Revision of Artificial Intelligence (AI)

Give names of any two online shopping websites where you have observed the use of AI. Write your observations also.

Answer

Two online shopping websites where the use of Artificial Intelligence can be observed are:

1. Amazon
   Observation: Amazon uses AI to suggest similar or related products based on a user’s previous searches and purchases. It also recommends products that other customers have bought together, which improves the shopping experience.

2. Flipkart
   Observation: Flipkart uses AI to show personalised product recommendations and targeted advertisements. It analyses customer behaviour, purchase history, and preferences to suggest suitable products to users.

From the following sentences, identify the sentences that depict data and information. Write them under the proper heading.

1. The temperature is 25 degrees Celsius.
2. A patient's blood pressure is 120/80 mmHg.
3. The patient's blood pressure is 120/80 mmHg, which is in the normal range.
4. The stock price of the Company XYZ has increased.
5. The city received a significant amount of rainfall, which may lead to improved water reserves and agricultural productivity.
6. The customer rating for the new phone is good, indicating high satisfaction and desirability.
7. Number of website visitors are 10,000.

Answer

Write the names of any two online surveying tools.

Answer

The names of any two online surveying tools are:

1. Google Form
2. Emails

Deep learning includes algorithms based on the concept of artificial neural network.

Answer

True

Reason — Deep learning includes specialised artificial neural networks, which are inspired by the structure of the human brain.

Turing test was proposed by John McCarthy.

Answer

False

Reason — The Turing test was proposed by Alan Turing in 1950.

Chatbots are helpful in improving sales and marketing.

Answer

True

Reason — AI-enabled chatbots help in sales and marketing by interacting with customers, handling their queries, providing product recommendations, and collecting feedback, which helps improve sales and marketing activities.

AI can be used to develop only semi-automatic machines.

Answer

False

Reason — AI can be used to develop autonomous machines such as robots and self-driving vehicles that work with little or no human intervention. Therefore, AI is not limited to developing only semi-automatic machines.

Natural language processing helps in the analysis of image data.

Answer

False

Reason — Natural Language Processing (NLP) is used to process and understand human language, such as text and speech. The analysis of image data is done using other AI techniques, not NLP.

AI systems cannot be used in natural disaster management.

Answer

False

Reason — AI can be used in natural disaster management for analysing data from satellite images, sensors, and other sources to predict disasters, assess damage, and support speedy disaster recovery.

Information is the processed form of data.

Answer

True

Reason — Information is the processed form of data.

Video data is not useful for developing AI applications.

Answer

False

Reason — Data available in the form of video is considered as video data, and video data is used in developing AI applications such as online lectures, videos captured through mobile phones, and YouTube videos.

Kaggle is a platform which provides plenty of datasets for machine learning purpose.

Answer

True

Reason — Platforms like Kaggle offer a huge number of datasets for different topics and provide datasets for machine learning purpose.

Data should be relevant for developing a successful AI system.

Answer

True

Reason — To design an accurate AI system, relevant data must be identified, collected, and explored.

Data is used to identify patterns.

Answer

True

Reason — To learn patterns and relationships, AI models, such as deep learning neural networks, require extensive training with the help of data.

Survey is a method to collect desired data.

Answer

True

Reason — Surveys can be done online or offline using web forms or emails. Users are asked a number of important questions, and their replies are recorded as text, audio, or video.

OR gate produces '1' if at least one input is '1'.

Answer

True

Reason — OR gate produces output '1' when at least one of the inputs is '1', it produces '0' only when both inputs are '0', as shown in the OR gate truth table:

Binary logic is the base of all types of computing.

Answer

True

Reason — Binary logic, which uses 1s and 0s, is the basis of modern computing, and that all modern computing techniques still use binary logic at the backend, even for advanced systems like AI.

Assembly language is less readable as compared to binary language.

Answer

False

Reason — Assembly language was developed to provide a more readable representation of machine code or binary code for humans. Binary language consists only of 0s and 1s and is less readable, whereas assembly language uses symbols and mnemonics, making it easier for humans to understand.

Who devised the term "Artificial Intelligence"?

1. Alan Turing
2. Marvin Minsky
3. John McCarthy
4. None of these

Answer

John McCarthy

Reason — The term "Artificial Intelligence" was first coined by John McCarthy in 1956, and he is also known as the Father of Artificial Intelligence.

The structure of neural networks was inspired by ................ .

1. Human brain structure
2. Computer programming
3. Logical reasoning
4. Statistical analysis and data modelling

Answer

Human brain structure

Reason — Artificial neural networks are inspired by the structure of the human brain.

The Turing test includes a human judge who interacts with ............... .

1. Two computer programs
2. An AI machine and a human
3. Two humans
4. A human

Answer

An AI machine and a human

Reason — In the Turing test, a human judge (evaluator) interacts with both a human and a machine simultaneously and compares their responses to determine whether the machine shows human-like intelligence.

............... is an important application of AI in banking.

1. Route planning
2. Customer health monitoring
3. Fraud detection
4. Patient surgery

Answer

Fraud detection

Reason — In the banking sector, AI is used to analyse historical and real-time financial data to identify fraudulent or abnormal transactions, which helps banks prevent financial losses.

............... is an AI method used to unlock a mobile phone's screen.

1. Object recognition
2. Path planning
3. Reasoning
4. Face recognition

Answer

Face recognition

Reason — Face recognition is an AI-based technique used to identify a person by analysing facial features, and it is commonly used in smartphones to unlock the mobile phone screen.

Explainability means ............... .

1. Explanations for how AI system derives the conclusion
2. Who is responsible for developed AI system
3. Reasoning
4. All of these

Answer

Explanations for how AI system derives the conclusion

Reason — Explainability in AI refers to providing clear and understandable explanations for how an AI system arrives at its decisions or conclusions. It helps users understand and trust the reasoning behind AI outputs.

Information can be defined as ............... .

1. Raw facts
2. Abrupt sentences
3. Processed data
4. Collection of dates only

Answer

Processed data

Reason — Information is the processed form of data.

The primary purpose of data in AI is ............... .

1. To train AI models
2. To generate revenue
3. To develop algorithms
4. None of these

Answer

To train AI models

Reason — The primary purpose of data in AI is to train AI models. AI algorithms use huge amount of data to learn and make predictions.

Data can be collected through ............... .

1. Newspapers
2. Audio files
3. Images
4. All of these

Answer

All of these

Reason — Data is represented in many forms such as text, image, audio, and video, and can be collected through newspapers, audio files, and images.

Which technique would be suitable to process the data from an article?

1. Computer vision
2. Natural Language Processing
3. Speech recognition
4. None of these

Answer

Natural Language Processing

Reason — Natural Language Processing would be suitable to process the data from an article. Large text data collections, such as books and articles, are utilised to train AI models to understand language and context.

Which platform(s) use(s) recommendation system?

1. YouTube
2. Netflix
3. Amazon
4. All of these

Answer

All of these

Reason — Platforms such as Netflix, Amazon, Spotify, YouTube, etc., use AI-based recommendation systems to recommend personalised content to users.

Which of the following is not used in data visualisation?

1. Images
2. Graphs
3. Charts
4. Text

Answer

Text

Reason — Data visualisation allows the graphical representation of data in the form of charts, graphs, or diagrams.

Digital circuits work on which of the following?

1. Decimal logic
2. Binary logic
3. Both a and b
4. None of these

Answer

Binary logic

Reason — Digital circuits are based on binary logic and use binary signals (0 and 1) through logic gates to perform logical functions and process information.

Which is true for X-OR gate?

1. It gives '1' when both inputs are '1'.
2. It gives '1' when both inputs are '0'.
3. It gives '1' when one inputs is '1' and other input is '0'.
4. None of these

Answer

It gives '1' when one inputs is '1' and other input is '0'.

Reason — The X-OR gate produces output '1' when both inputs are complement to each other, and produces '0' when both inputs are the same.

In AND gate, if one input is '1', then what would be the value of other input to get '1' as the output?

1. 0
2. 1
3. Any
4. None of these

Answer

1

Reason — An AND gate produces output '1' only when both inputs are '1'. Therefore, if one input is already '1', the other input must also be '1' to get output '1'.

Fill in the blanks:

1. The program ................, developed by Joseph Weizenbaum, was able to perform conversation between a user and a computer.
2. In the Turing test, the machine tries to convince the judge that it is a ................ .
3. Remote patient monitoring can be done through AI and ................ .
4. ................ is an example of an AI platform for analysing research and development data.
5. AI can keep an eye on the wellbeing and behaviour of animals via ................ and ................ .
6. ................ is used to collect data from a large number of people.
7. ................ helps in getting useful information from websites and other online tools.
8. ................ Machine Learning Repository provides many datasets.
9. ................ and ................ are examples of descriptive statistics.
10. ................ create abstraction between hardware and software.
11. ................ and ................ are example of deep learning models.
12. ................ is the sub domain of machine learning.
13. ................ is the basis of all types of computing.
14. Deterministic computing is suitable for ................ .

Answer

1. The program ELIZA, developed by Joseph Weizenbaum, was able to perform conversation between a user and a computer.
2. In the Turing test, the machine tries to convince the judge that it is a Human.
3. Remote patient monitoring can be done through AI and Smart devices.
4. Knime Analytics Platform is an example of an AI platform for analysing research and development data.
5. AI can keep an eye on the wellbeing and behaviour of animals via Wearables and sensors.
6. Crowdsourcing is used to collect data from a large number of people.
7. Web scraping helps in getting useful information from websites and other online tools.
8. UCI Machine Learning Repository provides many datasets.
9. Mean and median are examples of descriptive statistics.
10. Operating systems create abstraction between hardware and software.
11. CNN and RNN are example of deep learning models.
12. Deep learning is the sub domain of machine learning.
13. Binary logic system is the basis of all types of computing.
14. Deterministic computing is suitable for Simple calculations.

How does AI help in enhancing cyber security in defence? Explain.

Answer

AI helps in enhancing cyber security in defence by threat detection, anomaly detection, and mitigation. Machine learning algorithms analyse a huge amount of data to identify patterns indicative of cyber threats or attacks, which helps in protecting defence systems from cyber threats.

How is AI used in generating choice-based recommendation of online entertainment videos? Explain.

Answer

AI is used in generating choice-based recommendation of online entertainment videos by analysing user preferences, viewing patterns, and historical data. AI algorithms study information such as watching history, ratings, and genre preferences to recommend movies and TV series according to the user’s interests. This helps in providing personalised content suggestions on entertainment platforms.

How is AI helpful in assisting humans? Explain.

Answer

AI is helpful in assisting humans by providing personalised assistance through technologies such as chatbots and virtual assistants. These AI systems help users by responding to queries, providing recommendations, and assisting with tasks, which improves customer service and user experience.

AI-powered virtual assistants such as Amazon Alexa, Apple Siri, Google Assistant, and Microsoft Cortana help users in creating reminders, answering queries, delivering information, and managing smart home devices.

How does AI help in reducing human error? Explain.

Answer

AI helps in reducing human errors in many ways. Some examples are:

• Human errors induced by weariness, supervision, or carelessness are reduced by eliminating human involvement in dull and repetitive processes.
• AI algorithms may validate data to assure its accuracy and integrity. Inconsistencies, abnormalities, or missing values in datasets can be identified and flagged. This helps in minimising errors.
• Natural language processing systems can understand context, remove spelling errors, and recommend acceptable replies.

What do you understand by prejudice? Explain with the help of an example.

Answer

Prejudice is an unfavourable view or assumption that is formed without knowledge, reason, or justification. It is a judgement or opinion formed without knowing the facts, particularly against an ethnic, racial, socio-economic, or religious group.

Example: An AI system is designed to predict the chances of diabetes. If the data is collected by assuming that obesity leads to diabetes, the data may include only the weight of people and ignore other factors such as family history, blood pressure, anxiety, etc. In this case, the prediction generated by the AI model will be wrong in most cases due to prejudice in data collection.

Why is data important in AI-based recommendation systems?

Answer

Data is important in AI-based recommendation systems because AI algorithms use large amounts of data to learn user preferences and behaviour. Recommendation systems analyse data such as user choices, past interactions, ratings, and browsing history to identify patterns. The quality, quantity, and relevance of data directly affect the performance and accuracy of the recommendations. Accurate and well-processed data helps the AI system generate personalised and meaningful recommendations, whereas poor or insufficient data can lead to incorrect or less useful suggestions.

Differentiate between data and information.

Answer

The difference between data and information is as follows:

What do you understand by Natural Language Processing?

Answer

Natural Language Processing (NLP) is an application of artificial intelligence that enables machines to understand language and context. NLP applications rely extensively on large collections of text data, such as books, articles, and social media postings, to train AI models. This helps AI systems to generate accurate translations, understand sentiments, and answer queries based on the data’s knowledge.

What do you understand by machine learning and deep learning? Explain.

Answer

Machine Learning is a technique in which computing systems learn from data and observations and improve their performance by updating models.

Deep Learning is a sub-domain of machine learning. CNN and RNN are examples of deep learning models.

What are the various characteristics of deterministic computing? Explain.

Answer

The main characteristics of deterministic computing include:

1. Consistency: In deterministic computing, the execution of a program or system always produces the same output for a given input, regardless of how many times it is executed. This consistency guarantees repeatability and predictability of outcomes.
2. Non-adaptability: Deterministic computing is dependent on predefined algorithms or sets of rules that control the system's behaviour. These algorithms define the sequence of operations to be executed based on the input without variation or adaptability during execution.
3. Absence of Randomness: Deterministic computing does not contain random elements. The computations are based on logical operations, arithmetic calculations, and if-then statements, and contain no inherent uncertainty.

Write various applications of AI in commercial field.

Answer

AI has impacted many industries and organisations. Some important applications of AI in commercial field are:

1. 24 x 7 Customer service: AI-enabled chat bots can handle customer queries 24 x 7. These chatbots can also help with product recommendations and collecting feedback.

2. Sales and marketing: AI helps improve the sale of a product by sending personalised messages to customers by understanding their buying patterns and choices.

3. Supply chain management: The supply chain system can be managed by understanding product demand and supply. This can be done by analysing product reviews through AI-enabled tools.

4. Fraud detection: Financial data can be analysed with the help of AI tools. It will help in detecting fraudulent activities and handling financial losses.

5. Product development: AI tools can be used to understand customer requirements and feedback that will help in developing optimised products. It will also help in understanding product shortcomings and future consequences.

6. Risk management: Financial risks can be analysed through AI tools by observing historical data. These tools also suggest risk-handling solutions.

Write various applications of AI in healthcare.

Answer

AI has several applications in the medical and healthcare domain. Some common applications of AI in healthcare are:

1. Understanding medical images: AI tools are used to understand medical images such as X-rays, CT scans, and MRIs. This helps medical professionals diagnose diseases like cancer, cardiovascular conditions, and other abnormalities.

2. Diagnosis of diseases: AI algorithms help in diagnosing diseases by analysing patient history, symptoms, and medical records. AI-enabled tools can generate warning messages regarding diseases based on a person’s symptoms and lifestyle.

3. Drug discovery: AI helps in analysing a huge amount of biomedical data to identify potential drug combinations and predict the effectiveness or side effects of drugs.

4. Personalised medicine: AI helps in prescribing personalised medical treatments by analysing a patient’s genetic information, medical history, and lifestyle data.

5. Virtual assistants: AI-assisted virtual assistants help in handling patient's queries and provide full-time support to monitor the physical and mental health of patients.

6. Robotic surgery: AI-enabled robots are used to perform complex surgeries, which enhance surgical accuracy, reduce invasiveness, and improve results.

7. Predictive analytics: AI algorithms analyse patient data to predict disease conditions, identify risks, and recommend preventive measures, especially for chronic diseases.

8. Healthcare administration: AI is used to manage medical records, appointment scheduling, billing, and other administrative tasks, improving hospital administration.

What are the important applications of AI in transport?

Answer

Some of the important applications of AI in transport are:

1. Traffic management: AI analyses real-time traffic data to improve traffic flow and reduce congestion. It helps in forecasting traffic patterns, identifying jams, and dynamically changing traffic signals to reduce travel time, fuel use, and carbon emissions.

2. Maintenance prediction: AI monitors the condition of vehicles and predicts repair requirements by examining sensor data and previous performance.

3. Intelligent Transportation Systems (ITS): AI is used in ITS to improve the effectiveness and security of transportation networks. It analyses data from traffic cameras, GPS systems, and sensors to provide real-time traffic information.

4. Autonomous vehicles: AI is used in self-driving vehicles to process data from sensors, radar, and cameras, enabling vehicles to assess surroundings, make quick decisions, and navigate safely.

5. Logistics: AI analyses data on transit routes to optimise logistics operations, enhance route planning, reduce delivery time, and save costs.

6. Customer service: AI-enabled virtual assistants help customers with ticket booking, answering queries, providing personalised suggestions, and real-time travel information.

7. Safety and security: AI systems analyse video feeds from surveillance cameras to identify suspicious activities, monitor crowd behaviour, and enhance security at transportation hubs.

8. Demand prediction: AI systems forecast transportation demand by analysing historical data, current events, and other variables, helping in capacity management and service optimisation.

What are the various benefits of AI in monitoring the progression of contagious diseases?

Answer

AI may be used to track the spread of infectious diseases by analysing data from diverse sources, such as social media, news stories, medical records, and public health databases. Some examples of AI in monitoring contagious diseases are:

• AI techniques help in identifying keywords, phrases, or patterns related to symptoms, sickness, or infection.
• AI may anticipate prospective disease outbreaks or follow the progress of an existing infectious disease by recognising similar content or geolocation data.
• The use of AI technologies during COVID-19 is a recent example of the application of AI to monitor contagious diseases. During this pandemic, AI tools were used to spread awareness, identify the virus, identify disease through X-Ray and CT scans, develop vaccines, anticipate and track the spread of the virus, and monitor patients.

What do you understand by transparency in AI? Explain with the help of an example.

Answer

Transparency in AI refers to the transparency and openness for the decision-making processes of AI systems. Users and stakeholders should understand how AI systems work, make choices, and what data they utilise. Transparent AI systems allow for inspection, the identification and correction of biases, and the development of user trust.

Example: An example of transparency in AI may be reviewing loan applications and deciding eligibility. Transparency in this sense means providing explicit information about how the AI system reviews loan applications and decides creditworthiness. This involves revealing the elements and criteria taken into account, such as credit history, income, debt-to-income ratio, and other important characteristics. Transparent AI solutions also improve applicants' access to the decision-making process. If a loan application is declined, the AI system may deliver an explanation to the applicant, outlining the particular reasons for the decision and the elements that led to it.

What do you understand by data? Explain its various types.

Answer

Data refers to the raw facts that are generated by almost all activities of our daily routine. Data is everything that we can get by reading, writing, speaking, and seeing. It can be made up of numbers, alphabets, symbols, or a mix of any or all these elements. The collection of data or facts is considered as a dataset.

Various types of data are as follows:

1. Text Data: Data available in the form of text is considered as text data. Examples of text data are research articles, any information available on websites in text form, information available in books, newspapers, etc.

2. Image Data: Pictures are images that can be processed as image data. Examples of image data are the images related to a specific subject.

3. Audio Data: This type of data contains only audio files. Examples of audio data are audio clips of songs, recordings of speeches, recordings of lectures, news, etc.

4. Video Data: Data available in the form of video is considered as video data. Examples of video data are movies, online lectures, videos captured through mobile phones, YouTube videos, etc.

What are the various methods of collecting relevant data in AI project development?

Answer

The various methods of collecting relevant data in AI project development are as follows:

1. Survey: Surveys can be done online or offline using web forms or emails. Users are asked a number of important questions, and their replies are recorded as text, audio, or video.

2. Observations: Data can be collected through observations by keeping track of people, things, or events in their natural environment and recording the observations.

3. Data Logging and Sensor Deployment: Sensors or data loggers are used to collect useful environmental data for AI projects that use the Internet of Things (IoT) or sensor-based data collection.

4. Web Scraping: Web scraping helps in getting useful information from websites and other online tools by crawling web pages and extracting structured or unstructured data.

5. Application Programming Interfaces (APIs): APIs allow developers to get and use specific data from online platforms such as social media sites, weather services, banking databases, and public data sources.

6. Collaborations and Data Partnerships: Data can be collected by making agreements to share data or by building partnerships with organisations that possess proprietary or specialised datasets.

7. Crowdsourcing: Crowdsourcing tools let people from all over the world work together to acquire data by performing assigned tasks and following given instructions.

8. Existing Datasets: Data can be collected from publicly available datasets provided by platforms such as Kaggle, UCI Machine Learning Repository, government data portals, and research institutions.

What are the various applications of data in AI? Explain.

Answer

The various applications of data in AI are as follows:

1. Natural Language Processing (NLP): NLP applications rely extensively on data. Large text data collections, such as books, articles, and social media postings, are utilised to train AI models to understand language and context. This enables the AI system to generate accurate translations, understand sentiments, and answer queries based on the data’s knowledge.

2. Autonomous Vehicles: Data is essential for the development of autonomous vehicles. Sensors and cameras collect a huge amount of data about the surrounding environment, such as road conditions, other vehicles, and pedestrians. This data is used to train AI models to perceive and understand their surroundings, make decisions in real time, and drive safely.

3. Recommendations: Data plays a vital role in designing AI-based recommendation systems. Platforms such as Netflix, Amazon, Spotify, and YouTube use AI-based recommendation systems to recommend personalised content to users based on viewing history, purchase behaviour, and preferences.

4. Fraud Detection: AI models are used to analyse a huge amount of transactional data in fraud detection systems. By analysing data patterns and anomalies, these models help in identifying potentially fraudulent activities and generating alerts.

5. Medical Imaging: AI models can analyse medical imaging data, such as X-rays, CT scans, and MRIs, to help in disease detection and diagnosis in the healthcare industry. By training on labelled medical images, AI algorithms learn to recognise patterns associated with various conditions.

What are the different methods of exploring relevant data in AI project development?

Answer

Exploring relevant data in AI requires various techniques to obtain insights and understand the data's characteristics. Some important data exploration techniques are:

1. Data Visualisation: Data visualisation techniques allow the graphical representation of data in the form of charts, graphs, or diagrams. Data visualisation can reveal patterns, trends, or relationships within the data, making it simpler to recognise important features and understand the data.
2. Statistical Analysis: It permits the quantification and summarisation of data using statistical methods. The descriptive statistics, such as mean, median, standard deviation, and percentiles, summarise the central tendency, dispersion, and shape of the data.

Why is binary logic system important?

Answer

The binary logic system is important because it is a big part of how computers work and how decisions are made. Binary logic, which employs a system of ones and zeros (bits) to represent and manipulate data, is the basis of modern computing. The basis of digital electronics, which is the basis of all current computer systems, is binary logic. Logic gates like AND, OR, and NOT are used to build electronic circuits. These gates use binary signals (0s and 1s) to perform logical functions and process information.

Binary logic is very important while creating and understanding digital circuits. Logic gates can be used to make circuits that perform mathematical calculations, handle signals, store and change data in binary form. This binary reasoning is the basis for how computers and microprocessors are built. Binary reasoning is also an important part of programming a computer. Programming languages use Boolean data types (true/false) and logical operators to analyse conditions and control how programs run. Decision-making systems, such as expert systems and rule-based systems, also use binary reasoning. These systems use if-then rules and logical conditions to review inputs and decide the correct actions or conclusions.

Find out any five activities in your surroundings or your daily routine that are using artificial intelligence. Also, write which technology of AI they are using.

Answer

Some activities in our daily routine that use Artificial Intelligence and the AI technology used in them are:

Suppose you have a collection of X-ray images for a disease. Which AI technique would be suitable for identifying the disease through these images and why?

Answer

AI technique based on medical imaging would be suitable for identifying the disease through X-ray images because AI models can analyse medical imaging data, such as X-rays, to help in disease detection and diagnosis in the healthcare industry. By training on labelled medical images, AI algorithms learn to recognise patterns associated with various conditions and help radiologists and physicians in making more precise decisions.

Identify a real-world problem of your environment where you feel that AI computing is more suitable than deterministic computing.

Answer

Weather prediction is a real-world problem where AI computing is more suitable than deterministic computing.

Weather conditions depend on many uncertain factors such as temperature, humidity, wind speed, and atmospheric pressure. AI computing can analyse large amounts of past and real-time data, learn patterns, and predict the probability of events like rainfall. Deterministic computing, which works on fixed rules, cannot handle such uncertainty effectively.