Which of the following is NOT listed as a major stage in the AI lifecycle?

• A. Data labeling
• B. Problem definition
• C. Data collection/curation
• D. Model deployment

Answer: (A)

In AI project lifecycles, the major stages typically include defining the problem, collecting and curating data, training and validating the model, and deploying the model into production. Data labeling is a crucial activity for supervised learning, but it’s usually treated as part of data preparation rather than a standalone major stage. It involves adding annotations to data so the model can learn from it, and it often happens within the data preparation step after data collection. Therefore, data labeling is not listed as a major stage, while problem definition, data collection/curation, and model deployment are.