The Rise Of Ai User Applications

Artificial Intelligence (AI) in Healthcare is more than a comprehensive introduction to artificial intelligence as a tool in the generation and analysis of healthcare data. The book is split into two sections where the first section describes the current healthcare challenges and the rise of AI in this arena. The ten following chapters are written by specialists in each area, covering the whole healthcare ecosystem. First, the AI applications in drug design and drug development are presented followed by its applications in the field of cancer diagnostics, treatment and medical imaging. Subsequently, the application of AI in medical devices and surgery are covered as well as remote patient monitoring. Finally, the book dives into the topics of security, privacy, information sharing, health insurances and legal aspects of AI in healthcare. Highlights different data techniques in healthcare data analysis, including machine learning and data mining Illustrates different applications and challenges across the design, implementation and management of intelligent systems and healthcare data networks Includes applications and case studies across all areas of AI in healthcare data

Librarians are uniquely positioned to rise to the challenge that artificial intelligence (AI) presents to the field. Libraries and their like have existed for millennia; they progress with society, altering and adapting their services to meet the information needs of their communities. The Rise of AI collects projects, collaborations, and future uses from academic librarians who have begun to embrace AI in their work. In three parts--User Services, Collections and Discovery, and Toward Future Applications--it explores: machine translation creating incubation spaces robotics combining information literacy initiatives with AI literacy fostering partnerships with other on-campus groups integrating AI technology into collections to enhance discoverability using AI to refine metadata for images, articles, and theses machine learning The Rise of AI introduces implications and applications of artificial intelligence in academic libraries and hopes to provoke conversations and inspire new ways of engaging with the technology. As the discussion surrounding ethics, bias, and privacy in AI continues to grow, librarians will be called to make informed decisions and position themselves as leaders in this discourse.

Companies that don't use AI to their advantage will soon be left behind. Artificial intelligence and machine learning will drive a massive reshaping of the economy and society. What should you and your company be doing right now to ensure that your business is poised for success? These articles by AI experts and consultants will help you understand today's essential thinking on what AI is capable of now, how to adopt it in your organization, and how the technology is likely to evolve in the near future. Artificial Intelligence: The Insights You Need from Harvard Business Review will help you spearhead important conversations, get going on the right AI initiatives for your company, and capitalize on the opportunity of the machine intelligence revolution. Catch up on current topics and deepen your understanding of them with the Insights You Need series from Harvard Business Review. Featuring some of HBR's best and most recent thinking, Insights You Need titles are both a primer on today's most pressing issues and an extension of the conversation, with interesting research, interviews, case studies, and practical ideas to help you explore how a particular issue will impact your company and what it will mean for you and your business.

Artificial intelligence is emerging as a game-changer in the business world, with impacts across all sectors. AI allows business to process massive amounts of data instantaneously, and to scale solutions at almost zero marginal cost, forcing companies to adapt and reimagine their business and operations. The Rise of AI-Powered Companies examines some of the most successful examples of companies using artificial intelligence to their advantage. From AI-enabled countries across the globe that stayed resilient and strong in the face of COVID-19, to Business-to-Consumer businesses that transformed their product development processes thanks to unprecedented amounts of consumer data, increasing their revenues manifold along the way. The book then delves into the critical enablers to becoming AI-powered and the critical steps to activate and integrate them within business organizations. Starting with data strategy, it examines new forms of data sharing and how companies should think about governance and privacy risks. It then focuses on human–AI collaboration and its role in building a stronger team culture. Finally, "Responsible AI" is discussed as well as the impact of AI-powered businesses on society at large. AI-powered companies will become the norm in the years to come. By unpacking and showcasing the major steps of a successful AI transformation, this book will help guide organizations in making the critical leap to become AI-powered—essential to survive and remain competitive in the near future.

More than half of the analytics and machine learning (ML) models created by organizations today never make it into production. Some of the challenges and barriers to operationalization are technical, but others are organizational. Either way, the bottom line is that models not in production can't provide business impact. This book introduces the key concepts of MLOps to help data scientists and application engineers not only operationalize ML models to drive real business change but also maintain and improve those models over time. Through lessons based on numerous MLOps applications around the world, nine experts in machine learning provide insights into the five steps of the model life cycle--Build, Preproduction, Deployment, Monitoring, and Governance--uncovering how robust MLOps processes can be infused throughout. This book helps you: Fulfill data science value by reducing friction throughout ML pipelines and workflows Refine ML models through retraining, periodic tuning, and complete remodeling to ensure long-term accuracy Design the MLOps life cycle to minimize organizational risks with models that are unbiased, fair, and explainable Operationalize ML models for pipeline deployment and for external business systems that are more complex and less standardized

How will AI change our world within twenty years? A pioneering technologist and acclaimed writer team up for a “dazzling” (The New York Times) look at the future that “brims with intriguing insights” (Financial Times). This edition includes a new foreword by Kai-Fu Lee. A BEST BOOK OF THE YEAR: The Wall Street Journal, The Washington Post, Financial Times Long before the advent of ChatGPT, Kai-Fu Lee and Chen Qiufan understood the enormous potential of artificial intelligence to transform our daily lives. But even as the world wakes up to the power of AI, many of us still fail to grasp the big picture. Chatbots and large language models are only the beginning. In this “inspired collaboration” (The Wall Street Journal), Lee and Chen join forces to imagine our world in 2041 and how it will be shaped by AI. In ten gripping, globe-spanning short stories and accompanying commentary, their book introduces readers to an array of eye-opening settings and characters grappling with the new abundance and potential harms of AI technologies like deep learning, mixed reality, robotics, artificial general intelligence, and autonomous weapons.

Master the skills required to become an AI product manager and drive the successful development and deployment of AI products to deliver value to your organization. Purchase of the print or Kindle book includes a free PDF eBook. Key Features Build products that leverage AI for the common good and commercial success Take macro data and use it to show your customers you’re a source of truth Best practices and common pitfalls that impact companies while developing AI product Book DescriptionProduct managers working with artificial intelligence will be able to put their knowledge to work with this practical guide to applied AI. This book covers everything you need to know to drive product development and growth in the AI industry. From understanding AI and machine learning to developing and launching AI products, it provides the strategies, techniques, and tools you need to succeed. The first part of the book focuses on establishing a foundation of the concepts most relevant to maintaining AI pipelines. The next part focuses on building an AI-native product, and the final part guides you in integrating AI into existing products. You’ll learn about the types of AI, how to integrate AI into a product or business, and the infrastructure to support the exhaustive and ambitious endeavor of creating AI products or integrating AI into existing products. You’ll gain practical knowledge of managing AI product development processes, evaluating and optimizing AI models, and navigating complex ethical and legal considerations associated with AI products. With the help of real-world examples and case studies, you’ll stay ahead of the curve in the rapidly evolving field of AI and ML. By the end of this book, you’ll have understood how to navigate the world of AI from a product perspective.What you will learn Build AI products for the future using minimal resources Identify opportunities where AI can be leveraged to meet business needs Collaborate with cross-functional teams to develop and deploy AI products Analyze the benefits and costs of developing products using ML and DL Explore the role of ethics and responsibility in dealing with sensitive data Understand performance and efficacy across verticals Who this book is for This book is for product managers and other professionals interested in incorporating AI into their products. Foundational knowledge of AI is expected. If you understand the importance of AI as the rising fourth industrial revolution, this book will help you surf the tidal wave of digital transformation and change across industries.