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Give a computer a task that can be crisply defined — win at chess, predict the weather — and the machine bests humans nearly every time. Yet when problems are nuanced or ambiguous, or require combining varied sources of information, computers are no match for human intelligence.
Few challenges in computing loom larger than unraveling semantics, understanding the meaning of language. One reason is that the meaning of words and phrases hinges not only on their context, but also on background knowledge that humans learn over years, day after day.

Since the start of the year, a team of researchers at Carnegie Mellon University — supported by grants from the Defense Advanced Research Projects Agency and Google, and tapping into a research supercomputing cluster provided by Yahoo — has been fine-tuning a computer system that is trying to master semantics by learning more like a human. Its beating hardware heart is a sleek, silver-gray computer — calculating 24 hours a day, seven days a week — that resides in a basement computer center at the university, in Pittsburgh. The computer was primed by the researchers with some basic knowledge in various categories and set loose on the Web with a mission to teach itself.

“For all the advances in computer science, we still don’t have a computer that can learn as humans do, cumulatively, over the long term,” said the team’s leader, Tom M. Mitchell, a computer scientist and chairman of the machine learning department.

The Never-Ending Language Learning system, or NELL, has made an impressive showing so far. NELL scans hundreds of millions of Web pages for text patterns that it uses to learn facts, 390,000 to date, with an estimated accuracy of 87 percent. These facts are grouped into semantic categories — cities, companies, sports teams, actors, universities, plants and 274 others. The category facts are things like “San Francisco is a city” and “sunflower is a plant.”

NELL also learns facts that are relations between members of two categories. For example, Peyton Manning is a football player (category). The Indianapolis Colts is a football team (category). By scanning text patterns, NELL can infer with a high probability that Peyton Manning plays for the Indianapolis Colts — even if it has never read that Mr. Manning plays for the Colts. “Plays for” is a relation, and there are 280 kinds of relations. The number of categories and relations has more than doubled since earlier this year, and will steadily expand.

The learned facts are continuously added to NELL’s growing database, which the researchers call a “knowledge base.” A larger pool of facts, Dr. Mitchell says, will help refine NELL’s learning algorithms so that it finds facts on the Web more accurately and more efficiently over time.

NELL is one project in a widening field of research and investment aimed at enabling computers to better understand the meaning of language. Many of these efforts tap the Web as a rich trove of text to assemble structured ontologies — formal descriptions of concepts and relationships — to help computers mimic human understanding. The ideal has been discussed for years, and more than a decade ago Sir Tim Berners-Lee, who invented the underlying software for the World Wide Web, sketched his vision of a “semantic Web.”

Today, ever-faster computers, an explosion of Web data and improved software techniques are opening the door to rapid progress. Scientists at universities, government labs, Google, Microsoft, I.B.M. and elsewhere are pursuing breakthroughs, along somewhat different paths.

For example, I.B.M.’s “question answering” machine, Watson, shows remarkable semantic understanding in fields like history, literature and sports as it plays the quiz show “Jeopardy!” Google Squared, a research project at the Internet search giant, demonstrates ample grasp of semantic categories as it finds and presents information from around the Web on search topics like “U.S. presidents” and “cheeses.”

Still, artificial intelligence experts agree that the Carnegie Mellon approach is innovative. Many semantic learning systems, they note, are more passive learners, largely hand-crafted by human programmers, while NELL is highly automated. “What’s exciting and significant about it is the continuous learning, as if NELL is exercising curiosity on its own, with little human help,” said Oren Etzioni, a computer scientist at the University of Washington, who leads a project called TextRunner, which reads the Web to extract facts.

Computers that understand language, experts say, promise a big payoff someday. The potential applications range from smarter search (supplying natural-language answers to search queries, not just links to Web pages) to virtual personal assistants that can reply to questions in specific disciplines or activities like health, education, travel and shopping.

“The technology is really maturing, and will increasingly be used to gain understanding,” said Alfred Spector, vice president of research for Google. “We’re on the verge now in this semantic world.”

With NELL, the researchers built a base of knowledge, seeding each kind of category or relation with 10 to 15 examples that are true. In the category for emotions, for example: “Anger is an emotion.” “Bliss is an emotion.” And about a dozen more.

The label is scrawled and inky, but it unmistakably says "Nyassa. Dr Livingston." Despite the spelling mistake, it's the Doctor Livingstone, I presume (quite rightly). Suddenly we are transported back to tropical central Africa in the early 1860s. David Livingstone was in what is modern-day Malawi, where it is hot and dry or hot and humid, except in the freezing night-time highlands. Livingstone's wife Mary had recently died, and members of his expedition were starving by the end of a long trip.

For all this, the medical missionary was also a professional explorer, and what he had found was a new plant he called Faroa nyasica. The sample of dried flowers, stems, leaves and roots (like a shrivelled brown miniature hydrangea, though it is unrelated) was preserved and taken back to England, where it was donated to the Royal Botanic Gardens at Kew in west London, taped to the top corner of a piece of paper and filed. And there it still is, along with 7 million other specimens stored in Kew's Herbarium – the 18th century building attached to the grounds of the gardens dedicated to this purpose.

David Simpson, one of the assistant keepers of the Herbarium, shows me several specimens that illustrate its history, encompassing the rise and fall of the British Empire and figures including Captain Bligh, Charles Darwin and the Hookers of Kew (Sir William Hooker was the first director of the Royal Botanic Gardens, followed in that role by his son, Joseph, in 1865). There were many lesser-known adventurers, too, successes and failures who gave up their creature comforts – even their lives – to help build what is believed to be the world's finest collection of samples of plants and fungi and related diaries, journals, letters, books and paintings .

The Herbarium might be run by "keepers", but it is an active research centre: every year many of its 180 scientists travel the world, returning with 30,000 to 50,000 new samples. They are mapping new or lost discoveries (last year more than 250 of 2,000 newly "discovered" plants were found by Kew staff) and examining how ecosystems are coping in the face of human exploitation and climate change.

Each week, on average, 50 scientists visit the Herbarium to consult the specimens, and hundreds of samples are loaned out elsewhere. Every 40 years, on average, the building has to be extended to cope with the growing collection, with the opening of a new wing officially celebrated this month.. In two weeks' time, scientists at Kew will also announce the results of the most comprehensive study ever to find out how many of the world's one million or so named plants are at risk of extinction.

"This collection is not a museum," says David Simpson. "It's a museum in one sense, but it's also a well-used, vitally important collection that's equivalent to a database of plant information. Plants are not just beautiful and decorative; without them we simply couldn't survive. From the sheets we sleep on, the clothes we wear for warmth and the food and medicine we depend on, plants are invaluable to humanity; their diversity sustains us now, and in the future it will enable us to adapt, innovate and ultimately to survive."

History's first enthusiastic botanist, as Carolyn Fry recounts in her recent study of the subject, The Plant Hunters, was the bearded Queen Hatshepsut, an Egyptian pharaoh in the 15th century BC. Reliefs from her prosperous reign show ships loaded with ebony and myrrh trees, as well as apes and panther skins taken from a mysterious land called Punt (its identity is still disputed). Later, Alexander the Great sent home specimens from his wars in north Africa and the east, and successive armies transported plants into their new territories: the Romans sowing wheat, corn, barley and olives to feed their armies; Muslims spreading orchard fruits like sour oranges, lemons, limes and apricots, and showy flowers – most famously at the Alhambra palace in the Spanish city Granada.

drive from www.guardian.co.uk

We have all witnessed it – a packed dancefloor of bodies gyrating perfectly to the beat suddenly being emptied by the unwelcome appearance of a man flailing his arms about wildly.

But for the millions of wannabe lotharios who find it impossible to dance without looking like a malfunctioning windmill, a solution may be at hand: psychologists claim to have discovered the key dance moves that make men attractive to women.

As the single most important arena where humans select their mates, the dancefloor can inspire terror and longing – but more often embarrassment and hilarity. Millions strut their stuff every night in venues across the country, but no scientific study of what makes a successful dancer has been made until now.

Researchers at Northumbria University identified differences between "good" and "bad" male dancers based on the responses they provoke in women. The results, which are surprisingly detailed, suggest that the speed of the right knee is critical, as is the size and variability of movement of the neck, trunk, left shoulder and wrist.

Women were most excited by men who danced vigorously, making large movements of their upper body and head, but who also varied their movements, showing creativity and flair. Head bangers were a definite turn-off. Those who can emulate the street dancers Diversity, who won Britain's Got Talent last year, will garner plenty of female admirers, they said. But those who lean towards folk dancing of the Riverdance kind face disappointment – Irish dancing, with its focus on leg kicking and a static upper body, is unlikely to set women's hearts racing.

Nick Neave, who led the research, published in Biology Letters, said: "This is the first study to show objectively what differentiates a good dancer from a bad one. Men all over the world will be interested to know what moves they can throw to attract women."

The researchers have posted videos of good and bad dancers on the web, so men keen to put the findings into practice can do so.

Male volunteers were filmed with a 3D camera system as they danced to a basic rhythm, and avatars – humanoid characters – were programmed to reproduce their moves so that 35 female volunteers could rate them for sex appeal without being influenced by their level of physical attractiveness.

Dr Neave said: "We now know which area of the body females are looking at when they are making a judgement about male dance attractiveness. If a man knows what the key moves are, he can get some training and improve his chances of attracting a female through his dance style."

But his own initial response had been more ambivalent, he confessed. "When I saw the good dancer I thought he was a bit of a show off. I thought 'What a pillock'. But he has got that flair and variability and creativity. If you had had a drink you might think 'He's interesting, I'll go and have a chat.'"

The bad dancer, walking around in a circle making the same stereotypical movements, was more obvious – small, tentative movements with little hint of vigour or variability.

The researchers added that movement plays an important role in animal courtship, with males performing elaborate courtship dances to attract females. Dance movements form "honest signals of a man's reproductive quality, in terms of health, vigour or strength".

drive from www.independent.co.uk

A little black calf with spindly legs has added a high-tech twist to the traditional world of Spanish bullfighting. Got, the country's first cloned fighting bull, was born this week, weighing in at 25kg, in the northern province of Palencia. His late father, Vasito, was a pedigree stud from Andalucia and his surrogate mother was a Swiss Holstein milk cow.

A team of scientists from the Valencia Foundation for Veterinary Research and the Prince Felipe Research Centre toiled for three years to achieve this test-tube feat, beating a rival bid to clone a prized Spanish stud in the US. "He's spectacular, healthy, black like a carbon mine and a perfect photocopy," lead researcher Vicente Torrent said as Got made his societal debut yesterday. Scientists say the objective of the experiment, which cost €28,000 (£24,000), is to perfect techniques that could be used to clone any endangered mammal.

Bullfighting enthusiasts are already speculating about the possibility of seeing clones of legendary fighting bulls in the ring. But animal rights activists are outraged at Got's arrival. "We express our deepest condemnation of this practice, for it leads to the genetic manipulation of a species, with the twisted objective of maintaining the falsehood that bulls are fighters by nature," a statement by AnimaNaturalis said.

drive from www.independent.co.uk