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Those are some consistent strokes right there, like wow Devour my nyash papi #sexytwink #sexy #homemade #doggy #backshots #gaysex #raw #moans #nyash #mrija #anal #gape #strokes #chudai
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![minghao🥺 🐸 i wish to be with carats for a long, long time. didn’t i say something like this previously? a fan asked me “what would you do if i leave you?” i used to say, if you climb on me and soar higher, it’s your path to growth. i will still cheer on for you if you leave me. that’s bc you cannot take energy from me anymore. i said that bc you grew so you don’t have to like me anymore, right? as i’ve done my job for a long time now, i feel like i’ve found the answer — it will be fine as long as i do well. i’ll continuously try to fuel new energy. my mindset, attitude, skills, my works, as an idol, an artist. i should continue to give carats positive energy through my works as an artist. [while doing these] wouldn’t our carats continue to be by my side? this is my thought. i just have to do well. so i hope that our carats will just live enjoyably and happily. i rly thought about such things a lot as i’ve been on this job for 10 years now. how should i live moving forward, how do i maintain this job, what kind of relationship should i have with carats moving forward. i think of everything. even if i do those, there are definitely still parts where i’m lacking in. there will be parts where i’m lacking inevitably but i will do my utmost best with sincerity. i’m not hoping for carats to acknowledge these but i’ll be very thankful if you will understand and love me. you can just look at our pictures, videos, lives. these alone are sufficient. if we can have deep conversations and giving and receiving emotions from each other, i think that’s the happiest thing for me. there are carats who can read my mind [about my work] when i release my work and i get goosebumps when i read those. “wow how do you know me so well?” sometimes i get to know that i have this side of me as a person when i look at carats. it’s rly fascinating. “wow that’s right! that’s how i thought.” i didn’t thought of it myself consciously. there are times where i do it without thinking about it consciously too but there are carats who are able to catch those points. and i’m rly thankful. it makes me feel like we have some deep emotional connection at times.](https://image.24vids.com/tw-1986744488329662744/amplify_video_thumb/1986743760777330688/img/svusF0Q_kkDbhTRm.jpg)
!["I'm not sure that we need the dog whistle at this point. And maybe there are ways to re-create it." ~Nolan "There might be a day when Skywatcher doesn't need to exist." ~Nolan "If I had been running the whole show, nobody would even know what Skywatcher is right now." ~Nolan ~My comments in ( )~ Garry P. Nolan: "We've got a lot of data from multiple alleged sightings, both radar and other kinds of data. First it was about getting the raw-data files all put in one place because some of the data was collected by James (Fowler) before there was, officially, kind of a Skywatcher. "And so, getting that data, getting the instrument names that he used for those, then getting the technical manuals of what the settings might be and how much of that information is collected in the metadata when you're collecting the thing... All of this is just the organization that you need to do before you do anything else. "And then, getting from the companies how it is that they parse their raw data. Because some of these data files are put into...I wouldn't call them encrypted, but they're stacked into a certain kind of file structure - and I've seen the file structure - which is, you can think of it as a giant spreadsheet with headings and numbers for each of the columns and time on the row axis. "And so, you know, we've started looking at some of the data and put it into, let's say, 3D tracking. And it's clear that there are some things about the data that we needed to go back to the vendor who makes the instrument and say, 'Why is this and this and this happening, you know, every few dozen milliseconds?'" (I wonder if some of what they saw in their data, and labelled as anomalous, has maybe turned out to be a sensor artifact?) Nolan: "And so, you know, just getting an answer from these companies, often, when you don't even own the instrument, they're like, 'Well, why should we give you the information about how our data is constructed? How do we know that you're not a competitor?' Right? I mean, and so these are the kinds of things that we then contact somebody who has a behind-the-scenes access to this so that we can, again, it's all of these little steps. "And I'm sure there's somebody who's gonna tweet, 'Well, why don't you just put all the raw data out on the internet?' For exactly the same reason you don't put the raw data from ancient DNA sequencing. Because people will make mistakes about it. And so, if I'm going to be involved, I'm not gonna make any mistakes like that. So I'm sorry if people want stuff early. "I think you know, perhaps, if... Well, if I had been running the whole show, nobody would even know what Skywatcher is right now. We'd just be collecting the data in a fully-stealthed mode. And...but, you know, it's...there's reasons, good reasons, why they wanted some publicity. And, you know, but I don't always get my way." Vinnie - 𝐕𝐢𝐧𝐧𝐢𝐞 𝐀𝐝𝐚𝐦𝐬 𝕏: "Would you say that the data is exciting?" Nolan: "Oh, there's some interesting stuff in there. I mean, frankly, perhaps some of the better data that we have is just a couple of pictures from the ground of the helicopter with something about, you know, 200 feet in front of it. It's a clear blue sky and there's an object right in front of the helicopter. And the people in the helicopter said at the time that they couldn't see anything, even though we could see it from the ground. "But meanwhile, all of their instruments are going haywire. So, there was an effect. So why couldn't they see it? Maybe it was just out of view? Who knows? So it wasn't a lens flare, and it certainly wasn't a seagull. Mick (both laugh)." Vinnie: "Not in the desert anyway." Nolan: "I can't help myself." Vinnie: "I'm all for it. I'm sure Mick would, too. Hopefully. You know, James Fowler, we know he's left and moved on working with a new company. You know, all the best to him. Am I right in saying some of the technology being utilized by Skywatcher was proprietary to him, specifically? Maybe the dog whistle even? Is that still going to be able to be used by Skywatcher? How's that going to look going forward?" Nolan: "Umm, I'm not sure that we need the dog whistle at this point. And maybe there are ways to recreate it. I'm not party to the discussions around that. And so, we'll see where that goes." (That sounds like Fowler is NOT going to allow Skywatcher to use the dog whistle. That's a big disappointment. I mean, if this is really NHI and the dog whistle works 100% of the time, as claimed, then the whole world deserves to know about it.) Nolan: "I mean, James is not like, gone and forgotten. I mean, I could Signal chat him right now. And so he's there to help us. But, you know, my take on things is, you know, James has a life to live and a family to feed, and maybe his focus isn't entirely on UAP. He certainly has an interest in it. And maybe he has, you know, a company to build, and an opportunity that, actually, we all see now in terms of detecting drones. And, you know, if he wants to run a company like that then running around with a bunch of UAPologists might not be to that benefit. "And there might be a day when Skywatcher doesn't need to exist. The whole idea of Skywatcher is to show that something like this can be done, and it can be done in a serious way." (jakebarber claimed that they could BRING DOWN a craft. If that's true, it would change the world. What happened with that? Barber also said, "Who is operating [UAP]? How are they being operated? Where are they coming from? We should be able to answer those questions, probably entirely, in the next 12 months." Time is running out. Does he still stand behind that? Full Barber post with video clip: ) ~ Nolan: "I mean, I would...I, frankly, hope that if UAPDA - Disclosure Act is passed, because then the information that can be allowed to be out can be let out, and the stuff that needs to be kept secret stays secret. Again, I'm not, I would never advocate for a data dump." (I would 100% advocate for a data dump, minus details on anything that can be used as a weapon. Nobody, including the USG or private contractors owns this information. If it's gonna be a slow drip, for decades, then I fully support an Edward Snowden-type of leaker.) Nolan: "And so, you know, call it controlled disclosure, what have you. It needs to be done the proper way. And, you know, if any of the claims are true, there are reasons why you want to be methodical about it." (Who gets to decide what "the proper way" looks like? It seems like we're having more gatekeeping on top of the original gatekeeping. Not good.)](https://image.24vids.com/tw-1959807609269342649/amplify_video_thumb/1959793613472493568/img/7KcE6RlaiWrJogSA.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)
![Former medical coder/whistleblower Zowe Smith describes waking up to the "vaccine" fraud: "[The] lab where I worked... everybody was saying... you get the flu from the flu shot... [then] when [the Covid jabs] came out, people were having strokes and encephalitis and blood clots like I've never seen before... [And] they were getting Covid-19 immediately after getting the shot." This clip of Smith (Zowe Smith), who is also the author of The COVID Code: My Life in the Thrill Kill Medical Cult, is taken from an interview with David Knight (David Knight Show LIVE 9am EST, M-F) posted to Rumble on November 13, 2025. -----------------Partial transcription of clip-------------- "I started to wake up during really, when they started declaring two weeks to flatten the curve, and I started seeing people wearing masks in public. I knew this was not a pandemic, and there was something, some kind of psychological operation going on because I had worked in the hospital for the swine flu scare, and it wasn't a thing in the hospital. It was just regular flu. I've even talked to, people that were on the front lines, like ER doctors and nurses, and they said— Some of them even said that they got it, and it wasn't that big of a deal. "When they declared Covid, I was really suspicious. This is just going to be another vaccination campaign because they already had mandates for the flu shot for health care workers for, like, a decade before that. And I had been doing the exemption every year. And the reason I did that is because the first year that they made health care workers get the flu shot, everybody was getting the flu. And so that was the year that we came up with the— It was just a rumor within the university lab where I worked, but everybody was saying it, that you get the flu from the flu shot. "Ever since then, I just didn't want to do it. So during that whole year of Operation Warp Speed, the only thing that's going to get us back to normal is this vaccine. I thought this— If the flu shot never worked, the chances that the COVID shot is going to work is slim to nil. And the amount of pressure for this one compared to the flu shot is astronomical. So there's something to it. So that made me actually not just look at the COVID shot, but look at all the other vaccines. "What I learned was they don't teach coders or doctors or nurses anything about vaccine side effects or adverse effects, despite the fact that they have, codes to assign for vaccine effects. But I would see patients come in with, like, Guillain Barre before this, and the doctors would try very hard not to relate it to a vaccine. "There would be codes in there, like adverse effect of flu shot or adverse effect of whatever. And those are supposed to be, like a safety signal code, like one of the reasons why the ICD10 system, which is owned by the WHO, by the way, so every. Every member state that is part of the WHO has to report these codes. And it's for statistical monitoring purposes. "This is how they monitor pandemics. This is how they monitor cancer, like how many cases of cancer there are throughout the world, or heart problems or pneumonia cases. This is the system that they use. And it's also supposed to be used, starting in clinical trials for devices and drugs to look for a safety signal. So I thought with this COVID-19 vaccine, there should be a code for adverse effect of this shot, and it should be my job to assign it. "I did my due diligence and I looked into all the warnings and what could happen if people got the shot. And then I looked at what could happen if people got the other vaccines. And I started to realize that they had been burying all of the effects that people would get from vaccines and not assigning these adverse effect codes up until 2020. "Then when the COVID-19 vaccine came out, there was no code to report it. So it should have been my job to collect that danger signal. And I even went on a podcast called Deborah Gets Red Pilled, was just a radio show, in early 2021, right after I quit my job. And I said the COVID-19 vaccine is more dangerous than all of the other vaccines combined. And that was with my— That was just an observation, but it was 10 years of medical coding experience and then learning what I learned about vaccine side effects and all the cases that I saw of children in the ER constantly having eczema or rashes or even anaphylactic responses. And then I look at the record, they just got a vaccine, but the doctor's not connecting the two. "So when COVID-19 came out, people were having strokes and encephalitis and blood clots like I've never seen before. Myocarditis. They were getting COVID-19 immediately after getting the shot, like the same day or the next day, and then being hospitalized. There are people with paralytic problems, seizure disorders, blood disorders, where they couldn't even figure out what was going on because the patient was clotting and bleeding at the same time and they didn't even know how to treat it. Crazy stuff started happening just in the first four months of the vaccine rollout."](https://image.24vids.com/tw-1990213939809193991/amplify_video_thumb/1990210046039646208/img/Y2g77UQnGT6VECri.jpg)