Book Image

Artificial Intelligence By Example

By : Denis Rothman
Book Image

Artificial Intelligence By Example

By: Denis Rothman

Overview of this book

Artificial intelligence has the potential to replicate humans in every field. Artificial Intelligence By Example serves as a starting point for you to understand how AI is built, with the help of intriguing examples and case studies. Artificial Intelligence By Example will make you an adaptive thinker and help you apply concepts to real-life scenarios. Using some of the most interesting AI examples, right from a simple chess engine to a cognitive chatbot, you will learn how to tackle the machine you are competing with. You will study some of the most advanced machine learning models, understand how to apply AI to blockchain and IoT, and develop emotional quotient in chatbots using neural networks. You will move on to designing AI solutions in a simple manner rather than get confused by complex architectures and techniques. This comprehensive guide will be a starter kit for you to develop AI applications on your own. By the end of this book, you will have understood the fundamentals of AI and worked through a number of case studies that will help you develop your business vision.
Table of Contents (19 chapters)

Chapter 3 – Apply Machine Thinking to a Human Problem

1. Can a human beat a chess engine? (Yes | No)

The answer is no. Today, the highest level chess tournaments are not between humans but between chess engines. Each chess engine software editor prepares for these competitions by making their algorithms faster and requiring less CPU. In fact today, a top chess engine running on a smartphone can beat humans. In human-to-human chess competitions, the level of chess has reached very high limits of complexity. Humans now mostly train against machines.

2. Humans can estimate decisions better than machines with intuition when it comes to large volumes of data. (Yes | No)

The answer is no. The sheer CPU power of an average machine or even a smartphone can generate better results than humans with the proper algorithms.

3. Building a reinforcement learning program with a Q function...