Simulation of 1M Flocking Birds

Hacker News

I love starlings and algorithms and decided to combine. I built a starling murmuration simulation that scales to one million birds. The flocking emerges from simple local rules and continuous adjustment to nearby birds. It is based on Boids - separation, alignment, cohesion, soft boundaries and a gentle pull toward the center. The flock’s motion also drives sound, where altitude controls pitch and local density shapes texture. Desktop supports up to one million birds with adaptive limits on mobile. Make sure to play around with the controls and let me know what you think.

Visit product View on Hacker NewsDec 27, 2025

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2points

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Launch Intel predictions

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Product HuntOn track for Day 1 leaderboard · Missing: mac, agents, macos

81%81% 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

54%54% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

44%44% 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

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

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

31%31% predicted probability of success on Indie Hackers, 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

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

Incorrect prediction on native model

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