From the NYT: In a Wired South Korea, Robots Will Feel Right at Home South Korea, the world’s most wired country, is rushing to turn what sounds like science fiction into everyday life. The government, which succeeded in getting broadband Internet into 72 percent of all households in the last half decade, has marshaled an army of scientists and business leaders to make robots full members of society. … If all goes according to plan, robots will be in every South Korean household between 2015 and 2020. That is the prediction, at least, of the Ministry of Information and Communication, which has grouped more than 30 companies, as well as 1,000 scientists from universities and research institutes, under its wing. Some want to move even faster. “My personal goal is to put a robot in every home by 2010,” said Oh Sang Rok, manager of the ministry’s intelligent service robot project. SK is desparate to move past the cloning hoax from a few months back; nothing like a little shame to get people motivated. Hopefully the next few years will let us confront our shame instead of hiding it behind self-righteous arrogance, because its really holding us back. South Koreans use futuristic technologies that are years away in the United States; companies like Microsoft and Motorola test products here before introducing them in the United States. Since January, Koreans have been able to watch television broadcasts on cellphones, free, thanks to government-subsidized technology. In April, South Korea will introduce the first nationwide superfast wireless Internet service, called WiBro, eventually making it possible for Koreans to remain online on the go — at 10 megabits per second, faster than most conventional broadband connections. South Korea, perhaps more than any other country, is transforming itself through technology. About 17 million of the […]

[Commentary on this post.] Ok, so no one seems to like the videos. But I think that’s rather uncritical. Lets look at this more carefully. The first important thing to notice is that it is the robot making this art. It is making aesthetic choices about the material and integrating those choices in novel ways to createthe final product. Its decisions are its– no one determines which decisions it will make, and its even incorrect to say this is a decision procedure: neural nets are trained, in this case on impressionists paintings, but no one has any priviledged access to the internal structure on the net, except the robot itself. The robot is in this special position because it can use the network. We don’t know the internal structure, but that doesn’t mean we are entirely blind to its evaluative criteria. In particular, we know the input/output dimensions, and what features or properties those dimensions code for. We can call this the machine’s understanding of the art work. Notice that what it understands about the images is radically unlike our own understanding. It doesn’t see cars or roads or traffic, like we do. It sees colors at places. It sees composition. I’m inclined to say that we can’t really evaluate the art here, because we lack the machine’s understanding of its film. I’m not claiming that we need to know the artist’s intentions and understanding in order to evaluate a piece of art, but just that what the machine sees is so radically different from what we see, that our gut reactions to the work doesn’t say much about its merit. Its important, then, to describe the machine’s relation to the art as a kind of understanding. Notice that this is different from attributing mental states to the neural net. […]

Cloaca This exhibition of Wim Delvoye’s large-scale installation Cloaca represents the first-ever solo presentation by a U.S. museum of the acclaimed young Belgian artist’s work. Built from chemical beakers, electric pumps, and plastic tubing arrayed on a series of seven stainless steel tables, Cloaca is the result of a three-year collaboration between the artist and scientists at the University of Antwerp, whose shared mission was to duplicate the functions of the human digestive system as closely as possible. Cloaca is fed twice a day from a large funnel reached by climbing a stepladder. At the work’s inauguration, Delvoye himself ascended the ladder carrying a tray laden with a tasty and substantial Belgian meal of mushroom soup, filet of fish, and a rich pudding, which he dropped in the funnel a dollop at a time. The food is chewed by a garbage disposal device before traveling on a 27-hour-long digestive trajectory, through six glass vats connected by tubes and pipes, pumps and various electronic components that are Cloaca‘s stomach, pancreas, and small and large intestines. The “digesting” food is constantly kept at a precise 37.2 degrees centigrade and each of Cloaca‘s “organs” is full of computer-monitored enzymes, bacteria, acids and bases such as pepsin, pancreatin, and hydrochloric acid. The product finally goes through a separator and the remaining solids are extruded onto a conveyer belt. Oh shit.

A filmmaking robot This robot makes short films based on its visual experience. Its eyes travel about the city on buses while the body sits in a gallery. The eyes collect snippets of video, and transmit them to the body when their buses come within range of a Cafenet wireless internet node. The robot body splits the video into individual frames and analyses each one, obtaining twenty numbers reflecting the arrangement of colour, shape and detail within the frame. These numbers are treated as coordinates in a twenty dimensional space, in which distance is somewhat related to visual difference. For twelve hours a day the robot traces a zigzagging path through this space. This path passes through a series of images, which become a video sequence. Visitors to the gallery can see this video, called variously the robot’s “dream” or “stream of consciousness”. At the end of the day the robot looks over its days work and joins the best parts together as a finished film. The robot uses neural networks and heuristic rules to choose waypoints for its daily dream, but the finished film is mainly selected for the smoothness of its movement through the space. The robot will remember everything it sees until it has five million images in its mind, after which it will replace its least favourite images with new ones. In addition to getting images from the eyes, the robot creates false memories by combining and manipulating well-liked and overused images. These notes are incomplete. You can see samples of his work on the page. It also gives a rundown if its aesthetic training, which gives some clue as to how it is making judgments. The most meaningful part of these pieces is definitely the credits: “By a Filmaking Robot”. The choice of the indefinite […]

Looking at a Boing Boing post from last week that features a bunch of kids in robot costumes, it occured to me that we have no word for robots in early stages of development, because there isn’t any use for such a word, at least right now. Then it occured to me that there is probably work I should be doing.

So I’ve got a this webhost with tons of space and lots of bandwidth, why not use it? I just found a pretty snazzy song that you should download. Post in the comments to tell me your download speeds. All files are mp3s. Prokofiev: Sonata No. 7 in B flat major Performed by Maurizio Pollini 1. Allegro inquieto – Andantino    [7:32] (8.63 megs) 2. Adante caloroso                 [6:12] (7.10 megs) 3. Precipitato                     [3:17] (3.88 megs) The 3rd movement is some hot shit. Also, for those not hacking around my webspace, all the pictures I post can be found here, and all the files I keep on site can be found here.

Uh huh. With the help of German microchip company Infineon, NACHIP placed 16,384 transistors and hundreds of capacitors on a chip just 1mm squared in size. The group had to find appropriate materials and refine the topology of the chip to make the connection with neurons possible. Biologically NACHIP uses special proteins found in the brain to essentially glue the neurons to the chip. These proteins act as more than a simple adhesive, however. “They also provided the link between ionic channels of the neurons and semiconductor material in a way that neural electrical signals could be passed to the silicon chip,” says Vassanelli. Once there, that signal can be recorded using the chip’s transistors. What’s more, the neurons can also be stimulated through the capacitors. This is what enables the two-way communications.|link| One more pic because neurons look awesome.

its cold outside there’s no kind of atmosphere I’m all alone, more or less let me fly far away from here fun fun fun in the sun sun sun I want to lie shipwrecked and comatose drinking fresh mango juice goldfish shoals nibbling at my toes fun fun fun in the sun sun sun

because boy do I need it. From The Economist: Computing the future This week, a group of computer scientists claimed that developments in their subject will trigger a scientific revolution of similar proportions in the next 15 years… They have concluded, in a report called “Towards 2020 Science”, that computing no longer merely helps scientists with their work. Instead, its concepts, tools and theorems have become integrated into the fabric of science itself. Indeed, computer science produces “an orderly, formal framework and exploratory apparatus for other sciences,” according to George Djorgovski, an astrophysicist at the California Institute of Technology. There is no doubt that computing has become increasingly important to science over the years. The volume of data produced doubles every year, according to Alexander Szalay, another astrophysicist, who works at Johns Hopkins University in Baltimore. Particle-physics experiments are particularly notorious in this respect. The next big physics experiment will be the Large Hadron Collider currently being built at CERN, a particle-physics laboratory in Geneva. It is expected to produce 800m collisions a second when it starts operations next year. This will result in a data flow of 1 gigabyte per second, enough to fill a DVD every five seconds. All this information must be transmitted from CERN to laboratories around the world for analysis. The computer science being put in place to deal with this and similar phenomena forms the technological aspect of the predicted scientific revolution. Such solutions, however, are merely an extension of the existing paradigm of collecting and ordering data by whatever technological means are available, but leaving the value-added stuff of interpretation to the human brain. What really interested Dr Emmott’s team was whether computers could participate meaningfully in this process, too. That truly would be a paradigm shift in scientific method. Dont I know […]

The robot developed here is named RI-MAN. RI-MAN exhibits the skill and ability to realize human care and welfare tasks. RI-MAN will become an invaluable partner robot. |link| See RI-MAN in action. (.mpg)

Burge’s paper focuses on the four color theorem as the standard case of so-called ‘computer proof‘. There is a more recent case, with an even cooler name: the Sphere Packing Conjecture: Following the approach suggested by Fejes Tóth, Thomas Hales, then at the University of Michigan, determined that the maximum density of all arrangements could be found by minimising a function with 150 variables. In 1992, assisted by his graduate student Samuel Ferguson, he embarked on a research programme to systematically apply linear programming methods to find a lower bound on the value of this function for each one of a set of over 5,000 different configurations of spheres. If a lower bound could be found for every one of these configurations that was greater than the value for the cubic close packing arrangement, then the Kepler conjecture would be proved. To find lower bounds for all cases involved solving around 100,000 linear programming problems. When presenting the progress of his project in 1996, Hales said that the end was in sight, but it might take “a year or two” to complete. In August 1998 Hales announced that the proof was complete. At that stage it consisted of 250 pages of notes and 3 gigabytes of computer programs, data and results. Despite the unusual nature of the proof, the editors of the Annals of Mathematics agreed to publish it, provided it was accepted by a panel of twelve referees. In 2003, after four years of work, the head of the referee’s panel Gábor Fejes Tóth (son of László Fejes Tóth) reported that the panel were “99% certain” of the correctness of the proof, but they could not certify the correctness of all of the computer calculations. In February 2003 Hales published a 100-page paper (PDF) describing the non-computer part of […]

The number of teenagers using the internet grew 24% in the past four years and 87% of those between the ages of 12 and 17 are online. … Email is losing its privileged place among many teens as they say they prefer instant messaging (IM) and text messaging on cell phones as ways to connect with their friends. Email is increasingly seen as a tool for communicating with adults such as teachers, institutions like schools, and as a way to convey lengthy and detailed information to large groups. Meanwhile, IM is used for everyday conversations with multiple friends that range from casual to more serious and private exchanges. At the same time, the landline phone still continues to be the most dominant communications medium in teens’ everyday lives, even as 45% of all American teens own a cell phone. Young people also approach online content from a unique perspective; this is a generation for which the ability to customize and participate in the content they find online has become a normalized practice. In all, 57% of online teens are “Media Makers” and engage in at least one content creating activity: 19% keep a blog, 22% create or work on a personal webpage, 32% create or work on webpages for others, 33% share personal artwork, media or content online, and 19% remix content they find online.|link|