AI Construction Steps

The steps to contruct AI from input data are as follow:

  • Accumulation

    : Data Collection begins with the accumulation of data from various sources, such as surveys, experiments, observations, external sources or refined data from previous cycles. The data collected may be raw, unprocessed or refined and validated.
  • Processing and Transformation

    : Data is processed, cleaned, refined, validated and transformed into a more structured and applicable format that is applicable for further processing. Some may not meet entry standards and be archived or deferred for additional analysis.
  • Storage and Organization

    : Data is categorized, classified and stored in databases or repositories.
  • Analysis and Interpretation

    : Data is analyzed to extract meaningful insights, patterns, and trends via statistical methods, machine learning and other analytical techniques. Analyzed data is converted into information and knowledge useful for decision-making, reporting, or research.
  • Distribution and Communication

    : Sharing the information is shared with relevant stakeholders, which may be individuals, organizations, or the public via reports, presentations, dashboards, websites, databases, or other platforms.
  • Maintenance

    : Regularly update and revise information to ensure its accuracy, reflect changes and new data. Expired or unused information may be archived for historical reference, compliance, or research purposes.
  • Feedback and Improvement

    : Seek feedback from users or stakeholders to improve the information cycle, including refining data collection processes, analysis methods and better information distribution strategies.
  • Security and Governance

    : Protect information from unauthorized access or breaches via security measures such as encryption and access controls. Ensure data Governance, including data quality, integrity, and compliance with relevant regulations.

The information steps may include local feedback loops and complete cycle iterations as new data becomes available, information evolves and intepretation changes.