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- Herausgeber: John Wiley & Sons
- Kategorie: Fachliteratur
- Sprache: Englisch
Cyber-solutions to real-world business problems
Artificial Intelligence in Practice is a fascinating look into how companies use AI and machine learning to solve problems. Presenting 50 case studies of actual situations, this book demonstrates practical applications to issues faced by businesses around the globe. The rapidly evolving field of artificial intelligence has expanded beyond research labs and computer science departments and made its way into the mainstream business environment. Artificial intelligence and machine learning are cited as the most important modern business trends to drive success. It is used in areas ranging from banking and finance to social media and marketing. This technology continues to provide innovative solutions to businesses of all sizes, sectors and industries. This engaging and topical book explores a wide range of cases illustrating how businesses use AI to boost performance, drive efficiency, analyse market preferences and many others.
Best-selling author and renowned AI expert Bernard Marr reveals how machine learning technology is transforming the way companies conduct business. This detailed examination provides an overview of each company, describes the specific problem and explains how AI facilitates resolution. Each case study provides a comprehensive overview, including some technical details as well as key learning summaries:
- Understand how specific business problems are addressed by innovative machine learning methods
- Explore how current artificial intelligence applications improve performance and increase efficiency in various situations
- Expand your knowledge of recent AI advancements in technology
- Gain insight on the future of AI and its increasing role in business and industry
Artificial Intelligence in Practice: How 50 Successful Companies Used Artificial Intelligence to Solve Problems is an insightful and informative exploration of the transformative power of technology in 21st century commerce.
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Seitenzahl: 338
Veröffentlichungsjahr: 2019
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Artificial Intelligence in Practice
How 50 SuccessfulCompanies Used ArtificialIntelligence to SolveProblems
BERNARD MARRwith MATT WARD
This edition first published 2019© 2019 Bernard Marr
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ISBN 978-1-119-54821-8 ISBN 978-1-119-54896-6 (ePDF)ISBN 978-1-119-54898-0 (ePub)
10987654321Cover Design: WileyCover Image: © mattjeacock/iStock.com
Set in 11/14pt MinionPro Light by Aptara, New Delhi, India
CONTENTS
Cover
Introduction
The Most Powerful Technology Of Mankind
What's Artificial Intelligence? The Rise Of Deep Machine Learning
Artificial Intelligence Opportunities In Business
The Strategic Use Of Artificial Intelligence In Business
Artificial Intelligence In Practice
Notes
Part 1 Artificial Intelligence Trailblazers
1 Alibaba: Using Artificial Intelligence To Power The Retail And Business-To-Business Services Of The Future
How Does Alibaba Use Artificial Intelligence?
Automated Sales Copy
Cloud Services
Smart Cities
Smart Farming
Academy For Discovery, Adventure, Momentum And Outlook
Key Challenges, Learning Points And Takeaways
Notes
2 Alphabet and Google: Maximizing The Potential Of Artificial Intelligence
How Does Alphabet Use Artificial Intelligence?
Artificial Intelligence Personal Assistants
Language Translation
Self-Driving Cars
Captioning Millions Of Videos
Diagnosing Disease
Google Brain
Deep Mind
Key Challenges, Learning Points And Takeaways
Notes
3 Amazon: Using Deep Learning To Drive Business Performance
How Does Amazon Use Artificial Intelligence?
Amazon Alexa
Amazon's Artificial Intelligence Flywheel
Amazon Web Services
Amazon Prime Air
Key Challenges, Learning Points And Takeaways
Notes
4 Apple: Integrating AI Into Products And Protecting User Privacy
How Does Apple Use Artificial Intelligence?
Smarter Apps
Natural Language Processing
Key Challenges, Learning Points And Takeaways
Notes
5 Baidu: Machine Learning For Search Engines And Autonomous Cars
How Does Baidu Use Artificial Intelligence?
Self-Driving Cars
Mobile Artificial Intelligence
Real-Time Translation
Key Challenges, Learning Points And Takeaways
Notes
6 Facebook: Using Artificial Intelligence To Improve Social Media Services
How Does Facebook Use Artificial Intelligence?
Monitoring Content
Facial Recognition
Understanding Text
Suicide Prevention
FBLearner Flow
Facebook AI Research
Key Challenges, Learning Points And Takeaways
Notes
7 IBM: Cognitive Computing Helps Machines Debate With Humans
How Does IBM Use Artificial Intelligence?
Project Debater
Key Challenges, Learning Points And Takeaways
Notes
8 JD.com: Automating Retail With Artificial Intelligence
What Does JD.com Use Artificial Intelligence For?
Automated Deliveries By Air And Road
Facial Recognition Technology
Smart Fridges
Smart Shops
Key Challenges, Learning Points And Takeaways
Notes
9 Microsoft: Making Artificial Intelligence Part Of The Fabric Of Everyday Life
How Does Microsoft Use Artificial Intelligence?
Underwater Data Centers
Who Uses Microsoft Artificial Intelligence?
Bonsai
Key Challenges, Learning Points And Takeaways
Notes
10 Tencent: Using Artificial Intelligence To Power WeChat And Healthcare
How Does Tencent Use Artificial Intelligence?
Robots And Autonomy
Medical Technology
Tencent Miying – Artificial Intelligence In Hospitals
Key Challenges, Learning Points And Takeaways
Notes
Part 2 Retail, Consumer Goods and Food and Beverage Companies
11 Burberry: Using Artificial Intelligence To Sell Luxury
What Problem Is Artificial Intelligence Helping To Solve?
How Is Artificial Intelligence Used In Practice?
What Technology, Tools And Data Were Used?
What Were The Results?
Key Challenges, Learning Points And Takeaways
Notes
12 Coca-Cola: Using Artificial Intelligence To Stay At The Top Of The Soft Drinks Market
What Problem Is Artificial Intelligence Helping To Solve?
How Is Artificial Intelligence Used In Practice?
What Technology, Tools And Data Were Used?
What Were The Results?
Key Challenges, Learning Points And Takeaways
Notes
13 Domino's: Using Artificial Intelligence To Serve Up Hundreds Of Thousands Of Pizzas Every Day
What Problems Is Artificial Intelligence Helping To Solve?
How Is Artificial Intelligence Used In Practice?
What Technology, Tools And Data Were Used?
What Were The Results?
Key Challenges, Learning Points And Takeaways
Notes
14 Kimberly-Clark: Using AI To Make Sense Of Customer Data
What Problems Is Artificial Intelligence Helping To Solve?
How Is Artificial Intelligence Used In Practice?
What Technology, Tools And Data Were Used?
What Were The Results?
Key Challenges, Learning Points And Takeaways
Notes
15 McDonald's: Using Robots And Artificial Intelligence To Automate Processes
What Problem Is Artificial Intelligence Helping To Solve?
How Is Artificial Intelligence Used In Practice?
What Technology, Tools And Data Were Used?
What Were The Results?
Key Challenges, Learning Points And Takeaways
Notes
16 Samsung: Automating The Home And Workplace With Artificial Intelligence
What Problems Is Artificial Intelligence Helping To Solve?
How Is Artificial Intelligence Used In Practice?
What Technology, Tools And Data Were Used?
What Were The Results?
Key Challenges, Learning Points And Takeaways
Notes
17 Starbucks: Using Artificial Intelligence To Sell Millions Of Coffees Every Day
What Problems Is Artificial Intelligence Helping To Solve?
How Is Artificial Intelligence Used In Practice?
What Key Tools, Technology And Data Were Used?
What Were The Results?
Key Challenges, Learning Points And Takeaways
Notes
18 Stitch Fix: Combining The Power Of Artificial Intelligence And Humans To Disrupt Fashion Retail
What Problems Is Artificial Intelligence Helping To Solve?
How Is Artificial Intelligence Used In Practice?
What Technology, Tools And Data Were Used?
What Were The Results?
Key Challenges, Learning Points And Takeaways
Notes
19 Unilever: Using Artificial Intelligence To Streamline Recruiting And Onboarding
What Problem Is Artificial Intelligence Helping To Solve?
How Is Artificial Intelligence Used In Practice?
What Technology, Tools And Data Were Used?
What Were The Results?
Key Challenges, Learning Points And Takeaways
Notes
20 Walmart: Using Artificial Intelligence To Keep Shelves Stacked And Customers Happy
What Problem Is Artificial Intelligence Helping To Solve?
How Is Artificial Intelligence Used In Practice?
What Technology, Tools And Data Were Used
What Were The Results?
Key Challenges, Learning Points And Takeaways
Notes
Part 3 Media, Entertainment and Telecom Companies
21 The Walt Disney Company: Using Artificial Intelligence To Make Magical Memories
What Problem Is Artificial Intelligence Used To Solve?
How Is Artificial Intelligence Used In Practice?
What Technology, Tools And Data Are Used?
What Were The Results?
Key Challenges, Learning Points And Takeaways
Notes
22 Instagram: Using Artificial Intelligence To Tackle Online Bullying
What Problems Is Artificial Intelligence Helping To Solve?
How Is Artificial Intelligence Used In Practice?
What Technology, Tools And Data Are Used?
What Were The Results?
Key Challenges, Learning Points And Takeaways
Notes
23 LinkedIn: Using Artificial Intelligence To Solve The Skills Crisis
What Problem Is Artificial Intelligence Helping To Solve?
How Is Artificial Intelligence Used In Practice?
What Technology, Tools And Data Were Used?
What Were The Results?
Key Challenges, Learning Points And Takeaways
Notes
24 Netflix: Using Artificial Intelligence To Give Us A Better TV Experience
What Problem Is Artificial Intelligence Helping To Solve?
How Is Artificial Intelligence Used In Practice?
What Technology, Tools And Data Were Used?
What Were The Results?
Key Challenges, Learning Points And Takeaways
Notes
25 Press Association: Using Artificial Intelligence To Cover Local News Stories
What Problems Is Artificial Intelligence Helping To Solve?
How Is Artificial Intelligence Used In Practice?
What Technology, Tools And Data Were Used?
What Are The Results?
Key Challenges, Learning Points And Takeaways
Notes
26 Spotify: Using Artificial Intelligence To Find New Music You Will Love
What Problems Is Artificial Intelligence Helping To Solve?
How Is Artificial Intelligence Used In Practice?
What Technology, Tools And Data Were Used?
What Were The Results?
Key Challenges, Learning Points And Takeaways
Notes
27 Telefonica: Using Artificial Intelligence To Connect The Unconnected
What Problem Is Artificial Intelligence Trying To Solve?
How Is Artificial Intelligence Used In Practice?
What Technology, Tools And Data Were Used?
What Were The Results?
Key Challenges, Learning Points And Takeaways
Notes
28 Twitter: Using Artificial Intelligence To Fight Fake News And Spambots
What Problem Is Artificial Intelligence Helping To Solve?
How Is Artificial Intelligence Used In Practice?
What Technology, Tools And Data Are Used?
What Were The Results?
Key Challenges, Learning Points And Takeaways
Notes
29 Verizon: Using Machine Learning To Assess Service Quality
What Problem Is Artificial Intelligence Helping To Solve?
How Is Artificial Intelligence Used In Practice?
What Technology, Tools And Data Were Used?
What Were The Results?
Key Challenges, Learning Points And Takeaways
Notes
30 Viacom: Using Artificial Intelligence To Stream Videos Faster And Improve Customer Experience
What Problem Is Artificial Intelligence Helping To Solve?
How Is Artificial Intelligence Used In Practice?
What Technology, Tools And Data Were Used?
What Were The Results?
Key Challenges, Learning Points And Takeaways
Notes
Part 4 Services, Financial and Healthcare Companies
31 American Express: Using Artificial Intelligence To Detect Fraud And Improve Customer Experience
What Problem Is Artificial Intelligence Helping To Solve?
How Is Artificial Intelligence Used In Practice?
What Technology, Tools And Data Were Used?
What Were The Results?
Key Challenges, Learning Points And Takeaways
Notes
32 Elsevier: Using Artificial Intelligence To Improve Medical Decisions And Scientific Research
What Problem Is Artificial Intelligence Helping To Solve?
How Is Artificial Intelligence Used In Practice?
What Tools, Technology And Data Were Used?
What Were The Results?
Key Challenges, Learning Points And Takeaways
Notes
33 Entrupy: Using Artificial Intelligence To Combat The $450 Billion Counterfeit Industry
What Problem Is Artificial Intelligence Helping To Solve?
How Is Artificial Intelligence Used In Practice?
What Technology, Tools And Data Were Used?
What Were The Results?
Key Challenges, Learning Points And Takeaways
Notes
34 Experian: Using Artificial Intelligence To Make Mortgages Simpler
What Problem Is Artificial Intelligence Helping To Solve?
How Is Artificial Intelligence Used In Practice?
What Technology, Tools And Data Were Used?
What Were The Results?
Key Challenges, Learning Points And Takeaways
Notes
35 Harley-Davidson: Using Artificial Intelligence To Increase Sales
What Problem Is Artificial Intelligence Helping To Solve?
How Is Artificial Intelligence Used In Practice?
What Technology, Tools And Data Were Used?
What Were The Results?
Key Challenges, Learning Points And Takeaways
Notes
36 Hopper: Using Artificial Intelligence To Travel For Less
What Problem Is Artificial Intelligence Helping To Solve
How Is Artificial Intelligence Used In Practice?
What Technology, Tools And Data Were Used?
What Were The Results?
Key Challenges, Learning Points And Takeaways
Notes
37 Infervision: Using Artificial Intelligence To Detect Cancer And Strokes
What Problem Is Artificial Intelligence Helping To Solve?
How Is Artificial Intelligence Used In Practice?
What Technology, Tools And Data Were Used?
What Were The Results?
Key Challenges, Learning Points And Takeaways
Notes
38 Mastercard: Using Artificial Intelligence To Cut Down The “False Declines” That Cost Businesses Billions Each Year
What Problem Is Artificial Intelligence Helping To Solve?
How Is Artificial Intelligence Used In Practice?
What Technology, Tools And Data Were Used?
What Were The Results?
Key Challenges, Learning Points And Takeaways
Notes
39 Salesforce: How Artificial Intelligence Helps Businesses Understand Their Customers
What Problem Is Artificial Intelligence Helping To Solve?
How Is Artificial Intelligence Used In Practice?
What Technology, Tools And Data Were Used?
What Were The Results?
Key Challenges, Learning Points And Takeaways
Notes
40 Uber: Using Artificial Intelligence To Do Everything
What Problems Is Artificial Intelligence Helping To Solve?
How Is Artificial Intelligence Used In Practice?
What Technology, Tools And Data Were Used?
What Were The Results?
Key Challenges, Learning Points And Takeaways
Notes
Part 5 Manufacturing, Automotive, Aerospace and Industry 4.0 Companies
41 BMW: Using Artificial Intelligence To Build And Drive The Cars Of Tomorrow
What Problems Is Artificial Intelligence Helping To Solve?
How Is Artificial Intelligence Used In Practice?
What Were The Results?
What Technology, Tools And Data Were Used?
Key Challenges, Learning Points And Takeaways
Sources
42 GE: Using Artificial Intelligence To Build The Internet Of Energy
What Problem Is Artificial Intelligence Helping To Solve?
How Is Artificial Intelligence Used In Practice?
What Technology, Tools And Data Were Used?
What Were The Results?
Key Challenges, Learning Points And Takeaways
Notes
43 John Deere: Using Artificial Intelligence To Reduce Pesticide Pollution In Agriculture
What Problem Is Artificial Intelligence Helping To Solve?
How Is Artificial Intelligence Used In Practice?
What Technology, Tools And Data Were Used?
What Are The Results?
Key Challenges, Learning Points And Takeaways
Notes
44 KONE: Using Artificial Intelligence To Move Millions Of People Every Day
What Problems Is Artificial Intelligence Helping To Solve?
How Is Artificial Intelligence Used In Practice?
What Technology, Tools And Data Are Used?
What Were The Results?
Key Challenges, Learning Points And Takeaways
Sources
45 Daimler AG: From Luxury Personal Cars To Passenger Drones
What Problems Is Artificial Intelligence Helping To Solve?
How Is Artificial Intelligence Used In Practice?
What Were The Results?
What Technology, Tools And Data Were Used?
Key Challenges, Learning Points And Takeaways
Sources
46 NASA: Using Artificial Intelligence To Explore Space And Distant Worlds
What Problem Is Artificial Intelligence Helping To Solve?
How Is Artificial Intelligence Used In Practice?
What Were The Results?
What Technology, Tools And Data Were Used?
Key Challenges, Learning Points And Takeaways
Sources
47 Shell: Using Artificial Intelligence To Tackle The Energy Transition
What Problem Is Artificial Intelligence Helping To Solve?
How Is Artificial Intelligence Used In Practice?
What Technology, Tools And Data Were Used?
What Were The Results?
Key Challenges, Learning Points And Takeaways
Notes
48 Siemens: Using Artificial Intelligence And Analytics To Build The Internet Of Trains
What Problems Is Artificial Intelligence Helping To Solve?
How Is Artificial Intelligence Used In Practice?
What Technology, Tools And Data Were Used?
What Were The Results?
Key Challenges, Learning Points And Takeaways
Notes
49 Tesla: Using Artificial Intelligence To Build Intelligent Cars
What Problems Is Artificial Intelligence Helping To Solve?
How Is Artificial Intelligence Used In Practice?
What Are The Results?
What Technology, Tools And Data Were Used?
Key Challenges, Learning Points And Takeaways
Sources
50 Volvo: Using Machine Learning To Build The World's Safest Cars
What Problems Is Artificial Intelligence Helping To Solve?
How Is Artificial Intelligence Used In Practice?
What Technology, Tools And Data Were Used?
What Were The Results?
Key Challenges, Learning Points And Takeaways
Sources
Part 6 Final Words and Artificial Intelligence Challenges
51 Final Words And Artificial Intelligence Challenges
Approach Artificial Intelligence Strategically
Develop Artificial Intelligence Awareness And Skills
Secure The Right Data
Update Your Technology And IT Systems
Use Artificial Intelligence Ethically
Prepare Yourself For Artificial Intelligence Disruption
Connect To Keep The Conversation Going
Notes
About the Author
Acknowledgments
Index
WILEY END USER LICENSE AGREEMENT
Guide
Cover
Table of Contents
Introduction
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E1
Introduction
One thing is very clear, artificial intelligence (AI) is going to change our world forever. And the change is likely to be more profound than most people realize today. No matter what job you are in, no matter what business or industry you work in, AI is going to augment, if not completely transform, it.
AI is giving machines the power to see, hear, taste, smell, touch, talk, walk, fly and learn. This in turn means businesses can develop completely new ways to interact with their customers, offer them much more intelligent products and service experiences, automate processes and boost business success.
Having said that, we also know there is a massive amount of hype and confusion about AI. Some see it as the ultimate threat to our civilization, while others believe AI is the savior that's going to solve humanity's biggest challenges, from tackling climate change to curing cancer. The aim of this book is to cut through the hype and scare-mongering, and provide a cutting-edge picture of how AI is actually being used by businesses today.
By sharing some of the latest and most innovative real world use cases from across many industries, we hope to demystify AI while at the same time inspiring you to see the immense opportunities AI is offering. We have written this book for anyone who would like to better understand AI and have therefore tried hard to keep the technical details to a level anyone can understand. At the same time, we have attempted to include just enough techie stuff to make it informative for people who already work in the field of AI.
In this book, you will of course gain insights into how some of the AI giants such as Google, Facebook, Alibaba, Baidu, Microsoft, Amazon and Tencent use it, but you will also learn how many traditional incumbent companies across most industries as well as innovative start-ups use AI. Our hope is that this will provide a realistic picture of the current state of the art: where the AI trailblazers are rolling full steam ahead, leaving many traditional businesses behind in the starting blocks; where traditional businesses are working hard at reinventing themselves and using AI to stay competitive; and where start-ups are using AI to challenge both the AI trailblazers and traditional businesses.
The Most Powerful Technology Of Mankind
AI is the most powerful technology available to mankind today and the biggest mistake anyone can make is to ignore it. Leaders of nations and businesses alike are seeing both the magnitude of opportunities AI brings and the risks of being left behind in the AI goldrush.
In the United States, the White House has released numerous policy documents that emphasize the strategic significance of AI. In 2016, under President Barack Obama, the White House issued the first report “Preparing for the Future of Artificial Intelligence”,1 which laid the foundation for a US AI strategy. In 2018, under Donald Trump, following an AI summit at the White House, the administration issued “Artificial Intelligence for the American People”2 in which President Trump states: “We're on the verge of new technological revolutions that could improve virtually every aspect of our lives, create vast new wealth for American workers and families, and open up bold, new frontiers in science, medicine, and communication.” The goal of the US Administration is to maintain American leadership in AI by accelerating AI research and deployment, and by training the future American workforce to take full advantage of the benefits of AI.3
Russia's President Putin said: “Artificial intelligence is the future, not only for Russia, but for all humankind. […] Whoever becomes the leader in this sphere will become the ruler of the world.”4 China has arguably developed the most ambitious plan to make use of AI with a goal of becoming the world leader in AI by 2030.5 In Europe, the European Commission released its AI strategy in 2018, in which it states: “Like the steam engine or electricity in the past, AI is transforming our world, our society and our industry. Growth in computing power, availability of data and progress in algorithms have turned AI into one of the most strategic technologies of the 21st century. The stakes could not be higher. The way we approach AI will define the world we live in.”6
Business leaders agree. Amazon CEO Jeff Bezos believes we have entered the “golden age” of AI that allows us to solve problems that once were the realm of sci-fi.7 Google co-founder Sergey Brin said: “The new spring in AI is the most significant development in computing in my lifetime”8 and Microsoft CEO Satya Nadella calls AI the “defining technology of our times”.9 The founder and executive chairman of the World Economic Forum, Klaus Schwab, together with many others, believes that AI (especially when combined with all other technological innovations) has triggered a fourth industrial revolution that is going to transform all parts of business and society.10
What's Artificial Intelligence? The Rise Of Deep Machine Learning
AI is nothing new and nothing magical. The first developments in AI date back to the 1950s. AI refers to the ability of computer systems or machines to display intelligent behavior that allows them to act and learn autonomously. In its most basic form, AI takes data, applies some calculation rules (or algorithms) to the data and then makes decisions or predicts outcomes.
For example, the data could be images of handwritten words, letters or numbers. The algorithm would be a computer program written by a human that contains rules such as the common shapes of each letter and spacing between words. This then allows a computer to analyze scanned images of handwritten text, apply the rules and make predictions about which letters, numbers and words it contains, enabling machines to recognize handwriting. This type of AI has been used, for example, by the US Postal Services to automatically read addresses on letters from as early as 1997. For narrow applications this kind of AI worked well.
This rule-based AI runs into difficulties when tasks are more complex or when we humans can't easily explain the rules and therefore can't program them into algorithms. Speaking our language, walking around and recognizing a friend in a crowd are all examples of skills that we have acquired through experience but for which we can't easily explain the rules.
We have learned those skills via a network of neurons in our brain that have been programmed to, for example, recognize a face by looking at the face from lots of different angles over a period of time, or we have learned how to walk and talk through trial and error. In modern AI, we basically replicate this process using artificial neural networks and instead of having humans programming the rules, we let the machines create the rules by themselves, similarly to how our brain learns from experience. We refer to this as machine learning.
In machine learning, we train AI with data by, for example, feeding it thousands of images that either contain human faces or don't contain human faces. The computer then takes in the information and creates its own algorithm either completely independently (unsupervised machine learning) or with help from humans (supervised or semi-supervised machine learning). When machine learning uses multiple layers of artificial neural networks to learn from training data (which makes them more powerful), we refer to it as deep learning.
Deep learning has given us many of the recent advances in AI, such as the ability for computers to see and recognize what or who is in an image or in a video (machine vision). Or it has given machines the ability to understand and reproduce written text or spoken words, which we call natural language processing and see in website chatbots or home smart speakers like Amazon's Echo.
There are two key reasons why deep learning is thriving today:
We have data: Data is the raw material that is fuelling AI and in today's big data world we are generating more data than ever before. The digitization of our world means that almost everything we do leaves a data trail and we are increasingly surrounded by smart devices that collect and transmit data. This is causing exponential growth in the volume and types of data we can now use to train AI.
We have computing power: We now have the ability to store and process vast amounts of data. Breakthroughs in cloud computing allow businesses to cheaply store almost unlimited volumes of data and use distributed computing to analyze big data in near real time. What's more, advances in chip technology mean AI computations can now be performed on devices such as smartphones or other smart connected devices. We refer to this as edge computing on Internet of Things devices.
We humans continuously learn and improve through experience. This “learning by doing” approach can now also be replicated by machine learning algorithms via reinforcement learning. Similarly to how toddlers learn to walk by adjusting actions based on the outcomes they experience, such as taking a smaller step if the previous broad step made them fall, AI uses reinforcement learning algorithms to determine the ideal behavior based upon feedback from the environment. Reinforcement learning gives machines (for example, robots) the ability to walk, drive or fly autonomously. Many leading-edge applications of machine learning combine deep and reinforcement learning techniques.
If you would like to learn more about any of these fascinating topics, head to www.bernardmarr.com where you can find hundreds of articles and videos explaining and discussing everything you need to know about AI and machine learning.
Artificial Intelligence Opportunities In Business
There are three key use cases for AI in business, which can overlap to some degree, but help to segment the opportunities. Businesses can use AI to: (1) change the way they understand and interact with customers, (2) offer more intelligent products and services, and (3) improve and automate business processes.
Customers: AI can help businesses better understand who their customers are, predict what products or services customers are likely to want, predict market trends and demands and provide more personalized interactions with customers. In this book, we will look at companies like Stitch Fix and Facebook, which use AI to really get to know their customers.
Products and services: AI can help businesses create more intelligent products and services to offer to their customers. Customers want more intelligent products such as smarter phones, smarter cars and smarter home devices. In this book, we will look at how Apple, Samsung and car companies such as Tesla and Volvo use AI to create smarter products and we explore how others like Spotify, Disney or Uber use AI to deliver more intelligent services to their customers.
Automate processes: AI can improve and help automate business processes. In this book, we will look at examples such as JD.com that is using autonomous drones, automated fulfilment centers and delivery robots to transform its retail operations. We will also look at how AI can automate medical diagnosis in the Infervision and Elsevier case studies, and even the pizza quality checks at Domino's.
The Strategic Use Of Artificial Intelligence In Business
Exploring the applications of AI in any business will often lead to a business model refresh or even a complete transformation of the business approach. It is important that companies don't use AI to automate and improve a business model that is no longer relevant during the fourth industrial revolution.
The starting point for any use of AI should be an AI and data strategy that identifies the biggest strategic opportunities and threats for any business and then pinpoints the most impactful applications. It is important to recognize that simply experimenting with AI around the edges is not going to deliver the necessary effects on business success.
Artificial Intelligence In Practice
In this book, you will find 50 company use cases and within them even more leading-edge examples of how these companies have used AI in practice to solve real world problems. We have divided the book into five parts.
Part 1 contains case studies from the AI trailblazers. These tech companies are the ones that have grabbed hold of the AI opportunities and are running with them to transform industries and deliver mouth-watering business results. Most of them have made innovative applications of AI part of all aspects of their business and therefore provide great insights into the art of the possible.
We could have segmented the remaining case studies in different ways, by AI application or by industry. Based on the feedback we received, we opted for the following industry segmentations.
In Part 2 we look at retail, consumer goods and food and beverage companies. In Part 3 we explore how media, entertainment and telecom companies use AI. Part 4 looks at the services sector, including financial services and healthcare. Finally, in Part 5 we look at manufacturing, automotive, aerospace and industry 4.0 case studies.
You can simply read this book cover to cover or dip in and out to explore the case studies or industries you are most interested in. We hope you will enjoy it!
Notes
1
Preparing for the Future of Artificial Intelligence, Executive Office of the President, National Science and Technology Council, National Science and Technology Council Committee on Technology, October 2016:
https://obamawhitehouse.archives.gov/sites/default/files/whitehouse_files/microsites/ostp/NSTC/preparing_for_the_future_of_ai.pdf
2
Artificial Intelligence for the American People, The White House:
https://www.whitehouse.gov/briefings-statements/artificial-intelligence -american-people/
3
Summary of the 2018 White House Summit on Artificial Intelligence for American Industry, The White House Office of Science and Technology Policy 10 May 2018:
https://www.whitehouse.gov/wp-content/ uploads/2018/05/Summary-Report-of-White-House-AI-Summit.pdf
4
“Whoever leads in AI will rule the world”: Putin to Russian children on Knowledge Day:
https://www.rt.com/news/401731-ai-rule-world-putin/
5
A Next Generation Artificial Intelligence Development Plan:
http:// www.gov.cn/zhengce/content/2017-07/20/content_5211996.htm
and Three-Year Action Plan to Promote the Development of New-Generation Artificial Intelligence Industry:
http://www.miit.gov.cn/ n1146295/n1652858/n1652930/n3757016/c5960820/content.html
6
Communication from the Commission to the European Parliament, the European Council, the Council, the European Economic and Social Committee and the Committee of the Regions, Artificial Intelligence for Europe, Brussels 2018:
https://ec.europa.eu/digital-single-market/en/news/communication-artificial-intelligence-europe
7
A.I. is in a “golden age” and solving problems that were once in the realm of sci-fi, Jeff Bezos says, CNBC:
https://www.cnbc.com/2017/05/ 08/amazon-jeff-bezos-artificial-intelligence-ai-golden-age.html
8
Google's Sergey Brin warns of the threat from AI in today's “technology renaissance”:
https://www.theverge.com/2018/4/28/17295064/google-ai-threat-sergey-brin-founders-letter-technology-renaissance
9
Microsoft CEO Satya Nadella on the rise of A.I.: “The future we will invent is a choice we make”:
https://www.cnbc.com/2018/05/24/ microsoft-ceo-satya-nadella-on-the-rise-of-a-i-the-future-we-will- invent-is-a-choice-we-make.html
10
The Fourth Industrial Revolution: what it means, how to respond, Klaus Schwab, World Economic Forum:
https://www.weforum.org/ agenda/2016/01/the-fourth-industrial-revolution-what-it-means-and- how-to-respond/
Part 1Artificial Intelligence Trailblazers
1Alibaba: Using Artificial Intelligence To Power The Retail And Business-To-Business Services Of The Future
Alibaba Group is a Chinese multinational conglomerate that operates the world's largest e-commerce network through its web portals, which include Alibaba.com, Taobao, Tmall and Ali Express. With global sales that dwarf those of Amazon and eBay combined,1 the business took what it learned from building a global online retail platform and has applied it to enterprises in just about every area of business and technology. Alibaba's success in delivering e-commerce and retail services, electronic payment, as well as business-to-business cloud services, has earned it a market cap in excess of US$500 billion.
Its customers use artificial intelligence (AI) tools to help them find what they want when they shop at its online portals, and as one of the world's largest cloud computing providers it also licenses platforms, tools and cloud services to other businesses to help them leverage AI.
Beyond that, Alibaba is rolling out AI across the wider society, with projects involving turning entire cities into “smart cities”. They are also planning on revolutionizing China's (and perhaps the world's) agricultural industries to ease the burden of feeding a growing population.
How Does Alibaba Use Artificial Intelligence?
The Chinese government has strongly supported efforts by businesses to adopt AI, clearly believing that it has enormous potential for driving economic growth. Its goal is to foster a $1 trillion industry and be the world leader in AI by 2030.2
This, combined with the fact that the country's enormous population gives companies access to huge amounts of data on customers’ lives, makes the country a fertile ground for AI development.
Alibaba's e-commerce portals use sophisticated AI to choose which items to display to customers when they visit and search for products they want to buy. It does this by building a custom page view for every visitor, aimed at showing them items they will be interested in, at prices that seem right.
By monitoring customer actions – whether they make a purchase, browse to a different item or leave the site – it learns in real time to make adjustments to these page views to increase the probability of the visit ending in a purchase.
To train its e-commerce portals to show visitors pages that are likely to result in a sale, Alibaba has deployed a form of semi-supervised learning known as reinforcement learning on its Taobao portal.3
Because collecting enough user data to train unsupervised learning algorithms from real-time customer actions would take a long time, and involve real business risks, a virtual Taobao was built, with customer behavior simulated from hundreds of thousands of hours’ worth of historical customer data.
This mass of data meant that it was possible for the algorithms to be exposed to a far wider range of customer behaviors, in a far shorter time span.
Alibaba also has its own AI-powered chatbot – Dian Xiaomi – that answers more than 350 million customer enquiries a day, successfully understanding more than 90% of them. These tools are necessary to help it deal with the huge spikes generated by special occasions such as the Alibaba-created “Singles’ Day” shopping event.4
Automated Sales Copy
With millions of different items on sale across its sites, Alibaba has invested in automated content generation to ease the burden of writing descriptions for everything it sells. The tools are also available to third-party sellers on its platforms.
Its AI copywriter uses natural language processing algorithms running on deep learning neural networks to produce 20,000 lines of copy in a second.5
Traditionally, sales copywriters have had to spend hours researching keywords and click-through rates to understand what is likely to make a customer click their link in a page of product search results. The AI copywriter allows Alibaba and others selling through its platforms to do it at the click of a button.
This is done by creating multiple versions of adverts and running them through algorithms trained on customer behavior data. The system works out which combination of words is most likely to result in customer clicks, and uses them to create its copy.
Cloud Services
Just like Amazon and Google, Alibaba offers artificially intelligent services through the cloud to its business customers. Its cloud service business is the largest of all the Chinese tech giants.6
Alibaba's AI offering is called Machine Learning Platform for AI, which offers solutions for businesses wanting to take advantage of cognitive computing functions such as natural language processing and computer vision, without the upfront costs of directly investing in infrastructure.
Alibaba's natural language processing technology was the first in the world to beat a Stanford University test designed to assess whether a machine can beat a human at reading comprehension.
