Tech firms race to make AI machines smarter
PROVIDENCE, R.I. — Seven years ago, a computer beat two human quizmasters on a “Jeopardy” challenge. Ever since, the tech industry has been training its machines to make them even better at amassing knowledge and answering questions.
And it’s worked, at least up to a point. Just don’t expect artificial intelligence to spit out a literary analysis of Leo Tolstoy’s “War and Peace” any time soon.
Research teams at Microsoft and Chinese tech company Alibaba reached what they described as a milestone earlier this month when their AI systems outperformed the estimated human score on a reading comprehension test. It was the latest demonstration of rapid advances that have improved search engines and voice assistants and that are finding broader applications in health care and other fields.
The answers they got wrong — and the test itself — also highlight the limitations of computer intelligence and the difficulty of comparing it directly to human intelligence.
“We are still a long way from computers being able to read and comprehend general text in the same way that humans can,” said Kevin Scott, Microsoft’s chief technology officer.
The test developed at Stanford University demonstrated that, in at least some circumstances, computers can beat humans at quickly “reading” hundreds of Wikipedia entries and coming up with accurate answers to questions about Genghis Khan’s reign or the Apollo space program.
The computers, however, also made mistakes that many people wouldn’t have.
“You need some very simple reasoning here, but the machine cannot get it,” said Jianfeng Gao, of Microsoft’s AI research division. It’s not uncommon for machine-learning competitions to pit the cognitive abilities of computers against humans. Machines first bested people in an imagerecognition competition in 2015 and a speech recognition competition last year, although they’re still easily tricked.
And since IBM’s “Jeopardy” victory in 2011, the tech industry has shifted its efforts to dataintensive methods that seek to not just find factoids, but better comprehend the meaning of multi-sentence passages.
Like the other tests, the Stanford Question Answering Dataset, nicknamed Squad, attracted a rivalry among research institutions and tech firms — with Google, Facebook, Tencent, Samsung and Salesforce also giving it a try.
“Academics love competitions,” said Pranav Rajpurkar, the Stanford doctoral student who helped develop the test. “All these companies and institutions are trying to establish themselves as the leader in AI.”