,ents
1. Preface
1. Who this book is for
2. What this book covers
3. To get the most out of this book
1. Download the example code files
2. Download the color images
3. Conventions used
4. Get in touch
1. Reviews
1. Section 1: Overview of Blockchain Technology
1. Getting Started with Blockchain
1. Technical requirements
2. Blockchain versus distributed ledger technology versus distributed databases
1. Comparing the technologies with examples
3. Public versus private versus permissioned blockchains
1. Comparing usage scenarios
4. Privacy in blockchains
1. Understanding Bitcoin
2. A brief overview of Bitcoin
5. Introduction to Ethereum
1. A brief overview of Ethereum
6. Introduction to Hyperledger
1. Overview of the project
2. Hyperledger Fabric
3. Hyperledger Sawtooth
4. Other Hyperledger frameworks and tools
7. Other blockchain platforms – Hashgraph, Corda, and IOTA
8. Consensus algorithms
1. Proof of work
2. Proof of stake
3. Proof of burn
1. Delegated Proof of Stake
4. Proof of authority
5. Practical Byzantine fault tolerance
6. Proof of elapsed time
7. RAFT
8. Ternary augmented RAFT architecture
9. Avalanche
9. Building DApps with blockchain tools
1. Blockchain toolchains and frameworks
2. Developing smart contracts using IDEs and plugins
, 1. The Remix IDE
2. The EthFiddle IDE
3. The YAKINDU plugin for Eclipse
4. The Solidity plugin for Visual Studio Code
5. The Etheratom plugin for Visual Studio Code
10. Summary
2. Introduction to the AI Landscape
1. Technical requirements
2. AI – key concepts
1. History of AI
2. AI winter
3. Types of AI
1. Weak AI
2. Strong AI
3. Super AI
4. Forms of AI and approaches
1. Statistical and expert systems
2. Machine learning
1. Supervised learning
2. Unsupervised learning
3. Reinforcement learning
3. Neural networks
4. Evolutionary computation
5. Swarm computation
5. AI in digital transformation
1. Data extraction
2. Data transformation
3. Processing
4. Storyboarding
5. Data utilization
6. Failure scenarios
1. Business requirements
2. Adaptability
3. Skill gaps
4. Process overhaul
6. AI platforms and tools
1. TensorFlow
2. Microsoft Cognitive Toolkit
3. IBM Watson
7. Summary
2. Section 2: Blockchain and Artificial Intelligence
3. Domain-Specific Applications of AI and Blockchain
1. <strong>Technical requirements</strong>
, 2. <strong>Applying AI and blockchain to healthcare</strong>
1. <strong>Issues in the domain</strong>
2. Emerging solutions in healthcare
3. <strong>Retrospective</strong>
3. <strong>Applying AI and blockchain to supply chains</strong>
1. <strong>Issues in the domain</strong>
2. <strong>Emerging solutions in the supply chain industry</strong>
3. <strong>Retrospective</strong>
4. <strong>Applying AI and blockchain to financial services</strong>
1. <strong>Issues in the domain</strong>
2. <strong>Emerging solutions in BFSI</strong>
3. <strong>Retrospective</strong>
5. <strong>Applying AI and blockchain to other domains</strong>
1. <strong>Applying AI and blockchain to knowledge management</strong>
1. <strong>Issues in the domain</strong>
2. Emerging solutions in knowledge <span>management</span>
3. <strong>Retrospective</strong>
2. <strong>Applying AI and blockchain to real estate</strong>
1. <strong>Issues in the domain</strong>
2. <strong>Emerging solutions in real estate</strong>
3. <strong>Retrospective</strong>
3. <strong>Applying AI and blockchain to media</strong>
1. <strong>Issues in the domain</strong>
2. <strong>Emerging solutions in media</strong>
3. <strong>Retrospective</strong>
4. <strong>Applying AI and blockchain to identity management</strong>
1. <strong>Issues in the domain</strong>
2. <strong>Emerging solutions in identity management</strong>
3. <strong>Retrospective</strong>
5. <strong>Applying AI and blockchain to royalty management</strong>
1. <strong>Issues in the domain</strong>
2. <strong>Emerging solutions in royalty management</strong>
3. <strong>Retrospective</strong>
6. <strong>Applying AI and blockchain to information security</strong>
1. <strong>Issues in the domain</strong>
2. <strong>Emerging solutions in information security</strong>
3. <strong>Retrospective</strong>
7. <strong>Applying AI and blockchain to document management</strong>
1. <strong>Issues in the domain</strong>
2. <strong>Emerging solutions in document management</strong>
3. <strong>Retrospective</strong>
6. <strong>Summary</strong>
4. AI- and Blockchain-Driven Databases
1. Technical requirements
2. Centralized versus distributed data
1. Preface
1. Who this book is for
2. What this book covers
3. To get the most out of this book
1. Download the example code files
2. Download the color images
3. Conventions used
4. Get in touch
1. Reviews
1. Section 1: Overview of Blockchain Technology
1. Getting Started with Blockchain
1. Technical requirements
2. Blockchain versus distributed ledger technology versus distributed databases
1. Comparing the technologies with examples
3. Public versus private versus permissioned blockchains
1. Comparing usage scenarios
4. Privacy in blockchains
1. Understanding Bitcoin
2. A brief overview of Bitcoin
5. Introduction to Ethereum
1. A brief overview of Ethereum
6. Introduction to Hyperledger
1. Overview of the project
2. Hyperledger Fabric
3. Hyperledger Sawtooth
4. Other Hyperledger frameworks and tools
7. Other blockchain platforms – Hashgraph, Corda, and IOTA
8. Consensus algorithms
1. Proof of work
2. Proof of stake
3. Proof of burn
1. Delegated Proof of Stake
4. Proof of authority
5. Practical Byzantine fault tolerance
6. Proof of elapsed time
7. RAFT
8. Ternary augmented RAFT architecture
9. Avalanche
9. Building DApps with blockchain tools
1. Blockchain toolchains and frameworks
2. Developing smart contracts using IDEs and plugins
, 1. The Remix IDE
2. The EthFiddle IDE
3. The YAKINDU plugin for Eclipse
4. The Solidity plugin for Visual Studio Code
5. The Etheratom plugin for Visual Studio Code
10. Summary
2. Introduction to the AI Landscape
1. Technical requirements
2. AI – key concepts
1. History of AI
2. AI winter
3. Types of AI
1. Weak AI
2. Strong AI
3. Super AI
4. Forms of AI and approaches
1. Statistical and expert systems
2. Machine learning
1. Supervised learning
2. Unsupervised learning
3. Reinforcement learning
3. Neural networks
4. Evolutionary computation
5. Swarm computation
5. AI in digital transformation
1. Data extraction
2. Data transformation
3. Processing
4. Storyboarding
5. Data utilization
6. Failure scenarios
1. Business requirements
2. Adaptability
3. Skill gaps
4. Process overhaul
6. AI platforms and tools
1. TensorFlow
2. Microsoft Cognitive Toolkit
3. IBM Watson
7. Summary
2. Section 2: Blockchain and Artificial Intelligence
3. Domain-Specific Applications of AI and Blockchain
1. <strong>Technical requirements</strong>
, 2. <strong>Applying AI and blockchain to healthcare</strong>
1. <strong>Issues in the domain</strong>
2. Emerging solutions in healthcare
3. <strong>Retrospective</strong>
3. <strong>Applying AI and blockchain to supply chains</strong>
1. <strong>Issues in the domain</strong>
2. <strong>Emerging solutions in the supply chain industry</strong>
3. <strong>Retrospective</strong>
4. <strong>Applying AI and blockchain to financial services</strong>
1. <strong>Issues in the domain</strong>
2. <strong>Emerging solutions in BFSI</strong>
3. <strong>Retrospective</strong>
5. <strong>Applying AI and blockchain to other domains</strong>
1. <strong>Applying AI and blockchain to knowledge management</strong>
1. <strong>Issues in the domain</strong>
2. Emerging solutions in knowledge <span>management</span>
3. <strong>Retrospective</strong>
2. <strong>Applying AI and blockchain to real estate</strong>
1. <strong>Issues in the domain</strong>
2. <strong>Emerging solutions in real estate</strong>
3. <strong>Retrospective</strong>
3. <strong>Applying AI and blockchain to media</strong>
1. <strong>Issues in the domain</strong>
2. <strong>Emerging solutions in media</strong>
3. <strong>Retrospective</strong>
4. <strong>Applying AI and blockchain to identity management</strong>
1. <strong>Issues in the domain</strong>
2. <strong>Emerging solutions in identity management</strong>
3. <strong>Retrospective</strong>
5. <strong>Applying AI and blockchain to royalty management</strong>
1. <strong>Issues in the domain</strong>
2. <strong>Emerging solutions in royalty management</strong>
3. <strong>Retrospective</strong>
6. <strong>Applying AI and blockchain to information security</strong>
1. <strong>Issues in the domain</strong>
2. <strong>Emerging solutions in information security</strong>
3. <strong>Retrospective</strong>
7. <strong>Applying AI and blockchain to document management</strong>
1. <strong>Issues in the domain</strong>
2. <strong>Emerging solutions in document management</strong>
3. <strong>Retrospective</strong>
6. <strong>Summary</strong>
4. AI- and Blockchain-Driven Databases
1. Technical requirements
2. Centralized versus distributed data
