Ciclul de viață al inteligenței artificiale

The life cycle of an AI system includes several interrelated phases, from its design and development (including subphases such as requirements analysis, data collection, training, testing, integration), installation, implementation, operation, maintenance and disposal. Given the complexity of artificial intelligence (and information systems in general), several models and methodologies can be defined to manage this complexity, especially in the design and development phases, such as agile, waterfall or spiral software development , rapid and incremental prototyping. The AI lifecycle defines the phases an organization should follow to take advantage of AI techniques and specifically machine learning models to achieve practical business value.