WorksheetsAIB Class Test - 2
Total questions: 50
Worksheet time: 25mins
Human intelligence is best defined as the ability to
Execute predefined instructions
Process numerical data only
Follow fixed algorithms
Learn, reason, solve problems, and adapt to new situations
Which of the following is a unique characteristic of human intelligence compared to AI?
High-speed computation
Data-driven decisions
Pattern recognition
Self-awareness and emotional integration
Artificial Intelligence primarily refers to
Machines with consciousness
Emotion-driven decision systems
Human-like creativity
Machines performing tasks requiring human intelligence
In a business context, AI mainly emphasizes
Emotional reasoning
Conscious thought
Human intuition
Data-driven decision making at scale
Detecting defects in manufacturing using images is an example of
Learning
Reasoning
Decision-making
Perception
Which is a limitation of current AI systems?
Pattern detection
Processing large datasets
Consistent performance
Understanding emotions and intent
Which task can AI perform well?
Ethical judgement
Moral reasoning
Understanding intent
Detecting patterns in large data
Increased efficiency in AI systems mainly comes from
Emotional intelligence
Subjective reasoning
Human supervision
Automation of repetitive tasks
Which type of data analytics answers the question “Why did it happen?”
Descriptive
Predictive
Prescriptive
Diagnostic
Predictive analytics focuses on
What happened
Why it happened
How to make it happen
What will happen
The approach that studies machines thinking like humans is called
Acting rationally
Acting humanly
Thinking rationally
Thinking humanly
Chatbots that converse naturally with users fall under
Thinking rationally
Acting rationally
Thinking humanly
Acting humanly
Rule-based expert systems mainly represent
Acting humanly
Thinking humanly
Acting emotionally
Thinking rationally
Modern business AI systems mainly focus on
Thinking humanly
Acting humanly
Thinking emotionally
Acting rationally
Narrow AI is characterized by
Human-level intelligence
Multi-domain reasoning
Self-awareness
Task-specific intelligence
Which of the following is an example of Narrow AI?
Human-like thinking machines
Self-improving AI
General problem-solving AI
Recommendation systems like Netflix
General AI is best described as
Commercially deployed AI
Task-specific intelligence
Rule-based intelligence
Human-like intelligence across domains
Super AI is considered
Commercially available
Rule-based
Narrowly focused
Hypothetical and futuristic
Natural language is
Designed for machines
Strictly structured
Unambiguous
Rich, flexible, and ambiguous
WhatsApp chats are examples of
Programming language
Formal language
Machine language
Natural language
Natural Language Processing (NLP) is a branch of
Computer vision
Robotics
Data mining
Artificial Intelligence
The primary goal of NLP is to
Store large datasets
Design hardware
Improve databases
Enable machines to understand and generate human language
Understanding the meaning of text is the role of
NLG
Machine Learning
Speech recognition
Natural Language Understanding
Generating human-like text from data is called
NLU
Feature extraction
Parsing
Natural Language Generation
Syntax in NLP deals with
Meaning of words
Context of sentences
Speaker intent
Sentence structure and grammar
Ambiguity in the sentence “The panda eats shoots and leaves” is resolved using
Syntax
Pragmatics
Discourse
Semantics
Understanding intent behind “Can you pass the salt?” involves
Syntax
Semantics
Discourse
Pragmatics
Understanding sentence relationships across conversations is called
Semantics
Syntax
Pragmatics
Discourse
Converting text into numerical representations is known as
Parsing
Tagging
Classification
Text vectorization
NLP systems improve accuracy mainly by
Reducing data size
Manual coding
Fixed rules
Increasing training data
Chatbots are an application of
Computer Vision
Robotics
Data analytics
Natural Language Processing
Automatically detecting unwanted emails is known as
Sentiment analysis
Text summarization
Speech recognition
Spam detection
Sentiment analysis is also called
Language parsing
Text clustering
Topic modeling
Opinion mining
Translating text from one language to another uses
Speech recognition
Text summarization
Information extraction
Machine translation
Speech recognition primarily converts
Text to speech
Images to text
Video to audio
Spoken words to text
Extracting structured data from unstructured documents is called
Parsing
Classification
Tokenization
Information extraction
The concept of a “universal machine” was proposed by
John McCarthy
Noam Chomsky
Marvin Minsky
Alan Turing
The Georgetown–IBM experiment focused on
Speech recognition
Text summarization
Sentiment analysis
Machine translation
SHRDLU was developed to
Translate languages
Recognize speech
Detect images
Manipulate blocks using language
Word2Vec introduced the concept of
Rule-based parsing
Decision trees
Grammar rules
Word embeddings
Transformer models power architectures like
CNN
RNN
HMM
BERT and GPT
Computer Vision mainly enables machines to
Understand emotions
Interpret text
Generate speech
Interpret images and videos
Automating visual inspection in factories is a need for
NLP
Robotics
Data mining
Computer Vision
Compared to human vision, computer vision is
Emotionally intelligent
Highly subjective
Fatigue-prone
Highly consistent once trained
Capturing images using cameras and sensors is called
Image preprocessing
Feature extraction
Image segmentation
Image acquisition
Removing noise and enhancing image quality is done during
Image acquisition
Image segmentation
Object detection
Image preprocessing
Dividing an image into meaningful regions is known as
Feature extraction
Image classification
Object detection
Image segmentation
Detecting edges and corners in images is part of
Image classification
Object detection
Motion tracking
Feature extraction
Assigning a single label to an entire image is called
Object detection
Image segmentation
Motion analysis
Image classification
Identifying object location and class using bounding boxes is known as
Image classification
Feature extraction
Image preprocessing
Object detection
