pun generator might not sound like serious work for an artificial intelligence researcher—more the sort of thing knocked out over the weekend to delight the labmates come Monday. But for He He, who designed just that during her postdoc at Stanford, it’s an entry point to a devilish problem in machine learning. He’s aim is to build AI that’s natural and fun to talk to—bots that don’t just read us the news or tell us the weather, but can crack jokes or compose a poem, even tell a compelling story. But getting there, she says, runs up against the limits of how AI typically learns.
Gregory Barber covers cryptocurrency, blockchain, and artificial intelligence for WIRED.
Neural networks are natural imitators, learning patterns of language by scouring vast amounts of text. If coherency is your aim, that approach works well—so well, in fact, that recent advances have sparked an ethical debate about whether people could abuse AI to generate convincing fake news. But the resulting prose is as dry as the newspaper text and Wikipedia articles typically used to train them. Neural networks, in other words, are rule-abiding to a fault, and that makes them terrible jokers. A well-crafted joke teeters at the edge of coherency without wading into nonsense, He says, and neural networks simply don’t have the sense to strike that balance. Besides, the whole point of creativity is to be, well, novel. “Even if we had a long list of puns it could learn from, that would miss the point,” she says.
Instead, He and her team, which included Nanyun Peng and Percy Liang, tried to give their AI some creative wit, using insights from humor theory. To anyone who’s dared craft a pun, the intuition will sound familiar. For a pun to work, He decided it needs to be surprising in a local context (“stopped to get a hare cut” makes little sense on its own) but also have an “aha” factor that ties it all together (in this case, thanks to the word “greyhound”). He and her team anoint th
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