Artificial Intelligence and Emerging Technology

 

Artificial Intelligence and Emerging Technology

Short Answer type questions: (2 marks each)

1.       What is Artificial Intelligence? Write in simple words. Artificial Intelligence (AI) is a branch of computer science focused on creating machines that can think, learn, and act like humans. They are programmed to replicate human abilities such as reasoning, problem-solving, planning, understanding language, and making decisions.

2.       What is Machine Learning and how is it different from AI? Machine Learning (ML) is a subset of AI that enables computers to learn from data and improve their performance over time without being directly programmed for every rule. While AI is the broader concept of making machines intelligent and human-like using reasoning and natural language processing, ML focuses specifically on identifying patterns in datasets to make predictions.

3.       Give real-life examples of Artificial Intelligence. Real-life examples of AI include chess-playing computers, self-driving cars, smart assistants (Siri, Alexa), face recognition lock on smartphones, language translation tools, and expert medical diagnosis systems.

4.       Why is Machine Learning important in today’s world? Machine learning is important because it allows systems to analyze massive volumes of data, detect hidden patterns, and make automated decisions or predictions without needing manual step-by-step programming.

5.       What is the relationship between AI and ML? AI is the overarching umbrella field dealing with making machines smart, whereas ML is a core subfield of AI that supplies the algorithms and data-driven methods that allow AI systems to learn from experience.

6.       What is supervised learning? Give examples. Supervised learning is a technique where a machine is trained using labeled data (data accompanied by clear answers or tags) under guidance, like learning with a teacher. Examples include training a system with tagged images of lions and tigers to identify them, or filtering emails into "spam" and "not spam".

7.       What is unsupervised learning? Give some examples. Unsupervised learning is a technique where a computer learns from unlabeled data and must discover hidden patterns or groupings by itself without external guidance. Examples include grouping pictures of animals by appearance without prior tags, or categorizing customers based on shopping patterns.

8.       What are the differences between supervised and unsupervised learning?

9.       Supervised Learning: Trains on labeled data, knows expected outputs during training, and acts like learning with a teacher (e.g., email spam filtering).

10.   Unsupervised Learning: Trains on unlabeled data, searches for inherent patterns or clusters, and acts like learning without a teacher (e.g., customer shopping segmentation).

11.   Differences between Artificial Intelligence and Machine Learning.

12.   Scope: AI is the broad branch aimed at creating human-like intelligence, whereas ML is a specific subset focused on learning from data patterns.

13.   Methods: AI incorporates problem-solving, robotics, and natural language processing; ML focuses primarily on predictive statistical patterns.

14.   Examples: AI includes smart hotel service robots; ML includes recommendation systems on platforms like YouTube or email filters.

15.   What are two e-commerce websites in Nepal? Write about each one briefly. While the textbook explicitly lists Daraz in its exercise options as a primary e-commerce platform and highlights e-commerce as buying and selling goods online 24/7 with doorstep delivery, detailed background profiles for individual Nepalese shopping portals beyond Daraz are not fully detailed in the text body.

16.   What is AI in Robotics? Write in simple words. AI in Robotics is the field of designing and operating robots equipped with sensors (like cameras and microphones) and AI software to sense their environment and perform complex, automated tasks safely without human risk.

17.   What is a line following robot? How does it work? While specific terms like "line following robot" are practical robotics applications, the text explains that robots use optical and movement sensors to detect environmental guidance cues and follow programmed paths.

18.   What is an Obstacle Avoidance Robot? How does it work? Robots and autonomous vehicles use distance and vision sensors to perceive surrounding objects, signs, and obstacles, making real-time decisions to turn or stop to avoid collisions.

19.   Why is simulation important in robotics? Robotic simulation (using platforms like Scratch or RoboBlocky) is important because it allows programmers to design, code, and test robotic tasks—such as moving in specific shapes or responding to conditions—safely in a virtual environment before deploying code to physical hardware.

20.   What is a Pick and Place robot? Where is it used? Though referred to broadly under intelligent robots, these systems use vision systems and grippers to move items automatically; they are heavily used in manufacturing assembly lines, warehouses, and factories.

21.   What is Generative AI? Write in simple words. Generative AI (GenAI) is artificial intelligence technology capable of creating new, original content—such as text, images, audio, or video—by learning from vast amounts of existing data.

22.   What is ChatGPT? What tasks does it perform? ChatGPT is a powerful AI chatbot developed by OpenAI. It processes natural language, text prompts, files, and images to generate responses, write text, answer queries, and assist in creative writing.

23.   What is Microsoft Copilot? Where is it used? Microsoft Copilot is a generative AI tool developed by Microsoft (in partnership with OpenAI and GitHub) designed to assist with text writing and coding. It is used directly inside Microsoft 365 apps like Word, Excel, PowerPoint, and development environments.

24.   What is Google Gemini? What makes it different? Google Gemini is Google’s advanced AI chatbot. What sets it apart is its direct integration across Google’s ecosystem of productivity tools, such as Google Docs and Gmail.

25.   Give two examples of how Generative AI is used in daily life.

26.   Creating custom artwork or educational images using text prompts (e.g., DALL-E, Craiyon).

27.   Drafting documents, generating auto-summaries, or writing emails in tools like Google Docs and Microsoft Word.

28.   What AI features are available in Google Docs? Integrated AI in Google Docs provides Smart Compose with auto-correction, Grammar and Spelling checks, Voice typing, Language translation, and Auto summary.

29.   What AI features are available in Gmail? Integrated AI in email includes Smart Compose and quick replies, Schedule email, Spam filtering, Grammar/writing suggestions, and Email summarization.

30.   What can Microsoft Copilot do in Word? In Word, Copilot acts as an AI-powered writing tool that helps draft, rewrite, format, and structure text content.

31.   What can Microsoft Copilot do in Excel? In Excel, Copilot performs AI-driven data analysis, identifying trends and generating insights from spreadsheet datasets.

32.   What can Microsoft Copilot do in PowerPoint? In PowerPoint, Copilot provides AI-enhanced presentation design, assisting in formatting slides and organizing visual content.

33.   What is bias in AI? Give an example. Bias in AI occurs when an AI system makes unfair decisions or discriminates based on factors like gender, race, or background due to incomplete or biased training data. Example: A job hiring AI trained primarily on male resumes might unfairly penalize or ignore applications submitted by female candidates.

34.   What is a privacy concern in AI? Why is it important? A privacy concern involves the risk of unauthorized access or misuse of personal data collected and stored by AI systems. Protecting privacy is vital to prevent identity theft, unauthorized spying, and unfair profiling.

35.   What is a security concern in AI? Give an example. An AI security concern involves threats like hacking or malicious tampering with an AI system’s training data, causing it to fail or act unsafely. Example: A hacked self-driving car whose data is tampered with might fail to recognize a red light and cause an accident.

36.   How can we reduce bias in AI? Bias can be reduced by auditing training datasets to ensure they are fair, diverse, and complete, and by actively checking and correcting model outputs for human biases.

37.   What is an adversarial attack on AI? While discussed in the context of system security, adversarial threats involve tampering with or altering input data to deceive an AI into making incorrect decisions or failing safety checks.

38.   What is the Internet of Things (IoT)? Write in simple words. The Internet of Things (IoT) is a network of physical objects (like vehicles, appliances, and sensors) that collect and exchange data over the internet automatically without human intervention.

39.   Give some examples of IoT in smart homes. Examples include smart home assistants, automated lighting, connected TVs, and smoke detectors that automatically alert fire services upon sensing smoke.

40.   Give examples of IoT in healthcare. Examples include smart health monitors and wearable sensors that remotely track patient vital signs and transmit records to doctors.

41.   Give examples of IoT in agriculture. Examples include smart farming sensors that monitor soil conditions, crop health, weather parameters, and automated irrigation.

42.   Give examples of IoT in smart cities. Examples include smart traffic management, smart power grids to conserve electricity, smart transportation systems, and predictive garbage collection monitoring.

43.   What is Virtual Reality (VR)? Give an example. Virtual Reality (VR) is a fully computer-generated environment that simulates a real or imagined world. Example: Wearing a VR headset to explore virtual worlds, play games, or attend virtual classrooms.

44.   What is Augmented Reality (AR)? Give an example. Augmented Reality (AR) is a technology that overlays digital graphics or information onto the real world using a smartphone screen or smart glasses. Example: Viewing 3D digital objects or navigation labels overlaid on top of physical surroundings via a mobile camera.

45.   What is Mixed Reality and how is it different from Augmented Reality? Under the umbrella of Extended Reality (XR), AR projects digital layers over the real world, whereas Mixed Reality blends real and digital elements so that physical and virtual objects co-exist and interact in real time.

46.   What does XR stand for? What does it include? XR stands for Extended Reality. It is an overarching term that includes Virtual Reality (VR), Augmented Reality (AR), and related immersive technologies that merge physical and digital realities.