A recycling depot already scores bin weight with a small fitted predictor. A vendor then offers a many-layer network on camera frames of the sorting line, and a third pitch offers a text model that drafts weekly recycling memos. How are classical machine learning, deep learning, and a generative LLM related?

Short Explanation

Think of three nested boxes. Machine learning is the outer box, deep learning sits inside it, and a generative LLM is a specialized deep model for text. They are not synonyms, and the small fitted predictor is still ML.

Full Explanation

Machine learning is the outer set. Deep learning is a subset that uses multi-layer neural networks. A generative LLM is a specialized deep model for text, not a replacement name for every ML method. Treating the three as synonyms, or putting an LLM outside deep learning, misses that nesting.

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