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  2. QANDA - Wikipedia

    en.wikipedia.org/wiki/QANDA

    QANDA (stands for 'Q and A') is an AI-based learning platform developed by Mathpresso Inc., a South Korea-based education technology company. Its best known feature is a solution search, which uses optical character recognition technology to scan problems and provide step-by-step solutions and learning content.

  3. You.com - Wikipedia

    en.wikipedia.org/wiki/You.com

    On December 23, 2022, You.com was the first search engine to launch a ChatGPT-style chatbot with live web results alongside its responses. [25] [26] [12] Initially known as YouChat, [27] the chatbot was primarily based on the GPT-3.5 large language model and could answer questions, suggest ideas, [28] translate text, [29] summarize articles, compose emails, and write code snippets, while ...

  4. Question answering - Wikipedia

    en.wikipedia.org/wiki/Question_answering

    Question answering (QA) is a computer science discipline within the fields of information retrieval and natural language processing (NLP) that is concerned with building systems that automatically answer questions that are posed by humans in a natural language.

  5. IBM Watson - Wikipedia

    en.wikipedia.org/wiki/IBM_Watson

    The high-level architecture of IBM's DeepQA used in Watson [9]. Watson was created as a question answering (QA) computing system that IBM built to apply advanced natural language processing, information retrieval, knowledge representation, automated reasoning, and machine learning technologies to the field of open domain question answering.

  6. Artificial intelligence - Wikipedia

    en.wikipedia.org/wiki/Artificial_intelligence

    Artificial intelligence (AI), in its broadest sense, is intelligence exhibited by machines, particularly computer systems.It is a field of research in computer science that develops and studies methods and software that enable machines to perceive their environment and use learning and intelligence to take actions that maximize their chances of achieving defined goals. [1]

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  8. 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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