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AIGP > Module 1 > Flashcards

Module 1 Flashcards

Foundations of AI

1
Q

What is AI?

A. A subset of data analytics that utilizes statistical methods to optimize business processes.
B. A field of computer science that enables systems to perform tasks requiring human intelligence, such as learning, reasoning, and decision-making.
C. A technology focused solely on automating repetitive tasks in businesses.
D. An advanced computational framework designed exclusively for robotics applications.

A

B. A field of computer science that enables systems to perform tasks requiring human intelligence, such as learning, reasoning, and decision-making.

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2
Q

Question:
What are the common elements of AI technology?

Options:
A. Algorithms, machine learning, and data analysis
B. Technology, autonomy, human involvement, and output
C. Automation, robotics, and mechanical engineering
D. Cloud computing, blockchain, and virtual reality

A

B. Technology, autonomy, human involvement, and output

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3
Q

In which year did Alan Turing develop a test to determine whether a machine was intelligent?

Options:
A. 1936
B. 1943
C. 1950
D. 1961

A

C. 1950

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4
Q

What is machine learning?

Options:
A. A branch of AI that enables machines to learn and improve from experience without being explicitly programmed.
B. A process of training machines to display AI behavior.
C. A statistical method used to analyze historical data for forecasting purposes.
D. A technology that mimics human emotions to enhance user interactions.

A

B. A process of training machines to display AI behavior.

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5
Q

What are the 3 main types of machine learning?

Options:
A. Supervised learning, unsupervised learning, and reinforcement learning
B. Linear regression, decision trees, and neural networks
C. Automation learning, cognitive learning, and predictive learning
D. Statistical learning, algorithmic learning, and heuristic learning

A

A. Supervised learning, unsupervised learning, and reinforcement learning

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6
Q

What does it mean that an AI system is a socio-technical system?

Options:
A. It is exclusively driven by technical algorithms without human interaction.
B. AI influences society and society influences AI.
C. It focuses solely on the technical aspects of data processing and computation.
D. It is a system designed specifically for social media platforms and technical communication.

A

B. AI influences society and society influences AI.

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7
Q

What are the OECD’s 5 main dimensions for classifying AI systems?

A
  1. people and planet
  2. economic context
  3. data and input
  4. AI model
  5. tasks and outputs
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8
Q

What is not one of the OECD’s dimensions for classifying AI systems?

Options:
A. People and planet
B. Economic context
C. Data and input
D. Autonomous decision-making

A

D. Autonomous decision-making

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9
Q

When was the Dartmouth Conference, considered the birthplace of artificial intelligence, held?

Options:
A. 1945
B. 1950
C. 1956
D. 1960

A

C. 1956

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10
Q

What was the time period of the first AI summer?

Options:
A. 1943–1950
B. 1956–1974
C. 1980–1987
D. 1995–2000

A

B. 1956-1974

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11
Q

The first AI summer was characterized by?

Options:
A. The development of the first AI programming language, LISP, and the creation of ELIZA.
B. Rapid advancements in neural networks and machine learning algorithms.
C. The widespread commercial adoption of AI technologies in various industries.
D. A focus on robotics and the development of autonomous vehicles.

A

Correct Answer:
A. The development of the first AI programming language, LISP, and the creation of ELIZA.

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12
Q

What was ELIZA an example of in early AI research?

Options:
A. Early natural language processing
B. Machine learning algorithms
C. Autonomous robotics development
D. Neural network experimentation

A

A. Early natural language processing

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13
Q

When was the first AI winter?

Options:
A. Mid-1950s to mid-1960s
B. Mid-1970s to mid-1980s
C. Late-1980s to early-1990s
D. Early-2000s to mid-2010s

A

B. Mid-1970s to mid-1980s

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14
Q

How was the first AI winter denoted?

Options:
A. A period marked by decreased funding and interest in AI research due to unmet expectations.
B. A time of rapid advancements in neural networks and symbolic AI.
C. A phase characterized by the widespread adoption of AI technologies in industries.
D. A significant focus on robotics and machine learning innovations.

A

A. A period marked by decreased funding and interest in AI research due to unmet expectations.

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15
Q

When was the second AI summer?

Options:
A. Mid-1980s to late-1980s
B. Mid-1990s to early-2000s
C. Late-1980s to mid-1990s
D. Early-2000s to mid-2010s

A

A. Mid-1980s to late-1980s

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16
Q

What was a key characteristic of the second AI summer?

Options:
A. Expert and computer systems emulated human decision-making ability.
B. Neural networks became the dominant technology in AI research.
C. AI systems achieved widespread commercial adoption in robotics.
D. The development of natural language processing tools like ELIZA.

A

A. Expert and computer systems emulated human decision-making ability.

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17
Q

When was the second AI winter?

Options:
A. Late 1970s to early 1980s
B. Late 1980s to late 1990s
C. Mid-1990s to early 2000s
D. Early 2000s to late 2010s

A

B. Late 1980s to late 1990s

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18
Q

What was the highlight of the second AI winter?

Options:
A. Decreased interest and funding due to the end of the Cold War and the high cost of maintaining expert systems.
B. The rapid development of machine learning algorithms and neural networks.
C. The commercial success of AI systems in industrial automation.
D. Increased government funding for AI research due to geopolitical tensions.

A

A. Decreased interest and funding due to the end of the Cold War and the high cost of maintaining expert systems.

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19
Q

When was the Renaissance and the era of big data in AI?

Options:
A. Early 1990s to early 2000s
B. Late 1990s to 2011
C. Mid-2000s to 2010
D. Early 2010s to mid-2020s

A

B. Late 1990s to 2011

20
Q

Which of these were NOT a highlight of the Renaissance and the era of big data?

Options:
A. IBM’s Deep Blue defeating the world chess champion in 1997
B. The emergence of the internet, marking the beginning of the big data era
C. Advancements in computational power and machine learning improving AI capabilities
D. Advancements in deep learning, which involves training neural networks with data

A

D. Advancements in deep learning, which involves training neural networks with data

21
Q

Which portion of the AI cycle was considered the turning point for AI?

Options:
A. The first AI summer (mid 1950s–mid 1970s)
B. The first AI winter (mid-1970s to mid-1980s)
C. The Renaissance and the era of big data (late 1990s to 2011)
D. The second AI winter (late 1980s to late 1990s)

A

C. The Renaissance and the era of big data (late 1990s to 2011)

22
Q

Which period is considered the AI boom?

Options:
A. Mid-2000s to late-2010s
B. Early 1990s to late 2000s
C. Late 1980s to mid-1990s
D. Early 2011 to present

A

D. Early 2011 to present

23
Q

What was NOT a highlight of the AI boom period?

Options:
A. Advancements in deep learning involving training neural networks with data
B. Victories of Google’s AlphaGo over the Go world champion in 2016
C. OpenAI’s GPT-3 showcasing the capabilities of language models
D. Development of early symbolic AI and expert systems

A

D. Development of early symbolic AI and expert systems

24
Q

What are the tech megatrends that have fueled AI and data science?

A
  1. cloud computing
  2. mobile technology and social media
  3. Internet of Things (IoT)
  4. Privacy-enhancing technologies (PETs)
  5. Blockchain
  6. Computer vision, AR/VR, and the metaverse
25
Q

What are the use cases of AI?

A
  1. Recognition
  2. Detection
  3. Forecasting
  4. Personalization
  5. Interaction support
  6. Goal-driven optimization
  7. Recommendation
26
Q

What marked the beginning of the era of “big data”?

A. Rise of mobile technology
B. Advent of the internet
C. increasing importance of data-driven decision making
D. increased use of databases

A

B. Advent of the internet

27
Q

Which is not a high-level category of AI?

A. Artificial Narrow Intelligence (ANI)
B. Artificial General Intelligence (AGI)
C. Artificial Broad Intelligence (ABI)
D. Artificial Super Intelligence (ASI)

A

C. Artificial Broad Intelligence (ABI)

28
Q

Which category of AI closely mimics human intelligence?

Options:
A. Artificial Narrow Intelligence (ANI)
B. Artificial General Intelligence (AGI)
C. Artificial Superintelligence (ASI)
D. Artificial Broad Intelligence (ABI)

A

B. Artificial General Intelligence (AGI)

29
Q

Which category of AI is considered full AI?

Options:
A. Artificial Narrow Intelligence (ANI)
B. Artificial General Intelligence (AGI)
C. Artificial Broad Intelligence (ABI)
D. Artificial Superintelligence (ASI)

A

B. Artificial General Intelligence (AGI)

30
Q

What are the subcategories of Supervised Learning Models?

A
  1. Classification
  2. Regression
31
Q

What are the subcategories of unsupervised learning models?

A
  1. Clustering
  2. Association Rule Learning
32
Q

Association rule Learning

A

identifying relationships and associations between data points (e.g. understanding consumer buying habits)

33
Q

Which of the following are examples of semi-supervised learning models?

Options:
A. Image and speech analysis, categorization and ranking of web page search results, Large Language Models (LLMs), and generative AI
B. Neural networks, decision trees, and reinforcement learning algorithms
C. Robotic process automation, autonomous vehicles, and symbolic AI models
D. Data clustering, unsupervised anomaly detection, and rule-based systems

A

A. Image and speech analysis, categorization and ranking of web page search results, Large Language Models (LLMs), and generative AI

34
Q

Large Language Models (LLMs)

A

A form of AI that utilizes deep learning algorithms to create models trained on massive text data sets to analyze and learn patterns and relationships among characters, words and phrases.

35
Q

What is NOT an element of an expert system?

Options:
A. Knowledge base
B. Inference engine
C. User interface
D. Autonomous neural networks

A

D. Autonomous neural networks

36
Q

What is the method of reasoning intended to mimic/resemble human decision-making called?

A

Fuzzy Logic

37
Q

What are the 4 standard steps in fuzzy logic systems?

A
  1. Fuzzification
  2. Rule evaluation
  3. Aggregation
  4. Defuzzification
38
Q

What are the common AI models?

A
  1. Linear and statistical models
  2. Decision trees
  3. Machine learning models
  4. Robotics
39
Q

Neural networks are a subcomponent of what common AI model?

A. Decision trees
B. Robotics
C. Machine Learning
D. Linear and statistical models

A

C. Machine Learning

40
Q

Robotics

A

multidisciplinary field encompassing the design, construction, operation, and programming of robotics

41
Q

What are the 4 types of neural networks?

A
  1. computer vision models
  2. speech recognition models
  3. language models
  4. reinforcement learning models
42
Q

Robotic Process Automation (RPA)

A

evolving tech that uses software robots to automate repetitive and rule-based tasks within a business process. It is designed to mimic human actions on digital systems and utilized natural language processing or machine learning.

43
Q

What are examples of robotic process automation (RPA)?

Options:
A. Data entry, invoice processing, customer service chatbots, and payroll automation
B. Autonomous vehicles, industrial robotics, and smart home assistants
C. Image recognition, natural language processing, and machine learning model training
D. Video game AI, reinforcement learning, and unsupervised clustering algorithms

A

A. Data entry, invoice processing, customer service chatbots, and payroll automation

44
Q

What are the main areas of AI infrastructure?

A
  1. Compute
  2. Storage and network
  3. Software Development
45
Q

What are the 4 general stages of AI?

A
  1. Ingestion
  2. Preparation
  3. Training
  4. Output (Inference)
46
Q

What are the challenges with AI?

A
  1. Data Integrity
  2. Data Drift
  3. Bias and discrimination

AIGP (6 decks)

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