_____ AI is able to perform dedicated task. A. Narrow AI B. General AI C. Neural AI D. None of above

_____ AI is able to perform dedicated task. A. Narrow AI B. General AI C. Neural AI D. None of above
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A. Narrow AI 
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Related questions

Machine can perform any task better than human with cognitive properties is known as ___ AI. A. Narrow AI B. General AI C. Super AI D. None of above

Description : Machine can perform any task better than human with cognitive properties is known as ___ AI. A. Narrow AI B. General AI C. Super AI D. None of above

Last Answer : C. Super AI 

____ AI is a type of intelligence which could perform any intellectual task with efficiency like human. A. Narrow AI B. General AI C. Super AI D. None of above

Description :  ____ AI is a type of intelligence which could perform any intellectual task with efficiency like human. A. Narrow AI B. General AI C. Super AI D. None of above

Last Answer : B. General AI 

IBM Watson supercomputer comes under ____ AI. A. Narrow AI B. General AI C. Neural AI D. None of above

Description : IBM Watson supercomputer comes under ____ AI. A. Narrow AI B. General AI C. Neural AI D. None of above

Last Answer : A. Narrow AI 

Apple siri is a good example of ______ AI. A. Narrow AI B. General AI C. Neural AI D. None of above

Description : Apple siri is a good example of ______ AI. A. Narrow AI B. General AI C. Neural AI D. None of above

Last Answer : A. Narrow AI 

Weak AI is also known as ____ A. Narrow AI B. General AI C. Neural AI D. None of above

Description : Weak AI is also known as ____ A. Narrow AI B. General AI C. Neural AI D. None of above

Last Answer : A. Narrow AI 

Narrow AI is performs multiple task at a time. A. True B. False

Description : Narrow AI is performs multiple task at a time. A. True B. False

Last Answer : B. False 

____ AI is hypothetical concept of AI. A. Narrow AI B. General AI C. Super AI D. None of above

Description : ____ AI is hypothetical concept of AI. A. Narrow AI B. General AI C. Super AI D. None of above

Last Answer : C. Super AI 

Ability to think, puzzle, make judgments, plan, learn, communication by its own is known as ___ AI. A. Narrow AI B. General AI C. Super AI D. None of above

Description : Ability to think, puzzle, make judgments, plan, learn, communication by its own is known as ___ AI. A. Narrow AI B. General AI C. Super AI D. None of above

Last Answer : C. Super AI 

Playing chess, purchasing suggestions on e-commerce site, self-driving cars, speech recognition, and image recognition are the example of ____. A. Narrow AI B. General AI C. Super AI D. None of above

Description : Playing chess, purchasing suggestions on e-commerce site, self-driving cars, speech recognition, and image recognition are the example of ____. A. Narrow AI B. General AI C. Super AI D. None of above

Last Answer : A. Narrow AI 

The worldwide researchers are now focusing on developing machines with ___ AI. A. Narrow AI B. General AI C. Super AI D. None of above

Description : The worldwide researchers are now focusing on developing machines with ___ AI. A. Narrow AI B. General AI C. Super AI D. None of above

Last Answer : B. General AI 

The idea behind _________AI to make such a system which could be smarter and think like a human by its own. A. Narrow AI B. General AI C. Super AI D. None of above

Description : The idea behind _________AI to make such a system which could be smarter and think like a human by its own. A. Narrow AI B. General AI C. Super AI D. None of above

Last Answer : B. General AI 

Which of the following is true? Single layer associative neural networks do not have the ability to: (i) perform pattern recognition (ii) find the parity of a picture (iii)determine whether two or more shapes in a picture are connected or not a) (ii) and (iii) are true b) (ii) is true c) All of the mentioned d) None of the mentioned

Description : Which of the following is true? Single layer associative neural networks do not have the ability to: (i) perform pattern recognition (ii) find the parity of a picture (iii)determine whether two or more shapes in ... ) are true b) (ii) is true c) All of the mentioned d) None of the mentioned

Last Answer : a) (ii) and (iii) are true

Which of the following is true? Single layer associative neural networks do not have the ability to: (i) perform pattern recognition (ii) find the parity of a picture (iii)determine whether two or more shapes in a picture are connected or not a) (ii) and (iii) are true b) (ii) is true c) All of the mentioned d) None of the mentioned

Description : Which of the following is true? Single layer associative neural networks do not have the ability to: (i) perform pattern recognition (ii) find the parity of a picture (iii)determine whether two or more shapes in a ... ) are true b) (ii) is true c) All of the mentioned d) None of the mentioned

Last Answer : a) (ii) and (iii) are true

Deep learning is a subfield of machine learning where concerned algorithms are inspired by the structured and function of the brain called _____. A. Machine learning B. Artificial neural networks C. Deep learning D. Robotics

Description : Deep learning is a subfield of machine learning where concerned algorithms are inspired by the structured and function of the brain called _____. A. Machine learning B. Artificial neural networks C. Deep learning D. Robotics

Last Answer : B. Artificial neural networks 

_____ model were developed and incorporated in machines which mimicked the functionalities of human origin. A. Functional model B. Neural model C. Computational model D. None of above

Description : _____ model were developed and incorporated in machines which mimicked the functionalities of human origin. A. Functional model B. Neural model C. Computational model D. None of above

Last Answer : C. Computational model 

Which AI should understand the human emotions, people, and beliefs and be able to interact socially like humans. A. Reactive machine B. Limited memory C. Theory of mind D. None of above

Description : Which AI should understand the human emotions, people, and beliefs and be able to interact socially like humans. A. Reactive machine B. Limited memory C. Theory of mind D. None of above

Last Answer : C. Theory of mind  

The “Turing Machine” showed that you could use a/an _____ system to program any algorithmic task. a) binary b) electro-chemical c) recursive d) semantic

Description : The “Turing Machine” showed that you could use a/an _____ system to program any algorithmic task. a) binary b) electro-chemical c) recursive d) semantic

Last Answer : a) binary

Perceptron is A. General class of approaches to a problem. B. Performing several computations simultaneously C. Structures in a database those are statistically relevant D. Simple forerunner of modern neural networks, without hidden layers

Description : Perceptron is A. General class of approaches to a problem. B. Performing several computations simultaneously C. Structures in a database those are statistically relevant D. Simple forerunner of modern neural networks, without hidden layers

Last Answer : D. Simple forerunner of modern neural networks, without hidden layers

A _________ is a decision support tool that uses a tree-like graph or model of decisions and their possible consequences, including chance event outcomes, resource costs, and utility. a) Decision tree b) Graphs c) Trees d) Neural Networks

Description : A _________ is a decision support tool that uses a tree-like graph or model of decisions and their possible consequences, including chance event outcomes, resource costs, and utility. a) Decision tree b) Graphs c) Trees d) Neural Networks

Last Answer : a) Decision tree

Which of the following is an application of NN (Neural Network)? a) Sales forecasting b) Data validation c) Risk management d) All of the mentioned

Description : Which of the following is an application of NN (Neural Network)? a) Sales forecasting b) Data validation c) Risk management d) All of the mentioned

Last Answer : d) All of the mentioned

The network that involves backward links from output to the input and hidden layers is called _________ a) Self organizing maps b) Perceptrons c) Recurrent neural network d) Multi layered perceptron

Description : The network that involves backward links from output to the input and hidden layers is called _________ a) Self organizing maps b) Perceptrons c) Recurrent neural network d) Multi layered perceptron

Last Answer : c) Recurrent neural network

Neural Networks are complex ______________ with many parameters. a) Linear Functions b) Nonlinear Functions c) Discrete Functions d) Exponential Functions

Description : Neural Networks are complex ______________ with many parameters. a) Linear Functions b) Nonlinear Functions c) Discrete Functions d) Exponential Functions

Last Answer : a) Linear Functions

Which of the following is not the promise of artificial neural network? a) It can explain result b) It can survive the failure of some nodes c) It has inherent parallelism d) It can handle noise

Description : Which of the following is not the promise of artificial neural network? a) It can explain result b) It can survive the failure of some nodes c) It has inherent parallelism d) It can handle noise

Last Answer : a) It can explain result

Why is the XOR problem exceptionally interesting to neural network researchers? a) Because it can be expressed in a way that allows you to use a neural network b) Because it is complex binary operation that cannot be solved using neural networks c) Because it can be solved by a single layer perceptron d) Because it is the simplest linearly inseparable problem that exists.

Description : Why is the XOR problem exceptionally interesting to neural network researchers? a) Because it can be expressed in a way that allows you to use a neural network b) Because it is complex ... solved by a single layer perceptron d) Because it is the simplest linearly inseparable problem that exists.

Last Answer : d) Because it is the simplest linearly inseparable problem that exists.

What is Neuro software? a) A software used to analyze neurons b) It is powerful and easy neural network

Description : What is Neuro software? a) A software used to analyze neurons b) It is powerful and easy neural network

Last Answer : b) It is powerful and easy neural network

Which is true for neural networks? a) It has set of nodes and connections b) Each node computes it’s weighted input c) Node could be in excited state or non-excited state d) All of the mentioned

Description : Which is true for neural networks? a) It has set of nodes and connections b) Each node computes it’s weighted input c) Node could be in excited state or non-excited state d) All of the mentioned

Last Answer : d) All of the mentioned

What are the advantages of neural networks over conventional computers? (i) They have the ability to learn by example (ii) They are more fault tolerant (iii)They are more suited for real time operation due to their high ‘computational’ rates a) (i) and (ii) are true b) (i) and (iii) are true c) Only (i) d) All of the mentioned

Description : What are the advantages of neural networks over conventional computers? (i) They have the ability to learn by example (ii) They are more fault tolerant (iii)They are more suited for real time operation due to their high ... true b) (i) and (iii) are true c) Only (i) d) All of the mentioned

Last Answer : d) All of the mentioned

Which of the following is true? (i) On average, neural networks have higher computational rates than conventional computers. (ii) Neural networks learn by example. (iii) Neural networks mimic the way the human brain works. a) All of the mentioned are true b) (ii) and (iii) are true c) (i), (ii) and (iii) are true d) None of the mentioned

Description : Which of the following is true? (i) On average, neural networks have higher computational rates than conventional computers. (ii) Neural networks learn by example. (iii) Neural networks mimic the way the human brain works. ... ) are true c) (i), (ii) and (iii) are true d) None of the mentioned

Last Answer : a) All of the mentioned are true

What is an auto-associative network? a) a neural network that contains no loops b) a neural network that contains feedback c) a neural network that has only one loop d) a single layer feed-forward neural network with pre-processing

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Last Answer : b) a neural network that contains feedback

What is perceptron? a) a single layer feed-forward neural network with pre-processing b) an auto-associative neural network c) a double layer auto-associative neural network d) a neural network that contains feedback

Description : What is perceptron? a) a single layer feed-forward neural network with pre-processing b) an auto-associative neural network c) a double layer auto-associative neural network d) a neural network that contains feedback

Last Answer : a) a single layer feed-forward neural network with pre-processing

A perceptron is a ______________ a) Feed-forward neural network b) Backpropagation algorithm c) Backtracking algorithm d) Feed Forward-backward algorithm

Description : A perceptron is a ______________ a) Feed-forward neural network b) Backpropagation algorithm c) Backtracking algorithm d) Feed Forward-backward algorithm

Last Answer : a) Feed-forward neural network

Neural Networks are complex ______________with many parameters. a) Linear Functions b) Nonlinear Functions c) Discrete Functions d) Exponential Functions

Description : Neural Networks are complex ______________with many parameters. a) Linear Functions b) Nonlinear Functions c) Discrete Functions d) Exponential Functions

Last Answer : b) Nonlinear Functions

Claude Shannon described the operation of electronic switching circuits with a system of mathematical logic called _____________ a) LISP b) XLISP c) Neural networking d) Boolean algebra

Description : Claude Shannon described the operation of electronic switching circuits with a system of mathematical logic called _____________ a) LISP b) XLISP c) Neural networking d) Boolean algebra

Last Answer : c) Neural networking

Research scientists all over the world are taking steps towards building computers with circuits patterned after the complex interconnections existing among the human brain’s nerve cells. What name is given to such type of computers? a) Intelligent computers b) Supercomputers c) Neural network computers d) Smart computers

Description : Research scientists all over the world are taking steps towards building computers with circuits patterned after the complex interconnections existing among the human brain's nerve cells. What name ... ? a) Intelligent computers b) Supercomputers c) Neural network computers d) Smart computers

Last Answer : c) Neural network computers

An Artificial Neural Network Is based on? a) Strong Artificial Intelligence approach b) Weak Artificial Intelligence approach c) Cognitive Artificial Intelligence approach d) Applied Artificial Intelligence approach

Description : An Artificial Neural Network Is based on? a) Strong Artificial Intelligence approach b) Weak Artificial Intelligence approach c) Cognitive Artificial Intelligence approach d) Applied Artificial Intelligence approach

Last Answer : c) Cognitive Artificial Intelligence approach

Three main basic features involved in characterizing membership function are A. Intution, Inference, Rank Ordering B. Fuzzy Algorithm, Neural network, Genetic Algorithm C. Core, Support , Boundary D. Weighted Average, center of Sums, Median

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Last Answer : C. Core, Support , Boundary

Neural Computing A. mimics human brain B. information processing paradigm C. Both (a) and (b) D. None of the above

Description : Neural Computing A. mimics human brain B. information processing paradigm C. Both (a) and (b) D. None of the above

Last Answer : C. Both (a) and (b)

Core of soft Computing is A. Fuzzy Computing, Neural Computing, Genetic Algorithms B. Fuzzy Networks and Artificial Intelligence C. Artificial Intelligence and Neural Science D. Neural Science and Genetic Science

Description : Core of soft Computing is A. Fuzzy Computing, Neural Computing, Genetic Algorithms B. Fuzzy Networks and Artificial Intelligence C. Artificial Intelligence and Neural Science D. Neural Science and Genetic Science

Last Answer : D. Neural Science and Genetic Science

In artificial Neural Network interconnected processing elements are called A. nodes or neurons B. weights C. axons D. Soma

Description : In artificial Neural Network interconnected processing elements are called A. nodes or neurons B. weights C. axons D. Soma

Last Answer : A. nodes or neurons

Artificial neural network used for A. Pattern Recognition B. Classification C. Clustering D. All of these

Description : Artificial neural network used for A. Pattern Recognition B. Classification C. Clustering D. All of these

Last Answer : D. All of these

A Neural Network can answer A. For Loop questions B. what-if questions C. IF-The-Else Analysis Questions D.

Description : A Neural Network can answer A. For Loop questions B. what-if questions C. IF-The-Else Analysis Questions D.

Last Answer : B. what-if questions

Which of the following is the model used for learning? a) Decision trees b) Neural networks c) Propositional and FOL rules d) All of the mentioned

Description : Which of the following is the model used for learning? a) Decision trees b) Neural networks c) Propositional and FOL rules d) All of the mentioned

Last Answer : d) All of the mentioned

A perceptron is a ——————————–. a) Feed-forward neural network b) Back-propagation algorithm c) Back-tracking algorithm d) Feed Forward-backward algorithm e) Optimal algorithm with Dynamic programming

Description : A perceptron is a ——————————–. a) Feed-forward neural network b) Back-propagation algorithm c) Back-tracking algorithm d) Feed Forward-backward algorithm e) Optimal algorithm with Dynamic programming

Last Answer : a) Feed-forward neural network

Neural Networks are complex ———————–with many parameters. a) Linear Functions b) Nonlinear Functions c) Discrete Functions d) Exponential Functions e) Power Functions

Description : Neural Networks are complex ———————–with many parameters. a) Linear Functions b) Nonlinear Functions c) Discrete Functions d) Exponential Functions e) Power Functions

Last Answer : b) Nonlinear Functions

Which of the following is an application of NN (Neural Network)? a) Sales forecasting b) Data validation c) Risk management d) All of the mentioned

Description : Which of the following is an application of NN (Neural Network)? a) Sales forecasting b) Data validation c) Risk management d) All of the mentioned

Last Answer : d) All of the mentioned

The network that involves backward links from output to the input and hidden layers is called as ____. a) Self organizing maps b) Perceptrons c) Recurrent neural network d) Multi layered perceptron

Description : The network that involves backward links from output to the input and hidden layers is called as ____. a) Self organizing maps b) Perceptrons c) Recurrent neural network d) Multi layered perceptron

Last Answer : c) Recurrent neural network

Neural Networks are complex ______________ with many parameters. a) Linear Functions b) Nonlinear Functions c) Discrete Functions d) Exponential Functions

Description : Neural Networks are complex ______________ with many parameters. a) Linear Functions b) Nonlinear Functions c) Discrete Functions d) Exponential Functions

Last Answer : a) Linear Functions

Which of the following is not the promise of artificial neural network? a) It can explain result b) It can survive the failure of some nodes c) It has inherent parallelism d) It can handle noise

Description : Which of the following is not the promise of artificial neural network? a) It can explain result b) It can survive the failure of some nodes c) It has inherent parallelism d) It can handle noise

Last Answer : a) It can explain result

Why are linearly separable problems of interest of neural network researchers? a) Because they are the only class of problem that network can solve successfully b) Because they are the only class of problem that Perceptron can solve successfully c) Because they are the only mathematical functions that are continue d) Because they are the only mathematical functions you can draw

Description : Why are linearly separable problems of interest of neural network researchers? a) Because they are the only class of problem that network can solve successfully b) Because they are the only ... mathematical functions that are continue d) Because they are the only mathematical functions you can draw

Last Answer : b) Because they are the only class of problem that Perceptron can solve successfully

This set of Artificial Intelligence MCQs focuses on “Neural Networks – 2”. 1. Why is the XOR problem exceptionally interesting to neural network researchers? a) Because it can be expressed in a way that allows you to use a neural network b) Because it is complex binary operation that cannot be solved using neural networks c) Because it can be solved by a single layer perceptron d) Because it is the simplest linearly inseparable problem that exists.

Description : This set of Artificial Intelligence MCQs focuses on Neural Networks - 2 . 1. Why is the XOR problem exceptionally interesting to neural network researchers? a) Because it can be expressed in ... by a single layer perceptron d) Because it is the simplest linearly inseparable problem that exists.

Last Answer : d) Because it is the simplest linearly inseparable problem that exists.