Robotic arms prepare dishes at a hot pot restaurant in Beijing, China on Dec. 5, 2018. Read the article in TIME.

In 2015, a man named Nigel Richards won the title of French-­language Scrabble World Champion. This was especially noteworthy because Richards does not speak French. What the New Zealander had done was memorize each of the 386,000 words in the entire French Scrabble dictionary, in the space of just nine weeks.

Richards’ impressive feat is a useful metaphor for how artificial intelligence works—real AI, not the paranoid fantasies that some self-­appointed “futurists” like to warn us about. Just as Richards committed vast troves of words to memory in order to master the domain of the Scrabble board, state-of-the-art AI—or deep ­learning—takes in massive amounts of data from a single domain and automatically learns from the data to make specific decisions within that domain. Deep learning can automatically optimize human-given goals—called ­“objective ­functions”—with unlimited memory and superhuman accuracy.

Richards’ impressive feat is a useful metaphor for how artificial intelligence works—real AI, not the paranoid fantasies that some self-­appointed “futurists” like to warn us about. Just as Richards committed vast troves of words to memory in order to master the domain of the Scrabble board, state-of-the-art AI—or deep ­learning—takes in massive amounts of data from a single domain and automatically learns from the data to make specific decisions within that domain. Deep learning can automatically optimize human-given goals—called ­“objective ­functions”—with unlimited memory and superhuman accuracy.

 

Read the full article in TIME.

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