Is Google Misogynistic?

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.

Text classification – areas of application on the Internet

There are billions of websites with countless texts on the Internet. This makes it difficult to keep track of them. Text classification is a method that provides an overall view and structures the offer. Which application areas are there for text classifications in the World Wide Web?

Realistic training data for machine learning

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.

A Snapshot of AI, Machine Learning, and Deep Learning

Real-world examples, prominent use cases, and AI’s (artificial intelligence) potential

The industrialized world is full of machines that outdo humans in strength and speed. Cranes lift steel beams to towering heights, car engines send passengers flying down the road at impossible speeds, and tree shredders pulverize entire pine trunks in a snap. Such inventions replicate and vastly outperform humans at tasks requiring physical exertion. They possess “artificial brawn”.

What then is artificial intelligence?

At a first pass, we can think of AI as a machine (i.e., a computer) replicating human cognitive tasks. A calculator, for example, embodies basic AI to do a job for which humans must use their brains: math. While definitions of “artificial intelligence” abound, Peter Norvig and Stuart Russell, forefathers of the discipline, explain it well when talking about “rational agents”. A rational agent, they say, “acts so as to achieve the best outcome or, when there is uncertainty, the best expected outcome”. Most explorations into AI fit the “rational agent” description in some way. An exemplary case of AI application in developing rational agents is in the realm of face recognition software, where training data plays a critical role. For insight on how training data influences the effectiveness of such technology, you might find this case study on training data for face recognition software highly informative.

Image annotation and artificial intelligence

Everyone has heard something about artificial intelligence. However, the term image annotation is less common. Image annotation describes the classification of information that is of relevance to an image. Recognizing the content of images is an important factor for many automatized processes. In order for machines to capture the meaning and individual components of images, artificial intelligence is required, in which a human-like analysis of images is simulated. To achieve this, countless training data in terms of human input are required.