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Free Salesforce-AI-Specialist Exam Braindumps (page: 9)

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PDF with 152 Questions

Universal Containers needs a tool that can analyze voice and video call records to provide insights on competitor mentions, coaching opportunities, and other key information. The goal is to enhance the team's performance by identifying areas for improvement and competitive intelligence.
Which feature provides insights about competitor mentions and coaching opportunities?

  1. Call Summaries
  2. Einstein Sales Insights
  3. Call Explorer

Answer(s): C

Explanation:

For analyzing voice and video call records to gain insights into competitor mentions, coaching opportunities, and other key information, Call Explorer is the most suitable feature. Call Explorer, a part of Einstein Conversation Insights, enables sales teams to analyze calls, detect patterns, and identify areas where improvements can be made. It uses natural language processing (NLP) to extract insights, including competitor mentions and moments for coaching. These insights are vital for improving sales performance by providing a clear understanding of the interactions during calls. Call Summaries offer a quick overview of a call but do not delve deep into competitor mentions or coaching insights.
Einstein Sales Insights focuses more on pipeline and forecasting insights rather than call-based analysis.


Reference:

Salesforce Einstein Conversation Insights Documentation:
https://help.salesforce.com/s/articleView?id=einstein_conversation_insights.htm



An AI Specialist at Universal Containers (UC) Is tasked with creating a new custom prompt template to populate a field with generated output. UC enabled the Einstein Trust Layer to ensure AI Audit data is captured and monitored for adoption and possible enhancements.
Which prompt template type should the AI Specialist use and which consideration should they review?

  1. Flex, and that Dynamic Fields is enabled
  2. Field Generation, and that Dynamic Fields is enabled
  3. Field Generation, and that Dynamic Forms is enabled

Answer(s): B

Explanation:

When creating a custom prompt template to populate a field with generated output, the most appropriate template type is Field Generation. This template is specifically designed for generating field-specific outputs using generative AI.

Additionally, the AI Specialist must ensure that Dynamic Fields are enabled. Dynamic Fields allow the system to use real-time data inputs from related records or fields when generating content, ensuring that the AI output is contextually accurate and relevant. This is crucial when populating specific fields with AI-generated content, as it ensures the data source remains dynamic and up-to-date. The Einstein Trust Layer will track and audit the interactions to ensure the organization can monitor AI adoption and make necessary enhancements based on AI usage patterns. For further reading, refer to Salesforce's guidelines on Field Generation templates and the Einstein Trust Layer.



Universal Containers plans to implement prompt templates that utilize the standard foundation models.
What should the AI Specialist consider when building prompt templates in Prompt Builder?

  1. Include multiple-choice questions within the prompt to test the LLM's understanding of the context.
  2. Ask it to role-play as a character in the prompt template to provide more context to the LLM.
  3. Train LLM with data using different writing styles including word choice, intensifiers, emojis, and punctuation.

Answer(s): C

Explanation:

When building prompt templates in Prompt Builder, it is essential to consider how the Large Language Model (LLM) processes and generates outputs. Training the LLM with various writing styles, such as different word choices, intensifiers, emojis, and punctuation, helps the model better understand diverse writing patterns and produce more contextually appropriate responses. This approach enhances the flexibility and accuracy of the LLM when generating outputs for different use cases, as it is trained to recognize various writing conventions and styles. The prompt template should focus on providing rich context, and this stylistic variety helps improve the model's adaptability.
Options A and B are less relevant because adding multiple-choice questions or role-playing scenarios doesn't contribute significantly to improving the AI's output generation quality within standard business contexts.
For more details, refer to Salesforce's Prompt Builder documentation and LLM tuning strategies.



Universal Containers (UC) has a mature Salesforce org with a lot of data in cases and Knowledge articles. UC is concerned that there are many legacy fields, with data that might not be applicable for Einstein AI to draft accurate email responses.
Which solution should UC use to ensure Einstein AI can draft responses from a defined data source?

  1. Service AI Grounding
  2. Work Summaries
  3. Service Replies

Answer(s): A

Explanation:

Service AI Grounding is the solution that Universal Containers should use to ensure Einstein AI drafts responses based on a well-defined data source. Service AI Grounding allows the AI model to be anchored in specific, relevant data sources, ensuring that any AI-generated responses (e.g., email replies) are accurate, relevant, and drawn from up-to-date information, such as Knowledge articles or cases.
Given that UC has legacy fields and outdated data, Service AI Grounding ensures that only the valid and applicable data is used by Einstein AI to craft responses. This helps improve the relevance of responses and avoids inaccuracies caused by outdated or irrelevant fields. Work Summaries and Service Replies are useful features but do not address the need for grounding AI outputs in specific, current data sources like Service AI Grounding does. For more details, you can refer to Salesforce's Service AI Grounding documentation for managing AI- generated content based on accurate data sources.






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