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Discriminative and Generative

Updated Jan 14, 2025 ·

Overview​

Artificial Intelligence (AI) refers to the ability of machines to mimic human cognitive functions like learning and problem-solving. It can be broadly categorized into two types:

  • Discriminative AI
  • Generative AI

Discriminative AI​

Discriminative AI focuses on classification tasks and predictions based on models trained using supervised learning techniques. It learns from labeled datasets to distinguish between different classes or categories.

  • Works with labeled data to predict outcomes
  • Commonly used for classification and anomaly detection tasks

Discriminative models learn the relationship between input data and labels, often predicting a number, class, or probability. An example is detecting machine anomalies based on sensor data.

Discriminative AI

Generative AI​

Generative AI, on the other hand, is trained using unsupervised or semi-supervised learning techniques. It is capable of generating new data that mimics the patterns of the training data.

  • Often uses large datasets of unstructured content
  • Can generate creative content like images, text, or music

Generative AI models focus on understanding the patterns within data and producing new, similar content. For instance, it can generate text in natural language such as English.

Generative AI