What does "computer literacy" refer to?

B) The ability to use computers and technology effectively

C) Understanding programming languages

D) The ability to repair computer hardware

Why is computer literacy important in today's world?

B) It helps people communicate, access information, and work efficiently

A) It is only useful for people in technical jobs

C) It guarantees a high-paying job

D) It is only useful for using social media

Which of the following is NOT considered a basic computer skill?

B) Installing a computer’s hardware components

D) Using an internet search engine

Which fingers are typically used to type the "F" and "J" keys?

A) Left index finger for F, right index finger for J

B) Left middle finger for F, right middle finger for J

C) Left pinky finger for F, right pinky for J

D) Left thumb for F, right thumb for J

Why should you use the "home row" when typing?

A) It’s where the most frequently used keys are located

B) It reduces the amount of stretching your fingers do

C) It helps keep your hands from getting tired quickly

What is generative AI?

A) AI that can generate images, videos, or text

B) AI that learns from data but does not create content

C) AI used only for analyzing historical data

D) AI designed only for automating tasks

How does generative AI differ from other types of AI?

A) It can generate new content based on patterns it learns

B) It only analyzes existing data

C) It can only function with structured data

D) It doesn’t use machine learning

Why is it important to understand the historical impact of technological innovations when discussing AI?

B) To learn from past mistakes and successes

A) To predict future technology trends

C) To understand only the technical aspects of AI

D) To focus on developing more advanced AI models

How might generative AI affect society in the future?

B) It will significantly change how people interact with technology

C) It will only impact businesses

D) It will replace all human jobs

Why is training data essential for AI systems?

A) It helps AI learn how to make decisions

B) It allows AI to function without human input

C) It is only needed for hardware components

D) It is only useful for analyzing historical data

How does generative AI use large datasets to understand and process language?

A) By analyzing patterns and relationships in the data

B) By storing raw data without processing it

C) By using pre-programmed rules

D) By focusing only on the most common words

How is AI’s process of categorizing words similar to human learning?

C) It recognizes patterns and groups words with similar meanings

A) It categorizes words based on emotions

B) It uses memory to remember words

D) It categorizes words randomly

What role does the internet play in providing data for AI models?

B) It provides vast amounts of unstructured data for AI to learn from

A) It provides structured data exclusively

C) It is not relevant to AI learning

D) It only provides images for AI models

How does AI learn from the data it is trained on to build a vocabulary?

B) By finding relationships between words in the data

A) By memorizing every word it encounters

C) By creating its own definitions for words

D) By ignoring words it doesn’t understand

What is bias in AI, and how does it occur in generative AI models?

B) When AI makes decisions based on imperfect or skewed data

A) When AI intentionally favors certain outcomes

C) When AI avoids using any data

D) When AI creates perfect results every time

How can bias in AI data impact the outcomes it produces?

B) It can lead to unfair or unrepresentative results

A) It can ensure fair and balanced outcomes

C) It has no effect on outcomes

D) It only affects the input process

What are some examples of biases that can emerge in generative AI?

A) Gender, racial, or geographical bias

B) Bias towards futuristic technologies

C) Bias towards more complicated data

D) No bias, as AI models are neutral

What are embeddings in AI, and why are they important?

B) A way to represent words as numbers so AI can process them

A) A method to measure physical distances

C) A programming technique for creating visuals

D) A way to compress large datasets

How do embeddings help language models understand the meanings of words?

B) By representing words with numbers that capture relationships between them

A) By assigning random values to words

C) By categorizing words alphabetically

D) By making word choices based solely on frequency

How can numerical representations of words help AI models process language?

C) By allowing AI to compare words based on their meanings

A) By making words easier to spell

B) By simplifying grammar rules

D) By eliminating all irrelevant words

How are word embeddings created based on context?

B) By using the word’s meaning in multiple contexts to form a numerical representation

A) By ignoring surrounding words

C) By categorizing words by their letter count

D) By randomly selecting numbers for each word

How do different contexts lead to different word embeddings?

B) Because the model adjusts its representation based on the context it appears in

A) Because the word's meaning is stable regardless of context

C) Because context doesn’t affect word meaning

D) Because the model ignores context when creating embeddings

What happens when a word’s meaning changes depending on its context?

B) The AI model creates different embeddings for the word in different contexts

A) The word is removed from the model’s vocabulary

C) The AI model cannot process the word

D) The word becomes unimportant in all contexts

Why do different contexts lead to different word embeddings?

B) Because the model adjusts its representation based on the context it appears in

A) Because the word's meaning is stable regardless of context

C) Because context doesn’t affect word meaning

D) Because the model ignores context when creating embeddings

What is a neural network, and how does it function in AI systems?

A) A system that mimics the way the human brain processes information

B) A series of connected rules for making decisions

C) A program that performs simple arithmetic

D) A database for storing information

How does a neural network help AI models make decisions?

B) By adjusting its parameters based on input data

A) By following a fixed set of rules

C) By randomly selecting answers

What is the purpose of hidden layers in a neural network?

B) To process data before generating an output

How do weights influence the decision-making process in a neural network?

B) Weights determine the strength of connections between nodes and influence decisions

A) Weights are irrelevant in decision-making

C) Weights adjust the model’s training speed

D) Weights only affect input data

How do neural networks adjust based on feedback from previous outcomes?

A) They update their weights to improve accuracy

B) They ignore all past results

C) They randomly change their structure

D) They rely solely on new data inputs

Is training a neural network the same as teaching it true intelligence? Why or why not?

B) No, because neural networks rely on patterns and feedback rather than true understanding

A) Yes, because neural networks can learn like humans

C) Yes, because neural networks can think independently

D) No, because neural networks don’t require any feedback

Why is context important for understanding language in AI models?

A) It helps the model determine the correct meaning of words

B) It has no impact on understanding language

C) It limits the model’s capacity to process information

D) It ensures the model only processes specific words

What is the role of attention in generative AI models?

A) It helps the model focus on the most relevant parts of a sentence

B) It allows the model to randomly choose which words to focus on

D) It reduces the model’s accuracy

How do AI models use attention to update word meanings?

A) By considering the surrounding context when interpreting words

B) By ignoring context and processing words in isolation

D) By storing all word meanings in a fixed list

How can ambiguous words be clarified through context?

A) By analyzing the surrounding words to determine the intended meaning

B) By removing them from the sentence

C) By focusing on only one meaning

D) By ignoring all ambiguous words

How do AI models generate output based on probabilities?

A) By choosing the word with the highest likelihood based on training data

B) By ignoring probability and focusing on frequency

D) By following predefined rules

Why do AI models sometimes produce results that are nonsensical even if they are highly probable?

B) Because the training data might not cover all possible scenarios

A) Because the model cannot process probability correctly

C) Because the model always focuses on coherence

D) Because the model avoids randomness at all costs

How do AI models ensure that their outputs are coherent?

A) By selecting words that fit the overall structure and context

C) By following a fixed pattern

D) By excluding less likely words

What factors influence the probability of a word being selected by an AI model?

B) The alphabetical order of words

What does storage refer to in Generative AI?

B) The embeddings used to represent the meanings of words and their relationships

A) The process of selecting the most probable word based on context

C) The step where the model breaks down the sentence into tokens

D) The neural network that processes the input data

How does the output of a Generative AI model get generated?

B) By predicting the next word based on learned probabilities and context

A) By storing all the data in a database

C) By selecting words randomly from a list

D) By breaking down the sentence into smaller parts

What are hallucinations in the context of generative AI?

A) Mistakes where the AI creates false or inaccurate information

B) Accurate outputs generated by the model

C) Explanations that always match human expectations

D) Outputs based solely on probabilities

How can bias in training data lead to hallucinations in AI-generated content?

A) By providing the AI with skewed or incomplete data that influences its output

B) By helping the AI focus on more accurate results

C) By improving the model’s understanding of language

D) By eliminating irrelevant information

Why is it important for AI systems to avoid fabricating or hallucinating information?

A) Because fabricated information can be harmful or misleading

B) Because hallucinations help improve the system’s learning

C) Because fabricated content is less predictable

D) Because it makes the AI system less complex

Computer Literacy Midterm

Quiz

•

Computers

•

1st Grade

•

Practice Problem

•

Medium

Nicole Matthews

Used 13+ times

FREE Resource

C) Building a computer from scratch

D) Writing code for an app

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