Game Changers—Artificial Intelligence: What You Need to Know : Understanding the Impact and Applications of Artificial Intelligence, Machine Learning, and Deep Learning
It is difficult to understand what is happening in the field of artificial intelligence (AI). New developments seem to happen weekly, and companies use different words to describe their products. The terms artificial intelligence, cognitive intelligence, autonomous machines, and machine learning are all thrown around. This research brings clarity to the complex AI landscape and explores recent breakthroughs in a technique called deep learning, explaining how it is making progress in AI challenges such as language, vision, and motion. Finally, the research takes a broad look at the impact of AI in the enterprise, specifically the energy, financial services, healthcare, manufacturing, and transportation industries.
Artificial intelligence (AI) is a vision, a goal, and a set of technologies. Its breadth and complexity make it a difficult subject to understand and explain. Adding to the confusion is the number and variety of terms used. Machine learning (ML), deep learning, neural networks, and predictive analytics describe different AI approaches. Other marketing terms such as cognitive computing or autonomous machines further muddy the water.
- The term artificial intelligence is often used to refer to artificial general intelligence (AGI). This is a type of AI that can transfer learning from one domain to another. AGI will be able to apply learning techniques to gain new skills without pre-programming. This AI is also called 'strong AI' and would be indistinguishable from a human mind.
- Artificial super-intelligence (ASI) is the second type of AI. This is an extension of AGI, and would be superior to humans in every domain—from logic to creativity and from social intelligence to persuasion. It is this type of AI that forms the basis of media and cultural stories about the future of AI and robotics.
- The most ground-breaking developments are occurring in the third category: artificial narrow intelligence (ANI). ANI systems have the ability to complete pre-defined and limited tasks. ANI is already part of software such as Google Search, Netflix, and Apple Siri. Once ANI algorithms are embedded in software, the threshold for what constitutes ANI shifts higher.
- ML is the AI approach that gives machines the ability to learn from data. Other AI approaches, symbolic and statistical, use a different rule-based approach.
Table Of Contents
Game ChangersâArtificial Intelligence: What You Need to KnowÂ 1 EXECUTIVE SUMMARY
Executive Summary 1. Key Findings 2. Key Findings
2 WHY EXPLORE ARTIFICIAL INTELLIGENCE?
Why Explore Artificial Intelligence? 1. Why Explore Artificial Intelligence? 2. Identification of 30 Key Technology Trends 3. Scoring Technology Trends by Disruptive Potential 4. Scoring Technology Trends by Disruptive Potential 5. Scoring Technology Trends by Disruptive Potential
Machine Learning 1. Machine Learning Overview 2. Drivers in the Development of Machine Learning 3. Restraints in the Development of Machine Learning 4. Most Important RestraintâThe End of Moore's Law 5. Most Important RestraintâThe End of Moore's Law 6. Most Important RestraintâThe End of Moore's Law 7. Machine Learning by Learning Style 8. Machine Learning by Function 9. Key Machine Learning Algorithm Classes by Function 10. Machine Learning Business Models
5 NEURAL NETWORKS
Neural Networks 1. Neural Networks Overview 2. Neural Networks by Class 3. Neural Networks by Class
6 WHAT IS DEEP LEARNING?
What is Deep Learning? 1. Deep Learning Overview 2. Key Deep Neural Network Architectures 3. Key Deep Neural Network Architectures 4. Key Deep Neural Network Architectures 5. Leaders in Deep LearningâB2C Business Model 6. Leaders in Deep LearningâB2B Business Model 7. Deep Learning Applications
7 APPLICATIONSâTEXT NATURAL LANGUAGE PROCESSING
ApplicationsâText Natural Language Processing 1. Text Natural Language Processing Overview 2. Leaders in Text Natural Language Processing
8 APPLICATIONSâAUDIO NATURAL LANGUAGE PROCESSING
ApplicationsâAudio Natural Language Processing 1. Audio Natural Language Processing Overview 2. Leaders in Audio Natural Language Processing
9 APPLICATIONSâCOMPUTER VISION
ApplicationsâComputer Vision 1. Computer Vision 2. Leaders in Machine Vision
10 THE ENTERPRISE
The Enterprise 1. Machine Learning Will be a Part of Every Function in Every Business 2. Machine Learning Will be a Part of Every Function in Every Business 3. Machine Learning Will be a Part of Every Function in Every Business 4. Machine Learning for Sales, Marketing, and Personal Assistants 5. Machine Learning for Communication, HR, and Security 6. Machine Learning for Customer Service, Finance, and Productivity 7. What Happens When Jobs Run Out?
11 ENERGY and NATURAL RESOURCES INDUSTRY
Energy and Natural Resources Industry 1. Trend 1âDistributed Energy Resources 2. Trend 2âSmart Grid 3. Trend 3âDigital Oilfield (DOF)
12 FINANCIAL SERVICES INDUSTRY
Financial Services Industry 1. Trend 1âPayments and Loyalty 2. Trend 2âRetail Banking Data Mining 3. Trend 3âBlockchains
13 HEALTHCARE INDUSTRY
Healthcare Industry 1. Trend 1âDigital Hospital 2. Trend 2âmHealth Services 3. Trend 3âPersonalised Medicine
The Frost and Sullivan Story 1. The Frost and Sullivan Story 2. Value PropositionâFuture of Your Company and Career 3. Global Perspective 4. Industry Convergence 5. 360Âº Research Perspective 6. Implementation Excellence 7. Our Blue Ocean Strategy