1. The main goal of AI?

A) Automating routine tasks

B) Imitating Human Intelligence and Behavior

C) Requires Less Hardware:

D) Building faster computers

Answer: B) Imitating Human Intelligence and Behavior

2. What is the major core Part of AI?

A) Machine Learning

B) Web Development

C) Database Management

D) Cloud Computing

Answer: A) Machine Learning

3. Which of the following is an example of supervised learning?

A) Decision Trees

B) K-means Clustering

C) Reinforcement Learning

D) Autoencoders

Answer: A) Decision Trees

4. Response: Introduction to Neural Networks in AI??

A) A system of real computers

B) A bunch of algorithms that go hunt for patterns in all this data

C) A data storage system

D) A task managing program.

Answer: B) A bunch of algorithms that go hunt for patterns in all this data

5. Which of the following is an INCORRECT usage of AI?

A) Face Recognition

B) Sentiment Analysis

C) Common Type Arithmetic

D) Self-driving Cars

Answer: C) Common Type Arithmetic

6. The Turing test: What can we learn from it?

A ) Speed: how the machine is faster in performing tasks than a human.

B) If a machine is capable of carrying out any intelligent act, which if it would have been performed by humans may feel deceptive…but better.

C) The accuracy of algorithms

D) Speed of Computer Answer:

Answer: B) If a machine is capable of carrying out any intelligent act, which if it would have been performed by humans may feel deceptive…but better.

7. NLP and which one of the following?

A) Neural Networks

B) Decision Trees

C) Convolutional Networks

D) Transformers

Answer: D) Transformers

8. In Reinforcement learning, what does an agent aim to accomplish?

A) To classify data

B) To increase the cumulative reward received.

C) To minimize error

D) To make decisions faster

Answer: B) To increase the cumulative reward received.

9. Stemgar is most widely used in combinations with deep learning/neural networks. Frame.

A) TensorFlow

B) MySQL

C) Apache Hadoop

D) Flask

Answer: A) TensorFlow

10. Overfitting in Machine Learning

A) The complex common stranding of a model that has good training performance for grabs as bad new data from the same distribution

B) For the model that underfits data.

C) When a model is too simple

D) A model which requires a long time to train

Answer: A) The complex common stranding of a model that has good training performance for grabs as bad new data from the same distribution

11. What is the very basic and initial need of an Activation function in a Neural network?

A) To introduce non-linearity in the network

B) To process inputs

C) To reduce errors

D) To store data

Answer: A) To introduce non-linearity in the network

12. What are unsupervised learning objectives?

A) Label new data

B) Identify data patterns anomalies

C)Supervised learning problems.

D) Maximize output accuracy

Answer: B) Identify data patterns anomalies

13. what is the core of AI reign-worn recommendation systems?

A) Collaborative filtering

B) Genetic Algorithms

C) Regression Analysis

D) Principle Component Analysis.

Answer: A) Collaborative filtering

14. What does backpropagation do in a neural network?

A) gradient descent to change the weights of the network so as it minimize error

B) Real-time feedback

C) Classifies images

D) Manages input data

Answer: A) gradient descent to change the weights of the network so as it minimize error

15. Which domain of AI is concerned with the meaning behind human language?

A) Natural Language Processing (NLP)

B) Reinforcement Learning

C) Deep Learning

D) Image Recognition

Answer: A) Natural Language Processing (NLP)

16. Unsupervised: Which of the following is an unsupervised learning?

A) K-means Clustering

B) Decision Trees

C) Logistic Regression

D) Support Vector Machines

Answer: A) K-means Clustering

17. what we are talking about here is a machine-learning technology called Transformers.

A) Machine Learning

B) Data Analytics

C) Cloud Computing

D) Virtual Reality

Answer: A) Machine Learning

18. Transfer Learning in AI

A) Fine-tuning a pre-trained model on the new problem

B) Create a model from nothing

C) Transfer the data from Network A to B

D) Retraining a failed model

Answer: A) Fine-tuning a pre-trained model on the new problem

19. What does AI bias refer to?

A) A model that is a bad predictor

B) Seemingly ethical impacts within a system as a result of the use of biased data (The Right Answer

Reform option: Option C) Non-performance of AI utilities

D) AI overfitting

Answer: D) AI overfitting

20. What AREA of AI ETHICS gets the MOST ATTENTION?

A) Reducing AI errors

B) Issues of Morality with AI systems

C) Optimizing AI performance

D) Lowering system costs

Answer: B) Issues of Morality with AI systems

21. Is this next example an AGI(predictions) application?

A) something a person does mentally

B) AI that plays chess

C) AI face recognition

D) AI of Self-driving cars

Answer: A) something a person does mentally

22. So, what is AI technology; Does complex domain play a role in decision-making?

A) Reinforcement Learning

B) Decision Trees

C) Unsupervised Learning

D) Genetic Algorithms

Answer: A) Reinforcement Learning

23. Generative adversarial networks (or GANs for short) — so where did they come from?

A) Because it is utilized to fabricate new data by setting two systems in opposition.

B) Optimal Communication within Neural Networks

C) To classify data

D) To increase training speed

Answer: A) Because it is utilized to fabricate new data by setting two systems in opposition.

24. AI Generalization — In Detail

A) How well a model can predict new data

B) How fast a model can train

C) Option CExplanation: Data overfitting done by a system.

D) Increasing the precision by Training data

Answer: A) How well a model can predict new data

25. What is Explainable AI (XAI)?

A) AI approaches with E (true by the definition, it is exactly what we call explainable modified BA– due to human intervention).

B) Less-Data AI Systems

C ) hardware optimized AI

D) AI that learns faster

Answer: A) AI approaches with E (true by the definition, it is exactly what we call explainable modified BA– due to human intervention).

26. Convolutional Neural Network (CNN)- Generally used in all the tasks related to Image recognition.

A) CNN(Convolutional Neural Networks)

B) Support Vector Machines

C) Logistic Regression

D) K-means clustering

Answer: A) CNN(Convolutional Neural Networks)

27. A health-oriented challenge is encountered by the AI in which of these?

A) Data privacy concerns

B) Limited data availability

C) Slow processing speeds

D) Inconsistent algorithms

Answer: A) Data privacy concerns

28. How is RPA for AI

A) (Automating infrequent tasks)

B) Robot movement control

C) Building neural networks

D) Generating training data

Answer: A) (Automating infrequent tasks)

29. Why an AI-based chatbot?

A) Chat in an informal language with users

B) For transaction 6, to make payments for transactions

C) In training machine-learning models

D) To control robotic arms

Answer: A) Chat in an informal language with users

30. AI systems that leverage human-like emotions for improved user interfacing?

A) Affective Computing

B) Predictive Modeling

C) Deep Learning

D) Image Classification

Answer: A) Affective Computing

31. what would be the purpose of AI for self-driving carsjavatpoint

A) Better and Rapid decision-making with AI algorithms

B) To process large datasets

C) To classify objects

D) To manage cloud data

Answer: A) Better and Rapid decision-making with AI algorithms

32. Response: Algorithmic bias caused by biased training data

A) Data Bias

B) Systematic Error

C) Model Drift

D) Overtraining

Answer: A) Data Bias

33. A methodology to make sure that the model never overfits?

A) Cross-validation

B) Gradient Descent

C) Batch Normalization

D) K-means clustering

Answer: A) Cross-validation

34. Keyword Ans(HUman Like UNDERstanding And REasoning)

A) [ Cognitive Computing ]

B) Deep Learning

C) Reinforcement Learning

D) Data Engineering

Answer: A) [ Cognitive Computing ]

35. Sinisto: How AI models are rated?

A) Accuracy and Precision

B) Image Quality

C) Processing Time

D) Data Flow

Answer: A) Accuracy and Precision

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