AI-supported tools such as smart fridges, assistance systems in cars and Alexa, Siri & Co. have long since become part of our everyday lives. However, artificial intelligence is continuing to grow - many use cases are being developed at a rapid pace for various industries and, with its economic benefits, it will also significantly change the way companies work and interact with customers in the future.
One of the most versatile AI technologies is machine learning. It enables IT systems to learn from data without being explicitly programmed. With the help of algorithms, they analyze data sets and attempt to generate new, artificial knowledge from recognized rules and regularities and develop solutions that can be automatically applied to future events.
Machine learning is often used in robotics, data mining and automation; it is also an important component of autonomous systems used in industry, healthcare and the transportation sector.
This technology is a sub-area of machine learning. Deep learning imitates multi-level neural networks, allowing the system to learn in structures similar to those of the human brain. This is how artificial intelligence is trained: Certain patterns and models that can be recognized in the analysis of huge amounts of data are reconnected using the artificial neural network. In this way, more and more layers develop within the neural network, and the more linking levels are formed, the more complex tasks the artificial intelligence can solve.
Deep learning is mainly used in text processing, image classification and pattern recognition.
Computer vision is a technology that enables machines to capture and process visual data. It enables computers to analyze images and videos and automatically extract information from them that would be difficult for a human to recognize. Computer vision has many practical applications such as facial recognition, autonomous driving, medical imaging and robotics.
NLP helps to understand and process natural language in order to enable communication between humans and machines on the basis of language. It is primarily used in speech recognition systems, chatbots and voice assistants.
A technology that makes it possible to automate processes or make complex decisions by implementing algorithms, such as in autonomous driving. It is used wherever we encounter networked technical systems: In automated production, self-driving cars, household robots, etc.
AI technologies are used in a wide variety of areas to analyze large amounts of data and identify correlations. With their help, complex problems can be solved, business processes optimized and services offered in many industries, while comprehensive data analysis also provides companies with the basis for better decisions.
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