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Valid Salesforce-AI-Associate Test Objectives & Salesforce-AI-Associate Latest Braindumps Pdf

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Salesforce Salesforce-AI-Associate Latest Braindumps Pdf - Salesforce-AI-Associate Preparation Store

Actual4Cert certification training exam for Salesforce-AI-Associate are written to the highest standards of technical accuracy, using only certified subject matter experts and published authors for development. Actual4Cert Salesforce-AI-Associate certification training exam material including the examination question and the answer, complete by our senior lecturers and the Salesforce-AI-Associate product experts, included the current newest Salesforce-AI-Associate examination questions.

Salesforce Salesforce-AI-Associate Exam Syllabus Topics:

Topic
Details

Topic 1

Ethical Considerations of AI: It delves into the ethical challenges of AI such as human bias in machine learning, lack of transparency, etc. The topic also explains how to apply the Trusted AI Principles of Salesforce to given scenarios.

Topic 2

Data for AI: Questions about the importance of data quality and different elements or components of data quality are related to this topic.

Topic 3

AI Fundamentals: This topic discusses the major principles and applications of AI within Salesforce. It also focuses on different types of AI and their capabilities.

Topic 4

AI Capabilities in CRM: Get familiar with the benefits of AI and capabilities of CRM.

Salesforce Certified AI Associate Exam Sample Questions (Q95-Q100):

NEW QUESTION # 95
What is a benefit of a diverse, balanced, and large dataset?

A. Training time
B. Data privacy
C. Model accuracy

Answer: C

Explanation:
Explanation
"Model accuracy is a benefit of a diverse, balanced, and large dataset. A diverse dataset can capture a variety of features and patterns that are relevant for the AI task. A balanced dataset can avoid overfitting or underfitting the model to a specific subset of data. A large dataset can provide enough information for the model to learn from and generalize well to new data."

NEW QUESTION # 96
A service leader wants use AI tohelp customer resolve their issues quicker in a guided self-serve application.
Which Einstein functionality provides the best solution?

A. Bots
B. Recommendation
C. Case Classification

Answer: A

Explanation:
"Bots provide the best solution for a service leader whowants to use AI to help customers resolve their issues quicker in a guided self-serve application. Bots are a feature that uses natural language processing (NLP) and natural language understanding (NLU) to create conversational interfaces that can interactwith customers using text or voice. Bots can help automate and streamline customer service processes by providing answers, suggestions, or actions based on the customer's intent and context."

NEW QUESTION # 97
What Is a benefit of data quality and transparency as it pertains to bias in generated AI?

A. Chances of bias are remove
B. Chances of bIas and mitigated
C. Chances of bias are aggravated

Answer: B

Explanation:
"Data quality and transparency can help mitigate the chances of bias in generative AI. Data quality means that the data is accurate, complete, consistent, relevant, and timely for the AI task. Data quality can help mitigate bias by ensuring that the generative AI model learns from a balanced and representative sample of the target population or domain. Data transparency means that the data sources, methods, and processes are clear and open to inspection and verification. Data transparency can help mitigate bias by allowing users to understand and evaluate the dataused or generated by the generative AI model."

NEW QUESTION # 98
To avoid introducing unintended bias to an AI model, which type of data should be omitted?

A. Transactional
B. Engagement
C. Demographic

Answer: C

Explanation:
"Demographic data should be omitted to avoid introducing unintended bias to an AI model. Demographic data is data that describes the characteristics of a population or a group of people, such as age, gender, race, ethnicity, income, education, or occupation. Demographic data can lead to bias if it is used to discriminate or treat people differently based on their identity or attributes. Demographic data can also reflect existing biases or stereotypes in society or culture, which can affect the fairnessand ethics of AI systems."

NEW QUESTION # 99
What are the three commonly used examples of AI in CRM?

A. Predictive scoring,reporting, Image classification
B. Einstein Bots, face recognition, recommendations
C. Predictive scoring, forecasting, recommendations

Answer: C

Explanation:
"Predictive scoring, forecasting, and recommendations are three commonly used examples of AI in CRM.Predictive scoring can help prioritize leads, opportunities, and customers based on their likelihood to convert, churn, or buy. Forecasting can help predict future sales, revenue, or demand based on historical data and trends. Recommendations can help suggest the best products, services, or actions for each customer based on their preferences, behavior, and needs."

NEW QUESTION # 100
......

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Ray Rogers Ray Rogers

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