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Imagine you have a robot that can predict what type of ice cream people will like. With offline inference, you give the robot a list of people and the robot thinks about it for a while before giving you a list of ice cream predictions for everyone. It doesn't need to tell you right away what each person likes, and it doesn't need you to keep giving it more information while it's thinking. The robot can take its time to process everything and give you the best possible answers. | Imagine you have a robot that can predict what type of ice cream people will like. With offline inference, you give the robot a list of people and the robot thinks about it for a while before giving you a list of ice cream predictions for everyone. It doesn't need to tell you right away what each person likes, and it doesn't need you to keep giving it more information while it's thinking. The robot can take its time to process everything and give you the best possible answers. | ||
[[Category:Terms]] [[Category:Machine learning terms]] [[Category:Not Edited]] [[Category:updated]] | [[Category:Terms]] [[Category:Machine learning terms]] [[Category:Not Edited]] [[Category:updated]] |