An

An AI-art, Jackbox-like multiplayer game

Hacker News

An AI-art, Jackbox-like multiplayer game

Dallestrations is like a mix of Drawful and the game telephone. Each player enters a prompt which an AI then draws. Then another player will guess what prompt generated that image. Then the AI draws that guess and so on. At the end players can see how consistent each prompt stayed throughout the rounds. Here are the results from an example game https://dallestrations.herokuapp.com/ede93e19-ecb8-4d91-b973... . Actually uses stable diffusion rather than Dalle-2

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Actual performance

1points
Did not reach leaderboard

Launch Intel predictions

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TrustMRRFits verified-revenue profile · Missing: mobile apps, ios, personal
60%60% predicted probability of success on TrustMRR, 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, podcasting
55%55% 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 released
51%51% 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
34%34% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Product HuntUnlikely to reach the leaderboard · Missing: mac, agents, macos
29%29% 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
17%17% 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
8%8% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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