Chinese Machine Learning Beats Humans in Reading Test
A deep neural network machine built by the AI research arm of China’s biggest online commerce company, Alibaba, has scored higher than humans on a reading test for the first time.
The machine-learning models scored 82.44 on the Stanford Question Answering Dataset, a large-scale reading comprehension test with more than 100,000 questions, compared with 82.304 by humans.
Stanford tests are used by several international universities and global technology firms, including Google, Facebook, IBM and Microsoft, to determine whether their machine learning models are able to answer the questions in the data set.
Machines have already bested humans in complex games like chess, where skills such as infallible memory and raw computing power align with the intrinsic capabilities of bots.
In December last year (2017), DeepMind, Google’s artificial intelligence programme, was able to win a game of chess after first learning how to play the game.
Where computers have surpassed human ability before in games of chess by using pre-conditioned programming, DeepMind’s AlphaZero program experimented by playing games against itself until it had discerned the effectiveness of all possible moves.
In a #alibaba warehouse ! #IoT #AI #robotics v/ @jblefevre60 cc @Fisher85M @MikeQuindazzi @ipfconline1 @mallys_ @evankirstel @guzmand @SpirosMargaris @TheMisterFavor @JimMarous @JacBurns_Comext @helene_wpli pic.twitter.com/RypduSZaLR— Christine Boursin (@chboursin) January 14, 2018
Alibaba’s breakthrough means that bots are closer to performing a wide range of customer service tasks.
The machine learning model was tested with Ali Xiaomi, a mobile customer service chatbot used by retailers on Alibaba’s online market platforms.
They found the bots could identify the questions raised by consumers and look for the most relevant answers from prepared documents.
The system currently works best with questions that offer clear-cut answers.
If the language or expressions are too vague or ungrammatical, or there is no prepared answer, the bot may not work properly.
In an interview with South China Morning Port, Si Luo, a chief scientist of natural language processing at Alibaba’s research arm, said: “We believe the underlying technology can be gradually applied to numerous applications such as customer service, museum tutorials, and online response to inquiries from patients, freeing up human efforts in an unprecedented way.”
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