12 Key Terms to Help You Understand Artificial Intelligence
Knowing basic AI terminology helps you confidently navigate conversations, articles, and everyday discussions about artificial intelligence. This short list clearly explains essential terms, without unnecessary theory or jargon, making them easy to grasp immediately.
Artificial Intelligence (AI)
Technology enabling computers or software to perform tasks typically requiring human intelligence, such as analyzing data, drawing conclusions, or proposing solutions. AI is often associated with automation, smart services, and virtual assistants.
Large Language Model (LLM)
A type of neural network trained on vast amounts of text data. These models understand text meaning and can generate new content upon request. ChatGPT is an example of an LLM.
Agent
Software or systems that independently perform tasks, respond to environmental changes, and interact with other software or humans when needed. Agents can search for information, book tickets, analyze data, and even coordinate other AI services.
Generative AI
Technologies that not only analyze data but also create new content, including text, images, music, or video. These systems generate original material based on learned patterns.
Chatbot
Software you can converse or interact with as if speaking to another human. Chatbots answer questions, provide information, or simply hold a conversation. They're a user-friendly interface for interacting with AI.
Natural Language Processing (NLP)
An AI field allowing computers to understand human speech and text. NLP powers translation tools, voice assistants, and systems analyzing customer feedback or messages.
Computer Vision
An area of AI enabling machines to "see" and recognize objects, faces, or scenes in images and videos. Used in security systems, medicine, and autonomous vehicles, among other applications.
Prompt
A request or instruction given by a user to an AI model. A well-formulated prompt clearly defines what the model should do or the question it needs to answer, leading to useful results.
AI Hallucination
A situation where AI confidently provides information that isn’t accurate or real. Essentially, the model "makes up" facts, even if they sound believable.
AI Ethics
Concerns around safety, honesty, privacy, and fairness in developing and deploying artificial intelligence. Ethical guidelines ensure AI benefits humanity and avoids causing harm.
Model Training
The process of teaching AI using examples, where the system analyzes data and gradually improves its task performance. Without training, an AI model cannot produce high-quality responses or make accurate predictions.
Artificial General Intelligence (AGI)
Currently a theoretical concept: an AI capable of performing any intellectual task humans can do, not just specialized ones. AGI is widely discussed in scientific circles as a possible future milestone in technology development.
These terms frequently appear in conversations and articles about artificial intelligence. Understanding them helps clarify what modern AI systems truly involve.
