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Project Cherub – A Forked TempleOS. Early Build and Future Plans

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Project Cherub – A Forked TempleOS. Early Build and Future Plans

Hello! I, Rubinosław from REParadoxy, I'm presenting Project Cherub - a modernized version of TempleOS, very well known operating system made by Terry A. Davis. My vision is to create a minimalist, fully-functional and secure operating system. For home users, for bussiness users, for programmers, for artists, for everyone! Where THE USERS matter the most! I've already changed FPS rate from 30 to 120 via modifying "KernelA.HH.Z" file, a part of the system kernel. I've changed WINMGR_FPS in that file from "(30000.0/1001)" to "(120000.0/1001)", and WINMGR_PERIOD from "(1001/30000.0)" to "(1001/120000.0)". I've also changed the system name from "TempleOS" to "Project Cherub". As I said - its just a very early build. But my plan is to add also 32-bit colors support, support for SATA AHCI, NVMe, Blu-ray, videos, GPU and USB. But I'll keep the 640x480 screen resolution, you know why. Full presentation of an early build with 120 FPS, future plan, and installation showcase: https://www.youtube.com/watch?v=NNq_4vG5Src More information: https://github.com/Rubinoslaw/Project-Cherub - GitHub repository (with ISO!) https://rubinoslaw.github.io/projectcherub.github.io/ - the official website of the project

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Indie HackersFits the IH revenue-focused audience · Strong signals: para · Missing: supports, reddit linkedin, podcasting
67%67% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: ide, 000, io · Missing: https docs, excited, just released
65%65% 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 HuntOn track for Day 1 leaderboard · Strong signals: user · Missing: mac, agents, macos
58%58% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: video, users, para · Missing: mobile apps, ios, personal
49%49% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Strong signals: users · Missing: plus, platform, intuitive
39%39% 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
14%14% 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
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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