Artificial intelligence: development, training and integration · ENGLISH
Service page for projects serving Bogota. Prepare examples and quality criteria to guide model behaviour. In Bogota, products with several modules need clear distinctions between frequent tasks, permissions and pending states.
01 · CONTEXT
In Bogota, products with several modules need clear distinctions between frequent tasks, permissions and pending states.
02 · PRACTICAL BRIEF
Models, integration and evaluation
Define the task, representative examples, permitted data, evaluation goal and runtime environment. Leave sensitive data out of the initial brief. Before finalising the brief for Bogota, confirm with the people involved: In Bogota, products with several modules need clear distinctions between frequent tasks, permissions and pending states.
A training plan covering its goal, data sources, supervision and evaluation.
Confirm data provenance and permissions, and reserve separate evaluation examples.
03 · METHOD
Models, integration and evaluation
04 · ANSWERS
Prepare examples and quality criteria to guide model behaviour. A training plan covering its goal, data sources, supervision and evaluation.
Prepare the task, representative examples, permitted data, privacy constraints and target environment. Avoid sharing sensitive data in an initial enquiry.
Confirm data provenance and permissions, and reserve separate evaluation examples.