Getting Salesforce-AI-Associate Certification Made Easy!

“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.”

“Providing call summaries is how AI with CRM helps sales representatives better understand previous customer interactions. Call summaries are a feature that uses natural language processing (NLP) to analyze voice conversations between sales representatives and customers and generate summaries or transcripts of the calls. Call summaries can help sales representatives better understand previous customer interactions by providing key information, insights, or action items from the calls.”

“Implementing Salesforce’s Trusted AI Principles is what Cloud Kicks should consider doing to minimize potential AI bias. Salesforce’s Trusted 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.”

“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 and preferences 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.”

“Reliability is an essential data quality dimension to achieve the goal of predicting the demand for shoes using historical data on sales and regional characteristics. Reliability means that the data values are trustworthy, credible, and authoritative for the AI task. Reliable data can improve the accuracy and confidence of AI predictions, as they reflect the true state or condition of the target population or domain. For example, reliable data can help predict the demand for shoes by using verified and validated sales and regional data.”