Story Generator

Hacker News

Story Generator

Hi everyone! Want to share something I'm working on. Here is the brief description: From a single text prompt, craft dynamic worlds (both fictional and real-life, of any kind) filled with interacting NPCs pursuing goals, and control (human-in-the-loop) their behaviour and world state in real-time. Text-to-image to visualise every single step of change in the world's and NPC's state. My main goal was to check if it's possible to use LLMs (GPT-4 currently) to make characters interact with each other but in the end, it ended up with a neat little app where users can interfere with NPC's (and world) state, guiding the story the way they like, step by step. Would love to see someone using it!

Visit product View on Hacker NewsJan 30, 2024

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Actual performance

5points

Did not reach leaderboard

Launch Intel predictions

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting

86%86% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

Product HuntOn track for Day 1 leaderboard · Strong signals: user, visual, single · Missing: mac, agents, macos

86%86% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

AppSumoStrong fit for a featured deal · Strong signals: users · Missing: plus, platform, intuitive

50%50% predicted probability of success on AppSumo, based on ML models trained on real launch data.

TrustMRRLess likely to generate early MRR · Strong signals: users, way · Missing: mobile apps, ios, personal

46%46% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: io · Missing: https docs, excited, just released

45%45% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue

15%15% 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

0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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