Artificial Intelligence Quiz
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Questions and Answers

What is the primary characteristic of Artificial narrow intelligence?

  • It mimics human emotional intelligence.
  • It typically does one job well. (correct)
  • It performs multiple complex tasks simultaneously.
  • It can surpass human intelligence.

    • Which type of AI is described as being as smart as a human?

  • Artificial narrow intelligence.
  • Artificial super intelligence.
  • Artificial emotional intelligence.
  • Artificial general intelligence. (correct)

    • What are the two broad areas within Artificial Intelligence?

  • Neural Networks and Expert Systems.
  • Symbolic Reasoning and Machine Learning. (correct)
  • Deep Learning and Natural Language Processing.
  • Genetic Algorithms and Robotics.

    • Which of the following is NOT an example of statistical learning in Machine Learning?

    <p>Symbolic Reasoning.</p> Signup and view all the answers

    What does the AND function in Boolean logic return when both inputs are 1?

    <p>1</p> Signup and view all the answers

    Who among the following is known as a significant figure in the field of Machine Learning?

    <p>Geoffrey Hinton.</p> Signup and view all the answers

    What is the key implication of Artificial super intelligence?

    <p>It can consistently outperform all human capabilities.</p> Signup and view all the answers

    What is one reason why advances in AI stalled historically?

    <p>Boolean logic functions restricted advancements.</p> Signup and view all the answers

    What is the output of the XOR operation when both inputs are 1?

    <p>0</p> Signup and view all the answers

    Which of the following statements best describes the function of XOR?

    <p>It returns true only if one of the inputs is true, but not both.</p> Signup and view all the answers

    What significant problem did Minsky and Papert highlight regarding XOR?

    <p>It cannot be derived from AND and OR functions accurately.</p> Signup and view all the answers

    How many neurons are estimated to be in a human brain?

    <p>100 billion</p> Signup and view all the answers

    In the basic Perceptron model, what is the role of weights?

    <p>They control the influence of each input on the output.</p> Signup and view all the answers

    What kind of problem does the XOR function represent?

    <p>Non-linearly separable problem.</p> Signup and view all the answers

    Which component of an AI neuron is responsible for generating the output based on inputs and weights?

    <p>Activation Function</p> Signup and view all the answers

    What is the risk of overfitting in an artificial neural network?

    <p>It only recognizes the training data set.</p> Signup and view all the answers

    In supervised learning, when can unlabelled data be introduced?

    <p>Only after achieving acceptable results.</p> Signup and view all the answers

    Which of the following techniques uses a reward signal for training?

    <p>Reinforcement learning</p> Signup and view all the answers

    What characterizes hybrid learning methods?

    <p>They use a small amount of labeled data alongside unlabelled data.</p> Signup and view all the answers

    Which type of neural network is particularly effective for sequential data processing?

    <p>Recurrent Neural Network</p> Signup and view all the answers

    What is typically true about unsupervised learning?

    <p>The algorithm identifies underlying patterns in unlabelled data.</p> Signup and view all the answers

    Which statement best describes the concept of underfitting?

    <p>The model fails to capture the underlying trend of the data.</p> Signup and view all the answers

    What is an example of a task where hybrid learning might be particularly useful?

    <p>Situations where acquiring labeled data is difficult or costly.</p> Signup and view all the answers

    What is the primary purpose of using multiple linear classifiers in the context of the XOR problem?

    <p>To create a non-linear decision boundary</p> Signup and view all the answers

    In supervised learning, what is necessary for the model to improve its accuracy?

    <p>Access to labeled test data</p> Signup and view all the answers

    Which of the following best describes the concept of unsupervised learning?

    <p>Adjusting parameters based on a derived cost function</p> Signup and view all the answers

    What technique does reinforced learning primarily utilize to guide a neural network's actions?

    <p>Continuous feedback through rewards and penalties</p> Signup and view all the answers

    What role does a cost function play in the context of neural networks?

    <p>It measures the network's performance against the target</p> Signup and view all the answers

    When training a neural network, what is the significance of the process involving 'Compare the output against the known result'?

    <p>It allows for adjusting model parameters</p> Signup and view all the answers

    What is an advantage of using multiple layers in a neural network?

    <p>To improve the ability to learn non-linear relationships</p> Signup and view all the answers

    Which of the following statements best describes the objective of backpropagation in neural networks?

    <p>To adjust weights based on the error calculated</p> Signup and view all the answers

    Study Notes

    Artificial Intelligence Introduction

    • Artificial intelligence (AI) is a subset of computer science
    • AI involves two broad areas: Symbolic Reasoning and Machine Learning
    • Symbolic reasoning is the work of expert systems and hard-coded human reasoning (if-then statements)
    • Machine Learning includes statistical learning, speech recognition, natural language processing and deep learning

    Types of AI

    • Artificial Narrow Intelligence (Weak AI): performs specific tasks well
    • Artificial General Intelligence (Strong AI): as smart as a human
    • Artificial Superintelligence: surpasses human intelligence

    Influential Machine Learning Minds

    • Geoffrey Hinton
    • Michael I. Jordan
    • Andrew Ng
    • Yann LeCun
    • Yoshua Bengio
    • Demis Hassabis

    Why AI Development Stalled

    • Boolean logic functions are fundamental in computer operation
    • "True" is represented as 1, "false" as 0
    • Boolean logic, particularly XOR, faced problems in separating data linearly.

    Biological Neurons

    • The human brain has approximately 100 billion neurons
    • Neurons communicate through electrical signals along axons

    Artificial Neural Network (ANN)

    • ANNs are modeled after biological neurons
    • The basic Perceptron model is a type of artificial neuron.
    • Inputs are weighted then passed to a node and output based on activation function

    Activation Functions

    • Activation functions introduce non-linearity into ANNs examples include step, sigmoid, tanh, ReLU and leaky ReLU, ELU

    Supervised Learning

    • Uses labeled training data
    • Aims to produce acceptable results, then unlabeled data can be used

    Unsupervised Learning

    • Works with unlabeled data
    • Helps with clustering and association

    Reinforcement Learning

    • No labelled data is needed
    • A method to quantify performance with reward
    • Popular in recent development

    Hybrid Learning

    • A combination of supervised and unsupervised approaches
    • Useful when only a small amount of labelled data is available in real world applications

    Deep Learning

    • Multi-layered neural networks
    • Uses feed forward but back propagation is needed

    XOR

    • XOR presented non-linearly separable problem

    Solving XOR with Deep Learning

    • Using multiple layers, deep learning can solve issues presented by single layered ANNs

    Other AI Topics

    • Convolutional Neural Networks
    • Generative Adversarial Networks
    • Recurrent Neural Networks
    • Long Short-Term Memory Networks
    • Recursive Neural Networks
    • Natural Language Processing

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    Description

    Test your knowledge on the fundamentals of Artificial Intelligence with this quiz. Explore topics such as characteristics of AI, functions of logic gates, and key figures in the field. Perfect for anyone interested in strengthening their understanding of AI concepts.

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