Book Image

Practical Artificial Intelligence and Blockchain

By : Ganesh Prasad Kumble
Book Image

Practical Artificial Intelligence and Blockchain

By: Ganesh Prasad Kumble

Overview of this book

AI and blockchain are two emerging technologies catalyzing the pace of enterprise innovation. With this book, you’ll understand both technologies and converge them to solve real-world challenges. This AI blockchain book is divided into three sections. The first section covers the fundamentals of blockchain, AI, and affiliated technologies, where you’ll learn to differentiate between the various implementations of blockchains and AI with the help of examples. The second section takes you through domain-specific applications of AI and blockchain. You’ll understand the basics of decentralized databases and file systems and connect the dots between AI and blockchain before exploring products and solutions that use them together. You’ll then discover applications of AI techniques in crypto trading. In the third section, you’ll be introduced to the DIApp design pattern and compare it with the DApp design pattern. The book also highlights unique aspects of SDLC (software development lifecycle) when building a DIApp, shows you how to implement a sample contact tracing application, and delves into the future of AI with blockchain. By the end of this book, you’ll have developed the skills you need to converge AI and blockchain technologies to build smart solutions using the DIApp design pattern.
Table of Contents (15 chapters)
Section 1: Overview of Blockchain Technology
Section 2: Blockchain and Artificial Intelligence
Section 3: Developing Blockchain Products

Forms of AI and approaches

Implementations of AI have come in various forms due to the varying nature of the intended application and the technology available for the solution. Hence, AI has been manifested in code in various forms, utilized by a wide range of developers in different domains for respective problems.

In the following Venn diagram, we can see various forms of AI:

Fig 2.2: Relationships between forms of AI

In the preceding diagram, I have mentioned all the major forms of AI categorized into three major manifestations. Each form is explained in detail in the following section, broken down into expert systems, machine learning, and neural networks.

We will now explore these primary approaches and forms of AI with brief introductions to their backgrounds and applications.

Statistical and expert systems

Statistical systems were one of the most primitive forms of AI, dating back to the late 1960s. As the name suggests, statistical approaches used a huge amount of data to arrive...