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商业 - 科技

AI的阅读理解能力已经超过人类

彭博社 2018年01月22日

电商巨头阿里巴巴已开始发力AI开发,跟腾讯、百度等对手展开竞争。

在斯坦福大学的阅读理解考试中,阿里巴巴开发的人工智能模型成绩超过了人类。

阿里巴巴上周测试了深度神经网络模型,要求AI给出超过10万道问题的答案。该测试是世界上最权威的机器阅读测验之一。最后阿里巴巴数据科学与技术研究院开发的AI得到82.44分,略高于人类对手的82.304分。

阿里巴巴表示,这是机器首次在此类测试中超过人类。微软研发的AI在该测试中成绩差不多,得分为82.650,只是其成绩确认比阿里巴巴的AI晚了一天。

中国电商巨头阿里巴巴已开始发力AI开发,跟腾讯、百度等对手展开竞争。AI可以丰富社交媒体信息流,实现广告和服务精准投放,甚至可以协助自动驾驶。中国政府已经在国家级规划中公开肯定AI技术,还提出到2030年中国要成为行业领跑者。

所谓自然语言处理技术,是指模仿人类理解词语和句子的方式。斯坦福大学的测试内容包括500多篇维基百科文章,提出的问题旨在评估机器学习模型能否在处理大量信息后准确回答问题。

阿里研究院自然语言处理首席科学家司罗发表声明称:“也就是说,现在机器可以准确地回答客观问题,比如‘为什么会下雨?’背后的技术可以逐步用于大量应用,比如客户服务、博物馆导览和在线解答患者的咨询,从而大大降低人力投入。”(财富中文网)

译者:Charlie

审校: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.”

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