If you are looking for an answer to the question What is Artificial Intelligence? and you only have a minute, then here's the definition the Association for the Advancement of Artificial Intelligence offers on its home page: "the scientific understanding of the mechanisms underlying thought and intelligent behavior and their embodiment in machines."
However, if you are fortunate enough to have more than a minute, then please get ready to embark upon an exciting journey exploring AI (but beware, it could last a lifetime) …
It is difficult to count demons. In the Gospel of Mark, when Jesus meets a man on the far side of the Sea of Galilee who is possessed, he asks the demon to identify itself. It replies: "My name is Legion, for we are many." The thirteenth-century German abbot Richalmus suspected the number of demons was incalculable, as numerous as grains of sand in the sea. Three centuries later, when the Dutch physician Johann Weyer composed his demonology, he identified some sixty-nine demons by name, who commanded millions of others: at least eleven hundred and eleven distinct legions, each with six thousand six hundred and sixty-six demons.
If you follow the news on artificial intelligence, you'll find two diverging threads. The media and cinema often portray AI with human-like capabilities, mass unemployment, and a possible robot apocalypse. Scientific conferences, on the other hand, discuss progress toward artificial general intelligence while acknowledging that current AI is weak and incapable of many of the basic functions of the human mind. But regardless of where they stand in comparison to human intelligence, today's AI algorithms have already become a defining component for many sectors, including health care, finance, manufacturing, transportation, and many more. And very soon "no field of human endeavor will remain independent of artificial intelligence," as Harvard Business School professors Marco Iansiti and Karim Lakhani explain in their book Competing in the Age of AI: Strategy and Leadership When Algorithms and Networks Run the World.
As far back as mid-March, people were suggesting that the best thing to do with 2020 was hit the fast-forward button and move on swiftly to 2021. In the long slog since, endless Zoom calls and panels have explored the kind of future we might want to build, as and when we can. This year's book reviews wrap-up therefore focuses on futurist titles, even though all of them were written before SARS-CoV-2 reared its ugly protein spikes. The countries that have done best in this crisis have been those that benefited from recent epidemic experience. Their prompt response may be what David Weinberger, co-author of the well-known The Cluetrain Manifesto, means when he writes in Everyday Chaos about a "normal chaos" that looks positively restful compared to our present situation.
The long-anticipated revision of Artificial Intelligence: A Modern Approach explores the full breadth and depth of the field of artificial intelligence (AI). The 4th Edition brings readers up to date on the latest technologies, presents concepts in a more unified manner, and offers new or expanded coverage of machine learning, deep learning, transfer learning, multiagent systems, robotics, natural language processing, causality, probabilistic programming, privacy, fairness, and safe AI.
The Non-Programmers' Tutorial For Python 3 is a tutorial designed to be an introduction to the Python programming language. This guide is for someone with no programming experience. "The Coder's Apprentice" aims at teaching Python 3 to students and teenagers who are completely new to programming. Contrary to many of the other books that teach Python programming, this book assumes no previous knowledge of programming on the part of the students, and contains numerous exercises that allow students to train their programming skills. The book aims at striking the balance between a tutorial and reference book. Includes some fun exercises at the end! "A Byte of Python" is a free book on programming using the Python language. It serves as a tutorial or guide to the Python language for a beginner audience. If all you know about computers is how to save text files, then this is the book for you.
The "great man" theory holds that history is largely made by heroes--big, brawny, brainy dudes (always dudes) who reshape the future with brute force and brilliance. In Driven, Davies digs into the history of autonomous vehicles and the goofy, spirited cast of characters (still mostly dudes) who are working to shepherd the tech into existence. As Davies reveals, teamwork makes the dream work. Then the lawsuits--and in one engineer's case, handcuffs--fly. Eventually, robot cars might reshape the way modern life works.
Artificial Intelligence (AI) is the study of how computers can be made to act intelligently. For most of us lay book (and movie) nerds, we mostly experience AI through science fiction where humans create robots to think and feel like people, and those robots eventually turn against their creators and seek to destroy them. While fiction may make us feel like we are decades away from this AI reality, some of the best books on artificial intelligence will show AI is actually a staple in most of our everyday lives. It's there when we say "Hey Google (or Alexa or Siri)" or when the item we were searching for on Amazon starts to show up in our Facebook feed. As artificial intelligence becomes even more ingrained within our lives both at work and at home, it's important to understand the topic.
"Data indeed is the new oil" When I heard this for the first time many years ago, I mocked and ignored the statement. And, I am pretty sure many people like me are now thinking about how accurate this statement was. Currently, Data science has taken over all the industries without leaving any stones unturned. Every firm is trying to leverage a panoply of data at each and every step of its operations to obtain ultimate efficiency. It only makes sense for people to familiarize themselves with at least basic algorithms and tools to analyze the data in their respective domains to better understand the trends and in turn, make better decisions.
'An excellent book that treats the fundamentals of machine learning from basic principles to practical implementation. The book is suitable as a text for senior-level and first-year graduate courses in engineering and computer science. It is well organized and covers basic concepts and algorithms in mathematical optimization methods, linear learning, and nonlinear learning techniques. The book is nicely illustrated in multiple colors and contains numerous examples and coding exercises using Python.' John G. Proakis, University of California, San Diego'Some machine learning books cover only programming aspects, often relying on outdated software tools; some focus exclusively on neural networks; others, solely on theoretical foundations; and yet more books detail advanced topics for the specialist.
The rediscovery of the potential of artificial intelligence (AI) to improve healthcare delivery and patient outcomes has led to an increasing application of AI techniques such as deep learning, computer vision, natural language processing, and robotics in the healthcare domain. Many governments and health authorities have prioritized the application of AI in the delivery of healthcare. Also, technological giants and leading universities have established teams dedicated to the application of AI in medicine. These trends will mean an expanded role for AI in the provision of healthcare. Yet, there is an incomplete understanding of what AI is and its potential for use in healthcare.