AI Associate Salesforce Einstein AI Features Practice Question
A developer needs to use the Einstein Vision and Language Platform to classify images and extract named entities from text. Which THREE API capabilities should they use?
⚠ Common exam trap
Watch out — candidates often confuse custom model training or deployment strategies (like fine-tuning BERT or edge deployment) with the pre-built API capabilities that the Einstein platform directly offers, leading them to select options that are not available as out-of-the-box APIs.
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Named Entity Recognition (NER)
Named Entity Recognition (NER) is a core API capability of the Einstein Vision and Language Platform for extracting named entities (e.g., people, organizations, locations) from unstructured text. It directly addresses the requirement to extract named entities from text, making option A correct.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Named Entity Recognition (NER)
Why this is correct
Correct.
- ✓
Object detection
Why this is correct
Correct.
- ✗
Fine-tuning BERT models
Why it's wrong here
Not part of the platform.
- ✓
Image classification
Why this is correct
Correct.
- ✗
Deploying custom models on edge devices
Why it's wrong here
Not supported by the platform.
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This AI Associate practice question is part of Courseiva's free Salesforce certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the AI Associate exam.