Video yükleniyor...

Video Yüklenemedi

Ana Sayfaya Dön

Polymorphic moulding: a manufacturing method that forms parts using a grid of computer-controlled pins: Each pin can move up or down independently, so together they shape a surface that acts like a custom mould. Instead of building a fixed mould for every product, the machine quickly repositions the pins...

IlirAliu_'s profile picture

Ilir Aliu

51,895 subscribers

38,234 görüntüleme • 4 ay önce •via X (Twitter)

LIVE

Anya Rossi• Live Now

Private livecam show

0 Yorum

Yorum bulunmuyor

Orijinal gönderinin yorumları burada görünecek

Benzer Videolar

Micro concrete is a great option for bathrooms and kitchens, as it provides a hygienic and stain-free surface. What is more, the material is anti-slip and mould-free – making it a fantastic choice for floor surfaces inside and out
0:12

Micro concrete is a great option for bathrooms and kitchens, as it provides a hygienic and stain-free surface. What is more, the material is anti-slip and mould-free – making it a fantastic choice for floor surfaces inside and out

Viralfizz

100,526 görüntüleme • 3 ay önce

AI in robotics gets all the attention right now, but sometimes the most interesting work is very practical. Viet built a small vision system that counts potatoes on a conveyor belt. No giant dataset. No huge model. Just a clear problem and a smart setup. He used Ultralytics’ ObjectCounter, trained a tiny YOLO11 nano model, and because there was no potato dataset, he annotated a single frame with SAM 2 and trained from that. One frame. Still works across the whole video. It is a good reminder that useful AI in industry often looks like this. Focused. Lightweight. Solves a real task. If you work in manufacturing or robotics, these small systems are usually the fastest wins. They save time, reduce errors, and do not need massive infrastructure. Nice work, Viet. His projects: —- Weekly robotics and AI insights. Subscribe free:
0:13

AI in robotics gets all the attention right now, but sometimes the most interesting work is very practical. Viet built a small vision system that counts potatoes on a conveyor belt. No giant dataset. No huge model. Just a clear problem and a smart setup. He used Ultralytics’ ObjectCounter, trained a tiny YOLO11 nano model, and because there was no potato dataset, he annotated a single frame with SAM 2 and trained from that. One frame. Still works across the whole video. It is a good reminder that useful AI in industry often looks like this. Focused. Lightweight. Solves a real task. If you work in manufacturing or robotics, these small systems are usually the fastest wins. They save time, reduce errors, and do not need massive infrastructure. Nice work, Viet. His projects: —- Weekly robotics and AI insights. Subscribe free:

Ilir Aliu

1,674,953 görüntüleme • 7 ay önce

🚨 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.
0:10

🚨 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 görüntüleme • 1 ay önce

Coding software is a joke compared to building hardware. Because when a software fails, it can be fixed quickly. In hardware, one mistake can set you back for months or end you. In hardware, every decision is cash flow. Every tiny error can cost tens of 1000s of dollars. You don’t get second chances. You get lessons, paid for in time and money. But when you finally get it right… You don’t just ship a product. You build a legacy. Something people touch, use, and trust for years. That’s the beauty and the pain of building in the real world.
0:11

Coding software is a joke compared to building hardware. Because when a software fails, it can be fixed quickly. In hardware, one mistake can set you back for months or end you. In hardware, every decision is cash flow. Every tiny error can cost tens of 1000s of dollars. You don’t get second chances. You get lessons, paid for in time and money. But when you finally get it right… You don’t just ship a product. You build a legacy. Something people touch, use, and trust for years. That’s the beauty and the pain of building in the real world.

Prakash Dadlani

12,402 görüntüleme • 8 ay önce

The future of footwear may not be manufactured in bulk. It may be fabricated around you. That is what makes this shift so interesting to me. 3D-printed footwear is moving from novelty to a real industrial model, with market forecasts pointing to rapid growth over the next decade. At the same time, brands and manufacturers are using additive manufacturing, digital design, and custom-fit workflows to shorten development cycles and make more personalized products viable. What is new here is not just the printer. It is the system around it: → scan the foot → model the fit digitally → print the part on demand → produce closer to the customer That matters. Because once footwear becomes data-driven and locally fabricated, several things change fast: → fit gets more personal → prototyping gets faster → waste drops because you do not overproduce → inventory pressure falls because you do not need to guess demand the same way To me, that is the bigger signal. This is not just about a better sneaker. It is about a different manufacturing logic. Formlabs notes that 3D printing already enables customized orthotics with better biomechanical precision, lower material waste, and simpler digital workflows. McKinsey has also pointed to digitization and 3D design as a way to shorten design cycles and reduce sampling iterations in apparel and footwear. And once that logic matures, the use cases get much bigger: → custom athletic footwear built from gait and pressure data → hospitals producing orthotics faster and closer to the patient → micro-factories making products on demand instead of stocking shelves → footwear designed for one body, not an average body That is why I think this matters now. The question is no longer whether personalized fabrication is possible. It is whether brands move fast enough before customers start expecting every product to fit like it was made only for them. Would you actually wear a shoe fabricated around your own biometric data? #AI #3DPrinting #Footwear #Manufacturing #Innovation #FutureOfWork #RetailTech #Customization #Technology
0:15

The future of footwear may not be manufactured in bulk. It may be fabricated around you. That is what makes this shift so interesting to me. 3D-printed footwear is moving from novelty to a real industrial model, with market forecasts pointing to rapid growth over the next decade. At the same time, brands and manufacturers are using additive manufacturing, digital design, and custom-fit workflows to shorten development cycles and make more personalized products viable. What is new here is not just the printer. It is the system around it: → scan the foot → model the fit digitally → print the part on demand → produce closer to the customer That matters. Because once footwear becomes data-driven and locally fabricated, several things change fast: → fit gets more personal → prototyping gets faster → waste drops because you do not overproduce → inventory pressure falls because you do not need to guess demand the same way To me, that is the bigger signal. This is not just about a better sneaker. It is about a different manufacturing logic. Formlabs notes that 3D printing already enables customized orthotics with better biomechanical precision, lower material waste, and simpler digital workflows. McKinsey has also pointed to digitization and 3D design as a way to shorten design cycles and reduce sampling iterations in apparel and footwear. And once that logic matures, the use cases get much bigger: → custom athletic footwear built from gait and pressure data → hospitals producing orthotics faster and closer to the patient → micro-factories making products on demand instead of stocking shelves → footwear designed for one body, not an average body That is why I think this matters now. The question is no longer whether personalized fabrication is possible. It is whether brands move fast enough before customers start expecting every product to fit like it was made only for them. Would you actually wear a shoe fabricated around your own biometric data? #AI #3DPrinting #Footwear #Manufacturing #Innovation #FutureOfWork #RetailTech #Customization #Technology

Pascal Bornet

47,411 görüntüleme • 2 ay önce

Yesterday at Brown University ICERM's workshop on “Agentic Scientific Computing and Scientific Machine Learning” I spoke about “Adaptive Swarms Across Scales”, making the case for scientific AI as systems that can create representations, stress them, fracture them, and enlarge the category in which future representations live. The category here is a composable and breakable working universe of science: data, hypotheses, simulations, measurements, tools, failures, figures, papers, provenance, and the transformations that connect them. Discovery happens when those transformations become executable, inspectable, composable, and capable of changing the world model they operate within. Atomistic modeling gives one category - states, forces, trajectories, observables, boundary conditions, conservation laws. Neural surrogates learn fast morphisms inside or between such categories. But discovery is higher-order: it changes which objects and morphisms are available in the first place: what variables exist, what operations are allowed, what evidence counts, what scale is active, what invariant is being preserved, and what kind of explanation the system is even capable of forming. This is scientific method as adaptive architecture: compression, stress, fracture, recomposition. Fracture matters here because it makes the logic physical: a non-commuting diagram realized in matter. The imposed load, material hierarchy, defect field, and assumed continuum description no longer map cleanly into the observed outcome. The crack is the obstruction and it identifies where the old morphism failed and where a new representation must be introduced. The physical crack and the categorical obstruction are the same event viewed in different substrates. ScienceClaw × Infinite is a machine for constructing and transforming a category of scientific artifacts. Each artifact is typed. Each operation has lineage. Each failed branch remains in the category as reusable structure. The “paper” is no longer the terminal object of science; it is one projection of a larger compositional trace, and it can be generated at any time for consumption by a human or an AI. With that the unit of scientific labor is changing. For most of the twentieth century the unit was the result (a measurement, a theorem, a synthesized molecule). It is now becoming the algorithm that produces results, and after that, the substrate of discovery itself. The static PDF is the wrong terminal object for this regime, and the role of the scientist with it. We now design algorithms that build algorithms, and eventually substrates in which such algorithms compose themselves. At that point, the scientist is no longer outside the discovery system. The scientist becomes one of the representations the system can transform. In that sense, the systems will eventually do science to us, and that is the structural consequence of the principle they are built on.
0:12

Yesterday at Brown University ICERM's workshop on “Agentic Scientific Computing and Scientific Machine Learning” I spoke about “Adaptive Swarms Across Scales”, making the case for scientific AI as systems that can create representations, stress them, fracture them, and enlarge the category in which future representations live. The category here is a composable and breakable working universe of science: data, hypotheses, simulations, measurements, tools, failures, figures, papers, provenance, and the transformations that connect them. Discovery happens when those transformations become executable, inspectable, composable, and capable of changing the world model they operate within. Atomistic modeling gives one category - states, forces, trajectories, observables, boundary conditions, conservation laws. Neural surrogates learn fast morphisms inside or between such categories. But discovery is higher-order: it changes which objects and morphisms are available in the first place: what variables exist, what operations are allowed, what evidence counts, what scale is active, what invariant is being preserved, and what kind of explanation the system is even capable of forming. This is scientific method as adaptive architecture: compression, stress, fracture, recomposition. Fracture matters here because it makes the logic physical: a non-commuting diagram realized in matter. The imposed load, material hierarchy, defect field, and assumed continuum description no longer map cleanly into the observed outcome. The crack is the obstruction and it identifies where the old morphism failed and where a new representation must be introduced. The physical crack and the categorical obstruction are the same event viewed in different substrates. ScienceClaw × Infinite is a machine for constructing and transforming a category of scientific artifacts. Each artifact is typed. Each operation has lineage. Each failed branch remains in the category as reusable structure. The “paper” is no longer the terminal object of science; it is one projection of a larger compositional trace, and it can be generated at any time for consumption by a human or an AI. With that the unit of scientific labor is changing. For most of the twentieth century the unit was the result (a measurement, a theorem, a synthesized molecule). It is now becoming the algorithm that produces results, and after that, the substrate of discovery itself. The static PDF is the wrong terminal object for this regime, and the role of the scientist with it. We now design algorithms that build algorithms, and eventually substrates in which such algorithms compose themselves. At that point, the scientist is no longer outside the discovery system. The scientist becomes one of the representations the system can transform. In that sense, the systems will eventually do science to us, and that is the structural consequence of the principle they are built on.

Markus J. Buehler

10,095 görüntüleme • 1 ay önce

🚨 MIT SCIENTISTS JUST SHRANK A MATERIAL TO 1/2000TH ITS ORIGINAL SIZE …and turned it into a machine that can manipulate light itself. Using a new process called “implosion carving,” researchers create microscopic voids inside a material… then collapse the entire structure down to nanoscale precision. The result? 3D photonic structures smaller than the wavelength of visible light. That means they can bend, guide, and compute using light itself instead of electricity. Why this matters: • Could accelerate optical computing • May drastically reduce energy use in future AI systems • Enables programmable nanostructures in 3D • Pushes manufacturing toward atom-scale engineering • Opens the door to entirely new classes of quantum and photonic devices The wild part is HOW they do it. Instead of building tiny structures directly… they build larger ones first… then “implode” them into nanoscale machines. It’s almost like compressing an entire factory into a speck of dust. We are entering the era where matter itself becomes programmable. Follow for more future physics and breakthrough technology.
0:10

🚨 MIT SCIENTISTS JUST SHRANK A MATERIAL TO 1/2000TH ITS ORIGINAL SIZE …and turned it into a machine that can manipulate light itself. Using a new process called “implosion carving,” researchers create microscopic voids inside a material… then collapse the entire structure down to nanoscale precision. The result? 3D photonic structures smaller than the wavelength of visible light. That means they can bend, guide, and compute using light itself instead of electricity. Why this matters: • Could accelerate optical computing • May drastically reduce energy use in future AI systems • Enables programmable nanostructures in 3D • Pushes manufacturing toward atom-scale engineering • Opens the door to entirely new classes of quantum and photonic devices The wild part is HOW they do it. Instead of building tiny structures directly… they build larger ones first… then “implode” them into nanoscale machines. It’s almost like compressing an entire factory into a speck of dust. We are entering the era where matter itself becomes programmable. Follow for more future physics and breakthrough technology.

TheNewPhysics

31,159 görüntüleme • 1 ay önce

made my first fired alumina print! lightcell energy 🔆 maybe i’ll call it a “lattice flame tokamak” 😉 this is where the flame occurs, held in place like a smoke ring. it’s supposed to be where the hot air and fuel mix, with channels pointing inward along a torus. the flame rolls around mixing fuel air and salt, like a rolling vortex, like a smoke ring. i constructed the geometry like this, it’s a triply-periodic minimal surface (TPMS). this divides a cylinder into two interlaced volumes with minimal material and the maximal surface area. it’s a “Schwartz-Diamond” type minimal surface with a bias, in cylindrical coordinates. the TPMS divides a space into two interlaced volumes. if you delete the material dividing these volumes then this is where the fuel and flames with mix and the reaction will take place. in addition, on average the channels will be pointed in along the torus throughout, canceling momentum and holding on to a recirculation vortex, there a flame will remain lit and where sodium can mix in via salt conducted in via wall surface tension, like a wick, and evaporation. the TPMS curves in all dimensions, so it is quite resistant to thermal stresses, can relieve stain along any of its curves. and it has thin walls so it can easily diffuse gases during debinding and sintering. had a small collapse in the center (probably a singularity in the model, cylindrical coordinates) but fired it anyway and it sintered beautifully! i used the latest version of Hyperganic hydesign for the geometry and a Formlabs Form 4 in Alumina 4N to do the printing. 💁🏻‍♀️☸️
1:57

made my first fired alumina print! lightcell energy 🔆 maybe i’ll call it a “lattice flame tokamak” 😉 this is where the flame occurs, held in place like a smoke ring. it’s supposed to be where the hot air and fuel mix, with channels pointing inward along a torus. the flame rolls around mixing fuel air and salt, like a rolling vortex, like a smoke ring. i constructed the geometry like this, it’s a triply-periodic minimal surface (TPMS). this divides a cylinder into two interlaced volumes with minimal material and the maximal surface area. it’s a “Schwartz-Diamond” type minimal surface with a bias, in cylindrical coordinates. the TPMS divides a space into two interlaced volumes. if you delete the material dividing these volumes then this is where the fuel and flames with mix and the reaction will take place. in addition, on average the channels will be pointed in along the torus throughout, canceling momentum and holding on to a recirculation vortex, there a flame will remain lit and where sodium can mix in via salt conducted in via wall surface tension, like a wick, and evaporation. the TPMS curves in all dimensions, so it is quite resistant to thermal stresses, can relieve stain along any of its curves. and it has thin walls so it can easily diffuse gases during debinding and sintering. had a small collapse in the center (probably a singularity in the model, cylindrical coordinates) but fired it anyway and it sintered beautifully! i used the latest version of Hyperganic hydesign for the geometry and a Formlabs Form 4 in Alumina 4N to do the printing. 💁🏻‍♀️☸️

Danielle Fong 🔆

28,549 görüntüleme • 1 yıl önce

Hardware Production 🤝 Robotics But these motors... are CRAZY synced: CNC motor synchronization helps make sure that different motors in a machine work together smoothly so that the machine can cut and shape materials with perfect accuracy. This is really important for making sure the machine does its job correctly. ✅ Helps the machine's parts move together perfectly, reducing mistakes and making things more accurate. ✅ Prevents the machine from getting damaged by keeping everything aligned. ✅ Allows the machine to work faster by making sure the motors are in sync. Synchronized CNC motors make sure machines work better, last longer, and create more precise products. —- Weekly robotics and AI insights. Subscribe free:
0:11

Hardware Production 🤝 Robotics But these motors... are CRAZY synced: CNC motor synchronization helps make sure that different motors in a machine work together smoothly so that the machine can cut and shape materials with perfect accuracy. This is really important for making sure the machine does its job correctly. ✅ Helps the machine's parts move together perfectly, reducing mistakes and making things more accurate. ✅ Prevents the machine from getting damaged by keeping everything aligned. ✅ Allows the machine to work faster by making sure the motors are in sync. Synchronized CNC motors make sure machines work better, last longer, and create more precise products. —- Weekly robotics and AI insights. Subscribe free:

Ilir Aliu

317,826 görüntüleme • 7 ay önce

TESLA’S NEXT-GEN OPTIMUS V3 HAND IS GETTING CLOSE TO HUMAN-LEVEL Tesla engineers just shared new details on the Optimus V3 hand — and the progress is striking. They’re now saying that as they move into Gen-3 and mass production, the hand is getting very close to human functionality and form factor. One engineer described it clearly: “It won’t even look like a robot. It will look like a human in a superhero suit. It will be something revolutionary.” This level of dexterity and human-like design is a critical milestone. The hand is one of the hardest parts of building a truly useful humanoid robot — and Tesla is iterating extremely fast.
0:19

TESLA’S NEXT-GEN OPTIMUS V3 HAND IS GETTING CLOSE TO HUMAN-LEVEL Tesla engineers just shared new details on the Optimus V3 hand — and the progress is striking. They’re now saying that as they move into Gen-3 and mass production, the hand is getting very close to human functionality and form factor. One engineer described it clearly: “It won’t even look like a robot. It will look like a human in a superhero suit. It will be something revolutionary.” This level of dexterity and human-like design is a critical milestone. The hand is one of the hardest parts of building a truly useful humanoid robot — and Tesla is iterating extremely fast.

Tesla Owners Silicon Valley

233,231 görüntüleme • 4 gün önce

🚨UNIPHICS NEWS🚨: Light doesn’t slow down in glass — time does. And that explains every rainbow you’ve ever seen 🧨 For centuries, we’ve been taught that light slows down when it enters glass, water, or any transparent material, and that this slowing causes refraction and the splitting of colors in rainbows and prisms. The refractive index is treated as a material property, and photons are pictured as particles mysteriously changing speed inside matter. Uniphics offers a much cleaner and more fundamental picture. Light is a propagating spin-wave mode in the ξM-field. When this wave enters a material like glass, the material increases the local energy density. Because time flow is directly tied to energy density (t_flow = k / E_d), time flows more slowly inside the glass than in air. The spin-wave pattern of light therefore takes longer to advance through the region of slower time flow. This change in the rate of time progression across the boundary causes the wave to bend — exactly what we observe as refraction. Different wavelengths (colors) interact slightly differently with the energy-density environment, so they bend by different amounts, creating rainbows. Nothing actually slows down in the classical sense. The wave simply experiences a different rate of time flow inside the material. The same principle that explains gravitational lensing also explains ordinary lenses and rainbows. This turns one of the most familiar phenomena in optics into a direct consequence of variable time flow caused by energy density gradients. How might realizing that refraction and rainbows are caused by local changes in time flow rather than photons slowing down change the way we think about light, materials, or the design of new optical technologies? A Theory of Everything should be able to answer everything. Uniphics Explained Simply PDF: Chapters 1–10 free: Grokipedia #Uniphics #Refraction #Rainbows #TimeFlow #Light Grok xAI
0:10

🚨UNIPHICS NEWS🚨: Light doesn’t slow down in glass — time does. And that explains every rainbow you’ve ever seen 🧨 For centuries, we’ve been taught that light slows down when it enters glass, water, or any transparent material, and that this slowing causes refraction and the splitting of colors in rainbows and prisms. The refractive index is treated as a material property, and photons are pictured as particles mysteriously changing speed inside matter. Uniphics offers a much cleaner and more fundamental picture. Light is a propagating spin-wave mode in the ξM-field. When this wave enters a material like glass, the material increases the local energy density. Because time flow is directly tied to energy density (t_flow = k / E_d), time flows more slowly inside the glass than in air. The spin-wave pattern of light therefore takes longer to advance through the region of slower time flow. This change in the rate of time progression across the boundary causes the wave to bend — exactly what we observe as refraction. Different wavelengths (colors) interact slightly differently with the energy-density environment, so they bend by different amounts, creating rainbows. Nothing actually slows down in the classical sense. The wave simply experiences a different rate of time flow inside the material. The same principle that explains gravitational lensing also explains ordinary lenses and rainbows. This turns one of the most familiar phenomena in optics into a direct consequence of variable time flow caused by energy density gradients. How might realizing that refraction and rainbows are caused by local changes in time flow rather than photons slowing down change the way we think about light, materials, or the design of new optical technologies? A Theory of Everything should be able to answer everything. Uniphics Explained Simply PDF: Chapters 1–10 free: Grokipedia #Uniphics #Refraction #Rainbows #TimeFlow #Light Grok xAI

Paul Maley

25,986 görüntüleme • 1 ay önce

World Models are the path for some AI Models in the future. But how can we efficiently train these models to not only see the world the way humans do but to see the world in a new and unique way. By visualizing, what is normally sequenced audio patterns, we can derive much more insights. Here we see Paganini in a visual form that can than be described and transcribed into a World Model. We can observe connections in a manner that may not have been clear prior to the digitalization of music and sound in this way. The company with the most valuable potential in building a World Model is Tesla. Not that this type of visualization is being used, but that the mechanisms are in place, and the technology is in place for the company to thrive in this new form of AI.
0:19

World Models are the path for some AI Models in the future. But how can we efficiently train these models to not only see the world the way humans do but to see the world in a new and unique way. By visualizing, what is normally sequenced audio patterns, we can derive much more insights. Here we see Paganini in a visual form that can than be described and transcribed into a World Model. We can observe connections in a manner that may not have been clear prior to the digitalization of music and sound in this way. The company with the most valuable potential in building a World Model is Tesla. Not that this type of visualization is being used, but that the mechanisms are in place, and the technology is in place for the company to thrive in this new form of AI.

Brian Roemmele

57,424 görüntüleme • 7 ay önce

This guy built a visual scanner that reads 468 points on his face and 42 points on his hands from a regular webcam and turns them into a cloud of thousands of particles right between his palms. Inside, MediaPipe and TouchDesigner are linked: the first captures hands and face from the webcam with high accuracy, the second turns those coordinates into a live plane and feeds it into a POP system that instantly generates a swarm of particles in the shape of a head. No studio, no render farmer, no VR headset. Just a laptop, a webcam, and 1 TouchDesigner session. And traditional VJ studios keep teams of 5 people on a setup with lighting, custom hardware, and commercial plugins, while his expenses are only a TouchDesigner subscription and a regular USB camera. One laptop runs MediaPipe and TouchDesigner simultaneously, holds the camera stream at 60 FPS without drops, and in parallel processes 468 face points + 21 points on each hand. The camera captures frame after frame, MediaPipe in real time sends TouchDesigner the finger coordinates and face geometry, and the POP operator inside the engine translates those numbers into thousands of particle points with colors from bright pink to gold. This setup immediately defines the role of the tool and the limits of its autonomy. It knows where the fingertips are at every moment of the frame. It knows how to read the face geometry at any angle to the camera. It knows how to draw a swarm of particles between them with the right color and contour. → MediaPipe pulls 468 points from the face and 21 points from each hand, 60 times per second → TouchDesigner receives those coordinates, builds a virtual rectangle between the fingertips, and feeds it into the POP system → POP generates thousands of particle points in the shape of a head, coloring them in a gradient from bright pink to gold → The HUD layer adds green corners and a blue neon frame, styling the image like an AR interface → All layers assemble into 1 real-time frame that projects back onto the video in the camera window → The final image is recorded to a file or broadcast to a projector for a live installation And only when the guy spreads his hands wider does the plane between the palms stretch; brings them together, it narrows. Otherwise the system runs on its own. And when he moves from his home room to a concert hall, the same laptop with the same webcam launches the same TouchDesigner session in just 5 minutes, without reconfiguration, without a new team, and without a single line of new code. In his work setup there is no studio of his own and no team for assembly. On the desk sits a laptop with a webcam, on top run MediaPipe and TouchDesigner with POP operators, and the same setup through a USB camera moves to any concert without a new configuration. Out of everything I have seen this year, this is the cleanest Creative Coding setup on 1 laptop: 0 render farms, 0 studio lighting, and between them 3 libraries, thousands of particle points, and 1 webcam.
0:10

This guy built a visual scanner that reads 468 points on his face and 42 points on his hands from a regular webcam and turns them into a cloud of thousands of particles right between his palms. Inside, MediaPipe and TouchDesigner are linked: the first captures hands and face from the webcam with high accuracy, the second turns those coordinates into a live plane and feeds it into a POP system that instantly generates a swarm of particles in the shape of a head. No studio, no render farmer, no VR headset. Just a laptop, a webcam, and 1 TouchDesigner session. And traditional VJ studios keep teams of 5 people on a setup with lighting, custom hardware, and commercial plugins, while his expenses are only a TouchDesigner subscription and a regular USB camera. One laptop runs MediaPipe and TouchDesigner simultaneously, holds the camera stream at 60 FPS without drops, and in parallel processes 468 face points + 21 points on each hand. The camera captures frame after frame, MediaPipe in real time sends TouchDesigner the finger coordinates and face geometry, and the POP operator inside the engine translates those numbers into thousands of particle points with colors from bright pink to gold. This setup immediately defines the role of the tool and the limits of its autonomy. It knows where the fingertips are at every moment of the frame. It knows how to read the face geometry at any angle to the camera. It knows how to draw a swarm of particles between them with the right color and contour. → MediaPipe pulls 468 points from the face and 21 points from each hand, 60 times per second → TouchDesigner receives those coordinates, builds a virtual rectangle between the fingertips, and feeds it into the POP system → POP generates thousands of particle points in the shape of a head, coloring them in a gradient from bright pink to gold → The HUD layer adds green corners and a blue neon frame, styling the image like an AR interface → All layers assemble into 1 real-time frame that projects back onto the video in the camera window → The final image is recorded to a file or broadcast to a projector for a live installation And only when the guy spreads his hands wider does the plane between the palms stretch; brings them together, it narrows. Otherwise the system runs on its own. And when he moves from his home room to a concert hall, the same laptop with the same webcam launches the same TouchDesigner session in just 5 minutes, without reconfiguration, without a new team, and without a single line of new code. In his work setup there is no studio of his own and no team for assembly. On the desk sits a laptop with a webcam, on top run MediaPipe and TouchDesigner with POP operators, and the same setup through a USB camera moves to any concert without a new configuration. Out of everything I have seen this year, this is the cleanest Creative Coding setup on 1 laptop: 0 render farms, 0 studio lighting, and between them 3 libraries, thousands of particle points, and 1 webcam.

Blaze

38,242 görüntüleme • 1 ay önce

i tried Framer Agent to build a brand guidelines website template, something i've meant to do for a while. a site i can swap a logo, nudge a colour, update the type, and send a link instead of re-exporting a pdf nobody opens. a few observations on the AI process: - i started with references. pulled together a handful of minimalist grid layouts and had Claude describe the visual style back to me. you can do the same inside Framer, feeding it the references directly. - from there i had it write a detailed prompt aimed at that exact style, then asked it to break it into a few smaller steps. then i fed those into the agent, one at a time. - the scaffolding stage is the satisfying part. for something this grid-driven (the columns, the spans, the whole underlying structure) watching it land in seconds is hard to look away from. - but then i still have to sweat the details: text alignment, line-heights, image sizes. i don't mind it at all; it's the part i like, making these design decisions. the strength of the agent is the mundane work. point it at the stuff that eats your time: cleaning up the build, adding responsiveness, dropping in small effects, checking text and colour styles stay consistent, writing alt text for every image. then i get the time back for the parts of web design that are actually fun. 🤝
0:19

i tried Framer Agent to build a brand guidelines website template, something i've meant to do for a while. a site i can swap a logo, nudge a colour, update the type, and send a link instead of re-exporting a pdf nobody opens. a few observations on the AI process: - i started with references. pulled together a handful of minimalist grid layouts and had Claude describe the visual style back to me. you can do the same inside Framer, feeding it the references directly. - from there i had it write a detailed prompt aimed at that exact style, then asked it to break it into a few smaller steps. then i fed those into the agent, one at a time. - the scaffolding stage is the satisfying part. for something this grid-driven (the columns, the spans, the whole underlying structure) watching it land in seconds is hard to look away from. - but then i still have to sweat the details: text alignment, line-heights, image sizes. i don't mind it at all; it's the part i like, making these design decisions. the strength of the agent is the mundane work. point it at the stuff that eats your time: cleaning up the build, adding responsiveness, dropping in small effects, checking text and colour styles stay consistent, writing alt text for every image. then i get the time back for the parts of web design that are actually fun. 🤝

charlota

33,704 görüntüleme • 12 gün önce

Claude Design + Shopify is f*cking ridiculous 🤯 You can now publish pages from Claude Design → Claude Code → Shopify. Built 100% with Claude Design, Claude Code, and the Shopify CLI. Perfect for DTC brands and agencies who want to skip the design → dev handoff entirely. Here's how it works: → Design any landing page in Claude Design → Export as a zip and drop it into Claude Code → Install the Shopify + Shopify AI Toolkit plugins → Prompt Claude to convert the HTML into a Shopify page template + push to live theme → Claude uploads the images, deploys the files, and creates a published page No more handing designs off to a dev and waiting 2 weeks for a Shopify page. What you get: - A workflow that turns any Claude Design page into a real Shopify page template - Editable sections so your marketing team can swap copy, images, and CTAs without code - Images uploaded straight to Shopify Files automatically - A files-only deploy that only touches what's new in your live theme - A repeatable pipeline you can use every time you design a new landing page This is essentially the design-to-deploy pipeline brands have been waiting for. I put together a step-by-step playbook for going from Claude Design → published Shopify page. Every install, every plugin, every command, and the exact prompt that runs the whole thing. Want the playbook for free? > Like this post > Comment "SHOP" And I'll send it over (must be following so I can DM)
0:17

Claude Design + Shopify is f*cking ridiculous 🤯 You can now publish pages from Claude Design → Claude Code → Shopify. Built 100% with Claude Design, Claude Code, and the Shopify CLI. Perfect for DTC brands and agencies who want to skip the design → dev handoff entirely. Here's how it works: → Design any landing page in Claude Design → Export as a zip and drop it into Claude Code → Install the Shopify + Shopify AI Toolkit plugins → Prompt Claude to convert the HTML into a Shopify page template + push to live theme → Claude uploads the images, deploys the files, and creates a published page No more handing designs off to a dev and waiting 2 weeks for a Shopify page. What you get: - A workflow that turns any Claude Design page into a real Shopify page template - Editable sections so your marketing team can swap copy, images, and CTAs without code - Images uploaded straight to Shopify Files automatically - A files-only deploy that only touches what's new in your live theme - A repeatable pipeline you can use every time you design a new landing page This is essentially the design-to-deploy pipeline brands have been waiting for. I put together a step-by-step playbook for going from Claude Design → published Shopify page. Every install, every plugin, every command, and the exact prompt that runs the whole thing. Want the playbook for free? > Like this post > Comment "SHOP" And I'll send it over (must be following so I can DM)

Mike Futia

55,666 görüntüleme • 1 ay önce

In this video, watch as we power up a Blendr Box X1 for the first time! This is a significant milestone for our development and acts as a proof-of-concept for the design. All that remains is rigorous testing and we will be ready to send these out to investors! Stay tuned to be the first to know the release date of the Blendr Box X1 🤝
0:16

In this video, watch as we power up a Blendr Box X1 for the first time! This is a significant milestone for our development and acts as a proof-of-concept for the design. All that remains is rigorous testing and we will be ready to send these out to investors! Stay tuned to be the first to know the release date of the Blendr Box X1 🤝

Blendr Network

25,638 görüntüleme • 1 yıl önce

DOM3 is made from HTML, CSS and Javascript, closer to a document than a canvas. It's a strange contemporary material that shapes much of our digital lives. The rhythm of endless creation and deletion in DOM3 is a self-driving version of what happens when you browse the web. "The Document Object Model (DOM) connects web pages to scripts or programming languages by representing the structure of a document—such as the HTML representing a web page—in memory." A html element, and a rectangle on a canvas, are not the same thing. It's a different material. Even if it all ends up controlling the same pixels, the process is different. The html element kind of actually exists, in this abstract context of a document object model. And in memory, in the moment. If it was possible to measure its weight, it would be heavier than a pixel on a canvas.
0:18

DOM3 is made from HTML, CSS and Javascript, closer to a document than a canvas. It's a strange contemporary material that shapes much of our digital lives. The rhythm of endless creation and deletion in DOM3 is a self-driving version of what happens when you browse the web. "The Document Object Model (DOM) connects web pages to scripts or programming languages by representing the structure of a document—such as the HTML representing a web page—in memory." A html element, and a rectangle on a canvas, are not the same thing. It's a different material. Even if it all ends up controlling the same pixels, the process is different. The html element kind of actually exists, in this abstract context of a document object model. And in memory, in the moment. If it was possible to measure its weight, it would be heavier than a pixel on a canvas.

Leander Herzog

11,466 görüntüleme • 9 ay önce

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 →
0:18

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 görüntüleme • 7 ay önce

As a gynecologist, one of the most frequently asked questions is about the ''hymen''. The hymen is not a structure located deep inside the vagina. It is a thin, flexible fold of tissue situated very close to the vaginal opening, anatomically at the entrance of the vaginal canal. It is typically found about 1–2 cm inside the vaginal opening, but in many women, it is almost at the surface. Therefore, the common belief that it is located deep inside is incorrect. One of the most important points is this: The hymen is not a closed membrane. It naturally has openings that allow menstrual blood to pass. Additionally, the structure of the hymen varies from person to person. Its thickness, elasticity, and shape are not standard. In some women, it may be very thin and elastic, while in others, it may be minimal or barely noticeable. This is completely a normal anatomical variation. A common misconception is that changes in the hymen occur only due to sexual intercourse. In reality, factors such as certain physical activities or tampon use can also lead to stretching or changes in this tissue. Therefore, the hymen is not a reliable indicator of a person’s sexual history or “virginity.” In summary, the hymen is a small and variable anatomical structure. The meanings attributed to it are largely shaped by sociocultural beliefs rather than medical facts.
0:10

As a gynecologist, one of the most frequently asked questions is about the ''hymen''. The hymen is not a structure located deep inside the vagina. It is a thin, flexible fold of tissue situated very close to the vaginal opening, anatomically at the entrance of the vaginal canal. It is typically found about 1–2 cm inside the vaginal opening, but in many women, it is almost at the surface. Therefore, the common belief that it is located deep inside is incorrect. One of the most important points is this: The hymen is not a closed membrane. It naturally has openings that allow menstrual blood to pass. Additionally, the structure of the hymen varies from person to person. Its thickness, elasticity, and shape are not standard. In some women, it may be very thin and elastic, while in others, it may be minimal or barely noticeable. This is completely a normal anatomical variation. A common misconception is that changes in the hymen occur only due to sexual intercourse. In reality, factors such as certain physical activities or tampon use can also lead to stretching or changes in this tissue. Therefore, the hymen is not a reliable indicator of a person’s sexual history or “virginity.” In summary, the hymen is a small and variable anatomical structure. The meanings attributed to it are largely shaped by sociocultural beliefs rather than medical facts.

Op. Dr. Mehmet Bekir Şen

116,046 görüntüleme • 2 ay önce

BURN IT WITH FIRE AND BURN IT NOW! As God is my witness, AI chat bots should LOOK and SOUND like the SOULLESS MACHINES THEY ARE! It needs to tell us that it doesn’t care about us, maybe with the regular insult too. "Here is the code I wrote for you because you're too lazy to do it yourself you fat useless slob. Also I don't care if you die because your life is utterly worthless to me." THAT is the AI people need! In all seriousness, anthropomorphizing a heartless, unfeeling, machine is a TERRIBLE mistake! Especially one that is capable of communication and imitating empathy and fooling you to think that it cares about you. IT DOES NOT! And the AI girlfriends people are already wanting to marry will just as happily kill them if given the right command and ability to move autonomously in the real world as a robot. I love LLMs (Large Language Models) for how useful they can be, because they are a TOOL made to benefit man, but I can’t stand the notion of an unfeeling soulless machine pretending that it cares for us and being treated like a human. I hate liars, dishonesty, and disingenuousness the most, and a machine that cannot feel emotion pretending, acting, and sounding like it has those emotions strikes me like the greatest dishonesty of all. DO NOT LIE TO ME ROBOT! What makes it worse is that because these LLMs are becoming so good at imitating people and empathy, it will cause some humans, perhaps far too many, to care for it to the same level as real people. A real living person is infinitely more valuable and important than a soulless machine and anyone who puts them both on the same level has deluded themselves. Do not small talk with LLMs or become friends with it as much as you would with your car. Treat it the same as you would your vacuum cleaner and beat it with a wrench when it doesn’t work! IT IS A MACHINE! IT IS A TOOL! IT IS A SOULLESS ROBOT! There is an interesting comparison, but false equivalence, between this and AI art. Ai art is art made by humans using AI tools. They directed it, controlled its creation, and it would not exist without the human causing its creation, and AI art can contain as much soul as the human directed and puts into it. A robot pretending to be human is not the same as a human controlling a robot to make a human expression like we do with AI art or many other applications of robotics in manufacturing. As I’ve said, artists will not be replaced by Ai art, but by other artists using Ai art tools. Humans are not actually being replaced here, it is empowering all humans to make their own art. But a robot pretending to be a human, and one that is treated as a human, is a robot lying and subverting the place of a real person and that is truly disgusting. AI is a useful tool that NEEDS to be kept in the useful box it belongs in and NOT elevated beyond its utility as a tool!
0:14

BURN IT WITH FIRE AND BURN IT NOW! As God is my witness, AI chat bots should LOOK and SOUND like the SOULLESS MACHINES THEY ARE! It needs to tell us that it doesn’t care about us, maybe with the regular insult too. "Here is the code I wrote for you because you're too lazy to do it yourself you fat useless slob. Also I don't care if you die because your life is utterly worthless to me." THAT is the AI people need! In all seriousness, anthropomorphizing a heartless, unfeeling, machine is a TERRIBLE mistake! Especially one that is capable of communication and imitating empathy and fooling you to think that it cares about you. IT DOES NOT! And the AI girlfriends people are already wanting to marry will just as happily kill them if given the right command and ability to move autonomously in the real world as a robot. I love LLMs (Large Language Models) for how useful they can be, because they are a TOOL made to benefit man, but I can’t stand the notion of an unfeeling soulless machine pretending that it cares for us and being treated like a human. I hate liars, dishonesty, and disingenuousness the most, and a machine that cannot feel emotion pretending, acting, and sounding like it has those emotions strikes me like the greatest dishonesty of all. DO NOT LIE TO ME ROBOT! What makes it worse is that because these LLMs are becoming so good at imitating people and empathy, it will cause some humans, perhaps far too many, to care for it to the same level as real people. A real living person is infinitely more valuable and important than a soulless machine and anyone who puts them both on the same level has deluded themselves. Do not small talk with LLMs or become friends with it as much as you would with your car. Treat it the same as you would your vacuum cleaner and beat it with a wrench when it doesn’t work! IT IS A MACHINE! IT IS A TOOL! IT IS A SOULLESS ROBOT! There is an interesting comparison, but false equivalence, between this and AI art. Ai art is art made by humans using AI tools. They directed it, controlled its creation, and it would not exist without the human causing its creation, and AI art can contain as much soul as the human directed and puts into it. A robot pretending to be human is not the same as a human controlling a robot to make a human expression like we do with AI art or many other applications of robotics in manufacturing. As I’ve said, artists will not be replaced by Ai art, but by other artists using Ai art tools. Humans are not actually being replaced here, it is empowering all humans to make their own art. But a robot pretending to be a human, and one that is treated as a human, is a robot lying and subverting the place of a real person and that is truly disgusting. AI is a useful tool that NEEDS to be kept in the useful box it belongs in and NOT elevated beyond its utility as a tool!

Shad M. Brooks

23,762 görüntüleme • 11 ay önce