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2D animator Mayde created an incredibly smooth hand-drawn dance animation at 48 FPS, using Flash 8 and Animate 2024. It took 83 individual drawings and over 200 hours:

80 LEVEL

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44,096 views • 8 months ago •via X (Twitter)

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This is hand and finger motion capture powered by AI. 3D motion data is generated from 2D video. No suits or gloves required. This example was captured using Move Multi-Cam with 8 GoPro cameras shooting at 4K and 120 FPS.

This is hand and finger motion capture powered by AI. 3D motion data is generated from 2D video. No suits or gloves required. This example was captured using Move Multi-Cam with 8 GoPro cameras shooting at 4K and 120 FPS.

Move AI

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From 30 years ago, a spacecraft I designed and rendered using POVRay for an animation I created portraying the diversion of a comet using a nuclear weapon. This wasn't designed in a modeling program, it was hand drafted and the geometry transcribed into POV Scene description language by hand.

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Scott Manley

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3D $ANIME ? Using 3D in anime or a complete series in 3D style, how does this affect the anime industry? Probably the most hated anime after which people hated 3D in anime was Berserk in 2016, it was really terrible, but 3D in anime is no longer what it was in 2010-20. Let's look at the pros and cons of 3D in anime and what series can be called good 3D anime Pros of 3D Animation: 🟢Dynamic camera angles & smooth motion 🟢Saves time & production costs 🟢Consistent character proportions Cons of 3D Animation: 🔴Can look stiff or "plastic" 🔴Limited facial expressions 🔴Often disliked by traditional anime fans Top 3D $ANIME series in my opinion: 🔵Houseki no Kuni – stunning visuals & fluid animation 🔵Dorohedoro – dark, gritty style perfectly fits CGI 🔵Beastars – expressive character animation 🔵Trigun: Stampede – cinematic action & high-quality CGI The best studio that combines 2D and 3D well is, I think, Ufotable Ufotable blends 2D & 3D seamlessly: 🟡3D backgrounds + 2D character animation 🟡Anime-style shading makes 3D look hand-drawn 🟡Frame-by-frame touch-ups for smooth motion 🟡Mixing 2D effects (fire, water) with 3D for impact Example: "Demon Slayer" – epic battle scenes like Tanjiro’s Water Breathing, using 3D camera movement while preserving 2D aesthetics. Which 3D $ANIME impressed you the most?

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Kvintestar⛩️ Anime Artist

15,599 views • 1 year ago

Here's how you can make an extra $137,900 by the end of 2024 with your Shopify store. I could easily charge $3k for it but it’s FREE for the next 48 hours. Like + Comment "SHOPIFY" and I'll send it over. (Follow so I can DM)

Here's how you can make an extra $137,900 by the end of 2024 with your Shopify store. I could easily charge $3k for it but it’s FREE for the next 48 hours. Like + Comment "SHOPIFY" and I'll send it over. (Follow so I can DM)

Kamil Kozar | Google Ads for DTC eCommerce Brands

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Katinka 🇭🇺 won a ridiculous 26 individual world titles from 2009-2019. After a disappointing Olympics in 2012, she came back with a vengeance racing all over the place and breaking world records at World Cup meets like it was nbd. She was basically unstoppable from 2013-2019. She won the 200 and 400 IM’s back-to-back-to-back-to-back at long course World Championships. 🤯 And let’s also not forget the Hong Kong stop of the 2014 World Cup where she won 10 individual EVENTS in 48 hours. 🤪 🐐

Katinka 🇭🇺 won a ridiculous 26 individual world titles from 2009-2019. After a disappointing Olympics in 2012, she came back with a vengeance racing all over the place and breaking world records at World Cup meets like it was nbd. She was basically unstoppable from 2013-2019. She won the 200 and 400 IM’s back-to-back-to-back-to-back at long course World Championships. 🤯 And let’s also not forget the Hong Kong stop of the 2014 World Cup where she won 10 individual EVENTS in 48 hours. 🤪 🐐

SWIMNERD

18,975 views • 1 year ago

The B-Wing Cockpit animation and model are done! I've been at this one for a while, and I'm relieved to have it finished, so I can move onto something else. Enjoy! Rendered in 3dsmax 2024 using VRay 7 GPU on a 4090 RTX. It took about 3-3.5m per frame.

The B-Wing Cockpit animation and model are done! I've been at this one for a while, and I'm relieved to have it finished, so I can move onto something else. Enjoy! Rendered in 3dsmax 2024 using VRay 7 GPU on a 4090 RTX. It took about 3-3.5m per frame.

Howie Day

57,513 views • 1 year ago

We can't quite believe it, but we've never posted an FX Animation Breakdown before! There's been such amazing FX work done on so many of our projects, we're definitely going to show you more of how it's done. This film in particular was so FX heavy, we had to highlight the crazy work that went into it. You all know we love an action sequence. But for this one, we took a pretty different approach than we usually do! The entire thing was rendered through FX animation. The animator did their rough and tie-downs but instead of going into clean-up and BG paint, the FX team rendered the characters as well as animated the background FX (which is a super rare thing to do!). The result is this abstract representation of two magnificent powers colliding in an epic battle!!! Client: Digital Extremes Character Layout: Colin Tan 2D Animation: Shane Dering 2D Animation Lighting and Render: Simon Duclos FX Animation: Christophe Madeleine, Louve Karnas Compositing: Maxime Temple #FXAnimationBreakdown

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THE LINE

10,212 views • 1 month ago

UMBRA by UE Specialist and CG Generalist/Designer Jay H Patel combines aspects of nature, sci-fi and brutalist architecture to create an imposing scene. It used Unreal Engine's Lumen in its rendering and Quixel Megascans are utilized to provide the rock, moss and stone assets. "I've been using TSR rendering for all my recent Lumen based projects. Even at the default 1/8 AA value, it produces an extremely clean result without any major AA issues. It's incredibly powerful." - Jay H Patel

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Unreal Engine

19,056 views • 1 year ago

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THE LINE

258,397 views • 4 months ago

for this video wanted to see how far i could get with claude code no premiere or after effects allowed this would've taken 15 min using those traditional tools instead i prompted the entire edit and described all effects through natural language it wound up being an incredibly terrible user experience that took me 4 hours and burned through a ton of tokens 😂 shot in ibiza on a $50 camera i got on amazon by my guy Wut

for this video wanted to see how far i could get with claude code no premiere or after effects allowed this would've taken 15 min using those traditional tools instead i prompted the entire edit and described all effects through natural language it wound up being an incredibly terrible user experience that took me 4 hours and burned through a ton of tokens 😂 shot in ibiza on a $50 camera i got on amazon by my guy Wut

figge

18,358 views • 1 month ago

Komugiko2000 is the ending director, solo key animator, storyboard artist, and holds many other credits. They’re one of the most prominent names in indie animation and the creator of the #indie_anime hashtag. They explained that the filming of the Dandadan ending involved a highly unique process - “shooting real light on a monitor with a smartphone and compositing it.” The horizontal streaks of light were created by pressing the handle of a transparent spoon (the kind you get at convenience stores) against the lens. They call this technique “monitor light.” Video flow: Dance Material-> monitor light material -> monitor light material 2 -> Completed video

Komugiko2000 is the ending director, solo key animator, storyboard artist, and holds many other credits. They’re one of the most prominent names in indie animation and the creator of the #indie_anime hashtag. They explained that the filming of the Dandadan ending involved a highly unique process - “shooting real light on a monitor with a smartphone and compositing it.” The horizontal streaks of light were created by pressing the handle of a transparent spoon (the kind you get at convenience stores) against the lens. They call this technique “monitor light.” Video flow: Dance Material-> monitor light material -> monitor light material 2 -> Completed video

Daily Dandadan

23,903 views • 9 months ago

This extraordinary illustration, titled Wild World, is a hand-drawn global map created by artist and cartographer Anton thomas. Instead of political borders and city names, the map highlights wildlife, placing animals in their native habitats across every continent and ocean. Over the course of three years, Thomas meticulously illustrated 1, 642 species using coloured pencil and pen. Each animal is positioned according to its natural range, transforming the familiar shape of the world into a celebration of biodiversity. By removing human boundaries and focusing on ecosystems, the map offers a powerful reminder that the planet is shared space. It invites us to see geography not just as nations and borders, but as living habitats that connect species across land and sea.

This extraordinary illustration, titled Wild World, is a hand-drawn global map created by artist and cartographer Anton thomas. Instead of political borders and city names, the map highlights wildlife, placing animals in their native habitats across every continent and ocean. Over the course of three years, Thomas meticulously illustrated 1, 642 species using coloured pencil and pen. Each animal is positioned according to its natural range, transforming the familiar shape of the world into a celebration of biodiversity. By removing human boundaries and focusing on ecosystems, the map offers a powerful reminder that the planet is shared space. It invites us to see geography not just as nations and borders, but as living habitats that connect species across land and sea.

Oceaiii🐋🐬

115,693 views • 4 months ago

Seedance V2 This used to take people month of study and practice on Adobe Flash, now it can be done with Seedance V2, not perfect but this is the worst it will be. 15 seconds, stylized 2D hand-drawn animation, overhead battlefield on aged yellow lined notebook paper, clear blue horizontal ruled lines and a red left margin line always visible, fine paper grain, pencil marks, ink strokes, minimal classroom-material aesthetic at the start. The entire video must preserve the same paper world from start to finish. No live action, no 3D rendering, no realistic human faces, no modern objects, no narration, no subtitles. Core concept: A childish classroom doodle of an ancient war gradually transforms into a legendary illustrated battlefield, then collapses back into scribbles after the climax. The escalation must feel smooth, intentional, and visually magical, as if imagination is taking over the page. Army design: Two opposing ancient armies drawn first as simple colored stick figures, one faction in red, one faction in blue. Dense infantry blocks with spears and swords, cavalry units with long lances, banner carriers, archers. At first they are crude doodles with simple line limbs and circular heads. As the battle intensifies, they evolve step by step into more detailed inked warriors with clearer armor silhouettes, horses, weapons, helmets, capes, and expressive movement, but still remain inside a hand-drawn 2D illustrated style on paper. Visual progression and timing: 0-3 seconds: Wide top-down view of a large notebook-paper battlefield. Rough stick-figure armies face each other across the page. The drawing feels playful and simple at first. The camera slowly glides forward over the paper as both sides begin charging. Tiny horses gallop, infantry rushes, arrows are sketched into existence and start falling. Everything still looks like rough schoolbook doodles. 3-7 seconds: The first major collision. Spears thrust, swords swing, cavalry crashes into cavalry, formations break apart. With each impact, the art style upgrades. Simple stick limbs become stronger ink lines, bodies gain armor shapes, horses gain muscular form, banners gain flowing detail, shadows and dust marks appear. The battlefield becomes denser, faster, more dramatic. Red and blue strokes smear across the page with the force of combat. 7-11 seconds: The battle reaches full transformation. The once-crude doodles are now a glorious hand-illustrated ancient war scene, still clearly drawn on notebook paper but far more detailed and cinematic. The camera pushes into a central duel between two opposing generals on horseback. Their weapons clash with a powerful burst of ink lines and paper tremor. Around them, infantry and cavalry continue fighting in layered motion, arrows rain down, fallen soldiers scatter across the ruled lines. 11-15 seconds: At the peak of the duel, one final strike lands. A shockwave ripples through the page. The detailed warriors, horses, banners, and battle effects suddenly break apart into loose pencil scribbles, sketch fragments, and drifting paper-line debris. The great war rapidly collapses back into childish rough doodles, then into scattered marks and unfinished lines, as if the imagination has burned out. End on the overhead notebook page with the battlefield reduced to messy hand-drawn remnants. Animation and motion: Smooth fluid motion, strong timing, readable silhouettes, at least 24fps feel. The escalation from crude doodle to epic illustrated warfare must be gradual and continuous, not abrupt. Impacts should feel sharp and rhythmic. Keep all action legible from overhead. Maintain strong contrast between the innocent notebook-paper setting and the seriousness of the war. Atmosphere: Starts playful and curious, grows intense and heroic, peaks as a mythic battlefield, then ends with a strange quiet after the collapse. The whole piece should feel like a child’s imagination turning into an epic war vision on paper.

Seedance V2 This used to take people month of study and practice on Adobe Flash, now it can be done with Seedance V2, not perfect but this is the worst it will be. 15 seconds, stylized 2D hand-drawn animation, overhead battlefield on aged yellow lined notebook paper, clear blue horizontal ruled lines and a red left margin line always visible, fine paper grain, pencil marks, ink strokes, minimal classroom-material aesthetic at the start. The entire video must preserve the same paper world from start to finish. No live action, no 3D rendering, no realistic human faces, no modern objects, no narration, no subtitles. Core concept: A childish classroom doodle of an ancient war gradually transforms into a legendary illustrated battlefield, then collapses back into scribbles after the climax. The escalation must feel smooth, intentional, and visually magical, as if imagination is taking over the page. Army design: Two opposing ancient armies drawn first as simple colored stick figures, one faction in red, one faction in blue. Dense infantry blocks with spears and swords, cavalry units with long lances, banner carriers, archers. At first they are crude doodles with simple line limbs and circular heads. As the battle intensifies, they evolve step by step into more detailed inked warriors with clearer armor silhouettes, horses, weapons, helmets, capes, and expressive movement, but still remain inside a hand-drawn 2D illustrated style on paper. Visual progression and timing: 0-3 seconds: Wide top-down view of a large notebook-paper battlefield. Rough stick-figure armies face each other across the page. The drawing feels playful and simple at first. The camera slowly glides forward over the paper as both sides begin charging. Tiny horses gallop, infantry rushes, arrows are sketched into existence and start falling. Everything still looks like rough schoolbook doodles. 3-7 seconds: The first major collision. Spears thrust, swords swing, cavalry crashes into cavalry, formations break apart. With each impact, the art style upgrades. Simple stick limbs become stronger ink lines, bodies gain armor shapes, horses gain muscular form, banners gain flowing detail, shadows and dust marks appear. The battlefield becomes denser, faster, more dramatic. Red and blue strokes smear across the page with the force of combat. 7-11 seconds: The battle reaches full transformation. The once-crude doodles are now a glorious hand-illustrated ancient war scene, still clearly drawn on notebook paper but far more detailed and cinematic. The camera pushes into a central duel between two opposing generals on horseback. Their weapons clash with a powerful burst of ink lines and paper tremor. Around them, infantry and cavalry continue fighting in layered motion, arrows rain down, fallen soldiers scatter across the ruled lines. 11-15 seconds: At the peak of the duel, one final strike lands. A shockwave ripples through the page. The detailed warriors, horses, banners, and battle effects suddenly break apart into loose pencil scribbles, sketch fragments, and drifting paper-line debris. The great war rapidly collapses back into childish rough doodles, then into scattered marks and unfinished lines, as if the imagination has burned out. End on the overhead notebook page with the battlefield reduced to messy hand-drawn remnants. Animation and motion: Smooth fluid motion, strong timing, readable silhouettes, at least 24fps feel. The escalation from crude doodle to epic illustrated warfare must be gradual and continuous, not abrupt. Impacts should feel sharp and rhythmic. Keep all action legible from overhead. Maintain strong contrast between the innocent notebook-paper setting and the seriousness of the war. Atmosphere: Starts playful and curious, grows intense and heroic, peaks as a mythic battlefield, then ends with a strange quiet after the collapse. The whole piece should feel like a child’s imagination turning into an epic war vision on paper.

Emily

35,023 views • 3 months ago

K-Means is simple. Making it fast on GPU isn't. Flash-KMeans is an IO-aware implementation of exact k-means that rethinks the algorithm around modern GPU bottlenecks. By attacking the memory bottlenecks directly, Flash-KMeans achieves: - 30x speedup over cuML - 200x speedup over FAISS Using the same exact algorithm, just engineered for today’s hardware. At the million-scale, Flash-KMeans can complete a k-means iteration in milliseconds. Here's why this matters today: K-means has always been an offline primitive. Something you run once to preprocess data and move on. These speedups change that. ↳ Vector databases like FAISS use k-means to build search indices. Faster k-means means you can re-index dynamically as data changes, not batch it overnight. ↳ LLM quantization methods need k-means to find optimal weight codebooks, per layer, repeatedly. What takes hours could now take minutes. ↳ MoE models need fast token routing at inference time. Millisecond k-means makes it viable to run this inside the inference loop, not just in preprocessing. The 200x over FAISS is the number to internalize. FAISS is the industry standard. Most production vector search systems sit on top of it. Link to the paper and code in next tweet!

K-Means is simple. Making it fast on GPU isn't. Flash-KMeans is an IO-aware implementation of exact k-means that rethinks the algorithm around modern GPU bottlenecks. By attacking the memory bottlenecks directly, Flash-KMeans achieves: - 30x speedup over cuML - 200x speedup over FAISS Using the same exact algorithm, just engineered for today’s hardware. At the million-scale, Flash-KMeans can complete a k-means iteration in milliseconds. Here's why this matters today: K-means has always been an offline primitive. Something you run once to preprocess data and move on. These speedups change that. ↳ Vector databases like FAISS use k-means to build search indices. Faster k-means means you can re-index dynamically as data changes, not batch it overnight. ↳ LLM quantization methods need k-means to find optimal weight codebooks, per layer, repeatedly. What takes hours could now take minutes. ↳ MoE models need fast token routing at inference time. Millisecond k-means makes it viable to run this inside the inference loop, not just in preprocessing. The 200x over FAISS is the number to internalize. FAISS is the industry standard. Most production vector search systems sit on top of it. Link to the paper and code in next tweet!

Akshay 🚀

36,317 views • 3 months ago

K-Means is simple. Making it fast on GPU isn't. Flash-KMeans is an IO-aware implementation of exact k-means that rethinks the algorithm around modern GPU bottlenecks. By attacking the memory bottlenecks directly, Flash-KMeans achieves: - 30x speedup over cuML - 200x speedup over FAISS Using the same exact algorithm, just engineered for today’s hardware. At the million-scale, Flash-KMeans can complete a k-means iteration in milliseconds. Here's why this matters today: K-means has always been an offline primitive. Something you run once to preprocess data and move on. These speedups change that. ↳ Vector databases like FAISS use k-means to build search indices. Faster k-means means you can re-index dynamically as data changes, not batch it overnight. ↳ LLM quantization methods need k-means to find optimal weight codebooks, per layer, repeatedly. What takes hours could now take minutes. ↳ MoE models need fast token routing at inference time. Millisecond k-means makes it viable to run this inside the inference loop, not just in preprocessing. The 200x over FAISS is the number to internalize. FAISS is the industry standard. Most production vector search systems sit on top of it. Link to the paper and code in next tweet!

K-Means is simple. Making it fast on GPU isn't. Flash-KMeans is an IO-aware implementation of exact k-means that rethinks the algorithm around modern GPU bottlenecks. By attacking the memory bottlenecks directly, Flash-KMeans achieves: - 30x speedup over cuML - 200x speedup over FAISS Using the same exact algorithm, just engineered for today’s hardware. At the million-scale, Flash-KMeans can complete a k-means iteration in milliseconds. Here's why this matters today: K-means has always been an offline primitive. Something you run once to preprocess data and move on. These speedups change that. ↳ Vector databases like FAISS use k-means to build search indices. Faster k-means means you can re-index dynamically as data changes, not batch it overnight. ↳ LLM quantization methods need k-means to find optimal weight codebooks, per layer, repeatedly. What takes hours could now take minutes. ↳ MoE models need fast token routing at inference time. Millisecond k-means makes it viable to run this inside the inference loop, not just in preprocessing. The 200x over FAISS is the number to internalize. FAISS is the industry standard. Most production vector search systems sit on top of it. Link to the paper and code in next tweet!

Daily Dose of Data Science

23,748 views • 2 months ago

BEWARE buyers and sellers! E&L Poké Rips and I agreed to a $3,420 deal on an psa 9 error Coro Coro Mew, at the time there was no recent sales data on the card and I took the risk on the card paying over current 9 normal comps. An auction for a psa 8 at the time of deal was at $1200. I sent over the money and it was confirmed. That auction today finished high and now he has backed out of the deal, he had also transferred the money immediately and was not able to send an immediate refund. Both actions in my opinion are terrible ways to do business and I advise caution dealing with someone who’s willing to back out of a deal this large just because he “lost value”. Especially since I essentially took all the risk betting on the auction since now that it finished well he’s is just not going to send the card. (I bet it would’ve been sent if the auction finished low :) ) I have attached a screen recording of our entire convo including the deal we made I have now received my refund and feel comfortable sending this post.

BEWARE buyers and sellers! E&L Poké Rips and I agreed to a $3,420 deal on an psa 9 error Coro Coro Mew, at the time there was no recent sales data on the card and I took the risk on the card paying over current 9 normal comps. An auction for a psa 8 at the time of deal was at $1200. I sent over the money and it was confirmed. That auction today finished high and now he has backed out of the deal, he had also transferred the money immediately and was not able to send an immediate refund. Both actions in my opinion are terrible ways to do business and I advise caution dealing with someone who’s willing to back out of a deal this large just because he “lost value”. Especially since I essentially took all the risk betting on the auction since now that it finished well he’s is just not going to send the card. (I bet it would’ve been sent if the auction finished low :) ) I have attached a screen recording of our entire convo including the deal we made I have now received my refund and feel comfortable sending this post.

Mitchell Cox

251,426 views • 4 months ago

Everyone's sleeping on image-to-3D AI models. They can make your app look incredibly unique, with just a little effort. Here's how. This is my calorie tracker, built in a week with nothing but prompting. Just Claude Code + a couple APIs. The visuals are all AI-generated. I'll be sharing the full workflow + all the crazy technical stuff Claude and I did to make this work, so nobody has to struggle through it like me. Deep dive coming soon! Till then, this is the high-level idea: 1. Get a clean image of the food (or whatever your asset is) - In my app, the user describes foods via text, or attaches images (or both) - If text, an LLM extracts the food description and formats it into a specific prompt I tuned for this design, and we generate an image using Z-Image Turbo through fal - If image, we do the same thing but with FLUX.2 [dev] to edit the user image into our reference design - Originally, both used Google Nano Banana, but switching to open models cut costs and latency a ton 2. Gaussian splatting (2D image → 3D model) - I tried various 2D-to-3D options on fal and ended up with TripoSplat as my preferred balance of speed, cost, latency; this turns an image into a 3D model that looks super high quality (link below) - The app displays the 2D image while our backend generates the 3D splat - We "groom" the splat to reduce size and load time by culling low-opacity/scale points 3. Render efficiently on device Originally, it looked great but ran at 10 FPS. Getting to 120 FPS was a crazy journey. TL;DR: - SwiftUI had to go; it forced us to render each asset in independent MTKViews, which wasn't workable - Instead, we composite every dish into one full-bleed CAMetalLayer using MetalSplatter (link below) - We had to make some optimizations within MetalSplatter's code too, to reduce the overhead of sorting points per render Then I added some finishing touches like the subtle rotation and parallax as they move around. I think it turned out pretty cool :) Overall, this took some effort, but we still got it done in less than a day. Hopefully your agent can follow in the footsteps of mine and do it much faster. Keep an eye out for the bigger writeup, which'll give your agent everything it needs. If you have any questions, drop em below!

Everyone's sleeping on image-to-3D AI models. They can make your app look incredibly unique, with just a little effort. Here's how. This is my calorie tracker, built in a week with nothing but prompting. Just Claude Code + a couple APIs. The visuals are all AI-generated. I'll be sharing the full workflow + all the crazy technical stuff Claude and I did to make this work, so nobody has to struggle through it like me. Deep dive coming soon! Till then, this is the high-level idea: 1. Get a clean image of the food (or whatever your asset is) - In my app, the user describes foods via text, or attaches images (or both) - If text, an LLM extracts the food description and formats it into a specific prompt I tuned for this design, and we generate an image using Z-Image Turbo through fal - If image, we do the same thing but with FLUX.2 [dev] to edit the user image into our reference design - Originally, both used Google Nano Banana, but switching to open models cut costs and latency a ton 2. Gaussian splatting (2D image → 3D model) - I tried various 2D-to-3D options on fal and ended up with TripoSplat as my preferred balance of speed, cost, latency; this turns an image into a 3D model that looks super high quality (link below) - The app displays the 2D image while our backend generates the 3D splat - We "groom" the splat to reduce size and load time by culling low-opacity/scale points 3. Render efficiently on device Originally, it looked great but ran at 10 FPS. Getting to 120 FPS was a crazy journey. TL;DR: - SwiftUI had to go; it forced us to render each asset in independent MTKViews, which wasn't workable - Instead, we composite every dish into one full-bleed CAMetalLayer using MetalSplatter (link below) - We had to make some optimizations within MetalSplatter's code too, to reduce the overhead of sorting points per render Then I added some finishing touches like the subtle rotation and parallax as they move around. I think it turned out pretty cool :) Overall, this took some effort, but we still got it done in less than a day. Hopefully your agent can follow in the footsteps of mine and do it much faster. Keep an eye out for the bigger writeup, which'll give your agent everything it needs. If you have any questions, drop em below!

Anshu

19,931 views • 23 days ago

PETITION AGAINST SONY HIT OVER 30,000 SIGNATURES IN 48 HOURS. Yesterday morning it was at 12,000. The backlash isn't cooling - it's compounding. - It wasn't started by a fan: a game retailer launched it on behalf of the entire physical industry - Sony's announcement post: 57,000 replies and 55,000 retweets, per Forbes - the biggest PlayStation scandal in 20 years - Retailers mobilized: GAME launched #GamersUnidos in Spain, GameFly and GameStop issued statements defending physical - PlayStation itself? Silent on every account for 24+ hours, per Push Square. Even the routine PS Plus post got skipped. And Sony has folded before: the PS3 Store shutdown in 2021, the Helldivers 2 PSN mandate in 2024. Both reversed after revolts exactly like this one. In one week, Sony wiped 550 purchased movies, condemned two storefronts, and killed the disc. Turns out there's exactly one piece of digital content they can't delete.

PETITION AGAINST SONY HIT OVER 30,000 SIGNATURES IN 48 HOURS. Yesterday morning it was at 12,000. The backlash isn't cooling - it's compounding. - It wasn't started by a fan: a game retailer launched it on behalf of the entire physical industry - Sony's announcement post: 57,000 replies and 55,000 retweets, per Forbes - the biggest PlayStation scandal in 20 years - Retailers mobilized: GAME launched #GamersUnidos in Spain, GameFly and GameStop issued statements defending physical - PlayStation itself? Silent on every account for 24+ hours, per Push Square. Even the routine PS Plus post got skipped. And Sony has folded before: the PS3 Store shutdown in 2021, the Helldivers 2 PSN mandate in 2024. Both reversed after revolts exactly like this one. In one week, Sony wiped 550 purchased movies, condemned two storefronts, and killed the disc. Turns out there's exactly one piece of digital content they can't delete.

frostzy

83,425 views • 13 days ago