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

Centralized versus distributed data

Databases have been primarily consumed in a centralized manner since their earliest applications, dawning in the mid-1960s. Databases were meant to provide direct access to the information requested by either users or client applications. This centralized approach was influenced majorly by the client-server architecture introduced in the early days. This design paradigm was popularly followed by the market with successful products in commercial- and consumer-level databases such as DB2 and dBASE, respectively. Relational Database Management System (RDBMS)-based databases followed the client-server model. These centralized databases managed data redundancy by making regular copies of the data on disks and magnetic tapes.

However, the dawn of NoSQL in the 2000s is credited with distributed databases that scale horizontally, with higher tolerance to failures and less chance of data corruption. NoSQL databases are able to manage data without schemas and...