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Salesforce Certified AI Associate Exam Sample Questions (Q44-Q49):

NEW QUESTION # 44
Cloud Kicks wants to evaluate its data quality to ensure accurate and up-to-date records.
Which type of records negatively impact data quality?

A. Duplicate
B. Structured
C. Complete

Answer: A

Explanation:
Duplicate records negatively impact data quality by creating inconsistencies and confusion in database management, leading to potential errors in customer relationship management (CRM) systems like Salesforce. Duplicates can skew analytics results, lead to inefficiencies in customer service, and result in redundant marketing efforts. Salesforce offers various tools to identify and merge duplicate records, thereby maintaining high data integrity. More about managing duplicate records in Salesforce and ensuring data quality can be found in Salesforce's documentation on duplicate management at Salesforce Duplicate Management.

NEW QUESTION # 45
Cloud Kicks uses Einstein to generate predictions out is not seeing accurate results?
What to a potential mason for this?

A. Poor data quality
B. Too much data
C. The wrong product

Answer: A

Explanation:
Explanation
"Poor data quality is a potential reason for not seeing accurate results from an AI model. Poor data quality means that the data is inaccurate, incomplete, inconsistent, irrelevant, or outdated for the AI task. Poor data quality can affect the performance and reliability of AI models, as they may not have enough or correct information to learn from or make accurate predictions."

NEW QUESTION # 46
What is a benefit of a diverse, balanced, and large dataset?

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

Answer: B

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 # 47
What are predictive analytics, machine learning, natural language processing (NLP), and computer vision?

A. Different types of automation tools used in Salesforce
B. Different types of data models used in Salesforce
C. Different types of AI that can be applied in Salesforce

Answer: C

Explanation:
Predictive analytics, machine learning, natural language processing (NLP), and computer vision are all types of artificial intelligence technologies that can be applied in Salesforce to enhance various aspects of business operations and customer interactions. Predictive analytics uses historical data to make predictions about future events. Machine learning involves algorithms that can learn from and make decisions based on data. NLP is concerned with the interactions between computers and humans using natural language, and computer vision interprets and processes visual information from the world to make sense of it in the way humans do.
Salesforce harnesses these AI technologies, particularly through its Einstein platform, to provide powerful tools that help businesses automate tasks, make better decisions, and offer more personalized services. For more on how Salesforce utilizes these AI technologies, you can explore the Einstein AI services documentation at Salesforce Einstein.

NEW QUESTION # 48
Which statement exemplifies Salesforces honesty guideline when training AI models?

A. Control bias, toxicity, and harmful content withembedded guardrails and guidance.
B. Minimize the AI models carbon footprint and environment impact during training.
C. Ensure appropriate consent and transparency when using AI-generated responses.

Answer: C

Explanation:
"Ensuring appropriate consent and transparency when using AI-generated responses is a statement that exemplifies Salesforce's honesty guideline when training AI models. Salesforce's honesty guideline is one of the Trusted AI Principles that states that AI systems should be designed and developed with respect for honesty and integrity in how they work and what they produce. Ensuring appropriate consent and transparency means respecting and honoring the choices andpreferences of users regarding how their data is used or generated by AI systems. Ensuring appropriate consent and transparency also means providing clear and accurate information and documentation about the AI systems and their outputs."

NEW QUESTION # 49
......

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