Finite Capacity-Based System – Breaking the Infinite Illusion

Hacker News

Infinity has long been the silent assumption in mathematics, economics, religion, and computing. Our new blog post challenges this dogma by presenting a finite approach built entirely from first principles—an alternative that sidesteps the endless errors of infinite assumptions and exposes the Matrix of our societal constructs. This isn’t just about better software; it’s about rethinking the very frameworks that govern our world. What do you think happens when we finally confront the illusion of infinity in everything we build? https://voids.blog/2025/02/14/breaking-infinitys-grip-the-fi... https://github.com/probabilistic-minds-consortium/finite-cap...

Visit product View on Hacker NewsFeb 14, 2025

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

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

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

62%62% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

58%58% 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

47%47% 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

33%33% 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

15%15% 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

2%2% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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