Which features of Einstein enhance sales efficiency and effectiveness?
A. Opportunity Scoring, Lead Scoring, Account Insights
B. Opportunity List View, Lead List View, Account List view
C. Opportunity Scoring, Opportunity List View, Opportunity Dashboard
Cloud Kicks wants to optimize its business operations by incorporating AI into CRM. What should the company do first to prepare its data for use with AI?
A. Remove biased data.
B. Determine data availability
C. Determine data outcomes.
A developer is tasked with selecting a suitable dataset for training an AI model in Salesforce to accurately predict current customer behavior. What Is a crucial factor that the developer should consider during selection?
A. Number of variables ipn the dataset
B. Size of the dataset
C. Age of the dataset
Explanation:
The size of the dataset is a crucial factor that the developer should consider during selection. The size of the dataset refers to the amount or volume of data available for training an AI model. The size of the dataset can affect the feasibility and quality of the AI model, as well as the choice of AI techniques and tools. The size of the dataset should be large enough to provide sufficient information for the AI model to learn from and generalize well to new data.
Cloud Kicks wants to implement AI features on its Salesforce Platform but has concerns about potential ethical and privacy challenges. What should they consider doing to minimize potential AI bias?
A. Use demographic data to identify minority groups.
B. Integrate AI models that auto-correct biased data.
C. Implement Salesforce's Trusted AI Principles.
Cloud Kicks is testing a new AI model. Which approach aligns with Salesforce's Trusted AI Principle of Inclusivity?
A. Test only with data from a specific region or demographic to limit the risk of data leaks.
B. Rely on a development team with uniform backgrounds to assess the potential societal implications of the model.
C. Test with diverse and representative datasets appropriate for how the model will be used.
Explanation:
Testing with diverse and representative datasets appropriate for how the model will be used aligns with Salesforce’s Trusted AI Principle of Inclusivity. Inclusivity means that AI systems should be designed and developed with respect for diversity and inclusion of different perspectives, backgrounds, and experiences. Testing with diverse and representative datasets can help ensure that the models are fair, unbiased, and representative of the target population or domain.
What is a sensitive variable that car esc to bias?
A. Education level
B. Country
C. Gender
Explanation:
Gender is a sensitive variable that can lead to bias. A sensitive variable is a variable that can potentially cause discrimination or unfair treatment based on a person’s identity or characteristics. For example, gender is a sensitive variable because it can affect how people are perceived, treated, or represented by AI systems.
Which Einstein capability uses emails to create content for Knowledge articles?
A. Generate
B. Discover
C. Predict
Explanation: “Einstein Generate uses emails to create content for Knowledge articles. Einstein Generate is a natural language generation (NLG) feature that can automatically write summaries, descriptions, or recommendations based on data or text inputs. For example, Einstein Generate can analyze email conversations between agents and customers and generate draft articles for the Knowledge base.”
What is the role of Salesforce Trust AI principles in the context of CRM system?
A. Guiding ethical and responsible use of AI
B. Providing a framework for AI data model accuracy
C. Outlining the technical specifications for AI integration
Explanation: “The role of Salesforce Trust AI principles in the context of CRM systems is guiding ethical and responsible use of AI. Salesforce Trust AI principles are a set of guidelines and best practices for developing and using AI systems in a responsible and ethical way. The principles include Accountability, Fairness & Equality, Transparency & Explainability, Privacy & Security, Reliability & Safety, Inclusivity & Diversity, Empowerment & Education. The principles aim to ensure that AI systems are aligned with the values and interests of customers, partners, and society.”
What is a potential outcome of using poor-quality data in AI application?
A. AI model training becomes slower and less efficient
B. AI models may produce biased or erroneous results.
C. AI models become more interpretable
Explanation: “A potential outcome of using poor-quality data in AI applications is that AI models may produce biased or erroneous results. Poor-quality data means that the data is inaccurate, incomplete, inconsistent, irrelevant, or outdated for the AI task. Poor-quality data 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. Poor-quality data can also introduce or exacerbate biases or errors in AI models, such as human bias, societal bias, confirmation bias, or overfitting or underfitting.”
What is a key benefit of effective interaction between humans and AI systems?
A. Leads to more informed and balanced decision making
B. Alerts humans to the presence of biased data
C. Reduces the need for human involvement
Explanation: “A key benefit of effective interaction between humans and AI systems is that it leads to more informed and balanced decision making. Effective interaction means that humans and AI systems can communicate and collaborate with each other in a clear, natural, and respectful way. Effective interaction can help leverage the strengths and complement the weaknesses of both humans and AI systems. Effective interaction can also help increase trust, confidence, and satisfaction in using AI systems.”
Which best describes the different between predictive AI and generative AI?
A. Predictive new and original output for a given input.
B. Predictive AI and generative have the same capabilities differ in the type of input they receive: predictive AI receives raw data whereas generation AI receives natural language.
C. Predictive AI uses machine learning to classes or predict output from its input data whereas generative AI does not use machine learning to generate its output
Explanation: “The difference between predictive AI and generative AI is that predictive AI analyzes existing data to make predictions or recommendations based on patterns or trends, while generative AI creates new content based on existing data or inputs. Predictive AI is a type of AI that uses machine learning techniques to learn from existing data and make predictions or recommendations based on the data. For example, predictive AI can be used to forecast sales, revenue, or demand based on historical data and trends. Generative AI is a type of AI that uses machine learning techniques to generate novel content such as images, text, music, or video based on existing data or inputs. For example, generative AI can be used to create realistic faces, write summaries, compose songs, or produce videos.”
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. Structured
B. Complete
C. Duplicate
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.
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