Cognitive Technologies Survey


Cognitive Technologies Survey

Get insights from early adopters of cognitive and AI

What do 250 of the most aggressive adopters of artificial intelligence (AI) and cognitive technologies have to say about their efforts to date? From the impact on jobs to their specific goals and exactly which cognitive technologies they’re using, this report shares their views with the broader business world.

What cognitive technologies are included in this survey?

“Cognitive technologies” include machine learning, deep learning neural networks, natural language processing, rule engines, robotic process automation, and combinations of these capabilities for higher-level applications. The cognitive technologies discussed in this report include:

  • Robotic process automation (RPA) is software that automates repetitive, rules-based processes usually performed by people sitting in front of computers. By interacting with applications just as humans would, software robots can open email attachments, complete e-forms, record and re-key data, and perform other tasks that mimic human action.
  • Computer vision is the ability to extract meaning and intent out of visual elements, whether characters (in the case of document digitization), or the categorization of content in images such as faces, objects, scenes, and activities.
  • Machine learning is the ability of statistical models to develop capabilities and improve their performance overtime without the need to follow explicitly programmed instructions.
  • Natural language processing/generation (NLP/G) is the ability to extract or generate meaning and intent from text in a readable, stylistically natural, and grammatically correct form. 
  • Speech recognition is the ability to automatically and accurately recognize and transcribe human speech.
  • Rules-based systems is the ability to use databases of knowledge and rules to automate the process of making inferences about information.
  • Deep learning is a relatively complex form of machine learning involving neural networks, with many layers of abstract variables. Deep learning models are excellent for image and speech recognition, but are difficult or impossible for humans to interpret.
  • Physical robots can perform many different tasks in unpredictable environments, often in collaboration with human workers. The broader field of robotics is embracing cognitive technologies to create robots that can work alongside, interact with, assist, or entertain people.
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