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Generate Custom Quizzes with AI from Any Topic or Presentation

Hacker News

Generate Custom Quizzes with AI from Any Topic or Presentation

Hello HN, I’ve built a tool that generates quizzes using AI, allowing users to create custom questions from any topic or uploaded presentations. It’s particularly useful for students who want to prep for exams or educators looking to enhance their lessons. The tool instantly generates relevant questions based on the input and exports them as PDFs for offline use. Key features: - Generate quizzes on any topic or from uploaded presentations - Export quizzes as PDFs for offline study or classroom use - 30,000 free characters monthly on a forever free plan This project aims to simplify quiz creation, making it easier for both learners and educators to practice or teach effectively. Would love to get feedback from the HN community!

Visit productView on Hacker NewsOct 21, 2024
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Launch Intel predictions

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
79%79% 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, presentations, using · Missing: mac, agents, macos
57%57% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: month, monthly, users · Missing: mobile apps, ios, personal
43%43% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Strong signals: users · Missing: plus, platform, intuitive
41%41% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: 000, io · Missing: https docs, excited, just released
28%28% 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
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
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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