A
1. What was the name of the first computer program considered to be an AI, developed in the 1950s?
a) ELIZA
b) Deep Blue
c) The Logic Theorist
d) Watson
The Logic Theorist
Trivia: The Logic Theorist was developed by Allen Newell and Herbert A. Simon in 1956 and is considered the first AI program. It was capable of proving mathematical theorems.
2. Which AI system famously defeated the world champion Garry Kasparov in a chess match in 1997?
a) AlphaGo
b) Watson
c) Deep Blue
d) GPT-3
Trivia: Deep Blue, developed by IBM, made history by defeating Garry Kasparov, the reigning world chess champion, in a six-game match in 1997.
Deep Blue
Trivia: Deep Blue, developed by IBM, made history by defeating Garry Kasparov, the reigning world chess champion, in a six-game match in 1997.
3. What does the term "NLP" stand for in AI?
a) Neural Language Processing
b) Natural Language Processing
c) Networked Language Protocol
d) Nominal Linguistic Patterns
Natural Language Processing (NLP)
Trivia: Natural Language Processing (NLP) involves the interaction between computers and humans through natural language, enabling machines to understand and interpret human language.
4. Which company developed the AI system "AlphaGo" that defeated a professional Go player?
a) Apple
b) Microsoft
c) Google DeepMind
d) IBM
AlphaGo
Trivia: AlphaGo, developed by Google DeepMind, defeated the world champion Go player, Lee Sedol, in 2016, marking a significant achievement in AI research.
5. In Big Data, what does the term "volume" refer to?
a) The amount of data
b) The speed at which data is processed
c) The accuracy of data
d) The types of data
Volume
Trivia: Volume refers to the sheer amount of data generated every second, which can be in terabytes, petabytes, or even exabytes.
6. Which of the following is an application of AI in everyday life?
a) Online shopping recommendations
b) Traditional landline telephones
c) Analog watches
d) Handwritten letters
Online shopping recommendations
Trivia: AI-powered recommendation systems analyze user behavior to suggest products or services, enhancing the online shopping experience.
7. Which of the following is a key characteristic of Big Data?
a) Limited variety of data
b) Low velocity of data
c) High volume of data
d) Small datasets
High volume of data
Trivia: Big Data is often characterized by the "3 Vs": Volume (large amounts of data), Velocity (high-speed data generation), and Variety (different types of data).
8. What does "deep learning" refer to?
a) A shallow approach to problem-solving
b) A subset of machine learning involving neural networks with many layers
c) Learning how to swim
d) A basic form of AI
b) A subset of machine learning involving neural networks with many layers
Trivia: Deep learning involves neural networks with many layers (deep networks) that enable advanced learning and decision-making capabilities.
9. In the context of Big Data, what does "velocity" refer to?
a) The variety of data sources
b) The amount of data
c) The accuracy of data
d) The speed at which data is generated and processed
The speed at which data is generated and processed
Trivia: Velocity in Big Data refers to the rapid pace at which data is generated, processed, and analyzed.
10. What is the primary function of a data warehouse?
a) Storing small amounts of data for quick access
b) Analyzing trends in data
c) Storing and managing large volumes of structured data
d) Creating data visualizations
Storing and managing large volumes of structured data
Trivia: A data warehouse is designed for query and analysis, and it stores large volumes of structured data from various sources.
11. Which AI technique is used for recognizing patterns in data and making predictions?
a) Machine learning
b) Pattern recognition
c) Sorting algorithms
d) Data compression
Machine Learning
Trivia: Machine learning algorithms can identify patterns in data and make predictions or decisions without being explicitly programmed to perform the task.
12. What is the main advantage of using cloud computing for Big Data?
a) Limited storage capacity
b) High cost
c) Limited accessibility
d) Scalability and flexibility in handling large datasets
Scalability and flexibility in handling large datasets
Trivia: Cloud computing offers scalable resources and flexible storage solutions, making it ideal for handling the vast amounts of data in Big Data applications.