ABSTRACT

Artificial Intelligence: An Introduction for the Inquisitive Reader guides readers through the history and development of AI, from its early mathematical beginnings through to the exciting possibilities of its potential future applications. To make this journey as accessible as possible, the authors build their narrative around accounts of some of the more popular and well-known demonstrations of artificial intelligence including Deep Blue, AlphaGo and even Texas Hold’em, followed by their historical background, so that AI can be seen as a natural development of mathematics and computer science. As the book moves forward, more technical descriptions are presented at a pace that should be suitable for all levels of readers, gradually building a broad and reasonably deep understanding and appreciation for the basic mathematics, physics, and computer science that is rapidly developing artificial intelligence as it is today.

Features:

  • Only mathematical prerequisite is an elementary knowledge of calculus
  • Accessible to anyone with an interest in AI and its mathematics and computer science
  • Suitable as a supplementary reading for a course in AI or the History of Mathematics and Computer Science in regard to artificial intelligence.

part I|49 pages

The Arrival of AI in the Human World

chapter Chapter 1|17 pages

Game-Playing Machines

chapter Chapter 2|13 pages

Working Machines

chapter Chapter 3|9 pages

Intelligence

chapter Chapter 4|5 pages

The AI Singularity

part II|43 pages

The Artificial Intelligence Infrastructure

chapter Chapter 5|21 pages

Hardware

chapter Chapter 6|4 pages

Software

chapter Chapter 7|7 pages

Computer Communications

chapter Chapter 8|7 pages

Open Source Software

part III|41 pages

From Top to Bottom

chapter Chapter 9|13 pages

Top-Down Artificial Intelligence

chapter Chapter 10|7 pages

Bottom-Up Artificial Intelligence

chapter Chapter 11|6 pages

Machine Learning Modeling

chapter Chapter 12|11 pages

Markov Chain Monte Carlo Simulation

part IV|38 pages

Structure and Operation

chapter Chapter 13|5 pages

Artificial Neural Networks

chapter Chapter 14|4 pages

Pattern Recognition

chapter Chapter 15|8 pages

Parameterization

chapter Chapter 16|6 pages

Gradient Descent

chapter Chapter 17|5 pages

Backpropagation

chapter Chapter 18|6 pages

Convolutional Neural Networks

part V|26 pages

Progression

chapter Chapter 19|5 pages

The Cross-Entropy Cost Function

chapter Chapter 20|3 pages

Hyperparameterization

chapter Chapter 21|5 pages

Big Data

chapter Chapter 22|8 pages

Massively Parallel Processing

part VI|51 pages

Powers of Prediction

chapter Chapter 23|6 pages

Predictive Analytics

chapter Chapter 24|7 pages

Restricted Boltzmann Machine

chapter Chapter 25|6 pages

Latent Factors in Collaborative Filtering

chapter Chapter 26|7 pages

Support Vector Machines

chapter Chapter 27|6 pages

Reinforcement Learning

chapter Chapter 28|6 pages

Alphago and Alphastar

chapter Chapter 29|9 pages

Game Theory

part VII|34 pages

Natural Language Processing

chapter Chapter 30|5 pages

Top-Down Speech Recognition

chapter Chapter 31|17 pages

Bottom Up Speech Recognition

chapter Chapter 32|8 pages

Speech Synthesis

part VIII|23 pages

The Robotworld

chapter Chapter 33|12 pages

Robots at Work

chapter Chapter 34|4 pages

The Robot Millennial

chapter Chapter 35|5 pages

The Robot Future