Best HFY Stories: Karatsuba
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- Опубликовано: 8 фев 2025
- You calculated WHAT!?
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Alien employer: I need you to build a hyperdrive navigation computer.
Human engineer: Raspberry pi loaded up with galactic maps and the A* Pathfinder algorithm.
I mean its good enough for Stellaris it's probably fine
i see a plot hole, anyone who casually overclocks a threadripper with liquid helium is either very well employed, or is not seeking for a job in the slightest.
maybe a rich kid who's bored?
You telling me that a computer engineer in NASA wouldn't apply for a job in the Galactic Federation?
When do you think they'll realize that we've even put our pictures into math on the computer?
That most of our music is mathematically inclined?
Our Art that uses the Golden Ratio has math as a foundation?
Look a human and it already has broken a rule. Ah look a hundred humans "How in the hell did they break all the rules in a month?"
Only a month? Geez seems like we’ve been patient and generous
@@kaviyalinikarthi6767we have to have breaks for coffee
Oh of course sorry, although I don’t drink coffee 🤔
Wait till they find out that human computers are based on nano size on/off electrical switches.
Would have been even better if that theradripper was not new but old, maybe 30 years old or something and the latest was much better
Wait till they hear about FFT's and Tensors...
Yes, but can it run doom?
you mean crysis
@@julesmasseffectmusic No, Doom. We can run Doom on a damn pregnancy test. No need to give the xenos an impossible problem.
🤣👍
Damn a read it as Kamasutra.
Fast multiplication.
Wait a moment, do they not have logarithms?
A * B = log(A) + log(B)
@nathanielhill8156 They should have, but the multiplying by taking the logarithm and then adding just shifts the time complexity to calculating the logarithm. Arguably, the time complexity is actually made worse.
Cool👍🏻
Huh?
Karatsuba is the Russian mathematician that found a faster algorithm for multiplication.
Before him, the known algorithms (such as school multiplication) ran for ~n² steps for n digits. In computer science jargon: the algorithms has O(n²) time complexity.
His algorithm ran for ~n^(log₂(3)) steps for every n digits. In computer science jargon: his algorithm has O(n^(log₂(3))) time complexity.
LOL
Third