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AIF Exam Brain Dumps - Study Notes and Theory
NEW QUESTION 13
Sustainability focuses on which three core areas?
- A. Social, Entrepreneurial and Environmental.
- B. Scientific, Environmental and Economic.
- C. Social, Economic and Environmental.
- D. Social, Economic and Entrepreneurial.
Answer: C
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%20actually%20refers%20to,the%20four%20pillars%20of%20sustainability.&text=Human%20sustainability%20aims%20to%20maintain%20and%20improve%20the%20human%20capital%20in%20society.
NEW QUESTION 14
From the Ell's ethics guidelines for Al, what does 'The Principle of Autonomy,' mean?
- A. Robots will have freewill.
- B. Al systems will be human-centric
- C. Al systems will preserve human agency.
- D. Al agents will behave as humans.
Answer: B
NEW QUESTION 15
What does TRL stand for?
- A. Technology Readiness Level.
- B. Transform Reinforced Learning
- C. Transport Ready Level.
- D. Technical Robotic Level.
Answer: A
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
NEW QUESTION 16
How could machine learning make a robot autonomous?
- A. Use NLP (Natural Language Processing) to listen
- B. Use actuators to modify its environment
- C. Use OCR, optical character recognition, to read documents
- D. Learn from sensor data and plan to carry out a task.
Answer: A
Explanation:
https://arxiv.org/pdf/1803.10813
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. Batch learning.
- B. Patchwork learning.
- C. Big Data learning.
- D. Online learning.
Answer: A
Explanation:
NEW QUESTION 18
What technique can be adopted when a weak learners hypothesis accuracy is only slightly better than 50%?
- A. Boosting.
- B. Over-fitting
- C. Iteration.
- D. Activation.
Answer: A
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 19
Professor David Chalmers described consciousness as having two questions. What were these?
- A. An easy one and a hard one.
- B. What is the sub conscious and what is the conscious?
- C. Are only humans conscious and are machines always unconscious?
- D. Can we integrate our knowledge to form consciousness and can we simulate consciousness?
Answer: C
NEW QUESTION 20
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
NEW QUESTION 21
What does TRL stand for?
- A. Technology Readiness Level.
- B. Transform Reinforced Learning
- C. Transport Ready Level.
- D. Technical Robotic Level.
Answer: A
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 22
How could machine learning make a robot autonomous?
- A. Use NLP (Natural Language Processing) to listen
- B. Use actuators to modify its environment
- C. Use OCR, optical character recognition, to read documents
- D. Learn from sensor data and plan to carry out a task.
Answer: A
Explanation:
Explanation
https://arxiv.org/pdf/1803.10813
NEW QUESTION 23
Ensemble learning methods do what with the hypothesis space?
- A. Extract ergodic solutions.
- B. Use stochastic gradient descent to optimise a network.
- C. Test multiple hypotheses simultaneously.
- D. Select a combination of hypothesis to combine their predictions
Answer: D
Explanation:
Explanation
https://link.springer.com/referenceworkentry/10.1007/978-0-387-73003-5_293#:~:text=Definition,and%20comb
NEW QUESTION 24
What is defined as a philosophy, or set of assumptions and/or techniques, which characterise an approach to a
class of problems?
- A. An algorithm.
- B. An approach.
- C. A set
- D. A paradigm.
Answer: D
NEW QUESTION 25
Narrow or weak Al can be useful to robots.
Which of the following is an example of narrow Al?
- A. Conscioussimul-ation.
- B. Conscious integration.
- C. Artificial General Al.
- D. NLP - Natural Language Processing.
Answer: D
NEW QUESTION 26
Which factor of a Waterfall' approach is most likely to result in the failed delivery of an Al project?
- A. Takes longer to deliver all functional requirements.
- B. Discourages revisiting and revising any prior phase once it is complete.
- C. Takes longer to complete the design phase of the project.
- D. Discourages collaboration and cross boundary communication.
Answer: C
NEW QUESTION 27
What is defined as a machine that can carry out a complex series of tasks automatically?
- A. A robot
- B. A computer.
- C. An autonomous vehicle.
- D. A production line.
Answer: A
Explanation:
Explanation
https://en.wikipedia.org/wiki/Robot#:~:text=A%20robot%20is%20a%20machine,control%20may%20be%20em
NEW QUESTION 28
Splitting data into Training and Test data sets is part of what?
- A. Machine learning post processing.
- B. Machine learning data preparation.
- C. Batch learning.
- D. High performance computing strategy.
Answer: B
NEW QUESTION 29
What are monotonous and repetitive tasks, that require accuracy BEST suited to?
- A. Human plus machine.
- B. Human.
- C. Machine.
- D. Artificial General Intelligence.
Answer: D
NEW QUESTION 30
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