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Chess on a Donut/Torus and Deep-Dive

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Chess on a Donut/Torus and Deep-Dive

Hey there! I just finished a youtube video explaining our donut chess in detail: https://youtu.be/iRcfHCPFgkM So I thought it'd be cool to show it off here too- it can be played around with at mchess.io/donut - you can also set up an AI or online game on the site. This is all indie dev work from a couple friends and myself.

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Launch Intel predictions

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TrustMRRFits verified-revenue profile · Strong signals: video · Missing: mobile apps, ios, personal
52%52% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
Product HuntUnlikely to reach the leaderboard · Strong signals: plain · Missing: mac, agents, macos
44%44% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
42%42% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: ide, io · Missing: https docs, excited, just released
35%35% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting
32%32% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
19%19% 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
19%19% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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