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Math Puzzle

Hacker News

Math Puzzle

Paste 'big.js' [1] into your web console. Run the following code - can you figure out WHY it works and what it represents? let printN = (maxN) => { let nextVal = (x,n) => { let b2 = new Big(2); let val = b2.pow(n).mul(3).mul(b2.minus(x).sqrt()); console.log(val.toString()); return x.plus(2).sqrt(); }; let s = (new Big(3)).sqrt().plus(2).sqrt(); for (let n=2; n<maxN; n++) { Big.DP = n + 10; s = nextVal(s,n); } }; printN(500); [1] Big decimal: https://raw.githubusercontent.com/MikeMcl/big.js/master/big.min.js [2] Try on JSFiddle: https://jsfiddle.net/asgxL84y/ [3] The math: https://pasteboard.co/JeNGeB0.png

Visit productView on Hacker NewsJun 26, 2020
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Launch Intel predictions

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Hacker NewsMay not resonate with HN audience · Missing: https docs, excited, just released
48%48% 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 · Missing: mobile apps, ios, personal
47%47% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Indie HackersIH features products with proven revenue · 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 · Strong signals: plus · Missing: platform, intuitive, reviews
45%45% 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
23%23% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
Product HuntUnlikely to reach the leaderboard · Strong signals: user, new, code · Missing: mac, agents, macos
23%23% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto
6%6% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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