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Modern robotic wrist joints often use timing belt differentials to achieve smooth, multi-axis movement within compact spaces. By distributing motion through synchronized belt systems, a single actuator can control multiple rotational outputs with high precision. This design reduces weight, minimizes backlash, and allows for more efficient force transmission compared... show more

Mechanical Knowledge

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117,717 次观看 • 5 个月前 •via X (Twitter)

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NEURALINK: WHERE YOUR THOUGHTS LITERALLY CONTROL THE WORLD AROUND YOU It’s not imagination. It’s movement, precision, and control, all from the mind alone. •⁠ ⁠Neuralink bypasses broken pathways, restoring motion through direct brain signals •⁠ ⁠Thought turns into action in under 100ms: faster than most natural reflexes •⁠ ⁠Robotic limbs respond instantly, moving like seamless extensions of your body •⁠ ⁠Users play games, browse, and type with pure intention, no movement required •⁠ ⁠This is more than tech; it’s the foundation of human-AI symbiosis The mind-machine merge has started, rewriting what it means to be human forever. Source: xAI, Massachusetts Institute of Technology (MIT)

NEURALINK: WHERE YOUR THOUGHTS LITERALLY CONTROL THE WORLD AROUND YOU It’s not imagination. It’s movement, precision, and control, all from the mind alone. •⁠ ⁠Neuralink bypasses broken pathways, restoring motion through direct brain signals •⁠ ⁠Thought turns into action in under 100ms: faster than most natural reflexes •⁠ ⁠Robotic limbs respond instantly, moving like seamless extensions of your body •⁠ ⁠Users play games, browse, and type with pure intention, no movement required •⁠ ⁠This is more than tech; it’s the foundation of human-AI symbiosis The mind-machine merge has started, rewriting what it means to be human forever. Source: xAI, Massachusetts Institute of Technology (MIT)

Mario Nawfal

99,457 次观看 • 8 个月前

🤖 Robotic hands are evolving faster than we realize — and they’re learning to master our world. I find this both fascinating and a little unsettling. At first glance, these robotic hands still look awkward - stiff fingers, clumsy motion. But behind the scenes, every iteration brings: ➡️ Tighter sensors ➡️ Smarter control loops ➡️ Better training on human-designed objects Week by week, they move closer to something astonishing — not imitation, but mastery. They’re learning to grip, twist, and adapt to tools made for our anatomy. And once they reach human-level dexterity, they won’t stop there. They’ll surpass it — steadier than surgeons, faster than assembly lines, tireless and precise. This is more than robotics. It’s the moment machines stop mimicking us… and start outperforming us. How do we redefine “human skill” in a world where robots master it too? #AI #Robotics #Innovation #Technology #Automation #FutureOfWork #Engineering

🤖 Robotic hands are evolving faster than we realize — and they’re learning to master our world. I find this both fascinating and a little unsettling. At first glance, these robotic hands still look awkward - stiff fingers, clumsy motion. But behind the scenes, every iteration brings: ➡️ Tighter sensors ➡️ Smarter control loops ➡️ Better training on human-designed objects Week by week, they move closer to something astonishing — not imitation, but mastery. They’re learning to grip, twist, and adapt to tools made for our anatomy. And once they reach human-level dexterity, they won’t stop there. They’ll surpass it — steadier than surgeons, faster than assembly lines, tireless and precise. This is more than robotics. It’s the moment machines stop mimicking us… and start outperforming us. How do we redefine “human skill” in a world where robots master it too? #AI #Robotics #Innovation #Technology #Automation #FutureOfWork #Engineering

Pascal Bornet

97,943 次观看 • 8 个月前

Robora Sim: A PyBullet-Powered Environment for Learning Robotic Physical Intelligence We are currently building our Robora simulation environment setup for our sim based learning, leveraging PyBullet, an industry-standard physics engine widely used in AI-driven robotics research and development. The environment is optimized with GPU-accelerated learning algorithms, enabling high-speed imitation learning and reinforcement learning within a safe and controlled virtual setup before shipping out to real world. This simulation platform allows our models to learn, adapt, and generalize across different robot morphologies, terrain types and task objectives - all before deployment to the real world. At it's core, the system combines a VLA-powered high-level planner with low-level motion control algorithms, working cohesively to produce emergent, physically intelligent behaviors. This synergy between simulation, learning, and real-world transfer marks a major step forward in our pursuit of adaptive and intelligent robotic systems. Through advanced domain randomization and synthetic data generation, the Robora Simulation Environment ensures that policies trained in simulation transfer effectively to real-world robots, minimizing the sim-to-real gap. Moreover, users will be able to test and integrate their own hardware kits within selected simulation environments in the Robora Dapp, ensuring seamless compatibility and safer real-world implementation.

Robora Sim: A PyBullet-Powered Environment for Learning Robotic Physical Intelligence We are currently building our Robora simulation environment setup for our sim based learning, leveraging PyBullet, an industry-standard physics engine widely used in AI-driven robotics research and development. The environment is optimized with GPU-accelerated learning algorithms, enabling high-speed imitation learning and reinforcement learning within a safe and controlled virtual setup before shipping out to real world. This simulation platform allows our models to learn, adapt, and generalize across different robot morphologies, terrain types and task objectives - all before deployment to the real world. At it's core, the system combines a VLA-powered high-level planner with low-level motion control algorithms, working cohesively to produce emergent, physically intelligent behaviors. This synergy between simulation, learning, and real-world transfer marks a major step forward in our pursuit of adaptive and intelligent robotic systems. Through advanced domain randomization and synthetic data generation, the Robora Simulation Environment ensures that policies trained in simulation transfer effectively to real-world robots, minimizing the sim-to-real gap. Moreover, users will be able to test and integrate their own hardware kits within selected simulation environments in the Robora Dapp, ensuring seamless compatibility and safer real-world implementation.

Robora

23,522 次观看 • 11 个月前

5-Axis CNC machining of turbocharger impellers sits in the same league as aerospace manufacturing, precision engineering pushed to physical limits. These machines run with positional accuracy in the 1-5 micron range, spindle speeds of 20,000-40,000 RPM, and continuous 5-axis interpolation to carve complex blade geometry without collision, vibration, or thermal drift during cutting of nickel alloys and titanium. A production-grade 5-axis system for impellers typically costs $300,000 to $3 million+ The real constraint is not motion, but stability, suppressing chatter, tool deflection, and microscopic surface defects that would quietly destroy efficiency at 100,000+ RPM operating cycles. Without this class of machining, modern turbocharged engines, high-efficiency industrial compressors, and compact propulsion systems simply would not exist.

5-Axis CNC machining of turbocharger impellers sits in the same league as aerospace manufacturing, precision engineering pushed to physical limits. These machines run with positional accuracy in the 1-5 micron range, spindle speeds of 20,000-40,000 RPM, and continuous 5-axis interpolation to carve complex blade geometry without collision, vibration, or thermal drift during cutting of nickel alloys and titanium. A production-grade 5-axis system for impellers typically costs $300,000 to $3 million+ The real constraint is not motion, but stability, suppressing chatter, tool deflection, and microscopic surface defects that would quietly destroy efficiency at 100,000+ RPM operating cycles. Without this class of machining, modern turbocharged engines, high-efficiency industrial compressors, and compact propulsion systems simply would not exist.

Ammanichanda

48,750 次观看 • 3 个月前

Interestingly, Xynova’s technological approach shares the same origins as the dexterous hand technology used in Optimus v3 (though Elon has noted that this design still needs further refinement). The Flex2 is an upgraded version built on the Flex1: v1 featured 25 DOF and used a cable-driven system; the v2 introduces direct drive, which reduces the DOF to 23 but also sheds 400g in weight. It seems a hybrid drive mechanism may be the more practical solution. In March this year, following the successful completion of its Series A funding round (with investors including Xiaomi and others), this robotics company--founded in 2024--began construction of a large-scale production facility. Spanning over 5,000 square meters, the base is designed to achieve an annual output of 200,000 miniature electric cylinders and 10,000 dexterous hands. However, hardware alone is far from enough. A truly capable dexterous hand must be the result of the co-evolution of data, models, and the physical hardware. In other words, in addition to mass production, Xynova is simultaneously developing a complete integrated system that combines perception capabilities, robotic manipulation intelligence, and hand-specific coordination. This is essentially a foundational robotic module. Yet its applications go far beyond that. It can be directly adapted to industrial robotic arms on production lines, as well as integrated into the bodies of humanoid robots. That said, what I’m most eager to see is its use in advanced bionic prosthetics for humans. If it can successfully demonstrate this expanded capability, its impact will reach well beyond the realm of humanoid robots. (Cyborg)

Interestingly, Xynova’s technological approach shares the same origins as the dexterous hand technology used in Optimus v3 (though Elon has noted that this design still needs further refinement). The Flex2 is an upgraded version built on the Flex1: v1 featured 25 DOF and used a cable-driven system; the v2 introduces direct drive, which reduces the DOF to 23 but also sheds 400g in weight. It seems a hybrid drive mechanism may be the more practical solution. In March this year, following the successful completion of its Series A funding round (with investors including Xiaomi and others), this robotics company--founded in 2024--began construction of a large-scale production facility. Spanning over 5,000 square meters, the base is designed to achieve an annual output of 200,000 miniature electric cylinders and 10,000 dexterous hands. However, hardware alone is far from enough. A truly capable dexterous hand must be the result of the co-evolution of data, models, and the physical hardware. In other words, in addition to mass production, Xynova is simultaneously developing a complete integrated system that combines perception capabilities, robotic manipulation intelligence, and hand-specific coordination. This is essentially a foundational robotic module. Yet its applications go far beyond that. It can be directly adapted to industrial robotic arms on production lines, as well as integrated into the bodies of humanoid robots. That said, what I’m most eager to see is its use in advanced bionic prosthetics for humans. If it can successfully demonstrate this expanded capability, its impact will reach well beyond the realm of humanoid robots. (Cyborg)

CyberRobo

45,071 次观看 • 4 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

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

China now has its own “Bolt” — a robot named after sprint legend Usain Bolt. A Chinese research team has unveiled the world’s first full-size humanoid robot to reach a peak speed of 10 meters per second, setting a new global benchmark for humanoid running. Bolt runs like a body pushed to the limit. Its joints and power systems work in tight coordination, keeping it balanced even at sprint speed. Built to match the build of an adult man—1.75 meters tall and 75 kilograms—it is a life-sized system operating at the edge of physics. Compared with Usain Bolt’s iconic 9.58-second 100-meter world record, which many experts believe may stand for decades, the gap between humans and machines is narrowing fast. Chinese robots are now challenging the ceiling of human performance—much as AlphaGo once challenged Go champion Ke Jie. The breakthrough builds on earlier world-record achievements in high-speed robotic running and marks a giant leap for China in humanoid motion and control. Beyond records, Bolt also carries practical value: robots are leaving the lab and stepping into real-world settings—sports training, emergency response, and demanding industrial tasks where speed, balance and control truly matter.

China now has its own “Bolt” — a robot named after sprint legend Usain Bolt. A Chinese research team has unveiled the world’s first full-size humanoid robot to reach a peak speed of 10 meters per second, setting a new global benchmark for humanoid running. Bolt runs like a body pushed to the limit. Its joints and power systems work in tight coordination, keeping it balanced even at sprint speed. Built to match the build of an adult man—1.75 meters tall and 75 kilograms—it is a life-sized system operating at the edge of physics. Compared with Usain Bolt’s iconic 9.58-second 100-meter world record, which many experts believe may stand for decades, the gap between humans and machines is narrowing fast. Chinese robots are now challenging the ceiling of human performance—much as AlphaGo once challenged Go champion Ke Jie. The breakthrough builds on earlier world-record achievements in high-speed robotic running and marks a giant leap for China in humanoid motion and control. Beyond records, Bolt also carries practical value: robots are leaving the lab and stepping into real-world settings—sports training, emergency response, and demanding industrial tasks where speed, balance and control truly matter.

Sinical

111,438 次观看 • 7 个月前

This isn’t teleportation in the sci-fi sense. It’s something deeper and more fundamental. What’s actually happening is quantum state transfer, where information is reconstructed at another location using entanglement. But here’s the interesting part In my τ-framework, this works because reality isn’t continuous in the way we think. It’s structured through a time-field, where information exists as stable patterns across a temporal lattice. When two systems are entangled, they’re not “connected through space”… they’re sharing the same underlying time-structure. So the information doesn’t travel across distance. It reappears where the time-field allows the same pattern to stabilize. That’s why it looks instant. Not because it breaks physics but because it bypasses distance entirely. If this is correct, then teleportation isn’t movement… it’s reconstruction through temporal symmetry. The real question is: Can we control the time-field enough to scale this beyond quantum systems? Follow me for more answers

This isn’t teleportation in the sci-fi sense. It’s something deeper and more fundamental. What’s actually happening is quantum state transfer, where information is reconstructed at another location using entanglement. But here’s the interesting part In my τ-framework, this works because reality isn’t continuous in the way we think. It’s structured through a time-field, where information exists as stable patterns across a temporal lattice. When two systems are entangled, they’re not “connected through space”… they’re sharing the same underlying time-structure. So the information doesn’t travel across distance. It reappears where the time-field allows the same pattern to stabilize. That’s why it looks instant. Not because it breaks physics but because it bypasses distance entirely. If this is correct, then teleportation isn’t movement… it’s reconstruction through temporal symmetry. The real question is: Can we control the time-field enough to scale this beyond quantum systems? Follow me for more answers

TheNewPhysics

36,141 次观看 • 6 个月前

The difference between SEALSQ silicon-based spin-qubit QPUs and quantum processors built on superconducting circuits or trapped ions comes down to physics, manufacturability, and long-term industrial scalability. SEALSQ’s approach uses electron spins confined in silicon semiconductor structures—essentially quantum dots fabricated with CMOS-compatible processes—where the qubit is the spin state of an electron rather than a macroscopic electrical current or a free ion. This makes spin qubits orders of magnitude smaller, potentially allowing millions of qubits on a single silicon wafer, and critically aligns the technology with existing semiconductor fabs, supply chains, and design tools. In contrast, superconducting qubits rely on exotic materials and microwave resonators that are physically large, wiring-heavy, and difficult to scale beyond a few thousand qubits without massive cryogenic and control overhead. Trapped-ion systems achieve excellent qubit coherence but depend on ultra-high vacuum chambers, precision lasers, and optical alignment, making them closer to scientific instruments than manufacturable chips. Silicon spin qubits also benefit from long intrinsic coherence times (especially in isotopically purified silicon), low power dissipation, and a natural path to tight integration with classical control, cryogenic electronics, and security primitives—an area where SEALSQ’s semiconductor and hardware-security DNA becomes a strategic advantage. The trade-off is that spin qubits are technically harder to control at the single-qubit level and are earlier in large-scale deployment than superconducting systems, but if solved, they offer the most credible route to industrial-scale, cost-effective, secure quantum processors, rather than lab-scale demonstrations.

The difference between SEALSQ silicon-based spin-qubit QPUs and quantum processors built on superconducting circuits or trapped ions comes down to physics, manufacturability, and long-term industrial scalability. SEALSQ’s approach uses electron spins confined in silicon semiconductor structures—essentially quantum dots fabricated with CMOS-compatible processes—where the qubit is the spin state of an electron rather than a macroscopic electrical current or a free ion. This makes spin qubits orders of magnitude smaller, potentially allowing millions of qubits on a single silicon wafer, and critically aligns the technology with existing semiconductor fabs, supply chains, and design tools. In contrast, superconducting qubits rely on exotic materials and microwave resonators that are physically large, wiring-heavy, and difficult to scale beyond a few thousand qubits without massive cryogenic and control overhead. Trapped-ion systems achieve excellent qubit coherence but depend on ultra-high vacuum chambers, precision lasers, and optical alignment, making them closer to scientific instruments than manufacturable chips. Silicon spin qubits also benefit from long intrinsic coherence times (especially in isotopically purified silicon), low power dissipation, and a natural path to tight integration with classical control, cryogenic electronics, and security primitives—an area where SEALSQ’s semiconductor and hardware-security DNA becomes a strategic advantage. The trade-off is that spin qubits are technically harder to control at the single-qubit level and are earlier in large-scale deployment than superconducting systems, but if solved, they offer the most credible route to industrial-scale, cost-effective, secure quantum processors, rather than lab-scale demonstrations.

Carlos Creus Moreira

19,616 次观看 • 7 个月前

Cams ARE the original "programmable" automation - these mechanical marvels orchestrate complex sequences without a single line of code. By carefully profiling cam shapes, engineers encode timing, positioning, and sequencing directly into metal. What makes cams brilliant for automation: - Deterministic timing - no software, no edge cases - Self-synchronising - no syncing clocks of different systems - Incredibly durable - cam-driven machines run for decades - Simple maintenance - mechanics can "read" the program by looking at cam profiles The cam followers, springs, and linkages in machines like this execute intricate routines - bending, cutting, feeding, and positioning with clockwork precision. Each bump and valley on those rotating cams tells a different part of the machine exactly when to move. With all the dancing robots, we sometimes forget how high-tech old-school automation is.

Cams ARE the original "programmable" automation - these mechanical marvels orchestrate complex sequences without a single line of code. By carefully profiling cam shapes, engineers encode timing, positioning, and sequencing directly into metal. What makes cams brilliant for automation: - Deterministic timing - no software, no edge cases - Self-synchronising - no syncing clocks of different systems - Incredibly durable - cam-driven machines run for decades - Simple maintenance - mechanics can "read" the program by looking at cam profiles The cam followers, springs, and linkages in machines like this execute intricate routines - bending, cutting, feeding, and positioning with clockwork precision. Each bump and valley on those rotating cams tells a different part of the machine exactly when to move. With all the dancing robots, we sometimes forget how high-tech old-school automation is.

Jack 🤖

40,142 次观看 • 1 年前

AI-Powered weed control! 🌱 The LaserWeeder machine from Carbon Robotics has captured the imagination of American farmers. This technology uses AI system to identify weeds in crops and zap them with precision thermal bursts from lasers. Bit of facts about the cool robot: → The machine can remove weeds from over 40 crops and can also be used for thinning crops. → It can operate in virtually all weather conditions, with millimeter accuracy at all times, and can work through the night thanks to its built-in lighting system. → High-resolution cameras and computer machine learning enable it to distinguish weeds from crops in milliseconds. → The LaserWeeder can replace about 70 workers on farms where manual weeding is used, and can weed up to four acres per hour. What other applications can we expect to see in the future in farming applications? Btw. I believe farming robots are A HUGE THING in robotics! 🔥 ~~ ♻ Join the weekly robotics newsletter, and never miss any news →

AI-Powered weed control! 🌱 The LaserWeeder machine from Carbon Robotics has captured the imagination of American farmers. This technology uses AI system to identify weeds in crops and zap them with precision thermal bursts from lasers. Bit of facts about the cool robot: → The machine can remove weeds from over 40 crops and can also be used for thinning crops. → It can operate in virtually all weather conditions, with millimeter accuracy at all times, and can work through the night thanks to its built-in lighting system. → High-resolution cameras and computer machine learning enable it to distinguish weeds from crops in milliseconds. → The LaserWeeder can replace about 70 workers on farms where manual weeding is used, and can weed up to four acres per hour. What other applications can we expect to see in the future in farming applications? Btw. I believe farming robots are A HUGE THING in robotics! 🔥 ~~ ♻ Join the weekly robotics newsletter, and never miss any news →

Lukas Ziegler

54,776 次观看 • 9 个月前

This fact absolutely shatters evolution. ...And makes the intelligent design in Life certain. All the systems in Life that make things function - like everything that enables birds to fly - require a whole set of complex interconnected parts. Nothing works in isolation. Something evolutionists overlook is how the nature of all these systems are intricately interconnected. Every part relies on something else to make it work. You need the whole system, down to the DNA itself, or the function fails. This coordinattion between so many systems makes step-by-step evolution all but impossible. For instance... A wing isn’t just bones and feathers (or membrane). A wing requires a certain type of hollow bones, which the alleged ancestors of birds didn't have. And wings by themselves are useless - what reproductive benefit would wings have without the accompanying systems that lead to actual flight (the simultaneous requirements for bone pneumatization, muscle attachment sites, feather or membrane development, and the regulatory changes that control all of them)? Wings without these features would be harmful. Hollow bones without flight would be detrimental. The step-by-step path leading from non-bird to flying birds is filled with easily killed, unselectable intermediates. This is where evolutionists constantly fail - they look at modification in isolation, without considering that these systems are large, interconnected networks of functional parts all working together. And it all starts at the genetic level, from the DNA itself. DNA genes code for proteins. Regulatory information organizes when these proteins are built and how much should be made. Further regulatory systems coordinate where these proteins go after they’re built. And yet more informational networks place the proteins into the final system in coordination with other proteins. Then these protein systems are fit together to make entire organs, tissues, bones, etc. All of these systems and processes are coordinated from the DNA - which means major modification like turning a fish fin into a bird wing requires many coordinated DNA changes across the entire network. One change at a time simply cannot lead to the coordination of an entire multi-part coordinated system like this. A mutation that changes one protein would need another coordinated mutation to fit that mutated protein into the right place, which would require other proteins to be mutated to fit together into that system, which would also require yet more regulatory mutations to keep everything coordinated... Nothing works in isolation. It's all connected. Which is why it can't evolve one step at a time. One step at a time does nothing. Life requires all or nothing systems. Only intelligence can engineer all or nothing systems.

This fact absolutely shatters evolution. ...And makes the intelligent design in Life certain. All the systems in Life that make things function - like everything that enables birds to fly - require a whole set of complex interconnected parts. Nothing works in isolation. Something evolutionists overlook is how the nature of all these systems are intricately interconnected. Every part relies on something else to make it work. You need the whole system, down to the DNA itself, or the function fails. This coordinattion between so many systems makes step-by-step evolution all but impossible. For instance... A wing isn’t just bones and feathers (or membrane). A wing requires a certain type of hollow bones, which the alleged ancestors of birds didn't have. And wings by themselves are useless - what reproductive benefit would wings have without the accompanying systems that lead to actual flight (the simultaneous requirements for bone pneumatization, muscle attachment sites, feather or membrane development, and the regulatory changes that control all of them)? Wings without these features would be harmful. Hollow bones without flight would be detrimental. The step-by-step path leading from non-bird to flying birds is filled with easily killed, unselectable intermediates. This is where evolutionists constantly fail - they look at modification in isolation, without considering that these systems are large, interconnected networks of functional parts all working together. And it all starts at the genetic level, from the DNA itself. DNA genes code for proteins. Regulatory information organizes when these proteins are built and how much should be made. Further regulatory systems coordinate where these proteins go after they’re built. And yet more informational networks place the proteins into the final system in coordination with other proteins. Then these protein systems are fit together to make entire organs, tissues, bones, etc. All of these systems and processes are coordinated from the DNA - which means major modification like turning a fish fin into a bird wing requires many coordinated DNA changes across the entire network. One change at a time simply cannot lead to the coordination of an entire multi-part coordinated system like this. A mutation that changes one protein would need another coordinated mutation to fit that mutated protein into the right place, which would require other proteins to be mutated to fit together into that system, which would also require yet more regulatory mutations to keep everything coordinated... Nothing works in isolation. It's all connected. Which is why it can't evolve one step at a time. One step at a time does nothing. Life requires all or nothing systems. Only intelligence can engineer all or nothing systems.

Divinely Designed

47,292 次观看 • 1 个月前

recreated this exact hook with AI in 3 minutes generated first frame with nano banana -> uploaded it along with reference video to Kling motion control, done when the quality is actually there, AI UGC beats real creators every time we built the best system for this right now: - realistic visuals - realistic voice - realistic movement - all optimized for virality and conversions way cheaper than a real creator and built for scale across thousands of posts and multiple accounts this isn't generic AI slop, these are high quality systems built with real effort and ready to scale your business it works across ecom,apps, saas, coaching, DTC... everything yet people are still paying $300-500 per UGC video from creators who ghost halfway through the project

recreated this exact hook with AI in 3 minutes generated first frame with nano banana -> uploaded it along with reference video to Kling motion control, done when the quality is actually there, AI UGC beats real creators every time we built the best system for this right now: - realistic visuals - realistic voice - realistic movement - all optimized for virality and conversions way cheaper than a real creator and built for scale across thousands of posts and multiple accounts this isn't generic AI slop, these are high quality systems built with real effort and ready to scale your business it works across ecom,apps, saas, coaching, DTC... everything yet people are still paying $300-500 per UGC video from creators who ghost halfway through the project

MAX

171,662 次观看 • 6 个月前

New robot hands just dropped! But it seems to be missing a couple fingers. Tacta Systems Tacta Systems is a Palo Alto robotics startup that just came out of stealth, and raised with $75M and a dexterity platform, TactaBot, aimed at high-value manufacturing. TactaBot has three parts: - the Tacta Hand -> a human-scale robotic hand with 15 independently actuated joints, proprietary "Fluidic Tendon" actuation, pitched as reliable for millions of factory cycles. - the Tacta Sensor -> a tiny tactile sensor reading force from 250 Pa to 700,000 Pa, sampling at 400 Hz, resolving temperature to 0.1 °C. - Skill Capture -> a data system built around the Tacta Glove. It contains the same sensor embedded in a glove that factory workers wear. Sounds similar to what mimic is doing! Except with 3 fingers instead of 5. Tacta's vision sees 3 fingers as more than enough to complete all tasks, and less complex to simulate than 5. My opinion: Tacta is very strong at semiconductor/MEMS, their moat lies in their ability to manufacture their touch sensor as large as a grain of sand, not the hand or the model. One caveat though: there is no detail nor explanation of how the 5 finger data acquisition glove maps to the 3 finger hand -> I would love to learn more about it! This is where the interesting part of the tech is imho. If this does not work, then nothing does. Still, I have to admit it looks very cool, slick, and minimal, I love it:

New robot hands just dropped! But it seems to be missing a couple fingers. Tacta Systems Tacta Systems is a Palo Alto robotics startup that just came out of stealth, and raised with $75M and a dexterity platform, TactaBot, aimed at high-value manufacturing. TactaBot has three parts: - the Tacta Hand -> a human-scale robotic hand with 15 independently actuated joints, proprietary "Fluidic Tendon" actuation, pitched as reliable for millions of factory cycles. - the Tacta Sensor -> a tiny tactile sensor reading force from 250 Pa to 700,000 Pa, sampling at 400 Hz, resolving temperature to 0.1 °C. - Skill Capture -> a data system built around the Tacta Glove. It contains the same sensor embedded in a glove that factory workers wear. Sounds similar to what mimic is doing! Except with 3 fingers instead of 5. Tacta's vision sees 3 fingers as more than enough to complete all tasks, and less complex to simulate than 5. My opinion: Tacta is very strong at semiconductor/MEMS, their moat lies in their ability to manufacture their touch sensor as large as a grain of sand, not the hand or the model. One caveat though: there is no detail nor explanation of how the 5 finger data acquisition glove maps to the 3 finger hand -> I would love to learn more about it! This is where the interesting part of the tech is imho. If this does not work, then nothing does. Still, I have to admit it looks very cool, slick, and minimal, I love it:

Léo

15,474 次观看 • 1 个月前

A New Era with V3🪄 V3's new engine introduces significant advancements in output generation. Unlike V2, where the multi-model system processed prompts to produce a single output, V3 is designed to generate multiple outputs and logically link them together. This enhancement effectively removes limitations on output size, enabling more complex and expansive results. Key Features Seamless Multi-Output Generation: V3 has been trained to generate separate outputs and connect them logically. This advancement ensures that there are no longer any limitations on output size. Intelligent Image Creation: V3 improves image generation with better tools, allowing the AI to create as many images as needed and place them within the project’s context. It supports various formats like PNG, JPEG, SVG, and GLB. Web-Integrated Intelligence: V3 can now search the web for documentation and data, providing real-time context and up-to-date references. For example, if you run a restaurant and want to update your website, simply ask Alchemist AI to “generate this website in a more modern style,” and it will update all content accordingly. Improved Creativity and Output Quality: V3's creative capacity has significantly increased. Simple prompts now generate more complete and refined results, with the system efficiently combining multiple elements into cohesive outputs.

A New Era with V3🪄 V3's new engine introduces significant advancements in output generation. Unlike V2, where the multi-model system processed prompts to produce a single output, V3 is designed to generate multiple outputs and logically link them together. This enhancement effectively removes limitations on output size, enabling more complex and expansive results. Key Features Seamless Multi-Output Generation: V3 has been trained to generate separate outputs and connect them logically. This advancement ensures that there are no longer any limitations on output size. Intelligent Image Creation: V3 improves image generation with better tools, allowing the AI to create as many images as needed and place them within the project’s context. It supports various formats like PNG, JPEG, SVG, and GLB. Web-Integrated Intelligence: V3 can now search the web for documentation and data, providing real-time context and up-to-date references. For example, if you run a restaurant and want to update your website, simply ask Alchemist AI to “generate this website in a more modern style,” and it will update all content accordingly. Improved Creativity and Output Quality: V3's creative capacity has significantly increased. Simple prompts now generate more complete and refined results, with the system efficiently combining multiple elements into cohesive outputs.

ALCHEMIST AI 🔮

48,748 次观看 • 1 年前

NEW: After swearing in new recruits at the Los Angeles Military Entrance Processing Station (MEPS), Secretary of War Pete Hegseth departed for Divergent as part of his Arsenal Freedom Tour. Divergent Technologies, Inc. (Divergent) is a Torrance, California-based advanced manufacturing company specializing in defense and aerospace production. Its Divergent Adaptive Production System (DAPS) integrates AI-driven generative design, metal 3D printing, and automated robotic assembly to produce lightweight, high-performance structures rapidly and cost-effectively, reducing weight, part counts, and environmental impact compared to traditional methods. Since pivoting heavily into defense in 2022, Divergent has secured major contracts with prime contractors including General Atomics, Lockheed Martin, Raytheon, and Triumph Group. These cover everything from sustainment parts to full airframe systems and hypersonic components. One thing that makes Divergent unique is they only hire US persons, and they are 100% independent from Chinese supply chains. The company raised $290 million in Series E funding in September 2025, achieving a $2.3 billion valuation to scale production for U.S. military needs. Hegseth’s Pete Hegseth Arsenal Freedom Tour highlights innovative defense manufacturing, AI integration, and technologies to strengthen the U.S. Defense Industrial Base under President Trump's peace-through-strength agenda. Hegseth is traveling with press, myself included, to showcase companies like Divergent that enable faster, more agile production for warfighters. This visit aligns with the Trump administration's push to revitalize American defense manufacturing and rapidly field emerging technologies.

NEW: After swearing in new recruits at the Los Angeles Military Entrance Processing Station (MEPS), Secretary of War Pete Hegseth departed for Divergent as part of his Arsenal Freedom Tour. Divergent Technologies, Inc. (Divergent) is a Torrance, California-based advanced manufacturing company specializing in defense and aerospace production. Its Divergent Adaptive Production System (DAPS) integrates AI-driven generative design, metal 3D printing, and automated robotic assembly to produce lightweight, high-performance structures rapidly and cost-effectively, reducing weight, part counts, and environmental impact compared to traditional methods. Since pivoting heavily into defense in 2022, Divergent has secured major contracts with prime contractors including General Atomics, Lockheed Martin, Raytheon, and Triumph Group. These cover everything from sustainment parts to full airframe systems and hypersonic components. One thing that makes Divergent unique is they only hire US persons, and they are 100% independent from Chinese supply chains. The company raised $290 million in Series E funding in September 2025, achieving a $2.3 billion valuation to scale production for U.S. military needs. Hegseth’s Pete Hegseth Arsenal Freedom Tour highlights innovative defense manufacturing, AI integration, and technologies to strengthen the U.S. Defense Industrial Base under President Trump's peace-through-strength agenda. Hegseth is traveling with press, myself included, to showcase companies like Divergent that enable faster, more agile production for warfighters. This visit aligns with the Trump administration's push to revitalize American defense manufacturing and rapidly field emerging technologies.

Laura Loomer

109,862 次观看 • 8 个月前

5-axis CNC machining – but different... Most 5-axis machines use serial kinematics: stack a rotary A-axis on top of a rotary B-axis, mount that on linear X/Y/Z stages. Each axis carries the weight of everything after it. Heavy and slow. 🤖 The Sprint Z3 uses parallel kinematics: three linear drives working together to create BOTH the Z-axis motion AND the A/B tilt simultaneously. No stacked rotary joints. No heavy tilting head carrying a motor on top of another motor. The entire barrel-shaped headstock moves as one unit vertically in the column, while the three internal drives handle the spindle positioning and orientation. ⚙️ How it works: Three linear actuators are arranged in a circle, all connected to the spindle platform through pivot arms. - Extend all three equally → spindle moves straight up/down (Z-axis) - Extend them different amounts → spindle tilts (A/B axes) It's using geometry instead of stacked rotary joints to create tilt 🤔 Why this is useful: Way less moving mass than serial kinematics. Less mass = faster accelerations, higher precision, better surface finish. For high-speed machining, dynamics matter more than workspace. Question: Is this a good design or overcomplicated❓

5-axis CNC machining – but different... Most 5-axis machines use serial kinematics: stack a rotary A-axis on top of a rotary B-axis, mount that on linear X/Y/Z stages. Each axis carries the weight of everything after it. Heavy and slow. 🤖 The Sprint Z3 uses parallel kinematics: three linear drives working together to create BOTH the Z-axis motion AND the A/B tilt simultaneously. No stacked rotary joints. No heavy tilting head carrying a motor on top of another motor. The entire barrel-shaped headstock moves as one unit vertically in the column, while the three internal drives handle the spindle positioning and orientation. ⚙️ How it works: Three linear actuators are arranged in a circle, all connected to the spindle platform through pivot arms. - Extend all three equally → spindle moves straight up/down (Z-axis) - Extend them different amounts → spindle tilts (A/B axes) It's using geometry instead of stacked rotary joints to create tilt 🤔 Why this is useful: Way less moving mass than serial kinematics. Less mass = faster accelerations, higher precision, better surface finish. For high-speed machining, dynamics matter more than workspace. Question: Is this a good design or overcomplicated❓

Jack 🤖

121,259 次观看 • 10 个月前

🚨 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