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This isn't sci-fi. It's built using Direct Metal Laser Sintering (DMLS), a 3D-printing process that fuses titanium powder layer by layer with high-precision lasers. Each print forms thousands of tiny interlocking links, creating a flexible, chainmail-like sheet that moves almost like real fabric.

Philosophy Of Physics

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12,941 次观看 • 8 个月前 •via X (Twitter)

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🚨 CHINESE SCIENTISTS JUST INVENTED 3D PRINTING THAT CREATES OBJECTS IN 0.6 SECONDS USING ONLY LIGHT. Researchers at Tsinghua University have developed a new method called DISH (Digital Incoherent Synthesis of Holographic light fields) that can print complex millimeter-scale objects almost instantly. Instead of slowly building layer by layer, the system fires thousands of precisely patterned light images from multiple angles into a still vat of liquid resin. Where the light overlaps, the resin instantly hardens into a solid 3D object. The entire process takes just 0.6 seconds. Why this matters: • It’s currently the fastest volumetric 3D printing method ever demonstrated • Achieves extremely fine detail features thinner than a human hair • The resin stays completely still, so there’s no vibration or distortion • It can work with watery (low-viscosity) resins, making it suitable for biological applications • The team has already printed complex structures like blood vessel-like tubes and even a tiny bust of a historical figure The deeper implication: Traditional 3D printing has always been limited by speed and the need to move either the print head or the resin. This approach removes both constraints by using light itself as the sculptor. Because it can print directly into still liquid (and potentially onto living tissue), it opens new possibilities in bioprinting, medical devices, and rapid manufacturing. If the technology can be scaled beyond millimeter sizes, it could fundamentally change how we think about making physical objects turning “print” from a slow process into something closer to instantaneous fabrication. We’re moving from “layer by layer” to “all at once.” How do you think instant volumetric 3D printing like this could change medicine, manufacturing, or everyday life if it becomes widely available? Follow for more frontier manufacturing and materials science breakthroughs.

🚨 CHINESE SCIENTISTS JUST INVENTED 3D PRINTING THAT CREATES OBJECTS IN 0.6 SECONDS USING ONLY LIGHT. Researchers at Tsinghua University have developed a new method called DISH (Digital Incoherent Synthesis of Holographic light fields) that can print complex millimeter-scale objects almost instantly. Instead of slowly building layer by layer, the system fires thousands of precisely patterned light images from multiple angles into a still vat of liquid resin. Where the light overlaps, the resin instantly hardens into a solid 3D object. The entire process takes just 0.6 seconds. Why this matters: • It’s currently the fastest volumetric 3D printing method ever demonstrated • Achieves extremely fine detail features thinner than a human hair • The resin stays completely still, so there’s no vibration or distortion • It can work with watery (low-viscosity) resins, making it suitable for biological applications • The team has already printed complex structures like blood vessel-like tubes and even a tiny bust of a historical figure The deeper implication: Traditional 3D printing has always been limited by speed and the need to move either the print head or the resin. This approach removes both constraints by using light itself as the sculptor. Because it can print directly into still liquid (and potentially onto living tissue), it opens new possibilities in bioprinting, medical devices, and rapid manufacturing. If the technology can be scaled beyond millimeter sizes, it could fundamentally change how we think about making physical objects turning “print” from a slow process into something closer to instantaneous fabrication. We’re moving from “layer by layer” to “all at once.” How do you think instant volumetric 3D printing like this could change medicine, manufacturing, or everyday life if it becomes widely available? Follow for more frontier manufacturing and materials science breakthroughs.

TheNewPhysics

347,458 次观看 • 3 个月前

Ok so I've been teasing this Non-Planar print to show off another use case for the E3D #NippleNozzles besides belt printing but now its time to reveal the greater purpose. In collaboration with Michael Wüthrich we developed a technique to illustrate one of practical values of Non-Planar 3D Printing. It may not look like much now but you can clearly see there is much less friction imparted to the steel ball in the front ramp which was 3D Printed using Michaels current NP slicing process as compared to a traditional layer by layer topographical print. What are some other practical uses for Non-Planar? More on this soon!

Ok so I've been teasing this Non-Planar print to show off another use case for the E3D #NippleNozzles besides belt printing but now its time to reveal the greater purpose. In collaboration with Michael Wüthrich we developed a technique to illustrate one of practical values of Non-Planar 3D Printing. It may not look like much now but you can clearly see there is much less friction imparted to the steel ball in the front ramp which was 3D Printed using Michaels current NP slicing process as compared to a traditional layer by layer topographical print. What are some other practical uses for Non-Planar? More on this soon!

Pooch

26,574 次观看 • 3 年前

🚨 AMERICA JUST BUILT THE WORLD’S MOST POWERFUL METAL 3D PRINTER AND IT’S ABOUT TO MASS-PRODUCE ROCKETS AND MISSILES. Divergent Technologies has unveiled the Monolith One, a giant industrial metal printer standing over 8 meters tall and armed with 12 high-powered lasers delivering a combined 24 kilowatts of energy. Unlike typical 3D printers used for prototypes, this machine is built for serious, high-volume production. It can print large, complex aerospace and defense parts in aluminum, titanium, steel, and nickel alloys and it roughly doubles the output of current systems. Why this matters: • Divergent plans to install 64 more of these machines in a massive new 430,000 sq ft factory in Long Beach, California • Once running, the facility aims to produce tens of thousands of munition airframes per year plus hundreds of thousands of critical metal components • It slashes manufacturing time from months down to weeks or even days • The company already supplies major players like Lockheed Martin and RTX The deeper implication: This isn’t just another 3D printer. It represents a shift toward software-defined, on-demand manufacturing at industrial scale for mission-critical hardware. As defense and aerospace demand skyrockets, traditional supply chains are too slow. Systems like Monolith One could become a cornerstone of faster, more resilient domestic production especially for complex structures that are difficult or impossible to make conventionally. We’re watching the industrialization of additive manufacturing in real time. How do you think large-scale 3D printing will change aerospace and defense manufacturing over the next decade? Follow for more frontier manufacturing and defense technology.

🚨 AMERICA JUST BUILT THE WORLD’S MOST POWERFUL METAL 3D PRINTER AND IT’S ABOUT TO MASS-PRODUCE ROCKETS AND MISSILES. Divergent Technologies has unveiled the Monolith One, a giant industrial metal printer standing over 8 meters tall and armed with 12 high-powered lasers delivering a combined 24 kilowatts of energy. Unlike typical 3D printers used for prototypes, this machine is built for serious, high-volume production. It can print large, complex aerospace and defense parts in aluminum, titanium, steel, and nickel alloys and it roughly doubles the output of current systems. Why this matters: • Divergent plans to install 64 more of these machines in a massive new 430,000 sq ft factory in Long Beach, California • Once running, the facility aims to produce tens of thousands of munition airframes per year plus hundreds of thousands of critical metal components • It slashes manufacturing time from months down to weeks or even days • The company already supplies major players like Lockheed Martin and RTX The deeper implication: This isn’t just another 3D printer. It represents a shift toward software-defined, on-demand manufacturing at industrial scale for mission-critical hardware. As defense and aerospace demand skyrockets, traditional supply chains are too slow. Systems like Monolith One could become a cornerstone of faster, more resilient domestic production especially for complex structures that are difficult or impossible to make conventionally. We’re watching the industrialization of additive manufacturing in real time. How do you think large-scale 3D printing will change aerospace and defense manufacturing over the next decade? Follow for more frontier manufacturing and defense technology.

TheNewPhysics

80,575 次观看 • 3 个月前

One of the least understood systems in aerospace manufacturing is the BeAM Magic 800 directed energy deposition platform used for printing turbine nozzles and hot-section components. It uses a laser to melt metal powder or wire feedstock, depositing material layer by layer with positioning accuracy in the 20-50 micron range, building complex nickel superalloy structures that can withstand extreme thermal cycling. A full industrial setup can cost $800,000 to $1.5M+ The materials are not simple metals, but aerospace-grade alloys like Inconel 718 and 625, designed to survive temperatures above 700-900°C while resisting creep and oxidation. But the printed part is never the final part. Critical sealing surfaces, flanges, and precision interfaces are still finished on CNC machines to tolerances under 10 microns, because additive alone cannot guarantee repeatable surface integrity under flight loads. Video :- Fictiv

One of the least understood systems in aerospace manufacturing is the BeAM Magic 800 directed energy deposition platform used for printing turbine nozzles and hot-section components. It uses a laser to melt metal powder or wire feedstock, depositing material layer by layer with positioning accuracy in the 20-50 micron range, building complex nickel superalloy structures that can withstand extreme thermal cycling. A full industrial setup can cost $800,000 to $1.5M+ The materials are not simple metals, but aerospace-grade alloys like Inconel 718 and 625, designed to survive temperatures above 700-900°C while resisting creep and oxidation. But the printed part is never the final part. Critical sealing surfaces, flanges, and precision interfaces are still finished on CNC machines to tolerances under 10 microns, because additive alone cannot guarantee repeatable surface integrity under flight loads. Video :- Fictiv

Ammanichanda

69,921 次观看 • 2 个月前

Rhuna has powered more than 165 live events, served over 2M users, and processed $90M+ in volume across its existing infrastructure. At this scale, latency, fragmentation, and settlement uncertainty can have a massive impact on hundreds of thousands of live users. By integrating OmniSet, Rhuna taps into a unified liquidity and settlement layer that can coordinate payments and digital assets across ecosystems. Built on FastSet, OmniSet delivers fast, verifiable settlement that holds up under real-world demand, making it suitable for high-throughput environments like live events. This partnership reflects Pi²’s focus on deploying infrastructure where performance and reliability are essential.

Rhuna has powered more than 165 live events, served over 2M users, and processed $90M+ in volume across its existing infrastructure. At this scale, latency, fragmentation, and settlement uncertainty can have a massive impact on hundreds of thousands of live users. By integrating OmniSet, Rhuna taps into a unified liquidity and settlement layer that can coordinate payments and digital assets across ecosystems. Built on FastSet, OmniSet delivers fast, verifiable settlement that holds up under real-world demand, making it suitable for high-throughput environments like live events. This partnership reflects Pi²’s focus on deploying infrastructure where performance and reliability are essential.

Pi Squared

11,613 次观看 • 9 个月前

Multi-axis 3D printing with curved layers! 🖨️ Researchers from the The University of Manchester introduced a neural network-based computational pipeline as a representation-agnostic slicer for multi-axis 3D printing. Traditional 3D printing works like stacking pancakes, flat layers on top of each other. 🥞 This often requires temporary support structures that get thrown away after printing, wastes material, and creates weaker parts. Multi-axis 3D printing can print along curved paths that follow the object's natural shape. This eliminates support structures and makes stronger parts. But figuring out these curved paths is mathematically complex, you need to avoid collisions, respect what the printer can physically do, and optimize for strength. The neural network solves this automatically. It learns to create a "field" around the object, then extracts curved printing paths from this field. Because the entire process is differentiable (translation for non-math specialists, meaning you can optimize it end-to-end), the AI can directly optimize for manufacturing goals like "no support structures needed" and "make it as strong as possible." Here's the project: ~~ ♻️ Join the weekly robotics newsletter, and never miss any news →

Multi-axis 3D printing with curved layers! 🖨️ Researchers from the The University of Manchester introduced a neural network-based computational pipeline as a representation-agnostic slicer for multi-axis 3D printing. Traditional 3D printing works like stacking pancakes, flat layers on top of each other. 🥞 This often requires temporary support structures that get thrown away after printing, wastes material, and creates weaker parts. Multi-axis 3D printing can print along curved paths that follow the object's natural shape. This eliminates support structures and makes stronger parts. But figuring out these curved paths is mathematically complex, you need to avoid collisions, respect what the printer can physically do, and optimize for strength. The neural network solves this automatically. It learns to create a "field" around the object, then extracts curved printing paths from this field. Because the entire process is differentiable (translation for non-math specialists, meaning you can optimize it end-to-end), the AI can directly optimize for manufacturing goals like "no support structures needed" and "make it as strong as possible." Here's the project: ~~ ♻️ Join the weekly robotics newsletter, and never miss any news →

Lukas Ziegler

57,048 次观看 • 6 个月前

🚨 SCIENTISTS JUST INVENTED A WAY TO PRINT CIRCUIT BOARDS WITH LIQUID METAL AND IT LOOKS LIKE SOMETHING OUT OF TERMINATOR. A startup called Itera has developed a system that can create working PCB prototypes in minutes instead of weeks. You upload your design, and electric fields force a liquid metal alloy into the exact shape of the traces on a glass substrate. The board is then tested and ready almost instantly. Why this matters: • Traditional PCB prototyping can take days or even weeks this could reduce it to minutes • It uses liquid metal instead of etched copper, making it potentially much faster and more flexible for rapid iteration • Backed by $12 million in funding, the company is already focusing on single-layer boards with surface-mount components • The process looks genuinely futuristic glowing rivers of metal flowing into place on command The deeper implication is enormous: We may be watching the beginning of a completely new era of hardware development. Instead of waiting days for a prototype, engineers and makers could design, test, and iterate multiple versions in a single afternoon. This could dramatically speed up innovation in electronics, robotics, AI hardware, and even consumer devices. What happens when making a new circuit board becomes as fast and easy as printing a document? Follow for more frontier physics and future technology.

🚨 SCIENTISTS JUST INVENTED A WAY TO PRINT CIRCUIT BOARDS WITH LIQUID METAL AND IT LOOKS LIKE SOMETHING OUT OF TERMINATOR. A startup called Itera has developed a system that can create working PCB prototypes in minutes instead of weeks. You upload your design, and electric fields force a liquid metal alloy into the exact shape of the traces on a glass substrate. The board is then tested and ready almost instantly. Why this matters: • Traditional PCB prototyping can take days or even weeks this could reduce it to minutes • It uses liquid metal instead of etched copper, making it potentially much faster and more flexible for rapid iteration • Backed by $12 million in funding, the company is already focusing on single-layer boards with surface-mount components • The process looks genuinely futuristic glowing rivers of metal flowing into place on command The deeper implication is enormous: We may be watching the beginning of a completely new era of hardware development. Instead of waiting days for a prototype, engineers and makers could design, test, and iterate multiple versions in a single afternoon. This could dramatically speed up innovation in electronics, robotics, AI hardware, and even consumer devices. What happens when making a new circuit board becomes as fast and easy as printing a document? Follow for more frontier physics and future technology.

TheNewPhysics

19,878 次观看 • 3 个月前

This is the kind of project that quietly changes an industry. Instead of using traditional slicers, this creator built an app that converts hand-drawn curves directly into printable G-code for spiral vase mode prints. App → G-code → Print. - No complicated workflow. - No heavy setup. - Just turning ideas into physical objects almost instantly. The interesting part isn’t just the print quality. It’s how tools are becoming so simple that more people can create complex things without needing advanced technical knowledge. Would tools like this make 3D printing finally mainstream? 🎥 Media: ( Instagram ) ⚠️ This content is shared for informational purposes only. CTO Robotics Media is a media platform and does not own or develop the technology shown. Credit belongs to the original creators.

This is the kind of project that quietly changes an industry. Instead of using traditional slicers, this creator built an app that converts hand-drawn curves directly into printable G-code for spiral vase mode prints. App → G-code → Print. - No complicated workflow. - No heavy setup. - Just turning ideas into physical objects almost instantly. The interesting part isn’t just the print quality. It’s how tools are becoming so simple that more people can create complex things without needing advanced technical knowledge. Would tools like this make 3D printing finally mainstream? 🎥 Media: ( Instagram ) ⚠️ This content is shared for informational purposes only. CTO Robotics Media is a media platform and does not own or develop the technology shown. Credit belongs to the original creators.

CTO ROBOTICS Media

132,290 次观看 • 4 个月前

A metal origami! 🪭 This method is called Hyperbolic Metal Forming and is hypnotizing to watch. Instead of shaping metal with slow mechanical force, HMF uses controlled shockwaves to form complex geometries at extreme speed, often without the need for heavy dies or post-processing. The result is stronger, lighter parts with shapes that are almost impossible using traditional stamping. That’s why you see it popping up in aerospace, automotive structures, and defense components. Think of it like metal origami, but driven by high-energy pulses instead of presses. A small reminder that some things in manufacturing come from physics, not just automation. ~~ ♻️ Join the weekly robotics newsletter, and never miss any news →

A metal origami! 🪭 This method is called Hyperbolic Metal Forming and is hypnotizing to watch. Instead of shaping metal with slow mechanical force, HMF uses controlled shockwaves to form complex geometries at extreme speed, often without the need for heavy dies or post-processing. The result is stronger, lighter parts with shapes that are almost impossible using traditional stamping. That’s why you see it popping up in aerospace, automotive structures, and defense components. Think of it like metal origami, but driven by high-energy pulses instead of presses. A small reminder that some things in manufacturing come from physics, not just automation. ~~ ♻️ Join the weekly robotics newsletter, and never miss any news →

Lukas Ziegler

567,473 次观看 • 10 个月前

Laser treatment is a modern medical technique that can reduce or even remove wound marks (scars) by carefully targeting the skin with concentrated light energy. It's commonly used in. When a laser is applied to a scar, it works in two main ways. First, it removes the damaged outer layer of skin, allowing fresh, healthier skin to grow in its place. Second, it stimulates the production of collagen-a protein that helps keep skin smooth and firm. Over time, this process can make scars appear lighter, flatter, and less noticeable. There are different types of lasers used depending on the scar. For example, ablative lasers remove thin layers of skin, while non-ablative lasers go deeper without damaging the surface. These treatments are often used for acne scars, surgical scars, and injury marks. However, complete removal is not always guaranteed-most treatments significantly improve the appearance rather than erase scars completely. The procedure is usually quick and done by a dermatologist, but it may require multiple sessions. Some redness, swelling, or mild discomfort can occur afterward, and proper aftercare is important for healing. In simple terms, laser treatment doesn't magically erase scars-it helps your skin repair itself in a more even and natural way.

Laser treatment is a modern medical technique that can reduce or even remove wound marks (scars) by carefully targeting the skin with concentrated light energy. It's commonly used in. When a laser is applied to a scar, it works in two main ways. First, it removes the damaged outer layer of skin, allowing fresh, healthier skin to grow in its place. Second, it stimulates the production of collagen-a protein that helps keep skin smooth and firm. Over time, this process can make scars appear lighter, flatter, and less noticeable. There are different types of lasers used depending on the scar. For example, ablative lasers remove thin layers of skin, while non-ablative lasers go deeper without damaging the surface. These treatments are often used for acne scars, surgical scars, and injury marks. However, complete removal is not always guaranteed-most treatments significantly improve the appearance rather than erase scars completely. The procedure is usually quick and done by a dermatologist, but it may require multiple sessions. Some redness, swelling, or mild discomfort can occur afterward, and proper aftercare is important for healing. In simple terms, laser treatment doesn't magically erase scars-it helps your skin repair itself in a more even and natural way.

Dr Honey choudhary 🩺

11,694 次观看 • 3 个月前

This is an 80,000-tonne hydraulic forging press from China’s Northern Heavy Industries, one of the largest metal-forming machines ever built. But it is not simply a machine that bends metal like traditional presses do. At this scale, forging is about changing the internal structure of the material itself, compressing the metal, refining its molecular grain flow and eliminating hidden defects that could cause failure decades later. Machines like this are used to create some of the most critical components on Earth, aircraft landing gear, titanium aerospace structures, nuclear reactor components, massive gas turbine rotors and ship propulsion shafts. The metals being forged are among the most advanced engineering materials available, ultra-high-strength steels, titanium alloys and nickel-based superalloys designed to survive extreme temperatures, pressure and millions of fatigue cycles. An 80,000-tonne press is an industrial ecosystem by itself. The press, hydraulic systems, furnaces, manipulators and supporting infrastructure can require hundreds of millions of dollars in investment, with hydraulic systems requiring tens of megawatts of power to control forces equivalent to thousands of tonnes. The biggest industrial machines often do not make the final products. They make the materials that make those products possible.

This is an 80,000-tonne hydraulic forging press from China’s Northern Heavy Industries, one of the largest metal-forming machines ever built. But it is not simply a machine that bends metal like traditional presses do. At this scale, forging is about changing the internal structure of the material itself, compressing the metal, refining its molecular grain flow and eliminating hidden defects that could cause failure decades later. Machines like this are used to create some of the most critical components on Earth, aircraft landing gear, titanium aerospace structures, nuclear reactor components, massive gas turbine rotors and ship propulsion shafts. The metals being forged are among the most advanced engineering materials available, ultra-high-strength steels, titanium alloys and nickel-based superalloys designed to survive extreme temperatures, pressure and millions of fatigue cycles. An 80,000-tonne press is an industrial ecosystem by itself. The press, hydraulic systems, furnaces, manipulators and supporting infrastructure can require hundreds of millions of dollars in investment, with hydraulic systems requiring tens of megawatts of power to control forces equivalent to thousands of tonnes. The biggest industrial machines often do not make the final products. They make the materials that make those products possible.

Ammanichanda

231,269 次观看 • 1 个月前

I showed this video to a few friends before telling them it was AI. Every single one believed it was a real creator. They thought someone had picked up a camera, filmed the shots, recorded the voiceover, and edited everything together. None of that happened. The person isn't real. The voice isn't real. The video wasn't filmed. The entire thing was created using Arcads AI. What's fascinating isn't just how realistic the face looks—it's the tiny details. The natural expressions, the eye contact, the pacing, the body language, and the way everything comes together to feel like authentic UGC. We're moving into a world where creating high-quality content no longer requires a camera, actors, or a production team. If you have an idea, AI can turn it into a video in minutes. This technology is improving incredibly fast, and the gap between AI-generated content and traditional creator content is getting smaller with every update. If you're a founder, marketer, or creator, it's worth paying attention. Comment "Send" and I'll share the exact workflow I used to create this video.

I showed this video to a few friends before telling them it was AI. Every single one believed it was a real creator. They thought someone had picked up a camera, filmed the shots, recorded the voiceover, and edited everything together. None of that happened. The person isn't real. The voice isn't real. The video wasn't filmed. The entire thing was created using Arcads AI. What's fascinating isn't just how realistic the face looks—it's the tiny details. The natural expressions, the eye contact, the pacing, the body language, and the way everything comes together to feel like authentic UGC. We're moving into a world where creating high-quality content no longer requires a camera, actors, or a production team. If you have an idea, AI can turn it into a video in minutes. This technology is improving incredibly fast, and the gap between AI-generated content and traditional creator content is getting smaller with every update. If you're a founder, marketer, or creator, it's worth paying attention. Comment "Send" and I'll share the exact workflow I used to create this video.

Oliver

12,928 次观看 • 1 个月前

🚨 Quantum computers don’t run on electricity. They run on light. And that’s been the problem. Each quantum system needs very specific laser colors to control atoms and qubits. Until now… those lasers were: huge expensive stuck in labs But scientists just changed that. They built a chip that can generate ANY wavelength of light inside a tiny circuit. ~10,000 photonic circuits full spectrum control on a single chip This is massive. Because it means: Quantum computers could go from room-sized labs… to portable systems. So the real question is If we can control reality at the quantum level with light… what happens when that control fits in your hand? Follow me the future won’t be powered by electrons.

🚨 Quantum computers don’t run on electricity. They run on light. And that’s been the problem. Each quantum system needs very specific laser colors to control atoms and qubits. Until now… those lasers were: huge expensive stuck in labs But scientists just changed that. They built a chip that can generate ANY wavelength of light inside a tiny circuit. ~10,000 photonic circuits full spectrum control on a single chip This is massive. Because it means: Quantum computers could go from room-sized labs… to portable systems. So the real question is If we can control reality at the quantum level with light… what happens when that control fits in your hand? Follow me the future won’t be powered by electrons.

TheNewPhysics

14,321 次观看 • 5 个月前

Check out this Stereo4D paper from Google DeepMind. It's a pretty clever approach to a persistent problem in computer vision -- getting good training data for how things move in 3D. The key insight is using VR180 videos -- those stereo fisheye videos we launched back in 2017 for YouTubeVR. It was always clear that structured stereo datasets would be valuable for computer vision -- and we launched some powerful VR tools with it back in 2017 (link below). But what's the game changer now in 2024 is the scale -- they're providing 110K high quality clips :-) That's the kind of massive, real-world AI dataset that was just a dream back then! They're using it to train this model called DynaDUSt3R that can predict both 3D structure and motion from video frames. Which means it tracks how objects move between frames while simultaneously reconstructing their 3D shape. And given we're dealing with real stereoscopic content, results are notably better than synthetic data, giving you a faithful rendition of the real-world with a diverse set of subject matter. It's one of those through lines when tackling a timeless mission like mapping the world or spatial computing -- VR content created for immersion becoming the foundation for teaching machines to understand how the world moves. Sometimes innovation chains together in unexpected ways! Links to projects below⛓️

Check out this Stereo4D paper from Google DeepMind. It's a pretty clever approach to a persistent problem in computer vision -- getting good training data for how things move in 3D. The key insight is using VR180 videos -- those stereo fisheye videos we launched back in 2017 for YouTubeVR. It was always clear that structured stereo datasets would be valuable for computer vision -- and we launched some powerful VR tools with it back in 2017 (link below). But what's the game changer now in 2024 is the scale -- they're providing 110K high quality clips :-) That's the kind of massive, real-world AI dataset that was just a dream back then! They're using it to train this model called DynaDUSt3R that can predict both 3D structure and motion from video frames. Which means it tracks how objects move between frames while simultaneously reconstructing their 3D shape. And given we're dealing with real stereoscopic content, results are notably better than synthetic data, giving you a faithful rendition of the real-world with a diverse set of subject matter. It's one of those through lines when tackling a timeless mission like mapping the world or spatial computing -- VR content created for immersion becoming the foundation for teaching machines to understand how the world moves. Sometimes innovation chains together in unexpected ways! Links to projects below⛓️

Bilawal Sidhu

68,515 次观看 • 1 年前

Tesla's Ultra Red is one of the most expensive paint options in the lineup, and seeing it in person is an absolutely mind-blowing experience 🔥 To really understand why this color looks so incredible, we need to dive into how Tesla actually builds it from the ground up 👇 🎨 Unlike traditional car paint that uses a simple base and clear coat, Tesla uses an advanced multi-coat system applied by precision robotic sprayers. This technique builds the color layer by layer to create massive visual depth. 🚗 The process starts with a primer layer to ensure a perfectly smooth surface on the metal vehicle body. Once prepped, the factory robotics apply a high-chroma base coat. This initial layer contains rich red pigments that give the car its fundamental, vibrant color profile. ✨ Next comes the magic ingredient. The robots spray a metallic mid-coat over the solid base. This layer contains metallic flakes that catch the sunlight. Because this middle layer is slightly translucent, the base color shines from underneath while the metallic flakes reflect light in different directions. 🛡️ Finally, the car receives its finishing touch. Instead of a standard transparent protective seal, Tesla uses a specially tinted clear coat for these premium red finishes. This means the top protective layer actually has a hint of red mixed right into it to protect against UV rays while enhancing the color. 🔥 When you combine a vibrant base, a sparkling metallic middle, and a tinted protective shield on top, the result is exactly what we see on the road. The light travels through the tinted clear coat, bounces off the metallic flakes, and reflects the deep base pigment back to your eyes, giving Ultra Red its famous color-shifting glow. 🛠️ That mesmerizing depth is also exactly why fixing a scratch takes serious expertise. Known in the collision industry by its official paint code PR01, this specific tri-coat formula is notoriously tricky for human painters to replicate perfectly. 💸 Since that magical mid-coat gets darker with every single pass of the spray gun, body shops have to spray physical let-down test panels. They use these cards to match the exact factory thickness before they even think about touching the actual car. 🏎️ They also cannot just patch a single spot. Painters have to perform adjacent panel blending, fading the fresh paint deep into the surrounding undamaged doors or fenders to trick the human eye and hide the repair transition. It requires intense precision and labor, but the tradeoff is absolutely worth it for such a jaw-dropping look on the road.

Ming

149,017 次观看 • 1 个月前

Jeff Bezos just told you exactly how to price AI. Nobody listened. Bezos: “AI is real and it is going to change every industry. In fact it’s a very unusual technology in that regard in that it’s a horizontal enabling layer.” Horizontal enabling layer. Three words that reprice the entire technology sector. The iPhone was a vertical. One product. One new market. Electricity was a horizontal. One substrate that rewired every market on Earth. Wall Street is pricing AI like it is the next iPhone. Bezos is telling you it is the next electrical grid. Right now, thousands of companies are trying to sell AI as a product. A feature. A tool. A subscription tier. Every single one of them will be priced to zero. You do not sell a horizontal layer. You do not compete with it. You build on top of it or you disappear beneath it. For a century, entire industries survived on one thing. Complexity. The friction of navigating law, medicine, logistics, finance. That was the moat. If you could not memorize the maze, you could not compete. A horizontal layer does not navigate the maze. It dissolves the walls. Electricity did not compete with the candle industry. It erased the need for one. The most dangerous part of a horizontal shift is how quiet it is. It moves underneath the economy. The surface looks normal. Revenue still holds. Every day you operate on the old substrate, you accumulate a debt you cannot see and cannot repay. The internet repriced distribution. AI is repricing cognition itself. When intelligence becomes a utility that runs through the walls of every company on Earth, the premium on human expertise does not erode. It evaporates. This is not a disruption. Disruptions replace products. This replaces the ground you are standing on.

Jeff Bezos just told you exactly how to price AI. Nobody listened. Bezos: “AI is real and it is going to change every industry. In fact it’s a very unusual technology in that regard in that it’s a horizontal enabling layer.” Horizontal enabling layer. Three words that reprice the entire technology sector. The iPhone was a vertical. One product. One new market. Electricity was a horizontal. One substrate that rewired every market on Earth. Wall Street is pricing AI like it is the next iPhone. Bezos is telling you it is the next electrical grid. Right now, thousands of companies are trying to sell AI as a product. A feature. A tool. A subscription tier. Every single one of them will be priced to zero. You do not sell a horizontal layer. You do not compete with it. You build on top of it or you disappear beneath it. For a century, entire industries survived on one thing. Complexity. The friction of navigating law, medicine, logistics, finance. That was the moat. If you could not memorize the maze, you could not compete. A horizontal layer does not navigate the maze. It dissolves the walls. Electricity did not compete with the candle industry. It erased the need for one. The most dangerous part of a horizontal shift is how quiet it is. It moves underneath the economy. The surface looks normal. Revenue still holds. Every day you operate on the old substrate, you accumulate a debt you cannot see and cannot repay. The internet repriced distribution. AI is repricing cognition itself. When intelligence becomes a utility that runs through the walls of every company on Earth, the premium on human expertise does not erode. It evaporates. This is not a disruption. Disruptions replace products. This replaces the ground you are standing on.

Dustin

542,264 次观看 • 5 个月前

🚨 SCIENTISTS JUST BUILT A CHIP THAT CAN SEE, THINK, AND REMEMBER ALL AT THE SAME TIME. And it works more like a biological brain than a traditional computer. Researchers at RMIT University have created a neuromorphic vision chip that mimics the human eye and brain. Unlike conventional systems that capture images and send data to external processors, this chip performs sensing, processing, and memory storage directly where the light hits. The active layer is thousands of times thinner than a human hair. It uses doped indium oxide to detect light, process the information on-chip, and retain what it sees over time without constant electrical refreshing. Why this matters: • It dramatically cuts energy use and latency by eliminating data transfer to separate processors • Enables much faster real-time decision making for autonomous systems • Works more like biological vision than traditional machine vision • Could power the next generation of efficient edge AI in vehicles, robots, and remote sensors The deeper implication: For decades, we’ve built vision systems by bolting cameras, processors, and memory together like separate organs. This chip collapses those functions into one biological-style unit. It’s a step toward machines that don’t just “see” but actually perceive and remember in a more efficient, brain-like way. If scaled successfully, it could become a foundational component for autonomous systems that need to operate intelligently with minimal power and minimal delay. We’re moving from cameras that take pictures to chips that truly see. How do you think neuromorphic vision chips like this will change what’s possible for self-driving cars and autonomous robots? Follow for more frontier neuromorphic computing, AI hardware, and brain-inspired technology.

🚨 SCIENTISTS JUST BUILT A CHIP THAT CAN SEE, THINK, AND REMEMBER ALL AT THE SAME TIME. And it works more like a biological brain than a traditional computer. Researchers at RMIT University have created a neuromorphic vision chip that mimics the human eye and brain. Unlike conventional systems that capture images and send data to external processors, this chip performs sensing, processing, and memory storage directly where the light hits. The active layer is thousands of times thinner than a human hair. It uses doped indium oxide to detect light, process the information on-chip, and retain what it sees over time without constant electrical refreshing. Why this matters: • It dramatically cuts energy use and latency by eliminating data transfer to separate processors • Enables much faster real-time decision making for autonomous systems • Works more like biological vision than traditional machine vision • Could power the next generation of efficient edge AI in vehicles, robots, and remote sensors The deeper implication: For decades, we’ve built vision systems by bolting cameras, processors, and memory together like separate organs. This chip collapses those functions into one biological-style unit. It’s a step toward machines that don’t just “see” but actually perceive and remember in a more efficient, brain-like way. If scaled successfully, it could become a foundational component for autonomous systems that need to operate intelligently with minimal power and minimal delay. We’re moving from cameras that take pictures to chips that truly see. How do you think neuromorphic vision chips like this will change what’s possible for self-driving cars and autonomous robots? Follow for more frontier neuromorphic computing, AI hardware, and brain-inspired technology.

TheNewPhysics

23,196 次观看 • 3 个月前

Elon Musk is building a data center that no grid has to power and no county has to approve. Musk: “Think of it as a rack of compute in space.” Orbital hardware has always been custom. Each satellite is its own program, its own team, its own decade. SpaceX’s AI1 satellites are copies of each other. Each is built around a single Nvidia NVL72, the same rack-scale architecture running the largest data centers on the ground, redesigned to fly. Space stops being a program and becomes an inventory. Designing for orbit made the rack simpler and cheaper than the ground version, so SpaceX plans to run the space design in terrestrial data centers too. Racks alone have never made a data center. A thousand of them in a building with no network between them is a thousand computers. The interconnect is what turns them into one machine. Training a frontier model means moving enormous volumes of data between processors without pause, and the whole system runs at the speed of its slowest link. That is why the fabric between chips is fought over as hard as the chips themselves. Musk: “And then you can connect these racks of compute to either each other by the laser links, or directly to the Starlink constellation.” Light moves through glass at about two thirds of its speed in a vacuum, and fiber optic cable is glass. Every backbone route and undersea cable on Earth pays that tax. A laser between two satellites pays nothing. Over long distances, an orbital link arrives sooner than the same run in fiber. Orbit was supposed to be a trade, unlimited power in exchange for a worse network. The network is faster. The compute plugs into a delivery layer that is already finished. Thousands of satellites are up there right now carrying laser links, terminating at ground stations and dishes across most of the planet. The last mile was built years before the thing it delivers existed. Anyone else attempting this needs the rocket, the satellite bus, the solar manufacturing, the laser mesh, the ground network, and a supply line to a chipmaker. SpaceX had five of them before the project had a name. None of it was built for this. Starlink existed to sell internet subscriptions. The lasers existed so those subscriptions would work over open ocean. Starship existed for Mars. Nobody planned this. It assembled itself out of problems solved for other reasons. That is what twenty years of hard engineering leaves behind. Every previous expansion of human capability ran on a resource sitting inside somebody’s borders. Coal, oil, water, land. Sunlight in orbit belongs to nobody and never runs out. Compute still has an address. A building in Virginia, a substation, a county that had to approve it, a grid connection someone waited four years for. He is describing a version that only has an altitude.

Elon Musk is building a data center that no grid has to power and no county has to approve. Musk: “Think of it as a rack of compute in space.” Orbital hardware has always been custom. Each satellite is its own program, its own team, its own decade. SpaceX’s AI1 satellites are copies of each other. Each is built around a single Nvidia NVL72, the same rack-scale architecture running the largest data centers on the ground, redesigned to fly. Space stops being a program and becomes an inventory. Designing for orbit made the rack simpler and cheaper than the ground version, so SpaceX plans to run the space design in terrestrial data centers too. Racks alone have never made a data center. A thousand of them in a building with no network between them is a thousand computers. The interconnect is what turns them into one machine. Training a frontier model means moving enormous volumes of data between processors without pause, and the whole system runs at the speed of its slowest link. That is why the fabric between chips is fought over as hard as the chips themselves. Musk: “And then you can connect these racks of compute to either each other by the laser links, or directly to the Starlink constellation.” Light moves through glass at about two thirds of its speed in a vacuum, and fiber optic cable is glass. Every backbone route and undersea cable on Earth pays that tax. A laser between two satellites pays nothing. Over long distances, an orbital link arrives sooner than the same run in fiber. Orbit was supposed to be a trade, unlimited power in exchange for a worse network. The network is faster. The compute plugs into a delivery layer that is already finished. Thousands of satellites are up there right now carrying laser links, terminating at ground stations and dishes across most of the planet. The last mile was built years before the thing it delivers existed. Anyone else attempting this needs the rocket, the satellite bus, the solar manufacturing, the laser mesh, the ground network, and a supply line to a chipmaker. SpaceX had five of them before the project had a name. None of it was built for this. Starlink existed to sell internet subscriptions. The lasers existed so those subscriptions would work over open ocean. Starship existed for Mars. Nobody planned this. It assembled itself out of problems solved for other reasons. That is what twenty years of hard engineering leaves behind. Every previous expansion of human capability ran on a resource sitting inside somebody’s borders. Coal, oil, water, land. Sunlight in orbit belongs to nobody and never runs out. Compute still has an address. A building in Virginia, a substation, a county that had to approve it, a grid connection someone waited four years for. He is describing a version that only has an altitude.

Dustin

13,444 次观看 • 1 个月前