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

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Google machine learning modeling is different from other privacy-forward proposals because Google’s signed-in base of users allows their models to function 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 data can be exported from the platforms and be used to gather insights for marketing teams.
  • 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 signed-in base of users allows their models to continue functioning independently of cookies and other identifiers.

The correct answer is: Google’s signed-in base of users allows their models to continue functioning independently of cookies and other identifiers

Explanation: Google’s machine learning modeling is distinct because it leverages a large base of signed-in users, enabling its models to function effectively even without cookies or other identifiers. This capability allows Google to provide robust and privacy-safe performance, maintaining the effectiveness of its algorithms while respecting user privacy and consent choices.

Reference article: Harness the Power of Machine Learning

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