Science & technology

The popularity of cloud computing is rising faster now than at any time in the past. And it's no wonder; accessing services and applications through the Internet rather than storing the necessary data on your own computer makes sense now that links are so fast and reliable.

However, cloud computing has some significant drawbacks. Instead of localizing failures as conventional Internet computing does, the cloud makes failures system wide, say Alexandros Marinos at the University of Surrey and Gerard Briscoe at the London School of Economics, both in the U.K.. If the cloud goes down, as happened earlier this year with Gmail and last year with Amazon's S3 service, entire companies and the industries associated with them can grind to a halt.

So Marinos and Briscoe have come up with an alternative: community clouds in which individuals offer a portion of their computing resources to a virtual cloud. That's not unlike distributed computing ventures such as SETI@home and Folding@home that use processing cycles on idling personal computers to carry out intensive data analysis.

A virtual cloud would be more demanding but could have substantial benefits. Marinos and Briscoe say that Wikipedia might be an ideal test bed on which to try out the idea. At the moment, Wikipedia depends on substantial donations to keep its servers running and to keep the service free of advertisements. An interesting alternative might be a virtual cloud based on computing resources donated by users around the world.

Marinos and Briscoe point out that a virtual cloud should also be greener than the rapidly expanding data centers that are springing up all over the world. The combined carbon footprint of data centers is expected to exceed that of the world's airlines by 2020. Even now, these facilities are challenging the capacity of power grids to deliver enough power to keep them going.

That alone may provide the necessary vision and momentum to get an idea like this off the ground.

Ref: arxiv.org/abs/0907.2485: Community Cloud Computing
 

A new study of neural prostheses in monkeys suggests that learning to control a robotic arm with the power of thought may happen more naturally than scientists had expected. Jose Carmena and Karunesh Ganguly at the University of California, Berkeley (UCB), found that the animals create a mental map of the device, much as we do when learning to swim or swing a tennis racket.

A number of labs have already shown that monkeys--and in a few cases, humans--with electrodes implanted into their brains can learn to control a computer cursor or robotic arm. To train the subjects, scientists first record the activity in a group of neurons as the monkey moves its real arm (or in the case of a paralyzed human, as the person imagines moving his or her arm). Researchers then analyze the neural activity to develop a decoding algorithm that can translate the pattern of brain-cell firing into an action--say, moving a cursor to a certain point on a computer screen.

In the new study, published today in the journal PLoS Biology, monkeys learned to precisely control a computer cursor over a few days. As the animals became proficient at the task, the researchers identified a specific pattern of neural activity in the brain associated with the movement. "The profound part of our study is that this is all happening with something that is not part of one's own body. We have demonstrated that the brain is able to form a motor memory to control a disembodied device in a way that mirrors how it controls its own body. That has never been shown before," said Carmena in a press release from UCB.

The research also suggests that optimizing the decoders may not be as important as expected. A few weeks after the monkeys learned to control the arm with the original decoder, Carmena and Ganguly introduced a new one, indicated by a different colored cursor. According to the release:

As the monkeys were mastering the second decoder, the researchers would suddenly switch back to the original decoder and saw that the monkeys could immediately perform the task without missing a beat. The ability to switch back and forth between the two decoders shows a level of neural plasticity never before associated with the control of a prosthetic device. "This is a study that says that maybe one day, we can really think of the ultimate neuroprosthetic device that humans can use to perform many different tasks in a more natural way," said Carmena.