Can you explain what the cold start problem is in AI?
The cold start problem refers to the challenge of making accurate predictions or recommendations when there is little to no data available.
Why is it a problem for recommendation systems?
It's problematic because recommendation systems rely on user data to suggest relevant items, and without data, they struggle to provide useful suggestions.
How can it be addressed?
It can be addressed by using techniques like collaborative filtering, content-based filtering, or incorporating external data sources.
Can you give an example of a cold start scenario?
Sure! A new user on a streaming service has no viewing history, making it hard for the system to recommend shows.
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