Let’s face it: Jell-O is already gross enough. The boiled bones, sugar, and coloring concoction is a “food” best left to children and drunken college freshmen. And now, apparently, neural nets.
Janelle Shane, an author, blogger, and researcher, made the case for the latter by combining machine learning with a bunch of Jell-O recipes and letting the results run wild.
Oh boy, run wild it did.
“WHAT HAS OCCURRED CANNOT BE UNDONE,” she wrote on Twitter. “I have trained a neural net on a crowdsourced set of vintage jello-centric recipes[.] I believe this to possibly be the worst recipe-generating algorithm in existence.” Read more…
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