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Generative and discriminative AI are two forms of machine learning. The difference lies in how they handle data and in their output.
The Difference Between Generative and Discriminative AI
Generative and discriminative artificial intelligence are different ways of handling data and instructions to generate output.
- Generative AI is primarily used to create new content based on existing data. Using deep learning and artificial neural networks, generative AI can, for example, generate image, text, and video content.
- Discriminative AI , on the other hand, is primarily used for classifying datasets. Unlike generative AI, it does not create new content; instead, the input is simply interpreted and output according to the respective instructions.
Examples and Applications of Generative and Discriminative AI
Due to their different approaches to handling data, generative and discriminative artificial intelligence are also used in other fields and for other tasks. This can be illustrated with a simple example:
- Generative AI is capable of generating an appropriate output in response to instructions such as: “Write me a text about the lifestyle of robins,” or “Draw me a robin.” An example of generative AI is the chatbot ChatGPT.
- Discriminative AI, on the other hand, works with prompts such as: “Is this image of a robin or a blackbird?” or “Is that the song of a robin?” Examples of discriminative AI include speech recognition programs like Alexa.
