I train neural networks, which are a type of machine learning program that imitates the way human brains learn. (Technically, they’re artificial neural networks, to differentiate them from the biological sort). Unlike traditional computer programming, where a human programmer comes up with a long set of rules for a computer to follow, with neural networks, the computer learns by example and comes up with its own rules.

Most of us encounter neural networks every day - they power face recognition, automatic language translation, object recognition, and self-driving cars. The neural networks I train, though, are for more modest, and sillier purposes - inventing new paint colors (like Burf Pink and Stanky Bean) or new names for guinea pigs (Popchop and Fuzzable, for example).

Today’s experiment: computer algorithms.

Not the algorithms themselves, mind you - that sounds difficult. Just their names. 2045 of them from the Wikipedia list of computer algorithms (big thanks to Joshua Schachter for extracting the data). I gave them to a simple char-rnn neural network, thinking it would be very interesting to find out what one computer program decides to name another.

The results do sound pretty algorithmic - you might be able to get away with recommending these to a programmer who’s stuck on a problem, if you leave before they google it.

Moshwack algorithm
Stardand’s algorithm
Super–Kelnic algorithm
Soft sort
Vandical time algorithm
Go sort
Hair mato-sort
Speedated heeling tree
Jusi tree Shamer
Gorper’s algorithm
Spade optimization
Wash problem
Gore search
Bollard method

These are a bit less plausible (especially the inevitable fart algorithms. For some reason, the word “fart” often comes up in this neural network’s results.)

Farter search
Prebabel strung parser
Boonfus-(computer scearch
Stani computer somplerity farter estimator
Purparden argloximication
Rendamical fimfering
Pint blops
Wolgaren farting
Gimprach relucing
Suav clopping
Random damplestremptic ferchion
Pand fassing
Aromatic pashering contex algorithm
Farter-hear srial fecty optimization

And these prove that basic and simple does not necessarily mean more believable. Don’t suggest using these. You will not sound smart.

Jashen computer statistication
Computer algorithms
Mathator sort
Somperting problem
Complexity computing
Code forting algorithms
Rare algorithm
Lean mathing
Rarge problem
Compater partimation
Gerertic proplem
Spreeer–Mate proplem
Barse me

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