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Answer :
Generative AI is a fascinating subfield of artificial intelligence that stands out from traditional AI due to its ability to create new content. Let's explore the differences between Generative AI and Traditional AI by analyzing the given multiple-choice options.
Generative AI is designed for solving clearly defined problems.
- This option (A) is more characteristic of Traditional AI. Traditional AI systems are often built to solve specific, well-defined problems through a series of programmed steps and rules.
Generative AI generates new data based on existing data.
- Option (B) accurately describes Generative AI. Generative AI models, like GPT (Generative Pre-trained Transformer), have the ability to create new content, such as text, images, or music, based on patterns and information learned from existing datasets. This generation aspect is what makes Generative AI distinctive.
Generative AI focuses on performing a specific task intelligently.
- This option (C) aligns more with Traditional AI, which is typically designed to perform specific tasks, such as playing chess or diagnosing diseases, using intelligent algorithms.
Generative AI consists of rules programmed to perform specific tasks.
- Option (D) also describes Traditional AI, where tasks are accomplished through predefined rules and logic.
Therefore, the correct choice here is B. Generative AI generates new data based on existing data.
Generative AI models are incredibly versatile and can be used in various applications, including creating realistic images, composing music, or even coding. These models learn from large amounts of data and use it to generate new, original outputs, which is why they are called 'generative.'
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