I made a programmable computer from NAND gates

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I am proud to present my solo hobby project NAND. This year-long undertaking follows the completed Nand to Tetris course, but ported to the web with its own runtime, user interface, and IDE. Using the "Load example program" selector, you can try out some programs I wrote on NAND's emulated hardware such as 2048, a genetic algorithm, and a manual stack overflow to corrupt the screen. Check out NAND at https://nand.arhan.sh Additionally, I've authored an extensive writeup about the project. Read about it on the GitHub repository's readme.

Visit product View on Hacker NewsApr 25, 2024

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Product HuntOn track for Day 1 leaderboard · Strong signals: user, computer, using · Missing: mac, agents, macos

91%91% predicted probability of success on Product Hunt, 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, io · Missing: https docs, excited, just released

80%80% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting

71%71% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

49%49% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

43%43% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

18%18% 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.

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