Video yükleniyor...
Video Yüklenemedi
EVERYONE’S GOT ISSUES has been a guiding light for Fizzy. Nearly all bug/issue trackers are targeted to software developers. For good reason! Software has a lot of bugs. And since most trackers are built for developers, they tend to be overly technical. Their UIs are dark and menacing. Their... show more
75,138 görüntüleme • 7 ay önce •via X (Twitter)
0 Yorum
Yorum bulunmuyor
Orijinal gönderinin yorumları burada görünecek
![🚨Whitney Webb on where the Trump admin's taking us: "Trump works for bankers. Big surprise." "Peter Thiel... basically created JD Vance in a lab." "[The goal is] an AI-powered surveillance state that is authoritarian in nature and neo-feudal economically. "A lot of these people are obsessed with End Times things." This clip of Webb (Whitney Webb), author of One Nation Under Blackmail and contributing editor of unlimitedhangout(.)com, is taken from an interview with The Last American Vagabond (The Last American Vagabond) posted to X on March 13, 2026. ----------------Partial transcription of clip--------------- Ryan Cristian: "On that general idea, where do you feel like a lot of this is going? Is this just another administration profiteering or do you feel there's a larger agenda in kind of what's happening right now?" Webb: "You mean where the Trump administration is taking us? Well, I think the best summary of it is to look at the big tech Silicon Valley oligarchs that installed themselves in very insidious ways in the levers of power via this administration. "And probably the best thing you can do to learn about them is to buy Iain Davis' new book the Technocratic Dark State or you know, borrow a copy from someone else who bought it or it is the best, most forensic breakdown of those people and what their interests are and what they are doing. "And you can read some of Iain Davis' articles, about aspects of that. For example, he did a amazing investigation into the city states, sort of this, this idea of the network state and all of that and how it's just as bad as the globalist global governance that a lot of people in right-leaning conspiracy quote unquote, conspiracy world are worried about. "You know, it's that on steroids and is being marketed to those people as the solution. And a lot of these people are overt transhumanists. I mean they call themselves 'techno-optimists.' Again sort of a play on that same thing we were just talking about in the Trump era where like we're the optimists and avoid the negative Nancies, feel good with us. They'll just make you feel bad. "And it's all about feeling, not about facts. Yeah, so I mean there's obviously a lot of other agendas at play too. But I think obviously it's pretty clear that in the Trump administration there's going to be some type of big switcheroo economically. "And we will see the rise of, you know, stablecoins, the Bitcoin dollar system as laid out by Mark Goodwin back in 2021. But I mean that has definitely played out. And so I think, you know, a lot of that stuff with digital currency is going to advance, and then we're going to be herded further into sort of this techno-feudal reality. "And then at the same time you have you know, these other aspects of the Trump administration at work that have you know, this very deep set, you know, feeling about eschatology. Like you know, there's an overlap actually if you look at people like Peter Thiel, who's, you know, the person who basically created JD Vance in a lab, and his obsession with the Antichrist and, and all of this stuff. A lot of these people are obsessed with End Times things. "There's been plenty of people pointing out recently how this has influenced likely, the current war with Iran. So, you know, there's obviously a lot of different angles to talk about, but basically, you know, this is not fighting against global governance and global tyranny. "This is going to be a furtherance of the same thing that every administration, whether Democratic or Republican, has advanced, since 9/11 and obviously before that too. But it's, they've, they sped it up. You know, the type of gradualism that they practice increased significantly, after that point. "And the goal was to create, you know, an AI-powered surveillance state, that is authoritarian in nature and neo-feudal economically. And the vast majority of us are meant to be, serfs, or rather, if you want to use the Yuval Noah Harari phrasing, we will become the exploited because it's better than being expendable. "So, you know, Trump works for bankers. Big surprise. They all work for bankers. And these banker, you know, cronies, what they do is they steal your money, and they use your tax dollars to build your prison. So I mean, that's. I don't really anticipate seeing anything beyond that at this point. "And so people that have been going back, looking either at my work on Epstein or work on other stuff and being like, wow, she was early, like, okay, if I have this track record now of working for 10 years and I've been early on multiple big stories, maybe you should look at what I'm talking about now. And not just me obviously, but what a lot of people are talking about now that were right on a lot of those things too."](https://image.24vids.com/tw-2032542651162177836/amplify_video_thumb/2032540470212177921/img/srwGF8_OgGcumsSU.jpg)
![TIM DILLON on the Charlie Kirk assassination and trial—and Butler and the WH correspondents' dinner—as all being "fishy"🐟🐟🐟 "It's fishy to me. The whole thing's fishy. It's always been fishy" "[I've] found a lot of the things that Candace [Owens] has raised to be valid" "And I think a lot of people I know that are really smart people think this is really a weird case" "And I'm not saying that the kid didn't do it. I'm not saying Tyler Robinson didn't do it. I'm not saying that. But the circumstances of like, who he is and why he did it and all that stuff, we just don't feel like we're getting the full story" "It feels like we're getting fragments of a story. And I'm not saying that it is incorrect, but I'm saying that we kind of lack information. There's holes in the story" "It does seem to not line up as nicely as they would like it to" "Whenever somebody says a case closed, it's, it's usually not somebody who is saying that because they want to share information or they're not in a deep search for the truth. Usually" "I come from a time... when the media was all over these people's families. We knew everything about them. We watched the O.J. Simpson trial for an entire year. We knew everything about the Menendez brothers. We knew everything about Laci Peterson. We knew everything about all of these cases. We don't know a ton about this" "We know nothing about Butler. Almost nothing. We don't know a ton about this case. [Also,] we don't know... a lot about the guy who ran into the White House correspondents' dinner. Remember that? We don't know about that" "We don't know about all this stuff. We know a little bit. There's a little bit. They introduced someone, yeah, it's a teacher. And they just went nuts. You're like, okay" "And it seems like the media's being guided on these stories, the traditional media, in a way that leaves chunks of them out" Tim Dillon](https://image.24vids.com/tw-2076040385642762380/amplify_video_thumb/2076038288427876352/img/NYSBJdzjcds0t4VP.jpg)
![Whitney Webb on 15-minute cities: "The goal [is] to have people... corralled [so] they're easily surveilled and controlled." "[They would] share... apartments when [they're] not there." "[They would] lose... car ownership, [so they] can't really control where [they] go." This clip of Webb (Whitney Webb), author of One Nation Under Blackmail and contributing editor of unlimitedhangout(.)com, is taken from an interview with Jimmy Dore (Jimmy Dore) posted to Rumble on March 26, 2026. ----------------Partial transcription of clip--------------- "So I haven't written extensively about 15- minute cities, but I would argue that the goal, there is basically to have people more or less corralled into an area where they're easily surveilled and controlled. And that's basically the... interest here is how do a small few rule the many forever without the many ever being able to complain or do anything about it. "Ultimately, this ruling system that they've been attempting to impose on, on people really around the world, because this is a global governance project at the end of the day, is, you know, using Big Tech tools in, in mass surveillance to basically create an entirely new way of life and system of living. "Part of that is to basically reduce the share of what the many, i.e., the 99% or whatever, have. So, you know, a lot of this, you know, became extremely, you know, unpopular. But also like people learned about it during the COVID era because of, you know, these groups like the World Economic Forum, which by the way, bills itself, is the premier promoter of public-private partnerships, that, you know, we need to not own our cars, we need to, rent them. And there should be autonomous fleets of Ubers that drive everyone around a specific radius. We shouldn't own homes. We should, you know, rent apartments and then share those apartments when we're not there and we leave, someone else can occupy the space. "These were all things, that were promoted under the guise, you know, of, of sustainability and other things at the time. But they're actively being, you know, designed and acted upon. "Actually one of the Columbus smart city initiatives that's connected to this Columbus partnership that that Wexner ran. He chaired it basically from 2001, I think, until 2021. So like 20 years, including when this was created. Columbus got a huge Department of Transportation grant from the government and also, you know, funding from private individuals, probably Wexner, but who knows, to to basically create a new system that in Columbus where private car ownership would not exist. "It would be fleets of, you know, smart cars, autonomous cars that drive people around. And so if you lose private car ownership, you can't really control where you go. And so these cars would determine, you know, would. Would have specific routes that you could, you know, pay to use and what have you. "And, interestingly enough, this was actually a goal for the entire United States, described in this by this national Security Commission on AI which was chaired by Eric Schmidt of Google and had a lot of these same Big Tech guys, who's who are have major roles at companies with New Albany data centers. "They basically said that in order for the US they said to beat China in AI it was necessary to end private car ownership in the United States and instead have autonomous, you know, Waymos, basically, drive every, fleets of them, Uber everybody around to where they were supposed to go and have things you know, sort of planned out by AI. Like where people are going, where people are working and all of this. "So the Technocracy Inc. model that you highlighted earlier, you know it was really influenced by things like Taylorism and a lot of these schools of thought that came out of the Industrial revolution that prioritize efficiency above all else. You know, having the trains run on time and all of that stuff being you know the kind of obsession of of these people in that particular era. "And so they want to sort of apply that not just to industry but to micromanaging people's lives as they you know, extract and exploit us for data and how much money our serf-like lives will make for them."](https://image.24vids.com/tw-2038319939497709608/amplify_video_thumb/2038316420845711360/img/_jjyJy6vXOx4xQkj.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)
!["One of the challenging things about the really important stuff in life is that they’re endless battles. If you do a good job focusing today and prioritizing today, if you pick the right thing to focus on, it earns you no bonus points for tomorrow. Tomorrow you show up, and if you spend all that time on YouTube or getting distracted or whatever, that day is gone. Other things are like that, too. Just because you worked out two weeks ago doesn’t mean you don’t need to do it today. Or just because you were a good spouse yesterday, that earns you no bonus points for today. You still need to show up for them. And so I’m trying to get comfortable with the endless nature of those things. A lot of the time we try to resist the endless nature of that stuff. “Oh, I wish it wasn’t that way.” We try to convince ourselves that it’s like a finish line. “If I just do this 21-day cleanse, then I’ll be a healthy person and I won’t have to think about it anymore. If I just buy her something nice for her anniversary, then I can stop worrying about it and I don’t have to [do other things].” No, it’s not like that. It’s endless. As soon as you accept the endless nature, you start looking at it differently. You say, “Okay, it’s not about getting to a particular finish line; it’s about living a daily life that feels sustainable and that I like and that I’m fully engaged in. So it’s about liking my days." James Clear on The Knowledge Project](https://image.24vids.com/tw-2007485420435845613/amplify_video_thumb/2007484938728144896/img/0lC15kUi7XPd90ew.jpg)
