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Salesforce-AI-Specialist 100％시험패스 덤프자료, Salesforce-AI-Specialist유효한 시험덤프

Salesforce인증 Salesforce-AI-Specialist시험을 패스하여 자격증을 취득하시면 찬란한 미래가 찾아올것입니다. Salesforce인증 Salesforce-AI-Specialist인증시험을 패스하여 취득한 자격증은 IT인사로서의 능력을 증명해주며 IT업계에 종사하는 일원으로서의 자존심입니다. ITDumpsKR 의 Salesforce인증 Salesforce-AI-Specialist덤프는 시험패스에 초점을 맞추어 제일 간단한 방법으로 시험을 패스하도록 밀어주는 시험공부가이드입니다.구매전Salesforce인증 Salesforce-AI-Specialist무료샘플을 다운받아 적성에 맞는지 확인하고 구매할지 않할지 선택하시면 됩니다.

최신 AI Associate Salesforce-AI-Specialist 무료샘플문제 (Q141-Q146):

질문 # 141
Universal Containers (UC) has implemented Generative AI within Salesforce to enable summarization of a custom object called Guest. Users have reported mismatches in the generated information.
In refining its prompt design strategy, which key practices should UC prioritize?

A. Create concise, clear, and consistent prompt templates with effective grounding, contextual role- playing, clear instructions, and iterative feedback.
B. Enable prompt test mode, allocate different prompt variations to a subset of users for evaluation, and standardize the most effective model based on performance feedback.
C. Submit a prompt review case to Salesforce and conduct thorough testing In the playground to refine outputs until they meet user expectations.

정답：A

설명：
ForUniversal Containers (UC)to refine itsGenerative AIprompt design strategy and improve the accuracy of the generated summaries for the custom objectGuest, the best practice is to focus on craftingconcise, clear, and consistent prompt templates. This includes:
* Effective grounding: Ensuring the prompt pulls data from the correct sources.
* Contextual role-playing: Providing the AI with a clear understanding of its role in generating the summary.
* Clear instructions: Giving unambiguous directions on what to include in the response.
* Iterative feedback: Regularly testing and adjusting prompts based on user feedback.
* Option Bis correct because it follows industry best practices for refining prompt design.
* Option A(prompt test mode) is useful but less relevant for refining prompt design itself.
* Option C(prompt review case with Salesforce) would be more appropriate for technical issues or complex prompt errors, not general design refinement.
References:
* Salesforce Prompt Design Best Practices:https://help.salesforce.com/s/articleView?id=sf.
prompt_design_best_practices.htm

질문 # 142
When a customer chat is initiated, which functionality in Salesforce provides generative AI replies or draft emails based on recommended Knowledge articles?

A. Einstein Service Replies
B. Einstein Grounding
C. Einstein Reply Recommendations

정답：A

설명：
When a customer chat is initiated, Einstein Service Replies provides generative AI replies or draft emails based on recommended Knowledge articles. This feature uses the information from the Salesforce Knowledge base to generate responses that are relevant to the customer's query, improving the efficiency and accuracy of customer support interactions.
Option B is correct because Einstein Service Replies is responsible for generating AI-driven responses based on knowledge articles.
Option A (Einstein Reply Recommendations) is focused on recommending replies but does not generate them.
Option C (Einstein Grounding) refers to grounding responses in data but is not directly related to drafting replies.
Reference:
Einstein Service Replies Overview: https://help.salesforce.com/s/articleView?id=sf.einstein_service_replies.htm

질문 # 143
Universal Container (UC) has effectively utilized prompt templates to update summary fields on Lightning record pages. An admin now wishes to incorporate similar functionality into UC's automation process using Flow.
How can the admin get a response from this prompt template from within a flow to use as part of UC's automation?

A. Einstein for Flow
B. Invocable Apex
C. Flow Action

정답：A

설명：
* Context of the Question
* Universal Container (UC) has used prompt templates to update summary fields on record pages.
* Now, the admin wants to incorporate similar generative AI functionality within a Flow for automation purposes.
* How to Call a Prompt Template Within a Flow
* Flow Action: Salesforce provides a standard way to invoke generative AI templates or prompts within a Flow step. From the Flow Builder, you can add an "Action" that references the prompt template you created in Prompt Builder.
* Other Options:
* Invocable Apex: Possible fallback if there's no out-of-the-box Flow Action available.
However, Salesforce is releasing native Flow integration for AI prompts, making custom Apex less necessary.
* Einstein for Flow: A broad label for Salesforce's generative AI features within Flow.
Under the hood, you typically use a "Flow Action" that points to your prompt.
* Conclusion
* The easiest out-of-the-box solution is to use a Flow Action referencing the prompt template.
Hence, Option B is correct.
Salesforce AI Specialist References & Documents
* Salesforce Trailhead: Use Prompt Templates in FlowDemonstrates how to add an Action in Flow that calls a prompt template.
* Salesforce Documentation: Einstein GPT for FlowExplains standard flow actions to invoke and handle generative AI responses.

질문 # 144
How does the Einstein Trust Layer ensure that sensitive data isprotected while generating useful and meaningful responses?

A. Masked data will be de-masked during response journey.
B. Masked data will be de-masked during request journey.
C. Responses that do not meet the relevance threshold will be automatically rejected.

정답：A

설명：
The Einstein Trust Layer ensures that sensitive data is protected while generating useful and meaningful responses by masking sensitive data before it is sent to the Large Language Model (LLM) and then de- masking it during the response journey.
How It Works:
* Data Masking in the Request Journey:
* Sensitive Data Identification:Before sending the prompt to the LLM, the Einstein Trust Layer scans the input for sensitive data, such as personally identifiable information (PII), confidential business information, or any other data deemed sensitive.
* Masking Sensitive Data:Identified sensitive data is replaced with placeholders or masks. This ensures that the LLM does not receive any raw sensitive information, thereby protecting it from potential exposure.
* Processing by the LLM:
* Masked Input:The LLM processes the masked prompt and generates a response based on the masked data.
* No Exposure of Sensitive Data:Since the LLM never receives the actual sensitive data, there is no risk of it inadvertently including that data in its output.
* De-masking in the Response Journey:
* Re-insertion of Sensitive Data:After the LLM generates a response, the Einstein Trust Layer replaces the placeholders in the response with the original sensitive data.
* Providing Meaningful Responses:This de-masking process ensures that the final response is both meaningful and complete, including the necessary sensitive information where appropriate.
* Maintaining Data Security:At no point is the sensitive data exposed to the LLM or any unintended recipients, maintaining data security and compliance.
Why Option A is Correct:
* De-masking During Response Journey:The de-masking process occurs after the LLM has generated its response, ensuring that sensitive data is only reintroduced into the output at the final stage, securely and appropriately.
* Balancing Security and Utility:This approach allows the system to generate useful and meaningful responses that include necessary sensitive information without compromising data security.
Why Options B and C are Incorrect:
* Option B (Masked data will be de-masked during request journey):
* Incorrect Process:De-masking during the request journey would expose sensitive data before it reaches the LLM, defeating the purpose of masking and compromising data security.
* Option C (Responses that do not meet the relevance threshold will be automatically rejected):
* Irrelevant to Data Protection:While the Einstein Trust Layer does enforce relevance thresholds to filter out inappropriate or irrelevant responses, this mechanism does not directly relate to the protection of sensitive data. It addresses response quality rather than data security.
References:
* Salesforce AI Specialist Documentation -Einstein Trust Layer Overview:
* Explains how the Trust Layer masks sensitive data in prompts and re-inserts it after LLM processing to protect data privacy.
* Salesforce Help -Data Masking and De-masking Process:
* Details the masking of sensitive data before sending to the LLM and the de-masking process during the response journey.
* Salesforce AI Specialist Exam Guide -Security and Compliance in AI:
* Outlines the importance of data protection mechanisms like the Einstein Trust Layer in AI implementations.
Conclusion:
The Einstein Trust Layer ensures sensitive data is protected by masking it before sending any prompts to the LLM and then de-masking it during the response journey. This process allows Salesforce to generate useful and meaningful responses that include necessary sensitive information without exposing that data during the AI processing, thereby maintaining data security and compliance.

질문 # 145
Leadership needs to populate a dynamic form field with a summary or description created by a large language model (LLM) to facilitate more productive conversations with customers. Leadership also wants to keep a human in the loop to be considered in their AI strategy.
Which prompt template type should the AI Specialist recommend?

A. Field Generation
B. Record Summary
C. Sales Email

정답：A

설명：
The correct answer isField Generationbecause this template type is designed to dynamically populate form fields with content generated by a large language model (LLM). In this scenario, leadership wants a dynamic form field that contains a summary or description generated by AI to aid customer interactions. Additionally, they want to keep a human in the loop, meaning the generated content will likely be reviewed or edited by a person before it's finalized, which aligns with theField Generationprompt template.
* Field Generation: This prompt type allows you to generate content for specific fields in Salesforce, leveraging large language models to create dynamic and contextual information. It ensures that AI content is available within the record where needed, but it allows human oversight or review, supporting the "human-in-the-loop" strategy.
* Sales Email: This prompt type is mainly used for generating email content for outreach or responses, which doesn't align directly with populating fields in a form.
* Record Summary: While this option might seem close, it is typically used to summarize entire records for high-level insights rather than filling specific fields with dynamic content based on AI generation.
Salesforce AI Specialist References:
* You can explore more about these prompt templates and AI capabilities through Salesforce documentation and official resources on Prompt Builder:https://help.salesforce.com/s/articleView?id=sf.
prompt_builder_templates_overview.htm

질문 # 146
......

많은 분들이 고난의도인 Salesforce관련인증시험을 응시하고 싶어 하는데 이런 시험은 많은 전문적인 관련지식이 필요합니다. 시험은 당연히 완전히 전문적인 Salesforce-AI-Specialist관련지식을 터득하자만이 패스할 가능성이 높습니다. 하지만 지금은 많은 방법들로 여러분의 부족한 면을 보충해드릴 수 있으며 또 힘든 Salesforce시험도 패스하실 수 있습니다. 혹은 여러분은 전문적인 Salesforce Certified AI Specialist Exam관련지식을 터득하자들보다 더 간단히 더 빨리 시험을 패스하실 수 있습니다.

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