Archive for the ‘Cool stuff’ Category

The psychological refractory period

Tuesday, November 23rd, 2010

Pop quiz: What is 357 times 289? No pencils allowed. No calculators. Just use your brain.

Got an answer yet? Got it now? How about now? Chances are you still don’t. As you solved the problem one step at a time, you lost track of the numbers. Maybe you tried to start over, lost track again, and eventually gave up in frustration before you could discover that the answer was 103,173. I used a calculator to get that, I confess.

Our mutual failure is absurd. The brain is, in the words of neuroscientist Floyd Bloom, “the most complex structure that exists in the universe.” Its trillions of connections let it carry out all sorts of sophisticated computations in very little time. You can scan a crowded lobby and pick out a familiar face in a fraction of a second, a task that pushes even today’s best computers to their limit. Yet multiplying 357 by 289, a task that demands a puny amount of processing, leaves most of us struggling.

For psychologists, this kind of mental shortcoming is like a crack in a wall. They can insert a scientific crowbar and start to pry open the hidden life of the mind. The fact that we struggle with certain simple tasks speaks volumes about how we are wired. It turns out the evolution of our complex brain has come at a price: Sometimes we end up with a mental traffic jam in there.

Psychologists have long been puzzled by the psychological refractory period because it doesn’t fit with other things we know about how the brain works. We are very good at doing many things at once. As you read this column, your brain can also manage your heartbeat, perceive the melody of a song playing on the radio, and send out complicated instructions for drinking a cup of coffee. It can do all that because it is parceled into hundreds of relatively self-contained regions. These regions can work on different tasks at the same time. Yet there are simple jobs—like math problems—that our brains can handle only one at a time. It is as if signals were flying down a 20-lane superhighway, and then the road narrowed to a single lane.

Each time we perform a task we perform it in three steps. Step 1: Take in information from the senses. Step 2: Figure out what to do in response. Step 3: Carry out that plan by moving muscles. Stanislas Dehaene, chair of experimental cognitive psychology at the College of France, and neuroscientist Mariano Sigman of the University of Buenos Aires wondered where along these steps the traffic jam arises. To find out, they designed new variations on the classic Telford experiments.

In these experiments, subjects had to decide whether a number was higher or lower than 45. In each version of the test, the scientists varied one of the three steps of the thought process to see if they could change the length of the psychological refractory period. Only when they tinkered with step 2—figuring out what response to make—could they produce a change. In that case, they showed people numbers that were either close to 45 or far from 45. When the number was close to 45, the psychological refractory period got longer.

It is a remarkable discovery when you consider that the mental activity that takes place in Step 2 includes some of the most sophisticated forms of thought we are capable of: weighing lots of information, thinking about our short-term and long-term goals, and figuring out how to meet them. We like to imagine that it is exactly this kind of thinking we do much better than other animals. But when we have any two simple decisions to make, we must wait for the first task to move through a bottleneck before taking on the second. That is what makes mental multiplication so hard. Instead of carrying out many steps simultaneously, we have to do them one at a time.

Dehaene now thinks he knows why our thoughts get stuck in bottlenecks: The neurons that take in sensory information send it to a neural network that he and his colleagues call the “router.” Like the router in a computer network, the brain’s version can be reconfigured to send signals to different locations. Depending on the task at hand, it can direct signals to the parts of the brain that produce speech, for instance, or to the parts that can make a foot push down on a brake pedal. Each time the router switches to a new configuration, however, it experiences a slight delay.

Recently Dehaene tested this theory by building a model of the brain. He wrote a computer program that would track the behavior of 21,000 simulated neurons joined by more than 46 million connections. This neural network could take in two kinds of sensory information and produce two kinds of responses. And just like a human brain, if a new task came along too quickly, it could not respond until its router reset.

If Dehaene is correct, the brain’s inner traffic jam may actually reflect a cunning evolutionary compromise. We face new and unexpected decisions many times a day. We couldn’t possibly carry a separate network of neurons for every response to every possible situation. But we can learn rules, and we can use those rules to rearrange an all-purpose router. One of the deepest flaws in our brains, then, might be a by-product of one of its most impressive strengths.

Source: Discover Magazine

Nanocrystal conductors could lead to massive, robust 3-D storage

Wednesday, September 1st, 2010

When I was a child, watching various sci-fi movies, I was dreaming of how matter would be organized on those blocky crystals they showed off as storage for endless quantities of information. Well, it seems we’re getting there now:

Rice University scientists have created the first two-terminal memory chips that use only silicon, one of the most common substances on the planet, in a way that should be easily adaptable to nanoelectronic manufacturing techniques and promises to extend the limits of miniaturization subject to Moore’s Law.

Last year, researchers in the lab of Rice Professor James Tour showed how electrical current could repeatedly break and reconnect 10-nanometer strips of graphite, a form of carbon, to create a robust, reliable memory “bit.” At the time, they didn’t fully understand why it worked so well.

Now, they do. A new collaboration by the Rice labs of professors Tour, Douglas Natelson and Lin Zhong proved the circuit doesn’t need the carbon at all.

Jun Yao, a graduate student in Tour’s lab and primary author of the paper that appears today in the online edition of Nano Letters, confirmed his breakthrough idea when he sandwiched a layer of silicon oxide, an insulator, between semiconducting sheets of polycrystalline silicon that served as the top and bottom electrodes.

Applying a charge to the electrodes created a conductive pathway by stripping oxygen atoms from the silicon oxide and forming a chain of nano-sized silicon crystals. Once formed, the chain can be repeatedly broken and reconnected by applying a pulse of varying voltage.

The nanocrystal wires are as small as 5 nanometers (billionths of a meter) wide, far smaller than circuitry in even the most advanced computers and electronic devices.

“The beauty of it is its simplicity,” said Tour, Rice’s T.T. and W.F. Chao Chair in Chemistry as well as a professor of mechanical engineering and materials science and of computer science. That, he said, will be key to the technology’s scalability. Silicon oxide switches or memory locations require only two terminals, not three (as in flash memory), because the physical process doesn’t require the device to hold a charge.

It also means layers of silicon-oxide memory can be stacked in tiny but capacious three-dimensional arrays. “I’ve been told by industry that if you’re not in the 3-D memory business in four years, you’re not going to be in the memory business. This is perfectly suited for that,” Tour said.

Silicon-oxide memories are compatible with conventional transistor manufacturing technology, said Tour, who recently attended a workshop by the National Science Foundation and IBM on breaking the barriers to Moore’s Law, which states the number of devices on a circuit doubles every 18 to 24 months.

“Manufacturers feel they can get pathways down to 10 nanometers. Flash memory is going to hit a brick wall at about 20 nanometers. But how do we get beyond that? Well, our technique is perfectly suited for sub-10-nanometer circuits,” he said.

How Much Smaller Can Chips Go?

Wednesday, August 18th, 2010

Seven of the finest minds Intel can muster are lined up on stage, ready to take questions from a pack of visibly intimidated European journalists.

These are Intel fellows – the highest rank of technical merit afforded to the company’s engineers – whose CVs are stuffed with PhDs and patents in the places that most people put fillers such as “excellent typing skills” and “interest in badminton”.

Finally, one of the press pack plucks up the courage to ask a question. Is Moore’s Law – Gordon Moore’s legendary prediction that the number of transistors on a processor will double every two years – dead? One or two of the fellows chuckle politely, others are visibly irritated. Almost all are eager to grab the microphone and put the impertinent questioner straight.

One by one, they deliver measured and witty responses. “The number of people predicting the end of Moore’s Law doubles every two years,” quips the Scandinavian Tryggve Fossum, before American fellow Karl Kempf delivers a cutting dénouement. “The first microprocessor had 2,300 transistors, now we have processors with 2.3 billion transistors. That’s Moore’s Law. That’s what we do.”

Indeed, it’s what Intel’s been doing for more than 30 years. Now, the company is preparing to defy the laws of physics to “print” its next generation of chips. Chips so crammed with transistors that the machinery is working with sub-atomic precision to make them.

But when you’re already working with transistors a fraction of the size of a virus cell, how much further can you push the miniaturisation before the plucky journalist’s predicted demise of Moore’s Law comes true?

The complexity of a modern processor is almost beyond comprehension. A working 1GHz core on ARM’s latest Cortex A9 processors occupies less than 1.5mm2, using the 65nm production process. To put that into perspective: a nanometre is a billionth of a metre, which means a nanometre is to a tennis ball what a tennis ball is to the planet Earth.

“Microscopic” doesn’t even come close.

Yet, if that sounds impossibly fiddly, Intel’s latest Core processors are built using a 32nm process. While you might just be able to spot one of ARM’s cores with the naked eye, to see one of the 32nm transistors on an Intel chip, you would need to enlarge the processor to beyond the size of a house.

Working at such precision is an enormous challenge for chip manufacturers. As processes are refined every two years to keep Moore’s Law alive, Intel’s engineers are forced to show remarkable levels of ingenuity to keep processors ticking. “The end has been predicted many times, and we have shown this is not the case,” said Intel fellow Jose Maiz. “At least, not yet.”

Read full article: http://www.pcpro.co.uk