Editor's Note: This article was originally printed in the 2008 Scientific American Special Report on Robots. It is being published on the Web as part of ScientificAmerican.com's In recent years the mushrooming power, functionality and ubiquity of computers and the Internet have outstripped early forecasts about technology's rate of advancement and usefulness in everyday life. Alert pundits now foresee a world saturated with powerful computer chips, which will increasingly insinuate themselves into our gadgets, dwellings, apparel and even our bodies. Yet a closely related goal has remained stubbornly elusive. In stark contrast to the largely unanticipated explosion of computers into the mainstream, the entire endeavor of robotics has failed rather completely to live up to the predictions of the 1950s. In those days experts who were dazzled by the seemingly miraculous calculational ability of computers thought that if only the right software were written, computers could become the artificial brains of sophisticated autonomous robots. Within a decade or two, they believed, such robots would be cleaning our floors, mowing our lawns and, in general, eliminating drudgery from our lives.

What does 2011 hold for the field of robotics? Plenty, if 2010 is any indication. This will not be the year that mobile, artificially intelligent robot nurses assume the responsibility of caring for the world's growing elderly population, but it does promise to be a pivotal time for the development of the underlying technology that will enable safe and reliable automated elder care, not to mention other services that robots are expected to perform in the coming decade. Thanks to a standardized platform introduced in 2010, roboticists can now collaborate as never before. Last May, Willow Garage, a Menlo Park, Calif., maker of robot hardware and software, released a test version of its personal robot platform.

She was totally skeptical of the idea that humans would fall in love with robots. She's still fairly skeptical, but she's beginning to appreciate something like this will happen. What happens if 50 years from now your predictions have not proved true, and humans and robots don't marry? I know some people think the idea is totally outlandish. But I am totally convinced it's inevitable. I would be absolutely astounded if I'm proven wrong--not if I'm a few years off, but if I'm proven completely wrong.

The crowd went wild, almost as if it were a World Cup match. Actually, it was RoboCup 2002. The annual robotic soccer tournament was held in Fukuoka, Japan, this past June as the World Cup was getting under way. The timing was no coincidence. The notion of robots taking on Brazil would be laughable if roboticists around the world were not so enthusiastically answering the call.

Editor's note: This excerpt of a chapter from Louder Than Words: The New Science of How the Mind Makes Meaning by Benjamin K. Bergen (Basic Books, 2012) relates that our brain's capacity to both perceive a pig and then imagine what the animal is like, even one that flies, points to an essential cognitive skill that makes humans different from all other species. Excerpted from Louder Than Words: The New Science of How the Mind Makes Meaning by Benjamin K. Bergen. Starting as early as the 1970s, some cognitive psychologists, philosophers, and linguists began to wonder whether meaning wasn't something totally different from a language of thought [Call it Mentalese, whichtranslates words into actual concepts: a polar bear or speed limit, for instance]. They suggested that--instead of abstract symbols--meaning might really be something much more closely intertwined with our real experiences in the world, with the bodies that we have. As a self-conscious movement started to take form, it took on a name, embodiment, which started to stand for the idea that meaning might be something that isn't distilled away from our bodily experiences but is instead tightly bound by them. For you, the word dog might have a deep and rich meaning that involves the ways you physically interact with dogs--how they look and smell and feel.

Can training to become ambidextrous improve brain function? Although teaching people to become ambidextrous has been popular for centuries, this practice does not appear to improve brain function, and it may even harm our neural development. Calls for ambidexterity were especially prominent in the late 19th and early 20th centuries. For instance, in the early 20th century English propagandist John Jackson established the Ambidextral Culture Society in pursuit of universal ambidexterity and "two-brainedness" for the betterment of society. This hype died down in the mid-20th century as benefits of being ambidextrous failed to materialize.

The brain performs its canonical task -- learning -- by tweaking its myriad connections according to a secret set of rules. To unlock these secrets, scientists 30 years ago began developing computer models that try to replicate the learning process. Now, a growing number of experiments are revealing that these models behave strikingly similar to actual brains when performing certain tasks. Researchers say the similarities suggest a basic correspondence between the brains' and computers' underlying learning algorithms. The algorithm used by a computer model called the Boltzmann machine, invented by Geoffrey Hinton and Terry Sejnowski in 1983, appears particularly promising as a simple theoretical explanation of a number of brain processes, including development, memory formation, object and sound recognition, and the sleep-wake cycle.

From the nature of the cosmos to the nature of societies, the following 100 questions span the sciences. Some are pieces of questions discussed above; others are big questions in their own right. Some will drive scientific inquiry for the next century; others may soon be answered. Many will undoubtedly spawn new questions. A number of quantum theorists and cosmologists are trying to figure out whether our universe is part of a bigger "multiverse." But others suspect that this hard-to-test idea may be a question for philosophers. In the first moments after the big bang, the universe blew up at an incredible rate. But what did the blowing? Measurements of the cosmic microwave background and other astrophysical observations are narrowing the possibilities. When and how did the first stars and galaxies form? The broad brush strokes are visible, but the fine details aren't.

Issac Asimov, widely regarded as the spiritual father of science fiction, outlined three rules that all robots in his future worlds must obey. The most important two were: a robot may not injure a human being or, through inaction, allow a human being to come to harm; and a robot must obey orders given to it by human beings, except where such orders would conflict with the First Law. However, robotics in the real world has trouble striking a workable balance between these two requirements. Robots can perform tasks efficiently in controlled environments away from humans, or they can interact with humans if properly equipped with sensors to avoid any harm. But that degree of'sensing' also creates complexity and a lack of robustness to hardware and software failures which, in turn, affects safety.

And now, after putting dozens of computers to work night and day for 18 years--jump, jump, jump--he says he has solved the game--king me!. "The starting position, assuming no side makes a mistake, is a draw," he says. Schaeffer's proof, described today in Science (and freely available here for others to verify), would make checkers the most complex game yet solved by machines, beating out the checker-stacking game Connect Four in difficulty by a factor of a million. "It's a milestone," says Murray Campbell, a computer scientist at IBM's T. J. Watson Research Center in Hawthorne, N.Y., and co-inventor of the chess program Deep Blue. "He's stretched the state of the art." Although technological limits prohibit analyzing each of the 500 billion billion possible arrangements that may appear on an eight-by-eight checkerboard, Schaeffer and his team identified moves that guaranteed the game would end in a draw no matter how tough the competition.