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  2. AI Models Are Getting Smarter. New Tests Are Racing to ... - AOL

    www.aol.com/news/ai-models-getting-smarter-tests...

    “They can solve complex closed problems if you serve them the problem description neatly on a platter in the prompt, but they struggle to coherently string together long, autonomous, problem ...

  3. Stanford Research Institute Problem Solver - Wikipedia

    en.wikipedia.org/wiki/Stanford_Research...

    The Stanford Research Institute Problem Solver, known by its acronym STRIPS, is an automated planner developed by Richard Fikes and Nils Nilsson in 1971 at SRI International. [1] The same name was later used to refer to the formal language of the inputs to this planner.

  4. 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.

  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. Symbolab - Wikipedia

    en.wikipedia.org/wiki/Symbolab

    Symbolab is an answer engine [1] that provides step-by-step solutions to mathematical problems in a range of subjects. [2] It was originally developed by Israeli start-up company EqsQuest Ltd., under whom it was released for public use in 2011.

  7. This is the biggest question in AI right now - AOL

    www.aol.com/ai-leaders-starting-rethink-best...

    AI leaders are rethinking data-heavy training for large language models. Traditional models scale linearly with data, but this approach may hit a dead end. Smaller, more efficient models and new ...

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