Artificial intelligence: development, training and integration · ENGLISH
Service page for projects serving Sao Paulo. Measure quality, latency and resource use before choosing an optimisation. For Sao Paulo, separating audiences, features and priorities helps review products with multiple goals.
01 · CONTEXT
For Sao Paulo, separating audiences, features and priorities helps review products with multiple goals.
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 Sao Paulo, confirm with the people involved: For Sao Paulo, separating audiences, features and priorities helps review products with multiple goals.
Measurements of quality, response time and resource use before each change.
Compare the same test workload before and after without missing the agreed quality threshold.
03 · METHOD
Models, integration and evaluation
04 · ANSWERS
Measure quality, latency and resource use before choosing an optimisation. Measurements of quality, response time and resource use before each change.
Prepare the task, representative examples, permitted data, privacy constraints and target environment. Avoid sharing sensitive data in an initial enquiry.
Compare the same test workload before and after without missing the agreed quality threshold.