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Automation, Artificial Intelligence And The Human

Automation has already far exceeded the physical capabilities of humans and now artificial intelligence is on the brink of surpassing our mental capacity. Combining the two may be playing with fire, but could the correct application lead to untold benefits?

In his collection of essays, A Message to Garcia, Elbert Hubbard wrote, ‘One machine can do the work of fifty ordinary men. No machine can do the work of one extraordinary man.’ This might have been true of pure automation, but combined with artificial intelligence, our fears are Hubbard’s line will be rendered redundant. That is to say, in comparison to the super-efficient and hyper-intelligent, we will all be somewhat ordinary. But it doesn’t have to be this way. Not if we work together...

Before I explain why, there is a very distinct, albeit fine line, between artificial intelligence and automation which needs to be addressed. Today, automation is the more ubiquitous. It can be found everywhere and is programmed to remove manual, repetitive and tedious work. It is a failsafe which does not make human error, but functions exactly as it is designed to, without cognitive thought. Automation, for instance, orchestrates the processes that enable you to order a takeaway at the push of a button.

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IBM’s Newest Program Uses AI to Solve the Biggest Problems Facing Humanity Today

IN BRIEF

IBM announced its Science for Social Good initiative and the 12 projects that will comprise it for 2017. The program uses big data, deep learning, and AI to solve complex social problems.

DATA-DRIVEN SOLUTIONS

On June 6, IBM launched Science for Social Good, a new program designed to take on some of the world’s weightiest problems using technology and data. The team of researchers, nonprofits, and postdoctoral fellows will be working on 12 projects for the remainder of 2017 alone, each aligning with at least one of the United Nations’ (UN) Sustainable Development Goals. These goals describe the most significant threats and inequalities that exist in the world today and sets them forth as problems to be solved by 2030.

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IBM Watson presents Soul Machines, LENDIT Conference 2017 (Professional Camera)

Published on 19 Mar 2017

Shantenu Agarwal from IBM Watson introduces "Rachel" Avatar from Soul Machines, on stage at the LendIt Conference in New York City 2017. Human-like Avatars with personality and character. Powered by Watson Artificial Intelligence in conjunction with Soul Machines Emotional Intelligence. She can see you and hear you, as well as being emotionally responsive and receptive. Human-like Avatars with character and personality. Emotional Cognition creating the link between humans and computers; humanising technology

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Why Tech Companies Like IBM and Amazon Brand Artificial Intelligence With Human Names

Artificial intelligence can write copy and manage programmatic media buying at warp speed. It can drive a car and even diagnose cancer. AI is increasingly acting like humans, so companies are putting big resources and marketing money into branding AI with human-like qualities, down to naming their technology after people.

Amazon reportedly picked Alexa for its smart assistant because of its ties to Star Trek and use of soft vowels combined with an ‘x’, making it a unique word that doesn’t easily roll off the tongue (unless you have the misfortune of being named Alexa). Meanwhile, IBM considered a slew of names before landing on Watson, a nod to the company’s first CEO Thomas J. Watson.

“Watson is a human name because it’s a person and it does make the system feel approachable and warm,” said Ann Rubin, vp of branded content and global creative at IBM. “When we do research on Watson, we found that people do think of Watson that way—they think he’s approachable, a ‘humble genius.’ They think he’s smart, that he’s not condescending.”

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AI In The Past And The Future

20 years ago, IBM’s computer, Deep Blue, defeated at the time the undisputed World Chess Champion, Garry Kasparov (who is considered by many to be the greatest chess player of all time). On May 11, 1997, the overall score between Kasparov and Deep Blue was equal when game six was played. The winner of the game would be the winner of the tournament. Deep Blue won the game through a daring move that wrecked Kasparov’s defense and forced him to resign in less than 20 moves.

This was a giant leap in artificial intelligence (AI), the technology that tries to mimic and beat the human intelligence. In spite of this big progress in beating humans in the game of chess, which was considered by many as a symbol of intelligence for a long time, the belief that AI was close to human intelligence in general was rather weak. The game between Deep Blue and the world champion was still fairly even, and as a matter of fact, Kasparov defeated Deep Blue a year before in 1996.

The next challenge for AI was to take on the ancient Chinese game of go. In a 1997 New York Times article, Dr. Piet Hut, an astrophysicist at the Institute for Advanced Study in Princeton, stated that the computer’s ability in defeating humans in go wasn’t very close.

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IBM Watson Concept Expansion

Published on 14 Oct 2015

Concept Expansion enables you to build a specialized dictionary for your cognitive applications. You can enable your app to correctly understand industry specific terminology, or local euphemisms and colloquial terms. With your data and basic training, Watson Concept Expansion rapidly produces a dictionary of concepts that you can use to perform powerful tasks.

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IBM Cloud Targets AI, Compliance And Science Collaboration

Smorgasbord of announcements from IBM includes cloud for deep learning, cloud for compliance, and cloud for scientists

IBM has made three announcements concerning its cloud offerings, which have been tailored for particular vertical industry segments.

The first concerns a private cloud version of its collaborative development environment, called the Data Science Experience. This is geared towards the scientific community.

The second concerns a deep learning cloud that is claimed to significantly reduce deep learning training time thanks to the inclusion of GPU technology.

And the third announcement centres around a more controlled offering for the enterprise market, where compliance and security challenges can often hinder the adoption of cloud technology.

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40% of jobs’ taken by robots by 2030 but AI companies say they’re here to help

In the next 15 years, machines are expected to be able to drive cars, replace soldiers, work on the factory line building components, provide comprehensive customer service, run our financial services, translate and interpret text quicker than humans and and and (the list goes on and on).

Machines are already writing articles for national newspapers (no, not this article) and the fear is that all jobs will go to robots.

Around 40% of jobs will be gone by 2030 in the US, says analysts PwC, and 30% of jobs will go in the UK.

This dystopian view of the future, the one of Terminator destruction rather than Iron Man superhuman powers, is something that artificial intelligence companies are very keen to distance themselves from.

‘We use the term augmented intelligence [rather than artificial intelligence],’ Paul Ryan, head of Watson Artificial Intelligence, IBM UK, tells Metro.co.uk at the AI Summit.

‘We are not pursuing general AI, we’re not building systems that are trying to explore self awareness or consciousness.

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IBM Watson AI system replaces 34 staff at Japanese insurance firm

4TH MAY 2017

Hardly a day goes by without some story or another about robots taking over the world. When they were doing the dirty or dangerous work – digging for coal, checking on high-altitude electrical connections – the robots were welcomed by most. Now, though, they are taking on jobs which are neither dirty nor dangerous and which, it can be argued, are an increasing threat to how our world works today.

One recent example comes out of Japan where an insurance company is replacing 34 of its staff with an artificial intelligence system. The computer – at Fukoku Mutual Life Insurance – will calculate how much policyholders should be paid out. Until now, it was a job done by people but will soon be done by a computer based on IBM’s Watson Explorer, a technology which learns to think and act like a human.

According to reports in Japanese newspapers, the computer will be able to understand medical certificates and the length of hospital stays. It will also be able to understand a patient’s medical history and surgical procedures and then work out how much people should be paid.
The company reckons this switch will help them save about £1 million a year. The system itself will cost £1.4 million with annual £100,000 maintenance costs.

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