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Hue v4.6.1

Hacker News

Hue v4.6.1

I'm working again on this project I started months ago. Made a lot of improvements in a week, and I wanted to share some images and stuff to others. It's currently at Version 4.6.1 Basically it's a multi-room chat platform with internet radio, image uploading (latest uploaded image is displayed and the colors of the room change according to it), administration commands and stuff. It doesn't use passwords, everything is key based which are stored in the localStorage of the browser, plus some IP checks for spam reasons. Image 1: https://i.imgur.com/oiNv3aw.jpg Image 2: https://i.imgur.com/u1GfRuK.jpg Image 3: https://i.imgur.com/s4owCvY.jpg Hacker News room: https://i.imgur.com/8zoK7P3.jpg https://hue.merkoba.com/Hacker%20News Source code: https://github.com/madprops/Hue

Visit productView on Hacker NewsOct 13, 2017
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Actual performance

2points
1comments
Did not reach leaderboard

Launch Intel predictions

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Indie HackersFits the IH revenue-focused audience · Strong signals: started · Missing: supports, reddit linkedin, podcasting
72%72% 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.
Hacker NewsStrong engagement from HN community · Strong signals: hacker news, io · Missing: https docs, excited, just released
52%52% 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 · Strong signals: month · 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 · Strong signals: plus, platform · Missing: intuitive, reviews, host
44%44% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Product HuntUnlikely to reach the leaderboard · Strong signals: new, code · Missing: mac, agents, macos
21%21% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
14%14% 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
0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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