Video wird geladen...

Video konnte nicht geladen werden

Beim Laden dieses Videos ist ein Problem aufgetreten. Dies könnte an einem vorübergehenden Netzwerkproblem liegen oder das Video ist möglicherweise nicht verfügbar.

This is how a freehand is born - layer by layer, painted by the artist’s hand, with no decals and no shortcuts. Want to add a freehand to your army, vehicle, or model? Message us: [email protected] #Freehand #Warhammer30k #HorusHeresy #Miniature #WarhammerCommunity

Den of Imagination

5,957 subscribers

12,443 Aufrufe • vor 3 Monaten •via X (Twitter)

#Freehand #Warhammer30k #HorusHeresy #Miniature #WarhammerCommunity

Anya Rossi• Live Now

Private livecam show

0 Kommentare

Keine Kommentare verfügbar

Kommentare vom Original-Post werden hier angezeigt

Ähnliche Videos

Freehand is not an addition – it’s the signature of your army. On an Imperial Knight’s shoulder, a Battle Sister comes alive with every brushstroke. Freehand Commissions -service@denofimagination.com #Warhammer40k #ImperialKnight #Freehand #AdeptusSororitas #MiniaturePainting

Freehand is not an addition – it’s the signature of your army. On an Imperial Knight’s shoulder, a Battle Sister comes alive with every brushstroke. Freehand Commissions [email protected] #Warhammer40k #ImperialKnight #Freehand #AdeptusSororitas #MiniaturePainting

Den of Imagination

11,426 Aufrufe • vor 11 Monaten

Every symbol must work both up close and from a distance. The process of creating freehand on a Titan shoulder pad – no decals, no compromises. Want a similar project? Write → service@denofimagination.com #Freehand #Wargaming #Warhammer40k #PaintingWarhammer #ModelPainting

Every symbol must work both up close and from a distance. The process of creating freehand on a Titan shoulder pad – no decals, no compromises. Want a similar project? Write → [email protected] #Freehand #Wargaming #Warhammer40k #PaintingWarhammer #ModelPainting

Den of Imagination

16,019 Aufrufe • vor 9 Monaten

#WATCH | Mumbai: Maharashtra Deputy CM Eknath Shinde says, " An important meeting related to security has taken place with Army, Navy, Air Force and Civil Defence...a discussion was held to appoint a nodal officer.. This is the financial capital, so Mumbai is always targeted...I want to thank all three services for giving a befitting reply...Thanks to PM Modi for giving freehand to all three services. Earlier, no one ever dared to give freehand to armed forces, no matter how bad the situation was..."

#WATCH | Mumbai: Maharashtra Deputy CM Eknath Shinde says, " An important meeting related to security has taken place with Army, Navy, Air Force and Civil Defence...a discussion was held to appoint a nodal officer.. This is the financial capital, so Mumbai is always targeted...I want to thank all three services for giving a befitting reply...Thanks to PM Modi for giving freehand to all three services. Earlier, no one ever dared to give freehand to armed forces, no matter how bad the situation was..."

ANI

31,988 Aufrufe • vor 1 Jahr

Here’s an eyeball I drew freehand with a 12-pack of Crayola Crayons. Never tell me to pick up a pencil if you draw with a stylus or photoshop.. No Ai was used in this, but saying that is not a mark of quality or integrity whatsoever. I also use Ai because it is a powerful tool.

Here’s an eyeball I drew freehand with a 12-pack of Crayola Crayons. Never tell me to pick up a pencil if you draw with a stylus or photoshop.. No Ai was used in this, but saying that is not a mark of quality or integrity whatsoever. I also use Ai because it is a powerful tool.

Doug TenNapel

38,742 Aufrufe • vor 7 Monaten

No, this isn’t a Transformer. It’s a Leopard 2 Leguan, folding its 26-meter bridge. This bridge layer is operated by engineers of the Royal Netherlands Army.

No, this isn’t a Transformer. It’s a Leopard 2 Leguan, folding its 26-meter bridge. This bridge layer is operated by engineers of the Royal Netherlands Army.

Klaas Meijer

48,417 Aufrufe • vor 1 Jahr

🎓Learn how to create a powerful Torn Fabric smart material in a matter of seconds in my latest video series (AAA) Pro Tips! This smart material can be used on virtually any 3D asset. ____________________________________________________ In this video, the steps are as follows: 1. Create a base fill layer containing no information. We will use this layer to call out the core effects. Add a black mask to this layer and inside that mask add a paint layer and draw a simple pill shape. 2. Next, add a blur directional and be sure the direction is the same direction that your fabric is flowing to. 3. Add a UV border generator set to subtract to mask out any uv seams followed by an anchorpoint. Additionally, add a messy Fibers 3 fill layer set to overlay. 4. Use a levels to adjust the mask along with a sharpen filter. A warp filter should also be added to introduce some randomness. Add an anchor point at the top of the mask as well. 5. Create another fill layer with its opacity channel set to black and apply a black mask to the fill layer. Inside its mask retrieve the anchorpoint information from the previous fill layer. 6. Create an additional fill layer with a bright diffuse color along with a black mask applied to it. Add the anchorpoint information from the previous mask into its mask as well and this should give us some white fibers on the edges. Now we have a torn fabric effect wherever we paint using the paint layer created inside the callout mask! ____________________________________________________ More AAA Game Dev Tips can be found on my YouTube channel here: Stay tuned for more weekly Tips! Happy Texturing!💚 #gamedev #gameart #tutorial #3dmodeling #hardsurface #texturing

🎓Learn how to create a powerful Torn Fabric smart material in a matter of seconds in my latest video series (AAA) Pro Tips! This smart material can be used on virtually any 3D asset. In this video, the steps are as follows: 1. Create a base fill layer containing no information. We will use this layer to call out the core effects. Add a black mask to this layer and inside that mask add a paint layer and draw a simple pill shape. 2. Next, add a blur directional and be sure the direction is the same direction that your fabric is flowing to. 3. Add a UV border generator set to subtract to mask out any uv seams followed by an anchorpoint. Additionally, add a messy Fibers 3 fill layer set to overlay. 4. Use a levels to adjust the mask along with a sharpen filter. A warp filter should also be added to introduce some randomness. Add an anchor point at the top of the mask as well. 5. Create another fill layer with its opacity channel set to black and apply a black mask to the fill layer. Inside its mask retrieve the anchorpoint information from the previous fill layer. 6. Create an additional fill layer with a bright diffuse color along with a black mask applied to it. Add the anchorpoint information from the previous mask into its mask as well and this should give us some white fibers on the edges. Now we have a torn fabric effect wherever we paint using the paint layer created inside the callout mask! More AAA Game Dev Tips can be found on my YouTube channel here: Stay tuned for more weekly Tips! Happy Texturing!💚 #gamedev #gameart #tutorial #3dmodeling #hardsurface #texturing

Cohen Brawley

78,842 Aufrufe • vor 2 Jahren

#Amaravati is not just being imagined - it is being built. Roads are taking shape across the capital region, with underground cabling and modern drainage systems progressing in parallel. No patchwork. No temporary fixes. Only world-class, future-ready infrastructure. This is how great cities are built - layer by layer, with planning and precision. Amaravati’s rapid progress reflects our commitment to creating a capital that is resilient, sustainable, and globally competitive.

#Amaravati is not just being imagined - it is being built. Roads are taking shape across the capital region, with underground cabling and modern drainage systems progressing in parallel. No patchwork. No temporary fixes. Only world-class, future-ready infrastructure. This is how great cities are built - layer by layer, with planning and precision. Amaravati’s rapid progress reflects our commitment to creating a capital that is resilient, sustainable, and globally competitive.

Lokesh Nara

51,704 Aufrufe • vor 7 Monaten

This is the Meltio Engine, a 3D printer that creates metal parts with high precision. It uses laser-based technology with wire and powder together to build complex parts layer by layer. It is faster than traditional methods and can also repair or upgrade existing metal parts.

This is the Meltio Engine, a 3D printer that creates metal parts with high precision. It uses laser-based technology with wire and powder together to build complex parts layer by layer. It is faster than traditional methods and can also repair or upgrade existing metal parts.

Space and Technology

48,793 Aufrufe • vor 5 Monaten

Don't talk directly to a model. You can make your application 10x more flexible by simply adding one intermediate layer between your code and the model. This is the simplest trick you can use to improve the architecture of whatever you are building.

Don't talk directly to a model. You can make your application 10x more flexible by simply adding one intermediate layer between your code and the model. This is the simplest trick you can use to improve the architecture of whatever you are building.

Santiago

88,884 Aufrufe • vor 5 Monaten

It’s not every day you see an Inquisitor piloting a winged Hive Tyrant! An absolutely crazy miniature from our Custom Service team! Create your Custom Service character: Our client has conceptualised an awesome Inquisition army, for which this was the centrepiece! We absolutely loved creating and painting it! Want to get a bespoke miniature created by our team? Get in touch with the links in our profile! #warhammer #warhammer40k #warhammercommunity #warhammer40000 #siegestudios

Siege Studios

15,338 Aufrufe • vor 8 Monaten

Rogal Dorn in Centurion armour which we have converted, sculpted and now painted through Custom Service! Create your Custom Service character: This one off bespoke miniature received a crazy response when we initially showed off the conversion and sculpt. We wanted to show you a 360 of him looking dashing with his moustache! Want to get your own custom character created for you by our team? Get in touch with the links in our profile! #warhammer #warhammer40k #40k #rogaldorn #warhammercommunity

Siege Studios

14,325 Aufrufe • vor 7 Monaten

Have you ever seen the decapsulating of a microchip layer by layer using a 30W JPT Fiber Laser? Well now you have and the the precision is wild to see.

Have you ever seen the decapsulating of a microchip layer by layer using a 30W JPT Fiber Laser? Well now you have and the the precision is wild to see.

Bluntly Put Philosopher (BPP)

84,053 Aufrufe • vor 5 Monaten

Backpropagation by hand ✍️ ~ 11 steps walkthrough below Backpropagation is the algorithm that actually trains a neural network, and it is where most people stop following along. It is not calculus you cannot do. It is matrix multiplication, working backward, one layer at a time. So I drew and calculated one entirely by hand. Goal: push the loss gradient back through a 3-layer network and land on a new value for every weight and bias. = 1. Given = A 3-layer perceptron, an input X, predictions Ypred = [0.5, 0.5, 0], and the truth Ytarget = [0, 1, 0]. = 2. Backprop gradient cells = Let us draw empty cells for every gradient we are about to compute. The shape of the answer comes first. = 3. Layer 3 softmax = We get dL/dz3 straight from Ypred minus Ytarget = [0.5, -0.5, 0]. No chain rule needed, and that shortcut is the whole reason softmax and cross-entropy are paired. = 4. Layer 3 weights and biases = Let us multiply dL/dz3 by [a2 | 1]. One multiplication gives the gradient for W3 and b3 together. = 5. Layer 2 activations = We multiply dL/dz3 by W3 to get dL/da2. The gradient moves back across a layer the same way the signal moved forward. = 6. Layer 2 ReLU = Let us pass it through the gate: keep the gradient where the activation was positive, zero it everywhere else. = 7. Layer 2 weights and biases = We multiply dL/dz2 by [a1 | 1]. The same figure as step 4, one layer up. = 8. Layer 1 activations = Let us multiply dL/dz2 by W2. = 9. Layer 1 ReLU = We apply the same gate again, now on a1. = 10. Layer 1 weights and biases = Let us multiply dL/dz1 by [x | 1], and every weight in the network now has a gradient. = 11. Update = We subtract, and the network has learned. In practice a learning rate scales this step. The gradients: dL/dz3 = [0.5, -0.5, 0] dL/da1 = [1, -2, 2, -1] dL/dz1 = [0, -2, 2, -1] The takeaway: matrix multiplication is all you need. Just like the forward pass, backpropagation is matrix multiplications end to end. You can do every one by hand, slowly and imperfectly, which is exactly why a GPU's ability to do them fast mattered so much to deep learning. 💾 Save this post!

Backpropagation by hand ✍️ ~ 11 steps walkthrough below Backpropagation is the algorithm that actually trains a neural network, and it is where most people stop following along. It is not calculus you cannot do. It is matrix multiplication, working backward, one layer at a time. So I drew and calculated one entirely by hand. Goal: push the loss gradient back through a 3-layer network and land on a new value for every weight and bias. = 1. Given = A 3-layer perceptron, an input X, predictions Ypred = [0.5, 0.5, 0], and the truth Ytarget = [0, 1, 0]. = 2. Backprop gradient cells = Let us draw empty cells for every gradient we are about to compute. The shape of the answer comes first. = 3. Layer 3 softmax = We get dL/dz3 straight from Ypred minus Ytarget = [0.5, -0.5, 0]. No chain rule needed, and that shortcut is the whole reason softmax and cross-entropy are paired. = 4. Layer 3 weights and biases = Let us multiply dL/dz3 by [a2 | 1]. One multiplication gives the gradient for W3 and b3 together. = 5. Layer 2 activations = We multiply dL/dz3 by W3 to get dL/da2. The gradient moves back across a layer the same way the signal moved forward. = 6. Layer 2 ReLU = Let us pass it through the gate: keep the gradient where the activation was positive, zero it everywhere else. = 7. Layer 2 weights and biases = We multiply dL/dz2 by [a1 | 1]. The same figure as step 4, one layer up. = 8. Layer 1 activations = Let us multiply dL/dz2 by W2. = 9. Layer 1 ReLU = We apply the same gate again, now on a1. = 10. Layer 1 weights and biases = Let us multiply dL/dz1 by [x | 1], and every weight in the network now has a gradient. = 11. Update = We subtract, and the network has learned. In practice a learning rate scales this step. The gradients: dL/dz3 = [0.5, -0.5, 0] dL/da1 = [1, -2, 2, -1] dL/dz1 = [0, -2, 2, -1] The takeaway: matrix multiplication is all you need. Just like the forward pass, backpropagation is matrix multiplications end to end. You can do every one by hand, slowly and imperfectly, which is exactly why a GPU's ability to do them fast mattered so much to deep learning. 💾 Save this post!

Tom Yeh

961,451 Aufrufe • vor 2 Monaten

A cattle rancher ordered a filet and knew something was off INSTANTLY. “This steak is GLUED together.” He pulled it apart, layer by layer. Scraps bound into one cut. Marketed as premium. No disclosure. This is what a profit-first system looks like when it touches your food.

A cattle rancher ordered a filet and knew something was off INSTANTLY. “This steak is GLUED together.” He pulled it apart, layer by layer. Scraps bound into one cut. Marketed as premium. No disclosure. This is what a profit-first system looks like when it touches your food.

MatrixMysteries

2,692,376 Aufrufe • vor 7 Monaten

Add a face to your voice agent. LiveAvatar by HeyGen is now supported in LiveKit Agents. Add a realtime human avatar to your agent without rebuilding the conversation loop. Your LiveKit agent still owns the room, turn-taking, model orchestration, and voice pipeline. LiveAvatar renders the synchronized face and video stream. Useful for product demos, onboarding, tutoring, and support agents that need a visual layer.

LiveKit

10,885 Aufrufe • vor 4 Monaten

How do we enable single-layer PCBs to support the routing complexity of multi-layer PCBs? We're making a "Bridge-Programmable Interconnect" chip. This chip is "programmed" by traces etched on the top layer of the PCB, it allows any configurable pin to connect to any other configurable pin Why is this a big deal? Single-layer PCB etching can be done in minutes on a UV laser, but because they don't have vias it is impossible to change layers. Using an interconnect chip, you are guaranteed to be able to route any signal over any other signal. By placing these on your single-layer PCB, you can reconfigure wiring such that you don't need any vias!

How do we enable single-layer PCBs to support the routing complexity of multi-layer PCBs? We're making a "Bridge-Programmable Interconnect" chip. This chip is "programmed" by traces etched on the top layer of the PCB, it allows any configurable pin to connect to any other configurable pin Why is this a big deal? Single-layer PCB etching can be done in minutes on a UV laser, but because they don't have vias it is impossible to change layers. Using an interconnect chip, you are guaranteed to be able to route any signal over any other signal. By placing these on your single-layer PCB, you can reconfigure wiring such that you don't need any vias!

Seve

30,046 Aufrufe • vor 10 Monaten