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A rough simulation of a sail boat (2D Wireframe)

Hacker News

A rough simulation of a sail boat (2D Wireframe)

Link : http://firstglitch.com/html_projects/sailboat/sail-gl.html This is a very rough simulation of a sail boat (2D wireframe), that you can sail using force of "wind" (modeled as a million particles, animated using webgl) striking on the sails. The position of the wind particles and the forces of the particles striking on the sails is computed in WebGL shaders. The forces are NOT re-calculated at each frame. Which might cause some artifacts. For example, the boat might start moving after the wind has passed, if you continue adjusting the rudder and sail angle. You can adjust rudder using q/w keys and sail angle using o/p keys. See if you can sail into the wind, by finding the right combination of sail angle and rudder. It is a bit hard. Adjusting rudder and sail to changing wind directions can be challenging. But it should be fun once you figure it out.

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Hacker NewsStrong engagement from HN community · Strong signals: io · Missing: https docs, excited, just released
81%81% 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: model, using · Missing: mac, agents, macos
54%54% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
42%42% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting
40%40% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal
38%38% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto
20%20% predicted probability of success on BetaList, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
13%13% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

Incorrect prediction on native model

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