Techniken

Generative Adversarial Network (GAN)

Definition

A framework consisting of two neural networks—a generator and a discriminator—that compete against each other. The generator creates synthetic data; the discriminator tries to distinguish real from fake. GANs produce highly realistic images and are also studied in the context of deepfake detection.

Verwandte Begriffe

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.

Generative AI

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.

Deepfake Detection

AI-powered methods for identifying media—images, video, audio—that have been synthetically generated or manipulated using generative AI. Deepfake detection is increasingly important for trust infrastructure in elections, financial services, and media.

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