From spam filters and self-driving cars to cutting edge medical diagnosis and real-time language translation, there has been an increasing need for our computers to learn from data and apply that knowledge to make predictions and decisions. This is the heart of machine learning which sits inside the more ambitious goal of artificial intelligence.
As computers play an increasing role in our daily lives there has been a growing demand for voice user interfaces, but speech is also terribly complicated. Vocabularies are diverse, sentence structures can often dictate the meaning of certain words, and computers also have to deal with accents, mispronunciations, and many common linguistic faux pas.
In the past 70 years, electronic computing has fundamentally changed how we live our lives, and we believe it’s just getting started. From ubiquitous computing, artificial intelligence, and self-driving cars to brain-computer interfaces, wearable computers, and maybe even the singularity there is so much amazing potential on the horizon.
Artificial Intelligence conjures up all sorts of images – perhaps you think of friendly systems that can talk to you and solve tough problems; or maniac robots that are bent on world domination? There's the promise of driverless cars that are safer than human drivers, and the worry of medical advice systems that hold people's lives in their virtual hands. The field of Artificial Intelligence is a part of computer science that has a lot of promise and also raises a lot of concerns. It can be used to make decisions in systems as large as an airplane or an autonomous dump truck, or as small as a mobile phone that accurately predicts text being typed into it. What they have in common is that they try to mimic aspects of human intelligence. And importantly, such systems can be of significant help in people's everyday lives.
AI (also known as intelligent systems) is primarily a branch of computer science but it has borrowed a lot of concepts and ideas from other fields, especially mathematics (particularly logic, combinatorics, statistics, probability and optimization theory), biology, psychology, linguistics, neuroscience, and philosophy.
In this chapter, we'll explore a range of these intelligent systems. Inevitably this will mean dealing with ethical and philosophical issues too – do we really want machines to take over some of our jobs? Can we trust them? Might it all go too far one day? What do we really mean by a computer being intelligent? While we won't address these questions directly in this chapter, gaining some technical knowledge about AI will enable you to make more informed decisions about the deeper issues.
