Robotics & Mechanical Limbs

The BrainGate implantable microelectrode array

As people continue to struggle with problems involving organ donation, a few robotic engineers continue to push the boundaries between humanity and machinery. A recent report in Nature (cited below) showed that two patients were able to overcome some aspects of their paralysis by way of an implant. Reaching and grabbing motions were possible by way of a carefully designed robotic arm. One individual involved in the study was able to enjoy a drink by herself. She didn’t seem to require assistance outside of the prosthetic limb. Read More →

Is ‘Mind Hacking’ a Threat of the Future?

Often when I write/speak about synthetic biology or the future merging of humans and technology at the biologic level, one of the primary concerns expressed by others involves the possibility of virus corruption. The fear of hackers that engineer viruses or bacteria to control humans may be a valid concern. What do you think? Is mind hacking a real threat to humans down the road once we’re “plugged in”?

A Look Back at the Alabama Virus 

Computer viruses are never a positive thing. They’re malicious, and there has been a great deal of debate over them. However, the Alabama virus can be used as an interesting thought experiment. Considering that it infected computers in October 1989, using it as a point of reference is probably innocuous.

In its day, the Alabama virus infected executable DOS files. It was loaded up into memory when a user executed an infected program. Infected programs grew by 1,560 bytes. Each Friday, the virus started to mess with the file allocation tables in order to insure that infected files were run preferentially over uninfected ones. This process was dangerous, and caused people to loose files.

Interestingly enough, it had an anti-piracy message. After staying in memory for an hour, the virus would tell the user that software copies were forbidden under international law. It then displayed a PO box address located in Tuscambia, Alabama. Tuscambia actually doesn’t exist. Since the virus was probably developed in Israel, the author may have confused the spelling of Tuscumbia.

Additional infections were carried out by carefully inspecting the directory to note which files were clean. The virus attacked the program being run if there were no further files to infect. Considering this selective nature, the virus program almost seemed like a living thing. It was apparently supposed to impart a moral lesson and act on behalf of its creator. In that respect, it almost seems like the living arm of the individual who programmed it.

While it would certainly be foolish to call it a completely independently acting piece of artificial intelligence, the Alabama virus does have some aspects that make it resemble a living thing. It also may represent the dangers of letting computers act in a totally autonomous fashion.

So do we need to worry about viruses/hacking used to control robots and/or humans in the future? What are your thoughts?

Reference:

http://www.probertencyclopaedia.com/cgi-bin/res.pl?keyword=Alabama+Virus&offset=0

Robot Reveals the Inner Workings of Brain Cells

Gaining access to the inner workings of a neuron in the living brain offers a wealth of useful information: its patterns of electrical activity, its shape, even a profile of which genes are turned on at a given moment. However, achieving this entry is such a painstaking task that it is considered an art form; it is so difficult to learn that only a small number of labs in the world practice it. Read More →

Humanity 2.0 – Cybernetic Individuals Today

Future humans might very well be a certain variety of organic machine hybrid. But what about right now? Are we witnessing the emergence of cyborg life within our society today? Consider that artificial hearts and prosthetic limbs are probably the best-known types of machinery intended to be grafted onto or within human flesh. Such artificial designs are supposed to fulfill a medical need. They are used when human organs or tissue have failed or has been amputated. Is this not a form of cybernetic integration? One would not usually receive a prosthetic for any recreational reason today however, I can see a future where perhaps this may be commonplace (or even trendy) in instances where prosthetic devices or artificial organs might enhance human performance and/or prolong life. Given that we’re headed into the weekend, I thought this might be a good topic to wrap up the week.  Read More →

Superintelligence Must be Carefully Tapped

I’m of the opinion that if we’re ever going to achieve long-range space exploration/colonization, human engineering of some sort will be required. This not only applies to space exploration however, but most likely the long-range survival of humanity in general. The common fear in this topic seems to always conjure up a ‘rise of the machines’ scenario when I’m discussing this with others. So I thought that today I’d post a few thoughts on how these fears might be alleviated in the future. Read More →

The Merging of Biology and Electronics [Research]

The boundary between electronics and biology is blurring with the first detection by researchers at Department of Energy’s Oak Ridge National Laboratory of ferroelectric properties in an amino acid called glycine.

A multi-institutional research team led by Andrei Kholkin of the University of Aveiro, Portugal, used a combination of experiments and modeling to identify and explain the presence of ferroelectricity, a property where materials switch their polarization when an electric field is applied, in the simplest known amino acid—glycine (referenced below). Read More →

Next Generation Artificial Intelligence

As computer scientists this year celebrate the 100th anniversary of the birth of the mathematical genius Alan Turing, who set out the basis for digital computing in the 1930s to anticipate the electronic age, they still quest after a machine as adaptable and intelligent as the human brain.

Now, computer scientist Hava Siegelmann of the University of Massachusetts Amherst, an expert in neural networks, has taken Turing’s work to its next logical step. She is translating her 1993 discovery of what she has dubbed “Super-Turing” computation into an adaptable computational system that learns and evolves, using input from the environment in a way much more like our brains do than classic Turing-type computers. She and her post-doctoral research colleague Jeremie Cabessa report on the advance in the current issue of Neural Computation.

“This model is inspired by the brain,” she says. “It is a mathematical formulation of the brain’s neural networks with their adaptive abilities.” The authors show that when the model is installed in an environment offering constant sensory stimuli like the real world, and when all stimulus-response pairs are considered over the machine’s lifetime, the Super Turing model yields an exponentially greater repertoire of behaviors than the classical computer or Turing model. They demonstrate that the Super-Turing model is superior for human-like tasks and learning.

“Each time a Super-Turing machine gets input it literally becomes a different machine,” Siegelmann says. “You don’t want this for your PC. They are fine and fast calculators and we need them to do that. But if you want a robot to accompany a blind person to the grocery store, you’d like one that can navigate in a dynamic environment. If you want a machine to interact successfully with a human partner, you’d like one that can adapt to idiosyncratic speech, recognize facial patterns and allow interactions between partners to evolve just like we do. That’s what this model can offer.”

Classical computers work sequentially and can only operate in the very orchestrated, specific environments for which they were programmed. They can look intelligent if they’ve been told what to expect and how to respond, Siegelmann says. But they can’t take in new information or use it to improve problem-solving, provide richer alternatives or perform other higher-intelligence tasks.

In 1948, Turing himself predicted another kind of computation that would mimic life itself, but he died without developing his concept of a machine that could use what he called “adaptive inference.” In 1993, Siegelmann, then at Rutgers, showed independently in her doctoral thesis that a very different kind of computation, vastly different from the “calculating computer” model and more like Turing’s prediction of life-like intelligence, was possible. She published her findings in Science and in a book shortly after.

“I was young enough to be curious, wanting to understand why the Turing model looked really strong,” she recalls. “I tried to prove the conjecture that neural networks are very weak and instead found that some of the early work was faulty. I was surprised to find out via mathematical analysis that the neural models had some capabilities that surpass the Turing model. So I re-read Turing and found that he believed there would be an adaptive model that was stronger based on continuous calculations.”

Each step in Siegelmann’s model starts with a new Turing machine that computes once and then adapts. The size of the set of natural numbers is represented by the notation aleph-zero, א0, representing also the number of different infinite calculations possible by classical Turing machines in a real-world environment on continuously arriving inputs. By contrast, Siegelmann’s most recent analysis demonstrates that Super-Turing computation has 2א0 possible behaviors. “If the Turing machine had 300 behaviors, the Super-Turing would have 2300, more than the number of atoms in the observable universe,” she explains.

The new Super-Turing machine will not only be flexible and adaptable but economical. This means that when presented with a visual problem, for example, it will act more like our human brains and choose salient features in the environment on which to focus, rather than using its power to visually sample the entire scene as a camera does. This economy of effort, using only as much attention as needed, is another hallmark of high artificial intelligence, Siegelmann says.

“If a Turing machine is like a train on a fixed track, a Super-Turing machine is like an airplane. It can haul a heavy load, but also move in endless directions and vary its destination as needed. The Super-Turing framework allows a stimulus to actually change the computer at each computational step, behaving in a way much closer to that of the constantly adapting and evolving brain,” she adds.

Siegelmann and two colleagues recently were notified that they will receive a grant to make the first ever Super-Turing computer, based on Analog Recurrent Neural Networks. The device is expected to introduce a level of intelligence not seen before in artificial computation.

Source: University of Massachusetts at Amherst

Reference:

Cabessa, J., & Siegelmann, H. (2012). The Computational Power of Interactive Recurrent Neural Networks Neural Computation, 24 (4), 996-1019 DOI: 10.1162/NECO_a_00263

ResearchBlogging.org

Are Robots the Future of Space Exploration?

Mashable recently posted about the upcoming We Robot 2012 conference and naturally I had to check it out to see if anything space related is included. Alas it’s not but it got me thinking about the future of space exploration in terms of robotics/artificial intelligence (AI). This topic is of course always hotly debated but one worth exploring nonetheless. Read More →