The meaning of words can often be ambiguous, especially to those whose first language is not English. This also can pose a challenge with artificial intelligence (AI) technologies like machine learning as they learn to interpret and analyze language. This interesting topic came to us from Phys.org in their article, “Machine learning reveals role of culture in shaping meanings of words.”
According to a machine learning analysis of dozens of languages conducted at Princeton University, the meaning of words does not necessarily refer to an intrinsic, essential constant. Instead, it is significantly shaped by culture, history and geography.
Because language is the prism through which we conceptualize and understand the world, linguists and anthropologists have worked to simplify the complexity that can be our communication systems.
Machine learning models have recently emerged that use the concept of semantic associations or simply words that have meaningful relationships to each other, which linguists find to be one of the best ways to go about defining a word and comparing it to another.
Melody K. Smith
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