Using only her thoughts, a Massachusetts woman paralyzed for 15 years directed a robotic arm to pick up a bottle of coffee and bring it to her lips, researchers report in the latest advance in harnessing brain waves to help disabled people. In the past year, similar stories have included a quadriplegic man in Pennsylvania who made a robotic arm give a high-five and stroke his girlfriend's hand, and a partially paralyzed man who remotely controlled a small robot that scooted around in a Swiss lab. But will the experimental brain-controlled technology ever help paralyzed people in everyday life? Experts in the technology and in rehabilitation medicine say they are optimistic that it will, once technology improves and the cost comes down. The latest report, which was published online Wednesday in the journal Nature, comes from scientists at Brown University, the Providence VA Medical Center in Rhode Island, Harvard Medical School and elsewhere.

Jean-Pierre Changeux is France's most famous neuroscientist. Though less well known in the United States, he has directed a famous laboratory at the Pasteur Institute for more than thirty years, taught as a professor at the Collège de France, and written a number of works exploring "the neurobiology of meaning." Aside from his own books, Changeux has published two wide-ranging dialogues about mind and matter, one with the mathematician Alain Connes and the other with the late French philosopher Paul Ricoeur. Changeux came of age at a fortunate time. Born in 1936, he began his studies when the advent both of the DNA age and of high-resolution images of the brain heralded a series of impressive breakthroughs. Changeux took part in one such advance in 1965 when, together with Jacques Monod and Jeffries Wyman, he established an important model of protein interactions in bacteria, which, when applied to the brain, became crucial for understanding the behavior of neurons. Since that time, Changeux has written a number of books exploring the functions of the brain. The brain is of course tremendously complex: a bundle of some hundred billion neurons, or nerve cells, each sharing as many as ten thousand connections with other neurons.

In 1985, in Hamburg, I played against thirty-two different chess computers at the same time in what is known as a simultaneous exhibition. I walked from one machine to the next, making my moves over a period of more than five hours. The four leading chess computer manufacturers had sent their top models, including eight named after me from the electronics firm Saitek. It illustrates the state of computer chess at the time that it didn't come as much of a surprise when I achieved a perfect 32–0 score, winning every game, although there was an uncomfortable moment. At one point I realized that I was drifting into trouble in a game against one of the "Kasparov" brand models. If this machine scored a win or even a draw, people would be quick to say that I had thrown the game to get PR for the company, so I had to intensify my efforts. Eventually I found a way to trick the machine with a sacrifice it should have refused. From the human perspective, or at least from my perspective, those were the good old days of man vs. machine chess. Eleven years later I narrowly defeated the supercomputer Deep Blue in a match.

A woman holds up a tablet to showcase data analytics conducted by IBM's Watson technology. A woman holds up a tablet to showcase data analytics conducted by IBM's Watson technology. Guruduth Banavar is an executive at IBM leading the team developing a new generation of cognitive systems -- don't call it artificial intelligence -- known as Watson. Watson, of course, is the supercomputer most famous for its victory against two men on Jeopardy! in 2011. IBM is now lending Watson's computing power to startups and businesses across all types of industries, including healthcare, energy, education and even food.

Last spring, I taught a literature seminar called "Before Wikipedia." The subject was the history of encyclopedic writing, from ancient times to the present day. We read excerpts of Isidore of Seville's "Etymologies" and Diderot's "Encyclopédie" alongside works by Calvino, Sebald, and Flaubert. The word "Wikipedia" in the course title seemed to attract an unusual preponderance of science majors for a seminar in comparative literature. There were physicists and mathematicians, a cluster of coders, an engineer, a neuroscience major.

In Leena Krohn's novella "Datura, or A Figment Seen by Everyone," the narrator, who works for a paranormal-news magazine, transcribes the inscrutable fifteenth-century text known as the Voynich manuscript while slowly poisoning herself with the seeds from a datura plant. Datura is known to cause delirium and dissociation, but it may also ease the symptoms of asthma, which the narrator has. Though she is skeptical of supernatural phenomena, the datura slowly undermines that skepticism; each day seems to bring one serendipitous event after another, not to mention mild hallucinations. The narrator describes feeling as though meaning is floating on the surface of things, untethered from their physical reality. "What does the word refer to," she asks, in a deconstructionist turn, "does it really signify anything at all?"

A framework for translating the write-ups of experiments into a format that can be processed by computers has been developed by academics. The new tool could revolutionise the way scientific papers are written and help scientists make creative leaps, researchers say. Computers already help scientists by performing complex calculations and making information easier to analyse. But they are less suited to analysing and comparing experimental results. "Computers are not very good with natural language, they need to have things as formalised as possible," says Ross King, a researcher at Aberystwyth University in Wales, who developed the framework with colleague Larisa Soldatova.

The first 11 teams for a race in which robot cars will jostle with real ones along mocked-up city streets have been announced. The teams must construct autonomous vehicles to navigate an unfamiliar urban environment in the shortest time possible. The robot racers will face a "simulated" urban course 96 kilometres (60 miles) in length in November 2007. The course will feature urban obstacles, such as trees and buildings, traffic signs and other moving vehicles. Its location is yet to be disclosed.

A computer that learns to play a'scissors, paper, stone' by observing and mimicking human players could lead to machines that automatically learn how to spot an intruder or perform vital maintenance work, say UK researchers. CogVis, developed by scientists at the University of Leeds in Yorkshire, UK, teaches itself how to play the children's game by searching for patterns in video and audio of human players and then building its own "hypotheses" about the game's rules. In contrast to older artificial intelligence (AI) programs that mimic human behaviour using hard-coded rules, CogVis takes a more human approach, learning through observation and mimicry, the researchers say. The older approach is fraught with problems, as computers struggle when faced with situations that fall outside the remit of these rules and when new rules are introduced. "A system that can observe events in an unknown scenario, learn and participate just as a child would is almost the Holy Grail of AI," says Derek Magee from the University of Leeds.