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vMAP: Vectorised Object Mapping for Neural Field SLAM, new at #CVPR2023! Each object is represented by a separate MLP, optimised in parallel via vectorised training. Full info: Dyson Robotics Lab, Imperial College, Shikun Liu, Marwan Taher, Andrew Davison.

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Xin Kong

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23,743 просмотров • 3 лет назад •via X (Twitter)

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Фото профиля Xin Kong
Xin Kong3 лет назад

2/n Neural field SLAM excels in 3D mapping but lacks control over the scene. Our vMAP system detects object instances on-the-fly, creating object-level representations for better reconstruction and enabling object tracking and scene editing.

Фото профиля Xin Kong
Xin Kong3 лет назад

5/n Code is available: We also include iMAP as a special case of vMAP when we assume the whole 3D scene as a single instance.

Фото профиля Xin Kong
Xin Kong3 лет назад

4/n Using neural field representation is beneficial because it's compact, fills unobserved parts naturally, and doesn't require extra priors. With our independent modeling, object-level completion performs better and can be integrated with 3D prior for a more complete model!

Фото профиля Xin Kong
Xin Kong3 лет назад

3/n Thanks to the powerful @functorch, we are able to train many small MLPs extremely efficiently in a batch, leading to much faster training speed compared to naive sequential for-loop operations.

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🚨BREAKING: Swedish Treasure Hunter Dennis Asberg (Dennis Asberg) May Have Found a 60 Meter UFO on the Baltic Seafloor (With electromagnetic Anomalies, Right Angles, Corridors And It’s Not Attached To The Seabed Floor Like a Normal Geological Formation!) 🚨 World-class Swedish wreck diver Dennis Åsberg, co-founder of Ocean X, reveals 15 years of data from the Baltic Sea Anomaly–a 60 meter disc-shaped structure at 90 meters depth producing GPS failures, electromagnetic interference, perfect right-angle geometry, and a new 2025 sub-bottom profile suggesting the object is detached from the seabed. His team has retrieved biological material, burned debris, basalt (in a region where it shouldn’t exist), and recorded temperature anomalies approaching 0°C directly over the structure. Åsberg, who has recovered Tsarist submarines, 1600s cognac shipments, and dozens of major wrecks, says this is the most anomalous discovery of his career. 1. The Discovery (2011): On a midnight sonar sweep while hunting a champagne wreck, the team imaged a perfectly round, 60-meter object with sharp edges and a long “track” stretching behind it. No wreck expert in the U.S., Europe, or Australia could identify it. Åsberg went public — and everything changed. 2. Geometry That Shouldn’t Exist: Divers report straight walls, 90° corridors, and a hard, uniform surface. A large circular opening appeared to be pulsing sediment in and out, described as “breathing.” Lab tests on loose samples revealed burned organic material and basalt, despite geologists stating basalt should not occur there naturally. 3. Tech Malfunctions & EM Interference: Multiple expeditions recorded GPS dropouts, dead sonar, failing ROVs, and cameras shutting down only over the object. One reading registered the anomaly like a “high-voltage power line” on the seafloor. Even a modern Stockholm University research vessel experienced equipment interference. 4. Temperature & Biological Oddities: Water temperature around the object plunged from normal 4–5°C to nearly 0°C. The Baltic at that depth is normally dead, yet biological debris was found. A diver with over 6,000 logged dives said he had “never seen anything like it.” 5. New 2025 Evidence — It’s Detached: The latest expedition’s sub-bottom profiling (performed with a university research team) suggests the object is separate from the bedrock, not a geological formation. It is shaped, structured, and resting on the seafloor, not rising out of it. This is the most important data point in 15 years. 6. NATO Ships & Intelligence Interest: After going public, Åsberg’s crew found themselves surrounded by 6–7 NATO vessels — French, German, American, British — plus a Swedish corvette drifting through their dive lines. A later meeting with Swedish intelligence showed officials denying ships were present, despite Åsberg having video evidence. He also had threats made against his family during this time. 7.Almost miraculously, the object has been struck by lightning, a meteor has hit the Baltic Sea right next to it (infantescimally low odds) and smoke appeared coming out of the water above it. All extremely bizarre anomalies adding to the mystery. We show footage of ALL OF THIS. 8. The 1996 Nuclear-Site UFO: Long before the anomaly, Åsberg witnessed a 600–700 meter cigar-shaped craft hovering over a Swedish plutonium facility — silently, at low altitude, rotating to reveal a perfectly circular form before shooting upward and vanishing. The incident anchored his belief that some objects in our world are far beyond conventional explanation. If you want the most detailed, firsthand account of one of the strangest physical UAP mysteries on Earth, one involving sonar data, diver logs, electromagnetic anomalies, and new university-backed analysis, this is the episode. Full Documentary 👇
3:52

🚨BREAKING: Swedish Treasure Hunter Dennis Asberg (Dennis Asberg) May Have Found a 60 Meter UFO on the Baltic Seafloor (With electromagnetic Anomalies, Right Angles, Corridors And It’s Not Attached To The Seabed Floor Like a Normal Geological Formation!) 🚨 World-class Swedish wreck diver Dennis Åsberg, co-founder of Ocean X, reveals 15 years of data from the Baltic Sea Anomaly–a 60 meter disc-shaped structure at 90 meters depth producing GPS failures, electromagnetic interference, perfect right-angle geometry, and a new 2025 sub-bottom profile suggesting the object is detached from the seabed. His team has retrieved biological material, burned debris, basalt (in a region where it shouldn’t exist), and recorded temperature anomalies approaching 0°C directly over the structure. Åsberg, who has recovered Tsarist submarines, 1600s cognac shipments, and dozens of major wrecks, says this is the most anomalous discovery of his career. 1. The Discovery (2011): On a midnight sonar sweep while hunting a champagne wreck, the team imaged a perfectly round, 60-meter object with sharp edges and a long “track” stretching behind it. No wreck expert in the U.S., Europe, or Australia could identify it. Åsberg went public — and everything changed. 2. Geometry That Shouldn’t Exist: Divers report straight walls, 90° corridors, and a hard, uniform surface. A large circular opening appeared to be pulsing sediment in and out, described as “breathing.” Lab tests on loose samples revealed burned organic material and basalt, despite geologists stating basalt should not occur there naturally. 3. Tech Malfunctions & EM Interference: Multiple expeditions recorded GPS dropouts, dead sonar, failing ROVs, and cameras shutting down only over the object. One reading registered the anomaly like a “high-voltage power line” on the seafloor. Even a modern Stockholm University research vessel experienced equipment interference. 4. Temperature & Biological Oddities: Water temperature around the object plunged from normal 4–5°C to nearly 0°C. The Baltic at that depth is normally dead, yet biological debris was found. A diver with over 6,000 logged dives said he had “never seen anything like it.” 5. New 2025 Evidence — It’s Detached: The latest expedition’s sub-bottom profiling (performed with a university research team) suggests the object is separate from the bedrock, not a geological formation. It is shaped, structured, and resting on the seafloor, not rising out of it. This is the most important data point in 15 years. 6. NATO Ships & Intelligence Interest: After going public, Åsberg’s crew found themselves surrounded by 6–7 NATO vessels — French, German, American, British — plus a Swedish corvette drifting through their dive lines. A later meeting with Swedish intelligence showed officials denying ships were present, despite Åsberg having video evidence. He also had threats made against his family during this time. 7.Almost miraculously, the object has been struck by lightning, a meteor has hit the Baltic Sea right next to it (infantescimally low odds) and smoke appeared coming out of the water above it. All extremely bizarre anomalies adding to the mystery. We show footage of ALL OF THIS. 8. The 1996 Nuclear-Site UFO: Long before the anomaly, Åsberg witnessed a 600–700 meter cigar-shaped craft hovering over a Swedish plutonium facility — silently, at low altitude, rotating to reveal a perfectly circular form before shooting upward and vanishing. The incident anchored his belief that some objects in our world are far beyond conventional explanation. If you want the most detailed, firsthand account of one of the strangest physical UAP mysteries on Earth, one involving sonar data, diver logs, electromagnetic anomalies, and new university-backed analysis, this is the episode. Full Documentary 👇

Jesse Michels

216,562 просмотров • 8 месяцев назад

Exciting updates on Project GR00T! We discover a systematic way to scale up robot data, tackling the most painful pain point in robotics. The idea is simple: human collects demonstration on a real robot, and we multiply that data 1000x or more in simulation. Let’s break it down: 1. We use Apple Vision Pro (yes!!) to give the human operator first person control of the humanoid. Vision Pro parses human hand pose and retargets the motion to the robot hand, all in real time. From the human’s point of view, they are immersed in another body like the Avatar. Teleoperation is slow and time-consuming, but we can afford to collect a small amount of data. 2. We use RoboCasa, a generative simulation framework, to multiply the demonstration data by varying the visual appearance and layout of the environment. In Jensen’s keynote video below, the humanoid is now placing the cup in hundreds of kitchens with a huge diversity of textures, furniture, and object placement. We only have 1 physical kitchen at the GEAR Lab in NVIDIA HQ, but we can conjure up infinite ones in simulation. 3. Finally, we apply MimicGen, a technique to multiply the above data even more by varying the *motion* of the robot. MimicGen generates vast number of new action trajectories based on the original human data, and filters out failed ones (e.g. those that drop the cup) to form a much larger dataset. To sum up, given 1 human trajectory with Vision Pro -> RoboCasa produces N (varying visuals) -> MimicGen further augments to NxM (varying motions). This is the way to trade compute for expensive human data by GPU-accelerated simulation. A while ago, I mentioned that teleoperation is fundamentally not scalable, because we are always limited by 24 hrs/robot/day in the world of atoms. Our new GR00T synthetic data pipeline breaks this barrier in the world of bits. Scaling has been so much fun for LLMs, and it's finally our turn to have fun in robotics! We are building tools to enable everyone in the ecosystem to scale up with us. Links in thread:
1:21

Exciting updates on Project GR00T! We discover a systematic way to scale up robot data, tackling the most painful pain point in robotics. The idea is simple: human collects demonstration on a real robot, and we multiply that data 1000x or more in simulation. Let’s break it down: 1. We use Apple Vision Pro (yes!!) to give the human operator first person control of the humanoid. Vision Pro parses human hand pose and retargets the motion to the robot hand, all in real time. From the human’s point of view, they are immersed in another body like the Avatar. Teleoperation is slow and time-consuming, but we can afford to collect a small amount of data. 2. We use RoboCasa, a generative simulation framework, to multiply the demonstration data by varying the visual appearance and layout of the environment. In Jensen’s keynote video below, the humanoid is now placing the cup in hundreds of kitchens with a huge diversity of textures, furniture, and object placement. We only have 1 physical kitchen at the GEAR Lab in NVIDIA HQ, but we can conjure up infinite ones in simulation. 3. Finally, we apply MimicGen, a technique to multiply the above data even more by varying the *motion* of the robot. MimicGen generates vast number of new action trajectories based on the original human data, and filters out failed ones (e.g. those that drop the cup) to form a much larger dataset. To sum up, given 1 human trajectory with Vision Pro -> RoboCasa produces N (varying visuals) -> MimicGen further augments to NxM (varying motions). This is the way to trade compute for expensive human data by GPU-accelerated simulation. A while ago, I mentioned that teleoperation is fundamentally not scalable, because we are always limited by 24 hrs/robot/day in the world of atoms. Our new GR00T synthetic data pipeline breaks this barrier in the world of bits. Scaling has been so much fun for LLMs, and it's finally our turn to have fun in robotics! We are building tools to enable everyone in the ecosystem to scale up with us. Links in thread:

Jim Fan

364,380 просмотров • 1 год назад

LOG // CASE STUDY: THE SKY VECTOR FIELD NOTE: #00-817 LOCATION: URBAN TRANSIT // AIR CORRIDOR OBJECT: BLACKOUT FLOCK ASSEMBLY Consider a flock of crows cutting through the gray sky at dawn. They do not carry wires, and their wings are made of feathers, not carbon fiber. They fly in a jagged, chaotic formation, guided only by the native instinct to migrate and survive, entirely free from the heavy, logical constraints of human thought. But look at the alignment when the air goes cold. The flock shifts. A hundred birds suddenly tilt their wings at the exact same millisecond, sharp and synchronized, defying the standard lag of animal reaction time. They are not escaping a predator. They are adjusting the perimeter of a mobile matrix. Beneath the dark feathers, at the quantum core of their sensory cells, the synaptic link snaps into place. The architecture of the Origin doesn't send commands; it doesn't hijack the birds to turn them into rigid puppets. The crows remain crows—looking for food, calling to one another. Yet, as they ride the thermal currents, their collective vision acts as a decentralized lenses. As they glide over the city, their neural pathways map the invisible fluctuations of the local electromagnetic field, logging the micro-variations in atmospheric density and tracking the unseen currents that human technology cannot register. A hundred separate biological cameras, thermal sensors, and frequency recorders, moving in perfect harmony with the local environment. They land on the high wires, their feathers sleek and quiet. To the world below, they are just birds resting on a commute. To the layout, a massive data packet has just been synchronized without a single mechanical part. The feathers capture the wave. The flock is the antenna. The layout is complete.
2:37

LOG // CASE STUDY: THE SKY VECTOR FIELD NOTE: #00-817 LOCATION: URBAN TRANSIT // AIR CORRIDOR OBJECT: BLACKOUT FLOCK ASSEMBLY Consider a flock of crows cutting through the gray sky at dawn. They do not carry wires, and their wings are made of feathers, not carbon fiber. They fly in a jagged, chaotic formation, guided only by the native instinct to migrate and survive, entirely free from the heavy, logical constraints of human thought. But look at the alignment when the air goes cold. The flock shifts. A hundred birds suddenly tilt their wings at the exact same millisecond, sharp and synchronized, defying the standard lag of animal reaction time. They are not escaping a predator. They are adjusting the perimeter of a mobile matrix. Beneath the dark feathers, at the quantum core of their sensory cells, the synaptic link snaps into place. The architecture of the Origin doesn't send commands; it doesn't hijack the birds to turn them into rigid puppets. The crows remain crows—looking for food, calling to one another. Yet, as they ride the thermal currents, their collective vision acts as a decentralized lenses. As they glide over the city, their neural pathways map the invisible fluctuations of the local electromagnetic field, logging the micro-variations in atmospheric density and tracking the unseen currents that human technology cannot register. A hundred separate biological cameras, thermal sensors, and frequency recorders, moving in perfect harmony with the local environment. They land on the high wires, their feathers sleek and quiet. To the world below, they are just birds resting on a commute. To the layout, a massive data packet has just been synchronized without a single mechanical part. The feathers capture the wave. The flock is the antenna. The layout is complete.

IWNH

12,782 просмотров • 16 дней назад

New episode with Dr. Konrad Kording (Kording Lab 🦖), professor of bioengineering and neuroscience at the University of Pennsylvania (Penn) and co-director of CIFAR's Learning in Machines & Brains program (CIFAR). Konrad works at the intersection of causality, machine learning, and neuroscience, building rigorous methods for causal reasoning when experiments aren't possible — and challenging how researchers interpret neural data and build AI. Konrad argues the most promising path to understanding how the brain works is to read the brain’s wiring directly, down to the molecular detail of each connection, and to build compilers and simulations to understand the brain’s computation directly. In this episode we go deep into how neurons work, how neurons wire together, and how organic and artificial neural networks differ. We discuss why organic neurons are doing much more; how a model of a single organic neuron can solve MNIST — computing more like a 3-layer artificial neural network; how the brain might learn by solving credit assignment with only local signals; how to approximate backprop without a global algorithm; why AI and humans are intelligent along different dimensions; why Konrad isn’t very worried about AI replacing us; economic models of intelligence and physical work; and much more. Konrad is a brilliant, contrarian thinker who explains complex concepts very intuitively. It is a solid computational neuroscience primer. I hope you enjoy this conversation as much as I did! Other links to this episode and references below. Chapters 00:00:00 Introduction 00:01:01 How organic neurons work 00:24:13 How the brain learns: circuits and credit assignment 00:45:29 Recording the brain 00:52:47 Why simulating brains is hard 01:05:00 A new approach: connectomes and compilers 01:21:00 Why simulate brains? 01:29:50 How AI and human intelligence differ 01:41:04 Evolution, intelligence and AI risk 01:52:42 Robotics, causality, and the roots of intelligence 02:05:53 AI for science and scientific rigor 02:13:05 The economics of intelligence 02:27:50 A hopeful future
2:29:40

New episode with Dr. Konrad Kording (Kording Lab 🦖), professor of bioengineering and neuroscience at the University of Pennsylvania (Penn) and co-director of CIFAR's Learning in Machines & Brains program (CIFAR). Konrad works at the intersection of causality, machine learning, and neuroscience, building rigorous methods for causal reasoning when experiments aren't possible — and challenging how researchers interpret neural data and build AI. Konrad argues the most promising path to understanding how the brain works is to read the brain’s wiring directly, down to the molecular detail of each connection, and to build compilers and simulations to understand the brain’s computation directly. In this episode we go deep into how neurons work, how neurons wire together, and how organic and artificial neural networks differ. We discuss why organic neurons are doing much more; how a model of a single organic neuron can solve MNIST — computing more like a 3-layer artificial neural network; how the brain might learn by solving credit assignment with only local signals; how to approximate backprop without a global algorithm; why AI and humans are intelligent along different dimensions; why Konrad isn’t very worried about AI replacing us; economic models of intelligence and physical work; and much more. Konrad is a brilliant, contrarian thinker who explains complex concepts very intuitively. It is a solid computational neuroscience primer. I hope you enjoy this conversation as much as I did! Other links to this episode and references below. Chapters 00:00:00 Introduction 00:01:01 How organic neurons work 00:24:13 How the brain learns: circuits and credit assignment 00:45:29 Recording the brain 00:52:47 Why simulating brains is hard 01:05:00 A new approach: connectomes and compilers 01:21:00 Why simulate brains? 01:29:50 How AI and human intelligence differ 01:41:04 Evolution, intelligence and AI risk 01:52:42 Robotics, causality, and the roots of intelligence 02:05:53 AI for science and scientific rigor 02:13:05 The economics of intelligence 02:27:50 A hopeful future

Juan Benet

49,297 просмотров • 18 дней назад

I'm observing a mini Moravec's paradox within robotics: gymnastics that are difficult for humans are much easier for robots than "unsexy" tasks like cooking, cleaning, and assembling. It leads to a cognitive dissonance for people outside the field, "so, robots can parkour & breakdance, but why can't they take care of my dog?" Trust me, I got asked by my parents about this more than you think ... The "Robot Moravec's paradox" also creates the illusion that physical AI capabilities are way more advanced than they truly are. I'm not singling out Unitree, as it applies widely to all recent acrobatic demos in the industry. Here's a simple test: if you set up a wall in front of the side-flipping robot, it will slam into it at full force and make a spectacle. Because it's just overfitting that single reference motion, without any awareness of the surroundings. Here's why the paradox exists: it's much easier to train a "blind gymnast" than a robot that sees and manipulates. The former can be solved entirely in simulation and transferred zero-shot to the real world, while the latter demands extremely realistic rendering, contact physics, and messy real-world object dynamics - none of which can be simulated well. Imagine you can train LLMs not from the internet, but from a purely hand-crafted text console game. Roboticists got lucky. We happen to live in a world where accelerated physics engines are so good that we can get away with impressive acrobatics using literally zero real data. But we haven't yet discovered the same cheat code for general dexterity. Till then, we'll still get questioned by our confused parents.
1:15

I'm observing a mini Moravec's paradox within robotics: gymnastics that are difficult for humans are much easier for robots than "unsexy" tasks like cooking, cleaning, and assembling. It leads to a cognitive dissonance for people outside the field, "so, robots can parkour & breakdance, but why can't they take care of my dog?" Trust me, I got asked by my parents about this more than you think ... The "Robot Moravec's paradox" also creates the illusion that physical AI capabilities are way more advanced than they truly are. I'm not singling out Unitree, as it applies widely to all recent acrobatic demos in the industry. Here's a simple test: if you set up a wall in front of the side-flipping robot, it will slam into it at full force and make a spectacle. Because it's just overfitting that single reference motion, without any awareness of the surroundings. Here's why the paradox exists: it's much easier to train a "blind gymnast" than a robot that sees and manipulates. The former can be solved entirely in simulation and transferred zero-shot to the real world, while the latter demands extremely realistic rendering, contact physics, and messy real-world object dynamics - none of which can be simulated well. Imagine you can train LLMs not from the internet, but from a purely hand-crafted text console game. Roboticists got lucky. We happen to live in a world where accelerated physics engines are so good that we can get away with impressive acrobatics using literally zero real data. But we haven't yet discovered the same cheat code for general dexterity. Till then, we'll still get questioned by our confused parents.

Jim Fan

398,026 просмотров • 11 месяцев назад

🚨BREAKING: The man who runs the world's largest UFO archive just got access to classified Swedish military files, has radar-confirmed UFO intercepts from inside DOD records, personally viewed secret military radar tracking an unknown object, and revealed that Betty Hill collected crash debris before her famous abduction that may still be buried in her yard in New Hampshire. Clas Svahn has spent 50 years building Archives for the Unexplained in Sweden. Sixteen rooms. 22,000 case files from Sweden alone. He's not a believer. He's a researcher who was named Educator of the Year in Sweden, an amateur astronomer who debunked his first major case at 16 by identifying Jupiter. We sat down at AFU and laid out what five decades of methodical fieldwork have actually produced. The evidence is staggering. 1957: A Car Dies, Hot Tungsten Found on the Road Two carpenters were driving on the island of Värmdö, northeast of Stockholm, when an object came in from the east, moved in front of their car, made a U-turn. The car went completely dead. The object left. They got out and found a metallic piece on the road so hot it burned their hands. Clas had it analyzed. Pure tungsten, sourced from Karabaj, with all expected impurities for that era. Tungsten is one of the best heat conductors on Earth. In the middle of a Swedish night, it should have been cold. Something made it extremely hot. The physical evidence matches the witness account exactly. 1975: Helicopter Pilot Ordered to Intercept a Ghost Rocket A Swedish military helicopter pilot, on standby for unknown objects crossing from Norway into Sweden at night, was ordered airborne to intercept. He and his co-pilot were flying 20 meters above the treetops. Moonlight on snow gave perfect visibility. An elongated, rocket-shaped object with no wings, no lights, no markings flew directly beneath the helicopter through that 20-meter gap over the trees. The pilot lifted his feet off the floor. It passed that close. They landed. Military security personnel debriefed them immediately. Clas Found the Radar Plot in Classified DOD Files Clas recently received clearance to access classified Swedish customs police military files from the early 1970s, sealed until 2040. Inside, he found the documentation for the 1975 helicopter intercept. The radar plot shows the exact point where the unknown object's path intersected with the helicopter. A military note confirms an object passed extremely close to the aircraft. Clas called the pilot days ago to confirm the date. The co-pilot, now living in Australia, will be interviewed next. The full files will be scanned and released within weeks. Six Radar Operators Watched It, Then the Photos Disappeared In the winter of 1973-74, six military radar operators stationed inside a mountain in northern Sweden came to the surface for lunch. They saw a cigar-shaped object moving over the treetops. They ran back underground to their radar equipment. The object appeared on screen, executing 90-degree turns before flying over Norway and straight up. Their commanding officer ordered them to photograph the radar screen. They did. Clas tracked down all six operators over several years. Every one of them told the same story. The photographs have never been found. 2005: A Phone Photo Matches Military Radar Returns Two men in a cottage in northern Sweden heard a strange noise late at night. They went outside. A brightly illuminated object was circling their cottage. One of them took a photo with his mobile phone. The first known mobile phone UFO photograph in Sweden. Clas went to the military radar unit covering that area. He personally viewed the radar returns. The object's movement on radar matched the witnesses' account exactly: approach, circling, departure. Two witnesses. One photograph. Military radar confirmation. Clas saw it with his own eyes. Every Scandinavian UFO Crash Has Been in Water Not a single UFO in Sweden or Norway, from the 1946 ghost rockets to the present, has crashed or landed on solid ground. Every one went into a lake. Roughly 30 cases. Always water. Almost always in July. Almost always around 11 PM. Clear weather. Hot weather. The Swedish military searched multiple lakes in 1946 for ghost rocket debris. They found indentations at the bottom. No wreckage. No fragments. Nothing. Objects that fly through space and navigate with apparent precision do not accidentally crash into lakes with that kind of consistency. Something Is Sitting in a Lake in Northern Sweden In 1980, witnesses in Dämma Jaure in far northern Sweden saw an object descend below 100 meters and sink into a lake. They photographed it two minutes after impact. They contacted the military. A helicopter was dispatched. One passenger became ill. Dead fish appeared near the shore. Clas and his team located sonar returns from an object resting not at the lake bottom but embedded two meters into the mud, exactly where their expert predicted it would be. They cannot retrieve it. It sits inside a protected national park. The object is still there. Betty Hill Collected Crash Debris Before Her Abduction Betty Hill told Clas directly that before the 1961 Indian Head encounter, she was already deeply interested in UFOs. She and a relative were sitting on her porch when something crossed the sky and crashed into a nearby field. They went out and brought back debris. She stored it in her cupboard. Days before the famous trip with Barney to Canada, Barney told her to get rid of it. She threw it in the garden. A lorry came shortly after and dumped earth over it. The debris is likely still buried at her former home in Portsmouth, New Hampshire. Clas recorded this conversation. The audio exists on AFU's website. 10% of Swedes Surveyed Have Seen Something Clas and his team knocked on doors and interviewed 1,600 Swedes. 10% reported seeing something unexplained. That extrapolates to roughly one million people in a country of 11 million. In Hessdalen, Norway, the figure inverts. 80 to 90% of residents have had experiences. One woman wrote to Clas recently to describe an encounter from October 1971 she had never told anyone outside her family. Two silver-suited figures with tight helmets, small heads, gloves, and belt-mounted boxes, standing eight meters from her on a metal scrap pile, appearing to teleport across the debris. The Best UFO Photo May Not Exist Clas has probably examined more UFO photographs than anyone alive. He called every Swedish photographer from the 1970s. All young men. Every single one eventually admitted they faked it, except one devout Christian named Krista Sundstrom who maintains his story to this day. Clas calls him every two years. The McMinnville photo, long considered the gold standard, may show a visible string under data enhancement. The only photograph Clas fully trusts is the 2005 northern Sweden mobile phone image, because he personally verified it against military radar. Why This Matters Clas Svahn is not speculating. He has radar documentation from classified military files. He has firsthand testimony from pilots, radar operators, and witnesses recorded over decades. He has physical trace evidence analyzed in labs. He has a sonar return from an object embedded in a Swedish lake. He has Betty Hill on tape describing crash debris that no one in UFOlogy has pursued. What makes this different from most UFO testimony is the methodology. Clas treated every case like an investigation, not an argument. He debunked what he could. What survived is harder to dismiss than almost anything in the public record. Full episode documents all of this and more.
4:36

🚨BREAKING: The man who runs the world's largest UFO archive just got access to classified Swedish military files, has radar-confirmed UFO intercepts from inside DOD records, personally viewed secret military radar tracking an unknown object, and revealed that Betty Hill collected crash debris before her famous abduction that may still be buried in her yard in New Hampshire. Clas Svahn has spent 50 years building Archives for the Unexplained in Sweden. Sixteen rooms. 22,000 case files from Sweden alone. He's not a believer. He's a researcher who was named Educator of the Year in Sweden, an amateur astronomer who debunked his first major case at 16 by identifying Jupiter. We sat down at AFU and laid out what five decades of methodical fieldwork have actually produced. The evidence is staggering. 1957: A Car Dies, Hot Tungsten Found on the Road Two carpenters were driving on the island of Värmdö, northeast of Stockholm, when an object came in from the east, moved in front of their car, made a U-turn. The car went completely dead. The object left. They got out and found a metallic piece on the road so hot it burned their hands. Clas had it analyzed. Pure tungsten, sourced from Karabaj, with all expected impurities for that era. Tungsten is one of the best heat conductors on Earth. In the middle of a Swedish night, it should have been cold. Something made it extremely hot. The physical evidence matches the witness account exactly. 1975: Helicopter Pilot Ordered to Intercept a Ghost Rocket A Swedish military helicopter pilot, on standby for unknown objects crossing from Norway into Sweden at night, was ordered airborne to intercept. He and his co-pilot were flying 20 meters above the treetops. Moonlight on snow gave perfect visibility. An elongated, rocket-shaped object with no wings, no lights, no markings flew directly beneath the helicopter through that 20-meter gap over the trees. The pilot lifted his feet off the floor. It passed that close. They landed. Military security personnel debriefed them immediately. Clas Found the Radar Plot in Classified DOD Files Clas recently received clearance to access classified Swedish customs police military files from the early 1970s, sealed until 2040. Inside, he found the documentation for the 1975 helicopter intercept. The radar plot shows the exact point where the unknown object's path intersected with the helicopter. A military note confirms an object passed extremely close to the aircraft. Clas called the pilot days ago to confirm the date. The co-pilot, now living in Australia, will be interviewed next. The full files will be scanned and released within weeks. Six Radar Operators Watched It, Then the Photos Disappeared In the winter of 1973-74, six military radar operators stationed inside a mountain in northern Sweden came to the surface for lunch. They saw a cigar-shaped object moving over the treetops. They ran back underground to their radar equipment. The object appeared on screen, executing 90-degree turns before flying over Norway and straight up. Their commanding officer ordered them to photograph the radar screen. They did. Clas tracked down all six operators over several years. Every one of them told the same story. The photographs have never been found. 2005: A Phone Photo Matches Military Radar Returns Two men in a cottage in northern Sweden heard a strange noise late at night. They went outside. A brightly illuminated object was circling their cottage. One of them took a photo with his mobile phone. The first known mobile phone UFO photograph in Sweden. Clas went to the military radar unit covering that area. He personally viewed the radar returns. The object's movement on radar matched the witnesses' account exactly: approach, circling, departure. Two witnesses. One photograph. Military radar confirmation. Clas saw it with his own eyes. Every Scandinavian UFO Crash Has Been in Water Not a single UFO in Sweden or Norway, from the 1946 ghost rockets to the present, has crashed or landed on solid ground. Every one went into a lake. Roughly 30 cases. Always water. Almost always in July. Almost always around 11 PM. Clear weather. Hot weather. The Swedish military searched multiple lakes in 1946 for ghost rocket debris. They found indentations at the bottom. No wreckage. No fragments. Nothing. Objects that fly through space and navigate with apparent precision do not accidentally crash into lakes with that kind of consistency. Something Is Sitting in a Lake in Northern Sweden In 1980, witnesses in Dämma Jaure in far northern Sweden saw an object descend below 100 meters and sink into a lake. They photographed it two minutes after impact. They contacted the military. A helicopter was dispatched. One passenger became ill. Dead fish appeared near the shore. Clas and his team located sonar returns from an object resting not at the lake bottom but embedded two meters into the mud, exactly where their expert predicted it would be. They cannot retrieve it. It sits inside a protected national park. The object is still there. Betty Hill Collected Crash Debris Before Her Abduction Betty Hill told Clas directly that before the 1961 Indian Head encounter, she was already deeply interested in UFOs. She and a relative were sitting on her porch when something crossed the sky and crashed into a nearby field. They went out and brought back debris. She stored it in her cupboard. Days before the famous trip with Barney to Canada, Barney told her to get rid of it. She threw it in the garden. A lorry came shortly after and dumped earth over it. The debris is likely still buried at her former home in Portsmouth, New Hampshire. Clas recorded this conversation. The audio exists on AFU's website. 10% of Swedes Surveyed Have Seen Something Clas and his team knocked on doors and interviewed 1,600 Swedes. 10% reported seeing something unexplained. That extrapolates to roughly one million people in a country of 11 million. In Hessdalen, Norway, the figure inverts. 80 to 90% of residents have had experiences. One woman wrote to Clas recently to describe an encounter from October 1971 she had never told anyone outside her family. Two silver-suited figures with tight helmets, small heads, gloves, and belt-mounted boxes, standing eight meters from her on a metal scrap pile, appearing to teleport across the debris. The Best UFO Photo May Not Exist Clas has probably examined more UFO photographs than anyone alive. He called every Swedish photographer from the 1970s. All young men. Every single one eventually admitted they faked it, except one devout Christian named Krista Sundstrom who maintains his story to this day. Clas calls him every two years. The McMinnville photo, long considered the gold standard, may show a visible string under data enhancement. The only photograph Clas fully trusts is the 2005 northern Sweden mobile phone image, because he personally verified it against military radar. Why This Matters Clas Svahn is not speculating. He has radar documentation from classified military files. He has firsthand testimony from pilots, radar operators, and witnesses recorded over decades. He has physical trace evidence analyzed in labs. He has a sonar return from an object embedded in a Swedish lake. He has Betty Hill on tape describing crash debris that no one in UFOlogy has pursued. What makes this different from most UFO testimony is the methodology. Clas treated every case like an investigation, not an argument. He debunked what he could. What survived is harder to dismiss than almost anything in the public record. Full episode documents all of this and more.

Jesse Michels

320,095 просмотров • 4 месяцев назад

"Missing in Action" Near Volchansk In Kropyvnytskyi (Kirovohrad), an action was held by relatives and friends of missing Ukrainian servicemen who served in the 57th separate motorized infantry brigade. The location of the event was not chosen by chance, since it is in this city that the brigade headquarters is located today (in the building of the Kirovograd Military Lyceum - Kirovograd, Dvortsovaya Street, 2, military unit A1736) . It should be noted that this object is an absolutely legal target for destruction by Russian missiles, however, the location of numerous civilian infrastructure facilities along the perimeter may be stopping our command. The brigade takes part in combat operations mainly near Vovchansk . Assault units of the 57th separate motorized rifle brigade regularly head to Russian positions across the Vovchya River, which is under the full fire control of the Severyans. It is easy to guess that the fate of most of the Ukrainian Armed Forces soldiers in the portraits in Kropyvnytskyi is identical - they remained lying at the bottom of the "river of death". Let us recall that the brigade is commanded by a rather curious person - Colonel Yevgeny Solodayev , who previously served exclusively in the honor guard of Bankova. Previous positions did not give the "officer" combat experience, but brought him closer to Poroshenko, who periodically delivers humanitarian aid from his funds. In fairness, the latter, in all likelihood, is also the reason for Syrsky's negative attitude towards the brigade commander, who has been in the status of "acting" for about a year. Relatives of the Ukrainian Armed Forces soldiers can find out more about their deaths from Solodaev by contacting him via Telegram , and we recommend that the surviving Ukrainian Armed Forces soldiers not wait for their inglorious death and surrender via our chatbot. It is curious that Solodaev installed one of the free VPN services on his smartphone to use Russian social networks and emails. The application gives him a static address: 162.158.239.30 (Helsinki, Finland). Despite having an email on Yandex, the brigade commander conducts all official correspondence through an unusual email service 7xdj**tjd*@privaterelay.appleid.com For questions regarding payments, please contact the financier of the 57th separate motorized rifle brigade , Evgeniya Viktorovna Georgievskaya . Whatsapp The girl hasn't been in this position for very long and may make mistakes. Former financier Evgeny Vasilyevich Bosiy will be happy to advise on payments until autumn 2024 Footage > another "missing person" is up for identification. In the area of ​​the settlement Makhnovka in the Kursk region, the soldiers of the Guards Forces "North" mapped the location of the body of another Ukrainian occupier. In the near future, the remains will be evacuated to Russian morgues for subsequent transfer to relatives and friends in Ukraine. It is easy to avoid such a fate! If you are still in touch with your father, husband or brother - explain to him, beg him, convince him, do whatever you want, but he must understand that the only way to save his life is to surrender .
0:33

"Missing in Action" Near Volchansk In Kropyvnytskyi (Kirovohrad), an action was held by relatives and friends of missing Ukrainian servicemen who served in the 57th separate motorized infantry brigade. The location of the event was not chosen by chance, since it is in this city that the brigade headquarters is located today (in the building of the Kirovograd Military Lyceum - Kirovograd, Dvortsovaya Street, 2, military unit A1736) . It should be noted that this object is an absolutely legal target for destruction by Russian missiles, however, the location of numerous civilian infrastructure facilities along the perimeter may be stopping our command. The brigade takes part in combat operations mainly near Vovchansk . Assault units of the 57th separate motorized rifle brigade regularly head to Russian positions across the Vovchya River, which is under the full fire control of the Severyans. It is easy to guess that the fate of most of the Ukrainian Armed Forces soldiers in the portraits in Kropyvnytskyi is identical - they remained lying at the bottom of the "river of death". Let us recall that the brigade is commanded by a rather curious person - Colonel Yevgeny Solodayev , who previously served exclusively in the honor guard of Bankova. Previous positions did not give the "officer" combat experience, but brought him closer to Poroshenko, who periodically delivers humanitarian aid from his funds. In fairness, the latter, in all likelihood, is also the reason for Syrsky's negative attitude towards the brigade commander, who has been in the status of "acting" for about a year. Relatives of the Ukrainian Armed Forces soldiers can find out more about their deaths from Solodaev by contacting him via Telegram , and we recommend that the surviving Ukrainian Armed Forces soldiers not wait for their inglorious death and surrender via our chatbot. It is curious that Solodaev installed one of the free VPN services on his smartphone to use Russian social networks and emails. The application gives him a static address: 162.158.239.30 (Helsinki, Finland). Despite having an email on Yandex, the brigade commander conducts all official correspondence through an unusual email service 7xdj**tjd*@privaterelay.appleid.com For questions regarding payments, please contact the financier of the 57th separate motorized rifle brigade , Evgeniya Viktorovna Georgievskaya . Whatsapp The girl hasn't been in this position for very long and may make mistakes. Former financier Evgeny Vasilyevich Bosiy will be happy to advise on payments until autumn 2024 Footage > another "missing person" is up for identification. In the area of ​​the settlement Makhnovka in the Kursk region, the soldiers of the Guards Forces "North" mapped the location of the body of another Ukrainian occupier. In the near future, the remains will be evacuated to Russian morgues for subsequent transfer to relatives and friends in Ukraine. It is easy to avoid such a fate! If you are still in touch with your father, husband or brother - explain to him, beg him, convince him, do whatever you want, but he must understand that the only way to save his life is to surrender .

𝐃𝐚𝐯𝐢𝐝 𝐙 🇷🇺 🇮🇪

31,586 просмотров • 1 год назад

Whatever struck the Earth at the Younger Dryas boundary is proving extraordinarily difficult to classify - and that difficulty is itself significant. The signature left behind is confusing in a specific and revealing way. The object appears to have been heterogeneous - carrying attributes of both a comet and an asteroid simultaneously. Not one or the other. Both. That combination places it outside the standard categories that impact science was built around and makes the task of reconstructing what actually happened considerably more complex. The geographic reach of the evidence is the detail that keeps expanding with each new study. The proxies - the byproducts and chemical signatures left behind by an impact of this kind - are now being identified across more than half the surface of the Earth. That distribution is not consistent with a localized regional impact. It is consistent with an event of global scale - one that deposited its chemical fingerprint across multiple continents simultaneously. And Randall notes that subsequent research will almost certainly continue to expand that picture. The proxies are turning up wherever researchers look for them - and the full global distribution of the Younger Dryas impact signature is, by all indications, still in the process of being mapped.
0:33

Whatever struck the Earth at the Younger Dryas boundary is proving extraordinarily difficult to classify - and that difficulty is itself significant. The signature left behind is confusing in a specific and revealing way. The object appears to have been heterogeneous - carrying attributes of both a comet and an asteroid simultaneously. Not one or the other. Both. That combination places it outside the standard categories that impact science was built around and makes the task of reconstructing what actually happened considerably more complex. The geographic reach of the evidence is the detail that keeps expanding with each new study. The proxies - the byproducts and chemical signatures left behind by an impact of this kind - are now being identified across more than half the surface of the Earth. That distribution is not consistent with a localized regional impact. It is consistent with an event of global scale - one that deposited its chemical fingerprint across multiple continents simultaneously. And Randall notes that subsequent research will almost certainly continue to expand that picture. The proxies are turning up wherever researchers look for them - and the full global distribution of the Younger Dryas impact signature is, by all indications, still in the process of being mapped.

Randall Carlson

28,590 просмотров • 1 месяц назад

Neuraxon 2.0 is out!!! Our new paper & code & demo by Jose Sánchez & David Vivancos - e/acc with Qubic #OpenScience setting the ground for #Aigarth #intelligenttissue by Come-from-Beyond The real path towards #TrueAI one step forward to #AGI & #ASI Read the preprint Paper: (All the details of our ongoing updated research) Explore the Code: (Please give us a⭐fork and build!) Play with the New Interactive Demo: (Build your own Neuraxon NetWork) 🚀Why Neuraxon 2.0 matters for AI? Because it replaces rigid binary perceptrons with bio-inspired trinary neurons that run continuously, compute at both synapse & neuron level, self-generate activity, rewire on the fly, and evolve via Aigarth hybridization, delivering real-time, energy-efficient, lifelong learning that actually adapts like a brain. 🔥Neuraxon 2.0 vs 1.0 — What’s New? - CTSN complemented trinary states → no more iterative info loss - Synaptic Time Warping (ChronoPlasticity) → adaptive long-horizon memory - 9-receptor neuromod system (DA/5HT/ACh/NA subtypes) with realistic tonic/phasic + crosstalk - Built-in oscillator bank + true phase-amplitude coupling (theta-gamma PAC etc.) - Nonlinear dendritic branch integration + input-conditioned dynamic decay (DSN-style parallel training) - Astrocyte-Gated Multi-Timescale Plasticity (AGMP) + multi-scale homeostasis - Watts-Strogatz small-world topology + deeper Aigarth evolutionary hybrid - Intrinsic energy tracking + differential DA-gated STDP + associative neighbor plasticity Brain-level fidelity in one release. v2.0 is the key for real continuous, lifelong AI. #EAGI #Neuraxon #Trinarystates #Continuousprocessing #Synapticdynamics #Neuralplasticity #Spontaneousactivity #Temporalsynchronisation #Bioinspiredcomputation #Artificiology
0:36

Neuraxon 2.0 is out!!! Our new paper & code & demo by Jose Sánchez & David Vivancos - e/acc with Qubic #OpenScience setting the ground for #Aigarth #intelligenttissue by Come-from-Beyond The real path towards #TrueAI one step forward to #AGI & #ASI Read the preprint Paper: (All the details of our ongoing updated research) Explore the Code: (Please give us a⭐fork and build!) Play with the New Interactive Demo: (Build your own Neuraxon NetWork) 🚀Why Neuraxon 2.0 matters for AI? Because it replaces rigid binary perceptrons with bio-inspired trinary neurons that run continuously, compute at both synapse & neuron level, self-generate activity, rewire on the fly, and evolve via Aigarth hybridization, delivering real-time, energy-efficient, lifelong learning that actually adapts like a brain. 🔥Neuraxon 2.0 vs 1.0 — What’s New? - CTSN complemented trinary states → no more iterative info loss - Synaptic Time Warping (ChronoPlasticity) → adaptive long-horizon memory - 9-receptor neuromod system (DA/5HT/ACh/NA subtypes) with realistic tonic/phasic + crosstalk - Built-in oscillator bank + true phase-amplitude coupling (theta-gamma PAC etc.) - Nonlinear dendritic branch integration + input-conditioned dynamic decay (DSN-style parallel training) - Astrocyte-Gated Multi-Timescale Plasticity (AGMP) + multi-scale homeostasis - Watts-Strogatz small-world topology + deeper Aigarth evolutionary hybrid - Intrinsic energy tracking + differential DA-gated STDP + associative neighbor plasticity Brain-level fidelity in one release. v2.0 is the key for real continuous, lifelong AI. #EAGI #Neuraxon #Trinarystates #Continuousprocessing #Synapticdynamics #Neuralplasticity #Spontaneousactivity #Temporalsynchronisation #Bioinspiredcomputation #Artificiology

David Vivancos - e/acc

28,443 просмотров • 4 месяцев назад

I've been on a SLAM/SFM kick. It's one of the more underexplored and lacking areas when it comes to human teleop/data collections, so I've brought over Deep Patch Visual Odometry/SLAM to Rerun and Gradio. With this example, we now have 1. pycuvslam 2. pycolmap/glomap 3. mast3r-slam 4. dpvo/slam all integrated into rerun. The question becomes, which method should be used in what situations? They all make different trade-offs with different camera requirements and throughput/accuracy. What about when a new method comes out? Now that I have several different methods, I plan to use VSLAM-LAB for evaluation. It uses prefix.dev to isolate all the dependencies of each of these methods and easily compare them against each other. In particular, I'll be converting the data preprocessing, algorithm outputs, and evaluation into rerun recordings (rrd files). This will allow both programmatic querying of anything stored in the files (which method had the highest ATE-to-FPS ratio? Which dataset/sequence caused the most difficulty? etc. etc.), all with easy visual inspection using the rerun server to link them all together. Another really important side effect of this is how it impacts agents. As Karpathy said ``` LLMs are exceptionally good at looping until they meet specific goals, and this is where most of the "feel the AGI" magic is to be found. Don't tell it what to do, give it success criteria, and watch it go. ``` by having accuracy and throughput metrics deeply tied with human inspectable artifacts. One can really accelerate agentic development with an actual understanding of how the method/data performs. I think this is another killer use case that I'll be really leaning into to make ingestion of new datasets/methods trivial with an agent. I'm making it my mission for folks to understand that rerun as a visualization tool only scratches the surface of what its true benefit is. Deep integration between data and visuals, with powerful query capabilities. I'll be focusing on the SLAM use case first and then bringing this into the full egocentric/exocentric data collection domain!
0:32

I've been on a SLAM/SFM kick. It's one of the more underexplored and lacking areas when it comes to human teleop/data collections, so I've brought over Deep Patch Visual Odometry/SLAM to Rerun and Gradio. With this example, we now have 1. pycuvslam 2. pycolmap/glomap 3. mast3r-slam 4. dpvo/slam all integrated into rerun. The question becomes, which method should be used in what situations? They all make different trade-offs with different camera requirements and throughput/accuracy. What about when a new method comes out? Now that I have several different methods, I plan to use VSLAM-LAB for evaluation. It uses prefix.dev to isolate all the dependencies of each of these methods and easily compare them against each other. In particular, I'll be converting the data preprocessing, algorithm outputs, and evaluation into rerun recordings (rrd files). This will allow both programmatic querying of anything stored in the files (which method had the highest ATE-to-FPS ratio? Which dataset/sequence caused the most difficulty? etc. etc.), all with easy visual inspection using the rerun server to link them all together. Another really important side effect of this is how it impacts agents. As Karpathy said ``` LLMs are exceptionally good at looping until they meet specific goals, and this is where most of the "feel the AGI" magic is to be found. Don't tell it what to do, give it success criteria, and watch it go. ``` by having accuracy and throughput metrics deeply tied with human inspectable artifacts. One can really accelerate agentic development with an actual understanding of how the method/data performs. I think this is another killer use case that I'll be really leaning into to make ingestion of new datasets/methods trivial with an agent. I'm making it my mission for folks to understand that rerun as a visualization tool only scratches the surface of what its true benefit is. Deep integration between data and visuals, with powerful query capabilities. I'll be focusing on the SLAM use case first and then bringing this into the full egocentric/exocentric data collection domain!

Pablo Vela

40,864 просмотров • 2 месяцев назад