Describe Convergence of AI, High-Performance Computing, and Analytics CERTIFIED-AI-EXPERT Practice Questions (Page 4)

Questions 16–20

1. 16application · medium

   A university research team is developing an AI model to simulate climate patterns. The model requires more computational power than their current workstations can provide. They have access to a university HPC center. What is the best way to utilize the HPC center for this AI workload?

   • APort the AI training code to run on the HPC cluster using parallel computing techniques
   • BUse the HPC center only for data storage and keep the AI training on workstations
   • CAsk the HPC center to run the AI model as a batch job without any code changes
   • DRun the AI model on a single powerful workstation with a high-end GPU
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2. 17foundation · easy

   What is the role of HPC in the context of analytics?

   • AIt secures data during analysis
   • BIt allows analytics to handle large-scale data processing tasks
   • CIt provides a user interface for analytics tools
   • DIt replaces the need for data scientists
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4. 18foundation · easy

   What is a key benefit of converging AI with analytics?

   • AIt makes analytics purely manual
   • BIt eliminates the need for data quality checks
   • CIt enables analytics to not only describe past events but also predict future outcomes
   • DIt reduces the need for data storage
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5. 19foundation · easy

   Which statement accurately describes high-performance computing?

   • AIt is primarily used for word processing and spreadsheet tasks
   • BIt is a type of database management system
   • CIt uses supercomputers or clusters to perform computations at high speeds
   • DIt focuses on storing data in a distributed file system
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6. 20application · medium

   A bank wants to use AI to detect fraudulent transactions in real time. They have a data analytics platform that processes transaction data in batches. The batch processing is too slow for real-time fraud detection. What should they do to converge AI and analytics for real-time detection?

   • AReplace the analytics platform with a rule-based system that flags transactions without using AI
   • BImplement a stream processing analytics platform that feeds a machine learning model for real-time scoring
   • CUse an HPC cluster to speed up the batch processing so it is almost real-time
   • DKeep the batch processing but add a machine learning model that scores transactions after the batch completes
   Reveal Solution Discussion Select an answer first