At the beginning of 2018, artificial intelligence made great breakthroughs. In January 11th, Stanford University launched the top ranking competition of SQuAD in machine reading field. The industry's inspiration is AI's reading ability is the first time to surpass human in history. The Alibaba broke the world record with a 82.440 precision and surpassed 82.304 of the human achievement.
The head of SQuAD, Pranav Rajpurkar, is hard to hide the excitement. He said on social media that it was a strong start to 2018. The first model (SLQA submitted by the Alibaba iDST team) surpassed human performance in terms of accuracy matching! Next challenge: fuzzy match, humans are still 2.5 points ahead!
SQuAD game to build a large-scale machine reading data set (including 100 thousand), articles from the more than 500 Wikipedia article.
After reading a short paper on data set, AI needs to answer several questions based on the content of the article, then compare it with the standard answers, and get the results of exact matching (Exact Match) and fuzzy matching (F1-score).
SQuAD is the industry's recognized machine reading comprehension top competition, attracting Google, Carnegie. Mellon University, Stanford University,MicrosoftThe Asian Institute, the Alan Institute, the IBM, Facebook and other well-known enterprise research institutions and universities are deeply involved.
The major breakthrough in the technology came from the Alibaba research team.
The model can capture problems in specific areas of association and articles at the same time, with the help of hierarchical strategy, gradually focus, make the answer clear boundary; on the other hand, in order to avoid too much attention to details, the fusion will join the mechanism of attention to global information, appropriate correction, to ensure the correct focus.
Alibaba Natural language processing Chief Scientist Siro said that the machine has achieved very good results in solving the question and answer of objective knowledge of the wiki class, and we will continue to work on the
In the future, the focus of R & D is to apply this technology to the actual scene, and make the machine intelligent life.
In fact, this technology has been widely used within the Alibaba. For example, a large number of customers have a large number of customers every year to consult the rules of the activity. Ali team by using the Auror team Xiaomi technology, make the machine directly on the rules of reading, reading provides regular service for users, is the most natural way of interaction.
For example, customers will also ask a large number of basic questions for a single commodity, which are actually answers to the details of the product. Now, through machine reading and understanding technology, the machine can read and answer the texts more intelligently, and reduce the cost of services and improve the purchase conversion rate.
The Natural language processing team, led by Mr. Siro, supports Alibaba's entire ecological technology needs. The AliNLP Natural language Technology platform, developed by them, is invoked 120 billion times a day. The Alitranx translation system provides over 700 million calls per day in 20 languages.
Previously, it won the world's first achievement in the 2016 ACM CIKM personalized business search, 2017 IJCNLP Chinese grammar test CGED evaluation, and the 2017 annual US Standard Bureau TAC comparison of English entity classification and other competitions.