Lots of news today as we empty the editor's inbox. An MIT Technology Review article argues their are fatal flaws in Ray Kurzweil's new AI project for Google. If you read Bruce Sterling's piece in the answers to the annual Edge question, he did a little debunking of "the singularity". George Dvorsky begs to differ with Sterling, offering a collection of responses from those who are still faithful believers in the nerd rapture. And speaking of Edge, they posted a fascinating article and video detailing what philosopher Daniel Dennett has been up to lately, including why he thinks the vision of the brain as a computer is still correct, but he wants to correct a mistake he made in the past regarding the approach to homuncular functionalism. Also on the subject of human brains, remember the old science fiction novels that imagined a future with sleep learning machines? Researchers have finally discovered why our past attempts at sleep learning failed and have built a sleep learning machine that actually works, using a process called cued memory reactivation, paper is paywalled but there's an NSF summary of the research with a demonstration video. Unless you're short on sleep, you probably remember our recent story on the new release of ROS. Our friends over at NooTriX have released a ready-to-use virtual machine version of ROS Groovy Galapagos - an Open Virtualization Format .ova file that will run under VmWare, Parallels, and other VMs that support the standard format. Finally, The Swirling Brain pointed out an interesting CNN story on a humanoid robot design that can be built using parts made on a 3D printer. Unfortunately the design is not actually open source as the article suggests (the non-commercial-use license doesn't meet the guidelines of either the Open Source Hardware Association or the Free hardware definition) but it is a cool idea and hopefully will inspire similar designs under an open/free hardware license eventually. Know any other robot news, gossip, or amazing facts we should report? Send 'em our way please. Don't forget to follow us on twitter and Facebook. And now you can add us to your Google+ circles too.

According to a Cornell news release, Cornell University’s College of Veterinary Medicine is working on an advanced robot dog, code-named Butch, that will simulate doggy medical emergencies for veterinarians in training. The dog is part of an overall plan for a simulation center with robot cats and dogs that will be the most advanced training center of its kind in the world. More on the new robot dog from the news release:

[Dan Fletcher] is now building a more advanced model code-named “Butch.” Butch will run with inexpensive, off-the-shelf electronic components and sports a more realistic airway, a soft abdomen compartment, articulating joints, more areas for catheters, more space inside the body and a more realistic overall feel.

The new-and-improved robot dog will also integrate with a new veterinary simulation tookit called Ursula (the Universal Realistic Simulation of a Living Animal) that will be open source and shared with other veterinary institutions. Ursula will simulate physiological responses for a variety of animals and will integrate with inexpensive hardware. For more see also the Chronical Online article, the Cornell College of Veterinary Medicine news release and the Cornell University Center for Advanced Computing news release.

Every year Edge asks one question of the world's smartest people; people like Daniel Dennett, Steven Pinker, Rodney Brooks, Roger Schank, and dozens of others; scientists, philosophers, artists. Every year robots and AI are recurring topics throughout the answers. This year's question is "What *should* we be worried about?" From the introduction, here's the full question:

We worry because we are built to anticipate the future. Nothing can stop us from worrying, but science can teach us how to worry better, and when to stop worrying. WHAT SHOULD WE BE WORRIED ABOUT? Tell us something that worries you (for scientific reasons), but doesn't seem to be on the popular radar yet—and why it should be. Or tell us something that you have stopped worrying about, even if others do, and why it should be taken off the radar.

And here are the responses. Kevin Kelly thinks we should worry about the "underpopulation bomb" - the first time in human history to experience a diminishing number of young people combined with an increasing number of robots. Gregory Benford warns that our life on Earth is beginning to resemble rats in a spherical trap and that we need to get off this rock before it's too late; a project that calls for robots, nuclear rockets, asteroid mining, and more robots. David Berreby worries that "global greying" will result in increasingly elderly, xenophobic populations who choose to boost their workforces with robots rather than immigrants. Paul Saffo worries about a coming fight between two extreme classes he calls "engineers" and "druids", basically optimists and pessimists respectively who either want to use technology or ban technology. "Druids fear that robot cars are unsafe; Engineers wonder why humans are allowed to drive at all." Andy Clark says we don't need to worry about Super-AIs ruling the world, unless they get culture first. That's just a sampling of the many references to robots, robotics, and machine intelligence. As it has been in past years, the full set of responses is well worth a read for anyone with an interest in the future of the world.

A UCSD news release touts their new android child that is designed to mimic the expressions of a one year old human child as it learns to control its body and interact with humans. There have been a lot of creepy baby-headed robots lately but you may notice this one is a little less creepy and a little more life-like than others. Why? Because the android combines the work of some of the best technology out there: Japanese humanoid robotics hardware and a Hanson Robotics head. David Hanson's android heads have received wide-spread recognition as the most human-like and expressive around. From the news release:

"We developed machine-learning methods to analyze face-to-face interaction between mothers and infants, to extract the underlying social controller used by infants, and to port it to Diego-san. We then analyzed the resulting interaction between Diego-san and adults. With high definition cameras in the eyes, Diego San sees people, gestures, expressions, and uses A.I. modeled on human babies, to learn from people, the way that a baby hypothetically would. The facial expressions are important to establish a relationship, and communicate intuitively to people."

Diego-San was developed at the Machine Perception Lab and funded by the National Science Foundation. The robot is another small step towards robots that are able to interact emotionally with humans. There's still a long way to go, particularly with the development of affective systems in the robot itself. Most work to date has been on expressing simulated affects and on recognizing emotions in humans. For more, seen an earlier UCSD article on the development of Diego-San. Read on for some cool video of Diego-San in action.

Rob Saunders is Lecturer in Design Computing and Faculty of Architecture, Design and Planning at the University of Sydney where he joined the Design Lab. His research interest lies in understanding human creativity and producing tools that support it. His curious design assistants for example are interface agents that have been developed to support human creativity by filtering and exploring design spaces. Saunders also aims to build minimal and well rounded models of creativity at the individual, social and cultural level for autonomous systems that work independently from humans. Curiosity is one of the driving forces behind creative activity. As such, Saunders creates curious agents that are computational models of self-motivated learning based on interest in novelty.

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Today's edition of best robot photos of the week includes fan art of androids Lore and Data, some freaky Japanese half-robot half-woman things, a cow-milking robot, kids with robots, cats with robots, a Robby the Robot diorama, and a coffee shop sign warning customers about the robot shortage. Every week we post a collection of the best robot photos submitted by our readers to our robots.net flickr group. Why? Because everyone likes to see cool new robots! Want to see your robot here? Post it to flickr and add it to the robots.net flickr group. It's easy! If you're not already a flickr member, it's free and easy to sign up. Read on to see the best robot photos of the week!

Are you using the open hardware Raspberry Pi for your robot? If so, or even if you don't have a Pi yet, you may want to check out MAKE's First International Raspberry Pi Meetup. It's on Thursday, 17 Jan in cities all over the world. Check for the location nearest you. Bring a Raspberry Pi project along to show off if you have one. I'll be at the Dallas, TX meetup. LEGO's MINDSTORMS may not be open hardware yet but the new MINDSTORMS EV3 platform is moving in the right direction, dumping proprietary software for standard GNU/Linux (lots of other new features too). Arduino is open hardware all the way and they've got a new toy too, the Arduino Esplora, an Arduino-based input or control device. The Esplora might come in handy for roboticists. The Swirling Brain sent some news our way on robotic clothing, a dress with spider like appendages that use sensors to react to the environment, and a dress that shifts from opaque to transparent depending the arousal level of the wearer (NSFW). He also spotted a cyborg music project in which sensors alter the music based on the performer's facial expressions. If robots that make love and music aren't your thing, maybe you'll prefer a story about Army researchers training mobile robots to navigate by voice command. Know any other robot news, gossip, or amazing facts we should report? Send 'em our way please. Don't forget to follow us on twitter and Facebook. And now you can add us to your Google+ circles too.

According to a CMU news release, CMU's Robotics Institute has entered a five year agreement with Anglo American PLC to develop autonomous robots for a variety of mining tasks including mapping and inspection. From the news release:

Automating the most difficult, costly and dangerous mining jobs will improve safety and increase the productivity and efficiency of Anglo American’s operations. Advances in robotics will allow the mining of hard-to-reach ore deposits that cannot be economically extracted under existing methods and mine layouts

Mining is a very dangerous business and seems like an ideal job for robots. The robot pictured above is a multi-purpose mining robot that is being developed at the Robotics Institute NREC facility. More information can be found in the NREC new release. The technology described here is probably descended from the CMU Groundhog mine-mapping robot that we've reported on as far back as 2002.

The annual Cornell Cup USA competition is a general engineering contest sponsored by Intel. But, while it's not a robot competition, many of the entries are robots, such as the University of Pennsylvania HAWK (Helicopter Aircraft Wielding Kinect) UAV, pictured above, one of the 2012 winners. This year is no exception. Cornell announced the 30 teams who will participate in the 2013 event. Among this year's entries are speech recognition systems, STEM robots, a wheelchair mounted robot arm, several elder-care robots, an autonomous ocean search robot, a smart-home project, a brain-interfaced wheelchair, AUVs, UAVs, a robot shopping cart, a robot for firefighters, a black box for humans, a leaf collection robot, an upper-body exoskeleton, and a swarm of robot that will sanitize hospitals with UV light. Cornell is in the process of creating blogs for each of the teams to post status updates. You can find the team descriptions and blog links in the news release.

Skin is the human body's largest sensory organ. Understanding how it works will help roboticists create more useful android skins. We're a step closer to understanding the skin's sensory system thanks to a new report announced by Johns Hopkins researchers. The scientists created detailed maps of the branching patterns of sensory nerves in mouse skin. The resulting maps revealed ten distinct groups that seem to correspond to differences in nerve functions. For example, some nerve types gather information from a single hair follicle while others branch into groups that collect averaged information from 200 or more different locations. From the new release:

Nathans says the images now in hand will help scientists “make more sense” out of known responses to stimulation of the skin. For example, if a single nerve cell is responsible for monitoring a patch of skin a quarter of an inch square, multiple simultaneous points of pressure within that patch will only be perceived by the brain as a single signal. “That is why we can’t read Braille using the skin on our backs: the multiple bumps that make up a Braille symbol are within such a small area that the axon branches can’t distinguish them. By contrast, each sensory axon on the fingertip occupies a much smaller territory and this permits our fingertips to accurately distinguish small objects.

For all the details on the research, including lots of diagrams and images of the nerve networks, see the paper, "Morphological diversity of cutaneous sensory afferents revealed by genetically directed sparse labeling" (PDF format). In a related new release, Johns Hopkins researchers announced the discovery of strong evidence that there are specific nerve cells responsible for itch signals, distinct from nerves involved in pain.

Today's edition of best robot photos of the week just goes to show that humans and robots love to hang out together. Whether it's at dance parties, school, coffee shops, bus stops, or the park; humans and robots can run into each other anywhere and enjoy some much needed digital to analog social interaction. Every week we post a collection of the best robot photos submitted by our readers to our robots.net flickr group. Why? Because everyone likes to see cool new robots! Want to see your robot here? Post it to flickr and add it to the robots.net flickr group. It's easy. If you're not already a flickr member, it's free and easy to sign up. Read on to see the best robot photos of the week!

Several mainstream news items on robots this week including an interesting piece in the New Yorker titled, Why Making Robots Is So Darn Hard. Meanwhile Salon and the New York Times dragged robots into the growing debate of "profits without prosperity" - the recent phenomenon in which big corporations are making more and more profit but without the traditional increase in general prosperity among corporate employees. In the New York Times article, Robots and Robber Barons, economist Paul Krugman cites robots as one of two possible causes for the problem. Salon, in the article, Robots don't destroy jobs by economist William Lazonick, counters that for every human worker a robot replaces, it adds multiple new job opportunities for humans. The Salon article posits the real problem is not robots but corporate abuse of profits, the fault of humans, not machines. Leaving economics behind, The Swirling Brain pointed us to some cool photos and video of a robot ornithoper made from 3D printed parts. And everybody loves a top ten list, right? The Public Library of Science (PLOS) recently posted a list of Ten Simple Rules for the Open Development of Scientific Software. Know any other robot news, gossip, or amazing facts we should report? Send 'em our way please. Don't forget to follow us on twitter and Facebook. And now you can add us to your Google+ circles too.

The latest release of the popular robot operating system ROS, nicknamed Groovy Galapagos, was released on 31 December. The Groovy release includes a lot of changes to the core infrastructure aimed at making ROS easier to use, more modular, and more scalable. Portability has also been improved with support for most GNU/Linux distros, Android, and even some proprietary operating systems such as Mac OS X and Windows. Developers will also be happy to see that all ROS packages have been consolidated on GitHub:

Traditionally, ROS code has been scattered across numerous version control systems (git, svn, hg, etc) across different hosting services throughout the world. Though the ROS wiki has acted as a central point of documentation, issue/ticket tracking has been just as disparate as the usage of VCS tools. With ROS Groovy, an effort has been made to move core packages to GitHub along with all issue tracking. This has brought several benefits including making ROS more available to the wider open source community and providing VCS consistency for ROS packages. Most importantly, utilizing GitHub has involved the ROS community more and given it more ownership of the codebase. GitHub's pull requests have made it much easier for the core ROS development team to apply patches from the community as well as respond to design feedback more rapidly.

Developers should expect to see a few changes in the build tools as well. Stacks have been removed, rosbuild has been replaced with a new build tool called catkin, the core ROS GUI tools have been replaced by a single tool called rqt, the Wx toolkit has been replaced with Qt. For a full list of changes, see the ROS Groovy Galapagos release notes. ROS is free software released under a variety of licenses that meet the guidelines of the Free Software Foundation and Open Source Initiative. If you'd like it try ROS, you can download the source or pre-packaged binaries for most systems.

The National Geographic Explorers Journal blog brought to our attention the OpenROV Project, which was recently funded by a successful Kickstarter campaign that raised over $100,000 USD. The project was founded by friends Eric and David, who wanted to build an ROV from low-cost off-the-shelf parts. The OpenROV can be used for educational purposes or for actual underwater exploration. The current version of the OpenROV is limited to a depth of 100 meters but the design is open source and you're invited to modify and improve it. In addition to the open source hardware, this little underwater robot relies on open source software running on a GNU/Linux-based embedded processor. There's a USB HD video camera and LED light arrays on board too so you can see where you're going. At present the OpenROV is strictly a DIY project that you build from the designs and source code available on the OpenROV wiki. But kits for about $750 and even fully assembled ROVs should be available soon. Read on to see the original kickstarter video that describes the ROV and a more recent video of the ROV in action

In episode #120, reporter Per speaks with Mel Torrie of Autonomous Solutions, Inc., which he founded in 2000, with encouragement from John Deere, as a spin-off of the Center for Self Organizing and Intelligent Systems (CSOIS) at Utah State University (USU). From agriculture, the company branched out into mining and construction, then survived one lean period because it had also invested in golf course mowing. ASI has also participated in three DARPA challenges, supporting the University of Florida's team for both runnings of the DARPA Grand Challenge, and then as an independent entrant in the DARPA Urban Challenge. ASI has distilled its autonomous vehicle experience into a kit that can be quickly and easily installed in new vehicles, now marketing this kit to automotive manufacturers for use in their internal testing programs, allowing them to push their cars through grueling tests more quickly than human drivers can tolerate.

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Circuit Cellar magazine recently posted in full their two-part article by Tom Kibalo on the construction of his subsumption-based mobile robot, called TOMBOT. Part 1 of the article covers construction of the hardware and Part 2 covers the subsumption software and basic behaviors for obstacle avoidance, collisions, and light tracking. The robot is a differential drive design using continuous-turn RC Servos as motor. It lacks wheel encoders. The robot sports an XBee radio, a PIC32 CPU, and a small LCD display. It's a good basic introduction to behavior-based robots and well worth a read.

Just as researchers today struggle to find working definitions for words like consciousness and intelligence, they struggled to find a standardized meaning for the word information in the early 1900s. Ralph Hartley, a research for Bell Laboratories, first introduced a theory of information based on the idea that information consisted of strings of symbols, a reasonable idea in the age of telegraph, telephones, and radio. Shannon and Weaver moved things along in the 1940s, resulting in Shannon-Weaver Information Theory (SWIT). While Hartley's theory was concerned primarily with sets of symbols, SWIT was concerned with the probability or uncertainty of events (the likelihood a particular structure or sequence of symbols are meaningful). Both theories fall far short of describing what a modern cognitive scientist or AI researcher means when they talk about information. A newer theory was developed in the field of psychological research, Representational Information Theory (RIT). The idea behind RIT is that communication between animals and their environment is mediated by concepts. The only drawback of RIT is that it only supported binary dimensions. RIT looks at information in terms of complexity rather than uncertainty like SWIT. In a new paper published in the journal Information, researchers described a generalized version of RIT, called GRIT that may be useful in the fields of AI and robotics:

"concepts live in the mental space of organisms ranging from aplasia to insects and from dolphins to humans. Some may argue that they also live in the mental spaces of intelligent robots and expert systems. Regardless, the point is that only by using concepts as mediators can information as a measurable quantity reflect human intuitions as to what is informative."

The paper includes a technical appendix with mathematical examples of Generalized Representational Information Theory (GRIT) showing examples such as the one above that includes three dimensions (shape, color, and size). For all the details, read the paper, titled, "Complexity over Uncertainty in Generalized Representational Information Theory (GRIT): A Structure-Sensitive General Theory of Information" (PDF format). The paper was written by Ronalda Vigo of the Center for the Advancement of Cognitive Science, Psychology Department, Ohio University. Hartley's 1928 paper is available online as Transmission of Information (PDF format). Shannon's 1948 paper (on which the later Shannon-Weaver book was based) can be found as "A Mathematical Theory of Communication" (PDF format).

This week's edition of Best Robot Photos of the Week is a special holiday collection of Christmas robots submitted by our readers. We also received one holiday photo made by Hanukkah nanobots. No one posted photos of Kwanzaa bots or Festivus droids this year. Whatever your preferred winter holiday, just remember that Axial Tilt is the reason for the season and enjoy our these photos of holiday robots. Want to see your robot photo here? Post it to flickr and add it to the robots.net flickr group. If you're not a flickr member yet, it's free and easy to sign up. Read on to see the best robot photos of the week!

Yet another brain mapping project has announced some pretty amazing new findings. Researchers at UC Berkeley's Gallant Lab have succeeded in decoding the semantic mapping space in which the brain stores all the information we take in. They've mapped the space both as abstract, multi-dimensional graphics and they've mapped the actual locations where the information nodes are stored in the physical brain. They've learned all sorts of new things about how the brain categorizes things. For example, one semantic dimension (abbreviated PC) of our brain space categorizes things by whether they move - cars, motorcycles, people vs buildings, cities, and the sky. Another dimension distinguishes between things involved in social interaction (people, verbs, furniture) and things involved in less interactive outdoor activities (geological formations, animals, vehicles). They've identified four semantic dimensions so far but believe with higher resolution scans and more work, many more will be revealed.

"Across the cortex, semantic representation is organized along smooth gradients that seem to be distributed systematically. Functional areas defined using classical contrast methods are merely peaks or nodal points within these broad semantic gradients. Furthermore, cortical maps based on the group semantic space are significantly smoother than expected by chance. These results suggest that semantic representation is analogous to retinotopic representation, in which many smooth gradients of visual eccentricity and angle selectivity tile the cortex (Engel, Glover, & Wandell, 1997; Hansen, Kay, & Gallant, 2007). Unlike retinotopy, however, the relevant dimensions of the space underlying semantic representation are not known a priori, and so must be derived empirically"

The mapping of the semantic space onto the brain reveals that as much as 20% of the brain, including parts of the somatosensory and frontal cortices, is devoted to storing these highly organized semantic maps. Less surprisingly, the maps confirm the location of previously established specialized areas. Information about humans, for example, overlaps the fusiform face area (FFA) of the brain which is known to be involved in face recognition. For more see the paper "A continuous semantic space describes the representation of thousands of object and action categories across the human brain" (PDF format). The paper will be in Neuron Vol 76, Iss 6. If you're using a browser such as Google's Chrome that supports WebGL graphics, you can explore an interactive version of the researcher's semantic brain map. And read on to see examples of the semantic space mapped onto the physical brain as well as a short video describing the research.

For the past two weeks the Boston Dynamics LS3 (Legged Squad Support System) robot has been undergoing field tests in the woods of central Virginia with personnel from the Marine Corps Warfighting Lab. DARPA issued a news release with video of LS3 following a marine through real world terrain and responding to voice commands. The four legged robot is designed to carry up to 400 lbs of gear anywhere a squad can go. The robot is semi-autonomous and designed to look out for itself and while keeping up with the marines. The tests seem to have positive results, Lt. Col. Joseph Hitt of DARPA reports:

"This was the first time DARPA and MCWL were able to get LS3 out on the testing grounds together to simulate military-relevant training conditions. The robot’s performance in the field expanded on our expectations, demonstrating, for example, how voice commands and 'follow the leader' capability would enhance the robot’s ability to interact with warfighters. We were able to put the robot through difficult natural terrain and test its ability to right itself with minimal interaction from humans.”

Read on to see the video, which includes shots of the robot following a soldier through the woods and being intentionally forced into situations where it will stumble. At times the robot has to run to keep up, while climbing hills, slogging through mud, and following a soldier through a maze of shipping containers.