Unit I- Introduction to Artificial Intelligence (817) Class 9

Introduction to Artificial Intelligence Multiple Choice Questions:

Introduction to Artificial Intelligence Fill in the Blanks :

  1. _______________test checks the machine’s ability to exhibit intelligent behaviour. [Turing test]
  2. __________________year is known as AI winter.[1974]
  3. Microsoft introduced the ________ software in 2014.[Cortana]
  4. ______________are based on data that Google collects about you.[Predictive searches]
  5. ______________is the type of AI that can understand or learn any intellectual task that a human being can.[AGI (Artificial General Intelligence)]
  6. A ___________is a computer program designed to simulate conversation with human users, especially over the Internet.[Chatbot]
  7. A__________ allows homeowners to control appliances, thermostats, lights, and other devices remotely using a smartphone or tablet through an internet connection.[Smart home]
  8. An Al-powered_____________ accepts voice commands to create to-do lists, order items online, set reminders, and answer questions (via internet searches).[Personal assistant]
  9. _____________is a subfield of machine learning.[Deep learning]
  10. The program called ______________defeated the Go champion.[AlphaGo]


Introduction to Artificial Intelligence true or false statements.

  1. Artificial intelligence today is rightly known as narrow AI.[True]
  2. AGI systems are used to assist doctors.[False]
  3. Banks use Al is by sending mobile alerts to help prevent against fraud.[True]
  4. Ahuman-machine interface is also known as a man-machine interface (MMI).[False]
  5. To expertise in AI, programmers should not have a curious and creative mindset[False]
  6. A smart home allows homeowners to control appliances, thermostats, lights, and other devices remotely using a smartphone or tablet through an internet connection.[True]
  7. Smart Governance is a feature of the Smart City.[True]
  8. Engineers do not need to learn programming languages such as Python, C++, Rand Java.[False]
  9. Deep Learning is a subfield of Algorithm Bias.[False]
  10. Robotic science is used for multiple functions from space exploration, healthcare, security to many other scientific fields.[True]


Introduction to Artificial Intelligence Short Answer type Questions:

1. Why is the Turing test performed?

The Turing test is performed to evaluate a machine’s ability to exhibit intelligent behavior indistinguishable from that of a human. It was proposed by Alan Turing in 1950 as a way to determine if a machine can exhibit human-like intelligence.


2. What are the types of AI?

There are various types of AI, including:

a) Narrow or Weak AI: This type of AI is designed to perform specific tasks or functions and is focused on a limited area. Examples include voice assistants like Siri or Alexa.

b) General AI: General AI refers to AI systems that possess human-level intelligence and can understand, learn, and apply knowledge across various domains. However, true general AI does not yet exist and remains a goal for future development.

c) Superintelligent AI: This refers to AI systems that surpass human intelligence and possess exceptional cognitive capabilities. Superintelligent AI is hypothetical and represents a level of AI that surpasses human intellectual capacity.


3. Write the name of applications of Al in daily life?

Some applications of AI in daily life include:

a) Virtual assistants: Voice-activated virtual assistants like Siri, Alexa, or Google Assistant help with tasks such as setting reminders, answering questions, and controlling smart home devices.

b) Recommendation systems: AI-powered recommendation systems suggest products, movies, music, or articles based on user preferences and behavior.

c) Image and speech recognition: AI is used in applications like facial recognition, object detection, and speech-to-text conversion, improving the accuracy and efficiency of these technologies.

d) Autonomous vehicles: AI plays a crucial role in self-driving cars, enabling them to perceive the environment, make decisions, and navigate safely.

e) Personalized healthcare: AI is used in areas like medical imaging analysis, drug discovery, and personalized treatment recommendations.


4. What are simple and smart chatbots?

Simple chatbots are basic AI systems that follow predefined rules and provide programmed responses based on keywords or patterns. They have limited capabilities and cannot understand complex queries beyond their programmed responses.

Smart chatbots, on the other hand, utilize advanced AI techniques such as natural language processing and machine learning. They can understand and interpret user queries, learn from interactions, and provide more intelligent and contextually relevant responses.


5. Define smart city?

A smart city is a concept that describes the integration of technology and data-driven solutions to improve the quality of life for its residents. It involves the use of various technologies, including AI, to enhance urban infrastructure, services, and sustainability. Smart cities aim to optimize resource usage, improve transportation, enhance public safety, promote efficient governance, and provide better overall living conditions for citizens.


6. What are the main features of a Smart school?

The main features of a smart school may include:

a) Digital classrooms: Smart schools incorporate technology such as interactive whiteboards, tablets, and educational software to enhance the learning experience.

b) Personalized learning: AI-powered educational platforms can adapt to individual student needs, providing customized learning paths and personalized feedback.

c) Smart infrastructure: Schools can implement automated systems for tasks like attendance tracking, security, and energy management.

d) Data-driven decision making: Smart schools use data analytics to track student performance, identify areas for improvement, and optimize teaching strategies.

e) Collaboration tools: AI-based collaboration tools enable students and teachers to work together remotely, share resources, and engage in interactive learning experiences.


7. What is human-machine interaction? Write about HYMI interface with some examples.

Human-machine interaction (HMI) refers to the communication and interaction between humans and machines or computers. It involves the design and development of interfaces that allow users to interact with machines effectively and intuitively.

An example of HMI is a touch screen interface on a smartphone, where users can interact with the device by tapping, swiping, or typing. Another example is a voice-controlled virtual assistant like Siri or Alexa, where users can give commands or ask questions using natural language.


8.Name Al career opportunities.

AI career opportunities include:

a) Machine learning engineer: They develop and implement machine learning models and algorithms for various applications.

b) Data scientist: They analyze and interpret complex data to derive insights and build predictive models using machine learning techniques.

c) AI research scientist: They work on cutting-edge research in AI, developing new algorithms and advancing the field.

d) AI ethics specialist: They focus on the ethical implications of AI technologies and ensure their responsible and fair use.

e) AI software developer: They design and develop software applications that utilize AI techniques and algorithms.

f) Robotics engineer: They work on designing, building, and programming robots with AI capabilities.

g) AI consultant: They provide expertise and guidance on implementing AI solutions in various industries.


9.Which skills are required to become a data scientist?

To become a data scientist, some essential skills include:

a) Strong programming skills: Proficiency in languages like Python or R is crucial for data manipulation, analysis, and building machine learning models.

b) Statistical knowledge: Understanding statistical concepts and techniques is important for analyzing data and drawing meaningful conclusions.

c) Machine learning expertise: Knowledge of machine learning algorithms, techniques, and frameworks is essential for building predictive models.

d) Data visualization: The ability to effectively visualize and communicate data insights using tools like Matplotlib or Tableau.

e) Domain knowledge: Familiarity with the specific domain or industry in which the data scientist operates allows for better context and more relevant analysis.

f) Problem-solving skills: Data scientists need to approach complex problems with a logical and analytical mindset.


10.What are machine learning engineers expecting to know?

Machine learning engineers are expected to have a deep understanding of machine learning algorithms, techniques, and frameworks. They should be proficient in programming languages like Python or R and have experience in data preprocessing, feature engineering, and model evaluation. Knowledge of statistical concepts and data visualization is also important. Additionally, machine learning engineers should be familiar with software engineering principles, version control systems, and deployment techniques to operationalize machine learning models efficiently.