Technut News

The video below shows a scenario that is likely to become real as industrial robots improve: a human and a robot work together to assemble an object from its parts. But in the clip from the University of Minho, Portugal, not everything is going to plan. The human gets a stern warning from the robot that they are doing it wrong.

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I hope Intel warned the Luddites and pessimists away at the door, because the chipmaker had a lot of bullish statements Thursday about its belief that computers will become smarter than humans.

At the Intel Developer Forum here, Intel Chief Technology Officer Justin Rattner showed off a number of technologies in computing, robotics, and communication that he cited as evidence that Ray Kurzweil’s concept of “singularity,” when machine intelligence surpasses human intelligence, is impending. Demonstrations spotlighted the wireless transmission of electrical power, dextrous robots with new sensory abilities, a direct interface to the brain, programmable materials that can be used for shape-shifting devices such as resizable cell phones, and silicon photonics that enables chips to communicate with photons rather than electrons.

“We’re making steady progress toward Ray Kurzweil’s singularity,” Rattner said.

Intel of course remains at its heart a chipmaker, and Rattner began with a brief tour, assisted by Mike Garner, senior technologist for Intel’s emerging materials group, of various successors to the current complimentary metal oxide semiconductor (CMOS) process used to make processors. Future ideas that pack ever more computing capacity into a given volume include spintronics, quantum computing, carbon nanotubes.

It’s good to see a big name such as Intel take seriously Kurzweil’s ideas on accelerating progress, the Singularity, etc.

The more people are working towards a common goal, the better.

Researchers in Leipzig have demonstrated software designed for robots that allows them to “learn” to move through trial and error.

The software mimics the interconnected sensing and processing of a brain in a so-called “neural network”.

Armed with such a network, the simulated creatures start to explore.

In video demonstrations, a simulated dog learns to jump over a fence, and a humanoid learns how to get upright, as well as do back flips

Ralf Der at the Max Planck Institute for Mathematics in the Sciences has also applied the software to simulated animals and humans.

The only input to the network is the types of motion that the robot can achieve; in the case of a humanoid, there are 15 joints and the angles through which they can move. No information about the robot’s environment is given.

The network then sends out signals to move in a particular way, and predicts where it should end up, based on that movement.

If it encounters an obstacle such as itself, a wall or the floor, the prediction is wrong, and the robot tries different moves, learning about itself and its environment as it does so.

“In the beginning, we just drop a robot into a space. But they don’t know anything, so they don’t do anything,” Professor Der said. The neural network eventually picks up on electronic noise, which causes small motions.

It eventually tries larger motions as it learns about its range of movement. “It’s like a newborn baby—it doesn’t know anything but tries motions that are natural for its body. Half an hour later, it’s rolling and jumping,” Professor Der said.

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A device that reads glucose levels and delivers insulin may be close at hand.

Today, people with diabetes have a range of technologies to help keep their blood sugar in check, including continuous monitors that can keep tabs on glucose levels throughout the day and insulin pumps that can deliver the drug. But the diabetic is still responsible for making executive decisions–when to test his blood or give himself a shot–and the system has plenty of room for human error. Now, however, researchers say that the first generations of an artificial pancreas, which would be able to make most dosing decisions without the wearer’s intervention, could be available within the next few years.

Type 1 diabetes develops when the islet cells of the human pancreas stop producing adequate amounts of insulin, leaving the body unable to regulate blood-sugar levels on its own. Left unchecked, glucose fluctuations over the long term can lead to nerve damage, blindness, stroke and heart attacks. Even among the most vigilant diabetics, large dips and surges in glucose levels are still common occurrences. “We have data on hand today that suggests that you could get much better diabetes outcomes with the computer taking the lead instead of the person with diabetes doing it all themselves,” says Aaron Kowalski, research director of the Juvenile Diabetes Research Foundation’s Artificial Pancreas Project.

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This is the giant rescue robot called T-52 Enryu (”Rescue Dragon”). It has a bulldozer-like base and a 5-meter long arms that can lift cars stuck in the snow. In the tests T-52 Enryu showed off its avalanche prevention skills by removing accumulated snow from the edge of a cliff. The robot also demonstrated its ability to extract a car buried under a bank of snow.”

T-52 Enryu stands 3.45 meters tall and weighs 5 tons.

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Meet Gordon, probably the world’s first robot controlled exclusively by living brain tissue.

Stitched together from cultured rat neurons, Gordon’s primitive grey matter was designed at the University of Reading by scientists who unveiled the neuron-powered machine on Wednesday.

Their groundbreaking experiments explore the vanishing boundary between natural and artificial intelligence, and could shed light on the fundamental building blocks of memory and learning, one of the lead researchers told AFP.

“The purpose is to figure out how memories are actually stored in a biological brain,” said Kevin Warwick, a professor at the University of Reading and one of the robot’s principle architects.

Observing how the nerve cells cohere into a network as they fire off electrical impulses, he said, may also help scientists combat neurodegenerative diseases that attack the brain such as Alzheimer’s and Parkinson’s.

“If we can understand some of the basics of what is going on in our little model brain, it could have enormous medical spinoffs,” he said.

Looking a bit like the garbage-compacting hero of the blockbuster animation “Wall-E”, Gordon has a brain composed of 50,000 to 100,000 active neurons.

Once removed from rat foetuses and disentangled from each other with an enzyme bath, the specialised nerve cells are laid out in a nutrient-rich medium across an eight-by-eight centimetre (five-by-five inch) array of 60 electrodes.

This “multi-electrode array” (MEA) serves as the interface between living tissue and machine, with the brain sending electrical impulses to drive the wheels of the robots, and receiving impulses delivered by sensors reacting to the environment.

Because the brain is living tissue, it must be housed in a special temperature-controlled unit — it communicates with its “body” via a Bluetooth radio link.

The robot has no additional control from a human or computer.

From the very start, the neurons get busy. “Within about 24 hours, they start sending out feelers to each other and making connections,” said Warwick.

“Within a week we get some spontaneous firings and brain-like activity” similar to what happens in a normal rat — or human — brain, he added.

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Advances like these are why I think superior artificial intelligence will be built in the next decade or two.

How many of you expected to see this happening in 2008?

If you didn’t see a robot with a biological brain coming, then why even bother to hold on to the idea that superior AI won’t be possible for hundreds of years?

HIV can be stopped dead in its tracks using a revolutionary technique for “silencing” genes, a study has shown. The discovery raises the possibility of a treatment for HIV that does not involve potentially toxic anti-viral drugs.

Scientists have found that RNA interference – where genes are artificially silenced using a natural molecular switch in the cell – can inhibit the replication of HIV in human blood cells.

Professor Premlata Shankar of Texas Tech University, who carried out the work when she was at Harvard Medical School in Boston, said: “RNA interference has great potential as an antiviral treatment… We think it has real promise, but there is a lot more to be done.”

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At Intel Corp., just passing its 40th anniversary and with myriad chips in its historical roster, a top company exec looks 40 years into the future to a time when human intelligence and machine intelligence have begun to merge.

Justin Rattner, CTO and a senior fellow at Intel, told Computerworld that perhaps as early as 2012 we’ll see the lines between human and machine intelligence begin to blur. Nanoscale chips or machines will move through our bodies, fixing deteriorating organs or unclogging arteries. Sensors will float around our internal systems monitoring our blood sugar levels and heart rates, and alerting doctors to potential health problems.

Virtual worlds will become increasingly realistic, while robots will develop enough intelligence and human-like characteristics that they’ll become companions, not merely vacuum cleaners and toys.

Most aspects of our lives, in fact, will be very different as we close in on the year 2050. Computing will be less about launching applications and more about living lives in which computers are inextricably woven into our daily activities.

“What we think of as a computer and what we think of as IT, in general, is likely to change,” said Rattner, who has been at Intel for 35 of the company’s 40 years. “The intelligent systems will move from being information systems to intelligent systems that will carry out a whole variety of tasks that we just won’t think of as computing tasks…. The technology will find its way into so many things we do, and we won’t even think about it. The explicit way we’ve done computing in the past will be there, but it will be a very small subset of what we’ll be doing.”

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How can you predict that the merger will happen in 40 years, while also saying it will start in 2012.

If it starts in 2012, I’d say we’re going to get ‘there’ one helluva lot quicker than 40 years.

Performance

• Scanning the cube: 1 minute
• Calculating a solution: 20 - 40 seconds
• Executing the moves: 1 - 5 minutes. Average 4.5 minutes (60 faceturns)
• Average total time: 6 minutes

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