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  2. Generative artificial intelligence - Wikipedia

    en.wikipedia.org/wiki/Generative_artificial...

    Generative artificial intelligence (generative AI, GenAI, [1] or GAI) is a subset of artificial intelligence that uses generative models to produce text, images, videos, or other forms of data. [ 2 ] [ 3 ] [ 4 ] These models learn the underlying patterns and structures of their training data and use them to produce new data [ 5 ] [ 6 ] based on ...

  3. Prompt engineering - Wikipedia

    en.wikipedia.org/wiki/Prompt_engineering

    Prompt engineering is the process of structuring an instruction that can be interpreted and understood by a generative artificial intelligence (AI) model. [1] [2] A prompt is natural language text describing the task that an AI should perform. [3]

  4. AI in education - Wikipedia

    en.wikipedia.org/wiki/AI_in_education

    Ai companies that focus on education, are currently preoccupied with Generative artificial intelligence (GAI), although data science and data analytics is another popular educational theme. At present, there is little scientific consensus on what Ai is or how to classify and sub-categorize Ai [ 19 ] [ 20 ] This has not hampered the growth of Ai ...

  5. Retrieval-augmented generation - Wikipedia

    en.wikipedia.org/wiki/Retrieval-augmented_generation

    Retrieval Augmented Generation (RAG) is a technique that grants generative artificial intelligence models information retrieval capabilities. It modifies interactions with a large language model (LLM) so that the model responds to user queries with reference to a specified set of documents, using this information to augment information drawn from its own vast, static training data.

  6. Why We’re Introducing Generative AI to TIME’s Journalism

    www.aol.com/why-introducing-generative-ai-time...

    Of the experience, Scale AI’s Chief Strategy Officer Jason Droege says, "TIME AI shows how generative AI can amplify engagement, broaden accessibility, and foster deeper connections between ...

  7. Multimodal learning - Wikipedia

    en.wikipedia.org/wiki/Multimodal_learning

    Multimodal learning is a type of deep learning that integrates and processes multiple types of data, referred to as modalities, such as text, audio, images, or video.This integration allows for a more holistic understanding of complex data, improving model performance in tasks like visual question answering, cross-modal retrieval, [1] text-to-image generation, [2] aesthetic ranking, [3] and ...

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