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I made a 3D clone of myself for my website

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I made a 3D clone of myself for my website

I wanted to bring together a few projects I've been working with recently, and figured the best way to do so was to make an interactive 3D clone of myself for my own website. This uses my flutter_filament[0] package for rendering (ignore the name, it's no longer Flutter-only), Jaspr[1] (a Dart framework for building reactive UIs, syntax inspired by Flutter), Avaturn[2] for the avatar, Cartesia[3] for the voice cloning, DiffSHEG[4] for the skeletal animations (though scaled down considerably), FaceDiffuser[5] for the facial animation and sherpa-onnx[6] for the speech recognition. [0] https://github.com/nmfisher/flutter_filament [1] https://github.com/schultek/jaspr [2] https://avaturn.me [3] https://cartesia.ai [4] https://github.com/JeremyCJM/DiffSHEG [5] https://github.com/uuembodiedsocialai/FaceDiffuser [6] https://github.com/k2-fsa/sherpa-onnx

Visit productView on Hacker NewsJun 14, 2024
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Actual performance

3points
Did not reach leaderboard

Launch Intel predictions

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
58%58% 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 · Missing: mac, agents, macos
56%56% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
TrustMRRFits verified-revenue profile · Strong signals: way · Missing: mobile apps, ios, personal
53%53% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: ide, io · Missing: https docs, excited, just released
53%53% 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
40%40% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Strong signals: active · Missing: arr, mrr, revenue
13%13% 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
1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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