Artificial Intelligence (AI), Machine Learning (ML), Deep Learning (DL), and Generative AI are distinct yet interconnected fields within the realm of AI. Here is the correct hierarchical relationship among them:
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Artificial Intelligence (AI): AI encompasses a broad range of techniques focused on creating intelligent machines that can perform tasks that typically require human intelligence, such as visual perception, speech recognition, decision-making, and language translation.
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Machine Learning (ML): Machine learning is a subset of AI that focuses on the development of algorithms that enable systems to learn from and make predictions or decisions based on input data.
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Deep Learning (DL): Deep learning is a subset of machine learning that uses neural networks with many layers to learn and make predictions or decisions based on input data.
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Generative AI: Generative AI is an advanced branch of AI that utilizes machine learning techniques to generate new, original content such as images, text, audio, and video. Unlike traditional machine learning, which focuses on mapping input to output, generative models aim to produce novel and realistic outputs based on the patterns and information present in the training data.
Therefore, AI is the broadest field, while ML is a subset of AI, and DL is a subset of ML. Generative AI is a subset of machine learning that focuses on generating new content based on the patterns and information present in the training data.
