Künstliche Intelligenz Natural Language Processing Linguistik

HOW TO AI: Navigating the buzzwords of artificial intelligence

Arti­fi­ci­al intel­li­gence, machi­ne learning, deep learning and natu­ral lan­guage pro­ces­sing – when the con­ver­sa­ti­on turns to arti­fi­ci­al intel­li­gence and the ubi­qui­tous buz­zwor­ds begin to fly, non-deve­l­o­­pers soon switch off. The­se terms are often used too broad­ly, syn­ony­mous­ly, or sim­ply incor­rect­ly. To shed a litt­le light on this mat­ter, and to help you deal with AI

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keeping robots and humans separate

Keeping Robots and Humans Separate

At the begin­ning of this month, the Finan­ci­al Times posted an arti­cle about the set­up of hybrid systems—where auto­ma­ted pro­ces­ses and humans work together—and of the dif­fe­rent approa­ches that they often take. The sto­ry begins by tel­ling of how a pede­stri­an was kil­led by one of Uber’s self-dri­ving cars. It was an acci­dent that occur­red when the

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textengine.io — The Democratisation of Automation

We are pret­ty posi­ti­ve about Natu­ral Lan­guage Gene­ra­ti­on (NLG). It would be a sur­pri­se, frank­ly, if we were not. We honest­ly belie­ve that NLG solu­ti­ons can be vital to ans­we­ring ques­ti­ons facing com­pa­nies and orga­ni­sa­ti­ons today. The­re are nume­rous bene­fits to com­pa­nies that deci­de to imple­ment NLG pro­ducts as a sup­port to their ever­y­day ope­ra­ti­ons.

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