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isometric.nyc/snow

isometric.nyc/snow

by cannoneyed·Feb 23, 2026·10 points·2 comments

AI Analysis

●●SolidEye CandyRabbit HoleWizardry

Beautiful isometric snow effect, but it's a visual novelty—art project, not a tool or product.

Strengths
  • Data normalization + crosshatch water pattern teach the model structure instead of hallucinating—clever ML craft.
  • Modal inference scaling allowed 10s of thousands of tiles in hours; smart infrastructure choice.
Weaknesses
  • No interactive features, API, or extensibility—purely a static visual artifact and art project.
  • Seasonal gimmick with no utility or reuse; 'wintry mix' positioning limits durability.
Category
Target Audience

Generative art enthusiasts, map design nerds, NYC visual culture fans

Post Description

Hey HN,

As NYC wakes up to the largest blizzard in years, I’d like to share [isometric.nyc/snow](http://isometric.nyc/snow) - a wintry mix of the original isometric pixel map of NYC .

This work builds on the original isometric.nyc ideas but aims to increasingly automate the process of generating the tiled images. I’ve written up a follow-up addendum at [cannoneyed.com/projects/isometric-nyc\#snow](http://cannoneyed.com/projects/isometric-nyc#snow) that describes some of this work, but the tl;dr is:

* ensuring that training data and generations are color balanced / normalized goes a long way for consistency (duh) * augmenting water with a crosshatch pattern allowed the model to learn what it was instead of hallucinating (interesting!) * dramatically increasing inference throughput on [modal.com](http://modal.com) meant I could generate 10s of thousands of tiles in a few hours at very little cost, allowing me to experiment much more rapidly

This project continues to be a lot of fun, but I’m now mostly focusing on the agentic workflows that power this kind of ambitious generation at scale. Can’t wait to share more soon.

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