What is artificial intelligence? An explanation


Discover what artificial intelligence is, how it works and what types there are. An easy-to-understand introduction to the fascinating world of AI and its applications. So, what is artificial intelligence anyway?

Artificial intelligence (AI) is a hot topic that everyone is talking about. But what exactly is behind this term? Various terms and concepts within artificial intelligence help to understand the different approaches and interpretations in this rapidly developing field. Let's take a closer look.

Definition of artificial intelligence

Artificial intelligence, also known as AI, encompasses technologies that mimic human cognitive abilities. There are various definitions and categories of artificial intelligence, ranging from basic concepts to specific aspects such as transparency and compliance with European regulations. These include, for example, strategic thinking, problem solving and linguistic abilities.

Types of artificial intelligence

There are two main categories of AI:

  1. Weak AI (weak AI/narrow AI): This is currently the predominant form. It solves specific problems in clearly defined areas. One of the best-known examples is facial recognition, which is used in security applications, or voice assistants such as Siri and Alexa, which influence our everyday lives.
  2. Strong AIThis hypothetical form would attempt to imitate humans completely, but does not yet exist.

How does AI work?

AI systems work as software agents that perceive their environment and react to it. They use various data sources, from sensors to internet data, to perform the following functions:

  • Assessment of perceptions
  • Derivation of conclusions
  • Execution of actions

Important sub-areas of AI

Machine learning (ML)

Machine learning is a central component of AI. AI research aims to technically replicate human learning and thinking and to develop new technologies and systems that can learn independently and solve complex problems. It enables systems to learn from data and recognize patterns. There are three main types:

  1. Supervised learning
  2. Unsupervised learning
  3. Reinforcing learning

Deep learning

Deep learning is an advanced form of machine learning that uses artificial neural networks to recognize particularly complex relationships in large amounts of data. AI models are able to solve specific tasks such as image recognition or generative AI and pose challenges in the development of explainable and secure systems.

Applications of AI

AI is used in many areas, including:

  • Automation of repetitive tasks
  • Voice assistants
  • Image recognition. Modern AI models are not only capable of analyzing images, but also of generating creative content such as original images and recognizing patterns in unstructured data.
  • Autonomous driving
  • Personalized recommendations

AI applications in safety-critical areas such as automotive and biometrics pose particular challenges and requirements in terms of the robustness and reliability of the systems.

AI and security

Safe AI: Safeguarding AI systems

The safety of AI systems is a crucial aspect that must be taken into account in the development and use of AI technologies. Safe AI is an approach that aims to make AI systems safe and reliable. This can be achieved by implementing security measures such as data encryption, access control and regular software updates. In addition, it is important that AI systems are transparent and explainable to ensure that their decisions and actions are comprehensible. This is the only way to strengthen trust in AI technologies and increase their acceptance in society.

AI and society

Impact of AI on the cyber threat landscape

AI technology is having a significant impact on the cyber threat landscape. AI systems can be used to detect and defend against cyberattacks by identifying unusual patterns and anomalies in the data. At the same time, however, attackers can also use AI to develop new, sophisticated attacks and bypass security measures. It is therefore of utmost importance that organizations and individuals are aware of the risks and challenges associated with AI technology. Measures such as the implementation of firewalls, antivirus software and regular software updates are essential to protect systems and data. Only through a comprehensive security concept can the balance between the benefits and potential dangers of AI technology be maintained.

The future of AI

The development of AI is progressing rapidly. With increasing computing power and data availability, AI systems are becoming more and more powerful and are finding their way into more and more areas of our daily lives.

Artificial intelligence is undoubtedly one of the most important technologies of our time. It offers enormous opportunities, but also poses challenges that need to be overcome. The more we understand about AI, the better we can exploit its potential and use it responsibly.