GENERATIVE-AI-ENGINEER-ASSOCIATE · Question #71
A Generative AI Engineer is designing an LLM-powered live sports commentary platform. The platform provides real-time updates and LLM-generated analyses for any users who would like to have live…
The correct answer is C. Feature Serving. Feature Serving is the correct answer because it provides low-latency, real-time access to up-to-date feature data for ML and LLM applications. In Databricks, Feature Serving exposes features (like live game scores) via a REST API so applications can retrieve the latest values…
Question
A Generative AI Engineer is designing an LLM-powered live sports commentary platform. The platform provides real-time updates and LLM-generated analyses for any users who would like to have live summaries, rather than reading a series of potentially outdated news articles. Which tool below will give the platform access to real-time data for generating game analyses based on the latest game scores?
Options
- ADatabricksIQ
- BFoundation Model APIs
- CFeature Serving
- DAutoML
How the community answered
(41 responses)- A2% (1)
- B12% (5)
- C80% (33)
- D5% (2)
Explanation
Feature Serving is the correct answer because it provides low-latency, real-time access to up-to-date feature data for ML and LLM applications. In Databricks, Feature Serving exposes features (like live game scores) via a REST API so applications can retrieve the latest values at inference time. DatabricksIQ (A) is an AI assistant built into Databricks for productivity. Foundation Model APIs (B) provide access to pre-trained LLMs but do not supply real-time data. AutoML (D) automates model training and does not serve live data.
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