarks. [00:01:27] Anush Elangovan: Yeah, that's a very good question. So when we typically talk about speed, everyone's like, Hey, hardware benchmark specs, right? Like, uh, memory bandwidth or, or flops. And that is one important part of it, uh, AMD does very well. With that, we do have, a, a very good history of executing on that axis. [00:01:47] Anush Elangovan: But when I say speed is the moat, it is about, uh, how we prepare, how we build the muscle to run the race for a long time and run it fast. And it is [00:02:00] not about a single point in time that you've, you've beat some you know, benchmark and, and you declare victory. It's about building the ability to consistently develop and deliver. [00:02:13] Anush Elangovan: Both hardware and software innovation at scale and do it fast, right? Like, you know, we we're increasingly getting to a point where models come out and they're, uh, you know, a year or two ago it was like, Hey, they work on AMD on day zero, which is great, but now they are performing on AMD the day it releases, right? [00:02:32] Anush Elangovan: So, what does it take to Prefetch where the industry is going? Be prepared to intercept. At that point is what you know, I, I refer to as you know, the, the speed factor in, in creating this mode, right? And the mode is just shed all things that hold you back and run as fast as you can. [00:02:53] Anush Elangovan: Uh, because the pace of innovation that is, uh, being seen in, in AI [00:03:00] industries is just. Amazing. Right? And it's like, it's transformational at at how you generate electricity. It's transformational as at how you build data centers. It's transformational at how you deploy compute, networking. It's transformational at what kind of use cases you, you know, uh, use AI for. [00:03:17] Anush Elangovan: Uh, and for that, you need to be prepared to, see what comes tomorrow and be prepared to run the race tomorrow. [00:03:23] Andrew Zigler: Yeah, it's a really great perspective because it highlights that it's not just like a checkpoint that you run through. I like how you called out, like it's not just hitting that benchmark or being the best in class at that moment, in that snapshot, it's about having a. The throughput and about having that dedication to the idea and continuing to deliver on it. [00:03:43] Andrew Zigler: It's not just crossing the threshold, but it's also being the engine. And that's what, that's what protects a business. That is the moat, because the moat is that innovation layer, the faster and more, uh, future forward. That you can work and think, [00:04:00] you know, the better. Uh, we, we talk a lot about like future forward work styles. [00:04:04] Andrew Zigler: Like what are the things I could be doing right now today that are gonna be like, way more useful tomorrow? Let, let's abandon those, workflows that are older and that kind of like, that translates into. An advantage when you work that way. You know, what kind of things have you learned working with, uh, like across all spectrums of people who would use ROCm, right? [00:04:23] Andrew Zigler: You have like the developers, but then you also have the enterprises and you have this large span of adoptees, right? So what is the, what does that look like that you learn? [00:04:32] Anush Elangovan: Yeah, so, so the way I look at it is there are gonna be pockets of different, uh, you know, cadences, right? Like, so people who are deploying in enterprises, for example, right? The validation and how long it takes for them to deploy an LLM that's secure. It's, with guardrails, et cetera, maybe longer. [00:04:52] Anush Elangovan: but you still have to go through the process and you have to be prepared to like, walk that walk to deploy an enterprises. That doesn't mean it's [00:05:00] not fast, that's as fast as you can do for that industry, right? And if you are deploying AI in healthcare, right, it's, it's got its own, uh, cycle. [00:05:07] Anush Elangovan: but in each one of these, you want to see how, like, go down to the essence of what is it that you actually have to do. And, you know, I, I, I like how you framed it. It's like it's, you shed your prior assumptions of how things are done, right. And, and you kind of build up from a, uh, first principles, uh, approach to say, this is how I could use AI to unlock, whatever I'm doing. [00:05:33] Anush Elangovan: And, and, some of it, you know, it's good to really step back and look at. Just question every part of it, right? Like right now you're getting chat GPT and, Gemini competing for like, math, olympiads and, and, uh, college, uh, reasoning, uh, tests. Right? And, and those are like that, that is amazing and increasingly like complex tasks that they're trying to do. [00:05:58] Anush Elangovan: But there may also be like. [00:06:00] More mundane things that AI could, could get applied to. Right? And, and so when we think about shedding old ways, you wanna shed it not just in like the tip of the spear. It's like, you know, I'm gonna see what's the frontier model. It's also, it could be something as simple as. [00:06:18] Anush Elangovan: How do you choose a, a movie, uh, you know, like a recommendation system, right? Or, or, uh, an automated, uh, flight, uh, rebooking system. So the moment, you know, your flight is late, uh, right now it's a notification, right? It's like, oh, you got a text message saying your flight's late. And I got that like three times this week. [00:06:38] Anush Elangovan: But anyway, uh, and, and, and, and, I was just like, okay, so if I were to rethink this. All this MCPs that we have that should be hooked up into an MCP that says, your flight's delayed. Here are your options. If you want, you know, these are the paid options. Yeah. Here are the free options. This will get you back into your you know, Toronto airport [00:07:00] tonight. [00:07:00] Anush Elangovan: Or if you stay, here's a hotel plus this, plus this, plus. It's just like, go ahead is all I should say. Versus now I'm like, okay, can someone, you know, can I call a travel agent? Can I do this? Can I go online and log into And you know, so we gotta fundamentally rethink even those like small, nuances of, things that we do that can be automated out and AI is really, really good at doing something like this, right? Maybe I just explained an AI startup idea right now. Somebody should just start that. [00:07:29] Andrew Zigler: I think you did. Yeah, you definitely did. Someone, one of our listeners is definitely going to lift that off of you. I, I, I, you know, I hate being on the receiving end of those. You feel a little helpless and then you have to like, follow the whole flow. So I know what you mean. Like I, I like how you called out that the build and this like. [00:07:45] Andrew Zigler: Where speed is your moat and the innovation layer is protecting you, is what makes you better than your competitors. How you scale that and you bring that to market. So by understanding the problems that you're solving, uh, throwing away those older assumptions, but also [00:08:00] recognizing that like. We're building every single day, new things and new ways of using stuff that we're still figuring out the implications of. [00:08:08] Andrew Zigler: And so when you have a lot of velocity and you're introducing a lot of new ideas, and maybe you have that workflow now that automatically rebook your flight off of your late flight text message, and uh, I know I would certainly use it, but you know, what kind of philosophies guide the way that y'all think about building this ecosystem to manage that stability while letting folks. [00:08:29] Andrew Zigler: Play with the speed and the assumptions and the airplane re bookings. [00:08:34] Anush Elangovan: so, so I think, you know, we need to peel one layer down, right? and the philosophy is, Hey, we, we just discovered electricity, right? And you know what we're gonna do? We are gonna make motors, uh, or dynamos, right? Like engines. Uh, sure. We don't know if it's gonna be a Ferrari that you're gonna make, or it's a a a a dump truck. [00:08:57] Anush Elangovan: That's good for doing this. But let's [00:09:00] let, which is also required, right? You need a dump truck. You need a garbage truck. And, [00:09:04] Andrew Zigler: Yeah. You need the [00:09:04] Anush Elangovan: course you need, uh, a Ferrari for a midlife crisis, right? So, [00:09:09] Andrew Zigler: precisely. [00:09:10] Anush Elangovan: But, but my, uh, point is what do we build next? And, uh, and this is what I meant by like, okay, let's, let's take those baby steps to build the. [00:09:20] Anush Elangovan: Infrastructure that's required that we know we'll have to use, right? So, so if I just discovered electricity, okay, great. Now one, how do I save this electricity and how do I use it? So there's battery technology, so you need to do something like that, right? Like so. But then you also want to make it into an actionable thing. [00:09:37] Anush Elangovan: You want to make it for like automobiles, or you wanna use it for, you know, powering, uh, entire cities. So it is that transformational. So, uh, AI is that transformational. So, if you distill down, it'll, it'll come down to how do we think about, what we can do with this this fundamental technology that, We may not be aware of what it [00:10:00] is gonna unlock next, but at least you know the next step is clear, right? It's like a dense fog, you know, it's gonna be like, it, it's the right path. You see the light, but it's kind of like out there and, and the steps you're taking are concrete and you're like, okay, this is good. [00:10:16] Anush Elangovan: I, this is better than where I was or where we were. So we are moving forward. So you can build with the. Intuition from what you see in the short term and a tactical view, but towards what you think the future is gonna be. [00:10:28] Andrew Zigler: Right. You almost like we're all in this like fog of war, right? And like you said, you're reaching out and you're trying to step through it. You could think of it too, as like you're in the dark and your hands are up in front of you and you know that. You're, you're not gonna run your face into a wall because your hands are out in front of you, but you're not gonna maybe do much better than that. [00:10:45] Andrew Zigler: So that's kind of like, I think the eco, the, the industry, the world that we find ourselves in, uh, and we all have to, then this becomes the power of an ecosystem, of a group of people working together to create that layer of, [00:11:00] uh, of establishing the [00:11:01] Anush Elangovan: exactly. And I, I, I just, instead of, you know, saying fog of war I describe it as like, you're in this. Beautiful valley with like a morning, uh, fog that's in. You can smell the flowers. You, you hear the birds. You are like, okay, it's, we are in like, uh, utopian paradise and yes, I just need to like, continue the walk, right? [00:11:24] Anush Elangovan: and then move forward with that, conviction that you're in the right spot. [00:11:27] Andrew Zigler: Yeah. So let's talk about that ecosystem world. This nice, I love how you describe it, this grassy side of a hill in the morning that's covered in some mist and maybe we can't see 30 feet in one direction, but it sure is a beautiful hill and it smells nice. And so we're all here. And why is, in that world, why is. [00:11:44] Andrew Zigler: You know, open source, their strategic advantage that y'all are going for in the AI hardware market. And, and then how does like ROCm turn that into wins for people within that ecosystem? [00:11:56] Anush Elangovan: you know, the, the way we look at it is this, is kind of like how I view [00:12:00] AI and the ecosystem, right? But, but it is for everyone to enjoy. Uh, and so we do want to make sure that. You know, it is, uh, beneficial for everyone. [00:12:09] Anush Elangovan: The ecosystem can come in and, and innovate. It's an open innovation engine. and uh, it is very different from, you know, having a walled garden with, Hey, only I know how to do this and I'm gonna do it and throw it over the fence and you can use it or keep walking, right? So we'd like to be good citizens that way, but also. [00:12:30] Anush Elangovan: Uh, it is self-fulfilling in a way, right? Like it, the, the pace at which we innovate with open source is unmatched. Like, you know, our serving engines are like VLLM and, and sg l. Those things, uh, those frameworks are like super, super aggressive in terms of how fast they come out with features and how fast they can you know, get performant models out. [00:12:52] Anush Elangovan: And that compared with what, uh, you'd get from, you know, the likes of like T-R-T-L-L-M or something is always lagging, right? Because you [00:13:00] just can't keep up with you know, 200 commits a week just on one particular model to get that model really performant [00:13:06] Andrew Zigler: And, and, and in that world where, you know, everyone can enjoy the winds of this, what kind of customer stories or innovation stories have really stood out to you and excite you about building and creating this place for developers? [00:13:19] Anush Elangovan: Yeah. So I think the parts that are super exciting for me are when when we get to see a customer that is first skeptical. Then they start a little like, okay, fine, we'll give you a chance. Uh, we do a simple, uh, POC and then they're like, huh, this seems to work. Yeah, we told you it works. [00:13:42] Anush Elangovan: You don't have to change one line of code. Really? Yes, no need to change one line of code. Okay, let's try a production workload. So then they try it. Oh, you're more performant than the competition. Yes. We're more performant than, than the competition. So how much does it cost? And we're like, oh, it's your TCO is better with, uh, [00:14:00] AMD. [00:14:00] Anush Elangovan: So again, they're like, wow, okay, good. So now how do we deploy at scale? And then we go deploy it at scale. And when they give a thumbs up on that and they say, this is good, right? That's when you know, you, you see it go full circle from like, oh, we, we've never heard about AMD to like actually deploy to tens of thousands of GPUs In the order of a few months, right? It, it, it really is fascinating to see and very exciting and invigorating to [00:14:28] Andrew Zigler: Yeah. At like a great exposure to a lot of interesting problems. And, and then people using the infrastructure, the, the technology available to solve those problems. Really specific problems by the way, that's often why they're bringing their data and AI to it, uh, is because it is really specific and important for them. [00:14:45] Andrew Zigler: And there's a, a lot I think that other engineering orgs can learn and even emulate from AMD's success and, and having this open source ecosystem and it causing this acceleration within. You [00:15:00] know, uh, customers and enterprises that use and adopt the tools and, and, and that creates an advantage. And that goes back to why we're talking and like the real thesis of our conversation today. [00:15:10] Andrew Zigler: So how do you think engineering leaders that are listening to this and obviously tapping into this great success AMD has from an open source flywheel, how do you think other, other folks building in the same space can foster that open, first, that open source oriented culture in order to, you know, accelerate their innovation goals? [00:15:29] Anush Elangovan: Yeah, that's a very good question. So the startup that um, was acquired by AMD we, we built, I mean, we started off doing iot stuff and you know, smart ring and all that, right? But in the, the end of like, uh, and not the end, the last six years of the company was building ML compilers. [00:15:47] Anush Elangovan: And ml, ML compilers are like super, uh, complicated, sophisticated, advanced algorithms, dah, dah, dah. but it was all open source, right? So our VCs were like, wait, what do you mean your core [00:16:00] IP is open source? And um, the speed is the moat applied even then, right? It was just like, yes, if you have an idea that. [00:16:08] Anush Elangovan: Because someone saw this idea that you are, they're gonna be able to catch up, then you probably have the wrong idea anyway. But if they are, you know, you execute and they're gonna catch up, that you should assume they're gonna catch up. Right? So you gotta move forward. So keeping it open source is super important. [00:16:25] Anush Elangovan: But also to your question on like, you know, the learnings from an AMD standpoint, right? If there are, hard problems, I'd say dig in and work through it, right? Like there's no way but through it, right? That should be the simple mentality. And more, uh, frequently than not. you'll see that you'll just make it through in a, in, in good form. [00:16:52] Anush Elangovan: But if you doubt it and you're like, oh, I don't know if I should commit, if I'm, I, you know, what should just commit to do the right thing [00:17:00] every step, right? Every step, and just keep taking one step in front of the other. And in no time you'll see that you'll be running. Right. And, and yes, the first few steps will be like, yeah, everyone's complaining about your software quality. [00:17:15] Anush Elangovan: Everyone's complaining about this and that, and it doesn't work. And, and a few steps in, you know, you get, you get the hang of all the complaints that are coming in. You get the feedback loop. You're like, okay, what, what are you prioritizing again? One step in front of the other, right? You just keep knocking that out and then you get to a point where you're, it just becomes second nature, right? To do the, to do the right thing. And, and then yes, if someone gives you two options, you'll be like, fine. This is, uh, you know, there's always the resource trade off. There's always a human capital trade off, but what's the right thing to do? of course, I, I'm pragmatic about what we choose, but, but if the right thing for your long-term success is dig in, go first, principles, make it [00:18:00] happen. [00:18:00] Anush Elangovan: Well. Then just go for that. There's, there is no shortcut to [00:18:04] Andrew Zigler: acknowledging, you know, how it aligns with your mission, your core company goals, and what you're looking to achieve. And, and I, I love how you rightfully called out that in the open source world and you know, you have your technology that you've built, what you think is your moat upon, right? [00:18:22] Andrew Zigler: It's your code and, and to open source that, or to just make it where anyone could peer in is, you know. Scary in one regard, but two, it just kind of feels like you're handing away your throne room in some kind of sense, a very direct feeling sense. But the ultimately, you were really right to call out, and this is something I think about all the time, that the real power there is still the speed This the speed. [00:18:42] Andrew Zigler: That was the moat at the beginning of our conversation. It's the speed in combination with your. Very specific domain understanding of what you're building and what you're creating, and your new role as the steward of that world and how people plug into it, which [00:19:00] has frankly, a lot more influence and power than lording over a closed. [00:19:04] Andrew Zigler: You know, repository or an ecosystem, and like you said, like throwing things over the wall. Sure. There, there might be people always on the other side of that wall, but you're not gonna have a great connection with them. You're not gonna be able to really clearly understand them. I, I like your metaphor of the side of the field of the mountain a lot more. [00:19:23] Andrew Zigler: But, but in the, in this world, you know, where. That speed is, is the power and, and open source is just one way that you can harness that speed to get really far ahead and to innovate. , There's other parts of this equation that you can be experimenting with too, and I'd love to pick your brain about them as a software leader and, and, and one of them is about looking forward and kind of understanding that future that we're all building towards and beyond today's models and hardware. [00:19:48] Andrew Zigler: You know, what do you see as the next major bottleneck or opportunity in the AI compute space? As, as you know, enterprises and folks start to get a little more mature about what's available to [00:20:00] them. [00:20:00] Anush Elangovan: Yeah, I think, the bottleneck and opportunity is, uh, what I'd call, call walking the last mile of ai. Right. Uh, and like I I, I gave you an example, uh, previously, but, but it's similar to that. It's like there are cases where Humans have so many, uh, things to do in your day. You know, like the, if we sit down and actually had a customer focus like, okay, these customers lives, I'm gonna save four hours of this customer's life. And if you actually sit down and look at all of that, it'll be. Easily automatable, easily you know, uh, applicable, uh, for ai, right? [00:20:39] Anush Elangovan: Like, but then making it happen is gonna take a little bit, right? It's like maybe it's, uh, paying your utility bill, right? Or something like that, right? Or, or, your healthcare explanation of benefits. Uh, like, I'm sure you get an explanation of benefits, and I'm like, I, I don't even know what that thing is. [00:20:55] Anush Elangovan: It's just like EOB and like. [00:20:57] Andrew Zigler: it's a big, a big old PDF. Yeah, [00:21:00] exactly. [00:21:01] Anush Elangovan: Like, like, I'm like great straight to the, uh, shredder, right? And but that could be, you know, automated with the ai, right? It, it, it'd be like, Hey, the summary of this thing is you went and visited this day. Everything is okay. Everything is paid for, so don't worry, it's not a bill. [00:21:17] Anush Elangovan: That again, the same, uh, thing, but the sense of what that information overload is could be. Digested by ai, uh, accumulated over time and retrieved when you need it. Like, I don't, I actually don't even need to know this EOB right now, unless of course, whenever I need to know it, that maybe, you know, like for some benefits I need to figure out what do, what did I do over the past year and how do I apply it? Source:](https://image.24vids.com/tw-1994972575768727743/amplify_video_thumb/1994972220930621440/img/_5CCZJyz89oDfqQJ.jpg)
![Apple’s iPad “Crush” Ad Is Bleak, Ominous and Threatening I don’t know if you’ve seen Apple’s just-released commercial for the “New” iPad Pro, but it’s pretty awful. It is dark, humorless, and feels like a not-so-thinly veiled threat to writers, musicians, game makers, developers, and artists of all kinds. …and children, even. I’ve watched it at least five times today alone, and I’m left with one big question. “Who on earth approved this?” It’s absolutely baffling that the world’s largest technology company, with the world’s biggest marketing budget, thought this would be a good idea. What kind of idiot—or idiots, since dozens or hundreds of people had to be involved in the writing, staging, producing, recording, and editing—felt this kind of ad would somehow create a positive emotional connection with consumers? Seriously, it’s terrifying. In a dank, cold warehouse, devoid of all life and humanity, an industrial crusher comes to life, and slowly starts destroying a collection of musical, philosophical, and artistic devices and instruments. For no apparent reason, everything starts getting smashed: first, a trumpet, then an arcade video game, then cans of paint, a piano, a globe, a metronome, a guitar… on and on it goes, obliterating everything in sight into a colorful, gooey, explosive mess. Books, camera lenses, lamps, a guitar, a sculpture, and a typewriter—all tools of the liberal arts—get mangled into a garbage heap as Sonny & Cher cheerfully sing, “All I ever need is you.” In the penultimate moment, a goofy yellow smiley emoji becomes a bug-eyed scary-clown freak as it, too, is crushed to death. Worse, if you enable closed captions like I do by default, the video says: “[POPPING] [SPLAT]” right as its eyeballs pop out of its head when Cher sings, “Give me a reason to build my world around you.” It’s enough to make a child cry. It has all the comforting vibes of the burnt pink teddy bear floating in the swimming pool on Breaking Bad after two planes crash in mid-air. I have so many questions (aside from simply wondering the names of the soon-to-be ex-employees who greenlit this abomination). First of all, as a trumpet player myself, I am personally offended that they made me watch a perfectly good trumpet get smashed to smithereens like it’s no big deal. Why would they torture me like this? Second of all, what is the message here? No, not that “the most powerful iPad ever is also the thinnest,” as the voiceover artist states in the last few seconds of the clip. I mean: what is the message? Ostensibly, pulverizing children’s toys, arcade games, architectural models, and ceramic Angry Birds into a paste implies something like “We’re taking all the best of humanity; all the collective works of Western Civilization, smashing it into pieces and putting it inside this remarkably thin device so you can have all of it in the palm of your hand.” But my oh my, is there an elephant in this room… he’s hiding behind the monstrous destroying machine. Did anyone inside Apple realize that everyone outside Apple will recognize this imagery in a metaphorical sense, but not the one Apple intended? We don’t see a crushing machine gently consolidating the greatest output of all our artistic endeavors, simply reformatted for a digital age and consumed by everyone with instant, fingertip access. We see what is painstakingly obvious to us, and the timing couldn’t possibly be worse. We see a giant, soulless machine consuming our work in a very different way. Right now, AI models are training themselves on our intellectual property and even our very own personally-identifying data. We aren’t the ones doing the consuming. We’re the ones being consumed. The tech industry has become one massive gaping maw, opening wide and swallowing everything in sight, chewing it up into little bits and pieces of comminuted waste, like a paper shredder or a garbage disposal. It’s destruction in its most literal form. And for what? For a newer version of the iPad that is only slightly thinner than its predecessor? For an only marginally improved version of Apple’s tablet device that has been around for 14 years? For increased profits? This is a terrible look for Apple. They may as well be saying: “All your work are belong to us.” Personally, I am a fan of artificial intelligence. I am eagerly embracing our robot overlords and I welcome our new CSV god (as the actual developers of AI models like to say). I look forward to the freedom and innovation that will come as a result of humanity augmenting our intelligence with AI like a force multiplier on a battlefield. But if Apple has the same perspective I do, they’re selling it in the worst possible way. When I see this video, I see that Apple is definitely crushing something… but I’m not sure what. -Crushing small companies that develop apps for the extremely heavy-handed App Store, which imposes byzantine restrictions on what they can and can’t do with their own apps? -Crushing competitors by limiting what they can do on the iOS and MacOS platforms with arbitrary and capricious rules about enabling functionalities that Apple doesn’t like, even if users do? -Crushing publishers and content creators with a punitive 30% fee on all subscriptions and in-app purchases? -Crushing choice and competition by not allowing app makers to make apps and programs that do the same thing that native apps already do, even if they do it better? -Crushing all human creativity and innovation by automating and systematizing everything? In the early days of the “Google vs. Apple” fight over the web and app stores, I was really concerned that Google was becoming way, way too powerful. Specifically, in 2015, when Google came up with “app streaming,” they announced a desire to form a “web of apps.” This was concerning. Especially when coupled with Google’s efforts to steal content from other websites and provide it to users via the “knowledge graph” results, ending up with the creation of “zero-click” search results pages, which absolutely punished website owners and content creators. By taking the most valuable content off a website and showing it to Google users without them needing to click through to the website itself, Google had essentially stolen everybody’s intellectual property with only the most minimal attribution possible (to fend off lawsuits no doubt, but with no intention of users actually visiting the website in question anymore). “Google is eating the internet,” I thought, and said out loud, (although I probably wasn’t the first person to use that phrase) But what I meant was purely an analogy. It was vague and ambiguous, almost silly. Maybe I was wrong, though: maybe it’s Apple that’s doing the eating. Maybe Apple is not only gobbling up everyone else’s work, but also homogenizing it—and us—and forcing us to use their platform, pay their fees, abide by their rules, and constantly keep upgrading, upgrading, upgrading, to an ever-thinner iPad in order to use it. Watch the video again. This is the stuff of nightmares. To be perfectly fair, even if I were to take the commercial at face value and ignore it’s off-the-charts creepiness and just stick to its one stated claim—that the new iPad Pro is thinner—it still fails as a commercial. Why? Because nobody cares how thin an iPad is. Seriously. I’ve owned an iPad since 2010: that means I’ve carried around a version of Apple’s already-thin tablet every day for over a dozen years. Never once have I said to myself: “You know what improvement I’d really like to see in this thing? I wish it were thinner.” Never. That thought has never crossed my mind, even once. You know what has? -Better battery life. -I’d like my iPad to not get hot to the touch when I use the Apple Pencil to take notes. -I wish it wasn’t so fragile: I dropped my brand-new iPad 2 back in the day when it slipped out of the arm-hold I was carrying it in, it bounced on the pavement, and the screen shattered into a thousand pieces, making it unusable. -I wish it had more storage. -I wish Apple would stop changing the type of cable connector it uses: I’ve gone from the original 30-pin connector to the Lightning connector, and now to the current USB-C/Thunderbolt connector. -I wish I could view the screen in direct sunlight. -I wish it wouldn’t overheat and turn off automatically when I use it outdoors in the summertime. Those are announcements I would welcome in a new iPad Pro commercial. None of this “now even thinner” nonsense nobody needs or cares about. So, back to the commercial. In my opinion, whoever made this ad should be fired. I almost never say that about other companies, especially for good-faith marketing efforts gone wrong… those of us who work in marketing make mistakes sometimes, and we learn from them. But cases like this warrant a special exception. Marketing and advertising are designed to make people want to buy your products. This commercial doesn’t just not make me want to buy Apple’s products. It makes me not want to buy Apple’s products, which is something altogether different. It turns me from someone who likes iPads into someone who is almost rethinking iPads entirely. That’s not just a bad advertisement; it’s a harmful advertisement. Apple’s usually known for great commercials. The legendary 1984 Super Bowl commercial was, of course, their best. I thought “Hello, I’m a Mac” was absolutely brilliant. They have made some missteps along the way, but this one is really bad. Not even their nauseatingly preachy and woke “Mother Nature” ad from a few years ago was this bad. Steve Jobs once said, “Technology alone is not enough—it’s technology married with liberal arts, married with the humanities, that yields us the results that make our heart sing.” My goodness, that last line alone is poetry itself! This ad seems to be Apple signaling that they don’t believe in that anymore. And I don’t think all this handwringing is an overreaction to where you could say “Oh, c’mon, it’s just a commercial! What’s the big deal?” It is a big deal. It tells you about the values of the company, and what they intend to communicate. Really, how is this the same company that used to sell iPhones by showing grandmas using FaceTime to connect with their baby grandchildren from afar during the holidays? Everything about it is wrong: even the thumbnail they chose for it (the bulging-eyed smiley face) and the fact that they gave it the title “Crush!” It was fun to see the reactions to the video online today. I find it fascinating that Apple shared it on YouTube but turned off the comments. On X, Tim Cook shared it Tuesday, and the video, which so richly deserves to be mocked, is getting it in spades. Some people are calling it “anti-art.” One user called it “soul-crushing,” which was about as literal and logical a response as you’d expect. It turns out Apple actually made an announcement about the commercial. In response to the (apparently unexpected) poor welcome it got, Apple wrote: “We missed the mark with this video, and we’re sorry.” Lame response from a tone-deaf tech behemoth, but still, they hopefully got the message. C’mon, Apple. I have seen the future, and this ain’t it.](https://image.24vids.com/tw-1788740167194579387/media/GNLjSOOaEAAZ6VT.jpg)