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Machine learning means you have a painstaking, slow process of acquiring information through millions of examples.
Machine learning means that a computer can identify and replicate the patterns in data on its own.
Machine learning means learning from data; AI is a buzzword.
But the rise of text-mining and machine learning means that we must cast our net much wider.
The combination of these data sources, with machine learning, means that data can be synthesized and applied in new ways.
Compounding this, the perceived complexity of machine learning means that when it fails there is little recognition of harm and no appeal for those affected, thanks to what Cathy O'Neil calls "the authority of the inscrutable".
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Lynch says developments in computer vision and machine learning mean the ability of computers to recognize objects in real world environments has made leaps and bounds in recent years.
And there is a virtuous cycle here: more data means better machine learning, which means better services and more users, which means more data.
However, the way machine learning works means that making algorithms available isn't necessarily as useful as one might think.
So in particular, we use supervised machine learning, which means that we take a set of our data that's labeled, and we call this our training data that we train our classifier on.
Gurdeep Pall, Microsoft's corporate vice-president of Skype and Lync, said in a blog post that Skype Translator would "open up endless possibilities", adding: "Skype Translator relies on machine learning, which means that the more the technology is used, the smarter it gets.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com