Which of the following is a reason that makes Google machine learning modeling different from other privacy-forward proposals?

Google's signed-in base of users allows their models to continue functioning independently of cookies and other identifiers.

Google's Display and Video campaigns use data from channels and placements of competitors to ensure the algorithms have enough information to perform well.

Google's machine learning can use third-party cookies as an input even though they're deprecated when users accept the cookies of a certain site.

Google's machine learning data can be exported from the platforms and be used to gather insights for marketing teams.


Choose an option to see if it’s correct. Check the explanation below. Learn Smarter, not Harder.

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Explanation: Which of the following is a reason that makes Google machine learning modeling different from other privacy-forward proposals?


Explanation: The selected answer is correct because Google's signed-in base of users allows their machine learning models to continue functioning independently of cookies and other identifiers. By leveraging signed-in data, Google can maintain the effectiveness of its machine learning models without relying on third-party cookies, which enhances privacy while still delivering relevant and personalized ad experiences. This privacy-forward approach enables more accurate targeting and performance without compromising user privacy, differentiating Google’s model from other proposals that may still rely on cookies or external identifiers.

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