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Adventures in UTM – Busy Beaver in under 5–10 mins

Hacker News

Adventures in UTM – Busy Beaver in under 5–10 mins

Explorations in geometric computation and dimensional math. This demo runs Busy Beaver 5 and 6 through a CPU-only simulation using a custom logic layer (ZerothInit), written in both Python and Odin. No GPU. No external libraries. Just raw logic and branch evaluation. Repo: https://github.com/ElSolem/al_dara_ia/blob/main/math/busybea... https://github.com/ElSolem/al_dara_ia/blob/main/math/busybea... https://github.com/ElSolem/al_dara_ia/blob/main/math/busybea...

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Actual performance

2points
2comments
Did not reach leaderboard

Launch Intel predictions

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Hacker NewsMay not resonate with HN audience · Strong signals: lua, io · Missing: https docs, excited, just released
48%48% 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
46%46% 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
44%44% 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
44%44% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Product HuntUnlikely to reach the leaderboard · Strong signals: using · Missing: mac, agents, macos
40%40% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
14%14% 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
7%7% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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