SALESFORCE-AI-SPECIALIST BRAINDUMPS DOWNLOADS, FLEXIBLE SALESFORCE-AI-SPECIALIST LEARNING MODE

Salesforce-AI-Specialist Braindumps Downloads, Flexible Salesforce-AI-Specialist Learning Mode

Salesforce-AI-Specialist Braindumps Downloads, Flexible Salesforce-AI-Specialist Learning Mode

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Salesforce Salesforce-AI-Specialist Exam Syllabus Topics:

TopicDetails
Topic 1
  • Einstein Trust Layer: This section evaluates the skills of Salesforce AI specialists responsible for implementing security protocols and safeguarding data privacy. It emphasizes the security, privacy, and foundational features of the Einstein Trust Layer.
Topic 2
  • Prompt Builder: This section evaluates the expertise of AI specialists working with Salesforce's AI tools. It focuses on the Prompt Builder feature, requiring candidates to understand its usage based on business needs.
Topic 3
  • Generative AI in CRM Applications: This part of the exam assesses AI specialists’ knowledge of generative AI within CRM systems. It covers the use of generative AI features in Einstein for Sales and Einstein for Service.
Topic 4
  • Agentforce Tools: In this topic, AI specialists get knowledge using agents when it is appropriate. Moreover, the topic explains the working of agents and reasoning engine powers Agentforce. Lastly, the topic focuses on managing and monitoring agent adoption.
Topic 5
  • Model Builder: This portion of the exam focuses on Salesforce AI specialists' expertise in working with AI models within Salesforce environments. Candidates will need to demonstrate knowledge of when to use the Model Builder and how to configure standard, custom, or Bring Your Own Large Language Model (BYOLLM) generative models to meet business needs.

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Salesforce Certified AI Specialist Exam Sample Questions (Q111-Q116):

NEW QUESTION # 111
Universal Containers (UC) wants to offer personalized service experiences and reduce agent handling time with Al-generated email responses, grounded in Knowledge base.
Which AI capability should UC use?

  • A. Einstein Service Replies for Email
  • B. Einstein Generative Service Replies for Email
  • C. Einstein Email Replies

Answer: A

Explanation:
For Universal Containers (UC) to offer personalized service experiences and reduce agent handling time using AI-generated responses grounded in the Knowledge base, the best solution is Einstein Service Replies for Email. This capability leverages AI to automatically generate responses to service-related emails based on historical data and the Knowledge base, ensuring accuracy and relevance while saving time for service agents.
Einstein Email Replies (option A) is more suited for sales use cases.
Einstein Generative Service Replies for Email (option C) could be a future offering, but as of now, Einstein Service Replies for Email is the correct choice for grounded, knowledge-based responses.
Reference:
Einstein Service Replies Overview: https://help.salesforce.com/s/articleView?id=sf.einstein_service_replies.htm


NEW QUESTION # 112
Universal Containers wants to be able to detect with a high level confidence if content generated by a large language model (LLM) contains toxic language.
Which action should an Al Specialist take in the Trust Layer to confirm toxicity is being appropriately managed?

  • A. Access the Toxicity Detection log in Setup and export all entries where isToxicityDetected is true.
  • B. Create a flow that sends an email to a specified address each time the toxicity score from the response exceeds a predefined threshold.
  • C. Create a Trust Layer audit report within Data Cloud that uses a toxicity detector type filter to display toxic responses and their respective scores.

Answer: C

Explanation:
To ensure that content generated by a large language model (LLM) is appropriately screened for toxic language, the AI Specialist should create a Trust Layer audit report within Data Cloud. By using the toxicity detector type filter, the report can display toxic responses along with their respective toxicity scores, allowing Universal Containers to monitor and manage any toxic content generated with a high level of confidence.
Option C is correct because it enables visibility into toxic language detection within the Trust Layer and allows for auditing responses for toxicity.
Option A suggests checking a toxicity detection log, but Salesforce provides more comprehensive options via the audit report.
Option B involves creating a flow, which is unnecessary for toxicity detection monitoring.
Reference:
Salesforce Trust Layer Documentation: https://help.salesforce.com/s/articleView?id=sf.einstein_trust_layer_audit.htm


NEW QUESTION # 113
After creating a foundation model in Einstein Studio, which hyperparameter should an AI Specialist use to adjust the balance between consistency and randomness of a response?

  • A. Presence Penally
  • B. Temperature
  • C. Variability

Answer: B

Explanation:
The Temperature hyperparameter controls the randomness of model outputs:
* Low Temperature (e.g., 0.2): More deterministic, consistent responses.
* High Temperature (e.g., 1.0): More creative, varied responses.
* Presence Penalty (Option A): Discourages repetition of tokens, unrelated to randomness.
* Variability (Option B): Not a standard hyperparameter in Einstein Studio.
References:
* Einstein Studio Documentation: Model Hyperparameters
* Explicitly states "Temperature adjusts the balance between predictable and random outputs."


NEW QUESTION # 114
A data science team has trained an XGBoost classification model for product recommendations onDatabricks.
The AI Specialist is tasked with bringing inferences for product recommendations from this model into Data Cloud as a stand-alone data model object (DMO).
How should the AI Specialist set this up?

  • A. Create the serving endpoint in Einstein Studio, then configure the model using Model Builder.
  • B. Create the serving endpoint in Databricks, then configure the model using a Python SDK connector.
  • C. Create the serving endpoint in Databricks, then configure the model using Model Builder.

Answer: C

Explanation:
To integrate inferences from an XGBoost model into Salesforce's Data Cloud as a stand-alone Data Model Object (DMO):
* Create the Serving Endpoint in Databricks:
* The serving endpoint is necessary to make the trained model available for real-time inference.
Databricks provides tools to host and expose the model via an endpoint.
* Configure the Model Using Model Builder:
* After creating the endpoint, the AI Specialist should configure it within Einstein Studio'sModel Builder, which integrates external endpoints with Salesforce Data Cloud for processing and storing inferences as DMOs.
* Option B: Serving endpoints are not created in Einstein Studio; they are set up in external platforms like Databricks before integration.
* Option C: A Python SDK connector is not used to bring model inferences into Salesforce Data Cloud; Model Builder is the correct tool.


NEW QUESTION # 115
An AI Specialist at Universal Containers is working on a prompt template to generate personalized emails for product demonstrationrequests from customers. It is important for the Al-generated email to adhere strictly to the guidelines, using only associated opportunityinformation, and to encourage the recipient to take the desired action.
How should the AI Specialist include these instructions on a new line in the prompt template?

  • A. Surround them with triple quotes (""").
  • B. Use curly brackets {} to encapsulate instructions.
  • C. Make sure merged fields are defined.

Answer: A

Explanation:
In Salesforce prompt templates, instructions that guide how the Large Language Model (LLM) should generate content (in this case, personalized emails) can be included by surrounding the instruction text with triple quotes ("""). This formatting ensures that the LLM adheres to the specific instructions while generating the email content.
The use oftriple quotesallows the AI to understand that the enclosed text is a directive for how to approach the task, such as limiting the content to associated opportunity information or encouraging a specific action from the recipient.
Refer toSalesforce Prompt Builder documentationfor detailed instructions on how to structure prompts for generative AI.


NEW QUESTION # 116
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