Close this search box.

Quality Assurance (QA) in the Context of AI

AI operationalization is different than traditional deployment and putting things into “production”. But if it’s different for deployment and different in development, then it follows that AI projects are unlike traditional projects even with regards to QA. Simply put, you don’t QA AI projects like you QA other projects. This is because the concept of what we’re testing, how we test, and when we test is radically different in AI Projects.

Operationalizing AI

When AI practitioners talk about taking their machine learning models and deploying them into real-world environments, they don’t call it deployment. Instead the term that’s used in the industry is “operationalizing”. This might be confusing for traditional IT operations managers and applications developers. Why don’t we deploy or put into production AI models? What does …

Operationalizing AI Read More »

Login Or Register


Register to View Event


Get The Operationalizing AI


AI Best Practices

Get the Step By Step Checklist for AI Projects


Login to register for events. Don’t have an account? Just register for an event and an account will be created for you!