在斯坦福大學的閱讀理解考試中，阿里巴巴開發(fā)的人工智能模型成績超過了人類。

阿里巴巴上周測試了深度神經(jīng)網(wǎng)絡(luò)模型，要求AI給出超過10萬道問題的答案。該測試是世界上最權(quán)威的機器閱讀測驗之一。最后阿里巴巴數(shù)據(jù)科學與技術(shù)研究院開發(fā)的AI得到82.44分，略高于人類對手的82.304分。

阿里巴巴表示，這是機器首次在此類測試中超過人類。微軟研發(fā)的AI在該測試中成績差不多，得分為82.650，只是其成績確認比阿里巴巴的AI晚了一天。

中國電商巨頭阿里巴巴已開始發(fā)力AI開發(fā)，跟騰訊、百度等對手展開競爭。AI可以豐富社交媒體信息流，實現(xiàn)廣告和服務(wù)精準投放，甚至可以協(xié)助自動駕駛。中國政府已經(jīng)在國家級規(guī)劃中公開肯定AI技術(shù)，還提出到2030年中國要成為行業(yè)領(lǐng)跑者。

所謂自然語言處理技術(shù)，是指模仿人類理解詞語和句子的方式。斯坦福大學的測試內(nèi)容包括500多篇維基百科文章，提出的問題旨在評估機器學習模型能否在處理大量信息后準確回答問題。

阿里研究院自然語言處理首席科學家司羅發(fā)表聲明稱：“也就是說，現(xiàn)在機器可以準確地回答客觀問題，比如‘為什么會下雨？’背后的技術(shù)可以逐步用于大量應(yīng)用，比如客戶服務(wù)、博物館導覽和在線解答患者的咨詢，從而大大降低人力投入?！保ㄘ敻恢形木W(wǎng)）

譯者：Charlie

審校：夏林

Alibaba has developed an artificial intelligence model that scored better than humans in a Stanford University reading and comprehension test.

Alibaba Group Holding (BABA, -0.52%) put its deep neural network model through its paces last week, asking the AI to provide exact answers to more than 100,000 questions comprising a quiz that’s considered one of the world’s most authoritative machine-reading gauges. The model developed by Alibaba’s Institute of Data Science of Technologies scored 82.44, edging past the 82.304 that rival humans achieved.

Alibaba said it’s the first time a machine has out-done a real person in such a contest. Microsoft achieved a similar feat, scoring 82.650 on the same test, but those results were finalized a day after Alibaba’s, the company said.

The Chinese e-commerce titan has joined the likes of Tencent Holdings (TCTZF, +2.68%)and Baidu (BIDU, +1.06%) in a race to develop AI that can enrich social media feeds, target ads and services or even aid in autonomous driving. Beijing has endorsed the technology in a national-level plan that calls for the country to become the industry leader 2030.

So-called natural language processing mimics human comprehension of words and sentences. Based on more than 500 Wikipedia articles, Stanford’s set of questions are designed to tease out whether machine-learning models can process large amounts of information before supplying precise answers to queries.

“That means objective questions such as ‘what causes rain’ can now be answered with high accuracy by machines,” Luo Si, chief scientist for natural language processing at the Alibaba institute, said in a statement. “The technology underneath can be gradually applied to numerous applications such as customer service, museum tutorials and online responses to medical inquiries from patients, decreasing the need for human input in an unprecedented way.”