Is Google misogynistic? The ranking for certain keywords certainly provides grounds for this suspicion. However, the phenomenon of unequal treatment isn’t really the fault of the algorithms but is a fundamental problem with the German language. And those who want to can ensure for themselves that the results list is free from discrimination.
Artificial intelligence has long been a reality in copywriting. On the basis of structured data, machines create product descriptions, stock market information, and weather forecasts. So well in fact that the results can hardly be distinguished from compositions produced by humans. But AI can do even more: the creation of fairy tales and stories is also possible at the push of a button.
Text-to-speech (TTS) – this term is virtually self-explanatory: It is the conversion of text into spoken. The programs used are being continually further developed words.
Although there are still no applications today in which the machine origin of the spoken word is not discernible, the technological progress is unstoppable. What are the advantages of text-to-speech systems? Vision impaired people can benefit from those systems, besides they can also be used by companies as a means of expanding their outreach.
Natural language processing, also known as NLP, describes the machine processing of natural language. NLP is a sub-field of artificial intelligence (AI). Humans are more and more frequently coming into contact with AI in their daily lives – whether with Alexa at home, with OK Google on their smartphone or when making a call to customer support. Today, humans are speaking more often with machines. And the areas of application of NLP are steadily on the rise.
Data are the foundation for training algorithms. The more realistic the data, the better the results. This is because artificial intelligence is based on precise and reliable information for training its algorithms. This is obvious but it is often overlooked. The training data are realistic when they reflect the data that the AI system gathers in real operation. Unrealistic data sets prevent machine learning and lead to expensive false interpretations.