Sting has had his brain scanned - so scientists can work out what makes gifted musicians tick. He underwent the examination at a Montreal university the afternoon before a Police concert in the city. Researchers say the scans uncovered an incredible ability to link seemingly different pieces of music together. A Montreal University -professor scanned Sting's brain the afternoon before a Police concert in the city in a bid to find how music is mapped in the brain. The results led to unexpected connections between the 1960s Beatles hit'Girl' and Astor Piazzolla's evocative tango composition'Libertango', at least in the mind of the famously eclectic singer songwriter.

The IQ test has long been dismissed as an inaccurate way to discern how intelligent a person really is - but now scientists may have found a better way. Researchers say MRI scans can measure human intelligence, and define exactly what it is. This could lead to radical leaps in AI with machines programmed to think in the same way we do. Researchers say MRI scans can measure human intelligence - and define what it is. This could lead to radical leaps in AI with machines programmed to think in the same way we do.

Scientists claim to have discovered how and where human imagination comes from. Researchers in the US say the ability to create art, invent tools and think scientifically comes from a neural network which spreads across a large area of the brain. The team, from Dartmouth College, describe the network as'the brain's "mental workspace"' where a person is able to manipulate images, ideas or theories which allows them to come up with new ideas. The researchers have published their report, 'Network structure and dynamics of the mental workspace' in this week's Proceedings of the National Academy of Sciences. The research could also lead scientists to reproduce a similar creative process in artificial intelligence.

Many and long were the conversations between Lord Byron and Shelley to which I was a devout and silent listener. During one of these, various philosophical doctrines were discussed, and among others the nature of the principle of life, and whether there was any probability of its ever being discovered and communicated. They talked of the experiments of Dr. Darwin (I speak not of what the doctor really did or said that he did, but, as more to my purpose, of what was then spoken of as having been done by him), who preserved a piece of vermicelli in a glass case till by some extraordinary means it began to move with a voluntary motion. Not thus, after all, would life be given. Perhaps a corpse would be reanimated; galvanism had given token of such things: perhaps the component parts of a creature might be manufactured, brought together, and endued with vital warmth (Butler 1998).

One of the great aspirations of computer science has been to understand and emulate capabilities that we recognize as expressive of intelligence in humans. Research has addressed tasks ranging from our sensory interactions with the world (vision, speech, locomotion) to the cognitive (analysis, game playing, problem solving). This quest to understand human intelligence in all its forms also stimulates research whose results propagate back into the rest of computer science--for example, lists, search, and machine learning. Going beyond simply retrieving information, machine learning draws inferences from available data. Mitchell describes the application of classifying text documents automatically and shows how this research exemplifies the experiment-analyze-generalize style of experimental research.

In 1950, Alan Turing invented a test for determining a machine's ability to exhibit intelligent behavior. At the time, some predicted that so-called "Strong A.I.," that is, artificial intelligence that matches or exceeds human intelligence, could be achieved in a few decades. Over sixty years later, every machine that has been tasked with simulating human intelligence has failed the so-called Turing Test. And yet, scientists have become both impressed and alarmed by the tremendous leaps forward in A.I. capabilities in recent years. A.I. has been put into common use by financial institutions, and found promising applications in medical equipment, search technology, games and transportation systems.

Your child is already a creative genius by virtue of being human. Humans are far more creative than any other species. Sure, chimpanzees have come up with ideas like termite fishing (using a stick to get tasty termites out of a hole), but most of us would contend that inventions such as space travel and the Large Hadron Collider are slightly more impressive. Expert reveals five tips that parents can use to make their kids creative geniuses. Yet humans vary in creative ability – some of us are simply better at thinking outside the box than others.

Axiom, a legal staffing-turned-technology company, recently announced a five-year deal with Johnson & Johnson (J & J) to provide multi-shore contract management services to the pharmaceutical giant. Axiom will support J&J's global procurement contracting function, helping to standardize its vast trove of procurement agreements across a dozen contract types and 10 languages. This is not Axiom's lone big dollar, long-term contract with a major corporation. A couple years ago, it inked an eye-popping $73 million deal with Credit Suisse to process the bank's "master trading agreements." Axiom's metamorphosis from staffing to technology is emblematic of the maturing face and changing focus of legal service providers.

Owing to the data deluge and the Cambrian explosion of machine learning techniques over the past decade, one might have expected the transformation of marketing strategy into a predominantly quantitative discipline by now. The fact that it hasn't happened yet, and the observation that marketing is still influenced by a lot of qualitative inputs can be ascribed to two reasons, in my opinion. The first and principal reason continues to be institutional inertia. Second, there is a significant communication and knowledge gap between data scientists and marketers, owing to their relative lack of familiarity with the other side's perspectives and paradigms. The successful marketer of the next decade is someone who is conversant with management theories of Kotler[1] as well as machine learning advances by Hinton[2]/LeCun[3]/ Ng[4].

One of the most commonly used methods of measuring human intelligence is the IQ test. However, this approach has received widespread criticism due to its perceived inability to capture the whole gamut of elements that determines human intelligence. Howard Gardner, proposed the theory of multiple intelligences in 1983. According to him, IQ tests have little relevance in reality. He denies there is general intelligence, and his theory instead suggests the presence of separate domains of ability.