This blog post was originally posted on MIT Technology Review by Will Knight
From Alexa and Siri to countless chatbots and automated customer support lines, computers are gradually learning to talk. The only trouble is they are still very easily confused.
A research team at Salesforce has come up with a clever way to improve the performance of many modern language programs—teaching an algorithm to speak another language before training it to do other tasks.
Teaching machines to hold a coherent conversation remains one of the big outstanding challenges in AI because untangling the meaning of spoken or written text so often relies on a broader understanding of the world, or commonsense knowledge (see “AI’s Language Problem”).
It turns out that training a machine-learning system to translate between two languages automatically teaches it useful things about the relationship and appropriate context of words. When this system is used as the foundation for another machine-learning system—one trained to hold a conversation, say, or to detect the sentiment in text—it performs far better than a system trained from scratch.