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A simple Italian to English translator written in C (Hello World joke)
Hacker NewsA simple Italian to English translator written in C (Hello World joke)
#include <stdio.h> int main() { puts((char[]){ ~-~-~-~-~-~-~-~-~-~-~- 'S', -~-~-~-~ 'a', 'l', ~-~-~-~-~-~-~-~-~-~- 'v', -~-~-~-~-~-~-~-~-~-~ 'e', ',', ' ', -~-~-~-~-~-~-~-~-~-~ 'M', 'o', -~-~-~-~ 'n', -~-~-~-~-~-~-~-~ 'd', ~-~-~-~-~-~-~-~-~-~-~- 'o', '!', 0}); }
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5points
3comments
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AppSumoStrong fit for a featured deal · Missing: plus, platform, intuitive66%66% predicted probability of success on AppSumo, 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, podcasting63%63% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: io · Missing: https docs, excited, just released60%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.
TrustMRRFits verified-revenue profile · Missing: mobile apps, ios, personal54%54% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto38%38% predicted probability of success on BetaList, based on ML models trained on real launch data.
Product HuntUnlikely to reach the leaderboard · Missing: mac, agents, macos38%38% 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, revenue16%16% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
Incorrect prediction on native model
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