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Will the next generation of self-checkouts be able to initiate discussions with consumers? Photograph: Micha Theiner / Rex Features In 1950, computer science pioneer Alan Turing famously predicted that "... in about 50 years' time it will be possible to programme computers ... to make them play the imitation game so well that an average interrogator will not have more than 70% chance of making the right identification (between computer and human) after five minutes of questioning." In some ways, Turing was spot on: today's artificial intelligence (AI) has become an integral part of many everyday relationships between consumers and brands. It's the automated chatbot that helps with your banking inquiry, the voice-recognition software that takes your call to the airline company, the self-checkout technology in the supermarket. We talk to the machine and the machine talks back, but often, not very well. The problem is that today's AI is pretty functiona

If you think robots are mainly the stuff of space movies, think again. Right now, all over the world, robots are on the move. They’re painting cars at Ford plants, assembling Milano cookies for Pepperidge Farms, walking into live volcanoes, driving trains in Paris, and defusing bombs in Northern Ireland. As they grow tougher, nimbler, and smarter, today’s robots are doing more and more things we can’t –or don’t want to–do. Robots have been with us for less than 50 years, but the idea of inanimate creations to do our bidding is much, much older. The ancient Greek poet Homer described maidens of gold, metallic helpers for the Hephaistos, the Greek god of the forge. The golems of medieval Jewish legend were robot-like servants made of clay, brought to life by a spoken charm. Leonardo da Vinci drew plans for a mechanical man in 1495. But real robots wouldn’t become pos

A SHORT HISTORY OF ROBOTS AND THINKING MACHINES     Although robots are considered a 20th-century invention, their origins lie in the distant past. From the earliest times, people have created myths about mechanical beings built in their own likeness with superhuman powers. The ancient Egyptians and Greeks built mechanical automatons to perform simple tasks. In modern times, mechanical toys entertained and ever-more-complicated machines were invented. The idea of a lifelike mechanical humanoid influenced both art and science; in 1818, Mary Shelley’s Frankenstein explored what happens when a man-made monster is given life by a well-meaning scientist. As computer technology became more advanced, scientists became more interested in building intelligent machines that could eventually think for themselves. Today, robots of all kinds populate our world and are used for varied applications in space exploration, the military, medicine, industry

Artificial Neural Networks What They Are    A neural network is, in essence, an attempt to simulate the brain. Neural network theory revolves around the idea that certain key properties of biological neurons can be extracted and applied to simulations, thus creating a simulated (and very much simplified) brain. The first important thing to understand then, is that the components of an artificial neural network are an attempt to recreate the computing potential of the brain. The second important thing to understand, however, is that no one has ever claimed to simulate anything as complex as an actual brain. Whereas the human brain is estimated to have something on the order of ten to a hundred billion neurons, a typical artificial neural network (ANN) is not likely to have more than 1,000 artificial neurons.    Before discussing the specifics of artificial neural nets though, let us examine what makes real neural nets - brains - function the way they do. Pe