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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. 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.

  4. Flex (lexical analyser generator) - Wikipedia

    en.wikipedia.org/wiki/Flex_(lexical_analyser...

    Normally the generated scanner contains references to the unistd.h header file, which is Unix specific. To avoid generating code that includes unistd.h , %option nounistd should be used. Another issue is the call to isatty (a Unix library function), which can be found in the generated code.

  5. Optical mark recognition - Wikipedia

    en.wikipedia.org/wiki/Optical_mark_recognition

    The first mark sense scanner was the IBM 805 Test Scoring Machine; this read marks by sensing the electrical conductivity of graphite pencil lead using pairs of wire brushes that scanned the page. In the 1930s, Richard Warren at IBM experimented with optical mark sense systems for test scoring, as documented in US Patents 2,150,256 (filed in ...

  6. LinkedIn COO tells workers to be prepared for this AI ... - AOL

    www.aol.com/finance/linkedin-coo-tells-workers...

    What the open-ended job interview question shows, however, is that finding ways you can use AI effectively at home and at work is a cheat code to impressing future hiring managers. This story was ...

  7. Question answering - Wikipedia

    en.wikipedia.org/wiki/Question_answering

    Question answering systems in the context of [vague] machine reading applications have also been constructed in the medical domain, for instance related to [vague] Alzheimer's disease. [3] Open-domain question answering deals with questions about nearly anything and can only rely on general ontologies and world knowledge. Systems designed for ...