HexSeq – A physics-based ambient music sequencer

Hacker News

HexSeq is a web-based recreation of Teenage Engineering's Tombola sequencer from their OP-1 synthesizer. It uses React Three Fibre and Rapier physics to create generative music through bouncing balls inside a rotating hexagon. Drop chords in with your keyboard, control the hexagon's rotation speed, adjust its shape, and experiment with different physics parameters to create unique musical "patterns". The lack of structure probably makes it best suited for generating some interesting ambient sounds. It can be quite mesmerising to play with. Made using React Three Fibre (three.js) for 3D rendering with the rapier physics engine, and Tone.js for audio. The mobile experience isn't great as I think triggering too many sounds causes crackling and audio clipping, at least on android/chrome.

Visit product View on Hacker NewsOct 28, 2024

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

67%67% 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.

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

62%62% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

AppSumoStrong fit for a featured deal · Missing: plus, platform, intuitive

56%56% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: ide, io · Missing: https docs, excited, just released

47%47% 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

46%46% 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

15%15% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Strong signals: audio · Missing: web3, chat, crypto

4%4% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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