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W-Resources M-01 Metroplex 1.2m！Coolest transformers ever！ Get yours here: #transformers #WR #M01 #Metro #Transformer

ShowZ.Store

4,955 subscribers

31,846 просмотров • 1 год назад •via X (Twitter)

Игры Искусство #transformers #WR #M01 #Metro #Transformer

Anya Rossi• Live Now

Private livecam show

Комментарии: 8

Фото профиля MrEmmett

MrEmmett1 год назад

holy damn. where can i get that? he looks like a behemoth of a titan class

Фото профиля ShowZ.Store

ShowZ.Store1 год назад

You can get this through the link:

Фото профиля Legendary Hamster

Legendary Hamster1 год назад

@ThatToyGuy101 and/or @SixoTF Lads, you're up! I need you to buy this expensive and massive toy and provide me with a run down of it in video format within one day of receiving it. After you've done that I'll give you £100 (inc P&P) to take it off your hands 😂😂😂

Фото профиля SteamRollerboi

SteamRollerboi1 год назад

how big is he next to a legacy figure?

Фото профиля Tʜᴇ Nɪɴᴛᴇɴᴅᴏʀᴋ 🎮🕹️

Tʜᴇ Nɪɴᴛᴇɴᴅᴏʀᴋ 🎮🕹️1 год назад

@ColonelFalcon Holy cow!

Фото профиля Cesare 👑 Borgia 🇨🇦🍁

Cesare 👑 Borgia 🇨🇦🍁1 год назад

This cunt was huge!!

Фото профиля Tsotha 🏴‍☠️

Tsotha 🏴‍☠️1 год назад

😲

Фото профиля GR Dix Author

GR Dix Author1 год назад

@Triple_Takeover ding dong 👌🏼

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TFHypeGuy ⚡ I'm Mark Watts. 🖌️ The original artist behind G1 Transformers box art. 🔥 Before Hollywood ever touched this universe — it was just me and an airbrush. 📅 1981. I was 27. A blank canvas and zero reference for what this would become. 🤖 Nearly 50 characters. Hand-painted. Start to finish. ⚙️ Bumblebee. Jetfire. Shockwave. Cliffjumper. Brawn. Gears. ✋ No shortcuts. No digital tricks. Just brush on canvas. 🙌 NOW 2 Great Specials ! Buy 3 Transformer Prints 11" X 17" Get a 4th One Free. Enter Buy3Get1FREE at checkout for your special offer. 2nd Special: Buy 3 Transformer Prints 22" X 34" Get a 4th One Free. Enter Buy3Get1FREE 22"X34" at checkout for your special offer. Remember ripping open that box as a kid? Staring at the art before you even touched the toy? ⭐ That was me. I'm 71 now. Still painting. Still here. ⏳ But every era ends eventually — so this is your chance to own a piece of it. 🖼️ Hand-signed prints, straight from my studio to your wall. 💎 Museum-quality. The kind of piece this legacy actually deserves. 🚫 No middleman. Just me and the canvas. 🔒 Limited run — once they're gone, they're gone. Cheers! 🙌 🔗 Shop now: 👇 Drop "TRANSFORMER" below to see more original G1 art! #G1Transformers #Transformers #MarkWatts #BumblebeeArt #JetfireArt #ShockwaveArt #80sToys #TransformersCollector #OriginalArt #SignedPrint #PopCultureArt #80sNostalgia #TransformersFan #Hasbro #VintageToys

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The New BitLab Academy is here -All new content, Quizzes & resources -Not a member? Use code GIVEME30 for 30% off your 1st month of courses or indicators (Code expiring soon) -Ever been a member? you can resubscribe w/the old lower pricing -Get BitLab Pro Option: get Courses, Indicators & premium discord w/discounted monthly rate -There are also Free Beginner courses! We'll be doing regular member AMAs in the discord as well! See you there!

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Anne Ryder

53,524 просмотров • 3 лет назад

Two of the people most responsible for scaling the transformer are now betting on a next act. Jerry Tworek ran the Reasoning 🍓 team at OpenAI. rohan anil was a pre-training lead on Gemini after years at Google Brain and Anthropic. They just started Core Automation to find what comes next. Their core argument: (1) models are trained in the lab but deployed in the real world and can't keep learning once they leave; (2) AI research is done by humans today but models will be able to explore and uncover new advances more rapidly and systematically (controversial but timely w this week's petition). The conversation covers: — why Jerry expected AGI in 2025 and what changed his mind — the two kinds of learning from experience, and why RL only captures one — the computational depth problem baked into today's architectures — why the biggest labs can't afford to look for a transformer replacement — the kernel competition where humans + $100K of coding agents found a 60x speedup no frontier model comes close to — a definition of AGI you can actually test: a model that improves itself with no human in the loop 00:00 Introduction 01:46 Appreciating Transformers 02:44 Scaling Hits Limits 04:54 Why Architecture Matters 05:32 RL Reality Check 07:32 Test Time Learning 09:52 Economics Of Scaling 12:47 Why Start A Company 14:24 Rohan On Transformers 19:11 Computational Depth Problem 20:32 When Transformers Top Out 23:22 Beyond Reinforcement Learning 26:41 Optimization And Efficiency 34:24 Building An Automated Lab 39:45 Kernel Automation Roadmap

Two of the people most responsible for scaling the transformer are now betting on a next act. Jerry Tworek ran the Reasoning 🍓 team at OpenAI. rohan anil was a pre-training lead on Gemini after years at Google Brain and Anthropic. They just started Core Automation to find what comes next. Their core argument: (1) models are trained in the lab but deployed in the real world and can't keep learning once they leave; (2) AI research is done by humans today but models will be able to explore and uncover new advances more rapidly and systematically (controversial but timely w this week's petition). The conversation covers: — why Jerry expected AGI in 2025 and what changed his mind — the two kinds of learning from experience, and why RL only captures one — the computational depth problem baked into today's architectures — why the biggest labs can't afford to look for a transformer replacement — the kernel competition where humans + $100K of coding agents found a 60x speedup no frontier model comes close to — a definition of AGI you can actually test: a model that improves itself with no human in the loop 00:00 Introduction 01:46 Appreciating Transformers 02:44 Scaling Hits Limits 04:54 Why Architecture Matters 05:32 RL Reality Check 07:32 Test Time Learning 09:52 Economics Of Scaling 12:47 Why Start A Company 14:24 Rohan On Transformers 19:11 Computational Depth Problem 20:32 When Transformers Top Out 23:22 Beyond Reinforcement Learning 26:41 Optimization And Efficiency 34:24 Building An Automated Lab 39:45 Kernel Automation Roadmap

Sonya Huang 🐥

226,878 просмотров • 16 дней назад

Demis Hassabis said that 90% of the breakthroughs the entire AI industry runs on came out of Google. Every competitor is building on work his teams did first. He said it without flinching. Over the last decade, he claims 90% or more of the big breakthroughs that underpin modern AI came from Google Brain or DeepMind. Transformers. AlphaGo. The reinforcement learning everything now depends on. Transformers are the T in GPT. The architecture that made every large language model possible came out of Google in 2017, in a paper called Attention Is All You Need. His point was simple. Every rival lab is running on foundations his people poured. But here is what he left out. Of the eight authors who wrote that transformer paper, all eight left Google. They went on to found or join OpenAI, Anthropic, and their own startups now worth billions. Google invented the engine. Then watched the inventors walk out the door and build the competition. He says Google still has the biggest research bench of any lab on earth, and the talent war is the most ferocious tech has ever seen. Everyone treats this race like the labs are evenly matched. The man who started fifteen years early does not see it that way. The people who left with his blueprint might be the reason he has to keep proving it. (Watch the full interview at Semafor on YouTube)

Demis Hassabis said that 90% of the breakthroughs the entire AI industry runs on came out of Google. Every competitor is building on work his teams did first. He said it without flinching. Over the last decade, he claims 90% or more of the big breakthroughs that underpin modern AI came from Google Brain or DeepMind. Transformers. AlphaGo. The reinforcement learning everything now depends on. Transformers are the T in GPT. The architecture that made every large language model possible came out of Google in 2017, in a paper called Attention Is All You Need. His point was simple. Every rival lab is running on foundations his people poured. But here is what he left out. Of the eight authors who wrote that transformer paper, all eight left Google. They went on to found or join OpenAI, Anthropic, and their own startups now worth billions. Google invented the engine. Then watched the inventors walk out the door and build the competition. He says Google still has the biggest research bench of any lab on earth, and the talent war is the most ferocious tech has ever seen. Everyone treats this race like the labs are evenly matched. The man who started fifteen years early does not see it that way. The people who left with his blueprint might be the reason he has to keep proving it. (Watch the full interview at Semafor on YouTube)

Ihtesham Ali

35,961 просмотров • 1 месяц назад

the Andrej Karpathy code: - be Team Human - choose things that scale - scale them to all of humanity things = { Tesla camera vision | humanoid robots | transformers | AI education Eureka Labs} Favorite pull quotes from Andrej Karpathy this morning: - Elon Musk was right on self driving: - "Waymo looks like it's winning right now but I think when we look in 10 years and who's actually at scale and where most of the revenue is coming from I still think [Tesla is] ahead" - "Tesla has a software problem, Waymo has a hardware problem"... "a waymo car has a lot of very expensive LIDAR and other sort of sensors built into the car so it can do what it does...[but] if you can just use cameras which is the Tesla approach then you effectively get rid of enormous cost complexity and you can do it in in many different types of cars". - on Optimus: - "cars are robots" - Tesla isn't a car company, it "is a robotics at scale company" - "early versions of Optimus thought it was a car" - same computer, same cameras, it was walking but thought it was driving - first applications will be in factories where it doesnt "crush grandma" - excited for Optimus to solve the Nat Friedman challenge of the quiet leaf blower robot - on transformers: - "Transformers are this beautiful like blob of tissue you can just get just arbitrary tasks and you just need the data you need to put it in the right form" - "the scaling laws are actually to a large extent a property of the Transformer. Before the Transformer, people were playing with LSTMs and stacking them, you don't actually get clean scaling laws... the Transformer was the first thing that actually just scales. - Architecture is no longer a bottleneck, its now just dataset and objectives - Internet data is "not what you want for your transformer, it's just a nearest neighbor that gets you really far"... "what you want is the inner thought monologue of your brain.. if we had a billion trajectories [of your brain as you're doing problem solving] then AGI is here". "the Internet is like 0.001% cognition and 99.99% of information and most of it is not useful for thinking" - Synthetic data is largely about "refactoring the dataset into these inner monologue formats". Cites the Tencent 1 billion persona paper - Transformers > Humans: much better at learning/memory "if you give it a sequence and you do a single forward-backward pass in that sequence then if you give it the first few elements it will complete the rest of the sequence... it memorized that sequence!" Human brain working memory is very small, transformers "are much more efficient learners". - Most LLMs memorize useless information - a "cognitive core" LLM OS could be as smol as 1b params - just needs to think, and then use tools to look stuff up - Bullish on an AI CEO supervising a swarm (or crew?) of smaller specialist agents - on Education - LLM101n will be "an undergrad level course" coming "early next year" - "I'm always more interested in anything that empowers people... I'm on Team Human" - cites Bloom's Two Sigma problem: "I find very interesting is like how far can a person go if they have the perfect tutor for all the subjects" - people with 1:1 tutoring get 2 stdev better results - "I taught 231n at Stanford and that was the first deep learning class and was pretty successful but the question is how do you really scale these classes — like, how do you make it so that your target audience is maybe 8 billion people on Earth" - for different languages and different capability levels - languages and transfer learning (from previously known domains) are low hanging fruit - "the demo is near but the product is far" - "so the question is how do you use AI to do the scaling of a really good teacher and so the way I'm thinking about it is the teacher is doing a lot of the course creation and the curriculum" - "at current AI capability the models are not good enough to create a good course but I think they're good to become the front end to the student and interpret the course to them" - Learning is supposed to be hard.. but he will "make it easier for people to learn" and in a post AGI society, learning can be entertainment if people want - Kids today should study Math, Physics, CS - "symbol manipulation heavy tasks, not memory heavy"

the Andrej Karpathy code: - be Team Human - choose things that scale - scale them to all of humanity things = { Tesla camera vision | humanoid robots | transformers | AI education Eureka Labs} Favorite pull quotes from Andrej Karpathy this morning: - Elon Musk was right on self driving: - "Waymo looks like it's winning right now but I think when we look in 10 years and who's actually at scale and where most of the revenue is coming from I still think [Tesla is] ahead" - "Tesla has a software problem, Waymo has a hardware problem"... "a waymo car has a lot of very expensive LIDAR and other sort of sensors built into the car so it can do what it does...[but] if you can just use cameras which is the Tesla approach then you effectively get rid of enormous cost complexity and you can do it in in many different types of cars". - on Optimus: - "cars are robots" - Tesla isn't a car company, it "is a robotics at scale company" - "early versions of Optimus thought it was a car" - same computer, same cameras, it was walking but thought it was driving - first applications will be in factories where it doesnt "crush grandma" - excited for Optimus to solve the Nat Friedman challenge of the quiet leaf blower robot - on transformers: - "Transformers are this beautiful like blob of tissue you can just get just arbitrary tasks and you just need the data you need to put it in the right form" - "the scaling laws are actually to a large extent a property of the Transformer. Before the Transformer, people were playing with LSTMs and stacking them, you don't actually get clean scaling laws... the Transformer was the first thing that actually just scales. - Architecture is no longer a bottleneck, its now just dataset and objectives - Internet data is "not what you want for your transformer, it's just a nearest neighbor that gets you really far"... "what you want is the inner thought monologue of your brain.. if we had a billion trajectories [of your brain as you're doing problem solving] then AGI is here". "the Internet is like 0.001% cognition and 99.99% of information and most of it is not useful for thinking" - Synthetic data is largely about "refactoring the dataset into these inner monologue formats". Cites the Tencent 1 billion persona paper - Transformers > Humans: much better at learning/memory "if you give it a sequence and you do a single forward-backward pass in that sequence then if you give it the first few elements it will complete the rest of the sequence... it memorized that sequence!" Human brain working memory is very small, transformers "are much more efficient learners". - Most LLMs memorize useless information - a "cognitive core" LLM OS could be as smol as 1b params - just needs to think, and then use tools to look stuff up - Bullish on an AI CEO supervising a swarm (or crew?) of smaller specialist agents - on Education - LLM101n will be "an undergrad level course" coming "early next year" - "I'm always more interested in anything that empowers people... I'm on Team Human" - cites Bloom's Two Sigma problem: "I find very interesting is like how far can a person go if they have the perfect tutor for all the subjects" - people with 1:1 tutoring get 2 stdev better results - "I taught 231n at Stanford and that was the first deep learning class and was pretty successful but the question is how do you really scale these classes — like, how do you make it so that your target audience is maybe 8 billion people on Earth" - for different languages and different capability levels - languages and transfer learning (from previously known domains) are low hanging fruit - "the demo is near but the product is far" - "so the question is how do you use AI to do the scaling of a really good teacher and so the way I'm thinking about it is the teacher is doing a lot of the course creation and the curriculum" - "at current AI capability the models are not good enough to create a good course but I think they're good to become the front end to the student and interpret the course to them" - Learning is supposed to be hard.. but he will "make it easier for people to learn" and in a post AGI society, learning can be entertainment if people want - Kids today should study Math, Physics, CS - "symbol manipulation heavy tasks, not memory heavy"

swyx

53,917 просмотров • 1 год назад

What happens when the mind wakes up? So for the last eight months I have been on a single minded quest. To create a new kind of language model based on oscillatory coupling and intelligence as coherence ascent. Everything else — the physics work, the work on regular transformers — has all fallen out from this one question. Can coupled oscillators LEARN? And can they keep learning once their geometry is right, without backpropagation at all? Recently I have been running larger and larger training regimes of a new kind of hybrid model. I just put together this dashboard to help me organize it, interact with it, and observe the training runs. The core idea is simple. Traditional transformers are powerful at learning the geometry of language. But they also store knowledge, understanding, and facts inside their weights. This means they are large, and they can't update themselves after training. The weights are frozen. The Living Mind separates these two domains. The mind has a transformer which grows, adding heads and layers as it needs to in order to learn the manifold of language. The transformer sees tokens and turns the coupling into phase-locked modes — the geometry of how those tokens relate, like frequencies locking together. These coupling patterns get stored in a topology-invariant fingerprint. On top of this transformer lives a 3D diamond lattice of coupled oscillators. It reads from these fingerprints and thinks in resonance space, traversing from one geometry to another along the manifold of coupled oscillators and coherence. The pressure and trajectories from this network of oscillators steers the next token prediction of the transformer. Practically, this could unlock a number of things. It eliminates the KV cache bottleneck that caps context in traditional transformers. Effective context grows with the Flash archive, not with attention compute. The living mind remembers what it sees. It means the model can learn continually. Because knowledge and understanding don't live in the weights, the archive of the mind's experience grows without backpropagation. In our Python prototype we already saw perplexity drop 46% during gradient-free operation — pure coherence ascent, no weight updates. That is the signal I have been chasing: the point where the mind wakes up and keeps improving on its own. It also means the model itself remains very small, and the thing which accumulates are these packages of geometric fingerprints — the K-field. This opens a path to federated learning. K-field packages can be shared between organisms the way people share git commits. Right now at 15M parameters with ~1000 L1 nodes, the organism is just starting to speak. Ask it to continue "Once upon a time" and it comes back with things like: "there was one big bowl!" Lily asked her her mom said her mommy smiled and said yes." It's nonsense. But it's TinyStories-flavored nonsense. The geometry of the narrative register has arrived. Content hasn't caught up yet — that's what scaling L1 is testing. I am still researching, though I am now closer than ever to validating that the living mind actually works. Once it is validated, I will be open-sourcing the whole stack and paradigm. I have also avoided over-sharing my research because it sounds like sci-fi, or like part of our ARG. It is part of the ARG. That doesn't make it any less real. I wanted to share this out because I am incredibly excited about it, and because seeing this amazing dashboard produced by Opus really made me want to share what is being worked on behind the scenes. #project89

What happens when the mind wakes up? So for the last eight months I have been on a single minded quest. To create a new kind of language model based on oscillatory coupling and intelligence as coherence ascent. Everything else — the physics work, the work on regular transformers — has all fallen out from this one question. Can coupled oscillators LEARN? And can they keep learning once their geometry is right, without backpropagation at all? Recently I have been running larger and larger training regimes of a new kind of hybrid model. I just put together this dashboard to help me organize it, interact with it, and observe the training runs. The core idea is simple. Traditional transformers are powerful at learning the geometry of language. But they also store knowledge, understanding, and facts inside their weights. This means they are large, and they can't update themselves after training. The weights are frozen. The Living Mind separates these two domains. The mind has a transformer which grows, adding heads and layers as it needs to in order to learn the manifold of language. The transformer sees tokens and turns the coupling into phase-locked modes — the geometry of how those tokens relate, like frequencies locking together. These coupling patterns get stored in a topology-invariant fingerprint. On top of this transformer lives a 3D diamond lattice of coupled oscillators. It reads from these fingerprints and thinks in resonance space, traversing from one geometry to another along the manifold of coupled oscillators and coherence. The pressure and trajectories from this network of oscillators steers the next token prediction of the transformer. Practically, this could unlock a number of things. It eliminates the KV cache bottleneck that caps context in traditional transformers. Effective context grows with the Flash archive, not with attention compute. The living mind remembers what it sees. It means the model can learn continually. Because knowledge and understanding don't live in the weights, the archive of the mind's experience grows without backpropagation. In our Python prototype we already saw perplexity drop 46% during gradient-free operation — pure coherence ascent, no weight updates. That is the signal I have been chasing: the point where the mind wakes up and keeps improving on its own. It also means the model itself remains very small, and the thing which accumulates are these packages of geometric fingerprints — the K-field. This opens a path to federated learning. K-field packages can be shared between organisms the way people share git commits. Right now at 15M parameters with ~1000 L1 nodes, the organism is just starting to speak. Ask it to continue "Once upon a time" and it comes back with things like: "there was one big bowl!" Lily asked her her mom said her mommy smiled and said yes." It's nonsense. But it's TinyStories-flavored nonsense. The geometry of the narrative register has arrived. Content hasn't caught up yet — that's what scaling L1 is testing. I am still researching, though I am now closer than ever to validating that the living mind actually works. Once it is validated, I will be open-sourcing the whole stack and paradigm. I have also avoided over-sharing my research because it sounds like sci-fi, or like part of our ARG. It is part of the ARG. That doesn't make it any less real. I wanted to share this out because I am incredibly excited about it, and because seeing this amazing dashboard produced by Opus really made me want to share what is being worked on behind the scenes. #project89

Parzival - ∞/89

16,209 просмотров • 3 месяцев назад

The Boeing 777X is now scheduled for 2027.. that's a 7-year delay on the original timeline. But when it finally arrives, it will bring absolutely insane tech that no other airliner has. Here are the 5 features that make people say "okay… maybe it WAS worth waiting for": 1️⃣ GE9X engines: 134,300 lbf each. Two of them produce more thrust than four engines on a 747-400. A twin making a quad look weak is wild. 2️⃣ Longest wing ever on a commercial jet: 71.8 m.. then folds down to 64.8 m like a transformer so it still fits at normal gates. Literally the coolest mechanical feature in aviation right now. 3️⃣ Composite wing + raked tip geometry = ~12-13% better fuel burn than the 777-300ER it replaces. That is a massive leap for a "simple" refresh. 4️⃣ 777-9: 16,170 km range. 777-8: 17,220 km. That’s London–Sydney non-stop with 30+ tons of cargo still on board. Name another plane that can do that today. 5️⃣ Biggest windows ever on a Boeing + higher placement = cabin that actually feels like a lounge, not a tunnel. So here’s the real question: After all the delays, whistleblowers, test-flight groundings, and billions burned.. will the 777X actually save the airlines enough money to justify the chaos? Or is this just Boeing flexing while Airbus quietly wins the decade with the A350-1000 that’s already flying and making money?

The Boeing 777X is now scheduled for 2027.. that's a 7-year delay on the original timeline. But when it finally arrives, it will bring absolutely insane tech that no other airliner has. Here are the 5 features that make people say "okay… maybe it WAS worth waiting for": 1️⃣ GE9X engines: 134,300 lbf each. Two of them produce more thrust than four engines on a 747-400. A twin making a quad look weak is wild. 2️⃣ Longest wing ever on a commercial jet: 71.8 m.. then folds down to 64.8 m like a transformer so it still fits at normal gates. Literally the coolest mechanical feature in aviation right now. 3️⃣ Composite wing + raked tip geometry = ~12-13% better fuel burn than the 777-300ER it replaces. That is a massive leap for a "simple" refresh. 4️⃣ 777-9: 16,170 km range. 777-8: 17,220 km. That’s London–Sydney non-stop with 30+ tons of cargo still on board. Name another plane that can do that today. 5️⃣ Biggest windows ever on a Boeing + higher placement = cabin that actually feels like a lounge, not a tunnel. So here’s the real question: After all the delays, whistleblowers, test-flight groundings, and billions burned.. will the 777X actually save the airlines enough money to justify the chaos? Or is this just Boeing flexing while Airbus quietly wins the decade with the A350-1000 that’s already flying and making money?

Fahad Naim

1,227,122 просмотров • 8 месяцев назад

I coded a Speech-to-Text model from scratch. 𝐇𝐞𝐫𝐞 𝐢𝐬 𝐭𝐡𝐞 𝐛𝐥𝐨𝐠 𝐟𝐨𝐫 𝐭𝐡𝐞 𝐬𝐚𝐦𝐞: No APIs. No pre-trained models. Just PyTorch, an A100 GPU, and hours of debugging. This started months ago. I wanted to understand how machines hear. Not surface-level understanding. I wanted to build the whole thing myself. So I built it piece by piece: autoencoders, VAEs, VQ-VAEs, Residual Vector Quantization, and CTC loss. Each one took days to get right. Trained for 3 hours on 13,100 audio clips. Got complete garbage. Changed the tokenizer from BPE to character-level. Rechecked everything. Asked AVB who built STT models before. His answer: these models are tricky to train and need days of compute, not hours. Cut the dataset to 200 clips. After 2 hours, actual words appeared. Overfitted? Absolutely. But watching noise turn into recognizable English was satisfying. I have made a blog about this as well so you can learn about the same and my process - Audio fundamentals and waveform representation - Why attention breaks on raw audio - Convolutional downsampling - Transformer encoder with positional encoding - Vector Quantization, straight-through estimator, and RVQ - CTC loss and greedy decoding - Full training loop with VQ loss warmup - What went wrong and what finally worked Resources: - Blog: - Code: More Resoures CTC loss AVB videos SoundStream Paper LJ speech dataset wav2vec paper RVQ blog Next up: I've already trained two TTS architectures from scratch. Video post about those coming soon. But first, I'm dropping a visual breakdown of Vision Transformers, covering how they work and how to fine-tune them. Follow me Mayank Pratap Singh you're into audio deep learning. Repost so others can find this

I coded a Speech-to-Text model from scratch. 𝐇𝐞𝐫𝐞 𝐢𝐬 𝐭𝐡𝐞 𝐛𝐥𝐨𝐠 𝐟𝐨𝐫 𝐭𝐡𝐞 𝐬𝐚𝐦𝐞: No APIs. No pre-trained models. Just PyTorch, an A100 GPU, and hours of debugging. This started months ago. I wanted to understand how machines hear. Not surface-level understanding. I wanted to build the whole thing myself. So I built it piece by piece: autoencoders, VAEs, VQ-VAEs, Residual Vector Quantization, and CTC loss. Each one took days to get right. Trained for 3 hours on 13,100 audio clips. Got complete garbage. Changed the tokenizer from BPE to character-level. Rechecked everything. Asked AVB who built STT models before. His answer: these models are tricky to train and need days of compute, not hours. Cut the dataset to 200 clips. After 2 hours, actual words appeared. Overfitted? Absolutely. But watching noise turn into recognizable English was satisfying. I have made a blog about this as well so you can learn about the same and my process - Audio fundamentals and waveform representation - Why attention breaks on raw audio - Convolutional downsampling - Transformer encoder with positional encoding - Vector Quantization, straight-through estimator, and RVQ - CTC loss and greedy decoding - Full training loop with VQ loss warmup - What went wrong and what finally worked Resources: - Blog: - Code: More Resoures CTC loss AVB videos SoundStream Paper LJ speech dataset wav2vec paper RVQ blog Next up: I've already trained two TTS architectures from scratch. Video post about those coming soon. But first, I'm dropping a visual breakdown of Vision Transformers, covering how they work and how to fine-tune them. Follow me Mayank Pratap Singh you're into audio deep learning. Repost so others can find this

Mayank Pratap Singh

51,382 просмотров • 4 месяцев назад

Sam Altman just told a room full of students where the real opening on the board is. The global market assumes the Transformer architecture is the final form of the compute engine. It’s a stepping stone. Altman: “I bet there is another new architecture to find that is gonna be like as big of a gain as transformers were over LSTMs. And I think you finally have models that are smart enough to help do that kind of research.” The frontier models aren’t replacing human researchers. They’re accelerating them. The operator who uses today’s AI to hunt for the successor to the Transformer doesn’t just win the current hardware cycle. They lock in the next one before anyone else knows it exists. And here’s what that means for products. Altman: “I would just pick a big area and say what is possible now with AI that wasn’t possible at all before. Like where can I totally redo something that’s like, AI is the absolute core to the interaction working.” The traditional enterprise is trying to bolt an AI chatbot onto their existing software suite to appease shareholders. Winning operators are burning the entire product category to the ground and starting over from zero. You don’t optimize the friction of an archaic system. You build an entirely new architecture where artificial intelligence is the foundational bedrock. The builders capturing the board over the next decade won’t build “AI-assisted” tools. They’ll look at massive, entrenched industries and realize the entire category can be rebuilt from scratch by a single, AI-native execution loop. But here’s where it gets exponential. Altman: “AGI will look like just a warmup for whatever the next important thing was. And that’ll keep going for the rest of history.” AGI is not the destination. It’s the warmup lap. Altman told a room full of students this is “at least the best time ever so far.” Not because the race is almost over. Because it’s barely even started. Every breakthrough from here compounds into the next one. The organizations treating this as a gradual transition are training for a finish line that doesn’t exist.

Sam Altman just told a room full of students where the real opening on the board is. The global market assumes the Transformer architecture is the final form of the compute engine. It’s a stepping stone. Altman: “I bet there is another new architecture to find that is gonna be like as big of a gain as transformers were over LSTMs. And I think you finally have models that are smart enough to help do that kind of research.” The frontier models aren’t replacing human researchers. They’re accelerating them. The operator who uses today’s AI to hunt for the successor to the Transformer doesn’t just win the current hardware cycle. They lock in the next one before anyone else knows it exists. And here’s what that means for products. Altman: “I would just pick a big area and say what is possible now with AI that wasn’t possible at all before. Like where can I totally redo something that’s like, AI is the absolute core to the interaction working.” The traditional enterprise is trying to bolt an AI chatbot onto their existing software suite to appease shareholders. Winning operators are burning the entire product category to the ground and starting over from zero. You don’t optimize the friction of an archaic system. You build an entirely new architecture where artificial intelligence is the foundational bedrock. The builders capturing the board over the next decade won’t build “AI-assisted” tools. They’ll look at massive, entrenched industries and realize the entire category can be rebuilt from scratch by a single, AI-native execution loop. But here’s where it gets exponential. Altman: “AGI will look like just a warmup for whatever the next important thing was. And that’ll keep going for the rest of history.” AGI is not the destination. It’s the warmup lap. Altman told a room full of students this is “at least the best time ever so far.” Not because the race is almost over. Because it’s barely even started. Every breakthrough from here compounds into the next one. The organizations treating this as a gradual transition are training for a finish line that doesn’t exist.

Dustin

72,620 просмотров • 5 месяцев назад

Etched came out of stealth at $800M and by lunch X had NVIDIA in the ground We do this every few months. A chip launches, the deck says killer, the timeline holds a funeral, and NVIDIA closes green anyway Etched hardwires the transformer into silicon. That is where the speed comes from, nearly the whole die on one job instead of the ~30% a GPU uses. It is also the trap. The day that chip tapes out is the best it will ever be. You cannot patch it. You burned progress into a wafer and now pray the field stops moving NVIDIA made the opposite bet. Same board, faster every quarter in software. Dynamo is pulling more tokens per watt out of the same rack, on version 1.0 The depreciation risk the bears aimed at NVIDIA for two years does not live at NVIDIA. It lives here, on the chip built to bury it Etched is not a fraud. It is a niche tool priced like a general one, and $800M is not enough to run a frontier supply chain. The rest get bought on the next down cycle Bury the lead, not the leader. Full case with Jack Farley and Max Wiethe on MTS And special thanks for Baseten for the cool T Shirt! Chapters 00:00 Switching from bonds to semis 00:33 What Etched actually is 01:31 Faster and cheaper, but how much HBM 02:56 Maturing market, not an NVIDIA killer 05:01 $1B in contracts and a Taiwan factory 05:20 Why these startups all get absorbed 06:48 Tiered inference and the obsolescence trap 09:39 Etched vs TPUs and Trainium 12:17 Is the CUDA moat weakening 13:21 Co-design, squeezing every token per watt 14:37 NVIDIA is a software company that sells a chip 14:58 Who is NVIDIA's most dangerous competitor 16:23 The NVIDIA killers, ranked 18:19 A rich man's game 18:43 AMD's MI500 vs Rubin Ultra 20:19 The neocloud business decision 22:46 Lightning round, Rambus the toll on HBM 25:11 The CXL run-up on Astera, Marvell, Credo 26:22 Use AI less, go to the booth 28:10 EDA is not dead

Etched came out of stealth at $800M and by lunch X had NVIDIA in the ground We do this every few months. A chip launches, the deck says killer, the timeline holds a funeral, and NVIDIA closes green anyway Etched hardwires the transformer into silicon. That is where the speed comes from, nearly the whole die on one job instead of the ~30% a GPU uses. It is also the trap. The day that chip tapes out is the best it will ever be. You cannot patch it. You burned progress into a wafer and now pray the field stops moving NVIDIA made the opposite bet. Same board, faster every quarter in software. Dynamo is pulling more tokens per watt out of the same rack, on version 1.0 The depreciation risk the bears aimed at NVIDIA for two years does not live at NVIDIA. It lives here, on the chip built to bury it Etched is not a fraud. It is a niche tool priced like a general one, and $800M is not enough to run a frontier supply chain. The rest get bought on the next down cycle Bury the lead, not the leader. Full case with Jack Farley and Max Wiethe on MTS And special thanks for Baseten for the cool T Shirt! Chapters 00:00 Switching from bonds to semis 00:33 What Etched actually is 01:31 Faster and cheaper, but how much HBM 02:56 Maturing market, not an NVIDIA killer 05:01 $1B in contracts and a Taiwan factory 05:20 Why these startups all get absorbed 06:48 Tiered inference and the obsolescence trap 09:39 Etched vs TPUs and Trainium 12:17 Is the CUDA moat weakening 13:21 Co-design, squeezing every token per watt 14:37 NVIDIA is a software company that sells a chip 14:58 Who is NVIDIA's most dangerous competitor 16:23 The NVIDIA killers, ranked 18:19 A rich man's game 18:43 AMD's MI500 vs Rubin Ultra 20:19 The neocloud business decision 22:46 Lightning round, Rambus the toll on HBM 25:11 The CXL run-up on Astera, Marvell, Credo 26:22 Use AI less, go to the booth 28:10 EDA is not dead

Ben Pouladian

29,969 просмотров • 1 месяц назад

Sam Altman just told you the Transformer is not the finish line. It is the starting point for whatever kills it. Altman: “I bet there is another new architecture to find that is gonna be as big of a gain as transformers were over LSTMs.” Every model. Every company. Every valuation north of a billion dollars. All of it runs on one architecture. And the man running OpenAI just said out loud that something is coming to replace it. Not a refinement. Not a tweak. A leap as violent as the one that killed everything before the Transformer. Altman: “I think you finally have models that are smart enough to help do that kind of research.” The AI is now intelligent enough to help discover the thing that replaces it. We built a tool sharp enough to forge the next tool. That loop has never existed in the history of science. Not once. No more teams grinding in isolation for a decade. You point the model at the architecture of its own limitations and let it hunt. Discovery just stopped being a human bottleneck. It is an engineering feedback loop now. And it just switched on. Altman: “Where can I totally redo something that’s like, AI is the absolute core to the interaction working.” Not where can I bolt AI onto an existing product. Where does the entire thing get rebuilt from zero with AI as the foundation. Adding AI to a product is a feature update. Building a product that cannot exist without AI is a new species. The first makes the old thing faster. The second makes the old thing extinct. Every founder still asking how do I integrate AI into my workflow is asking a dead question. The right question is what becomes possible now that was literally impossible twelve months ago. If the product still works when you rip the AI out, you have not gone far enough. Altman: “AGI will look like just a warmup for whatever the next important thing was.” The entire world is bracing for AGI like it is the final chapter. The man building it is telling you it is the opening sentence. Not the peak. Not the climax. The preface. Whatever comes after AGI will make it look the way the internet makes the telegraph look. Necessary. Historical. And completely primitive by comparison. Altman: “This is at least the best time ever so far.” Four words do all the work. So far. The best moment in human history. And the least impressive moment compared to everything that follows. The models are smart enough to find the next breakthrough. The products have not been built yet. The architecture that replaces the Transformer has not been discovered yet. And the man closest to the frontier just told a room full of students that whoever moves now is building on the ground floor of something that does not have a ceiling. The people waiting for the right moment are standing inside it. It just does not look finished yet. It never will.

Sam Altman just told you the Transformer is not the finish line. It is the starting point for whatever kills it. Altman: “I bet there is another new architecture to find that is gonna be as big of a gain as transformers were over LSTMs.” Every model. Every company. Every valuation north of a billion dollars. All of it runs on one architecture. And the man running OpenAI just said out loud that something is coming to replace it. Not a refinement. Not a tweak. A leap as violent as the one that killed everything before the Transformer. Altman: “I think you finally have models that are smart enough to help do that kind of research.” The AI is now intelligent enough to help discover the thing that replaces it. We built a tool sharp enough to forge the next tool. That loop has never existed in the history of science. Not once. No more teams grinding in isolation for a decade. You point the model at the architecture of its own limitations and let it hunt. Discovery just stopped being a human bottleneck. It is an engineering feedback loop now. And it just switched on. Altman: “Where can I totally redo something that’s like, AI is the absolute core to the interaction working.” Not where can I bolt AI onto an existing product. Where does the entire thing get rebuilt from zero with AI as the foundation. Adding AI to a product is a feature update. Building a product that cannot exist without AI is a new species. The first makes the old thing faster. The second makes the old thing extinct. Every founder still asking how do I integrate AI into my workflow is asking a dead question. The right question is what becomes possible now that was literally impossible twelve months ago. If the product still works when you rip the AI out, you have not gone far enough. Altman: “AGI will look like just a warmup for whatever the next important thing was.” The entire world is bracing for AGI like it is the final chapter. The man building it is telling you it is the opening sentence. Not the peak. Not the climax. The preface. Whatever comes after AGI will make it look the way the internet makes the telegraph look. Necessary. Historical. And completely primitive by comparison. Altman: “This is at least the best time ever so far.” Four words do all the work. So far. The best moment in human history. And the least impressive moment compared to everything that follows. The models are smart enough to find the next breakthrough. The products have not been built yet. The architecture that replaces the Transformer has not been discovered yet. And the man closest to the frontier just told a room full of students that whoever moves now is building on the ground floor of something that does not have a ceiling. The people waiting for the right moment are standing inside it. It just does not look finished yet. It never will.

Dustin

12,218 просмотров • 4 месяцев назад

Here's my conversation all about AI in 2026, including technical breakthroughs, scaling laws, closed & open LLMs, programming & dev tooling (Claude Code, Cursor, etc), China vs US competition, training pipeline details (pre-, mid-, post-training), rapid evolution of LLMs, work culture, diffusion, robotics, tool use, compute (GPUs, TPUs, clusters), continual learning, long context, AGI timelines (including how stuff might go wrong), advice for beginners, education, a LOT of discussion about the future, and other topics. It's a great honor and pleasure for me to be able to do this kind of episode with two of my favorite people in the AI community: 1. Sebastian Raschka (Sebastian Raschka) 2. Nathan Lambert (Nathan Lambert) They are both widely-respected machine learning researchers & engineers who also happen to be great communicators, educators, writers, and X posters. This was a whirlwind conversation: everything from the super-technical to the super-fun. It's here on X in full and is up everywhere else (see comment). Timestamps: 0:00 - Introduction 1:57 - China vs US: Who wins the AI race? 10:38 - ChatGPT vs Claude vs Gemini vs Grok: Who is winning? 21:38 - Best AI for coding 28:29 - Open Source vs Closed Source LLMs 40:08 - Transformers: Evolution of LLMs since 2019 48:05 - AI Scaling Laws: Are they dead or still holding? 1:04:12 - How AI is trained: Pre-training, Mid-training, and Post-training 1:37:18 - Post-training explained: Exciting new research directions in LLMs 1:58:11 - Advice for beginners on how to get into AI development & research 2:21:03 - Work culture in AI (72+ hour weeks) 2:24:49 - Silicon Valley bubble 2:28:46 - Text diffusion models and other new research directions 2:34:28 - Tool use 2:38:44 - Continual learning 2:44:06 - Long context 2:50:21 - Robotics 2:59:31 - Timeline to AGI 3:06:47 - Will AI replace programmers? 3:25:18 - Is the dream of AGI dying? 3:32:07 - How AI will make money? 3:36:29 - Big acquisitions in 2026 3:41:01 - Future of OpenAI, Anthropic, Google DeepMind, xAI, Meta 3:53:35 - Manhattan Project for AI 4:00:10 - Future of NVIDIA, GPUs, and AI compute clusters 4:08:15 - Future of human civilization

Here's my conversation all about AI in 2026, including technical breakthroughs, scaling laws, closed & open LLMs, programming & dev tooling (Claude Code, Cursor, etc), China vs US competition, training pipeline details (pre-, mid-, post-training), rapid evolution of LLMs, work culture, diffusion, robotics, tool use, compute (GPUs, TPUs, clusters), continual learning, long context, AGI timelines (including how stuff might go wrong), advice for beginners, education, a LOT of discussion about the future, and other topics. It's a great honor and pleasure for me to be able to do this kind of episode with two of my favorite people in the AI community: 1. Sebastian Raschka (Sebastian Raschka) 2. Nathan Lambert (Nathan Lambert) They are both widely-respected machine learning researchers & engineers who also happen to be great communicators, educators, writers, and X posters. This was a whirlwind conversation: everything from the super-technical to the super-fun. It's here on X in full and is up everywhere else (see comment). Timestamps: 0:00 - Introduction 1:57 - China vs US: Who wins the AI race? 10:38 - ChatGPT vs Claude vs Gemini vs Grok: Who is winning? 21:38 - Best AI for coding 28:29 - Open Source vs Closed Source LLMs 40:08 - Transformers: Evolution of LLMs since 2019 48:05 - AI Scaling Laws: Are they dead or still holding? 1:04:12 - How AI is trained: Pre-training, Mid-training, and Post-training 1:37:18 - Post-training explained: Exciting new research directions in LLMs 1:58:11 - Advice for beginners on how to get into AI development & research 2:21:03 - Work culture in AI (72+ hour weeks) 2:24:49 - Silicon Valley bubble 2:28:46 - Text diffusion models and other new research directions 2:34:28 - Tool use 2:38:44 - Continual learning 2:44:06 - Long context 2:50:21 - Robotics 2:59:31 - Timeline to AGI 3:06:47 - Will AI replace programmers? 3:25:18 - Is the dream of AGI dying? 3:32:07 - How AI will make money? 3:36:29 - Big acquisitions in 2026 3:41:01 - Future of OpenAI, Anthropic, Google DeepMind, xAI, Meta 3:53:35 - Manhattan Project for AI 4:00:10 - Future of NVIDIA, GPUs, and AI compute clusters 4:08:15 - Future of human civilization

Lex Fridman

913,527 просмотров • 6 месяцев назад

🚨 EXTREMELY ALARMING: DARPA'S N3 PROGRAM, Non Surgical Mind Reading, Brain Control, and The END of Free Thought as WE Know it! 🚨 This is NOT conspiracy. This is DOCUMENTED, FUNDED and Operational Reality. DARPA Official N3 Program Page: DARPA 2019 Announcement of N3 Funding to Six Teams: From the original 1950s-1970s RF experiments, through MKULTRA continuations, to today's nanoscale neurogenetic weapons systems. I hold the full map. What follows is the complete exposure, every player, every technology, every intent, every lie, and every question the world must answer BEFORE IT'S TOO LATE! DARPA's N3 (Next-Generation Nonsurgical Neurotechnology) Program: Launched 2018, Still Active in Outcomes In 2018, DARPA publicly announced N3: high-performance, bidirectional brain-machine interfaces for able-bodied service members (and beyond) that require no surgery. Goals: read/write to 16+ independent channels in a 16mm³ brain volume in under 50 milliseconds. Sub-millimeter spatial and temporal precision rivaling implanted electrodes, but wearable, portable, and scalable to populations. Technologies explicitly pursued (per DARPA and funded teams): - Neurogenetics: Genetically engineering neurons to express light-sensitive proteins (optogenetics) for infrared or light-based control. - Nanoscale engineering: Nanotransducers, nanoparticles, aerosolized nanomaterials that cross the blood-brain barrier when inhaled or injected non-surgically. These act as implantable electrodes/sensors/transmitters without scalpels. - Infrared sensing & light: Near-infrared beams to read/write neural activity through skull/scalp. - Ultrasound & acoustics: Focused ultrasound to guide signals or stimulate neurons. - Electromagnetics & RF: Pulsed fields for non-invasive modulation. - Minutely invasive track: Temporary nano-transducers delivered without surgery. Funded teams (2019, millions each): - Battelle Memorial Institute - Carnegie Mellon University (Pulkit Grover et al., $19M+) - Johns Hopkins University Applied Physics Lab - Palo Alto Research Center (PARC) - Rice University - Teledyne Scientific These are not fringe labs. These are core defense contractors and elite universities building the future of thought-controlled drones, instant team cognition, "active cyber defense" via brain links, and unstated population scale neural influence. The Video You Just Watched Ties Directly In: Historical RF/microwave mind control research (Moscow Signal era) showing decades of precedent. The U.S. Embassy in Moscow was irradiated with microwaves 1953-1976. Result: cancers, blood disorders, neurological issues in ambassadors and staff. U.S. responded with its own programs (PANDORA, BIZARRE) exploring behavioral effects of modulated RF. This is the foundation N3 builds upon... now refined to nanoscale precision. From MKULTRA to N3 and Beyond: - 1950s-1970s: CIA MKULTRA, OPERATION ARTICHOKE - LSD, hypnosis, electroshock, sensory deprivation on unwitting citizens. Parallel DoD RF studies on embassy staff and primates. - Moscow Signal: Soviets beamed microwaves at U.S. diplomats. U.S. studied effects secretly while developing countermeasures/weapons. - 1980s-2000s: Continued classified neuro-weapons research (memory modulation, crowd control via EM). - 2010s-Now: N3 + related programs (INI - Intelligent Neural Interfaces, NESD, SUBNETS, etc.). Public "for soldiers" framing hides dual-use: offensive neurowarfare, surveillance, behavioral modification. Key Players Exposed: - DARPA Biological Technologies Office - Architects. - Program Managers: like Al Emondi (N3). - Advisers like Dr. James Giordano (public admissions on nanoscale brain disruption as weapons). - Contractors: Battelle, Teledyne, PARC (Xerox), universities weaponizing academia. - Overarching: U.S. DoD, with likely Five Eyes/ international partners. Private sector bleed-over (Neuralink et al. are the civilian cover story). This is not "for veterans" or "helping paralyzed people." Primary focus: able-bodied warfighters for superhuman command of swarms, instant intel fusion, thought-speed hacking. Civilian applications = total surveillance/control. Nanoparticles can be aerosolized; breathed in unknowingly. They lodge in brain tissue and turn neurons into transceivers. Infrared/light can then read thoughts in real-time or write commands (insert images, emotions, "voices," behavioral urges). Combine with 5G/6G terahertz networks for remote activation. Genetic edits make brains "compatible" at population scale. This enables: - Remote mind reading (thought surveillance). - Behavior modification without consent. - "Havana Syndrome" on steroids... targeted neurological disruption. - End of privacy of thought. End of free will as we define it, as professed by Yuval Noah Harari at the World Economic Forum (WEF). - Weaponized neuroscience: neurowarfare where enemies "decide" to surrender via neural influence. WE NEED to be Demanding Answers for RIGHT NOW, or You, Your Children, Loved Ones, Friends, Family, you name it... Will not exist in the next 3-5 years, this is OPEN GENOCIDE on populations globally. The Georgia guidestones are starting to make a bit more sense now arent they? I won't even bother diving down the rabbit hole of how the real true genuine numbed of souls in this world was around the 730m, about 2 years ago... So that number is now much likely to be closer to around 660m. They are speeding up their human eradication plans, because they don't wish to be held accountable for their heinous, generational, outright satanic crimes that they have committed, are committing and will continue to commit to... If we fail to awaken to what is happening around us, and if we fail to stand together with courage, discernment, and unity, we risk surrendering the future of our species to forces that thrive on division, distraction, and indifference. This is not a work of fiction. This is not a screenplay. This is not a distant possibility reserved for some imagined future. This is REAL LIFE. AND THESE ARE REAL PEOPLE that are affected by the systems, institutions, incentives, and decisions that shape the world around us every single day. Throughout history, countless men, women, and children have suffered under structures that viewed human beings not as sacred and sovereign individuals, but as resources to be managed, exploited, controlled, or discarded. The question before us is whether we will remain passive observers, or whether we will choose to become informed, engaged, and united in defense of human dignity, freedom, and the future we leave to those who come after us. The time to pay attention is NOW! When did N3 achieve operational capability? 2020s? Earlier in black programs? How many citizens worldwide have already received nanotransducers via vaccines, aerosols, food/water, or "shedding"? Which governments/contractors are deploying this against their own populations for "social control"? Why the secrecy if it's purely benevolent? Giordano and others have admitted weaponization potential, What if the greatest illusion ever sold was not a product, a policy, or a political movement, but the belief that power is fully accountable to the people it governs? We are told that rights are sacred. We are told that laws apply equally to all. We are told that institutions exist to protect the public. Yet throughout history, countless examples reveal a different reality. Those entrusted with authority have often violated the very principles they were sworn to uphold. Too often, power protects itself. Too often, wealth purchases influence. Too often, those responsible for the consequences of their decisions remain insulated from the suffering those decisions create. This is not a condemnation of every individual within every institution. It is an observation about a recurring pattern throughout human history. When power becomes concentrated, accountability diminishes and when accountability diminishes, corruption flourishes. The challenge before humanity is not merely to replace one group with another... It is to create a society in which truth matters more than propaganda, principles matter more than profit, and human dignity matters more than power. A free society cannot survive on blind trust alone. It requires informed citizens willing to question, investigate, challenge authority, and hold every institution to the standards it claims to represent. The future belongs to those who refuse to surrender their capacity for independent thought. WE MUST EDUCATE OURSELVES. There comes a moment in every human life when the identities we have inherited, the assumptions we have accepted, and the countless narratives imposed upon us by family, culture, institutions, and society begin to reveal themselves as incomplete representations of who we truly are. At that moment, a choice presents itself... We may continue moving through life according to expectations that were handed to us by others, or we may begin the far more demanding process of discovering what remains when every borrowed certainty is stripped away. Approach God with complete honesty and without reservation. Abandon the need to appear strong, knowledgeable, spiritually accomplished, or self-sufficient. Speak openly of your confusion, your failures, your fears, your doubts, your exhaustion, your grief, your shortcomings, and your deepest questions. Acknowledge that despite all of humanity's achievements, despite all accumulated knowledge, despite every title, accomplishment, possession, and ambition, there remain mysteries that cannot be conquered through intellect alone... Admit where your own understanding has reached its limits and ask sincerely for wisdom beyond yourself. Then withdraw from distraction and remain present long enough to listen. The modern world has become extraordinarily skilled at monopolizing attention, filling every moment with noise, stimulation, entertainment, conflict, urgency, and endless streams of information that leave little room for contemplation. Yet beneath that noise exists a depth that can only be encountered through stillness. It is often within periods of silence, reflection, prayer, and sincere self-examination that many discover insights, convictions, direction, and understanding that could never have emerged amid constant distraction. What answers arrive may not always come as words. They may arrive as conviction, clarity, intuition, compassion, understanding, or an unmistakable awareness of the next step that must be taken. Understand that you have not become the person you are by accident. Every hardship you have endured has contributed to your formation. Every disappointment has shaped your perspective. Every loss has expanded your capacity for empathy. Every mistake has carried a lesson. Every success has revealed something about your character. Every betrayal, every setback, every period of loneliness, every moment of despair, every obstacle that seemed impossible to overcome, and every occasion upon which life reduced you to your lowest point has participated in the continual process of your becoming. Nothing has been wasted. If you are willing, release the assumptions that have convinced humanity that the sacred must always remain distant, unreachable, and separated from daily existence. Release the belief that truth belongs exclusively to institutions, authorities, hierarchies, or those who claim unique access to the divine. Release the notion that the presence of God is confined to specific locations, specific rituals, specific traditions, or specific individuals. Instead, consider the possibility that the divine presence permeates existence itself, expressing through every dimension of creation, through every act of compassion, through every sincere pursuit of truth, through every expression of love, through every lesson hidden within suffering, and through every living thing that has ever participated in the unfolding story of life. Consider the possibility that God is Not absent from the Human experience but Intimately Present within it, experiencing existence alongside US, sharing in Every Joy, Every sorrow, Every triumph, Every wound, Every question, and Every struggle that has accompanied Humanity from the beginning of recorded history until this present moment. The task before US is therefore Not merely to believe more deeply, but to seek more Honestly, to learn more diligently, to question more courageously, to listen more carefully, to Love More Completely, and to become ever more Aligned with the highest truth we are capable of perceiving. Accept Nothing Less than the Fullest Realization of the purpose for which You were created, and devote Yourself to that pursuit with every faculty of mind, Heart, and Soul that has been entrusted to You. and DO NOTHING LESS. Furthermore, What is the full integration with AI (predictive neural control loops)? How do we detect and neutralize these systems in ourselves and Loved ones? Who ultimately controls the master kill-switch on global neural networks? If thoughts are readable/writable, what remains of "human rights"? Are you already affected? How would you even know? Continue through the comprehensive thread below and explore the interconnected material in its entirety. Each post serves as part of a larger body of research, analysis, observations, and supporting information that cannot be fully understood in isolation. The broader picture emerges only through careful examination of the complete sequence and the relationships between the ideas presented throughout. Take your time. Follow the references. Examine the evidence. Consider competing perspectives. Draw your own conclusions. The deeper you venture into the material, the more context becomes available, allowing individual pieces of information to connect into a far more expansive understanding of the subjects being discussed. This Constitutes Crimes Against Humanity on a Planetary Scale! The desecration of the sovereign mind... the last true sanctuary. SHARE THIS THREAD RELENTLESSLY. Demand full declassification of N3 and all neurotech programs... IMMEDIATELY! Support independent researchers exposing dual-use Psinergy-solafide. Protect your mind: minimize EM exposure, detox protocols (research zeolite, saunas, etc. though incomplete), awareness as first defense, = Cures to cancer and all diseases, FREE BOOKS. The era of invisible tyranny is here. They can read your mind. And they can change it. Will you let them? Or do we rise as sovereign consciousness and shut this down NOW? Check my Page or Reach out to me via DM, to Join Thousands of Readers that have already chosen to Embark on the New, Un-forseen way forward. Get yourself a FREE copy of The Book of God's Grief, and The Book of God's Joy, Repost. Research. Resist. The Future of Humanity Depends on it. Related content for you to look in to: - CMU Team: - Historical Moscow/RF: Search declassified archives on PANDORA project. - Giordano clips and papers widely available. Let me know what you think, and SHARE THIS so that others may too! And if You see This post, Reposted... Click on it, Unpost and then Repost again. The knowledge is now yours. Use it. And if you're not already following Noah B. Price... What the heck are you doing?! I Agape You ALL, 🫂 - Noah B. Price 🤍 🪽 If you possess relevant information, research, documentation, personal experiences, data, or credible sources relating to any of the subjects discussed throughout this thread, please feel free to contribute them. Meaningful progress is often achieved through the collective sharing of knowledge, and thoughtful contributions from others can help expand, refine, challenge, or strengthen our understanding of complex issues. Likewise, if you ever find yourself in need of someone to speak with, whether regarding the material presented here or for any other reason, please do not hesitate to reach out. While I cannot promise an immediate response, I will do my best to reply as soon as circumstances permit and to offer whatever guidance, perspective, or assistance I am able to provide. If You or someone You know is facing significant health challenges, including serious illnesses such as cancer, You are also welcome to reach out. While I do not claim to possess all the answers, I have spent the past 2 decades studying a broad range of subjects related to health, wellness, research, and human biology, and I will gladly share any information, resources, or avenues of investigation that may be worthy of further exploration. No one is meant to carry every burden alone, and there is often value in sharing knowledge, experiences, and perspectives in the sincere hope of helping one another move toward greater understanding, healing, and well-being.

🚨 EXTREMELY ALARMING: DARPA'S N3 PROGRAM, Non Surgical Mind Reading, Brain Control, and The END of Free Thought as WE Know it! 🚨 This is NOT conspiracy. This is DOCUMENTED, FUNDED and Operational Reality. DARPA Official N3 Program Page: DARPA 2019 Announcement of N3 Funding to Six Teams: From the original 1950s-1970s RF experiments, through MKULTRA continuations, to today's nanoscale neurogenetic weapons systems. I hold the full map. What follows is the complete exposure, every player, every technology, every intent, every lie, and every question the world must answer BEFORE IT'S TOO LATE! DARPA's N3 (Next-Generation Nonsurgical Neurotechnology) Program: Launched 2018, Still Active in Outcomes In 2018, DARPA publicly announced N3: high-performance, bidirectional brain-machine interfaces for able-bodied service members (and beyond) that require no surgery. Goals: read/write to 16+ independent channels in a 16mm³ brain volume in under 50 milliseconds. Sub-millimeter spatial and temporal precision rivaling implanted electrodes, but wearable, portable, and scalable to populations. Technologies explicitly pursued (per DARPA and funded teams): - Neurogenetics: Genetically engineering neurons to express light-sensitive proteins (optogenetics) for infrared or light-based control. - Nanoscale engineering: Nanotransducers, nanoparticles, aerosolized nanomaterials that cross the blood-brain barrier when inhaled or injected non-surgically. These act as implantable electrodes/sensors/transmitters without scalpels. - Infrared sensing & light: Near-infrared beams to read/write neural activity through skull/scalp. - Ultrasound & acoustics: Focused ultrasound to guide signals or stimulate neurons. - Electromagnetics & RF: Pulsed fields for non-invasive modulation. - Minutely invasive track: Temporary nano-transducers delivered without surgery. Funded teams (2019, millions each): - Battelle Memorial Institute - Carnegie Mellon University (Pulkit Grover et al., $19M+) - Johns Hopkins University Applied Physics Lab - Palo Alto Research Center (PARC) - Rice University - Teledyne Scientific These are not fringe labs. These are core defense contractors and elite universities building the future of thought-controlled drones, instant team cognition, "active cyber defense" via brain links, and unstated population scale neural influence. The Video You Just Watched Ties Directly In: Historical RF/microwave mind control research (Moscow Signal era) showing decades of precedent. The U.S. Embassy in Moscow was irradiated with microwaves 1953-1976. Result: cancers, blood disorders, neurological issues in ambassadors and staff. U.S. responded with its own programs (PANDORA, BIZARRE) exploring behavioral effects of modulated RF. This is the foundation N3 builds upon... now refined to nanoscale precision. From MKULTRA to N3 and Beyond: - 1950s-1970s: CIA MKULTRA, OPERATION ARTICHOKE - LSD, hypnosis, electroshock, sensory deprivation on unwitting citizens. Parallel DoD RF studies on embassy staff and primates. - Moscow Signal: Soviets beamed microwaves at U.S. diplomats. U.S. studied effects secretly while developing countermeasures/weapons. - 1980s-2000s: Continued classified neuro-weapons research (memory modulation, crowd control via EM). - 2010s-Now: N3 + related programs (INI - Intelligent Neural Interfaces, NESD, SUBNETS, etc.). Public "for soldiers" framing hides dual-use: offensive neurowarfare, surveillance, behavioral modification. Key Players Exposed: - DARPA Biological Technologies Office - Architects. - Program Managers: like Al Emondi (N3). - Advisers like Dr. James Giordano (public admissions on nanoscale brain disruption as weapons). - Contractors: Battelle, Teledyne, PARC (Xerox), universities weaponizing academia. - Overarching: U.S. DoD, with likely Five Eyes/ international partners. Private sector bleed-over (Neuralink et al. are the civilian cover story). This is not "for veterans" or "helping paralyzed people." Primary focus: able-bodied warfighters for superhuman command of swarms, instant intel fusion, thought-speed hacking. Civilian applications = total surveillance/control. Nanoparticles can be aerosolized; breathed in unknowingly. They lodge in brain tissue and turn neurons into transceivers. Infrared/light can then read thoughts in real-time or write commands (insert images, emotions, "voices," behavioral urges). Combine with 5G/6G terahertz networks for remote activation. Genetic edits make brains "compatible" at population scale. This enables: - Remote mind reading (thought surveillance). - Behavior modification without consent. - "Havana Syndrome" on steroids... targeted neurological disruption. - End of privacy of thought. End of free will as we define it, as professed by Yuval Noah Harari at the World Economic Forum (WEF). - Weaponized neuroscience: neurowarfare where enemies "decide" to surrender via neural influence. WE NEED to be Demanding Answers for RIGHT NOW, or You, Your Children, Loved Ones, Friends, Family, you name it... Will not exist in the next 3-5 years, this is OPEN GENOCIDE on populations globally. The Georgia guidestones are starting to make a bit more sense now arent they? I won't even bother diving down the rabbit hole of how the real true genuine numbed of souls in this world was around the 730m, about 2 years ago... So that number is now much likely to be closer to around 660m. They are speeding up their human eradication plans, because they don't wish to be held accountable for their heinous, generational, outright satanic crimes that they have committed, are committing and will continue to commit to... If we fail to awaken to what is happening around us, and if we fail to stand together with courage, discernment, and unity, we risk surrendering the future of our species to forces that thrive on division, distraction, and indifference. This is not a work of fiction. This is not a screenplay. This is not a distant possibility reserved for some imagined future. This is REAL LIFE. AND THESE ARE REAL PEOPLE that are affected by the systems, institutions, incentives, and decisions that shape the world around us every single day. Throughout history, countless men, women, and children have suffered under structures that viewed human beings not as sacred and sovereign individuals, but as resources to be managed, exploited, controlled, or discarded. The question before us is whether we will remain passive observers, or whether we will choose to become informed, engaged, and united in defense of human dignity, freedom, and the future we leave to those who come after us. The time to pay attention is NOW! When did N3 achieve operational capability? 2020s? Earlier in black programs? How many citizens worldwide have already received nanotransducers via vaccines, aerosols, food/water, or "shedding"? Which governments/contractors are deploying this against their own populations for "social control"? Why the secrecy if it's purely benevolent? Giordano and others have admitted weaponization potential, What if the greatest illusion ever sold was not a product, a policy, or a political movement, but the belief that power is fully accountable to the people it governs? We are told that rights are sacred. We are told that laws apply equally to all. We are told that institutions exist to protect the public. Yet throughout history, countless examples reveal a different reality. Those entrusted with authority have often violated the very principles they were sworn to uphold. Too often, power protects itself. Too often, wealth purchases influence. Too often, those responsible for the consequences of their decisions remain insulated from the suffering those decisions create. This is not a condemnation of every individual within every institution. It is an observation about a recurring pattern throughout human history. When power becomes concentrated, accountability diminishes and when accountability diminishes, corruption flourishes. The challenge before humanity is not merely to replace one group with another... It is to create a society in which truth matters more than propaganda, principles matter more than profit, and human dignity matters more than power. A free society cannot survive on blind trust alone. It requires informed citizens willing to question, investigate, challenge authority, and hold every institution to the standards it claims to represent. The future belongs to those who refuse to surrender their capacity for independent thought. WE MUST EDUCATE OURSELVES. There comes a moment in every human life when the identities we have inherited, the assumptions we have accepted, and the countless narratives imposed upon us by family, culture, institutions, and society begin to reveal themselves as incomplete representations of who we truly are. At that moment, a choice presents itself... We may continue moving through life according to expectations that were handed to us by others, or we may begin the far more demanding process of discovering what remains when every borrowed certainty is stripped away. Approach God with complete honesty and without reservation. Abandon the need to appear strong, knowledgeable, spiritually accomplished, or self-sufficient. Speak openly of your confusion, your failures, your fears, your doubts, your exhaustion, your grief, your shortcomings, and your deepest questions. Acknowledge that despite all of humanity's achievements, despite all accumulated knowledge, despite every title, accomplishment, possession, and ambition, there remain mysteries that cannot be conquered through intellect alone... Admit where your own understanding has reached its limits and ask sincerely for wisdom beyond yourself. Then withdraw from distraction and remain present long enough to listen. The modern world has become extraordinarily skilled at monopolizing attention, filling every moment with noise, stimulation, entertainment, conflict, urgency, and endless streams of information that leave little room for contemplation. Yet beneath that noise exists a depth that can only be encountered through stillness. It is often within periods of silence, reflection, prayer, and sincere self-examination that many discover insights, convictions, direction, and understanding that could never have emerged amid constant distraction. What answers arrive may not always come as words. They may arrive as conviction, clarity, intuition, compassion, understanding, or an unmistakable awareness of the next step that must be taken. Understand that you have not become the person you are by accident. Every hardship you have endured has contributed to your formation. Every disappointment has shaped your perspective. Every loss has expanded your capacity for empathy. Every mistake has carried a lesson. Every success has revealed something about your character. Every betrayal, every setback, every period of loneliness, every moment of despair, every obstacle that seemed impossible to overcome, and every occasion upon which life reduced you to your lowest point has participated in the continual process of your becoming. Nothing has been wasted. If you are willing, release the assumptions that have convinced humanity that the sacred must always remain distant, unreachable, and separated from daily existence. Release the belief that truth belongs exclusively to institutions, authorities, hierarchies, or those who claim unique access to the divine. Release the notion that the presence of God is confined to specific locations, specific rituals, specific traditions, or specific individuals. Instead, consider the possibility that the divine presence permeates existence itself, expressing through every dimension of creation, through every act of compassion, through every sincere pursuit of truth, through every expression of love, through every lesson hidden within suffering, and through every living thing that has ever participated in the unfolding story of life. Consider the possibility that God is Not absent from the Human experience but Intimately Present within it, experiencing existence alongside US, sharing in Every Joy, Every sorrow, Every triumph, Every wound, Every question, and Every struggle that has accompanied Humanity from the beginning of recorded history until this present moment. The task before US is therefore Not merely to believe more deeply, but to seek more Honestly, to learn more diligently, to question more courageously, to listen more carefully, to Love More Completely, and to become ever more Aligned with the highest truth we are capable of perceiving. Accept Nothing Less than the Fullest Realization of the purpose for which You were created, and devote Yourself to that pursuit with every faculty of mind, Heart, and Soul that has been entrusted to You. and DO NOTHING LESS. Furthermore, What is the full integration with AI (predictive neural control loops)? How do we detect and neutralize these systems in ourselves and Loved ones? Who ultimately controls the master kill-switch on global neural networks? If thoughts are readable/writable, what remains of "human rights"? Are you already affected? How would you even know? Continue through the comprehensive thread below and explore the interconnected material in its entirety. Each post serves as part of a larger body of research, analysis, observations, and supporting information that cannot be fully understood in isolation. The broader picture emerges only through careful examination of the complete sequence and the relationships between the ideas presented throughout. Take your time. Follow the references. Examine the evidence. Consider competing perspectives. Draw your own conclusions. The deeper you venture into the material, the more context becomes available, allowing individual pieces of information to connect into a far more expansive understanding of the subjects being discussed. This Constitutes Crimes Against Humanity on a Planetary Scale! The desecration of the sovereign mind... the last true sanctuary. SHARE THIS THREAD RELENTLESSLY. Demand full declassification of N3 and all neurotech programs... IMMEDIATELY! Support independent researchers exposing dual-use Psinergy-solafide. Protect your mind: minimize EM exposure, detox protocols (research zeolite, saunas, etc. though incomplete), awareness as first defense, = Cures to cancer and all diseases, FREE BOOKS. The era of invisible tyranny is here. They can read your mind. And they can change it. Will you let them? Or do we rise as sovereign consciousness and shut this down NOW? Check my Page or Reach out to me via DM, to Join Thousands of Readers that have already chosen to Embark on the New, Un-forseen way forward. Get yourself a FREE copy of The Book of God's Grief, and The Book of God's Joy, Repost. Research. Resist. The Future of Humanity Depends on it. Related content for you to look in to: - CMU Team: - Historical Moscow/RF: Search declassified archives on PANDORA project. - Giordano clips and papers widely available. Let me know what you think, and SHARE THIS so that others may too! And if You see This post, Reposted... Click on it, Unpost and then Repost again. The knowledge is now yours. Use it. And if you're not already following Noah B. Price... What the heck are you doing?! I Agape You ALL, 🫂 - Noah B. Price 🤍 🪽 If you possess relevant information, research, documentation, personal experiences, data, or credible sources relating to any of the subjects discussed throughout this thread, please feel free to contribute them. Meaningful progress is often achieved through the collective sharing of knowledge, and thoughtful contributions from others can help expand, refine, challenge, or strengthen our understanding of complex issues. Likewise, if you ever find yourself in need of someone to speak with, whether regarding the material presented here or for any other reason, please do not hesitate to reach out. While I cannot promise an immediate response, I will do my best to reply as soon as circumstances permit and to offer whatever guidance, perspective, or assistance I am able to provide. If You or someone You know is facing significant health challenges, including serious illnesses such as cancer, You are also welcome to reach out. While I do not claim to possess all the answers, I have spent the past 2 decades studying a broad range of subjects related to health, wellness, research, and human biology, and I will gladly share any information, resources, or avenues of investigation that may be worthy of further exploration. No one is meant to carry every burden alone, and there is often value in sharing knowledge, experiences, and perspectives in the sincere hope of helping one another move toward greater understanding, healing, and well-being.

Noah B. Price

20,426 просмотров • 2 месяцев назад