Cold start problem

The cold start problem occurs when a system, like a recommendation engine or a machine learning model, has little or no existing data about new users or items. This lack of information makes it difficult for the system to make accurate suggestions or predictions initially. For example, a new streaming service doesn't know your preferences yet, so it struggles to recommend shows you might like. Over time, as more data is gathered, the system becomes better at personalizing its recommendations. The challenge is to provide relevant results despite having limited information at the start.