If you were building an autocomplete experience, how would you use underlying data to predict the next word a person is going to type?

Focus on the types of data you would leverage for the autocomplete feature, such as historical user input, common phrases, and contextual cues. Discuss how you would implement algorithms like n-grams or machine learning models to analyze this data and improve prediction accuracy. Consider the balance between speed and accuracy in your approach, and mention any potential challenges, such as handling misspellings or varying user intents. Finally, think about how you would iterate on the model based on user feedback and usage patterns to continuously enhance the experience.