Antimemetic message that escapes screen capture

Hacker News

The message is clearly visible, but it cannot be screen captured. (Or just pause the effect with click/tap.) I think this TV static effect is more realistic than others on the web: - Wide CRT "pixel" aspect ratio - Larger "grains" (to match low CRT resolution) - CRT "scan lines" (Toggle with 'C' key) When I attempted this effect many years ago, it didn't seem possible without GPU shaders. With advances in hardware/JS performance, the CPU can easily blast a higher resolution (2560x1440) at 1000 FPS. (ENTER key to go into fullscreen mode) --- Customize the message with url param: https://fx.leftium.com/static?text=HN (To see all options: 'U' key copies URL to clipboard and also outputs to dev console.) Made with SvelteKit: https://github.com/Leftium/fx

Visit product View on Hacker NewsMay 25, 2026

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3points

Did not reach leaderboard

Launch Intel predictions

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Hacker NewsStrong engagement from HN community · Strong signals: ide, 000, io · Missing: https docs, excited, just released

63%63% 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 · Missing: mac, agents, macos

55%55% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

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

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

41%41% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

40%40% 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

21%21% 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

10%10% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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