Natural language processing models capture rich knowledge of words’ meanings through statistics.
Among adults who vary in their knowledge of number words, the ability to reason about numbers is bound by the highest number they can count to.
A new method automatically describes, in natural language, what the individual components of a neural network do.
Reducing the complexity of a powerful machine-learning model may help level the playing field for automatic speech-recognition around the world.
Neuroscientists find the internal workings of next-word prediction models resemble those of language-processing centers in the brain.
System developed at MIT CSAIL aims to help linguists decipher languages that have been lost to history.
Even when people believed Hillary Clinton would win the 2016 election, they did not use “she” to refer to the next president.
Using deductive reasoning, the bot identifies friend or foe to ensure victory over humans in certain online games.
A neural network can read scientific papers and render a plain-English summary.
Study uncovers language patterns that AI models link to factual and false articles; underscores need for further testing.
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