The neural network meets its match: Fish biologists
3 min read

The neural network meets its match: Fish biologists

The neural network meets its match: Fish biologists
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(Drawing by Max Graenitz)

I train machine learning programs called neural networks - they work by looking at lists of data and then deducing their own rules about how to generate similar data. They’re used in everything from ad targeting to facial recognition to self-driving cars, but I use them for humor by giving them very silly datasets.

Usually in my experiment, I give the neural network an unfair dataset - like paint colors - and it tries its best, but ends up with something unintentionally weird, like a brownish color called Stanky Bean, or a bright blue color called Dad.

Fish biologist Colin Gross sent me a new dataset for the neural network, a list of the common names of 37,265 fish from fishbase.

I gave the list to an open-source neural network and let it start trying to generate more fish.

Here’s a snapshot of its early attempts, as it tried to spell common words like “butterflyfish” and “shark” and “snapper”

Blue-spotted erlerfish
Seer batterfly
Seelet guby
Pit-hard fish
Seate shurper
Seelee murchlip
Segfish
Seare moatherfish
Seale multerflyfish
Seeled cudfish
Seored barshont
Seare sputterfish
Spotfin spunterfly
Spotfin sul shripper
Sponted stripper
Spotfin shurk
Spotfin snarper
Blue-spotted mrinnfish

But then, it got good at this. I mean, really really good at this. You may think these names are the neural network being weird? No. They are pretty much indistinguishable from actual fish common names because, let me tell you, fish biologists are the weird ones.

The rest of this post is going to be the neural network’s ode to its new best friends, the fish biologists. And, I am very lucky to have excellent drawings by the talented Max Graenitz who wanted to get in on the weird-fest.

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Black Sea sweetlips
Eastern Dear eel
Oastern nose sucker
Vermillion assfin
Cuban fork head sucker
Gempofloise sand flaky
Vumberfish
Gerpike dwarf monocle bream
Wrink clown-shark
Bluebanded smooth-eet
Bluebacked tube-spot skate
Wallare pipe-eyed parrotfish
Moon-lined wad
Kascopcan tonguefish
Highfin stonebasher
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Dantuman ghost puffer
Moo lanternfish
Darfer butterflyfish
Hornmack croaker
Horny deepwater darter
Horseshark
Orangespotted smooth-hound
Yellow-black yellowtail dragonet
Small-dotted catshark
Small-mouthed unicorn fish
Orangespotted tilefish
Horse-eye grunt
Horse-snout fang-tailed dogfish
Pacific squeaker
Pacific headless lamprey
Little weakfish
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Mottonsfish
Danubiec spring-striped lumpsucker
Kaire-fin eartheater
Sputtail
Vague-lined sleeper-banded soapfish
Dangle shark
Daui’s deepwater redhorse
Khan’s hound shark
Rathead batfish
Lanto sand tiger unicorn fish
Bockon cubehead
Bow spiny lumpsucker
Boster weedfish
Deep dogfish
Binder’s flathead parrotfish
Hawaiian Stump ray
Black Sea gardenfish
Black Sea jobfish
Horny humbug
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Short-nose batfish
Short-nosed leatherjacket
Short-nosed jewelled-eyed rainbowfish
Short-lined pigfish
Short-toothed trumpeter
Short-face shrampgoby
Short-headed hogfish
Bokinker’s tubeshoulder
Bottlenose wobbegong
Bostriebann flute-tooth wolffish
Boguu dragonet
Pighead mullet
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Moanygoby
Mottled utterfish
Kack’s coral gropes
Kalhal gardensean block ray
Wurp fish
Whitley assfish
Sudderspot happy ghost-perch
Sucking puller
Sunsetnose spider shark
Witcheefin squirrelfish
Orangeside slickhead
Hawaiian doctorfish
Chornacher comb-tooth
Black Sea lampeye
Striped flying fang loach
Striped hone-spine dottyback
Greater butterfly tube-snouted ghost knifefish
Cuban armoured cat
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I’ve posted the original dataset so you can see I am NOT KIDDING about how weird fish names are.

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