I train computer programs called neural networks to imitate datasets of human things. Basically, I give the neural network a long list of things like band names or guinea pig names to look at, and it does its best to figure out the rules that will let it generate more.
The neural network starts with a fresh slate every time, and becomes the World’s Biggest Fan of whatever it’s given - if I give it Pokemon names, it will invent Pokemon after Pokemon; if I give it Star Wars names, it will invent new characters like Darth Tina and Ban Sand.
There was one time when I gave the neural network a list of 37,000 common names of fish, and it invented fish that were, well, honestly no weirder than existing fish names. Fish names are That Weird.
Since that day, and even before, I have been hearing from birders. Any of you who know birders or are birders yourselves will not be surprised. Not only are birders very eager to find out what a neural network would make of bird species, they are also very organized. There is, for example, a downloadable checklist of about 32,000 birds, 14,000 of which have English common names. Big thanks to Kaija Gahm, Dana Terry, and Emily Davis, who sent me this and similar datasets.
The neural network, after reading intently through the entire list about 7 times, is now a dedicated birder.
I asked it to generate some birds. Not too wild - plausible.
Ecuadorian Helmeted Parrot
Slaty White-throated Fairy-bellied Ground-Tyrant
Ground-Tyrant, I asked? Cuckooshrike? It turns out, yes. There are 57 cuckooshrikes, including a Cerulean Cuckooshrike and a Blue Cuckooshrike, but not an actual Lazuli Cuckooshrike. Similarly, that ground-tyrant would pass as plausible among birders.
Fine, I said. What does actual weird look like? I upped the neural network’s creativity level to 1.0, the highest level I usually use.
Nukh’s Dull Gull
Banded Spectacled Snake-Eagle
Bunticus Gray-chinned Laughingthrush
Ecuadorian Strange-tailed Cuckoo
Horned Yellow Flycatcher
Red-capped Lynert’s Leafbird
Rufous-fronted Grassy Owl
Chestnut-bellied Ged Parrot-Weaver
Unicolored Painted Blue-cowled White-browed Cave-Magpie
Ha, I said. Banded Spectacled Snake-Eagle? That’s hilarious.
Yes, the neural network would have replied (if it was equipped for conversation as well as for birding enthusiasm). Banded AND Spectacled? Ha!
It turns out there are 6 snake-eagles, 41 spectacled birds, and 106 banded birds, but nothing that’s banded AND spectacled.
I turned the creativity up to 1.2, a point at which for other datasets, the neural network is emitting unpronounceable strings of letters with only a vague resemblance to the original. Here’s what the birding neural net produced:
Blue-winged Cruz White Kiwi
Marabor Island Sooty-Whistler
Rus Efricans Puffbird
Northern Narrow Lark
Wilson’s Blue-eared Hummingbird
Crinete Bor-billed Mountain-eater
Pygmy Sea Shag
Granted, even I am registering some of these as weird. Mountain-eater? The neural network made that up. But Wattle-eye, puffbird, stonechat, and shag are all real things. Apparently an *Olive* stonechat is just that weird.
At creativity 1.4 the results get stranger but not as strange as you’d think.
Temetai African Pope Catbird
Eastern Shove Crake
For reference, this is what a neural network trained on pie produces at creativity 1.4:
Dibble Ice Fraini Pien Daria Futgo Crustdamamatsna-LiGmeat Pieb
Pe sivle Hed Rice Frozen Mincemeat Mop shb
Impossible Titer: Fiag
Caramel Apple Wime Figl’s Topped Sugrum’s Pumpar
The birders are probably nodding in agreement with the neural network, though. “FOREST Tern? That’s unutterably silly.”
Finally, once I have increased the creativity to 1.6, I declare the neural network’s names to be Obviously Strange.
African White-capped Hocky Owl
Fairy-collared Barblering Bush-Roe Hyra
Dusky Sicky-faced Petrel
Hoaly Titco’s Badwinch
Snowy Mourning Heron-Robin
Javan Clamper Leafbird
Red-bellied Pale-tufted Junkletar
Moustached White Owl
Pacific Three-hong-toed Thick-dee
warn-winged Wood-banded-Black-breasted Stesing-Patein-fronted Crimsonwing
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