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The Probability Times

Hacker News

The Probability Times

Hey HN! The idea for this started when I came across the election forecast of FiveThirthyEight [1]. They show a 1000 different possible election outcomes - each one possible. In this newspaper homepage, I try to turn these simulations into reality by feeding AI with as much detailed information about a simulation as I can (e.g. voting results per state). See source code here [2]. The whole process is explained in more depth in my blog post: https://nerology.substack.com/p/how-i-made-the-probability-t... [1] https://projects.fivethirtyeight.com/2024-election-forecast/ [2] https://gitlab.com/NeroVanbiervliet/the-probability-times/-/...

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Indie HackersFits the IH revenue-focused audience · Strong signals: started · Missing: supports, reddit linkedin, podcasting
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best fitHighest predicted score across all platforms for this description.
Product HuntUnlikely to reach the leaderboard · Strong signals: new, code, plain · Missing: mac, agents, macos
45%45% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal
43%43% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: ide, 000, io · Missing: https docs, excited, just released
40%40% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
32%32% 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
12%12% 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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