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NEW QUESTION # 12
The EU and United Nations have made designing for all individuals a core principle. What is this type of design called?
- A. Biophilic design.
- B. Universal design.
- C. Utopic design.
- D. Core design
Answer: B
Explanation:
https://universaldesign.ie/What-is-Universal-Design/
NEW QUESTION # 13
The Scrum Master is part of which team?
- A. Software development team.
- B. Agile project team.
- C. Data preparation team
- D. Management team
Answer: B
Explanation:
Explanation
https://www.techtarget.com/whatis/definition/scrum-master#:~:text=A%20Scrum%20Master%20is%20a,in%20a
NEW QUESTION # 14
What are monotonous and repetitive tasks, that require accuracy BEST suited to?
- A. Machine.
- B. Human.
- C. Artificial General Intelligence.
- D. Human plus machine.
Answer: A
Explanation:
Explanation
Monotonous and repetitive tasks that require accuracy are best suited to machines. Machines are able to accurately and quickly perform tasks that require little to no creativity, such as data entry or image recognition.
This is because machines are able to process large amounts of data quickly and accurately, and are less likely to make mistakes than humans. Additionally, machines are able to process large amounts of data without becoming bored or distracted, making them ideal for tasks that require consistent accuracy. For more information, please see the BCS Foundation Certificate In Artificial Intelligence Study Guide or the resources listed above.
Search results: BCS Foundation Certificate in Artificial Intelligence Study Guide, Chapter 4: Machine Learning: https://www.bcs.org/category/19669
NEW QUESTION # 15
What does Prof David Chalmers describe the hard consciousness problem to be as comples as?
- A. Turbulence.
- B. Psychology.
- C. The universe.
- D. Quantum mechanics.
Answer: C
Explanation:
Explanation
Prof David Chalmers describes the hard consciousness problem to be as complex as the universe. He argues that understanding consciousness is as hard as understanding the universe itself, due to the number of variables and dimensions involved. He has compared the complexity of the problem to that of turbulence, quantum mechanics, and psychology, but believes that the problem of consciousness is even more complex than all of these.
References:
[1] https://www.bcs.org/upload/pdf/foundation-certificate-ai-syllabus-v1.pdf
[2] https://www.apmg-international
David J. Chalmers, "The Hard Problem of Consciousness", in J. Shear (ed.), Explaining Consciousness:
The "Hard Problem", MIT Press, 1997.
NEW QUESTION # 16
With a large dataset, limited computational resources or frequent new data to learn from, we can adopt what type of machine learning?
- A. Patchwork learning.
- B. Big Data learning.
- C. Online learning.
- D. Batch learning.
Answer: D
Explanation:
NEW QUESTION # 17
With a large dataset, limited computational resources or frequent new data to learn from, we can adopt what
type of machine learning?
- A. Big Data learning.
- B. Patchwork learning.
- C. Batch learning.
- D. Online learning.
Answer: A
NEW QUESTION # 18
In an Al project the domain expert is the person...
- A. with technical and managerial oversight of the business plan
- B. who measures the trustworthiness of the Al system
- C. with special knowledge or skills in the area of endeavour and defines what is fit for purpose'
- D. who manages the agile project and writes the technical terms of reference
Answer: B
NEW QUESTION # 19
What is an intelligent robot?
- A. A robot that acts like ahuman.
- B. A robot that has consciousness
- C. A robot that uses Al techniques.
- D. A robot that takes the place of a human.
Answer: C
Explanation:
Explanation
An intelligent robot is one that uses AI techniques, such as machine learning and natural language processing, to perceive, plan and act on its environment. Intelligent robots are able to process large amounts of data quickly and accurately, allowing them to make decisions and carry out tasks autonomously. Intelligent robots can be used in a variety of applications, from industrial automation to healthcare.
NEW QUESTION # 20
A human manipulates what using their intelligence?
- A. Objective
- B. Environment
- C. Space
- D. Mission
Answer: C
NEW QUESTION # 21
The EU and United Nations have made designing for all individuals a core principle. What is this type of
design called?
- A. Biophilic design.
- B. Universal design.
- C. Utopic design.
- D. Core design
Answer: B
Explanation:
Explanation
https://universaldesign.ie/What-is-Universal-Design/
NEW QUESTION # 22
What is one of the MAIN contributions of Al to the rapid development of The Fourth Industrial Revolution?
- A. Big Data
- B. Al personal assistants.
- C. Enhanced design.
- D. Automation
Answer: D
Explanation:
Explanation
https://research.com/careers/what-is-the-fourth-industrial-revolution
Artificial Intelligence (AI) is playing a major role in the rapid development of the Fourth Industrial Revolution. AI technologies are enabling the automation of many processes that were previously carried out by humans or machines, which has greatly increased the speed, efficiency, and accuracy of these processes.
Automation is one of the main contributions of AI to the Fourth Industrial Revolution, as it has greatly increased the productivity of businesses and industries, while reducing the cost of production and improving the quality of products.
References: https://www.bcs.org/more/certifications/foundation-certificate-in-artificial-intelligence/ https://www
NEW QUESTION # 23
Tensor flow is a typical open source what?
- A. Cloud based AI application.
- B. Machine learning library.
- C. Intelligent robot paradigm.
- D. Agent based modelling application
Answer: B
Explanation:
Explanation
TensorFlow is an end-to-end open source platform for machine learning. It has a comprehensive, flexible
ecosystem of tools, libraries and community resources that lets researchers push the state-of-the-art in ML and
developers easily build and deploy ML powered applications.
https://www.tensorflow.org/#:~:text=TensorFlow%20is%20an%20end%2Dto,and%20deploy%20ML%20power
NEW QUESTION # 24
A vector in vector calculus is a quantity that has magnitude and direction.
What is a vector in computer programming?
- A. A two-dimensional array of scalars.
- B. An array of complex numbers
- C. An array with one dimension.
- D. A constant
Answer: A
NEW QUESTION # 25
An Al agentrelies on its perceptual input.This is called the agent's what?
- A. Position
- B. World
- C. Environment
- D. Percept
Answer: D
Explanation:
Explanation
* Performance Measure of Agent It is the criteria, which determines how successful an agent is.
* Behavior of Agent It is the action that agent performs after any given sequence of percepts.
* Percept It is agent's perceptual inputs at a given instance.
* Percept Sequence It is the history of all that an agent has perceived till date.
* Agent Function It is a map from the precept sequence to an action.
Agent Terminology
https://www.tutorialspoint.com/artificial_intelligence/artificial_intelligence_agents_and_environments.htm
NEW QUESTION # 26
Which factor of a Waterfall' approach is most likely to result in the failed delivery of an Al project?
- A. Discourages collaboration and cross boundary communication.
- B. Discourages revisiting and revising any prior phase once it is complete.
- C. Takes longer to complete the design phase of the project.
- D. Takes longer to deliver all functional requirements.
Answer: C
NEW QUESTION # 27
Which of the following is an example of fitting a curve to a set of data?
- A. Backwardpropagation.
- B. Least squares regression.
- C. Bayesian network.
- D. Python.
Answer: B
Explanation:
Explanation
Least Squares Regression is a statistical technique used for fitting a curve to a set of data. It involves minimizing the sum of the squares of the differences between the observed data and the fitted curve. This is done by finding the line of best fit, which is the line that minimizes the sum of the squared residuals. The line of best fit is determined by finding the parameters that give the minimum sum of the squared residuals. This technique is often used in data science and machine learning to create models that can be used to make predictions. References: BCS Foundation Certificate In Artificial Intelligence Study Guide, https://bcs.org/certifications/foundation-certificates/artificial-intelligence/
NEW QUESTION # 28
What term do computer scientists and economists use to describe how happy an agent is?
- A. Warm.
- B. Index.
- C. Return
- D. Utility.
Answer: D
Explanation:
https://griffinshare.fontbonne.edu/cgi/viewcontent.cgi?article=1008&context=ijds
NEW QUESTION # 29
Reflex and Model-based Reflex are two types of what?
- A. Robot
- B. Compilers.
- C. Algorithms.
- D. Artificial intelligent agents.
Answer: D
NEW QUESTION # 30
What does TRL stand for?
- A. Transport Ready Level.
- B. Transform Reinforced Learning
- C. Technology Readiness Level.
- D. Technical Robotic Level.
Answer: C
Explanation:
Technology Readiness Level (TRL) Technology Readiness Levels (TRL) are a method of estimating the technology maturity of Critical Technology Elements (CTE) of a program during the acquisition process.
https://acqnotes.com/acqnote/tasks/technology-readiness-level#:~:text=Technology%20Development-,Technology%20Readiness%20Level%20(TRL),program%20during%20the%20acquisition%20process.
NEW QUESTION # 31
What technique can be adopted when a weak learners hypothesis accuracy is only slightly better than 50%?
- A. Activation.
- B. Iteration.
- C. Boosting.
- D. Over-fitting
Answer: C
Explanation:
Explanation
* Weak Learner: Colloquially, a model that performs slightly better than a naive model.
More formally, the notion has been generalized to multi-class classification and has a different meaning
beyond better than 50 percent accuracy.
For binary classification, it is well known that the exact requirement for weak learners is to be better than
random guess. [...] Notice that requiring base learners to be better than random guess is too weak for
multi-class problems, yet requiring better than 50% accuracy is too stringent.
- Page 46, Ensemble Methods, 2012.
It is based on formal computational learning theory that proposes a class of learning methods that possess
weakly learnability, meaning that they perform better than random guessing. Weak learnability is proposed as
a simplification of the more desirable strong learnability, where a learnable achieved arbitrary good
classification accuracy.
A weaker model of learnability, called weak learnability, drops the requirement that the learner be able to
achieve arbitrarily high accuracy; a weak learning algorithm needs only output an hypothesis that performs
slightly better (by an inverse polynomial) than random guessing.
- The Strength of Weak Learnability, 1990.
It is a useful concept as it is often used to describe the capabilities of contributing members of ensemble
learning algorithms. For example, sometimes members of a bootstrap aggregation are referred to as weak
learners as opposed to strong, at least in the colloquial meaning of the term.
More specifically, weak learners are the basis for the boosting class of ensemble learning algorithms.
The term boosting refers to a family of algorithms that are able to convert weak learners to strong learners.
https://machinelearningmastery.com/strong-learners-vs-weak-learners-for-ensemble-learning/
NEW QUESTION # 32
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