Latest Nov 01, 2022 Real AIF Exam Dumps Questions Valid AIF Dumps PDF
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NEW QUESTION 14
What is one of the MAIN contributions of Al to the rapid development of The Fourth Industrial Revolution?
- A. Enhanced design.
- B. Automation
- C. Big Data
- D. Al personal assistants.
Answer: C
Explanation:
Explanation
https://research.com/careers/what-is-the-fourth-industrial-revolution
NEW QUESTION 15
What is defined as a machine that can carry out a complex series of tasks automatically?
- A. A production line.
- B. A computer.
- C. A robot
- D. An autonomous vehicle.
Answer: C
Explanation:
https://en.wikipedia.org/wiki/Robot#:~:text=A%20robot%20is%20a%20machine,control%20may%20be%20embedded%20within.
NEW QUESTION 16
What does TRL stand for?
- A. Technical Robotic Level.
- B. Transport Ready Level.
- C. Transform Reinforced Learning
- D. Technology Readiness Level.
Answer: D
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 17
Who was the pioneer of computer programming?
- A. Dame Wendy Hall.
- B. Karen Spark Jones.
- C. Sophie Wilson
- D. Ada Lovelace.
Answer: D
Explanation:
Explanation
https://www.techopedia.com/2/31564/watercooler/ada-lovelace-enchantress-of-numbers
NEW QUESTION 18
If Al undertakes routine and monotonous tasks and takes these away from humans, what will humans do?
- A. Higher value work.
- B. Leisure activities
- C. Sabotage the Al.
- D. Change jobs.
Answer: D
NEW QUESTION 19
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 20
Para View allows large data sets to be visualised on a parallel computer.
Which of the following is one of the techniques used?
- A. Norm calculation.
- B. Eigen function analysis.
- C. Contour plot
- D. Dashboard.
Answer: C
NEW QUESTION 21
An intelligent robot uses Al to do what?
- A. Plan, act and speak.
- B. Perceive, plan and act.
- C. Sense, plan and move.
- D. Sense, plan and act
Answer: D
NEW QUESTION 22
Healthcare can benefit from Al, and in particular Machine Learning, an example of which is?
- A. Diagnostic image analysis
- B. Autonomous vehicles.
- C. Autonomous wheelchairs.
- D. Automated blood sampling.
Answer: A
NEW QUESTION 23
How could machine learning make a robot autonomous?
- A. Learn from sensor data and plan to carry out a task.
- B. Use OCR, optical character recognition, to read documents
- C. Use NLP (Natural Language Processing) to listen
- D. Use actuators to modify its environment
Answer: C
Explanation:
https://arxiv.org/pdf/1803.10813
NEW QUESTION 24
An agent based model is asimul-ationof autonomous agents (individual and collective). What can be used to
learn from the data generated by thesimul-ations?
- A. Machine Learning.
- B. Python.
- C. A spreadsheet
- D. Paraview.
Answer: C
Explanation:
Explanation
https://www.pnas.org/doi/10.1073/pnas.082080899
NEW QUESTION 25
What are monotonous and repetitive tasks, that require accuracy BEST suited to?
- A. Machine.
- B. Artificial General Intelligence.
- C. Human.
- D. Human plus machine.
Answer: B
NEW QUESTION 26
Which of the following is an advantage of a machine based system?
- A. Undertakes monotonous tasks reliably and accurately.
- B. Capable of sympathising with humans.
- C. Can explain the output of an Al system
- D. Able to judge ambiguous and unknown situations.
Answer: A
NEW QUESTION 27
In the 1800's the development of statistics led to___________theorem and is used in probabilistic inference.
(Select the missing word.)
- A. Kolmogorov's
- B. The central limit
- C. Bayes'
- D. Boltzmann's
Answer: A
NEW QUESTION 28
Human-centric trustworthy Al must be...
- A. continually assessed and monitored.
- B. financially sustainable.
- C. quality assurance certified.
- D. tested by humans.
Answer: C
NEW QUESTION 29
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: C
Explanation:
NEW QUESTION 30
What is defined as a machine that can carry out a complex series of tasks automatically?
- A. A production line.
- B. A computer.
- C. A robot
- D. An autonomous vehicle.
Answer: C
Explanation:
Explanation
https://en.wikipedia.org/wiki/Robot#:~:text=A%20robot%20is%20a%20machine,control%20may%20be%20em
NEW QUESTION 31
What technique can be adopted when a weak learners hypothesis accuracy is only slightly better than 50%?
- A. Over-fitting
- B. Activation.
- C. Boosting.
- D. Iteration.
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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