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My entry for the Games with Rive challenge, finally! I was super happy to put my game dev skills to use.
⚔️ Battle Stride — a card-based dungeon crawler where you lay down path cards to guide a soldier through procedurally generated dungeons, battle enemies, and collect relics.
I used Rive's state machines to drive all the character and card animations, data binding to keep the HUD in sync with game state, and listeners for interactive hover and click effects on the cards.
All the art—characters, cards, tiles, and relics—was hand-drawn and animated in Rive's editor using vector shapes, then exported as lightweight files for the web.
Audio events in the state machine handle combat and pickup sounds. The whole thing runs in the browser with lightweight vector exports.
🕹️ Play it here: https://battle-stride.netlify.app/
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Lately I've recognized this direction on the rise and been inspired to create a collection of 18 images blending the Classical Art - Renaissance oil painting mastery with digital pixel/ASCII aesthetics, Classcii. It is a mix of centuries, a modernized and futuristic direction of the classic.
Each image is crafted around a specific tension, the classical figure or scene rendered in full oil mastery, while the digital/ASCII layer intrudes at a specific point.
Using the @Contra Labs ecosystem to choose the most adequate Ai models from the Creative Arena Leaderboard, I wanted to briefly share my personal taste and evaluation on the outputs these models generated, based on the benhchmark methodology.
For the imagery references I used Seedream 5 Lite and Google Nano Banana 2, whereas for the Image to Video I used Kling 3.0 and Veo 3.1 Fast.
In terms of Visual quality & aesthetics overall I would rank them fairly simillar with Seedream having a slight edge on the composition, specfically achieving more symmetrical outcomes featuring center alignment and a better use of whitespace, opposed to Nano Banana 2 where the use of rule of thirds is more prominent, making it visually in comparison less balanced.
Considering the Prompt adherence & accuracy, I find both models very much aligned, having Nano Banana 2 more intensified use of asscii / pixels across all outcomes, which according to my minimal taste I would rank this a weakness rather than a strong side.
Finally, in terms of Motion Realism I would unanimously rank Kling 3.0 as the better option here, considering the fluidness and physics consistency among majority of the elements in the reference. Additional advantage will be the ability to perform better at no prompt insertion compared to Veo 3.1 fast.
You can download the collection here.
Super work
Silicard Network is a collection of digital operatives set in REI III, a retro-sci-fi world where megacorporations, surveillance infrastructure, and underground factions compete for control of the last functioning city on the planet: Metroplex.
Each character is built as an operative dossier, AI-generated artwork, editorial visual identity, original lore, and presentation materials across multiple formats: character sheet, front card, and video post. The aesthetic draws from classic retro-sci-fi iconography and analog tech design, rendered through a sharp red, black, and orange visual language.
SIGMA is the second operative released in the collection. A signal breach specialist working for the Hardlink faction, his role is to force open temporary corridors through Metroplex's surveillance and control networks, drawing system attention away from physical runners on the ground. The work is short, precise, and physically punishing, with hard limits before his own body starts to fail.
Recently, something has changed. The city's infrastructure has begun adapting to his methods, anticipating breach patterns that should be untraceable. In REI III, when a system starts to learn, the operative who taught it becomes the next target.
Silicard Network is a Silica Graphics project, worldbuilding, lore, and character design built with AI.
Nice 👍
The Vehicle HMI with Rive Challenge is officially wrapped!
Big shoutout to everyone who participated, liked, commented, shared, and scrolled through. 🙌
Congratulations to the winners:
#1 - Paweł Andrzejewski: Submission
#2 - Ian Sterling: Submission
#3 - Javier: Submission
Excited to see you all at the next one!
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