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How Machine Learning Is Reshaping Online Search
- Accounting for individual user differences. You can use a 'general' pattern to understand the bulk of user search behavior, but there will always be distinct individual differences to account for. Only a machine learning algorithm could be able to dedicate time to these outliers, and account for them with improved functionality.
- Speed and scalability. Algorithms with the potential to learn from themselves can be updated faster than those that rely on manual inputs. Similarly, they have tremendous scalability; as long as you have the processing power to devote, a machine learning algorithm could be applied to billions of queries the same way it could be applied to a dozen.
- Unlimited application potential. RankBrain is currently the only example we have of a machine learning algorithm in the search world, but it's not the only potential application here. Machine learning processes could be used to improve almost any element of Google's core search algorithm in the future.