Semiconductors are building blocks of Technology and gadgets and the limiting factor of Silicon chips has always been heat dissipation: More efficiently we can remove heat from semiconductor chips, higher clock they can run on.

LASERs are here to save the future, as they pave way to building most effective, efficient means of cooling Semiconductors.

How LASER Cooling works

Ironically, cooling is observed by actually heating the material. Using lasers, researchers cooled membrane fluctuations to minus 269 degrees C with fractions of energy utilization.

“In experiments, we succeeded in achieving a new and efficient cooling of a solid material by using lasers. We have produced a semiconductor membrane with a thickness of 160 nanometers and an unprecedented surface area of 1 by 1 millimeter,” explained Koji Usami, associate professor at Quantop at the Niels Bohr Institute. “In the experiments, we let the membrane interact with the laser light in such a way that its mechanical movements affected the light that hit it. We carefully examined the physics and discovered that a certain oscillation mode of the membrane cooled from room temperature down to minus 269 degrees C, which was a result of the complex and fascinating interplay between the movement of the membrane, the properties of the semiconductor and the optical resonances.

What is worth noting here is that even though the membrane is getting a little bit warmer overall, the membrane is cooled at a certain oscillation and the cooling can be controlled with laser light. So it is cooling by warming! Laser cooling of atoms has been work in progress for years in the institute and they have successfully cooled gas clouds of cesium atoms down to near absolute zero i.e. minus 273 degrees C – using focused lasers – while creating entanglement between two atomic systems.

This is like rocket science, but they make it sound so easy.

What it means for Science & Computing

It Opens entirely new possibilities for a new field of Science called Optomechanics, which is the interaction between light, and a mechanical motion. Optomechanics could pave the way for cooling components in quantum computers, computers of the Future.

This invention could also lead to the development of new sensors for electric current and mechanical forces. Such cooling in some cases could replace expensive cryogenic cooling, which is used today and could result in extremely sensitive sensors that are only limited by quantum fluctuations. The possibilities are endless, you could hold a supercomputer  without melting your hands in the future, thanks to Laser cooling.

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Sound can do one more great thing, it can heal various problems that were previously treated using surgeries only.

Imagine having a surgery with no knives involved. Yoav Medan shares a technique that uses MRI to find trouble spots and focused ultrasound to treat such issues as brain lesions, uterine fibroids and several kinds of cancerous growths.

This innovation comes from convergence of two non-technologies:

• Force of Ultrasound and
• Vision enabled by magnetic resonance imaging.

Ultrasound is no longer just a tool of detecting structures, it can actually be used to shave away parts for treatment. Focussed Ultrasound can be quiet powerful and has endless value in modern medical treatments.

You know all about imaging, right, ultrasound imaging. And you know also about lithotripsy — breaking kidney stones. But ultrasound can be shaped to be anything in between, because it’s a mechanical force. Basically, it’s a force acting on a tissue that it transverses. So you can change the intensity, the frequency, the duration, the pulse shape of the ultrasound to create anything from an airbrush to a hammer.

Think about the amount of suffering that is saved from patients undergoing noninvasive surgery, and also the economical and emotional burden removed from their families and communities and the society at large.

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We’ve already seen it dance, sing and read minds. The new ASIMO is faster, skinnier and more ergonomic than any Robot ever made. It can walk, run backward and forward, run on a single leg, twist and rip the the bottle caps and what not.  In fact, Honda claims that its bot is now less “automated” than it is “autonomous” — all thanks to new behavior control technology that allows it to move and make decisions on its own, independent of human operators.

It can rapidly process information about its environment, and undertand the dynamics of the situation before making the next move. ITs even smart enough to combine long- and short-term sensor data to predict human movements and automatically recognize voices or gestures.This is what makes it co-exist with Humans, naturally.

Structure wise, its more flexible and capable. It can now run at 9 km/h. Its hands are now more dexterous than ever, thanks to new independent finger control functions, this allows it to execute delicate tasks, with ease.

Checkout more Robotics posts.

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Microsoft researchers have come up with a way to make devices sensitive to touch input through fabric — for silencing a phone or even entering text without taking the device out of a pocket or bag.

PocketTouch uses a custom sensor on the back of a smartphone that can detect multitouch gestures even through heavy fleece or a jacket pocket. The The first prototype is complete and we would see a demonstration sometime soon.

Microsoft uses “orientation-defining unlock gesture” that essentially tells the device which way is up, thereby removing the problem where device can be in a different orientation inside pockets. Grid of touch sensors can detect finger strokes through cloth and hence make it possible to have a specific unlock gesture that reorientates the screen each time you use it – avoiding the need to flip your phone upside down before using the interface.

OmniTouch

OmniTouch makes any surface touch compatible. OmniTouch uses a a pico projector and a depth camera (like Kinect) to let people interact with programs projected onto their skin or other surfaces. Users can define the size and location of their own interfaces, or let the system decide the best choice of display.

The researcher calls it a “mega Kinect hack” and an extension of his previous device which could only work on skin. While the prototype device is quite bulky, soon it would be possible to reduce the size of the equipment to the size of matchbox.

Both systems are being presented this week at the User Interface Software and Technology symposium in Santa Barbara, California.

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Scientists at UC Berkeley have developed a system to capture visual activity in human brains and reconstruct it as digital video clips. Soon, this advancement would make it possible to record and reconstruct your own dreams on an ordinary computer.

Its not April 1st, and this is happening for Real. Professor Jack Gallant—UC Berkeley neuroscientist and coauthor of the research said today:

“this is a major leap toward reconstructing internal imagery. We are opening a window into the movies in our minds.”

How Brain Image Mapping Works
They used three different subjects for the experiments— They were kept under functional Magnetic Resonance Imaging system for hours at a time. Subjects were prone to two different groups of  Hollywood movie trailers as the fMRI system recorded the brain’s blood flow through their brains’ visual cortex. These magnetic readings were then  fed into a computer program in which they were divided into three-dimensional pixels units called voxels (volumetric pixels). This process effectively decodes the brain signals generated by moving pictures, connecting the shape and motion information from the movies to specific brain actions.

Computer learned more and more about how the visual activity presented on the screen corresponded to the brain activity and finally was able to create a decent correlation between video being shown to suspect and magnetic radiation being captured from human brain.

Machine Learning: The computer analyzed 18 million seconds of random YouTube video, building a database of potential brain activity for each clip. From all these videos, the software picked the one hundred clips that caused a brain activity more similar to the ones the subject watched, combining them into one final movie. Although the resulting video is low resolution and blurry, it clearly matched the actual clips watched by the subjects.

This is how it learns: It analyzes how the brain reacts to certain stimuli, compares it to the brain reactions to the 18-million-second palette, and picks what more closely matches those brain reactions. Then it combines the clips into a new one that duplicates what the subject was seeing. Notice that the 18 million seconds of motion video are not what the subject is seeing. They are random bits used just to compose the brain image.

The Result: Given a big enough database of video material and enough computing power, the system would be able to re-create any images in your brain.

As of now, the resulting quality is not good, but the potential is enormous.

Our natural visual experience is like watching a movie. In order for this technology to have wide applicability, we must understand how the brain processes these dynamic visual experiences.

The Future of Brain Recording

Imagine that. Capturing your visual memories, your dreams, the wild ramblings of your imagination into a video that you and others can watch with your own eyes. Perhaps one day you would be able to wakeup in the morning and playback your Dream.

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Festo, a bionic design company, has come up with a breakthrough — World’s first Robot that Flies like an Actual Bird. The company has invested a lot of time studying the natural flight of a bird. The wingspread, the angles, the thrust, the art and engineered all of them to a masterpiece which they call it as “SmartBird“.

SmartBird is an ultralight but powerful flight model, weighing just 450grams, including batteries. This bionic technology bird can start, fly and land autonomously – with no additional drive mechanism. It can twist at specific angles, jut like a bird can. Active articulated torsional drive unit in combination with a complex control system attains an unprecedented level of efficiency in flight operation.

SmartBird @ TED

SmartBird is energy efficient at 25 wattts during take-offs and nearly 16watts during normal flying. However, the plan is to make it even more efficient. So far, it had been made possible with minimal use of materials and the extremely lightweight construction with components like Carbon-fiber.

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Often non-tech users ask this question, “If a car, truck, train, engines ALWAYS work in the expected way, why can’t software?” . The answer lies in the complexities of the logics, software engineering is packed with way many larger number of permutations and combinations than any other system.

“For critical operations, I can’t come anywhere close to that reliability with the laptops,” Klausman said, technical manager for United Space Alliance for the backup flight system and multifunction electronic display subsystem. “They are wonderful items, but they are susceptible to radiation particles, they are susceptible to badly written software. I could put five laptops on board and all five would suffer radiation upsets within the first day.”

However, for one field the software engineering has never failed: Space shuttles, other space programs.

Perfection is a need

When you have to lift a 120-ton space shuttle that is powered by a 4 million pounds of rocket fuel, you cant take chances. A single mistake can cost billions, there’s no chance for a blunder. For years, computers had been driving all those space giants, and so far, we haven’t seen a failure that was caused by computers. Rigorous testing, realtime simulations and top notch development have made them robust.

Computers at work @ Space shuttles

Four identical computers, running identical software, pull information from thousands of sensors, make hundreds of decisions within a milli-second, collectively vote on every decision before making the move. And there is a fifth one to take control incase any of the four misbehave or disfunction.

Pre-check: Just 6 seconds before the launch, computers probe the pressures, pumps, and temperatures and make the call whether its all safe to fireup the engines and take a flight. Each engine  firesup precisely 160 milliseconds apart. Computer waits till the engines create enough thrust of the level of  one million pounds and you see those bright blue flames burn the hell out of super pure fuel.

Solid rocket boosters kick in when it Time zero, in under a second, thrust goes upto 6.6 million pounds, this is the time when computers unbolt the shuttle from the ground and lifts the massive mammoth into space. Throughout the shuttle launch process, no human interferes, no one presses even a single button, its too risky to trust humans, for which humans are prone to err.

The software throttles the engines to make sure the craft doesn’t accelerate too fast. It keeps track of where the shuttle is, orders the solid rocket boosters to fall away, makes minor course corrections, and after about 10 minutes, directs the shuttle into orbit more than 100 miles up. When the software is satisfied with the shuttle’s position in space, it orders the main engines to shut down — weightlessness begins and everything starts to float and it propels occasionally incase it sees a trouble with the path/trajectory.

No Crashes, no errors, no bugs

This software never crashes, no reboots needed and finding a bug is a distant dream. It is perfect, perfection we have achieved in mechanical, electronics engineering.

The proof comes from stats: The last three versions of the space program were each 420,000 lines of code and had no more than one error each.

However, commercial applications of this complexity would have thousands of bugs.

The Brains behind software perfection

Such NASA software is work of 260 men and women who have learned to deliver perfection. This software team is lead by Lockheed Martin Corps space shuttle division. Their software controls a $4 billion shuttle,and they understand the responsibility well.

NASA knows how good the software has to be. Bill Pate, one of the software engineer for the company has worked on it for last 22 years, says that these guys take things seriously, “If the software isn’t perfect, some of the people we go to meetings with might die.”

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Till date, world’s thinnest smartphone was crowned to Samsung Galaxy SII, but the days are not far when such smartphones would go even thinner. The new contendor is flexible enough to fold like a paper.

The e-paper prototype PaperPhone sports a 3.75-inch thin-film display. Its s smartphone and hence can do everything you would expect it to do: make calls, Read books, and Play music. The rest of the phone’s hardware is situated alongside the non-bendablepart, which is also surprisingly thin.

Queen’s Human Media Lab director says, “This is the future. Everything is going to look and feel like this within five years”.

However, the prototype is based on e-ink technology, the same technology that powers Amazon’s kindle ebook readers. It can be operated by bending the corners to turn a page, squeezing to make a call, and even written on with a pen. Were you expecting more ?

The research institute, Vertegaal along with MERG claims that the larger versions of the displays could eliminate paper and printers from offices. This is possible because E-ink displays require no power until the information on screen is refreshed.

So this is flexible, but how much would it cost?  It’s a $7,000 prototype, but the final product would be ultra affordable.

And yes, the prototype uses Android. Of course its not ready for the primetime, but we grab a fairly good idea of where we are heading.

Watch the thinnest bendable phone in action:

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We love to see Microsoft Research’s Future vision with their occasional demos. Their latest idea revolves around Future Home Vision, a playground to demonstrate the potential of the future homes.

Microsoft has taken its surface technology and has integrated it into real life. Previous versions of surface were way too commercial to be used at normal user’s homes. From charging plates to connected surfaces that talk even to your wrist watch, its all pretty cool.

Watch the Future home Vision from the Microsoft Capmus Tours

It might look little fancy today but it would sure be invading our homes over the next decade. Those interactive wallpapers sure would come usefull tomorrow, you wont need one side facing TVs or computer screen any longer. And if Super AMOLED plus technology goes further, you wont need windows to see the scenic beauty.

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In August 2010, they found their home in Abbottabad, a suburb which is less than 40 miles from the Islamabad, the capital of Pakistan. Everything about Osama’s compound was extraordinarily unique which brought more and more attention. It was not just 8 times larger than the other homes in the area, it had a lot of physical security in place with 12 to 18 feet walls, guarded by two giant security gates.

Strangely enough, there was barely any communication between this compound and the outer world. There were little to no social activity and had strange forensics. It preferred burning its trash, and there were no open windows for fresh air to come in. Despite the gigantic and costly architecture, it had no means of communications: No internet, no phones.

The secret agencies and the army had no concrete proof, but everything leaded to the same conclusion. No one could afford and match the semantics of this place other than the man himself. Whole of this information was not shared with anyone, and was limited to a small group of people, which made the attack possible.

Background Intelligence (Technology Used to Track Osama)

All of this has a longer history. Joint Special Operations Command or JSOC had been in command for years trying to find tits and bits of information and compile them into something more concrete.

The way JSOC solved this problem still remains a top secret, but it is said that commandos learned basic criminal forensic techniques and then used highly advanced and still-classified technology to transform bits of information into actionable intelligence. One way they did this was to create forward-deployed fusion cells, where JSOC units were paired with intelligence analysts from the NSA and the NGA. Such analysis helped the CIA to establish, with a high degree of probability, that Osama bin Laden and his family were hiding in that particular compound.

These technicians could “exploit and analyze” data obtained from the battlefield instantly, using their access to the government’s various biometric, facial-recognition, and voice-print databases. These cells also used highly advanced surveillance technology and computer-based pattern analysis to layer predictive models of insurgent behavior onto real-time observations.

The military has begun to incorporate such techniques across the services and improvements are on their way in areas where intelligence is gathered, analyzed, and utilized.

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Morgan Quigley’s low-cost Robot possess 7 degree-of-freedom (7-DoF). It possess a series elastic actuator (SEA) arm that costs way under $5,000  The hand possess shape deposition manufacturing (SDM) that gives it  reflexes to catch flying (tossed) balls.

Morgan calls it A Low-Cost Compliant 7-DOF Robotic Manipulator [PDF] that costs just $4135. The arm is made from lasercut plywood, and is powered by four stepper motors in the base and three small dynamixel servo motors in the lower arm. This is done via rubber tubes that get squished between two plates, as can be seen in the video. The arm is pretty light that makes it human-safe. The arm moves at 1.5m/s carrying a 2kg payload. The arm is used to demonstrate pancake cooking (pouring batter, flipping pancakes), using the intrinsic compliance of the arm to aid in interaction with objects.

The mechanism of catching the ball is based on inputs taken from multiple sensors. It uses accelerometers and magnetometers to detect the wearer’s pose. It then calculates the location of the thrower’s hand and inverse kinematics (tracking trajectory) are used to get the robot’s gripper to track that location. The robot is powered by the Robot Operating System (ROS).

Watch the Stanford’s creation in action:

Rollin Justin Robot, a much faster and mature version based on similar concept

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The basic principle behind quantum computation is simple. Instead of silicon transistors, quantum properties are used to represent data and perform operations on these data. Bits  from current generation computers are replaced with two-state Qubits.

April 18th, 2011 would be considered the first remarkable achievement in the history of quantum computers. For years to come, this day would be recalled for making it possible to transfer a complex set of quantum data in light form. Researchers have achieved a breakthrough in quantum communications and computing using a teleporter and a paradoxical cat.The breakthrough is the first-ever transfer, or teleportation, of a particular complex set of quantum information from one point to another, opening the way for high-speed, high-fidelity transmission of large volumes of information, such as quantum encryption keys, via quantum communications networks.

Before this day, the data transmitted was slow and faced data losses.

Teleportation is the phenomena of transferring Quantum information from one location to another using traditional communication media like lasers over Optical fibers using the machine which is called “the teleporter“.

The research is a work of the Australian Defence Force Academy (ADFA), and University of Tokyo researchers.

“One of the limitations of high-speed quantum communication at present is that some detail is lost during the teleportation process. It’s the Star Trek equivalent of beaming the crew down to a planet and having their organs disappear or materialize in the wrong place.

This research is invaluable as for the first time, it enables us to quickly and reliably move quantum information around.

This process means we will be able to move blocks of quantum information around within a computer or across a network, just as we do now with existing computer technologies. The speeds hence achieved would be hundreds of times faster than current generation computers that rely on slow silicon transistors, consuming only the fractions of power.

via unsw

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Ruthless Software Patents are Evil

The tech world has recently seen remarkable number of instances driven by patent litigations, often involving low-quality software patents, which threatens to decelerate innovation. The problem with it is that most Patents are held with people/companies that have never actually materialized any of it. The patent system  should instead concentrate on rewarding patents to those innovators who create the most useful applications from ideas, for the good of the society.

Google is taking a step here to lighten things up, both in the best interest of the company’s products and for its partners. Google has bought all of Nortel‘s remaining patents and applications for $900 Million for a total of 6,000 patents covering wired, wireless and digital communications technologies. Google would get patents for wireless, 4G, data networking, optical, voice, semiconductors and other telecom areas.

What would Google Do with Telecom patents? Google would use these patents to innovate in its own products like Android, Chrome and let anyone in the Open Source community play with all of it. In other words, these patents will now be owned by everyone, thereby not restricting in sort of innovation, which could have been stuck for years.

Google adds:

Today, Nortel selected our bid as the “stalking-horse bid,” which is the starting point against which others will bid prior to the auction. If successful, we hope this portfolio will not only create a disincentive for others to sue Google, but also help us, our partners and the open source community—which is integrally involved in projects like Android and Chrome—continue to innovate. In the absence of meaningful reform, we believe it’s the best long-term solution for Google, our users and our partners.

O yeah! Openness, the way to go. But what would Google do with the non-related Telecom patents? Build another Gigabit fibre ISP? We would have to wait for that.

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Researchers at UaC & University of Washington have spent years trying to fin security flaws in modern cars which are controlled via mini-computer systems and so far they have identified a bunch of security flaws in cars.

The most interesting attacks were triggered via car’s Bluetooth and cellular network systems, or through malicious software in the diagnostic tools used in automotive repair shops.

The one that interested us was on the Car stereo. By adding extra code to a digital music file, they were able to turn a song burned to CD into a Trojan horse. When played on the car’s stereo, this song could alter the firmware of the car’s stereo system, giving attackers an entry point to change other components on the car. This type of attack could be spread on P2P file-sharing networks without arousing suspicion.

“It’s hard to think of something more innocuous than a song,” said Stefan Savage, a professor at the University of California.

The same team had achieved wide Car hacks in experiments in which they were able to kill the engine, lock the doors, turn off the brakes and falsify speedometer readings on a late-model car of 2009. In that experiment, they had to plug a laptop into the car’s internal diagnostic system in order to install their malicious code. In 2010, team also hacked Cars from wireless tyre sensors.

But the latest research, is about remotely controlling cars. The attacks over Bluetooth, the cellular network, malicious music files and via the diagnostic tools used in dealerships were all possible, if difficult to pull off, Savage said. “The easiest way remains what we did in our first paper: Plug into the car and do it,” he said.

Car Hacking: Possibilities & Future

Now, thieves could instruct cars to unlock their doors and report their GPS coordinates and Vehicle Identification Numbers to a central server. “An enterprising thief might stop stealing cars himself, and instead sell his capabilities as a service to other thieves,” Savage said. A thief looking for certain kinds of cars in a given area could ask to have them identified and unlocked, he said.

With the high technical barrier to entry, the researchers believe that hacker attacks on cars will be very difficult to pull off, but they say they want to make the auto industry aware of potential problems before they become pervasive.

Another problem for would-be car thieves is the fact that there are significant differences among the electronic control units in cars. Even though an attack might work on one year and model of vehicle, it’s unlikely to work on another. ”

So far, carmakers have been very receptive to the university researchers’ work and appear to be taking the security issues they’ve raised very seriously.

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Every year, millions die in a car accident, worldwide. We’ve little intelligence to reduce this number, and subsequent efforts have failed to reduce the agony. Google has jumped into the stream to find a solution last year, and This year at TED 2011, we see first public demos.

At the TED conference 2011, the folks from Search Engine Land got handson experience with the world’s first Truly driverless car that can drive without any assistance on any road. Their experience was one of its kind, the car drove itself around a pretty aggressive closed circuit.

Looks like Google is right on track with their research and with further development it can only get better. It looks like humans probably won’t have to deal with parking woes in the future – just get off and let the car park itself.

Check out video footage of the drive after the break:

Here’s a Refresher video from 2010:

Latest Handson (TED 2011) With Google’s Self-driving Car:

How Self-driven Cars Work

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Google Goggles is a Visual  search engine for mobile phones which allows users to take a picture of anything, such as a landmark, or a celebrity and then run a search for what/who they are.

Google wishes to expands its plans further when they acquired like.com, a visual search engine. Prior to Google’s acquisition, Like.com helped online shoppers search site called Riya which used facial recognition technology to search images that users had uploaded and tagged. The latest patent filed by Google: User Interface for Presenting Search Results for Multiple Regions of a Visual Query suggests that Google’s visual search for smartphones might be evolving into something that’s totally new and powerful.

Another Google patent, Facial Recognition With Social Network Aiding, describes facial recognition searches for “one or more likely names” of the people in the image based upon “communications applications, social networking applications, calendar applications, and collaborative applications” to create a list of possible identities for each person. The patent description also mentions that if the photo is tagged with a person’s name, “that picture might be used in future facial recognition queries to recognize the person.”

After receiving the visual query with one or more facial images, the system identifies images that potentially match the respective facial image in accordance with visual similarity criteria. Then one or more persons associated with the potential images are identified. For each identified person, person-specific data comprising metrics of social connectivity to the requester are retrieved from a plurality of applications such as communications applications, social networking applications, calendar applications, and collaborative applications. An ordered list of persons is then generated by ranking the identified persons in accordance with at least metrics of visual similarity between the respective facial image and the potential image matches and with the social connection metrics. Finally, at least one person identifier from the list is sent to the requester.

Benefits aside, Google could face serious privacy allegations. In regards to privacy, Google has several possible scenarios: to send only one of the “identifiers” to the person searching; to possibly allow only the person identified to make the photo public, or to send a request after a person is positively identified, asking if the image can be a face search result for other people’s visual queries from within their social network, which is kind of tricky as Google would need partnership with Twitter & Facebook for this to work. Its not hard to get the former but latter is what we doubt.

Okay, now that we know Google is serious about social facial recognition, how can we confirm is targetting mobile platforms like Android & iPhone? Coincidently, “David Petrou, Andrew Rabinovich, and Adam Hartwig” who worked on Google Goggles, are the patent filers.

What would make it better is that we would see some competition as well.  Viewdle is also working on mobile facial recognition that works on the fly, and might help “government stalkers.” by allowing users to tag and save “faceprints” of people, and “then share the faceprint of them with other Viewdle users so they can recognize that person too!” The photosharing privacy settings are integrated with Facebook privacy settings.

Viewdle in action:

Viewdle – Photo and Video Face Tagging from Viewdle on Vimeo.

There are many privacy issues which need to be addressed here before they can make a public appearance. But one field where they would work without obligations would be with Dictators and governments who are already identifying people based upon real names and photos posted in social media.

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You might be surprised by that technology till date couldn’t actually create a device that could Transmit and receive at the same time wirelessly – aka Full Duplex communication. You might argue that your GSM/CDMA phone, your wifi already does that. But if you jump into the details of how these wireless networks operate, you will realize they use Time division multiplexing or a similar technique to make it simulate a full duplex communication. TDM divides the time into slots (of the order of ms) which are used for Transmit and followed by Receive, both in separate slots, i.e. at a different time. Because these time slots are as large as 2-10 milliseconds, they feel to be happening at the same time.

Radio traffic can flow in only one direction at a time on a specific frequency, hence the frequent use of “over” by pilots and air traffic controllers, walkie-talkie users and emergency personnel as they take turns speaking.

Stanford‘s engineering labs have discovered new ways of avoiding wireless interference, and hence make it to possible to have full duplex communication even in a noisy environment.  Electrical engineering graduate students, Jung Il Choi, Mayank Jain and Kannan Srinivasan, began working on a new approach when they came up with a seemingly simple idea. What if radios could do the same thing our brains do when we listen and talk simultaneously.

A newfangled wireless technology developed is proving that signals can indeed be sent and received at the same time. Typical wireless signals have to take turns when it comes to listening and transmitting. As an example, it’s impossible for a WiFi router to “shout” out signals while also being intelligent enough to quiet its own voice in order to hear “whispers” from a connected device.

Their main roadblock to two-way simultaneous conversation was this: Incoming signals are overwhelmed by the radio’s own transmissions, making it impossible to talk and listen at the same time.

The breakthrough came when researchers found that radios could be tweaked to filter out the signal from its own transmitter. This phenomena has been derived from noise-canceling headphones, which cancel out the sound waves from surroundings.

“When a radio is transmitting, its own transmission is millions, billions of times stronger than anything else it might hear [from another radio],” Levis said. “It’s trying to hear a whisper while you yourself are shouting.”

If a radio receiver could filter out the signal from its own transmitter, weak incoming signals could be heard. “You can make it so you don’t hear your own shout and you can hear someone else’s whisper,” Levis said.

This technology can help overcome various current challenges like overcoming a major problem with air traffic control communications. With current systems, if two aircraft try to call the control tower at the same time on the same frequency, neither will get through. Levis says these blocked transmissions have caused aircraft collisions, which the new system would help prevent.

If this can be packaged into a commercially viable platform, it could instantly double the amount of information sent over existing networks, and on an even grander scale, it could allow airplanes to radio into control towers simultaneously.

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United States is now owns the fastest SuperComputer, pushing China to the second place, of course leaving Google Plex aside. Very recently, China had pushed Cray XT5 Jaguar to the Rank 2. Although, you can Build yourself Supercomputers, it does cost millions when its built as a nation’s pride.

The Tianhe-1A, meaning Milky Way, was designed by the National University of Defense Technology (NUDT) in China. It is the work of 200 scientists, that makes groundbreaking performance record of 2.507 petaflops, or quatrillion calculations per second, making it the fastest system in the world today. Ordinarily the computer runs at 563.1 teraflops, or trillion calculations per second.

Lets welcome Blue Gene/Q, aka “Mira”,  IBM’s latest and greatest supercomputer boasting a ten-petaflops of raw power. Mira is capable of running programs at ten quadrillion calculations a second.

To give you an idea of how powerful this supercomputer is IBM’s statement tries to explain it:

“If every man, woman and child in the United States performed one calculation each second, it would take them almost a year to do as many calculations as Mira will do in one second.”

Where would the Most Powerful SuperComputer be used?

Mira would be employed with US Department of Energy’s Argonne National Laboratory, where it’ll be used to tackle 16 projects in particular that were drawn from a pool of proposals to gain access to her capabilities. We’re told that these include a range of initiatives — from reducing energy inefficiencies in transportation and developing advanced engine designs to spurring advances in energy technologies — and in time, it could lead to exascale-class computers “that will be faster than petascale-class computers by a factor of a thousand.”

Here are notes from IBM’s press release:

WASHINGTON – 08 Feb 2011: IBM (NYSE: IBM) today announced that the U.S. Department of Energy’s (DOE) Argonne National Laboratory will use IBM’s next-generation Blue Gene supercomputer to enable significant advances in areas such as designing ultra-efficient electric car batteries, understanding global climate change and exploring the evolution of our universe.

The 10-petaflop IBM Blue Gene/Q supercomputer, named “Mira”, will be operational in 2012 and made available to scientists from industry, academia and government research facilities around the world.

“Computation and supercomputing are critical to solving some of our greatest scientific challenges, like advancing clean energy and understanding the Earth’s climate,” said Rick Stevens, associate laboratory director for computing, environment and life sciences at Argonne National Laboratory. “Argonne’s new IBM supercomputer will help address the critical demand for complex modeling and simulation capabilities, which are essential to improving our economic prosperity and global competitiveness.”

Argonne to use IBM Blue Gene/Q

Argonne National Laboratory will use IBM’s next-generation Blue Gene/Q supercomputer to stoke economic growth and improve U.S. competitiveness for such challenges as designing electric car batteries, understanding climate change and exploring the evolution of the universe. The 10 petaflop system, named “Mira”, will be twice as fast as today’s fastest supercomputer, providing a strong science and technology engine that will fuel national innovation. Argonne is one of the U.S. Department of Energy’s oldest and largest labs for science and engineering research, located some 20 minutes outside Chicago, IL (Feature Photo Service).

Mira will offer an opportunity for scientists to become more familiar with the capabilities an exascale machine will offer and the programming changes it will require. For example, scientists will have to scale their current computer codes to more than 750,000 individual computing cores, providing them preliminary experience on how scalability might be achieved on an exascale-class system with 100s of millions of cores.

Once Mira is online, the DOE’s Innovative and Novel Computational Impact on Theory and Experiment (INCITE) and the ASCR Leadership Computing Challenge (ALCC) programs will award blocks of computing time via a peer-reviewed, competitive process to researchers who are working on scientific challenges that are best addressed by the capabilities of high-performance supercomputers.

Blue Gene is one of 100 Icons of Progress in IBM’s 100 year history because it is a radical departure from the supercomputers of its time, consuming only a fraction of the energy and floor space. The system is part of a collaboration between Argonne, IBM and Lawrence Livermore National Laboratory. Blue Gene’s speed and expandability have enabled industry and the scientific community to address a wide range of complex problems and make more informed decisions.

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AI

IBM’s Watson has blazed the news when the system played Jeopardy, showcasing the greatest advancements in AI. Prior to that IBM was famous for the Deep Blue, a chess playing Robot, which took a brute-force approach, relying on a giant opening book and sheer computational power to search the game tree, rather than the intuitive approach apparently taken by human players.

In computer science, we often get to see a large number of algorithms that deal with making decisions. The one being used here for Jeopardy is Question Answering (QA), which is part of algorithm called Information Retrieval (IR). IR helps in retrieval of  relevant information or documents from a store (which can be wikis), while QA specifically deals with returning information in response to natural language questions (who, where, when, what, etc.).

On one side where QA goes focuses on answering specifically (just a word or phrase), on the other side IR commonly returns whole documents (as search engines do). IBM calls such a combination of algorithm : DeepQA.

“DeepQA”, Davidian explained, “scales out with and searches vast amounts of unstructured information. Effective execution of this software, corresponding to a less than three second response time to a Jeopardy! question, is not just based on raw execution power. Effective system throughput includes having available data to crunch on. Without an efficient memory sub-system, no amount of compute power will yield effective results. A balanced design is comprised of main memory, several levels of local cache and execution power. IBM’s POWER 750’s scalable design is capable of filling execution pipelines with instructions and data, keeping all the POWER7 processor cores busy. At 3.55 GHz, each of Watson’s POWER7 on-chip bandwidth is 500 Gigabytes per second. The total on-chip bandwidth for Watson’s 360 POWER7 processors is an astounding 180,000 Gigabytes per second!”

The algorithms used to compute the answers are far more complex than normal AI used in Robots. It can be considered as complex as a search engine itself which actually makes decisions. The paper (Ferucci et al 2010, AI magazine), outlines Watson’s approach to Question Answering in detail. It’s 20 pages long, but it’s not incredibly technical, highly recommended for everyone who have the passion.

The machine is named after Thomas J Watson, the founder of IBM.

If you want to succeed, double your failure rate - Thomas J. Watson

The paper begins with acknowledgements of the complexity of the problem and the scope:

“we appreciate that this challenge alone does not address all aspects of QA and does not by any means close the book on the QA challenge the way that Deep Blue may have for playing chess. However, note that while the Jeopardy! game requires that answers are delivered in the form of a question …  this transformation is trivial and for purposes of this paper we will just show the answers themselves”

How Watson is able to Answer in Jeopardy

• When it starts, Watson patiently hears to the question and then figures out answer within a span of 1-3 seconds. The category becomes the core fact for answering the question —  determining the domain of the answer.
• Watson heavily relies on clues & sub-clues. When the clue contains more than a single statement, Watson decides to break it down into subclues. The next step is to identify ‘what kind’ of answer the is being looked for. Its being called Lexical Answer Type (LAT) – Algorithm that helps figuring out which word among the clues represents the required answer. e.g if the question being asked is like “What was the year in history …”, the Lexical Answer Type is ‘year’. However, its really tough to for watson when the question has more pronouns than nouns. “If this is like it, how would that …”. Its easy to lose the context for an Artificial Intelligence engine.
• If all had been well so far, Watson knows the type of the answer it is looking for (year, city, singer), one or more clues relating to the answer, and the category the clue is in. It then searches in its repository for answers — no it doesn’t google search for the answer, as we know, its not answering engine. Apart from that, Jeopardy restricts access to internet, as per the game’s rules. So instead, the DeepQA system builds a large database of web documents which are then stored and searched offline during the live Jeopardy game. It looks for Q&A, encyclopedias, etc as the base to generate web searches used to retrieve pointers to relevant web snippets. These web snippets, together with the initial resources and many other downloadable knowledge bases (dbpedia, freebase, etc) form the “extended corpus” that is Watson’s knowledge base.
• The next step is to analyze the clue further in order to find out how to search the knowledge base. The question analysis section involves intensive Natural Language Processing techniques. The clue fragments are parsed, first syntactically and then semantically, to extract a logical form. The semantic roles in the clue are identified. Semantic role labeling is a major breakthrough in NLP, giving us algorithms that can identify the type of the subject and object in a parsed sentence.
• Coreference resolution detects which entities pronouns refer to, named entity recognition detects terms that are proper nouns referring to people or organizations, relation extraction identifies the parts of the clue that make up predicates or relations between nouns or entities in the clue.
• The process of searching the extended corpus is divided into two steps – at first the focus is on recall – the system generates a bulk of answers in the hope that the correct answer is somewhere in this list. This is done by querying its corpus in varied ways ( using reverse algorithms like Lucene and SPARQL), and returning small snippets of text and individual candidate answers. This list of possible answers is then weighted based upon some additional standalone algorithms, which employs computational lingusitics techniques to examine a particular aspect of the answer. This is actually much tougher and unclear. IBM didn’t explain the aspect in detail.
  “Each of the scorers implemented in Watson, how they work, how they interact, and their independent impact on Watson’s performance deserves its own research paper.”
• The information range and variation collected at this stage is sky-high. There are various components then come into play next — e.g. a component that can compare dates and times,a component for figuring out geographic coordinates, a component for matching the syntactic form of the clue with passages retrieved from web documents, and other scorers that can influence the confidence judgement for a particular answer. Watson tries to be as precise as possible, and it decides the confidence in the answer, based upon the above mentioned components. If its not absolutely sure, it might skip answering.
• Hardware & OS: Watson’s hardware is equally complex. Its powered by lots of parallel computation using Hadoop, which is managed using UIMA. Watson is based on the IBM POWER7 750 in a standard rack mounted configuration. It can run AIX, IBM’s house-brand Unix; IBM I; and Linux. To compete on Jeopardy Watson is running Novell’s SUSE Linux Enterprise Server. IBM didn’t go into detail of the hardware, but its based upon their modern supercomputer engine.

Watson is made up of ninety IBM POWER 750 servers, 16 Terabytes of memory, and 4 Terabytes of clustered storage. Davidian sontinued, “This is enclosed in ten racks including the servers, networking, shared disk system, and cluster controllers. These ninety POWER 750 servers have four POWER7 processors, each with eight cores. IBM Watson has a total of 2880 POWER7 cores.”

Apart from the original paper, there’s one more paper that conceptualizes Large Scale Relation Detection . The paper describes methods for detecting relations between entities in a large corpus (over a billion words of text). This makes most of the things more clearer discussing how patterns of words in text such as “appeared together at the premier of “ can be used to predict other, more useful relations like “co-star in”.  In order to get it to work, there is a need for a large number of built-in, detailed relations between concepts that can be populated using patterns of words in text.

Given the multitude of AI components interacting to solve all the little tasks that must be accomplished to parse a question and relate it to knowledge gained from previously seen documents, it really is Rocket science.

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For years, audiophiles had been hearing audible frequencies (20 Hz – 20Khz) & synthesizing the perfect sound. But there are few Secrets about Sounds that you don’t actually hear.

Infrasound is a sound that is lower in frequency than 20 Hz (Hertz), lower than the “normal” limit of human hearing. We mostly hear infrasound through our ears, but at higher levels it is possible to feel infrasound vibrations in various parts of the body. Examples of natural events that produce ultrasound include: lightning, earthquakes, volcanoes, etc.

Human ear’s ability to listen to lower frequencies decreases logarithmically. In simple language, you need very high intensity (high air pressure) of lower frequency sound to be actually heard. This intensity needs to be really high for human ears to hear something near or below 20hz.

However, when pure sine waves are reproduced under ideal conditions and at very high volume, a human listener will be able to identify tones as low as 12 Hz. Below 10 Hz it is possible to perceive the single cycles of the sound, along with a sensation of pressure at the eardrums.

Such sound waves fall under science of infrasonics, covering sounds beneath 20 Hz down to 0.001 Hz. This frequency range has its applications too. It is utilized for monitoring earthquakes, charting rock and petroleum formations below the earth, and also in ballistocardiography and seismocardiography to study the mechanics of the heart. Infrasound is characterized by an ability to cover long distances and get around obstacles with little dissipation.

Human Reactions to Infrasounds

Infrasound has been known to cause feelings of awe or fear in humans. Since it is not consciously perceived, it can make people feel vaguely that supernatural events are taking place. Truth be told, some Movie soundtracks make use of infrasound to produce unease or disorientation in the audience. Irreversible & Paranormal Activity are among them. We often only perceive them subconsciously, and it is usually in the pits of stomachs, or in our bones.

Research by Vic Tandy suggested that an infrasonic signal of 19 Hz might be responsible for some ghost sightings. One night, Tandy was working alone in a supposedly haunted laboratory at Warwick, when he felt very anxious and could detect a grey blob out of the corner of his eye. When Tandy turned to face the grey blob, there was nothing.

Although there was nothing touching fencing foil, the blade started to vibrate wildly. Further investigation led Tandy to discover that the extractor fan in the lab was emitting a frequency of 18.98 Hz, very close to the resonant frequency of the eye given as 18 Hz by NASA. This was why Tandy had seen a ghostly figure-it was an optical illusion caused by his eyeballs resonating. The room was exactly half a wavelength in length, and the desk was in the center, thus causing a standing wave which was detected by the foil.

Tandy’s research led to the removal of many doubts humans had about haunted houses. He carried out a number of investigations at various sites believed to be haunted, including the basement of the Tourist Information Bureau next to Coventry Cathedral and Edinburgh Castle.

Sounds play with human emotions, when we hear them and when we don’t. 16Hz is the sweet spot, when produced from a high quality Amp and Woofers. One would hear the deepest Bass with a frequency that resonates your bones and/or the brain. The feeling is immense, the experience is amplified by several multipliers. Most of the High-end Home theaters and even IMAX grade theaters would have it. Else, check it out with an audiophile, your woofers probably won’t do it.

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Tan Le, head of Emotive systems, demonstrates the next generation of computer human interface that promises to allow direct mental control of computers by people. This innovative and astonishing headset computer interface reads its user’s EEG brainwaves, making it possible to control virtual objects, and even electronics with only concentrated thought.

The application learns about individual Human brains. The sosftware needs initial training to estimate specific person’s brain waves intensity, pitch.

Watch the video to get a deeper insight:

Video Highlights: User pulls a virtual object (~4:55) and even make that object disappear (~6:45) using monitored brain activity. In both these cases EPOC only had a single point of reference from which to base the commands. Clearly the learning algorithm of the system is fairly capable. Eventually, commercial BCIs like EPOC may enjoy a wide range of applications. Le highlights a few in the video below, including video games (8:20), automated machines (8:50), and wheelchairs (9:30).

Available as low as $300, EPOC is one of the least expensive brain computer interfaces you can find on the market. Watch the Emotiv headset in action during Le’s TED Talk in the video below. She reveals parts of the UI and capabilities of the device that you haven’t seen anywhere else.

Calling the EPOC a brain computer interface is a little bit generous. With only 14 channels, it’s a fairly simple version of EEG.

Aren’t we already into the Future? Intel wants to put chip in every brain by 2020.

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The technology is named Ngara, and it allows up to 6 users to occupy the equivalent spectrum space of one television channel (7 megahertz) and has a spectral efficiency of 20 bits per second per hertz. If these numbers confuse you, here’s something more simplistic — Ngara can handle up to 3 times that of similar technology and maintains a data rate more than 10 times the industry minimum standard.

Ngara is capable of delivering wireless data services to houses within a 20 kilometer radius of a broadcast tower.

What makes this recent development interesting is how the technology coincides with the phasing out of analog TV by the Department of Broadband, Communications and the Digital Economy.

However, there are tradeoffs. The trouble with Broadband-over-analog is that many of today’s existing analog terrestrial broadcast towers are not being maintained in the conversion to digital. The question is whether those broadcast towers will continue to transmit signals for wireless broadband, if not this technology would fail before even it impresses us.

Another point to consider is cost and practical bandwidth. If its not better than satellite, then it’s unlikely to take the home market by big margins.

Ngara can achieve “ symmetrical 12Mbps per 1000 homes”, which is of course nothing but a dialup connection. If Ngara can be made to scale like commercial GSM and WiMax systems, we can hope to see its usage to start in Australia, and spreading to the world.

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Although you can Build yourself Supercomputers, it does cost millions when its built as a nation’s pride.

The Tianhe-1A, meaning Milky Way, was designed by the National University of Defense Technology (NUDT) in China. It is the work of 200 scientists,  that makes groundbreaking performance  record of 2.507 petaflops, or quatrillion calculations per second, making it the fastest system in the world today. Ordinarily the computer runs at 563.1 teraflops, or trillion calculations per second.

This giant comfortably costed over $88 million.

Compare this: as of June 2010, the 500 fastest supercomputers in the world combine for 32.4 petaflops of computing power and Chinese new supercomputer does 2.5 petaflops alone.

The whole system weighs 155-ton and is cooled by 103 refrigerator-like cabinets lined up on an area of about 1,000 square meters. The Tianhe-1A will be employed in calculations of seismic data for oil exploration, conduct bio-medical computing and help design aerospace vehicles.

Tianhe-1A is powered by 7,168 Nvidia Tesla M2050 GPUs and 14,336 Intel Xeon CPUs. But the design is intuitive enough to beat 50,000 CPUs & half the floor space.

The second best, Cray XT5 Jaguar system has more than 19000 computers and 224,000 CPUs based on AMDs.

The performance scale was definitely not possible without GPUs. GPUs are redefining high performance computing. With the Tianhe-1A, GPUs now power two of the top three fastest computers in the world today. These GPU supercomputers are essential tools for scientists looking to turbocharge their rate of discovery.

Power Consumption:

Its not worlds Greenest Supercomputer, but Tianhe-1A is energy efficient, saving enough power to provide electricity to over 5,000 homes for a year, Tianhe-1A consumes only 4.04 megawatts, making it 3 times more power efficient compared to a 2.507 petaflop system built entirely with CPUs that would consume more than 12 megawatts. However, affording its yearly bill still means $2.7 million hole.

The battle to build the fastest supercomputer has become a point of national pride as these high performance computers are used in a areas like defense, energy, finance, science. They are also used for drug discovery, hurricane and tsunami modeling, cancer research, car design, and studying the formation of galaxies.

Of the world’s fastest 500 supercomputers, the United States has 291, while Europe has 145 and Asia 49.

UPDATE: World’s Fastest Supercomputer – IBM’s Mira US owns the crown, again.

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Actroid is one of the best examples that showcased how Robotics can effectively mimic humans, as they have evolved the tech over last decade. Their current iteration of Actroid is better known as Actroid-F, looks like a  humanoid robot that can mock the operator’s facial expressions and head movements with accuracy seen never before.

Actroid-F is characterized by expressive engine, and one that can reproduce such a laugh and toothy smile, naturally. She can easily trace the movement based upon facial image recognition, which includes gestures like  such as nodding or shaking head.

During the builtup, it achieved significant cost reduction by about one third of the minimum necessary to narrow the degrees of freedom than Akutoroidoshirizu conventional remote control.

During the video she acts “as an observer in hospitals to gauge patient reactions.” She amazes us with real-life facial expressions, watch the video after the break:

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