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Brainly. App I hacked while you watched the Facebook IPO

Hacker News

Brainly. App I hacked while you watched the Facebook IPO

This is a little tool I made for myself. Had been meaning to write it for a while, but never had the chance.<p>Decided to do it while I followed the Facebook IPO. It was way more fun than seeing people make millions...<p>About it:<p>PHP Bootstrap<p>It is quite slow, because it goes over a 150,000+ word dictionary three times before the html is generated.<p>But, in my defense, I just run it on my XAMPP install and is pretty snappy.<p>So hey, check it out. I have my flame suit on already. clicky: http://brainly.innovafy.com

Visit productView on Hacker NewsMay 18, 2012
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5points
4comments
Did not reach leaderboard

Launch Intel predictions

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
87%87% 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: ide, 000, io · Missing: https docs, excited, just released
68%68% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
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.
Product HuntUnlikely to reach the leaderboard · Missing: mac, agents, macos
50%50% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
33%33% 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
17%17% 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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