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In Stack Machines, Expression Evaluation, and the Magic of Reverse Polish, I showed how expressions can be evaluated by rewriting them in reverse Polish and translating this into machine-code instructions for a stack machine. I demonstrated with a stack-machine interpreter that I'd written as part of a working model of a Pascal compiler. But as well as expressions, the compiler needs to compile assignments and jumps, so — in my progress towards explaining the compiler — I'm going to extend the machine code so it can handle these. I'll demonstrate by interpreting a program that calculates five factorial.

The purpose of this essay is to examine whether or not there would be practical reasons for creating a conscious, emotional machine.  I will not delve to deeply into whether or not it is possible to create such a machine, as the argument as to what exactly would constitute a living conscious machine seems largely unsettled.  Rather I will concentrate on whether or not we should create such a machine, if the possibility becomes available to us.  Are there uses for such a machine that could not be satisfied by a complex automaton?  Is there anything about real emotional response that would be necessary for a machine to operate autonomously, and still interact with human beings?  What are the dangers? What are the ethical ramifications? It is questions such as these that will be the interest of this paper.

Microsoft Research who brought us some wonderful technologies such as the incredible Photosynth continue to impress with a much improved web mapping application integrated with the company's new Bing search engine. During the TED 2010 conference, Microsoft engineer Blaise Aguera y Arcas demoed the new Bing augmented reality maps showing real-time registration of video taken with a smart phone and street-view type maps. He showed how the live video can be overlayed over the static images and additional information about the area can be accessed via a Web interface. Much of this is made possible because of the advanced computer vision technology that has been developed in the past decade at Microsoft Research. The Seadragon technology is the back-end that makes it possible to manipulate such vast amounts of data in real-time. Microsoft has also integrated Photosynth and Worldwide telescope into their maps product. You are probably wondering what does this have to do with robotics other than the fact that it is a very impressive application? I can imagine robots using Bing maps to keep localized within a city. One of the most difficult and important problem in robotics is that of Simultaneous Localization and Mapping. Bing maps solve the mapping problem and the new vision techniques (with a bit of help from GPS) can be used to solve the localization problem. The registered video can be used by a robot to localized itself when it goes out to buy your weekly groceries.  You can watch the 10-minute demo below; I bet that it won't be long before Microsoft makes these new features available to us all for free.

"An industrial assembly line includes a factory, workers, and a conveyor system," said NYU Chemistry Professor Nadrian Seeman, the study's senior author. "We have emulated each of those features using DNA components." The assembly line relies on three DNA-based components. The first is DNA origami, a composition that uses a few hundred short DNA strands to direct a very long DNA strand to form structures to any desired shape. These shapes are approximately 100 x 100 nanometers in area, and about 2 nm thick (a nanometer is one billionth of a meter). DNA origami serves as the assembly line's framework and also houses its track. The second are three DNA machines, or cassettes, that serve as programmable cargo-donating devices. The cargo species the researchers used are gold nanoparticles, which measure 5 to 10 nanometers in diameter. Changing the cassette's control sequences allows the researchers to enable or prevent the donation of the cargoes to the growing construct. The third is a DNA "walker," which is analogous to the chassis of a car being assembled. It moves along the assembly line's track, stopping at the DNA machines to collect and carry the DNA "cargo." As the walker moves along the pathway prescribed by the origami tile track, it encounters sequentially the three DNA devices. These devices can be switched between an "on" state, allowing its cargo to be transferred to the walker, and an "off" state, in which no transfer occurs. In this way, the DNA product at the end of the assembly line may include cargo picked up from one, two, or three of the DNA machines. "A key feature of the assembly line is the programmability of the cargo-donating DNA machines, which allows the generation of eight different products," explained Seeman.

The MATLAB team at MathWorks tested performance scaling of the backslash ("\") matrix division operator to solve for x in the equation A*x = b. In their testing, matrix A occupies far more memory (290 GB) than is available in a single high-end desktop machine—typically a quad core processor with 4-8 GB of RAM, supplying approximately 20 Gigaflops. Therefore, they spread the calculation across machines. In order to solve linear systems of equations they need to be able to access all of the elements of the array even when the array is spread across multiple machines. This problem requires significant amounts of network communication, memory access, and CPU power. They scaled up to a cluster in EC2, giving them the ability to work with larger arrays and to perform calculations at up to 1.3 Teraflops, a 60X improvement. They were able to do this without making any changes to the application code. Here's a graph showing the near-linear scalability of an EC2 cluster across a range of matrix sizes with corresponding increases in cluster size for MATLAB's parallel backslash operator:

PC-compatible industrial computers are increasing in computing power at a rapid rate due to the availability of multi-core microprocessor chips, and Microsoft Windows has become the de-facto software platform for implementing human-machine interfaces (HMIs). PCs are also becoming more reliable. With these trends, the practice of building robotic systems as complex multi-architecture, multi-platform systems is being challenged. It is now becoming possible to integrate all the functions of machine control and HMI into a single platform, without sacrificing performance and reliability of processing. Through new developments in software, we are seeing industrial systems evolving to better integrate Windows with real-time functionality such as machine vision and motion control. Software support to simplify motion control algorithm implementation already exists for the Intel processor architecture.

The moving parts of micromechanical machines tend to seize up under the forces of sticking and friction that engineers call stiction. The problem yields to solid lubricants, notably graphite (sheets of carbon atoms called graphene stacked in layers), although for a long time no one understood exactly why this happens. Now nanotechnology researchers, led by Professor Robert Carpick at the University of Pennsylvania and Professor James Hone at Columbia University, in New York City, have shown that how effective the lubrication is depends on the number of layers of graphene in the graphite. In particular, more layers means better lubrication. Because the same relationship between layers and lubrication occurs in thin sheets of molybdenum disulfide, niobium diselenide, and boron nitride—materials of widely differing properties—the workers conclude that this behavior is a fundamental aspect of friction. They expect that the discovery will lead to better lubrication of tiny moving parts. The researchers published details of their experiments in a recent issue of Science.

Researchers at Purdue University have developed two new techniques for computer-vision technology that mimic how humans perceive three-dimensional shapes.The techniques, heat mapping and heat distribution, apply mathematical methods to enable machines to perceive three-dimensional objects by mimicking how humans perceive three-dimensional shapes by instantly recognizing objects no matter how they are twisted or bent, an advance that could help machines see more like people.

California-based company Anybots continues work on a telepresence robot that can take communication to a whole new level by eliminating the need for people to actually be present at board meetings or conferences. Because God knows executives work hard enough. The idea behind QA, the robot, is to interact with people, such as clients or partners, from anywhere in the world, which will save a lot of money on travel costs and different remote-communications equipment. Designed not unlike a sophisticated Skype program, QA relies on a Wi-Fi connection to allow users to interact through video, sound and diagrams projected from and onto the robot’s interface. With a sleek white exterior design, the armless 5-foot robot looks just about how you would expect a robot tailored for the boardroom to look. His rectangular-shaped face with two big eyes reminds a bit of Steven Spielberg’s E.T., so people should warm up to it fairly quickly.

Tilikum the killer whale (Orcinus orca) made news recently in the tragic death of his Sea World trainer, Dawn Brancheau. Tilikum pulled Brancheau into the water when he grabbed her floating ponytail — much like a cat might grab yarn attached to a stick. Complex play behavior is a sign of intelligence, but unfortunately little is known of the circuitry of even a cat’s brain, much less the massive brain of an orca — roughly four times the size of a human brain. See Also The Race to Reverse Engineer the Human Brain Ray Kurzweil Interview Brain on a Chip MIT neuroscientists are developing computerized techniques to map the millions of miles of neuronal circuits in the brain that may one day shed some light on the differences between Homo sapiens sapiens and other species, and will likely clarify how those neurons give rise to intelligence, personality, and memory. Developing connectomes (maps of neurons and synapses) may have just as much impact as sequencing the human genome. Here’s a video showing 3D rotating nodes and edges in a small connectome:

I remember when, a decade ago, Kevin Warwick, a professor at the University of Reading, in the U.K., implanted a radio chip in his own arm. The feat caused quite a stir. The implant allowed him to operate doors, lights, and computers without touching anything. On a second version of the project he could even control an electric wheelchair and produce artificial sensations in his brain using the implanted chip. Warwick had become, in his own words, a cyborg. The idea of a cyborg -- a human-machine hybrid -- is common in science fiction and although the term dates back to the 1960s it still generates a lot of curiosity. I often hear people asking, When will we become cyborgs? When will humans and machines merge? Although some researchers might have specific time frames in mind, I think a better answer is: It's already happening. When we look back at the history of technology, we tend to see distinct periods -- before the PC and after the PC, before the Internet and after the Internet, and so forth -- but in reality most technological advances unfold slowly and gradually. That's particularly true with the technologies that are allowing us to modify and enhance our bodies.

You might think that some devices in the modern age have reached their maximum development level, such as the common desk-lamp, but you would be wrong. Natan Linder, a student from The Massachusetts Institute of Technology (MIT) has created a robotic version that can not only light your room, but project internet pages on your desk as well. It is an upgrade on the AUR lamp from 2007, which tracks movements around a desk or table and can alter the color, focus, and strength of its light to suit the user’s needs. The LuminAR comes with those abilities, and much more. The robotic arm can move about on its own, and combines a vision system with a pico projector, wireless computer and camera. When turned on, the projector will look for a flat space around your room on which to display images. Since it can project more than one internet window, you can check your email and browse another website at the same time.

Humans have been coming up with innovative ways with which to plunder the Earth and its resources for as long as we have existed, so perhaps its time we give back a little. Leading aquatic animals, such as fish, away from underwater power plant turbines seems like a good place to begin, and a researcher at the Polytechnic Institute of New York University has designed a robot that will help just with that. Assistant professor Maurizio Porfiri studied the characteristics of small schools of fish to learn what exactly they look for in a leader, and he designed a palm-sized robot that possesses these traits. By taking command, this leader can be programmed to guide the fish away from danger, but the tricky part is getting the animals to accept the robot as one of their own.

Humans aren't the only ones playing soccer right now. In just two days, robots from world-renowned universities will compete in Singapore for RoboCup 2010. This is the other World Cup, where players range from 15-centimeter tall Wall-E-like bots to adult-sized advanced humanoids. The RoboCup, now in its 14th edition, is the world’s largest robotics and artificial intelligence competition with more than 400 teams from dozens of countries. The idea is to use the soccer bots to advance research in machine vision, multi-agent collaboration, real-time reasoning, sensor-fusion, and other areas of robotics and AI. But its participants also aim to develop autonomous soccer playing robots that will one day be able to play against humans. The RoboCup's mission statement:

A team of evangelical Christian explorers claim they've found the remains of Noah's ark beneath snow and volcanic debris on Turkey's Mount Ararat (map). But some archaeologists and historians are taking the latest claim that Noah's ark has been found about as seriously as they have past ones—which is to say not very.

“CMS” stands for Compact Muon Solenoid, a general-purpose particle physics detector built on the Large Hadron Collider. The CMS project posted a few comics which provide a nice, simple (if somewhat cheesy) explanation of what the CMS/LHC does. The LHC generates massive amounts of data of all different varieties, which is distributed across a worldwide grid. It sends status messages to some of the computers, job monitoring info to other computers, bookkeeping info still elsewhere, and so on. This means that each location has specialized queries it can do on the data it has, but up until now it’s been very difficult to query across the whole grid. Enter the Data Aggregation System, designed to allow anything to be queried across all of the machines.

Researchers at MIT’s McGovern Institute for Brain Research are working on a new mathematical model to mimic the human brain's ability to identify objects. The model can predict human performance on certain visual-perception tasks suggesting it’s a good indication of what's actually happening in the brain. Researchers are hoping the new findings will make their way into future object-recognition systems for automation, mobile robotics, and other applications.