Daily Archives: June 29, 2017

By reverse-engineering signals sent by the brain, researchers at Carnegie Mellon University have been working on an AI that can read complex thoughts simply by looking at brain scans. Using data collected from a functional magnetic resonance imaging (fMRI) machine, the CMU scientists feed that data into their machine learning algorithms, which then locate the building blocks that the brain uses to create complex thoughts.

Impressively, the study showed that the team were able to demonstrate where and how the brain was being triggered while processing 240 complex events, covering everything from individuals to places and even various physical actions or aspects of social interaction. It's by understanding these triggers that the algorithm can use the brain scans to predict what is being thought about at the time, connecting these thoughts into a coherent sentence.

Selecting 239 of these complex sentences and feeding the AI the corresponding brain scans, the algorithm managed to successfully predict the correct thoughts with an astounding 87 percent accuracy. It could also do the reverse, receiving a sentence and then outputting an accurate image of how it predicted that thought would be mapped inside a human brain.

The astonishing research shows just how far deep learning has come. If you weren't worried about the rise of super powered machines before, now that they can read minds, it's probably time to start preparing for the inevitable robot apocalypse.

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Scientists made an AI that can read minds - Engadget

Chinese activist Ai Weiwei is one of the world's most famous artists, known for sticking his finger in the eye of the Chinese government and symbols of state power.

One of Ai's latest American exhibits--which features the portraits nearly 200 activists, prisoners and free speech advocates--has just made its East Coast debut in Washington's Hirshhorn Museum.

This exhibit is Ai's second in Washington, but the first he will be able to attend. During his first debut there, the Chinese government kept him from leaving China, reports CBS News' Errol Barnett.

That experience drove him to create works celebrating other activists and to bring awareness to major human rights issues.

"This is first time I've seen my work here," Ai said.

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Ai Weiwei's provocative art has gotten him harassed by police, thrown in detention and driven out of China. But in order to be relevant, he says ...

Assembled by hand with thousands of plastic Lego bricks, 176 portraits cover 700 feet around the ring-shaped museum. Some names are familiar to Americans: from controversial whistleblowers like Edward Snowden and Chelsea Manning to civil rights giants like Nelson Mandela and Martin Luther King, Jr. Others are lesser known but include freedom fighters imprisoned for life. "I have so many friends who never get released," Ai said. On the day we met with Ai, longtime friend Liu Xiaobo was said to have been moved from prison and held on medical parole because of his deteriorating health.

Edward Snowden's portrait at Ai Weiwei's Hirshhorn Museum exhibit.

CBS News

"He believes China should become a democratic society. That's all he did," Ai said of his friend. In 2010 Liu and Ai were both stopped from traveling abroad after Liu became the first Chinese citizen awarded the Nobel Peace Prize, an honor he never received in person.

But Ai says the entire installation is a portrait of activism. "Those are real people, real story. It represents the most bright ideas fighting for freedom," Ai said of his work.

But the Lego-made face of one notable Chinese activist is missing - his own.

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The dissident artist is one of the foremost figures to emerge from China's contemporary art scene

A 2008 earthquake in China's Sichuan province killed at least 70,000 people, including more than 5,000 children. Enraged, Ai lead a "citizens" investigation, discovering low-quality building materials contributed to student deaths. He also gathered and published the names of all the youngest victims. Ai was beaten by police, resulting in a cerebral hemorrhage, which he also documented.

In 2011, authorities put a bag over Ai's head while he waited for a flight, detaining him for 81 days. Ai used that experience as inspiration for a music video and dioramas with guards watching his every move.

Asked whether he feels he's created change, Ai said, "It's very hard to measure. I would not say in the larger scale because I still think the structure is quite fragile."

Ai Weiwei's exhibit at the Hirshhorn Museum.

CBS News

He continued, "In the way they have to censor someone like me. They're never sure if they can be really winning if there's a freedom of speech." On Instagram, Ai documents just about everything he does and everyone he meets. He also posts images without clothes on. It too is a response to censorship. "My name cannot appear on Chinese social media," Ai said.

"Yeah, it's illegal words. Nobody can put my name on social media and sometimes even they see a photo of my backside, they can recognize, that's him. They will delete the whole article," Ai said.

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60 Minutes correspondent Holly Williams and producer Michael Gavshon talk about the provocative Chinese artist and the criticism of his work

Speaking just a few miles from the White House, Ai told Barnett he's delighted by the social media habits of its powerful resident. "I was amazed or charmed to see a president wake up at midnight and tweets. Normally we think a president holds all the secrets will never tell you what he thinks about," Ai said. "It can be controversy or can be unpredictable."

Ai finds it to be authentic.

"When he touches that sending key, he believes it's a good idea to share it," he said.

Ai left China in 2015, four years after the Chinese government confiscated his passport, preventing him from leaving the country.

After Ai was detained he still had to wait four years for the Chinese government to return his passport.

He now has a studio in Berlin and travels the world with his young son, who was part of his inspiration to use a children's toy as part of his work.

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Chinese artist and activist Ai Weiwei's new exhibit puts a spotlight on free speech advocates - CBS News

Instagram is introducing an enhanced comment filter today meant to wipe out nasty remarks using AI. The app first began offering a comment filter last September, but it was a very simple approach: Instagram would only remove comments that contained words and phrases it had specifically identified as offensive. (Users could also add their own custom banned phrases.)

Now, the system is getting a lot smarter. It uses machine learning to identify comments that seem offensive, giving the system some ability to take into account the replys context, potentially catching more bad comments and cutting down on false positives at the same time. Wired has a big story on how the system was made, and it mentions that when a comment gets flagged, itll be blocked for everyone except the person who wrote it, so they wont know their remark didnt get through.

An AI spam filter has secretly been in place since October

One other notable change here: Instagram is turning the offensive comment filter on by default, whereas the earlier filter had to be enabled. Youll still be given the option to turn it off from inside the apps settings, and Instagram still includes the ability to block custom words and phrases.

The filter only works in English at launch, but Instagram says its working to expand it to other languages over time.

Instagram is also announcing an AI spam-filtering system today, too. The spam filter has secretly been in place since last October, but its only being revealed today. Given that no one has noticed it in the past nine months, the filter probably isnt blocking too many comments that it shouldnt. That filter is active in nine languages, including English. (As a side note: Instagram really needs a better system for blocking spam accounts, as well. I set my profile to private recently in order to cut down on spam followers, but now Im just getting follow requests from spam accounts instead.)

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Instagram now uses AI to block offensive comments - The Verge

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Meet Penny, an AI That Predicts a Neighborhood's Wealth From ... - WIRED

Imagine you're stuck in a hospital bed after having surgery. You can't even close the window blinds without a nurse's help. And you can forget about requesting a blanket to take off the chill or getting details on visiting hours when everyone's busy handling more-pressing matters.

You feel powerless.

But what if you got what you needed just by saying it? You could instantly open the blinds, find out more about your doctor's expertise or turn up the room temperature. Sounds great, right? All you'd need is one of today's digital voice assistants that constantly listen for a request, send your query to the internet and either answer your question or complete a task.

Unfortunately, you can't do that right now with the current crop of smart assistants like Apple's Siri, Amazon's Alexa and Google's Assistant because they can't satisfy hospitals' privacy and security requirements. Yet according to Bret Greenstein, vice president of IBM's Watson Internet of Things platform, some medical staff can spend nearly 10 percent of their time with patients answering questions about lunch, physician credentials and visiting hours. If a smart speaker can answer those questions, doctors and nurses could spend more time on patient care.

Harman's JBL clock radio packs smarts from IBM's AI technology to help patients get information and control their hospital room's lighting and temperature.

It's why Thomas Jefferson University Hospitals in Philadelphia decided to work with audio giant Harman and IBM's Watson artificial intelligence technology. Together, they developed smart speakers that will respond to about a dozen commands. When a patient says "Watson," the speakers can, for instance, play calming sounds and adjust the room's lighting, thermostat and blinds.

"This is a way for patients to get some simple comfort measures addressed just by speaking," says Dr. Andrew Miller, associate chief medical officer at the Philadelphia hospital group. "How great is that?"

For the hospital, it's just the beginning.

Like Amazon's popular Echo speaker, Harman's JBL clock radio packs smarts that respond to command words it hears spoken.

Jefferson Hospital experimented with Amazon's popular Echo speaker, but found the hospital couldn't simultaneously control multiple speakers from one management system. What's more, the Echo couldn't access the hospital's secure Wi-Fi network, and it didn't have the right "skills," or capabilities, for a medical environment.

Dr. Andrew Miller

"It would have done simple things people are used to doing in the home, but not the things we wanted to do," says Neil Gomes, the hospital's chief digital officer.

So late last year, Jefferson Hospital started testing five prototype speakers that Harman made using the external casing of a regular JBL cylindrical speaker and components specially designed for artificial intelligence.

The initial trial tested two models. One required patients to press a button to wake up the device, getting around privacy concerns of an ever-listening microphone. The other woke when someone said "Watson," the name of IBM's AI technology that won the $1 million first-place prize on "Jeopardy" in 2011.

"The button gives a sense of privacy, but it proved to be very frustrating to users because they had to keep pushing it," says Greenstein.

Harman's JBL smart speakers have gone through a range of shapes and sizes.

The newest speakers, now built into Harman's round JBL clock radios, rely solely on voice commands. The hospital is testing about 40 of the new speakers, with IBM and Harman tweaking the smarts as they go. The speakers also tie into the hospital's automated facilities management system, which lets administrators control things like heating, air conditioning and lighting online. That's a convenience for everyone.

"When my father-in-law was in the hospital, we had to talk to the nurse about adjusting the thermostat," says Kevin Hague, vice president of technology strategy at Harman. "It was absurd that we had to have an RN come in and figure out on the computer how to adjust the temperature."

As of this writing, the hospital hadn't decided if it would stick with "Watson" or go with some other wake-up word, like "Jefferson."

It's fair to say we'd rather voice assistants do our bidding in a hotel room instead of in a hospital.

Some hotels are exploring that option and finding that off-the-shelf digital assistants work just fine.

Marriott, for instance, has been testing Apple's Siri and Amazon's Alexa at an Aloft Hotel in Boston. The hotel installed iPad tablets and Echo speakers in 10 rooms, letting guests speak commands to control the TV and adjust the lighting. That sounds awfully tempting considering how tough it can be sometimes to figure out which switch does what.

See more from CNET Magazine.

"The room would become an extension to your personal tech," says Toni Stoeckl, Marriott global brand leader and vice president. "I don't think we're there quite yet."

In the meantime, Jefferson Hospital, Harman and IBM are working on ways to teach their smart speaker to branch out beyond simple tasks. The possibilities are intriguing. Maybe Watson could follow you home to make sure you're taking your medication correctly. Or it could prompt you to take a walk so you could heal faster, easily change pharmacies or arrange follow-up appointments.

Right now, the speakers don't need regulatory approval, although that could change if they provide information about your diagnosis or explain your medications.

No matter how the hospital ends up using them, one thing is certain. It sucks being in a hospital. Having a little control over your environment could make it suck a little less.

This story appears in the summer 2017 edition of CNET Magazine. Click here formore magazine stories.

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AI enters the hospital room - CNET

Inspirational posters have their place. But if you're not the kind of person to take workplace spark from a beautiful photograph of a random person canoeing at twilight or an eagle soaring, you might want to turn the poster-making over to an artificial intelligence.

An AI dubbed InspiroBot, brought to our attention by IFL Science, puts together some of the most bizarre (and thus delightful) inspirational posters around.

This one's probably not a good idea for either a stranger or a friend.

The dog's cute, but this isn't great advice either.

Hard to argue with this one, which is kinda Yoda-esque.

Hey! Who you callin' "desperate"?

This bot obviously doesn't know many LARPers, or hang around at Renaissance Faires.

The bot's posters fall in between Commander Data trying to offer advice and a mistranslated book of quaint sayings. And they're mostly fun. Except sometimes, when the AI gets really dark and it's time to leave the site entirely and Google kittens fighting themselves in the mirror.

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This is why AI shouldn't design inspirational posters - CNET - CNET

JUNE 29, 2017

CHESS IS THE GAME not just of kings but of geniuses. For hundreds of years, it has served as standard and symbol for the pinnacles of human intelligence. Staring at the pieces, lost to the world, the chess master seems a figure of pure thought: brain without body. Its hardly a surprise, then, that when computer scientists began to contemplate the creation of an artificial intelligence in the middle years of the last century, they adopted the chessboard as their proving ground. To build a machine able to beat a skilled human player would be to fabricate a mind. It was a compelling theory, and to this day it shapes public perceptions of artificial intelligence. But, as the former world chess champion Garry Kasparov argues in his illuminating new memoir Deep Thinking, the theory was flawed from the start. It reflected a series of misperceptions about chess, about computers, and about the mind.

At the dawn of the computer age, in 1950, the influential Bell Labs engineer Claude Shannon published a paper in Philosophical Magazine called Programming a Computer for Playing Chess. The creation of a tolerably good computerized chess player, he argued, was not only possible but would also have metaphysical consequences. It would force the human race either to admit the possibility of a mechanized thinking or to further restrict [its] concept of thinking. He went on to offer an insight that would prove essential both to the development of chess software and to the pursuit of artificial intelligence in general. A chess program, he wrote, would need to incorporate a search function able to identify possible moves and rank them according to how they influenced the course of the game. He laid out two very different approaches to programming the function. Type A would rely on brute force, calculating the relative value of all possible moves as far ahead in the game as the speed of the computer allowed. Type B would use intelligence rather than raw power, imbuing the computer with an understanding of the game that would allow it to focus on a small number of attractive moves while ignoring the rest. In essence, a Type B computer would demonstrate the intuition of an experienced human player.

When Shannon wrote his paper, he and everyone else assumed that the Type A method was a dead end. It seemed obvious that, under the time restrictions of a competitive chess game, a computer would never be fast enough to extend its analysis more than a few turns ahead. As Kasparov points out, there are over 300 billion possible ways to play just the first four moves in a game of chess, and even if 95 percent of these variations are terrible, a Type A program would still have to check them all. In 1950, and for many years afterward, no one could imagine a computer able to execute a successful brute-force strategy against a good player. Unfortunately, Shannon concluded, a machine operating according to the Type A strategy would be both slow and a weak player.

Type B, the intelligence strategy, seemed far more feasible, not least because it fit the scientific zeitgeist. Fascination with digital computers intensified during the 1950s, and the so-called thinking machines began to influence theories about the human mind. Many scientists and philosophers came to assume that the brain must work something like a digital computer, using its billions of networked neurons to calculate thoughts and perceptions. Through a curious kind of circular logic, this analogy in turn guided the early pursuit of artificial intelligence: if you could figure out the codes that the brain uses in carrying out cognitive tasks, youd be able to program similar codes into a computer. Not only would the machine play chess like a master, but it would also be able to do pretty much anything else that a human brain can do. In a 1958 paper, the prominent AI researchers Herbert Simon and Allen Newell declared that computers are machines that think and, in the near future, the range of problems they can handle will be coextensive with the range to which the human mind has been applied. With the right programming, a computer would turn sapient.

It took only a few decades after Shannon wrote his paper for engineers to build a computer that could play chess brilliantly. Its most famous victim: Garry Kasparov.

One of the greatest and most intimidating players in the history of the game, Kasparov was defeated in a six-game bout by the IBM supercomputer Deep Blue in 1997. Even though it was the first time a machine had beaten a world champion in a formal match, to computer scientists and chess masters alike the outcome wasnt much of a surprise. Chess-playing computers had been making strong and steady gains for years, advancing inexorably up the ranks of the best human players. Kasparov just happened to be in the right place at the wrong time.

But the story of the computers victory comes with a twist. Shannon and his contemporaries, it turns out, had been wrong. It was the Type B approach the intelligence strategy that ended up being the dead end. Despite their early optimism, AI researchers utterly failed in getting computers to think as people do. Deep Blue beat Kasparov not by matching his insight and intuition but by overwhelming him with blind calculation. Thanks to years of exponential gains in processing speed, combined with steady improvements in the efficiency of search algorithms, the computer was able to comb through enough possible moves in a short enough time to outduel the champion. Brute force triumphed. It turned out that making a great chess-playing computer was not the same as making a thinking machine on par with the human mind, Kasparov reflects. Deep Blue was intelligent the way your programmable alarm clock is intelligent.

The history of computer chess is the history of artificial intelligence. After their disappointments in trying to reverse-engineer the brain, computer scientists narrowed their sights. Abandoning their pursuit of human-like intelligence, they began to concentrate on accomplishing sophisticated, but limited, analytical tasks by capitalizing on the inhuman speed of the modern computers calculations. This less ambitious but more pragmatic approach has paid off in areas ranging from medical diagnosis to self-driving cars. Computers are replicating the results of human thought without replicating thought itself. If in the 1950s and 1960s the emphasis in the phrase artificial intelligence fell heavily on the word intelligence, today it falls with even greater weight on the word artificial.

Particularly fruitful has been the deployment of search algorithms similar to those that powered Deep Blue. If a machine can search billions of options in a matter of milliseconds, ranking each according to how well it fulfills some specified goal, then it can outperform experts in a lot of problem-solving tasks without having to match their experience or insight. More recently, AI programmers have added another brute-force technique to their repertoire: machine learning. In simple terms, machine learning is a statistical method for discovering correlations in past events that can then be used to make predictions about future events. Rather than giving a computer a set of instructions to follow, a programmer feeds the computer many examples of a phenomenon and from those examples the machine deciphers relationships among variables. Whereas most software programs apply rules to data, machine-learning algorithms do the reverse: they distill rules from data, and then apply those rules to make judgments about new situations.

In modern translation software, for example, a computer scans many millions of translated texts to learn associations between phrases in different languages. Using these correspondences, it can then piece together translations of new strings of text. The computer doesnt require any understanding of grammar or meaning; it just regurgitates words in whatever combination it calculates has the highest odds of being accurate. The result lacks the style and nuance of a skilled translators work but has considerable utility nonetheless. Although machine-learning algorithms have been around a long time, they require a vast number of examples to work reliably, which only became possible with the explosion of online data. Kasparov quotes an engineer from Googles popular translation program: When you go from 10,000 training examples to 10 billion training examples, it all starts to work. Data trumps everything.

The pragmatic turn in AI research is producing many such breakthroughs, but this shift also highlights the limitations of artificial intelligence. Through brute-force data processing, computers can churn out answers to well-defined questions and forecast how complex events may play out, but they lack the understanding, imagination, and common sense to do what human minds do naturally: turn information into knowledge, think conceptually and metaphorically, and negotiate the worlds flux and uncertainty without a script. Machines remain machines.

That fact hasnt blunted the publics enthusiasm for AI fantasies. Along with TV shows and movies featuring scheming computers and bloody-minded robots, weve seen a slew of earnest nonfiction books with titles like Superintelligence, Smarter Than Us, and Our Final Invention, all suggesting that machines will soon be brainier than we are. The predictions echo those made in the 1950s and 1960s, and, as before, theyre founded on speculation, not fact. Despite monumental advances in hardware and software, computers give no sign of being any nearer to self-awareness, volition, or emotion. Their strength what Kasparov describes as an amnesiacs objectivity is also their weakness.

In addition to questioning the common wisdom about artificial intelligence, Kasparov challenges our preconceptions about chess. The game, particularly when played at its highest levels, is far more than a cerebral exercise in logic and calculation, and the expert player is anything but a stereotypical egghead. The connection between chess skill and the kind of intelligence measured by IQ scores, Kasparov observes, is weak at best. There is no more truth to the thought that all chess players are geniuses than in saying that all geniuses play chess, he writes. [O]ne of the things that makes chess so interesting is that its still unclear exactly what separates good chess players from great ones.

Chess is a grueling sport. It demands stamina, resilience, and an aptitude for psychological warfare. It also requires acute sensory perception. Move generation seems to involve more visuospatial brain activity than the sort of calculation that goes into solving math problems, writes Kasparov, referring to recent neurological experiments. To the chess master, the boards 64 squares definenot just an abstract geometry but an actual terrain. Like figures on a landscape, the pieces form patterns that the master, drawing on years of experience, reads intuitively, often at a glance. Methodical analysis is important, too, but it is carried out as part of a multifaceted and still mysterious thought process involving the body and its senses as well as the brains neurons and synapses.

The contingency of human intelligence, the way it shifts with health, mood, and circumstance, is at the center of Kasparovs account of his historic duel with Deep Blue. Having beaten the machine in a celebrated match a year earlier, the champion enters the 1997 competition confident that he will again come out the victor. His confidence swells when he wins the first game decisively. But in the fateful second game, Deep Blue makes a series of strong moves, putting Kasparov on the defensive. Rattled, he makes a calamitous mental error. He resigns the game in frustration after the computer launches an aggressive and seemingly lethalattack on his queen. Only later does he realize that his position had not been hopeless; he could have forced the machine into a draw. The loss leaves Kasparov confused and in agony, unable to regain his emotional bearings. Though the next three games end in draws, Deep Blue crushes him in the sixth and final game to win the match.

One of Kasparovs strengths as a champion had always been his ability to read the minds of his adversaries and hence anticipate their strategies. But with Deep Blue, there was no mind to read. The machines lack of personality, its implacable blankness, turned out to be one of its greatest advantages. It disoriented Kasparov, breeding doubts in his mind and eating away at his self-confidence. I didnt know my opponent at all, he recalls. This intense confusion left my mind to wander to darker places. The irony is that the machines victory was as much a matter of psychology as of skill.[1]

If Kasparov hadnt become flustered, he might have won the 1997 match. But that would have just postponed the inevitable. By the turn of the century, the era of computer dominance in chess was well established. Today, not even the grandest of grandmasters would bother challenging a computer to a match. They know they wouldnt stand a chance.

But if computers have become unbeatable at the board, they remain incapable of exhibiting what Kasparov calls the ineffable nature of human chess. To Kasparov, this is cause for optimism about the future of humanity. Unlike the eight-by-eight chessboard, the world is an unbounded place, and making sense of it will always require more than mathematical or statistical calculations. The inherent rigidity of computer intelligence leavesplenty of room for humans to exercise their flexible and intuitive intelligence. If we remain vigilant in turning the power of our computers to our own purposes, concludes Kasparov, our machines will not replace us but instead propel us to ever-greater achievements.

One hopes hes right. Still, as computers become more powerful and more adept at fulfilling our needs, there is a danger. The benefits of computer processing are easy to measure in speed, in output, in dollars while the benefits of human thought are often impossible to express in hard numbers. Given contemporary societys worship of the measurable and suspicion of the ineffable, our own intelligence would seem to be at a disadvantage as we rush to computerize more and more aspects of our jobs and lives. The question isnt whether the subtleties of human thought will continue to lie beyond the reach of computers. They almost certainly will. The question is whether well continue to appreciate the value of those subtleties as we become more dependent on the mindless but brutally efficient calculations of our machines. In the face of the implacable, the contingent can seem inferior, its strengths appearing as weaknesses.

Near the end of his book, Kasparov notes, with some regret, that humans today are starting to play chess more like computers. Once again, the ancient game may be offering us an omen.

Nicholas Carr is the author of several books about computers and culture, including The Shallows, The Glass Cage, and, most recently, Utopia Is Creepy.

[1] A bit of all-too-human deviousness was also involved in Deep Blues win. IBMs coders, it was later revealed, programmed the computer to display erratic behavior delaying certain moves, for instance, and rushing others in an attempt to unsettle Kasparov. Computers may be innocents, but that doesnt mean their programmers are.

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A Brutal Intelligence: AI, Chess, and the Human Mind - lareviewofbooks