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The math of shuffling cards almost brought down an online poker empire

(www.scientificamerican.com)
97 points indigodaddy | 1 comments | 05 Sep 25 22:50 UTC | HN request time: 0.199s | source
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sneak ◴[07 Sep 25 02:05 UTC] No.45154725[source]▶
> Card dealers create a unique deck with each shuffle, something computers cannot replicate

This is entirely, unequivocally false.

Shuffling as an algorithm to implement is easy to fuck up, but if you use a good one and a true RNG source, computers can shuffle better than humans - just as randomly, and many orders of magnitude faster.

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smallerize ◴[07 Sep 25 02:12 UTC] No.45154759[source]▶
I think the RNG source is the point here. It's not as impossible as stated, but you have to put some work in to get a good one.
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awesome_dude ◴[07 Sep 25 02:15 UTC] No.45154786[source]▶
Go (and probably other languages) has the Fisher-Yates algorithm for shuffling

https://en.wikipedia.org/wiki/Fisher%E2%80%93Yates_shuffle

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vesche ◴[07 Sep 25 04:33 UTC] No.45155420[source]▶
Python's random.shuffle also uses Fisher-Yates
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1. awesome_dude ◴[07 Sep 25 07:19 UTC] No.45156094[source]▶
I wonder how many other languages have it implemented as their shuffle algorithm