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Each country as a Pokemon, using Stable Diffusion

Hacker News

Each country as a Pokemon, using Stable Diffusion

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Actual performance

60points
21comments
Made the leaderboard

Launch Intel predictions

Analyze your own launch →
BetaListSuited for BetaList early-adopters · Missing: web3, chat, crypto
73%73% predicted probability of success on BetaList, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
Hacker NewsStrong engagement from HN community · Strong signals: io · Missing: https docs, excited, just released
64%64% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal
50%50% 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
49%49% 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
44%44% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting
36%36% 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
24%24% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

Correct prediction on native model

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