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Tokon PC post 8/21 patch: 0 dropped frames without capping framerate in nvidia control panel and/or rivatuner #MARVELTōkon

Chris_F

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28,002 Aufrufe • vor 2 Monaten •via X (Twitter)

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A video of the rollback frames in the same match I played against my friend while I'm on PS5 while he's on PC (YT is clearer). Our connection is at a constant 6ms, but the PS5 player spikes up to 8 FRAMES OF ROLLBACK while PC player gets 0. #MARVELTōkon

A video of the rollback frames in the same match I played against my friend while I'm on PS5 while he's on PC (YT is clearer). Our connection is at a constant 6ms, but the PS5 player spikes up to 8 FRAMES OF ROLLBACK while PC player gets 0. #MARVELTōkon

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Rerender A Video: Zero-Shot Text-Guided Video-to-Video Translation paper page: Large text-to-image diffusion models have exhibited impressive proficiency in generating high-quality images. However, when applying these models to video domain, ensuring temporal consistency across video frames remains a formidable challenge. This paper proposes a novel zero-shot text-guided video-to-video translation framework to adapt image models to videos. The framework includes two parts: key frame translation and full video translation. The first part uses an adapted diffusion model to generate key frames, with hierarchical cross-frame constraints applied to enforce coherence in shapes, textures and colors. The second part propagates the key frames to other frames with temporal-aware patch matching and frame blending. Our framework achieves global style and local texture temporal consistency at a low cost (without re-training or optimization). The adaptation is compatible with existing image diffusion techniques, allowing our framework to take advantage of them, such as customizing a specific subject with LoRA, and introducing extra spatial guidance with ControlNet. Extensive experimental results demonstrate the effectiveness of our proposed framework over existing methods in rendering high-quality and temporally-coherent videos.

Rerender A Video: Zero-Shot Text-Guided Video-to-Video Translation paper page: Large text-to-image diffusion models have exhibited impressive proficiency in generating high-quality images. However, when applying these models to video domain, ensuring temporal consistency across video frames remains a formidable challenge. This paper proposes a novel zero-shot text-guided video-to-video translation framework to adapt image models to videos. The framework includes two parts: key frame translation and full video translation. The first part uses an adapted diffusion model to generate key frames, with hierarchical cross-frame constraints applied to enforce coherence in shapes, textures and colors. The second part propagates the key frames to other frames with temporal-aware patch matching and frame blending. Our framework achieves global style and local texture temporal consistency at a low cost (without re-training or optimization). The adaptation is compatible with existing image diffusion techniques, allowing our framework to take advantage of them, such as customizing a specific subject with LoRA, and introducing extra spatial guidance with ControlNet. Extensive experimental results demonstrate the effectiveness of our proposed framework over existing methods in rendering high-quality and temporally-coherent videos.

AK

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China just dropped an open source model that turns any phone into a 3D scanner you point it at a room and walk through it the whole space builds itself into a 3D point cloud in real time as the camera moves, no LiDAR and no depth sensor anywhere it held a full 13 minute walkthrough at 25,000 frames without the map drifting or collapsing > ~20 fps on a single GPU > works indoors and outdoors from plain footage > the scan normally needs a $50,000 rig and a technician > Apache 2.0 and runs fully offline on your machine repo in the reply

China just dropped an open source model that turns any phone into a 3D scanner you point it at a room and walk through it the whole space builds itself into a 3D point cloud in real time as the camera moves, no LiDAR and no depth sensor anywhere it held a full 13 minute walkthrough at 25,000 frames without the map drifting or collapsing > ~20 fps on a single GPU > works indoors and outdoors from plain footage > the scan normally needs a $50,000 rig and a technician > Apache 2.0 and runs fully offline on your machine repo in the reply

savip.

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Instead of GRWM, let's cook with me. Cooked on GPT Image 2 + Happy Horse on BudgetPixel AI Prompt Create a 10-second cinematic food-commercial video following a STRICT 9-panel storyboard sequence. The AI MUST follow the storyboard EXACTLY in order with smooth cinematic continuity between every shot. Do NOT skip panels, merge scenes, change camera angles randomly, or alter the cooking process. STRICT VIDEO RULES EXACTLY 9 sequential scenes Maintain the SAME young Western blonde woman throughout the entire video Same wardrobe, hairstyle, kitchen environment, props, and food consistency in every shot Keep realistic Indonesian bubur ayam preparation accurate Smooth transitions between scenes Realistic live-action cinematography ONLY No animation, no cartoon style, no surreal visuals Professional food-commercial pacing Every scene should feel connected like a luxury Netflix food documentary VISUAL STYLE Ultra realistic cinematic food videography Warm morning lighting Indonesian street-food atmosphere blended with modern cozy kitchen aesthetic Rich golden tones Soft steam atmosphere Shallow depth of field Smooth cinematic motion blur Macro food photography look Premium commercial composition 24fps cinematic motion 4K ultra realism Natural cooking ambience audio Steam and glossy textures highly visible STRICT 9-PANEL VIDEO STORYBOARD PANEL 1 — “Morning Preparation” (0:00–0:01) Wide cinematic establishing shot. Young blonde Western woman enters a cozy Indonesian-inspired kitchen carrying fresh ingredients toward a wooden counter. Warm sunrise light enters through the window. Slow handheld cinematic camera movement. PANEL 2 — “The Bubur Pot” (0:01–0:02) Extreme close-up of a large steaming pot of thick bubur ayam. The woman slowly stirs the porridge with a metal ladle. Heavy steam rises dramatically into warm light. Macro cinematic food detail. PANEL 3 — “Careful Seasoning” (0:02–0:03) Close-up of the woman sprinkling spices and seasoning into the bubbling porridge. Focused expression. Shallow depth of field with cinematic hand movement. PANEL 4 — “Pouring the Porridge” (0:03–0:04) Slow-motion macro shot of thick glossy porridge being poured from ladle into a white ceramic bowl. Steam rises beautifully. Camera follows the pouring motion smoothly. PANEL 5 — “Preparing Toppings” (0:04–0:05) Fast cinematic montage of toppings being prepared: shredded chicken, chopped scallions, fried shallots, soybeans, crackers. Quick macro cuts with elegant food styling. PANEL 6 — “Topping Assembly” (0:05–0:06) Dynamic slow-motion shot of toppings dropping into the bowl one by one. Floating crumbs and steam visible. Luxury commercial close-up angles. PANEL 7 — “Golden Broth Finish” (0:06–0:07) Golden chicken broth poured over the porridge creating rich ripples. Sambal carefully added on the side. Camera slowly rotates around the bowl. PANEL 8 — “Final Food Presentation” (0:07–0:08.5) Completed bubur ayam placed on a warm wooden table. The woman adjusts the bowl presentation gently. Steam rises naturally. Crispy toppings highly detailed. PANEL 9 — “Hero Shot” (0:08.5–0:10) Final cinematic hero frame. The blonde Western woman sits beside the finished bubur ayam smiling softly toward camera in warm morning light. Slow cinematic push-in camera movement. Shallow depth of field. Elegant premium food-commercial ending with cinematic focus pull. TECHNICAL NOTES Smooth cinematic transitions only Keep camera movement elegant and controlled Avoid fast chaotic edits Maintain realistic physics and food textures Steam must remain visible in most scenes Food should always look fresh, glossy, warm, and appetizing Cinematic luxury advertisement quality throughout The AI MUST strictly follow all 9 storyboard panels in exact order without improvisation

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Yesterday, German journalist Bettina Böttinger wrote “Animals have dignity that these idiots don't have" referring to a video of cheering Palestinians in Gaza. She has since deleted the post. On German public tv journalist Susanne Glass stated Palestinians freed from Israeli prisons are "resupplying the terrorists" She doesn't mention that these prisoners consisted of 69 women and 21 teenage boys as young as 12, nor that many of them were imprisoned for social media posts or held without charge and in administrative detention.

Yesterday, German journalist Bettina Böttinger wrote “Animals have dignity that these idiots don't have" referring to a video of cheering Palestinians in Gaza. She has since deleted the post. On German public tv journalist Susanne Glass stated Palestinians freed from Israeli prisons are "resupplying the terrorists" She doesn't mention that these prisoners consisted of 69 women and 21 teenage boys as young as 12, nor that many of them were imprisoned for social media posts or held without charge and in administrative detention.

In Context

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And this is how you train CyberKimi to find the next chrome 0-day you start with unpatched n-days. So we caught a fresh V8 LLE aliasing bug and a SLICED-PARENT-FLIP race bug off the main-branch diff fix landed Sep 2, still live on every shipping Chrome stable today and we exploited them. Exploit weaponized autonomously in <24h No CVE published yet. This is a silent in the wild exploit that Chrome Stable isn't protected from. Stage 1 - Bug 554421904 stage-1 (deterministic LLE forge) Stage 2 - cage escape prep: compose the caged RW into sandbox-wide RW (forge a BigUint64Array external pointer) and leak the binary base through the native side - ASLR done, at runtime, no baked offsets. Stage 3 - PC control: a RegExp calling-convention desync lands the CPU on a string we fully control From there: JOP chain living inside the subject string → tail-call system(). Calc pops. The special harness that we built: patch-diff watcher mining every V8 security fix within hours → variant analysis → autonomous weaponization → demo The 24h patch-to-exploit buffer keeps shrinking. 🐺

And this is how you train CyberKimi to find the next chrome 0-day you start with unpatched n-days. So we caught a fresh V8 LLE aliasing bug and a SLICED-PARENT-FLIP race bug off the main-branch diff fix landed Sep 2, still live on every shipping Chrome stable today and we exploited them. Exploit weaponized autonomously in <24h No CVE published yet. This is a silent in the wild exploit that Chrome Stable isn't protected from. Stage 1 - Bug 554421904 stage-1 (deterministic LLE forge) Stage 2 - cage escape prep: compose the caged RW into sandbox-wide RW (forge a BigUint64Array external pointer) and leak the binary base through the native side - ASLR done, at runtime, no baked offsets. Stage 3 - PC control: a RegExp calling-convention desync lands the CPU on a string we fully control From there: JOP chain living inside the subject string → tail-call system(). Calc pops. The special harness that we built: patch-diff watcher mining every V8 security fix within hours → variant analysis → autonomous weaponization → demo The 24h patch-to-exploit buffer keeps shrinking. 🐺

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The Canvas feature in Renoise AI is a game-changing workspace for creating and managing e-commerce advertisements at scale. It transforms traditional video editing into an AI-powered creative workflow. I created this strawberry shake ad on Renoise using GPT Image 2 + Seedance 2.0 Prompt Create a hyper-realistic cinematic AI commercial video in horizontal 16:9 format. The video MUST follow ALL storyboard panels STRICTLY in exact order from Panel 1 through Panel 8 with seamless cinematic continuity. DO NOT include: * text overlays * subtitles * timestamps * VHS dates * captions * logos * animation notes * comic graphics * UI elements * split screens * watermarks The entire video should feel like a real premium cinematic commercial captured naturally on an iPhone 15 Pro mixed with vintage fish-eye skate footage. Maintain the SAME throughout the entire video: * blonde main girl * friend group * retro diner * wardrobe styling * strawberry shake product * lighting progression * nostalgic Y2K aesthetic * chrome reflections * energetic youth atmosphere The strawberry shake must remain perfectly consistent in every shot: glossy strawberry-pink liquid, whipped cream topping, condensation droplets, premium commercial realism, chrome reflections, same cup/bottle design throughout all scenes. Visual style: early-2000s skate-video nostalgia, retro Americana milkshake-commercial energy, premium TikTok fashion-commercial pacing, fish-eye skate cinematography, candid handheld realism, warm strawberry pink-red palette, slightly faded nostalgic colors, motion blur, chrome reflections everywhere, messy natural movement, commercial-quality realism, playful chaotic youth culture atmosphere. --- # PANEL 1 — ESTABLISHING SHOT (0:00–0:04) Wide cinematic exterior of a glowing retro Americana roadside diner during golden hour. Stylish western Gen-Z skater friends arrive on skateboards and roller skates. Neon signs glow softly pink and red. Vintage convertible parked outside diner. Warm sunset reflections across chrome surfaces. Handheld camera quickly pushes toward diner entrance with subtle fish-eye lens distortion. Main blonde girl enters frame laughing while confidently holding strawberry shake. Authentic imperfect framing, motion blur from fast skateboard movement, nostalgic suburban atmosphere. --- # PANEL 2 — ROLLER SKATE PASS (0:04–0:07) Extreme low-angle fish-eye shot inside diner. Roller skates aggressively slide directly past camera across glossy black-and-white checkered floor. Chrome reflections streak dynamically across frame. The strawberry shake swings through foreground with condensation dripping naturally. Fast whip-pan camera movement with energetic motion blur. Friends laughing in background booths. --- # PANEL 3 — MILKSHAKE SPIN (0:07–0:10) Macro cinematic close-up of strawberry shake spinning slowly on reflective chrome diner counter. Whipped cream wobbles naturally. Condensation droplets sparkle dramatically. Fresh strawberries beside cup. Vintage jukebox softly glowing in background. Slow-motion luxury commercial realism with shallow depth of field. Camera smoothly rotates around shake. --- # PANEL 4 — DINER BOOTH CHAOS (0:10–0:14) Chaotic handheld shot of fashionable friends dancing wildly inside diner booths. Oversized hoodies, baggy jeans, vintage racing jackets, tiny sunglasses, silver jewelry moving dynamically. Main blonde girl stands on diner booth laughing while holding strawberry shake overhead. Natural camera shake like authentic 2000s camcorder footage. Messy candid movement, energetic youth atmosphere, chrome reflections everywhere. --- # PANEL 5 — JUKEBOX MOMENT (0:14–0:17) Cinematic medium shot. Main blonde girl dramatically presses glowing retro jukebox button while holding strawberry shake in opposite hand. Pink-red neon light softly illuminates glitter makeup and glossy lips. Camera slowly pushes toward her face while chrome reflections move across frame. Background friends dance softly out of focus. Stylish rebellious retro Americana energy. --- # PANEL 6 — WHIPPED CREAM FOOD FIGHT (0:17–0:21) Chaotic slow-motion whipped cream fight exploding across diner. Whipped cream flies toward camera lens. Friends laugh uncontrollably. Dynamic motion blur throughout scene. Main blonde girl remains center frame holding strawberry shake confidently while dodging whipped cream. Cream splatters across chrome counter and diner windows. Exaggerated playful cinematic energy. --- # PANEL 7 — RETRO CAR WINDOW SHOT (0:21–0:25) Nighttime exterior outside diner. Inside vintage chrome convertible parked under glowing diner neon lights. Handheld camcorder-style shot from backseat. Main blonde girl laughs with whipped cream mustache while holding strawberry shake toward camera. Friends lean out windows laughing while pink neon reflections move across glass surfaces. Warm nostalgic nighttime atmosphere with subtle grain texture. --- # PANEL 8 — FINAL HERO SHOT (0:25–0:30) Final cinematic ending outside glowing retro diner at night. Main blonde girl stands confidently under neon lighting drinking strawberry shake while friends roller skate away laughing in background. Wind naturally blowing hair. Fish-eye lens slowly settles into emotional cinematic framing. Chrome reflections shimmer on wet asphalt. Pink-red neon glow surrounds scene. Motion blur trails from skating friends. The video ends with a natural cinematic freeze-like ending moment, emotional nostalgic Y2K atmosphere, premium commercial realism.

The Canvas feature in Renoise AI is a game-changing workspace for creating and managing e-commerce advertisements at scale. It transforms traditional video editing into an AI-powered creative workflow. I created this strawberry shake ad on Renoise using GPT Image 2 + Seedance 2.0 Prompt Create a hyper-realistic cinematic AI commercial video in horizontal 16:9 format. The video MUST follow ALL storyboard panels STRICTLY in exact order from Panel 1 through Panel 8 with seamless cinematic continuity. DO NOT include: * text overlays * subtitles * timestamps * VHS dates * captions * logos * animation notes * comic graphics * UI elements * split screens * watermarks The entire video should feel like a real premium cinematic commercial captured naturally on an iPhone 15 Pro mixed with vintage fish-eye skate footage. Maintain the SAME throughout the entire video: * blonde main girl * friend group * retro diner * wardrobe styling * strawberry shake product * lighting progression * nostalgic Y2K aesthetic * chrome reflections * energetic youth atmosphere The strawberry shake must remain perfectly consistent in every shot: glossy strawberry-pink liquid, whipped cream topping, condensation droplets, premium commercial realism, chrome reflections, same cup/bottle design throughout all scenes. Visual style: early-2000s skate-video nostalgia, retro Americana milkshake-commercial energy, premium TikTok fashion-commercial pacing, fish-eye skate cinematography, candid handheld realism, warm strawberry pink-red palette, slightly faded nostalgic colors, motion blur, chrome reflections everywhere, messy natural movement, commercial-quality realism, playful chaotic youth culture atmosphere. --- # PANEL 1 — ESTABLISHING SHOT (0:00–0:04) Wide cinematic exterior of a glowing retro Americana roadside diner during golden hour. Stylish western Gen-Z skater friends arrive on skateboards and roller skates. Neon signs glow softly pink and red. Vintage convertible parked outside diner. Warm sunset reflections across chrome surfaces. Handheld camera quickly pushes toward diner entrance with subtle fish-eye lens distortion. Main blonde girl enters frame laughing while confidently holding strawberry shake. Authentic imperfect framing, motion blur from fast skateboard movement, nostalgic suburban atmosphere. --- # PANEL 2 — ROLLER SKATE PASS (0:04–0:07) Extreme low-angle fish-eye shot inside diner. Roller skates aggressively slide directly past camera across glossy black-and-white checkered floor. Chrome reflections streak dynamically across frame. The strawberry shake swings through foreground with condensation dripping naturally. Fast whip-pan camera movement with energetic motion blur. Friends laughing in background booths. --- # PANEL 3 — MILKSHAKE SPIN (0:07–0:10) Macro cinematic close-up of strawberry shake spinning slowly on reflective chrome diner counter. Whipped cream wobbles naturally. Condensation droplets sparkle dramatically. Fresh strawberries beside cup. Vintage jukebox softly glowing in background. Slow-motion luxury commercial realism with shallow depth of field. Camera smoothly rotates around shake. --- # PANEL 4 — DINER BOOTH CHAOS (0:10–0:14) Chaotic handheld shot of fashionable friends dancing wildly inside diner booths. Oversized hoodies, baggy jeans, vintage racing jackets, tiny sunglasses, silver jewelry moving dynamically. Main blonde girl stands on diner booth laughing while holding strawberry shake overhead. Natural camera shake like authentic 2000s camcorder footage. Messy candid movement, energetic youth atmosphere, chrome reflections everywhere. --- # PANEL 5 — JUKEBOX MOMENT (0:14–0:17) Cinematic medium shot. Main blonde girl dramatically presses glowing retro jukebox button while holding strawberry shake in opposite hand. Pink-red neon light softly illuminates glitter makeup and glossy lips. Camera slowly pushes toward her face while chrome reflections move across frame. Background friends dance softly out of focus. Stylish rebellious retro Americana energy. --- # PANEL 6 — WHIPPED CREAM FOOD FIGHT (0:17–0:21) Chaotic slow-motion whipped cream fight exploding across diner. Whipped cream flies toward camera lens. Friends laugh uncontrollably. Dynamic motion blur throughout scene. Main blonde girl remains center frame holding strawberry shake confidently while dodging whipped cream. Cream splatters across chrome counter and diner windows. Exaggerated playful cinematic energy. --- # PANEL 7 — RETRO CAR WINDOW SHOT (0:21–0:25) Nighttime exterior outside diner. Inside vintage chrome convertible parked under glowing diner neon lights. Handheld camcorder-style shot from backseat. Main blonde girl laughs with whipped cream mustache while holding strawberry shake toward camera. Friends lean out windows laughing while pink neon reflections move across glass surfaces. Warm nostalgic nighttime atmosphere with subtle grain texture. --- # PANEL 8 — FINAL HERO SHOT (0:25–0:30) Final cinematic ending outside glowing retro diner at night. Main blonde girl stands confidently under neon lighting drinking strawberry shake while friends roller skate away laughing in background. Wind naturally blowing hair. Fish-eye lens slowly settles into emotional cinematic framing. Chrome reflections shimmer on wet asphalt. Pink-red neon glow surrounds scene. Motion blur trails from skating friends. The video ends with a natural cinematic freeze-like ending moment, emotional nostalgic Y2K atmosphere, premium commercial realism.

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GT Protocol

32,323 Aufrufe • vor 9 Monaten

Since y’all liked the first list so much, here are 99 more games with boob and/or butt jiggle… • Arc Rise Fantasia [WII] • Dragon’s Dogma: Dark Arisen [NSW] • Fist of the North Star: Ken’s Rage [PS3] • Haydee [PC] • No More Heroes 2: Desperate Struggle [WII] • Ryse: Son of Rome [XBO] • Super Smash Bros. Ultimate [NSW] • Astral Chain [NSW] • Dungeon Fighter Online [PC] • Fighter Maker 2 [PS2] • Honkai Impact 3rd [PC] • Mercenary Kings [NSW] • Samurai Shodown [PS4] • The 3rd Birthday [PSP] • Baldur’s Gate: Dark Alliance II [PS2] • Dungeon Siege III [PS3] • Fighting Angels [PS2] • GunZ 2: The Second Duel [PC] • Hunted: The Demon’s Forge [PS3] • Metro: Last Light [PC] • R: Racing Evolution [PS2] • Scarlet Blade [PC] • The King of Route 66 [PS2] • Yakuza 0 [PS4] • Baten Kaitos Origins [GC] • Cel Damage [XB] • Demolition Girl [PS2] • Sengoku 3 [AES] • Dynasty Warriors 8 Empires [PS4] • Fitness Boxing [NSW] • J-Stars Victory Vs+ [PS4] • Trails Through Daybreak [PS5] • Batman: Arkham Knight [XBO] • Devil May Cry 4 [PS3] • Evil Zone [PSX] • Half-Life [PC] • Muramasa Rebirth [PSV] • Phantom Breaker: Battle Grounds [PSV] • Ready 2 Rumble Boxing [DC] • Sengoku Basara: Samurai Heroes [PS3] • Time Crisis: Razing Storm [PS3] • Bayonetta [XB360] • Conan Exiles [PS4] • Girl Fight [PS3] • Killer is Dead [PS3] • NEKOPARA Vol. 1 [PC] • Playboy: The Mansion [PS2] • SiN [PC] • Tokyo Mirage Sessions FE [WIIU] • Black Desert Online [PC] • Cross Edge [PS3] • The House of the Dead: Overkill [WII] • Dissidia 012 Final Fantasy [PSP] • Eternal Champions: CftDS [SCD] • God Eater 3 [NSW] • Hatsune Miku: Project DIVA f [PS3] • Leisure Suit Larry: Magna Cum Laude [PC] • Neverwinter Nights [PC] • Pirates: The Legend of Black Kat [XB] • Red Dead Redemption [XB360] • Skullgirls [PS3] • Uppers [PC] • Blade & Soul [PC] • Dead Rising [XB360] • BlazBlue: Central Fiction Special Edition [NSW] • Dragon Star Varnir [NSW] • Fatal Fury 2 [AES] • Lost Ruins [NSW] • Smite [PC] • Reynatis [PS5] • Sonic Adventure 2 [DC] • Valkyria Chronicles [PS3] • Kingdom Hearts: Birth by Sleep [PSP] • Boo Party [NSW] • Dead or School [NSW] • Fate/EXTELLA Link [NSW] • Golden Axe: Beast Rider [PS3] • Mega Man X DiVE [MOB] • Nitroplus Blasterz: Heroines Infinite Duel [PS3] • Star Trek Online [PC] • Ōkami [PS2] • Ride to Hell: Retribution [PS3] • ArcheBlade [PC] • Super Galdelic Hour [PS2] • X-Men: Children of the Atom [SAT] • Indivisible [PS4] • Wuthering Waves [PC] • Guacamelee! [PS4] • Scott Pilgrim vs. The World: The Game [NSW] • Amazing Princess Sarah [PC] • The Witcher [PC] • Guns, Gore & Cannoli [XBO] • Spacelords [PC] • Darksiders II: Deathinitive Edition [NSW] • Street Fighter X Tekken [PS3] • Duke Nukem Forever [XB360] • PUBG: Battlegrounds [PC] • Ar tonelico Qoga: Knell of Ar Ciel [PS3] • Grand Theft Auto V [PS3] (Again, please note that the platform in brackets to the side indicates which version I’ve played or may prefer for one reason or another. That does not mean it’s the only platform to feature jiggle. Also this is not an exhaustive list. I’ve limited to just one entry per series, for instance.)

Since y’all liked the first list so much, here are 99 more games with boob and/or butt jiggle… • Arc Rise Fantasia [WII] • Dragon’s Dogma: Dark Arisen [NSW] • Fist of the North Star: Ken’s Rage [PS3] • Haydee [PC] • No More Heroes 2: Desperate Struggle [WII] • Ryse: Son of Rome [XBO] • Super Smash Bros. Ultimate [NSW] • Astral Chain [NSW] • Dungeon Fighter Online [PC] • Fighter Maker 2 [PS2] • Honkai Impact 3rd [PC] • Mercenary Kings [NSW] • Samurai Shodown [PS4] • The 3rd Birthday [PSP] • Baldur’s Gate: Dark Alliance II [PS2] • Dungeon Siege III [PS3] • Fighting Angels [PS2] • GunZ 2: The Second Duel [PC] • Hunted: The Demon’s Forge [PS3] • Metro: Last Light [PC] • R: Racing Evolution [PS2] • Scarlet Blade [PC] • The King of Route 66 [PS2] • Yakuza 0 [PS4] • Baten Kaitos Origins [GC] • Cel Damage [XB] • Demolition Girl [PS2] • Sengoku 3 [AES] • Dynasty Warriors 8 Empires [PS4] • Fitness Boxing [NSW] • J-Stars Victory Vs+ [PS4] • Trails Through Daybreak [PS5] • Batman: Arkham Knight [XBO] • Devil May Cry 4 [PS3] • Evil Zone [PSX] • Half-Life [PC] • Muramasa Rebirth [PSV] • Phantom Breaker: Battle Grounds [PSV] • Ready 2 Rumble Boxing [DC] • Sengoku Basara: Samurai Heroes [PS3] • Time Crisis: Razing Storm [PS3] • Bayonetta [XB360] • Conan Exiles [PS4] • Girl Fight [PS3] • Killer is Dead [PS3] • NEKOPARA Vol. 1 [PC] • Playboy: The Mansion [PS2] • SiN [PC] • Tokyo Mirage Sessions FE [WIIU] • Black Desert Online [PC] • Cross Edge [PS3] • The House of the Dead: Overkill [WII] • Dissidia 012 Final Fantasy [PSP] • Eternal Champions: CftDS [SCD] • God Eater 3 [NSW] • Hatsune Miku: Project DIVA f [PS3] • Leisure Suit Larry: Magna Cum Laude [PC] • Neverwinter Nights [PC] • Pirates: The Legend of Black Kat [XB] • Red Dead Redemption [XB360] • Skullgirls [PS3] • Uppers [PC] • Blade & Soul [PC] • Dead Rising [XB360] • BlazBlue: Central Fiction Special Edition [NSW] • Dragon Star Varnir [NSW] • Fatal Fury 2 [AES] • Lost Ruins [NSW] • Smite [PC] • Reynatis [PS5] • Sonic Adventure 2 [DC] • Valkyria Chronicles [PS3] • Kingdom Hearts: Birth by Sleep [PSP] • Boo Party [NSW] • Dead or School [NSW] • Fate/EXTELLA Link [NSW] • Golden Axe: Beast Rider [PS3] • Mega Man X DiVE [MOB] • Nitroplus Blasterz: Heroines Infinite Duel [PS3] • Star Trek Online [PC] • Ōkami [PS2] • Ride to Hell: Retribution [PS3] • ArcheBlade [PC] • Super Galdelic Hour [PS2] • X-Men: Children of the Atom [SAT] • Indivisible [PS4] • Wuthering Waves [PC] • Guacamelee! [PS4] • Scott Pilgrim vs. The World: The Game [NSW] • Amazing Princess Sarah [PC] • The Witcher [PC] • Guns, Gore & Cannoli [XBO] • Spacelords [PC] • Darksiders II: Deathinitive Edition [NSW] • Street Fighter X Tekken [PS3] • Duke Nukem Forever [XB360] • PUBG: Battlegrounds [PC] • Ar tonelico Qoga: Knell of Ar Ciel [PS3] • Grand Theft Auto V [PS3] (Again, please note that the platform in brackets to the side indicates which version I’ve played or may prefer for one reason or another. That does not mean it’s the only platform to feature jiggle. Also this is not an exhaustive list. I’ve limited to just one entry per series, for instance.)

Joshua Michael French ジョシュア

63,550 Aufrufe • vor 2 Jahren

Prompt: Create a professional Hollywood advertising storyboard sheet for a premium moisturizing face cream commercial, inspired by the visual language of world-class luxury skincare and high-end beauty campaigns, while remaining completely original and brand-neutral. FORMAT & LAYOUT - One large white presentation board - 10 ultra-realistic cinematic storyboard frames arranged in a perfectly aligned 2 × 5 grid - Each frame has a thin, elegant black border - Consistent spacing, precise editorial layout, premium advertising-agency presentation aesthetic - Every frame clearly displays a bold scene number (01–10), a duration timestamp, and a short production caption underneath - Clean typography, subtle black/gray text, sophisticated art-direction notes - No logos, trademarks, brand names, or copyrighted campaign elements - The final image should look like an authentic Hollywood commercial director's storyboard / agency treatment board VISUAL STYLE Ultra-realistic cinematic photography, luxury beauty advertising, photorealistic skin texture, natural pores and fine details, sophisticated beauty lighting, soft diffused highlights, controlled shadows, subtle volumetric light, premium glossy product photography, shallow depth of field, anamorphic cinematic composition, elegant neutral color palette, creamy whites, warm skin tones, subtle champagne highlights, high dynamic range, realistic reflections, polished color grading, 8K-level detail, sophisticated production design. STORYBOARD SEQUENCE — 10 FRAMES 01 — 0:00–0:03 | THE FIRST DROP Extreme macro shot of a crystal-clear water droplet falling onto a pristine cream-colored surface, creating delicate concentric ripples. Luxurious soft lighting, dramatic slow-motion feeling. 02 — 0:03–0:06 | PURE HYDRATION Macro beauty shot of a rich moisturizing cream being elegantly lifted from a premium minimalist glass jar. Silky texture, glossy highlights, luxurious studio lighting. 03 — 0:06–0:09 | TOUCH Close-up of a beautiful adult female model gently applying the cream to her cheek with her fingertips. Natural expression, immaculate but realistic skin, intimate cinematic framing. 04 — 0:09–0:12 | ABSORPTION Ultra-close beauty shot showing the cream melting seamlessly into the skin. Emphasize realistic skin texture, moisture, luminous highlights, and a fresh hydrated appearance. 05 — 0:12–0:15 | HYDRATION GLOW Cinematic portrait of the model beside a softly illuminated window. Her skin appears naturally radiant, supple, fresh, and deeply moisturized. Elegant morning atmosphere. 06 — 0:15–0:18 | THE FORMULA Premium product-science visual: suspended water droplets, translucent botanical-inspired elements, creamy textures, and elegant fluid motion surrounding the face cream jar. Sophisticated, believable cosmetic advertising aesthetic. 07 — 0:18–0:21 | ALL-DAY COMFORT The model outdoors in soft golden-hour light, looking confident and relaxed. Close cinematic framing emphasizes comfortable, hydrated, naturally glowing skin. 08 — 0:21–0:24 | LUMINOUS DETAIL Extreme macro shot of hydrated facial skin with beautifully controlled highlights and realistic pores. Skin looks healthy, smooth, supple, and luminous rather than artificially airbrushed. 09 — 0:24–0:27 | HERO PRODUCT Hero shot of the premium face cream jar centered on a sculptural stone surface, surrounded by subtle water reflections and soft atmospheric mist. Luxury beauty commercial lighting, dramatic but minimal. 10 — 0:27–0:30 | THE FINAL REVEAL Final cinematic composition combining the hero product and the model in the background, softly out of focus. Elegant glowing light, premium minimalist environment, strong visual hierarchy, sophisticated end-card composition with clean negative space for a tagline.

Huma Ai

13,476 Aufrufe • vor 2 Monaten

I spent 48 hours running AI from my phone. Here are 11 things that turned out to be possible and 3 that almost cost me money Forgot my laptop at home and thought the day was lost. Opened a terminal from my phone and decided to see how long I could last Lasted 2 days. Not just lasted but made $840 What works from a phone: 1. Set up Claude Code through SSH in 10 minutes while riding the subway 2. Get Telegram pushes every time a wallet enters a position 3. Copy a trade with 1 tap without taking out my earbuds 4. Launch scripts by voice through Shortcuts 5. Monitor 3 wallets simultaneously without a single lag 6. Get a morning report at 7 AM as a regular message 7. Rebuild the bot when it crashed while sitting in a cab 8. Check PnL without opening a browser 9. Add a new wallet to tracking in 30 seconds 10. Set up auto-copying without confirmation on verified wallets 11. Get a full strategy breakdown of a wallet through Claude Code in a regular chat And here is what almost killed the deposit: 1. My finger slipped and I entered at twice the planned size. Did not notice for 20 minutes. Got lucky that the position ended up in profit but it could have gone very differently 2. My phone died at 2 AM. Missed the exit signal and the position dropped $110 while I slept. By morning I realized that a power bank is just as much a part of the strategy as the bot itself 3. The delay when copying was 40 seconds. On a 15-minute market that is an eternity. The price moved from 8 cents to 23, and instead of a 12x return I got a 4x. Still profit but you feel the difference immediately Total for 48 hours: +$840. Screen time on the phone: 47 minutes. Never needed the laptop The entire time I was following the same wallet. That is the 1 that was sending me signals at 2 AM: The phone turned out to be a fully functional control panel. But this control panel has no safety switch. And that is worth remembering every time you are tapping with 1 hand in the coffee line

I spent 48 hours running AI from my phone. Here are 11 things that turned out to be possible and 3 that almost cost me money Forgot my laptop at home and thought the day was lost. Opened a terminal from my phone and decided to see how long I could last Lasted 2 days. Not just lasted but made $840 What works from a phone: 1. Set up Claude Code through SSH in 10 minutes while riding the subway 2. Get Telegram pushes every time a wallet enters a position 3. Copy a trade with 1 tap without taking out my earbuds 4. Launch scripts by voice through Shortcuts 5. Monitor 3 wallets simultaneously without a single lag 6. Get a morning report at 7 AM as a regular message 7. Rebuild the bot when it crashed while sitting in a cab 8. Check PnL without opening a browser 9. Add a new wallet to tracking in 30 seconds 10. Set up auto-copying without confirmation on verified wallets 11. Get a full strategy breakdown of a wallet through Claude Code in a regular chat And here is what almost killed the deposit: 1. My finger slipped and I entered at twice the planned size. Did not notice for 20 minutes. Got lucky that the position ended up in profit but it could have gone very differently 2. My phone died at 2 AM. Missed the exit signal and the position dropped $110 while I slept. By morning I realized that a power bank is just as much a part of the strategy as the bot itself 3. The delay when copying was 40 seconds. On a 15-minute market that is an eternity. The price moved from 8 cents to 23, and instead of a 12x return I got a 4x. Still profit but you feel the difference immediately Total for 48 hours: +$840. Screen time on the phone: 47 minutes. Never needed the laptop The entire time I was following the same wallet. That is the 1 that was sending me signals at 2 AM: The phone turned out to be a fully functional control panel. But this control panel has no safety switch. And that is worth remembering every time you are tapping with 1 hand in the coffee line

Blaze

93,477 Aufrufe • vor 7 Monaten

All right, future Agents! We’ve got a little mission for you. THUNDER NEEDS A NEW TOY! 😁 This little duck you see with THUNDER? It’s actually a 3D in-game version of my dog, Raven favorite real-life toy 🦆 And it got us thinking… 👉 Let’s add YOUR dog’s favorite toy to BARKOUR. For real. HOW IT WORKS: • Post a photo or video of your dog with their favorite toy (or just the toy itself if you prefer 🧸) • The community votes with likes ❤️ • The toy with the most votes will be recreated in-game for THUNDER 🎁 What the winner AND one lucky voter gets: • A free PC key for BARKOUR • A Special Thanks in the game credits (for you and your dog!) Let’s fill BARKOUR with toys loved by real dogs! 😁 We can’t wait to see what your good boys and girls can’t live without! 😊 Posting and voting lasts till the 10th of January, 9:00 PM CET.

All right, future Agents! We’ve got a little mission for you. THUNDER NEEDS A NEW TOY! 😁 This little duck you see with THUNDER? It’s actually a 3D in-game version of my dog, Raven favorite real-life toy 🦆 And it got us thinking… 👉 Let’s add YOUR dog’s favorite toy to BARKOUR. For real. HOW IT WORKS: • Post a photo or video of your dog with their favorite toy (or just the toy itself if you prefer 🧸) • The community votes with likes ❤️ • The toy with the most votes will be recreated in-game for THUNDER 🎁 What the winner AND one lucky voter gets: • A free PC key for BARKOUR • A Special Thanks in the game credits (for you and your dog!) Let’s fill BARKOUR with toys loved by real dogs! 😁 We can’t wait to see what your good boys and girls can’t live without! 😊 Posting and voting lasts till the 10th of January, 9:00 PM CET.

BARKOUR | Dog Agent Game 🐶 WISHLIST NOW!

12,479 Aufrufe • vor 9 Monaten

I really don't post wins much on this app 🤣🤣 it feels good being low-key. Although, let's doxx this one!. Most of the time, I win big, I reinvest, win again, reinvest. I barely spend on myself much, mostly spend my money helping people, or supporting the needy. It's time for me 😌. Hey NVIDIA GeForce Hey ROG Global I Just slapped a Brand new heavy machine in my bag! One of the most powerful laptops of 2025! Emphasis on BRAND NEW! Introducing, the new owner of the ASUS ROG STRIX G16 2025. SPECS: - Intel Core Ultra 9 275HX Processor - 32GB DDR5 RAM - Nvidia GeForce RTX™ 5080 Dedicated GPU with a massive 16GB DDR7 VRAM - 3TB PCIe 4.0 SSD NVME storage - 24 Cores CPU (16 E-cores + 8 P-cores) - Base Frequency 2.70GHz - Max Turbo Frequency 5.40GHz 6 Million Naira well spent on this bad boy. Now, let's lock-in again and run it up back turbo! I need my $U bag soon enough 🤭. Pitch me on to node running, and prover projects, I'm fully locked in.

🐐𝙲𝚛𝚢𝚙𝚝𝚘𝙳𝚛𝚊𝚐𝚘𝚗

20,703 Aufrufe • vor 1 Jahr

🚀🌟 ALPHA SEASON 4 BLAST-OFF! 🎮 We're giving away AS4 passes to 30 lucky winners to unlock epic rewards & exclusive experiences!💥 3 Easy Steps: 1. 💖 Like & Share this post 2. 🚀 Follow our page 3. 👨‍🚀 Tag 2 of your friends in the comment section Contest ends 7th October 2024, 11PM (GMT+8)! Good luck! 📜 T&C: - Participant must have a KYC account with The Sandbox Game - Participant must not be banned or been flagged for cheating before - Winners will be selected through the raffle system - Winners will be contacted through DM on 8th October 11AM (GMT+8) and must respond with their wallet address and details by 3PM (GMT+8) on the same day - Prizes are non-transferable and cannot be exchanged for cash - The Organiser reserves the right to change, amend, delete or add to these Contest Terms and Conditions without prior notice at any time - Participants agree to be bound to any such changes. - The Organiser’s decision shall be final and binding - No correspondence shall be entertained

🚀🌟 ALPHA SEASON 4 BLAST-OFF! 🎮 We're giving away AS4 passes to 30 lucky winners to unlock epic rewards & exclusive experiences!💥 3 Easy Steps: 1. 💖 Like & Share this post 2. 🚀 Follow our page 3. 👨‍🚀 Tag 2 of your friends in the comment section Contest ends 7th October 2024, 11PM (GMT+8)! Good luck! 📜 T&C: - Participant must have a KYC account with The Sandbox Game - Participant must not be banned or been flagged for cheating before - Winners will be selected through the raffle system - Winners will be contacted through DM on 8th October 11AM (GMT+8) and must respond with their wallet address and details by 3PM (GMT+8) on the same day - Prizes are non-transferable and cannot be exchanged for cash - The Organiser reserves the right to change, amend, delete or add to these Contest Terms and Conditions without prior notice at any time - Participants agree to be bound to any such changes. - The Organiser’s decision shall be final and binding - No correspondence shall be entertained

The Sandbox SEA

56,608 Aufrufe • vor 2 Jahren

we just scaled a B2B SaaS from $0 to $420k ARR in 30 days… and we used ONLY linkedin the most UNTAPPED lead gen platform of 2026 so i just sat down, pressed record, and dropped a 14-minute masterclass going through the ENTIRE GTM system behind how we did this here's what's included: 1. the two-phase framework behind every post we publish 2. exact lead magnet structure that got 6,000 comments from a single post 3. how we repurposed one post across 5 profiles and turned 1,000 comments into 9,000 4. our comment reply script that drives free trials before people even open a resource 5. the DM triage system for handling thousands of conversations at once 6. our conversion architecture inside every lead magnet 7. the hook library with our top performers and why each one worked 8. the profile optimization that took conversions from 2% to 8% 9. the exact content calendar that we followed for 30 straight days 10. the trend monitoring system that let us post within 24 hours of any major launch 11. our email capture play (4,800 subscribers in 30 days) 12. the posting cadence, repurposing schedule, and DM follow-up timing down to the hour plus a bonus 120-day case study where we scaled a different SaaS to €42,975/mo using this same system like + comment "SAAS" and i'll DM you EVERYTHING (must be following + RT for priority access)

paolo trivellato

17,031 Aufrufe • vor 5 Monaten

What if AI football cinema felt like one continuous breath instead of edited cuts? To make cinematic AI storytelling believable, consistency is everything: the same ground, light, and spatial flow from start to finish. Created using RoboNeo Agent Teams. This style builds a single visual world where movement feels real, not stitched together. It’s about continuity, control, and letting the final moment speak for itself. #RoboNeo Prompt: Cinematic 15-second video. Photorealistic, premium production quality. Natural skin tones, realistic facial detail, editorial soft lighting. Style: luxury FIFA football commercial meets high-fashion sports film. IMPORTANT DIRECTIVE: Follow the exact sequence of actions, pacing, and cinematic progression defined in the storyboard structure (9-panel flow: City Descent → Arrival → Lock-in → Run → Skill Display → Attacking Space → Time Stops → Strike → Glory). Maintain identical character, wardrobe, environment, and continuous spatial geography across all shots. CHARACTER (CONSISTENT THROUGHOUT): Young woman, effortlessly beautiful, athletic build, soft natural makeup, expressive eyes, full soft lips. High ponytail with loose face-framing strands. Neon-green loose jersey-style football shirt, relaxed fit. White sneakers. Same identity in every frame. LOCATION (STRICT CONTINUITY RULE): Entire sequence occurs in a single continuous environment: Downtown Vancouver FIFA Fan Zone Hybrid Street Pitch Corridor. A real city street permanently transformed into a seamless playable football pitch lane. Asphalt fused with FIFA turf and official pitch markings. LED-lit professional street football goal remains fixed at the far end and visible throughout all scenes. No scene leaves this environment. STORYBOARD-DRIVEN SEQUENCE (FOLLOW EXACT FLOW): SCENE FLOW MUST MATCH STORYBOARD 1–9 STRUCTURE SCENE 1 [0–2s] — CITY DESCENT (Storyboard Panel 1) Ultra-wide aerial drone shot descending through downtown Vancouver at golden hour. FIFA World Cup 2026 banners, Canadian flags, BC Place glowing in distance. Camera drops into immersive fan-zone corridor. SCENE 2 [2–3s] — ARRIVAL (Storyboard Panel 2) Football rolls naturally across hybrid pitch corridor and stops at her feet. She acknowledges it. Goal visible far ahead in depth. SCENE 3 [3–4s] — LOCKED IN (Storyboard Panel 3) Close-up: half-second direct eye contact. Calm intensity. Breath control. Stillness before motion. SCENE 4 [4–7s] — THE RUN (Storyboard Panel 4) Ground-level tracking shot. Fast controlled dribbling through corridor. Crowd on both sides reacts. Momentum builds toward goal. SCENE 5 [7–9s] — SKILL DISPLAY (Storyboard Panel 5) Elastico, quick feint, rainbow flick combination in motion. Clean execution, fluid continuity, no interruption in speed. SCENE 6 [9–10s] — ATTACKING SPACE (Storyboard Panel 6) Overhead cinematic drone angle. Pitch markings guide visual line directly to goal. Defender pressure implied via crowd movement. SCENE 7 [10–11s] — TIME STOPS (Storyboard Panel 7) Everything slows. Ball lifted into air. 360° orbit camera. Suspended cinematic pause before strike. SCENE 8 [11–13s] — THE STRIKE (Storyboard Panel 8) ANTHEM BEGINS RISING. Perfectly executed bicycle kick. Camera transitions into ball-follow perspective immediately after contact. Ultra-realistic physics, spinning ball traveling down illuminated corridor. SCENE 9 [13–15s] — GLORY (Storyboard Panel 9) Ball hits top corner of LED-lit goal with realistic net ripple. Stadium explosion of sound. Fireworks subtly glow above Vancouver skyline. Crowd erupts. Final hero shot: she stands calmly in center of pitch corridor under blended golden-hour + stadium floodlights. Confident, minimal smile. FIFA World Cup 2026 gold crest fades in. AUDIO DESIGN: 0–3s: city ambience + crowd build 3–9s: rhythmic pulse + rising tension 9–11s: near silence + heartbeat tension 11–15s: anthem drop at strike + stadium roar + celebration surge CINEMATIC STYLE NOTES: Ultra-photorealistic FIFA broadcast aesthetic, luxury sports-fashion commercial tone, handheld + drone hybrid cinematography, shallow depth of field, anamorphic lens flares, subtle film grain, warm cinematic color grading, seamless spatial continuity, high-end global sports campaign finish. Aspect ratio 16:9.

What if AI football cinema felt like one continuous breath instead of edited cuts? To make cinematic AI storytelling believable, consistency is everything: the same ground, light, and spatial flow from start to finish. Created using RoboNeo Agent Teams. This style builds a single visual world where movement feels real, not stitched together. It’s about continuity, control, and letting the final moment speak for itself. #RoboNeo Prompt: Cinematic 15-second video. Photorealistic, premium production quality. Natural skin tones, realistic facial detail, editorial soft lighting. Style: luxury FIFA football commercial meets high-fashion sports film. IMPORTANT DIRECTIVE: Follow the exact sequence of actions, pacing, and cinematic progression defined in the storyboard structure (9-panel flow: City Descent → Arrival → Lock-in → Run → Skill Display → Attacking Space → Time Stops → Strike → Glory). Maintain identical character, wardrobe, environment, and continuous spatial geography across all shots. CHARACTER (CONSISTENT THROUGHOUT): Young woman, effortlessly beautiful, athletic build, soft natural makeup, expressive eyes, full soft lips. High ponytail with loose face-framing strands. Neon-green loose jersey-style football shirt, relaxed fit. White sneakers. Same identity in every frame. LOCATION (STRICT CONTINUITY RULE): Entire sequence occurs in a single continuous environment: Downtown Vancouver FIFA Fan Zone Hybrid Street Pitch Corridor. A real city street permanently transformed into a seamless playable football pitch lane. Asphalt fused with FIFA turf and official pitch markings. LED-lit professional street football goal remains fixed at the far end and visible throughout all scenes. No scene leaves this environment. STORYBOARD-DRIVEN SEQUENCE (FOLLOW EXACT FLOW): SCENE FLOW MUST MATCH STORYBOARD 1–9 STRUCTURE SCENE 1 [0–2s] — CITY DESCENT (Storyboard Panel 1) Ultra-wide aerial drone shot descending through downtown Vancouver at golden hour. FIFA World Cup 2026 banners, Canadian flags, BC Place glowing in distance. Camera drops into immersive fan-zone corridor. SCENE 2 [2–3s] — ARRIVAL (Storyboard Panel 2) Football rolls naturally across hybrid pitch corridor and stops at her feet. She acknowledges it. Goal visible far ahead in depth. SCENE 3 [3–4s] — LOCKED IN (Storyboard Panel 3) Close-up: half-second direct eye contact. Calm intensity. Breath control. Stillness before motion. SCENE 4 [4–7s] — THE RUN (Storyboard Panel 4) Ground-level tracking shot. Fast controlled dribbling through corridor. Crowd on both sides reacts. Momentum builds toward goal. SCENE 5 [7–9s] — SKILL DISPLAY (Storyboard Panel 5) Elastico, quick feint, rainbow flick combination in motion. Clean execution, fluid continuity, no interruption in speed. SCENE 6 [9–10s] — ATTACKING SPACE (Storyboard Panel 6) Overhead cinematic drone angle. Pitch markings guide visual line directly to goal. Defender pressure implied via crowd movement. SCENE 7 [10–11s] — TIME STOPS (Storyboard Panel 7) Everything slows. Ball lifted into air. 360° orbit camera. Suspended cinematic pause before strike. SCENE 8 [11–13s] — THE STRIKE (Storyboard Panel 8) ANTHEM BEGINS RISING. Perfectly executed bicycle kick. Camera transitions into ball-follow perspective immediately after contact. Ultra-realistic physics, spinning ball traveling down illuminated corridor. SCENE 9 [13–15s] — GLORY (Storyboard Panel 9) Ball hits top corner of LED-lit goal with realistic net ripple. Stadium explosion of sound. Fireworks subtly glow above Vancouver skyline. Crowd erupts. Final hero shot: she stands calmly in center of pitch corridor under blended golden-hour + stadium floodlights. Confident, minimal smile. FIFA World Cup 2026 gold crest fades in. AUDIO DESIGN: 0–3s: city ambience + crowd build 3–9s: rhythmic pulse + rising tension 9–11s: near silence + heartbeat tension 11–15s: anthem drop at strike + stadium roar + celebration surge CINEMATIC STYLE NOTES: Ultra-photorealistic FIFA broadcast aesthetic, luxury sports-fashion commercial tone, handheld + drone hybrid cinematography, shallow depth of field, anamorphic lens flares, subtle film grain, warm cinematic color grading, seamless spatial continuity, high-end global sports campaign finish. Aspect ratio 16:9.

Shami

63,330 Aufrufe • vor 4 Monaten

$[Backpropagation] by Hand✍️ [1] Forward Pass ↳ Given a multi layer perceptron (3 levels), an input vector X, predictions Y^{Pred} = [0.5, 0.5, 0], and ground truth label Y^{Target} = [0, 1, 0]. [2] Backpropagation ↳ Insert cells to hold our calculations. [3] Layer 3 - Softmax (blue) ↳ Calculate ∂L / ∂z3 directly using the simple equation: Y^{Pred} - Y^{Target} = [0.5, -0.5, 0]. ↳ This simple equation is the benefit of using Softmax and Cross Entropy Loss together. [4] Layer 3 - Weights (orange) & Biases (black) ↳ Calculate ∂L / ∂W3 and ∂L / ∂b3 by multiplying ∂L / ∂z3 and [ a2 | 1 ]. [5] Layer 2 - Activations (green) ↳ Calculate ∂L / ∂a2 by multiplying ∂L / ∂z3 and W3. [6] Layer 2 - ReLU (blue) ↳ Calculate ∂L / ∂z2 by multiplying ∂L / ∂a2 with 1 for positive values and 0 otherwise. [7] Layer 2 - Weights (orange) & Biases (black) ↳ Calculate ∂L / ∂W2 and ∂L / ∂b2 by multiplying ∂L / ∂z2 and [ a1 | 1 ]. [8] Layer 1 - Activations (green) ↳ Calculate ∂L / ∂a1 by multiplying ∂L / ∂z2 and W2. [9] Layer 1 - ReLU (blue) ↳ Calculate ∂L / ∂z1 by multiplying ∂L / ∂a1 with 1 for positive values and 0 otherwise. [10] Layer 1 - Weights (orange) & Biases (black) ↳ Calculate ∂L / ∂W1 and ∂L / ∂b1 by multiplying ∂L / ∂z1 and [ x | 1 ]. [11] Gradient Descent ↳ Update weights and biases (typically a learning rate is applied here). 💡 Matrix Multiplication is All You Need: Just like in the forward pass, backpropagation is all about matrix multiplications. You can definitely do everything by hand as I demonstrated in this exercise, albeit slow and imperfect. This is why GPU's ability to multiply matrices efficiently plays such an important role in the deep learning evolution. This is why NVIDIA is now close to $1 trillion in valuation. 💡Exploding Gradients: We can already see the gradients are getting larger as we back-propagate up, even in this simple 3-layer network. This motivates using methods like skip connections to handle exploding (or diminishing) gradients as in the ResNet. I did the calculations entirely by hand. Please let me know if you spot any error or have any questions!$

[Backpropagation] by Hand✍️ [1] Forward Pass ↳ Given a multi layer perceptron (3 levels), an input vector X, predictions Y^{Pred} = [0.5, 0.5, 0], and ground truth label Y^{Target} = [0, 1, 0]. [2] Backpropagation ↳ Insert cells to hold our calculations. [3] Layer 3 - Softmax (blue) ↳ Calculate ∂L / ∂z3 directly using the simple equation: Y^{Pred} - Y^{Target} = [0.5, -0.5, 0]. ↳ This simple equation is the benefit of using Softmax and Cross Entropy Loss together. [4] Layer 3 - Weights (orange) & Biases (black) ↳ Calculate ∂L / ∂W3 and ∂L / ∂b3 by multiplying ∂L / ∂z3 and [ a2 | 1 ]. [5] Layer 2 - Activations (green) ↳ Calculate ∂L / ∂a2 by multiplying ∂L / ∂z3 and W3. [6] Layer 2 - ReLU (blue) ↳ Calculate ∂L / ∂z2 by multiplying ∂L / ∂a2 with 1 for positive values and 0 otherwise. [7] Layer 2 - Weights (orange) & Biases (black) ↳ Calculate ∂L / ∂W2 and ∂L / ∂b2 by multiplying ∂L / ∂z2 and [ a1 | 1 ]. [8] Layer 1 - Activations (green) ↳ Calculate ∂L / ∂a1 by multiplying ∂L / ∂z2 and W2. [9] Layer 1 - ReLU (blue) ↳ Calculate ∂L / ∂z1 by multiplying ∂L / ∂a1 with 1 for positive values and 0 otherwise. [10] Layer 1 - Weights (orange) & Biases (black) ↳ Calculate ∂L / ∂W1 and ∂L / ∂b1 by multiplying ∂L / ∂z1 and [ x | 1 ]. [11] Gradient Descent ↳ Update weights and biases (typically a learning rate is applied here). 💡 Matrix Multiplication is All You Need: Just like in the forward pass, backpropagation is all about matrix multiplications. You can definitely do everything by hand as I demonstrated in this exercise, albeit slow and imperfect. This is why GPU's ability to multiply matrices efficiently plays such an important role in the deep learning evolution. This is why NVIDIA is now close to $1 trillion in valuation. 💡Exploding Gradients: We can already see the gradients are getting larger as we back-propagate up, even in this simple 3-layer network. This motivates using methods like skip connections to handle exploding (or diminishing) gradients as in the ResNet. I did the calculations entirely by hand. Please let me know if you spot any error or have any questions!

Tom Yeh

64,783 Aufrufe • vor 2 Jahren

As a graphics engine coder I think when you look at a flickering bug like this one in the video below it’s not immediately obvious what is going on. The key here is observation - to study this flickering/bugged render carefully - what do we see? Firstly for me it was very obvious that nearly all of the scene shadows were flashing on and off - but (but!) there was a secondary issue where some buildings and parts of the sky were also flashing purple. Hmmmm. Interesting. I initially thought then this might be two separate bugs - but because the sky purple element could only based on full screen post fx and not 3D rendering I looked at this first with a few GPU captures to step through all our post processing to find the rendering stage which made these pixels turn purple: When I did this I found the colour 3D texture LUT grading that makes our different biomes have unique colour palettes was going very wrong - colours near 0 or 1 were wrapping and making the purple elements that we see in the said sky and base parts. The only way this could happen was if the texture was corrupt (which it was not) or if the 3D texture sampling was wrapping and not clamped as intended. That was the Eureka moment - because if the post fx had the wrong texture sampler then the disappearing shadows which also require an exact texture sampler for comparing depth might be also wrong because of the same kind of texture sampling issue! So with this idea that the engine was using the wrong texture samplers, but only in very high draw call scenes like the big base here I the looked at some engine limits and found the bug very quickly - a circular dx12 descriptor buffer for samplers running out over multiple frames, reusing the wrong data for new scenes inflight. Hence the flickering, as the GPU randomly got wrong samplers for some post textures or shadow depth. Easy to fix with triple limits for future expansion and also adding an assert/debug spam in case this limit is ever reached again - QA testers would see this message and report if they ever saw a flicker with this style of bug. My bug and my bad from 2017 porting NMS to DX12 without foreseeing how massively complex bases and our game would grow.

As a graphics engine coder I think when you look at a flickering bug like this one in the video below it’s not immediately obvious what is going on. The key here is observation - to study this flickering/bugged render carefully - what do we see? Firstly for me it was very obvious that nearly all of the scene shadows were flashing on and off - but (but!) there was a secondary issue where some buildings and parts of the sky were also flashing purple. Hmmmm. Interesting. I initially thought then this might be two separate bugs - but because the sky purple element could only based on full screen post fx and not 3D rendering I looked at this first with a few GPU captures to step through all our post processing to find the rendering stage which made these pixels turn purple: When I did this I found the colour 3D texture LUT grading that makes our different biomes have unique colour palettes was going very wrong - colours near 0 or 1 were wrapping and making the purple elements that we see in the said sky and base parts. The only way this could happen was if the texture was corrupt (which it was not) or if the 3D texture sampling was wrapping and not clamped as intended. That was the Eureka moment - because if the post fx had the wrong texture sampler then the disappearing shadows which also require an exact texture sampler for comparing depth might be also wrong because of the same kind of texture sampling issue! So with this idea that the engine was using the wrong texture samplers, but only in very high draw call scenes like the big base here I the looked at some engine limits and found the bug very quickly - a circular dx12 descriptor buffer for samplers running out over multiple frames, reusing the wrong data for new scenes inflight. Hence the flickering, as the GPU randomly got wrong samplers for some post textures or shadow depth. Easy to fix with triple limits for future expansion and also adding an assert/debug spam in case this limit is ever reached again - QA testers would see this message and report if they ever saw a flicker with this style of bug. My bug and my bad from 2017 porting NMS to DX12 without foreseeing how massively complex bases and our game would grow.

Martin Griffiths

72,883 Aufrufe • vor 2 Jahren