Ace Artificial-Intelligence-Foundation Certification with 40 Actual Questions
PASS APMG-International Artificial-Intelligence-Foundation EXAM WITH UPDATED DUMPS
APMG-International Artificial-Intelligence-Foundation Certification Exam is a computer-based exam that consists of 40 multiple-choice questions. Artificial-Intelligence-Foundation exam is 60 minutes long, and candidates must score at least 65% to pass. Artificial-Intelligence-Foundation exam is available in multiple languages, including English, Spanish, French, German, and Chinese.
NEW QUESTION # 17
If Al undertakes routine and monotonous tasks and takes these away from humans, what will humans do?
- A. Change jobs.
- B. Sabotage the Al.
- C. Leisure activities
- D. Higher value work.
Answer: D
Explanation:
Explanation
Al is designed to take on routine and monotonous tasks, freeing up humans to take on more complex, higher value work. This can include tasks such as research, problem-solving, and decision-making. This shift in work roles is expected to increase productivity and efficiency, allowing humans to focus on more creative and innovative tasks. For example, robots can be used to automate mundane manufacturing processes, freeing up human workers to take on jobs that require more creative thinking and problem-solving.
References:
[1] https://www.bcs.org/upload/pdf/foundation-certificate-ai-syllabus-v1.pdf [2] https://www.apmg-international
NEW QUESTION # 18
Sustainability focuses on which three core areas?
- A. Scientific, Environmental and Economic.
- B. Social, Economic and Environmental.
- C. Social, Economic and Entrepreneurial.
- D. Social, Entrepreneurial and Environmental.
Answer: B
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 # 19
Collaboration, learning and iterative are terms used to describe what?
- A. Rapid software development.
- B. Waterfall projects.
- C. Agile projects
- D. Trustworthy Al.
Answer: C
Explanation:
Explanation
Collaboration, learning, and iterative are terms used to describe agile projects. Agile projects are designed to be adaptive and flexible, allowing teams to incorporate feedback and learn from their mistakes. This process encourages collaboration between team members, and emphasizes the importance of iterative development and continual improvement. Agile projects focus on delivering value quickly and efficiently, allowing teams to make changes and adapt to changing customer needs.
References:
[1] https://www.bcs.org/upload/pdf/foundation-certificate-ai-syllabus-v1.pdf [2] https://www.apmg-international
NEW QUESTION # 20
In Machine learning what are a brain's axons called?
- A. Dendrites
- B. Nodes
- C. Edges
- D. Tetrahedra.
Answer: B
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 # 21
Narrow or weak Al can be useful to robots.
Which of the following is an example of narrow Al?
- A. NLP - Natural Language Processing.
- B. Artificial General Al.
- C. Conscious simul-ation.
- D. Conscious integration.
Answer: A
Explanation:
Explanation
NLP - Natural Language Processing is an example of narrow AI. It is a type of AI system that is able to understand, interpret, and generate natural language. NLP has become increasingly popular over the past few years, as it has been used to create applications such as chatbots, virtual assistants, and search engines. NLP systems are able to learn language and the context in which it is used, and they are able to understand the nuances of language and its different meanings. References: BCS Foundation Certificate In Artificial Intelligence Study Guide, https://bcs.org/certifications/foundation-certificates/artificial-intelligence/
NEW QUESTION # 22
How could machine learning make a robot autonomous?
- A. Use actuators to modify its environment
- B. Learn from sensor data and plan to carry out a task.
- C. Use OCR, optical character recognition, to read documents
- D. Use NLP (Natural Language Processing) to listen
Answer: B
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 # 23
Reflex and Model-based Reflex are two types of what?
- A. Robot
- B. Compilers.
- C. Artificial intelligent agents.
- D. Algorithms.
Answer: C
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 # 24
Who was the pioneer of computer programming?
- A. Sophie Wilson
- B. Ada Lovelace.
- C. Karen Spark Jones.
- D. Dame Wendy Hall.
Answer: B
Explanation:
Explanation
https://www.techopedia.com/2/31564/watercooler/ada-lovelace-enchantress-of-numbers Ada Lovelace was an English mathematician and writer who is widely credited as the pioneer of computer programming. In 1842, she wrote an article in which she outlined the fundamental principles of computing, making her the first person to recognize the potential of computers and to describe algorithms that could be used to program them. Her work laid the basis for modern computing and is recognized as one of the most significant contributions to the field of computing.
References: https://www.bcs.org/more/certifications/foundation-certificate-in-artificial-intelligence/ https://www
NEW QUESTION # 25
Splitting data into Training and Test data sets is part of what?
- A. Batch learning.
- B. Machine learning data preparation.
- C. Machine learning post processing.
- D. High performance computing strategy.
Answer: B
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 # 26
From the Ell's ethics guidelines for Al, what does 'The Principle of Autonomy,' mean?
- A. Al systems will be human-centric
- B. Al systems will preserve human agency.
- C. Al agents will behave as humans.
- D. Robots will have freewill.
Answer: B
Explanation:
Explanation
The Principle of Autonomy from the ELL's ethics guidelines for Al states that Al systems should be designed in a way that preserves human agency and responsibility. This means that Al systems should be designed in a way that allows humans to remain in control of their decisions, and that the Al system should not be able to act without human input or permission. 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 # 27
Which of the following is an advantage of a machine based system?
- A. Capable of sympathising with humans.
- B. Able to judge ambiguous and unknown situations.
- C. Can explain the output of an Al system
- D. Undertakes monotonous tasks reliably and accurately.
Answer: D
Explanation:
Explanation
One of the main advantages of a machine-based system is its ability to reliably and accurately undertake monotonous and repetitive tasks. This is especially useful for tasks that require a high level of accuracy and precision, such as data entry or analysis. Machine-based systems are also able to process large amounts of data quickly, meaning that they are able to complete tasks more quickly and efficiently than humans. Additionally, machine-based systems can be programmed to take certain decisions and actions based on the input data, allowing them to automate certain processes without the need for human intervention. References:
* BCS Foundation Certificate In Artificial Intelligence Study Guide (2019), AI Systems, Chapter 8.
* https://www.apmg-international.com/en/al-adoption/advantages-of-al/
NEW QUESTION # 28
An Al agent relies on its perceptual input. This is called the agent's what?
- A. Position
- B. Environment
- C. Percept
- D. World
Answer: C
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 # 29
What are monotonous and repetitive tasks, that require accuracy BEST suited to?
- A. Human plus machine.
- B. Machine.
- C. Human.
- D. Artificial General Intelligence.
Answer: B
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 # 30
Human-centric trustworthy Al must be...
- A. quality assurance certified.
- B. financially sustainable.
- C. tested by humans.
- D. continually assessed and monitored.
Answer: D
Explanation:
Explanation
Human-centric trustworthy Al must be continually assessed and monitored in order to ensure that it is behaving in a safe and ethical manner. This includes conducting regular tests and audits to ensure that the Al is functioning as intended, and is not taking any actions or decisions that could potentially harm humans or their environment. 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 # 31
What does TRL stand for?
- A. Technical Robotic Level.
- B. Transform Reinforced Learning
- C. Technology Readiness Level.
- D. Transport Ready 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 # 32
What does Prof David Chalmers describe the hard consciousness problem to be as comples as?
- A. Quantum mechanics.
- B. The universe.
- C. Turbulence.
- D. Psychology.
Answer: B
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 # 33
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APMG-International Artificial-Intelligence-Foundation Certification Exam is suitable for professionals from various backgrounds, including IT, business, and management. It is especially relevant for those who work in industries that are likely to be impacted by AI, such as healthcare, finance, and retail. Foundation Certification Artificial Intelligence certification is also useful for individuals who wish to stay up-to-date with the latest developments in AI and their potential impact on society.
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