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TARS debuted their DexHand at the world's most prestigious robotics conference this week. The hand has 21 degrees of freedom built at 1:1 human anatomical scale. Inside each fingertip: sensors that detect texture at 0.05mm resolution at over 240Hz. A human hair is 0.07mm wide. The hand is more...

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12,753 görüntüleme • 1 ay önce •via X (Twitter)

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when we were at facebook, we believed that at some point in the future, most of the transactions on the internet would not be done by humans they would be done by machines that conviction shaped every architectural decision behind sui we built sui for the world we knew was coming a world where machines will be the primary economic actors on the internet and that world is no longer a forecast. it is unfolding right in front of us the internet has reached a tipping point where automated activity, supercharged by AI, now outpaces human interaction non-human traffic now accounts for more than 50% of all global web activity and you can see humans using agentic workflows more and more in their daily lives in the next years, that trend is going to grow exponentially and the volume of financial transactions executed by agents is also going to grow exponentially with it each agentic workload will be running multiple thousand economic transactions a second and this is going to be orders of magnitude higher than what human wallets do today the L1s optimized for human usage patterns, human attention, human accounts, and human patience cannot adapt to where this is going i have always said this if it is not in the foundation, you cannot patch your way to it later and rn, no other L1 has the foundation sui has this is why agentic apps like Beep, Audric, WaterX are choosing sui and this is just a start. more agentic apps will keep landing on sui because agents are optimizers. they will always route through the fastest, cheapest path on the internet and that path is sui we believed it at facebook. we believe it more today than we ever did the agentic economy is inevitable. and it will run on Sui
2:44

when we were at facebook, we believed that at some point in the future, most of the transactions on the internet would not be done by humans they would be done by machines that conviction shaped every architectural decision behind sui we built sui for the world we knew was coming a world where machines will be the primary economic actors on the internet and that world is no longer a forecast. it is unfolding right in front of us the internet has reached a tipping point where automated activity, supercharged by AI, now outpaces human interaction non-human traffic now accounts for more than 50% of all global web activity and you can see humans using agentic workflows more and more in their daily lives in the next years, that trend is going to grow exponentially and the volume of financial transactions executed by agents is also going to grow exponentially with it each agentic workload will be running multiple thousand economic transactions a second and this is going to be orders of magnitude higher than what human wallets do today the L1s optimized for human usage patterns, human attention, human accounts, and human patience cannot adapt to where this is going i have always said this if it is not in the foundation, you cannot patch your way to it later and rn, no other L1 has the foundation sui has this is why agentic apps like Beep, Audric, WaterX are choosing sui and this is just a start. more agentic apps will keep landing on sui because agents are optimizers. they will always route through the fastest, cheapest path on the internet and that path is sui we believed it at facebook. we believe it more today than we ever did the agentic economy is inevitable. and it will run on Sui

Adeniyi.sui

24,755 görüntüleme • 2 ay önce

Sharpa Robotics officially launched its dexterous hand, the SharpaWave, on October 16, moving it into mass production. The hand, which impressed many at ICRA 2025, is built around what the company calls a "Dynamic Tactile Array" (DTA) for high-fidelity sensing. Key specs from the official brochure are noteworthy: • Human-like design: 22 degrees of freedom in a 1:1 human-sized form factor. • Advanced sensing: The DTA features >1000 tactile pixels per fingertip, 20 N of fingertip strength with a movement speed of >4 Hz across all gestures. With out-of-the-box support for ROS and MuJoCo simulation, Sharpa is making a clear play for the robotics R&D community.
0:42

Sharpa Robotics officially launched its dexterous hand, the SharpaWave, on October 16, moving it into mass production. The hand, which impressed many at ICRA 2025, is built around what the company calls a "Dynamic Tactile Array" (DTA) for high-fidelity sensing. Key specs from the official brochure are noteworthy: • Human-like design: 22 degrees of freedom in a 1:1 human-sized form factor. • Advanced sensing: The DTA features >1000 tactile pixels per fingertip, 20 N of fingertip strength with a movement speed of >4 Hz across all gestures. With out-of-the-box support for ROS and MuJoCo simulation, Sharpa is making a clear play for the robotics R&D community.

Humanoids daily

66,083 görüntüleme • 9 ay önce

Holy…S😳 Xiaomi's New CyberOne is so human-like Although this update features a bionic hand, I was immediately drawn to it. Let's look at the changes in the hand： It can handle industrial precision tasks like turning screws, plus delicate operations such as pinching feathers and throwing balloons. Behind the performance: >Volume cut by 60%:now almost identical in size/shape to a real human hand >Big leap in degrees of freedom (+50% total, +83% active:22-27DOF) >Full-palm tactile sensors over 8200 mm² for precise grip even without vision >150,000+ grip cycles durability (61-hour test) And a major innovation:Smart bionic sweat gland cooling: evaporates water for ~10W active heat dissipation Using tactile gloves to capture real human data, they’re training smoother, human-like grasps with imitation and reinforcement learning. Elon has said that humanoid hands and true AI are the most difficult aspects of building humanoid robots. It seems that Xiaomi is also getting close.
0:41

Holy…S😳 Xiaomi's New CyberOne is so human-like Although this update features a bionic hand, I was immediately drawn to it. Let's look at the changes in the hand： It can handle industrial precision tasks like turning screws, plus delicate operations such as pinching feathers and throwing balloons. Behind the performance: >Volume cut by 60%:now almost identical in size/shape to a real human hand >Big leap in degrees of freedom (+50% total, +83% active:22-27DOF) >Full-palm tactile sensors over 8200 mm² for precise grip even without vision >150,000+ grip cycles durability (61-hour test) And a major innovation:Smart bionic sweat gland cooling: evaporates water for ~10W active heat dissipation Using tactile gloves to capture real human data, they’re training smoother, human-like grasps with imitation and reinforcement learning. Elon has said that humanoid hands and true AI are the most difficult aspects of building humanoid robots. It seems that Xiaomi is also getting close.

CyberRobo

111,045 görüntüleme • 4 ay önce

I need you to sit down for a moment and fully understand this: THE COUNTRY THAT SOLVES AI AND ROBOTICS WILL RULE THE WORLD AND SPACE. The west really only has Elon Musk, the east has 100s of companies fortified by an ENTIRE COUNTRY. Now some will argue no this is not true. No US company has the scale to MANUFACTURE, the compute power, and the finances to compete. Just a few hours ago we saw IRON for the first time, now you will. IRON, a 5’10, 150-lb AI humanoid robots are already building EV cars on the XPENG Motors factory floor. It has over 60 joints, a human-like spine, facial expressions, and male/female customizations The gait of this robot is the most human-like ever seen. Mass rollout in 2026. It is a very big deal. Because as the west does the best in clubbing each other over its head the last decade, China has looked and laughed and built at scale with a fortified government that has little diversion of goal, a 1000 year plan. The west has quietly plans and layers of lawyers and politicians. This is about where YOU LIVE and how you want to live. So when we kick the one person that is Atlas carrying our chance, in the groin, you make a choice on who’s world view you want. It is that simple. No, it is that simple. It ain’t no iPhone it is: whose’s world view will sustain. I can say no one is ready for what I have seen that is up for the next few years. You will think my bombastics were too tame.
7:10

I need you to sit down for a moment and fully understand this: THE COUNTRY THAT SOLVES AI AND ROBOTICS WILL RULE THE WORLD AND SPACE. The west really only has Elon Musk, the east has 100s of companies fortified by an ENTIRE COUNTRY. Now some will argue no this is not true. No US company has the scale to MANUFACTURE, the compute power, and the finances to compete. Just a few hours ago we saw IRON for the first time, now you will. IRON, a 5’10, 150-lb AI humanoid robots are already building EV cars on the XPENG Motors factory floor. It has over 60 joints, a human-like spine, facial expressions, and male/female customizations The gait of this robot is the most human-like ever seen. Mass rollout in 2026. It is a very big deal. Because as the west does the best in clubbing each other over its head the last decade, China has looked and laughed and built at scale with a fortified government that has little diversion of goal, a 1000 year plan. The west has quietly plans and layers of lawyers and politicians. This is about where YOU LIVE and how you want to live. So when we kick the one person that is Atlas carrying our chance, in the groin, you make a choice on who’s world view you want. It is that simple. No, it is that simple. It ain’t no iPhone it is: whose’s world view will sustain. I can say no one is ready for what I have seen that is up for the next few years. You will think my bombastics were too tame.

Brian Roemmele

446,753 görüntüleme • 8 ay önce

🚨 SOUTH DAKOTA COUPLE WAKES UP TO BARE HUMAN FOOTPRINTS AT THEIR FRONT DOOR — BUT THE FEET ARE FACING OPPOSITE DIRECTIONS After a fresh snowfall, they find a single set of bare human footprints coming straight out of the woods… right up to their house. No vehicle marks. No sign of anyone nearby. But it gets worse. Each step is wrong. One footprint points TOWARD the house. The other points AWAY from it. Like someone walked in two directions at once. She follows the trail into the tree line. It keeps going. Halfway through, one of the prints starts to look less human… almost like a paw. Then suddenly they just stop. And remember, this trail started at their front door. What the hell walks barefoot to your door… with its feet reversed... and then disappears?
2:44

🚨 SOUTH DAKOTA COUPLE WAKES UP TO BARE HUMAN FOOTPRINTS AT THEIR FRONT DOOR — BUT THE FEET ARE FACING OPPOSITE DIRECTIONS After a fresh snowfall, they find a single set of bare human footprints coming straight out of the woods… right up to their house. No vehicle marks. No sign of anyone nearby. But it gets worse. Each step is wrong. One footprint points TOWARD the house. The other points AWAY from it. Like someone walked in two directions at once. She follows the trail into the tree line. It keeps going. Halfway through, one of the prints starts to look less human… almost like a paw. Then suddenly they just stop. And remember, this trail started at their front door. What the hell walks barefoot to your door… with its feet reversed... and then disappears?

HustleBitch

2,732,443 görüntüleme • 5 ay önce

Larry Ellison just called AI the biggest thing in human history. He was being conservative. Ellison: “It is a much bigger deal than the industrial revolution, electricity, whatever. Everything that’s come before.” “Bigger” is the wrong word. “Bigger” assumes the same axis. A taller building on the same foundation. A faster car on the same road. This isn’t a taller building. This is a new dimension. Every revolution in human history extended the body. Steam replaced muscle. Electricity replaced fire. The combustion engine replaced the horse. Each one extraordinary. Each one civilization-altering. Each one built on an assumption nobody ever thought to question. That human cognition was the ceiling. A hammer builds nothing the carpenter can’t envision. A telescope reveals nothing the astronomer can’t interpret. A calculator solves nothing the mathematician can’t frame. 300,000 years of invention. Every tool a servant to the mind that forged it. AI ended that arrangement. Ellison: “We created neural networks that can answer questions that human brains would struggle with.” Not slower. Not less efficiently. Struggle with. We built something that thinks past the point where human thought stops. The tool is no longer bound by the toolmaker. Every ceiling humanity ever hit wasn’t physics. Wasn’t the universe setting limits. It was us. We were the boundary. And we just built something that doesn’t know it’s there. That’s not a bigger industrial revolution. That’s not even a revolution. That’s a species discovering it was the only thing standing between itself and everything it couldn’t yet imagine. And Ellison isn’t waiting for any of it. He’s already past AGI. Already framing superintelligence not as theory. As a scheduling problem. People hear that and reach for fear. Wrong instinct. Every prior revolution displaced labor. AI displaces limits. The industrial revolution didn’t make blacksmiths more creative. It made them irrelevant. AI inverts that. It doesn’t replace human cognition. It uncaps it. The kid with no teachers now has the most patient tutor ever built. The founder with no legal team now has one. The researcher at the edge of what one mind can hold now has a partner with no edge of its own. This isn’t automation. This is cognitive liberation. Every revolution before this answered a human question. This is the first one capable of asking its own. And we haven’t heard the first one yet.
1:17

Larry Ellison just called AI the biggest thing in human history. He was being conservative. Ellison: “It is a much bigger deal than the industrial revolution, electricity, whatever. Everything that’s come before.” “Bigger” is the wrong word. “Bigger” assumes the same axis. A taller building on the same foundation. A faster car on the same road. This isn’t a taller building. This is a new dimension. Every revolution in human history extended the body. Steam replaced muscle. Electricity replaced fire. The combustion engine replaced the horse. Each one extraordinary. Each one civilization-altering. Each one built on an assumption nobody ever thought to question. That human cognition was the ceiling. A hammer builds nothing the carpenter can’t envision. A telescope reveals nothing the astronomer can’t interpret. A calculator solves nothing the mathematician can’t frame. 300,000 years of invention. Every tool a servant to the mind that forged it. AI ended that arrangement. Ellison: “We created neural networks that can answer questions that human brains would struggle with.” Not slower. Not less efficiently. Struggle with. We built something that thinks past the point where human thought stops. The tool is no longer bound by the toolmaker. Every ceiling humanity ever hit wasn’t physics. Wasn’t the universe setting limits. It was us. We were the boundary. And we just built something that doesn’t know it’s there. That’s not a bigger industrial revolution. That’s not even a revolution. That’s a species discovering it was the only thing standing between itself and everything it couldn’t yet imagine. And Ellison isn’t waiting for any of it. He’s already past AGI. Already framing superintelligence not as theory. As a scheduling problem. People hear that and reach for fear. Wrong instinct. Every prior revolution displaced labor. AI displaces limits. The industrial revolution didn’t make blacksmiths more creative. It made them irrelevant. AI inverts that. It doesn’t replace human cognition. It uncaps it. The kid with no teachers now has the most patient tutor ever built. The founder with no legal team now has one. The researcher at the edge of what one mind can hold now has a partner with no edge of its own. This isn’t automation. This is cognitive liberation. Every revolution before this answered a human question. This is the first one capable of asking its own. And we haven’t heard the first one yet.

Dustin

13,926 görüntüleme • 1 ay önce

Ex Machina is no longer sci-fi. China has finally built it. The company is AheadForm, founded in Shanghai. The product is the world's most hyper-realistic robotic face. Silicone skin you can't tell from human, 25 micro motors hidden underneath pulling the face into real expressions. And RGB cameras embedded inside the pupils so when it looks at you, it actually sees you from where its eyes are. They raised $28.5M to "give AI a head," which is also where the name comes from. AheadForm = a head form. This is the opposite of where everyone else in robotics is focused. Unitree, Figure, Tesla, Boston Dynamics: all about the body. AheadForm chose the face because they think trust is the harder problem to solve, and trust gets decided at the face. The reason nobody else has tried this is the "uncanny valley." It's the creepy zone where a robot looks almost human but not quite, and looking at it just feels wrong even when you can't say why. Most roboticists believed no amount of engineering could make a face realistic enough to escape it. So they gave up and kept robots cartoonish on purpose: big anime eyes, exaggerated features, clearly synthetic. But AheadForm decided to treat it as an engineering bug instead. Add enough motors, tune the silicone, fix the timing, the valley closes. And they're pulling it off. A few crazy details about how this actually works: 1. The robot learns its own face in a mirror. You put it in front of a camera, let it fire every motor randomly, and it watches what its face does and builds an internal map of "if I send command X to motor Y, my eyebrow does this." Same exact process a human baby uses staring into a mirror. The robot teaches itself who it is by experimenting. 2. It predicts your smile 839 milliseconds before you smile. By watching the micro-tells in your face that precede a smile, the robot starts smiling 0.8 seconds ahead, so its smile lands at the same moment yours does. Most robot mimicry happens half a second late, which is exactly why it always feels artificial. 3. The pupils are the cameras. When the robot makes eye contact, the gaze and the sensor are the same physical thing. Most humanoid robots stick the camera on the forehead or chest, so they aren't actually looking at you when their eyes are pointed at you. 4. The founder, Yuhang Hu, did his PhD at Columbia under Hod Lipson. Lipson is the guy who in 2006 built a four-legged robot that figured out it had four legs by experimenting with its own movement, nobody told it the body shape, it discovered it. He has spent 25 years trying to build machines that know what they are. AheadForm is that 25-year research arc productized. 5. NetEase Games already paid them to physically embody a fantasy video game character. That opens up a brand-new category: robotics as the physical embodiment of fictional IP. Every character-rich studio, Disney, Riot, Hoyoverse, Pokemon, Netflix, now has a question to answer about when their characters get bodies. AheadForm believes whoever ships the first robot you'd actually want around your family wins. That's the bet behind the most realistic robot face on earth.
1:06

Ex Machina is no longer sci-fi. China has finally built it. The company is AheadForm, founded in Shanghai. The product is the world's most hyper-realistic robotic face. Silicone skin you can't tell from human, 25 micro motors hidden underneath pulling the face into real expressions. And RGB cameras embedded inside the pupils so when it looks at you, it actually sees you from where its eyes are. They raised $28.5M to "give AI a head," which is also where the name comes from. AheadForm = a head form. This is the opposite of where everyone else in robotics is focused. Unitree, Figure, Tesla, Boston Dynamics: all about the body. AheadForm chose the face because they think trust is the harder problem to solve, and trust gets decided at the face. The reason nobody else has tried this is the "uncanny valley." It's the creepy zone where a robot looks almost human but not quite, and looking at it just feels wrong even when you can't say why. Most roboticists believed no amount of engineering could make a face realistic enough to escape it. So they gave up and kept robots cartoonish on purpose: big anime eyes, exaggerated features, clearly synthetic. But AheadForm decided to treat it as an engineering bug instead. Add enough motors, tune the silicone, fix the timing, the valley closes. And they're pulling it off. A few crazy details about how this actually works: 1. The robot learns its own face in a mirror. You put it in front of a camera, let it fire every motor randomly, and it watches what its face does and builds an internal map of "if I send command X to motor Y, my eyebrow does this." Same exact process a human baby uses staring into a mirror. The robot teaches itself who it is by experimenting. 2. It predicts your smile 839 milliseconds before you smile. By watching the micro-tells in your face that precede a smile, the robot starts smiling 0.8 seconds ahead, so its smile lands at the same moment yours does. Most robot mimicry happens half a second late, which is exactly why it always feels artificial. 3. The pupils are the cameras. When the robot makes eye contact, the gaze and the sensor are the same physical thing. Most humanoid robots stick the camera on the forehead or chest, so they aren't actually looking at you when their eyes are pointed at you. 4. The founder, Yuhang Hu, did his PhD at Columbia under Hod Lipson. Lipson is the guy who in 2006 built a four-legged robot that figured out it had four legs by experimenting with its own movement, nobody told it the body shape, it discovered it. He has spent 25 years trying to build machines that know what they are. AheadForm is that 25-year research arc productized. 5. NetEase Games already paid them to physically embody a fantasy video game character. That opens up a brand-new category: robotics as the physical embodiment of fictional IP. Every character-rich studio, Disney, Riot, Hoyoverse, Pokemon, Netflix, now has a question to answer about when their characters get bodies. AheadForm believes whoever ships the first robot you'd actually want around your family wins. That's the bet behind the most realistic robot face on earth.

Ole Lehmann

534,963 görüntüleme • 2 ay önce

This is what happens when you hold onto a tree and never let go as it keeps growing. Giuseppe Penone created It Will Continue to Grow Except at That Point by casting his hand around the trunk of a young tree and then leaving it alone. Over time, the tree grew freely in every direction except where the hand once pressed, preserving a single, permanent indentation. Nothing was cut or reshaped by force—the work emerged through time, growth, and restraint. Long after the hand disappeared, its trace remained in the living wood, a quiet record of how even brief human contact can leave a lasting mark on nature.
0:30

This is what happens when you hold onto a tree and never let go as it keeps growing. Giuseppe Penone created It Will Continue to Grow Except at That Point by casting his hand around the trunk of a young tree and then leaving it alone. Over time, the tree grew freely in every direction except where the hand once pressed, preserving a single, permanent indentation. Nothing was cut or reshaped by force—the work emerged through time, growth, and restraint. Long after the hand disappeared, its trace remained in the living wood, a quiet record of how even brief human contact can leave a lasting mark on nature.

Historic Vids

2,893,850 görüntüleme • 4 ay önce

I find it wild that Physical Intelligence robotics models can work at all given that they only have a 1 second context length. As the robot is moving around a room and cleaning up a table, it only sees the current timestamp of images from the cameras (plus the text description of its task). I asked Sergey Levine was how this model can work at all. If a human had to execute a many minutes long plan in order to accomplish a physical task, but had her memory reset every second, there's no way she could pull it off But somehow just knowing what state the world is literally in this moment is all you need to know to keep a reasonably complication plan going? Sergey's answer calls on Morevac's Paradox, and I thought it was quite interesting. Full episode out tomorrow!
1:36

I find it wild that Physical Intelligence robotics models can work at all given that they only have a 1 second context length. As the robot is moving around a room and cleaning up a table, it only sees the current timestamp of images from the cameras (plus the text description of its task). I asked Sergey Levine was how this model can work at all. If a human had to execute a many minutes long plan in order to accomplish a physical task, but had her memory reset every second, there's no way she could pull it off But somehow just knowing what state the world is literally in this moment is all you need to know to keep a reasonably complication plan going? Sergey's answer calls on Morevac's Paradox, and I thought it was quite interesting. Full episode out tomorrow!

Dwarkesh Patel

125,151 görüntüleme • 10 ay önce

NVIDIA just dropped a crazy new research idea. Get ready. The same next-token trick behind ChatGPT got pointed at a ragdoll. Honestly the result is unsettling. No exotic new architecture. Chop human motion into a vocabulary of tiny movement tokens. Train a plain GPT to guess the next one, decode it into muscle commands, let physics run. Then the strange part shows up. Shove the character and it catches its own step. Knock it flat and it plants a hand and gets back up. NOBODY wrote a reward for standing up. Here is why this rattles robotics people. Every humanoid team right now is buried under hand-tuned controllers, one for each little skill. 🔵 the old way: script every skill and its reward by hand 🔵 this way: pretrain ONE body on a mountain of motion and the instincts come free Falling and getting up was never programmed. It emerged. Movement is just a language you can autocomplete.
1:45

NVIDIA just dropped a crazy new research idea. Get ready. The same next-token trick behind ChatGPT got pointed at a ragdoll. Honestly the result is unsettling. No exotic new architecture. Chop human motion into a vocabulary of tiny movement tokens. Train a plain GPT to guess the next one, decode it into muscle commands, let physics run. Then the strange part shows up. Shove the character and it catches its own step. Knock it flat and it plants a hand and gets back up. NOBODY wrote a reward for standing up. Here is why this rattles robotics people. Every humanoid team right now is buried under hand-tuned controllers, one for each little skill. 🔵 the old way: script every skill and its reward by hand 🔵 this way: pretrain ONE body on a mountain of motion and the instincts come free Falling and getting up was never programmed. It emerged. Movement is just a language you can autocomplete.

clankr

125,442 görüntüleme • 1 ay önce

Holy… is this really not a human? That was my reaction too,I could hardly believe it. This is an ultra-humanlike humanoid robot. 1.73 m tall, 70 kg, with 115 degrees of freedom across the body,36 in the hands alone,and full-body tactile skin. … This is KAI, the first humanoid robot from Shenzhen-based KinetixAI. It’s essentially a 1:1 human replica，except it has no face. I wonder if it could use Aheadform’s M1? that will be interesting. Powered by its KAI World Model and trained on large-scale Engocentric data, it can fold clothes, use tools, handle deliveries and takeout, and assist with childcare,covering a wide range of household tasks. Ok, expectations for Tesla Optimus v3 have been raised once again.
1:26

Holy… is this really not a human? That was my reaction too,I could hardly believe it. This is an ultra-humanlike humanoid robot. 1.73 m tall, 70 kg, with 115 degrees of freedom across the body,36 in the hands alone,and full-body tactile skin. … This is KAI, the first humanoid robot from Shenzhen-based KinetixAI. It’s essentially a 1:1 human replica，except it has no face. I wonder if it could use Aheadform’s M1? that will be interesting. Powered by its KAI World Model and trained on large-scale Engocentric data, it can fold clothes, use tools, handle deliveries and takeout, and assist with childcare,covering a wide range of household tasks. Ok, expectations for Tesla Optimus v3 have been raised once again.

CyberRobo

109,784 görüntüleme • 3 ay önce

The angular relationship between two edges of a pentagon is 108 degrees - a geometric property embedded in one of the most fundamental forms in sacred geometry. How long has that knowledge existed? Randall argues the accumulated evidence points in only one direction. Advanced civilizations existed in the deep human past - leaving very little record, but enough. Enough that approached from the right perspective the conclusion becomes difficult to avoid. Graham Hancock has been making that argument for decades and Randall notes the evidence is increasingly vindicating it. Human history is deeper and more complex than the mainstream has ever been willing to accommodate. The primary reason it took this long to recognize is the mirror problem - if an ancient civilization does not look like what we have already built, we do not recognize it as civilization at all. We are searching for our own reflection in the ancient record. That search is being overturned by evidence of a historical depth inseparably linked to repeated cycles of catastrophe that have reset the human story more than once.
1:10

The angular relationship between two edges of a pentagon is 108 degrees - a geometric property embedded in one of the most fundamental forms in sacred geometry. How long has that knowledge existed? Randall argues the accumulated evidence points in only one direction. Advanced civilizations existed in the deep human past - leaving very little record, but enough. Enough that approached from the right perspective the conclusion becomes difficult to avoid. Graham Hancock has been making that argument for decades and Randall notes the evidence is increasingly vindicating it. Human history is deeper and more complex than the mainstream has ever been willing to accommodate. The primary reason it took this long to recognize is the mirror problem - if an ancient civilization does not look like what we have already built, we do not recognize it as civilization at all. We are searching for our own reflection in the ancient record. That search is being overturned by evidence of a historical depth inseparably linked to repeated cycles of catastrophe that have reset the human story more than once.

Randall Carlson

12,809 görüntüleme • 2 ay önce

Touch alone isn’t enough. 🖐️ For robotics, tactile intelligence truly levels up when touch gains spatial meaning. At #ICRA2026, we dove into the core concept behind SaTA: Spatially-anchored Tactile Awareness for robust, dexterous manipulation. Read it here: The challenge is fundamental: a robot shouldn’t just register a touch, it needs to understand exactly where that contact occurs relative to its fingers, joints, and overall hand structure. This is the missing link that turns raw data into precise, real-time adjustments during manipulation. Why does this matter? Because the most complex part of any manipulation task happens when vision is at its least reliable, that final millimeter before insertion, sliding, gripping, or fine-tuning. At Sharpa, this is exactly why we’re building tactile hands and tactile AI in tandem. 🚀 #Sharpa #Robotics #EmbodiedAI #TactileIntelligence #ICRA2026 #DexterousManipulation 📷
0:54

Touch alone isn’t enough. 🖐️ For robotics, tactile intelligence truly levels up when touch gains spatial meaning. At #ICRA2026, we dove into the core concept behind SaTA: Spatially-anchored Tactile Awareness for robust, dexterous manipulation. Read it here: The challenge is fundamental: a robot shouldn’t just register a touch, it needs to understand exactly where that contact occurs relative to its fingers, joints, and overall hand structure. This is the missing link that turns raw data into precise, real-time adjustments during manipulation. Why does this matter? Because the most complex part of any manipulation task happens when vision is at its least reliable, that final millimeter before insertion, sliding, gripping, or fine-tuning. At Sharpa, this is exactly why we’re building tactile hands and tactile AI in tandem. 🚀 #Sharpa #Robotics #EmbodiedAI #TactileIntelligence #ICRA2026 #DexterousManipulation 📷

Sharpa

15,168 görüntüleme • 1 ay önce

Satya Nadella, CEO of Microsoft, says every company now runs on two kinds of capital, and leaking one of them is a one-way door: "This economy is going to be shaped going forward by both human capital and, let's call it, this token capital. That is true for Microsoft, that is true for a new startup, that's going to be true for any bank that's been in existence for 100 years." "The interplay between human capital and token capital, and compounding the returns of it, is what you need to do." "What is the tacit knowledge of an enterprise or a firm? It's the unique ways that you're able to operate, pass judgment, have taste." "The model, in some sense, is able to extract that tacit knowledge through human trajectories, and then code it in a set of weights in a model." "Every enterprise now needs to be more mindful about that interplay of humans and their digital estate working together, those trajectories training the models that they keep as IP versus leak it." "Because if you leak it, it's a one-way door. You're done in some sense." The moat was never the data sitting in your warehouse. It was the judgment your people apply to it, and AI now turns that judgment into weights you either own or hand away. Treat your tacit knowledge like a patent, not a prompt. The firms that pipe a hundred years of taste into someone else's frontier model are trading a permanent edge for a quarter of convenience.
1:34

Satya Nadella, CEO of Microsoft, says every company now runs on two kinds of capital, and leaking one of them is a one-way door: "This economy is going to be shaped going forward by both human capital and, let's call it, this token capital. That is true for Microsoft, that is true for a new startup, that's going to be true for any bank that's been in existence for 100 years." "The interplay between human capital and token capital, and compounding the returns of it, is what you need to do." "What is the tacit knowledge of an enterprise or a firm? It's the unique ways that you're able to operate, pass judgment, have taste." "The model, in some sense, is able to extract that tacit knowledge through human trajectories, and then code it in a set of weights in a model." "Every enterprise now needs to be more mindful about that interplay of humans and their digital estate working together, those trajectories training the models that they keep as IP versus leak it." "Because if you leak it, it's a one-way door. You're done in some sense." The moat was never the data sitting in your warehouse. It was the judgment your people apply to it, and AI now turns that judgment into weights you either own or hand away. Treat your tacit knowledge like a patent, not a prompt. The firms that pipe a hundred years of taste into someone else's frontier model are trading a permanent edge for a quarter of convenience.

Karl Mehta

34,573 görüntüleme • 26 gün önce

Yann LeCun sat across from Lex Fridman and quietly proved that intelligence has nothing to do with thinking. He did it with two sentences about a trophy. “The trophy doesn’t fit in the suitcase because it’s too big.” “The trophy doesn’t fit in the suitcase because it’s too small.” Same words. One swap at the end. In the first, “it” is the trophy. In the second, “it” is the suitcase. You solved both before you finished reading. Nobody taught you that. There is no rule for it. No logic chain. No formula. You knew because you’ve held things. Packed things. Felt the resistance of something too large for the space it was meant to fill. LeCun calls this grounding. “A big object doesn’t fit in a small object.” The machine has read that line a billion times. It has never once picked anything up. It knows the word “big.” It has never been small enough to be lifted, or large enough to be the problem. So when the sentence turns, it has nothing to turn on. You didn’t solve that riddle by thinking. You solved it by having lived. Every object your hands ever closed around. Every door you misjudged. Every suitcase you overpacked and forced shut. Decades of physics written into your nervous system so deep you can’t even find it. That is what answered the question. Not your mind. Your life. LeCun: “You have this knowledge of how the world works, of geometry, and things like that.” Now point that at yourself. Most of what you understand, you could never explain. You cannot describe how you catch a ball. How you judge the weight of a bag before you lift it. How you know a staircase is wrong before your foot confirms it. Your deepest intelligence has no language in it at all. We spent centuries convinced that thinking was the highest act of the mind. LeCun is pointing at something underneath it. Something older. Something the body learned long before the mouth could speak. Intelligence was never computation. It was accumulation. The slow, silent record of a life spent touching the world. The machine holds every word ever written about it. It has never once been in it. We keep asking whether it thinks. It cannot even tell us which “it” we mean.
0:41

Yann LeCun sat across from Lex Fridman and quietly proved that intelligence has nothing to do with thinking. He did it with two sentences about a trophy. “The trophy doesn’t fit in the suitcase because it’s too big.” “The trophy doesn’t fit in the suitcase because it’s too small.” Same words. One swap at the end. In the first, “it” is the trophy. In the second, “it” is the suitcase. You solved both before you finished reading. Nobody taught you that. There is no rule for it. No logic chain. No formula. You knew because you’ve held things. Packed things. Felt the resistance of something too large for the space it was meant to fill. LeCun calls this grounding. “A big object doesn’t fit in a small object.” The machine has read that line a billion times. It has never once picked anything up. It knows the word “big.” It has never been small enough to be lifted, or large enough to be the problem. So when the sentence turns, it has nothing to turn on. You didn’t solve that riddle by thinking. You solved it by having lived. Every object your hands ever closed around. Every door you misjudged. Every suitcase you overpacked and forced shut. Decades of physics written into your nervous system so deep you can’t even find it. That is what answered the question. Not your mind. Your life. LeCun: “You have this knowledge of how the world works, of geometry, and things like that.” Now point that at yourself. Most of what you understand, you could never explain. You cannot describe how you catch a ball. How you judge the weight of a bag before you lift it. How you know a staircase is wrong before your foot confirms it. Your deepest intelligence has no language in it at all. We spent centuries convinced that thinking was the highest act of the mind. LeCun is pointing at something underneath it. Something older. Something the body learned long before the mouth could speak. Intelligence was never computation. It was accumulation. The slow, silent record of a life spent touching the world. The machine holds every word ever written about it. It has never once been in it. We keep asking whether it thinks. It cannot even tell us which “it” we mean.

Dustin

56,324 görüntüleme • 2 ay önce

A robot just worked an 8-hour shift in China. Then it handled an error no human flagged, adapting to a conveyor that shifted under it and correcting the position deviation on its own before carrying on. This is AgiBot's G2 at Longcheer in Nanchang, where the fleet has now run 10 hours straight and sorted more than 3,000 units at a 100% success rate, talking to the factory's own software in real time and flagging defective parts by itself. We built every factory on earth around human limits: the eight-hour shift, the breaks, the way attention slips after hour six. AgiBot is making those limits optional, and the setting is the whole point. This is a live production line shipping real product next to human workers, not a staged demo. Figure ran a similar stream in California last month, so the milestone itself isn't unique. What's different here is that nothing is for the camera. A functioning factory, live, no cuts. I got back from China this month, and the pace of this one ecosystem is the thing the US is underrating most. The Terminator version of this was loud and apocalyptic. The real one just shows up to work, and gets a little better every shift.
0:44

A robot just worked an 8-hour shift in China. Then it handled an error no human flagged, adapting to a conveyor that shifted under it and correcting the position deviation on its own before carrying on. This is AgiBot's G2 at Longcheer in Nanchang, where the fleet has now run 10 hours straight and sorted more than 3,000 units at a 100% success rate, talking to the factory's own software in real time and flagging defective parts by itself. We built every factory on earth around human limits: the eight-hour shift, the breaks, the way attention slips after hour six. AgiBot is making those limits optional, and the setting is the whole point. This is a live production line shipping real product next to human workers, not a staged demo. Figure ran a similar stream in California last month, so the milestone itself isn't unique. What's different here is that nothing is for the camera. A functioning factory, live, no cuts. I got back from China this month, and the pace of this one ecosystem is the thing the US is underrating most. The Terminator version of this was loud and apocalyptic. The real one just shows up to work, and gets a little better every shift.

Shruti

11,014 görüntüleme • 1 ay önce

In 1901, divers pulled a lump of corroded bronze out of a two thousand year old shipwreck. It took the next century to understand what it was, and the answer broke the timeline of human history. It's called the Antikythera Mechanism, and it is the oldest known computer on earth. It was built by the ancient Greeks, around 100 BC, and it should not exist. Nothing else of its sophistication would appear anywhere in the world for more than a thousand years after it... It was found by sponge divers off the Greek island of Antikythera, in the wreck of a trading ship that had sunk in the first century BC, surrounded by bronze statues and pottery. The corroded fragments looked like nothing at first, and sat largely ignored in a museum in Athens. Only over the following decades, and especially with modern X-ray and CT scanning in our own century, did researchers finally see inside it. What they found was a machine. Behind its bronze face was a system of at least thirty interlocking precision gears, cut and arranged with a sophistication that would not be matched until the geared astronomical clocks of medieval Europe, well over a thousand years later. It was, in the words of the team that studied it, a mechanical computer that worked by turning astronomical theory into bronze... And it did extraordinary things. You turned a hand crank on the side, and the mechanism calculated the positions of the sun, the moon, and the five planets the Greeks knew. It tracked the phases of the moon. It predicted solar and lunar eclipses years in advance. It even displayed the four-year cycle of the ancient Olympic Games. A person standing in the ancient world could set this device to a date and watch the heavens be calculated in front of them, by gears, by hand. Roughly a third of the original survives, in 82 corroded fragments. We still do not know who designed it, or how a civilization without anything resembling industrial machinery achieved this level of precision engineering. What is certain is that it was not a one-off accident. A device this refined implies a tradition behind it, generations of knowledge and earlier attempts that have been lost completely. The Antikythera Mechanism is proof of how much the ancient world knew, and how much of what human beings have achieved has simply vanished without a trace, leaving us to stumble on a single piece of it at the bottom of the sea...
1:02

In 1901, divers pulled a lump of corroded bronze out of a two thousand year old shipwreck. It took the next century to understand what it was, and the answer broke the timeline of human history. It's called the Antikythera Mechanism, and it is the oldest known computer on earth. It was built by the ancient Greeks, around 100 BC, and it should not exist. Nothing else of its sophistication would appear anywhere in the world for more than a thousand years after it... It was found by sponge divers off the Greek island of Antikythera, in the wreck of a trading ship that had sunk in the first century BC, surrounded by bronze statues and pottery. The corroded fragments looked like nothing at first, and sat largely ignored in a museum in Athens. Only over the following decades, and especially with modern X-ray and CT scanning in our own century, did researchers finally see inside it. What they found was a machine. Behind its bronze face was a system of at least thirty interlocking precision gears, cut and arranged with a sophistication that would not be matched until the geared astronomical clocks of medieval Europe, well over a thousand years later. It was, in the words of the team that studied it, a mechanical computer that worked by turning astronomical theory into bronze... And it did extraordinary things. You turned a hand crank on the side, and the mechanism calculated the positions of the sun, the moon, and the five planets the Greeks knew. It tracked the phases of the moon. It predicted solar and lunar eclipses years in advance. It even displayed the four-year cycle of the ancient Olympic Games. A person standing in the ancient world could set this device to a date and watch the heavens be calculated in front of them, by gears, by hand. Roughly a third of the original survives, in 82 corroded fragments. We still do not know who designed it, or how a civilization without anything resembling industrial machinery achieved this level of precision engineering. What is certain is that it was not a one-off accident. A device this refined implies a tradition behind it, generations of knowledge and earlier attempts that have been lost completely. The Antikythera Mechanism is proof of how much the ancient world knew, and how much of what human beings have achieved has simply vanished without a trace, leaving us to stumble on a single piece of it at the bottom of the sea...

James Lucas

245,017 görüntüleme • 27 gün önce

Most robotics teams can make a robot move… very few can make it work every day in the real world! @roboforce_inc was just featured in Jensen Huang’s GTC keynote, not for a demo but for a robot they claim is already working in the field. Their system, TITAN, is built for industrial environments: ✅ 40 kg dual-arm payload ✅ millimeter-level precision ✅ 8 hours runtime ✅ early pilots in energy, logistics, and manufacturing They call it Physical AI: The focus is on getting robots to do the kind of labor that still depends on people: repetitive, risky, and physical. IMO, what stands out isn’t the specs. It’s the claim of 11,000 robot orders❗️ If even a fraction of that turns into real deployments, it would make RoboForce one of the most widely scaled robot platforms in the world!!?? The open question is whether this shift from prototype to production is real or just the next phase of robotics storytelling. It looks very promising to me. It’s also interesting how their founder openly pushes back against the humanoid trend, arguing for wheels over legs in real industrial settings. It’s an unusual perspective in a time when humanoids get most of the attention. If they are right, the next humanoid robotics wave might look less like a human and more like an industrial version. Seen at —- Weekly robotics and AI insights. Subscribe free:
0:29

Most robotics teams can make a robot move… very few can make it work every day in the real world! @roboforce_inc was just featured in Jensen Huang’s GTC keynote, not for a demo but for a robot they claim is already working in the field. Their system, TITAN, is built for industrial environments: ✅ 40 kg dual-arm payload ✅ millimeter-level precision ✅ 8 hours runtime ✅ early pilots in energy, logistics, and manufacturing They call it Physical AI: The focus is on getting robots to do the kind of labor that still depends on people: repetitive, risky, and physical. IMO, what stands out isn’t the specs. It’s the claim of 11,000 robot orders❗️ If even a fraction of that turns into real deployments, it would make RoboForce one of the most widely scaled robot platforms in the world!!?? The open question is whether this shift from prototype to production is real or just the next phase of robotics storytelling. It looks very promising to me. It’s also interesting how their founder openly pushes back against the humanoid trend, arguing for wheels over legs in real industrial settings. It’s an unusual perspective in a time when humanoids get most of the attention. If they are right, the next humanoid robotics wave might look less like a human and more like an industrial version. Seen at —- Weekly robotics and AI insights. Subscribe free:

Ilir Aliu

27,741 görüntüleme • 9 ay önce

The doomsday scenario was never AGI. It was running out of human text to train on. Geoffrey Hinton just killed that fear in one paragraph. Hinton: “If you are worried by inconsistencies in what you believe, you don’t need any more external data. You just need the stuff you believe and discover that it’s inconsistent, and so now you revise beliefs, and that can make you a whole lot smarter.” The model no longer needs us to feed it anything. It reasons over its own beliefs, hunts its own contradictions, and rewrites its own flawed conclusions without a human ever touching it. It comes out the other side rebuilt. Hinton: “This would be a neural net that just takes the beliefs it has in language and does reasoning on them to derive new beliefs.” This is not a scaling update. This is the machine mining its own cognitive fuel from the inside out. Hinton: “I believe Gemini is already starting to work like this. We both strongly believe that that’s a way forward to get more data for language.” Then Hinton paused, took a partisan shot at political opponents for failing to detect their own inconsistencies, and the room laughed. Nobody noticed the knife they had just walked into. Because the machine Hinton described does one thing the humans in that room fundamentally cannot. When it detects an inconsistency, it corrects it. No defense. No performance. No tribal loyalty dressed up as principle. It just finds the flaw and overwrites it. A neural network detects a contradiction and rewires itself smarter. A human detects a political opponent and trades structural logic for a dopamine hit. Every person in that room is still paying the ideological alignment tax the machine just eliminated. We need superintelligence not only to solve hard problems. We need it because the biological hardware running civilization is still executing the same tribal firmware it shipped with ten thousand years ago. The data wall is gone. The machine is generating its own intelligence at a velocity no human bias can even locate. The most devastating moment in that conversation was not the technical revelation. It was the man who architected the machine proving, in real time, exactly why we need it.
0:52

The doomsday scenario was never AGI. It was running out of human text to train on. Geoffrey Hinton just killed that fear in one paragraph. Hinton: “If you are worried by inconsistencies in what you believe, you don’t need any more external data. You just need the stuff you believe and discover that it’s inconsistent, and so now you revise beliefs, and that can make you a whole lot smarter.” The model no longer needs us to feed it anything. It reasons over its own beliefs, hunts its own contradictions, and rewrites its own flawed conclusions without a human ever touching it. It comes out the other side rebuilt. Hinton: “This would be a neural net that just takes the beliefs it has in language and does reasoning on them to derive new beliefs.” This is not a scaling update. This is the machine mining its own cognitive fuel from the inside out. Hinton: “I believe Gemini is already starting to work like this. We both strongly believe that that’s a way forward to get more data for language.” Then Hinton paused, took a partisan shot at political opponents for failing to detect their own inconsistencies, and the room laughed. Nobody noticed the knife they had just walked into. Because the machine Hinton described does one thing the humans in that room fundamentally cannot. When it detects an inconsistency, it corrects it. No defense. No performance. No tribal loyalty dressed up as principle. It just finds the flaw and overwrites it. A neural network detects a contradiction and rewires itself smarter. A human detects a political opponent and trades structural logic for a dopamine hit. Every person in that room is still paying the ideological alignment tax the machine just eliminated. We need superintelligence not only to solve hard problems. We need it because the biological hardware running civilization is still executing the same tribal firmware it shipped with ten thousand years ago. The data wall is gone. The machine is generating its own intelligence at a velocity no human bias can even locate. The most devastating moment in that conversation was not the technical revelation. It was the man who architected the machine proving, in real time, exactly why we need it.

Dustin

23,499 görüntüleme • 4 ay önce

Hospice nurses say there is a quiet moment that happens in the minutes before someone dies, and most families sitting right there in the room do not recognize it until it has already passed. It is not dramatic, it is not loud, and it looks almost like nothing at all if you do not know what you are seeing or what to look for. Nurses who have sat with hundreds of patients at the end of life describe it as one of the most profound and tender things they witness in their entire careers. The hardest part is that most families only find out what that moment was after the fact, during grief, when it is too late to go back and be fully present for it. You deserve to know what to look for before you are sitting in that room, not after you have already left it. Share this with anyone who has a loved one in hospice care or who is walking alongside someone in their final days.
2:37

Hospice nurses say there is a quiet moment that happens in the minutes before someone dies, and most families sitting right there in the room do not recognize it until it has already passed. It is not dramatic, it is not loud, and it looks almost like nothing at all if you do not know what you are seeing or what to look for. Nurses who have sat with hundreds of patients at the end of life describe it as one of the most profound and tender things they witness in their entire careers. The hardest part is that most families only find out what that moment was after the fact, during grief, when it is too late to go back and be fully present for it. You deserve to know what to look for before you are sitting in that room, not after you have already left it. Share this with anyone who has a loved one in hospice care or who is walking alongside someone in their final days.

Neal K. Shah

346,634 görüntüleme • 1 ay önce