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Create a Children's book with AI – with illustrations

Hacker News

Create a Children's book with AI – with illustrations

Hey together with wife we took part in AssemblyAI hackathon and although we didn't win we felt good enough about our inital MVP that we took it a bit further. You can describe your characters and give a title and however long/detailed description you want, the gpt-3 will generate a children's story from it, dall-e will generate images. Images are postprocessed with stable-diffusion custom model (for stylisation) and that's the final result. It's still early as it was done in about 2 weeks, but I count on your feedback. I am software engineer and did basically all of the engineering work myself. Feel free to ask question regarding implementation plans, etc. cannot wait to learn what you think. I'll appriciate any feedback.

Visit product View on Hacker NewsDec 22, 2022

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

80%80% 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: model · Missing: mac, agents, macos

59%59% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

Hacker NewsStrong engagement from HN community · Strong signals: io · Missing: https docs, excited, just released

56%56% 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

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

AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive

26%26% 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

21%21% 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.

Correct prediction on native model

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