How Language Led To The Artificial Intelligence Revolution

In 2013 I had a long interview with Peter Lee, corporate vice president of Microsoft Research, about advances in machine learning and neural networks and how language would be the focal point of artificial intelligence in the coming years.

At the time the notion of artificial intelligence and machine learning seemed like a “blue sky” researcher’s fantasy. Artificial intelligence was something coming down the road … but not soon.

I wish I had taken the talk more seriously.

Language is, and will continue to be, the most important tool for the advancement of artificial intelligence. In 2017, natural language understanding engines are what drive the advancement of bots and voice-activated personal assistants like Microsoft’s Cortana, Google Assistant, Amazon’s Alexa and Apple’s Siri. Language was the starting point and the locus of all new machine learning capabilities that have come out in recent years.

Language—both text and spoken—is what is giving rise to a whole new era of human-computer interaction. When people had trouble imagining what could possibly come after smartphone apps as the pinnacle of user experience, researchers were building the tools for a whole new generation of interface based on language.

Read more: ARC

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