Learn how predictive AI and generative AI differ in their goals, capabilities, and use cases, and how they can help businesses solve various problems and create value.
Table of Contents
Question
Which best describes the difference between predictive AI and generative AI?
A. Predictive AI and generative AI have the same capabilities but differ in the type of input they receive; predictive AI receives raw data whereas generative AI receives natural language.
B. Predictive AI uses machine learning to classify or predict outputs from its input data whereas generative AI does not use machine learning to generate its output.
C. Predictive AI uses machine learning to classify or predict outputs from its input data whereas generative AI uses machine leaning to generate new and original output for a given input.
Answer
C. Predictive AI uses machine learning to classify or predict outputs from its input data whereas generative AI uses machine leaning to generate new and original output for a given input.
Explanation
The correct answer is C. Predictive AI uses machine learning to classify or predict outputs from its input data whereas generative AI uses machine leaning to generate new and original output for a given input. Predictive AI and generative AI are two types of AI applications that have different goals and capabilities. Predictive AI aims to analyze existing data and make predictions or recommendations based on patterns and trends. For example, predictive AI can be used to forecast sales, detect fraud, or recommend products. Generative AI, on the other hand, aims to create new data or content that is novel and realistic. For example, generative AI can be used to generate images, text, music, or videos.
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