CompTIA
Checkpoint
ISC
HP
Dell
EC-Council
EXIN
Fortinet
ITIL®
Juniper
PMI
Microsoft
VMware
Avaya
Google
Salesforce
Amazon
Palo Alto Networks
Certiport
ISC2
All Vendors
  2. Home
  3. Exams
  4. Salesforce
  5. Salesforce-AI-Specialist

Free Salesforce-AI-Specialist Exam Braindumps (page: 19)

Page 18 of 39
PDF with 152 Questions

An AI Specialist configured Data Masking within the Einstein Trust Layer. How should the AI Specialist begin validating that the correct fields are being masked?

  1. Use a Flow-based resource in Prompt Builder to debug the fields' merge values using Flow Debugger.
  2. Request the Einstein Generative AI Audit Data from the Security section of the Setup menu.
  3. Enable the collection and storage of Einstein Generative AI Audit Data on the Einstein Feedback setup page.

Answer(s): B

Explanation:

To begin validating that the correct fields are being masked in Einstein Trust Layer, the AI Specialist should request the Einstein Generative AI Audit Data from the Security section of the Salesforce Setup menu. This audit data allows the AI Specialist to see how data is being processed, including which fields are being masked, providing transparency and validation that the configuration is working as expected.
Option B is correct because it allows for the retrieval of audit data that can be used to validate data masking.
Option A (Flow Debugger) and Option C (Einstein Feedback) do not relate to validating field masking in the context of the Einstein Trust Layer.


Reference:

Salesforce Einstein Trust Layer Documentation:
https://help.salesforce.com/s/articleView?id=sf.einstein_trust_layer_audit.htm



Universal Containers (UC) recently rolled out Einstein Generative capabilities and has created a custom prompt to summarize case records. Users have reported that the case summaries generated are not returning the appropriate information.
What is a possible explanation for the poor prompt performance?

  1. The data being used for grounding Is incorrect or incomplete.
  2. The prompt template version is incompatible with the chosen LLM.
  3. The Einstein Trust Layer is incorrectly configured.

Answer(s): A

Explanation:

Poor prompt performance when generating case summaries is often due to the data used for grounding being incorrect or incomplete. Grounding involves feeding accurate, relevant data to the AI so it can generate appropriate outputs. If the data source is incomplete or contains errors, the generated summaries will reflect that by being inaccurate or insufficient. Option B (prompt template incompatibility with the LLM) is unlikely because such incompatibility usually results in more technical failures, not poor content quality. Option C (Einstein Trust Layer misconfiguration) is focused on data security and auditing, not the quality of prompt responses.
For more information, refer to Salesforce documentation on grounding AI models and data quality best practices.



What is best practice when refining Einstein Copilot custom action instructions?

  1. Provide examples of user messages that are expected to trigger the action.
  2. Use consistent introductory phrases and verbs across multiple action instructions.
  3. Specify the persona who will request the action.

Answer(s): A

Explanation:

When refining Einstein Copilot custom action instructions, it is considered best practice to provide examples of user messages that are expected to trigger the action. This helps ensure that the custom action understands a variety of user inputs and can effectively respond to the intent behind the messages.
Option B (consistent phrases) can improve clarity but does not directly refine the triggering logic. Option C (specifying a persona) is not as crucial as giving examples that illustrate how users will interact with the custom action.
For more details, refer to Salesforce's Einstein Copilot documentation on building and refining custom actions.



Universal Containers' service team wants to customize the standard case summary response from Einstein Copilot.
What should the AI Specialist do to achieve this?

  1. Customize the standard Record Summary template for the Case object,
  2. Summarize the Case with a standard copilot action.
  3. Create a custom Record Summary prompt template for the Case object.

Answer(s): C

Explanation:

To customize the case summary response from Einstein Copilot, the AI Specialist should create a custom Record Summary prompt template for the Case object. This allows Universal Containers to tailor the way case data is summarized, ensuring the output aligns with specific business requirements or user preferences.
Option A (customizing the standard Record Summary template) does not provide the flexibility required for deep customization.
Option B (standard Copilot action) won't allow customization; it will only use default settings. Refer to Salesforce Prompt Builder documentation for guidance on creating custom templates for record summaries.






Post your Comments and Discuss Salesforce Salesforce-AI-Specialist exam with other Community members: