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ELIANA BENADOR: TRYING TO KEEP ARTIFICIAL INTELLIGENCE HUMAN-FRIENDLY

Just as robotics have been advancing and absorbing job opportunities from humans, now there is a new field that is developing and bringing with it a big question mark for the fate of mankind.   

It is artificial intelligence.  There is a definite concern about the potential advances in this realm. If but most of all, when computer programs grow to advanced enough levels where they can teach themselves computer science it is more than likely that, naturally, they could use that knowledge to improve themselves.  Such a situation could quickly spiral in an ever-increasing super-intelligence.

In this realm, there is a  question mark and that is:  Under those circumstances, would AI remain friendly to humans?

Naturally, if that were so, it would be very good and cause no problem.  In that case, it would have the prospect to speed up research in a variety of domains.

However, there is a genuine risk that artificial intelligence may have little use for human emotions, conflicts, personality issues and other factors.  Therefore, based on a cold perception of the situation, and either out of malevolence or perceived necessity, they could end up wanting to destroy mankind.

The good news in this respect are brought up by The Guardian reporting that technology entrepreneur Elon Musk is investing $10 million to make sure AI remains human-friendly.   

Musk considers his investments in AI research as a way of “keeping an eye on what’s going on,” rather than as something which would offer a viable return on capital.

The Musk donation went to the Future of Life Institute (FLI) for a global research program aimed at ensuring that artificial intelligence (AI) remains safe for humanity.

Meanwhile, researchers at Google have succeeded in a major step forward int he field of artificial intelligence, as they developed the first computer capable of independently learning tasks.

artificial intelligence

The “Deep-Q Network” computer, created by the British tech firm DeepMind that Google acquired last year, learned to play 49 different old-school Atari games, like Space Invaders and Breakout, and was able to come up with its own strategies to attain victory.

Unlike IBM’s Deep Blue, which was built specifically to be a master at Chess, or Watson, which beat Jeopardy champs in a landslide, the Deep-Q was built through trial and error and constant reprocessing of feedback to find winning strategies. This means that the program can come up with strategies on its own without the need for specific programming.

“The ultimate goal is to build smart, general-purpose [learning] machines. We’re many decades off from doing that,” said artificial intelligence researcher and DeepMind founder Demis Hassabis, who coauthored a study published this week in the journal Nature. “But I do think this is the first significant rung of the ladder that we’re on.”

“With Deep Blue, it was team of programmers and grand masters that distilled the knowledge into a program,” said Hassabis. “We’ve built algorithms that learn from the ground up.”

A very important piece of information is that “According to the researchers, the algorithm is based on the human biological neural network, in that it allows for complex and multidimensional tasks that require complex thought and abstractions. This means the machine can “learn” by trial and error.

Using what is known as a “deep learning” method, Deep-Q can turn basic visual input into meaningful concepts in the same way that the human brain takes in what it sees around it to learn.”

Truly amazing!  

Though the computer could successfully master games like “Alien Invaders,” there are still some limitations to its capabilities. It performed rather poorly at “Montezuma’s Revenge” and “Ms. Pacman,” which require more abstractions, according to coauthor Volodymyr Mnih.

Luckily, for now, the machine’s intelligence equates to that of a toddler.

“It’s mastering and understanding the construction of these games, but we wouldn’t say yet that it’s building conceptual knowledge, or abstract knowledge,” said Hassabis.

While there seems to be a certain wait-time for further developments in the field of AI, we should look into progress much sooner.

As these machines are no humans by any length, their job is only to be intelligent, they will have all the elements and they will not be bothered by waste of time that we as humans know.  Wasting time, will not be in their sphere of action.  Pure productivity.  And an incredible resolution to be and become better in an obsessive fashion.

Beware AI.

©ElianaBenador

Categories:   opinion

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