robots & ai

Some, to example, there are again whose movements are automatic. Perceive. That is his appropriate sun.

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There’s growing privacy concern over flying robots, or “drones.” Organizations like the EFF and ACLU have been raising the alarm over increased government surveillance of US citizens. Legislators haven’t been quick to respond to concerns of government spying on citizens. But Texas legislators are apparently quite concerned that private citizens operating hobby drones might spot environmental violations by businesses.

{ Robots | Continue reading }

‘Between grief and nothing I will take grief.’ –Faulkner

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There are good reasons for any species to think darkly of its own extinction. […]

Simple, single-celled life appeared early in Earth’s history. A few hundred million whirls around the newborn Sun were all it took to cool our planet and give it oceans, liquid laboratories that run trillions of chemical experiments per second. Somewhere in those primordial seas, energy flashed through a chemical cocktail, transforming it into a replicator, a combination of molecules that could send versions of itself into the future.

For a long time, the descendants of that replicator stayed single-celled. They also stayed busy, preparing the planet for the emergence of land animals, by filling its atmosphere with breathable oxygen, and sheathing it in the ozone layer that protects us from ultraviolet light. Multicellular life didn’t begin to thrive until 600 million years ago, but thrive it did. In the space of two hundred million years, life leapt onto land, greened the continents, and lit the fuse on the Cambrian explosion, a spike in biological creativity that is without peer in the geological record. The Cambrian explosion spawned most of the broad categories of complex animal life. It formed phyla so quickly, in such tight strata of rock, that Charles Darwin worried its existence disproved the theory of natural selection.

No one is certain what caused the five mass extinctions that glare out at us from the rocky layers atop the Cambrian. But we do have an inkling about a few of them. The most recent was likely borne of a cosmic impact, a thudding arrival from space, whose aftermath rained exterminating fire on the dinosaurs. […]

Nuclear weapons were the first technology to threaten us with extinction, but they will not be the last, nor even the most dangerous. […] There are still tens of thousands of nukes, enough to incinerate all of Earth’s dense population centers, but not enough to target every human being. The only way nuclear war will wipe out humanity is by triggering nuclear winter, a crop-killing climate shift that occurs when smoldering cities send Sun-blocking soot into the stratosphere. But it’s not clear that nuke-levelled cities would burn long or strong enough to lift soot that high. […]

Humans have a long history of using biology’s deadlier innovations for ill ends; we have proved especially adept at the weaponisation of microbes. In antiquity, we sent plagues into cities by catapulting corpses over fortified walls. Now we have more cunning Trojan horses. We have even stashed smallpox in blankets, disguising disease as a gift of good will. Still, these are crude techniques, primitive attempts to loose lethal organisms on our fellow man. In 1993, the death cult that gassed Tokyo’s subways flew to the African rainforest in order to acquire the Ebola virus, a tool it hoped to use to usher in Armageddon. In the future, even small, unsophisticated groups will be able to enhance pathogens, or invent them wholesale. Even something like corporate sabotage, could generate catastrophes that unfold in unpredictable ways. Imagine an Australian logging company sending synthetic bacteria into Brazil’s forests to gain an edge in the global timber market. The bacteria might mutate into a dominant strain, a strain that could ruin Earth’s entire soil ecology in a single stroke, forcing 7 billion humans to the oceans for food. […]

The average human brain can juggle seven discrete chunks of information simultaneously; geniuses can sometimes manage nine. Either figure is extraordinary relative to the rest of the animal kingdom, but completely arbitrary as a hard cap on the complexity of thought. If we could sift through 90 concepts at once, or recall trillions of bits of data on command, we could access a whole new order of mental landscapes. It doesn’t look like the brain can be made to handle that kind of cognitive workload, but it might be able to build a machine that could. […]

To understand why an AI might be dangerous, you have to avoid anthropomorphising it. […] You can’t picture a super-smart version of yourself floating above the situation. Human cognition is only one species of intelligence, one with built-in impulses like empathy that colour the way we see the world, and limit what we are willing to do to accomplish our goals. But these biochemical impulses aren’t essential components of intelligence. They’re incidental software applications, installed by aeons of evolution and culture. Bostrom told me that it’s best to think of an AI as a primordial force of nature, like a star system or a hurricane — something strong, but indifferent. If its goal is to win at chess, an AI is going to model chess moves, make predictions about their success, and select its actions accordingly. It’s going to be ruthless in achieving its goal, but within a limited domain: the chessboard. But if your AI is choosing its actions in a larger domain, like the physical world, you need to be very specific about the goals you give it. […]

‘The really impressive stuff is hidden away inside AI journals,’ Dewey said. He told me about a team from the University of Alberta that recently trained an AI to play the 1980s video game Pac-Man. Only they didn’t let the AI see the familiar, overhead view of the game. Instead, they dropped it into a three-dimensional version, similar to a corn maze, where ghosts and pellets lurk behind every corner. They didn’t tell it the rules, either; they just threw it into the system and punished it when a ghost caught it. ‘Eventually the AI learned to play pretty well,’ Dewey said. ‘That would have been unheard of a few years ago, but we are getting to that point where we are finally starting to see little sparkles of generality.’

{ Ross Andersen/Aeon | Continue reading }

Blow me to Bermuda

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This research constitutes an initial investigation into key issues which arise in designing a flying humanoid robot (FHR), with a focus on human-robot interaction (HRI). The humanoid form offers an interface for natural communication; flight offers excellent mobility. Combining both will yield companion robots capable of approaching, accompanying, and communicating naturally with humans in difficult environments. Problematic is how such a robot should best fly around humans, and what effect a robot’s flight will have on a person in terms of non-verbal communicative cues. To answer these questions, we propose an extension to existing proxemics theory (“z-proxemics”) and predict how typical humanoid flight motions will be perceived (“z-kinesics”). Data obtained from participants watching animated sequences are analyzed to check our predictions. The paper also reports on the building of a flying humanoid robot, which we will use in interactions. […]

One possible design for a flying humanoid robot (FHR): “Angel”, a soft, safe companion robot intended for playful and affectionate interactions who a) approaches b) entertains, c) accompanies and guides, and d) serves humans.

{ IEEE | PDF }

‘I used to think I could change the world but now I think it changed me.’ –John Isaacs

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Memory is a strange thing. Just using the verb “smash” in a question about a car crash instead of “bump” or “hit” causes witnesses to remember higher speeds and more serious damage. Known as the misinformation effect, it is a serious problem for police trying to gather accurate accounts of a potential crime. There’s a way around it, however: get a robot to ask the questions. […]

Two groups - one with a human and one a robot interviewer - were asked identical questions that introduced false information about the crime, mentioning objects that were not in the scene, then asking about them later. When posed by humans, the questions caused the witnesses’ recall accuracy to drop by 40 per cent - compared with those that did not receive misinformation - as they remembered objects that were never there. But misinformation presented by the NAO robot didn’t have an effect.

{ NewScientist | Continue reading }

I’m sorry, I wasn’t listening

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Slowly, but surely, robots (and virtual ’bots that exist only as software) are taking over our jobs; according to one back-of-the-envelope projection, in ninety years “70 percent of today’s occupations will likewise be replaced by automation.” […]

If history repeats itself, robots will replace our current jobs, but, says Kelly, we’ll have new jobs, that we can scarcely imagine:

In the coming years robot-driven cars and trucks will become ubiquitous; this automation will spawn the new human occupation of trip optimizer, a person who tweaks the traffic system for optimal energy and time usage. Routine robosurgery will necessitate the new skills of keeping machines sterile. When automatic self-tracking of all your activities becomes the normal thing to do, a new breed of professional analysts will arise to help you make sense of the data.

Well, maybe. Or maybe the professional analysts will be robots (or least computer programs), and ditto for the trip optimizers and sterilizers.

{ The New Yorker | Continue reading }

Subjectivity after Wittgenstein: The Post-Cartesian Subject and the ‘Death of Man’

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Foxconn, the maker of Apple’s iPhone and iPad, plans to rely more on robots for manufacturing over the coming years, allowing the company to invest more in research and development and save on labor costs. […]

Local Chinese media reported that Foxconn CEO Terry Gou had said the company plans on deploying 1 million robots over the next three years to complete routine assembly tasks. Foxconn currently uses 10,000 robots. […]

The Taiwan-based company has more than 1 million employees, the majority of which are located at facilities in mainland China. Foxconn is one of the world’s largest producers of electronics. Aside from Apple, the company also manufactures products for companies like HP, Sony and Nintendo.

{ IT World | Continue reading }

Each one is sister to another and he binds them all with an outer ring and giveth speed to the feet of men

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The gap between professional race drivers and self-driven cars isn’t all that big, as a race at the Thunderhill Raceway in California proved yesterday. Although the human driver achieved victory against the self-driven Audi TTS in a head-to-head, he only managed to shave off a few seconds from the computer’s time.

{ Silicon Angle | Continue reading }

photo { Roger Minick }

‘We’re fucked.’ –Tim Geoghegan

{ Thanks Tim }

Try it with the glycerine

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Can you determine a person’s character in a single interaction? Can you judge whether someone you just met can be trusted when you have only a few minutes together? And if you can, how do you do it?

Using a robot named Nexi, psychology professor David DeSteno and collaborators […] have figured out the answer. […]

In the absence of reliable information about a person’s reputation, nonverbal cues can offer a look into a person’s likely actions. This concept has been known for years, but the cues that convey trustworthiness or untrustworthiness have remained a mystery. Collecting data from face-to-face conversations with research participants where money was on the line, DeSteno and his team realized that it’s not one single non-verbal movement or cue that determines a person’s trustworthiness, but rather sets of cues.

{ EurekAlert | Continue reading }

photo { Garry Winogrand }

‘Mistakes are the portals of discovery.’ –James Joyce

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Mr. Arnuk is a professional stockbroker. But suddenly, and improbably, he has emerged as a leading critic of the very market in which he works. He and his business partner, Joseph C. Saluzzi, have become the voice of those plucky souls who try to swim with Wall Street’s sharks without getting devoured. […]

These two men are taking on one of the most powerful forces in finance today: high-frequency trading. H.F.T., as it’s known, is the biggest thing to hit Wall Street in years. On any given day, this lightning-quick, computer-driven form of trading accounts for upward of half of all of the business transacted on the nation’s stock markets. […]

Proponents of high-frequency trading call them embittered relics — quixotic, old-school stockbrokers without the skills to compete in sophisticated, modern markets. And, in a sense, those critics are right: they are throwbacks. Both men say they wish Wall Street could go back to a calmer, simpler time, all the way back to, say, 2004. […]

The two want to require H.F.T. firms to honor the prices they offer for a stock for at least 50 milliseconds — less than a wink of an eye, but eons in high-frequency time. […]

Mr. Arnuk then eyed the stock’s price on dozens of other trading platforms — private ones most people can’t see. Known as the dark pools, they help hedge funds and other big-money players trade in relative secrecy.

Everywhere, different prices kept flickering on the screens. Computers at high-speed trading firms, Mr. Arnuk said, were issuing buy and sell orders and then canceling them almost as fast, testing the market. It can be hell on human brokers. On the tape, the stock’s price was unchanged, but beneath the tape, things were changing all the time. […]

On the afternoon of May 6, 2010, shortly before 3 o’clock, the stock market plummeted. In just 15 minutes, the Dow tumbled 600 points — bringing its loss for the day to nearly 1,000. Then, just as fast, and just as inexplicably, it sprang back nearly 600 points, like a bungee jumper.

It was one of the most harrowing moments in Wall Street history. And for many people outside financial circles, it was the first clue as to just how much new technology was changing the nation’s financial markets. The flash crash, a federal report later concluded, “portrayed a market so fragmented and fragile that a single large trade could send stocks into a sudden spiral.” It turned out that a big mutual fund firm had sold an unusually large number of futures contracts, setting off a feedback loop among computers at H.F.T. firms that sent the market into a free fall. […]

Since the 2010 flash crash, mini flash crashes have occurred with surprising regularity in a wide range of individual stocks. Last spring, a computer glitch scuttled the initial public offering of one of the nation’s largest electronic exchanges, BATS, and computer problems at the Nasdaq stock market dogged the I.P.O. of Facebook.

And last month, Knight Capital, a brokerage firm at the center of the nation’s stock market for almost a decade, nearly collapsed after it ran up more than $400 million of losses in minutes, because of errant technology.

{ NY Times | Continue reading }

A Hobson’s choice is a choice in which only one option is offered

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You walk into your shower and find a spider. You are not an arachnologist. You do, however, know that any one of the four following options is possible:

a. The spider is real and harmless.

b. The spider is real and venomous.

c. Your next-door neighbor, who dislikes your noisy dog, has turned her personal surveillance spider (purchased from “Drones ‘R Us” for $49.95) loose and is monitoring it on her iPhone from her seat at a sports bar downtown. The pictures of you, undressed, are now being relayed on several screens during the break of an NFL game, to the mirth of the entire neighborhood.

d. Your business competitor has sent his drone assassin spider, which he purchased from a bankrupt military contractor, to take you out. Upon spotting you with its sensors, and before you have any time to weigh your options, the spider shoots an infinitesimal needle into a vein in your left leg and takes a blood sample. As you beat a retreat out of the shower, your blood sample is being run on your competitor’s smartphone for a DNA match. The match is made against a DNA sample of you that is already on file at EVER.com (Everything about Everybody), an international DNA database (with access available for $179.99). Once the match is confirmed (a matter of seconds), the assassin spider outruns you with incredible speed into your bedroom, pausing only long enough to dart another needle, this time containing a lethal dose of a synthetically produced, undetectable poison, into your bloodstream. Your assassin, who is on a summer vacation in Provence, then withdraws his spider under the crack of your bedroom door and out of the house and presses its self-destruct button. No trace of the spider or the poison it carried will ever be found by law enforcement authorities.

This is the future. According to some uncertain estimates, insect-sized drones will become operational by 2030.

{ Gabriella Blum/Hoover Institution/Stanford University | PDF }

photo { Alexander Hammid, Maya Deren, 1945 }

Who is Patricia? THIS IS PATRICIA.

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Previous research on gender effects in robots has largely ignored the role of facial cues. We fill this gap in the literature by experimentally investigating the effects of facial gender cues on stereotypical trait and application ascriptions to robots. As predicted, the short-haired male robot was perceived as more agentic than was the long-haired female robot, whereas the female robot was perceived as more communal than was the male counterpart. Analogously, stereotypically male tasks were perceived more suitable for the male robot, relative to the female robot, and vice versa.

{ Journal of Applied Social Psychology | via Mind Hacks }

photo { Barbara Crane }

With all my worldly goods I thee and thou. (She murmurs.) You did that. I hate you.

Nokia accuses Apple of bias after Siri no longer says that the Lumia 900 is the best smartphone ever

Until recently Siri had responded that the best smartphone was the newly-released Nokia Lumia 900, although this is no longer the case. […] If you now ask the question, Siri responds tongue-in-cheek “Wait… there are other phones?”

{ TechWeek | Continue reading }

OMG guys, UFO

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Robotics is a game-changer in national security. We now find military robots in just about every environment: land, sea, air, and even outer space. They have a full range of form-factors from tiny robots that look like insects to aerial drones with wingspans greater than a Boeing 737 airliner. Some are fixed onto battleships, while others patrol borders in Israel and South Korea; these have fully-auto modes and can make their own targeting and attack decisions. There’s interesting work going on now with micro robots, swarm robots, humanoids, chemical bots, and biological-machine integrations. As you’d expect, military robots have fierce names like: TALON SWORDS, Crusher, BEAR, Big Dog, Predator, Reaper, Harpy, Raven, Global Hawk, Vulture, Switchblade, and so on. But not all are weapons–for instance, BEAR is designed to retrieve wounded soldiers on an active battlefield.

{ The Atlantic | Continue reading }

One more sign of a growing ‘entourage’ culture, where behavior is influenced by like-minded cohorts rather than essential values

Everyone complains about his memory, and no one complains about his judgment

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It’s now been a couple of weeks since Siri debuted as part of Apple’s iPhone 4S. (…)

Siri is hard to copy. For anyone who doesn’t understand voice applications, it’s easy to think that Siri will be easy to copy. It won’t.  There are 2 parts to making a successful voice app: the voice rec technology which has improved a lot but is basically a commodity and the app itself, which is a combination of art and artificial intelligence.  It’s that 2nd part that’s so tough to replicate and that’s why Apple bought Siri last year.  It’s true Google has experience in the voice rec space and doing some simple voice apps but they do not have the personality and AI of Siri and that will be very difficult to copy — especially for a company that doesn’t sit at the intersection of the humanities and technology.

{ Forbes | Continue reading }

related { Apple gets Siri-ous about TV }

‘In three words, I can sum up everything I’ve learned about life: It goes on.’ –Robert Frost

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A fundamental difficulty in artificial intelligence is that nobody really knows what intelligence is, especially for systems with senses, environments, motivations and cognitive capacities which are very different to our own.

Although there is no strict consensus among experts over the definition of intelligence for humans, most definitions share many key features. In all cases, intelligence is a property of an entity, which we will call the agent, that interacts with an external problem or situation, which we will call the environment. An agent’s intelligence is typically related to its ability to succeed with respect to one or more objectives, which we will call the goal. The emphasis on learning, adaptation and flexibility common to many definitions implies that the environment is not fully known to the agent. Thus true intelligence requires the ability to deal with a wide range of possibilities, not just a few specific situations. Putting these things together gives us our informal definition: Intelligence measures an agent’s general ability to achieve goals in a wide range of environments. We are confident that this definition captures the essence of many common perspectives on intelligence. It also describes what we would like to achieve in machines: A very general capacity to adapt and perform well in a wide range of situations.

{ Shane Legg and Marcus Hutter | Continue reading | PDF }

Artificial general intelligence (AGI) refers to research aimed at tackling the full problem of artificial intelligence, that is, create truly intelligent agents. This sets it apart from most AI research which aims at solving relatively narrow domains, such as character recognition, motion planning, or increasing player satisfaction in games. But how do we know when an agent is truly intelligent? A common point of reference in the AGI community is Legg and Hutter’s formal definition of universal intelligence, which has the appeal of simplicity and generality but is unfortunately incomputable. (…)

Intelligence is one of those interesting concepts that everyone has an opinion about, but few people are able to give a definition for – and when they do, their definitions tend to disagree with each other. And curiously, the consensus opinions change over time: consider for example a number of indicators for human intelligence like arithmetic skills, memory capacity, chess playing, theorem proving – all of which were commonly employed in the past, but since machines now outperform humans on those tasks, they have fallen into disuse. We refer the interested reader to a comprehensive treatment of the subject matter in Legg (2008).

The current artificial intelligence literature features a panoply of benchmarks, many of which, unfortunately, are very narrow, applicable only on a small class of tasks. This is not to say that they cannot be useful for advancing the field, but in retrospect it often becomes clear how little an advance on a narrow task contributed to the general field. For example, researchers used to argue that serious progress on a game as complex as chess would necessarily generate many insights, and the techniques employed in the solution would be useful for real-world problems – well, no. (…)

Legg and Hutter propose their definition as a basis for any test of artificial general intelligence. Among the advantages they list are its wide range of applicability (from random to super-human), its objectivity, its universality, and the fact that it is formally defined.

Unfortunately however, it suffers from two major limitations: a) Incomputability: Universal intelligence is incomputable, because the Kolmogorov complexity is incomputable for any environment (due to the halting problem). b) Unlimited resources: The authors deliberately do not include any consideration of time or space resources in their definition. This means that two agents that act identically in theory will be assigned the exact same intelligence Υ, even if one of them requires infinitely more computational resources to choose its action (i.e. would never get to do any action in practice) than the other.

{ Tom Schaul, Julian Togelius, Jürgen Schmidhuber, Measuring Intelligence through Games, 2011 | Continue reading | PDF }

‘There is always a sheet of paper. There is always a pen. There is always a way out.’ –H. L. Mencken

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{ George Widener, for future robots, orientation map of events, for the year 4421| Elenore Weber of Ricco/Maresca Gallery in New York defined Widener, one of the most widely collected living outsider artists, as “a high-functioning savant” and a “lightning calculator.” His bio reads: “Like some people with aspergers, he is gifted in dates, numbers, and drawing. In his memory, he has several thousand historical dates, thousands of calendars, and more than a thousand census statistics.” | Salon }

I put a message in my music, hope it brightens your day

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Long before we communicated with language, we communicated with our bodies, especially our faces. Everyone knows we ‘talk’ with facial expressions, but do we ‘hear’ ourselves with them?

{ Thoughts on Thoughts | Continue reading }

The Turing test is a test of a machine’s ability to exhibit intelligent behavior. A human judge engages in a natural language conversation with one human and one machine, each emulating human responses. All participants are separated from one another. If the judge cannot reliably tell the machine from the human, the machine is said to have passed the test.

{ Wikipedia | Continue reading }

images { 1 | 2. Trisha Donnelly }

You need a fifth and 2 clips to try and check me, 12 in the afternoon we can start the clappin

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One group of Australian researchers have managed to teach robots to do something that, until now, was the reserve of humans and a few other animals: they’ve taught them how to invent and use spoken language. The robots, called LingoDroids, are introduced to each other. In order to share information, they need to communicate. Since they don’t share a common language, they do the next best thing: they make one up. The LingoDroids invent words to describe areas on their maps, speak the word aloud to the other robot, and then find a way to connect the word and the place, the same way a human would point to themselves and speak their name to someone who doesn’t speak their language.”

{ Slashdot | Continue reading }

artwork { Thomas Schütte, United Enemies, 1994-95 | fimo, fabric, wood glass and PVC }