AKTU Artificial Intelligence For Engineering(KMC 101) Part 2
Q:1. What is an advantage of Artificial Intelligence
1.Potential for misuse
2.Highly dependent on machines
3.Requires Supervision
4.Rational Decision Maker
Solution- 4- Rational Decision Maker
Reason 1- This is because Rational choice theory in A.I. states that it rely on rational calculations to make rational choices that result in outcomes aligned with their own best interests.
Reason 2- This is because Rational choice theory during a .I. states that it believe rational calculations to form rational choices that end in outcomes aligned with their own best interests.
Reason 3- This is because Rational choice theory during artificial intelligence states that it believe rational calculations to make rational choices that end in outcomes aligned with their own best interests.
Q:2. Who is known as the “Father of AI”?
1.Fisher Ada
2.Alan Turing
3.John McCarthy
4.Allen Newell
Solution- 3.John McCarthy
Reason 1- John McCarthy, widely recognized as the father of Artificial Intelligence due to his astounding contribution in the field of Computer Science and AI.
Reason 2- John McCarthy, widely known because the father of AI thanks to his astounding contribution within the field of computing and AI.
Reason 3- John McCarthy, widely known because the father of Artificial intelligence because of his astounding contribution within the sector of computing and AI.
Q:3. Which of the following is not a branch of Artificial Intelligence?
1.Expert systems
2.Robotics
3.Natural language Processing
4.None of the above
Solution- 4.None of the above
Reason 1- This is because Expert System, Robotics and Natural Language processing all have their roles in Artificial Intelligence. There are 6 branches of A.I and these 3 above come under these branches.
Reason 2- This is because Expert System, Robotics and NLP all have their roles in AI . There are 6 branches of A.I and these 3 above come under these branches.
Reason 3- This is because Expert System, Robotics and NLP processing have their roles in AI . There are six branches of A.I and these three above come under these branches.
Q:4. Which of the following is not an application of Unsupervised Learning?
1.Document clustering
2.Speech recognition
3.Image compression
4.Association analysis
Solution- 4. Speech Recognition
Reason 1- This is the kind of application where you teach the algorithm about your voice and it will be able to recognize you. The most well-known real-world applications are virtual assistants such as Google Assistant and Siri, which will wake up to the keyword with your voice only. That is the reason it comes under supervised learning.
Reason 2-This is the type of application where you teach the algorithm about your voice and it’ll be ready to recognize you. the foremost well-known real-world applications are virtual assistants like Google Assistant and Siri, which can awaken to the keyword together with your voice only. that’s the rationale it comes under supervised learning.
Reason 3-This is the type of application where you teach the algorithm about your voice and it’ll be ready to recognize you. the foremost well-known real-world applications are virtual assistants like Google Assistant and Siri, which can awaken to the keyword in conjunction with your voice only. that’s the rationale it comes under supervised learning.
Q:5. The multi-armed bandit problem is a generalized use case for-
1.Reinforcement learning
2.Supervised learning
3.Unsupervised learning
4.All the above
Solution- 1.Reinforcement learning
Reason 1- Multi–Arm Bandit is a classic reinforcement learning problem, in which a player is facing with k slot machines or bandits, each with a different reward distribution, and the player is trying to maximise his cumulative reward based on trials.
Reason 2- Multi-Arm Bandit may be a classic reinforcement learning problem, during which a player is facing with k slot machines or bandits, each with a special reward distribution, and therefore the player is trying to maximise his cumulative reward supported trials.
Reason 3- Multi-Arm Bandit could also be a classic reinforcement learning problem, during which a player is facing with k slot machines or bandits, each with a special reward distribution, and thus the player is trying to maximise his cumulative reward supported trials.
Q:6. Why IOT now?
1.Electronic companies are building Wi-Fi and cellular wireless connectivity into a wide range of devices.
2.Mobile data coverage has improved significantly
3.The size and cost of wireless radios has dropped
4.All the above
Solution- 4.All the above
Reason 1- All of the above options that have provided in this question are correct and helping IOT to evolve in the future.
Reason 2- All of the above options that have provided during this question are correct and helping IOT to evolve within the future.
Q:7. Scalability of IoT means:
1.Expandable/reducible in terms of scale or size.
2.Measurable
3.Increasing/decreasing monetary costs.
4.All of these.
Solution- 4.All of these.
Reason 1- This is because the IOT is expandable/reducible in size or to scale. It is also measurable and its cost can be increased or decreased.
Reason 2- This is because the IOT is expandable/reducible in size or to scale. it’s also measurable and its cost are often increased or decreased.
Q:8. Which of the following statement is incorrect for AI?
1.Humans can not evolve as soon as AI evolves to control and handle it
2.The community working towards safe and beneficial superintelligence has grown worldwide.
3.It is typically managed by a peer-to-peer network working simultaneously together to solve complex mathematical problems in order to validate new blocks
4.AI is the new electricity
Solution- 1.Humans can not evolve as soon as AI evolves to control and handle it
Reason 1- We cannot say humans cannot evolve to control and handle it because humans are working on it regularly to make an A.I that will reduce their workload and time to complete a task, which they will adapt later.
Reason 2- We cannot say humans cannot evolve to regulate and handle it because humans are performing on it regularly to form an A.I which will reduce their workload and time to finish a task, which they’re going to adapt later.
Reason 3- We cannot say humans cannot evolve to manage and handle it because humans are working on it regularly to make an A.I which can reduce their workload and time to end a task, which they go to adapt later.
Q:9. Overfitting
1.The model remembers a huge number of examples instead of learning to notice features and may fail to predict future observations reliably.
2.Occurs when a statistical model cannot adequately capture the underlying structure of the data.
3.Occurs if the model or algorithm shows low variance but high bias
4.None of the above
Solution- 1.The model remembers a huge number of examples instead of learning to notice features and may fail to predict future observations reliably.
Reason 1- Overfitting is “the production of an analysis that corresponds too closely or exactly to a particular set of data, and may therefore fail to fit additional data or predict future observations reliably”
Reason 2- Overfitting is “the production of an analysis that corresponds too closely or exactly to a specific set of knowledge , and should therefore fail to suit additional data or predict future observations reliably”
Q:10. AI in security will:
1.Not detect threats based on application behavior and a whole network’s activity.
2.Not be able to identify and stop cyber threats with less human intervention than is typically expected or needed with traditional security approaches.
3.Not detect when new threats are imminent
4.Not replace a security analyst’s insights or understanding of the field.
Solution- 4. Not replace a security analyst’s insights or understanding of the field.
Reason 1- This is because we do not have A.I’s that can understand and gathered field intelligence without human intervention.
Reason 2- This is because we don’t have A.I’s which will understand and gathered field intelligence without human intervention.
1.Potential for misuse
2.Highly dependent on machines
3.Requires Supervision
4.Rational Decision Maker
Solution- 4- Rational Decision Maker
Reason 1- This is because Rational choice theory in A.I. states that it rely on rational calculations to make rational choices that result in outcomes aligned with their own best interests.
Reason 2- This is because Rational choice theory during a .I. states that it believe rational calculations to form rational choices that end in outcomes aligned with their own best interests.
Reason 3- This is because Rational choice theory during artificial intelligence states that it believe rational calculations to make rational choices that end in outcomes aligned with their own best interests.
Q:2. Who is known as the “Father of AI”?
1.Fisher Ada
2.Alan Turing
3.John McCarthy
4.Allen Newell
Solution- 3.John McCarthy
Reason 1- John McCarthy, widely recognized as the father of Artificial Intelligence due to his astounding contribution in the field of Computer Science and AI.
Reason 2- John McCarthy, widely known because the father of AI thanks to his astounding contribution within the field of computing and AI.
Reason 3- John McCarthy, widely known because the father of Artificial intelligence because of his astounding contribution within the sector of computing and AI.
Q:3. Which of the following is not a branch of Artificial Intelligence?
1.Expert systems
2.Robotics
3.Natural language Processing
4.None of the above
Solution- 4.None of the above
Reason 1- This is because Expert System, Robotics and Natural Language processing all have their roles in Artificial Intelligence. There are 6 branches of A.I and these 3 above come under these branches.
Reason 2- This is because Expert System, Robotics and NLP all have their roles in AI . There are 6 branches of A.I and these 3 above come under these branches.
Reason 3- This is because Expert System, Robotics and NLP processing have their roles in AI . There are six branches of A.I and these three above come under these branches.
Q:4. Which of the following is not an application of Unsupervised Learning?
1.Document clustering
2.Speech recognition
3.Image compression
4.Association analysis
Solution- 4. Speech Recognition
Reason 1- This is the kind of application where you teach the algorithm about your voice and it will be able to recognize you. The most well-known real-world applications are virtual assistants such as Google Assistant and Siri, which will wake up to the keyword with your voice only. That is the reason it comes under supervised learning.
Reason 2-This is the type of application where you teach the algorithm about your voice and it’ll be ready to recognize you. the foremost well-known real-world applications are virtual assistants like Google Assistant and Siri, which can awaken to the keyword together with your voice only. that’s the rationale it comes under supervised learning.
Reason 3-This is the type of application where you teach the algorithm about your voice and it’ll be ready to recognize you. the foremost well-known real-world applications are virtual assistants like Google Assistant and Siri, which can awaken to the keyword in conjunction with your voice only. that’s the rationale it comes under supervised learning.
Q:5. The multi-armed bandit problem is a generalized use case for-
1.Reinforcement learning
2.Supervised learning
3.Unsupervised learning
4.All the above
Solution- 1.Reinforcement learning
Reason 1- Multi–Arm Bandit is a classic reinforcement learning problem, in which a player is facing with k slot machines or bandits, each with a different reward distribution, and the player is trying to maximise his cumulative reward based on trials.
Reason 2- Multi-Arm Bandit may be a classic reinforcement learning problem, during which a player is facing with k slot machines or bandits, each with a special reward distribution, and therefore the player is trying to maximise his cumulative reward supported trials.
Reason 3- Multi-Arm Bandit could also be a classic reinforcement learning problem, during which a player is facing with k slot machines or bandits, each with a special reward distribution, and thus the player is trying to maximise his cumulative reward supported trials.
Q:6. Why IOT now?
1.Electronic companies are building Wi-Fi and cellular wireless connectivity into a wide range of devices.
2.Mobile data coverage has improved significantly
3.The size and cost of wireless radios has dropped
4.All the above
Solution- 4.All the above
Reason 1- All of the above options that have provided in this question are correct and helping IOT to evolve in the future.
Reason 2- All of the above options that have provided during this question are correct and helping IOT to evolve within the future.
Q:7. Scalability of IoT means:
1.Expandable/reducible in terms of scale or size.
2.Measurable
3.Increasing/decreasing monetary costs.
4.All of these.
Solution- 4.All of these.
Reason 1- This is because the IOT is expandable/reducible in size or to scale. It is also measurable and its cost can be increased or decreased.
Reason 2- This is because the IOT is expandable/reducible in size or to scale. it’s also measurable and its cost are often increased or decreased.
Q:8. Which of the following statement is incorrect for AI?
1.Humans can not evolve as soon as AI evolves to control and handle it
2.The community working towards safe and beneficial superintelligence has grown worldwide.
3.It is typically managed by a peer-to-peer network working simultaneously together to solve complex mathematical problems in order to validate new blocks
4.AI is the new electricity
Solution- 1.Humans can not evolve as soon as AI evolves to control and handle it
Reason 1- We cannot say humans cannot evolve to control and handle it because humans are working on it regularly to make an A.I that will reduce their workload and time to complete a task, which they will adapt later.
Reason 2- We cannot say humans cannot evolve to regulate and handle it because humans are performing on it regularly to form an A.I which will reduce their workload and time to finish a task, which they’re going to adapt later.
Reason 3- We cannot say humans cannot evolve to manage and handle it because humans are working on it regularly to make an A.I which can reduce their workload and time to end a task, which they go to adapt later.
Q:9. Overfitting
1.The model remembers a huge number of examples instead of learning to notice features and may fail to predict future observations reliably.
2.Occurs when a statistical model cannot adequately capture the underlying structure of the data.
3.Occurs if the model or algorithm shows low variance but high bias
4.None of the above
Solution- 1.The model remembers a huge number of examples instead of learning to notice features and may fail to predict future observations reliably.
Reason 1- Overfitting is “the production of an analysis that corresponds too closely or exactly to a particular set of data, and may therefore fail to fit additional data or predict future observations reliably”
Reason 2- Overfitting is “the production of an analysis that corresponds too closely or exactly to a specific set of knowledge , and should therefore fail to suit additional data or predict future observations reliably”
Q:10. AI in security will:
1.Not detect threats based on application behavior and a whole network’s activity.
2.Not be able to identify and stop cyber threats with less human intervention than is typically expected or needed with traditional security approaches.
3.Not detect when new threats are imminent
4.Not replace a security analyst’s insights or understanding of the field.
Solution- 4. Not replace a security analyst’s insights or understanding of the field.
Reason 1- This is because we do not have A.I’s that can understand and gathered field intelligence without human intervention.
Reason 2- This is because we don’t have A.I’s which will understand and gathered field intelligence without human intervention.
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