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Mac40th.com: 40 Years of Macintosh

Hacker News

Mac40th.com: 40 Years of Macintosh

Hi HN. Please check out mac40th.com - a site I’ve launched today to celebrate the Macintosh’s 40th birthday happening tomorrow on January 24th, 2024. mac40th.com features over 1,000 photos covering every Macintosh desktop and portable made by Apple since the original 128K M0001 was released in 1984 - all the way through to the latest Mac Pro, iMac and MacBook lines. So many people have come across a Mac at some point in their lives - mac40th.com is about giving fans a fun trip down memory lane with the hope that the Macintosh’s 40th anniversary evokes happy memories for anyone who has ever had an experience with an Apple Mac. I'd love to get your feedback and also fix any errors :) Enjoy! Jonathan.

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
89%89% 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.
Product HuntOn track for Day 1 leaderboard · Strong signals: mac, apple · Missing: agents, macos, agent
82%82% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: 000 · Missing: https docs, excited, just released
58%58% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
45%45% predicted probability of success on AppSumo, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: way · Missing: mobile apps, ios, personal
29%29% 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
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
0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

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