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JUCO Highlights Mixtape- TE/ath, 6’3” 230 lbs playmaker @ NEO A&M. D1 transfer. 3.7 GPA. AA in hand!! -11.6 YPC -Graded out highest verse two, top ten nationally ranked teams‼️ -Can get open consistently vs. man or zone coverage✅ -Got better every single week💯
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![Did You Know⁉️ One of hip-hop’s most infamous late-’90s beefs—between LL Cool J and Canibus‼️started over a single line on the 1997 posse cut “4, 3, 2, 1” (featuring Method Man, Redman, DMX, and later Master P on the extended version)⁉️. If you dont, I gat you‼️ LL Cool J’s account‼️ LL has said (in interviews including the Joe Budden Podcast, Drink Champs, and others) that Canibus approached him outside the studio and mentioned wanting a tattoo just like the microphone on LL’s arm‼️. At the time, LL was “leading with my ego” and feeling territorial/immature, so he told Canibus to “get your own.”‼️ Then, when LL heard Canibus’s original verse—“Yo L, is that a mic on your arm? Let me borrow that”‼️he took it as a challenge or disrespect tied to that conversation, not a compliment‼️. He told Canibus the line had to go (or he’d be left off the record). Canibus changed it‼️. LL has later reflected that Canibus “really didn’t do nothing wrong,” that it was a compliment/admiration he misread due to his own mindset, and that the beef was more his fault‼️. He kept (or added) responsive lines on the final track that targeted the mic/tattoo reference‼️. Canibus’s account⁉️ Canibus has consistently said the line was pure respect and a term of endearment‼️not a diss‼️. In a recorded conversation with Mos Def, Big Pun, and DMX, he explained that the full original opening (“Yo Method Man, where the gods at? / Yo Redman, where the Squad at? / Yo L, is that a mic on your arm? Let me borrow that”) was him showing love and excitement at being included with veterans‼️. He has described asking about the tattoo idea as a salute (not biting), and stressed he wasn’t stupid enough to diss the host on his own record‼️. When LL called about 48 hours later accusing him of “playing” him, Canibus reportedly replied that he was arrogant and got busy when needed, “but I’m not stupid! I’m not gonna get on another ni**a’s record and [diss him].”‼️ He offered to re-record; LL indicated he’d adjust his own side too‼️. Canibus changed his verse (the released version starts more generally with lines about fighting for mics). He later felt betrayed when the final track dropped with LL’s responsive bars still in place (and Canibus was left out of the main video)‼️. That led him to drop “Second Round K.O.” (with Mike Tyson) in 1998‼️. Both sides agree on the core facts‼️: the original “mic on your arm / let me borrow that” line existed, LL objected and required a rewrite, Canibus complied, and LL’s final verse addressed the reference while Canibus’s did not‼️. The disagreement is intent and follow-through—LL initially heard a challenge (and has since owned his ego/immaturity); Canibus insists it was admiration and felt played when the response stayed in‼️. Redman (who was on the track and mentoring Canibus at the time) has backed Canibus’s view that it wasn’t aimed as disrespect‼️. The leaked original verse, phone call between the two, and later reflections from both have kept the story alive for decades‼️. They eventually appeared to squash it publicly years later, but the “4, 3, 2, 1” incident remains a classic example of how one ambiguous bar + egos + competitive culture can spark a full-blown rap war‼️💯. You're welcome‼️](https://image.24vids.com/tw-2086907247012020520/amplify_video_thumb/2086906160469200896/img/nw5_u_bxoOrQkUoe.jpg)
![🚨What is she carrying? Part 2⁉️ Depending on your AI platform preference … we get either a $40,000 handheld X-ray device or a $40 thermos-and-lunch-bag cooler combo? What was your conclusion, and which was right? When we first came across this video months ago, I immediately said it looked like she was “carrying a lunch bag,” or some kind of cooler. But for whatever reason, and what we were more focused on at the time, we didn’t spend the hours and hours and hours required to drill down on those few seconds of video. Not until this week. Tons of social media critics say I should “just release everything we know, and let the truth fall where it may.” But that’s how we get in trouble. And we HAVE gotten things wrong in this five-year-long investigation. EVERYONE has made mistakes. Left and right media, major legacy media, alternative media, and even the best of the independent journalists have made mistakes or misreported details of the January 6, 2021 event. Whether on purpose, by accident, or careless disregard of the truth … you can be the judge of each incident. I’ve explained on numerous occasions that we’ve spent more than a year researching, investigating, and preparing some stories before going public. In this case, when we finally started looking hard at it, the Brave New World of AI took us on a wild goose chase. We now have good reason to finally drill down on the timelines and available video leading up to the sequence of events on the night of January 5, 2021 … the night before the discovery of the two “devices” at the RNC and DNC headquarters. When inputting into AI that first video — which I posted last night — It began spitting out some shocking alternatives to my original “lunch bag” assumption. Unprompted, the AI drew its own conclusion about what Ms. Kerkhoff was carrying, probably because they were “cops” in the video. To be clear, UNPROMPTED, AI was initially adamant that the item in her hand was a portable X-ray device for sniffing out narcotics, weapons, and explosives. Even some The U.S. Capitol Police sources we shared the video with said the same thing. Other Capitol Police sources were more skeptical. Then, suddenly AI wasn’t so sure. As I mentioned last night, in my second post, X’s Grok and Google’s Gemini were arguing with each other. Gemini was shockingly specific: “The item being carried by the officer in that CCTV footage matches the exact structural form factor, top-handle position, and multi-point shoulder strap design of a Viken Detection HBI-120 Handheld Backscatter X-Ray Imager … Rather than being transported bare, it is housed in its specialized tactical, weather-resistant soft deployment carry case.” Wow. You can imagine how that hit like a bolt of lightning, considering whom we were looking at. Grok was less committed, offering varying possibilities ranging from a “paper takeout bag” to all manner of sophisticated law enforcement-used electronic devices. When I pitted Grok against Gemini — and vice versa — Gemini dug in its heels, saying: “Based on the visual evidence in the video and the analysis circulating in response to Steve Baker's query, the device carried by Officer Kerkhoff is almost certainly a Viken Detection (formerly Heuresis) HBI-120 in its tactical soft-carry case. While officially unconfirmed, the visual and structural match is highly specific.” Grok countered: “The competitor [Gemini] write-up describes that pouch as if it were a catalog item with a unique layout, then maps the CCTV blob onto it and calls it an ‘exact’ match. The citations in that text are HBI-120 product pages, not photos of a factory soft case that looks like this bag. That is overfit. Size class + top handle + ‘looks tactical’ is not an identification of an 8-pound 120 keV imager. Could an agency have put an HBI-120 in some aftermarket or unit-made padded bag? Yes. Does this video prove that? No.” But Grok was also an absolute mess in describing the basic video scene itself: “A gray-haired person in dark clothing walks in from the left carrying a dark bag by a single top handle. Papers or a light object in the other hand. Two uniformed officers come down the ramp. They meet. Later two officers walk the sidewalk; one has a light-colored item (bag or papers), and a dark bag is still in the scene. Someone else walks away across the lot with a bag.” Huh? Anyway… Gemini didn’t like what it called “The Thermos Theory”: “Soft Lunch Coolers typically use flexible nylon webbing straps or soft padded handles that pinch or deform when lifted. The handle in the video does not appear to ‘pinch’ like a soft strap; it remains an open loop. This structural rigidity strongly favors the Viken device (or a hard-shelled case) over a soft lunch bag.” Grok’s conclusion: “On evidence quality, the Viken ID is the weaker of the two. It is possible in the abstract and unsupported as a positive ID here. The honest read is: dark soft top-handle bag, lunch-cooler to small-kit size, contents unknown. Anything more specific needs a better frame, a still of the bag on the ground, or provenance outside this clip.” Gemini’s conclusion: “This single frame is ambiguous due to the blur and lighting (reflection). However, the rigid, non-deforming handle visible in the officer's grip is a mechanical characteristic of the Viken HBI-120 (or similar heavy equipment) and is inconsistent with the flexible straps of a standard soft lunch cooler. While the "silver" glint is a point for the thermos theory, it is plausibly explained by the Viken's glass screen or case window. Verdict: The structural analysis (rigid handle) still favors the heavier equipment (Viken) over a standard soft lunch bag.” So, depending on your AI preference … we get either a $40,000 handheld X-ray device or a $40 thermos-and-lunch-bag cooler combo? But there is more evidence in the alternate video angles available. (That I now present below.) They seem to confirm with the ‘human eye’ that Ms. Kerkhoff is carrying a metal cylinder (possibly a thermos) in the same hand as a soft-sided lunch bag cooler. Though the design conflicts with the common thermos handle configurations of most known cylinder thermoses. (Photos below.) And we've not been able to get an accurate hit on the so-called "lunch bag" with that specific handle and strap configuration. And THAT is why you don’t just “release what you know” without seeking every possible video angle and expert opinion. That is why we didn’t run to print with our original November 8 story on the OG topic without first taking it to a government intelligence agency and professional investigators for review. That is why so many bad theories about January 6 still abound — five and a half years later — because they were based on a single camera angle, when years later, the same scene was revealed to have been captured from multiple angles that change reality 180 degrees. This is exactly why all CCTV footage — not just from January 6, but also January 5 and 7 — still needs to be released to the public. When Speaker Mike Johnson authorized Rep. Barry Loudermilk's old investigative subcommittee to begin uploading CCTV footage to a Congressional Rumble channel, we were elated. I had already spent many weeks in the Capitol CCTV viewing room in D.C. The travel, the expense, and the scheduling hassles with the committee made it nearly impossible to spend the amount of time required to prepare any story correctly. Not only to view and harvest what you were looking for, but also to sift through far more than the infamous “41,000 hours” of footage. Congress made more than 1,800 cameras' worth of footage available, and ten total days of footage. That’s hundreds of thousands of hours of potentially useful footage to review. An impossible task for any one person or media organization to review if Congress didn’t make that footage directly available to the public. But they didn’t finish the project. Tens of thousands of vitally important hours from both January 5 and 6 were never uploaded to the Rumble page. Additionally, my team has made specific requests for curiously missing gaps in footage throughout that two-day timeline. In an arrangement made with the Committee, they had originally been very good about getting us the footage from the specific cameras and timestamps we requested. That suddenly stopped when the new Congress and Loudermilk’s new J6 investigative subcommittee took over in January of 2025. Joe Hanneman and I have made innumerable requests — REPEATEDLY — for missing and/or unreleased cameras and timestamps specifically related to the pipe bomb investigation. Despite being told — REPEATEDLY — that they would provide the requested footage, they never did. Something happened. As I’ve reported several times in the last few months, the Capitol Police were finally and successfully able to shut down Loudermilk’s subcommittee investigation into ALL THINGS related to the Capitol Police. They did this only with the complicity and surrender of Speaker Johnson and Judiciary Chairman Rep. Jim Jordan to Capitol Police leadership’s demands. On that note, and in conclusion … there are eight full hours of missing footage from January 5, right in the middle of the day. ALL CAMERAS are missing. These are important hours for what we are tracking. We can see Ms. Kerkhoff arrive at Capitol Police HQ early in the morning to clock in for her shift, but she is not carrying her “lunch bag and thermos” when she arrives. Her car is parked two blocks away, and is in the same parking spot at the end of her day. We can see her leave HQ late in the day (as I’ve documented in the last several posts on this page) with other officers and go to the Fairchild Building. Only to return some half hour later carrying that … thing(?) … and only to spend 45 seconds in the HQ to “clock out” from her overtime shift. We’re still missing vital video footage that both Speakers McCarthy and Johnson promised the American people. Including certain cameras deliberately withheld at the RNC bomb drop location, and other cameras with mysterious gaps at the most important of moments. Do the other video angles here prove that either Grok or Gemini was right, or does the X hive mind have better theories on what Kerkhoff is carrying? How about that high-definition CCTV camera that is right inside that west side door at Capitol Police HQ, with good lighting? They should release that video to us. A $40,000 bomb detection device or a Walmart thermos and lunch bag? I’m good with either. The truth is what we seek. But we should be able to see ALL the footage. Including all Capitol CCTV cameras and footage from January 6, and the days immediately preceding and following. Including the 39,000 video files the FBI claims to have in the entire J5/J6 pipe bomb investigation. Conspiracy theories are born and fester precisely because the government isn’t transparent and purposefully keeps the People in the dark. Then the lawyers who control government make billions from the legal aftermath. (More Photos in the thread below.)](https://image.24vids.com/tw-2094421342586044718/amplify_video_thumb/2094419261796077568/img/wP9SAk3OAQ58oFvt.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)
!["Where the hell are the [NHIs] in all this? Why aren't they coming out?" ~Semivan "What I experienced, you know, physical marks the whole thing, and my wife, worse." ~Semivan on their abduction "I would be very careful giving these entities that are f**king with you, like, all this great credit and putting them on a pedestal." ~DeLonge to Chris Bledsoe "It's indifferent to man." ~Vallée to Semivan "Are we evil when we go fishing and we hurt fish? Are we considered evil to the fish"? ~DeLonge Jay Stratton's, "got orbs flying around in his house, scaring the hell out of his wife and his kids." ~Semivan ( I enjoyed this episode because a lot of this is where I am when it comes to thinking about the phenomenon. I'm not saying this is the truth but it definitely resonates with me.) ~~~ Jim Semivan: "When we started 'To The Stars,' a while back, we took a little bit of flack because we were talking about...we weren't going along with the idea that the phenomenon was always a great, beneficial thing. We were saying, like, 'Look, let's just wait. There's been instances where it hasn't been...' I always like to use Chris Bledsoe as an example. He's just a dear, dear man, but when you listen to his story, up close and personally, and you could see the absolute fear that he went through, and his family went through, when he first encountered these beings, and this phenomena, and then later on how it transformed him into a very, very deeply spiritual man and healer. So you see this dichotomy. "And if you talk to Chris, Chris will tell you, 'No, this is a beneficial thing.' And then, you know, you run into guys like Keel, and even Jacques Vallée to a certain extent, where they'll tell you, 'Well, no, no, hold on a second.' Because I remember when when I had my experience, I was visited. It was years after my experience, I had met John Alexander at a conference and John put me in touch with some people. And then next thing I know, Jacques Vallée, you know, the guy, right? The house god of TTS calls me up and says, 'Can I come out and see you?' "So he flew out from San Francisco, came to my house in Virginia, and spent the day with my wife and I. And we had some very, very long, involved conversations about this. And I asked him, I said, 'Well, you know, what I experienced, you know, physical marks the whole thing, and my wife worse.' (That may be the first time he's said he had physical marks from his abduction-like experience with his wife when he was in grad school. We don't know details of what his wife experienced.) Semivan: "I said (to Vallée), 'Do you think this is evil?' And he said, 'I don't know, I don't think anybody knows. But I will tell you one thing: What I do know is that you can say that it's basically indifferent. It's indifferent to man. In other words, people get harmed by walking into it or getting caught in it, but it doesn't seem to have an evil intention, per se.'" (Reminds me of what Lue Elizondo said to Curt Jaimungal) Lue: "What if it turns out that a lot of the things that we thought were one way, aren’t. Are we prepared to have that honest question with ourselves? Are we prepared to recognize that we’re not at the top of the food chain, potentially?” (Most humans are indifferent to the welfare of most beings that are below us on the food chain. If we're driving and hit a squirrel, and they get hurt or killed, we may feel bad for a little bit, but we get on with our business and enjoy the rest of our day. How many cows, chickens and pigs are killed every day so we can eat them? Most humans, including me, don't give that a second thought. Indifference. That indifference may be happening with an intelligence (or multiple intelligences) that's above us on the food chain. And I'm not saying they're eating us, although that can't be ruled out 100%. I'm saying "they" just do their thing and if we get hurt or killed, it's not a huge deal to them. Indifference. And maybe some of them enjoy messing with us?) Semivan: "But then when you read Keel and you know, you read the Mothman and and a lot of these other stories like 'The Mojave Incident.' Well, holy cow! You look at this stuff. And, you know, you get these hobgoblins flying around, you know, with Jay Stratton. He's got orbs flying around in his house, scaring the hell out of his wife and his kids. I don't see, I don't know where there's any kind of a spiritual turn to that where you could look at all that and all of a sudden you say, 'Oh, now I'm a better person.'" (Most of us have known that Axelrod in "Skinwalkers at the Pentagon" is Jay Stratton but that's the first time one of his colleagues/friends has said it. And I agree: What's the purpose of orbs scaring, and leaving marks on, his kids? And the wolf that his wife, kids and their friends say they saw? Why? To make them better people? It makes zero sense to me.) Semivan: "It happened with Chris (Bledsoe) and, you know, great for him. Sure, as hell didn't happen to me. And I don't think it happened to Jay Stratton, either. I think it gave Jay a different outlook as with me, but sh*t, I mean, nothing I couldn't have got from reading books. What do you think?" Tom DeLonge: "I think like, yeah, you know, the idea of what we might call something evil, but to that, it's like, you know, are we evil when we go fishing and we hurt fish? You know, are we considered evil to the fish? So it's things looking out for its own interest." (100%. Someone asked me about good vs. evil last night and I wrote back, "Not about good vs. evil. About survival and food chain. Somber.") DeLonge: "The thing that I look at, you know, a lot of the ideas of good and evil come from like, religion, all different types of religions where it really defines the metaphysical nature of who we are and what we're living in. But I look at religion... I cannot think of one religion that hasn't left a wake of destruction. I mean, literally, every single one has done so much harm. And the one pattern in all these religions is that most of them, outside of the pagan ones, have really tried to just to get us to believe that the creator of the universe is some kind of human, or something. It's not like a source, an energy, it's like, it's a Jesus or an Allah, or it's a Buddha, or I don't know. Buddhism doesn't really say that, but you know what my point is. It's trying to humanize something. "And so, to me, it's like when Chris Bledsoe, or some of these others that have these kinds of spiritual experiences, these are the exact same experiences that are written about throughout the entire Bible, in the Quran, and like, all these other texts. And all of them are really setting the stage for us to worship the UFO and their occupants, to some degree." (You see this a lot with the folks who think we're dealing with ETs here to uplift humanity. The Space Brothers theory. I don't know the truth but, to me, it doesn't seem like that's the answer.) DeLonge: "And that, to me, is the one strong pattern, is to confuse us and not let us know of our own spiritual nature to source consciousness." (I've said many times that I believe a lot of this is about human potential and our untapped capabilities in the psi (psychic, pk, consciousness, etc.) area) DeLonge: "And as long as we don't know that, then we will think that, 'Okay, the aliens like, f**ked with our DNA and made us like this,' or 'The Tall Whites showed up and they were the Greek gods, too, and they gave us philosophy and all this whatever.' It's like we're always like, giving some kind of humanized form credit for everything. "And the one thing that's common in all these religions is that it's not giving credit to source energy that allows us to heal, that allows us to be telepathic, that allows us to have telekinesis, that allows us to have, like, compassion in energy to healing. Like, whether you do Reiki and meditate, or whether you sit and pray, it doesn't matter. Why does it work in every religion? Because it's source energy, it's not about the religion." (The one thing I could never get behind is healing because there was no data to back it up. That was until I was shown the work of Bill Bengston. Tons of data. How does it work? I don't know. Nobody does.) DeLonge: "But if you look at who's responsible for all the religions? Well, it's whatever UFO the Star of Bethlehem was, or whatever UFO the Fatima thing was, or whatever the Tall White was that met with Joseph Smith and started the Mormon religion was. Whatever the Jinn are that are in the Koran, or whatever the Demons are there in the Old Testament, they seem to be the things that come in, that take you in your sleep, and make you think things and deceive you. It's all the same." (Deception, deception, deception. A lot of this is very similar to what David Icke (and others) has written about.) DeLonge: "So you have all these things f**king with you, as the good ones and the bad ones. But all the religions, the pattern is, is never ever, ever let humans know the physics of their existence. Which is meditate, you can heal somebody and have all your information you need, or pray. It's the same thing, it doesn't matter. "That's more like my line of thinking is, is why it's so important for us to understand the true nature of spirituality, and why I step back when I hear the Chris Bledsoe stories. And it's wonderful that he's gotten to a place that it's helping him, because I really do like him as a person, and I really respect and honor his experiences because I firsthand have heard them from him. And he's just a wonderful human. I mean, it was an incredible story. But I told him personally, I said, I would be very careful giving these entities that are f**king with you, like, all this great credit and putting them on a pedestal, because these are the same groups that have been doing a lot of weird s*it throughout time, good and bad.' (Again, I think Bledsoe has had real experiences but IMO, his interpretation of what he's dealing with is off.) DeLonge: "And that, to me, seems, you know, that seems suspect. You know, it seems like if there is any really, true, beautiful, great force, and entities representing that force, like your angels in the Bible. I mean, even in the Bible, people would, you know, when they saw an angel, they would collapse on the ground in extreme fear, and like, they couldn't even look at them. It was like the scariest thing that's ever happened. And that doesn't sound like a real loving interaction to me (laughs). That sounds like some scary shit, you know? "So I think whatever would represent true love and unparalleled love, that doesn't seem to be showing up and f**king with our society and our timelines, and our behaviors, and trying to manage us. It's letting us do it on our own, you know, like, figure it out on your own, you know? But everything else that's showing up, seems to have its own interest at heart." (I think TD is saying that a loving/caring intelligence wouldn't try to manipulate us into doing things that just benefit THEM. And that's what appears to be going on. "They" only care about themselves. If there were ones here who truly cared about us, they would leave us alone and let us figure it on our own.) Semivan: "I tend to agree with you on this. I did a podcast a while back and somebody related to this. They were talking about why there hasn't been Disclosure? And I said, 'Well, you know, there's two sides of this story.' I said, 'You have the non human-intelligences, you know, or the phenomenon, and then you have the governments.' And I said 'Well, where the hell are the non-human intelligences in all this? Why aren't they coming out? They pretty sneakily running around, and they meet people in weird, obscured circumstances, make their experiences sound crazy. Yet, they sort of wanna be known, but they don't wanna be known.' As I mentioned to somebody once, 'They'll screw around with you but you can't take them home to meet your parents. They're not landing on the White House lawn for a reason.' I'm not quite sure what that is."](https://image.24vids.com/tw-1773078284487798811/ext_tw_video_thumb/1773040319740948480/pu/img/LNfQpFjqV8ZVbffs.jpg)