Bitwise Liminal – A Short Film in 256 Bytes of Code

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A Short Film in 256 Bytes of Code Programmed by KilledByAPixel Presented at Lovebyte Party 2024 ... I found an old VHS tape at a yard sale. It was labeled "Bitwise Liminal" in sharpie. But when I watched the video it was only static. Then I started having vivid and... unsettling dreams. Also I couldn't stop thinking about that weird VHS tape. After researching I learned it was a digital backup. Using some special software I recovered the data. To my shock, it was a 256 byte program... With trembling hands I opened it in a web browser. Strange. This reminds me of the dreams I've been having. Now I don't need to sleep anymore. I just keep watching. ... l ɐ u ᴉ ɯ ᴉ ⅂ ǝ s ᴉ ʍ ʇ ᴉ ᗺ <canvas id=c><svg onload=setInterval("for(t+=.1,R=T=C=Math.cos,c.width=w=128,i=9986,V=t/9&3;Y=i--/w;c.getContext`2d`.fillRect(X,Y,(C(t/6)*T^V*i/1e4*T+t)%20?(R=T++,1):(T=9,19/R),5/Z))for(Z=5,X=i%w+4/R;0<(V*95+C(t/3)+Z*X/64-Z^Z|(60-Y)*Z/58)%13;Z+=.2);",t=9)>

Visit product View on Hacker NewsFeb 11, 2024

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

80%80% 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 · 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: context, using, code · Missing: mac, agents, macos

63%63% 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 · Missing: mobile apps, ios, personal

47%47% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

44%44% 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

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

3%3% predicted probability of success on BetaList, based on ML models trained on real launch data.

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