Building Block: Artificial intelligence
Maturity: BETA
Artificial intelligence logo.

Short Description: Machine intelligence capabilities packaged as reusable services to perform work, extract insights from data, or provide other business capabilities.

Full Description: AI (artificial intelligence) is the process by which learning, pattern matching, and recognition and evolution of rules by inference takes place by mathematical modeling, filtering and classification algorithms on computer systems. These processes include learning (the acquisition of information and rules for using the information), reasoning (using the rules to reach approximate or definite conclusions) and self-correction. Examples of emerging AI services include:

  • Natural language processing (NLP)
  • Machine translation
  • Image recognition
  • Text-to-speech conversion

Other Names: Machine learning, Deep learning, Smart systems, Intelligent machines

Key Digital Functionalities:

  • Offers sensing or data capture and transmission by machine to machine (eg functionalities sensors) or humans to machine (eg data input)
  • Provides controllers to manipulate data collection tools and external systems in a predefined or adaptive way to achieve the desired result (eg a mail sorter rotating its bar code scanner each time an envelope appears on the scanning console)
  • Includes metadata standards and definitions to classify and index data in storage
  • Provides cognition and machine learning to understand input data in various contexts (eg hyper spectral image analysis to infer plant health conditions)
  • Offers logic and decision-making based on algorithms
  • Provides modeling, using data, algorithms and deep learning to predict outcomes or initiate action

Examples of use in different sectors:

  • Agriculture sector: 
    • Smart and precision agriculture applications use artificial intelligence to interpret data captured by other machines (eg drones or sensors) and create models and strategic inferences (eg whether to initiate harvesting or pesticide spray) and activate other smart machines (eg a remote operated pump-set to start irrigation of fields, farm robots or self-driven tractors)
    • Machine vision (image recognition) for diagnosing pests or soil defects
  • Education sector: 
    • Intelligent tutoring systems that work with learners directly and provide support to teachers on personalized learning support strategies
    • Artificially intelligent assessment software to support adaptive, personalized learning
  • Health sector:
    • Clinical decision support systems that assist doctors in diagnosing a patient’s disease condition and related intervention
    • Rehabilitation tools for patients with stroke, Alzheimer’s, autism, etc
    • AI can also help insurance companies detect high-yield and low-risk ROI patterns or fraud across various claim settlements


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