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![#TAEMIN Global Spin Live at the Grammy Museum - Fan Questions segment [FULL] 🎙️Host: What was the first song you heard from Taemin? 💎Audience: [shouts a bunch of songs] 🐣Taemin: What is your guys’ favorite song? 💎Fan: NEMO! My cat is named Nemo! Taemin: Oh my cat is named Ggung! 1:55 🎙️Question 1: Do you get embarrassed listening to your own voice? [from Denise] 🐣Taemin: When I record my sexy songs like Sexuality, Criminal, something something, I have to acting more emotional—sexy vibe right? Sometimes very embarssed [demonstrates with the sexy part of Want] 2:55 🎙️Question 2: Taemin, your choreo is always so unique. What’s your favorite choreo that you’ve ever danced? [from Stasia] 🐣Taemin: Honestly my choreographer is in here, Kasper! His choreo is very cool but very hard and fast and aggressive, energetic, but I love that style. So for example—Advice. Recently my favorite song is Flame of Love. It’s Korean style, the moves are more contemporary style, that’s more interesting to me recently Lastly my favorite song is Criminal. That song is very conceptive and also choreographed by Kasper. 5:00 🎙️Question 3: What would you consider to be your greatest achievement in live? [from Emily] 🐣Taemin: When I was young I go to audition for…to be artist. So that is my very important moment. I did it! I debuted! 5:50 🎙️Question 4: What is your favorite pre-show ritual [from Gloria] 🐣Taemin: I always clean my teeth, it’s refreshing….and then recently I started consuming things that are a little sour like lemon juice. It helps with the bloating a little bit. And they said it helps with anxiety. 🎙️Host: It helps with bloating?? 🐣Taemin: ah yes!… ah…maybe? That is not… please search it please! [lololololol he was scared he was giving unproven medical advice] 7:20 🎙️Question 5: If you could collaborate with any artist globally who would it be and what kind of sound do you want to create together? [from Jihae] 🐣Taemin: Ah that’s what you’re curious about! There’s so many artist that I love so it’s really hard to pick one but maybe Billie Eilish? I love her attitude. She could draw in concentration even when she makes small sounds and in contrast I can do something much more energetic and maybe the contrast could create something very special. 9:00 🎙️Question 6: Do you ever sing or perform for your cats? 🐣Taemin: I put them on my lap and I maneuver them a little bit and they dance a little bit [Taemin demonstrates the song he sings them] 🎙️Host: Do you do it to your music or other people’s music? 🐣Taemin: It’s an improvised song! 🎙️Host: Are you gonna show these videos? 🐣Taemin: I don’t have hands to film it! Lol 10:15 🎙️Question 7: What’s the style of your new album? 🐣Taemin: You know just yesterday I was sorting through all the music that I wrote and it kind of gets categorized into 3 categories! We have songs that are really powerful and energetic, and songs that are really emotional and beautiful, and then the third category is a little different…maybe RnB? and now it’s something I have to think about how to present these all together. #TAEMIN_Grammy_Museum](https://image.24vids.com/tw-2013909144324166101/amplify_video_thumb/2013904017244770304/img/zR7HNv3JlclJpJ8w.jpg)
![At a campaign rally in Hamilton, Ontario, Liberal leader Mark Carney unveiled what can only be described as a coordinated assault on digital freedom in Canada. Behind the slogans, applause lines, and empty rhetoric about unity, one portion of Carney’s remarks stood out for its implications: a bold, unapologetic commitment to controlling online speech under the guise of “safety” and “misinformation.” “We announced a series of measures with respect to online harm… a sea of misogyny, anti-Semitism, hatred, conspiracy theories—the sort of pollution that's online that washes over our virtual borders from the United States.” He then made clear his intention to act: “My government, if we are elected, will be taking action on those American giants who come across [our] border.” The former central banker, who now postures as a man of the people, made it clear that if the Liberals are re-elected, the federal government will intensify efforts to regulate what Canadians are allowed to see, say, and share online. His language was deliberate. Carney condemned what he called a “sea of misogyny, anti-Semitism, hatred, conspiracy theories” polluting Canada’s internet space—language borrowed directly from the Trudeau-era playbook. But this wasn’t just a moral denunciation. It was a legislative preview. Carney spoke of a future Liberal government taking “action on those American giants who come across our borders.” Translation: he wants to bring Big Tech platforms under federal control, or at least force them to play the role of speech enforcers for the Canadian state. He blamed the United States for exporting “hate” into Canada, reinforcing the bizarre Liberal narrative that the greatest threat to national unity isn’t foreign actors like the CCP or radical Islamists—it’s Facebook memes and American podcasts. But the most revealing moment came when Carney linked online speech directly to violence. He asserted that digital “pollution” affects how Canadians behave in real life, specifically pointing to conjugal violence, antisemitism, and drug abuse. This is how the ground is prepared for censorship: first by tying speech to harm, then by criminalizing what the state deems harmful. What Carney didn’t say is just as important. He made no distinction between actual criminal incitement and political dissent. He offered no assurance that free expression—a right enshrined in Canada’s Charter of Rights and Freedoms—would be respected. He provided no definition of what constitutes a “conspiracy theory” or who gets to make that determination. Under this framework, any criticism of government policy, of global institutions, or of the new technocratic order could be flagged, throttled, and punished. And that’s the point. Mark Carney isn’t interested in dialogue. He wants obedience. He doesn't trust Canadians to discern truth from fiction. He believes it’s the job of government—his government—to curate the national conversation, to protect citizens from wrongthink, to act as referee over what is and isn’t acceptable discourse. In short, he wants Ottawa to become the Ministry of Truth. Why They Don’t Actually Care About Antisemitism The Liberal establishment talks a big game about fighting hate—but when it comes to actual antisemitic violence, they’ve shown nothing but selective enforcement and political cowardice. Let’s look at the facts. In 2023, B’nai Brith Canada recorded nearly 6,000 antisemitic incidents, including 77 violent attacks—from firebombed synagogues to shots fired at Jewish schools in Montreal and Toronto. This wasn’t a marginal increase. It was a 208% spike in violent antisemitism in a single year. Statistics Canada echoed the same alarm bells. Jews—who make up just 1% of Canada’s population—were the victims of 70% of all religiously motivated hate crimes. That’s nearly 900 recorded incidents, up 71% from the previous year. Then came October 2023, when Hamas launched its attack on Israel—and the wave of hate turned into a tsunami: a 670% increase in antisemitic incidents across the country. Jewish schools, synagogues, and community centers were hit with bomb threats, arson attempts, and intimidation campaigns. This was a national security issue, not just a policing matter. And yet, the government's response? Virtually nonexistent. Case in point: the Montreal Riot, November 2024. A 600-person mob, waving anti-NATO and pro-Palestinian banners, turned violent—setting fires, smashing windows, and attacking police. Amid this chaos, a man was filmed screaming “Final Solution”—a direct reference to the Nazi plan to exterminate the Jews. It went viral. There was no ambiguity, no misunderstanding. It was a public call for genocide. So what happened? Three arrests. None for hate crimes. None related to antisemitism. Montreal Police Chief Fady Dagher insisted there were “no confirmed antisemitic acts,” and as of early 2025, no hate crime charges have been filed against the individual caught on camera. That man, as it turns out, owned a Second Cup franchise. His punishment? His café was shut down by the company. Not by law enforcement. Not by hate crime investigators. A corporate HR department showed more backbone than Canada’s justice system. And this is what reveals the truth: they don’t care. They’ll enforce hate speech laws when it’s politically convenient—when it can be used to silence critics, crush dissent, or placate woke constituencies. But when Jewish communities are being threatened, attacked, and terrorized? The same laws suddenly go limp. The same political class that claims to protect minorities becomes paralyzed. They won’t touch it. Because confronting real antisemitism would require standing up to their political allies in activist circles, university campuses, and radical protest movements. This isn't an accident. It's a pattern. The Liberals aren’t weak on antisemitism because they’re unaware of it. They’re weak on it because they don’t see political value in enforcing the law when it conflicts with their ideological allies. Their obsession isn’t with hate speech—it’s with controlling “wrong” speech. And what qualifies as “wrong” isn’t defined by law or principle. It’s defined by what the Liberal establishment deems unacceptable. Their target isn’t violent bigotry. It’s dissent. They’ll chase down citizens for questioning carbon taxes or criticizing globalist policy—but when Jewish schools get shot at, or someone calls for genocide in the street, they shrug. This isn’t leadership. It’s selective justice. And it proves, beyond any doubt, that their agenda was never about protecting Canadians. It was always about protecting control. The Online Harms Act: Carney’s Blueprint for Speech Control This isn’t hypothetical. Mark Carney’s remarks in Hamilton mirror the exact logic and intent behind the Online Harms Act (Bill C-63)—legislation drafted under the Liberal banner and introduced in 2024 that pushes Canada into territory no free society should accept. At its core, Bill C-63 hands the federal government sweeping powers to police digital speech. It creates a Digital Safety Commission, an unelected bureaucratic authority empowered to monitor, investigate, and punish online platforms and individuals for content deemed "harmful." That word—harmful—is never concretely defined. It includes things like “hate speech,” “conspiracy theories,” and vague notions of “harm to children,” but it’s written broadly enough to be used as a political weapon. The most chilling provision? Preemptive imprisonment. Under this law, Canadians could be jailed for up to a year—without having committed a crime—if a judge believes they might post something harmful in the future. This isn’t law enforcement. This is thought policing. Carney didn’t just echo this approach—he amplified it. In his Hamilton rally, he described the internet as being flooded with “misogyny, anti-Semitism, hatred, conspiracy theories,” and laid blame on foreign content “washing over our borders from the United States.” He didn’t argue for open debate or for empowering users to challenge dangerous ideas. He argued for the state to intervene and shut them down. He told Canadians that these ideas are “changing how people behave” and claimed his government will go after “those American giants” that allow this content to circulate. There’s no ambiguity here: this is a public declaration that a Liberal government under Mark Carney intends to censor, de-platform, and penalize dissenting views. Not illegal ones—just ones they don't like. And this isn’t new for him. Back in 2022, during the Freedom Convoy, Carney referred to protesters as committing “sedition” and demanded the government “thoroughly punish” them. These weren’t violent rioters or foreign agitators—these were working-class Canadians honking their horns and standing in the cold, protesting vaccine mandates. For Carney, their real crime was disobedience. Carney’s view of speech is simple: if it challenges the ruling order, it’s dangerous. And now, with Bill C-63 on the table and Carney at the helm, he’s building the legal infrastructure to lock down the digital public square—not to protect Canadians from violence, but to protect the Liberal establishment from criticism. That law is real. Carney’s agenda is real. And if he wins, enforcement is coming. Final thoughts This is the Canada Mark Carney envisions—one where citizens can’t speak freely online without first checking their views against government guidelines. A country where speech is no longer a right but a privilege granted by bureaucrats. A country where opposition isn’t argued with, it’s labeled harmful and erased. There was a time when Liberals championed civil liberties. That era is over. The new Liberalism is authoritarian—cloaked in the language of safety and inclusion, but animated by control. Carney’s rally in Hamilton wasn’t a policy rollout. It was a warning to anyone who still thinks they live in a country where dissent is allowed. They don’t want to fight hate. They want to define “wrong” speech—and then eliminate it. And by “wrong,” they mean anything the Liberal establishment disapproves of. Criticize the government, question the orthodoxy, challenge the state’s narrative, and you’ll be branded a threat. Not a citizen. Not a participant. A threat. So here we are. The speech laws are written. The censors are waiting. And Mark Carney is ready to pull the trigger. This election isn’t about tax credits or campaign slogans. It’s about whether Canada remains a free country or slides deeper into soft tyranny, one regulation, one commission, one silenced voice at a time. There is a choice. And the choice is this: bring it home—restore freedom, restore sanity, restore this country. Or: hand the keys to the same people who think you’re the problem for having the nerve to think for yourself.](https://image.24vids.com/tw-1911016400912859219/amplify_video_thumb/1911015612068839424/img/frTZBF9wAo75ED79.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)
