On stage, a woman takes a seat at the piano. She
a) sits on a bench as her sister plays with the doll.
b) smiles with someone as the music plays.
c) is in the crowd, watching the dancers.
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For you, that would be an easy question. But for a computer, it was pretty hard. While humans answered more than 88 per cent of the test questions correctly, the lab’s AI systems hovered around 60 per cent. Among experts — those who know just how difficult it is to build systems that understand natural language — that was an impressive number.
Then, two months later, a team of Google researchers unveiled a system called Bert. Its improved technology answered those questions just as well as humans did — and it was not even designed to take the test.
Bert’s arrival punctuated a significant development in artificial intelligence. Over the last few months, researchers have shown that computer systems can learn the vagaries of language in general ways and then apply what they have learned to a variety of specific tasks.
Built in quick succession by independent research organisations, including Google and the Allen Institute, these systems could improve technology as diverse as digital assistants like Alexa and Google Home as well as software that automatically analyses documents.
“Each time we build new ways of doing something close to human level, it allows us to automate or augment human labour,” said Jeremy Howard, the founder of Fast.ai, an independent lab based in San Francisco “This can make life easier for a lawyer or a paralegal. But it can also help with medicine.” It may even lead to technology that can — finally — carry on a decent conversation.
But there is a downside: On social media, this new research could also lead to more convincing bots designed to fool us into thinking they are human, Howard said.
©2018 The New York Times News Service
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