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Did You Know? XANA Builder Has an Explorer Panel! 🗂️ 📋 View all placed objects in an organized hierarchy with parent-child relationships. 🔧 Easily identify and fix components that aren't configured correctly. 🎯 Navigate complex scenes effortlessly with structured object management. ▶Download now and build efficiently Windows: Mac: #XANA... show more
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![This is one way they're going to fill those ICE warehouses IMO: "With PCR [they] can declare you a carrier of any possible virus...[and] certain viruses are... written into law as quarantineable.... [So they can] violate your constitutional rights and imprison you without due cause." This clip of retired pharma R&D executive Sasha Latypova (sashalatypova.substack.com "Due Diligence and Art") is taken from an interview with Shannon Joy (Shannon Joy) posted to Rumble on February 10, 2026. ----------------Partial transcription of clip--------------- "With PCR, we can declare you a carrier of any possible virus. Any possible virus on the planet existing now, imaginary, non-imaginary, the one we just drew in a cartoon. We can diagnose you with that virus with the PCR, and then depends on how. "And also the US law is set out such a way that certain viruses are actually written into law as quarantineable. And quarantineable means the government can violate your constitutional rights and imprison you without due cause. And this is why they build those centers in the marketplace mall, by the way. "So this, the detention center. There are several viruses, including influenza and Covid and a few others that are written into the US Law that gives CDC and the military unlimited power to. To detain you, take you off a cruise ship like, just like they did with those, Grand Princes and, the other. Yeah, International Princess. I forget those two. And, send you to the military base where you will be treated against your will and killed there and then declared you dead from COVID or disease acts or whatever next virus we're going to have on the menu. "And so that's why. That's why these, these are, you know, these are not just to harvest people's bodies. That's. That's a given. Yeah, they've been doing that, that for ages. Now this is also designed to imprison anyone by declaring them a carrier of a, of an emergency threat virus. And so imprison any dissident, anybody the state wants to get rid of is a perfectly easy way to do... And also broadly establish control measures. "So if they want to roll out CBDC programmable money, this is a way to do it, by tying it to your health records. They already tying everything to the. To the health records. They're already centrally collecting all the health data through the electronic medical records, which. Which, you know, technically the practice of medicine, including these electronic medical records, supposed to be a purview of the state regulation, not federal regulation. But... we have blown past that a long time ago. "And now all these records, health records, have been centrally sucked into federal databases, which are then turned over to Palantir to target you, to the sum up, to AI, to set up some AI to surveil you. So now they can force you, especially with people with children, they can threaten them, and you've been participating in those, in those cases many times where they can threaten the parent if they deny some sort of a health intervention. "And, you know, and parents will comply just because they're afraid for their children. But guess what? They can also test your child for some novel virus. Find it, and then you. And then you become it. Then you become the sentinel case. Then you become that case that they need to demonstrate there is a pandemic... Lock down the whole community, do whatever they wish there. It becomes an unlimited scenario for totalitarian dystopia."](https://image.24vids.com/tw-2022860302728204613/amplify_video_thumb/2022857785420189696/img/ZNrGkP3F2EKfpU0b.jpg)
![🛸 Vegas UFOs 🛸 Wanna support my efforts? Info. is at the end. And, as always, my comments are in ( ). "Jim Dolan (owns Sphere) and Jane Rosenthal made me an offer: 'Could you build an observatory on top of the Sphere?' Dolan is interested in finding whether there is some alien intelligence out there." ~Avi (Since I live here, this is pretty cool! It also doesn't hurt that the owner (Dolan) of my favorite basketball team (NEW YORK KNICKS), and 2nd-fav hockey team (New York Rangers) is one of the folks who helped get this started. Learn something new every day!) Dr. Avi Loeb: "This one is about Sphere in Las Vegas. As you know, it's the most impressive venue for entertainment in the world. Not only have I been [there], I've been to the top of the Sphere, which is like 120 meters high. Here you see me from inside the Sphere. This is the exosphere, by the way, it's covered with LED displays. We went all the way to the top. Why? "Because a year ago, two very distinguished visitors came to the front door of my home. By the way, lots of interesting people show up at my front door. This was Jim Dolan, who owns the Madison Square Garden, as you know, and also the Sphere, and jane rosenthal, the CEO of Tribeca Enterprises, and they made me an offer that I cannot refuse. I'm leading the Galileo Project to look for unusual objects around the Earth. And they said, 'Could you build an observatory on top of the Sphere?' "Because, you know, Jim Dolan really is interested in science, and especially in finding, you know, whether there is some alien intelligence out there. And I said, 'Of course! I will be delighted.' So that was September 2024, one year after the Sphere was opened with a concert, as you may know. I don't know if you've been there." Joe Rogan: "Yeah, I've been there for the UFC." Avi: "Yeah. UFC, exactly. So anyway, I was there just a few months ago with my research team. We went all the way to the top and installed, as you can see here, an array of infrared cameras that monitors the entire sky above Vegas, at all times. So you can see some of these images show the landscape of Vegas in the background. It's like a freckle, you know, on top of the Sphere, the exosphere, which is the biggest display on Earth. But we measured that there is not much light pollution, actually, and we can operate this observatory." (I'm surprised they measured "not much light pollution" since we all know that one nickname for Vegas is The City of Lights due to the millions of lights from the casinos on The Strip and surrounding area.) Avi: "We also put an array of visible-light cameras there, and it's operating, okay? And we hope to see a few million objects over the sky of Vegas and decide whether any of them has performance that deviates from the envelope of human-made technologies." (Absolutely nothing wrong with that. And if anybody craps on it, ask them if they're even interested in this subject.) Avi: "How do we do that? We have the Sphere as one point, but then we put two copies of that observatory ten kilometers away on a triangle. And that allows us to look at objects in the sky from different directions, just like we have two eyes so we can gage the distance. So here we have three eyes looking at the sky above Vegas, and we can tell the distance, the velocity, the acceleration of objects, and ask whether they are lying within the performance envelopes of human-made objects. And that would be amazing, it's very exciting." (It would be nice if there were people who could (allegedly) summon UAP to the Vegas area by meditating or using technology. Oh, wait... 👽 ) Avi: "I see that also as an opportunity to communicate to the public the excitement about science. That's what Jim Dolan and Jane Rosenthal really wanted to deliver. And I'm hoping that we will find something really anomalous. You know, because, as we know, the intelligence agencies are reporting to the U.S. Congress about objects they cannot identify. And, you know, that could be two things." (It can be more than two things. A few possibilities: Foreign adversaries. A human, non-state actor that has acquired a technological breakthrough. A previous human civilization that had a technological breakthrough, survived a cataclysm, and remains hidden on this planet in smaller numbers. A non-human intelligence that's based here and has always been here. A non-human intelligence from another planet. Time-traveling humans. Non-humans who exist in other dimensions that humans can't perceive with their normal senses. Aka Interdimensional or a shadow biome. Nod to Dr. Eric Davis for the latter.) ~ Avi: "They're getting, you know, the defense budget for 2026 is a trillion dollars, okay? If they tell us that with a trillion dollars, there are still objects they cannot identify above the U.S., they're not doing their job. They're not doing their job, and we should be worried." (100%. But there may be some folks in government who CAN identify some of these objects and they're keeping that information hidden for various reasons.) Avi: "Who sent these objects? Could it be adversarial nations? Okay? That's one possibility, which has to do with national security. The second possibility is that it's maybe something from outside of this Earth which would be even more significant." (Again, there are plenty of other possibilities.) Avi: "So either way, we need to figure this out. And I don't think I'm wasting my time leading the Galileo Project to figure out whether there are anomalies, you know, that go beyond human-made technologies. Because if it turns out that all the objects are human made, I will be happy to deliver the set of sensors we developed with the machine-learning software that we developed, to the Department of War 🇺🇸 so that they can employ it for national-security purposes. So my time was not wasted, as a scientist. I'm doing something useful to society." Rogan: "Of course." Avi: "The Department of War can use it. I have no problem. Everything made by humans, by the way, is boring, as far as I'm concerned. I want to see something from outside the solar system, which is not what the government should be about. The government should worry about national security, not about what lies outside the solar system. That's my job definition as an astrophysicist, okay?" (Not to sound like a broken record, but...some of what we're seeing that appears to be anomalous may be from within this solar system or, potentially, Earth-based.) Avi: "And so, I feel that this is worthy [of] pursuing, but the Galileo Project is really the first organized project that constructed a reliable set of sensors in an observatory configuration that does systematic study of the sky to collect millions of objects in the sky per year. We have three observatories, one in Las Vegas, as I mentioned. And by the way, this is the first time it's mentioned publicly, so..." Rogan: "That's amazing." Avi: "And another one in Massachusetts, and a third one in Pennsylvania. They were all funded by people who approached me and said, 'Here is the money.'" Rogan: "Let me ask you this: If it wasn't for those, how many observatories are looking for objects that are not from this Earth? Like, is that very rare?" Avi: "None." Rogan: "None?" Avi: "Well, there are some teams that are, you know, doing it, making a trip to collect some data." Rogan: "There is not constant observation?" Avi: "Of scientific-quality data? No." Rogan: "That's crazy." Avi: "That's crazy! That's what I'm saying." ~ (One of the groups that collected data was the AAWSAP/BAASS team headed up by Dr. James Lacatski. This is from my March 2024 post... Here's an excerpt from "Initial Revelations" by Lacatski, Kelleher and George Knapp. Chapter 18 Integrated Sensor Package to Detect UAP An autonomous sensor package to detect UAP for AAWSAP BAASS was developed by an engineering team located at Bigelow Aerospace. The following is a short summary of the specifications by which the BAASS engineering team began designing an autonomous sensor package. The project started at the conceptual stage with a meeting in late January 2009 and a complete operational prototype was built by August 2009. Design Goals: Device will operate unattended Autonomous data collection Survivability: weather, vandalism, critters Portable: “Two men and a truck.” Limited power No reliance on AC power Must be sized for full nighttime operations Sufficient communications May use WiFi, satellite phone, and cellular phone transmis- sions as the situation warrants Internet appliance for remote connection Short-range sensing (<20ft.) Long-range sensing (up to 5-mile planar radius, indeterminate altitude) Internal clock: GPS or network time-based COTS (Commercial Off-The_Shelf ~Joe) or very near COTS components only Reduce on-site maintenance to the minimum possible Camouflage based on geographic location Sensor Suite Visual, IR, near-IR, and UV spectra cameras Microwave band detection Radio band detection EMI detection in the electronics emission band RADAR LIDAR (Light Detection and Ranging) Audio Radiation (gamma, beta, alpha) Gravimeter See equipment details and illustrations in Tweets 2 and 3. ~End "IR" Excerpt~ ~ Avi: "And, by the way, I gave a briefing to the U.S. congress on May 1, 2025 and Congresswoman Rep. Anna Paulina Luna was there and she was very excited about the work we are doing. But the day before that, I visited an office in the Pentagon that is called the All-domain Anomaly Resolution Office - AARO - All-domain Anomaly Resolution Office. And I asked them, 'You looked into all these unidentified objects reported in the past by military personnel. Did anything trigger your attention as something truly anonymous?' And they said, 'Not really. There are some reports by FBI agents that's really crazy stuff, but we don't have any data from instruments.'" (Here's a tweet from me about the director of AARO, Jon Kosloski, describing three, potentially, anomalous cases AARO is analyzing. ) ~ Avi: "And this is an office within the Pentagon which is funded to figure out things. And so, obviously, what they might want to do is imitate the Galileo Project that I'm leading. But you would think that it would be sort of the vested interest of government, you know, to invest in research related to that, which is what the Galileo Project is doing." Rogan: "Well, here's the thing. I would have thought it was already done." Avi: "I don't know." Rogan: "Until we're having this conversation, I can't believe that they're not monitoring the sky constantly for anomalous objects." Avi: "Well, you remember the Chinese spy balloon that was missed, right? And shot down?" Rogan: "Yes. Yeah, but that was silly." Avi: "So the thing to keep in mind, they're getting data on things in the sky, but if you don't have the right software now, with AI. If you don't have high-quality scientists, the way that the Manhattan Project employed, you might not figure out things. There is a reason why the Manhattan Project recruited the very best scientists. "So I say, put a billion dollars on this or more, bring in the best scientists in the world to figure it out. I'm funded at the level of millions of dollars through the Galileo Project. The government can do a billion... What is a billion dollars? It's a drop in the bucket for the Pentagon. But, if, you know, you should think about the potential risk from drones that are used by adversarial nations and..." (1000%. Put a billion dollars into that and also an AAWSAP-like program that is run by a PUBLIC company, and make all of their data available to us as soon as they receive it.) ~ If you appreciate what I do on Twitter/X (and my Blog and, occasional, YT), and wanna support my efforts, you can subscribe on here. Or.... Patreon - PayPal - ufojoe11@aol.com Venmo - My Patreon is simple. No hidden content and no tiers. If you DO support me, it will be much appreciated. If you can't afford it, don't think twice. I've been there and I get it. If you don't think my content is worth supporting, I still appreciate you reading and commenting on tweets, articles and videos.](https://image.24vids.com/tw-1983635340494803377/amplify_video_thumb/1983584911736070144/img/_2338jo98pR7iciz.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)
