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Generative AI & LLMs: How are They Different or Similar?
- Generative AI and Large Language Models (LLMs) differ significantly in purpose, architecture, and capabilities.
- Generative AI refers to a class of AI systems designed to create new content, based on patterns learned from existing data.
- Generative AI functions by learning patterns from vast amounts of data and producing something new from scratch.
- Generative AI uses neural networks, which are algorithms inspired by how the human brain works.
- Recurrent Neural Networks (RNNs) are often used when generating text or music.
- Generative Adversarial Networks (GANs) work by pitting two neural networks against each other.
- Large Language Models (LLMs) are a specialized form of artificial intelligence designed to understand and generate human language.
- LLMs leverage Natural Language Processing (NLP), a branch of AI dedicated to understanding and interpreting human language.
- LLMs use an architecture called transformers, a model that revolutionized natural language processing.
- Generative AI and LLMs complement each other well, enabling the creation of unique, contextually relevant content across various media types.
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