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An otherworldly 3D scene in 16 kB of JavaScript

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An otherworldly 3D scene in 16 kB of JavaScript

(trigger warning: I know HN isn't keen on anything related to crypto, and this is crypto-art.) Over the course of a couple of months this year I learned path tracing, signed distance fields, GLSL coding, and compacting JavaScript using a coding style you should never use in real life. But this all resulted in a system that can create "photo-realistic" 3D images of an otherworldly scene in 16000 bytes, no dependencies. Monte Carlo path tracing is a very interesting technique, albeit very slow to render. It still amazes me how you can get a huge amount of variation and realistic lighting from a tiny amount of code that basically simulates millions of light rays bouncing around in a mathematically defined scene with some randomness applied.

Visit productView on Hacker NewsDec 30, 2024
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Product HuntOn track for Day 1 leaderboard · Strong signals: tiny, using, coding · Missing: mac, agents, macos
76%76% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
71%71% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: 000, io · Missing: https docs, excited, just released
55%55% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
TrustMRRLess likely to generate early MRR · Strong signals: month · Missing: mobile apps, ios, personal
39%39% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
39%39% predicted probability of success on AppSumo, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Strong signals: crypto, real life · Missing: web3, chat, cryptocurrency
24%24% predicted probability of success on BetaList, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
18%18% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

Incorrect prediction on native model

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