Thursday, February 23, 2012

'Genius' computer with an IQ of 150 is 'more intelligent' than 96 per cent of humans !!!


  • Software uses mixture of logic and 'human-like' thinking 

  • Score is classified as 'genius' 

  • It could 'spot patterns' in financial data


  • A computer has become the first to be classed as a 'genius' after scoring 150 in an IQ test.

    The average score for people is 100. A score of 150 ranks the artificial intelligence programme among the top four per cent of humans.

    The programme uses a mixture of mathematical logic and 'human-like' thinking, enabling it to outperform previous software on IQ tests.



    Even advanced maths programmes usually score below 100.

    The software was designed by a team led by researcher Claes Strannegård at the University of Gothenburg. His aim was to make a programme that 'thinks' like a person.
    'We're trying to make programmes that can discover the same types of patterns that humans can see,' he says.
    IQ tests are based on two types of problems - seeing visual patterns and guessing number sequences.

    The Swedish research group believes that number sequence problems are only partly mathematics – psychology is important too.
    Strannegård says 'One, two - what comes next? Most people would say 3, but it could also be a repeating sequence like 1, 2, 1 or a doubling sequence like 1, 2, 4. Neither of these alternatives is more mathematically correct than the others. What it comes down to is that most people have learned the 1-2-3 pattern.'

    he group is therefore using a psychological model of human patterns in their software.

    They have integrated a mathematical model that models human-like The group has improved the programme that specialises in number sequences to the point where its score implies an IQ of at least 150.
    'Our programmes are beating the conventional math programmes because we are combining mathematics and psychology.'

    The programme's 'human-like' thinking could have uses outside IQ tests. It can spot 'patterns' in any information that has a human component, such as financial data.

    'Our method can potentially be used to identify patterns in any data with a psychological component, such as financial data. But it is not as good at finding patterns in more science-type data, such as weather data, since then the human psyche is not involved,' says Strannegård.