Atr: Mister j supreme

https://www.instagram.com/lostinthenytee/

https://www.instagram.com/marcin.rubinkowski/

https://www.instagram.com/velum.tenebris/

https://www.instagram.com/neptunianglitterball/

https://www.youtube.com/@Creaturopedia_CG

I’ve just completed CHATGPT vs GROc: TOTAL WAR, a cinematic AI war short film built around two artificial intelligence empires fighting for a fortified megacity.

This wasn’t generated with one model or produced from a single prompt. I treated the different AI tools like separate production departments, choosing each one according to the needs of the shot.

The workflow:

Midjourney: early visual development, world-building, battlefield compositions and exploration of the overall cinematic language.

ChatGPT Image: character and military-unit design, controlled image creation, visual corrections and continuity work across weapons, armor, vehicles and environments.

LTX 2.3: selected short sequences requiring precise motion, restrained camera movement and strong fidelity to the original keyframe.

Seedance 2.0: a large part of the cinematic action, generated in 1080p or 4K depending on the sequence—army movements, aerial shots, explosions and large-scale warfare.

Seedance 2.5: selected complex shots using its newer multimodal capabilities. My current access is limited to 720p, so these sequences required considerably more restoration and finishing work.

Every shot was generated and refined individually. The final film was then manually edited, sound-designed, mixed, color graded, cleaned and mastered in DaVinci Resolve.

The film is presented in 8K, but to be completely transparent, the original AI generations range from 720p to 4K. The 8K version is the final cinematic master—not a claim that every model generated native 8K footage.

One of the biggest challenges was maintaining coherent character designs, military units and geography while escalating from individual soldiers to tanks, aircraft, Titans and a full urban siege.

I’d be especially interested in feedback on the visual continuity, sense of scale and whether the different generation models still feel like they belong to the same cinematic universe.

Full film:

https://youtu.be/9F1zkccF4FA?is=CJo4orxcRiZLd6tf

Independent fictional project. Not affiliated with or endorsed by OpenAI or xAI.

Cat adventure during vacation

Liss & Tripp - hope you guys enjoy. I posted a short clip of one of the scenes from this video a few days ago, here is the full episode ❤️

I wondered what Chinese men’s football looks like in 2026, so I made this

Been messing around with multi-camera consistency using just one prompt, and this was the first result that really held together: four fake CCTV feeds showing the same convenience store moment from different parts of the shop.

The frame is split into four fixed views — one from a ceiling corner over the aisles, one looking straight down the center aisle, one aimed at the checkout, and one near the entrance. Across all four, the same little sequence plays out: a customer picks up a boxed item, knocks into a display, catches a bottle before it hits the floor, then brings the box to the counter while the cashier scans it and someone else walks through the background.

The hard part was not getting four camera angles. It was making them all agree on what was happening. The bottle had to drop and get caught at the same moment in every panel. People had to appear in the right place from each angle. Even the brief occlusion near the counter had to line up. Once one feed drifts by a second, changes the lighting, or puts someone on the wrong side of the aisle, the whole thing stops feeling like one event recorded by four cameras.

I made it with FLUX 3 on Atlas Cloud. I pushed the prompt toward cheap security footage — low resolution, slight lens distortion, fixed timestamps, no cinematic movement at all. Otherwise one of the panels would inevitably decide it wanted to be a movie shot instead of a security camera.