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Researchers develop a method for low-viscosity ink 3D bioprinting, based on aqueous two-phase stabilization of the ink-bath interface. The technique offers impressive nozzle-independent control over filament diameter. 👉

Advanced Portfolio

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63,972 次观看 • 3 年前 •via X (Twitter)

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The Baker Lab designs protein on/off switches 1/🧵 Instead of optimizing for how tightly a given protein binds to a target, Adam and team develop a method to control the duration of binding.

The Baker Lab designs protein on/off switches 1/🧵 Instead of optimizing for how tightly a given protein binds to a target, Adam and team develop a method to control the duration of binding.

Deniz Kavi

32,427 次观看 • 10 个月前

Visual Preset #01 Ink-Brush Cinematic 3D: A high-end cinematic 3D style where expressive ink-brush effects become the primary visual language for fast-paced anime action. Lately I've noticed that I've been experimenting with different visual presets across my videos and I'd like to explore that direction even further. Going forward, I'll be sharing some of these style experiments. The video below was generated using only a character sheet, a single-line scene description and the visual preset shown below. Created with Seedance 2.0 on Try ArtCraft Seedance 2.0 Prompt: A mesmerizing display of @[character]'s masterful swordsmanship. High-end cinematic 3D realism fused with expressive ink-brush action. High-sakuga anime choreography, sweeping sumi-e brush strokes, flowing ink splashes, dynamic calligraphic energy and graphic black ink trails define every movement. Extreme perspective, dramatic foreshortening, cinematic tracking shots, volumetric lighting, heavy atmospheric haze and explosive ink bursts replace conventional visual effects, while realistic materials and feature-film rendering preserve depth, weight and scale.

Visual Preset #01 Ink-Brush Cinematic 3D: A high-end cinematic 3D style where expressive ink-brush effects become the primary visual language for fast-paced anime action. Lately I've noticed that I've been experimenting with different visual presets across my videos and I'd like to explore that direction even further. Going forward, I'll be sharing some of these style experiments. The video below was generated using only a character sheet, a single-line scene description and the visual preset shown below. Created with Seedance 2.0 on Try ArtCraft Seedance 2.0 Prompt: A mesmerizing display of @[character]'s masterful swordsmanship. High-end cinematic 3D realism fused with expressive ink-brush action. High-sakuga anime choreography, sweeping sumi-e brush strokes, flowing ink splashes, dynamic calligraphic energy and graphic black ink trails define every movement. Extreme perspective, dramatic foreshortening, cinematic tracking shots, volumetric lighting, heavy atmospheric haze and explosive ink bursts replace conventional visual effects, while realistic materials and feature-film rendering preserve depth, weight and scale.

Kōda

42,883 次观看 • 2 个月前

Human Hair Reconstruction with Strand-Aligned 3D Gaussians Contributions (cited): – We propose a new 3D line lifting scheme that uses a modified 3DGS reconstruction technique to lift 2D orientation maps into a 3D field while also providing refinement of the camera parameters; – We introduce a dual representation of hair strand polylines and 3D Gaussians to achieve differentiable rasterization of hair strands and leverage photometric constraints for strand-based hair reconstruction; – Based on these components, we propose a coarse-to-fine optimization method for prior-guided hair reconstruction that leverages both latent and explicit representations of the hairstyle.

Human Hair Reconstruction with Strand-Aligned 3D Gaussians Contributions (cited): – We propose a new 3D line lifting scheme that uses a modified 3DGS reconstruction technique to lift 2D orientation maps into a 3D field while also providing refinement of the camera parameters; – We introduce a dual representation of hair strand polylines and 3D Gaussians to achieve differentiable rasterization of hair strands and leverage photometric constraints for strand-based hair reconstruction; – Based on these components, we propose a coarse-to-fine optimization method for prior-guided hair reconstruction that leverages both latent and explicit representations of the hairstyle.

MrNeRF

106,525 次观看 • 1 年前

Each Operation is different, and offers two difficulty options depending on the level of challenge you're looking for. Operations themselves can be solely ship-based, entirely on-foot, or a mixture of the two. There are various different Operations, including Firestorm Rescue, a ship-based Operation, which tasks you and your squad with evacuating trapped hostages from a nearby station. Read more:

Each Operation is different, and offers two difficulty options depending on the level of challenge you're looking for. Operations themselves can be solely ship-based, entirely on-foot, or a mixture of the two. There are various different Operations, including Firestorm Rescue, a ship-based Operation, which tasks you and your squad with evacuating trapped hostages from a nearby station. Read more:

Elite Dangerous

21,810 次观看 • 3 个月前

Had early access to Gemini with Deep Think. Very good model, big gains over standard Gemini 2.5 Pro for a lot of problems. Here is the first attempt at the starship control panel prompt I try with every model. First time I have seen a model make a 3D interface in response.

Had early access to Gemini with Deep Think. Very good model, big gains over standard Gemini 2.5 Pro for a lot of problems. Here is the first attempt at the starship control panel prompt I try with every model. First time I have seen a model make a 3D interface in response.

Ethan Mollick

252,665 次观看 • 1 年前

🚨 RESEARCHERS JUST MADE WATER-BASED BATTERIES LAST OVER 2,800 HOURS WITH RECORD CAPACITY. A team in South Korea has developed a simple zwitterionic electrolyte additive that dramatically improves the performance of aqueous (water-based) batteries a technology long seen as a safer, cheaper, and more environmentally friendly alternative to lithium-ion. The additive forms tiny nanostructures that guide zinc to deposit evenly on the electrode and create a protective layer that prevents corrosion and unwanted side reactions with water. This solves two of the biggest problems that have limited aqueous batteries: uneven metal buildup and rapid capacity fade. In testing, the modified batteries achieved a world-leading areal capacity of 8.10 mAh cm⁻² and ran stably for more than 2,800 hours. Why this matters: • Aqueous batteries are non-flammable and use abundant, low-cost materials, but have historically suffered from poor lifespan and performance • This approach improves both cycle life and capacity at the same time — something many previous solutions struggled to achieve together • It uses a simple additive rather than requiring expensive new materials or complex manufacturing changes • The technology is particularly relevant for large-scale energy storage needed for renewables and AI data centers The deeper implication: We’re getting closer to making safe, scalable, and affordable grid storage a reality. While lithium-ion still dominates, aqueous batteries could become a strong contender for stationary storage where safety, cost, and longevity matter more than energy density. A small molecular tweak unlocking major performance gains shows how materials engineering at the nanoscale can have outsized real-world impact. This is the kind of incremental but meaningful progress that compounds over time. How important do you think safer, water-based batteries will be for the future energy grid compared to improving lithium-ion or other alternatives? Follow for more frontier energy storage and battery materials research.

🚨 RESEARCHERS JUST MADE WATER-BASED BATTERIES LAST OVER 2,800 HOURS WITH RECORD CAPACITY. A team in South Korea has developed a simple zwitterionic electrolyte additive that dramatically improves the performance of aqueous (water-based) batteries a technology long seen as a safer, cheaper, and more environmentally friendly alternative to lithium-ion. The additive forms tiny nanostructures that guide zinc to deposit evenly on the electrode and create a protective layer that prevents corrosion and unwanted side reactions with water. This solves two of the biggest problems that have limited aqueous batteries: uneven metal buildup and rapid capacity fade. In testing, the modified batteries achieved a world-leading areal capacity of 8.10 mAh cm⁻² and ran stably for more than 2,800 hours. Why this matters: • Aqueous batteries are non-flammable and use abundant, low-cost materials, but have historically suffered from poor lifespan and performance • This approach improves both cycle life and capacity at the same time — something many previous solutions struggled to achieve together • It uses a simple additive rather than requiring expensive new materials or complex manufacturing changes • The technology is particularly relevant for large-scale energy storage needed for renewables and AI data centers The deeper implication: We’re getting closer to making safe, scalable, and affordable grid storage a reality. While lithium-ion still dominates, aqueous batteries could become a strong contender for stationary storage where safety, cost, and longevity matter more than energy density. A small molecular tweak unlocking major performance gains shows how materials engineering at the nanoscale can have outsized real-world impact. This is the kind of incremental but meaningful progress that compounds over time. How important do you think safer, water-based batteries will be for the future energy grid compared to improving lithium-ion or other alternatives? Follow for more frontier energy storage and battery materials research.

TheNewPhysics

22,736 次观看 • 2 个月前

Pi Network Unveils A Fresh Look For Its Mining App Pi Network (Pi Network) has rolled out the first phase of a redesign for its mining app. The update refreshes the side menu and profile page, making key Pioneer information and ecosystem features easier to find and navigate. The project said future interface improvements will be introduced gradually based on community feedback.

BSCN

34,240 次观看 • 1 个月前

🌀 #Live3D #Live2D #Live2DWIP 🌀 Today, I’d like to share two of the three methods I use to create joint twisting in my Live2D-based 2D Pseudo-3D concept. On the right is the Glue Joint： The basic idea is to use Glue to connect two pseudo-3D ArtMeshes. By taking advantage of Glue’s weight settings, it can create an effect similar to a 3D joint. Once the weights are set up, it can move very freely with a relatively low amount of work. However, it also shares the same weakness as 3D joints: when rotated at large angles, it can produce unpleasant twisting and distortion. On the left is the Hand-Bent Joint： The basic idea is to add bending Keyforms directly to a Warp Deformer, then manually sculpt the ideal deformation. This method can create the most detailed and refined joints, depending entirely on how the rigger designs them. The downside is that it requires much more work. Every additional degree of freedom requires a significant amount of manual adjustment. These two joint methods have almost opposite characteristics, so in actual Live3D work, I choose the most suitable method depending on the situation. For example, in this hand model, I used Hand-Bent Joints for the arm twisting and fingers, while the wrist uses a Glue Joint.✨

🌀 #Live3D #Live2D #Live2DWIP 🌀 Today, I’d like to share two of the three methods I use to create joint twisting in my Live2D-based 2D Pseudo-3D concept. On the right is the Glue Joint： The basic idea is to use Glue to connect two pseudo-3D ArtMeshes. By taking advantage of Glue’s weight settings, it can create an effect similar to a 3D joint. Once the weights are set up, it can move very freely with a relatively low amount of work. However, it also shares the same weakness as 3D joints: when rotated at large angles, it can produce unpleasant twisting and distortion. On the left is the Hand-Bent Joint： The basic idea is to add bending Keyforms directly to a Warp Deformer, then manually sculpt the ideal deformation. This method can create the most detailed and refined joints, depending entirely on how the rigger designs them. The downside is that it requires much more work. Every additional degree of freedom requires a significant amount of manual adjustment. These two joint methods have almost opposite characteristics, so in actual Live3D work, I choose the most suitable method depending on the situation. For example, in this hand model, I used Hand-Bent Joints for the arm twisting and fingers, while the wrist uses a Glue Joint.✨

📐Hephaestus📏Live2D匠人魂

18,781 次观看 • 2 个月前

POV: Dudes finally deciding Low Vis Armor + Chest Rigs wasn't just a GWOT vibe. - New video on YouTube going over the merits of this system and why it's becoming our favorite method of building "loadouts" for quickly gearing up with various weapons platforms. - #dirtycivilian

POV: Dudes finally deciding Low Vis Armor + Chest Rigs wasn't just a GWOT vibe. - New video on YouTube going over the merits of this system and why it's becoming our favorite method of building "loadouts" for quickly gearing up with various weapons platforms. - #dirtycivilian

Dirty Civilian

49,510 次观看 • 1 年前

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

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

TheNewPhysics

347,458 次观看 • 2 个月前

🇺🇦💣 🇷🇺 With domestic manufacturing reaching critical development goals, Ukrainian authorities are highlighting the deployment of highly precise, locally developed glide bombs that drastically enhance their independent striking capabilities. “Ukraine is already using domestically produced guided glide bombs in combat operations. A total of eight developers worked on the project, but the products of the best two were selected for use on the front lines,” – Minister of Defense of Ukraine, Mykhailo Fedorov. 🗣️According to him, the current results already demonstrate the high potential of the aforementioned bombs — the strike statistics and efficiency of the domestically produced guided aerial bombs during the testing phase are "pleasantly impressive," Fedorov notes. Video is generated by Grok AI

🇺🇦💣 🇷🇺 With domestic manufacturing reaching critical development goals, Ukrainian authorities are highlighting the deployment of highly precise, locally developed glide bombs that drastically enhance their independent striking capabilities. “Ukraine is already using domestically produced guided glide bombs in combat operations. A total of eight developers worked on the project, but the products of the best two were selected for use on the front lines,” – Minister of Defense of Ukraine, Mykhailo Fedorov. 🗣️According to him, the current results already demonstrate the high potential of the aforementioned bombs — the strike statistics and efficiency of the domestically produced guided aerial bombs during the testing phase are "pleasantly impressive," Fedorov notes. Video is generated by Grok AI

NSTRIKE

71,331 次观看 • 2 个月前

DFINITY ACTIVITY SURGES AS TRANSACTION COSTS PLUMMET Data from Chainspect highlights two impressive and important metrics for the DFINITY Foundation ecosystem. First, $ICP's average txn fee has fallen to a new 90 day low of around $0.0000465, making the network altogether more affordable and accessible. At the same time, $ICP processed more than 335 million transactions on May 8 - a significant spike and potentially a sign of real adoption for the network.

DFINITY ACTIVITY SURGES AS TRANSACTION COSTS PLUMMET Data from Chainspect highlights two impressive and important metrics for the DFINITY Foundation ecosystem. First, $ICP's average txn fee has fallen to a new 90 day low of around $0.0000465, making the network altogether more affordable and accessible. At the same time, $ICP processed more than 335 million transactions on May 8 - a significant spike and potentially a sign of real adoption for the network.

BSCN

17,791 次观看 • 3 个月前

Gaussian Head Avatar: Ultra High-fidelity Head Avatar via Dynamic Gaussians paper page: Creating high-fidelity 3D head avatars has always been a research hotspot, but there remains a great challenge under lightweight sparse view setups. In this paper, we propose Gaussian Head Avatar represented by controllable 3D Gaussians for high-fidelity head avatar modeling. We optimize the neutral 3D Gaussians and a fully learned MLP-based deformation field to capture complex expressions. The two parts benefit each other, thereby our method can model fine-grained dynamic details while ensuring expression accuracy. Furthermore, we devise a well-designed geometry-guided initialization strategy based on implicit SDF and Deep Marching Tetrahedra for the stability and convergence of the training procedure. Experiments show our approach outperforms other state-of-the-art sparse-view methods, achieving ultra high-fidelity rendering quality at 2K resolution even under exaggerated expressions.

AK

65,861 次观看 • 2 年前

Wonderland: Navigating 3D Scenes from a Single Image Contributions: • First, we introduce a representation for controllable 3D generation by leveraging the generative priors from camera-guided video diffusion models. Unlike image models, video diffusion models are trained on extensive video datasets. This enables them to capture comprehensive spatial relationships within scenes across multiple views and embed a form of "3D awareness" in their latent space, which allows us to maintain 3D consistency in novel view synthesis. • Second, to achieve controllable novel view generation, we empower video models with precise control over specified camera motions. We introduce a novel dual-branch conditioning mechanism that effectively incorporates desired diverse camera trajectories into the video diffusion model. This enables expansion of a single image into a multi-view consistent capture of a 3D scene with precise pose control. • Third, to achieve efficient 3D reconstruction, we directly transform video latents into 3DGS. We propose a novel latent-based large reconstruction model (LaLRM) that lifts video latents to 3D in a feed-forward manner. With this design, during inference, our model directly predicts 3DGS from a single input image, effectively aligning the generation and reconstruction tasks—and bridging image space and 3D space—through the video latent space. Compared with reconstructing scenes from images, the video latent space offers a 256× spatial-temporal reduction while retaining essential and consistent 3D structural details. Such a high degree of compression is crucial, as it allows the LaLRM to handle a wider range of 3D scenes within the reconstruction framework, with the same memory constraints.

Wonderland: Navigating 3D Scenes from a Single Image Contributions: • First, we introduce a representation for controllable 3D generation by leveraging the generative priors from camera-guided video diffusion models. Unlike image models, video diffusion models are trained on extensive video datasets. This enables them to capture comprehensive spatial relationships within scenes across multiple views and embed a form of "3D awareness" in their latent space, which allows us to maintain 3D consistency in novel view synthesis. • Second, to achieve controllable novel view generation, we empower video models with precise control over specified camera motions. We introduce a novel dual-branch conditioning mechanism that effectively incorporates desired diverse camera trajectories into the video diffusion model. This enables expansion of a single image into a multi-view consistent capture of a 3D scene with precise pose control. • Third, to achieve efficient 3D reconstruction, we directly transform video latents into 3DGS. We propose a novel latent-based large reconstruction model (LaLRM) that lifts video latents to 3D in a feed-forward manner. With this design, during inference, our model directly predicts 3DGS from a single input image, effectively aligning the generation and reconstruction tasks—and bridging image space and 3D space—through the video latent space. Compared with reconstructing scenes from images, the video latent space offers a 256× spatial-temporal reduction while retaining essential and consistent 3D structural details. Such a high degree of compression is crucial, as it allows the LaLRM to handle a wider range of 3D scenes within the reconstruction framework, with the same memory constraints.

MrNeRF

52,849 次观看 • 1 年前

The film’s budget was so low that many of the actors were asked to simply bring their own clothing as wardrobe. The signature black suits were provided for free by the designer, based on her love for the American crime film genre. Steve Buscemi wore his own black jeans instead of suit pants, and Michael Madsen wore a jacket and pants that came from two different suits. Reservoir Dogs (1992)

The film’s budget was so low that many of the actors were asked to simply bring their own clothing as wardrobe. The signature black suits were provided for free by the designer, based on her love for the American crime film genre. Steve Buscemi wore his own black jeans instead of suit pants, and Michael Madsen wore a jacket and pants that came from two different suits. Reservoir Dogs (1992)

anime visuals

74,760 次观看 • 1 年前

Three.js Water Pro v3.4 is now live! 🚀 Live Demo: This update adds Jerlov water types—a convenient way of modeling water color based on algae, silt and stain concentrations. The legacy color system is still available for those requiring more artistic control over the water color.

Three.js Water Pro v3.4 is now live! 🚀 Live Demo: This update adds Jerlov water types—a convenient way of modeling water color based on algae, silt and stain concentrations. The legacy color system is still available for those requiring more artistic control over the water color.

Dan Greenheck

30,460 次观看 • 23 天前

hi all, excited to join! i'm building an expressive mini "shoggoth" robot which will eventually be hooked up to gpt4o realtime voice. i'm currently working on the low-level policies, which are trained in a mujoco simulation with RL. to delay working on raw-pixels for now, i trained a pose-estimation model using deeplabcut and triangulate the position in 3d space using the stereo cameras. eventually, i'll use gpt4o's tool calling capabilities to activate several of these policies (closed and open loop) based on the dialog flow! captions: manual actuation of the tentacle / 3d pose estimation / target design

hi all, excited to join! i'm building an expressive mini "shoggoth" robot which will eventually be hooked up to gpt4o realtime voice. i'm currently working on the low-level policies, which are trained in a mujoco simulation with RL. to delay working on raw-pixels for now, i trained a pose-estimation model using deeplabcut and triangulate the position in 3d space using the stereo cameras. eventually, i'll use gpt4o's tool calling capabilities to activate several of these policies (closed and open loop) based on the dialog flow! captions: manual actuation of the tentacle / 3d pose estimation / target design

Matthieu LC

45,587 次观看 • 1 年前

I really like those 2.5D characters here's my Seedance2 prompt: MANGA READER TURNAROUND CHARACTER: Young Japanese man sitting cross-legged on the floor reading a colorful manga magazine, spiky messy black hair sticking up in chunky angular shapes, thick eyebrows, small round glasses, slight stubble, cross pendant necklace on a thin chain, wearing a loose open dark navy pinstripe yukata robe showing his chest, bare feet tucked under his legs, small ceramic ashtray with cigarette butts on the floor to his left, round ceramic pot to his right, focused slightly annoyed expression looking down at the magazine. 3D CG model with 2D hand-drawn overlay, scribble hatching in all shadow areas boiling every frame, thick ink outlines on silhouette edges redrawing with wobble, flat painted color textures on 3D geometry, color bleeding outside contour lines. SEQUENCE [0s–5s] Character sits cross-legged holding the manga open in both hands, not moving, just reading. Camera begins a smooth continuous 360 degree orbit around him at his eye level. As the camera moves from front to three-quarter to side profile, the 3D model rotates cleanly revealing his full volume but the 2D ink layer on top lives and breathes, scribble hatching in the shadows under his jaw and inside the yukata folds and between his crossed legs redraws every frame with jittery boiling energy, thick ink outlines on his silhouette wobble and shift in thickness as the angle changes, the flat painted navy yukata wraps around his torso showing new pinstripe ink lines and fold marks at each new angle, his spiky hair reveals its 3D chunky volume from new angles, the manga magazine pages catch the light differently as the camera passes, cigarette smoke curls upward as loose scribbled white lines drifting gently [5s–10s] Camera continues the smooth unbroken orbit past his side revealing the cross necklace hanging from his neck in profile, through his back showing the yukata fabric draped across his shoulders and the spiky hair from behind, past his left side and returning to front, the entire rotation fluid and steady, throughout the full 360 the boiling ink outlines never stop trembling on every edge, the scribble hatching in shadows keeps redrawing in slightly different positions each frame giving the whole image a living sketchbook vibration even though he holds perfectly still reading, the flat painted color planes on his skin shift between warm peach and darker shadow tones as new surfaces catch the light, the ashtray and ceramic pot on the floor rotate into and out of view naturally, white background STYLE: 2.5D painterly CG. 3D CG geometry underneath for volume and smooth rotation. 2D Grease Pencil layer on top, thick wobbly ink outlines, scribble hatching in all shadows boiling every frame, flat painted color planes not smooth gradients. No photorealism. No smooth CG rendering. Muted palette dark navy warm peach black white. Film grain. Clean white background. Smooth continuous camera orbit.

INK

15,192 次观看 • 4 个月前

Almost every robot you see... runs on this equation. Not AI. Not machine learning. PID. For over 100 years, this simple control algorithm has been quietly keeping robots balanced, drones stable, industrial machines precise, and even rockets on course. Most people never hear about it. Yet without PID, many of today's robots wouldn't even stand upright. If you could only learn ONE control algorithm in robotics... this would be it. What's the most impressive application of PID you've seen? 🎥 Media: medcorreia ( Instagram ) ⚠️ This content is shared for informational purposes only. CTO Robotics Media is a media platform and does not own or develop the technology shown. Credit belongs to the original creators.

Almost every robot you see... runs on this equation. Not AI. Not machine learning. PID. For over 100 years, this simple control algorithm has been quietly keeping robots balanced, drones stable, industrial machines precise, and even rockets on course. Most people never hear about it. Yet without PID, many of today's robots wouldn't even stand upright. If you could only learn ONE control algorithm in robotics... this would be it. What's the most impressive application of PID you've seen? 🎥 Media: medcorreia ( Instagram ) ⚠️ This content is shared for informational purposes only. CTO Robotics Media is a media platform and does not own or develop the technology shown. Credit belongs to the original creators.

CTO ROBOTICS Media

46,122 次观看 • 2 个月前

So remember that time machine I told you about? I managed to sneek out another video from my visit to the future.. this time I captured video of a 3d artist creating assets for a short commercial. They sculpted the bird in the video with nothing but two controllers which they used to manipulate generative matter in 3d. The AI model changed in realtime and adopted their style of work, both based on the work they did on the scene, and on reference images they gave the system. Seeing the 3d model transform in realtime as they were working on it was incredible. When it started moving and reacted to their instructions, I knew it was time to return to the present :D #art #ai

So remember that time machine I told you about? I managed to sneek out another video from my visit to the future.. this time I captured video of a 3d artist creating assets for a short commercial. They sculpted the bird in the video with nothing but two controllers which they used to manipulate generative matter in 3d. The AI model changed in realtime and adopted their style of work, both based on the work they did on the scene, and on reference images they gave the system. Seeing the 3d model transform in realtime as they were working on it was incredible. When it started moving and reacted to their instructions, I knew it was time to return to the present :D #art #ai

Martin Nebelong

22,044 次观看 • 2 年前