Utilizing web discovery projects allows for the identification of popular URLs that are accessed by many users, providing a method for fetching rather than blindly crawling the internet. This approach ensures that only public information is retrieved while minimizing noise in data collection. Blind crawling can lead to the accumulation of irrelevant data, such as duplicate sites that do not contribute value. By focusing on fetching content from trusted sites and accounts for user engagement, the process becomes more efficient, underscoring the importance of cleaning datasets in machine learning and AI initiatives.

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