What is AI
Artificial Intelligence
The discipline of artificial intelligence (AI) deals with the development of systems that imitate the characteristics of human intelligence.
The scientific community has been dealing with the term artificial intelligence, which was largely coined by John McCarthy, for about 60 years. In addition, progress in the field of machine learning (ML), which is considered a key technology for AI, is creating considerable potential and opportunities through AI:
- Process optimisation
- Cost reduction
- Quality improvement of products, processes and services
- Risk reduction
In general, the idea behind most machine learning techniques is that a computer system learns to perform a task, similarly to a human, by studying a certain set of training examples (or training data). The computer system is then able to perform the same task with unknown, new data. Progress in the field of ML can be attributed primarily to the development of new learning algorithms and theories, the availability of increasingly large amounts of data (big data) and a massive increase in computing power.
Machine Learning is the field of study that gives computer the ability to learn without being explicitly programmed.
In connection with AI, the capture of natural language and the processing of it with the help of rules and algorithms is described as Natural Language Processing (NLP).
Deep learning is a sub-area of machine learning. Neural networks are used here in connection with very large amounts of data. The structure of the neural networks is inspired by the functioning of the human brain.
In the field of AI, the recognition of objects on an image is referred to as image recognition. This usually involves assigning objects on an image to a previously determined category.
IT systems can use machine learning, based on existing data sets and algorithms, to recognise patterns in data and develop problem-specific solutions.
Transparency of AI
Aspects of AI
Supervised learning is a subfield of machine learning.
Unsupervised learning is a subfield of machine learning.
Reinforcement learning is a subfield of machine learning.