Random Number Seed Demo App

Hacker News

I have a demo app that generates a seed for the random number function of the VC++ library. You can download the demo app from here: http://zenoflotto.com/eBookDownloadFiles/Demo_4_0380503957.html The seed is generated without using the VC++ random number generator function. Four mouse-clicks and you have your seed. I would like people to download the app and comment on it. Also, comments on your download experience would be appreciated. The download file has a ReadMe file to help you set up the app. The demo app has a help feature with a brief set of instructions about using the app.

Visit product View on Hacker NewsAug 9, 2015

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TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal

46%46% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive

46%46% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

35%35% 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: using · Missing: mac, agents, macos

34%34% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting

29%29% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue

16%16% 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

4%4% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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