Anyone can sharpen their knowledge of AI with Artificial Intelligence Multiple Choice Questions And Answers.
Multiple Choice Questions and Answers:
Question 1:
What do you call he commonly used ai technology for learning input(A) to output(B) mapping? A. Artificial Intelligence B. Supervised learning C. Unsupervised learning D. Reinforcement learning
Answer: B
Question 2:
Which ai is being used in email spam filters, speech recognition and other specific applications? A. Artificial General Intelligence (AGI) B. Artificial Narrow Intelligence (ANI) C. Supervised machine learning D. Unsupervised machine learning
Answer: B
Question 3:
The only way to acquire data for a supervised learning algorithms is to manually label it i.e. given the input A to ask a human to provide output B A. False B. True
Answer: A
Question 4:
The best performance could be achieved to use supervised
learning to build a speech recognition system. What
would ideally you use?
A. A large dataset of audio files and the corresponding
text transcript
B. A large dataset of audio files and the corresponding
text transcript
C. A large neural network
D. A small neural network
E. Options B & D
F. Options A & C
Answer: F
Question 5:
Which of these statements regarding data acquisition do
you agree with?
A. It doesn't matter how data is acquired, the more
data is better choice
B. It doesn't help to give data to an AI team, because
they can produce data by themselves
C. Only structured data is valuable, AI cannot process
unstructured data
D. Some types of data are more valuable than others;
working with an AI team can help you figure out what
data to acquire.
Answer: D
Question 6:
You run a company that manufactures scooters. Which of
following are examples of unstructured data?
A. Picture of scooters
B. Audio files of the engines sound of your scooters
C. The maximum speed of each of your scooters
D. The number of scooters sold per week over the past
year
E. Options A & B
F. Options C & D
Answer: E
Question 7:
What of these do ai companies do well? A. Strategic data acquisition B. Invest in unified data warehouse C. Spot automation opportunities D. All of the above
Answer: D
Question 8:
Let us assume you want to input a picture of a person's face(A) and output whether or not they are smiling(B). Because this is a task that most human can do in less than 1 second, supervised learning can probably learn this A to B mapping. A. True B. False C. None of above
Answer: A
Question 9:
Biased data produces biased ai A. True B. False
Answer: A
Question 10:
The more data, the more better ai training A. True B. False
Answer: A
Question 11:
Which of the following statements are true depending upon the definition of terminologies A. AI is a type of deep learning i.e. ai algorithms are deep learning algorithms B. The terms "Machine learning" and "data science" are used almost interchangeably C. The terms "Deep learning" and "neural network" are used almost interchangeably D. Deep learning is a type of machine learning i.e. all deep learning algorithms are machine learning algorithms E. Both A & B are true F. Both C & D are true
Answer: F
Question 12:
Suppose a website sells dog food. Which of these might be a good result from a Data Science Project? A. A neural network that closely mimics how cat's brain work B. A large data set of images labelled as "Cat" and "Not Cat" C. Insights into how to market cat food more effectively, depending on the breed of cat D. A slide deck presenting a plan on how to modify pricing in order to improve sales E. Both C & D F. Both A & B G. None of the above
Answer: E
Question 13:
Machine learning is an "iterative process", meaning that an AI team often has to try many ideas before coming up with something that's good enough, rather than have the first thing they try to work on. A. True B. False
Answer: A
Question 14:
Let us assume we want to build an ai system to help recruiters with automated resume screening. Which of these steps could be possibly involved in "technical diligence" for the? A. Making sure we can get enough data for this project B. Defining an engineering timeline C. Making sure that an AI system can meet the desired performance D. ensuring that this is a valuable for our business E. Options A, B & C are true F. Options B, C & D are true G. All of the above
Answer: E
Question 15:
Let us assume we want to build an AI system to help sales team with automated lead sorting i.e. input A(a sales prospect) and output B(whether our sales team should prioritize them). The 3 steps of the workflow, in scrambled order, are: 1. Deploy a trained model and get data back from users 2. Collect data with both A and B 3. Train a machine learning system to input A and output B Which one could be the possible correct answer? A. 1, 2, 3 B. 1, 3, 2 C. 2, 3, 1 D. 2, 1, 3
Answer: C
Question 16:
Which statement best describes the "business diligence" do you agree with? A. Business diligence is the process of ensuring that AI technology, if it is built, is valuable for your business B. Business diligence is the process of ensuring that the envisioned AI technology is feasible C. Business diligence applies only if you are launching new product lines or businesses D. Business diligence can typically be completed in less than a day E. Options A, B & C are true F. Options B, C & D are true G. All of the above
Answer: A
Question 17:
What are the key steps of a Data Science Project? A. Collect data B. Analyze the data C. Suggest hypothesis or actions D. All of the above E. None of the above
Answer: D
Question 18:
You want to use supervised learning AI for automated resume screening, which statements are true regarding Training Set? as 1. The training set and Test set can be the same data set 2. Both the input A(resume) and the desired output B(whether to move forward s candidate) 3. Both the input A(resume) but not necessarily the desired output B(whether to move forward a candidate) 4. AI team has to train the supervised learning algorithm A. options 1 & 3 are true B. options 2 & 4 are true C. options 1, 2 and 4 are true D. All above options are true E. None of the options are true
Answer: B
Question 19:
Machine learning programs can help to: 1. Automate lead sorting in sales 2. Customize product recommendations 3. Automate resume screening 4. Automate visual inspection in a manufacturing line Which one could be the best option? A. Options 1, 2, 3 B. Options 1, 2, 3, 4 C. Only option 3 D. Only option 4
Answer: B
Question 20:
What are the reasons behind machine learning system that we could not achieve 100% accuracy? A. Not enough data B. Mislabeled data C. Ambiguous data D. All of the above E. None of the above
Answer: D
Question 21:
"Big Data" is worthless in machine learning projects on solving our problems: A. True B. False
Answer: B
Question 22:
Smart speakers have multiple functions. It can tell a joke, play music etc, is an example of Artificial General Intelligence(AGI): A. True B. False
Answer: B
Question 23:
Smart speaker containing the functions? A. Trigger word detection->speech recognition->intent recognition->command execution B. Trigger word detection->intent recognition->speech recognition->command execution C. Speech recognition->trigger word detection->intent recognition->command execution D. None of the above
Answer: A
Question 24:
One of the most important factor of your first pilot project? A. Be executed by an in house team B. Drive extremely high value for business C. Succeed and show traction within 6-10 months D. All of the above
Answer: C
Question 25:
For smart speaker, which is the best statement represents to accumulate data for your product through having many users? A. better smart speaker->more user of speaker->more user data B. better smart speaker->more user data->more users of speaker C. better smart speaker->more commands supported->more users of speaker D. better smart speaker->more users of speaker->more commands supported
Answer: A
Question 26:
Why is deploying an AI strategy not the first step in the AI Transformation Playbook? A. Without having some practical AI experience and knowing what it feels like to build an AI project, a company usually does not know enough to formulate a sound strategy B. There is no reason. Developing an AI strategy is the the first step in AI Transformation Playbook C. When transforming a company to an AI company, one does not need a strategy, therefore it can't be the first step D. The strategy must be to use the virtuous circle of AI, which comes after building a product
Answer: A
Question 27:
The component for pedestrian detection is usually built on? A. GANs B. A motion planning algorithm C. Supervised learning D. Reinforcement learning
Answer: C
Question 28:
Who will be the best suitable person to hire for writing a software like trigger word detection system to map from inputs A(audio clip) to output B? A. Data engineer B. Machine learning engineer C. AI Product Manager D. Machine learning researcher
Answer: B
Question 29:
What could be the very first step in the AI Transformation Playbook for helping your company become good at AI? A. Execute pilot projects to gain momentum B. Build an in-house AI team C. Develop an AI strategy D. Provide broad range AI training
Answer: A
Question 30:
According to AI Transformation Playbook, broad AI training needs to be provided not only to engineers but also to executives and senior business leaders and to the leaders of divisions working on AI projects A. True B. False
Answer: A
Question 31:
Which of the following AI pitfalls to avoid? 1. Expecting AI based projects to work the first time 2. Expecting AI to solve everything 3. Expecting traditional planning processes to apply without changes 4. Pairing engineering talent with business talent to identify feasible and valuable A. Options 1, 2, 3 as mentioned above B. Options 3 & 4 only C. Options 1 & 4 D. All of the above
Answer: A