Tuesday, April 07, 2015 12:22:09 AM
Elon Musk on Superintelligent Robots: We'll Be Lucky If They Enslave Us as Pets
Written by Jason Koebler
March 23, 2015 // 09:22 AM EST
It's no secret that modern-day renaissance man Elon Musk fears what could happen if super intelligence robots self actualize—he once said that we're "summoning the demon [ http://motherboard.vice.com/read/elon-musk-on-artificial-intelligence-pentagrams-and-hal-9000 (video next item below)]" with AI research—but Sunday, Musk detailed exactly how he thinks how artificial intelligence could end humanity.
Musk, the founder of Tesla and SpaceX, went on StarTalk, Neil deGrasse Tyson's weekly podcast, to talk about all things future, and AI was a main topic of conversation.
"I'm quite worried about artificial super intelligence these days. I think it's something that's maybe more dangerous than nuclear weapons," Musk said. "We should be really careful about that. If there was a digital super intelligence that was created that could go into rapid, recursive self improvement in a non logarithmic way, that could reprogram itself to be smarter and iterate really quickly and do that 24 hours a day on millions of computers, then that's all she wrote."
[audio of the complete interview ( https://soundcloud.com/startalk/the-future-of-humanity-with-elon-musk ) embedded; original source http://www.startalkradio.net/show/the-future-of-humanity-with-elon-musk/ ]
If artificial intelligence is going to kill us, that's generally the way it's been predicted in sci-fi movies and by people who ponder such things [ http://motherboard.vice.com/read/super-intelligent-ai-could-wipe-out-humanity-if-were-not-ready-for-it ]: The intelligence will self actualize and teach itself how to become much, much smarter than us, and then it will be uncontrollable (work on superintelligence is ongoing [ http://motherboard.vice.com/read/a-global-arms-race-to-create-a-superintelligent-ai-is-looming ]). Musk said that we have to consider why, exactly, we're trying to make super intelligent robots.
If it's for human companionship and to make us happier (as detailed in Her [ http://en.wikipedia.org/wiki/Her_%28film%29 ], which you should watch if you haven't), well, maybe that won't end so well.
"The utility function of the digital super intelligence is of stupendous importance. What does it try to optimize? We need to be really careful with saying, ‘how about human happiness?’" Musk said. "It can conclude that an unhappy human should be terminated. Or that we should all be captured and [constantly] injected with dopamine and serotonin to optimize happiness. I'm just saying we should exercise caution."
Tyson asked Musk if he thought they'd domesticate us: "We'll be like a pet labrador if we're lucky."
Of course, Musk wasn't just spitballing. This is something he's thought about for a long time, and it's one of his more controversial talking points. He's even ?spent $10 million trying to keep ultra intelligent AI from becoming dangerous [ http://www.wired.com/2015/01/elon-musk-ai-safety/ ].
Tyson and his cohost for the episode, Bill Nye, are of course no slouches when it comes to thinking about the implications of tech, and both of them thought his theories were a little out there.
"Twenty percent of the world's population does not have electricity. They've never made a phone call," Nye said. "I think people have to keep in mind—computers are so reliable—but somebody is literally or in a sense shoveling the coal. What happens if you unplug the supercomputer or intelligence?"
Tyson said that guys like Musk are worried super intelligent robots will prevent you from unplugging it, but Nye asked how a computer would "create that thing to keep you from doing that? It seems like a solvable problem."
Likewise, artificial intelligence researchers have said that Musk's comments have a chilling effect [ http://motherboard.vice.com/read/we-need-to-talk-about-how-we-talk-about-artificial-intelligence ] on research, and that we are far, far away from ever having to worry about being overrun by robots.
But the idea of creating digital software that goes haywire and is uncontrollable isn't just a nightmare scenario—it's already happened. Consider that Stuxnet, a computer virus believed to have been created by the NSA to physically damage Iranian uranium enrichment factories, has now spread far across the internet and has infected Russian nuclear plants [ http://motherboard.vice.com/blog/stuxnet-americas-nuclear-plant-attacking-virus-has-infected-the-international-space-station ].
Stuxnet is a very specific piece of software that doesn't do much on regular computers besides replicate and spread itself, but it's easy to imagine superintelligence spreading itself across connected devices around the world. And then, maybe the only answer is to pull the plug on computers that we need. And then where are we?
© 2015 Vice Media LLC
http://motherboard.vice.com/read/elon-musk-on-superintelligent-robots-well-be-lucky-if-they-enslave-us-as-pets [with comments; the included YouTube excerpt of the interview at http://www.youtube.com/watch?v=pt3n9B8_e-8 (no comments yet)]
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One-on-one with Elon Musk
Published on Oct 31, 2014 by AeroAstroMIT [ http://www.youtube.com/channel/UCDeOZ2v5NhlIioMGux4_h-A / http://www.youtube.com/user/AeroAstroMIT , http://www.youtube.com/user/AeroAstroMIT/videos ]
MIT Aeronautics and Astronautics Department Head Jaime Peraire interviews SpaceX and Tesla CEO/founder Elon Musk, October 24, 2014, as the final session of the AeroAstro 1914-2014 Centennial Symposium.
http://www.youtube.com/watch?v=PULkWGHeIQQ [the comments re AI that have been noted are in the Q&A; with comments]
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Elon Musk, Neil deGrasse Tyson laugh about artificial intelligence turning the human race into its pet labrador
“We won’t be like a pet labrador if we’re lucky,” Elon Musk said.
(Rebecca Cook/Reuters)
By Matt McFarland
March 24, 2015
Elon Musk has already ignited a debate over the dangers of artificial intelligence [ http://www.washingtonpost.com/blogs/innovations/wp/2014/10/24/elon-musk-with-artificial-intelligence-we-are-summoning-the-demon/ ]. The chief executive of Tesla and SpaceX has called it humanity’s greatest threat, and something even more dangerous than nuclear weapons.
Musk publicly hasn’t offered a lot of detail about why he’s concerned, and what could go wrong. That changed in an interview with scientist Neil deGrasse Tyson, posted Sunday [ http://www.startalkradio.net/show/the-future-of-humanity-with-elon-musk/ ].
Musk’s fears lie with a subset of artificial intelligence, called superintelligence. It’s defined by Nick Bostrom, author of the highly-cited book “Superintelligence [ http://www.amazon.com/Superintelligence-Dangers-Strategies-Nick-Bostrom/dp/0199678111 ],” as “any intellect that greatly exceeds the cognitive performance of humans in virtually all domains of interest.”
Musk isn’t worried about simpler forms of artificial intelligence, such as a driverless car or smart air conditioning unit. The danger is when a machine can rapidly educate itself, as Musk explained:
“If there was a very deep digital superintelligence that was created that could go into rapid recursive self-improvement in a non-algorithmic way … it could reprogram itself to be smarter and iterate very quickly and do that 24 hours a day on millions of computers, well–”
“Then that’s all she wrote,” interjected Tyson with a chuckle.
“That’s all she wrote,” Musk answered. “I mean, we won’t be like a pet Labrador if we’re lucky.”
“A pet Lab,” laughed Tyson.
“I have a pet Labrador by the way,” Musk said.
“We’ll be their pets,” Tyson said.
“It’s like the friendliest creature,” Musk said, then letting out his lone chuckle of the segment.
“No, they’ll domesticate us,” Tyson said.
“Yes! Exactly,” said Musk, sounding serious again.
“So we’ll be lap pets to them,” Tyson said.
“Yes,” Musk said. “Or something strange is going to happen.”
“They’ll keep the docile humans and get rid of the violent ones,” Tyson theorized.
“Yeah,” Musk said.
“And then breed the docile humans,” Tyson said.
Musk then stressed the importance of what the superintelligence is programmed to optimize. It might seem appealing to have a computer figure out how to make us happier, but that could backfire:
“It may conclude that all unhappy humans should be terminated,” Musk said. “Or that we should all be captured and with dopamine and serotonin directly injected into our brains to maximize happiness because it’s concluded that dopamine and serotonin are what cause happiness, therefore maximize it,” which brought another chuckle from Tyson.
“I’m just saying we should exercise caution,” Musk concluded. You can listen to the entire interview here [ http://www.startalkradio.net/show/the-future-of-humanity-with-elon-musk/ ].
© 2015 The Washington Post
http://www.washingtonpost.com/blogs/innovations/wp/2015/03/24/elon-musk-neil-degrasse-tyson-laugh-about-artificial-intelligence-turning-the-human-race-into-its-pet-labrador/ [with comments]
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Artificial Intelligence Super Mario Gets Hungry And Wants To Kill Goombas
[title taken from http://www.huffingtonpost.com/2015/01/19/artificial-intelligence-super-mario_n_6502664.html [with this video embedded]]
Published on Jan 15, 2015 by AAAI Video Competition [ http://www.youtube.com/channel/UCPnD-1TJvd-Sm7cbAbR83Jw / http://www.youtube.com/user/aaaivideocompetition , http://www.youtube.com/user/aaaivideocompetition/videos ]
Mario Lives! An Adaptive Learning AI Approach for Generating a Living and Conversing Mario Agent
Stephan Ehrenfeld, Fabian Schrodt, & Prof. Dr. Martin V. Butz
Cognitive Modeling, Department of Computer Science, Faculty of Science, University of Tübingen, Germany
Winner of the AAAI ( http://www.aaai.org ) Video Competition ( http://aaaivideos.org ) People's Choice Award.
Click here for a full list of videos:
http://www.youtube.com/playlist?list=PLuOoXrWK6Kz4xqxnoRWt_PtBu6Uu3TAU9
Scientists are teaching Super Mario to think and feel
January 19, 2015
http://www.theverge.com/2015/1/19/7852975/artificially-intelligent-mario-learns-feel [with this video embedded]
Artificial Intelligence helps Mario play his own game
19 January 2015
http://www.bbc.co.uk/newsbeat/30879456
http://www.youtube.com/watch?v=AplG6KnOr2Q [comments disabled]
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Stephen Hawking: 'AI could spell end of the human race'
Published on Dec 2, 2014 by BBC News [ http://www.youtube.com/channel/UC16niRr50-MSBwiO3YDb3RA / http://www.youtube.com/user/bbcnews , http://www.youtube.com/user/bbcnews/videos ]
Professor Stephen Hawking has told the BBC that artificial intelligence could spell the end for the human race.
In an interview after the launch of a new software system designed to help him communicate more easily, he said there were many benefits to new technology but also some risks.
http://www.bbc.com/news/science-environment-30289705 [original non-YouTube posting of same video]
Read more:
Stephen Hawking warns artificial intelligence could end mankind
2 December 2014
http://www.bbc.com/news/technology-30290540
Check out our website: http://www.bbc.com/news
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http://www.youtube.com/watch?v=fFLVyWBDTfo [with comments]
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Google’s Eric Schmidt downplays fears over artificial intelligence
Eric Schmidt sees a bright future for artificial intelligence.
(Shannon Stapleton/Reuters)
By Matt McFarland
March 16, 2015
AUSTIN — Arguably the most alarming part of concerns over artificial intelligence’s potential to end human civilization [ http://www.washingtonpost.com/blogs/innovations/wp/2015/02/20/the-12-threats-to-human-civilization-ranked/ ] is the voices that are speaking out. Proven technology visionaries — from Bill Gates [ http://www.washingtonpost.com/blogs/the-switch/wp/2015/01/28/bill-gates-on-dangers-of-artificial-intelligence-dont-understand-why-some-people-are-not-concerned/ ] to Elon Musk [ http://www.washingtonpost.com/blogs/innovations/wp/2014/10/24/elon-musk-with-artificial-intelligence-we-are-summoning-the-demon/ ] and Stephen Hawking — have warned about the dangers of artificial intelligence. Given humans’ generally poor track record for predicting the future, it stands to reason that the forward thinkers could identify huge technology risks while the rest of us live in ignorance.
But Monday at SXSW, a tech thinker with a long résumé, Google Chairman Eric Schmidt, offered reassurance that we don’t need to be so worried right now.
“I think that this technology will ultimately be one of the greatest forces for good in mankind’s history simply because it makes people smarter,” Schmidt said during a keynote address with author Walter Isaacson and Megan Smith, U.S. chief technology officer.
“I’m certainly not worried in the next 10 to 20 years about that. We’re still in the baby step of understanding things,” Schmidt said. “We’ve made tremendous progress in respect to [artificial intelligence].”
He highlighted benevolent uses of artificial intelligence, such as Google Voice and Google’s translation services. Indeed, from antilock brakes to your iPhone’s autocorrect function, artificial intelligence already surrounds us, with favorable results.
“Stuff beyond that is, at this point, really speculation,” Schmidt said. “I’m not a dystopian. I’m a utopian, if you phrase it that way.”
As chairman of Google, Schmidt has a unique vantage point on how artificial intelligence is impacting our world and how it will continue to do so. Google is a leader in the space. In February, DeepMind, a Google acquisition, devised an algorithm that taught itself to beat Atari video games [ http://www.washingtonpost.com/blogs/innovations/wp/2015/02/25/googles-artificial-intelligence-breakthrough-may-have-a-huge-impact-on-self-driving-cars-and-much-more/ ]. While there’s reason to see Schmidt’s views as reassuring, it’s also worth noting that as the chairman of a leader in artificial intelligence, he has an incentive to underplay the downside of artificial intelligence. If the general public or regulators move to hamper artificial intelligence, Google’s businesses could suffer.
Later in the talk, Schmidt singled out machine learning, a subset of artificial intelligence, as having huge potential to reshape our world for the better.
“I think the biggest trend is going to be the use of machine intelligence of large data sets to solve every problem,” Schmidt said. “I can’t think of a field of study, a field of research — whether it’s English, soft sciences, hard sciences or any corporation — that can’t become far more efficient, far more powerful, far more clever.”
© 2015 The Washington Post
http://www.washingtonpost.com/blogs/innovations/wp/2015/03/16/googles-eric-schmidt-downplays-fears-over-artificial-intelligence/ [with comments]
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I'll Be Back: The Return of Artificial Intelligence
Terminator Salvation, 2009.
Photographer: Richard Foreman Jr./Warner Bros./ Everett Collection
Google, Facebook, Amazon spur rebirth of industry after decades of little corporate attention
by Jack Clark
9:00 AM CST February 3, 2015
The artificial-intelligence industry, a field that conjures up images of humanoid robots and self-aware computer systems, is making a comeback at Silicon Valley companies like Scaled Inference Inc [ https://scaledinference.com/ ].
Inside a sparsely decorated office at the eight-month-old startup, founder Olcan Sercinoglu is developing an AI system that can help predict events, such as what website you’ll read next. While that’s far from the kind of AI found in science-fiction movies, there’s plenty of interest in this new generation of AI tools, which can help with everything from recognizing speech patterns to sorting through thousands of photos.
“There was interest to invest from almost all of the investors that I spoke to,” said Sercinoglu, who raised $13.6 million in funding for his venture in just five months last year after spending 13 years on-and-off at Google Inc. working on AI projects. “Many AI companies have raised significant money without any product plans.”
Scaled Inference is one of more than a dozen startups now forming the backbone of a mini-boom in AI, which is software that exhibits the intuition of people. After two decades of the field suffering from scant research funding and little corporate attention, a rebirth is being spurred by interest from Google, Facebook Inc., Amazon.com Inc. and others, with Alibaba Group Holding Ltd. Chairman Jack Ma saying this week [ http://www.bloomberg.com/news/videos/2015-02-02/ma-alibaba-s-future-is-robots-artificial-intelligence ] that the Chinese e-commerce company will invest significantly in the area. In addition, falling technology costs have made the numerous computations underlying AI cheaper to perform.
In total, 16 AI companies were funded for the first time in 2014, up from two in 2010, according to data compiled by researcher CB Insights for Bloomberg News. The amount invested in the startups—some of which describe themselves as doing machine learning or deep learning—soared to $309.2 million last year, up more than 20-fold from $14.9 million in 2010.
“The field was pretty static for 20 or 30 years,” said venture capitalist Vinod Khosla, who has invested in young AI startups including Scaled Inference and MetaMind Inc. Yet with advancements in computing power and the growing volume of digital information, “the promise has gone up,” he said.
Like Scaled Inference, many of the AI startups aren’t developing Skynet-like systems or human-like machines and instead are focused on making clever tools to solve specific corporate problems. Startup Expect Labs Inc. is creating software so retailers can add speech-processing capabilities to mobile applications. Clarifai Inc. has developed image-recognition systems that can sort through thousands of photos taken by wedding photographers to select the prettiest pictures.
Yet the startups face long odds, given a history of AI flops. In the 1970s, AI funding plunged after the U.S. and U.K. governments became fed up with the slow progress on efforts like autonomous robots. In the 1980s, the market for AI hardware collapsed further when personal computers from Apple Inc. and International Business Machines Corp. became popular.
“The thing I worry about most is over-hype,” Khosla said.
Behind much of the proliferation of AI startups are large companies such as Google, Microsoft Corp., and Amazon, which have quietly built up AI capabilities over the past decade to handle enormous sets of data and make predictions, like which ad someone is more likely to click on. Starting in the mid-2000s, the companies resurrected AI techniques developed in the 1980s, paired them with powerful computers and started making money.
Their efforts have resulted in products like Apple’s chirpy assistant Siri and Google’s self-driving cars. It has also spurred deal-making, with Facebook acquiring voice-recognition AI startup Wit.ai [ http://www.bloomberg.com/news/articles/2015-01-05/facebook-buying-speech-recognition-developer-wit-ai ] last month and Google buying DeepMind Technologies Ltd. in January 2014.
For Google, “the biggest thing will be artificial intelligence,” Chairman Eric Schmidt said last year [ http://www.bloomberg.com/news/articles/2014-03-06/google-s-schmidt-sees-robots-omnipresent-in-a-good-way- ] in an interview with Bloomberg Television’s Emily Chang.
The companies have hired AI academics and engineers, some of whom are now spawning their own startups. Apart from Scaled Inference, former Googlers also founded AI company Moloco Inc. and Petametrics Inc.’s LiftIgniter. Amazon, Microsoft and Google engineers are also in key roles at startups including Sentient Technologies Holdings Ltd., SignalSense Inc. and Clarifai.
“At the big tech companies, you’re working with data at a scale that forces you to solve different problems than you would otherwise,” said Adam Berenzweig, chief technology officer at Clarifai in New York and a former Googler.
Falling technology costs have also helped trigger AI startups. Processing large amounts of data—a foundation of AI work—is cheaper as computer chips have gotten faster and the prices of storing and accessing data have dropped.
Systems called graphical processing units from companies including Nvidia Corp.—which enable companies to take on more of the monotonous-but-numerous computations needed to train and develop AI systems—have also dropped in price as GPUs have been manufactured on a mass scale for gadgets such as video-game consoles.
“The increase in performance over the last 17 years has been extraordinary,” said Jon Peddie of semiconductor market-research firm Jon Peddie Research. In 2014, people could buy a video card that was 84.3 times the performance of one from 2004 for the same price, he said.
The AI boom has also been stoked by universities, which have noticed the commercial success of AI at places like Google and taken advantage of falling hardware costs to do more research and collaborate with closely held companies.
Last November, the University of California at San Francisco began working with Palo Alto, California-based MetaMind on two projects: one to spot prostate cancer and the other to predict what may happen to a patient after reaching a hospital’s intensive care unit so that staff can more quickly tailor their approach to the person.
Theresa O’Brien, an associate chancellor at UCSF, said the university teamed up with the startup—the first such collaboration she’s aware of—because it wants to develop better approaches to bespoke medical treatment by employing computers to sort and link data, which AI can help.
As more AI startups emerge, companies are turning into customers. American Express Co. said it has increasingly been using AI techniques to help automatically spot fraudulent transactions.
“Our machine learning models help protect $1 trillion in charge volume every year, making the decision in less than 2 milliseconds,” Vernon Marshall, American Express’s functional risk officer, wrote in an e-mail, without disclosing which AI companies it works with. “We have been delighted with how well this technology can detect fraud.”
Revenue—which has been in short supply for AI makers in the past—is now trickling in. Sentient [ http://www.sentient.ai/ ], founded in 2007, is charging clients for technology that uses evolutionary algorithms to continuously ingest information and solve quantifiable problems, like how to profitably trade shares on the stock market. The San Francisco-based company closed $103.5 million [ http://www.bloomberg.com/news/articles/2014-11-24/ai-startup-sentient-raises-103-5-million-in-funding ] in financing in November and anticipates having 100 employees by the end of the year, up from 60 workers now, said Sentient Chief Executive Officer Antoine Blondeau.
While Sentient originally made trading systems for its own purposes from its AI technology, it has since applied it to other industries, including using the system to evaluate a hospital’s data to predict the chance of a patient falling into sepsis.
“We expect to grow significantly,” said Blondeau, who declined to disclose Sentient’s revenue or how much it charges for its products. “This is a very nascent space where disruption can be very quick and because of the nature of the problems that are being addressed in a specific case, is highly lucrative.”
©2015 Bloomberg L.P.
http://www.bloomberg.com/news/articles/2015-02-03/i-ll-be-back-the-return-of-artificial-intelligence
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Artificial Intelligence Goes to the Arcade
By Nicola Twilley
February 25, 2015
A shaky video, recorded with a mobile phone and smuggled out of the inaugural First Day of Tomorrow technology conference, in April, 2014, shows an artificially intelligent computer program in its first encounter with Breakout, the classic Atari arcade game. Prototyped in 1975 by Steve Wozniak, the co-founder of Apple, with assistance from Steve Jobs, the other co-founder of Apple, Breakout is a variant of Pong, in which a player knocks bricks from a wall by hitting a ball against it. After half an hour of play, the A.I. program is doing about as well as I would, which is to say not very—but it is trying to move its paddle toward the ball, apparently grasping the rudiments of the game. After another thirty minutes, two hundred rounds in, the A.I. has become a talented amateur: it misses the ball only every third or fourth time. The audience laughs; isn’t this cool?
Then something happens. By the three hundredth game, the A.I. has stopped missing the ball. The auditorium begins to buzz. Demis Hassabis, the program’s creator, advances to the next clip in his video presentation. The A.I. uses four quick rebounds to drill a hole through the left-hand side of the wall above it. Then it executes a killer bank shot, driving the ball into the hole and through to the other side, where it ricochets back and forth, destroying the entire wall from within. Now there are exclamations, applause, and shocked whispers from the crowd. Hours after encountering its first video game, and without any human coaching, the A.I. has not only become better than any human player but has also discovered a way to win that its creator never imagined.
Today, in a paper published in Nature [ http://www.nature.com/nature/journal/v518/n7540/full/nature14236.html , ful access http://www.nature.com/articles/nature14236.epdf?referrer_access_token=6_ZCZLs44V5es9R6kaUl_tRgN0jAjWel9jnR3ZoTv0P5kedCCNjz3FJ2FhQCgXkAMnH5lxK3VZA5OqpAt24MB5m6iQOU8PQiVd1y_3ofu5gClTBtCq0w4US77EIvFh9VwNVL-EehLacalZNtXMyj5a67sdjXqEH_aksjdpCef_zKkFET2MY6qSg3ro1VUrQUplaJvHIcMh-hADJoKJogj4mBAdfaLtWlZ_CJ6FscEzc%3D&tracking_referrer=www.newyorker.com / http://www.nature.com/articles/nature14236.epdf?referrer_access_token=6_ZCZLs44V5es9R6kaUl_tRgN0jAjWel9jnR3ZoTv0P5kedCCNjz3FJ2FhQCgXkAMnH5lxK3VZA5OqpAt24MB5m6iQOU8PQiVd1y_3ofu5gClTBtCq0w4US77EIvFh9VwNVL-EehLacalZNtXMyj5a67sdjXqEH_aksjdpCef_zKkFET2MY6qSg3ro1VUrQUplaJvHIcMh-hADJoKJogj4mBAdfaLtWlZ_CJ6FscEzc%3D ], Hassabis and his colleagues Volodymyr Mnih, Koray Kavukcuoglu, and David Silver reveal that their A.I. has since achieved the same feat with an angling game (Fishing Derby, 1980), a chicken-crossing-the-road game (Freeway, 1981), an armored-vehicle game (Robot Tank, 1983), a martial-arts game (Kung-Fu Master, 1984), and twenty-five others.* In more than a dozen of them, including Stargunner and Crazy Climber, from 1982, it made the best human efforts look pathetic. The Nature article appears just over a year after Hassabis’s company, DeepMind, made its public début; Google bought the firm for six hundred and fifty million dollars in January, 2014, soon after Hassabis first demonstrated his program’s superhuman gaming abilities, at a machine-learning workshop in a Harrah’s casino on the edge of Lake Tahoe. That program, the DeepMind team now claims, is a “novel artificial agent” that combines two existing forms of brain-inspired machine intelligence: a deep neural network and a reinforcement-learning algorithm.
Deep neural networks rely on layers of connections, known as nodes, to filter raw sensory data into meaningful patterns, just as neurons do in the brain. Apple’s Siri uses such a network to decipher speech, sorting sounds into recognizable chunks before drawing on contextual clues and past experiences to guess at how best to group them into words. Siri’s deductive powers improve (or ought to) every time you speak to her or correct her mistakes. The same technique can be applied to decoding images. To a computer with no preëxisting knowledge of brick walls or kung fu, the pixel data that it receives from an Atari game is meaningless. Rather than staring uncomprehendingly at the noise, however, a program like DeepMind’s will start analyzing those pixels—sorting them by color, finding edges and patterns, and gradually developing an ability to recognize complex shapes and the ways in which they fit together.
The program’s second, complementary form of intelligence—reinforcement learning—allows for a kind of unsupervised obedience training. DeepMind’s A.I. starts each game like an unhousebroken puppy. It is programmed to find a score rewarding, but is given no instruction in how to obtain that reward. Its first moves are random, made in ignorance of the game’s underlying logic. Some are rewarded with a treat—a score—and some are not. Buried in the DeepMind code, however, is an algorithm that allows the juvenile A.I. to analyze its previous performance, decipher which actions led to better scores, and change its future behavior accordingly. Combined with the deep neural network, this gives the program more or less the qualities of a good human gamer: the ability to interpret the screen, a knack for learning from past mistakes, and an overwhelming drive to win.
Whipping humanity’s ass at Fishing Derby may not seem like a particularly noteworthy achievement for artificial intelligence—nearly two decades ago, after all, I.B.M.’s Deep Blue computer beat Garry Kasparov, a chess grandmaster, at his own more intellectually aspirational game—but according to Zachary Mason, a novelist and computer scientist, it actually is. Chess, he noted, has an extremely limited “feature space”; the only information that Deep Blue needed to consider was the positions of the pieces on the board, during a span of not much more than a hundred turns. It could play to its strengths of perfect memory and brute-force computing power. But in an Atari game, Mason said, “there’s a byte or so of information per pixel” and hundreds of thousands of turns, which adds up to much more and much messier data for the DeepMind A.I. to process. In this sense, a game like Crazy Climber is a closer analogue to the real world than chess is, and in the real world humans still have the edge. Moreover, whereas Deep Blue was highly specialized, and preprogrammed by human grandmasters with a library of moves and rules, DeepMind is able to use the same all-purpose code for a wide array of games.
That adaptability holds promise. Hassabis has begun partnering with satellite operators and financial institutions to see whether his A.I. could eventually “play” their data sets, perhaps learning to make weather predictions or trade oil futures. In the short term, though, his team has a more modest next step in mind: to design a program that can play video games from the nineteen-nineties. Hassabis, who began working as a game designer in 1994, at the age of seventeen, and whose first project was the Golden Joystick-winning Theme Park, in which players got ahead by, among other things, hiring restroom-maintenance crews and oversalting snacks in order to boost beverage sales, is well aware that DeepMind’s current system, despite being state of the art, is at least five years away from being a decade behind the gaming curve. Indeed, the handful of games in which DeepMind’s A.I. failed to achieve human-level performance were the ones that required longer-term planning or more sophisticated pathfinding—Ms. Pac-Man, Private Eye, and Montezuma’s Revenge. One solution, Hassabis suggested, would be to make the A.I. bolder in its decision-making, and more willing to take risks. Because of the rote reinforcement learning, he said, “it’s overexploiting the knowledge that it already knows.”
In the longer term, after DeepMind has worked its way through Warcraft, StarCraft, and the rest of the Blizzard Entertainment catalogue, the team’s goal is to build an A.I. system with the capability of a toddler. But this, Hassabi said, they are nowhere near reaching. For one thing, he explained, “toddlers can do transfer learning—they can bring to bear prior knowledge to a new situation.” In other words, a toddler who masters Pong is likely to be immediately good at Breakout, whereas the A.I. has to learn both from scratch. Beyond that challenge lies the much thornier question of whether DeepMind’s chosen combination of a deep neural network and reinforcement learning could, on its own, ever lead to conceptual cognition—not only a fluency with the mechanics of, say, 2001’s Sub Command but also an understanding of what a submarine, water, or oxygen are. For Hassabis, this is “an open question.”
Zachary Mason is less sanguine. “Their current line of research leads to StarCraft in five or ten years and Call of Duty in maybe twenty, and controllers for drones in live battle spaces in maybe fifty,” he told me. “But it never, ever leads to a toddler.” Most toddlers cannot play chess or StarCraft. But they can interact with the real world in sophisticated ways. “They can find their way across a room,” Mason said. “They can see stuff, and as the light and shadows change they can recognize that it’s still the same stuff. They can understand and manipulate objects in space.” These kinds of tasks—the things that a toddler does with ease but that a machine struggles to grasp—cannot, Mason is convinced, be solved by a program that excels at teaching itself Breakout. They require a model of cognition that is much richer than what Atari, or perhaps any gaming platform, can offer. Hassabis’s algorithm represents a genuine breakthrough, but it is one that reinforces just how much distance remains between artificial intelligence and the human mind.
© 2015 Condé Nast
http://www.newyorker.com/tech/elements/deepmind-artificial-intelligence-video-games
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'Killer robots' need to be strictly monitored, nations warn at UN meeting
A man walks past a graffiti, denouncing strikes by US drones in Yemen, painted on a wall in Sana’a.
Photograph: Khaled Abdullah/Reuters
Countries warn of potential dangers of autonomous weapons systems they say are at risk of violating international and humanitarian law
Ed Pilkington in New York
Thursday 13 November 2014 14.09 EST
Last modified on Thursday 13 November 2014 19.17 EST
“Killer robots” – autonomous weapons systems that can identify and destroy targets in the absence of human control – should be strictly monitored to prevent violations of international or humanitarian law, nations from around the world demanded on Thursday.
The European Union, France, Spain, Austria, Ireland, the Netherlands, Croatia, Mexico and Sierra Leone, among other states, lined up at a special UN meeting in Geneva to warn of the potential dangers of this rapidly advancing technology. Several countries spoke of the need for ongoing scrutiny to ensure that the weapons conformed to the Geneva conventions’ rules on proportionality in war.
The Spanish delegation went further, invoking the possibility of a new arms race as developed countries scrambled to get ahead. Ireland, the Netherlands and other countries called for “meaningful human control” of lethal weapons to be enshrined in international law, although the meeting also admitted that the precise definition of that principle had yet to be clarified.
The Geneva meeting was the second major gathering of world powers this year to discuss the looming threat or possibility of fully self-operating lethal weapons. As such, it was an indication of mounting global concern about the technology, as its adoption by military forces gathers apace.
The US, the leader in the field, has already switched most of its aerial surveillance capabilities [ http://www.theguardian.com/world/2014/sep/30/war-console-drones-us-military-air-force-pilots-video-games ] to unmanned aircraft – though the drones are still controlled by human pilots. It is a natural next step for the US air force to develop systems that can both deliver and then operate missiles and bombs robotically, with only minimal human intervention.
The New York Times reported [ http://www.nytimes.com/2014/11/12/science/weapons-directed-by-robots-not-humans-raise-ethical-questions.html ] this week that Lockheed Martin has developed a long-range anti-ship missile for the US air force and navy that can fly itself, with no human touch, for hundreds of miles, changing its flight-path autonomously to avoid radar detection. Britain, Israel and Norway already carry out attacks on radar installations, tanks and ships using autonomous drones and missiles, the paper said.
At the previous Geneva meeting on killer robots, Christof Heyns, the UN special rapporteur on extrajudicial, summary or arbitrary executions [ http://www.ohchr.org/EN/Issues/Executions/Pages/SRExecutionsIndex.aspx ], called for an outright ban. “Machines lack morality and mortality, and as a result should not have life and death powers over humans,” he said.
Human Rights Watch [ http://www.hrw.org/ ], which is a co-founder of the Campaign to Stop Killer Robots [ http://www.stopkillerrobots.org/ ], told Thursday’s plenary that a ban was the only practical solution. The group lamented the fact that the UN had spent only eight or nine days over the past two years focused on an area that was fast-moving and raised huge legal and ethical issues.
“There is a sense of urgency about how we deal with killer robots. Technology is racing ahead,” it said.
Regulation of autonomous weapons falls under the so-called “convention on certain conventional weapons [ http://www.unog.ch/80256EE600585943/(httpPages)/4F0DEF093B4860B4C1257180004B1B30?OpenDocument ]” or CCW – a part of the Geneva conventions that deals with the impact of the tools of war on civilian populations. Under CCW, weapons that are deemed to affect civilians indiscriminately or to cause inhumane suffering to combatants can be banned or heavily restricted.
© 2014 Guardian News and Media Limited
http://www.theguardian.com/world/2014/nov/13/killer-robots-strictly-monitored-un-meeting-geneva [with comments]
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Steve Wozniak on AI: Will we be pets to or mere ants to be squashed by our robot overlords?
Credit: Garry Knight
Apple co-founder Steve Wozniak predicts a 'scary' future when artificial intelligence takes over from humans. It will be 'very bad for people,' but will we be pets to our robot overlords or mere ants to be squashed?
By Darlene Storm
Mar 25, 2015 6:27 AM PT
When artificial intelligence truly becomes super smart, will we be pets to our robot overlords or ants to be squashed? Neither scenario is very encouraging, but both were questions asked by Apple co-founder Steve Wozniak as he joined the ranks of prominent people warning that AI will eventually take over and get rid of humans.
"Computers are going to take over from humans, no question," Wozniak said [ http://www.afr.com/technology/apple-cofounder-steve-wozniak-on-the-apple-watch-electric-cars-and-the-surpassing-of-humanity-20150323-1m3xxk ] during an interview with Australian Financial Review. His opinion on artificial intelligence now aligns with worrisome predictions by Tesla’s chief executive Elon Musk, Professor Stephen Hawking and even Microsoft co-founder Bill Gates.
Wozniak stated:
Like people including Stephen Hawking and Elon Musk have predicted, I agree that the future is scary and very bad for people. If we build these devices to take care of everything for us, eventually they'll think faster than us and they'll get rid of the slow humans to run companies more efficiently.
Will we be the gods? Will we be the family pets? Or will we be ants that get stepped on? I don't know about that … But when I got that thinking in my head about if I'm going to be treated in the future as a pet to these smart machines … well I'm going to treat my own pet dog really nice.
Before Woz, Gates was the latest to join the AI-will-end-humanity club. During a Reddit "Ask me Anything" session, Gates was asked “How much of an existential threat do you think machine superintelligence will be?”
“I am in the camp that is concerned about super intelligence,” Gates replied [ http://www.reddit.com/r/IAmA/comments/2tzjp7/hi_reddit_im_bill_gates_and_im_back_for_my_third/co3r3g8 ]. “First the machines will do a lot of jobs for us and not be super intelligent. That should be positive if we manage it well. A few decades after that though the intelligence is strong enough to be a concern. I agree with Elon Musk and some others on this and don't understand why some people are not concerned.”
Back in December, Professor Stephen Hawking warned [ http://www.computerworld.com/article/2855036/stephen-hawking-artificial-intelligence-could-end-up-like-skynet.html ], “The development of full artificial intelligence could spell the end of the human race….It would take off on its own, and re-design itself at an ever increasing rate," he said. "Humans, who are limited by slow biological evolution, couldn't compete, and would be superseded."
Musk has been very vocal about his belief that AI potentially could be “more dangerous than nukes” and “our biggest existential threat.” He added [id.], “With artificial intelligence we are summoning the demon. In all those stories where there’s the guy with the pentagram and the holy water, it’s like yeah he’s sure he can control the demon. Didn't work out.”
Both Hawking and Musk signed [ http://futureoflife.org/misc/open_letter#signatories ] an open letter [ http://futureoflife.org/misc/open_letter ] about research priorities for robust and beneficial artificial intelligence. The research priorities paper (pdf [ http://futureoflife.org/static/data/documents/research_priorities.pdf ]) cited a Stanford study on “Loss of Control of AI systems.” The study voiced concerns that “we could one day lose control of AI systems via the rise of superintelligences that do not act in accordance with human wishes – and that such powerful systems would threaten humanity.”
Yet Wozniak suggested [ http://www.afr.com/technology/apple-cofounder-steve-wozniak-on-the-apple-watch-electric-cars-and-the-surpassing-of-humanity-20150323-1m3xxk ] the day super-smart machines take over the world might never come if Moore’s Law fails. Since 2005, various experts have suggested that computer processing speeds cannot keep doubling every two years so Moore’s Law may only continue until 2015 – 2020 [ http://en.wikipedia.org/wiki/Moore%27s_law ]. If our processors don’t get faster and faster every couple years, then quantum computing will never really take off and robot overlords can’t take over.
However Wozniak is hopeful about quantum computers, which use [ http://www.biv.com/article/2015/3/quantum-computers-raise-corporate-encryption-conce/ ] "subatomic particles to process complex calculations almost instantaneously." He said, "I hope it does come, and we should pursue it because it is about scientific exploring. But in the end we just may have created the species that is above us."
It might be worth noting that earlier this month University of California Santa Barbara researchers developed [ http://www.news.ucsb.edu/2015/015060/strength-numbers ] the “first-ever quantum device that detects and corrects its own errors.” The UC Santa Barbara news release explained, “When scientists develop a full quantum computer, the world of computing will undergo a revolution of sophistication, speed and energy efficiency that will make even our beefiest conventional machines seem like Stone Age clunkers by comparison.”
Yeah, but those “stone-age clunkers” aren't smart enough to evolve into Skynet and end humanity either.
Copyright © 2015 Computerworld, Inc.
http://www.computerworld.com/article/2901679/steve-wozniak-on-ai-will-we-be-pets-or-mere-ants-to-be-squashed-our-robot-overlords.html [with comments]
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Are We Ready For the Coming 'Age of Abundance?' - with Dr. Michio Kaku (Full)
Uploaded on Jun 27, 2011 by TheSasss1 [ http://www.youtube.com/channel/UCtjt2cXPOB_Ls3s2_SLMChA / http://www.youtube.com/user/TheSasss1 , http://www.youtube.com/user/TheSasss1/videos ]
Dr. Michio Kaku discussing economics, technology, and the future - full video of conference/discussion - from SAP’s Sapphire Now conference in Orlando, Florida, May 16-18, 2011 [ http://www.asugnews.com/article/8-things-to-know-about-sapphire-now-2011 , http://www.zdnet.com/article/sapphire-now-2011-the-wrap/ ].
SAP Sapphire Now Video (Full)
Booz & Company's Chief and Marketing and Knowledge Officer Tom Stewart moderated the Big Think panel made up of Michael Schrage, MIT Sloan School of Management research fellow, theoretical physicist Dr. Michio Kaku, Peter Diamandis, Founder and Chairman of the X-Prize Foundation, and Isabel Aguilera, former CEO of Google's Spain & Portugal operations.
http://bigthink.com/videos/sap-sapphire-now-video-full [non-YouTube video of the panel discussion following the opening presentation; with transcript]
http://www.youtube.com/watch?v=ceEog1XS5OI [with (over 7,000) comments, and embedded at http://www.kurzweilai.net/michio-kaku-explaining-americas-h1b-visa-declining-skilled-worker-population-domestically ; also at http://www.youtube.com/watch?v=G0FsHuwSe4k (no comments yet)]
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Michio Kaku on Singularity 1 on 1: Science is the Engine of Prosperity!
Published on Jun 6, 2014 by Nikola Danaylov [ http://www.youtube.com/channel/UCvjt0No0sOsJPBZE_2gdjug / http://www.youtube.com/user/ndanaylov , http://www.youtube.com/user/ndanaylov/videos ]
http://www.singularityweblog.com/michio-kaku-future-of-the-mind/
Dr. Michio Kaku is a theoretical physicist, bestselling author, acclaimed public speaker, renowned futurist, and popularizer of science. As co-founder of String Field Theory, Dr. Kaku carries on Einstein's quest to unite the four fundamental forces of nature into a single grand unified theory of everything. You will not be surprised to hear that Michio Kaku has been on my guest dream-list since I started Singularity 1 on 1, and I was beyond ecstatic to finally have an opportunity to speak to him.
During our 90 min conversation with Dr. Michio Kaku we cover a variety of interesting topics such as: why he shifted his focus from the universe to the human mind; his definition, classification and ranking of consciousness; his take on the Penrose-Hameroff Orch OR model; Newton, Einstein, determinism and free will; whether the brain is a classical computer or not; Norman Doidge's work on neuro-plasticity and The Brain That Changes Itself; the underlying reality of everything; his dream to finish what Einstein has started and know the mind of God; The Future of the Mind; mind-uploading and space travel at the speed of light; Moore's Law and D-Wave's quantum computer; the Human Brain Project and whole brain simulation; alternatives paths to AI and the Turing Test as a way of judging progress; cryonics and what is possible and impossible...
http://www.youtube.com/watch?v=AAEB-5GOCJ4 [with comments]
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Robots may take our jobs and cause the economy to crash - and you need to start saving money NOW, claims report
Economists used a simulated economy to create a model plotting a range of possible robot scenarios. This model revealed the rise of robots will initially create a tech boom, but this boom will turn to bust as workers are forced from their jobs and don't have enough money to pay for the goods the robots are producing.
Using a simulated economy, the paper found the value of coders will increase as demand for machines rise. As tech advances, costs will decline to deliver a 'tech boom'. But over time, the stock of so-called 'legacy code' will grow causing demand for new code and high-tech workers to drop and see them replaced by robots.
The eventual decline in jobs will limit what young people can save and invest. This means less capital will be available for the future generations and means production could actually fall over time, despite the fact machines are capable of producing goods more efficiently. A robot hotel employee in China is shown.
An alternative outcome of this is that high-skilled workers will move into low-skilled, lower paid positions, which will force these low-skilled workers into unemployment. And once people are out of work, welfare costs will rise putting a greater strain on the economy. The authors suggest people start saving for this eventuality.
'The long run in such cases is no techno-utopia,' said the researchers. 'Code is abundant but capital is dear. Everyone is employed. But no one is earning very much. In short, when smart machines replace people, they eventually bite the hands of those that finance them.' A robot designed to replace a shop worker is pictured.
• Experts create a model that plotted a range of possible robot scenarios
• They wanted to see how a rise in machines could impact national incomes
• This model revealed the rise of robots will initially create a tech boom
• But this boom will turn to bust as workers are forced from their jobs
• Humans won't have enough money to pay for goods made by the robots
• And rising unemployment will cause an increase in welfare costs
• As fewer people have capital to invest, production could fall over time
• And these factors could combine to cause economic damage globally
By Victoria Woollaston for MailOnline
Published: 09:09 EST, 25 February 2015 | Updated: 10:59 EST, 25 February 2015
The race to create robots that look, act and work like humans could see unemployment soar, welfare costs increase and may eventually bring the global economy to its knees.
That's the dystopian scenario put forward in a report looking at how machines will revolutionise the workplace in the not-so-distant future.
Economists created a simple model to plot a range of possible robot scenarios to see how the machines could impact national income, capital and quality of service.
In their paper [ http://www.nber.org/papers/w20941 ] Robots are Us: Some Economics of Human Replacement, lead researcher Seth Benzell said: 'Whether it’s bombing our enemies, steering our planes, fielding our calls, rubbing our backs, vacuuming our floors, driving our taxis, or beating us at Jeopardy, it’s hard to think of hitherto human tasks that smart machines can’t do or won’t soon do.'
With this in mind, Mr Benzell and his colleagues at the National Bureau of Economic Research asked whether 'human replacement' - the act of building better versions of ourselves - will deliver an economic utopia or leave us earning too little to buy the goods the robots are making?
Using a simulated economy, they found that the value of coders and developers will increase as the demand for smart machines rise.
As processes improve and technology advances the price to produce these machines will decline, which will deliver a 'tech boom'. This in turn will raise the demand for new code.
But over time, the stock of so-called 'legacy code' will grow because so many people are working on the projects, causing an abundance.
Plus this code will ultimately cause machines to become smarter and learn how to use the legacy code themselves.
This will cause demand for new code and, thus for high-tech workers, to drop and see such workers replaced by robot employees.
'The resulting tech bust reflects past humans obsolescing current humans. These robots contain the stuff of humans - accumulated brain and saving power,' said the paper.
'In fact, high-tech workers can start out earning far more than low-tech workers, but end up earning far less.'
The paper uses the example of Junior, the reigning World Computer Chess Champion. Junior can beat every current and, possibly, every future human on the planet.
Consequently, his old code has largely put new chess programmers out of business.
The eventual decline in high-tech and, potentially, low-tech workers income will limit what young people can save and invest, continued the paper.
This means less capital will be available for the future generations and production could actually fall over time, despite the fact machines are capable of producing goods more efficiently.
An alternative outcome of this is that high-skilled workers will move into low-skilled, lower paid positions, which will force these low-skilled workers into unemployment.
And once people are out of work, welfare costs will rise putting a greater strain on the economy. The authors even suggest people start saving for this eventuality.
'The long run in such cases is no techno-utopia. Yes, code is abundant. But capital is dear. And yes, everyone is fully employed. But no one is earning very much,' said Mr Bezell.
'In short, when smart machines replace people, they eventually bite the hands of those that finance them.'
The study's model firmly predicts three things - a long-run decline in the share of labour income, techbooms followed by tech-busts, and a growing dependency of current output on past software investment.
'Our simple model illustrates the range of things that smart machines can do for us and to us,' continued the paper.
'Its central message is disturbing. Absent appropriate fiscal policy that redistributes from winners to losers, smart machines can mean long-term misery for all.'
This study follows a similar report by management consulting firm Boston Consulting Group [ http://www.dailymail.co.uk/sciencetech/article-2946704/Cheaper-robots-replace-factory-workers-study.html ] that predicted by 2025 the number of 'automatable' tasks will rise to 25 per cent.
In turn, labour costs stand to drop by 16 per cent on average globally over that time.
The shift will mean an increasing demand for skilled workers who can operate the machines, said Hal Sirkin, a senior partner at Boston Consulting.
Factory workers 'will be higher paid but there will be fewer of them,' Mr Sirkin said.
Companies tend to start thinking about replacing workers when the costs of owning and operating a system come at a 15 per cent discount to employing a human counterpart.
For example, in the US automotive industry, which is predicted to be one of the more aggressive adopters of robots, a spot-welding machine costs $8 an hour versus $25 an hour for a worker.
A robot that can perform certain repetitive tasks costs about one-tenth as much as it did more than 10 years ago, Mr Sirkin said.
Costs tied to one commonly used robotics system, a spot welder, are also expected to fall 22 percent between now and 2025.
Three-fourths of robot installations over the next decade are expected to be concentrated in four areas: transportation equipment, including the automotive sector; computer and electronic products; electrical equipment and machinery.
By 2025, robots should be able to handle 30 to 40 per cent of automatable tasks across multiple industries.
Adoption will be slower in industries such as food products, plastics, fabricated metal, and wood products, where many tasks will remain difficult to automate and wages are relatively low.
Thanks to technological advances, however, robots are making greater inroads in these industries as well.
'Regardless of whether it's time to invest in next-generation robots, manufacturers everywhere should start preparing,' added Mr Sirkin.
'They need to understand how costs and automation technologies are changing in their industries and what their competitors are up to.'
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ARE THE PREDICTIONS ALREADY COMING TRUE?
The 'Robear' has a cub-like face but packs enough strength to transfer patients from a wheelchair (pictured) or a floor-level bed to a bath, for example.
A recent report by management consulting firm Boston Consulting Group predicted by 2025 the number of 'automatable' tasks will rise to 25 per cent [ http://www.dailymail.co.uk/sciencetech/article-2946704/Cheaper-robots-replace-factory-workers-study.html ].
This will lead to robots replacing many human jobs - and is a trend that has already begun in Japan.
Earlier this week Riken-SRK Collaboration Centre for Human-Interactive Robot Research in Nagoya, Japan unveiled its latest Robear [ http://www.dailymail.co.uk/sciencetech/article-2966380/Japans-Robear-Strength-robot-face-bear.html ].
The 'Robear' has a cub-like face but has enough strength to transfer patients from a wheelchair or a floor-level bed to a bath.
It weighs 309lb (140kg) with extending legs that stop the 'bear' from falling over and it moves slowly and smoothly thanks to advance actuators in its mechanical arms.
And at the start of the month, Mitsubishi UFJ Financial Group said it will begin employing a humanoid called Nao in its branches from April, on a trial basis.
And if the trial is successful, the robotic employees will be rolled out to more branches of the Japanese bank by 2020.
Elsewhere, in China there is a hotel manned entirely by robots.
From reception desk staff to security doormen and waiters, the Pengheng Space Capsules Hotel in Shenzhen, China, has built, rather than hired, new employees.
Start-up costs and robot maintenance aside, staff bills are minimal and the hotel can pass these savings back to the customer as a night's stay costs just £6.80 per night.
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SHOULD WE FEAR ARTIFICIAL INTELLIGENCE? ELON MUSK AND STEPHEN HAWKING WARNS OF POTENTIAL DANGERS
Stark warning: Professor Stephen Hawking says we must be vigilant about artificial intelligence.
Artificial Intelligence has been described as a threat that could be 'more dangerous than nukes'.
Now a group of scientists and entrepreneurs, including Elon Musk and Stephen Hawking, have signed an open letter [ http://futureoflife.org/misc/open_letter ] promising to ensure AI research benefits humanity.
The letter warns that without safeguards on intelligent machines, mankind could be heading for a dark future.
The document, drafted by the Future of Life Institute, said scientists should seek to head off risks that could wipe out mankind.
The authors say there is a 'broad consensus' that AI research is making good progress and would have a growing impact on society.
It highlights speech recognition, image analysis, driverless cars, translation and robot motion as having benefited from the research.
'The potential benefits are huge, since everything that civilisation has to offer is a product of human intelligence; we cannot predict what we might achieve when this intelligence is magnified by the tools AI may provide, but the eradication of disease and poverty are not unfathomable,' the authors write.
But it issued a stark warning that research into the rewards of AI had to be matched with an equal effort to avoid the potential damage it could wreak.
For instance, in the short term, it claims AI may put millions of people out of work.
In the long term, it could have the potential to play out like a fictional dystopias in which intelligence greater than humans could begin acting against their programming.
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WHAT JOBS COULD DISAPPEAR?
According to Dr Maggie Aderin-Pocock, a research fellow in UCL Department of Science and Technology Studies, care for the elderly and even children are among the jobs to be replaced by artificially intelligent beings within the next 50 years.
Her research suggests human workers across a plethora of service sectors and caring professions could be replaced by droids within our lifetimes.
She believes that as the rapid advances in technology achieved this century are projected to continue at an astonishing rate, this will allow robots to break free of science fiction and establish themselves in our everyday life.
According to her research - which polled 2,000 people about which jobs they thought were most unpopular and could be among the first to be given to robots for the TC channel Syfy - traffic wardens (65 per cent), estate agents (40 per cent) and car salesman (33 per cent) could soon be lost to history.
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© Associated Newspapers Ltd
http://www.dailymail.co.uk/sciencetech/article-2968503/Robots-jobs-cause-economy-crash-need-start-saving-money-claims-report.html [with comment; comments closed]
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SHAKEY: Experimentation in Robot Learning and Planning (1969)
Published on Oct 25, 2012 by SRI International [ http://www.youtube.com/channel/UC5A9qmHJVtuKNl_GmsqvbDA / http://www.youtube.com/user/innovationSRI , http://www.youtube.com/user/innovationSRI/videos ]
SRI's Shakey the Robot (1966-1972) was the first mobile robot that could reason about its surroundings. This 1969 movie provides a good look at how Shakey worked.
http://www.youtube.com/watch?v=RhrLHkVuerc [with comments]
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CoCoCo, Coffee Collecting Companion
Published on Jul 31, 2014 by AAAI Video Competition
CoCoCo, Coffee Collecting Companion
Paul Hanzal, Anne Rubruck, Sohaib Younis, Sascha Winde, Azad Aminian, Jyothi Yalpi, Sathya Kuppusami, Stefan Thomas
University of Hamburg
http://www.youtube.com/watch?v=XRsqDErCHN4 [no comments yet]
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Japan will open world's first hotel entirely operated by robots this summer
Henn na Hotel opens this summer in Sasebo, Japan. It will be staffed entirely by robots.
The hotel androids will provide porter service, room cleaning and front desk management. The hotel will also have facial recognition so guests can enter their rooms without key cards.
The hotel will open in Sasebo, Japan on July 17. Robots will carry luggage, clean rooms and manage reservations.
February 4, 2015
http://www.nydailynews.com/news/world/japan-open-hotel-operated-robots-article-1.2103352 [with comments]
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Bleep blorp: New Japanese hotel to be staffed by robots
February 5, 2015
[...]
"In the future, we're hoping to build 1,000 similar hotels around the world," says Sawada, according to Japan's Nikkei News [ http://zh.cn.nikkei.com/trend/tourism/12953-20150202.html ].
[...]
http://www.cnn.com/2015/02/04/travel/japan-hotel-robots/
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This Is Big: A Robo-Car Just Drove Across the Country
04.03.15
http://www.wired.com/2015/04/delphi-autonomous-car-cross-country/ [with comments]
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Nissan pledges self-driving cars in Japan in 2016
AUTONOMOUS ALL THE WAY: Carlos Ghosn, chief executive, said formidable technological and legal challenges remain but that the direction of travel was plain.
April 3, 2015
http://www.thestar.com.my/Tech/Tech-News/2015/04/04/Nissan-pledges-self-driving-cars-in-Japan-in-2016/
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The Age of Artificial Intelligence: George John at TEDxLondonBusinessSchool 2013
Published on May 28, 2013 by TEDx Talks [ http://www.youtube.com/channel/UCsT0YIqwnpJCM-mx7-gSA4Q / http://www.youtube.com/user/TEDxTalks , http://www.youtube.com/user/TEDxTalks/videos ]
George, overly influenced by Star Trek, previously worked at NASA, earning his "rocket scientist" credentials. He currently manages Rocket Fuel and has married big data with artificial intelligence to create the leading programmatic media buying engine in digital advertising.
In the spirit of ideas worth spreading, TEDx is a program of local, self-organized events that bring people together to share a TED-like experience. At a TEDx event, TEDTalks video and live speakers combine to spark deep discussion and connection in a small group. These local, self-organized events are branded TEDx, where x = independently organized TED event. The TED Conference provides general guidance for the TEDx program, but individual TEDx events are self-organized.* (*Subject to certain rules and regulations)
http://www.youtube.com/watch?v=0qOf7SX2CS4 [with comments]
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Race Against the Machine: Andrew McAfee at TEDxBoston
Published on Jul 17, 2012 by TEDx Talks
"We ain't seen nothing yet when it comes to technology's impact on the labor force."
Automation redefined blue collar employment and reshaped a global economy. Now, technology is replacing higher skilled jobs by augmenting human brainpower the way steam engines augmented human labor. Andrew McAfee braces us for a fundamental transformation in the future of work.
http://www.youtube.com/watch?v=QfMGyCk3XTw [with comments]
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How Technology Is Destroying Jobs
Why It Matters
Economic theory and government policy will have to be rethought if technology is indeed destroying jobs faster than it is creating new ones.
By David Rotman on June 12, 2013
Also featured in MIT Technology Review magazine July/August 2013
Given his calm and reasoned academic demeanor, it is easy to miss just how provocative Erik Brynjolfsson’s contention really is. Brynjolfsson, a professor at the MIT Sloan School of Management, and his collaborator and coauthor Andrew McAfee have been arguing for the last year and a half that impressive advances in computer technology—from improved industrial robotics to automated translation services—are largely behind the sluggish employment growth of the last 10 to 15 years. Even more ominous for workers, the MIT academics foresee dismal prospects for many types of jobs as these powerful new technologies are increasingly adopted not only in manufacturing, clerical, and retail work but in professions such as law, financial services, education, and medicine.
That robots, automation, and software can replace people might seem obvious to anyone who’s worked in automotive manufacturing or as a travel agent. But Brynjolfsson and McAfee’s claim is more troubling and controversial. They believe that rapid technological change has been destroying jobs faster than it is creating them, contributing to the stagnation of median income and the growth of inequality in the United States. And, they suspect, something similar is happening in other technologically advanced countries.
Perhaps the most damning piece of evidence, according to Brynjolfsson, is a chart that only an economist could love. In economics, productivity—the amount of economic value created for a given unit of input, such as an hour of labor—is a crucial indicator of growth and wealth creation. It is a measure of progress. On the chart Brynjolfsson likes to show, separate lines represent productivity and total employment in the United States. For years after World War II, the two lines closely tracked each other, with increases in jobs corresponding to increases in productivity. The pattern is clear: as businesses generated more value from their workers, the country as a whole became richer, which fueled more economic activity and created even more jobs. Then, beginning in 2000, the lines diverge; productivity continues to rise robustly, but employment suddenly wilts. By 2011, a significant gap appears between the two lines, showing economic growth with no parallel increase in job creation. Brynjolfsson and McAfee call it the “great decoupling.” And Brynjolfsson says he is confident that technology is behind both the healthy growth in productivity and the weak growth in jobs.
It’s a startling assertion because it threatens the faith that many economists place in technological progress. Brynjolfsson and McAfee still believe that technology boosts productivity and makes societies wealthier, but they think that it can also have a dark side: technological progress is eliminating the need for many types of jobs and leaving the typical worker worse off than before. Brynjolfsson can point to a second chart indicating that median income is failing to rise even as the gross domestic product soars. “It’s the great paradox of our era,” he says. “Productivity is at record levels, innovation has never been faster, and yet at the same time, we have a falling median income and we have fewer jobs. People are falling behind because technology is advancing so fast and our skills and organizations aren’t keeping up.”
Brynjolfsson and McAfee are not Luddites. Indeed, they are sometimes accused of being too optimistic about the extent and speed of recent digital advances. Brynjolfsson says they began writing Race Against the Machine [ http://www.amazon.com/Race-Against-Machine-Accelerating-Productivity/dp/0984725113 ], the 2011 book in which they laid out much of their argument, because they wanted to explain the economic benefits of these new technologies (Brynjolfsson spent much of the 1990s sniffing out evidence that information technology was boosting rates of productivity). But it became clear to them that the same technologies making many jobs safer, easier, and more productive were also reducing the demand for many types of human workers.
Anecdotal evidence that digital technologies threaten jobs is, of course, everywhere. Robots and advanced automation have been common in many types of manufacturing for decades. In the United States and China, the world’s manufacturing powerhouses, fewer people work in manufacturing today than in 1997, thanks at least in part to automation. Modern automotive plants, many of which were transformed by industrial robotics in the 1980s, routinely use machines that autonomously weld and paint body parts—tasks that were once handled by humans. Most recently, industrial robots like Rethink Robotics’ Baxter (see “The Blue-Collar Robot [ http://www.technologyreview.com/featuredstory/513746/baxter-the-blue-collar-robot/ ],” May/June 2013), more flexible and far cheaper than their predecessors, have been introduced to perform simple jobs for small manufacturers in a variety of sectors. The website of a Silicon Valley startup called Industrial Perception features a video of the robot it has designed for use in warehouses picking up and throwing boxes like a bored elephant. And such sensations as Google’s driverless car suggest what automation might be able to accomplish someday soon.
A less dramatic change, but one with a potentially far larger impact on employment, is taking place in clerical work and professional services. Technologies like the Web, artificial intelligence, big data, and improved analytics—all made possible by the ever increasing availability of cheap computing power and storage capacity—are automating many routine tasks. Countless traditional white-collar jobs, such as many in the post office and in customer service, have disappeared. W. Brian Arthur, a visiting researcher at the Xerox Palo Alto Research Center’s intelligence systems lab and a former economics professor at Stanford University, calls it the “autonomous economy.” It’s far more subtle than the idea of robots and automation doing human jobs, he says: it involves “digital processes talking to other digital processes and creating new processes,” enabling us to do many things with fewer people and making yet other human jobs obsolete.
It is this onslaught of digital processes, says Arthur, that primarily explains how productivity has grown without a significant increase in human labor. And, he says, “digital versions of human intelligence” are increasingly replacing even those jobs once thought to require people. “It will change every profession in ways we have barely seen yet,” he warns.
McAfee, associate director of the MIT Center for Digital Business at the Sloan School of Management, speaks rapidly and with a certain awe as he describes advances such as Google’s driverless car. Still, despite his obvious enthusiasm for the technologies, he doesn’t see the recently vanished jobs coming back. The pressure on employment and the resulting inequality will only get worse, he suggests, as digital technologies—fueled with “enough computing power, data, and geeks”—continue their exponential advances over the next several decades. “I would like to be wrong,” he says, “but when all these science-fiction technologies are deployed, what will we need all the people for?”
New Economy?
But are these new technologies really responsible for a decade of lackluster job growth? Many labor economists say the data are, at best, far from conclusive. Several other plausible explanations, including events related to global trade and the financial crises of the early and late 2000s, could account for the relative slowness of job creation since the turn of the century. “No one really knows,” says Richard Freeman, a labor economist at Harvard University. That’s because it’s very difficult to “extricate” the effects of technology from other macroeconomic effects, he says. But he’s skeptical that technology would change a wide range of business sectors fast enough to explain recent job numbers.
David Autor, an economist at MIT who has extensively studied the connections between jobs and technology, also doubts that technology could account for such an abrupt change in total employment. “There was a great sag in employment beginning in 2000. Something did change,” he says. “But no one knows the cause.” Moreover, he doubts that productivity has, in fact, risen robustly in the United States in the past decade (economists can disagree about that statistic because there are different ways of measuring and weighing economic inputs and outputs). If he’s right, it raises the possibility that poor job growth could be simply a result of a sluggish economy. The sudden slowdown in job creation “is a big puzzle,” he says, “but there’s not a lot of evidence it’s linked to computers.”
To be sure, Autor says, computer technologies are changing the types of jobs available, and those changes “are not always for the good.” At least since the 1980s, he says, computers have increasingly taken over such tasks as bookkeeping, clerical work, and repetitive production jobs in manufacturing—all of which typically provided middle-class pay. At the same time, higher-paying jobs requiring creativity and problem-solving skills, often aided by computers, have proliferated. So have low-skill jobs: demand has increased for restaurant workers, janitors, home health aides, and others doing service work that is nearly impossible to automate. The result, says Autor, has been a “polarization” of the workforce and a “hollowing out” of the middle class—something that has been happening in numerous industrialized countries for the last several decades. But “that is very different from saying technology is affecting the total number of jobs,” he adds. “Jobs can change a lot without there being huge changes in employment rates.”
What’s more, even if today’s digital technologies are holding down job creation, history suggests that it is most likely a temporary, albeit painful, shock; as workers adjust their skills and entrepreneurs create opportunities based on the new technologies, the number of jobs will rebound. That, at least, has always been the pattern. The question, then, is whether today’s computing technologies will be different, creating long-term involuntary unemployment.
At least since the Industrial Revolution began in the 1700s, improvements in technology have changed the nature of work and destroyed some types of jobs in the process. In 1900, 41 percent of Americans worked in agriculture; by 2000, it was only 2 percent. Likewise, the proportion of Americans employed in manufacturing has dropped from 30 percent in the post–World War II years to around 10 percent today—partly because of increasing automation, especially during the 1980s.
While such changes can be painful for workers whose skills no longer match the needs of employers, Lawrence Katz, a Harvard economist, says that no historical pattern shows these shifts leading to a net decrease in jobs over an extended period. Katz has done extensive research on how technological advances have affected jobs over the last few centuries—describing, for example, how highly skilled artisans in the mid-19th century were displaced by lower-skilled workers in factories. While it can take decades for workers to acquire the expertise needed for new types of employment, he says, “we never have run out of jobs. There is no long-term trend of eliminating work for people. Over the long term, employment rates are fairly stable. People have always been able to create new jobs. People come up with new things to do.”
Still, Katz doesn’t dismiss the notion that there is something different about today’s digital technologies—something that could affect an even broader range of work. The question, he says, is whether economic history will serve as a useful guide. Will the job disruptions caused by technology be temporary as the workforce adapts, or will we see a science-fiction scenario in which automated processes and robots with superhuman skills take over a broad swath of human tasks? Though Katz expects the historical pattern to hold, it is “genuinely a question,” he says. “If technology disrupts enough, who knows what will happen?”
Dr. Watson
To get some insight into Katz’s question, it is worth looking at how today’s most advanced technologies are being deployed in industry. Though these technologies have undoubtedly taken over some human jobs, finding evidence of workers being displaced by machines on a large scale is not all that easy. One reason it is difficult to pinpoint the net impact on jobs is that automation is often used to make human workers more efficient, not necessarily to replace them. Rising productivity means businesses can do the same work with fewer employees, but it can also enable the businesses to expand production with their existing workers, and even to enter new markets.
Take the bright-orange Kiva robot, a boon to fledgling e-commerce companies. Created and sold by Kiva Systems, a startup that was founded in 2002 and bought by Amazon for $775 million in 2012, the robots are designed to scurry across large warehouses, fetching racks of ordered goods and delivering the products to humans who package the orders. In Kiva’s large demonstration warehouse and assembly facility at its headquarters outside Boston, fleets of robots move about with seemingly endless energy: some newly assembled machines perform tests to prove they’re ready to be shipped to customers around the world, while others wait to demonstrate to a visitor how they can almost instantly respond to an electronic order and bring the desired product to a worker’s station.
A warehouse equipped with Kiva robots can handle up to four times as many orders as a similar unautomated warehouse, where workers might spend as much as 70 percent of their time walking about to retrieve goods. (Coincidentally or not, Amazon bought Kiva soon after a press report revealed that workers at one of the retailer’s giant warehouses often walked more than 10 miles a day.)
Despite the labor-saving potential of the robots, Mick Mountz, Kiva’s founder and CEO, says he doubts the machines have put many people out of work or will do so in the future. For one thing, he says, most of Kiva’s customers are e-commerce retailers, some of them growing so rapidly they can’t hire people fast enough. By making distribution operations cheaper and more efficient, the robotic technology has helped many of these retailers survive and even expand. Before founding Kiva, Mountz worked at Webvan, an online grocery delivery company that was one of the 1990s dot-com era’s most infamous flameouts. He likes to show the numbers demonstrating that Webvan was doomed from the start; a $100 order cost the company $120 to ship. Mountz’s point is clear: something as mundane as the cost of materials handling can consign a new business to an early death. Automation can solve that problem.
Meanwhile, Kiva itself is hiring. Orange balloons—the same color as the robots—hover over multiple cubicles in its sprawling office, signaling that the occupants arrived within the last month. Most of these new employees are software engineers: while the robots are the company’s poster boys, its lesser-known innovations lie in the complex algorithms that guide the robots’ movements and determine where in the warehouse products are stored. These algorithms help make the system adaptable. It can learn, for example, that a certain product is seldom ordered, so it should be stored in a remote area.
Though advances like these suggest how some aspects of work could be subject to automation, they also illustrate that humans still excel at certain tasks—for example, packaging various items together. Many of the traditional problems in robotics—such as how to teach a machine to recognize an object as, say, a chair—remain largely intractable and are especially difficult to solve when the robots are free to move about a relatively unstructured environment like a factory or office.
Techniques using vast amounts of computational power have gone a long way toward helping robots understand their surroundings, but John Leonard, a professor of engineering at MIT and a member of its Computer Science and Artificial Intelligence Laboratory (CSAIL), says many familiar difficulties remain. “Part of me sees accelerating progress; the other part of me sees the same old problems,” he says. “I see how hard it is to do anything with robots. The big challenge is uncertainty.” In other words, people are still far better at dealing with changes in their environment and reacting to unexpected events.
For that reason, Leonard says, it is easier to see how robots could work with humans than on their own in many applications. “People and robots working together can happen much more quickly than robots simply replacing humans,” he says. “That’s not going to happen in my lifetime at a massive scale. The semiautonomous taxi will still have a driver.”
One of the friendlier, more flexible robots meant to work with humans is Rethink’s Baxter. The creation of Rodney Brooks, the company’s founder, Baxter needs minimal training to perform simple tasks like picking up objects and moving them to a box. It’s meant for use in relatively small manufacturing facilities where conventional industrial robots would cost too much and pose too much danger to workers. The idea, says Brooks, is to have the robots take care of dull, repetitive jobs that no one wants to do.
It’s hard not to instantly like Baxter, in part because it seems so eager to please. The “eyebrows” on its display rise quizzically when it’s puzzled; its arms submissively and gently retreat when bumped. Asked about the claim that such advanced industrial robots could eliminate jobs, Brooks answers simply that he doesn’t see it that way. Robots, he says, can be to factory workers as electric drills are to construction workers: “It makes them more productive and efficient, but it doesn’t take jobs.”
The machines created at Kiva and Rethink have been cleverly designed and built to work with people, taking over the tasks that the humans often don’t want to do or aren’t especially good at. They are specifically designed to enhance these workers’ productivity. And it’s hard to see how even these increasingly sophisticated robots will replace humans in most manufacturing and industrial jobs anytime soon. But clerical and some professional jobs could be more vulnerable. That’s because the marriage of artificial intelligence and big data is beginning to give machines a more humanlike ability to reason and to solve many new types of problems.
In the tony northern suburbs of New York City, IBM Research is pushing super-smart computing into the realms of such professions as medicine, finance, and customer service. IBM’s efforts have resulted in Watson, a computer system best known for beating human champions on the game show Jeopardy! in 2011. That version of Watson now sits in a corner of a large data center at the research facility in Yorktown Heights, marked with a glowing plaque commemorating its glory days. Meanwhile, researchers there are already testing new generations of Watson in medicine, where the technology could help physicians diagnose diseases like cancer, evaluate patients, and prescribe treatments.
IBM likes to call it cognitive computing. Essentially, Watson uses artificial-intelligence techniques, advanced natural-language processing and analytics, and massive amounts of data drawn from sources specific to a given application (in the case of health care, that means medical journals, textbooks, and information collected from the physicians or hospitals using the system). Thanks to these innovative techniques and huge amounts of computing power, it can quickly come up with “advice”—for example, the most recent and relevant information to guide a doctor’s diagnosis and treatment decisions.
Despite the system’s remarkable ability to make sense of all that data, it’s still early days for Dr. Watson. While it has rudimentary abilities to “learn” from specific patterns and evaluate different possibilities, it is far from having the type of judgment and intuition a physician often needs. But IBM has also announced it will begin selling Watson’s services to customer-support call centers, which rarely require human judgment that’s quite so sophisticated. IBM says companies will rent an updated version of Watson for use as a “customer service agent” that responds to questions from consumers; it has already signed on several banks. Automation is nothing new in call centers, of course, but Watson’s improved capacity for natural-language processing and its ability to tap into a large amount of data suggest that this system could speak plainly with callers, offering them specific advice on even technical and complex questions. It’s easy to see it replacing many human holdouts in its new field.
Digital Losers
The contention that automation and digital technologies are partly responsible for today’s lack of jobs has obviously touched a raw nerve for many worried about their own employment. But this is only one consequence of what Brynjolfsson and McAfee see as a broader trend. The rapid acceleration of technological progress, they say, has greatly widened the gap between economic winners and losers—the income inequalities that many economists have worried about for decades. Digital technologies tend to favor “superstars,” they point out. For example, someone who creates a computer program to automate tax preparation might earn millions or billions of dollars while eliminating the need for countless accountants.
New technologies are “encroaching into human skills in a way that is completely unprecedented,” McAfee says, and many middle-class jobs are right in the bull’s-eye; even relatively high-skill work in education, medicine, and law is affected. “The middle seems to be going away,” he adds. “The top and bottom are clearly getting farther apart.” While technology might be only one factor, says McAfee, it has been an “underappreciated” one, and it is likely to become increasingly significant.
Not everyone agrees with Brynjolfsson and McAfee’s conclusions—particularly the contention that the impact of recent technological change could be different from anything seen before. But it’s hard to ignore their warning that technology is widening the income gap between the tech-savvy and everyone else. And even if the economy is only going through a transition similar to those it’s endured before, it is an extremely painful one for many workers, and that will have to be addressed somehow. Harvard’s Katz has shown that the United States prospered in the early 1900s in part because secondary education became accessible to many people at a time when employment in agriculture was drying up. The result, at least through the 1980s, was an increase in educated workers who found jobs in the industrial sectors, boosting incomes and reducing inequality. Katz’s lesson: painful long-term consequences for the labor force do not follow inevitably from technological changes.
Brynjolfsson himself says he’s not ready to conclude that economic progress and employment have diverged for good. “I don’t know whether we can recover, but I hope we can,” he says. But that, he suggests, will depend on recognizing the problem and taking steps such as investing more in the training and education of workers.
“We were lucky and steadily rising productivity raised all boats for much of the 20th century,” he says. “Many people, especially economists, jumped to the conclusion that was just the way the world worked. I used to say that if we took care of productivity, everything else would take care of itself; it was the single most important economic statistic. But that’s no longer true.” He adds, “It’s one of the dirty secrets of economics: technology progress does grow the economy and create wealth, but there is no economic law that says everyone will benefit.” In other words, in the race against the machine, some are likely to win while many others lose.
Credits: Noma Bar (Illustration); Data from Bureau of Labor Statistics (Productivity, Output, GDP Per Capita); International Federation of Robotics; CIA World Factbook (GDP by Sector), Bureau of Labor Statistics (Job Growth, Manufacturing Employment); D. Autor and D. Dorn, U.S. Census, American Community Survey, and Department of Labor (Change in Employment and Wages by Skill, Routine Jobs)
Related:
Smart Robots Can Now Work Right Next to Auto Workers
It used to be too dangerous to have a person work alongside a robot. But at a South Carolina BMW plant, next-generation robots are changing that.
September 17, 2013
http://www.technologyreview.com/news/518661/smart-robots-can-now-work-right-next-to-auto-workers/
How Human-Robot Teamwork Will Upend Manufacturing
Robots are starting to collaborate with human workers in factories, offering greater efficiency and flexibility.
September 16, 2014
http://www.technologyreview.com/news/530696/how-human-robot-teamwork-will-upend-manufacturing/
Rise of the Robot Security Guards
Startup Knightscope is preparing to roll out human-size robot patrols.
November 13, 2014
http://www.technologyreview.com/news/532431/rise-of-the-robot-security-guards/
© 2013 MIT Technology Review
http://www.technologyreview.com/featuredstory/515926/how-technology-is-destroying-jobs/ [with comments]
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Artificial Intelligence and the Future of Humans and Robots in the Economy
Streamed live on Feb 27, 2015 by Council on Foreign Relations [ http://www.youtube.com/channel/UCL_A4jkwvKuMyToAPy3FQKQ / http://www.youtube.com/user/cfr , http://www.youtube.com/user/cfr/videos ]
MIT professor emeritus and Rethink Robotics’ founder Rodney Brooks, Carnegie Mellon’s Abhinav Gupta, and MIT’s Andrew McAfee, join Nicholas Thompson, editor at NewYorker.com, to discuss artificial intelligence (AI) and robot technology, and their economic impact on industry and society in the future.
The Malcolm and Carolyn Wiener Annual Lecture on Science and Technology addresses issues at the intersection of science, technology, and foreign policy.
Speakers:
Rodney Brooks, Panasonic Professor of Robotics (Emeritus), Computer Science and Artificial Intelligence Lab, Massachusetts Institute of Technology; Founder, Chairman, and Chief Technology Officer, Rethink Robotics
Abhinav Gupta, Assistant Research Professor, Robotics Institute, Carnegie Mellon University
Andrew McAfee, Principal Research Scientist and Cofounder, Initiative on the Digital Economy, Sloan School of Management, Massachusetts Institute of Technology
Presider:
Nicholas Thompson, Editor, "NewYorker.com"
http://www.youtube.com/watch?v=1TkcruN10-8 [with comments]
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Artificial Intelligence and the future | André LeBlanc | TEDxMoncton
Published on Jan 12, 2015 by TEDx Talks
This talk was given at a local TEDx event, produced independently of the TED Conferences. In his talk, Andre will explain the current and future impacts of Artificial Intelligence on industry, science, and how it will benefit and accelerate human progress.
With almost 20 years of business experience, André has a track record of success with multiple multi-million dollar ventures in multiple industries that have spanned the continent. His latest company works in the field of Artificial Intelligence (AI) and has created a one-of-a-kind neural network that simulates a growing neocortex. This system of neurons uses evolutionary concepts to self-organize to complete tasks only previously achievable by humans. Most futurists and experts believe that by 2035, AI will match and eventually surpass human intelligence.
http://www.youtube.com/watch?v=xH_B5xh42xc [with comments]
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The Share-the-Scraps Economy
By Robert Reich
Posted: 02/02/2015 1:51 pm EST Updated: 02/09/2015 5:59 pm EST
How would you like to live in an economy where robots do everything that can be predictably programmed in advance, and almost all profits go to the robots' owners?
Meanwhile, human beings do the work that's unpredictable - odd jobs, on-call projects, fetching and fixing, driving and delivering, tiny tasks needed at any and all hours - and patch together barely enough to live on.
Brace yourself. This is the economy we're now barreling toward.
They're Uber [ https://get.uber.com/cl/ ] drivers, Instacart [ https://www.instacart.com/ ] shoppers, and Airbnb [ https://www.airbnb.com/ ] hosts. They include Taskrabbit [ https://www.taskrabbit.com/careers ] jobbers, Upcounsel [ https://www.upcounsel.com/home/careers ]'s on-demand attorneys, and Healthtap [ https://www.healthtap.com/prime-trial ]'s on-line doctors.
They're Mechanical Turks [ https://www.mturk.com/mturk/welcome ].
The euphemism is the "share" economy [ http://www.economist.com/news/leaders/21573104-internet-everything-hire-rise-sharing-economy ]. A more accurate term would be the "share-the-scraps" economy.
New software technologies are allowing almost any job to be divided up into discrete tasks that can be parceled out to workers when they're needed, with pay determined by demand for that particular job at that particular moment.
Customers and workers are matched online. Workers are rated on quality and reliability.
The big money goes to the corporations that own the software. The scraps go to the on-demand workers.
Consider Amazon's "Mechanical Turk." Amazon calls it "a marketplace for work that requires human intelligence [ http://aws.amazon.com/mturk/ ]."
In reality, it's an Internet job board offering minimal pay for mindlessly-boring bite-sized chores. Computers can't do them because they require some minimal judgment, so human beings do them for peanuts -- say, writing a product description, for $3; or choosing the best of several photographs, for 30 cents; or deciphering handwriting, for 50 cents.
Amazon takes a healthy cut of every transaction.
This is the logical culmination of a process that began thirty years ago when corporations began turning over full-time jobs to temporary workers, independent contractors, free-lancers, and consultants.
It was a way to shift risks and uncertainties onto the workers - work that might entail more hours than planned for, or was more stressful than expected.
And a way to circumvent labor laws that set minimal standards for wages, hours, and working conditions. And that enabled employees to join together to bargain for better pay and benefits.
The new on-demand work shifts risks entirely onto workers, and eliminates minimal standards completely.
In effect, on-demand work is a reversion to the piece work of the nineteenth century - when workers had no power and no legal rights, took all the risks, and worked all hours for almost nothing.
Uber drivers [ http://www.businessinsider.com/uber-drivers-across-the-country-are-protesting-tomorrow--heres-why-2014-10 ] use their own cars, take out their own insurance, work as many hours as they want or can - and pay Uber a fat percent [ http://www.wsj.com/articles/ubers-new-funding-values-it-at-over-41-billion-1417715938 ]. Worker safety? Social Security? Uber says it's not the employer so it's not responsible.
Amazon's Mechanical Turks work for pennies, literally. Minimum wage? Time-and-a half for overtime? Amazon says it just connects buyers and sellers so it's not responsible.
Defenders of on-demand work emphasize its flexibility. Workers can put in whatever time they want, work around their schedules, fill in the downtime in their calendars.
"People are monetizing their own downtime," says [ http://www.nytimes.com/2015/01/29/technology/personaltech/uber-a-rising-business-model.html ] Arun Sundararajan, a professor at New York University's business school.
But this argument confuses "downtime" with the time people normally reserve for the rest of their lives.
There are still only twenty-four hours in a day. When "downtime" is turned into work time, and that work time is unpredictable and low-paid, what happens to personal relationships? Family? One's own health?
Other proponents of on-demand work point to studies, such as one recently commissioned by Uber, showing Uber's on-demand workers to be "happy [ http://www.newrepublic.com/article/120832/uber-study-uber-drivers-are-happy-uber ]."
But how many of them would be happier with a good-paying job offering regular hours?
An opportunity to make some extra bucks can seem mighty attractive in an economy whose median wage has been stagnant for thirty years and almost all of whose economic gains have been going to the top.
That doesn't make the opportunity a great deal. It only shows how bad a deal most working people have otherwise been getting.
Defenders also point out that as on-demand work continues to grow, on-demand workers are joining together in guild-like groups [ http://www.nytimes.com/2015/01/29/technology/personaltech/uber-a-rising-business-model.html ] to buy insurance and other benefits.
But, notably, they aren't using their bargaining power to get a larger share of the income they pull in, or steadier hours. That would be a union - something that Uber, Amazon, and other on-demand companies don't want.
Some economists laud on-demand work as a means of utilizing people more efficiently [ http://blogs.microsoft.com/work/2013/11/12/the-mobile-workforce-more-productive-efficient-and-healthy/ ].
But the biggest economic challenge we face isn't using people more efficiently. It's allocating work and the gains from work more decently.
On this measure, the share-the-scraps economy is hurtling us backwards.
Copyright ©2015 TheHuffingtonPost.com, Inc.
http://www.huffingtonpost.com/robert-reich/the-sharethescraps-econom_b_6597992.html [with comments]
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Apple co founder - Will AI Turn Us Into 'Family Pets' ??? Satanic Machines EXPOSED
Published on Mar 28, 2015 by Vigilant Christian [ http://www.youtube.com/channel/UCHKHC9bVGr49vuv1WyPp_5Q , http://www.youtube.com/channel/UCHKHC9bVGr49vuv1WyPp_5Q/videos ]
The transhumanist agenda will make men develop machines and AI without even thinking about the consequences! In this video I share an article that shows that even Apple's co-founder Mr Wozniak thinks this is a bad idea! Please share this video !! God Bless, STAY VIGILANT & FEAR NO EVIL !!!
Apple Co-Founder: Will AI Turn Us Into 'Family Pets'?
http://www.nbcnews.com/tech/tech-news/apple-co-founder-ai-will-take-over-humans-n329906
Illuminati Tranhumanist Agenda ! Man Merges with Machine to become a god http://www.youtube.com/playlist?list=PLTHDvEc6d7JFef03KNPTOhIW1qZJR8FpF
FaceLikeTheSun - Brother Gonz - NWO, Transhumanism, Entertainment Industry Exposed, Bible Teachings & more ...
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http://www.youtube.com/watch?v=-p4BWfyAir0 [with comments]
--
Apple Co-Founder Steve Wozniak Warns Artificial Intelligence May Enslave Humans
Published on Mar 25, 2015 by Mark Dice [ http://www.youtube.com/channel/UCzUV5283-l5c0oKRtyenj6Q / http://www.youtube.com/user/MarkDice , http://www.youtube.com/user/MarkDice/videos ]
Apple Co-Founder Steve Wozniak Fears Artificial Intelligence May Enslave Humans.
Mark Dice is a media analyst and author who, in an entertaining and educational way, reveals the effects of our celebrity obsessed culture and the manipulative power of mainstream media.
Mark's YouTube channel has received over 100 million views and his viral videos have been mentioned the Fox News Channel, CNN, the Drudge Report, TMZ, the New York Daily News, the Washington Times, and other media outlets around the world.
He has been featured on the History Channel's Decoded, Ancient Aliens, and America's Book of Secrets; Conspiracy Theory with Jesse Ventura on TruTV, Secret Societies of Hollywood on E! Channel, America Declassified on the Travel Channel, and is a frequent guest on Coast to Coast AM, and the Alex Jones Show.
Mark Dice is the author of several popular books on secret societies and conspiracies, including The Illuminati: Facts & Fiction, Big Brother: The Orwellian Nightmare Come True, The New World Order, Facts & Fiction, Inside the Illuminati, The Resistance Manifesto, and Illuminati in the Music Industry, which you can order now in paperback from Amazon.com or download the e-books through Kindle, iBooks, Nook, or Google Play.
While much of Mark's work confirms the existence and continued operation of the Illuminati today, he is also dedicated to debunking conspiracy theories and hoaxes and separating the facts from the fiction; hence the "Facts & Fiction" subtitle for several of his books. He has a bachelor's degree in communication from California State University.
He enjoys causing trouble for the New World Order, exposing corrupt scumbag politicians, and pointing out Big Brother's prying eyes. The term "fighting the New World Order" is used by Mark to describe some of his activities, and refers to his and others' resistance and opposition (The Resistance) to the overall system of political corruption, illegal wars, elite secret societies, mainstream media, Big Brother and privacy issues; as well as various economic and social issues. This Resistance involves self-improvement, self-sufficiency, personal responsibility and spiritual growth.
Be sure to subscribe to Mark's YouTube channel, checkout some of the previous videos and Playlists, and look him up on Facebook, Twitter, and Instagram.
http://www.Facebook.com/MarkDice
http://www.Twitter.com/MarkDice
http://Instagram.com/MarkDice
http://www.MarkDice.com
http://www.youtube.com/watch?v=Yu9uZ9IgsJU [with comments]
--
TechnoCalyps Part I TransHuman
TechnoCalyps Part II Preparing for the Singularity
TechnoCalyps Part III The Digital Messiah
Published on Jun 3, 2013 by TheDejavu434 [ http://www.youtube.com/channel/UCANw5MKh3A9q4ACtfdLwrKw / http://www.youtube.com/user/TheDejavu434 , http://www.youtube.com/user/TheDejavu434/videos ]
Technocalyps (2006)
http://www.imdb.com/title/tt0899298/
I do not own anything in this video. This video is only for educational purposes and I am not claiming this video as my own in any way.
http://www.youtube.com/watch?v=7MXQSbjBL7Q [with comments], http://www.youtube.com/watch?v=u1n0QSnWyAA [with comments], http://www.youtube.com/watch?v=EvWuF_KXuDk [with comments]
--
Google AI Ready For Takeover
Published on Jan 23, 2015 by The Alex Jones Channel [ http://www.youtube.com/channel/UCvsye7V9psc-APX6wV1twLg / http://www.youtube.com/user/TheAlexJonesChannel , http://www.youtube.com/user/TheAlexJonesChannel/videos ]
Alex Jones breaks down how AI is already here and they are just waiting to have it take control.
http://www.infowars.com/harvard-prof-government-mosquito-drones-will-extract-your-dna/
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http://www.youtube.com/watch?v=0KZKGcFlt64 [with comments]
--
Is The Age Of Man Over?
Published on Mar 15, 2015 by The Alex Jones Channel
Deep in the crowds of the South By Southwest Interactive Conference, Lee Ann McAdoo interviews Adam of http://www.stoptherobots.org/ in the midst of a raucous protest against the dehumanizing future of Artificial Intelligence. http://www.infowars.com/rage-against-the-machines-sxsw-anti-ai-protest-to-stop-the-robots/
‘Stop the Robots’ Protest Was Actually a Viral Stunt for a Dating App
March 16, 2015
The buzzy techno-skeptical protest group Stop the Robots is actually a viral marketing stunt for the dating app Quiver, Yahoo Tech has learned.
Quiver is a new matchmaking app from the company behind Couple, a popular app for those in relationships. It launched in February 2015; its conceit is that instead of a “cold, mechanical matchmaking algorithm,” the app uses humans (your friends) to pair you up with potential matches. Hence the synergy of a group called Stop the Robots.
[...]
https://www.yahoo.com/tech/stop-the-robots-protest-was-actually-a-viral-113822551229.html
http://www.youtube.com/watch?v=9eHmINo8sP8 [with comments]
--
The Furlough Gambit
Published on Jul 31, 2014 by AAAI Video Competition
The Furlough Gambit
Anthony M. Harrison, Laura M. Hiatt, William L. Adams, Wallace E. Lawson, Sangeet S. Khemlani, Franklin P. Tamborello, Samuel N. Blissard, J. Gregory Trafton
U.S. Naval Research Laboratory
AI Video Competition Features Robots Plotting Against Humans, More
11 Aug 2014
http://spectrum.ieee.org/automaton/robotics/artificial-intelligence/aaai-video-competition-2014
http://www.youtube.com/watch?v=c-yhWAnheKU [with comments]
===
Quantum computing, the story of a wild idea: Andris Ambainis at TEDxRiga 2013
Published on Aug 9, 2013 by TEDx Talks
Andris is a computer scientist active in the fields of quantum information theory and quantum computing. His valuable scientific input into quantum computer theory makes him one of the world's leading scientists in this field. Andris has invented several of world's first algorithms for quantum computers, including a method to show that some computing problems are hard to solve even with a quantum computer. He is the first Latvian scientist to receive a grant for further research in quantum computing from the European Research Council -- an organisation that supports Europe's best scientists.
Quantum computers are a radically different approach to computing. They use quantum physics (physical laws that work on the level of individual atoms) to achieve faster computing or more secure data transmission. In this talk, Andris Ambainis describes what quantum computers will be able to do, how they work and why building a quantum computer has become one of central problems in physics.
http://www.youtube.com/watch?v=Rvn_3cCrl9c [with comments]
--
Quantum Computing Update: Ray Laflamme at TEDxWaterloo 2013
Published on May 30, 2013 by TEDx Talks
Dr. Ray Laflamme returns to TEDxWaterloo to talk about what's new in the world of Quantum Computing since his 2010 appearance.
Ray is a Canadian physicist who did his Ph.D. with Stephen Hawking, worked at Los Alamos Laboratories and came to Waterloo in 2001 as a founding member of the Perimeter Institute. He is Director of the Institute for Quantum Computing and CSO of Universal Quantum Devices. He aims to bring the quantum revolution to your doorstep. Ray first appeared on the TEDxWaterloo stage in 2010 and is a great friend to the TEDxWaterloo community.
For more information on Ray Laflamme, see http://web7.iqc.uwaterloo.ca/~laflamme/
http://www.youtube.com/watch?v=mlstZ_xsTD4 [with comments]
--
Quantum Computers Animated
Published on Aug 22, 2013 by Piled Higher and Deeper (PHD Comics) [ http://www.youtube.com/channel/UCUL-pmhmDcZDwsA4cX2HO5w / http://www.youtube.com/user/phdcomics , http://www.youtube.com/user/phdcomics/videos ]
Theoretical Physicists John Preskill and Spiros Michalakis describe how things are different in the Quantum World and how that can lead to powerful Quantum Computers.
More at: http://phdcomics.com/tv
Animated by Jorge Cham: http://jorgecham.com
Featuring: John Preskill and Spiros Michalakis
Produced in Partnership with the Institute for Quantum Information and Matter ( http://iqim.caltech.edu ) at Caltech with funding provided by the National Science Foundation.
Animation Assistance: Meg Rosenburg
Transcription: Noel Dilworth
#FQXiVideoContest2014
http://www.youtube.com/watch?v=T2DXrs0OpHU [with comments]
--
Quantum Computing & the Entanglement Frontier - John Preskill
Published on Sep 3, 2013 by Institute for Quantum Computing [ http://www.youtube.com/channel/UCjbU8YFYBZAHAIVxY-OBaAQ / http://www.youtube.com/user/QuantumIQC , http://www.youtube.com/user/QuantumIQC/videos ]
John Preskill, the Richard Feynman Professor of Theoretical Physics at the California Institute of Technology, presents a public lecture: Quantum Computing & the Entanglement Frontier.
The quantum laws governing atoms and other tiny objects seem to defy common sense, and information encoded in quantum systems has weird properties that baffle our feeble human minds. John Preskill explains why he loves quantum entanglement, the elusive feature making quantum information fundamentally different from information in the macroscopic world. By exploiting quantum entanglement, quantum computers should be able to solve otherwise intractable problems, with far-reaching applications to cryptology, materials science, and medicine. Preskill is less weird than a quantum computer, and easier to understand.
Find out more about IQC!
Website - https://uwaterloo.ca/institute-for-quantum-computing/
Facebook - https://www.facebook.com/QuantumIQC
Twitter - https://twitter.com/QuantumIQC
Google Researchers Make Quantum Computing Components More Reliable
Researchers from Google and the University of California, Santa Barbara, used this chip to demonstrate a crucial method needed to make quantum computers reliable.
Researchers from a university and Google demonstrate a crucial error-correction step needed to make quantum computing practical.
March 4, 2015
http://www.technologyreview.com/news/535621/google-researchers-make-quantum-computing-components-more-reliable/
study:
State preservation by repetitive error detection in a superconducting quantum circuit
04 March 2015
http://www.nature.com/nature/journal/v519/n7541/full/nature14270.html
Thousands of atoms entangled with a single photon
This image illustrates the entanglement of a large number of atoms. The atoms, shown in purple, are shown mutually entangled with one another.
Result could make atomic clocks more accurate.
March 25, 2015
[...]
Eugene Polzik, a professor of quantum optics at the Niels Bohr Institute in Copenhagen, sees the group’s successful mutual entanglement of atoms as “a remarkable achievement.”
“The technique significantly broadens the options for generating and operating on non-classical, entangled states of atomic ensembles,” says Polzik, who was not involved in the research. “As such, it can be useful for clocks, quantum sensing of magnetic fields, and quantum communication.”
[...]
http://newsoffice.mit.edu/2015/thousands-atoms-entangled-single-photon-0325
study:
Entanglement with negative Wigner function of almost 3,000 atoms heralded by one photon
25 March 2015
http://www.nature.com/nature/journal/v519/n7544/full/nature14293.html
related article:
Quantum physics: Atomic doughnuts from single photons
25 March 2015
http://www.nature.com/nature/journal/v519/n7544/full/519420b.html
http://www.youtube.com/watch?v=3XbQpUtqgnU [with comments]
--
How To Tie A Quantum Knot
Published on Dec 2, 2014 by Piled Higher and Deeper (PHD Comics)
"The mysteries are just piling up." You can't split an electron, right? Wrong. Physicists Gil Refael and Jason Alicea explain the unique properties of electrons constrained to a 2 Dimensional world, and how they can be used to make noise-proof Quantum Computers.
More at: http://phdcomics.com/tv
Recorded and Animated by Jorge Cham: http://jorgecham.com
Featuring: Gil Refael and Jason Alicea
Read the blog post at Quantum Frontiers ( http://quantumfrontiers.com ):
http://quantumfrontiers.com/2014/12/04/this-video-of-scientists-splitting-an-electron-will-shock-you/
Produced in Partnership with the Institute for Quantum Information and Matter ( http://iqim.caltech.edu ) at Caltech with funding provided by the National Science Foundation.
http://www.youtube.com/watch?v=hKFecm9NKbM [with comments]
--
Quantum computation | Michelle Simmons | TEDxSydney
Published on Jun 22, 2012 by TEDx Talks
There is a shift coming in the very nature of computing which is being led by the likes of quantum physicist Michelle Simmons. Michelle wants you to put the binary world of ones and zeros on the shelf for a moment, as she introduces you to the idea of computing with atoms.
Michelle has always wanted to undertake the hardest research in the hardest subject: quantum physics. Her eccentric schooling, coupled with the sudden death of her PhD supervisor means she has spent most of her career teaching herself. Michelle is the Director of Australia's Centre of Excellence for Quantum Computation and Communication Technology [ http://www.cqc2t.org/ ]. This year, she and her team announced they had made the first ever single atom transistor. They now sit on the threshold of delivering the first ever quantum computer to the world.
TEDxSydney 2012 took place on Saturday 26 May 2012 at Carriageworks. Tens of thousands of people enjoyed the day: 800 in the theatre, over 1,000 via big screen simulcast in The Forum, many thousands online via YouTube and ABC Big Ideas ... and up to 80,000 tuning in to ABC Radio National.
http://www.youtube.com/watch?v=cugu4iW4W54 [with comments]
--
Quantum Computing 101
Published on Jul 24, 2014 by Microsoft [ http://www.youtube.com/channel/UCFtEEv80fQVKkD4h1PF-Xqw / http://www.youtube.com/user/Microsoft , http://www.youtube.com/user/Microsoft/videos ]
An introduction to the mind-bending world of quantum computing. Learn how Microsoft is blending quantum physics with computer science at http://www.microsoft.com/StationQ
Microsoft on Twitter
http://www.twitter.com/microsoft
Microsoft on Facebook
http://www.facebook.com/microsoft
http://www.youtube.com/watch?v=jg8iCnQTLfM [with comments]
--
Google and NASA's Quantum Artificial Intelligence Lab
Published on Oct 11, 2013 by Google [ http://www.youtube.com/channel/UCK8sQmJBp8GCxrOtXWBpyEA / http://www.youtube.com/user/Google , http://www.youtube.com/user/Google/videos ]
A peek at the early days of the Quantum AI Lab: a partnership between NASA, Google, USRA, and a 512-qubit D-Wave Two quantum computer. Learn more at:
http://google.com/+QuantumAILab
http://www.nas.nasa.gov/quantum/
http://www.usra.edu/quantum/
http://www.youtube.com/watch?v=CMdHDHEuOUE [with (over 5,000) comments]
===
Michio Kaku - Does the Cosmos have a Reason?
Published on Jan 7, 2013 by Closer To Truth [ http://www.youtube.com/channel/UCl9StMQ79LtEvlrskzjoYbQ / http://www.youtube.com/user/CloserToTruth1 , http://www.youtube.com/user/CloserToTruth1/videos ]
For more videos and information from Michio Kaku click here http://www.closertotruth.com/contributor/michio-kaku/profile
For more videos on whether the cosmos has a reason click here http://www.closertotruth.com/series/does-the-cosmos-have-reason
Cosmologists now develop credible theories about the beginning and end of our universe and theory-based speculations about vast numbers of multiple universes. But does the cosmos have a reason?
http://www.youtube.com/watch?v=VUTE5x-ghd8 [with comments]
===
Our Final Invention - AI and the end of the human era
Streamed live on Jan 26, 2014 by David Wood [ http://www.youtube.com/channel/UCYEil9jDXzug2ws6mHc8ZxQ / http://www.youtube.com/user/DeltaWisdom , http://www.youtube.com/user/DeltaWisdom/videos ]
The Hollywood cliché is that artificial intelligence will take over the world. Could this cliché soon become scientific reality, as AI matches then surpasses human intelligence?
Each year AI's cognitive speed and power doubles; ours does not. Corporations and government agencies are pouring billions into achieving AI's Holy Grail — human-level intelligence. Scientists argue that AI that advanced will have survival drives much like our own. Can we share the planet with it and survive?
The recently published book Our Final Invention: Artificial Intelligence and the End of the Human Era [ http://www.amazon.com/Our-Final-Invention-Artificial-Intelligence-ebook/dp/B00CQYAWRY ] explores how the pursuit of Artificial Intelligence challenges our existence with machines that won't love us or hate us, but whose indifference could spell our doom. Until now, intelligence has been constrained by the physical limits of its human hosts. What will happen when the brakes come off the most powerful force in the universe?
This London Futurists Hangout on Air will feature a live discussion between the author of Our Final Invention, James Barrat [ http://www.jamesbarrat.com/ ], and an international panel of leading futurists: Jaan Tallinn, William Hertling, Calum Chace, and Peter Rothman.
For more details of the panellists, see http://www.meetup.com/London-Futurists/events/154873102/
http://www.youtube.com/watch?v=F3sB7Nk-_oI [with comments]
--
Artificial intelligence: dream or nightmare? | Stefan Wess | TEDxZurich
Published on Nov 20, 2014 by TEDx Talks
This talk was given at a local TEDx event, produced independently of the TED Conferences. Artificial intelligence (AI) is a huge dream and vision for all mankind, and makes up a major part of most popular science fiction. John McCarthy coined the term in 1955 as "the science and engineering of making intelligent machines". Today, many notable companies have their stakes set on this technology, making AI a part of our everyday lives, e.g. Speech Recognition, Machine learning, Recommendation Systems and Personal Assistants. The ongoing global digital revolution, the unfailingly valid Moore’s Law, the Internet of Things and overall prevalent subject of Big Data, gives us the impression that creating “real” artificial intelligence is closer than ever before in history. AI has become “sexy” again. Besides large amounts of money flowing into the field of AI, numerous publications focus on the topic, AI shows up in our daily newsfeeds, and is already an integral part of most of our gadgets.
However, what would be the implications if a company could create “strong and real” AI? How would this influence our society and our jobs? Will it get smarter day by day? Would we be able to control a technical system of this nature?
Stefan Wess is a Researcher and Entrepreneur. He holds his PhD in Computer Science and is a highly recognized technology industry veteran with multinational front-line technology and scientific leadership experience. Stefan has written and published numerous books and articles on Artificial Intelligence. His professional career includes several Executive positions in international companies. As CEO of Empolis Information Management a Germany based IT company, he is still fascinated and excited how technology transforms our lives, the society and finally mankind.
http://www.youtube.com/watch?v=MaItaCQcYIE [with comments]
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The long-term future of AI (and what we can do about it): Daniel Dewey at TEDxVienna
Published on Dec 6, 2013 by TEDx Talks
Daniel Dewey is a research fellow in the Oxford Martin Programme on the Impacts of Future Technology at the Future of Humanity Institute, University of Oxford [ http://www.fhi.ox.ac.uk/ ]. His research includes paths and timelines to machine superintelligence, the possibility of intelligence explosion, and the strategic and technical challenges arising from these possibilities. Previously, Daniel worked as a software engineer at Google, did research at Intel Research Pittsburgh, and studied computer science and philosophy at Carnegie Mellon University. He is also a research associate at the Machine Intelligence Research Institute [ https://intelligence.org/ ].
http://www.tedxvienna.at/
http://www.facebook.com/tedxvienna
http://www.youtube.com/watch?v=CK5w3wh4G-M [with comments]
--
Exponential Technology Literacy: Neil Jacobstein at TEDxSanMigueldeAllende
Published on Jan 7, 2013 by TEDx Talks
Niell Jacobstein of NASA's Singularity University [ http://singularityu.org/ ] describes how artificial intelligence will change the world.
Neil Jacobstein Co-chairs the Artificial Intelligence and Robotics Track at Singularity University on the NASA Research Park campus in Mountain View California. He served as President of Singularity University from October 2010-2011. His work there focuses on the technical, business, and ethical implications of exponential technologies. Neil became a Reuters Research Fellow in the Digital Vision Program at Stanford University in 2006. He has been a Distinguished Visiting Scholar in Stanford's Media X Program since 2007. He Chaired AAAI's 17th Innovative Applications of Artificial Intelligence Conference, and has served as a technical consultant on AI research and development projects for many industrial and government agencies. Jacobstein was CEO of Teknowledge Corporation, a pioneering AI company. He worked as a graduate research intern in Alan Kay's Learning Research Group at Xerox's Palo Alto Research Center (PARC), and in PARC's Software Concepts Group. Neil is a Crown Fellow at the Aspen Institute. Jacobstein is deeply interdisciplinary, and for 20 years has served as Chairman of the Institute for Molecular Manufacturing, a nanotechnology R&D organization that has advised the White House Science Office, Foresight, and the Academy of Sciences. Neil has performed in executive and technical advisory roles for industry, NGOs, and government.
http://www.youtube.com/watch?v=nUWosx9lJ4o [with comments]
--
TEDxGWU - Peter Bock - Emergence of Creativity in Artificial Intelligence
Uploaded on Nov 17, 2011 by TEDx Talks
Peter Bock discusses the evolution of Artificial Intelligence and states his intention of creating the world's first artificial being. He shows the capabilities of the current system, known as ALISA, in creating works of art.
Peter Bock is a Professor Emeritus of the Department of Computer Science at The George Washington University. During his 40-year career, Peter has focused on developing his biologically-inspired statistical learning theory, known as Collective Learning Systems (CLS), to provide essential knowledge for reverse engineering the brain and understanding cognition. He worked with NASA as part of the Apollo Program.
http://www.youtube.com/watch?v=CpNfy7AUPl4 [with comments]
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How AI is Changing the Way We View Intelligence, the World, and Ourselves: Sam Spaulding at TEDxYale
Published on Jun 2, 2013 by TEDx Talks
http://www.youtube.com/watch?v=qXtCApIxap8 [with comments]
--
When creative machines overtake man: Jürgen Schmidhuber at TEDxLausanne
Published on Mar 10, 2012 by TEDx Talks
http://www.tedxlausanne.org - Machine intelligence is improving rapidly, to the point that the scientist of the future may not even be human! In fact, in more and more fields, learning machines are already outperforming humans.
Artificial intelligence expert Jürgen Schmidhuber isn't able to predict the future accurately, but he explains how machines are getting creative, why 40'000 years of Homo sapiens-dominated history are about to end soon, and how we can try to make the best of what lies ahead.
http://www.youtube.com/watch?v=KQ35zNlyG-o [with comments]
===
The Dominant Life Form in the Cosmos Is Probably Superintelligent Robots
December 19, 2014
http://motherboard.vice.com/read/the-dominant-life-form-in-the-cosmos-is-probably-superintelligent-robots [with comments]
===
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Written by Jason Koebler
March 23, 2015 // 09:22 AM EST
It's no secret that modern-day renaissance man Elon Musk fears what could happen if super intelligence robots self actualize—he once said that we're "summoning the demon [ http://motherboard.vice.com/read/elon-musk-on-artificial-intelligence-pentagrams-and-hal-9000 (video next item below)]" with AI research—but Sunday, Musk detailed exactly how he thinks how artificial intelligence could end humanity.
Musk, the founder of Tesla and SpaceX, went on StarTalk, Neil deGrasse Tyson's weekly podcast, to talk about all things future, and AI was a main topic of conversation.
"I'm quite worried about artificial super intelligence these days. I think it's something that's maybe more dangerous than nuclear weapons," Musk said. "We should be really careful about that. If there was a digital super intelligence that was created that could go into rapid, recursive self improvement in a non logarithmic way, that could reprogram itself to be smarter and iterate really quickly and do that 24 hours a day on millions of computers, then that's all she wrote."
[audio of the complete interview ( https://soundcloud.com/startalk/the-future-of-humanity-with-elon-musk ) embedded; original source http://www.startalkradio.net/show/the-future-of-humanity-with-elon-musk/ ]
If artificial intelligence is going to kill us, that's generally the way it's been predicted in sci-fi movies and by people who ponder such things [ http://motherboard.vice.com/read/super-intelligent-ai-could-wipe-out-humanity-if-were-not-ready-for-it ]: The intelligence will self actualize and teach itself how to become much, much smarter than us, and then it will be uncontrollable (work on superintelligence is ongoing [ http://motherboard.vice.com/read/a-global-arms-race-to-create-a-superintelligent-ai-is-looming ]). Musk said that we have to consider why, exactly, we're trying to make super intelligent robots.
If it's for human companionship and to make us happier (as detailed in Her [ http://en.wikipedia.org/wiki/Her_%28film%29 ], which you should watch if you haven't), well, maybe that won't end so well.
"The utility function of the digital super intelligence is of stupendous importance. What does it try to optimize? We need to be really careful with saying, ‘how about human happiness?’" Musk said. "It can conclude that an unhappy human should be terminated. Or that we should all be captured and [constantly] injected with dopamine and serotonin to optimize happiness. I'm just saying we should exercise caution."
Tyson asked Musk if he thought they'd domesticate us: "We'll be like a pet labrador if we're lucky."
Of course, Musk wasn't just spitballing. This is something he's thought about for a long time, and it's one of his more controversial talking points. He's even ?spent $10 million trying to keep ultra intelligent AI from becoming dangerous [ http://www.wired.com/2015/01/elon-musk-ai-safety/ ].
Tyson and his cohost for the episode, Bill Nye, are of course no slouches when it comes to thinking about the implications of tech, and both of them thought his theories were a little out there.
"Twenty percent of the world's population does not have electricity. They've never made a phone call," Nye said. "I think people have to keep in mind—computers are so reliable—but somebody is literally or in a sense shoveling the coal. What happens if you unplug the supercomputer or intelligence?"
Tyson said that guys like Musk are worried super intelligent robots will prevent you from unplugging it, but Nye asked how a computer would "create that thing to keep you from doing that? It seems like a solvable problem."
Likewise, artificial intelligence researchers have said that Musk's comments have a chilling effect [ http://motherboard.vice.com/read/we-need-to-talk-about-how-we-talk-about-artificial-intelligence ] on research, and that we are far, far away from ever having to worry about being overrun by robots.
But the idea of creating digital software that goes haywire and is uncontrollable isn't just a nightmare scenario—it's already happened. Consider that Stuxnet, a computer virus believed to have been created by the NSA to physically damage Iranian uranium enrichment factories, has now spread far across the internet and has infected Russian nuclear plants [ http://motherboard.vice.com/blog/stuxnet-americas-nuclear-plant-attacking-virus-has-infected-the-international-space-station ].
Stuxnet is a very specific piece of software that doesn't do much on regular computers besides replicate and spread itself, but it's easy to imagine superintelligence spreading itself across connected devices around the world. And then, maybe the only answer is to pull the plug on computers that we need. And then where are we?
© 2015 Vice Media LLC
http://motherboard.vice.com/read/elon-musk-on-superintelligent-robots-well-be-lucky-if-they-enslave-us-as-pets [with comments; the included YouTube excerpt of the interview at http://www.youtube.com/watch?v=pt3n9B8_e-8 (no comments yet)]
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One-on-one with Elon Musk
Published on Oct 31, 2014 by AeroAstroMIT [ http://www.youtube.com/channel/UCDeOZ2v5NhlIioMGux4_h-A / http://www.youtube.com/user/AeroAstroMIT , http://www.youtube.com/user/AeroAstroMIT/videos ]
MIT Aeronautics and Astronautics Department Head Jaime Peraire interviews SpaceX and Tesla CEO/founder Elon Musk, October 24, 2014, as the final session of the AeroAstro 1914-2014 Centennial Symposium.
http://www.youtube.com/watch?v=PULkWGHeIQQ [the comments re AI that have been noted are in the Q&A; with comments]
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Elon Musk, Neil deGrasse Tyson laugh about artificial intelligence turning the human race into its pet labrador
“We won’t be like a pet labrador if we’re lucky,” Elon Musk said.
(Rebecca Cook/Reuters)
By Matt McFarland
March 24, 2015
Elon Musk has already ignited a debate over the dangers of artificial intelligence [ http://www.washingtonpost.com/blogs/innovations/wp/2014/10/24/elon-musk-with-artificial-intelligence-we-are-summoning-the-demon/ ]. The chief executive of Tesla and SpaceX has called it humanity’s greatest threat, and something even more dangerous than nuclear weapons.
Musk publicly hasn’t offered a lot of detail about why he’s concerned, and what could go wrong. That changed in an interview with scientist Neil deGrasse Tyson, posted Sunday [ http://www.startalkradio.net/show/the-future-of-humanity-with-elon-musk/ ].
Musk’s fears lie with a subset of artificial intelligence, called superintelligence. It’s defined by Nick Bostrom, author of the highly-cited book “Superintelligence [ http://www.amazon.com/Superintelligence-Dangers-Strategies-Nick-Bostrom/dp/0199678111 ],” as “any intellect that greatly exceeds the cognitive performance of humans in virtually all domains of interest.”
Musk isn’t worried about simpler forms of artificial intelligence, such as a driverless car or smart air conditioning unit. The danger is when a machine can rapidly educate itself, as Musk explained:
“If there was a very deep digital superintelligence that was created that could go into rapid recursive self-improvement in a non-algorithmic way … it could reprogram itself to be smarter and iterate very quickly and do that 24 hours a day on millions of computers, well–”
“Then that’s all she wrote,” interjected Tyson with a chuckle.
“That’s all she wrote,” Musk answered. “I mean, we won’t be like a pet Labrador if we’re lucky.”
“A pet Lab,” laughed Tyson.
“I have a pet Labrador by the way,” Musk said.
“We’ll be their pets,” Tyson said.
“It’s like the friendliest creature,” Musk said, then letting out his lone chuckle of the segment.
“No, they’ll domesticate us,” Tyson said.
“Yes! Exactly,” said Musk, sounding serious again.
“So we’ll be lap pets to them,” Tyson said.
“Yes,” Musk said. “Or something strange is going to happen.”
“They’ll keep the docile humans and get rid of the violent ones,” Tyson theorized.
“Yeah,” Musk said.
“And then breed the docile humans,” Tyson said.
Musk then stressed the importance of what the superintelligence is programmed to optimize. It might seem appealing to have a computer figure out how to make us happier, but that could backfire:
“It may conclude that all unhappy humans should be terminated,” Musk said. “Or that we should all be captured and with dopamine and serotonin directly injected into our brains to maximize happiness because it’s concluded that dopamine and serotonin are what cause happiness, therefore maximize it,” which brought another chuckle from Tyson.
“I’m just saying we should exercise caution,” Musk concluded. You can listen to the entire interview here [ http://www.startalkradio.net/show/the-future-of-humanity-with-elon-musk/ ].
© 2015 The Washington Post
http://www.washingtonpost.com/blogs/innovations/wp/2015/03/24/elon-musk-neil-degrasse-tyson-laugh-about-artificial-intelligence-turning-the-human-race-into-its-pet-labrador/ [with comments]
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Artificial Intelligence Super Mario Gets Hungry And Wants To Kill Goombas
[title taken from http://www.huffingtonpost.com/2015/01/19/artificial-intelligence-super-mario_n_6502664.html [with this video embedded]]
Published on Jan 15, 2015 by AAAI Video Competition [ http://www.youtube.com/channel/UCPnD-1TJvd-Sm7cbAbR83Jw / http://www.youtube.com/user/aaaivideocompetition , http://www.youtube.com/user/aaaivideocompetition/videos ]
Mario Lives! An Adaptive Learning AI Approach for Generating a Living and Conversing Mario Agent
Stephan Ehrenfeld, Fabian Schrodt, & Prof. Dr. Martin V. Butz
Cognitive Modeling, Department of Computer Science, Faculty of Science, University of Tübingen, Germany
Winner of the AAAI ( http://www.aaai.org ) Video Competition ( http://aaaivideos.org ) People's Choice Award.
Click here for a full list of videos:
http://www.youtube.com/playlist?list=PLuOoXrWK6Kz4xqxnoRWt_PtBu6Uu3TAU9
Scientists are teaching Super Mario to think and feel
January 19, 2015
http://www.theverge.com/2015/1/19/7852975/artificially-intelligent-mario-learns-feel [with this video embedded]
Artificial Intelligence helps Mario play his own game
19 January 2015
http://www.bbc.co.uk/newsbeat/30879456
http://www.youtube.com/watch?v=AplG6KnOr2Q [comments disabled]
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Stephen Hawking: 'AI could spell end of the human race'
Published on Dec 2, 2014 by BBC News [ http://www.youtube.com/channel/UC16niRr50-MSBwiO3YDb3RA / http://www.youtube.com/user/bbcnews , http://www.youtube.com/user/bbcnews/videos ]
Professor Stephen Hawking has told the BBC that artificial intelligence could spell the end for the human race.
In an interview after the launch of a new software system designed to help him communicate more easily, he said there were many benefits to new technology but also some risks.
http://www.bbc.com/news/science-environment-30289705 [original non-YouTube posting of same video]
Read more:
Stephen Hawking warns artificial intelligence could end mankind
2 December 2014
http://www.bbc.com/news/technology-30290540
Check out our website: http://www.bbc.com/news
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http://www.youtube.com/watch?v=fFLVyWBDTfo [with comments]
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Google’s Eric Schmidt downplays fears over artificial intelligence
Eric Schmidt sees a bright future for artificial intelligence.
(Shannon Stapleton/Reuters)
By Matt McFarland
March 16, 2015
AUSTIN — Arguably the most alarming part of concerns over artificial intelligence’s potential to end human civilization [ http://www.washingtonpost.com/blogs/innovations/wp/2015/02/20/the-12-threats-to-human-civilization-ranked/ ] is the voices that are speaking out. Proven technology visionaries — from Bill Gates [ http://www.washingtonpost.com/blogs/the-switch/wp/2015/01/28/bill-gates-on-dangers-of-artificial-intelligence-dont-understand-why-some-people-are-not-concerned/ ] to Elon Musk [ http://www.washingtonpost.com/blogs/innovations/wp/2014/10/24/elon-musk-with-artificial-intelligence-we-are-summoning-the-demon/ ] and Stephen Hawking — have warned about the dangers of artificial intelligence. Given humans’ generally poor track record for predicting the future, it stands to reason that the forward thinkers could identify huge technology risks while the rest of us live in ignorance.
But Monday at SXSW, a tech thinker with a long résumé, Google Chairman Eric Schmidt, offered reassurance that we don’t need to be so worried right now.
“I think that this technology will ultimately be one of the greatest forces for good in mankind’s history simply because it makes people smarter,” Schmidt said during a keynote address with author Walter Isaacson and Megan Smith, U.S. chief technology officer.
“I’m certainly not worried in the next 10 to 20 years about that. We’re still in the baby step of understanding things,” Schmidt said. “We’ve made tremendous progress in respect to [artificial intelligence].”
He highlighted benevolent uses of artificial intelligence, such as Google Voice and Google’s translation services. Indeed, from antilock brakes to your iPhone’s autocorrect function, artificial intelligence already surrounds us, with favorable results.
“Stuff beyond that is, at this point, really speculation,” Schmidt said. “I’m not a dystopian. I’m a utopian, if you phrase it that way.”
As chairman of Google, Schmidt has a unique vantage point on how artificial intelligence is impacting our world and how it will continue to do so. Google is a leader in the space. In February, DeepMind, a Google acquisition, devised an algorithm that taught itself to beat Atari video games [ http://www.washingtonpost.com/blogs/innovations/wp/2015/02/25/googles-artificial-intelligence-breakthrough-may-have-a-huge-impact-on-self-driving-cars-and-much-more/ ]. While there’s reason to see Schmidt’s views as reassuring, it’s also worth noting that as the chairman of a leader in artificial intelligence, he has an incentive to underplay the downside of artificial intelligence. If the general public or regulators move to hamper artificial intelligence, Google’s businesses could suffer.
Later in the talk, Schmidt singled out machine learning, a subset of artificial intelligence, as having huge potential to reshape our world for the better.
“I think the biggest trend is going to be the use of machine intelligence of large data sets to solve every problem,” Schmidt said. “I can’t think of a field of study, a field of research — whether it’s English, soft sciences, hard sciences or any corporation — that can’t become far more efficient, far more powerful, far more clever.”
© 2015 The Washington Post
http://www.washingtonpost.com/blogs/innovations/wp/2015/03/16/googles-eric-schmidt-downplays-fears-over-artificial-intelligence/ [with comments]
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I'll Be Back: The Return of Artificial Intelligence
Terminator Salvation, 2009.
Photographer: Richard Foreman Jr./Warner Bros./ Everett Collection
Google, Facebook, Amazon spur rebirth of industry after decades of little corporate attention
by Jack Clark
9:00 AM CST February 3, 2015
The artificial-intelligence industry, a field that conjures up images of humanoid robots and self-aware computer systems, is making a comeback at Silicon Valley companies like Scaled Inference Inc [ https://scaledinference.com/ ].
Inside a sparsely decorated office at the eight-month-old startup, founder Olcan Sercinoglu is developing an AI system that can help predict events, such as what website you’ll read next. While that’s far from the kind of AI found in science-fiction movies, there’s plenty of interest in this new generation of AI tools, which can help with everything from recognizing speech patterns to sorting through thousands of photos.
“There was interest to invest from almost all of the investors that I spoke to,” said Sercinoglu, who raised $13.6 million in funding for his venture in just five months last year after spending 13 years on-and-off at Google Inc. working on AI projects. “Many AI companies have raised significant money without any product plans.”
Scaled Inference is one of more than a dozen startups now forming the backbone of a mini-boom in AI, which is software that exhibits the intuition of people. After two decades of the field suffering from scant research funding and little corporate attention, a rebirth is being spurred by interest from Google, Facebook Inc., Amazon.com Inc. and others, with Alibaba Group Holding Ltd. Chairman Jack Ma saying this week [ http://www.bloomberg.com/news/videos/2015-02-02/ma-alibaba-s-future-is-robots-artificial-intelligence ] that the Chinese e-commerce company will invest significantly in the area. In addition, falling technology costs have made the numerous computations underlying AI cheaper to perform.
In total, 16 AI companies were funded for the first time in 2014, up from two in 2010, according to data compiled by researcher CB Insights for Bloomberg News. The amount invested in the startups—some of which describe themselves as doing machine learning or deep learning—soared to $309.2 million last year, up more than 20-fold from $14.9 million in 2010.
“The field was pretty static for 20 or 30 years,” said venture capitalist Vinod Khosla, who has invested in young AI startups including Scaled Inference and MetaMind Inc. Yet with advancements in computing power and the growing volume of digital information, “the promise has gone up,” he said.
Like Scaled Inference, many of the AI startups aren’t developing Skynet-like systems or human-like machines and instead are focused on making clever tools to solve specific corporate problems. Startup Expect Labs Inc. is creating software so retailers can add speech-processing capabilities to mobile applications. Clarifai Inc. has developed image-recognition systems that can sort through thousands of photos taken by wedding photographers to select the prettiest pictures.
Yet the startups face long odds, given a history of AI flops. In the 1970s, AI funding plunged after the U.S. and U.K. governments became fed up with the slow progress on efforts like autonomous robots. In the 1980s, the market for AI hardware collapsed further when personal computers from Apple Inc. and International Business Machines Corp. became popular.
“The thing I worry about most is over-hype,” Khosla said.
Behind much of the proliferation of AI startups are large companies such as Google, Microsoft Corp., and Amazon, which have quietly built up AI capabilities over the past decade to handle enormous sets of data and make predictions, like which ad someone is more likely to click on. Starting in the mid-2000s, the companies resurrected AI techniques developed in the 1980s, paired them with powerful computers and started making money.
Their efforts have resulted in products like Apple’s chirpy assistant Siri and Google’s self-driving cars. It has also spurred deal-making, with Facebook acquiring voice-recognition AI startup Wit.ai [ http://www.bloomberg.com/news/articles/2015-01-05/facebook-buying-speech-recognition-developer-wit-ai ] last month and Google buying DeepMind Technologies Ltd. in January 2014.
For Google, “the biggest thing will be artificial intelligence,” Chairman Eric Schmidt said last year [ http://www.bloomberg.com/news/articles/2014-03-06/google-s-schmidt-sees-robots-omnipresent-in-a-good-way- ] in an interview with Bloomberg Television’s Emily Chang.
The companies have hired AI academics and engineers, some of whom are now spawning their own startups. Apart from Scaled Inference, former Googlers also founded AI company Moloco Inc. and Petametrics Inc.’s LiftIgniter. Amazon, Microsoft and Google engineers are also in key roles at startups including Sentient Technologies Holdings Ltd., SignalSense Inc. and Clarifai.
“At the big tech companies, you’re working with data at a scale that forces you to solve different problems than you would otherwise,” said Adam Berenzweig, chief technology officer at Clarifai in New York and a former Googler.
Falling technology costs have also helped trigger AI startups. Processing large amounts of data—a foundation of AI work—is cheaper as computer chips have gotten faster and the prices of storing and accessing data have dropped.
Systems called graphical processing units from companies including Nvidia Corp.—which enable companies to take on more of the monotonous-but-numerous computations needed to train and develop AI systems—have also dropped in price as GPUs have been manufactured on a mass scale for gadgets such as video-game consoles.
“The increase in performance over the last 17 years has been extraordinary,” said Jon Peddie of semiconductor market-research firm Jon Peddie Research. In 2014, people could buy a video card that was 84.3 times the performance of one from 2004 for the same price, he said.
The AI boom has also been stoked by universities, which have noticed the commercial success of AI at places like Google and taken advantage of falling hardware costs to do more research and collaborate with closely held companies.
Last November, the University of California at San Francisco began working with Palo Alto, California-based MetaMind on two projects: one to spot prostate cancer and the other to predict what may happen to a patient after reaching a hospital’s intensive care unit so that staff can more quickly tailor their approach to the person.
Theresa O’Brien, an associate chancellor at UCSF, said the university teamed up with the startup—the first such collaboration she’s aware of—because it wants to develop better approaches to bespoke medical treatment by employing computers to sort and link data, which AI can help.
As more AI startups emerge, companies are turning into customers. American Express Co. said it has increasingly been using AI techniques to help automatically spot fraudulent transactions.
“Our machine learning models help protect $1 trillion in charge volume every year, making the decision in less than 2 milliseconds,” Vernon Marshall, American Express’s functional risk officer, wrote in an e-mail, without disclosing which AI companies it works with. “We have been delighted with how well this technology can detect fraud.”
Revenue—which has been in short supply for AI makers in the past—is now trickling in. Sentient [ http://www.sentient.ai/ ], founded in 2007, is charging clients for technology that uses evolutionary algorithms to continuously ingest information and solve quantifiable problems, like how to profitably trade shares on the stock market. The San Francisco-based company closed $103.5 million [ http://www.bloomberg.com/news/articles/2014-11-24/ai-startup-sentient-raises-103-5-million-in-funding ] in financing in November and anticipates having 100 employees by the end of the year, up from 60 workers now, said Sentient Chief Executive Officer Antoine Blondeau.
While Sentient originally made trading systems for its own purposes from its AI technology, it has since applied it to other industries, including using the system to evaluate a hospital’s data to predict the chance of a patient falling into sepsis.
“We expect to grow significantly,” said Blondeau, who declined to disclose Sentient’s revenue or how much it charges for its products. “This is a very nascent space where disruption can be very quick and because of the nature of the problems that are being addressed in a specific case, is highly lucrative.”
©2015 Bloomberg L.P.
http://www.bloomberg.com/news/articles/2015-02-03/i-ll-be-back-the-return-of-artificial-intelligence
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Artificial Intelligence Goes to the Arcade
By Nicola Twilley
February 25, 2015
A shaky video, recorded with a mobile phone and smuggled out of the inaugural First Day of Tomorrow technology conference, in April, 2014, shows an artificially intelligent computer program in its first encounter with Breakout, the classic Atari arcade game. Prototyped in 1975 by Steve Wozniak, the co-founder of Apple, with assistance from Steve Jobs, the other co-founder of Apple, Breakout is a variant of Pong, in which a player knocks bricks from a wall by hitting a ball against it. After half an hour of play, the A.I. program is doing about as well as I would, which is to say not very—but it is trying to move its paddle toward the ball, apparently grasping the rudiments of the game. After another thirty minutes, two hundred rounds in, the A.I. has become a talented amateur: it misses the ball only every third or fourth time. The audience laughs; isn’t this cool?
Then something happens. By the three hundredth game, the A.I. has stopped missing the ball. The auditorium begins to buzz. Demis Hassabis, the program’s creator, advances to the next clip in his video presentation. The A.I. uses four quick rebounds to drill a hole through the left-hand side of the wall above it. Then it executes a killer bank shot, driving the ball into the hole and through to the other side, where it ricochets back and forth, destroying the entire wall from within. Now there are exclamations, applause, and shocked whispers from the crowd. Hours after encountering its first video game, and without any human coaching, the A.I. has not only become better than any human player but has also discovered a way to win that its creator never imagined.
Today, in a paper published in Nature [ http://www.nature.com/nature/journal/v518/n7540/full/nature14236.html , ful access http://www.nature.com/articles/nature14236.epdf?referrer_access_token=6_ZCZLs44V5es9R6kaUl_tRgN0jAjWel9jnR3ZoTv0P5kedCCNjz3FJ2FhQCgXkAMnH5lxK3VZA5OqpAt24MB5m6iQOU8PQiVd1y_3ofu5gClTBtCq0w4US77EIvFh9VwNVL-EehLacalZNtXMyj5a67sdjXqEH_aksjdpCef_zKkFET2MY6qSg3ro1VUrQUplaJvHIcMh-hADJoKJogj4mBAdfaLtWlZ_CJ6FscEzc%3D&tracking_referrer=www.newyorker.com / http://www.nature.com/articles/nature14236.epdf?referrer_access_token=6_ZCZLs44V5es9R6kaUl_tRgN0jAjWel9jnR3ZoTv0P5kedCCNjz3FJ2FhQCgXkAMnH5lxK3VZA5OqpAt24MB5m6iQOU8PQiVd1y_3ofu5gClTBtCq0w4US77EIvFh9VwNVL-EehLacalZNtXMyj5a67sdjXqEH_aksjdpCef_zKkFET2MY6qSg3ro1VUrQUplaJvHIcMh-hADJoKJogj4mBAdfaLtWlZ_CJ6FscEzc%3D ], Hassabis and his colleagues Volodymyr Mnih, Koray Kavukcuoglu, and David Silver reveal that their A.I. has since achieved the same feat with an angling game (Fishing Derby, 1980), a chicken-crossing-the-road game (Freeway, 1981), an armored-vehicle game (Robot Tank, 1983), a martial-arts game (Kung-Fu Master, 1984), and twenty-five others.* In more than a dozen of them, including Stargunner and Crazy Climber, from 1982, it made the best human efforts look pathetic. The Nature article appears just over a year after Hassabis’s company, DeepMind, made its public début; Google bought the firm for six hundred and fifty million dollars in January, 2014, soon after Hassabis first demonstrated his program’s superhuman gaming abilities, at a machine-learning workshop in a Harrah’s casino on the edge of Lake Tahoe. That program, the DeepMind team now claims, is a “novel artificial agent” that combines two existing forms of brain-inspired machine intelligence: a deep neural network and a reinforcement-learning algorithm.
Deep neural networks rely on layers of connections, known as nodes, to filter raw sensory data into meaningful patterns, just as neurons do in the brain. Apple’s Siri uses such a network to decipher speech, sorting sounds into recognizable chunks before drawing on contextual clues and past experiences to guess at how best to group them into words. Siri’s deductive powers improve (or ought to) every time you speak to her or correct her mistakes. The same technique can be applied to decoding images. To a computer with no preëxisting knowledge of brick walls or kung fu, the pixel data that it receives from an Atari game is meaningless. Rather than staring uncomprehendingly at the noise, however, a program like DeepMind’s will start analyzing those pixels—sorting them by color, finding edges and patterns, and gradually developing an ability to recognize complex shapes and the ways in which they fit together.
The program’s second, complementary form of intelligence—reinforcement learning—allows for a kind of unsupervised obedience training. DeepMind’s A.I. starts each game like an unhousebroken puppy. It is programmed to find a score rewarding, but is given no instruction in how to obtain that reward. Its first moves are random, made in ignorance of the game’s underlying logic. Some are rewarded with a treat—a score—and some are not. Buried in the DeepMind code, however, is an algorithm that allows the juvenile A.I. to analyze its previous performance, decipher which actions led to better scores, and change its future behavior accordingly. Combined with the deep neural network, this gives the program more or less the qualities of a good human gamer: the ability to interpret the screen, a knack for learning from past mistakes, and an overwhelming drive to win.
Whipping humanity’s ass at Fishing Derby may not seem like a particularly noteworthy achievement for artificial intelligence—nearly two decades ago, after all, I.B.M.’s Deep Blue computer beat Garry Kasparov, a chess grandmaster, at his own more intellectually aspirational game—but according to Zachary Mason, a novelist and computer scientist, it actually is. Chess, he noted, has an extremely limited “feature space”; the only information that Deep Blue needed to consider was the positions of the pieces on the board, during a span of not much more than a hundred turns. It could play to its strengths of perfect memory and brute-force computing power. But in an Atari game, Mason said, “there’s a byte or so of information per pixel” and hundreds of thousands of turns, which adds up to much more and much messier data for the DeepMind A.I. to process. In this sense, a game like Crazy Climber is a closer analogue to the real world than chess is, and in the real world humans still have the edge. Moreover, whereas Deep Blue was highly specialized, and preprogrammed by human grandmasters with a library of moves and rules, DeepMind is able to use the same all-purpose code for a wide array of games.
That adaptability holds promise. Hassabis has begun partnering with satellite operators and financial institutions to see whether his A.I. could eventually “play” their data sets, perhaps learning to make weather predictions or trade oil futures. In the short term, though, his team has a more modest next step in mind: to design a program that can play video games from the nineteen-nineties. Hassabis, who began working as a game designer in 1994, at the age of seventeen, and whose first project was the Golden Joystick-winning Theme Park, in which players got ahead by, among other things, hiring restroom-maintenance crews and oversalting snacks in order to boost beverage sales, is well aware that DeepMind’s current system, despite being state of the art, is at least five years away from being a decade behind the gaming curve. Indeed, the handful of games in which DeepMind’s A.I. failed to achieve human-level performance were the ones that required longer-term planning or more sophisticated pathfinding—Ms. Pac-Man, Private Eye, and Montezuma’s Revenge. One solution, Hassabis suggested, would be to make the A.I. bolder in its decision-making, and more willing to take risks. Because of the rote reinforcement learning, he said, “it’s overexploiting the knowledge that it already knows.”
In the longer term, after DeepMind has worked its way through Warcraft, StarCraft, and the rest of the Blizzard Entertainment catalogue, the team’s goal is to build an A.I. system with the capability of a toddler. But this, Hassabi said, they are nowhere near reaching. For one thing, he explained, “toddlers can do transfer learning—they can bring to bear prior knowledge to a new situation.” In other words, a toddler who masters Pong is likely to be immediately good at Breakout, whereas the A.I. has to learn both from scratch. Beyond that challenge lies the much thornier question of whether DeepMind’s chosen combination of a deep neural network and reinforcement learning could, on its own, ever lead to conceptual cognition—not only a fluency with the mechanics of, say, 2001’s Sub Command but also an understanding of what a submarine, water, or oxygen are. For Hassabis, this is “an open question.”
Zachary Mason is less sanguine. “Their current line of research leads to StarCraft in five or ten years and Call of Duty in maybe twenty, and controllers for drones in live battle spaces in maybe fifty,” he told me. “But it never, ever leads to a toddler.” Most toddlers cannot play chess or StarCraft. But they can interact with the real world in sophisticated ways. “They can find their way across a room,” Mason said. “They can see stuff, and as the light and shadows change they can recognize that it’s still the same stuff. They can understand and manipulate objects in space.” These kinds of tasks—the things that a toddler does with ease but that a machine struggles to grasp—cannot, Mason is convinced, be solved by a program that excels at teaching itself Breakout. They require a model of cognition that is much richer than what Atari, or perhaps any gaming platform, can offer. Hassabis’s algorithm represents a genuine breakthrough, but it is one that reinforces just how much distance remains between artificial intelligence and the human mind.
© 2015 Condé Nast
http://www.newyorker.com/tech/elements/deepmind-artificial-intelligence-video-games
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'Killer robots' need to be strictly monitored, nations warn at UN meeting
A man walks past a graffiti, denouncing strikes by US drones in Yemen, painted on a wall in Sana’a.
Photograph: Khaled Abdullah/Reuters
Countries warn of potential dangers of autonomous weapons systems they say are at risk of violating international and humanitarian law
Ed Pilkington in New York
Thursday 13 November 2014 14.09 EST
Last modified on Thursday 13 November 2014 19.17 EST
“Killer robots” – autonomous weapons systems that can identify and destroy targets in the absence of human control – should be strictly monitored to prevent violations of international or humanitarian law, nations from around the world demanded on Thursday.
The European Union, France, Spain, Austria, Ireland, the Netherlands, Croatia, Mexico and Sierra Leone, among other states, lined up at a special UN meeting in Geneva to warn of the potential dangers of this rapidly advancing technology. Several countries spoke of the need for ongoing scrutiny to ensure that the weapons conformed to the Geneva conventions’ rules on proportionality in war.
The Spanish delegation went further, invoking the possibility of a new arms race as developed countries scrambled to get ahead. Ireland, the Netherlands and other countries called for “meaningful human control” of lethal weapons to be enshrined in international law, although the meeting also admitted that the precise definition of that principle had yet to be clarified.
The Geneva meeting was the second major gathering of world powers this year to discuss the looming threat or possibility of fully self-operating lethal weapons. As such, it was an indication of mounting global concern about the technology, as its adoption by military forces gathers apace.
The US, the leader in the field, has already switched most of its aerial surveillance capabilities [ http://www.theguardian.com/world/2014/sep/30/war-console-drones-us-military-air-force-pilots-video-games ] to unmanned aircraft – though the drones are still controlled by human pilots. It is a natural next step for the US air force to develop systems that can both deliver and then operate missiles and bombs robotically, with only minimal human intervention.
The New York Times reported [ http://www.nytimes.com/2014/11/12/science/weapons-directed-by-robots-not-humans-raise-ethical-questions.html ] this week that Lockheed Martin has developed a long-range anti-ship missile for the US air force and navy that can fly itself, with no human touch, for hundreds of miles, changing its flight-path autonomously to avoid radar detection. Britain, Israel and Norway already carry out attacks on radar installations, tanks and ships using autonomous drones and missiles, the paper said.
At the previous Geneva meeting on killer robots, Christof Heyns, the UN special rapporteur on extrajudicial, summary or arbitrary executions [ http://www.ohchr.org/EN/Issues/Executions/Pages/SRExecutionsIndex.aspx ], called for an outright ban. “Machines lack morality and mortality, and as a result should not have life and death powers over humans,” he said.
Human Rights Watch [ http://www.hrw.org/ ], which is a co-founder of the Campaign to Stop Killer Robots [ http://www.stopkillerrobots.org/ ], told Thursday’s plenary that a ban was the only practical solution. The group lamented the fact that the UN had spent only eight or nine days over the past two years focused on an area that was fast-moving and raised huge legal and ethical issues.
“There is a sense of urgency about how we deal with killer robots. Technology is racing ahead,” it said.
Regulation of autonomous weapons falls under the so-called “convention on certain conventional weapons [ http://www.unog.ch/80256EE600585943/(httpPages)/4F0DEF093B4860B4C1257180004B1B30?OpenDocument ]” or CCW – a part of the Geneva conventions that deals with the impact of the tools of war on civilian populations. Under CCW, weapons that are deemed to affect civilians indiscriminately or to cause inhumane suffering to combatants can be banned or heavily restricted.
© 2014 Guardian News and Media Limited
http://www.theguardian.com/world/2014/nov/13/killer-robots-strictly-monitored-un-meeting-geneva [with comments]
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Steve Wozniak on AI: Will we be pets to or mere ants to be squashed by our robot overlords?
Credit: Garry Knight
Apple co-founder Steve Wozniak predicts a 'scary' future when artificial intelligence takes over from humans. It will be 'very bad for people,' but will we be pets to our robot overlords or mere ants to be squashed?
By Darlene Storm
Mar 25, 2015 6:27 AM PT
When artificial intelligence truly becomes super smart, will we be pets to our robot overlords or ants to be squashed? Neither scenario is very encouraging, but both were questions asked by Apple co-founder Steve Wozniak as he joined the ranks of prominent people warning that AI will eventually take over and get rid of humans.
"Computers are going to take over from humans, no question," Wozniak said [ http://www.afr.com/technology/apple-cofounder-steve-wozniak-on-the-apple-watch-electric-cars-and-the-surpassing-of-humanity-20150323-1m3xxk ] during an interview with Australian Financial Review. His opinion on artificial intelligence now aligns with worrisome predictions by Tesla’s chief executive Elon Musk, Professor Stephen Hawking and even Microsoft co-founder Bill Gates.
Wozniak stated:
Like people including Stephen Hawking and Elon Musk have predicted, I agree that the future is scary and very bad for people. If we build these devices to take care of everything for us, eventually they'll think faster than us and they'll get rid of the slow humans to run companies more efficiently.
Will we be the gods? Will we be the family pets? Or will we be ants that get stepped on? I don't know about that … But when I got that thinking in my head about if I'm going to be treated in the future as a pet to these smart machines … well I'm going to treat my own pet dog really nice.
Before Woz, Gates was the latest to join the AI-will-end-humanity club. During a Reddit "Ask me Anything" session, Gates was asked “How much of an existential threat do you think machine superintelligence will be?”
“I am in the camp that is concerned about super intelligence,” Gates replied [ http://www.reddit.com/r/IAmA/comments/2tzjp7/hi_reddit_im_bill_gates_and_im_back_for_my_third/co3r3g8 ]. “First the machines will do a lot of jobs for us and not be super intelligent. That should be positive if we manage it well. A few decades after that though the intelligence is strong enough to be a concern. I agree with Elon Musk and some others on this and don't understand why some people are not concerned.”
Back in December, Professor Stephen Hawking warned [ http://www.computerworld.com/article/2855036/stephen-hawking-artificial-intelligence-could-end-up-like-skynet.html ], “The development of full artificial intelligence could spell the end of the human race….It would take off on its own, and re-design itself at an ever increasing rate," he said. "Humans, who are limited by slow biological evolution, couldn't compete, and would be superseded."
Musk has been very vocal about his belief that AI potentially could be “more dangerous than nukes” and “our biggest existential threat.” He added [id.], “With artificial intelligence we are summoning the demon. In all those stories where there’s the guy with the pentagram and the holy water, it’s like yeah he’s sure he can control the demon. Didn't work out.”
Both Hawking and Musk signed [ http://futureoflife.org/misc/open_letter#signatories ] an open letter [ http://futureoflife.org/misc/open_letter ] about research priorities for robust and beneficial artificial intelligence. The research priorities paper (pdf [ http://futureoflife.org/static/data/documents/research_priorities.pdf ]) cited a Stanford study on “Loss of Control of AI systems.” The study voiced concerns that “we could one day lose control of AI systems via the rise of superintelligences that do not act in accordance with human wishes – and that such powerful systems would threaten humanity.”
Yet Wozniak suggested [ http://www.afr.com/technology/apple-cofounder-steve-wozniak-on-the-apple-watch-electric-cars-and-the-surpassing-of-humanity-20150323-1m3xxk ] the day super-smart machines take over the world might never come if Moore’s Law fails. Since 2005, various experts have suggested that computer processing speeds cannot keep doubling every two years so Moore’s Law may only continue until 2015 – 2020 [ http://en.wikipedia.org/wiki/Moore%27s_law ]. If our processors don’t get faster and faster every couple years, then quantum computing will never really take off and robot overlords can’t take over.
However Wozniak is hopeful about quantum computers, which use [ http://www.biv.com/article/2015/3/quantum-computers-raise-corporate-encryption-conce/ ] "subatomic particles to process complex calculations almost instantaneously." He said, "I hope it does come, and we should pursue it because it is about scientific exploring. But in the end we just may have created the species that is above us."
It might be worth noting that earlier this month University of California Santa Barbara researchers developed [ http://www.news.ucsb.edu/2015/015060/strength-numbers ] the “first-ever quantum device that detects and corrects its own errors.” The UC Santa Barbara news release explained, “When scientists develop a full quantum computer, the world of computing will undergo a revolution of sophistication, speed and energy efficiency that will make even our beefiest conventional machines seem like Stone Age clunkers by comparison.”
Yeah, but those “stone-age clunkers” aren't smart enough to evolve into Skynet and end humanity either.
Copyright © 2015 Computerworld, Inc.
http://www.computerworld.com/article/2901679/steve-wozniak-on-ai-will-we-be-pets-or-mere-ants-to-be-squashed-our-robot-overlords.html [with comments]
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Are We Ready For the Coming 'Age of Abundance?' - with Dr. Michio Kaku (Full)
Uploaded on Jun 27, 2011 by TheSasss1 [ http://www.youtube.com/channel/UCtjt2cXPOB_Ls3s2_SLMChA / http://www.youtube.com/user/TheSasss1 , http://www.youtube.com/user/TheSasss1/videos ]
Dr. Michio Kaku discussing economics, technology, and the future - full video of conference/discussion - from SAP’s Sapphire Now conference in Orlando, Florida, May 16-18, 2011 [ http://www.asugnews.com/article/8-things-to-know-about-sapphire-now-2011 , http://www.zdnet.com/article/sapphire-now-2011-the-wrap/ ].
SAP Sapphire Now Video (Full)
Booz & Company's Chief and Marketing and Knowledge Officer Tom Stewart moderated the Big Think panel made up of Michael Schrage, MIT Sloan School of Management research fellow, theoretical physicist Dr. Michio Kaku, Peter Diamandis, Founder and Chairman of the X-Prize Foundation, and Isabel Aguilera, former CEO of Google's Spain & Portugal operations.
http://bigthink.com/videos/sap-sapphire-now-video-full [non-YouTube video of the panel discussion following the opening presentation; with transcript]
http://www.youtube.com/watch?v=ceEog1XS5OI [with (over 7,000) comments, and embedded at http://www.kurzweilai.net/michio-kaku-explaining-americas-h1b-visa-declining-skilled-worker-population-domestically ; also at http://www.youtube.com/watch?v=G0FsHuwSe4k (no comments yet)]
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Michio Kaku on Singularity 1 on 1: Science is the Engine of Prosperity!
Published on Jun 6, 2014 by Nikola Danaylov [ http://www.youtube.com/channel/UCvjt0No0sOsJPBZE_2gdjug / http://www.youtube.com/user/ndanaylov , http://www.youtube.com/user/ndanaylov/videos ]
http://www.singularityweblog.com/michio-kaku-future-of-the-mind/
Dr. Michio Kaku is a theoretical physicist, bestselling author, acclaimed public speaker, renowned futurist, and popularizer of science. As co-founder of String Field Theory, Dr. Kaku carries on Einstein's quest to unite the four fundamental forces of nature into a single grand unified theory of everything. You will not be surprised to hear that Michio Kaku has been on my guest dream-list since I started Singularity 1 on 1, and I was beyond ecstatic to finally have an opportunity to speak to him.
During our 90 min conversation with Dr. Michio Kaku we cover a variety of interesting topics such as: why he shifted his focus from the universe to the human mind; his definition, classification and ranking of consciousness; his take on the Penrose-Hameroff Orch OR model; Newton, Einstein, determinism and free will; whether the brain is a classical computer or not; Norman Doidge's work on neuro-plasticity and The Brain That Changes Itself; the underlying reality of everything; his dream to finish what Einstein has started and know the mind of God; The Future of the Mind; mind-uploading and space travel at the speed of light; Moore's Law and D-Wave's quantum computer; the Human Brain Project and whole brain simulation; alternatives paths to AI and the Turing Test as a way of judging progress; cryonics and what is possible and impossible...
http://www.youtube.com/watch?v=AAEB-5GOCJ4 [with comments]
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Robots may take our jobs and cause the economy to crash - and you need to start saving money NOW, claims report
Economists used a simulated economy to create a model plotting a range of possible robot scenarios. This model revealed the rise of robots will initially create a tech boom, but this boom will turn to bust as workers are forced from their jobs and don't have enough money to pay for the goods the robots are producing.
Using a simulated economy, the paper found the value of coders will increase as demand for machines rise. As tech advances, costs will decline to deliver a 'tech boom'. But over time, the stock of so-called 'legacy code' will grow causing demand for new code and high-tech workers to drop and see them replaced by robots.
The eventual decline in jobs will limit what young people can save and invest. This means less capital will be available for the future generations and means production could actually fall over time, despite the fact machines are capable of producing goods more efficiently. A robot hotel employee in China is shown.
An alternative outcome of this is that high-skilled workers will move into low-skilled, lower paid positions, which will force these low-skilled workers into unemployment. And once people are out of work, welfare costs will rise putting a greater strain on the economy. The authors suggest people start saving for this eventuality.
'The long run in such cases is no techno-utopia,' said the researchers. 'Code is abundant but capital is dear. Everyone is employed. But no one is earning very much. In short, when smart machines replace people, they eventually bite the hands of those that finance them.' A robot designed to replace a shop worker is pictured.
• Experts create a model that plotted a range of possible robot scenarios
• They wanted to see how a rise in machines could impact national incomes
• This model revealed the rise of robots will initially create a tech boom
• But this boom will turn to bust as workers are forced from their jobs
• Humans won't have enough money to pay for goods made by the robots
• And rising unemployment will cause an increase in welfare costs
• As fewer people have capital to invest, production could fall over time
• And these factors could combine to cause economic damage globally
By Victoria Woollaston for MailOnline
Published: 09:09 EST, 25 February 2015 | Updated: 10:59 EST, 25 February 2015
The race to create robots that look, act and work like humans could see unemployment soar, welfare costs increase and may eventually bring the global economy to its knees.
That's the dystopian scenario put forward in a report looking at how machines will revolutionise the workplace in the not-so-distant future.
Economists created a simple model to plot a range of possible robot scenarios to see how the machines could impact national income, capital and quality of service.
In their paper [ http://www.nber.org/papers/w20941 ] Robots are Us: Some Economics of Human Replacement, lead researcher Seth Benzell said: 'Whether it’s bombing our enemies, steering our planes, fielding our calls, rubbing our backs, vacuuming our floors, driving our taxis, or beating us at Jeopardy, it’s hard to think of hitherto human tasks that smart machines can’t do or won’t soon do.'
With this in mind, Mr Benzell and his colleagues at the National Bureau of Economic Research asked whether 'human replacement' - the act of building better versions of ourselves - will deliver an economic utopia or leave us earning too little to buy the goods the robots are making?
Using a simulated economy, they found that the value of coders and developers will increase as the demand for smart machines rise.
As processes improve and technology advances the price to produce these machines will decline, which will deliver a 'tech boom'. This in turn will raise the demand for new code.
But over time, the stock of so-called 'legacy code' will grow because so many people are working on the projects, causing an abundance.
Plus this code will ultimately cause machines to become smarter and learn how to use the legacy code themselves.
This will cause demand for new code and, thus for high-tech workers, to drop and see such workers replaced by robot employees.
'The resulting tech bust reflects past humans obsolescing current humans. These robots contain the stuff of humans - accumulated brain and saving power,' said the paper.
'In fact, high-tech workers can start out earning far more than low-tech workers, but end up earning far less.'
The paper uses the example of Junior, the reigning World Computer Chess Champion. Junior can beat every current and, possibly, every future human on the planet.
Consequently, his old code has largely put new chess programmers out of business.
The eventual decline in high-tech and, potentially, low-tech workers income will limit what young people can save and invest, continued the paper.
This means less capital will be available for the future generations and production could actually fall over time, despite the fact machines are capable of producing goods more efficiently.
An alternative outcome of this is that high-skilled workers will move into low-skilled, lower paid positions, which will force these low-skilled workers into unemployment.
And once people are out of work, welfare costs will rise putting a greater strain on the economy. The authors even suggest people start saving for this eventuality.
'The long run in such cases is no techno-utopia. Yes, code is abundant. But capital is dear. And yes, everyone is fully employed. But no one is earning very much,' said Mr Bezell.
'In short, when smart machines replace people, they eventually bite the hands of those that finance them.'
The study's model firmly predicts three things - a long-run decline in the share of labour income, techbooms followed by tech-busts, and a growing dependency of current output on past software investment.
'Our simple model illustrates the range of things that smart machines can do for us and to us,' continued the paper.
'Its central message is disturbing. Absent appropriate fiscal policy that redistributes from winners to losers, smart machines can mean long-term misery for all.'
This study follows a similar report by management consulting firm Boston Consulting Group [ http://www.dailymail.co.uk/sciencetech/article-2946704/Cheaper-robots-replace-factory-workers-study.html ] that predicted by 2025 the number of 'automatable' tasks will rise to 25 per cent.
In turn, labour costs stand to drop by 16 per cent on average globally over that time.
The shift will mean an increasing demand for skilled workers who can operate the machines, said Hal Sirkin, a senior partner at Boston Consulting.
Factory workers 'will be higher paid but there will be fewer of them,' Mr Sirkin said.
Companies tend to start thinking about replacing workers when the costs of owning and operating a system come at a 15 per cent discount to employing a human counterpart.
For example, in the US automotive industry, which is predicted to be one of the more aggressive adopters of robots, a spot-welding machine costs $8 an hour versus $25 an hour for a worker.
A robot that can perform certain repetitive tasks costs about one-tenth as much as it did more than 10 years ago, Mr Sirkin said.
Costs tied to one commonly used robotics system, a spot welder, are also expected to fall 22 percent between now and 2025.
Three-fourths of robot installations over the next decade are expected to be concentrated in four areas: transportation equipment, including the automotive sector; computer and electronic products; electrical equipment and machinery.
By 2025, robots should be able to handle 30 to 40 per cent of automatable tasks across multiple industries.
Adoption will be slower in industries such as food products, plastics, fabricated metal, and wood products, where many tasks will remain difficult to automate and wages are relatively low.
Thanks to technological advances, however, robots are making greater inroads in these industries as well.
'Regardless of whether it's time to invest in next-generation robots, manufacturers everywhere should start preparing,' added Mr Sirkin.
'They need to understand how costs and automation technologies are changing in their industries and what their competitors are up to.'
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ARE THE PREDICTIONS ALREADY COMING TRUE?
The 'Robear' has a cub-like face but packs enough strength to transfer patients from a wheelchair (pictured) or a floor-level bed to a bath, for example.
A recent report by management consulting firm Boston Consulting Group predicted by 2025 the number of 'automatable' tasks will rise to 25 per cent [ http://www.dailymail.co.uk/sciencetech/article-2946704/Cheaper-robots-replace-factory-workers-study.html ].
This will lead to robots replacing many human jobs - and is a trend that has already begun in Japan.
Earlier this week Riken-SRK Collaboration Centre for Human-Interactive Robot Research in Nagoya, Japan unveiled its latest Robear [ http://www.dailymail.co.uk/sciencetech/article-2966380/Japans-Robear-Strength-robot-face-bear.html ].
The 'Robear' has a cub-like face but has enough strength to transfer patients from a wheelchair or a floor-level bed to a bath.
It weighs 309lb (140kg) with extending legs that stop the 'bear' from falling over and it moves slowly and smoothly thanks to advance actuators in its mechanical arms.
And at the start of the month, Mitsubishi UFJ Financial Group said it will begin employing a humanoid called Nao in its branches from April, on a trial basis.
And if the trial is successful, the robotic employees will be rolled out to more branches of the Japanese bank by 2020.
Elsewhere, in China there is a hotel manned entirely by robots.
From reception desk staff to security doormen and waiters, the Pengheng Space Capsules Hotel in Shenzhen, China, has built, rather than hired, new employees.
Start-up costs and robot maintenance aside, staff bills are minimal and the hotel can pass these savings back to the customer as a night's stay costs just £6.80 per night.
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SHOULD WE FEAR ARTIFICIAL INTELLIGENCE? ELON MUSK AND STEPHEN HAWKING WARNS OF POTENTIAL DANGERS
Stark warning: Professor Stephen Hawking says we must be vigilant about artificial intelligence.
Artificial Intelligence has been described as a threat that could be 'more dangerous than nukes'.
Now a group of scientists and entrepreneurs, including Elon Musk and Stephen Hawking, have signed an open letter [ http://futureoflife.org/misc/open_letter ] promising to ensure AI research benefits humanity.
The letter warns that without safeguards on intelligent machines, mankind could be heading for a dark future.
The document, drafted by the Future of Life Institute, said scientists should seek to head off risks that could wipe out mankind.
The authors say there is a 'broad consensus' that AI research is making good progress and would have a growing impact on society.
It highlights speech recognition, image analysis, driverless cars, translation and robot motion as having benefited from the research.
'The potential benefits are huge, since everything that civilisation has to offer is a product of human intelligence; we cannot predict what we might achieve when this intelligence is magnified by the tools AI may provide, but the eradication of disease and poverty are not unfathomable,' the authors write.
But it issued a stark warning that research into the rewards of AI had to be matched with an equal effort to avoid the potential damage it could wreak.
For instance, in the short term, it claims AI may put millions of people out of work.
In the long term, it could have the potential to play out like a fictional dystopias in which intelligence greater than humans could begin acting against their programming.
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WHAT JOBS COULD DISAPPEAR?
According to Dr Maggie Aderin-Pocock, a research fellow in UCL Department of Science and Technology Studies, care for the elderly and even children are among the jobs to be replaced by artificially intelligent beings within the next 50 years.
Her research suggests human workers across a plethora of service sectors and caring professions could be replaced by droids within our lifetimes.
She believes that as the rapid advances in technology achieved this century are projected to continue at an astonishing rate, this will allow robots to break free of science fiction and establish themselves in our everyday life.
According to her research - which polled 2,000 people about which jobs they thought were most unpopular and could be among the first to be given to robots for the TC channel Syfy - traffic wardens (65 per cent), estate agents (40 per cent) and car salesman (33 per cent) could soon be lost to history.
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© Associated Newspapers Ltd
http://www.dailymail.co.uk/sciencetech/article-2968503/Robots-jobs-cause-economy-crash-need-start-saving-money-claims-report.html [with comment; comments closed]
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SHAKEY: Experimentation in Robot Learning and Planning (1969)
Published on Oct 25, 2012 by SRI International [ http://www.youtube.com/channel/UC5A9qmHJVtuKNl_GmsqvbDA / http://www.youtube.com/user/innovationSRI , http://www.youtube.com/user/innovationSRI/videos ]
SRI's Shakey the Robot (1966-1972) was the first mobile robot that could reason about its surroundings. This 1969 movie provides a good look at how Shakey worked.
http://www.youtube.com/watch?v=RhrLHkVuerc [with comments]
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CoCoCo, Coffee Collecting Companion
Published on Jul 31, 2014 by AAAI Video Competition
CoCoCo, Coffee Collecting Companion
Paul Hanzal, Anne Rubruck, Sohaib Younis, Sascha Winde, Azad Aminian, Jyothi Yalpi, Sathya Kuppusami, Stefan Thomas
University of Hamburg
http://www.youtube.com/watch?v=XRsqDErCHN4 [no comments yet]
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Japan will open world's first hotel entirely operated by robots this summer
Henn na Hotel opens this summer in Sasebo, Japan. It will be staffed entirely by robots.
The hotel androids will provide porter service, room cleaning and front desk management. The hotel will also have facial recognition so guests can enter their rooms without key cards.
The hotel will open in Sasebo, Japan on July 17. Robots will carry luggage, clean rooms and manage reservations.
February 4, 2015
http://www.nydailynews.com/news/world/japan-open-hotel-operated-robots-article-1.2103352 [with comments]
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Bleep blorp: New Japanese hotel to be staffed by robots
February 5, 2015
[...]
"In the future, we're hoping to build 1,000 similar hotels around the world," says Sawada, according to Japan's Nikkei News [ http://zh.cn.nikkei.com/trend/tourism/12953-20150202.html ].
[...]
http://www.cnn.com/2015/02/04/travel/japan-hotel-robots/
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This Is Big: A Robo-Car Just Drove Across the Country
04.03.15
http://www.wired.com/2015/04/delphi-autonomous-car-cross-country/ [with comments]
*
Nissan pledges self-driving cars in Japan in 2016
AUTONOMOUS ALL THE WAY: Carlos Ghosn, chief executive, said formidable technological and legal challenges remain but that the direction of travel was plain.
April 3, 2015
http://www.thestar.com.my/Tech/Tech-News/2015/04/04/Nissan-pledges-self-driving-cars-in-Japan-in-2016/
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The Age of Artificial Intelligence: George John at TEDxLondonBusinessSchool 2013
Published on May 28, 2013 by TEDx Talks [ http://www.youtube.com/channel/UCsT0YIqwnpJCM-mx7-gSA4Q / http://www.youtube.com/user/TEDxTalks , http://www.youtube.com/user/TEDxTalks/videos ]
George, overly influenced by Star Trek, previously worked at NASA, earning his "rocket scientist" credentials. He currently manages Rocket Fuel and has married big data with artificial intelligence to create the leading programmatic media buying engine in digital advertising.
In the spirit of ideas worth spreading, TEDx is a program of local, self-organized events that bring people together to share a TED-like experience. At a TEDx event, TEDTalks video and live speakers combine to spark deep discussion and connection in a small group. These local, self-organized events are branded TEDx, where x = independently organized TED event. The TED Conference provides general guidance for the TEDx program, but individual TEDx events are self-organized.* (*Subject to certain rules and regulations)
http://www.youtube.com/watch?v=0qOf7SX2CS4 [with comments]
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Race Against the Machine: Andrew McAfee at TEDxBoston
Published on Jul 17, 2012 by TEDx Talks
"We ain't seen nothing yet when it comes to technology's impact on the labor force."
Automation redefined blue collar employment and reshaped a global economy. Now, technology is replacing higher skilled jobs by augmenting human brainpower the way steam engines augmented human labor. Andrew McAfee braces us for a fundamental transformation in the future of work.
http://www.youtube.com/watch?v=QfMGyCk3XTw [with comments]
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How Technology Is Destroying Jobs
Why It Matters
Economic theory and government policy will have to be rethought if technology is indeed destroying jobs faster than it is creating new ones.
By David Rotman on June 12, 2013
Also featured in MIT Technology Review magazine July/August 2013
Given his calm and reasoned academic demeanor, it is easy to miss just how provocative Erik Brynjolfsson’s contention really is. Brynjolfsson, a professor at the MIT Sloan School of Management, and his collaborator and coauthor Andrew McAfee have been arguing for the last year and a half that impressive advances in computer technology—from improved industrial robotics to automated translation services—are largely behind the sluggish employment growth of the last 10 to 15 years. Even more ominous for workers, the MIT academics foresee dismal prospects for many types of jobs as these powerful new technologies are increasingly adopted not only in manufacturing, clerical, and retail work but in professions such as law, financial services, education, and medicine.
That robots, automation, and software can replace people might seem obvious to anyone who’s worked in automotive manufacturing or as a travel agent. But Brynjolfsson and McAfee’s claim is more troubling and controversial. They believe that rapid technological change has been destroying jobs faster than it is creating them, contributing to the stagnation of median income and the growth of inequality in the United States. And, they suspect, something similar is happening in other technologically advanced countries.
Perhaps the most damning piece of evidence, according to Brynjolfsson, is a chart that only an economist could love. In economics, productivity—the amount of economic value created for a given unit of input, such as an hour of labor—is a crucial indicator of growth and wealth creation. It is a measure of progress. On the chart Brynjolfsson likes to show, separate lines represent productivity and total employment in the United States. For years after World War II, the two lines closely tracked each other, with increases in jobs corresponding to increases in productivity. The pattern is clear: as businesses generated more value from their workers, the country as a whole became richer, which fueled more economic activity and created even more jobs. Then, beginning in 2000, the lines diverge; productivity continues to rise robustly, but employment suddenly wilts. By 2011, a significant gap appears between the two lines, showing economic growth with no parallel increase in job creation. Brynjolfsson and McAfee call it the “great decoupling.” And Brynjolfsson says he is confident that technology is behind both the healthy growth in productivity and the weak growth in jobs.
It’s a startling assertion because it threatens the faith that many economists place in technological progress. Brynjolfsson and McAfee still believe that technology boosts productivity and makes societies wealthier, but they think that it can also have a dark side: technological progress is eliminating the need for many types of jobs and leaving the typical worker worse off than before. Brynjolfsson can point to a second chart indicating that median income is failing to rise even as the gross domestic product soars. “It’s the great paradox of our era,” he says. “Productivity is at record levels, innovation has never been faster, and yet at the same time, we have a falling median income and we have fewer jobs. People are falling behind because technology is advancing so fast and our skills and organizations aren’t keeping up.”
Brynjolfsson and McAfee are not Luddites. Indeed, they are sometimes accused of being too optimistic about the extent and speed of recent digital advances. Brynjolfsson says they began writing Race Against the Machine [ http://www.amazon.com/Race-Against-Machine-Accelerating-Productivity/dp/0984725113 ], the 2011 book in which they laid out much of their argument, because they wanted to explain the economic benefits of these new technologies (Brynjolfsson spent much of the 1990s sniffing out evidence that information technology was boosting rates of productivity). But it became clear to them that the same technologies making many jobs safer, easier, and more productive were also reducing the demand for many types of human workers.
Anecdotal evidence that digital technologies threaten jobs is, of course, everywhere. Robots and advanced automation have been common in many types of manufacturing for decades. In the United States and China, the world’s manufacturing powerhouses, fewer people work in manufacturing today than in 1997, thanks at least in part to automation. Modern automotive plants, many of which were transformed by industrial robotics in the 1980s, routinely use machines that autonomously weld and paint body parts—tasks that were once handled by humans. Most recently, industrial robots like Rethink Robotics’ Baxter (see “The Blue-Collar Robot [ http://www.technologyreview.com/featuredstory/513746/baxter-the-blue-collar-robot/ ],” May/June 2013), more flexible and far cheaper than their predecessors, have been introduced to perform simple jobs for small manufacturers in a variety of sectors. The website of a Silicon Valley startup called Industrial Perception features a video of the robot it has designed for use in warehouses picking up and throwing boxes like a bored elephant. And such sensations as Google’s driverless car suggest what automation might be able to accomplish someday soon.
A less dramatic change, but one with a potentially far larger impact on employment, is taking place in clerical work and professional services. Technologies like the Web, artificial intelligence, big data, and improved analytics—all made possible by the ever increasing availability of cheap computing power and storage capacity—are automating many routine tasks. Countless traditional white-collar jobs, such as many in the post office and in customer service, have disappeared. W. Brian Arthur, a visiting researcher at the Xerox Palo Alto Research Center’s intelligence systems lab and a former economics professor at Stanford University, calls it the “autonomous economy.” It’s far more subtle than the idea of robots and automation doing human jobs, he says: it involves “digital processes talking to other digital processes and creating new processes,” enabling us to do many things with fewer people and making yet other human jobs obsolete.
It is this onslaught of digital processes, says Arthur, that primarily explains how productivity has grown without a significant increase in human labor. And, he says, “digital versions of human intelligence” are increasingly replacing even those jobs once thought to require people. “It will change every profession in ways we have barely seen yet,” he warns.
McAfee, associate director of the MIT Center for Digital Business at the Sloan School of Management, speaks rapidly and with a certain awe as he describes advances such as Google’s driverless car. Still, despite his obvious enthusiasm for the technologies, he doesn’t see the recently vanished jobs coming back. The pressure on employment and the resulting inequality will only get worse, he suggests, as digital technologies—fueled with “enough computing power, data, and geeks”—continue their exponential advances over the next several decades. “I would like to be wrong,” he says, “but when all these science-fiction technologies are deployed, what will we need all the people for?”
New Economy?
But are these new technologies really responsible for a decade of lackluster job growth? Many labor economists say the data are, at best, far from conclusive. Several other plausible explanations, including events related to global trade and the financial crises of the early and late 2000s, could account for the relative slowness of job creation since the turn of the century. “No one really knows,” says Richard Freeman, a labor economist at Harvard University. That’s because it’s very difficult to “extricate” the effects of technology from other macroeconomic effects, he says. But he’s skeptical that technology would change a wide range of business sectors fast enough to explain recent job numbers.
David Autor, an economist at MIT who has extensively studied the connections between jobs and technology, also doubts that technology could account for such an abrupt change in total employment. “There was a great sag in employment beginning in 2000. Something did change,” he says. “But no one knows the cause.” Moreover, he doubts that productivity has, in fact, risen robustly in the United States in the past decade (economists can disagree about that statistic because there are different ways of measuring and weighing economic inputs and outputs). If he’s right, it raises the possibility that poor job growth could be simply a result of a sluggish economy. The sudden slowdown in job creation “is a big puzzle,” he says, “but there’s not a lot of evidence it’s linked to computers.”
To be sure, Autor says, computer technologies are changing the types of jobs available, and those changes “are not always for the good.” At least since the 1980s, he says, computers have increasingly taken over such tasks as bookkeeping, clerical work, and repetitive production jobs in manufacturing—all of which typically provided middle-class pay. At the same time, higher-paying jobs requiring creativity and problem-solving skills, often aided by computers, have proliferated. So have low-skill jobs: demand has increased for restaurant workers, janitors, home health aides, and others doing service work that is nearly impossible to automate. The result, says Autor, has been a “polarization” of the workforce and a “hollowing out” of the middle class—something that has been happening in numerous industrialized countries for the last several decades. But “that is very different from saying technology is affecting the total number of jobs,” he adds. “Jobs can change a lot without there being huge changes in employment rates.”
What’s more, even if today’s digital technologies are holding down job creation, history suggests that it is most likely a temporary, albeit painful, shock; as workers adjust their skills and entrepreneurs create opportunities based on the new technologies, the number of jobs will rebound. That, at least, has always been the pattern. The question, then, is whether today’s computing technologies will be different, creating long-term involuntary unemployment.
At least since the Industrial Revolution began in the 1700s, improvements in technology have changed the nature of work and destroyed some types of jobs in the process. In 1900, 41 percent of Americans worked in agriculture; by 2000, it was only 2 percent. Likewise, the proportion of Americans employed in manufacturing has dropped from 30 percent in the post–World War II years to around 10 percent today—partly because of increasing automation, especially during the 1980s.
While such changes can be painful for workers whose skills no longer match the needs of employers, Lawrence Katz, a Harvard economist, says that no historical pattern shows these shifts leading to a net decrease in jobs over an extended period. Katz has done extensive research on how technological advances have affected jobs over the last few centuries—describing, for example, how highly skilled artisans in the mid-19th century were displaced by lower-skilled workers in factories. While it can take decades for workers to acquire the expertise needed for new types of employment, he says, “we never have run out of jobs. There is no long-term trend of eliminating work for people. Over the long term, employment rates are fairly stable. People have always been able to create new jobs. People come up with new things to do.”
Still, Katz doesn’t dismiss the notion that there is something different about today’s digital technologies—something that could affect an even broader range of work. The question, he says, is whether economic history will serve as a useful guide. Will the job disruptions caused by technology be temporary as the workforce adapts, or will we see a science-fiction scenario in which automated processes and robots with superhuman skills take over a broad swath of human tasks? Though Katz expects the historical pattern to hold, it is “genuinely a question,” he says. “If technology disrupts enough, who knows what will happen?”
Dr. Watson
To get some insight into Katz’s question, it is worth looking at how today’s most advanced technologies are being deployed in industry. Though these technologies have undoubtedly taken over some human jobs, finding evidence of workers being displaced by machines on a large scale is not all that easy. One reason it is difficult to pinpoint the net impact on jobs is that automation is often used to make human workers more efficient, not necessarily to replace them. Rising productivity means businesses can do the same work with fewer employees, but it can also enable the businesses to expand production with their existing workers, and even to enter new markets.
Take the bright-orange Kiva robot, a boon to fledgling e-commerce companies. Created and sold by Kiva Systems, a startup that was founded in 2002 and bought by Amazon for $775 million in 2012, the robots are designed to scurry across large warehouses, fetching racks of ordered goods and delivering the products to humans who package the orders. In Kiva’s large demonstration warehouse and assembly facility at its headquarters outside Boston, fleets of robots move about with seemingly endless energy: some newly assembled machines perform tests to prove they’re ready to be shipped to customers around the world, while others wait to demonstrate to a visitor how they can almost instantly respond to an electronic order and bring the desired product to a worker’s station.
A warehouse equipped with Kiva robots can handle up to four times as many orders as a similar unautomated warehouse, where workers might spend as much as 70 percent of their time walking about to retrieve goods. (Coincidentally or not, Amazon bought Kiva soon after a press report revealed that workers at one of the retailer’s giant warehouses often walked more than 10 miles a day.)
Despite the labor-saving potential of the robots, Mick Mountz, Kiva’s founder and CEO, says he doubts the machines have put many people out of work or will do so in the future. For one thing, he says, most of Kiva’s customers are e-commerce retailers, some of them growing so rapidly they can’t hire people fast enough. By making distribution operations cheaper and more efficient, the robotic technology has helped many of these retailers survive and even expand. Before founding Kiva, Mountz worked at Webvan, an online grocery delivery company that was one of the 1990s dot-com era’s most infamous flameouts. He likes to show the numbers demonstrating that Webvan was doomed from the start; a $100 order cost the company $120 to ship. Mountz’s point is clear: something as mundane as the cost of materials handling can consign a new business to an early death. Automation can solve that problem.
Meanwhile, Kiva itself is hiring. Orange balloons—the same color as the robots—hover over multiple cubicles in its sprawling office, signaling that the occupants arrived within the last month. Most of these new employees are software engineers: while the robots are the company’s poster boys, its lesser-known innovations lie in the complex algorithms that guide the robots’ movements and determine where in the warehouse products are stored. These algorithms help make the system adaptable. It can learn, for example, that a certain product is seldom ordered, so it should be stored in a remote area.
Though advances like these suggest how some aspects of work could be subject to automation, they also illustrate that humans still excel at certain tasks—for example, packaging various items together. Many of the traditional problems in robotics—such as how to teach a machine to recognize an object as, say, a chair—remain largely intractable and are especially difficult to solve when the robots are free to move about a relatively unstructured environment like a factory or office.
Techniques using vast amounts of computational power have gone a long way toward helping robots understand their surroundings, but John Leonard, a professor of engineering at MIT and a member of its Computer Science and Artificial Intelligence Laboratory (CSAIL), says many familiar difficulties remain. “Part of me sees accelerating progress; the other part of me sees the same old problems,” he says. “I see how hard it is to do anything with robots. The big challenge is uncertainty.” In other words, people are still far better at dealing with changes in their environment and reacting to unexpected events.
For that reason, Leonard says, it is easier to see how robots could work with humans than on their own in many applications. “People and robots working together can happen much more quickly than robots simply replacing humans,” he says. “That’s not going to happen in my lifetime at a massive scale. The semiautonomous taxi will still have a driver.”
One of the friendlier, more flexible robots meant to work with humans is Rethink’s Baxter. The creation of Rodney Brooks, the company’s founder, Baxter needs minimal training to perform simple tasks like picking up objects and moving them to a box. It’s meant for use in relatively small manufacturing facilities where conventional industrial robots would cost too much and pose too much danger to workers. The idea, says Brooks, is to have the robots take care of dull, repetitive jobs that no one wants to do.
It’s hard not to instantly like Baxter, in part because it seems so eager to please. The “eyebrows” on its display rise quizzically when it’s puzzled; its arms submissively and gently retreat when bumped. Asked about the claim that such advanced industrial robots could eliminate jobs, Brooks answers simply that he doesn’t see it that way. Robots, he says, can be to factory workers as electric drills are to construction workers: “It makes them more productive and efficient, but it doesn’t take jobs.”
The machines created at Kiva and Rethink have been cleverly designed and built to work with people, taking over the tasks that the humans often don’t want to do or aren’t especially good at. They are specifically designed to enhance these workers’ productivity. And it’s hard to see how even these increasingly sophisticated robots will replace humans in most manufacturing and industrial jobs anytime soon. But clerical and some professional jobs could be more vulnerable. That’s because the marriage of artificial intelligence and big data is beginning to give machines a more humanlike ability to reason and to solve many new types of problems.
In the tony northern suburbs of New York City, IBM Research is pushing super-smart computing into the realms of such professions as medicine, finance, and customer service. IBM’s efforts have resulted in Watson, a computer system best known for beating human champions on the game show Jeopardy! in 2011. That version of Watson now sits in a corner of a large data center at the research facility in Yorktown Heights, marked with a glowing plaque commemorating its glory days. Meanwhile, researchers there are already testing new generations of Watson in medicine, where the technology could help physicians diagnose diseases like cancer, evaluate patients, and prescribe treatments.
IBM likes to call it cognitive computing. Essentially, Watson uses artificial-intelligence techniques, advanced natural-language processing and analytics, and massive amounts of data drawn from sources specific to a given application (in the case of health care, that means medical journals, textbooks, and information collected from the physicians or hospitals using the system). Thanks to these innovative techniques and huge amounts of computing power, it can quickly come up with “advice”—for example, the most recent and relevant information to guide a doctor’s diagnosis and treatment decisions.
Despite the system’s remarkable ability to make sense of all that data, it’s still early days for Dr. Watson. While it has rudimentary abilities to “learn” from specific patterns and evaluate different possibilities, it is far from having the type of judgment and intuition a physician often needs. But IBM has also announced it will begin selling Watson’s services to customer-support call centers, which rarely require human judgment that’s quite so sophisticated. IBM says companies will rent an updated version of Watson for use as a “customer service agent” that responds to questions from consumers; it has already signed on several banks. Automation is nothing new in call centers, of course, but Watson’s improved capacity for natural-language processing and its ability to tap into a large amount of data suggest that this system could speak plainly with callers, offering them specific advice on even technical and complex questions. It’s easy to see it replacing many human holdouts in its new field.
Digital Losers
The contention that automation and digital technologies are partly responsible for today’s lack of jobs has obviously touched a raw nerve for many worried about their own employment. But this is only one consequence of what Brynjolfsson and McAfee see as a broader trend. The rapid acceleration of technological progress, they say, has greatly widened the gap between economic winners and losers—the income inequalities that many economists have worried about for decades. Digital technologies tend to favor “superstars,” they point out. For example, someone who creates a computer program to automate tax preparation might earn millions or billions of dollars while eliminating the need for countless accountants.
New technologies are “encroaching into human skills in a way that is completely unprecedented,” McAfee says, and many middle-class jobs are right in the bull’s-eye; even relatively high-skill work in education, medicine, and law is affected. “The middle seems to be going away,” he adds. “The top and bottom are clearly getting farther apart.” While technology might be only one factor, says McAfee, it has been an “underappreciated” one, and it is likely to become increasingly significant.
Not everyone agrees with Brynjolfsson and McAfee’s conclusions—particularly the contention that the impact of recent technological change could be different from anything seen before. But it’s hard to ignore their warning that technology is widening the income gap between the tech-savvy and everyone else. And even if the economy is only going through a transition similar to those it’s endured before, it is an extremely painful one for many workers, and that will have to be addressed somehow. Harvard’s Katz has shown that the United States prospered in the early 1900s in part because secondary education became accessible to many people at a time when employment in agriculture was drying up. The result, at least through the 1980s, was an increase in educated workers who found jobs in the industrial sectors, boosting incomes and reducing inequality. Katz’s lesson: painful long-term consequences for the labor force do not follow inevitably from technological changes.
Brynjolfsson himself says he’s not ready to conclude that economic progress and employment have diverged for good. “I don’t know whether we can recover, but I hope we can,” he says. But that, he suggests, will depend on recognizing the problem and taking steps such as investing more in the training and education of workers.
“We were lucky and steadily rising productivity raised all boats for much of the 20th century,” he says. “Many people, especially economists, jumped to the conclusion that was just the way the world worked. I used to say that if we took care of productivity, everything else would take care of itself; it was the single most important economic statistic. But that’s no longer true.” He adds, “It’s one of the dirty secrets of economics: technology progress does grow the economy and create wealth, but there is no economic law that says everyone will benefit.” In other words, in the race against the machine, some are likely to win while many others lose.
Credits: Noma Bar (Illustration); Data from Bureau of Labor Statistics (Productivity, Output, GDP Per Capita); International Federation of Robotics; CIA World Factbook (GDP by Sector), Bureau of Labor Statistics (Job Growth, Manufacturing Employment); D. Autor and D. Dorn, U.S. Census, American Community Survey, and Department of Labor (Change in Employment and Wages by Skill, Routine Jobs)
Related:
Smart Robots Can Now Work Right Next to Auto Workers
It used to be too dangerous to have a person work alongside a robot. But at a South Carolina BMW plant, next-generation robots are changing that.
September 17, 2013
http://www.technologyreview.com/news/518661/smart-robots-can-now-work-right-next-to-auto-workers/
How Human-Robot Teamwork Will Upend Manufacturing
Robots are starting to collaborate with human workers in factories, offering greater efficiency and flexibility.
September 16, 2014
http://www.technologyreview.com/news/530696/how-human-robot-teamwork-will-upend-manufacturing/
Rise of the Robot Security Guards
Startup Knightscope is preparing to roll out human-size robot patrols.
November 13, 2014
http://www.technologyreview.com/news/532431/rise-of-the-robot-security-guards/
© 2013 MIT Technology Review
http://www.technologyreview.com/featuredstory/515926/how-technology-is-destroying-jobs/ [with comments]
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Artificial Intelligence and the Future of Humans and Robots in the Economy
Streamed live on Feb 27, 2015 by Council on Foreign Relations [ http://www.youtube.com/channel/UCL_A4jkwvKuMyToAPy3FQKQ / http://www.youtube.com/user/cfr , http://www.youtube.com/user/cfr/videos ]
MIT professor emeritus and Rethink Robotics’ founder Rodney Brooks, Carnegie Mellon’s Abhinav Gupta, and MIT’s Andrew McAfee, join Nicholas Thompson, editor at NewYorker.com, to discuss artificial intelligence (AI) and robot technology, and their economic impact on industry and society in the future.
The Malcolm and Carolyn Wiener Annual Lecture on Science and Technology addresses issues at the intersection of science, technology, and foreign policy.
Speakers:
Rodney Brooks, Panasonic Professor of Robotics (Emeritus), Computer Science and Artificial Intelligence Lab, Massachusetts Institute of Technology; Founder, Chairman, and Chief Technology Officer, Rethink Robotics
Abhinav Gupta, Assistant Research Professor, Robotics Institute, Carnegie Mellon University
Andrew McAfee, Principal Research Scientist and Cofounder, Initiative on the Digital Economy, Sloan School of Management, Massachusetts Institute of Technology
Presider:
Nicholas Thompson, Editor, "NewYorker.com"
http://www.youtube.com/watch?v=1TkcruN10-8 [with comments]
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Artificial Intelligence and the future | André LeBlanc | TEDxMoncton
Published on Jan 12, 2015 by TEDx Talks
This talk was given at a local TEDx event, produced independently of the TED Conferences. In his talk, Andre will explain the current and future impacts of Artificial Intelligence on industry, science, and how it will benefit and accelerate human progress.
With almost 20 years of business experience, André has a track record of success with multiple multi-million dollar ventures in multiple industries that have spanned the continent. His latest company works in the field of Artificial Intelligence (AI) and has created a one-of-a-kind neural network that simulates a growing neocortex. This system of neurons uses evolutionary concepts to self-organize to complete tasks only previously achievable by humans. Most futurists and experts believe that by 2035, AI will match and eventually surpass human intelligence.
http://www.youtube.com/watch?v=xH_B5xh42xc [with comments]
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The Share-the-Scraps Economy
By Robert Reich
Posted: 02/02/2015 1:51 pm EST Updated: 02/09/2015 5:59 pm EST
How would you like to live in an economy where robots do everything that can be predictably programmed in advance, and almost all profits go to the robots' owners?
Meanwhile, human beings do the work that's unpredictable - odd jobs, on-call projects, fetching and fixing, driving and delivering, tiny tasks needed at any and all hours - and patch together barely enough to live on.
Brace yourself. This is the economy we're now barreling toward.
They're Uber [ https://get.uber.com/cl/ ] drivers, Instacart [ https://www.instacart.com/ ] shoppers, and Airbnb [ https://www.airbnb.com/ ] hosts. They include Taskrabbit [ https://www.taskrabbit.com/careers ] jobbers, Upcounsel [ https://www.upcounsel.com/home/careers ]'s on-demand attorneys, and Healthtap [ https://www.healthtap.com/prime-trial ]'s on-line doctors.
They're Mechanical Turks [ https://www.mturk.com/mturk/welcome ].
The euphemism is the "share" economy [ http://www.economist.com/news/leaders/21573104-internet-everything-hire-rise-sharing-economy ]. A more accurate term would be the "share-the-scraps" economy.
New software technologies are allowing almost any job to be divided up into discrete tasks that can be parceled out to workers when they're needed, with pay determined by demand for that particular job at that particular moment.
Customers and workers are matched online. Workers are rated on quality and reliability.
The big money goes to the corporations that own the software. The scraps go to the on-demand workers.
Consider Amazon's "Mechanical Turk." Amazon calls it "a marketplace for work that requires human intelligence [ http://aws.amazon.com/mturk/ ]."
In reality, it's an Internet job board offering minimal pay for mindlessly-boring bite-sized chores. Computers can't do them because they require some minimal judgment, so human beings do them for peanuts -- say, writing a product description, for $3; or choosing the best of several photographs, for 30 cents; or deciphering handwriting, for 50 cents.
Amazon takes a healthy cut of every transaction.
This is the logical culmination of a process that began thirty years ago when corporations began turning over full-time jobs to temporary workers, independent contractors, free-lancers, and consultants.
It was a way to shift risks and uncertainties onto the workers - work that might entail more hours than planned for, or was more stressful than expected.
And a way to circumvent labor laws that set minimal standards for wages, hours, and working conditions. And that enabled employees to join together to bargain for better pay and benefits.
The new on-demand work shifts risks entirely onto workers, and eliminates minimal standards completely.
In effect, on-demand work is a reversion to the piece work of the nineteenth century - when workers had no power and no legal rights, took all the risks, and worked all hours for almost nothing.
Uber drivers [ http://www.businessinsider.com/uber-drivers-across-the-country-are-protesting-tomorrow--heres-why-2014-10 ] use their own cars, take out their own insurance, work as many hours as they want or can - and pay Uber a fat percent [ http://www.wsj.com/articles/ubers-new-funding-values-it-at-over-41-billion-1417715938 ]. Worker safety? Social Security? Uber says it's not the employer so it's not responsible.
Amazon's Mechanical Turks work for pennies, literally. Minimum wage? Time-and-a half for overtime? Amazon says it just connects buyers and sellers so it's not responsible.
Defenders of on-demand work emphasize its flexibility. Workers can put in whatever time they want, work around their schedules, fill in the downtime in their calendars.
"People are monetizing their own downtime," says [ http://www.nytimes.com/2015/01/29/technology/personaltech/uber-a-rising-business-model.html ] Arun Sundararajan, a professor at New York University's business school.
But this argument confuses "downtime" with the time people normally reserve for the rest of their lives.
There are still only twenty-four hours in a day. When "downtime" is turned into work time, and that work time is unpredictable and low-paid, what happens to personal relationships? Family? One's own health?
Other proponents of on-demand work point to studies, such as one recently commissioned by Uber, showing Uber's on-demand workers to be "happy [ http://www.newrepublic.com/article/120832/uber-study-uber-drivers-are-happy-uber ]."
But how many of them would be happier with a good-paying job offering regular hours?
An opportunity to make some extra bucks can seem mighty attractive in an economy whose median wage has been stagnant for thirty years and almost all of whose economic gains have been going to the top.
That doesn't make the opportunity a great deal. It only shows how bad a deal most working people have otherwise been getting.
Defenders also point out that as on-demand work continues to grow, on-demand workers are joining together in guild-like groups [ http://www.nytimes.com/2015/01/29/technology/personaltech/uber-a-rising-business-model.html ] to buy insurance and other benefits.
But, notably, they aren't using their bargaining power to get a larger share of the income they pull in, or steadier hours. That would be a union - something that Uber, Amazon, and other on-demand companies don't want.
Some economists laud on-demand work as a means of utilizing people more efficiently [ http://blogs.microsoft.com/work/2013/11/12/the-mobile-workforce-more-productive-efficient-and-healthy/ ].
But the biggest economic challenge we face isn't using people more efficiently. It's allocating work and the gains from work more decently.
On this measure, the share-the-scraps economy is hurtling us backwards.
Copyright ©2015 TheHuffingtonPost.com, Inc.
http://www.huffingtonpost.com/robert-reich/the-sharethescraps-econom_b_6597992.html [with comments]
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Apple co founder - Will AI Turn Us Into 'Family Pets' ??? Satanic Machines EXPOSED
Published on Mar 28, 2015 by Vigilant Christian [ http://www.youtube.com/channel/UCHKHC9bVGr49vuv1WyPp_5Q , http://www.youtube.com/channel/UCHKHC9bVGr49vuv1WyPp_5Q/videos ]
The transhumanist agenda will make men develop machines and AI without even thinking about the consequences! In this video I share an article that shows that even Apple's co-founder Mr Wozniak thinks this is a bad idea! Please share this video !! God Bless, STAY VIGILANT & FEAR NO EVIL !!!
Apple Co-Founder: Will AI Turn Us Into 'Family Pets'?
http://www.nbcnews.com/tech/tech-news/apple-co-founder-ai-will-take-over-humans-n329906
Illuminati Tranhumanist Agenda ! Man Merges with Machine to become a god http://www.youtube.com/playlist?list=PLTHDvEc6d7JFef03KNPTOhIW1qZJR8FpF
FaceLikeTheSun - Brother Gonz - NWO, Transhumanism, Entertainment Industry Exposed, Bible Teachings & more ...
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http://www.youtube.com/watch?v=-p4BWfyAir0 [with comments]
--
Apple Co-Founder Steve Wozniak Warns Artificial Intelligence May Enslave Humans
Published on Mar 25, 2015 by Mark Dice [ http://www.youtube.com/channel/UCzUV5283-l5c0oKRtyenj6Q / http://www.youtube.com/user/MarkDice , http://www.youtube.com/user/MarkDice/videos ]
Apple Co-Founder Steve Wozniak Fears Artificial Intelligence May Enslave Humans.
Mark Dice is a media analyst and author who, in an entertaining and educational way, reveals the effects of our celebrity obsessed culture and the manipulative power of mainstream media.
Mark's YouTube channel has received over 100 million views and his viral videos have been mentioned the Fox News Channel, CNN, the Drudge Report, TMZ, the New York Daily News, the Washington Times, and other media outlets around the world.
He has been featured on the History Channel's Decoded, Ancient Aliens, and America's Book of Secrets; Conspiracy Theory with Jesse Ventura on TruTV, Secret Societies of Hollywood on E! Channel, America Declassified on the Travel Channel, and is a frequent guest on Coast to Coast AM, and the Alex Jones Show.
Mark Dice is the author of several popular books on secret societies and conspiracies, including The Illuminati: Facts & Fiction, Big Brother: The Orwellian Nightmare Come True, The New World Order, Facts & Fiction, Inside the Illuminati, The Resistance Manifesto, and Illuminati in the Music Industry, which you can order now in paperback from Amazon.com or download the e-books through Kindle, iBooks, Nook, or Google Play.
While much of Mark's work confirms the existence and continued operation of the Illuminati today, he is also dedicated to debunking conspiracy theories and hoaxes and separating the facts from the fiction; hence the "Facts & Fiction" subtitle for several of his books. He has a bachelor's degree in communication from California State University.
He enjoys causing trouble for the New World Order, exposing corrupt scumbag politicians, and pointing out Big Brother's prying eyes. The term "fighting the New World Order" is used by Mark to describe some of his activities, and refers to his and others' resistance and opposition (The Resistance) to the overall system of political corruption, illegal wars, elite secret societies, mainstream media, Big Brother and privacy issues; as well as various economic and social issues. This Resistance involves self-improvement, self-sufficiency, personal responsibility and spiritual growth.
Be sure to subscribe to Mark's YouTube channel, checkout some of the previous videos and Playlists, and look him up on Facebook, Twitter, and Instagram.
http://www.Facebook.com/MarkDice
http://www.Twitter.com/MarkDice
http://Instagram.com/MarkDice
http://www.MarkDice.com
http://www.youtube.com/watch?v=Yu9uZ9IgsJU [with comments]
--
TechnoCalyps Part I TransHuman
TechnoCalyps Part II Preparing for the Singularity
TechnoCalyps Part III The Digital Messiah
Published on Jun 3, 2013 by TheDejavu434 [ http://www.youtube.com/channel/UCANw5MKh3A9q4ACtfdLwrKw / http://www.youtube.com/user/TheDejavu434 , http://www.youtube.com/user/TheDejavu434/videos ]
Technocalyps (2006)
http://www.imdb.com/title/tt0899298/
I do not own anything in this video. This video is only for educational purposes and I am not claiming this video as my own in any way.
http://www.youtube.com/watch?v=7MXQSbjBL7Q [with comments], http://www.youtube.com/watch?v=u1n0QSnWyAA [with comments], http://www.youtube.com/watch?v=EvWuF_KXuDk [with comments]
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Google AI Ready For Takeover
Published on Jan 23, 2015 by The Alex Jones Channel [ http://www.youtube.com/channel/UCvsye7V9psc-APX6wV1twLg / http://www.youtube.com/user/TheAlexJonesChannel , http://www.youtube.com/user/TheAlexJonesChannel/videos ]
Alex Jones breaks down how AI is already here and they are just waiting to have it take control.
http://www.infowars.com/harvard-prof-government-mosquito-drones-will-extract-your-dna/
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http://www.youtube.com/watch?v=0KZKGcFlt64 [with comments]
--
Is The Age Of Man Over?
Published on Mar 15, 2015 by The Alex Jones Channel
Deep in the crowds of the South By Southwest Interactive Conference, Lee Ann McAdoo interviews Adam of http://www.stoptherobots.org/ in the midst of a raucous protest against the dehumanizing future of Artificial Intelligence. http://www.infowars.com/rage-against-the-machines-sxsw-anti-ai-protest-to-stop-the-robots/
‘Stop the Robots’ Protest Was Actually a Viral Stunt for a Dating App
March 16, 2015
The buzzy techno-skeptical protest group Stop the Robots is actually a viral marketing stunt for the dating app Quiver, Yahoo Tech has learned.
Quiver is a new matchmaking app from the company behind Couple, a popular app for those in relationships. It launched in February 2015; its conceit is that instead of a “cold, mechanical matchmaking algorithm,” the app uses humans (your friends) to pair you up with potential matches. Hence the synergy of a group called Stop the Robots.
[...]
https://www.yahoo.com/tech/stop-the-robots-protest-was-actually-a-viral-113822551229.html
http://www.youtube.com/watch?v=9eHmINo8sP8 [with comments]
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The Furlough Gambit
Published on Jul 31, 2014 by AAAI Video Competition
The Furlough Gambit
Anthony M. Harrison, Laura M. Hiatt, William L. Adams, Wallace E. Lawson, Sangeet S. Khemlani, Franklin P. Tamborello, Samuel N. Blissard, J. Gregory Trafton
U.S. Naval Research Laboratory
AI Video Competition Features Robots Plotting Against Humans, More
11 Aug 2014
http://spectrum.ieee.org/automaton/robotics/artificial-intelligence/aaai-video-competition-2014
http://www.youtube.com/watch?v=c-yhWAnheKU [with comments]
===
Quantum computing, the story of a wild idea: Andris Ambainis at TEDxRiga 2013
Published on Aug 9, 2013 by TEDx Talks
Andris is a computer scientist active in the fields of quantum information theory and quantum computing. His valuable scientific input into quantum computer theory makes him one of the world's leading scientists in this field. Andris has invented several of world's first algorithms for quantum computers, including a method to show that some computing problems are hard to solve even with a quantum computer. He is the first Latvian scientist to receive a grant for further research in quantum computing from the European Research Council -- an organisation that supports Europe's best scientists.
Quantum computers are a radically different approach to computing. They use quantum physics (physical laws that work on the level of individual atoms) to achieve faster computing or more secure data transmission. In this talk, Andris Ambainis describes what quantum computers will be able to do, how they work and why building a quantum computer has become one of central problems in physics.
http://www.youtube.com/watch?v=Rvn_3cCrl9c [with comments]
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Quantum Computing Update: Ray Laflamme at TEDxWaterloo 2013
Published on May 30, 2013 by TEDx Talks
Dr. Ray Laflamme returns to TEDxWaterloo to talk about what's new in the world of Quantum Computing since his 2010 appearance.
Ray is a Canadian physicist who did his Ph.D. with Stephen Hawking, worked at Los Alamos Laboratories and came to Waterloo in 2001 as a founding member of the Perimeter Institute. He is Director of the Institute for Quantum Computing and CSO of Universal Quantum Devices. He aims to bring the quantum revolution to your doorstep. Ray first appeared on the TEDxWaterloo stage in 2010 and is a great friend to the TEDxWaterloo community.
For more information on Ray Laflamme, see http://web7.iqc.uwaterloo.ca/~laflamme/
http://www.youtube.com/watch?v=mlstZ_xsTD4 [with comments]
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Quantum Computers Animated
Published on Aug 22, 2013 by Piled Higher and Deeper (PHD Comics) [ http://www.youtube.com/channel/UCUL-pmhmDcZDwsA4cX2HO5w / http://www.youtube.com/user/phdcomics , http://www.youtube.com/user/phdcomics/videos ]
Theoretical Physicists John Preskill and Spiros Michalakis describe how things are different in the Quantum World and how that can lead to powerful Quantum Computers.
More at: http://phdcomics.com/tv
Animated by Jorge Cham: http://jorgecham.com
Featuring: John Preskill and Spiros Michalakis
Produced in Partnership with the Institute for Quantum Information and Matter ( http://iqim.caltech.edu ) at Caltech with funding provided by the National Science Foundation.
Animation Assistance: Meg Rosenburg
Transcription: Noel Dilworth
#FQXiVideoContest2014
http://www.youtube.com/watch?v=T2DXrs0OpHU [with comments]
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Quantum Computing & the Entanglement Frontier - John Preskill
Published on Sep 3, 2013 by Institute for Quantum Computing [ http://www.youtube.com/channel/UCjbU8YFYBZAHAIVxY-OBaAQ / http://www.youtube.com/user/QuantumIQC , http://www.youtube.com/user/QuantumIQC/videos ]
John Preskill, the Richard Feynman Professor of Theoretical Physics at the California Institute of Technology, presents a public lecture: Quantum Computing & the Entanglement Frontier.
The quantum laws governing atoms and other tiny objects seem to defy common sense, and information encoded in quantum systems has weird properties that baffle our feeble human minds. John Preskill explains why he loves quantum entanglement, the elusive feature making quantum information fundamentally different from information in the macroscopic world. By exploiting quantum entanglement, quantum computers should be able to solve otherwise intractable problems, with far-reaching applications to cryptology, materials science, and medicine. Preskill is less weird than a quantum computer, and easier to understand.
Find out more about IQC!
Website - https://uwaterloo.ca/institute-for-quantum-computing/
Facebook - https://www.facebook.com/QuantumIQC
Twitter - https://twitter.com/QuantumIQC
Google Researchers Make Quantum Computing Components More Reliable
Researchers from Google and the University of California, Santa Barbara, used this chip to demonstrate a crucial method needed to make quantum computers reliable.
Researchers from a university and Google demonstrate a crucial error-correction step needed to make quantum computing practical.
March 4, 2015
http://www.technologyreview.com/news/535621/google-researchers-make-quantum-computing-components-more-reliable/
study:
State preservation by repetitive error detection in a superconducting quantum circuit
04 March 2015
http://www.nature.com/nature/journal/v519/n7541/full/nature14270.html
Thousands of atoms entangled with a single photon
This image illustrates the entanglement of a large number of atoms. The atoms, shown in purple, are shown mutually entangled with one another.
Result could make atomic clocks more accurate.
March 25, 2015
[...]
Eugene Polzik, a professor of quantum optics at the Niels Bohr Institute in Copenhagen, sees the group’s successful mutual entanglement of atoms as “a remarkable achievement.”
“The technique significantly broadens the options for generating and operating on non-classical, entangled states of atomic ensembles,” says Polzik, who was not involved in the research. “As such, it can be useful for clocks, quantum sensing of magnetic fields, and quantum communication.”
[...]
http://newsoffice.mit.edu/2015/thousands-atoms-entangled-single-photon-0325
study:
Entanglement with negative Wigner function of almost 3,000 atoms heralded by one photon
25 March 2015
http://www.nature.com/nature/journal/v519/n7544/full/nature14293.html
related article:
Quantum physics: Atomic doughnuts from single photons
25 March 2015
http://www.nature.com/nature/journal/v519/n7544/full/519420b.html
http://www.youtube.com/watch?v=3XbQpUtqgnU [with comments]
--
How To Tie A Quantum Knot
Published on Dec 2, 2014 by Piled Higher and Deeper (PHD Comics)
"The mysteries are just piling up." You can't split an electron, right? Wrong. Physicists Gil Refael and Jason Alicea explain the unique properties of electrons constrained to a 2 Dimensional world, and how they can be used to make noise-proof Quantum Computers.
More at: http://phdcomics.com/tv
Recorded and Animated by Jorge Cham: http://jorgecham.com
Featuring: Gil Refael and Jason Alicea
Read the blog post at Quantum Frontiers ( http://quantumfrontiers.com ):
http://quantumfrontiers.com/2014/12/04/this-video-of-scientists-splitting-an-electron-will-shock-you/
Produced in Partnership with the Institute for Quantum Information and Matter ( http://iqim.caltech.edu ) at Caltech with funding provided by the National Science Foundation.
http://www.youtube.com/watch?v=hKFecm9NKbM [with comments]
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Quantum computation | Michelle Simmons | TEDxSydney
Published on Jun 22, 2012 by TEDx Talks
There is a shift coming in the very nature of computing which is being led by the likes of quantum physicist Michelle Simmons. Michelle wants you to put the binary world of ones and zeros on the shelf for a moment, as she introduces you to the idea of computing with atoms.
Michelle has always wanted to undertake the hardest research in the hardest subject: quantum physics. Her eccentric schooling, coupled with the sudden death of her PhD supervisor means she has spent most of her career teaching herself. Michelle is the Director of Australia's Centre of Excellence for Quantum Computation and Communication Technology [ http://www.cqc2t.org/ ]. This year, she and her team announced they had made the first ever single atom transistor. They now sit on the threshold of delivering the first ever quantum computer to the world.
TEDxSydney 2012 took place on Saturday 26 May 2012 at Carriageworks. Tens of thousands of people enjoyed the day: 800 in the theatre, over 1,000 via big screen simulcast in The Forum, many thousands online via YouTube and ABC Big Ideas ... and up to 80,000 tuning in to ABC Radio National.
http://www.youtube.com/watch?v=cugu4iW4W54 [with comments]
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Quantum Computing 101
Published on Jul 24, 2014 by Microsoft [ http://www.youtube.com/channel/UCFtEEv80fQVKkD4h1PF-Xqw / http://www.youtube.com/user/Microsoft , http://www.youtube.com/user/Microsoft/videos ]
An introduction to the mind-bending world of quantum computing. Learn how Microsoft is blending quantum physics with computer science at http://www.microsoft.com/StationQ
Microsoft on Twitter
http://www.twitter.com/microsoft
Microsoft on Facebook
http://www.facebook.com/microsoft
http://www.youtube.com/watch?v=jg8iCnQTLfM [with comments]
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Google and NASA's Quantum Artificial Intelligence Lab
Published on Oct 11, 2013 by Google [ http://www.youtube.com/channel/UCK8sQmJBp8GCxrOtXWBpyEA / http://www.youtube.com/user/Google , http://www.youtube.com/user/Google/videos ]
A peek at the early days of the Quantum AI Lab: a partnership between NASA, Google, USRA, and a 512-qubit D-Wave Two quantum computer. Learn more at:
http://google.com/+QuantumAILab
http://www.nas.nasa.gov/quantum/
http://www.usra.edu/quantum/
http://www.youtube.com/watch?v=CMdHDHEuOUE [with (over 5,000) comments]
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Michio Kaku - Does the Cosmos have a Reason?
Published on Jan 7, 2013 by Closer To Truth [ http://www.youtube.com/channel/UCl9StMQ79LtEvlrskzjoYbQ / http://www.youtube.com/user/CloserToTruth1 , http://www.youtube.com/user/CloserToTruth1/videos ]
For more videos and information from Michio Kaku click here http://www.closertotruth.com/contributor/michio-kaku/profile
For more videos on whether the cosmos has a reason click here http://www.closertotruth.com/series/does-the-cosmos-have-reason
Cosmologists now develop credible theories about the beginning and end of our universe and theory-based speculations about vast numbers of multiple universes. But does the cosmos have a reason?
http://www.youtube.com/watch?v=VUTE5x-ghd8 [with comments]
===
Our Final Invention - AI and the end of the human era
Streamed live on Jan 26, 2014 by David Wood [ http://www.youtube.com/channel/UCYEil9jDXzug2ws6mHc8ZxQ / http://www.youtube.com/user/DeltaWisdom , http://www.youtube.com/user/DeltaWisdom/videos ]
The Hollywood cliché is that artificial intelligence will take over the world. Could this cliché soon become scientific reality, as AI matches then surpasses human intelligence?
Each year AI's cognitive speed and power doubles; ours does not. Corporations and government agencies are pouring billions into achieving AI's Holy Grail — human-level intelligence. Scientists argue that AI that advanced will have survival drives much like our own. Can we share the planet with it and survive?
The recently published book Our Final Invention: Artificial Intelligence and the End of the Human Era [ http://www.amazon.com/Our-Final-Invention-Artificial-Intelligence-ebook/dp/B00CQYAWRY ] explores how the pursuit of Artificial Intelligence challenges our existence with machines that won't love us or hate us, but whose indifference could spell our doom. Until now, intelligence has been constrained by the physical limits of its human hosts. What will happen when the brakes come off the most powerful force in the universe?
This London Futurists Hangout on Air will feature a live discussion between the author of Our Final Invention, James Barrat [ http://www.jamesbarrat.com/ ], and an international panel of leading futurists: Jaan Tallinn, William Hertling, Calum Chace, and Peter Rothman.
For more details of the panellists, see http://www.meetup.com/London-Futurists/events/154873102/
http://www.youtube.com/watch?v=F3sB7Nk-_oI [with comments]
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Artificial intelligence: dream or nightmare? | Stefan Wess | TEDxZurich
Published on Nov 20, 2014 by TEDx Talks
This talk was given at a local TEDx event, produced independently of the TED Conferences. Artificial intelligence (AI) is a huge dream and vision for all mankind, and makes up a major part of most popular science fiction. John McCarthy coined the term in 1955 as "the science and engineering of making intelligent machines". Today, many notable companies have their stakes set on this technology, making AI a part of our everyday lives, e.g. Speech Recognition, Machine learning, Recommendation Systems and Personal Assistants. The ongoing global digital revolution, the unfailingly valid Moore’s Law, the Internet of Things and overall prevalent subject of Big Data, gives us the impression that creating “real” artificial intelligence is closer than ever before in history. AI has become “sexy” again. Besides large amounts of money flowing into the field of AI, numerous publications focus on the topic, AI shows up in our daily newsfeeds, and is already an integral part of most of our gadgets.
However, what would be the implications if a company could create “strong and real” AI? How would this influence our society and our jobs? Will it get smarter day by day? Would we be able to control a technical system of this nature?
Stefan Wess is a Researcher and Entrepreneur. He holds his PhD in Computer Science and is a highly recognized technology industry veteran with multinational front-line technology and scientific leadership experience. Stefan has written and published numerous books and articles on Artificial Intelligence. His professional career includes several Executive positions in international companies. As CEO of Empolis Information Management a Germany based IT company, he is still fascinated and excited how technology transforms our lives, the society and finally mankind.
http://www.youtube.com/watch?v=MaItaCQcYIE [with comments]
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The long-term future of AI (and what we can do about it): Daniel Dewey at TEDxVienna
Published on Dec 6, 2013 by TEDx Talks
Daniel Dewey is a research fellow in the Oxford Martin Programme on the Impacts of Future Technology at the Future of Humanity Institute, University of Oxford [ http://www.fhi.ox.ac.uk/ ]. His research includes paths and timelines to machine superintelligence, the possibility of intelligence explosion, and the strategic and technical challenges arising from these possibilities. Previously, Daniel worked as a software engineer at Google, did research at Intel Research Pittsburgh, and studied computer science and philosophy at Carnegie Mellon University. He is also a research associate at the Machine Intelligence Research Institute [ https://intelligence.org/ ].
http://www.tedxvienna.at/
http://www.facebook.com/tedxvienna
http://www.youtube.com/watch?v=CK5w3wh4G-M [with comments]
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Exponential Technology Literacy: Neil Jacobstein at TEDxSanMigueldeAllende
Published on Jan 7, 2013 by TEDx Talks
Niell Jacobstein of NASA's Singularity University [ http://singularityu.org/ ] describes how artificial intelligence will change the world.
Neil Jacobstein Co-chairs the Artificial Intelligence and Robotics Track at Singularity University on the NASA Research Park campus in Mountain View California. He served as President of Singularity University from October 2010-2011. His work there focuses on the technical, business, and ethical implications of exponential technologies. Neil became a Reuters Research Fellow in the Digital Vision Program at Stanford University in 2006. He has been a Distinguished Visiting Scholar in Stanford's Media X Program since 2007. He Chaired AAAI's 17th Innovative Applications of Artificial Intelligence Conference, and has served as a technical consultant on AI research and development projects for many industrial and government agencies. Jacobstein was CEO of Teknowledge Corporation, a pioneering AI company. He worked as a graduate research intern in Alan Kay's Learning Research Group at Xerox's Palo Alto Research Center (PARC), and in PARC's Software Concepts Group. Neil is a Crown Fellow at the Aspen Institute. Jacobstein is deeply interdisciplinary, and for 20 years has served as Chairman of the Institute for Molecular Manufacturing, a nanotechnology R&D organization that has advised the White House Science Office, Foresight, and the Academy of Sciences. Neil has performed in executive and technical advisory roles for industry, NGOs, and government.
http://www.youtube.com/watch?v=nUWosx9lJ4o [with comments]
--
TEDxGWU - Peter Bock - Emergence of Creativity in Artificial Intelligence
Uploaded on Nov 17, 2011 by TEDx Talks
Peter Bock discusses the evolution of Artificial Intelligence and states his intention of creating the world's first artificial being. He shows the capabilities of the current system, known as ALISA, in creating works of art.
Peter Bock is a Professor Emeritus of the Department of Computer Science at The George Washington University. During his 40-year career, Peter has focused on developing his biologically-inspired statistical learning theory, known as Collective Learning Systems (CLS), to provide essential knowledge for reverse engineering the brain and understanding cognition. He worked with NASA as part of the Apollo Program.
http://www.youtube.com/watch?v=CpNfy7AUPl4 [with comments]
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How AI is Changing the Way We View Intelligence, the World, and Ourselves: Sam Spaulding at TEDxYale
Published on Jun 2, 2013 by TEDx Talks
http://www.youtube.com/watch?v=qXtCApIxap8 [with comments]
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When creative machines overtake man: Jürgen Schmidhuber at TEDxLausanne
Published on Mar 10, 2012 by TEDx Talks
http://www.tedxlausanne.org - Machine intelligence is improving rapidly, to the point that the scientist of the future may not even be human! In fact, in more and more fields, learning machines are already outperforming humans.
Artificial intelligence expert Jürgen Schmidhuber isn't able to predict the future accurately, but he explains how machines are getting creative, why 40'000 years of Homo sapiens-dominated history are about to end soon, and how we can try to make the best of what lies ahead.
http://www.youtube.com/watch?v=KQ35zNlyG-o [with comments]
===
The Dominant Life Form in the Cosmos Is Probably Superintelligent Robots
December 19, 2014
http://motherboard.vice.com/read/the-dominant-life-form-in-the-cosmos-is-probably-superintelligent-robots [with comments]
===
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Greensburg, KS - 5/4/07
"Eternal vigilance is the price of Liberty."
from John Philpot Curran, Speech
upon the Right of Election, 1790
F6
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