Artificial Intelligence Overview

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Questions and Answers

What is the primary purpose of model cards in AI?

To record detailed performance metrics and operational conditions (correct)

To evaluate the temperature settings of large language models

To manage and optimize model prompts and templates

To describe ethical considerations in model development

Which aspect of prompt engineering is focused on systematically improving a model's performance?

Prompt management

Prompt chaining

Prompt injection

Prompt design (correct)

What does a high value of temperature in model outputs signify?

Outputs will lack variation altogether

Responses will be focused and reliable

Responses will be diverse and varied (correct)

Outputs will be more consistent and predictable

Which method is appropriate for managing a sequence of complex tasks in AI?

Prompt chaining Signup and view all the answers

In which scenario would retrieval-augmented generation (RAG) be most beneficial?

When enriching prompts with relevant historical data Signup and view all the answers

What is the main aim of Trusted AI guidelines?

To promote the responsible development of AI technologies Signup and view all the answers

What does toxicity in language models refer to?

Offensive or harmful language outputs Signup and view all the answers

Which term defines the placeholders used in prompt templates?

Values Signup and view all the answers

Which component of AI systems integrates information from model cards and addresses overall complexity?

System cards Signup and view all the answers

What process involves crafting prompts to optimize models' response performance?

Prompt engineering Signup and view all the answers

What is the primary function of a large language model (LLM)?

To generate human-like text based on large text data Signup and view all the answers

What does the term 'hallucination' refer to in AI models?

Generating text that is semantically correct but factually incorrect Signup and view all the answers

What is the main purpose of fine-tuning in AI?

To adapt a pre-trained model for specific tasks using a targeted dataset Signup and view all the answers

What does 'grounding' entail in the context of AI models?

Integrating domain-specific knowledge and context to improve response accuracy Signup and view all the answers

Which term describes systematic errors in AI that differ from the intended function?

Bias Signup and view all the answers

What is an inference pipeline in AI?

An organized flow of steps to generate AI output based on prompts Signup and view all the answers

In the context of AI, what does 'domain adaptation' refer to?

Integrating specific organizational knowledge into AI prompts Signup and view all the answers

What is the role of hyperparameters in machine learning?

To manage aspects of the training process that lie outside the model Signup and view all the answers

What is meant by 'human in the loop' (HITL) in AI systems?

A requirement for human supervision during AI output generation Signup and view all the answers

What primarily distinguishes machine learning from traditional programming?

Machine learning systems enhance their performance based on data feedback Signup and view all the answers

Study Notes

Artificial Intelligence (AI)

AI is a computer science branch where systems use data to infer, task, and solve problems using human-like reasoning.

Bias

Bias is a systematic error in computer systems.
It produces unfair outcomes, differing from intended function.
Bias arises due to inaccurate assumptions during machine learning.

Corpus

A corpus is a substantial collection of textual data used for training Large Language Models (LLMs).

Domain Adaptation

Domain adaptation integrates organization-specific knowledge.
It modifies the prompt and foundation model.

Fine-tuning

Fine-tuning adapts a pre-trained language model.
It trains the model on a specific, smaller dataset related to the task.

Generative AI Gateway

The gateway provides normalized APIs for interacting with foundation models and services from various vendors.

Generative Pre-trained Transformer (GPT)

GPT is a family of language models.
They're trained on large text datasets to generate human-like text.

Grounding

Grounding adds context to the model by integrating domain knowledge and customer information into the prompt.

Hallucination

Hallucination occurs when the model outputs semantically correct text but is factually wrong or nonsensical.

Human in the Loop (HITL)

HITL models require human interaction during the process.

Hyperparameter

Hyperparameters control the training process.
They exist independently of the model's generated structure.

Inference

Inference is the process of generating content from a model.

Inference Pipelines

Inference pipelines are sequences of steps to complete generation tasks.
They involve prompt processing, model interaction, result moderation, and delivery.

Intent

Intent represents a user's goal in interacting with an AI assistant.

Large Language Model (LLM)

An LLM is a large neural network trained on substantial text data.

Machine Learning

Machine learning focuses on computer systems that learn, adapt, and improve using data feedback.

Model Cards

Model cards provide detailed performance information on models.
Information includes inputs, outputs, training, optimal use conditions, and ethical considerations.

Natural Language Processing (NLP)

NLP uses machine learning to process human language.
LLMs are one NLP approach.

Parameter Size

Parameter size refers to the number of parameters in a model for processing and generating data.

Prompt

A prompt is a natural language description of a task.
It acts as input for an LLM.

Prompt Chaining

Prompt chaining breaks complex tasks into smaller steps.
It connects the steps for a more specific and improved result.

Prompt Design

Prompt design involves optimizing prompts to improve model response quality and accuracy.
It involves understanding and adjusting prompt structure for better results.

Prompt Engineering

Prompt engineering is the scientific process of improving model performance and reliability through systematic prompt structuring.

Prompt Injection

Prompt injection is an approach used to manipulate or control the model's output.
It's a method to perform actions not intended for the model.

Prompt Instructions

Prompt instructions are natural language instructions integrated into a prompt template.
Instructions are part of the prompt sent to the LLM.

Prompt Management

Prompt management provides tools for building, organizing, managing, and distributing prompts.

Prompt Template

A prompt template is a string with placeholders.
The placeholders are substituted with data values for the final prompt.

Retrieval-Augmented Generation (RAG)

RAG uses knowledge bases or information retrieval to provide relevant context for prompts.

Semantic Retrieval

Semantic retrieval uses similar historical data for better model accuracy.

System Cards

System cards are an extended version of model cards.
They cover the entire system's operation (components, models, processes).

Temperature

Temperature controls the predictability and variety of model output.
High temperature = diverse responses, Low temperature = consistent responses

Toxicity

Toxicity refers to various forms of inappropriate, offensive, harmful, or abusive language.

Trusted AI

Trusted AI is a set of Salesforce guidelines for responsible AI development and implementation.

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Description

This quiz explores fundamental concepts of artificial intelligence, including bias, corpus, domain adaptation, fine-tuning, and generative models. It is designed to test your understanding of how these elements work together in the field of AI and machine learning.