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CHINESE SCIENTIST BUILT A MEMORY SYSTEM THAT WATCHES ITS OWN INDICATORS FOR SIGNS OF DRIFT Most memory systems store facts flat, with no signal for when stored knowledge quietly goes stale. He built four indicators instead: reference frequency, contradiction rate, decay speed, and confidence spread. A memory scoring high... show more

wast3

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A RUSSIAN MATHEMATICIAN BUILT A SYSTEM WHERE MEMORY AND EVAL WORK AS ONE PIPELINE NOT TWO SEPARATE TOOLS Most setups run memory and evaluation as separate systems that never actually talk to each other. He wired them into one loop instead, memory stores every past output, eval scores each one before it gets kept. Anything that scores low never enters memory at all, so nothing weak gets carried into future decisions. High scorers get tagged with the exact eval criteria they passed, not just a raw pass or fail. The next task pulls only memories that passed the same bar it's about to be judged on. See how the two systems feed each other below👇

A RUSSIAN MATHEMATICIAN BUILT A SYSTEM WHERE MEMORY AND EVAL WORK AS ONE PIPELINE NOT TWO SEPARATE TOOLS Most setups run memory and evaluation as separate systems that never actually talk to each other. He wired them into one loop instead, memory stores every past output, eval scores each one before it gets kept. Anything that scores low never enters memory at all, so nothing weak gets carried into future decisions. High scorers get tagged with the exact eval criteria they passed, not just a raw pass or fail. The next task pulls only memories that passed the same bar it's about to be judged on. See how the two systems feed each other below👇

wast3

39,859 Aufrufe • vor 14 Tagen

LEONARDO, also called LEO, was built by researchers at Caltech’s Center for Autonomous Systems and Technologies. Its full name means LEgs ONboARD drOne. The idea is simple but unusual: • Build a small biped robot • Give it drone-style thrust • Use the legs for ground contact • Use the propellers for balance and lift • Combine walking, hopping and flying in one system LEO is basically a hybrid between a walking robot and a flying drone. How it was built: • Two lightweight legs • Three actuated joints in each leg • Four propeller thrusters near the shoulders • A lightweight body • Leg motors for ground movement • Propellers for balance, lift and aerial control • Real-time control software that synchronizes the legs and propellers How it walks: • The legs move the robot forward • The feet touch the ground like a normal biped • The propellers constantly correct balance from above • The robot can stay upright even in unstable situations • The thrust reduces the risk of falling during difficult motions How it flies: • The legs stop being the main locomotion system • The four propellers generate lift • The robot behaves more like a drone • It can take off, fly over obstacles and land back on its legs What makes it different: • It does not walk like a normal humanoid • It does not fly like a normal drone • It blends both systems • The legs handle contact with the ground • The propellers act like fast stabilizers • The control system decides how much help comes from the legs and how much comes from thrust That is why LEO can: • Walk • Hop • Fly over obstacles • Ride a skateboard • Balance on a slackline The key idea is walking with aerial stabilization.

LEONARDO, also called LEO, was built by researchers at Caltech’s Center for Autonomous Systems and Technologies. Its full name means LEgs ONboARD drOne. The idea is simple but unusual: • Build a small biped robot • Give it drone-style thrust • Use the legs for ground contact • Use the propellers for balance and lift • Combine walking, hopping and flying in one system LEO is basically a hybrid between a walking robot and a flying drone. How it was built: • Two lightweight legs • Three actuated joints in each leg • Four propeller thrusters near the shoulders • A lightweight body • Leg motors for ground movement • Propellers for balance, lift and aerial control • Real-time control software that synchronizes the legs and propellers How it walks: • The legs move the robot forward • The feet touch the ground like a normal biped • The propellers constantly correct balance from above • The robot can stay upright even in unstable situations • The thrust reduces the risk of falling during difficult motions How it flies: • The legs stop being the main locomotion system • The four propellers generate lift • The robot behaves more like a drone • It can take off, fly over obstacles and land back on its legs What makes it different: • It does not walk like a normal humanoid • It does not fly like a normal drone • It blends both systems • The legs handle contact with the ground • The propellers act like fast stabilizers • The control system decides how much help comes from the legs and how much comes from thrust That is why LEO can: • Walk • Hop • Fly over obstacles • Ride a skateboard • Balance on a slackline The key idea is walking with aerial stabilization.

Techniahqrobot | humanoid robots

135,515 Aufrufe • vor 1 Monat

A CHINESE GUY PUT 4 MINISFORUM MS-S1 MAX MINI PCs IN HIS BEDROOM AND TURNED THEM INTO A 24/7 AI AGENT CLUSTER. TOTAL POWER BILL: ABOUT $44/MO. each box is a tiny local AI workstation built around the Ryzen AI Max+ 395. around $3,000 per unit gets him 128GB of unified memory, 2TB storage, dual 10GbE, and up to roughly 96GB usable as VRAM on Linux. one MS-S1 Max can already run serious open models without touching the cloud. Qwen3-Coder 30B for fast coding, Llama 3.3 70B for heavier reasoning, and larger research models overnight when speed matters less than free inference. four boxes in one room changes the whole game. he is not opening a chatbot, paying for every loop, or shutting agents down before sleep. this is private infrastructure that keeps working even when he is offline. the agents can sort inboxes, review code, summarize documents, monitor feeds, prep meetings, and read papers overnight. on cloud APIs, that kind of always-on stack can easily burn $800 to $1,200 a month if used aggressively. his setup is roughly a $12,000 hardware spend, but the monthly cost is basically electricity. a rack, a switch, a NAS, a small monitor, and four tiny MS-S1 Max boxes turning a bedroom corner into a private inference factory. this is what AI looks like when it stops being rented and starts becoming something you own.

A CHINESE GUY PUT 4 MINISFORUM MS-S1 MAX MINI PCs IN HIS BEDROOM AND TURNED THEM INTO A 24/7 AI AGENT CLUSTER. TOTAL POWER BILL: ABOUT $44/MO. each box is a tiny local AI workstation built around the Ryzen AI Max+ 395. around $3,000 per unit gets him 128GB of unified memory, 2TB storage, dual 10GbE, and up to roughly 96GB usable as VRAM on Linux. one MS-S1 Max can already run serious open models without touching the cloud. Qwen3-Coder 30B for fast coding, Llama 3.3 70B for heavier reasoning, and larger research models overnight when speed matters less than free inference. four boxes in one room changes the whole game. he is not opening a chatbot, paying for every loop, or shutting agents down before sleep. this is private infrastructure that keeps working even when he is offline. the agents can sort inboxes, review code, summarize documents, monitor feeds, prep meetings, and read papers overnight. on cloud APIs, that kind of always-on stack can easily burn $800 to $1,200 a month if used aggressively. his setup is roughly a $12,000 hardware spend, but the monthly cost is basically electricity. a rack, a switch, a NAS, a small monitor, and four tiny MS-S1 Max boxes turning a bedroom corner into a private inference factory. this is what AI looks like when it stops being rented and starts becoming something you own.

Gipp 🦅

24,836 Aufrufe • vor 2 Monaten

Anthropic didn't build his memory system. He built it himself, and what you're looking at is the proof. Same source, no gatekeeping. The Obsidian CEO published it, anyone can install it. That's not a screensaver on his second monitor. It's his vault. Every point of light is a note. Every cluster is a project his AI already understands without being told again. He doesn't even touch the keyboard to move through it. One hand up, and the whole cluster tilts and spins, like he's turning a globe that happens to be his own head. A year ago he opened a new AI tab every morning and explained himself from scratch. Who he is, what he's building, what he wants. 200+ hours a year, just re-introducing himself to a machine. Then he stopped writing prompts and started writing one file instead. It loaded before every session. His goals, his projects, his blind spots. Claude read it first, every time, without asking. Now the cluster on that screen keeps growing on its own. New notes link themselves. Nothing gets explained twice. He's not showing off code. He's showing off the machine that finally stopped forgetting him.

Anthropic didn't build his memory system. He built it himself, and what you're looking at is the proof. Same source, no gatekeeping. The Obsidian CEO published it, anyone can install it. That's not a screensaver on his second monitor. It's his vault. Every point of light is a note. Every cluster is a project his AI already understands without being told again. He doesn't even touch the keyboard to move through it. One hand up, and the whole cluster tilts and spins, like he's turning a globe that happens to be his own head. A year ago he opened a new AI tab every morning and explained himself from scratch. Who he is, what he's building, what he wants. 200+ hours a year, just re-introducing himself to a machine. Then he stopped writing prompts and started writing one file instead. It loaded before every session. His goals, his projects, his blind spots. Claude read it first, every time, without asking. Now the cluster on that screen keeps growing on its own. New notes link themselves. Nothing gets explained twice. He's not showing off code. He's showing off the machine that finally stopped forgetting him.

Superior

108,125 Aufrufe • vor 1 Monat

What happens when you stop guessing and let machine learning read the market for you? $2.2M in 4 months. ilovecircle built something different on Polymarket. Not a speed bot. Not a spread farmer. An AI system that actually thinks. 1,347 predictions. 74% win rate. Biggest single hit: $258.4K. Current positions: basically zero he extracted everything. The setup: 10 machine learning models running in parallel, each trained on news feeds and social media data. They don't predict events they predict when the crowd is wrong about probabilities. Market prices an outcome at 50 cents. His ensemble says the real odds are 60%. That gap is the trade. Every week the models retrain themselves on fresh data. The edge evolves because the system never stops learning. Most traders react to headlines. This wallet front runs the market's understanding of what headlines actually mean. 51K people watching now. Most still think AI trading is a scam until they see a curve like this. → Following wallets that run AI-powered probability models is simpler with PMX.

What happens when you stop guessing and let machine learning read the market for you? $2.2M in 4 months. ilovecircle built something different on Polymarket. Not a speed bot. Not a spread farmer. An AI system that actually thinks. 1,347 predictions. 74% win rate. Biggest single hit: $258.4K. Current positions: basically zero he extracted everything. The setup: 10 machine learning models running in parallel, each trained on news feeds and social media data. They don't predict events they predict when the crowd is wrong about probabilities. Market prices an outcome at 50 cents. His ensemble says the real odds are 60%. That gap is the trade. Every week the models retrain themselves on fresh data. The edge evolves because the system never stops learning. Most traders react to headlines. This wallet front runs the market's understanding of what headlines actually mean. 51K people watching now. Most still think AI trading is a scam until they see a curve like this. → Following wallets that run AI-powered probability models is simpler with PMX.

Carver

13,072 Aufrufe • vor 6 Monaten

#MulaneyReads Read “The Remembered Soldier” by Anjet Danjee. I have been really into novels and poems about the First World War (and its aftermath) since I first read Wilfred Owen and Siegfried Sassoon in high school. Memoirs like “Goodbye to All That” by Robert Graves and the Pat Barker “Regeneration” trilogy, as well as Sebastian Faulk’s amazing “Birdsong” have been favorites of mine for years. So much powerful and existential writing came out of that early 20th century nightmare. “The Remembered Soldier” is a brilliant addition to that group. A soldier named Noon has spent four years at a hospital since he was discovered wandering the trenches with no memory of who he is. Then one day a woman arrives and says she is his wife. He leaves with her and we watch two people figure out how to be married after a war wiped away all of their history. It’s a knockout. Buy it wherever books are sold.

#MulaneyReads Read “The Remembered Soldier” by Anjet Danjee. I have been really into novels and poems about the First World War (and its aftermath) since I first read Wilfred Owen and Siegfried Sassoon in high school. Memoirs like “Goodbye to All That” by Robert Graves and the Pat Barker “Regeneration” trilogy, as well as Sebastian Faulk’s amazing “Birdsong” have been favorites of mine for years. So much powerful and existential writing came out of that early 20th century nightmare. “The Remembered Soldier” is a brilliant addition to that group. A soldier named Noon has spent four years at a hospital since he was discovered wandering the trenches with no memory of who he is. Then one day a woman arrives and says she is his wife. He leaves with her and we watch two people figure out how to be married after a war wiped away all of their history. It’s a knockout. Buy it wherever books are sold.

John Mulaney

101,999 Aufrufe • vor 7 Monaten

HTML Artifacts are a big part of how I work with agents now. Artifacts can be more than just static files. When combined with agents, they can take action or help you take action. This unlocks all kinds of interesting ways to work with agents. This is clearly the future. Check out this writing and scheduler artifact I built in a few minutes. It uses a bit of HTML and JS. All the data is in markdown (Obsidian vaults), so the agent can access and modify it at any time. No DB needed. No sophisticated functionalities. The agent decides all that for me based on the skills, context, and memory it has access to. The best part about this simple stack is that all the important information stays with me. This has allowed me to build a recursive self-improving system and automations that can better tap into coding agents like Codex or Claude Code. I could have paid or built an entire app for scheduling posts, and there are so many of them out there. But I don't need to. I've realized a simple artifact does the job. And the simplicity of it is actually an advantage. Very little maintenance for very high returns on personalization, time, and efficiency. The other benefit of this is that I can add features as I please. That level of personalization feels magical, and we should all be pursuing more of it. All of this just keeps compounding. Of course, this example is just about writing. But I have similar artifacts for research, design, experimentation, evaluation, and so much more. And no, I didn't actually publish the post example I shared in the clip. It was just for demonstration purposes. I actually spend more time than this when writing together with agents. Lastly, having built my own agent orchestrator tool has made me realize that simplifying the tool stack is a superpower. If you are curious about how all this works, I will do a live session next week:

HTML Artifacts are a big part of how I work with agents now. Artifacts can be more than just static files. When combined with agents, they can take action or help you take action. This unlocks all kinds of interesting ways to work with agents. This is clearly the future. Check out this writing and scheduler artifact I built in a few minutes. It uses a bit of HTML and JS. All the data is in markdown (Obsidian vaults), so the agent can access and modify it at any time. No DB needed. No sophisticated functionalities. The agent decides all that for me based on the skills, context, and memory it has access to. The best part about this simple stack is that all the important information stays with me. This has allowed me to build a recursive self-improving system and automations that can better tap into coding agents like Codex or Claude Code. I could have paid or built an entire app for scheduling posts, and there are so many of them out there. But I don't need to. I've realized a simple artifact does the job. And the simplicity of it is actually an advantage. Very little maintenance for very high returns on personalization, time, and efficiency. The other benefit of this is that I can add features as I please. That level of personalization feels magical, and we should all be pursuing more of it. All of this just keeps compounding. Of course, this example is just about writing. But I have similar artifacts for research, design, experimentation, evaluation, and so much more. And no, I didn't actually publish the post example I shared in the clip. It was just for demonstration purposes. I actually spend more time than this when writing together with agents. Lastly, having built my own agent orchestrator tool has made me realize that simplifying the tool stack is a superpower. If you are curious about how all this works, I will do a live session next week:

elvis

18,374 Aufrufe • vor 3 Monaten

According to the Book of Ezekiel, he was standing by the river Chebar when a storm cloud approached, filled with fire, brightness, and something metallic looking. Inside it were four living beings, each with four faces and four wings, moving in perfect coordination. Beside them were wheels within wheels that sparkled like beryl and could move in any direction without turning. The entire structure moved with intelligence and purpose. Ezekiel was very clear that this was not symbolic to him. It was something he saw. Check out this line in the text. “As I looked, I saw a windstorm coming out of the north, an immense cloud with flashing lightning and surrounded by brilliant light. The center of the fire looked like glowing metal.” He also says the wheels were “full of eyes all around,” which many experts try to say is a metaphor, but the language reads like observation. The beings moved, stopped, rose, and descended together, as if part of a single system. Above them was a platform that looked like crystal, and above that a throne like sapphire, with a figure that appeared human but radiant and overpowering. Ezekiel collapses afterward, clearly shaken. So what was this. The traditional explanation is that Ezekiel saw God and angelic beings. I'm not so sure. This could describe advanced beings using technology that an ancient person had no language for. It could be interdimensional entities appearing through a controlled interface. It could be a non human intelligence operating some kind of vehicle or system. Some people even say a breakaway civilization that existed alongside early humanity and later vanished. Whatever it was, to me Ezekiel described machinery, movement, structure, something solid and real. What was it?

According to the Book of Ezekiel, he was standing by the river Chebar when a storm cloud approached, filled with fire, brightness, and something metallic looking. Inside it were four living beings, each with four faces and four wings, moving in perfect coordination. Beside them were wheels within wheels that sparkled like beryl and could move in any direction without turning. The entire structure moved with intelligence and purpose. Ezekiel was very clear that this was not symbolic to him. It was something he saw. Check out this line in the text. “As I looked, I saw a windstorm coming out of the north, an immense cloud with flashing lightning and surrounded by brilliant light. The center of the fire looked like glowing metal.” He also says the wheels were “full of eyes all around,” which many experts try to say is a metaphor, but the language reads like observation. The beings moved, stopped, rose, and descended together, as if part of a single system. Above them was a platform that looked like crystal, and above that a throne like sapphire, with a figure that appeared human but radiant and overpowering. Ezekiel collapses afterward, clearly shaken. So what was this. The traditional explanation is that Ezekiel saw God and angelic beings. I'm not so sure. This could describe advanced beings using technology that an ancient person had no language for. It could be interdimensional entities appearing through a controlled interface. It could be a non human intelligence operating some kind of vehicle or system. Some people even say a breakaway civilization that existed alongside early humanity and later vanished. Whatever it was, to me Ezekiel described machinery, movement, structure, something solid and real. What was it?

Jason Wilde

21,394 Aufrufe • vor 6 Monaten

🚨 BREAKING: MIT researchers just built a quantum sensor that can measure multiple properties at once. That matters more than it sounds. Most solid-state quantum sensors have to measure things one by one: magnetic field, temperature, strain, frequency, phase. But reality doesn’t wait its turn. MIT used entangled qubits inside a diamond defect to measure multiple signal properties in a single shot. Read that again. This means Faster measurements Less error from repeating experiments Better sensing inside complex systems like materials and living cells The wild part? They did it at room temperature. Not in some ultra-cold, impractical lab-only setup. In a platform that could actually matter for real-world sensing. Inside a tiny defect in diamond, quantum correlations were used to pull out: amplitude frequency detuning phase all from the same measurement. That’s a big shift. Because the future of quantum tech isn’t just quantum computers. It’s quantum devices that can see more of reality at once. So the real question is When sensors stop measuring one thing at a time… how much of the hidden structure of matter becomes visible? Follow me for more physics breakthroughs that actually matter.

🚨 BREAKING: MIT researchers just built a quantum sensor that can measure multiple properties at once. That matters more than it sounds. Most solid-state quantum sensors have to measure things one by one: magnetic field, temperature, strain, frequency, phase. But reality doesn’t wait its turn. MIT used entangled qubits inside a diamond defect to measure multiple signal properties in a single shot. Read that again. This means Faster measurements Less error from repeating experiments Better sensing inside complex systems like materials and living cells The wild part? They did it at room temperature. Not in some ultra-cold, impractical lab-only setup. In a platform that could actually matter for real-world sensing. Inside a tiny defect in diamond, quantum correlations were used to pull out: amplitude frequency detuning phase all from the same measurement. That’s a big shift. Because the future of quantum tech isn’t just quantum computers. It’s quantum devices that can see more of reality at once. So the real question is When sensors stop measuring one thing at a time… how much of the hidden structure of matter becomes visible? Follow me for more physics breakthroughs that actually matter.

TheNewPhysics

23,131 Aufrufe • vor 4 Monaten

$Somewhere around sixty you get handed a new set of instructions. Lift lighter. Keep the reps high. Do not tax yourself too much. Put the saved effort into cardio. It is the exact reverse of what an ageing body needs, and the people handing it out have the mechanism sitting right in front of them. Recovery gets worse with age. Nobody argues with that. The older body clears fatigue more slowly, repairs more slowly, and tolerates far less accumulated work before progress stops entirely. Every GP, every physio, every trainer will nod along to that sentence. Then watch what gets prescribed on the back of it. High reps. Long burning sets. Circuits. Three sessions of cardio stacked on top. A protocol whose main product is fatigue, given to the person with the least capacity left to absorb any. They identified a recovery problem and prescribed more recovery cost. The answer runs the other way and it is not complicated. If your recovery budget has shrunk, you spend it on whatever returns the most growth per unit of fatigue, and that is a heavy set of five. Four to six reps, a handful of lifts, three minutes between sets, done inside the hour. Nearly every rep is a growth rep. Almost nothing goes on the burning, the sweating and the gasping, which build nothing at all and then bill you for four days. Twenty-five reps taken to failure is a fortnight of fatigue for a fraction of the stimulus. That is not the cautious option for a sixty-five-year-old. It is the most reckless thing on the timetable. Now the part that actually matters. Ageing is not one process. It is a list. Muscle wastes. Bone thins. Tendon softens. The fast fibres that catch you when the pavement arrives early vanish first while the slow ones sit there in perfect health. Motor units drop out. The nervous system stops asking for full effort because nothing has demanded full effort in fifteen years. Read that list back and tell me what heavy resistance training does. It builds muscle. It loads bone, which is the only language bone speaks. It stiffens tendon. It recruits the fast fibres, because that is what heavy means physiologically and there is no other route in. It forces the nervous system to ask for everything again. Every item on the list of what ageing takes is on the list of what a heavy set gives back. Nothing else on earth does that. Not a walk, not a class, not a pill, not twenty minutes on a machine with the paper open. You were told to go gently because somebody quietly decided you were finishing. Go heavy, because you are not.$

Somewhere around sixty you get handed a new set of instructions. Lift lighter. Keep the reps high. Do not tax yourself too much. Put the saved effort into cardio. It is the exact reverse of what an ageing body needs, and the people handing it out have the mechanism sitting right in front of them. Recovery gets worse with age. Nobody argues with that. The older body clears fatigue more slowly, repairs more slowly, and tolerates far less accumulated work before progress stops entirely. Every GP, every physio, every trainer will nod along to that sentence. Then watch what gets prescribed on the back of it. High reps. Long burning sets. Circuits. Three sessions of cardio stacked on top. A protocol whose main product is fatigue, given to the person with the least capacity left to absorb any. They identified a recovery problem and prescribed more recovery cost. The answer runs the other way and it is not complicated. If your recovery budget has shrunk, you spend it on whatever returns the most growth per unit of fatigue, and that is a heavy set of five. Four to six reps, a handful of lifts, three minutes between sets, done inside the hour. Nearly every rep is a growth rep. Almost nothing goes on the burning, the sweating and the gasping, which build nothing at all and then bill you for four days. Twenty-five reps taken to failure is a fortnight of fatigue for a fraction of the stimulus. That is not the cautious option for a sixty-five-year-old. It is the most reckless thing on the timetable. Now the part that actually matters. Ageing is not one process. It is a list. Muscle wastes. Bone thins. Tendon softens. The fast fibres that catch you when the pavement arrives early vanish first while the slow ones sit there in perfect health. Motor units drop out. The nervous system stops asking for full effort because nothing has demanded full effort in fifteen years. Read that list back and tell me what heavy resistance training does. It builds muscle. It loads bone, which is the only language bone speaks. It stiffens tendon. It recruits the fast fibres, because that is what heavy means physiologically and there is no other route in. It forces the nervous system to ask for everything again. Every item on the list of what ageing takes is on the list of what a heavy set gives back. Nothing else on earth does that. Not a walk, not a class, not a pill, not twenty minutes on a machine with the paper open. You were told to go gently because somebody quietly decided you were finishing. Go heavy, because you are not.

Sama Hoole

16,526 Aufrufe • vor 24 Tagen

THAT $70 "RUN YOUR OWN LLMS" PI KIT CAN'T RUN A SINGLE LLM. IT'S A VISION CHIP WITH NO RAM. that clip sells a raspberry pi 5 in a slick case with an ai accelerator and the caption "your own llms." clean build, fun kit. the claim is where it breaks. the fine print: the popular $70 pi ai kit uses a hailo-8l, 13 tops. it's built for vision, object detection and image processing, and it has no memory of its own. so it cannot run large language models. full stop the board that actually can is a different one: the newer ai hat+ 2, hailo-10h, 40 tops, with 8gb of dedicated ram. that's $130, not $70 and even that runs only tiny models. llama 3.2 at 1b, qwen 2.5 at 1.5b, deepseek r1 at 1.5b. edge llms live in the 1-7b range, against cloud models at 500b to 2 trillion so the honest pitch: for $130 you can run a very small language model on a pi, slowly, as a fun learning project. that's real and it's cool. "your own llms" on a $70 vision kit is not. why this keeps happening: "ai kit" and a big "tops" number sell. tops sounds like intelligence. but tops measures vision-style math, not whether the chip has the memory to hold a language model. the spec that matters for llms is ram, and the cheap kit has none. the honest caveats, both ways: the $70 kit is genuinely great, just at vision. cameras, object detection, that's its job the $130 hat really does run small llms locally, which a pi couldn't do at all two years ago. that's progress "small" is the load-bearing word. don't expect gpt at home on a pi the takeaway: before you buy a kit because the caption says llm, check two numbers. not the tops. the ram, and the size of the model it can actually load. no 70-dollar miracle, no gpt in a pi case, no tops number that means what you think. save this before you buy the wrong kit for the word on the box.

THAT $70 "RUN YOUR OWN LLMS" PI KIT CAN'T RUN A SINGLE LLM. IT'S A VISION CHIP WITH NO RAM. that clip sells a raspberry pi 5 in a slick case with an ai accelerator and the caption "your own llms." clean build, fun kit. the claim is where it breaks. the fine print: the popular $70 pi ai kit uses a hailo-8l, 13 tops. it's built for vision, object detection and image processing, and it has no memory of its own. so it cannot run large language models. full stop the board that actually can is a different one: the newer ai hat+ 2, hailo-10h, 40 tops, with 8gb of dedicated ram. that's $130, not $70 and even that runs only tiny models. llama 3.2 at 1b, qwen 2.5 at 1.5b, deepseek r1 at 1.5b. edge llms live in the 1-7b range, against cloud models at 500b to 2 trillion so the honest pitch: for $130 you can run a very small language model on a pi, slowly, as a fun learning project. that's real and it's cool. "your own llms" on a $70 vision kit is not. why this keeps happening: "ai kit" and a big "tops" number sell. tops sounds like intelligence. but tops measures vision-style math, not whether the chip has the memory to hold a language model. the spec that matters for llms is ram, and the cheap kit has none. the honest caveats, both ways: the $70 kit is genuinely great, just at vision. cameras, object detection, that's its job the $130 hat really does run small llms locally, which a pi couldn't do at all two years ago. that's progress "small" is the load-bearing word. don't expect gpt at home on a pi the takeaway: before you buy a kit because the caption says llm, check two numbers. not the tops. the ram, and the size of the model it can actually load. no 70-dollar miracle, no gpt in a pi case, no tops number that means what you think. save this before you buy the wrong kit for the word on the box.

RetroChainer

11,100 Aufrufe • vor 1 Monat

Elon Musk just told you exactly how America loses. Not to a better algorithm. Not to a smarter engineer. To itself. Elon Musk: “When you’re dealing with the government, common sense doesn’t make sense. It’s like arguing with the DMV. It’s impossible.” America split the atom, put men on the moon, and built the internet. It is now losing a civilization-defining race because it cannot get out of its own way. Not because the talent is gone. Not because the capital dried up. Because we built a machine that processes instead of builds. Every decision climbs ten levels. Every level costs a meeting. Every meeting births a committee. Every committee buries the idea in a report. And somewhere in that report, the urgency dies. This is not bureaucracy as inefficiency. This is bureaucracy as a national security threat. China does not debate internally. Beijing does not convene committee reviews. They identify the objective. They resource it. They execute. While America is still scheduling the kickoff call, China is pouring concrete. Look at what Musk built. SpaceX landed an orbital rocket booster in eleven years. NASA has five times the budget and cannot get astronauts home. Tesla scaled a global manufacturing operation while legacy automakers were forming task forces to study the transition. xAI stood up one of the most powerful supercomputers on earth in 122 days. Not years. Not after the third approval cycle. 122 days. The difference is not money. The difference is not genius. The difference is that Musk runs his companies the way civilizations used to run themselves when they still believed impossible things were worth attempting. Flat. Fast. Ruthless about what matters. No ten layers of sign-off. No thirty-person approval chain for a decision one person should make. No process worship dressed up as due diligence. A small group of exceptional people. A clear mission. The authority to execute without asking permission. That model built the moon landing. It built the transcontinental railroad. It built every institution America now holds up as proof of what this country can do. Then we forgot how to run it. We replaced builders with administrators. We replaced decisions with processes. We replaced urgency with compliance theater. And now we are asking that bloated machine to win the most consequential technological race in human history. The AI war is not being fought in the code. It is being fought in the gap between when a builder decides to move and when the institution permits it. That gap is where civilizations end. America does not have a talent problem. America does not have a capital problem. America has a bureaucracy problem. And nobody inside that bureaucracy has a single incentive to fix it. Musk is not fighting China. He is fighting the version of America that forgot how to move. The country that pours the concrete first does not just win the race. It writes the rules everyone else spends the next century living under.

Elon Musk just told you exactly how America loses. Not to a better algorithm. Not to a smarter engineer. To itself. Elon Musk: “When you’re dealing with the government, common sense doesn’t make sense. It’s like arguing with the DMV. It’s impossible.” America split the atom, put men on the moon, and built the internet. It is now losing a civilization-defining race because it cannot get out of its own way. Not because the talent is gone. Not because the capital dried up. Because we built a machine that processes instead of builds. Every decision climbs ten levels. Every level costs a meeting. Every meeting births a committee. Every committee buries the idea in a report. And somewhere in that report, the urgency dies. This is not bureaucracy as inefficiency. This is bureaucracy as a national security threat. China does not debate internally. Beijing does not convene committee reviews. They identify the objective. They resource it. They execute. While America is still scheduling the kickoff call, China is pouring concrete. Look at what Musk built. SpaceX landed an orbital rocket booster in eleven years. NASA has five times the budget and cannot get astronauts home. Tesla scaled a global manufacturing operation while legacy automakers were forming task forces to study the transition. xAI stood up one of the most powerful supercomputers on earth in 122 days. Not years. Not after the third approval cycle. 122 days. The difference is not money. The difference is not genius. The difference is that Musk runs his companies the way civilizations used to run themselves when they still believed impossible things were worth attempting. Flat. Fast. Ruthless about what matters. No ten layers of sign-off. No thirty-person approval chain for a decision one person should make. No process worship dressed up as due diligence. A small group of exceptional people. A clear mission. The authority to execute without asking permission. That model built the moon landing. It built the transcontinental railroad. It built every institution America now holds up as proof of what this country can do. Then we forgot how to run it. We replaced builders with administrators. We replaced decisions with processes. We replaced urgency with compliance theater. And now we are asking that bloated machine to win the most consequential technological race in human history. The AI war is not being fought in the code. It is being fought in the gap between when a builder decides to move and when the institution permits it. That gap is where civilizations end. America does not have a talent problem. America does not have a capital problem. America has a bureaucracy problem. And nobody inside that bureaucracy has a single incentive to fix it. Musk is not fighting China. He is fighting the version of America that forgot how to move. The country that pours the concrete first does not just win the race. It writes the rules everyone else spends the next century living under.

Dustin

32,139 Aufrufe • vor 4 Monaten

BREAKING: Eight days ago the White House paraded Apple as the champion of bringing chips home to America. This week Apple is quietly asking that same White House for permission to buy memory chips from a Chinese company sitting on the Pentagon's military blacklist. The decoupling did not break because anyone lost their nerve. It broke because AI made the chips too expensive to keep choosing sides. Watch the timing, because it is almost too perfect. On June 18, Trump announced an Apple and Intel partnership to build chips on American soil, the poster child for reshoring. Days later the Financial Times revealed Apple had spent over a month lobbying the administration for assurance it could buy DRAM from CXMT, a firm the Pentagon flags for alleged ties to the Chinese military. The same company, the same week, standing on both sides of the line Washington drew. What pushed Apple to the edge was pure cost. AI data centers have swallowed the world's memory supply and prices have rocketed. When Apple finally raised MacBook and iPad prices to cope, investors erased 263 billion dollars from its value in a single trading day, its worst since April of last year. The squeeze became unbearable, so the company went looking for the one supplier everyone else is warned away from. This is the part the chip war never priced in. Decoupling assumed American firms could afford to pick a side. That holds right up until a shortage gets severe enough that picking a side becomes unaffordable, and AI just found that point. The most valuable company on earth would rather approach the blacklist than keep paying the bill. A memory chip shortage did not just raise the price of a laptop. It bent the security policy of the United States until its flagship company walked up to a line it was told never to touch. Scarcity, it turns out, has no flag.

BREAKING: Eight days ago the White House paraded Apple as the champion of bringing chips home to America. This week Apple is quietly asking that same White House for permission to buy memory chips from a Chinese company sitting on the Pentagon's military blacklist. The decoupling did not break because anyone lost their nerve. It broke because AI made the chips too expensive to keep choosing sides. Watch the timing, because it is almost too perfect. On June 18, Trump announced an Apple and Intel partnership to build chips on American soil, the poster child for reshoring. Days later the Financial Times revealed Apple had spent over a month lobbying the administration for assurance it could buy DRAM from CXMT, a firm the Pentagon flags for alleged ties to the Chinese military. The same company, the same week, standing on both sides of the line Washington drew. What pushed Apple to the edge was pure cost. AI data centers have swallowed the world's memory supply and prices have rocketed. When Apple finally raised MacBook and iPad prices to cope, investors erased 263 billion dollars from its value in a single trading day, its worst since April of last year. The squeeze became unbearable, so the company went looking for the one supplier everyone else is warned away from. This is the part the chip war never priced in. Decoupling assumed American firms could afford to pick a side. That holds right up until a shortage gets severe enough that picking a side becomes unaffordable, and AI just found that point. The most valuable company on earth would rather approach the blacklist than keep paying the bill. A memory chip shortage did not just raise the price of a laptop. It bent the security policy of the United States until its flagship company walked up to a line it was told never to touch. Scarcity, it turns out, has no flag.

Shanaka Anslem Perera ⚡

2,191,937 Aufrufe • vor 1 Monat

🚨🌃 MINSK AT NIGHT 🇧🇾 — THE SLAVIC CAPITAL EUROPE PRETENDS NOT TO SEE At night, Minsk reveals something increasingly rare in Europe: order, continuity, and historical confidence. This city is not a coincidence. It is the product of history — and of deliberate choices. Minsk is one of the most destroyed capitals of World War II. More than 80% of the city was wiped out during the German occupation. What followed was not random reconstruction, but a state-led rebuilding project that treated the capital as a symbol of survival, sacrifice, and Slavic endurance. Wide avenues, monumental facades, axial symmetry, and integrated public transport were not aesthetic accidents — they were political statements. The result is a city that still functions according to mid-20th-century urban logic: clarity, scale, and permanence. While many European capitals dismantled their historical cores through privatization, speculation, and “creative destruction,” Minsk preserved a centralized civic structure. Its metro, public spaces, and housing were built to serve residents first — not tourists, investors, or branding agencies. That is precisely why Minsk is controversial. Not because it is chaotic — but because it did not surrender its spatial identity after 1991. For critics, Minsk represents authoritarian stagnation. For supporters, it represents stability and sovereignty. For outsiders, it is uncomfortable because it contradicts the familiar narrative of post-Soviet collapse and disorder. The illuminated metro sign in the night is more than infrastructure. It is a remnant of a time when cities were built as long-term national projects, not short-term economic experiments. The monumental buildings along Independence Avenue are not nostalgia — they are reminders that Belarus chose continuity over rupture. Minsk does not ask to be liked. It does not rebrand itself every decade. It does not apologize for being Eastern, Slavic, or different. And in a Europe increasingly uneasy with history, memory, and statehood, that makes Minsk quietly subversive. These images are not propaganda. They are documentation. And what they document is a capital that still knows what it was built for. ⸻ Slavic Networks Independent coverage of Slavic regions, power, and identity. If you like what we are doing — like, share, subscribe, and invite your friends for more. Follow us also on Facebook: Slavic Networks Nirali VVeles SlavicFreeSpirit

🚨🌃 MINSK AT NIGHT 🇧🇾 — THE SLAVIC CAPITAL EUROPE PRETENDS NOT TO SEE At night, Minsk reveals something increasingly rare in Europe: order, continuity, and historical confidence. This city is not a coincidence. It is the product of history — and of deliberate choices. Minsk is one of the most destroyed capitals of World War II. More than 80% of the city was wiped out during the German occupation. What followed was not random reconstruction, but a state-led rebuilding project that treated the capital as a symbol of survival, sacrifice, and Slavic endurance. Wide avenues, monumental facades, axial symmetry, and integrated public transport were not aesthetic accidents — they were political statements. The result is a city that still functions according to mid-20th-century urban logic: clarity, scale, and permanence. While many European capitals dismantled their historical cores through privatization, speculation, and “creative destruction,” Minsk preserved a centralized civic structure. Its metro, public spaces, and housing were built to serve residents first — not tourists, investors, or branding agencies. That is precisely why Minsk is controversial. Not because it is chaotic — but because it did not surrender its spatial identity after 1991. For critics, Minsk represents authoritarian stagnation. For supporters, it represents stability and sovereignty. For outsiders, it is uncomfortable because it contradicts the familiar narrative of post-Soviet collapse and disorder. The illuminated metro sign in the night is more than infrastructure. It is a remnant of a time when cities were built as long-term national projects, not short-term economic experiments. The monumental buildings along Independence Avenue are not nostalgia — they are reminders that Belarus chose continuity over rupture. Minsk does not ask to be liked. It does not rebrand itself every decade. It does not apologize for being Eastern, Slavic, or different. And in a Europe increasingly uneasy with history, memory, and statehood, that makes Minsk quietly subversive. These images are not propaganda. They are documentation. And what they document is a capital that still knows what it was built for. ⸻ Slavic Networks Independent coverage of Slavic regions, power, and identity. If you like what we are doing — like, share, subscribe, and invite your friends for more. Follow us also on Facebook: Slavic Networks Nirali VVeles SlavicFreeSpirit

Slavic Networks

60,822 Aufrufe • vor 8 Monaten

Obsidian became a neural network with 184,320 links and now runs as the most powerful second brain ever built for $0. 12,480 notes in 1 vault, 0 folders, 0 tabs, and he hasn't opened Notion in 7 months. Every night at 2 AM Claude Code walks the vault, reads all 12,480 notes, embeds them, and hunts for the pairs that should be linked but never were. Last night it found 61 and he accepted all 61. That's the move nobody makes by hand, because 12,480 notes means 77 million possible pairs, and a human links maybe 4 a day while the agent links 61 while he sleeps. Capture takes 2 seconds, a voice memo lands as a note in 1.4, a clip becomes a linked node on its own friction is what kills a second brain so he deleted the friction. Recall latency sits at 38 milliseconds, which means the graph answers before he finishes doubting himself. 36 clusters formed without him, decay score holds at 0.03, and 97% of everything he ever wrote is still reachable, while most people's notes rot past 90% in a year and turn into a graveyard with good search. Yesterday it surfaced 9 forgotten notes, one of them 412 days old, and that one became a product he shipped 48 hours later. Plain .md files on a laptop, no cloud, no subscription, no company that can delete his brain on a Tuesday. The graph doesn't store what he knows. It stores what he'd never have connected alone.

Obsidian became a neural network with 184,320 links and now runs as the most powerful second brain ever built for $0. 12,480 notes in 1 vault, 0 folders, 0 tabs, and he hasn't opened Notion in 7 months. Every night at 2 AM Claude Code walks the vault, reads all 12,480 notes, embeds them, and hunts for the pairs that should be linked but never were. Last night it found 61 and he accepted all 61. That's the move nobody makes by hand, because 12,480 notes means 77 million possible pairs, and a human links maybe 4 a day while the agent links 61 while he sleeps. Capture takes 2 seconds, a voice memo lands as a note in 1.4, a clip becomes a linked node on its own friction is what kills a second brain so he deleted the friction. Recall latency sits at 38 milliseconds, which means the graph answers before he finishes doubting himself. 36 clusters formed without him, decay score holds at 0.03, and 97% of everything he ever wrote is still reachable, while most people's notes rot past 90% in a year and turn into a graveyard with good search. Yesterday it surfaced 9 forgotten notes, one of them 412 days old, and that one became a product he shipped 48 hours later. Plain .md files on a laptop, no cloud, no subscription, no company that can delete his brain on a Tuesday. The graph doesn't store what he knows. It stores what he'd never have connected alone.

Spike 1%

11,546 Aufrufe • vor 5 Tagen

Elon Musk gave the entire entertainment industry its expiration date, and he is the one building the thing that kills it. Musk: “My guess is that we see the first compelling half hour, pure AI show next year.” Next year. A complete show generated entirely by AI. No writers. No actors. No cameras. No sets. No crew. No studio. Just a prompt and enough compute to render a reality that never physically existed. And shows are the easy part. Musk: “I say probably we’re maybe three years away from AI does the whole video game.” A show plays the same way every time. A game has to generate a living world that reacts to every decision in real time across every single frame. That is a fundamentally harder class of problem. And Musk put three years on it. Right now a single AAA title takes seven years and half a billion dollars across thousands of engineers and artists just to ship it. Musk is describing a world where one person types a paragraph and gets something comparable. The entire value proposition of a multi-billion dollar industry lives inside that gap. And it closes in thirty-six months. But the prediction is not the story. The person making it is. This is not an analyst speculating from the sidelines. This is the man building the largest AI compute clusters on the planet. The man who built xAI from zero in under two years. The man stacking hundreds of thousands of GPUs into facilities designed to do exactly what he is describing. When Musk says three years, he is not guessing about what someone else might eventually ship. He is reading you a delivery date off his own roadmap. Every media company on Earth is valued on a single assumption. That quality content is expensive and difficult to produce at scale. That one assumption is the structural foundation underneath every studio, every network, and every publisher in existence. Musk is dismantling it with raw compute. The studios still parading thousand-person production teams are not demonstrating strength. They are advertising the exact cost structure that one person with a prompt and a GPU allocation is about to make irrelevant. And it does not stop at entertainment. If AI can generate an interactive world that responds to human input in real time, it can generate anything. Advertising. Architecture. Training simulations. Product design. Every industry built on humans manually constructing visual experiences frame by frame is sitting on the same countdown Musk just read out loud. Now zoom out. Because this is not just an industry story. For the entire history of human civilization, the distance between imagining a world and actually creating one required thousands of people, millions of hours, and billions of dollars. That distance built Hollywood. That distance built the gaming industry. That distance made content scarce and studios powerful. Musk is collapsing that distance to zero. When the gap between imagining something and it existing disappears, every business model built on the difficulty of creation disappears with it. That is not disruption. That is a full inversion of how human beings create. Musk did not make a casual prediction on that podcast. He told you what he is building. He told you the timeline. And he told you which industries do not survive it. The entertainment industry is still debating whether this future is real. Musk is not part of that debate. He is building. And he just told you the delivery date.

Elon Musk gave the entire entertainment industry its expiration date, and he is the one building the thing that kills it. Musk: “My guess is that we see the first compelling half hour, pure AI show next year.” Next year. A complete show generated entirely by AI. No writers. No actors. No cameras. No sets. No crew. No studio. Just a prompt and enough compute to render a reality that never physically existed. And shows are the easy part. Musk: “I say probably we’re maybe three years away from AI does the whole video game.” A show plays the same way every time. A game has to generate a living world that reacts to every decision in real time across every single frame. That is a fundamentally harder class of problem. And Musk put three years on it. Right now a single AAA title takes seven years and half a billion dollars across thousands of engineers and artists just to ship it. Musk is describing a world where one person types a paragraph and gets something comparable. The entire value proposition of a multi-billion dollar industry lives inside that gap. And it closes in thirty-six months. But the prediction is not the story. The person making it is. This is not an analyst speculating from the sidelines. This is the man building the largest AI compute clusters on the planet. The man who built xAI from zero in under two years. The man stacking hundreds of thousands of GPUs into facilities designed to do exactly what he is describing. When Musk says three years, he is not guessing about what someone else might eventually ship. He is reading you a delivery date off his own roadmap. Every media company on Earth is valued on a single assumption. That quality content is expensive and difficult to produce at scale. That one assumption is the structural foundation underneath every studio, every network, and every publisher in existence. Musk is dismantling it with raw compute. The studios still parading thousand-person production teams are not demonstrating strength. They are advertising the exact cost structure that one person with a prompt and a GPU allocation is about to make irrelevant. And it does not stop at entertainment. If AI can generate an interactive world that responds to human input in real time, it can generate anything. Advertising. Architecture. Training simulations. Product design. Every industry built on humans manually constructing visual experiences frame by frame is sitting on the same countdown Musk just read out loud. Now zoom out. Because this is not just an industry story. For the entire history of human civilization, the distance between imagining a world and actually creating one required thousands of people, millions of hours, and billions of dollars. That distance built Hollywood. That distance built the gaming industry. That distance made content scarce and studios powerful. Musk is collapsing that distance to zero. When the gap between imagining something and it existing disappears, every business model built on the difficulty of creation disappears with it. That is not disruption. That is a full inversion of how human beings create. Musk did not make a casual prediction on that podcast. He told you what he is building. He told you the timeline. And he told you which industries do not survive it. The entertainment industry is still debating whether this future is real. Musk is not part of that debate. He is building. And he just told you the delivery date.

Dustin

22,390 Aufrufe • vor 1 Monat

I told ClawdBot: "build me a 6-agent system for Polymarket that works while I sleep"... 6 hours while i was asleep. Not a single question. Here's what it built: Monitoring agent - runs 24/7, watches Polymarket for mispriced markets. Spots an anomaly - writes to MEMORY md and pings me on Telegram instantly. Research agent - parses news, X, macro data via browser tool on a cron schedule. Every morning I have a full digest on all open positions before I even check my phone. Trading agent - reads the research agent's memory through Gateway, sees the market hasn't reacted yet, acts. Exec tool in gateway mode with a whitelist - no full access on a live server. Watchdog - HEARTBEAT md every 5 minutes: monitoring running, no errors, positions up to date. Something breaks - immediate Telegram message. All of this - one Gateway. One config.json. Isolation via dmScope: per-agent. The token trick: stopped dumping everything into AGENTS md. Critical rules - bootstrap. Try copytrade my bot here: Everything about markets, patterns, past trades - MEMORY md, semantic search pulls it when needed. Token spend dropped 3x, from $0.40/request to $0.13. First week running: - 47 mispriced markets caught before Polymarket adjusted - avg entry edge: 8-12¢ per position - watchdog fired 3 times, caught a broken RPC before it cost me anything The whole system is plain .md text files. Open an editor, change one line - agent behaves differently. No deploy. No build. A bot responds. An agent earns.

I told ClawdBot: "build me a 6-agent system for Polymarket that works while I sleep"... 6 hours while i was asleep. Not a single question. Here's what it built: Monitoring agent - runs 24/7, watches Polymarket for mispriced markets. Spots an anomaly - writes to MEMORY md and pings me on Telegram instantly. Research agent - parses news, X, macro data via browser tool on a cron schedule. Every morning I have a full digest on all open positions before I even check my phone. Trading agent - reads the research agent's memory through Gateway, sees the market hasn't reacted yet, acts. Exec tool in gateway mode with a whitelist - no full access on a live server. Watchdog - HEARTBEAT md every 5 minutes: monitoring running, no errors, positions up to date. Something breaks - immediate Telegram message. All of this - one Gateway. One config.json. Isolation via dmScope: per-agent. The token trick: stopped dumping everything into AGENTS md. Critical rules - bootstrap. Try copytrade my bot here: Everything about markets, patterns, past trades - MEMORY md, semantic search pulls it when needed. Token spend dropped 3x, from $0.40/request to $0.13. First week running: - 47 mispriced markets caught before Polymarket adjusted - avg entry edge: 8-12¢ per position - watchdog fired 3 times, caught a broken RPC before it cost me anything The whole system is plain .md text files. Open an editor, change one line - agent behaves differently. No deploy. No build. A bot responds. An agent earns.

Lunar

165,099 Aufrufe • vor 5 Monaten

🚨 WARNING: SOMETHING EXTREMELY BAD IS COMING ON MONDAY... Four things are breaking at the same time. Interest rate hikes by December is almost confirmed now. Not pauses. Not holds. HIKES. Everything priced on the assumption that cheap money returns just got repriced from scratch. Every leveraged position, every rate-sensitive asset, every model built on a pivot that isn't coming. Japan officially entered yen intervention, that sounds technical. Here's what it means in practice. Japan is burning through reserves defending a currency that's been collapsing for months. And to fund that defense they sell what they own. US Treasuries, at scale, Into a bond market that's already under pressure from every other direction. China hasn't stopped, while everyone was watching Iran and the Fed, China has been quietly and consistently dumping US Treasury holdings for weeks. No announcement, no fanfare. Just steady selling that shows up in the data for anyone paying attention. And the AI rally is dying in real time. The momentum that carried Nvidia, Microsoft, Google, and Meta to valuations that made no fundamental sense is reversing. Funds that loaded up on the AI narrative at the top are now the ones selling into every bounce. The multiple that drove three years of outperformance doesn't survive a rate hike cycle and a liquidity crisis simultaneously. Now put all four together. Rates going up, liquidity going out. The world's two largest foreign Treasury holders selling simultaneously. And the primary growth narrative of the last three years losing believers by the session. When liquidity disappears across multiple layers of the financial system at once markets don't correct. They don't dip, they don't give you a clean exit. They crash fast and they crash hard. Stocks. Bonds. Metals. Crypto. There is no rotation trade that works when everything is being sold to cover everything else. There is no safe haven when the people who need cash are selling whatever has a bid. Insiders are already out, funds are already cutting. The rotation happened this week while retail was still debating whether to buy the dip. By the time Monday's open confirms what's coming it's already too late to position. This sounds SCARY, but I will keep you updated on everything here When I rotate money, I will post my moves here so my FOLLOWERS can SAVE their money Many will regret not following me earlier...

🚨 WARNING: SOMETHING EXTREMELY BAD IS COMING ON MONDAY... Four things are breaking at the same time. Interest rate hikes by December is almost confirmed now. Not pauses. Not holds. HIKES. Everything priced on the assumption that cheap money returns just got repriced from scratch. Every leveraged position, every rate-sensitive asset, every model built on a pivot that isn't coming. Japan officially entered yen intervention, that sounds technical. Here's what it means in practice. Japan is burning through reserves defending a currency that's been collapsing for months. And to fund that defense they sell what they own. US Treasuries, at scale, Into a bond market that's already under pressure from every other direction. China hasn't stopped, while everyone was watching Iran and the Fed, China has been quietly and consistently dumping US Treasury holdings for weeks. No announcement, no fanfare. Just steady selling that shows up in the data for anyone paying attention. And the AI rally is dying in real time. The momentum that carried Nvidia, Microsoft, Google, and Meta to valuations that made no fundamental sense is reversing. Funds that loaded up on the AI narrative at the top are now the ones selling into every bounce. The multiple that drove three years of outperformance doesn't survive a rate hike cycle and a liquidity crisis simultaneously. Now put all four together. Rates going up, liquidity going out. The world's two largest foreign Treasury holders selling simultaneously. And the primary growth narrative of the last three years losing believers by the session. When liquidity disappears across multiple layers of the financial system at once markets don't correct. They don't dip, they don't give you a clean exit. They crash fast and they crash hard. Stocks. Bonds. Metals. Crypto. There is no rotation trade that works when everything is being sold to cover everything else. There is no safe haven when the people who need cash are selling whatever has a bid. Insiders are already out, funds are already cutting. The rotation happened this week while retail was still debating whether to buy the dip. By the time Monday's open confirms what's coming it's already too late to position. This sounds SCARY, but I will keep you updated on everything here When I rotate money, I will post my moves here so my FOLLOWERS can SAVE their money Many will regret not following me earlier...

ᴛʀᴀᴄᴇʀ

169,405 Aufrufe • vor 1 Monat

When a spacecraft leaves Earth, it doesn’t just fire its engines and head straight to its destination. In many missions, especially those going beyond low Earth orbit, there’s a more subtle and elegant strategy at play, one that uses gravity itself as part of the navigation system. This is often called a gravity assist, or a slingshot maneuver. But in the case of missions like #Artemis II, what’s being used is a closely related idea known as a free-return trajectory. At first glance, it might sound simple: the spacecraft goes to the Moon, loops around it, and comes back. But the physics behind it is anything but simple. Instead of relying on continuous propulsion, the spacecraft follows a carefully calculated path through the gravitational field of the Earth–Moon system. It is launched with just the right speed and direction so that, as it approaches the Moon, the Moon’s gravity bends its trajectory. The spacecraft is effectively flung around the Moon, redirected onto a path that naturally brings it back toward Earth. No major engine burn is needed for the return. Small trajectory corrections may still be required, but gravity does the heavy lifting. That’s the key. This kind of trajectory is not just efficient, it’s also safe. If something goes wrong with the spacecraft’s engines or onboard systems, gravity itself ensures the return. It’s an inherent backup plan, built into the trajectory from the very beginning. The same fundamental idea appears in gravity assists used across the Solar System. When a spacecraft flies past a planet, it can gain or lose speed by exchanging momentum with that planet. From the spacecraft’s point of view, it’s as if it has been accelerated without using fuel. In reality, it has borrowed a tiny amount of orbital energy from the planet itself. That’s how missions like Voyager reached the outer planets, and how probes continue to explore regions far beyond what their onboard fuel alone would allow. But there’s an important distinction. An interplanetary gravity assist is typically used to change speed and direction, often increasing the spacecraft’s energy. A free-return trajectory, like the one used in Artemis II, is designed for something more specific: a path that naturally loops back to Earth without requiring additional propulsion. It’s less about gaining energy, and more about shaping a trajectory that guarantees a return. To understand why this works, it helps to stop thinking in straight lines. In space, motion follows curves defined by gravity. The spacecraft is constantly falling, first toward Earth, then toward the Moon, and then back toward Earth again. What looks like a loop is really a continuous free fall through a changing gravitational landscape. This way of navigating space reveals something deeper. We tend to think of engines as the drivers of motion, but once a spacecraft is on its way, gravity does most of the work. The art of spaceflight is not just about thrust. It’s about knowing when not to use it. #GoodLuck #Artemis NASA Artemis

When a spacecraft leaves Earth, it doesn’t just fire its engines and head straight to its destination. In many missions, especially those going beyond low Earth orbit, there’s a more subtle and elegant strategy at play, one that uses gravity itself as part of the navigation system. This is often called a gravity assist, or a slingshot maneuver. But in the case of missions like #Artemis II, what’s being used is a closely related idea known as a free-return trajectory. At first glance, it might sound simple: the spacecraft goes to the Moon, loops around it, and comes back. But the physics behind it is anything but simple. Instead of relying on continuous propulsion, the spacecraft follows a carefully calculated path through the gravitational field of the Earth–Moon system. It is launched with just the right speed and direction so that, as it approaches the Moon, the Moon’s gravity bends its trajectory. The spacecraft is effectively flung around the Moon, redirected onto a path that naturally brings it back toward Earth. No major engine burn is needed for the return. Small trajectory corrections may still be required, but gravity does the heavy lifting. That’s the key. This kind of trajectory is not just efficient, it’s also safe. If something goes wrong with the spacecraft’s engines or onboard systems, gravity itself ensures the return. It’s an inherent backup plan, built into the trajectory from the very beginning. The same fundamental idea appears in gravity assists used across the Solar System. When a spacecraft flies past a planet, it can gain or lose speed by exchanging momentum with that planet. From the spacecraft’s point of view, it’s as if it has been accelerated without using fuel. In reality, it has borrowed a tiny amount of orbital energy from the planet itself. That’s how missions like Voyager reached the outer planets, and how probes continue to explore regions far beyond what their onboard fuel alone would allow. But there’s an important distinction. An interplanetary gravity assist is typically used to change speed and direction, often increasing the spacecraft’s energy. A free-return trajectory, like the one used in Artemis II, is designed for something more specific: a path that naturally loops back to Earth without requiring additional propulsion. It’s less about gaining energy, and more about shaping a trajectory that guarantees a return. To understand why this works, it helps to stop thinking in straight lines. In space, motion follows curves defined by gravity. The spacecraft is constantly falling, first toward Earth, then toward the Moon, and then back toward Earth again. What looks like a loop is really a continuous free fall through a changing gravitational landscape. This way of navigating space reveals something deeper. We tend to think of engines as the drivers of motion, but once a spacecraft is on its way, gravity does most of the work. The art of spaceflight is not just about thrust. It’s about knowing when not to use it. #GoodLuck #Artemis NASA Artemis

Erika 

235,010 Aufrufe • vor 4 Monaten