Grundlagen

Generative AI

Definition

AI models capable of creating new content—text, images, code, audio, or video—rather than just classifying existing data. Generative AI is driving a productivity wave in enterprise workflows but also introduces governance challenges around accuracy and intellectual property.

Beispiele

ChatGPT
Midjourney
GitHub Copilot
Stable Diffusion

Verwandte Begriffe

Large Language Model (LLM)

AI models trained on vast amounts of text data that can understand and generate human-like text. Examples include GPT-4, Claude, and Llama. LLMs power modern chatbots, content generation, and code assistance tools.

Diffusion Model

A class of generative models that learn to reverse a gradual noise-addition process to produce high-quality images, audio, or video from random noise. Diffusion models power leading image generators such as Stable Diffusion and DALL-E 3.

Hallucination

The tendency of LLMs to generate plausible-sounding but factually incorrect or fabricated content. Hallucination is a primary enterprise risk for generative AI and is mitigated through RAG, grounding techniques, output validation, and human-in-the-loop review processes.

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