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🚀 Fully offline AI TALKING AVATAR IS HERE! 💻 Stack: • Arcee.ai Virtuoso-Lite (with ollama ) • Kokoro-80M (TTS) • Whisper.cpp (ASR) 🎭 Streaming to Unreal Engine Metahuman via Audio2Face 🔥 Running smooth on RTX 4090 Laptop (12GB/16GB) (Excuse the jet engine fans 😅)
44,342 Aufrufe • vor 1 Jahr •via X (Twitter)
12 Kommentare
@arcee_ai @ollama @UnrealEngine bruh
@arcee_ai @ollama @UnrealEngine what do you think🙏
The Art of Flight is a homage to 80s/90s arcade action shmups with a fresh twist on the genre. Pilot multiple ships at the same time to take on oncoming waves of enemies in this fast paced space shooter. Wishlist on Steam today!
@arcee_ai @ollama @UnrealEngine this is aaaaaawesome! I am working on my own AI voicebot without the avatar though:
@arcee_ai @ollama @UnrealEngine are you gonna open-source this?
@arcee_ai @ollama @UnrealEngine yes!
@arcee_ai @ollama @UnrealEngine This is excellent! What kokoro blend are you using, or just the default?
@arcee_ai @ollama @UnrealEngine thank you! i am using everything default here
@arcee_ai @ollama @UnrealEngine 🔥
@arcee_ai @ollama @UnrealEngine opensourced?
@arcee_ai @ollama @UnrealEngine WOW, oh WOW! Great job!
@arcee_ai @ollama @UnrealEngine thank you🤗
![If you are running local LLMs without N-gram speculative decoding, you are wasting massive amounts of compute. Whether your AI is editing a document, outputting structured JSON, or rewriting boilerplate templates, a huge chunk of the text it generates is highly repetitive or already exists right there in the prompt. Standard decoding wastes expensive GPU compute cycles "re thinking" every single token. By adding one hidden flag in llama.cpp, you can instantly fast forward through the repetition. Zero draft models. Zero extra VRAM. And virtually zero compute overhead. Google Colab hands you an enterprise grade NVIDIA Tesla T4 GPU with 16GB of VRAM for free. It’s the perfect Ubuntu Linux sandbox to build a bleeding edge inference engine from scratch. Recently, I showed you how to double your local speeds using MTP (Multi Token Prediction). But MTP requires a secondary neural network draft model. That eats into your precious VRAM (slightly though) and burns extra compute for every guess it makes. N-gram Speculative Decoding gives you a massive speed boost for exactly 0 memory cost and minimal compute. And it's faster than MTP when it works. Here is how it actually works under the hood: Standard autoregressive decoding is slow because it predicts one token at a time. If you ask an agent to format a long JSON object or update one line in an HTML file, it runs heavy matrix multiplications to calculate the probability of every single bracket, space, and letter from scratch. N-gram changes the game. It acts as a lightweight caching system. Instead of running heavy neural network math to guess the next word, it uses a simple hash table. Whenever the LLM starts outputting a sequence of tokens that already exists anywhere in its context window, N-gram instantly recognizes the pattern. Because it is just doing lightning fast string matching, the compute cost is practically zero. It "fast forwards" through the text, drafting the boilerplate instantly from memory, and the main model just verifies it in parallel. Pure speed. Using quantized GGUFs from Unsloth via HuggingFace, I spun up DeepMind’s massive Gemma 4 26B A4B QAT MoE on a free Colab instance to test this. Just look at the raw benchmark data on code editing task: Without N-gram: [ Prompt: 638.6 t/s | Generation: 45.9 t/s ] With N-gram: [ Prompt: 601.9 t/s | Generation: 107.1 t/s ] Here is the exact llama.cpp CLI command to activate it. Notice we don't even need the --model-draft flag: ./llama-cli -m gemma-4-26B-A4B-it-qat-UD-Q4_K_XL.gguf -cnv -n 6000 -c 12000 -ngl 99 -fa on --spec-type ngram-mod Stop waiting for your GPU to re calculate words it already knows. I’ve built a free, interactive, cell by cell Google Colab notebook that lets you test this live in your browser. You can literally chat with the model and watch the text generation speed absolutely fly on the second turn when you ask it to edit a file. There are additional parameters for ngram-mod that you can tune once you get it working with the single flag. Link to the free Colab Notebook is in the comments below. It walks you through the entire stack: pulling pre built llama.cpp CUDA binaries for Linux, fetching GGUFs from HuggingFace, and spinning up the inference engine with ngram-mod from scratch. Let me know if you have already tried ngram-mod](https://image.24vids.com/tw-2077476686678151422/amplify_video_thumb/2077475852384960512/img/mC5h-t6vqd9H1r2j.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)
![💥 LAP Alert 💥 "I did this sort of spy thing where I changed hotel rooms and I changed taxis. I was making sure I wasn’t followed." ~Knapp Is Lacatski Lying to Us About the Craft and Breaching the Hull? ~ "If not for that [2017 NYT] story about AATIP and the problems that [Lacatski] saw with it, he would never have mentioned [AAWSAP]...I don't think, ever." ~Knapp (So, in other words...thank you from the UFO community, to the NYT, for getting it wrong? 🙂) ~ Jeremy Kenyon Lockyer Corbell: "Should we listen to Dr. James Lacatski on UFOs, on the fact, or the idea, that our government has at least one, he's admitted, and we breached the hull? Should we listen to him, George?" George Knapp: "I know a lot of people have noticed that he's talked about his role in counterintelligence as part of the AAWSAP program. And because they equate counterintelligence with lies, false info., cover stories, misdirection. Aha! He's putting out a bunch of false info. a decade after he retired from government service." (I saw one person suggest that, and I thought it was a questionable take...) Grant Lavac: "Given that Dr. James Lacatski was the 'counterintelligence coordinator' for AAWSAP, how much confidence can we invest in the veracity of his public statements that 'at least one recovered craft of unknown origin, a flying machine with no wings, no engine, no fuel, and no fuel tanks' is in the possession of the US government and that they had 'breached the hull' of the UFO? In the context of the counterintelligence value of UAP/UFO, his comments in this most recent interview on WEAPONIZED (edited for brevity) only raise more questions for me." ~~~ Knapp: "A, it's not [Lacatski]. He's not out there beating the bushes. He's talked to us, but that's pretty much it. He's telling the full story as much as he can in a series of books. And I was co-author on two of those, not on this one. And, you know, I remember the first time I met him, it was in 2018." ~ (In April of 2019, Knapp shared that story, minus Lacatski's name, at UFO MegaCon. Knapp in 2019: "I thought today I would share with you, sort of the informational foundation that I’ve acquired. So, one year ago, I made this trip to Washington, D.C. at the invitation of Senator Harry Reid. It was St. Patrick’s Day, 2018 and I already knew a little bit about AATIP and AAWSAP and what they’ve been studying and where the money came from and how the program was created. I did this sort of spy thing where I changed hotel rooms and I changed taxis. I was making sure I wasn’t followed. And if there was ever actually, anybody following me, they must have thought I looked ridiculous because it was way over the top. "But I ended up having to meet with Senator Reid and some other people who were directly involved in these programs and they gave me a download. And I thought I knew a lot about these programs when I went there and realized that I only knew a little tiny bit. The purpose of this was to learn about these programs. We all know about AATIP, but in reality, there was something before that. "I sat down for a couple of hours with Senator Reid and other people whose names, they don’t want to be known. They brought me up to speed on how AATIP was created. How its predecessor was under way for a number of years. It coexisted for a long time. People in this room. People who investigate this topic may have suspected for a long time that there was some kind of a program that still existed. We’ve all heard that Project Bluebook was the end. 1969 it ended and the government was done with UFOs. They closed up shop. And the reason they closed it down is because there was no evidence that it involved national security. "And we all knew that was baloney because of the stories that we’ve seen that are really well documented. For example, UFOs over nuclear missile bases. UFO encounters with the military installations and atomic facilities. Things of that sort the have been well documented over the years. There are cases that involved national security. So at the end of Blue Book, of course, this memo said, alright, any cases involving national security will continue to be investigated in the regular way. Well, what the heck was the regular way? We didn’t know. Well now we do know. At least a little bit of it." (Project Blue Book was shut down in December of 1969, but a few months earlier, in October, we had the Bolender memo, which noted that "reports of UFOs which could affect national security should continue to be handled through the standard Air Force procedure designed for this purpose." What standard Air Force procedure? The regular way? Where did those cases go? We still don't know what Bolender was referring to in that memo.) ~ Knapp in 2019: "And one of the regular ways was this program called AATIP. So I went on this trip. [and] I learned this stuff about AATIP. I had known a lot about it before but I got this briefing about this alphabet soup of different programs, how they began and what they studied. December 2017, the New York Times breaks this story about AATIP. Now, I had known about it for a long time because I lived in Las Vegas. I knew Bob Bigelow. I knew Harry Reid. We’d talk about UFO stuff and what was going on. "So when I was told the New York Times was gonna break the story, I’m kind ticked off about it. Because hey, I’ve been sitting on this for a long time. Why don’t I get to break the story? And they had to, one after another, gently remind me, 'You know. You’re not the New York Times.' Which I had to admit! It was true. And if I had done the story, the Times had said that they weren’t going to do it if somebody else breaks it. So, if I had done it, it’d be another story from a UFO reporter. "The New York Times did it and they changed everything. Because they did it, wider organizations did it. Some of them took shots at the New York Times because The Times got the story and they didn’t. But that story was accurate, to a degree. But the story that it told was not the full story. AATIP, that we know about…the AATIP that studies nuts and bolts saucers…case of UFOs that have encounters with military units such as the USS Nimitz, that is studied by a group of people, Lue Elizondo was the head of it. "It’s not so much a program as it was a loose network of intelligence officials in different agencies, including the Air Force and the Navy, CIA, DIA, DARPA…there might be a couple of other agencies. But a case would come in from any one of their units [and] it would be shared with this group of people, analysis would be done, evidence would be looked at and then stashed in a draw and nobody ever sees it. It’s not passed up the chain of command. "In 2007, that changed. One of the guys (Lacatski. ~Joe 2025) I met with in this meeting in Washington is the one who changed it. He had been in the same position that Lue Elizondo had been in. And his name is just not out there. He grew frustrated with what was happening with the phenomenon and he suspected that UFOs flying around the sky, buzzing our military units every once in a while, is not the full story. Even if you could solve that part of the mystery it wouldn’t solve the bigger part of the picture. "So he grew interested in Skinwalker Ranch and he had read the (Knapp/Kelleher – 'Hunt For The Skinwalker') book. And after he read it, he called up Bob Bigelow and said…actually, he wrote him a letter and said, 'Hey, can I go to the ranch…go look around? I’m with the DIA.' Bigelow says, 'Come on out to Las Vegas and I’ll take you there.' And that’s what happened. He flew to Las Vegas. They flew on Bigelow’s jet. They went to the ranch. "This guy’s not there fifteen minutes and he has an experience. And I’m not gonna go into detail. I’m hoping that he’s going to maybe come forward at some point and describe his experience. But it was just for him. Of all the people in this room, in the encounter, he was the only one who could see it. He’s the only one who had an angle on this thing that appeared. And he’s pretending that he’s not seeing it but it’s right out of the corner of his eye. And he doesn’t say anything until he leaves the ranch. And he gets off and he asks Bigelow if he had seen it. And he had not. The other people who had been in the room had not seen it. "He flies back to Las Vegas, goes back to Washington, D.C. and looks up Harry Reid and tells him about it. Now Reid had some experience in these matters that I’ll get into in a little bit. But as a result of that conversation, Reid, who had an interest in UFOs and had maintained that interest over many years – and I can attest to that personally – called in a couple of his friends in the Senate – Daniel Inouye and Ted Stevens. They had a conversation in a secure room and they decided to provide some funding for a much broader study. Something that looked at…beyond flying saucers, that looked at other paranormal aspects…supernatural aspects that we would not normally associate with aliens or ETs. Assuming that that’s what this is, which I’m not sure anyone knows for sure. And that is how AAWSAP was born. The Advanced Aerospace Weapon System Applications Program." ~~~ Knapp Yesterday: "The only reason [Lacatski] came forward, he was ticked off about how AATIP had been described in major media reports, and no mention had been given to the actual, real program. That one that had a $22 million budget, lasted 27 months, and which put together the biggest UFO data warehouse in history, that had written all these papers that still have not been released." (In the most-recent interview (Part 1) with Weaponized, Lacatski let it fly with his issues related to the 2017 NYT article: "The initial reporting...by the New York Times story in 2017 was totally inaccurate. Contrary to what some people claim, the authors knew my name and position at AAWSAP, yet never attempted to contact me. Likewise, the The Washington Post. POLITICO (laughs) contacted me within hours after the articles were published in the free publications, asking for my opinion. They knew my name, they had my phone number. Why didn't they contact me [beforehand]?" ~Dr. James Lacatski on Weaponized ~ Knapp: "So, Jim was a counterintelligence guy for AAWSAP, but in this role. He wasn't putting out cover stories or lies, he didn't put out anything. The world didn't hear that AAWSAP existed until years later, at least by that name. There was one statement made to the press about that program. It was by Robert Bigelow, whose company, BAASS, got the contract. A week after he signed it, he came on with me on Coast to Coast AM and said, 'We got this program dealing with UFOs, we have an unnamed partner, and we're excited to get going.' That was it. "Jim Lacatski wasn't putting out PR releases about AAWSAP. There was nothing. That was the last thing anybody said until the New York Times did the AATIP story, and then Jim Lacatski felt the real story was being covered up. If not for that story about AATIP and the problems that he saw with it, he would never have mentioned this. I don't think ever." (Well, then, thank you to the NYT journalists and editors for pissing off Lacatski!) Knapp: "You'll recall, AAWSAP, at the time that things went downhill, that the funding was moved away, they were trying to make it into a SAP, a Special Access Program. And if it had happened, we probably would never have heard of it. If it had happened, Lue Elizondo would have been the counterintelligence guy for AAWSAP, that he had already talked to Lacatski. "But Lacatski is not proclaiming the greatness of the program. He's not out there beating the bushes on podcasts and newscasts, other than with us, and he never put out in counterintelligence. His role, counterintelligence, meant something different for AAWSAP. The thing that DIA had told him was, 'Look, you know, it's not a rogue program. I know it gets weird into some of the phenomena that was at Skinwalker Ranch and other places. We don't care. Here's what we care about: Don't let the secret out. We don't want to see this on the front page of the Washington Post. We want it kept secret.' (John Greenewald was one person questioning whether AAWSAP was actually a prosaic program and Lacatski just decided to go rogue with a foray into UFOs and the paranormal.) Greenewald Tweet: "Did the U.S. government really sanction this, and if so, is this really how it was run? Or was this a rogue operation by a select few on the inside playing with Uncle Sam's coffers?" (Greenewald was quote tweeting a Greenstreet hit-piece video on AAWSAP. In his interview on Weaponized aired over the past few weeks, Lacatski said that former Deputy Director of AARO, Tim Phillips, also used the "rogue" word when describing AAWSAP. Did DIA really not know what AAWSAP was about? Did Lacatski go rogue and turn a program that was supposed to look at prosaic, advanced technology into one that studied UFOs and the paranormal? Here's an exchange from the 2023 interview Knapp and Corbell did with Lacatski and Colm Kelleher.) Kelleher: "The critical part of AAWSAP that we tried to convey in 'Skinwalkers at the Pentagon,' was that there were two fundamental, parallel tracks that AAWSAP ran on. The first one was the examination of UFO performance. And, you know, the UFO performance part was getting all of the data from eyewitnesses, plus deploying sensors into the field, in order to gather data on the performance of UFOs. That was track number one. And track number two was: What effects do UFOs have on humans? That was a parallel track that, from the get go, AAWSAP decided, unambiguously, to run both tracks in parallel. We documented psychological effects, and then we also documented paranormal effects." Lacatski: "Anything can be said on the internet it seems, factual or not. Well, one thing that is not factual is, DIA knew what it was getting into in regard to both aspects that Colm just described to you. And let me end my statement right here. We had no choice but to pursue both aspects." (That was a poor way of him saying: The claim that DIA was unaware of AAWSAP looking into all aspects of UFOs, including the paranormal, is NOT true.) Lacatski: "I want to emphasize something I said on my first and only interview. It was a closed program. It operated very similar to a SAP. The director, the director of analysis, and my office chief...and, of course, division chief, knew about this program. No one else did. Now, I was also protected by the stovepipe nature of that. I did not have to address political-type questions. I was insulated, but they were, too. There was no one else. People in the surrounding cubicles didn't know. Nothing was purposely being hid. It was a closed, stovepipe system, and it needed to be. It needed to be operated that way." ~~~ Knapp: "And so, Jim Lacatski took it on himself, put it in his own hands. He and Colm Kelleher interviewed all these people who applied for the jobs, the 50 full-time positions that they staffed, in a matter of months. They did background checks, they required security clearances for all those people, and they were worried about leaks. They didn't want information to get out. "They also were concerned about espionage by foreign players, by foreign companies, things of that sort. And some of that really did happen. As Jim has shared with us, there were a couple of phones that were transmitters that were found inside Bigelow Aerospace, inside the Bigelow, uh, facilities, and it was very alarming because they weren't sure who was doing it. I think they think it was a foreign government. I'm not going to say which one, uh, they suspected the most." (Lacatski said that the phones in question were made in China.) Knapp: "But, and then they also found weird frequencies emanating from Skinwalker Ranch. That's not strange, and there's a lot of unusual stuff that happens there, but it was some sort of a an espionage program that they believed was was not only looking at the ranch, but also at BAASS. "That was his primary concern. He was worried that the story gets out, because secrecy was of paramount interest to the heads of DIA and he's worried about the information getting out to the public. Because once it happened, then the knives come out in the Pentagon and within the intelligence community, which is kind of what happened. A memo was sent from Harry Reid's office, let other people know that AAWSAP existed, and that's when things started getting problematic." Corbell: "The bugging thing. So, it's not just like Bigelow Aerospace was tapped with something, he said, specifically, AAWSAP, right? So they were looking at that new UFO program. And I don't know how public this is, but he did say it was - not just him, other people have all said - it was multiple nations, multiple, different devices from those phones. And he also said that they worked with FBI, they had FBI liaisons looking at the ranch property, and also at Bigelow Aerospace. "Because, remember, they were supposed to receive a transfer of materials. That's why they reverse, reverse engineered (laughs), you know, they built everything to be able to hold SCIF-capable and material-capable property at that classification level. So, look, I think if we pull it back, the whole idea is, James Lacatski made a statement at some point that he was, you know, head of, or part of, or running the counterintelligence for AAWSAP. But his point was to keep AAWSAP itself secret from foreign nations. So then he has to keep it secret from the U.S. He did it. He did a great job. They actually kept it secret. That doesn't mean he's going out and creating false information to the public like he's been accused of. "So, should we listen to Jim Lacatski? That was like, you know, the main question. Oh, one second. He also identified that there is currently a counter-programming, counterintelligence operation going on to the American public, but not against the American public, by AARO." (In other words, spread misinformation to the American public so they can advance their goal of misinforming and confusing our adversaries who are always listening. National security! IMO, that's only acceptable if we're talking specifics related to propulsion, technology and weapons that can be used to give us a leg up on said adversaries. But everything else should come out and be made public. We shouldn't be told a bunch of lies about information we paid for and that could, potentially, give us some clarity about our species and other lifeforms on this planet.) Corbell: That was so clear in our interview with him that he said that, you know, 'Look, they're acting this way. They are telling you lies about AAWSAP and what happened.' And that's why he said, 'My books, I'm a government employee. This was paid by taxpayers. I'm trying to give you information.' And that's what his books are. "So it's clear from these rounds of interviews that we just had with Dr. Lacatski that he supports a controlled UFO disclosure. He made that very clear. So should we listen to what he has to say? I mean, he was a big dog, right, George?" Knapp: "He was the head of the largest U.S. government-funded UFO investigation in history, that we know of. He worked with Colm Kelleher, who was the boots-on-the-ground guy in Las Vegas. He worked with Jay Stratton. Stratton's role in the development of AAWSAP has not been really fully explored, but he's got a book coming out at some point, once it gets through the DOPSR process. But then we'll get additional information to buttress what Lacatski has said."](https://image.24vids.com/tw-1991268528771748027/amplify_video_thumb/1990932248116539392/img/QA2EH0b-Bfna8TB4.jpg)