Author: Cade Metz / Source: New York Times
Nicolas Ortega
In August, researchers from the Allen Institute for Artificial Intelligence, a lab based in Seattle, unveiled an English test for computers. It examined whether machines could complete sentences like this one:
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.
d) nervously sets her fingers on the keys.
For you, that would be an easy question. But for a computer, it was pretty hard. While humans answered more than 88 percent of the test questions correctly, the lab’s A.I. systems hovered around 60 percent. 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 several 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 several independent research organizations, 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 analyzes documents inside law firms, hospitals, banks and other businesses.
“Each time we build new ways of doing something close to human level, it allows us to automate or augment human labor,” said Jeremy Howard, the founder of Fast.ai, an independent lab based in San Francisco that is among those at the forefront of this research. “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 services like Twitter, this new research could also lead to more convincing bots designed to fool us into thinking they are human, Mr. Howard said.
Researchers have already shown that rapidly improving A.I. techniques can facilitate the creation of fake images that look real. As these kinds of technologies move into the language field as well, Mr. Howard said, we may need to be more skeptical than ever about what we encounter online.
These new language systems learn by analyzing millions of sentences written by humans. A system built by OpenAI, a lab based in San Francisco, analyzed thousands of self-published books, including romance novels, science fiction and more. Google’s Bert analyzed these same books plus the length and breadth of Wikipedia.
Each system learned a particular skill…
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