An infinite shared pixel art canvas

Hacker News

This is a fun project I’ve been slowly improving over the past few years. It started as a fun technical experiment and has grown into a canvas where over 300 million pixels have been placed, one pixel at a time. It’s a single realtime canvas shared by everyone around the world. And when I say it’s global, I truly mean that. Communities have popped up everywhere from Germany to Japan to Azerbaijan. It even had quite the following in China before it got banned by the Chinese firewall. I call it an “infinite canvas”, but of course, infinite values don’t exist in computing. See if you can find the edge ;)

Visit product View on Hacker NewsOct 11, 2024

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Actual performance

6points

3comments

Did not reach leaderboard

Launch Intel predictions

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Hacker NewsStrong engagement from HN community · Strong signals: exist, io · Missing: https docs, excited, just released

78%78% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

Product HuntOn track for Day 1 leaderboard · Strong signals: single · Missing: mac, agents, macos

68%68% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

Indie HackersFits the IH revenue-focused audience · Strong signals: started · Missing: supports, reddit linkedin, podcasting

68%68% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive

48%48% predicted probability of success on AppSumo, based on ML models trained on real launch data.

TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal

34%34% predicted probability of success on TrustMRR, 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.

BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto

3%3% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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