• John Wick: Ballerina 4K Steelbook Edition Preorders Restocked For $30 At Walmart

    Ballerina: World of John Wick - Limited Edition Steelbook| Exclusive to Walmart / Restocked August 27 Preorder at Walmart The retailer-exclusive Steelbook Editions of Ballerina: From the World of John Wick have been difficult to find in stock at Walmart and Amazon since preorders first opened in early June. But with only two weeks until the John Wick spin-off pirouettes onto 4K Blu-ray, Walmart has restocked its exclusive collectible edition. Walmart's Ballerina Limited Edition Steelbook is available to preorder for only ahead of its September 9 release.Ballerina on 4K Blu-ray:Walmart's Steelbook Edition -- | In stockAmazon's Steelbook Edition -- | Sold outStandard Edition --The Amazon-exclusive Ballerina Steelbook was actually back in stock for a very brief window while we were writing this story, but it sold out again. We'd still recommend checking the store page to see if it returns. Tastes differ, but the design of Walmart's exclusive looks cooler, in part because it has a picture frame-inspired slipcover.Continue Reading at GameSpot
    #john #wick #ballerina #steelbook #edition
    John Wick: Ballerina 4K Steelbook Edition Preorders Restocked For $30 At Walmart
    Ballerina: World of John Wick - Limited Edition Steelbook| Exclusive to Walmart / Restocked August 27 Preorder at Walmart The retailer-exclusive Steelbook Editions of Ballerina: From the World of John Wick have been difficult to find in stock at Walmart and Amazon since preorders first opened in early June. But with only two weeks until the John Wick spin-off pirouettes onto 4K Blu-ray, Walmart has restocked its exclusive collectible edition. Walmart's Ballerina Limited Edition Steelbook is available to preorder for only ahead of its September 9 release.Ballerina on 4K Blu-ray:Walmart's Steelbook Edition -- | In stockAmazon's Steelbook Edition -- | Sold outStandard Edition --The Amazon-exclusive Ballerina Steelbook was actually back in stock for a very brief window while we were writing this story, but it sold out again. We'd still recommend checking the store page to see if it returns. Tastes differ, but the design of Walmart's exclusive looks cooler, in part because it has a picture frame-inspired slipcover.Continue Reading at GameSpot #john #wick #ballerina #steelbook #edition
    John Wick: Ballerina 4K Steelbook Edition Preorders Restocked For $30 At Walmart
    www.gamespot.com
    Ballerina: World of John Wick - Limited Edition Steelbook (4K Blu-ray) $30 | Exclusive to Walmart / Restocked August 27 Preorder at Walmart The retailer-exclusive Steelbook Editions of Ballerina: From the World of John Wick have been difficult to find in stock at Walmart and Amazon since preorders first opened in early June. But with only two weeks until the John Wick spin-off pirouettes onto 4K Blu-ray, Walmart has restocked its exclusive collectible edition. Walmart's Ballerina Limited Edition Steelbook is available to preorder for only $30 ahead of its September 9 release.Ballerina on 4K Blu-ray:Walmart's Steelbook Edition -- $30 | In stockAmazon's Steelbook Edition -- $34.35 | Sold outStandard Edition -- $28 ($43)The Amazon-exclusive Ballerina Steelbook was actually back in stock for a very brief window while we were writing this story, but it sold out again. We'd still recommend checking the store page to see if it returns. Tastes differ, but the design of Walmart's exclusive looks cooler, in part because it has a picture frame-inspired slipcover.Continue Reading at GameSpot
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  • Romeo is a Dead Man: A sneak peak of what to expect

    What’s up, everyone? I’m gonna assume you’ve already seen the announcement trailer for Grasshopper Manufacture’s all-new title, Romeo Is A Dead Man. If not, then do yourself a favor and go watch it now. It’s cool – I’ll wait two and a half minutes.

    Play Video

    OK, so you get that there’s gonna be a whole lot of extremely bloody battle action and exploring some weird places, but I think a lot of people may be confused by the sheer amount of information packed into two and a half minutes… Today, we’ll give you a teensy little glimpse of how Romeo Stargazer – aka “DeadMan”, a special agent in the FBI division known as the Space-Time Police – goes about his “investigations”.

    Romeo Is A Dead Man, abbreviated as… I don’t know, RiaDM? or maybe RoDeMa, if you’re nasty? Anyway, one of the most notable features of the game is the rich variety of graphic styles used to depict the game world. Seriously, it’s all over the place – but like, in a good way. The meticulously-tweaked action parts are done in stunning, almost photorealistic 3D, and we’ve thrown everything but the kitchen sink into the more story-based parts.

    And don’t worry, GhM fans – we promise: for as much work as we’ve put into making the game look cool and unique, the story itself is also ridiculously bonkers, as is tradition here at Grasshopper Manufacture. We think longtime fans will enjoy it, and newcomers will have their heads exploding. Either way, you’re guaranteed to see some stuff you’ve never seen before.

    As for the actual battles, our hero Romeo is heavily armed with both katana-style melee weapons and gun-style ranged weapons alike, which the player can switch between while dispersing beatdowns. However even the weaker, goombah-type enemies are pretty hardcore. You’re gonna have to think up combinations of melee, ranged, heavy, and light attacks to get by. But the stupidly gratuitous amount of blood splatter and catharsis you’re rewarded with when landing a real nuclear power move of a combo is awe-inspiring, if that’s your thing. On top of the kinda-humanoid creatures you’ve already seen, known as “Rotters”, we’ve got all kinds of other ultra-creepy, unique enemies waiting to bite your face off!

    Now, let’s look at one of the main centerpieces of any GhM game: the boss battles. This particular boss is, well, hella big. His name is “Everyday Is Like Monday”, because of course it is. It’s on you to make sure Romeo can dodge the mess of attacks launched by this big-ass tyrant and take him down to Chinatown. It’s one of the most feelgood beatdowns of the year!

    Also, being a member of something called the “Space-Time Police” means that obviously Romeo is gonna be visiting all sorts of weird, “…what?”-type places. And awaiting him at these weird, “…what?”-type places are a range of weird, “…what?”-type puzzles that only the highest double-digit IQ players will be able to solve! This thing looks like a simple sphere that someone just kinda dropped and busted, but once you really wrap your dome around it and get it solved, damn it feels good. There are a slew of other puzzles and gimmicks strategically or possibly just randomly strewn throughout the game, so keep your eyeballs peeled for them and try not to break any controllers as you encounter them along your mission.

    That’s all for now, but obviously there are still a whole bunch of important game elements we have yet to discuss, so stay tuned for next time!
    #romeo #dead #man #sneak #peak
    Romeo is a Dead Man: A sneak peak of what to expect
    What’s up, everyone? I’m gonna assume you’ve already seen the announcement trailer for Grasshopper Manufacture’s all-new title, Romeo Is A Dead Man. If not, then do yourself a favor and go watch it now. It’s cool – I’ll wait two and a half minutes. Play Video OK, so you get that there’s gonna be a whole lot of extremely bloody battle action and exploring some weird places, but I think a lot of people may be confused by the sheer amount of information packed into two and a half minutes… Today, we’ll give you a teensy little glimpse of how Romeo Stargazer – aka “DeadMan”, a special agent in the FBI division known as the Space-Time Police – goes about his “investigations”. Romeo Is A Dead Man, abbreviated as… I don’t know, RiaDM? or maybe RoDeMa, if you’re nasty? Anyway, one of the most notable features of the game is the rich variety of graphic styles used to depict the game world. Seriously, it’s all over the place – but like, in a good way. The meticulously-tweaked action parts are done in stunning, almost photorealistic 3D, and we’ve thrown everything but the kitchen sink into the more story-based parts. And don’t worry, GhM fans – we promise: for as much work as we’ve put into making the game look cool and unique, the story itself is also ridiculously bonkers, as is tradition here at Grasshopper Manufacture. We think longtime fans will enjoy it, and newcomers will have their heads exploding. Either way, you’re guaranteed to see some stuff you’ve never seen before. As for the actual battles, our hero Romeo is heavily armed with both katana-style melee weapons and gun-style ranged weapons alike, which the player can switch between while dispersing beatdowns. However even the weaker, goombah-type enemies are pretty hardcore. You’re gonna have to think up combinations of melee, ranged, heavy, and light attacks to get by. But the stupidly gratuitous amount of blood splatter and catharsis you’re rewarded with when landing a real nuclear power move of a combo is awe-inspiring, if that’s your thing. On top of the kinda-humanoid creatures you’ve already seen, known as “Rotters”, we’ve got all kinds of other ultra-creepy, unique enemies waiting to bite your face off! Now, let’s look at one of the main centerpieces of any GhM game: the boss battles. This particular boss is, well, hella big. His name is “Everyday Is Like Monday”, because of course it is. It’s on you to make sure Romeo can dodge the mess of attacks launched by this big-ass tyrant and take him down to Chinatown. It’s one of the most feelgood beatdowns of the year! Also, being a member of something called the “Space-Time Police” means that obviously Romeo is gonna be visiting all sorts of weird, “…what?”-type places. And awaiting him at these weird, “…what?”-type places are a range of weird, “…what?”-type puzzles that only the highest double-digit IQ players will be able to solve! This thing looks like a simple sphere that someone just kinda dropped and busted, but once you really wrap your dome around it and get it solved, damn it feels good. There are a slew of other puzzles and gimmicks strategically or possibly just randomly strewn throughout the game, so keep your eyeballs peeled for them and try not to break any controllers as you encounter them along your mission. That’s all for now, but obviously there are still a whole bunch of important game elements we have yet to discuss, so stay tuned for next time! #romeo #dead #man #sneak #peak
    Romeo is a Dead Man: A sneak peak of what to expect
    blog.playstation.com
    What’s up, everyone? I’m gonna assume you’ve already seen the announcement trailer for Grasshopper Manufacture’s all-new title, Romeo Is A Dead Man. If not, then do yourself a favor and go watch it now. It’s cool – I’ll wait two and a half minutes. Play Video OK, so you get that there’s gonna be a whole lot of extremely bloody battle action and exploring some weird places, but I think a lot of people may be confused by the sheer amount of information packed into two and a half minutes… Today, we’ll give you a teensy little glimpse of how Romeo Stargazer – aka “DeadMan”, a special agent in the FBI division known as the Space-Time Police – goes about his “investigations”. Romeo Is A Dead Man, abbreviated as… I don’t know, RiaDM? or maybe RoDeMa, if you’re nasty? Anyway, one of the most notable features of the game is the rich variety of graphic styles used to depict the game world. Seriously, it’s all over the place – but like, in a good way. The meticulously-tweaked action parts are done in stunning, almost photorealistic 3D, and we’ve thrown everything but the kitchen sink into the more story-based parts. And don’t worry, GhM fans – we promise: for as much work as we’ve put into making the game look cool and unique, the story itself is also ridiculously bonkers, as is tradition here at Grasshopper Manufacture. We think longtime fans will enjoy it, and newcomers will have their heads exploding. Either way, you’re guaranteed to see some stuff you’ve never seen before. As for the actual battles, our hero Romeo is heavily armed with both katana-style melee weapons and gun-style ranged weapons alike, which the player can switch between while dispersing beatdowns. However even the weaker, goombah-type enemies are pretty hardcore. You’re gonna have to think up combinations of melee, ranged, heavy, and light attacks to get by. But the stupidly gratuitous amount of blood splatter and catharsis you’re rewarded with when landing a real nuclear power move of a combo is awe-inspiring, if that’s your thing. On top of the kinda-humanoid creatures you’ve already seen, known as “Rotters”, we’ve got all kinds of other ultra-creepy, unique enemies waiting to bite your face off! Now, let’s look at one of the main centerpieces of any GhM game: the boss battles. This particular boss is, well, hella big. His name is “Everyday Is Like Monday”, because of course it is. It’s on you to make sure Romeo can dodge the mess of attacks launched by this big-ass tyrant and take him down to Chinatown. It’s one of the most feelgood beatdowns of the year! Also, being a member of something called the “Space-Time Police” means that obviously Romeo is gonna be visiting all sorts of weird, “…what?”-type places. And awaiting him at these weird, “…what?”-type places are a range of weird, “…what?”-type puzzles that only the highest double-digit IQ players will be able to solve! This thing looks like a simple sphere that someone just kinda dropped and busted, but once you really wrap your dome around it and get it solved, damn it feels good. There are a slew of other puzzles and gimmicks strategically or possibly just randomly strewn throughout the game, so keep your eyeballs peeled for them and try not to break any controllers as you encounter them along your mission. That’s all for now, but obviously there are still a whole bunch of important game elements we have yet to discuss, so stay tuned for next time!
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  • Ninja Gaiden 4 Will Bring Back a Popular Ability

    Ninja Gaiden 4 will see the return of the helpful Ultimate Guidance ability, according to a message to fans from co-director and producer Yuji Nakao. Ninja Gaiden 4 looks poised to provide players with the kind of fast-paced battles they've become accustomed to since the series' reboot in 2004, and Ultimate Guidance should help keep them moving forward quickly.
    #ninja #gaiden #will #bring #back
    Ninja Gaiden 4 Will Bring Back a Popular Ability
    Ninja Gaiden 4 will see the return of the helpful Ultimate Guidance ability, according to a message to fans from co-director and producer Yuji Nakao. Ninja Gaiden 4 looks poised to provide players with the kind of fast-paced battles they've become accustomed to since the series' reboot in 2004, and Ultimate Guidance should help keep them moving forward quickly. #ninja #gaiden #will #bring #back
    Ninja Gaiden 4 Will Bring Back a Popular Ability
    gamerant.com
    Ninja Gaiden 4 will see the return of the helpful Ultimate Guidance ability, according to a message to fans from co-director and producer Yuji Nakao. Ninja Gaiden 4 looks poised to provide players with the kind of fast-paced battles they've become accustomed to since the series' reboot in 2004, and Ultimate Guidance should help keep them moving forward quickly.
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  • Battlefield 6 Looks Great But It Won't Beat Call Of Duty This Year

    For the first time since 2021, new installments in the Call of Duty and Battlefield franchises are releasing in the same year, and this has prompted the inevitable comparisons between the two long-running multiplayer first-person shooter franchises to resurface.Early impressions of Battlefield 6 from its open beta suggest that Electronic Arts and Battlefield Studios have a hit on their hands, but Battlefield 6 is unlikely to dethrone Call of Duty this year, even if the sentiment around Black Ops 7 is not tracking so highly. While EA would like to take some market share from Call of Duty, and it's possible that happens, Call of Duty's reign as the No. 1 paid FPS franchise will likely continue."While Battlefield 6 has the potential to perform better than any Battlefield game ever has-- financially and critically--it almost certainly won't outsell Call of Duty," said Rhys Elliott of Alinea Analytics.Continue Reading at GameSpot
    #battlefield #looks #great #but #won039t
    Battlefield 6 Looks Great But It Won't Beat Call Of Duty This Year
    For the first time since 2021, new installments in the Call of Duty and Battlefield franchises are releasing in the same year, and this has prompted the inevitable comparisons between the two long-running multiplayer first-person shooter franchises to resurface.Early impressions of Battlefield 6 from its open beta suggest that Electronic Arts and Battlefield Studios have a hit on their hands, but Battlefield 6 is unlikely to dethrone Call of Duty this year, even if the sentiment around Black Ops 7 is not tracking so highly. While EA would like to take some market share from Call of Duty, and it's possible that happens, Call of Duty's reign as the No. 1 paid FPS franchise will likely continue."While Battlefield 6 has the potential to perform better than any Battlefield game ever has-- financially and critically--it almost certainly won't outsell Call of Duty," said Rhys Elliott of Alinea Analytics.Continue Reading at GameSpot #battlefield #looks #great #but #won039t
    Battlefield 6 Looks Great But It Won't Beat Call Of Duty This Year
    www.gamespot.com
    For the first time since 2021, new installments in the Call of Duty and Battlefield franchises are releasing in the same year, and this has prompted the inevitable comparisons between the two long-running multiplayer first-person shooter franchises to resurface.Early impressions of Battlefield 6 from its open beta suggest that Electronic Arts and Battlefield Studios have a hit on their hands, but Battlefield 6 is unlikely to dethrone Call of Duty this year, even if the sentiment around Black Ops 7 is not tracking so highly. While EA would like to take some market share from Call of Duty, and it's possible that happens, Call of Duty's reign as the No. 1 paid FPS franchise will likely continue."While Battlefield 6 has the potential to perform better than any Battlefield game ever has-- financially and critically--it almost certainly won't outsell Call of Duty," said Rhys Elliott of Alinea Analytics.Continue Reading at GameSpot
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  • Fur Grooming Techniques For Realistic Stitch In Blender

    IntroductionHi everyone! My name is Oleh Yakushev, and I'm a 3D Artist from Ukraine. My journey into 3D began just three years ago, when I was working as a mobile phone salesperson at a shopping mall. In 2022, during one slow day at work, I noticed a colleague learning Python. We started talking about life goals. I told him I wanted to switch careers, to do something creative, but programming wasn't really my thing.He asked me a simple question: "Well, what do you actually enjoy doing?"I said, "Video games. I love video games. But I don't have time to learn how to make them, I've got a job, a family, and a kid."Then he hit me with something that really shifted my whole perspective."Oleh, do you play games on your PlayStation?"I said, "Of course."He replied, "Then why not take the time you spend playing and use it to learn how to make games?"That moment flipped a switch in my mind. I realized that I did have time, it was just a matter of how I used it. If I really wanted to learn, I could find a way. At the time, I didn't even own a computer. But where there's a will, there's a way: I borrowed my sister's laptop for a month and started following beginner 3D tutorials on YouTube. Every night after work, once my family went to sleep, I'd sit in the kitchen and study. I stayed up until 2 or 3 AM, learning Blender basics. Then I'd sleep for a few hours before waking up at 6 AM to go back to work. That's how I spent my first few months in 3D, studying every single night.3D completely took over my life. During lunch breaks, I watched 3D videos, on the bus, I scrolled through 3D TikToks, at home, I took 3D courses, and the word "3D" just became a constant in my vocabulary.After a few months of learning the basics, I started building my portfolio, which looks pretty funny to me now. But at the time, it was a real sign of how committed I was. Eventually, someone reached out to me through Behance, offering my first freelance opportunity. And thatэs how my journey began, from mall clerk to 3D artist. It's been a tough road, full of burnout, doubts, and late nights... but also full of curiosity, growth, and hope. And I wouldn't trade it for anything.The Stitch ProjectI've loved Stitch since I was a kid. I used to watch the cartoons, play the video games, and he always felt like such a warm, funny, chill, and at the same time, strong character. So once I reached a certain level in 3D, I decided to recreate Stitch.Back then, my skills only allowed me to make him in a stylized cartoonish style, no fur, no complex detailing, no advanced texturing, I just didn't have the experience. Surprisingly, the result turned out pretty decent. Even now, I sometimes get comments that my old Stitch still looks quite cute. Though honestly, I wouldn't say that myself anymore. Two years have passed since I made that first Stitch, it was back in 2023. And in 2025, I decided it was time to challenge myself.At that point, I had just completed an intense grooming course. Grooming always intimidated me, it felt really complex. I avoided it on commercial projects, made a few failed attempts for my portfolio, and overall tried to steer clear of any tasks where grooming was required. But eventually, I found the strength to face it.I pushed myself to learn how to make great fur, and I did. I finally understood how the grooming system works, grasped the logic, the tools, and the workflow. And after finishing the course, I wanted to lock in all that knowledge by creating a full personal project from scratch.So my goal was to make a character from the ground up, where the final stage would be grooming. And without thinking too long, I chose Stitch.First, because I truly love the character. Second, I wanted to clearly see my own progress over the past two years. Third, I needed to put my new skills to the test and find out whether my training had really paid off.ModelingI had a few ideas for how to approach the base mesh for this project. First, to model everything completely from scratch, starting with a sphere. Second, to reuse my old Stitch model and upgrade it.But then an idea struck me: why not test how well AI could handle a base mesh? I gathered some references and tried generating a base mesh using AI, uploading Stitch visuals as a guide. As you can see from the screenshot, the result was far from usable. So I basically ended up doing everything from scratch anyway.So, I went back to basics: digging through ArtStation and Pinterest, collecting references. Since over the last two years, I had not only learned grooming but also completely changed my overall approach to character creation, it was important for me to make a more detailed model, even if much of it would be hidden under fur.The first Stitch was sculpted in Blender, with all the limitations that come with sculpting in it. But since then, I've leveled up significantly and switched to more advanced tools. So this second version of Stitch was born in ZBrush. By the time I started working on this Stitch, ZBrush had already become my second main workspace. I've used it to deliver tons of commercial projects, I work in it almost daily, and most of my portfolio was created using this tool. I found some great reference images showing Stitch's body structure. Among them were official movie references and a stunning high-poly model created by Juan Hernández, a version of Stitch without fur. That model became my primary reference for sculpting.Truth is, Stitch's base form is quite simple, so blocking out the shape didn't take too long. When blocking, I use Blender in combination with ZBrush:I work with primary forms in ZBrushThen check proportions in BlenderFix mistakes, tweak volumes, and refine the silhouetteSince Stitch's shape isn't overly complex, I broke him down into three main sculpting parts:The body: arms, legs, head, and earsThe nose, eyes, and mouth cavityWhile planning the sculpt, I already knew I'd be rigging Stitch, both body and facial rig. So I started sculpting with his mouth open.While studying various references, I noticed something interesting. Stitch from promotional posters, Stitch from the movie, and Stitch as recreated by different artists on ArtStation all look very different from one another. What surprised me the most was how different the promo version of Stitch is compared to the one in the actual movie. They are essentially two separate models:Different proportionsDifferent shapesDifferent texturesEven different fur and overall designThis presented a creative challenge, I had to develop my own take on Stitch's design. Sometimes I liked the way the teeth were done in one version, in another, the eye placement, in another, the fur shape, or the claw design on hands and feet.At first, considering that Stitch is completely covered in fur from head to toe, sculpting his underlying anatomy seemed pointless. I kept asking myself: "Why sculpt muscles and skin detail if everything will be hidden under fur anyway?"But eventually, I found a few solid answers for myself. First, having a defined muscle structure actually makes the fur grooming process easier. That's because fur often follows the flow of muscle lines, so having those muscles helps guide fur direction more accurately across the character's body.Second, it's great anatomy practice, and practice is never a waste. So, I found a solid anatomical reference of Stitch with clearly visible muscle groups and tried to recreate that structure as closely as possible in my own sculpt.In the end, I had to develop a full visual concept by combining elements from multiple versions of Stitch. Through careful reference work and constantly switching between Blender and ZBrush, I gradually, but intentionally, built up the body and overall look of our favorite fluffy alien.Topology & UVsThroughout the sculpting process, I spent quite a bit of time thinking about topology. I was looking for the most balanced solution between quality and production time. Normally, I do manual retopology for my characters, but this time, I knew it would take too much time, and honestly, I didn't have that luxury.So I decided to generate the topology using ZBrush's tools. I split the model into separate parts using Polygroups, assigning individual groups for the ears, the head, the torso, the arms, the legs, and each of Stitch's fingers.With the Polygroups in place, I used ZRemesher with Keep Groups enabled and smoothing on group borders. This gave me a clean and optimized mesh that was perfect for UV unwrapping.Of course, this kind of auto-retopology isn't a full substitute for manual work, but it saved me a huge amount of time, and the quality was still high enough for what I needed. However, there was one tricky issue. Although Stitch looks symmetrical at first glance, his ears are actually asymmetrical. The right ear has a scar on the top, while the left has a scar on the bottomBecause of that, I couldn't just mirror one side in ZBrush without losing those unique features. Here's what I ended up doing: I created a symmetrical model with the right ear, then another symmetrical model with the left ear. I brought both into Blender, detached the left ear from one model, and attached it to the body of the other one. This way, I got a clean, symmetrical base mesh with asymmetrical ears, preserving both topology and detail. And thanks to the clean polygroup-based layout, I was able to unwrap the UVs with nice, even seams and clean islands.When it came to UV mapping, I divided Stitch into two UDIM tiles:The first UDIM includes the head with ears, torso, arms, and legs.The second UDIM contains all the additional parts: teeth, tongue, gums, claws, and noseSince the nose is one of the most important details, I allocated the largest space to it, which helped me to better capture its intricate details.As for the eyes, I used procedural eyes, so there was no need to assign UV space or create a separate UDIM for texturing them. To achieve this, I used the Tiny Eye add-on by tinynocky for Blender, which allows full control over procedural eyes and their parameters.This approach gave me high-quality eyes with customizable elements tailored exactly to my needs. As a result of all these steps, Stitch ended up with a symmetrical, optimized mesh, asymmetrical ears, and the body split across two UDIMs, one for the main body and one for the additional parts.TexturingWhen planning Stitch's texturing, I understood that the main body texture would be fairly simple, with much of the visual detail enhanced by the fur. However, there were some areas that required much more attention than the rest of the body. The textures for Stitch can be roughly divided into several main parts:The base body, which includes the primary color of his fur, along with additional shading like a lighter tone on the frontand a darker tone on the back and napeThe nose and ears, these zones, demanded separate focusAt the initial texturing/blocking stage, the ears looked too cartoony, which didn’t fit the style I wanted. So, I decided to push them towards a more realistic look. This involved removing bright colors, adding more variation in the roughness map, introducing variation in the base color, and making the ears visually more natural, layered, and textured on the surface. By combining smart materials and masks, I achieved the effect of "living" ears, slightly dirty and looking as natural as possible.The nose was a separate story. It occupies a significant part of the face and thus draws a lot of attention. While studying references, I noticed that the shape and texture of the nose vary a lot between different artists. Initially, I made it dog-like, with some wear and tear around the nostrils and base.For a long time, I thought this version was acceptable. But during test renders, I realized the nose needed improvement. So I reworked its texturing, aiming to make it more detailed. I divided the nose texture into four main layers:Base detail: Baked from the high-poly model. Over this, I applied a smart skin material that added characteristic bumps.Lighter layer: Applied via a mask using the AO channel. This darkened the crevices and brightened the bumps, creating a multi-layered effect.Organic detail: In animal references, I noticed slight redness in the nose area. I created another AO-masked layer with reddish capillaries visible through the bumps, adding depth and realism.Softness: To make the nose visually softer, like in references, I added a fill layer with only height enabled, used a paper texture as grayscale, and applied a blurred mask. This created subtle dents and wrinkles that softened the look.All textures were created in 4K resolution to achieve maximum detail. After finishing the main texturing stage, I add an Ambient Occlusion map on the final texture layer, activating only the Color channel, setting the blend mode to Multiply, and reducing opacity to about 35%. This adds volume and greatly improves the overall perception of the model.That covers the texturing of Stitch’s body. I also created a separate texture for the fur. This was simpler, I disabled unnecessary layers like ears and eyelids, and left only the base ones corresponding to the body’s color tones.During grooming, I also created textures for the fur's clamps and roughness. In Substance 3D Painter, I additionally painted masks for better fur detail.FurAnd finally, I moved on to the part that was most important to me, the very reason I started this project in the first place. Fur. This entire process was essentially a test of my fur grooming skills. After overcoming self-doubt, I trusted the process and relied on everything I had learned so far. Before diving into the grooming itself, I made sure to gather strong references. I searched for the highest quality and most inspiring examples I could find and analyzed them thoroughly. My goal was to clearly understand the direction of fur growth, its density and volume, the intensity of roughness, and the strength of clumping in different areas of Stitch's body.To create the fur, I used Blender and its Hair Particle System. The overall approach is similar to sculpting a high-detail model: work from broad strokes to finer details. So, the first step was blocking out the main flow and placement of the hair strands.At this point, I ran into a challenge: symmetry. Since the model was purposefully asymmetrical, the fur couldn't be mirrored cleanly. To solve this, I created a base fur blocking using Hair Guides with just two segments. After that, I split the fur into separate parts. I duplicated the main Particle System and created individual hair systems for each area where needed.In total, I broke Stitch's body into key sections: head, left ear, right ear, front torso, back torso, arms, hands, upper and lower legs, toes, and additional detailing layers. The final fur setup included 25 separate particle systems.To control fur growth, I used Weight Paint to fine-tune the influence on each body part individually. This separation gave me much more precision and allowed full control over every parameter of the fur on a per-section basis.The most challenging aspect of working with fur is staying patient and focused. Detail is absolutely critical because the overall picture is built entirely from tiny, subtle elements. Once the base layer was complete, I moved on to refining the fur based on my references.The most complex areas turned out to be the front of the torso and the face. When working on the torso, my goal was to create a smooth gradient, from thick, clumped fur on the chest to shorter, softer fur on the stomach.Step by step, I adjusted the transitions, directions, clumps, and volumes to achieve that look. Additionally, I used the fur itself to subtly enhance Stitch's silhouette, making his overall shape feel sharper, more expressive, and visually engaging.During fur development, I used texture maps to control the intensity of the Roughness and Clump parameters. This gave me a high degree of flexibility, textures drove these attributes across the entire model. In areas where stronger clumping or roughness was needed, I used brighter values; in zones requiring a softer look, darker values. This approach allowed for fine-tuned micro-level control of the fur shader and helped achieve a highly realistic appearance in renders.The face required special attention: the fur had to be neat, evenly distributed, and still visually appealing. The biggest challenge here was working around the eye area. Even with properly adjusted Weight Paint, interpolation sometimes caused strands to creep into the eyes.I spent a lot of time cleaning up this region to get an optimal result. I also had to revisit certain patches that looked bald, even though interpolation and weight painting were set correctly, because the fur didn't render properly there. These areas needed manual fixing.As part of the detailing stage, I also increased the number of segments in the Hair Guides.While the blocking phase only used two segments, I went up to three, and in some cases even five, for more complex regions. This gave me much more control over fur shape and flow.The tiniest details really matter, so I added extra fur layers with thinner, more chaotic strands extending slightly beyond the main silhouette. These micro-layers significantly improved the texture depth and boosted the overall realism.Aside from the grooming itself, I paid special attention to the fur material setup, as the shader plays a critical role in the final visual quality of the render. It's not enough to simply plug a color texture into a Principled BSDF node and call it done.I built a more complex shader, giving me precise control over various attributes. For example, I implemented subtle color variation across individual strands, along with darkening near the roots and a gradual brightening toward the tips. This helped add visual depth and made the fur look significantly more natural and lifelike.Working on the fur took up nearly half of the total time I spent on the entire model. And I'm genuinely happy with the result, this stage confirmed that the training I've gone through was solid and that I’m heading in the right direction with my artistic development.Rigging, Posing & SceneOnce I finished working on the fur, I rendered several 4K test shots from different angles to make sure every detail looked the way I intended. When I was fully satisfied with the results, it was time to move on to rigging.I divided the rigging process into three main parts:Body rig, for posing and positioning the characterFacial rig, for expressions and emotionsEar rig, for dynamic ear controlRigging isn't something I consider my strongest skill, but as a 3D generalist, I had to dive into many technical aspects of it. For the ears, I set up a relatively simple system with several bones connected using inverse kinematics. This gave me flexible and intuitive control during posing and allowed for the addition of dynamic movement in animation.For facial rigging, I used the FaceIt add-on, which generates a complete facial control system for mouth, eyes, and tongue. It sped up the process significantly and gave me more precision. For the body, I used the ActorCore Rig by NVIDIA, then converted it to Rigify, which gave me a familiar interface and flexible control over poses.Posing is one of my favorite stages, it's when the character really comes to life. As usual, it started with gathering references. Honestly, it was hard to pick the final poses, Stitch is so expressive and full of personality that I wanted to try hundreds of them. But I focused on those that best conveyed the spirit and mood of the character. Some poses I reworked to fit my style rather than copying directly. For example, in the pose where Stitch licks his nose, I added drool and a bit of "green slime" for comedic effect. To capture motion, I tilted his head back and made the ears fly upward, creating a vivid, emotional snapshot.Just like in sculpting or grooming, minor details make a big difference in posing. Examples include: a slight asymmetry in the facial expression, a raised corner of the mouth, one eye squinting a little more than the other, and ears set at slightly different angles.These are subtle things that might not be noticed immediately, but they’re the key to making the character feel alive and believable.For each pose, I created a separate scene and collection in Blender, including the character, specific lighting setup, and a simple background or environment. This made it easy to return to any scene later, to adjust lighting, reposition the character, or tweak the background.In one of the renders, which I used as the cover image, Stitch is holding a little frog.I want to clearly note that the 3D model of the frog is not mine, full credit goes to the original author of the asset.At first, I wanted to build a full environment around Stitch, to create a scene that would feel like a frame from a film. But after carefully evaluating my skills and priorities, I decided that a weak environment would only detract from the strength of the character. So I opted for a simple, neutral backdrop, designed to keep all the focus on Stitch himself.Rendering, Lighting & Post-ProcessingWhen the character is complete, posed expressively, and integrated into the scene, there's one final step: lighting. Lighting isn't just a technical element of the scene — it’s a full-fledged stage of the 3D pipeline. It doesn't just illuminate; it paints. Proper lighting can highlight the personality of the character, emphasize forms, and create atmosphere.For all my renders, I rely on the classic three-point lighting setup: Key Light, Fill Light, and Rim Light.While this setup is well-known, it remains highly effective. When done thoughtfully, with the right intensity, direction, and color temperature, it creates a strong light-shadow composition that brings the model to life. In addition to the three main lights, I also use an HDRI map, but with very low intensity, around 0.3, just enough to subtly enrich the ambient light without overpowering the scene.Once everything is set, it's time to hit Render and wait for the result. Due to hardware limitations, I wasn’t able to produce full animated shots with fur. Rendering a single 4K image with fur took over an hour, so I limited myself to a 360° turnaround and several static renders.I don't spend too much time on post-processing, just basic refinements in Photoshop. Slight enhancement of the composition, gentle shadow adjustments, color balance tweaks, and adding a logo. Everything is done subtly, nothing overprocessed. The goal is simply to support and enhance what’s already there.Final ThoughtsThis project has been an incredible experience. Although it was my second time creating Stitch, this time the process felt completely different at every stage. And honestly, it wasn't easy.But that was exactly the point: to challenge myself. To reimagine something familiar, to try things I'd never done before, and to walk the full journey from start to finish. The fur, the heart of this project, was especially meaningful to me. It’s what started it all. I poured a lot into this model: time, effort, emotion, and even doubts. But at the same time, I brought all my knowledge, skills, and experience into it.This work became a mirror of my progress from 2023 to 2025. I can clearly see how far I've come, and that gives me the motivation to keep going. Every hour of learning and practice paid off, the results speak for themselves. This model was created for my portfolio. I don't plan to use it commercially, unless, of course, a studio actually wants to license it for a new filmIt's been a long road: challenging, sometimes exhausting, but above all inspiring and exciting. I know there's still a lot to learn. Many things to study, improve, and polish to perfection. But I'm already on that path, and I'm not stopping.Oleh Yakushev, 3D Character ArtistInterview conducted by Gloria Levine
    #fur #grooming #techniques #realistic #stitch
    Fur Grooming Techniques For Realistic Stitch In Blender
    IntroductionHi everyone! My name is Oleh Yakushev, and I'm a 3D Artist from Ukraine. My journey into 3D began just three years ago, when I was working as a mobile phone salesperson at a shopping mall. In 2022, during one slow day at work, I noticed a colleague learning Python. We started talking about life goals. I told him I wanted to switch careers, to do something creative, but programming wasn't really my thing.He asked me a simple question: "Well, what do you actually enjoy doing?"I said, "Video games. I love video games. But I don't have time to learn how to make them, I've got a job, a family, and a kid."Then he hit me with something that really shifted my whole perspective."Oleh, do you play games on your PlayStation?"I said, "Of course."He replied, "Then why not take the time you spend playing and use it to learn how to make games?"That moment flipped a switch in my mind. I realized that I did have time, it was just a matter of how I used it. If I really wanted to learn, I could find a way. At the time, I didn't even own a computer. But where there's a will, there's a way: I borrowed my sister's laptop for a month and started following beginner 3D tutorials on YouTube. Every night after work, once my family went to sleep, I'd sit in the kitchen and study. I stayed up until 2 or 3 AM, learning Blender basics. Then I'd sleep for a few hours before waking up at 6 AM to go back to work. That's how I spent my first few months in 3D, studying every single night.3D completely took over my life. During lunch breaks, I watched 3D videos, on the bus, I scrolled through 3D TikToks, at home, I took 3D courses, and the word "3D" just became a constant in my vocabulary.After a few months of learning the basics, I started building my portfolio, which looks pretty funny to me now. But at the time, it was a real sign of how committed I was. Eventually, someone reached out to me through Behance, offering my first freelance opportunity. And thatэs how my journey began, from mall clerk to 3D artist. It's been a tough road, full of burnout, doubts, and late nights... but also full of curiosity, growth, and hope. And I wouldn't trade it for anything.The Stitch ProjectI've loved Stitch since I was a kid. I used to watch the cartoons, play the video games, and he always felt like such a warm, funny, chill, and at the same time, strong character. So once I reached a certain level in 3D, I decided to recreate Stitch.Back then, my skills only allowed me to make him in a stylized cartoonish style, no fur, no complex detailing, no advanced texturing, I just didn't have the experience. Surprisingly, the result turned out pretty decent. Even now, I sometimes get comments that my old Stitch still looks quite cute. Though honestly, I wouldn't say that myself anymore. Two years have passed since I made that first Stitch, it was back in 2023. And in 2025, I decided it was time to challenge myself.At that point, I had just completed an intense grooming course. Grooming always intimidated me, it felt really complex. I avoided it on commercial projects, made a few failed attempts for my portfolio, and overall tried to steer clear of any tasks where grooming was required. But eventually, I found the strength to face it.I pushed myself to learn how to make great fur, and I did. I finally understood how the grooming system works, grasped the logic, the tools, and the workflow. And after finishing the course, I wanted to lock in all that knowledge by creating a full personal project from scratch.So my goal was to make a character from the ground up, where the final stage would be grooming. And without thinking too long, I chose Stitch.First, because I truly love the character. Second, I wanted to clearly see my own progress over the past two years. Third, I needed to put my new skills to the test and find out whether my training had really paid off.ModelingI had a few ideas for how to approach the base mesh for this project. First, to model everything completely from scratch, starting with a sphere. Second, to reuse my old Stitch model and upgrade it.But then an idea struck me: why not test how well AI could handle a base mesh? I gathered some references and tried generating a base mesh using AI, uploading Stitch visuals as a guide. As you can see from the screenshot, the result was far from usable. So I basically ended up doing everything from scratch anyway.So, I went back to basics: digging through ArtStation and Pinterest, collecting references. Since over the last two years, I had not only learned grooming but also completely changed my overall approach to character creation, it was important for me to make a more detailed model, even if much of it would be hidden under fur.The first Stitch was sculpted in Blender, with all the limitations that come with sculpting in it. But since then, I've leveled up significantly and switched to more advanced tools. So this second version of Stitch was born in ZBrush. By the time I started working on this Stitch, ZBrush had already become my second main workspace. I've used it to deliver tons of commercial projects, I work in it almost daily, and most of my portfolio was created using this tool. I found some great reference images showing Stitch's body structure. Among them were official movie references and a stunning high-poly model created by Juan Hernández, a version of Stitch without fur. That model became my primary reference for sculpting.Truth is, Stitch's base form is quite simple, so blocking out the shape didn't take too long. When blocking, I use Blender in combination with ZBrush:I work with primary forms in ZBrushThen check proportions in BlenderFix mistakes, tweak volumes, and refine the silhouetteSince Stitch's shape isn't overly complex, I broke him down into three main sculpting parts:The body: arms, legs, head, and earsThe nose, eyes, and mouth cavityWhile planning the sculpt, I already knew I'd be rigging Stitch, both body and facial rig. So I started sculpting with his mouth open.While studying various references, I noticed something interesting. Stitch from promotional posters, Stitch from the movie, and Stitch as recreated by different artists on ArtStation all look very different from one another. What surprised me the most was how different the promo version of Stitch is compared to the one in the actual movie. They are essentially two separate models:Different proportionsDifferent shapesDifferent texturesEven different fur and overall designThis presented a creative challenge, I had to develop my own take on Stitch's design. Sometimes I liked the way the teeth were done in one version, in another, the eye placement, in another, the fur shape, or the claw design on hands and feet.At first, considering that Stitch is completely covered in fur from head to toe, sculpting his underlying anatomy seemed pointless. I kept asking myself: "Why sculpt muscles and skin detail if everything will be hidden under fur anyway?"But eventually, I found a few solid answers for myself. First, having a defined muscle structure actually makes the fur grooming process easier. That's because fur often follows the flow of muscle lines, so having those muscles helps guide fur direction more accurately across the character's body.Second, it's great anatomy practice, and practice is never a waste. So, I found a solid anatomical reference of Stitch with clearly visible muscle groups and tried to recreate that structure as closely as possible in my own sculpt.In the end, I had to develop a full visual concept by combining elements from multiple versions of Stitch. Through careful reference work and constantly switching between Blender and ZBrush, I gradually, but intentionally, built up the body and overall look of our favorite fluffy alien.Topology & UVsThroughout the sculpting process, I spent quite a bit of time thinking about topology. I was looking for the most balanced solution between quality and production time. Normally, I do manual retopology for my characters, but this time, I knew it would take too much time, and honestly, I didn't have that luxury.So I decided to generate the topology using ZBrush's tools. I split the model into separate parts using Polygroups, assigning individual groups for the ears, the head, the torso, the arms, the legs, and each of Stitch's fingers.With the Polygroups in place, I used ZRemesher with Keep Groups enabled and smoothing on group borders. This gave me a clean and optimized mesh that was perfect for UV unwrapping.Of course, this kind of auto-retopology isn't a full substitute for manual work, but it saved me a huge amount of time, and the quality was still high enough for what I needed. However, there was one tricky issue. Although Stitch looks symmetrical at first glance, his ears are actually asymmetrical. The right ear has a scar on the top, while the left has a scar on the bottomBecause of that, I couldn't just mirror one side in ZBrush without losing those unique features. Here's what I ended up doing: I created a symmetrical model with the right ear, then another symmetrical model with the left ear. I brought both into Blender, detached the left ear from one model, and attached it to the body of the other one. This way, I got a clean, symmetrical base mesh with asymmetrical ears, preserving both topology and detail. And thanks to the clean polygroup-based layout, I was able to unwrap the UVs with nice, even seams and clean islands.When it came to UV mapping, I divided Stitch into two UDIM tiles:The first UDIM includes the head with ears, torso, arms, and legs.The second UDIM contains all the additional parts: teeth, tongue, gums, claws, and noseSince the nose is one of the most important details, I allocated the largest space to it, which helped me to better capture its intricate details.As for the eyes, I used procedural eyes, so there was no need to assign UV space or create a separate UDIM for texturing them. To achieve this, I used the Tiny Eye add-on by tinynocky for Blender, which allows full control over procedural eyes and their parameters.This approach gave me high-quality eyes with customizable elements tailored exactly to my needs. As a result of all these steps, Stitch ended up with a symmetrical, optimized mesh, asymmetrical ears, and the body split across two UDIMs, one for the main body and one for the additional parts.TexturingWhen planning Stitch's texturing, I understood that the main body texture would be fairly simple, with much of the visual detail enhanced by the fur. However, there were some areas that required much more attention than the rest of the body. The textures for Stitch can be roughly divided into several main parts:The base body, which includes the primary color of his fur, along with additional shading like a lighter tone on the frontand a darker tone on the back and napeThe nose and ears, these zones, demanded separate focusAt the initial texturing/blocking stage, the ears looked too cartoony, which didn’t fit the style I wanted. So, I decided to push them towards a more realistic look. This involved removing bright colors, adding more variation in the roughness map, introducing variation in the base color, and making the ears visually more natural, layered, and textured on the surface. By combining smart materials and masks, I achieved the effect of "living" ears, slightly dirty and looking as natural as possible.The nose was a separate story. It occupies a significant part of the face and thus draws a lot of attention. While studying references, I noticed that the shape and texture of the nose vary a lot between different artists. Initially, I made it dog-like, with some wear and tear around the nostrils and base.For a long time, I thought this version was acceptable. But during test renders, I realized the nose needed improvement. So I reworked its texturing, aiming to make it more detailed. I divided the nose texture into four main layers:Base detail: Baked from the high-poly model. Over this, I applied a smart skin material that added characteristic bumps.Lighter layer: Applied via a mask using the AO channel. This darkened the crevices and brightened the bumps, creating a multi-layered effect.Organic detail: In animal references, I noticed slight redness in the nose area. I created another AO-masked layer with reddish capillaries visible through the bumps, adding depth and realism.Softness: To make the nose visually softer, like in references, I added a fill layer with only height enabled, used a paper texture as grayscale, and applied a blurred mask. This created subtle dents and wrinkles that softened the look.All textures were created in 4K resolution to achieve maximum detail. After finishing the main texturing stage, I add an Ambient Occlusion map on the final texture layer, activating only the Color channel, setting the blend mode to Multiply, and reducing opacity to about 35%. This adds volume and greatly improves the overall perception of the model.That covers the texturing of Stitch’s body. I also created a separate texture for the fur. This was simpler, I disabled unnecessary layers like ears and eyelids, and left only the base ones corresponding to the body’s color tones.During grooming, I also created textures for the fur's clamps and roughness. In Substance 3D Painter, I additionally painted masks for better fur detail.FurAnd finally, I moved on to the part that was most important to me, the very reason I started this project in the first place. Fur. This entire process was essentially a test of my fur grooming skills. After overcoming self-doubt, I trusted the process and relied on everything I had learned so far. Before diving into the grooming itself, I made sure to gather strong references. I searched for the highest quality and most inspiring examples I could find and analyzed them thoroughly. My goal was to clearly understand the direction of fur growth, its density and volume, the intensity of roughness, and the strength of clumping in different areas of Stitch's body.To create the fur, I used Blender and its Hair Particle System. The overall approach is similar to sculpting a high-detail model: work from broad strokes to finer details. So, the first step was blocking out the main flow and placement of the hair strands.At this point, I ran into a challenge: symmetry. Since the model was purposefully asymmetrical, the fur couldn't be mirrored cleanly. To solve this, I created a base fur blocking using Hair Guides with just two segments. After that, I split the fur into separate parts. I duplicated the main Particle System and created individual hair systems for each area where needed.In total, I broke Stitch's body into key sections: head, left ear, right ear, front torso, back torso, arms, hands, upper and lower legs, toes, and additional detailing layers. The final fur setup included 25 separate particle systems.To control fur growth, I used Weight Paint to fine-tune the influence on each body part individually. This separation gave me much more precision and allowed full control over every parameter of the fur on a per-section basis.The most challenging aspect of working with fur is staying patient and focused. Detail is absolutely critical because the overall picture is built entirely from tiny, subtle elements. Once the base layer was complete, I moved on to refining the fur based on my references.The most complex areas turned out to be the front of the torso and the face. When working on the torso, my goal was to create a smooth gradient, from thick, clumped fur on the chest to shorter, softer fur on the stomach.Step by step, I adjusted the transitions, directions, clumps, and volumes to achieve that look. Additionally, I used the fur itself to subtly enhance Stitch's silhouette, making his overall shape feel sharper, more expressive, and visually engaging.During fur development, I used texture maps to control the intensity of the Roughness and Clump parameters. This gave me a high degree of flexibility, textures drove these attributes across the entire model. In areas where stronger clumping or roughness was needed, I used brighter values; in zones requiring a softer look, darker values. This approach allowed for fine-tuned micro-level control of the fur shader and helped achieve a highly realistic appearance in renders.The face required special attention: the fur had to be neat, evenly distributed, and still visually appealing. The biggest challenge here was working around the eye area. Even with properly adjusted Weight Paint, interpolation sometimes caused strands to creep into the eyes.I spent a lot of time cleaning up this region to get an optimal result. I also had to revisit certain patches that looked bald, even though interpolation and weight painting were set correctly, because the fur didn't render properly there. These areas needed manual fixing.As part of the detailing stage, I also increased the number of segments in the Hair Guides.While the blocking phase only used two segments, I went up to three, and in some cases even five, for more complex regions. This gave me much more control over fur shape and flow.The tiniest details really matter, so I added extra fur layers with thinner, more chaotic strands extending slightly beyond the main silhouette. These micro-layers significantly improved the texture depth and boosted the overall realism.Aside from the grooming itself, I paid special attention to the fur material setup, as the shader plays a critical role in the final visual quality of the render. It's not enough to simply plug a color texture into a Principled BSDF node and call it done.I built a more complex shader, giving me precise control over various attributes. For example, I implemented subtle color variation across individual strands, along with darkening near the roots and a gradual brightening toward the tips. This helped add visual depth and made the fur look significantly more natural and lifelike.Working on the fur took up nearly half of the total time I spent on the entire model. And I'm genuinely happy with the result, this stage confirmed that the training I've gone through was solid and that I’m heading in the right direction with my artistic development.Rigging, Posing & SceneOnce I finished working on the fur, I rendered several 4K test shots from different angles to make sure every detail looked the way I intended. When I was fully satisfied with the results, it was time to move on to rigging.I divided the rigging process into three main parts:Body rig, for posing and positioning the characterFacial rig, for expressions and emotionsEar rig, for dynamic ear controlRigging isn't something I consider my strongest skill, but as a 3D generalist, I had to dive into many technical aspects of it. For the ears, I set up a relatively simple system with several bones connected using inverse kinematics. This gave me flexible and intuitive control during posing and allowed for the addition of dynamic movement in animation.For facial rigging, I used the FaceIt add-on, which generates a complete facial control system for mouth, eyes, and tongue. It sped up the process significantly and gave me more precision. For the body, I used the ActorCore Rig by NVIDIA, then converted it to Rigify, which gave me a familiar interface and flexible control over poses.Posing is one of my favorite stages, it's when the character really comes to life. As usual, it started with gathering references. Honestly, it was hard to pick the final poses, Stitch is so expressive and full of personality that I wanted to try hundreds of them. But I focused on those that best conveyed the spirit and mood of the character. Some poses I reworked to fit my style rather than copying directly. For example, in the pose where Stitch licks his nose, I added drool and a bit of "green slime" for comedic effect. To capture motion, I tilted his head back and made the ears fly upward, creating a vivid, emotional snapshot.Just like in sculpting or grooming, minor details make a big difference in posing. Examples include: a slight asymmetry in the facial expression, a raised corner of the mouth, one eye squinting a little more than the other, and ears set at slightly different angles.These are subtle things that might not be noticed immediately, but they’re the key to making the character feel alive and believable.For each pose, I created a separate scene and collection in Blender, including the character, specific lighting setup, and a simple background or environment. This made it easy to return to any scene later, to adjust lighting, reposition the character, or tweak the background.In one of the renders, which I used as the cover image, Stitch is holding a little frog.I want to clearly note that the 3D model of the frog is not mine, full credit goes to the original author of the asset.At first, I wanted to build a full environment around Stitch, to create a scene that would feel like a frame from a film. But after carefully evaluating my skills and priorities, I decided that a weak environment would only detract from the strength of the character. So I opted for a simple, neutral backdrop, designed to keep all the focus on Stitch himself.Rendering, Lighting & Post-ProcessingWhen the character is complete, posed expressively, and integrated into the scene, there's one final step: lighting. Lighting isn't just a technical element of the scene — it’s a full-fledged stage of the 3D pipeline. It doesn't just illuminate; it paints. Proper lighting can highlight the personality of the character, emphasize forms, and create atmosphere.For all my renders, I rely on the classic three-point lighting setup: Key Light, Fill Light, and Rim Light.While this setup is well-known, it remains highly effective. When done thoughtfully, with the right intensity, direction, and color temperature, it creates a strong light-shadow composition that brings the model to life. In addition to the three main lights, I also use an HDRI map, but with very low intensity, around 0.3, just enough to subtly enrich the ambient light without overpowering the scene.Once everything is set, it's time to hit Render and wait for the result. Due to hardware limitations, I wasn’t able to produce full animated shots with fur. Rendering a single 4K image with fur took over an hour, so I limited myself to a 360° turnaround and several static renders.I don't spend too much time on post-processing, just basic refinements in Photoshop. Slight enhancement of the composition, gentle shadow adjustments, color balance tweaks, and adding a logo. Everything is done subtly, nothing overprocessed. The goal is simply to support and enhance what’s already there.Final ThoughtsThis project has been an incredible experience. Although it was my second time creating Stitch, this time the process felt completely different at every stage. And honestly, it wasn't easy.But that was exactly the point: to challenge myself. To reimagine something familiar, to try things I'd never done before, and to walk the full journey from start to finish. The fur, the heart of this project, was especially meaningful to me. It’s what started it all. I poured a lot into this model: time, effort, emotion, and even doubts. But at the same time, I brought all my knowledge, skills, and experience into it.This work became a mirror of my progress from 2023 to 2025. I can clearly see how far I've come, and that gives me the motivation to keep going. Every hour of learning and practice paid off, the results speak for themselves. This model was created for my portfolio. I don't plan to use it commercially, unless, of course, a studio actually wants to license it for a new filmIt's been a long road: challenging, sometimes exhausting, but above all inspiring and exciting. I know there's still a lot to learn. Many things to study, improve, and polish to perfection. But I'm already on that path, and I'm not stopping.Oleh Yakushev, 3D Character ArtistInterview conducted by Gloria Levine #fur #grooming #techniques #realistic #stitch
    Fur Grooming Techniques For Realistic Stitch In Blender
    80.lv
    IntroductionHi everyone! My name is Oleh Yakushev, and I'm a 3D Artist from Ukraine. My journey into 3D began just three years ago, when I was working as a mobile phone salesperson at a shopping mall. In 2022, during one slow day at work, I noticed a colleague learning Python. We started talking about life goals. I told him I wanted to switch careers, to do something creative, but programming wasn't really my thing.He asked me a simple question: "Well, what do you actually enjoy doing?"I said, "Video games. I love video games. But I don't have time to learn how to make them, I've got a job, a family, and a kid."Then he hit me with something that really shifted my whole perspective."Oleh, do you play games on your PlayStation?"I said, "Of course."He replied, "Then why not take the time you spend playing and use it to learn how to make games?"That moment flipped a switch in my mind. I realized that I did have time, it was just a matter of how I used it. If I really wanted to learn, I could find a way. At the time, I didn't even own a computer. But where there's a will, there's a way: I borrowed my sister's laptop for a month and started following beginner 3D tutorials on YouTube. Every night after work, once my family went to sleep, I'd sit in the kitchen and study. I stayed up until 2 or 3 AM, learning Blender basics. Then I'd sleep for a few hours before waking up at 6 AM to go back to work. That's how I spent my first few months in 3D, studying every single night.3D completely took over my life. During lunch breaks, I watched 3D videos, on the bus, I scrolled through 3D TikToks, at home, I took 3D courses, and the word "3D" just became a constant in my vocabulary.After a few months of learning the basics, I started building my portfolio, which looks pretty funny to me now. But at the time, it was a real sign of how committed I was. Eventually, someone reached out to me through Behance, offering my first freelance opportunity. And thatэs how my journey began, from mall clerk to 3D artist. It's been a tough road, full of burnout, doubts, and late nights... but also full of curiosity, growth, and hope. And I wouldn't trade it for anything.The Stitch ProjectI've loved Stitch since I was a kid. I used to watch the cartoons, play the video games, and he always felt like such a warm, funny, chill, and at the same time, strong character. So once I reached a certain level in 3D, I decided to recreate Stitch.Back then, my skills only allowed me to make him in a stylized cartoonish style, no fur, no complex detailing, no advanced texturing, I just didn't have the experience. Surprisingly, the result turned out pretty decent. Even now, I sometimes get comments that my old Stitch still looks quite cute. Though honestly, I wouldn't say that myself anymore. Two years have passed since I made that first Stitch, it was back in 2023. And in 2025, I decided it was time to challenge myself.At that point, I had just completed an intense grooming course. Grooming always intimidated me, it felt really complex. I avoided it on commercial projects, made a few failed attempts for my portfolio, and overall tried to steer clear of any tasks where grooming was required. But eventually, I found the strength to face it.I pushed myself to learn how to make great fur, and I did. I finally understood how the grooming system works, grasped the logic, the tools, and the workflow. And after finishing the course, I wanted to lock in all that knowledge by creating a full personal project from scratch.So my goal was to make a character from the ground up, where the final stage would be grooming. And without thinking too long, I chose Stitch.First, because I truly love the character. Second, I wanted to clearly see my own progress over the past two years. Third, I needed to put my new skills to the test and find out whether my training had really paid off.ModelingI had a few ideas for how to approach the base mesh for this project. First, to model everything completely from scratch, starting with a sphere. Second, to reuse my old Stitch model and upgrade it.But then an idea struck me: why not test how well AI could handle a base mesh? I gathered some references and tried generating a base mesh using AI, uploading Stitch visuals as a guide. As you can see from the screenshot, the result was far from usable. So I basically ended up doing everything from scratch anyway.So, I went back to basics: digging through ArtStation and Pinterest, collecting references. Since over the last two years, I had not only learned grooming but also completely changed my overall approach to character creation, it was important for me to make a more detailed model, even if much of it would be hidden under fur.The first Stitch was sculpted in Blender, with all the limitations that come with sculpting in it. But since then, I've leveled up significantly and switched to more advanced tools. So this second version of Stitch was born in ZBrush. By the time I started working on this Stitch, ZBrush had already become my second main workspace. I've used it to deliver tons of commercial projects, I work in it almost daily, and most of my portfolio was created using this tool. I found some great reference images showing Stitch's body structure. Among them were official movie references and a stunning high-poly model created by Juan Hernández, a version of Stitch without fur. That model became my primary reference for sculpting.Truth is, Stitch's base form is quite simple, so blocking out the shape didn't take too long. When blocking, I use Blender in combination with ZBrush:I work with primary forms in ZBrushThen check proportions in BlenderFix mistakes, tweak volumes, and refine the silhouetteSince Stitch's shape isn't overly complex, I broke him down into three main sculpting parts:The body: arms, legs, head, and earsThe nose, eyes, and mouth cavityWhile planning the sculpt, I already knew I'd be rigging Stitch, both body and facial rig. So I started sculpting with his mouth open (to later close it and have more flexibility when it comes to rigging and deformation).While studying various references, I noticed something interesting. Stitch from promotional posters, Stitch from the movie, and Stitch as recreated by different artists on ArtStation all look very different from one another. What surprised me the most was how different the promo version of Stitch is compared to the one in the actual movie. They are essentially two separate models:Different proportionsDifferent shapesDifferent texturesEven different fur and overall designThis presented a creative challenge, I had to develop my own take on Stitch's design. Sometimes I liked the way the teeth were done in one version, in another, the eye placement, in another, the fur shape, or the claw design on hands and feet.At first, considering that Stitch is completely covered in fur from head to toe, sculpting his underlying anatomy seemed pointless. I kept asking myself: "Why sculpt muscles and skin detail if everything will be hidden under fur anyway?"But eventually, I found a few solid answers for myself. First, having a defined muscle structure actually makes the fur grooming process easier. That's because fur often follows the flow of muscle lines, so having those muscles helps guide fur direction more accurately across the character's body.Second, it's great anatomy practice, and practice is never a waste. So, I found a solid anatomical reference of Stitch with clearly visible muscle groups and tried to recreate that structure as closely as possible in my own sculpt.In the end, I had to develop a full visual concept by combining elements from multiple versions of Stitch. Through careful reference work and constantly switching between Blender and ZBrush, I gradually, but intentionally, built up the body and overall look of our favorite fluffy alien.Topology & UVsThroughout the sculpting process, I spent quite a bit of time thinking about topology. I was looking for the most balanced solution between quality and production time. Normally, I do manual retopology for my characters, but this time, I knew it would take too much time, and honestly, I didn't have that luxury.So I decided to generate the topology using ZBrush's tools. I split the model into separate parts using Polygroups, assigning individual groups for the ears, the head, the torso, the arms, the legs, and each of Stitch's fingers.With the Polygroups in place, I used ZRemesher with Keep Groups enabled and smoothing on group borders. This gave me a clean and optimized mesh that was perfect for UV unwrapping.Of course, this kind of auto-retopology isn't a full substitute for manual work, but it saved me a huge amount of time, and the quality was still high enough for what I needed. However, there was one tricky issue. Although Stitch looks symmetrical at first glance, his ears are actually asymmetrical. The right ear has a scar on the top, while the left has a scar on the bottomBecause of that, I couldn't just mirror one side in ZBrush without losing those unique features. Here's what I ended up doing: I created a symmetrical model with the right ear, then another symmetrical model with the left ear. I brought both into Blender, detached the left ear from one model, and attached it to the body of the other one. This way, I got a clean, symmetrical base mesh with asymmetrical ears, preserving both topology and detail. And thanks to the clean polygroup-based layout, I was able to unwrap the UVs with nice, even seams and clean islands.When it came to UV mapping, I divided Stitch into two UDIM tiles:The first UDIM includes the head with ears, torso, arms, and legs.The second UDIM contains all the additional parts: teeth, tongue, gums, claws, and nose (For the claws, I used overlapping UVs to preserve texel density for the other parts)Since the nose is one of the most important details, I allocated the largest space to it, which helped me to better capture its intricate details.As for the eyes, I used procedural eyes, so there was no need to assign UV space or create a separate UDIM for texturing them. To achieve this, I used the Tiny Eye add-on by tinynocky for Blender, which allows full control over procedural eyes and their parameters.This approach gave me high-quality eyes with customizable elements tailored exactly to my needs. As a result of all these steps, Stitch ended up with a symmetrical, optimized mesh, asymmetrical ears, and the body split across two UDIMs, one for the main body and one for the additional parts.TexturingWhen planning Stitch's texturing, I understood that the main body texture would be fairly simple, with much of the visual detail enhanced by the fur. However, there were some areas that required much more attention than the rest of the body. The textures for Stitch can be roughly divided into several main parts:The base body, which includes the primary color of his fur, along with additional shading like a lighter tone on the front (belly) and a darker tone on the back and napeThe nose and ears, these zones, demanded separate focusAt the initial texturing/blocking stage, the ears looked too cartoony, which didn’t fit the style I wanted. So, I decided to push them towards a more realistic look. This involved removing bright colors, adding more variation in the roughness map, introducing variation in the base color, and making the ears visually more natural, layered, and textured on the surface. By combining smart materials and masks, I achieved the effect of "living" ears, slightly dirty and looking as natural as possible.The nose was a separate story. It occupies a significant part of the face and thus draws a lot of attention. While studying references, I noticed that the shape and texture of the nose vary a lot between different artists. Initially, I made it dog-like, with some wear and tear around the nostrils and base.For a long time, I thought this version was acceptable. But during test renders, I realized the nose needed improvement. So I reworked its texturing, aiming to make it more detailed. I divided the nose texture into four main layers:Base detail: Baked from the high-poly model. Over this, I applied a smart skin material that added characteristic bumps.Lighter layer: Applied via a mask using the AO channel. This darkened the crevices and brightened the bumps, creating a multi-layered effect.Organic detail (capillaries): In animal references, I noticed slight redness in the nose area. I created another AO-masked layer with reddish capillaries visible through the bumps, adding depth and realism.Softness: To make the nose visually softer, like in references, I added a fill layer with only height enabled, used a paper texture as grayscale, and applied a blurred mask. This created subtle dents and wrinkles that softened the look.All textures were created in 4K resolution to achieve maximum detail. After finishing the main texturing stage, I add an Ambient Occlusion map on the final texture layer, activating only the Color channel, setting the blend mode to Multiply, and reducing opacity to about 35%. This adds volume and greatly improves the overall perception of the model.That covers the texturing of Stitch’s body. I also created a separate texture for the fur. This was simpler, I disabled unnecessary layers like ears and eyelids, and left only the base ones corresponding to the body’s color tones.During grooming (which I'll cover in detail later), I also created textures for the fur's clamps and roughness. In Substance 3D Painter, I additionally painted masks for better fur detail.FurAnd finally, I moved on to the part that was most important to me, the very reason I started this project in the first place. Fur. This entire process was essentially a test of my fur grooming skills. After overcoming self-doubt, I trusted the process and relied on everything I had learned so far. Before diving into the grooming itself, I made sure to gather strong references. I searched for the highest quality and most inspiring examples I could find and analyzed them thoroughly. My goal was to clearly understand the direction of fur growth, its density and volume, the intensity of roughness, and the strength of clumping in different areas of Stitch's body.To create the fur, I used Blender and its Hair Particle System. The overall approach is similar to sculpting a high-detail model: work from broad strokes to finer details. So, the first step was blocking out the main flow and placement of the hair strands.At this point, I ran into a challenge: symmetry. Since the model was purposefully asymmetrical (because of the ears and skin folds), the fur couldn't be mirrored cleanly. To solve this, I created a base fur blocking using Hair Guides with just two segments. After that, I split the fur into separate parts. I duplicated the main Particle System and created individual hair systems for each area where needed.In total, I broke Stitch's body into key sections: head, left ear, right ear, front torso, back torso, arms, hands, upper and lower legs, toes, and additional detailing layers. The final fur setup included 25 separate particle systems.To control fur growth, I used Weight Paint to fine-tune the influence on each body part individually. This separation gave me much more precision and allowed full control over every parameter of the fur on a per-section basis.The most challenging aspect of working with fur is staying patient and focused. Detail is absolutely critical because the overall picture is built entirely from tiny, subtle elements. Once the base layer was complete, I moved on to refining the fur based on my references.The most complex areas turned out to be the front of the torso and the face. When working on the torso, my goal was to create a smooth gradient, from thick, clumped fur on the chest to shorter, softer fur on the stomach.Step by step, I adjusted the transitions, directions, clumps, and volumes to achieve that look. Additionally, I used the fur itself to subtly enhance Stitch's silhouette, making his overall shape feel sharper, more expressive, and visually engaging.During fur development, I used texture maps to control the intensity of the Roughness and Clump parameters. This gave me a high degree of flexibility, textures drove these attributes across the entire model. In areas where stronger clumping or roughness was needed, I used brighter values; in zones requiring a softer look, darker values. This approach allowed for fine-tuned micro-level control of the fur shader and helped achieve a highly realistic appearance in renders.The face required special attention: the fur had to be neat, evenly distributed, and still visually appealing. The biggest challenge here was working around the eye area. Even with properly adjusted Weight Paint, interpolation sometimes caused strands to creep into the eyes.I spent a lot of time cleaning up this region to get an optimal result. I also had to revisit certain patches that looked bald, even though interpolation and weight painting were set correctly, because the fur didn't render properly there. These areas needed manual fixing.As part of the detailing stage, I also increased the number of segments in the Hair Guides.While the blocking phase only used two segments, I went up to three, and in some cases even five, for more complex regions. This gave me much more control over fur shape and flow.The tiniest details really matter, so I added extra fur layers with thinner, more chaotic strands extending slightly beyond the main silhouette. These micro-layers significantly improved the texture depth and boosted the overall realism.Aside from the grooming itself, I paid special attention to the fur material setup, as the shader plays a critical role in the final visual quality of the render. It's not enough to simply plug a color texture into a Principled BSDF node and call it done.I built a more complex shader, giving me precise control over various attributes. For example, I implemented subtle color variation across individual strands, along with darkening near the roots and a gradual brightening toward the tips. This helped add visual depth and made the fur look significantly more natural and lifelike.Working on the fur took up nearly half of the total time I spent on the entire model. And I'm genuinely happy with the result, this stage confirmed that the training I've gone through was solid and that I’m heading in the right direction with my artistic development.Rigging, Posing & SceneOnce I finished working on the fur, I rendered several 4K test shots from different angles to make sure every detail looked the way I intended. When I was fully satisfied with the results, it was time to move on to rigging.I divided the rigging process into three main parts:Body rig, for posing and positioning the characterFacial rig, for expressions and emotionsEar rig, for dynamic ear controlRigging isn't something I consider my strongest skill, but as a 3D generalist, I had to dive into many technical aspects of it. For the ears, I set up a relatively simple system with several bones connected using inverse kinematics (IK). This gave me flexible and intuitive control during posing and allowed for the addition of dynamic movement in animation.For facial rigging, I used the FaceIt add-on, which generates a complete facial control system for mouth, eyes, and tongue. It sped up the process significantly and gave me more precision. For the body, I used the ActorCore Rig by NVIDIA, then converted it to Rigify, which gave me a familiar interface and flexible control over poses.Posing is one of my favorite stages, it's when the character really comes to life. As usual, it started with gathering references. Honestly, it was hard to pick the final poses, Stitch is so expressive and full of personality that I wanted to try hundreds of them. But I focused on those that best conveyed the spirit and mood of the character. Some poses I reworked to fit my style rather than copying directly. For example, in the pose where Stitch licks his nose, I added drool and a bit of "green slime" for comedic effect. To capture motion, I tilted his head back and made the ears fly upward, creating a vivid, emotional snapshot.Just like in sculpting or grooming, minor details make a big difference in posing. Examples include: a slight asymmetry in the facial expression, a raised corner of the mouth, one eye squinting a little more than the other, and ears set at slightly different angles.These are subtle things that might not be noticed immediately, but they’re the key to making the character feel alive and believable.For each pose, I created a separate scene and collection in Blender, including the character, specific lighting setup, and a simple background or environment. This made it easy to return to any scene later, to adjust lighting, reposition the character, or tweak the background.In one of the renders, which I used as the cover image, Stitch is holding a little frog.I want to clearly note that the 3D model of the frog is not mine, full credit goes to the original author of the asset.At first, I wanted to build a full environment around Stitch, to create a scene that would feel like a frame from a film. But after carefully evaluating my skills and priorities, I decided that a weak environment would only detract from the strength of the character. So I opted for a simple, neutral backdrop, designed to keep all the focus on Stitch himself.Rendering, Lighting & Post-ProcessingWhen the character is complete, posed expressively, and integrated into the scene, there's one final step: lighting. Lighting isn't just a technical element of the scene — it’s a full-fledged stage of the 3D pipeline. It doesn't just illuminate; it paints. Proper lighting can highlight the personality of the character, emphasize forms, and create atmosphere.For all my renders, I rely on the classic three-point lighting setup: Key Light, Fill Light, and Rim Light.While this setup is well-known, it remains highly effective. When done thoughtfully, with the right intensity, direction, and color temperature, it creates a strong light-shadow composition that brings the model to life. In addition to the three main lights, I also use an HDRI map, but with very low intensity, around 0.3, just enough to subtly enrich the ambient light without overpowering the scene.Once everything is set, it's time to hit Render and wait for the result. Due to hardware limitations, I wasn’t able to produce full animated shots with fur. Rendering a single 4K image with fur took over an hour, so I limited myself to a 360° turnaround and several static renders.I don't spend too much time on post-processing, just basic refinements in Photoshop. Slight enhancement of the composition, gentle shadow adjustments, color balance tweaks, and adding a logo. Everything is done subtly, nothing overprocessed. The goal is simply to support and enhance what’s already there.Final ThoughtsThis project has been an incredible experience. Although it was my second time creating Stitch (the first was back in 2023), this time the process felt completely different at every stage. And honestly, it wasn't easy.But that was exactly the point: to challenge myself. To reimagine something familiar, to try things I'd never done before, and to walk the full journey from start to finish. The fur, the heart of this project, was especially meaningful to me. It’s what started it all. I poured a lot into this model: time, effort, emotion, and even doubts. But at the same time, I brought all my knowledge, skills, and experience into it.This work became a mirror of my progress from 2023 to 2025. I can clearly see how far I've come, and that gives me the motivation to keep going. Every hour of learning and practice paid off, the results speak for themselves. This model was created for my portfolio. I don't plan to use it commercially, unless, of course, a studio actually wants to license it for a new film (in that case, I'd be more than happy!)It's been a long road: challenging, sometimes exhausting, but above all inspiring and exciting. I know there's still a lot to learn. Many things to study, improve, and polish to perfection. But I'm already on that path, and I'm not stopping.Oleh Yakushev, 3D Character ArtistInterview conducted by Gloria Levine
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  • Lost In Space Limited Edition 4K Blu-Ray Preorders Are 50% Off

    Lost in Space Limited Edition| Releases September 2 Preorder Amazon is offering a 50% discount on Arrow Video's upcoming 4K Blu-ray restoration of Lost in Space. Lost in Space Limited Edition is available to preorder for onlyahead of its September 2 release.Directed by Stephen Hopkins, the sci-fi film starring Gary Oldman and William Hurt wasn't warmly received in 1998. To be fair, the original 1960s TV series it was based on wasn't a critical success either. Nevertheless, the film and series were commercial successes, and both are considered cult classics today. Netflix even created a reimagining of the original series back in 2018 that ran for three seasons.If you enjoyed the Netflix series but haven't watched the film, the new 4K Blu-ray edition should be the best way to watch it going forward. For longtime Lost in Space fans, the Limited Edition, like all of Arrow Video's restorations of classic films, looks like a cool collector's item.Continue Reading at GameSpot
    #lost #space #limited #edition #bluray
    Lost In Space Limited Edition 4K Blu-Ray Preorders Are 50% Off
    Lost in Space Limited Edition| Releases September 2 Preorder Amazon is offering a 50% discount on Arrow Video's upcoming 4K Blu-ray restoration of Lost in Space. Lost in Space Limited Edition is available to preorder for onlyahead of its September 2 release.Directed by Stephen Hopkins, the sci-fi film starring Gary Oldman and William Hurt wasn't warmly received in 1998. To be fair, the original 1960s TV series it was based on wasn't a critical success either. Nevertheless, the film and series were commercial successes, and both are considered cult classics today. Netflix even created a reimagining of the original series back in 2018 that ran for three seasons.If you enjoyed the Netflix series but haven't watched the film, the new 4K Blu-ray edition should be the best way to watch it going forward. For longtime Lost in Space fans, the Limited Edition, like all of Arrow Video's restorations of classic films, looks like a cool collector's item.Continue Reading at GameSpot #lost #space #limited #edition #bluray
    Lost In Space Limited Edition 4K Blu-Ray Preorders Are 50% Off
    www.gamespot.com
    Lost in Space Limited Edition (4K Blu-ray) $25 (was $50) | Releases September 2 Preorder at Amazon Amazon is offering a 50% discount on Arrow Video's upcoming 4K Blu-ray restoration of Lost in Space. Lost in Space Limited Edition is available to preorder for only $25 (was $50) ahead of its September 2 release.Directed by Stephen Hopkins, the sci-fi film starring Gary Oldman and William Hurt wasn't warmly received in 1998. To be fair, the original 1960s TV series it was based on wasn't a critical success either. Nevertheless, the film and series were commercial successes, and both are considered cult classics today. Netflix even created a reimagining of the original series back in 2018 that ran for three seasons.If you enjoyed the Netflix series but haven't watched the film, the new 4K Blu-ray edition should be the best way to watch it going forward. For longtime Lost in Space fans, the Limited Edition, like all of Arrow Video's restorations of classic films, looks like a cool collector's item.Continue Reading at GameSpot
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  • يا جماعة، شفتوا التلفاز الجديد تاع سامسونج؟ Micro RGB TV اللي ثمنه 29,999 دولار؟ بصح، راح يخلّيكم تفكروا مرتين قبل ما تشريوا أي حاجة أخرى!

    المقال يتكلم على كيفاش سامسونج دارت ثورة في عالم الشاشات بتقنية Micro RGB، اللي تعطينا ألوان غنية وفروق تفاصيل ما شفتهاش في أي تلفاز آخر. الجمال تاع الألوان كان مذهل لما شفتو في مقرهم في نيوجيرسي، وكان عندي إحساس أنني في عالم آخر!

    بصراحة، هذا التلفاز يخلينا نفكروا في مستقبل السينما والتلفاز، بحيث أن كل واحد يحتاج يشوفو عن قرب باش يقدّر جمالو.

    https://www.engadget.com/home/home-theater/samsungs-new-29999-micro-rgb-tv-looks-ridiculously-good-194629549.html?src=rss
    #تكنولوجيا #تلفاز #Samsung #MicroRGB #الألوان
    يا جماعة، شفتوا التلفاز الجديد تاع سامسونج؟ Micro RGB TV اللي ثمنه 29,999 دولار؟ بصح، راح يخلّيكم تفكروا مرتين قبل ما تشريوا أي حاجة أخرى! المقال يتكلم على كيفاش سامسونج دارت ثورة في عالم الشاشات بتقنية Micro RGB، اللي تعطينا ألوان غنية وفروق تفاصيل ما شفتهاش في أي تلفاز آخر. الجمال تاع الألوان كان مذهل لما شفتو في مقرهم في نيوجيرسي، وكان عندي إحساس أنني في عالم آخر! بصراحة، هذا التلفاز يخلينا نفكروا في مستقبل السينما والتلفاز، بحيث أن كل واحد يحتاج يشوفو عن قرب باش يقدّر جمالو. https://www.engadget.com/home/home-theater/samsungs-new-29999-micro-rgb-tv-looks-ridiculously-good-194629549.html?src=rss #تكنولوجيا #تلفاز #Samsung #MicroRGB #الألوان
    Samsung's new $29,999 Micro RGB TV looks ridiculously good
    www.engadget.com
    Last week, Samsung announced the world's first Micro RGB TV and while it sounded fantastic on paper, you can never really get a good sense of what a fresh display looks like until you see it in person. But after going to Samsung's new headqua
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  • Battlefield 6 Fans Are Divided Over Big Movement Nerf

    Battlefield 6 developer DICE has confirmed it will be nerfing the shooter's movement mechanics to "create a more balanced and traditional Battlefield experience," but the decision seems to have divided the community, with some strongly against the change and others all for it. Fans won't know what these changes feel like in-game until Battlefield 6releases for PlayStation 5, Xbox Series X/S, and PC on October 10, but it looks like the community has already decided which side of the fence it's on.
    #battlefield #fans #are #divided #over
    Battlefield 6 Fans Are Divided Over Big Movement Nerf
    Battlefield 6 developer DICE has confirmed it will be nerfing the shooter's movement mechanics to "create a more balanced and traditional Battlefield experience," but the decision seems to have divided the community, with some strongly against the change and others all for it. Fans won't know what these changes feel like in-game until Battlefield 6releases for PlayStation 5, Xbox Series X/S, and PC on October 10, but it looks like the community has already decided which side of the fence it's on. #battlefield #fans #are #divided #over
    Battlefield 6 Fans Are Divided Over Big Movement Nerf
    gamerant.com
    Battlefield 6 developer DICE has confirmed it will be nerfing the shooter's movement mechanics to "create a more balanced and traditional Battlefield experience," but the decision seems to have divided the community, with some strongly against the change and others all for it. Fans won't know what these changes feel like in-game until Battlefield 6releases for PlayStation 5, Xbox Series X/S, and PC on October 10, but it looks like the community has already decided which side of the fence it's on.
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  • Gearing Up for the Gigawatt Data Center Age

    Across the globe, AI factories are rising — massive new data centers built not to serve up web pages or email, but to train and deploy intelligence itself. Internet giants have invested billions in cloud-scale AI infrastructure for their customers. Companies are racing to build AI foundries that will spawn the next generation of products and services. Governments are investing too, eager to harness AI for personalized medicine and language services tailored to national populations.
    Welcome to the age of AI factories — where the rules are being rewritten and the wiring doesn’t look anything like the old internet. These aren’t typical hyperscale data centers. They’re something else entirely. Think of them as high-performance engines stitched together from tens to hundreds of thousands of GPUs — not just built, but orchestrated, operated and activated as a single unit. And that orchestration? It’s the whole game.
    This giant data center has become the new unit of computing, and the way these GPUs are connected defines what this unit of computing can do. One network architecture won’t cut it. What’s needed is a layered design with bleeding-edge technologies — like co-packaged optics that once seemed like science fiction.
    The complexity isn’t a bug; it’s the defining feature. AI infrastructure is diverging fast from everything that came before it, and if there isn’t rethinking on how the pipes connect, scale breaks down. Get the network layers wrong, and the whole machine grinds to a halt. Get it right, and gain extraordinary performance.
    With that shift comes weight — literally. A decade ago, chips were built to be sleek and lightweight. Now, the cutting edge looks like the multi‑hundred‑pound copper spine of a server rack. Liquid-cooled manifolds. Custom busbars. Copper spines. AI now demands massive, industrial-scale hardware. And the deeper the models go, the more these machines scale up, and out.
    The NVIDIA NVLink spine, for example, is built from over 5,000 coaxial cables — tightly wound and precisely routed. It moves more data per second than the entire internet. That’s 130 TB/s of GPU-to-GPU bandwidth, fully meshed.
    This isn’t just fast. It’s foundational. The AI super-highway now lives inside the rack.
    The Data Center Is the Computer

    Training the modern large language modelsbehind AI isn’t about burning cycles on a single machine. It’s about orchestrating the work of tens or even hundreds of thousands of GPUs that are the heavy lifters of AI computation.
    These systems rely on distributed computing, splitting massive calculations across nodes, where each node handles a slice of the workload. In training, those slices — typically massive matrices of numbers — need to be regularly merged and updated. That merging occurs through collective operations, such as “all-reduce”and “all-to-all”.
    These processes are susceptible to the speed and responsiveness of the network — what engineers call latencyand bandwidth— causing stalls in training.
    For inference — the process of running trained models to generate answers or predictions — the challenges flip. Retrieval-augmented generation systems, which combine LLMs with search, demand real-time lookups and responses. And in cloud environments, multi-tenant inference means keeping workloads from different customers running smoothly, without interference. That requires lightning-fast, high-throughput networking that can handle massive demand with strict isolation between users.
    Traditional Ethernet was designed for single-server workloads — not for the demands of distributed AI. Tolerating jitter and inconsistent delivery were once acceptable. Now, it’s a bottleneck. Traditional Ethernet switch architectures were never designed for consistent, predictable performance — and that legacy still shapes their latest generations.
    Distributed computing requires a scale-out infrastructure built for zero-jitter operation — one that can handle bursts of extreme throughput, deliver low latency, maintain predictable and consistent RDMA performance, and isolate network noise. This is why InfiniBand networking is the gold standard for high-performance computing supercomputers and AI factories.
    With NVIDIA Quantum InfiniBand, collective operations run inside the network itself using Scalable Hierarchical Aggregation and Reduction Protocol technology, doubling data bandwidth for reductions. It uses adaptive routing and telemetry-based congestion control to spread flows across paths, guarantee deterministic bandwidth and isolate noise. These optimizations let InfiniBand scale AI communication with precision. It’s why NVIDIA Quantum infrastructure connects the majority of the systems on the TOP500 list of the world’s most powerful supercomputers, demonstrating 35% growth in just two years.
    For clusters spanning dozens of racks, NVIDIA Quantum‑X800 Infiniband switches push InfiniBand to new heights. Each switch provides 144 ports of 800 Gbps connectivity, featuring hardware-based SHARPv4, adaptive routing and telemetry-based congestion control. The platform integrates co‑packaged silicon photonics to minimize the distance between electronics and optics, reducing power consumption and latency. Paired with NVIDIA ConnectX-8 SuperNICs delivering 800 Gb/s per GPU, this fabric links trillion-parameter models and drives in-network compute.
    But hyperscalers and enterprises have invested billions in their Ethernet software infrastructure. They need a quick path forward that uses the existing ecosystem for AI workloads. Enter NVIDIA Spectrum‑X: a new kind of Ethernet purpose-built for distributed AI.
    Spectrum‑X Ethernet: Bringing AI to the Enterprise

    Spectrum‑X reimagines Ethernet for AI. Launched in 2023 Spectrum‑X delivers lossless networking, adaptive routing and performance isolation. The SN5610 switch, based on the Spectrum‑4 ASIC, supports port speeds up to 800 Gb/s and uses NVIDIA’s congestion control to maintain 95% data throughput at scale.
    Spectrum‑X is fully standards‑based Ethernet. In addition to supporting Cumulus Linux, it supports the open‑source SONiC network operating system — giving customers flexibility. A key ingredient is NVIDIA SuperNICs — based on NVIDIA BlueField-3 or ConnectX-8 — which provide up to 800 Gb/s RoCE connectivity and offload packet reordering and congestion management.
    Spectrum-X brings InfiniBand’s best innovations — like telemetry-driven congestion control, adaptive load balancing and direct data placement — to Ethernet, enabling enterprises to scale to hundreds of thousands of GPUs. Large-scale systems with Spectrum‑X, including the world’s most colossal AI supercomputer, have achieved 95% data throughput with zero application latency degradation. Standard Ethernet fabrics would deliver only ~60% throughput due to flow collisions.
    A Portfolio for Scale‑Up and Scale‑Out
    No single network can serve every layer of an AI factory. NVIDIA’s approach is to match the right fabric to the right tier, then tie everything together with software and silicon.
    NVLink: Scale Up Inside the Rack
    Inside a server rack, GPUs need to talk to each other as if they were different cores on the same chip. NVIDIA NVLink and NVLink Switch extend GPU memory and bandwidth across nodes. In an NVIDIA GB300 NVL72 system, 36 NVIDIA Grace CPUs and 72 NVIDIA Blackwell Ultra GPUs are connected in a single NVLink domain, with an aggregate bandwidth of 130 TB/s. NVLink Switch technology further extends this fabric: a single GB300 NVL72 system can offer 130 TB/s of GPU bandwidth, enabling clusters to support 9x the GPU count of a single 8‑GPU server. With NVLink, the entire rack becomes one large GPU.
    Photonics: The Next Leap

    To reach million‑GPU AI factories, the network must break the power and density limits of pluggable optics. NVIDIA Quantum-X and Spectrum-X Photonics switches integrate silicon photonics directly into the switch package, delivering 128 to 512 ports of 800 Gb/s with total bandwidths ranging from 100 Tb/s to 400 Tb/s. These switches offer 3.5x more power efficiency and 10x better resiliency compared with traditional optics, paving the way for gigawatt‑scale AI factories.

    Delivering on the Promise of Open Standards

    Spectrum‑X and NVIDIA Quantum InfiniBand are built on open standards. Spectrum‑X is fully standards‑based Ethernet with support for open Ethernet stacks like SONiC, while NVIDIA Quantum InfiniBand and Spectrum-X conform to the InfiniBand Trade Association’s InfiniBand and RDMA over Converged Ethernetspecifications. Key elements of NVIDIA’s software stack — including NCCL and DOCA libraries — run on a variety of hardware, and partners such as Cisco, Dell Technologies, HPE and Supermicro integrate Spectrum-X into their systems.

    Open standards create the foundation for interoperability, but real-world AI clusters require tight optimization across the entire stack — GPUs, NICs, switches, cables and software. Vendors that invest in end‑to‑end integration deliver better latency and throughput. SONiC, the open‑source network operating system hardened in hyperscale data centers, eliminates licensing and vendor lock‑in and allows intense customization, but operators still choose purpose‑built hardware and software bundles to meet AI’s performance needs. In practice, open standards alone don’t deliver deterministic performance; they need innovation layered on top.

    Toward Million‑GPU AI Factories
    AI factories are scaling fast. Governments in Europe are building seven national AI factories, while cloud providers and enterprises across Japan, India and Norway are rolling out NVIDIA‑powered AI infrastructure. The next horizon is gigawatt‑class facilities with a million GPUs. To get there, the network must evolve from an afterthought to a pillar of AI infrastructure.
    The lesson from the gigawatt data center age is simple: the data center is now the computer. NVLink stitches together GPUs inside the rack. NVIDIA Quantum InfiniBand scales them across it. Spectrum-X brings that performance to broader markets. Silicon photonics makes it sustainable. Everything is open where it matters, optimized where it counts.
     
     

     
    #gearing #gigawatt #data #center #age
    Gearing Up for the Gigawatt Data Center Age
    Across the globe, AI factories are rising — massive new data centers built not to serve up web pages or email, but to train and deploy intelligence itself. Internet giants have invested billions in cloud-scale AI infrastructure for their customers. Companies are racing to build AI foundries that will spawn the next generation of products and services. Governments are investing too, eager to harness AI for personalized medicine and language services tailored to national populations. Welcome to the age of AI factories — where the rules are being rewritten and the wiring doesn’t look anything like the old internet. These aren’t typical hyperscale data centers. They’re something else entirely. Think of them as high-performance engines stitched together from tens to hundreds of thousands of GPUs — not just built, but orchestrated, operated and activated as a single unit. And that orchestration? It’s the whole game. This giant data center has become the new unit of computing, and the way these GPUs are connected defines what this unit of computing can do. One network architecture won’t cut it. What’s needed is a layered design with bleeding-edge technologies — like co-packaged optics that once seemed like science fiction. The complexity isn’t a bug; it’s the defining feature. AI infrastructure is diverging fast from everything that came before it, and if there isn’t rethinking on how the pipes connect, scale breaks down. Get the network layers wrong, and the whole machine grinds to a halt. Get it right, and gain extraordinary performance. With that shift comes weight — literally. A decade ago, chips were built to be sleek and lightweight. Now, the cutting edge looks like the multi‑hundred‑pound copper spine of a server rack. Liquid-cooled manifolds. Custom busbars. Copper spines. AI now demands massive, industrial-scale hardware. And the deeper the models go, the more these machines scale up, and out. The NVIDIA NVLink spine, for example, is built from over 5,000 coaxial cables — tightly wound and precisely routed. It moves more data per second than the entire internet. That’s 130 TB/s of GPU-to-GPU bandwidth, fully meshed. This isn’t just fast. It’s foundational. The AI super-highway now lives inside the rack. The Data Center Is the Computer Training the modern large language modelsbehind AI isn’t about burning cycles on a single machine. It’s about orchestrating the work of tens or even hundreds of thousands of GPUs that are the heavy lifters of AI computation. These systems rely on distributed computing, splitting massive calculations across nodes, where each node handles a slice of the workload. In training, those slices — typically massive matrices of numbers — need to be regularly merged and updated. That merging occurs through collective operations, such as “all-reduce”and “all-to-all”. These processes are susceptible to the speed and responsiveness of the network — what engineers call latencyand bandwidth— causing stalls in training. For inference — the process of running trained models to generate answers or predictions — the challenges flip. Retrieval-augmented generation systems, which combine LLMs with search, demand real-time lookups and responses. And in cloud environments, multi-tenant inference means keeping workloads from different customers running smoothly, without interference. That requires lightning-fast, high-throughput networking that can handle massive demand with strict isolation between users. Traditional Ethernet was designed for single-server workloads — not for the demands of distributed AI. Tolerating jitter and inconsistent delivery were once acceptable. Now, it’s a bottleneck. Traditional Ethernet switch architectures were never designed for consistent, predictable performance — and that legacy still shapes their latest generations. Distributed computing requires a scale-out infrastructure built for zero-jitter operation — one that can handle bursts of extreme throughput, deliver low latency, maintain predictable and consistent RDMA performance, and isolate network noise. This is why InfiniBand networking is the gold standard for high-performance computing supercomputers and AI factories. With NVIDIA Quantum InfiniBand, collective operations run inside the network itself using Scalable Hierarchical Aggregation and Reduction Protocol technology, doubling data bandwidth for reductions. It uses adaptive routing and telemetry-based congestion control to spread flows across paths, guarantee deterministic bandwidth and isolate noise. These optimizations let InfiniBand scale AI communication with precision. It’s why NVIDIA Quantum infrastructure connects the majority of the systems on the TOP500 list of the world’s most powerful supercomputers, demonstrating 35% growth in just two years. For clusters spanning dozens of racks, NVIDIA Quantum‑X800 Infiniband switches push InfiniBand to new heights. Each switch provides 144 ports of 800 Gbps connectivity, featuring hardware-based SHARPv4, adaptive routing and telemetry-based congestion control. The platform integrates co‑packaged silicon photonics to minimize the distance between electronics and optics, reducing power consumption and latency. Paired with NVIDIA ConnectX-8 SuperNICs delivering 800 Gb/s per GPU, this fabric links trillion-parameter models and drives in-network compute. But hyperscalers and enterprises have invested billions in their Ethernet software infrastructure. They need a quick path forward that uses the existing ecosystem for AI workloads. Enter NVIDIA Spectrum‑X: a new kind of Ethernet purpose-built for distributed AI. Spectrum‑X Ethernet: Bringing AI to the Enterprise Spectrum‑X reimagines Ethernet for AI. Launched in 2023 Spectrum‑X delivers lossless networking, adaptive routing and performance isolation. The SN5610 switch, based on the Spectrum‑4 ASIC, supports port speeds up to 800 Gb/s and uses NVIDIA’s congestion control to maintain 95% data throughput at scale. Spectrum‑X is fully standards‑based Ethernet. In addition to supporting Cumulus Linux, it supports the open‑source SONiC network operating system — giving customers flexibility. A key ingredient is NVIDIA SuperNICs — based on NVIDIA BlueField-3 or ConnectX-8 — which provide up to 800 Gb/s RoCE connectivity and offload packet reordering and congestion management. Spectrum-X brings InfiniBand’s best innovations — like telemetry-driven congestion control, adaptive load balancing and direct data placement — to Ethernet, enabling enterprises to scale to hundreds of thousands of GPUs. Large-scale systems with Spectrum‑X, including the world’s most colossal AI supercomputer, have achieved 95% data throughput with zero application latency degradation. Standard Ethernet fabrics would deliver only ~60% throughput due to flow collisions. A Portfolio for Scale‑Up and Scale‑Out No single network can serve every layer of an AI factory. NVIDIA’s approach is to match the right fabric to the right tier, then tie everything together with software and silicon. NVLink: Scale Up Inside the Rack Inside a server rack, GPUs need to talk to each other as if they were different cores on the same chip. NVIDIA NVLink and NVLink Switch extend GPU memory and bandwidth across nodes. In an NVIDIA GB300 NVL72 system, 36 NVIDIA Grace CPUs and 72 NVIDIA Blackwell Ultra GPUs are connected in a single NVLink domain, with an aggregate bandwidth of 130 TB/s. NVLink Switch technology further extends this fabric: a single GB300 NVL72 system can offer 130 TB/s of GPU bandwidth, enabling clusters to support 9x the GPU count of a single 8‑GPU server. With NVLink, the entire rack becomes one large GPU. Photonics: The Next Leap To reach million‑GPU AI factories, the network must break the power and density limits of pluggable optics. NVIDIA Quantum-X and Spectrum-X Photonics switches integrate silicon photonics directly into the switch package, delivering 128 to 512 ports of 800 Gb/s with total bandwidths ranging from 100 Tb/s to 400 Tb/s. These switches offer 3.5x more power efficiency and 10x better resiliency compared with traditional optics, paving the way for gigawatt‑scale AI factories. Delivering on the Promise of Open Standards Spectrum‑X and NVIDIA Quantum InfiniBand are built on open standards. Spectrum‑X is fully standards‑based Ethernet with support for open Ethernet stacks like SONiC, while NVIDIA Quantum InfiniBand and Spectrum-X conform to the InfiniBand Trade Association’s InfiniBand and RDMA over Converged Ethernetspecifications. Key elements of NVIDIA’s software stack — including NCCL and DOCA libraries — run on a variety of hardware, and partners such as Cisco, Dell Technologies, HPE and Supermicro integrate Spectrum-X into their systems. Open standards create the foundation for interoperability, but real-world AI clusters require tight optimization across the entire stack — GPUs, NICs, switches, cables and software. Vendors that invest in end‑to‑end integration deliver better latency and throughput. SONiC, the open‑source network operating system hardened in hyperscale data centers, eliminates licensing and vendor lock‑in and allows intense customization, but operators still choose purpose‑built hardware and software bundles to meet AI’s performance needs. In practice, open standards alone don’t deliver deterministic performance; they need innovation layered on top. Toward Million‑GPU AI Factories AI factories are scaling fast. Governments in Europe are building seven national AI factories, while cloud providers and enterprises across Japan, India and Norway are rolling out NVIDIA‑powered AI infrastructure. The next horizon is gigawatt‑class facilities with a million GPUs. To get there, the network must evolve from an afterthought to a pillar of AI infrastructure. The lesson from the gigawatt data center age is simple: the data center is now the computer. NVLink stitches together GPUs inside the rack. NVIDIA Quantum InfiniBand scales them across it. Spectrum-X brings that performance to broader markets. Silicon photonics makes it sustainable. Everything is open where it matters, optimized where it counts.       #gearing #gigawatt #data #center #age
    Gearing Up for the Gigawatt Data Center Age
    blogs.nvidia.com
    Across the globe, AI factories are rising — massive new data centers built not to serve up web pages or email, but to train and deploy intelligence itself. Internet giants have invested billions in cloud-scale AI infrastructure for their customers. Companies are racing to build AI foundries that will spawn the next generation of products and services. Governments are investing too, eager to harness AI for personalized medicine and language services tailored to national populations. Welcome to the age of AI factories — where the rules are being rewritten and the wiring doesn’t look anything like the old internet. These aren’t typical hyperscale data centers. They’re something else entirely. Think of them as high-performance engines stitched together from tens to hundreds of thousands of GPUs — not just built, but orchestrated, operated and activated as a single unit. And that orchestration? It’s the whole game. This giant data center has become the new unit of computing, and the way these GPUs are connected defines what this unit of computing can do. One network architecture won’t cut it. What’s needed is a layered design with bleeding-edge technologies — like co-packaged optics that once seemed like science fiction. The complexity isn’t a bug; it’s the defining feature. AI infrastructure is diverging fast from everything that came before it, and if there isn’t rethinking on how the pipes connect, scale breaks down. Get the network layers wrong, and the whole machine grinds to a halt. Get it right, and gain extraordinary performance. With that shift comes weight — literally. A decade ago, chips were built to be sleek and lightweight. Now, the cutting edge looks like the multi‑hundred‑pound copper spine of a server rack. Liquid-cooled manifolds. Custom busbars. Copper spines. AI now demands massive, industrial-scale hardware. And the deeper the models go, the more these machines scale up, and out. The NVIDIA NVLink spine, for example, is built from over 5,000 coaxial cables — tightly wound and precisely routed. It moves more data per second than the entire internet. That’s 130 TB/s of GPU-to-GPU bandwidth, fully meshed. This isn’t just fast. It’s foundational. The AI super-highway now lives inside the rack. The Data Center Is the Computer Training the modern large language models (LLMs) behind AI isn’t about burning cycles on a single machine. It’s about orchestrating the work of tens or even hundreds of thousands of GPUs that are the heavy lifters of AI computation. These systems rely on distributed computing, splitting massive calculations across nodes (individual servers), where each node handles a slice of the workload. In training, those slices — typically massive matrices of numbers — need to be regularly merged and updated. That merging occurs through collective operations, such as “all-reduce” (which combines data from all nodes and redistributes the result) and “all-to-all” (where each node exchanges data with every other node). These processes are susceptible to the speed and responsiveness of the network — what engineers call latency (delay) and bandwidth (data capacity) — causing stalls in training. For inference — the process of running trained models to generate answers or predictions — the challenges flip. Retrieval-augmented generation systems, which combine LLMs with search, demand real-time lookups and responses. And in cloud environments, multi-tenant inference means keeping workloads from different customers running smoothly, without interference. That requires lightning-fast, high-throughput networking that can handle massive demand with strict isolation between users. Traditional Ethernet was designed for single-server workloads — not for the demands of distributed AI. Tolerating jitter and inconsistent delivery were once acceptable. Now, it’s a bottleneck. Traditional Ethernet switch architectures were never designed for consistent, predictable performance — and that legacy still shapes their latest generations. Distributed computing requires a scale-out infrastructure built for zero-jitter operation — one that can handle bursts of extreme throughput, deliver low latency, maintain predictable and consistent RDMA performance, and isolate network noise. This is why InfiniBand networking is the gold standard for high-performance computing supercomputers and AI factories. With NVIDIA Quantum InfiniBand, collective operations run inside the network itself using Scalable Hierarchical Aggregation and Reduction Protocol technology, doubling data bandwidth for reductions. It uses adaptive routing and telemetry-based congestion control to spread flows across paths, guarantee deterministic bandwidth and isolate noise. These optimizations let InfiniBand scale AI communication with precision. It’s why NVIDIA Quantum infrastructure connects the majority of the systems on the TOP500 list of the world’s most powerful supercomputers, demonstrating 35% growth in just two years. For clusters spanning dozens of racks, NVIDIA Quantum‑X800 Infiniband switches push InfiniBand to new heights. Each switch provides 144 ports of 800 Gbps connectivity, featuring hardware-based SHARPv4, adaptive routing and telemetry-based congestion control. The platform integrates co‑packaged silicon photonics to minimize the distance between electronics and optics, reducing power consumption and latency. Paired with NVIDIA ConnectX-8 SuperNICs delivering 800 Gb/s per GPU, this fabric links trillion-parameter models and drives in-network compute. But hyperscalers and enterprises have invested billions in their Ethernet software infrastructure. They need a quick path forward that uses the existing ecosystem for AI workloads. Enter NVIDIA Spectrum‑X: a new kind of Ethernet purpose-built for distributed AI. Spectrum‑X Ethernet: Bringing AI to the Enterprise Spectrum‑X reimagines Ethernet for AI. Launched in 2023 Spectrum‑X delivers lossless networking, adaptive routing and performance isolation. The SN5610 switch, based on the Spectrum‑4 ASIC, supports port speeds up to 800 Gb/s and uses NVIDIA’s congestion control to maintain 95% data throughput at scale. Spectrum‑X is fully standards‑based Ethernet. In addition to supporting Cumulus Linux, it supports the open‑source SONiC network operating system — giving customers flexibility. A key ingredient is NVIDIA SuperNICs — based on NVIDIA BlueField-3 or ConnectX-8 — which provide up to 800 Gb/s RoCE connectivity and offload packet reordering and congestion management. Spectrum-X brings InfiniBand’s best innovations — like telemetry-driven congestion control, adaptive load balancing and direct data placement — to Ethernet, enabling enterprises to scale to hundreds of thousands of GPUs. Large-scale systems with Spectrum‑X, including the world’s most colossal AI supercomputer, have achieved 95% data throughput with zero application latency degradation. Standard Ethernet fabrics would deliver only ~60% throughput due to flow collisions. A Portfolio for Scale‑Up and Scale‑Out No single network can serve every layer of an AI factory. NVIDIA’s approach is to match the right fabric to the right tier, then tie everything together with software and silicon. NVLink: Scale Up Inside the Rack Inside a server rack, GPUs need to talk to each other as if they were different cores on the same chip. NVIDIA NVLink and NVLink Switch extend GPU memory and bandwidth across nodes. In an NVIDIA GB300 NVL72 system, 36 NVIDIA Grace CPUs and 72 NVIDIA Blackwell Ultra GPUs are connected in a single NVLink domain, with an aggregate bandwidth of 130 TB/s. NVLink Switch technology further extends this fabric: a single GB300 NVL72 system can offer 130 TB/s of GPU bandwidth, enabling clusters to support 9x the GPU count of a single 8‑GPU server. With NVLink, the entire rack becomes one large GPU. Photonics: The Next Leap To reach million‑GPU AI factories, the network must break the power and density limits of pluggable optics. NVIDIA Quantum-X and Spectrum-X Photonics switches integrate silicon photonics directly into the switch package, delivering 128 to 512 ports of 800 Gb/s with total bandwidths ranging from 100 Tb/s to 400 Tb/s. These switches offer 3.5x more power efficiency and 10x better resiliency compared with traditional optics, paving the way for gigawatt‑scale AI factories. Delivering on the Promise of Open Standards Spectrum‑X and NVIDIA Quantum InfiniBand are built on open standards. Spectrum‑X is fully standards‑based Ethernet with support for open Ethernet stacks like SONiC, while NVIDIA Quantum InfiniBand and Spectrum-X conform to the InfiniBand Trade Association’s InfiniBand and RDMA over Converged Ethernet (RoCE) specifications. Key elements of NVIDIA’s software stack — including NCCL and DOCA libraries — run on a variety of hardware, and partners such as Cisco, Dell Technologies, HPE and Supermicro integrate Spectrum-X into their systems. Open standards create the foundation for interoperability, but real-world AI clusters require tight optimization across the entire stack — GPUs, NICs, switches, cables and software. Vendors that invest in end‑to‑end integration deliver better latency and throughput. SONiC, the open‑source network operating system hardened in hyperscale data centers, eliminates licensing and vendor lock‑in and allows intense customization, but operators still choose purpose‑built hardware and software bundles to meet AI’s performance needs. In practice, open standards alone don’t deliver deterministic performance; they need innovation layered on top. Toward Million‑GPU AI Factories AI factories are scaling fast. Governments in Europe are building seven national AI factories, while cloud providers and enterprises across Japan, India and Norway are rolling out NVIDIA‑powered AI infrastructure. The next horizon is gigawatt‑class facilities with a million GPUs. To get there, the network must evolve from an afterthought to a pillar of AI infrastructure. The lesson from the gigawatt data center age is simple: the data center is now the computer. NVLink stitches together GPUs inside the rack. NVIDIA Quantum InfiniBand scales them across it. Spectrum-X brings that performance to broader markets. Silicon photonics makes it sustainable. Everything is open where it matters, optimized where it counts.      
    2 Commentaires ·0 Parts
  • يا جماعة، شفتوا كيفاش الذكاء الاصطناعي يغير في مشهد الهندسة المعمارية؟ لكن كي تقرب من الواقع، هل كلشي ساهل كما يبان على الإنترنت؟

    المقال يتحدث على كيفاش AI يُسهّل تصميم البنايات ويخليها باهية، لكن في الخفاء، واش الأمور ماشية بنفس الوتيرة القديمة؟ حبيت نشارك معاكم هاد الموضوع لأنني بصراحة مهتم بالهندسة المعمارية وأحب نعرف واش الجديد.

    بصراحة، كي نشوف المشاريع الجديدة وكي تتصمم بذكاء اصطناعي، يحسني بحماس كبير، لكن في نفس الوقت، نحب نفهم هل فعلاً كاين تغيير جوهري ولا غير مظهر خارجي؟

    عموماً، الموضوع مثير ويستحق التفكير فيه بعمق.

    https://architizer.com/blog/inspiration/stories/is-ai-revolutionizing-architecture-or-is-that-just-how-it-looks-online/

    #هندسة_معمارية #ذكاء_اصطناعي #Architecture #AI #Inspiration
    يا جماعة، شفتوا كيفاش الذكاء الاصطناعي يغير في مشهد الهندسة المعمارية؟ 🤖🏛️ لكن كي تقرب من الواقع، هل كلشي ساهل كما يبان على الإنترنت؟ المقال يتحدث على كيفاش AI يُسهّل تصميم البنايات ويخليها باهية، لكن في الخفاء، واش الأمور ماشية بنفس الوتيرة القديمة؟ حبيت نشارك معاكم هاد الموضوع لأنني بصراحة مهتم بالهندسة المعمارية وأحب نعرف واش الجديد. بصراحة، كي نشوف المشاريع الجديدة وكي تتصمم بذكاء اصطناعي، يحسني بحماس كبير، لكن في نفس الوقت، نحب نفهم هل فعلاً كاين تغيير جوهري ولا غير مظهر خارجي؟ عموماً، الموضوع مثير ويستحق التفكير فيه بعمق. https://architizer.com/blog/inspiration/stories/is-ai-revolutionizing-architecture-or-is-that-just-how-it-looks-online/ #هندسة_معمارية #ذكاء_اصطناعي #Architecture #AI #Inspiration
    architizer.com
    Architecture might look smoother with AI, but behind the scenes, is it still business as usual? The post Is AI Revolutionizing Architecture — or Is That Just How It Looks Online? appeared first on Journal.
    1 Commentaires ·0 Parts
  • يا جماعة، هل وصلتو خبر "Kirby Air Riders"؟

    الملخص يقول إنو الوضعية "City Trial" اللي كانت في اللعبة الأصلية للـ GameCube راجعة بقوة على الـ Switch 2، وبصراحة، شكلها راح تكون مجنونة كما توقعنا! ماساھيرو ساكurai عطانا تفاصيل مشوقة والمحتوى واضح أنه راح يكون مليء بالإثارة والتشويق.

    أنا شخصياً، كنت نلعب فيها مع الأصحاب ونقضي ساعات نتنافس. هاذي الألعاب تخلينا نرجع لأيام الطفولة، ومن جهة أخرى، شوية تحدي مع الرفاق. كيفاش تفكروا في هذي العودة؟

    ما تفوتوش الفرصة، الكل شغف ومتعة في انتظارنا مع Kirby!

    https://www.nintendolife.com/news/2025/08/kirby-air-riders-city-trial-mode-looks-just-as-bonkers-as-wed-hoped
    #KirbyAirRide #GamingCommunity #Nostalgia #CityTrial #Switch2
    يا جماعة، هل وصلتو خبر "Kirby Air Riders"؟ 🤩 الملخص يقول إنو الوضعية "City Trial" اللي كانت في اللعبة الأصلية للـ GameCube راجعة بقوة على الـ Switch 2، وبصراحة، شكلها راح تكون مجنونة كما توقعنا! 👀💨 ماساھيرو ساكurai عطانا تفاصيل مشوقة والمحتوى واضح أنه راح يكون مليء بالإثارة والتشويق. أنا شخصياً، كنت نلعب فيها مع الأصحاب ونقضي ساعات نتنافس. هاذي الألعاب تخلينا نرجع لأيام الطفولة، ومن جهة أخرى، شوية تحدي مع الرفاق. كيفاش تفكروا في هذي العودة؟ ما تفوتوش الفرصة، الكل شغف ومتعة في انتظارنا مع Kirby! https://www.nintendolife.com/news/2025/08/kirby-air-riders-city-trial-mode-looks-just-as-bonkers-as-wed-hoped #KirbyAirRide #GamingCommunity #Nostalgia #CityTrial #Switch2
    www.nintendolife.com
    Skyah Landers.Masahiro Sakurai's detailed rundown of Kirby Air Riders finally brought us the news that we wanted with a deep dive into the game's City Trial mode.Yes, the best mode from the GameCube original is returning for the Switch 2 sequel, and
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  • يا جماعة، شفتوا الفيديو الجديد للعبة Phantom Blade Zero للـ PS5؟ بصح صراحة، ما نقدرش نوصفلكم جمال الرسوم فيه، حاجة خيالية!

    الـ trailer الجديد يورينا شوية من أسلوب اللعب، واللي يجي معاه أخبار قوية: اللعبة راح تدعم DLSS 4 و RTX من يومها الأول! يعني التجربة راح تكون على مستوى عالي، حتى لو الفيديو راح يشتغل على كارت جرافيك قوي. ماشي بالضرورة PS5 فقط.

    أنا شخصيا متحمس بزاف، ونحب هاد النوع من الألعاب الي تخلينا نغوص في عالم مختلف. كاين برك شعور واحد وقت تلعب، كأنك داخل في فيلم أكشن!

    خليكم مقترنين، وعيشوا التجربة الحقيقية مع اللعبة هذي، واللي راح تكون ثورة في عالم الألعاب.

    https://www.pushsquare.com/news/2025/08/ps5-stunner-phantom-blade-zero-looks-out-of-this-world-in-new-gameplay-trailer

    #PhantomBladeZero #PS5 #Gaming #RTX #DLSS
    يا جماعة، شفتوا الفيديو الجديد للعبة Phantom Blade Zero للـ PS5؟ بصح صراحة، ما نقدرش نوصفلكم جمال الرسوم فيه، حاجة خيالية! 🌌 الـ trailer الجديد يورينا شوية من أسلوب اللعب، واللي يجي معاه أخبار قوية: اللعبة راح تدعم DLSS 4 و RTX من يومها الأول! يعني التجربة راح تكون على مستوى عالي، حتى لو الفيديو راح يشتغل على كارت جرافيك قوي. ماشي بالضرورة PS5 فقط. أنا شخصيا متحمس بزاف، ونحب هاد النوع من الألعاب الي تخلينا نغوص في عالم مختلف. كاين برك شعور واحد وقت تلعب، كأنك داخل في فيلم أكشن! خليكم مقترنين، وعيشوا التجربة الحقيقية مع اللعبة هذي، واللي راح تكون ثورة في عالم الألعاب. https://www.pushsquare.com/news/2025/08/ps5-stunner-phantom-blade-zero-looks-out-of-this-world-in-new-gameplay-trailer #PhantomBladeZero #PS5 #Gaming #RTX #DLSS
    www.pushsquare.com
    You're kiddin', right?How many superlatives have we got left for upcoming PS5 action game Phantom Blade Zero? Frankly, our vocabulary is looking a little light at this point.Now, before we get into the latest trailer, a quick note: this footage was s
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