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BREAKING: Documents Confirm RFK JR Right About Race Specific History of Covid-19 Jul 16, 2023 Alex Jones Show RFK JR is right about race specific bioweapons. Alex Jones goes over documents explaining how Covid-19 targets specific ethnicities. #newswars #infowars #alexjones #RFKJr #TuckerCarlson #covidwars #COVIDVACCINE #freedomofspeech #alexjoneswasright #bioweapons #lableak #DiedSuddenly... show more
23,255 просмотров • 3 лет назад •via X (Twitter)
Комментарии: 6
the messenger3 лет назад
The blue pilled would rather live in blissful ignorance and keep on trusting the eugenicist elite marketing over the evidence coming out. They parrot "follow the science!" and then later to shun it, when the big lies disagree with the experiment results. Lambs to the slaughter!
the messenger3 лет назад
"Why can't people learn to look this up themselves!"🎯
JRA3 лет назад
RFK still ultra liberal on many many issues , running Indy his only hope , just to screw the Big Guy 👏👏😂😂🤠🤠
Vanzemljak 👽🇷🇸3 лет назад
IMPORTANT 👇‼️‼️‼️‼️
John Connor3 лет назад
Meanwhile, Trump said Zelenskyy is honorable
iLostmysharpie3 лет назад
It’s called the fundamentalist vaccine. Old news new name.
![Whitney Webb warned us about what would happen with RFK Jr. at HHS—she is 100% vindicated: "You have to wonder why Trump decided to appoint RFK Jr. as head of HHS and... [Peter Thiel puppet] Jim O' Neill as the Deputy HHS Secretary...[that] conflict [is] rather [jarring]... the fact that O' Neill in his position, if confirmed, would be managing the day-to-day operations of HHS, including what the FDA does, what the CDC does, and things of that nature, he could easily undermine any sort of MAHA policy that RFK tries to impose." This clip of Webb (Whitney Webb) is taken from a January 31, 2025 interview with Clayton Morris (Clayton Morris) posted to the Redacted (Redacted) YouTube channel. For reference, Jim O'Neill, a puppet boy of technocrat goblin Peter Thiel, served as managing director of Mithril Capital Management from 2012 through 2019. Mithril was co-founded by Thiel. O'Neill was also the CEO of Peter Thiel's Thiel Foundation from 2009 through 2012. Furthermore, O'Neill co-founded the Thiel Fellowship in 2010. ---------------Partial transcription of clip--------------- "Well, you have to wonder why Trump decided to appoint RFK Jr. As head of HHS and then appoint Jim O' Neill as the Deputy HHS Secretary. Because, yes, it absolutely does seem to conflict rather jarringly. And the fact that O' Neill in his position, if confirmed, would be managing the day-to-day operations of HHS, including what the FDA does, what the CDC does and things of that nature, he could easily undermine any sort of MAHA policy that RFK tries to impose. "And also the Chief of staff that was appointed to essentially manage, you know, RF RFK's portfolio, who's going to be the chief of staff, for him is a woman named Heather Flick, who was previously played a major role in HHS under Trump's previous HHS Secretary, Alex Azar, who is a former head of Eli Lilly, a major pharmaceutical company, and has sort of been blamed for some of the big pharma patronage that happened in the, you know, early COVID-19 era, before the Biden administration came in. And you know, she's essentially been framed as someone that will keep, you know, basically babysit RFK Jr. At least that's sort of how the Wall Street Journal recently framed it. And what exactly does that mean when you combine her appointment with someone like, you know, Jim O'Neill being deputy? "And so essentially what I think people should look at again is even if RFK is confirmed, there needs to be a focus and pressure placed on these other people. And that's especially true of someone like Jim O'Neill who also has to go through, confirmation. So anyone that is, you know, vocally supporting, you know, RFK Jr. With the hopes that he'll fulfill part of this broader Make America Healthy Again agenda should also consider opposing the confirmation of Jim O'Neill. And also opposing this, you know, this type of deregulatory paradigm that he wants to impose. "Because, of course, Jim O'Neill frames it is free market innovation. But it would just be a field day for crony capitalism at the end of the day. And also, I forgot to add, one of the other, some of the figures that have inspired that he's cited as inspiring his views on eliminate eliminating efficacy testing. Say that the efficacy data should be tested on patients after these drugs are administered to them, through biosurveillance, including through digital wearables. And that big pharmaceutical companies, the producers of those products should be given access to the data so that they can jack up the price, you know, depending on how quote, unquote effective, the drug is based on this, this data. "And it's also a way to surveil, you know, what's going on inside people's bodies, which is eerily reminiscent of things said by people like Yuval Noah Harari, you know, who's, you know, affiliated with the World Economic Forum, talking about the utility, how the next frontier of mass surveillance is to surveil what's going on inside people's bodies. And it's quite disturbing that Palantir has now taken over major functions of HHS, including at the CDC, and other aspects, of, of agency functions. And because of O'Neill's deep ties to both Palantir and Peter Thiel, it's likely that he'll push for a deepening of those ties. "And Palantir is really the engine that the mass surveillance state runs on. It's a contractor, contractor to every single US intelligence agency, all 18 of them, as well as HHS, and it's currently operating programs within HHS that are trying to use Americans healthcare data to try and predict when people will get sick before they show symptoms. And one of their programs with the CDC has the potential to push for the declaration of a next pandemic before anyone shows symptoms."](https://image.24vids.com/tw-1990323050387231164/amplify_video_thumb/1990319805665292288/img/39ULIl3PI2DGzFxH.jpg)
![HOLEE SHIZZLES‼️ 🚨 RFK JR Sounds the Alarm on the WHO IHR Amendment's — A “Trojan Horse” is Quietly being Installed to implement Digital Health ID's and a Global Health Database • he expresses concerns about the proposed amendments to the International Health Regulations (IHR) and their potential to "open the door" to "that kind of system of health IDs," suggesting a pathway to broader surveillance and control mechanisms. • He says the WHO is laying the groundwork for a CENTRALIZED Medical Database for every human being • He connects the potential for digital health IDs to broader issues of surveillance and industry influence. He Mentions Mass "surveillance" and he refers to "industry influence," implying that these IDs could be part of a larger mass surveillance framework that benefits certain industries while encroaching on individual privacy and freedoms. • Kennedy's concerns are framed within the context of the COVID-19 pandemic, where he believes critical information and criticisms were suppressed. He suggests that the amendments could perpetuate similar dynamics, potentially using digital health IDs as a tool for narrative management and censorship, as seen during the pandemic. - His overall stance is that such measures, including digital health IDs, could jeopardize civil liberties and national sovereignty. He argues that the U.S. should not sign over authority that could lead to lockdowns and other public health measures without thorough consideration, especially when these measures might invite a system that undermines individual rights. What’s next? - Proposal and Adoption Process: The amendments were proposed and negotiated through the World Health Organization (WHO) processes, in an agreement by the World Health Assembly in May 2024 [World Health Assembly, 2024]. However, the implementation of these amendments is not automatic and requires further steps. - Opt-Out Period: There is a specific window for member states to opt out of these amendments. The U.S. and other countries have until NEXT WEEK, to formally reject the amendments. This opt-out period is crucial because it allows countries to decide whether to be bound by the new regulations.](https://image.24vids.com/tw-1946218711741792452/amplify_video_thumb/1946218544808476672/img/0S_qJrbIPu-Q-Ec-.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)
![United States government officials have for decades reassured the public that they are releasing all they have, save for the most sensitive information, on the origin of Covid, the CIA mind control program known as MKUltra, the JFK assassination, and the Church Committee investigation into the intelligence community (IC) abuses in 1975. In 2023, then-Director of National Intelligence (DNI) Avril Haines delivered a five-page summary of Covid origins in response to a unanimously passed law requiring the declassification of files. MKUltra involved drugging individuals without their knowledge in an effort to control their thoughts and behaviors. The CIA stated in 2022 that it had released 95% of its JFK collection, and the Trump administration released roughly 80,000 pages of JFK records on March 18, 2025. But an active-duty CIA official testified to the Senate Homeland Security and Governmental Affairs Committee today that the CIA and the Intelligence Community (IC) are still hiding information. James Erdman III, a senior CIA operations officer who led the Director’s Initiatives Group investigation into Covid origins under DNI Tulsi Gabbard, appeared under subpoena from committee Chairman Rand Paul. Erdman told senators that the CIA “did not comply with lawful oversight” during his investigation, and said, “CIA managers retaliated against [analysts] for their refusal to agree with management’s middle-of-the-night anonymous review.” Erdman testifie,d “The CIA illegally monitored the computer and phone usage of DIG [Director’s Initiative Group] personnel, their investigations, and contact with whistleblowers…One CIA contractor assisting with the DIG’s investigation into the events that transpired between 2022 and 2023 was fired by the CIA one day after meeting with the DIG.” Erdman said the CIA had not cleared his testimony or written statement before the hearing. The CIA denounced the hearing as “dishonest political theater,” and not a single Democratic Senator showed up for it. A CIA spokesperson, Liz Lyons, said in a statement that “the Committee acted in bad faith by subpoenaing an Agency officer for testimony today without notifying CIA.” She added that “the witness testifying today is not appearing as a whistleblower in pursuit of the truth, but instead in response to the subpoena issued by Chairman Paul.” And she implied the hearing was not needed since “the CIA has already assessed Covid-19 most likely originated from a lab leak, and efforts to undermine that conclusion are disingenuous.” But the public CIA statement quoted at the hearing did not address Erdman’s specific claims about DIG monitoring, the contractor firing, or the 40 boxes of JFK and MKUltra files. Sen. Paul, who noted that “closed-door testimony doesn’t provide oversight” and “public testimony provides oversight.” The CIA made public in January 2025 a low-confidence assessment that COVID-19 likely had a research-related origin, while saying both lab and natural-origin scenarios remained plausible, which Paul called “a cleanup operation.” Nor did she address Erdman’s claim that, “When the DIG ceased operations, the CIA also took back 40 boxes of JFK files and MKUltra files being processed for declassification by DNI.” Public reached out to the CIA for comment on Erdman’s specific allegations and will update this article if it replies. Support for Erdman’s claims came from former CBS News investigative reporter Catherine Herridge. “As early as February,” she wrote on X, “I began receiving credible reporting that DNI Tulsi Gabbard’s investigative team was being tracked and communications collected because their work was revealing ‘uncomfortable facts.’” Paul opened the hearing by describing the Biological Sciences Experts Group (BESG), an ODNI advisory body that he said included Dr. Ralph Baric and Dr. Peter Daszak, both of whom collaborated with Wuhan Institute of Virology researchers on coronavirus gain-of-function studies. Daszak, Paul noted, received “hundreds of millions of dollars from the US government and worked with Dr. Zhengli Shi in Wuhan to create gain-of-function coronaviruses,” and that Baric “was also part of BSEG and an active consultant to intelligence agencies on the origins of the COVID-19 pandemic.” Paul noted that “Dozens of times, [former NIAID Director Anthony Fauci] referred to the idea that the pandemic originating in the lab was a conspiracy theory.” Erdman said that as of August 12, 2021, the CIA was considering calling Covid a lab leak, but that the conclusion “changed on August 17th of 2021.” Erdman told the panel that “the CIA would not provide us documentation that we asked for” and “we have no idea why that changed.” Erdman also testified that “Director Gabbard is working through, I believe, 2,000 pages” of Covid origins records the CIA had been resisting releasing. That figure contrasts with the five-page summary the ODNI delivered to Congress in 2023. Senator Josh Hawley asked Erdman whether the five-page report was “all the information the United States government had,” and Erdman replied, “that is not all the information.” Erdman described a 2022 CIA “re-look” in which eight of 10 analysts and six of seven technical experts leaned toward a lab leak. He said management overruled the team and changed the analytic line to read that “we may never precisely know the origin of SARS-CoV-2.” Paul noted that there have been over 1,500 major lab leaks. Sen. Paul revealed that the CIA is still denying him information that Senators are entitled to see under the Constitution, which requires Congressional oversight of the executive branch. Paul said the CIA had resisted releasing to him the underlying Covid origins analyses by its own scientists, even in classified form. Paul also said, “I’ve been trying to get the classified version of the [1975] Church Committee [files] for over two years,” he said, “but I’m being blocked by the [Intelligence] Committee, including someone from our own party who is blocking me. They’ve shown me a room with 400 boxes. I can go look in all the boxes to see if I can find it. My staff’s not allowed to go in the room.” The CIA told Senate investigators in 1977 that, after the Church inquiry, it had discovered seven additional boxes of MKUltra files in its retired records center that prior searches had missed. The 1977 hearing identified 149 MKUltra subprojects involving human testing and 33 additional subprojects whose subject matter remained undisclosed. Reuters reported that in early April 2025, an ODNI team led by Defense Intelligence Agency official Paul Allen McDonald II arrived unannounced at a CIA archival facility in the Washington area to seize Kennedy assassination files. The team included Amaryllis Fox Kennedy, a former CIA officer and daughter-in-law of HHS Secretary Robert F. Kennedy Jr. The standoff stretched into the early morning hours and ended only after the CIA agreed to transfer a “massive trove” of documents to the National Archives for digitization. Why did these cover-ups occur and why are some of them still ongoing? And why didn’t any Democratic senators participate in the hearing?... Please subscribe now to support Public's award-winning investigative journalism, read the rest of the article, and watch the full video!](https://image.24vids.com/tw-2054703854185586887/amplify_video_thumb/2054702727482216448/img/N5qZ6a7WLzTYWSBi.jpg)