CandideAI – Where kids learn AI the fun way

Hacker News

Hello everyone, I am the founder of an edTech platform to help kids learn AI the fun way called Candideai.com. The goal is to help kids learn AI while building cool things and developing creativity. We have a list of courses we're testing with beta users, before a public release. Here is the kind of courses you'll find: Create your own Pokemon with Midjourney Train your own AI and turn yourself into an anime character Be the hero of your own story (introduction to chatGPT) Get advice from your favorite superhero: how to setup a chatbot to become Spiderman and get advices from him Create your coloring book from scratch (& print it!) I'd love to get the community's feedback on this idea and know more how you'd approach AI with your kids. Thanks.

Visit product View on Hacker NewsMay 9, 2023

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

89%89% 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.

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

47%47% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

44%44% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

Product HuntUnlikely to reach the leaderboard · Strong signals: user, chatgpt · Missing: mac, agents, macos

41%41% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Strong signals: platform, users · Missing: plus, intuitive, reviews

31%31% 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 · Strong signals: chat · Missing: web3, crypto, cryptocurrency

1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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