Artificial intelligence: development, training and integration · ENGLISH
Service page for projects serving Caracas. Prepare examples and quality criteria to guide model behaviour. In Caracas, comparing offers is easier when scope, next steps and contact routes are clear.
01 · CONTEXT
In Caracas, comparing offers is easier when scope, next steps and contact routes are clear.
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 Caracas, confirm with the people involved: In Caracas, comparing offers is easier when scope, next steps and contact routes are clear.
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.