China’s Baidu Uses AI Understanding in Chinese to Learn English

China’s giant tech company Baidu, has surpassed both
Microsoft and Google when it comes to AI and language learning. The company,
which is sometimes referred to as China’s Google, achieved the highest ever
score in the General Language Understanding Evaluation (Glue), which is widely
considered to be the benchmark for AI language understanding. It consists of
nine different tests for things like picking out the names of people in a
sentence, and figuring out what a pronoun like “it” refers to when there are
multiple potential options. The average person scores about 87 points out of a
hundred on the Glue scale—Baidu is the first to score over 90. The company used
it’s own AI language model, called ERNIE (which stands for “Enhanced
Representation through kNowledge IntEgration”).
According to Karen Hao of MIT Technology Review, what’s
notable about Baidu’s achievement is that it illustrates how AI research
benefits from a diversity of contributors. Baidu’s researchers developed a
technique with Ernie that was specifically for Chinese. This proved, however,
to make it better at understanding English as well.
Baidu’s ERNIE was modeled after Google’s BERT (Bidirectional
Encoder Representations from Transformers), which was created in 2018. Before
BERT, natural language models had much lower capabilities, and could only predict
words for applications like Autocomplete, but couldn’t sustain a train of
thought. When BERT came along, it considered the context before and after a
word at once, making it bidirectional and able to but each word in it’s
complete context.
The Baidu researchers took this idea further, and trained
ERNIE to predict sets of missing
words, which is essential for understanding Chinese, in which individual words
rarely work alone. While BERT specialized in predicting words, ERNIE was able
to predict phrases. This ability had great crossover into English, making it
able to predict entire sets of words. Just as Chinese, English has words that
have different meanings depending on their contexts.
“When we first started this work, we were thinking
specifically about certain characteristics of the Chinese language,” says Hao
Tian, the chief architect of Baidu Research. “But we quickly discovered that it
was applicable beyond that.”


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