Artificial Intelligence Overview Quiz
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Questions and Answers

Which of the following is NOT a type of Artificial Intelligence?

  • Supervised Learning
  • Natural Selection (correct)
  • Deep Learning
  • Cognitive Computing

Cognitive computing enhances human decision-making.

True (A)

What are the two main categories of learning in Artificial Intelligence?

Machine Learning and Deep Learning

AI includes domains such as __________, natural language processing, and computer vision.

<p>data science</p> Signup and view all the answers

Match the following AI concepts with their descriptions:

<p>Machine Learning = Algorithms that enable systems to learn from data Natural Language Processing = Field that focuses on the interaction between computers and humans through language Computer Vision = Technology that allows computers to interpret visual information Deep Learning = Subfield of machine learning that uses neural networks to analyze data</p> Signup and view all the answers

Which of the following is a limitation of AI?

<p>Data privacy concerns (D)</p> Signup and view all the answers

AI tools can only automate repetitive tasks but do not contribute to creativity.

<p>False (B)</p> Signup and view all the answers

What is one application of AI in healthcare?

<p>Drug discovery</p> Signup and view all the answers

AI advancements raise ethical concerns about _____ related to algorithm bias.

<p>transparency</p> Signup and view all the answers

Match the following AI applications with their descriptions:

<p>Semantris = NLP-based game focusing on word association Quick Draw = A game where a neural network guesses user-drawn pictures AutoDraw = Identifies user drawings and suggests related images AI in the News = Researching recent AI developments and ethical dilemmas</p> Signup and view all the answers

What defines fixed-function hardware?

<p>Devices that perform tasks without learning or thinking (A)</p> Signup and view all the answers

The Turing test was proposed by John McCarthy.

<p>False (B)</p> Signup and view all the answers

What was the significance of the Dartmouth Conference in 1956?

<p>It marked the birthplace of AI as a field.</p> Signup and view all the answers

The term 'Artificial Intelligence' was coined by __________.

<p>John McCarthy</p> Signup and view all the answers

Match the following time periods with their key events in the evolution of AI:

<p>1950 = Turing's paper on machine intelligence 1956 = Dartmouth Conference 1960-1970 = Development of expert systems 1980-1990 = AI winter and skepticism 21st Century = Breakthroughs in machine learning</p> Signup and view all the answers

Which programming language is particularly useful for machine learning and statistical functions?

<p>R (C)</p> Signup and view all the answers

Java is primarily used for data collection and organization.

<p>False (B)</p> Signup and view all the answers

What soft skills are essential for managing multiple projects and meeting deadlines?

<p>Time management and organizational skills</p> Signup and view all the answers

TensorFlow is an open-source machine learning platform that provides tools and libraries for developing ______ applications.

<p>AI</p> Signup and view all the answers

Match the following programming languages with their primary usage:

<p>Python = Advanced computing R = Statistical analysis Java = Intelligence programming C++ = Procedural programming</p> Signup and view all the answers

Flashcards

What is AI?

Artificial intelligence (AI) is the simulation of human intelligence processes by computer systems. These processes include learning, problem-solving, and decision-making.

AI Evolution

AI has evolved over decades, from early rule-based systems to modern deep learning algorithms. Key milestones include the Dartmouth Conference (1956) and the development of expert systems in the 1980s.

Types of AI

AI systems can be categorized based on their capabilities, including reactive machines, limited memory, theory of mind, and self-aware. Each type has different levels of understanding and reasoning.

Domains of AI

AI is applied across various domains, including data science, natural language processing, computer vision, robotics, and healthcare. Each domain uses AI to solve specific problems.

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AI Terminologies

Key terminologies in AI include machine learning, deep learning, and reinforcement learning. These terms explain different approaches to training AI systems.

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Fixed-Function Hardware

Machines like microwave ovens that perform tasks without learning or thinking.

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Non-Interactive Systems

Systems that do not change based on new information, like a basic electric fan.

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Basic Sensors

Sensors gather information but don't analyze or understand it.

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Artificial Intelligence

Machines that learn from data and can make decisions autonomously, like a smart washing machine adjusting settings.

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Turing Test

A test proposed by Alan Turing in 1950 to gauge a machine's ability to exhibit intelligent behavior equivalent to, or indistinguishable from, that of a human.

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What is R used for in AI?

A programming language used for data collection, organization, and analysis, particularly useful for machine learning and statistical functions.

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What is Python used for in AI?

A versatile programming language with libraries for advanced computing and scientific computation.

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What is TensorFlow?

An open-source machine learning platform with tools and libraries for developing sophisticated AI applications.

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What are NumPy and SciPy used for in AI?

Python libraries for scientific computing and mathematical operations, ideal for manipulating and visualizing data.

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Why is time management important for AI professionals?

Time management and organizational skills are crucial for success in AI, especially when handling multiple projects and tight deadlines.

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Machine Learning (ML)

The ability of AI to learn from data without explicit programming, enabling it to improve performance over time.

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Deep Learning (DL)

A subfield of machine learning that uses artificial neural networks, inspired by the human brain, to analyze and learn from complex data.

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Reinforcement Learning (RL)

A type of AI that uses algorithms to learn from past actions and rewards to make optimal decisions in dynamic environments.

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Natural Language Processing (NLP)

The ability of AI systems to understand, interpret, and generate human language, enabling tasks like text translation, sentiment analysis, and chatbot conversations.

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Computer Vision (CV)

A branch of AI that focuses on enabling computers to 'see' and interpret images and videos, allowing them to recognize objects, analyze scenes, and even create realistic visual content.

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