“What’s the accuracy of this machine learning (ML) model?”
“How long is the training time?”
“How much training data do you need?”
Working for a company that builds machine learning software for robotics, I hear these questions every day. Machine learning has become a shiny object that everyone wants to pursue. Over 80% of the companies are looking into at least one AI project.
Users generally want to know how long it would take to onboard a new item and how well the models perform or generalize. They want a way to measure the overall cost against performance. However, answers to the above questions don’t give you a full picture. Even worse, they are misleading.
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