Optimizing foundation modelsFull notesSummaryRingkasanStoriesPracticeBusiness Case7 exam-style questions on this lesson.Question 1 of 7An online fashion retailer has high cart abandonment because customers are overwhelmed by choice. What does it want from generative AI?AA new, faster payment methodBFaster servers for the checkout pageCA personalized shopping experienceDCheaper and faster shipping optionsCheck answerQuestion 2 of 7Which metric measures purchases per site visit?AAverage order valueBCustomer retention rateCROUGEDConversion rateCheck answerQuestion 3 of 7Which metric measures dollars spent per transaction?AAverage order valueBNet promoter scoreCCustomer retention rateDConversion rateCheck answerQuestion 4 of 7Which metric measures the percentage of customers who come back?AAverage order valueBCustomer retention rateCPerplexityDConversion rateCheck answerQuestion 5 of 7. Select two.The retailer fine-tunes an LLM for personalized advice. Which TWO data sources does it use? (Select TWO.)AInteraction data such as likes, clicks, and past purchasesBEmployees' personal emailsCRandom public imagesDCompetitors' private dataEPast transactions and customer feedbackCheck answer0 of 2 selectedQuestion 6 of 7How does the retailer adapt products and promotions to each customer in real time?ABy retraining the LLM for every visitorBBy removing product descriptionsCBy integrating the LLM with a recommendation engineDBy raising the temperatureCheck answerQuestion 7 of 7How does the retailer keep the model current with new fashion trends?AFreezing the model after launch to keep it stableBRemoving old products from the catalog onlyCManual retraining by the team every few yearsDContinuous learning from new customer data and trendsCheck answerEvaluate Results6 exam-style questions on this lesson.Fine-Tuning10 exam-style questions on this lesson.