what is difference between mind and machine ?

Man and machine:


As MATURE INDUSTRIES, information technology has advanced so rapidly that it has now become synonymous with "technology" itself
Today, more than 1.5 billion people enjoy instant access to the world's knowledge using pocket size device.
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Every one of today's smart phones has thousand of time more processing power than the computer that guide astronauts to the moon. And if Moore's law continues apace, tomorrow's computer will be even more powerful

Computer already have enough power to outperform people in activities we used to think of as distinctively human.

In 1997, IBM,s Deep blue defeat world chess champion Garry Kasparov. Jeopardy! best-ever contestant, Ken Jennings, succumbed to IBM,s Watson in 2011. 



And Google's self  deriving cares are already on California roads today. Dale Earnhardt Jr. needn't feel threatened by them, but the Guardian worries (on behalf of the million of chauffeurs and cabbies in the world) that self-driving cares "could drive the next way of unemployment.

SUBSTITUTION VS. COMPLEMENTARITY:

Fifteen year ago, American worker were worried about competition from cheaper Mexican substitutes. And that made sense, because human really can substitute for each other.

Today people think they can hear Ross Perot's giant sucking sound"Once more, but they trace it back to server farms somewhere in Texas instead of cut-rate factories in Tijuana.

Americans fear technology in the near future because they see it as a replay of the globalization of the near past.
But the situation are very different: people compete for jobs and for resources; computer for neither.


Globalization Means substitution:

When perot warned about foreign competition, both George H. W. Bush and Bill Clinton preached the gospel of free trade: since every person has a relative strength at some particular job, in theory the economy maximizes wealth when people specialize according to their advantages and then trade with each other. 

In practice, it's not unambiguously clear how well free trade has worked, for many workers least.

Gain from trade are greatest when there's a big discrepancy in comparative advantages, but the global supply of workers willing to do repetitive task for an extremely small wags is extremely large.

People don't just compete to supply labor; they also demand the same resource.
While American consumers have benefited trom access to cheap toys and textiles from china, they've had to pay higher prices for the the gasoline newly desired by millions of chinese motorist.

Whether people eat shark fins in shanghai or fish tacos in San Diego, they all need food and they all need shelter. And desire doesn't stop at subsistence-people will demand ever more as globalization continues.

Now that million of Chinese peasant can finally enjoy a secure supply of basic Calories, they want more of them to come from pork instead of just grain.

 The convergence of desire is even  more obvious at the top: all oligarchs have  the same taste in Cristal, from Petersburg to pyongyang. 


Technology means complementarity

Now think about the prospect of competition from computer instead of competition from human workers.

On the supply side, computers are far more different from people than any two people are different from each other: men and machines are good at fundamentally different things: People have intentionally-we from plans and make decision in complicated situation.

We're less good at making sense of enormous of data. Computer are exactly the opposite: they excel at efficient data processing, but they struggle to make basic judgments that would be simple for any human.


The Ideology of computer science.


Why do so many people miss the power of complementarity?
It start in school. Software engineer tend to work on projects that replace human efforts because that's what they're trained to do.

Academics make their reputations through specialized research; their primary goal is to publish papers, and publication means respecting the limits of a particular discipline.

For computer scientists, that means reducing human capabilities into specialized tasks that computers can be trained to conquer one by one.

Just look at the trendiest fields in computer science today. The very term "machine learning" evokes imagery of replacement, and its boosters seem to believe that computers can be taught to perform almost any task, so long as we feed them enough training data.

Any user of Netflix or Amazon has experienced the result of machine learning firsthand: both companies use algorithms to recommend product based on your viewing and purchase history.

Feed them more data and the recommendations get ever better. Google translate works the same way, providing rough but serviceable translation into any of the 80 languages it supports-not because the software understands human language, but because it has extracted patterns through statistical analysis of a huge corpus of text.


Ever smarter computer: friend or foe?

The future of computing is necessarily full of unknowns. It's become conventional to see ever-smarter anthropomorphized robot intelligence like Siri and Watson as harbingers of things to come; once computers can answer all our question, perhaps they'll ask why they should remain subservient to us at all.

The logical endpoint to this substitution  thinking is called "strong artificial intelligent (AI)".

Computer that eclipse human on every important dimension. Of course, the Luddites are terrified by the possibility.

It even makes the futurists a little uneasy; it's not clear whether strong AI would save humanity or doom it.

Technology is supposed to increase our mastery over nature and reduce the role of  chance in our lives; building smarter-than-human computers could actually bring chance back with a vengeance.

Strong AI is like a cosmic lottery ticket: if we win, we get utopia; if we lose, Skynet substitutes us out of existence.

But even if strong AI is a real possibility rather than an imponderable mystery, it won't happen anytime soon: replacement by computers is worry for the 22nd century.

Indefinite fears about the far future shouldn't stop us from making definite plans today.

Luddites claim that we shouldn't build the computers that might replace people someday; crazed futurist argue that we should. 

These two position are mutually exclusive but they are not exhaustive: there is room in between for sane people to build a vastly better world in the decades ahead.

As we find new ways to use computers, they won't just get better at the kinds of things people already do; they'll help us to do what was previously unimaginable.


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