Free Salesforce-AI-Associate Exam Braindumps

What is machine learning?

1. A. AI that can grow its intelligence
2. B. AI that creates new content
3. C. A data model used in Salesforce

Correct Answer: C
“A data model is a machine learning feature used in Salesforce. A data model is a representation or abstraction of a real-world phenomenon or process using data structures and algorithms. A data model can be used to describe, analyze, or predict various aspects of the phenomenon or process using machine learning techniques.”

Which best describes the difference between predictive AI and generative Al?

1. A. Predictive AT uses machine learning to classify or predict outputs from its input data whereas generative Al does not use machine learning to generate its output.
2. B. Predictive Al uses machine learning to classify or predict outputs from its input data whereas generative Al uses machine learning to generate new and original output for 4 given input
3. C. Predictive Al and generative Al have the same capabilities but differ in the type of input they receive; predictive AT receives raw data whereas generative AT receives natural language.

Correct Answer: B
Predictive AI and generative AI represent two different applications of machine learning technologies. Predictive AI focuses on making predictions based on historical data. It analyzes past data to forecast future outcomes, such as customer churn or sales trends. On the other hand, generative AI is designed to generate new and original outputs based on the learned data patterns. This includes tasks like creating new images, text, or music that resemble the training data but do not duplicate it. Both types of AI use machine learning, but their objectives and outputs are distinct. For detailed differences and applications in a Salesforce context, Salesforce's guide on AI technologies is a helpful resource, accessible at Salesforce AI Technologies.

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

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

Correct Answer: C
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.

Which AI tool is a web of connections, guided by weights and biases?

1. A. Neural networks
2. B. Predictive Analytics
3. C. Rules- based systems
4. D. Mark this item for later review,

Correct Answer: A
Neural networks are a key AI tool designed as a web of interconnected nodes, similar to the human brain's structure. Each connection, or synapse, in a neural network is guided by weights and biases that are adjusted during the learning process. These weights and biases determine the strength and influence of one node over another, facilitating complex pattern recognition and decision-making processes. Neural networks are extensively used in machine learning for tasks like image and speech recognition, among others. For more on neural networks in the context of Salesforce AI, see the Salesforce AI documentation on Neural Networks.

What is Salesforce's Trusted AI Principle of Transparency?

1. A. The customization of AT features to meet specific business requirements
2. B. The integration of AT models with Salesforce workflows
3. C. The clear and understandable explanation of Al decisions and actions

Correct Answer: C
Salesforce's Trusted AI Principle of Transparency emphasizes the importance of providing clear and understandable explanations of AI decisions and actions. This principle ensures that users can understand how AI conclusions are drawn, which is crucial for trust and accountability, especially in business applications where AI decisions can have significant impacts. Transparency helps mitigate the "black box" nature of AI systems by making them more interpretable and allows for better oversight, compliance, and alignment with ethical guidelines. Salesforce elaborates on these principles in their ethical AI practices, which can be further explored at Salesforce Ethical AI.