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Artificial Intelligence with Python

You're reading from   Artificial Intelligence with Python A Comprehensive Guide to Building Intelligent Apps for Python Beginners and Developers

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Product type Paperback
Published in Jan 2017
Publisher Packt
ISBN-13 9781786464392
Length 446 pages
Edition 1st Edition
Languages
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Author (1):
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Prateek Joshi Prateek Joshi
Author Profile Icon Prateek Joshi
Prateek Joshi
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Table of Contents (17) Chapters Close

Preface 1. Introduction to Artificial Intelligence FREE CHAPTER 2. Classification and Regression Using Supervised Learning 3. Predictive Analytics with Ensemble Learning 4. Detecting Patterns with Unsupervised Learning 5. Building Recommender Systems 6. Logic Programming 7. Heuristic Search Techniques 8. Genetic Algorithms 9. Building Games With Artificial Intelligence 10. Natural Language Processing 11. Probabilistic Reasoning for Sequential Data 12. Building A Speech Recognizer 13. Object Detection and Tracking 14. Artificial Neural Networks 15. Reinforcement Learning 16. Deep Learning with Convolutional Neural Networks

Defining intelligence using Turing Test

The legendary computer scientist and mathematician, Alan Turing, proposed the Turing Test to provide a definition of intelligence. It is a test to see if a computer can learn to mimic human behavior. He defined intelligent behavior as the ability to achieve human-level intelligence during a conversation. This performance should be sufficient to trick an interrogator into thinking that the answers are coming from a human.

To see if a machine can do this, he proposed a test setup: he proposed that a human should interrogate the machine through a text interface. Another constraint is that the human cannot know who's on the other side of the interrogation, which means it can either be a machine or a human. To enable this setup, a human will be interacting with two entities through a text interface. These two entities are called respondents. One of them will be a human and the other one will be the machine.

The respondent machine passes the test if the interrogator is unable to tell whether the answers are coming from a machine or a human. The following diagram shows the setup of a Turing Test:

Defining intelligence using Turing Test

As you can imagine, this is quite a difficult task for the respondent machine. There are a lot of things going on during a conversation. At the very minimum, the machine needs to be well versed with the following things:

  • Natural Language Processing: The machine needs this to communicate with the interrogator. The machine needs to parse the sentence, extract the context, and give an appropriate answer.
  • Knowledge Representation: The machine needs to store the information provided before the interrogation. It also needs to keep track of the information being provided during the conversation so that it can respond appropriately if it comes up again.
  • Reasoning: It's important for the machine to understand how to interpret the information that gets stored. Humans tend to do this automatically to draw conclusions in real time.
  • Machine Learning: This is needed so that the machine can adapt to new conditions in real time. The machine needs to analyze and detect patterns so that it can draw inferences.

You must be wondering why the human is communicating with a text interface. According to Turing, physical simulation of a person is unnecessary for intelligence. That's the reason the Turing Test avoids direct physical interaction between the human and the machine. There is another thing called the Total Turing Test that deals with vision and movement. To pass this test, the machine needs to see objects using computer vision and move around using Robotics.

You have been reading a chapter from
Artificial Intelligence with Python
Published in: Jan 2017
Publisher: Packt
ISBN-13: 9781786464392
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