Digital Fluency: Understanding the Basics of Artificial Intelligence, Blockchain Technology, Quantum Computing, and Their Applications for Digital Transformation

Contents
About the Author
Introduction
Chapter 1: Digitalization and Digital Transformation
	1.1 Historical Business Transformations
	1.2 Innovation and Disruption Theory
	1.3 The Digital Ecosystem
		1.3.1 Major Driving Forces
			Major Driving Forces: Complexity
			Major Driving Forces: Agility and Flexibility
			Major Driving Forces: Cybersecurity
			Major Driving Forces: Efficiency
			Major Driving Forces: Automation
			Major Driving Forces: Sustainability
			Major Driving Forces: Connectivity
			Major Driving Forces: Compliance
		1.3.2 Digital Transformation Strategy
		1.3.3 Digital Key Technologies
		1.3.4 Innovation Models of Google, Amazon & Co.
	1.4 Classical Data Processing
		1.4.1 The Digital Code
		1.4.2 Principles of Operation
		1.4.3 Computers and Other Digital Devices
			1st Computer Generation: Mechanical Switches
			2nd Computer Generation: Electromechanical Relays
			3rd Computer Generation: Vacuum Tubes
			4th Computer Generation: Transistors
			5th Computer Generation: Multicores
	1.5 Key Points
	1.6 Further Reading
	1.7 Online Classes
	1.8 References
Chapter 2: Quantum Computing
	2.1 Setting the Quantum Computing Scene
	2.2 The Strange World of Quantum Mechanics
		2.2.1 Spooky Quantum Reality
		2.2.2 How Quantum Computers Operate
		2.2.3 The Fussy Search for the Perfect Qubit
			Decoherence: Spin-Flip Process
			Decoherence: Energy Relaxation Process
			Decoherence: The Technical Solution
			Types of Qubits: Trapped Ion Qubits
			Types of Qubits: Electron Spin Qubits
			Types of Qubits: Superconducting Qubits
	2.3 Quantum Computing Today
		2.3.1 Commercially Available Systems
			Commercially Available Systems: Quantum Annealer
			Commercially Available Systems: Quantum Simulator
			Commercially Available Systems: Universal Quantum Computer
		2.3.2 Current Business Applications
			Current Business Applications: Simulation, Modeling, and Optimization
			Current Business Applications: Cybersecurity
			Current Business Applications: Quantum Cryptography
		2.3.3 Next Challenges
	2.4 Key Points
	2.5 Quantum Computing Framework
	2.6 Further Reading
	2.7 References
Chapter 3: Blockchain Technology
	3.1 Setting the Blockchain Scene
		3.1.1 The Role of Transactions and Money in History
		3.1.2 Basic Functions of Money in Society
	3.2 Blockchain Fundamentals
		3.2.1 Decentralization and the Arrival of Trust
		3.2.2 The Immutable Data Structure
		3.2.3 Digital Value Transfer
		3.2.4 The Authorization of Transactions by Digital Signatures
		3.2.5 Deploying Trust by Consensus and Mining
		3.2.6 Smart Business Contracts
	3.3 Blockchain Technology Today
		3.3.1 Implementation Challenges for Enterprises
		3.3.2 Current Business Applications
			Current Business Applications: Cryptocurrencies and Fundraising
			Current Business Applications: Trading, Payment, and Sharing Services
			Current Business Applications: Supply Chain Management and Logistics
			Current Business Applications: Anti-fraud of Consumer Goods
			Current Business Applications: Energy Commodities Platform
			Current Business Applications: Governmental Services
			Current Business Applications: Blockchain Consortia
		3.3.3 Further Use Cases
			Potential Use Cases: Governmental Services
			Further Use Cases: Law
			Further Use Cases: Healthcare
	3.4 Key Points
	3.5 Blockchain Technology Framework
	3.6 Further Reading
	3.7 References
Chapter 4: Artificial Intelligence
	4.1 Setting the Artificial Intelligence Scene
		4.1.1 The Symbiosis of Neurobiology and Information Theory
		4.1.2 The Conference That Started It All
		4.1.3 IBM’s Legendary Projects Deep Blue and Watson
	4.2 Central Ideas Behind Artificial Intelligence
		4.2.1 The Cost Function
		4.2.2 Minimization of the Cost Function
	4.3 The Five Categories of Learning
		4.3.1 Supervised Learning
			Supervised Learning: Regression
			Supervised Learning: Classification
		4.3.2 Unsupervised Learning
			Unsupervised Learning: Clustering
			Unsupervised Learning: Association
			Unsupervised Learning: Dimensionality Reduction
		4.3.3 Deep Learning
			Deep Learning: Artificial Neural Networks
			Deep Learning: Convolutional Neural Networks
			Deep Learning: Recurrent Neural Networks
			Deep Learning: Generative Adversarial Neural Networks
			Deep Learning: Recommender Systems
			Deep Learning: Auto Encoders
		4.3.4 Ensemble Methods
		4.3.5 Reinforcement Learning
	4.4 Top Use Cases and Business Applications
		4.4.1 AI Chips
		4.4.2 Computer Vision
			Computer Vision: Shopping Technology
			Computer Vision: Vision-Guided Robotics
			Computer Vision: Autonomous Driving
		4.4.3 Healthcare
		4.4.4 Natural Language Processing
		4.4.5 Energy Efficiency
		4.4.6 Drug Discovery
		4.4.7 Financial Services and Insurance
			Financial Services and Insurance: Cybersecurity
			Financial Services and Insurance: News Analytics and Intelligent Pricing
	4.5 Key Points
	4.6 Artificial Intelligence Framework
	4.7 Further Reading
	4.8 References
Chapter 5: Your Digital Action Plan
	5.1 Envision a Digital Strategy
		5.1.1 Envision a Digital Strategy: Develop a Digital Business Model
		5.1.2 Envision a Digital Strategy: Derive a Digital Operating Model
	5.2 Select the Right Technology Stack
	5.3 Digitize the Core
		5.3.1 Digitize the Core: Create a Central Database
		5.3.2 Digitize the Core: Develop a Software Tools Library
	5.4 Identify Pilot Projects
	5.5 Empower Management and Employees
	5.6 Shape the Organization and Structure
		5.6.1 Shape the Organization and Structure: Format Agile Project Teams
		5.6.2 Shape the Organization and Structure: Establish a Two-Speed IT
	5.7 Establish an Open Innovation Culture
		5.7.1 Establish an Open Innovation Culture: Adopt Agile at Scale
		5.7.2 Establish an Open Innovation Culture: Implement Design Thinking
	5.8 Leverage the Ecosystem
	5.9 Key Points
	5.10 Further Reading
	5.11 References
Glossary
Index