Artificial intelligence: development, training and integration · ENGLISH
The ai model adaptation and customisation service defines scope, stages and review criteria around the project goal.
01 · CONTEXT
The work defines inputs, expected outputs and checks before a task is automated.
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. Turn this guidance into an observable goal: Adapt instructions, context and data to the intended use without hiding model limits.
A comparison of instructions, context retrieval and model adaptation.
Choose the simplest option that meets the criterion and compare it with the base model.
03 · METHOD
Models, integration and evaluation
04 · ANSWERS
Adapt instructions, context and data to the intended use without hiding model limits. A comparison of instructions, context retrieval and model adaptation.
Prepare the task, representative examples, permitted data, privacy constraints and target environment. Avoid sharing sensitive data in an initial enquiry.
Choose the simplest option that meets the criterion and compare it with the base model.