Deep learning networks can play poker better than professional poker players and defeat a world champion at Go. In this book, Terry Sejnowski explains how deep learning went from being an arcane academic field to a disruptive technology in the information economy.Sejnowski played an important role in the founding of deep learning, as one of a small group of researchers in the 1980s who challenged the prevailing logic-and-symbol based version of AI. The new version of AI Sejnowski and others developed, which became deep learning, is fueled instead by data. Deep networks learn from data in the same way that babies experience the world, starting with fresh eyes and gradually acquiring the skills needed to navigate novel environments. Learning algorithms extract information from raw data; information can be used to create knowledge; knowledge underlies understanding; understanding leads to wisdom. Someday a driverless car will know the road better than you do and drive with more skill; a deep learning network will diagnose your illness; a personal cognitive assistant will augment your puny human brain. It took nature many millions of years to evolve human intelligence; AI is on a trajectory measured in decades. Sejnowski prepares us for a deep learning future.

    Now he's sharing his collection of antipatterns--the most common errors he's identified in those thousands of requests for help. Most developers aren't SQL experts, and most of the SQL that gets used is inefficient, hard to maintain, and sometimes just plain wrong. This book shows you all the common mistakes, and then leads you through the best fixes. What's more, it shows you what's behind these fixes, so you'll learn a lot about relational databases along the way. Each chapter in this book helps you identify, explain, and correct a unique and dangerous antipattern. The four parts of the book group the anti​patterns in terms of logical database design, physical database design, queries, and application development. The chances are good that your application's database layer already contains problems such as Index Shotgun, Keyless Entry, Fear of the Unknown, and Spaghetti Query. This book will help you and your team find them. Even better, it will also show you how to fix them, and how to avoid these and other problems in the future. SQL Antipatterns gives you a rare glimpse into an SQL expert's playbook. Now you can stamp out these common database errors once and for all. Whatever platform or programming language you use, whether you're a junior programmer or a Ph.D., SQL Antipatterns will show you how to design and build databases, how to write better database queries, and how to integrate SQL programming with your application like an expert. You'll also learn the best and most current technology for full-text search, how to design code that is resistant to SQL injection attacks, and other techniques for success.

    One of the great promises of the Internet and big data revolutions is the idea that we can improve the processes and routines of our work and personal lives to get more done in less time than ever before. There is no doubt that we're performing at higher scales and going faster than ever, but what if we're headed in the wrong direction?The Efficiency Paradox questions our ingrained assumptions about efficiency, persuasively showing how relying on the algorithms of platforms can in fact lead to wasted efforts, missed opportunities, and above all an inability to break out of established patterns. Edward Tenner offers a smarter way to think about efficiency, showing how we can combine artificial intelligence and our own intuition, leaving ourselves and our institutions open to learning from the random and unexpected.