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Layout analysis software, that divide scanned documents into zones suitable for OCR; Graphical interfaces to one or more OCR engines; Software development kits that are used to add OCR capabilities to other software (e.g. forms processing applications, document imaging management systems, e-discovery systems, records management solutions)
OMR software is a computer software application that makes OMR possible on a desktop computer by using an Image scanner to process surveys, tests, attendance sheets, checklists, and other plain-paper forms printed on a laser printer. OMR software is used to capture data from OMR sheets.
A computerized text DAISY book can be read using refreshable Braille display or screen-reading software, printed as Braille book on paper, converted to a talking book using synthesised voice or a human narration, and also printed on paper as large print book. In addition, it can be read as large print text on computer screen. [4] [5]
The 1970s and 1980s saw the development of comprehensive theories in computational linguistics, which led to the development of ambitious projects in text comprehension and question answering. One example was the Unix Consultant (UC), developed by Robert Wilensky at U.C. Berkeley in the late 1980s.
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.
Artificial intelligence detection software aims to determine whether some content (text, image, video or audio) was generated using artificial intelligence (AI). However, the reliability of such software is a topic of debate, [ 1 ] and there are concerns about the potential misapplication of AI detection software by educators.
Undetectable AI (or Undetectable.ai) is an artificial intelligence content detection and modification software designed to identify and alter artificially generated text, such as that produced by large language models.
The problem of attaining human-level competency at "commonsense knowledge" tasks is considered to probably be "AI complete" (that is, solving it would require the ability to synthesize a fully human-level intelligence), [4] [5] although some oppose this notion and believe compassionate intelligence is also required for human-level AI. [6]