What Is Artificial Intelligence?
iAs of: May 2026
Market data and model names in this module reflect the state as of May 2026. Fundamental concepts (what AI is, history, open vs. closed source) remain stable.
Wissen
What does "Artificial Intelligence" actually mean?
Imagine teaching a child to tell dogs apart from cats. You show it hundreds of photos, and eventually it recognizes the patterns on its own. That is exactly how Artificial Intelligence (AI) works at its core: a computer program learns from examples instead of following rigid rules.
Artificial Intelligence (AI) refers to computer systems that can perform tasks that normally require human intelligence -- for example, understanding language, recognizing images, making decisions, or writing text.
iAI in Everyday Life
You probably already use AI every day: when Spotify suggests a song, when your smartphone recognizes your face, or when Google Maps calculates the fastest route -- there is Artificial Intelligence behind it.
Everyday Examples of AI
- Voice assistants: Siri, Alexa, and Google Assistant understand spoken language
- Recommendations: Netflix, Spotify, and YouTube suggest content you might like
- Spam filters: Your email program automatically detects unwanted messages
- Navigation: Google Maps predicts traffic jams and calculates optimal routes
- Translation: DeepL and Google Translate translate texts in real time
AI is not a single program but an umbrella term for many different technologies that all share a common goal: making machines more intelligent.
Which of these examples does NOT use Artificial Intelligence?
Strong vs. Weak AI
In AI research, two types of Artificial Intelligence are distinguished:
Weak AI (Narrow AI) is specialized for a specific task. A chess computer can play chess but cannot write text. A spam filter detects unwanted emails but cannot paint pictures. All AI systems that exist today are weak AI -- even though they are often better than humans in their specialty.
Strong AI (General AI, or AGI) would be a machine that can perform any intellectual task as well as or better than a human -- from cooking to writing poetry to conducting scientific research. AGI so far exists only in theory and in science fiction movies.
!Important to Know
Even impressive systems like ChatGPT or Claude are weak AI. They can write astonishingly good text, but they do not understand the world the way humans do. They recognize patterns in data -- that is something different from true understanding.
Verstehen
Think of the difference this way: a calculator is like a math genius -- unbeatable at calculations, but completely helpless if you ask it to paint a picture. That is weak AI. A human, on the other hand, can calculate, paint, cook, learn languages, and much more. That would be strong AI.
AI Is More Than ChatGPT
Many people equate "AI" with ChatGPT. But Artificial Intelligence is a much broader term. Imagine three nested circles:
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The outer circle — AI encompasses all systems that exhibit intelligent behavior: Computer Vision (image recognition), robotics, speech recognition, and much more. Your smartphone uses AI for facial recognition, your car for lane-keeping assist.
The middle circle — LLM (Large Language Models) are a special type of AI that specializes in language. They can understand, generate, and translate text.
The inner circle — Chatbots like ChatGPT, Claude, and Gemini are products built on top of LLMs. They are what most people mean when they say "AI" — but they are just the tip of the iceberg.
*Paradigm Shift: From Calculator to Brain
Previous computers were like extremely fast calculators: they execute commands that humans programmed. AI is fundamentally different — it learns from examples and develops its own patterns. This is the biggest shift in computing since the invention of the computer itself.
What is the difference between AI and an LLM?
Why Is AI So Relevant Right Now?
The idea of Artificial Intelligence has been around since the 1950s. Why are we experiencing the big breakthrough right now? Three factors come together:
1. Computing Power (Hardware)
Modern graphics cards (GPUs) from NVIDIA can perform billions of calculations simultaneously. What used to take weeks now takes hours. Specialized AI chips like Google's TPUs and NVIDIA's Rubin generation make training huge models possible in the first place.
2. Data
The internet has generated an unimaginable amount of text, images, videos, and other data. AI systems need data like cars need fuel -- the more high-quality data, the better they learn.
3. Algorithms
Researchers have achieved decisive breakthroughs in recent years. In particular, the so-called Transformer architecture (developed in 2017 at Google) laid the foundation for all modern language models -- from GPT to Claude to Gemini.
*The Magic Trinity
Hardware + Data + Algorithms = the current AI boom. If any one of these three elements were missing, the breakthrough would not have happened. In the 1980s, the algorithms were already similar, but computers were too slow and there was too little data.
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These three factors reinforce each other: better hardware enables larger models, larger models need more data, and more data leads to better algorithms. This cycle has been accelerating since 2020.
Which factor does NOT belong to the three main reasons for the current AI boom?
Anwenden
If you want to understand AI, start by consciously noticing it in everyday life. Pay attention to which services you use daily that employ AI -- from music recommendations to voice assistants to facial recognition. This sharpens your understanding of how broadly AI is already deployed.
Reflect
Artificial Intelligence is not magic and not fiction -- it is a technology that already shapes our everyday lives. In the next section, we will look at how AI has developed historically: from the first dreams of the 1950s through several "AI winters" to today's boom with ChatGPT and Claude.