Module 1: Introduction and Applications of AI
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In this post, I provide accurate answers and detailed explanations for Module 1: Introduction and Applications of AI of Course 1: Introduction to Artificial Intelligence (AI) – IBM Generative AI Engineering Professional Certificate
Whether you’re preparing for quizzes or brushing up on your knowledge, these insights will help you master the concepts effectively. Let’s dive into the correct answers and detailed explanations for each question.
Practice Quiz: Introduction to AI
Practice Assignment
1. Which of the following categories of artificial intelligence (AI) engages and performs a diverse array of distinct and unrelated tasks?
- Narrow AI
- Machine learning AI
- Strong AI ✅
- Super AI
Explanation:
Strong AI (also called Artificial General Intelligence) is designed to perform any intellectual task a human can. It can handle diverse and unrelated tasks without needing specific training for each one. In contrast, Narrow AI handles only specific tasks (like chatbots, spam filters), and Super AI is hypothetical and would surpass human intelligence in all respects.
2. Artificial intelligence (AI) encompasses applying logical thinking, ______________________, interpreting sensory data, and comprehending language.
- Problem-solving ✅
- Algorithm development
- Knowledge representation
- Searching for data
Explanation:
AI aims to simulate human intelligence, which includes logical thinking, problem-solving, interpreting data (e.g., from cameras, microphones), and understanding language (like natural language processing).
While knowledge representation is important, it refers to how AI stores and organizes information, not what it does. Problem-solving is an active process that fits the list of core AI capabilities.
3. Generative AI is an AI technique capable of creating new and novel data. How does generative AI generate new data?
- By using shallow learning techniques and small data sets
- By mimicking the actions of human experts directly
- By using deep learning techniques and vast data sets ✅
- By following pre-defined rules and patterns
Explanation:
Generative AI (like ChatGPT, DALL·E, or music-generating models) uses deep learning — especially neural networks — trained on large-scale datasets to understand patterns and generate new text, images, or other content.
It doesn’t rely on predefined rules or mimic human experts directly — it learns patterns statistically.
Practice Quiz: Impact and Applications of AI
Practice Assignment
4. The manager of an online retail store wants to improve their customer engagement and increase sales. Which application of AI will be most beneficial for delivering personalized products to customers based on their purchasing behavior?
- Recommendation system ✅
- Chatbots
- Sentiment analysis
- AI-enabled video analytics
Explanation:
Recommendation systems analyze customer behavior, preferences, and purchase history to suggest relevant products. This increases engagement and sales by showing users items they’re more likely to buy — like Amazon’s “Customers who bought this also bought…” feature.
- Chatbots help with customer service, not personalized product delivery.
- Sentiment analysis gauges customer opinions, usually in reviews.
- AI-enabled video analytics is used more in surveillance and retail traffic analysis.
5. What is the large language model used by Amazon?
- GPT-4 model
- Titan model ✅
- Claude model
- Llama model
Explanation:
Titan is Amazon’s family of large language models (LLMs), part of AWS Bedrock. Titan models support various tasks like text generation, summarization, classification, and more.
- GPT-4 is by OpenAI.
- Claude is by Anthropic.
- LLaMA is by Meta.
6. Which AI application inspects products for defects on assembly lines?
- Predictive analytics
- Image recognition system ✅
- Robo-advisors
- Benevolent AI
Explanation:
Image recognition systems use computer vision to detect visual defects in products during manufacturing. This automates quality control and reduces human error.
- Predictive analytics forecasts future events or failures.
- Robo-advisors are used in finance.
- Benevolent AI is a healthcare/biotech company, not a specific inspection tool.
Graded Quiz: Introduction and Applications of AI
Graded Assignment
7. Which of the following examples best describes the applications of Narrow AI?
- A system that mimics human-level general intelligence
- An AI that can autonomously drive a car and solve complex scientific problems simultaneously
- An AI that can understand and perform any intellectual task similar to humans
- A virtual assistant that schedules appointments and sets reminders ✅
Explanation:
Narrow AI (also called Weak AI) is designed for a specific task. Virtual assistants like Siri or Alexa perform limited functions such as scheduling or setting reminders—perfect examples of Narrow AI.
Other options describe Strong AI or General AI, which can do tasks across domains.
8. Which of the following describes how AI improves the user experience with virtual assistants?
- Providing fixed, pre-programmed responses
- Understanding and processing natural language queries ✅
- Enabling manual task scheduling
- Storing a large database of facts
Explanation:
Natural Language Processing (NLP) allows AI assistants to understand user queries in natural, human language. This makes interactions smoother and more intuitive.
- Pre-programmed responses are rigid and outdated.
- Manual scheduling and large databases alone don’t improve user experience without intelligent interpretation.
9. In the context of personalized marketing, how does AI predict consumer behavior?
- By conducting surveys with consumers
- By using historical purchase data and browsing behavior ✅
- By analyzing social media trends alone
- By manually reviewing consumer feedback answers for this
Explanation:
AI analyzes large volumes of historical data (like what a user bought or searched for) to predict future buying patterns—enabling targeted ads and product recommendations.
- Surveys and manual reviews are slow and less scalable.
- Social media trends help but are not as precise alone.
10. Generative AI performs various tasks. Which of the following is a common use of generative AI?
- To create artwork and music ✅
- To perform complex mathematical calculations
- To manage cloud storage solutions
- To maintain network securities
Explanation:
Generative AI models like DALL·E or MusicLM can create images, art, music, text, and video—this is their most recognized and unique feature.
11. The healthcare sector uses AI for predictive analytics. Which of the following systems enables this technology?
- CT scans
- X-rays
- MRIs
- EHRs ✅
Explanation:
EHRs store vast medical histories and are the primary source of structured data for predictive AI models in healthcare—helping forecast risks, recommend treatments, and more.
CTs, X-rays, MRIs are imaging tools, not predictive data sources.
12. Choose the statement that best describes the capabilities of multimodal models in AI.
- Utilizes specialized algorithms to handle complex numerical computations
- Combines and interprets data from multiple sources, such as text, images, and audio, to provide comprehensive insights ✅
- Integrates data only from structured databases for comprehensive analysis
- Processes data from a single source at a time to improve accuracy
Explanation:
Multimodal AI can interpret multiple types of data (like ChatGPT with images, text, etc.)—offering a broader understanding than models limited to one input type.
13. Which of the following is a popular generative AI chatbot?
- Microsoft Cortana
- Amazon Alexa
- ChatGPT ✅
- Siri
Explanation:
ChatGPT (by OpenAI) is a state-of-the-art generative AI chatbot known for its human-like conversational abilities and creative content generation.
Cortana, Alexa, and Siri are virtual assistants but not generative AI.
14. Which of the following statements best describes a challenge associated with generative AI?
- Generative AI can produce content that lacks coherence or relevance if not properly guided by training data. ✅
- Generative AI models are incapable of learning from their mistakes, which limits their effectiveness.
- Generative AI models always require less data than other AI models to perform effectively.
- Generative AI is limited in its ability to produce varied content, often resulting in repetitive outputs.
Explanation:
Generative AI depends heavily on training data. If the data is biased, insufficient, or poorly structured, the output may be nonsensical or irrelevant.
15. What is a common challenge associated with deploying AI chatbots in customer service?
- Ensuring that chatbots can handle a wide range of queries with accuracy and context ✅
- Avoiding the use of chatbots due to their inability to gather customer feedback
- Reducing the cost of implementing chatbots, which is generally low compared to human representatives
- Integrating chatbots with traditional customer service systems that do not support digital interactions
Explanation:
The biggest challenge is making chatbots understand context, nuance, and diverse user intents—which are often unpredictable and complex.
16. In which of the following scenarios is generative AI most effectively utilized?
- Diagnosing medical conditions from patient symptoms using historical records
- Creating personalized marketing content based on customer data ✅
- Enhancing cybersecurity by identifying vulnerabilities in software systems
- Translating text from one language to another using predefined rules
Explanation:
Generative AI can use customer data to generate custom ad copy, emails, and offers, making it ideal for marketing automation.
- Medical diagnosis and cybersecurity are better handled by predictive or rule-based AI.
- Translation using predefined rules is outdated; modern AI uses deep learning instead.
17. Which of the following is NOT a good way to define Al?
- Al is the use of algorithms that enable computers to find patterns without humans having to hard code them manually
- Al is the application of computing to solve problems in an intelligent way using algorithms.
- Al is all about machines replacing human intelligence. ✅
- Al is Augmented Intelligence and is not intended to replace human intelligence rather extend human capabilities
Explanation: AI involves augmenting and extending human intelligence, not solely replacing it.
18. Which of the following is an attribute of Strong or Generalized Al?
- Operate with human-level consciousness
- Perform independent tasks ✅
- Cannot teach itself new strategies
- Can perform specific tasks, but cannot learn new ones
Explanation: Strong AI can teach itself new strategies and solve diverse problems.
19. Al is the fusion of many fields of study. Which of these fields, along with Computer Science, plays a role in the application of Al?
- All responses are correct ✅
- Philosophy
- Statistics
- Mathematics
Explanation: These fields collectively guide AI’s ethical, mathematical, and statistical foundations.
20. Which of these is NOT a current application of Al?
- Collaborative Robots helping humans lift heavy containers
- Self-Driving vehicles utilizing Computer Vision to navigate around objects
- Classifying rock samples to identify best places to drill for oil
- Making precise patient diagnosis and prescribing independent treatment ✅
Explanation: AI supports doctors but does not independently replace their role in patient interactions.
21. Natural Language Al algorithms that learn by example are the reason we can talk to machines and they can talk back to us.
- True ✅
- False
Explanation: Natural Language Processing and Generation enable this interaction.
22. Advances in the field of Computer Vision make which of the following possible?
- Detecting fraudulent transactions
- Detecting cancerous moles in skin images ✅
- On-demand online tutors
- Real-time transcription
Explanation: Computer Vision aids in medical diagnostics, such as analyzing skin images for cancer.
23. Which of these is currently NOT an application of Collaborative Robots or Cobots?
- Robots helping move items on shelves for stocking purposes
- Personal use in the home such as doing the laundry and cooking for example ✅
- Robots helping humans lift heavy containers
- Robots assisting or replacing humans in jobs that may be dull, dangerous, ineffective or inefficient when done by humans
Explanation: Collaborative robots are not yet widely used for independent personal tasks in homes.
24. Which of the following aspects involved in converting the stethoscope into a digital device to support patient diagnoses involves the use of Al?
- Inserting a digitizer into the stethoscope tube to convert the analog sound of the heart beat into a digital signal
- Graphing heart beat data on the mobile device allowing a physician to spot trends
- Sending digital signals to a mobile device with a machine learning app via bluetooth
- An app on the mobile device that applies learnings from previous diagnosis data to assist the physicians in their current diagnoses ✅
Explanation: Machine learning algorithms in the app analyze data to support diagnoses.
25. Which of the following are applications of Artificial Intelligence in action? A. IBM Watson utilizing its information retrieval capabilities to provide technical information to oil and gas company workers. B. Watson analyzing Grammy nominated song lyrics over a 60-year period and categorizing them based on their emotions. C. Assisting patients with neurological damage by detecting patterns in massive movement related datasets and using robots to trigger specific movements in the human body to create new neural pathways in the brain. D. Law enforcement authorities using facial recognition algorithms to identify suspects in multiple streams of video footage
- Only option A is correct
- Only options A, B, and C are correct
- None of the options are correct
- All of the options are correct ✅
Explanation: Each example showcases practical applications of AI across industries.
26. Which of the following is NOT a way that Al learns?
- Intuitive learning ✅
- Reinforcement learning
- Unsupervised learning
- Supervised learning
Explanation: AI learns through Supervised, Unsupervised, and Reinforcement Learning methods, but not through intuitive learning.
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