AI models beat humans at reading comprehension, but they've still got a ways to go

When computer models designed by tech giants Alibaba and Microsoft this month surpassed humans for the first time in a reading-comprehension test, both companies celebrated the success as a historic milestone. Luo Si, the chief scientist for natural-language processing at Alibaba's AI research unit, struck a poetic note, saying, "Objective questions such as'what causes rain' can now be answered with high accuracy by machines." Teaching a computer to read has for decades been one of artificial intelligence's holiest grails, and the feat seemed to signal a coming future in which AI could understand words and process meaning with the same fluidity humans take for granted every day. But computers aren't there yet -- and aren't even really that close, said AI experts who reviewed the test results. Instead, the accomplishment highlights not just how far the technology has progressed, but also how far it still has to go. "It's a large step" for the companies' marketing "but a small step for humankind," said Oren Etzioni, chief executive of the Allen Institute for Artificial Intelligence, an AI research group funded by Microsoft co-founder Paul Allen.