Artificial-Intelligence-Foundation Practice APMG-International Verified Answers - Pass Your Exams For Sure! [2023]
Valid Way To Pass Artificial Intelligence's Artificial-Intelligence-Foundation Exam
NEW QUESTION # 12
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. Takes longer to deliver all functional requirements.
- C. Discourages revisiting and revising any prior phase once it is complete.
- D. Takes longer to complete the design phase of the project.
Answer: C
Explanation:
Explanation
The Waterfall approach is a sequential design process in which each phase of development must be completed before the next phase can begin. This means that once a phase is complete, it is difficult to go back and make changes, as any changes made to the project could potentially affect all the other phases. As a result, the Waterfall approach can make it difficult to adapt to changing customer requirements or adjust to new technology. This can ultimately lead to the failed delivery of an AI project.
References: [1] BCS Foundation Certificate In Artificial Intelligence Study Guide, Page number 19 [2] APMG International, "What is a Waterfall Model?", https://apmg-international.com/en/blog/what-is-a-waterfall-model/ [3] EXIN, "What is the Waterfall Model?", https://www.exin.com/blog/what-is-the-waterfall-model/
NEW QUESTION # 13
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 # 14
What is an intelligent robot?
- A. A robot that acts like a human.
- 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 # 15
Splitting data into Training and Test data sets is part of what?
- A. Machine learning post processing.
- B. Batch learning.
- C. High performance computing strategy.
- D. Machine learning data preparation.
Answer: D
Explanation:
Explanation
Splitting data into training and test data sets is an important step in the machine learning data preparation process. This process involves splitting the data into subsets, usually in a 70:30 ratio, to create a training set and a test set. The training set is used to train the machine learning model, while the test set is used to evaluate the model's performance. This process allows for the model to be tested and evaluated on data that it has not seen before, in order to ensure that it is accurate and able to generalize to new data. References: BCS Foundation Certificate In Artificial Intelligence Study Guide, https://bcs.org/certifications/foundation-certificates/artificial-intelligence/
NEW QUESTION # 16
Sustainability focuses on which three core areas?
- A. Social, Economic and Environmental.
- B. Scientific, Environmental and Economic.
- C. Social, Economic and Entrepreneurial.
- D. Social, Entrepreneurial and Environmental.
Answer: A
Explanation:
Explanation
The term sustainability is broadly used to indicate programs, initiatives and actions aimed at the preservation of a particular resource. However, it actually refers to four distinct areas: human, social, economic and environmental - known as the four pillars of sustainability.
https://www.futurelearn.com/info/courses/sustainable-business/0/steps/78337#:~:text=However%2C%20it%20ac Sustainability focuses on these three core areas because they all have an impact on the environment and society. Social sustainability is concerned with the relationships between people and how to create a society that is equitable and fair for all members. Economic sustainability focuses on the creation of a viable economic system that provides for the needs of the present without compromising the ability of future generations to meet their own needs. Environmental sustainability focuses on protecting natural resources, ecosystems and habitats, and minimizing the impact of human activities on the environment.
References: https://www.bcs.org/more/certifications/foundation-certificate-in-artificial-intelligence/ https://www
NEW QUESTION # 17
Professor David Chalmers described consciousness as having two questions. What were these?
- A. An easy one and a hard one.
- B. Are only humans conscious and are machines always unconscious?
- C. Can we integrate our knowledge to form consciousness and can we simulate consciousness?
- D. What is the sub conscious and what is the conscious?
Answer: D
Explanation:
Explanation
Professor David Chalmers described consciousness as having two questions: "What is it like to be conscious?" and "Can machines be conscious?". The first question, "What is it like to be conscious?", is an attempt to understand what it is like to experience the subjective aspects of consciousness, such as feeling, emotion, and perception. The second question, "Can machines be conscious?", is an attempt to understand whether or not machines can have the same kinds of subjective experiences as humans. For more information, please see the BCS Foundation Certificate In Artificial Intelligence Study Guide or the resources listed above.
NEW QUESTION # 18
An Al agent relies 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 An AI agent relies on its perceptual input, which is referred to as the agent's percept. This is the data that the agent collects through its sensors about its environment. The percept allows the agent to make decisions and take actions based on its environment. The agent's percept is important for Artificial Intelligence systems to be able to operate effectively. References:
[1] BCS Foundation Certificate In Artificial Intelligence Study Guide, "Reinforcement Learning", p.96-97. [2] APMG-International.com, "Foundations of Artificial Intelligence" [3] EXIN.com, "Foundations of Artificial Intelligence"
NEW QUESTION # 19
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/ The best technique to adopt when a weak learner's hypothesis accuracy is only slightly better than 50% is boosting. Boosting is an ensemble learning technique that combines multiple weak learners (i.e., models with a low accuracy) to create a more powerful model. Boosting works by iteratively learning a series of weak learners, each of which is slightly better than random guessing. The output of each weak learner is then combined to form a more accurate model. Boosting is a powerful technique that has been proven to improve the accuracy of a wide range of machine learning tasks. For more information, please see the BCS Foundation Certificate In Artificial Intelligence Study Guide or the resources listed above.
NEW QUESTION # 20
With a large dataset, limited computational resources or frequent new data to learn from, we can adopt what type of machine learning?
- A. Online learning.
- B. Patchwork learning.
- C. Batch learning.
- D. Big Data learning.
Answer: A
Explanation:
Explanation
Online learning is a type of machine learning that can be used when a large dataset is limited in computational resources or if the data is frequently changing. It allows the system to learn from new data as it is being presented, rather than having to re-train the entire dataset each time new data is added. This makes it more efficient and effective than batch learning, as it only needs to process the new data and not the entire dataset.
Online learning is often used in applications such as fraud detection, where new data is constantly being added and needs to be analyzed quickly.
For more information, please refer to the BCS Foundation Certificate In Artificial Intelligence Study Guide (https://www.bcs.org/upload/pdf/bcs-foundation-certificate-in-artificial-intelligence-study-guide.pdf) or the EXIN Artificial Intelligence Foundation Certification (https://www.exin.com/en/exams/artificial-intelligence-foundation).
NEW QUESTION # 21
In Machine learning what are a brain's axons called?
- A. Nodes
- B. Tetrahedra.
- C. Edges
- D. Dendrites
Answer: A
Explanation:
Explanation
In Machine Learning, the brain's axons are referred to as nodes. Nodes are the components of a neural network that are responsible for processing the input data and generating the output. A node is a mathematical function that takes input data, performs a computation on it, and produces an output. Each node is connected to other nodes in the network via edges, which represent the strength of the connection between the respective nodes. The strength of the connection between two nodes is determined by the weights assigned to each edge.
The weights are adjusted during the training process to generate the desired results.
For more information, please refer to the BCS Foundation Certificate In Artificial Intelligence Study Guide (https://www.bcs.org/upload/pdf/bcs-foundation-certificate-in-artificial-intelligence-study-guide.pdf) or the EXIN Artificial Intelligence Foundation Certification (https://www.exin.com/en/exams/artificial-intelligence-foundation).
NEW QUESTION # 22
Reflex and Model-based Reflex are two types of what?
- A. Robot
- B. Compilers.
- C. Algorithms.
- D. Artificial intelligent agents.
Answer: D
Explanation:
Explanation
Reflex and Model-based Reflex are two types of Artificial Intelligent Agents. Artificial Intelligent Agents are computer systems designed to act and think in a manner similar to humans,incorporating elements of problem solving, decision-making, communication, and learning. Reflex agents are reactive agents which act based on the current environment and conditions, while Model-based Reflex agents use a model of the environment to make decisions. References: BCS Foundation Certificate In Artificial Intelligence Study Guide, https://bcs.org/ai/certificate/ and APMG International, https://www.apmg-international.com/qualifications/artificial-intelligence-foundation-certificate.
NEW QUESTION # 23
What does TRL stand for?
- A. Transport Ready Level.
- B. Transform Reinforced Learning
- C. Technology Readiness Level.
- D. Technical Robotic Level.
Answer: C
Explanation:
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-,Technolog TRL stands for Technology Readiness Level and is a measure of how close a technology is to being ready for use in a real-world environment. TRL is used to assess the progress of research and development of a technology, ranging from basic research (TRL 1) to fully operational (TRL 9). TRL is used to help determine the level of completion of a technology and its potential success in a real-world environment.
References:
[1] https://www.bcs.org/upload/pdf/foundation-certificate-ai-syllabus-v1.pdf [2] https://www.apmg-international
NEW QUESTION # 24
Healthcare can benefit from Al, and in particular Machine Learning, an example of which is?
- A. Diagnostic image analysis
- B. Autonomous wheelchairs.
- C. Autonomous vehicles.
- D. Automated blood sampling.
Answer: A
Explanation:
Explanation
Healthcare can benefit from AI, and in particular Machine Learning, in a number of ways. One example is diagnostic image analysis, which can help to automatically identify and classify abnormalities in medical images such as X-rays, CT scans, and MRI scans. Machine Learning algorithms can be used to detect patterns in the data which can be used to accurately diagnose diseases and illnesses.
References:
[1] https://www.bcs.org/upload/pdf/foundation-certificate-ai-syllabus-v1.pdf [2] https://www.apmg-international
NEW QUESTION # 25
How could machine learning make a robot autonomous?
- A. Use OCR, optical character recognition, to read documents
- B. Use actuators to modify its environment
- C. Learn from sensor data and plan to carry out a task.
- D. Use NLP (Natural Language Processing) to listen
Answer: C
Explanation:
Explanation
Machine learning can be used to make robots autonomous by allowing them to learn from sensor data and plan how to carry out a task. This involves using algorithms to analyze data from sensors and use this data to make decisions and take actions. By using machine learning, robots can learn from their environment and become more autonomous. References:
[1] BCS Foundation Certificate In Artificial Intelligence Study Guide, "Robotics", p.98. [2] APMG-International.com, "Foundations of Artificial Intelligence" [3] EXIN.com, "Foundations of Artificial Intelligence"
NEW QUESTION # 26
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/
Universal design is a type of design that takes into account the needs of all individuals, regardless of age, ability, or physical condition. It is a principle that is embraced by the European Union and the United Nations, and it is based on the idea that products, services, and environments should be designed to be usable by the widest range of people possible. Universal design emphasizes accessibility, usability, and inclusivity, and it is often used to create products and services that are easy to use for people of all ages and abilities.
References: https://www.bcs.org/more/certifications/foundation-certificate-in-artificial-intelligence/ https://www
NEW QUESTION # 27
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 TensorFlow is an open source machine learning library created by Google. It is used for dataflow programming and is widely used for a variety of applications, including machine learning and deep learning.
TensorFlow enables developers to build, train and deploy machine learning models easily and quickly. It has built-in support for a variety of deep learning frameworks, such as convolutional neural networks, recurrent neural networks, and autoencoders.
For more information, please refer to the BCS Foundation Certificate In Artificial Intelligence Study Guide (https://www.bcs.org/upload/pdf/bcs-foundation-certificate-in-artificial-intelligence-study-guide.pdf) or the EXIN Artificial Intelligence Foundation Certification (https://www.exin.com/en/exams/artificial-intelligence-foundation).
NEW QUESTION # 28
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