Deep Learning (DL) describes machine learning in neural networks with multiple layers. This approach can be used to identify hugely complex patterns and solve problems. DL has achieved significant progress in areas such as image recognition.

Artificial intelligence (AI) is the attempt to automate intelligent behaviour. The interplay between algorithms and data allows machines to learn, analyse and solve complex tasks that would usually require human intelligence. This technology enables machines to identify patterns, make decisions and solve problems. There are various different approaches and methods for developing intelligent systems.

Machine Learning (ML) is one of the best-known methods for developing AI applications. ML models are not programmed, but rather trained and further developed using data.

To this end, a suitable algorithm is consistently fed with available data until patterns are identified and the desired results are achieved. Following this training process, the model can be applied to new, unknown data in order to make predictions or take decisions.

Natural Language Processing (NLP) is the processing and analysis of human language. This technology enables machines to understand, interpret and respond to natural language. This can be used to develop language assistants and hold conversations with AI systems.

Neural Networks (NN) simulate how the human brain works. It consists of artificial neurons and layers that process information in order to learn about complex patterns and relationships. Areas of application include voice recognition.

Knowledge-based systems use the knowledge gathered by experts and a set of rules in a specific area to develop new AI applications. In their relevant subject area, they can answer questions, analyse problems and provide tailored solutions.