What do Amazon, Google, Visa and AirBnB all have in common? They are all platform businesses. They know they can go beyond their industry segments. They capitalize on wider ecosystems that strengthen their offering and expand commercial opportunities. And now your business can do the same. Welcome to the world of platform businesses. In Platform Strategy one of the world's most creative men in business according to Fast Company and a leading strategy professor at a Financial Times top 40 business school show you the ropes. They lead you through the seven steps you can take to turn your business into a successful platform. Learn to harness emerging technologies like artificial intelligence, cement your business into thriving ecosystems and go beyond industry boundaries. Uncover how business leaders at companies as diverse as John Deere, KONE, and Visa are leading their businesses to the future by reinventing their business model. Authors Tero Ojanperä and Timo Vuori distil the disrupters' methods to an actionable blueprint. In Platform Strategy they put the emphasis on what you can do as leader; harness new technologies, work with partners but also crucially, recognize the fear of change in your people and utilize that energy to drive progress. More than just about technology, this book is at the centre of the leadership agenda for the future.
It has quickly become apparent in the past year that online learning is not only an asset, but it is critical to the continued education of youth during times of crisis. However, districts and schools across the nation are in need of guidance and practical, research-backed approaches to distance and hybrid learning. The current COVID-19 crisis has demonstrated that effective learning in K-12 is possible, but many districts struggled and continue to struggle in achieving that reality. There is also the growing consensus that even if things “return to normal,” distance and blended learning strategies should continue to be employed in many ways across the K-12 environment. Designing Effective Distance and Blended Learning Environments in K-12 provides key insights into the ways that school districts and educators from across the world have effectively designed and implemented distance and blended learning approaches to enable and enhance student learning. The diverse collection of authors from various demographics and roles in school systems will benefit readers across a wide spectrum of school community stakeholders. There will also be an emphasis on how research and theory is put into practice, along with an honest discussion of what strategies and actions were successful as well as those that were less so. This book is essential for professionals and researchers working in the field of K-12 education, particularly superintendents, curriculum developers, professional learning designers, school principals, instructional technology specialists, and teachers, as well as administrators, researchers, academicians, and students interested in the effective practices being used in blended learning approaches.
Artificial intelligence (AI) and platforms are closely related. Most investments in AI, especially in critical technologies, are provided by large platforms. This book describes how platforms invest in AI and how AI will impact the next generation of competences, following a twofold approach to do so: on the one hand, the book seeks to understand how platforms for investment in intangibles and AI are organized, but on the other hand, it provides a framework to describe how AI will change jobs and competences in the future. Moreover, the book addresses five main themes: 1. platforms, platformization, and the foundations of their business models; 2. artificial intelligence, technological tendencies, and the policy agenda; 3. artificial intelligence, productivity, and the next generation of competences; 4. artificial intelligence, productivity, and the digital divide; 5. artificial intelligence, ethics, and the post-truth society. The book’s content is mostly based on papers presented at the last two installments of the World Conference on Intellectual Capital for Communities. It brings together the views of leading scholars and experts on how artificial intelligence and platformization will impact competences in the near future.
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.
"a provocative new book" — The New York Times AI-centric organizations exhibit a new operating architecture, redefining how they create, capture, share, and deliver value. Now with a new preface that explores how the coronavirus crisis compelled organizations such as Massachusetts General Hospital, Verizon, and IKEA to transform themselves with remarkable speed, Marco Iansiti and Karim R. Lakhani show how reinventing the firm around data, analytics, and AI removes traditional constraints on scale, scope, and learning that have restricted business growth for hundreds of years. From Airbnb to Ant Financial, Microsoft to Amazon, research shows how AI-driven processes are vastly more scalable than traditional processes, allow massive scope increase, enabling companies to straddle industry boundaries, and create powerful opportunities for learning—to drive ever more accurate, complex, and sophisticated predictions. When traditional operating constraints are removed, strategy becomes a whole new game, one whose rules and likely outcomes this book will make clear. Iansiti and Lakhani: Present a framework for rethinking business and operating models Explain how "collisions" between AI-driven/digital and traditional/analog firms are reshaping competition, altering the structure of our economy, and forcing traditional companies to rearchitect their operating models Explain the opportunities and risks created by digital firms Describe the new challenges and responsibilities for the leaders of both digital and traditional firms Packed with examples—including many from the most powerful and innovative global, AI-driven competitors—and based on research in hundreds of firms across many sectors, this is your essential guide for rethinking how your firm competes and operates in the era of AI.
This book offers an in-depth academic discourse on the convergence of AI, digital platforms, and popular culture, in order to understand the ways in which the platform and cultural industries have reshaped and developed AI-driven algorithmic cultural production and consumption. At a time of fundamental change for the media and cultural industries, driven by the emergence of big data, algorithms, and AI, the book examines how media ecology and popular culture are evolving to serve the needs of both media and cultural industries and consumers. The analysis documents global governments’ rapid development of AI-relevant policies and identifies key policy issues; examines the ways in which cultural industries firms utilize AI and algorithms to advance the new forms of cultural production and distribution; investigates change in cultural consumption by analyzing the ways in which AI, algorithms, and digital platforms reshape people’s consumption habits; and examines whether governments and corporations have advanced reliable public and corporate policies and ethical codes to secure socio-economic equality. Offering a unique perspective on this timely and vital issue, this book will be of interest to scholars and students in media studies, communication studies, anthropology, globalization studies, sociology, cultural studies, Asian studies, and science and technology studies (STS).
Over the last few years, interest in the industrial applications of AI and learning systems has surged. This book covers the recent developments and provides a broad perspective of the key challenges that characterize the field of Industry 4.0 with a focus on applications of AI. The target audience for this book includes engineers involved in automation system design, operational planning, and decision support. Computer science practitioners and industrial automation platform developers will also benefit from the timely and accurate information provided in this work. The book is organized into two main sections comprising 12 chapters overall: •Digital Platforms and Learning Systems •Industrial Applications of AI
Increasingly, business leaders and managers recognize that machine learning offers their companies immense opportunities for competitive advantage. But most discussions of machine learning are intensely technical or academic, and don't offer practical information leaders can use to identify, evaluate, plan, or manage projects. Deploying Machine Learning fills that gap, helping them clarify exactly how machine learning can help them, and collaborate with technologists to actually apply it successfully. You'll learn: What machine learning is, how it compares to "big data" and "artificial intelligence," and why it's suddenly so important What machine learning can do for you: solutions for computer vision, natural language processing, prediction, and more How to use machine learning to solve real business problems -- from reducing costs through improving decision-making and introducing new products Separating hype from reality: identifying pitfalls, limitations, and misconceptions upfront Knowing enough about the technology to work effectively with your technical team Getting the data right: sourcing, collection, governance, security, and culture Solving harder problems: exploring deep learning and other advanced techniques Understanding today's machine learning software and hardware ecosystem Evaluating potential projects, and addressing workforce concerns Staffing your project, acquiring the right tools, and building a workable project plan Interpreting results -- and building an organization that can increasingly learn from data Using machine learning responsibly and ethically Preparing for tomorrow's advances The authors conclude with five chapter-length case studies: image, text, and video analysis, chatbots, and prediction applications. For each, they don't just present results: they also illuminate the process the company undertook, and the pitfalls it overcame along the way.
Enterprise Artificial Intelligence Transformation AI is everywhere. From doctor's offices to cars and even refrigerators, AI technology is quickly infiltrating our daily lives. AI has the ability to transform simple tasks into technological feats at a human level. This will change the world, plain and simple. That's why AI mastery is such a sought-after skill for tech professionals. Author Rashed Haq is a subject matter expert on AI, having developed AI and data science strategies, platforms, and applications for Publicis Sapient's clients for over 10 years. He shares that expertise in the new book, Enterprise Artificial Intelligence Transformation. The first of its kind, this book grants technology leaders the insight to create and scale their AI capabilities and bring their companies into the new generation of technology. As AI continues to grow into a necessary feature for many businesses, more and more leaders are interested in harnessing the technology within their own organizations. In this new book, leaders will learn to master AI fundamentals, grow their career opportunities, and gain confidence in machine learning. Enterprise Artificial Intelligence Transformation covers a wide range of topics, including: Real-world AI use cases and examples Machine learning, deep learning, and slimantic modeling Risk management of AI models AI strategies for development and expansion AI Center of Excellence creating and management If you're an industry, business, or technology professional that wants to attain the skills needed to grow your machine learning capabilities and effectively scale the work you're already doing, you'll find what you need in Enterprise Artificial Intelligence Transformation.
AI as a Service is a practical handbook to building and implementing serverless AI applications, without bogging you down with a lot of theory. Instead, you’ll find easy-to-digest instruction and two complete hands-on serverless AI builds in this must-have guide! Summary Companies everywhere are moving everyday business processes over to the cloud, and AI is increasingly being given the reins in these tasks. As this massive digital transformation continues, the combination of serverless computing and AI promises to become the de facto standard for business-to-consumer platform development—and developers who can design, develop, implement, and maintain these systems will be in high demand! AI as a Service is a practical handbook to building and implementing serverless AI applications, without bogging you down with a lot of theory. Instead, you’ll find easy-to-digest instruction and two complete hands-on serverless AI builds in this must-have guide! Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the technology Cloud-based AI services can automate a variety of labor intensive business tasks in areas such as customer service, data analysis, and financial reporting. The secret is taking advantage of pre-built tools like Amazon Rekognition for image analysis or AWS Comprehend for natural language processing. That way, there’s no need to build expensive custom software. Artificial Intelligence (AI), a machine’s ability to learn and make predictions based on patterns it identifies, is already being leveraged by businesses around the world in areas like targeted product recommendations, financial forecasting and resource planning, customer service chatbots, healthcare diagnostics, data security, and more. With the exciting combination of serverless computing and AI, software developers now have enormous power to improve their businesses’ existing systems and rapidly deploy new AI-enabled platforms. And to get on this fast-moving train, you don’t have to invest loads of time and effort in becoming a data scientist or AI expert, thanks to cloud platforms and the readily available off-the-shelf cloud-based AI services! About the book AI as a Service is a fast-paced guide to harnessing the power of cloud-based solutions. You’ll learn to build real-world apps—such as chatbots and text-to-speech services—by stitching together cloud components. Work your way from small projects to large data-intensive applications. What's inside - Apply cloud AI services to existing platforms - Design and build scalable data pipelines - Debug and troubleshoot AI services - Start fast with serverless templates About the reader For software developers familiar with cloud basics. About the author Peter Elger and Eóin Shanaghy are founders and CEO/CTO of fourTheorem, a software solutions company providing expertise on architecture, DevOps, and machine learning. Table of Contents PART 1 - FIRST STEPS 1 A tale of two technologies 2 Building a serverless image recognition system, part 1 3 Building a serverless image recognition system, part 2 PART 2 - TOOLS OF THE TRADE 4 Building and securing a web application the serverless way 5 Adding AI interfaces to a web application 6 How to be effective with AI as a Service 7 Applying AI to existing platforms PART 3 - BRINGING IT ALL TOGETHER 8 Gathering data at scale for real-world AI 9 Extracting value from large data sets with AI
