#MachineLearning is getting more and more relevant by the day, with an increasing number of commercial applications hitting the market and impacting the life of communities all over the globe. It is thus gaining the spotlight in media discussions. [2/?]
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The research community (and the biggest companies in the space) are English-speaking but the impact of these methods goes far beyond language boundaries. Nonetheless, we keep talking about these topics borrowing English words in our native languages. [3/?]
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English words sound "correct" and "technical" to the ear of the expert practitioner, but they act as an additional barrier when the broader public tries to approach these topics. Each term becomes its own island and comprehension is seriously hindered. [4/?]
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It is thus important, I believe, to bridge this gap and try to find the proper equivalents for established terms in the
#MachineLearning space. We need to start building a native vocabulary to talk about these topics as they become more and more a public concern. [5/?]Show this thread -
@seb_ruder's article was a great opportunity to propose new translations for#MachineLearning terms that currently do not seem to have an Italian equivalent. It's a starting point - I plan to do much more work in this direction with@iaml_it this year. [6/?]Show this thread -
I am also curious to know what is the situation in other languages and what approaches people are using to address the issue! [7/end]
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Writing about stuff to learn how it works, mostly in Rust.
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