"3D" Pixel Canvas on Twitch

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I see submissions of people trying a creative take on Twitch here every now and then (mostly using AI or procedural content), so I thought I might as well post a little project I did two days ago. Maybe it inspires someone to do something in a similar fashion. Inspired by things like DrawBall, r/place or the recent rise of Wplace I decided to do something similar, but as a stream on Twitch. And I took the word "canvas" quite literally. You can draw single pixels using the chat. How it works exactly is in the channel description. Well, that's basically all to it. https://www.twitch.tv/canvasplace If anything is noteworthy about it it's probably that I made this using Blender and Godot, which are both excellent pieces of software that are frequently featured on HN. The Twitch integration I've done through Twitch' recent EventSub Websocket API, entirely in GDscript. Repo soon! That's it. If this gives someone else a couple of seconds of entertainment it was probably worth the evening I spent on it already. :) Since it's user generated content (which WILL need moderation) the stream will be offline at around Central European sleepy times. It will be shut down completely eventually if it dies out, or I put in more effort if there's people interested in it in the long run. Either works for me.

Visit product View on Hacker NewsAug 31, 2025

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

78%78% 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

74%74% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

60%60% 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 · Missing: mobile apps, ios, personal

42%42% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

27%27% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue

11%11% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

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

0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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