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Free Salesforce-AI-Associate Exam Braindumps (page: 13)

Page 12 of 27
PDF with 106 Questions

In the context of Salesforce's Trusted AI Principles what does the principle of Empowerment primarily aim to achieve?

  1. Empower users to off all skill level to build AI application with clicks, not code.
  2. Empower users to contribute to the growing body of knowledge of leading AI research.
  3. Empower users to solve challenging technical problems using neural networks.

Answer(s): A

Explanation:

"The principle of Empowerment primarily aims to achieve empowering users of all skill levels to build AI applications with clicks, not code. Empowerment is one of the Trusted AI Principles that states that AI systems should be designed and developed with respect for the empowerment and education of humans. Empowering users means enabling users to access, use, and benefit from AI systems regardless of their technical expertise or background. For example, empowering users means providing tools and platforms that allow users to build AI applications with clicks, not code, such as Einstein Prediction Builder or Einstein Discovery."



Cloud Kicks wants to use Einstein Prediction Builder to determine a customer's likelihood of buying specific products; however, data quality is a...
How can data quality be assessed quality?

  1. Build a Data Management Strategy.
  2. Build reports to expire the data quality.
  3. Leverage data quality apps from AppExchange

Answer(s): C

Explanation:

"Leveraging data quality apps from AppExchange is how data quality can be assessed. Data quality is the degree to which data is accurate, complete, consistent, relevant, and timely for the AI task. Data quality can affect the performance and reliability of AI systems, as they depend on the quality of the data they use to learn from and make predictions. Leveraging data quality apps from AppExchange means using third-party applications or solutions that can help measure, monitor, or improve data quality in Salesforce."



What should be done to prevent bias from entering an AI system when training it?

  1. Use alternative assumptions.
  2. Import diverse training data.
  3. Include Proxy variables.

Answer(s): B

Explanation:

"Using diverse training data is what should be done to prevent bias from entering an AI system when training it. Diverse training data means that the data covers a wide range of features and patterns that are relevant for the AI task. Diverse training data can help prevent bias by ensuring that the AI system learns from a balanced and representative sample of the target population or domain. Diverse training data can also help improve the accuracy and generalization of the AI system by capturing more variations and scenarios in the data."



What is a Key consideration regarding data quality in AI implementation?

  1. Techniques from customizing AI features in Salesforce
  2. Data's role in training and fine-tuning Salesforce AI models
  3. Integration process of AI models with Salesforce workflows

Answer(s): B

Explanation:

"Data's role in training and fine-tuning Salesforce AI models is a key consideration regarding data quality in AI implementation. Data quality is the degree to which data is accurate, complete, consistent, relevant, and timely for the AI task. Data quality can affect the performance and reliability of AI systems, as they depend on the quality of the data they use to learn from and make predictions. Data's role in training and fine-tuning Salesforce AI models means understanding how data is used to build, train, test, and improve AI models in Salesforce, such as Einstein Prediction Builder or Einstein Discovery."






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