Artificial Intelligence MCQ Quiz - Objective Question with Answer for Artificial Intelligence - Download Free PDF

Artificial Intelligence (AI) represents the advancement of machines that mimic human thinking, learning, and problem-solving. In the age of AI, candidates must be aware of all the advancements being made in the world of Artificial Intelligence and their impact. Artificial intelligence MCQs test individuals' understanding of key concepts and techniques in the field of artificial intelligence. These questions cover topics like machine learning, neural networks, natural language processing, computer vision, expert systems, and robotics. Artificial intelligence MCQs evaluate candidates' knowledge and problem-solving skills in this rapidly evolving field. Check how much you know about Artificial Intelligence and its role with the given Artificial Intelligence MCQs.

Latest Artificial Intelligence MCQ Objective Questions

Artificial Intelligence Question 1:

Which of the following is a major advancement in Natural Language Processing (NLP) that has significantly improved language understanding and generation in AI systems?

1. Symbolic AI
2. Convolutional Neural Networks (CNNs)
3. Transformer models
4. Genetic algorithms

Answer (Detailed Solution Below)

Artificial Intelligence Question 1 Detailed Solution

The correct answer is Transformer models.

Key Points

• Transformer models are a type of architecture for deep learning that primarily drives advancements in Natural Language Processing (NLP).
• They are known for their self-attention mechanism, which allows them to weigh the importance of different words in a sentence, irrespective of their positional distance.
• The introduction of transformer models, such as BERT and GPT, has significantly improved the capabilities of AI systems in language understanding and generation.

Additional Information

• Symbolic AI refers to AI models that process high-level human-like reasoning and logic but are not effective in processing natural language on their own.
• Convolutional Neural Networks (CNNs) are primarily used for processing visual imagery and have limited application in text except in specific contexts like sentence classification.
• Genetic algorithms are a type of optimization algorithm inspired by the process of natural selection, and they are generally not used for language processing tasks.

Artificial Intelligence Question 2:

________ is a method in statistics of inference used to update the probability estimate for a hypothesis as additional evidence is learned.

1. Bayesian Inference
2. Inductive probability
3. Markov theory
4. Information field theory

Answer (Detailed Solution Below)

Artificial Intelligence Question 2 Detailed Solution

The correct answer is Bayesian Inference.

Key Points

• Bayesian inference refers to a statistical method that updates the probability of a hypothesis as more evidence or information becomes available.
• In contrast to classical (frequentist) statistics, Bayesian inference allows for the factoring in of subjective, prior beliefs and their adjustment based on the data to arrive at a final, posterior distribution.
• It is an approach to statistics that relies upon Bayes' theorem.
• It's used in a wide variety of fields, from medicine and engineering to economics and linguistics.

Additional Information

• Inductive probability
  • Inductive probability refers to the probability that a hypothesis will yield a confirmed prediction.
  • While this concept plays an important role in reasoning and decision-making under uncertainty, it's not specifically used to continually update probabilities when new data is acquired.
  • Markov theory refers to a type of stochastic process characterized by the Markov property, where the probability of future states depends only on the current state and not on the sequence of events that preceded it.
  • Although it's used in statistics and is helpful in analysing sequences of events, it's not a method for updating the probability estimate for a hypothesis as new evidence is learned.
  • Information field theory (IFT) is a theoretical framework that allows codification of constraints or acquired knowledge.
  • It's used for signal inference in complex fields, such as astroparticle physics, but it's not a method for updating the probability estimate for a hypothesis as new evidence is acquired.
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  Artificial Intelligence Question 3:

  Which of the following characteristics refers to the use of technology to complete a task with as little human interaction as possible?

  1. Remembrance power
  2. No EQ
  3. No IQ
  4. Automation

  Answer (Detailed Solution Below)

  Option 4 : Automation

  Artificial Intelligence Question 3 Detailed Solution

  The correct answer is Automation

  

  Key Points

  • Automation, in general, is the technology by which a process or procedure is performed without human assistance. It is implemented in different fields such as manufacturing, transportation, utilities, defense, facilities, operations, and recently, in information technology.
  • In automation, automatic control is used, which is the use of various control systems for operating equipment with minimal or reduced human intervention. For example, machinery on an assembly line can be automated to perform tasks without the need for human/manual operation.
  • Some of the key characteristics of automation include:
    • Reduced Labor: Automation is commonly associated with reducing manual labor. Tasks that were once carried out by humans are programmed into a system, and machines perform these tasks without human intervention.
    • Consistency and Quality: Automated tasks typically produce consistent and high-quality results because machines are able to perform the same action in the exact same way every time, reducing the risk of errors that can occur with manual labor.
    • Speed and Efficiency: Machines can typically perform tasks faster than humans without getting tired. With automation, companies can drastically increase their production speeds and operate 24/7 if necessary.
    • Safety: It can replace humans in tasks that are dangerous or require working in hazardous conditions, improving workplace safety.
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    Artificial Intelligence Question 4:

    Which of the following algorithm is related to Artificial Intelligence?
    1. Routing algorithm
    2. Greedy Algorithms
    3. Hill Climbing Algorithm
    4. Recursive algorithm

    Answer (Detailed Solution Below)

    Option 3 : Hill Climbing Algorithm

    Artificial Intelligence Question 4 Detailed Solution

    The correct answer is option 3.

    Concept:

    Hill-climbing algorithm:

    A hill-climbing algorithm is a type of Artificial Intelligence (AI) algorithm that constantly improves in value until it reaches a peak solution. This method is used to solve mathematical issues as well as in real-world applications such as marketing and scheduling.

    • The hill-climbing algorithm is a local search algorithm that proceeds in the direction of rising elevation/value in order to discover the mountain's peak or the best solution to the issue. When it hits a peak value, it stops since no neighbor has a greater value.
    • Hill Climbing is mostly used when a good heuristic is available.
    • It's also known as greedy local search since it just considers its good nearby neighbor state and nothing else.

    Hence the correct answer is Hill Climbing Algorithm.

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    Artificial Intelligence Question 5:

    Use of internet to connect a wide variety of devices, machines and sensors for empowering brick and mortar stores by giving them the same access to data that online stores have is a facility falls under which of the following technologies ?

    1. Artificial Intelligence
    2. Deep Learning
    3. Machine Learning
    4. Internet of Thing

    Answer (Detailed Solution Below)

    Option 4 : Internet of Thing

    Artificial Intelligence Question 5 Detailed Solution

    • The Internet of Things (IoT) refers to the interconnected network of physical devices, machines, and sensors that are embedded with electronics, software, and sensors, and can collect and exchange data over the internet.
    • In the context of brick and mortar stores, IoT can be used to connect a variety of devices and sensors, such as smart shelves, cameras, and customer mobile devices, to provide access to data in real-time. This can empower brick and mortar stores by giving them the same access to data that online stores have, such as tracking inventory levels, customer behavior, and sales trends, allowing them to make informed decisions and provide a better shopping experience for their customers.
    • Artificial Intelligence - AI refers to the development of computer systems that can perform tasks that normally require human intelligence, such as visual perception, speech recognition, decision-making, and language translation.
    • Deep Learning - Deep learning is a type of machine learning that uses artificial neural networks with multiple layers to model and solve complex problems. It is a subset of AI and is used for tasks such as image and speech recognition.
    • Machine Learning - Machine learning is a subfield of artificial intelligence that involves the development of algorithms and models that allow computers to learn from data, make predictions, and improve over time without being explicitly programmed.
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    Top Artificial Intelligence MCQ Objective Questions

    Artificial Intelligence Question 6

    Which of the following languages is suitable for artificial intelligence?

    Answer (Detailed Solution Below)

    Option 3 : Prolog

    Artificial Intelligence Question 6 Detailed Solution

    The Correct Answer: Prolog is a general-purpose programming language associated with artificial intelligence and computational linguistics.

    • All of the listed languages can be used to implement some form of AI, but each one is suitable for different aspects of AI.

    

    Key Points

    • Fortran: It's an old language typically used for numerical and scientific computing. It's not commonly used for modern AI applications but can still be used if necessary, especially for tasks that require heavy numerical computations.
    • Basic: It's a beginner-friendly language. Though it's not typically used for AI applications due to the lack of advanced data structures and libraries, it can be used to implement simple AI systems.
    • Prolog: It's a logic programming language often associated with AI, especially in the domain of expert systems, natural language processing, and knowledge representation. It supports pattern matching and automatic backtracking, which are powerful for these types of tasks.
    • 'C': It's a low-level, general-purpose language. It can be used for AI development, but it might not be the most efficient choice. It lacks the high-level abstractions and libraries (such as TensorFlow or PyTorch) that Python provides, which are commonly used in AI.

    Out of these options, Prolog is likely the most directly associated with AI.

    

    Additional Information However, it should be noted that in current AI development, Python is by far the most widely used language due to its simplicity, flexibility, and the broad ecosystem of AI and machine learning libraries available. Other languages like Java, R, and Julia are also often used.

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    Artificial Intelligence Question 7

    Use of internet to connect a wide variety of devices, machines and sensors for empowering brick and mortar stores by giving them the same access to data that online stores have is a facility falls under which of the following technologies ?

    1. Artificial Intelligence
    2. Deep Learning
    3. Machine Learning
    4. Internet of Thing

    Answer (Detailed Solution Below)

    Option 4 : Internet of Thing

    Artificial Intelligence Question 7 Detailed Solution

    • The Internet of Things (IoT) refers to the interconnected network of physical devices, machines, and sensors that are embedded with electronics, software, and sensors, and can collect and exchange data over the internet.
    • In the context of brick and mortar stores, IoT can be used to connect a variety of devices and sensors, such as smart shelves, cameras, and customer mobile devices, to provide access to data in real-time. This can empower brick and mortar stores by giving them the same access to data that online stores have, such as tracking inventory levels, customer behavior, and sales trends, allowing them to make informed decisions and provide a better shopping experience for their customers.
    • Artificial Intelligence - AI refers to the development of computer systems that can perform tasks that normally require human intelligence, such as visual perception, speech recognition, decision-making, and language translation.
    • Deep Learning - Deep learning is a type of machine learning that uses artificial neural networks with multiple layers to model and solve complex problems. It is a subset of AI and is used for tasks such as image and speech recognition.
    • Machine Learning - Machine learning is a subfield of artificial intelligence that involves the development of algorithms and models that allow computers to learn from data, make predictions, and improve over time without being explicitly programmed.

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    Artificial Intelligence Question 8

    In Artificial Intelligence (AI), an environment is uncertain if it is.
    1. Not fully observable and not deterministic
    2. Not fully observable or not deterministic
    3. Fully observable but not deterministic
    4. Not fully observable but deterministic

    Answer (Detailed Solution Below)

    Option 2 : Not fully observable or not deterministic

    Artificial Intelligence Question 8 Detailed Solution

    In artificial intelligence, environment is that surrounds an agent. Environment is where agent lives, do its work or we can say that surrounding in which agent is present.

    Environment is clearly distinguishable from the agent, it is not the part of the agent. An environment can have various attributes from the point of view of the agent. These are :

    1) Observable and partially observable: An agent is considered to be an agent only if it has the ability to observe its environment. In some cases, environment may be partially observable. Uncertain environment is not fully observable.

    2) Deterministic and stochastic: A deterministic environment is one where any future state of the environment can be completely determines from preceding state and actions of agent. It is stochastic if there is some element of uncertainty.

    3) Episodic and sequential: If each of agent’s tasks do not rely on past performance than episodic otherwise it is sequential.

    4) Discrete and continuous: A discrete environment has finite number of possible states whereas number of states in continuous environment is infinite.