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  • richardmitnick 11:39 am on May 14, 2016 Permalink | Reply
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    From NOVA: “A Quantum Computer Has Been Hooked Up to the Cloud For the First Time” 



    04 May 2016
    Allison Eck

    You can now entangle quantum qubits directly from your smartphone.

    A team at IBM has announced today that it has hooked up a quantum processor—housed at the IBM T.J. Watson Research Center in New York—to the cloud. For the first time in history, non-scientists and scientists alike can run quantum experiments from their desktop or mobile devices.

    “It’s really about starting to have a new community of quantum learners,” said Jay Gambetta, manager of the Theory of Quantum Computing and Information Group at IBM. “We’re trying to take the mysteriousness out of quantum.”

    The five-qubit processor is maintained at a temperature of 15 millikelvin. That’s 180 times colder than outer space.

    IBM is calling the cloud-based quantum platform the IBM Research Quantum Experience (which consists of a simulator as well as the live processor), and it’s a step in the direction of creating a universal quantum computer: one that can perform any calculation that is in the realm of what quantum mechanics predicts. No such computer exists today, but IBM suspects that researchers will find the means to develop one within the next decade.

    Quantum computing is a complicated beast compared to classical computing. Classical computers use bits to process information, where a bit represents either a zero or a one. Quantum computing, on other other hand, employs qubits—which represent either a zero, a one, or a superposition of both.

    IBM’s quantum computer holds five superconducting qubits, a relatively small amount. The most expensive modern-day classical computer could emulate a 30- or 40-qubit system, the researchers say. So it’s not as though IBM’s cloud-based quantum processor is going to solve anything that scientists can’t already figure out using a classical computer. Instead, the strength of IBM’s processor is derived from its use as an educational tool—anyone who is curious can experiment, play with real qubits, and explore tutorials related to quantum computing.

    In addition, scientists who access the processor will be able to use it to develop a better intuition for quantum computing. “We’ll know more about nature itself when we understand these algorithms,” Gambetta said. Specifically, experts can become more skilled at parsing quantum “noise,” or the uncertainty in physical characteristics of quantum nature. If they can minimize uncertainty—flukes in the system that cause the quantum computer to malfunction—in a small, five-qubit processor, then they can scale those lessons to create stronger quantum computers in the future.

    Eventually, given the invention of 50- to 100-qubit processors, scientists may be able to deduce the complex behavior of molecules using quantum computing. They could even make significant strides in artificial intelligence, processing big data, and more.

    IBM’s announcement also marks the launch of the IBM Research Frontiers Institute, a consortium of organizations from various industries (including Samsung and Honda) that plans to collaborate on ground-breaking computing technologies. As classical computing becomes less relevant and Moore’s law starts to fade, such projects will become even more necessary. As Gambetta noted, the amount we know about quantum computing now is similar to what we knew about classical computing in the 1950s and 60s. It’s back to square one.

    “Everything you know about computing, you have to relearn it,” he said.



    See the full article here .

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    NOVA is the highest rated science series on television and the most watched documentary series on public television. It is also one of television’s most acclaimed series, having won every major television award, most of them many times over.

  • richardmitnick 9:42 am on April 23, 2016 Permalink | Reply
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    From WIRED:”Technology Aids in Fight Against Tuberculosis” 

    Discovery News
    Discovery News

    For the first time ever, a supercomputer will help in the fight against one of the deadliest and fastest-spreading diseases in the world: tuberculosis.



    In one corner of the ring you have the IBM World Community Grid.

    WCG Logo New


    This platform gives anyone a chance to join the fight by donating their devices’ spare energy. This means they can use the energy from your computer, tablet or smartphone when your device is idle. The World Community Grid is one the most powerful platforms on the planet, and its newly launched Help Stop TB project is fantastic news for the medical community. In the other corner, we have tuberculosis.

    What Is Tuberculosis?

    Tuberculosis is a highly contagious, airborne disease that kills about 1.5 million people each year. A tuberculosis infection can begin without any symptoms and can persist for years before it becomes an active disease. If TB is detected early, then it is easily treatable. It’s important to look for symptoms and seek treatment.

    Active tuberculosis is contagious and spread through the air. Sneezing, coughing or talking is all it takes to spread the disease to another person. Anyone can easily catch this disease. This is why it’s important to find a cure as soon as possible, and IBM’s technology can certainly help in a major way.

    The Advantages of Technology

    The World Community Grid is no stranger to medical advances. Since its creation in 2014, the World Community Grid has contributed to research for many causes like curing AIDS, cancer and world hunger.

    With about 700,000 people lending their devices’ energy to IBM, the World Community Grid is a top-10 supercomputer.



    This makes the research process much more efficient. Researchers can now categorize and go through data at rapid speeds.

    When it comes to medical research, the more technology the better. Scientists have been using cloud capabilities to apply tens of thousands of computer nodes to a single problem. Supercomputers offer a way to quickly scan through and recognize problems that may have taken years to uncover.

    A team at Novartis was able to run through 40 years of cancer drug simulations in just eight hours. It also cost them thousands of dollars instead of the millions it would’ve cost before supercomputers. Having a supercomputer that uses the energy from the devices of 700,000 people will only help tuberculosis research.

    The Fight Against Tuberculosis

    Tuberculosis is coined as the world’s deadliest disease, so it’s vital that scientists find a cure as soon as possible. It received this nickname because it kills about 1.5 million people a year. IBM’s World Community Grid supercomputer will tremendously speed up the process.

    Scientists will use the World Community Grid to get a complete understanding of TB’s cell wall. They’ll be able to simulate different variations of mycolic acid structures to see if they can impact the bacteria’s functions. The supercomputer lets them test many different structures instead of just a few. They hope that one of these structures will give scientists a better understanding of how to attack tuberculosis.

    You Can Help

    You can sign up to let IBM use your devices’ energy when you aren’t using them. Sign up today and be a part of the fight against tuberculosis.

    World Community Grid (WCG) brings people together from across the globe to create the largest non-profit computing grid benefiting humanity. It does this by pooling surplus computer processing power. We believe that innovation combined with visionary scientific research and large-scale volunteerism can help make the planet smarter. Our success depends on like-minded individuals – like you.”

    WCG projects run on BOINC software from UC Berkeley.

    BOINC is a leader in the field(s) of Distributed Computing, Grid Computing and Citizen Cyberscience.BOINC is more properly the Berkeley Open Infrastructure for Network Computing.

    BOINC WallPaper


    “Download and install secure, free software that captures your computer’s spare power when it is on, but idle. You will then be a World Community Grid volunteer. It’s that simple!” You can download the software at either WCG or BOINC.

    Please visit the project pages-
    Outsmart Ebola together

    Outsmart Ebola Together

    Mapping Cancer Markers

    Uncovering Genome Mysteries
    Uncovering Genome Mysteries

    Say No to Schistosoma

    GO Fight Against Malaria

    Drug Search for Leishmaniasis

    Computing for Clean Water

    The Clean Energy Project

    Discovering Dengue Drugs – Together

    Help Cure Muscular Dystrophy

    Help Fight Childhood Cancer

    Help Conquer Cancer

    Human Proteome Folding


    World Community Grid is a social initiative of IBM Corporation
    IBM Corporation

    IBM – Smarter Planet

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  • richardmitnick 4:18 pm on March 29, 2016 Permalink | Reply
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    From LLNL: “Lawrence Livermore and IBM collaborate to build new brain-inspired supercomputer” 

    Lawrence Livermore National Laboratory

    Mar. 29, 2016
    Don Johnston

    The 16-chip IBM TrueNorth platform Lawrence Livermore will receive later this week. The scalable platform will process the equivalent of 16 million neurons and 4 billion synapses and consume the energy equivalent of a hearing-aid battery – a mere 2.5 watts of power. Photo courtesy of IBM.

    Chip-architecture breakthrough accelerates path to exascale computing; helps computers tackle complex, cognitive tasks such as pattern recognition sensory processing

    Lawrence Livermore National Laboratory (LLNL) today announced it will receive a first-of-a-kind brain-inspired supercomputing platform for deep learning developed by IBM Research . Based on a breakthrough neurosynaptic computer chip called IBM TrueNorth, the scalable platform will process the equivalent of 16 million neurons and 4 billion synapses and consume the energy equivalent of a hearing aid battery – a mere 2.5 watts of power.

    The brain-like, neural network design of the IBM Neuromorphic System is able to infer complex cognitive tasks such as pattern recognition and integrated sensory processing far more efficiently than conventional chips.

    DARPA SyNAPSE 16 chip board with IBM TrueNorth

    Access mp4 video here .

    The new system will be used to explore new computing capabilities important to the National Nuclear Security Administration’s (NNSA) missions in cybersecurity, stewardship of the nation’s nuclear weapons stockpile and nonproliferation. NNSA’s Advanced Simulation and Computing (ASC) program will evaluate machine-learning applications, deep-learning algorithms and architectures and conduct general computing feasibility studies. ASC is a cornerstone of NNSA’s Stockpile Stewardship Program to ensure the safety, security and reliability of the nation’s nuclear deterrent without underground testing.

    Neuromorphic computing opens very exciting new possibilities and is consistent with what we see as the future of the high performance computing and simulation at the heart of our national security missions,” said Jim Brase, LLNL deputy associate director for Data Science. “The potential capabilities neuromorphic computing represents and the machine intelligence that these will enable will change how we do science.”

    The technology represents a fundamental departure from computer design that has been prevalent for the past 70 years, and could be a powerful complement in the development of next-generation supercomputers able to perform at exascale speeds, 50 times (or two orders of magnitude) faster than today’s most advanced petaflop (quadrillion floating point operations per second) systems. Like the human brain, neurosynaptic systems require significantly less electrical power and volume.

    “The low power consumption of these brain-inspired processors reflects industry’s desire and a creative approach to reducing power consumption in all components for future systems as we set our sights on exascale computing,” said Michel McCoy, LLNL program director for Weapon Simulation and Computing.

    “The delivery of this advanced computing platform represents a major milestone as we enter the next era of cognitive computing,” said Dharmendra Modha, IBM fellow and chief scientist of Brain-inspired Computing, IBM Research. “We value our partnerships with the national labs. In fact, prior to design and fabrication, we simulated the IBM TrueNorth processor using LLNL’s Sequoia supercomputer. This collaboration will push the boundaries of brain-inspired computing to enable future systems that deliver unprecedented capability and throughput, while minimizing the capital, operating and programming costs – keeping our nation at the leading edge of science and technology.”

    A single TrueNorth processor consists of 5.4 billion transistors wired together to create an array of 1 million digital neurons that communicate with one another via 256 million electrical synapses. It consumes 70 milliwatts of power running in real time and delivers 46 giga synaptic operations per second – orders of magnitude lower energy than a conventional computer running inference on the same neural network. TrueNorth was originally developed under the auspices of the Defense Advanced Research Projects Agency’s (DARPA) Systems of Neuromorphic Adaptive Plastic Scalable Electronics (SyNAPSE) program, in collaboration with Cornell University.

    Under terms of the $1 million contract, LLNL will receive a 16-chip TrueNorth system representing a total of 16 million neurons and 4 billion synapses. LLNL also will receive an end-to-end ecosystem to create and program energy-efficient machines that mimic the brain’s abilities for perception, action and cognition. The ecosystem consists of a simulator; a programming language; an integrated programming environment; a library of algorithms as well as applications; firmware; tools for composing neural networks for deep learning; a teaching curriculum; and cloud enablement.

    Lawrence Livermore computer scientists will collaborate with IBM Research, partners across the Department of Energy complex and universities to expand the frontiers of neurosynaptic architecture, system design, algorithms and software ecosystem.

    See the full article here .

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    LLNL Campus

    Operated by Lawrence Livermore National Security, LLC, for the Department of Energy’s National Nuclear Security
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  • richardmitnick 9:43 am on August 31, 2015 Permalink | Reply
    Tags: Air Pollution, , , IBM Corporation,   

    From MIT Tech Review: “How Artificial Intelligence Can Fight Air Pollution in China” 

    MIT Technology Review
    M.I.T Technology Review

    August 31, 2015
    Will Knight

    A woman wearing a face mask makes her way along a street in Beijing on January 16, 2014.

    IBM is testing a new way to alleviate Beijing’s choking air pollution with the help of artificial intelligence. The Chinese capital, like many other cities across the country, is surrounded by factories, many fueled by coal, that emit harmful particulates. But pollution levels can vary depending on factors such as industrial activity, traffic congestion, and weather conditions.

    The IBM researchers are testing a computer system capable of learning to predict the severity of air pollution in different parts of the city several days in advance by combining large quantities of data from several different models—an extremely complex computational challenge. The system could eventually offer specific recommendations on how to reduce pollution to an acceptable level—for example, by closing certain factories or temporarily restricting the number of drivers on the road. A comparable system is also being developed for a city in the Hebei province, a badly affected area in the north of the country.

    “We have built a prototype system which is able to generate high-resolution air quality forecasts, 72 hours ahead of time,” says Xiaowei Shen, director of IBM Research China. “Our researchers are currently expanding the capability of the system to provide medium- and long-term (up to 10 days ahead) as well as pollutant source tracking, ‘what-if’ scenario analysis, and decision support on emission reduction actions.”

    The project, dubbed Green Horizon, is an example of how broadly IBM hopes to apply its research on using advanced machine learning to extract insights from huge amounts of data—something the company calls “cognitive computing.” The project also highlights an application of the technology that IBM would like to export to other countries where pollution is a growing problem.

    IBM is currently pushing artificial intelligence in many different industries, from health care to consulting. The cognitive computing effort encompasses natural language processing and statistical techniques originally developed for the Watson computer system, which competed on the game show Jeopardy!, along with many other approaches to machine learning (see “Why IBM Just Bought Millions of Medical Images” and “IBM Pushes Deep Learning with a Watson Upgrade”).

    Predicting pollution is challenging. IBM uses data supplied by the Beijing Environmental Protection Bureau to refine its models, and Shen says the predictions have a resolution of a kilometer and are 30 percent more precise than those derived through conventional approaches. He says the system uses “adaptive machine learning” to determine the best combination of models to use.

    Pollution is a major public health issue in China, accounting for more than a million deaths each year, according to a study conducted by researchers at the University of California, Berkeley. It is also a major subject of public and political debate.

    China has committed to improving air quality 10 percent by 2017 through the Airborne Pollution Prevention and Control Action Plan. This past April, an analysis of 360 Chinese cities by the charity Greenpeace East Asia, based in Beijing, showed that 351 of them had pollution levels exceeding China’s own air quality standards, although levels had improved since the period 12 months before. The average level of airborne particulates measured was more than two and a half times the limit recommended by the World Health Organization.

    See the full article here.


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  • richardmitnick 9:39 am on August 18, 2015 Permalink | Reply
    Tags: , , IBM Corporation   

    From wired: “IBM’s ‘Rodent Brain’ Chip Could Make Our Phones Hyper-Smart” 

    Wired logo



    Smarter Planet

    Cade Metz

    At a lab near San Jose, IBM has built the digital equivalent of a rodent brain—roughly speaking. It spans 48 of the company’s experimental TrueNorth chips, a new breed of processor that mimics the brain’s biological building blocks. IBM

    Dharmendra Modha walks me to the front of the room so I can see it up close. About the size of a bathroom medicine cabinet, it rests on a table against the wall, and thanks to the translucent plastic on the outside, I can see the computer chips and the circuit boards and the multi-colored lights on the inside. It looks like a prop from a ’70s sci-fi movie, but Modha describes it differently. “You’re looking at a small rodent,” he says.

    He means the brain of a small rodent—or, at least, the digital equivalent. The chips on the inside are designed to behave like neurons—the basic building blocks of biological brains. Modha says the system in front of us spans 48 million of these artificial nerve cells, roughly the number of neurons packed into the head of a rodent.

    Modha oversees the cognitive computing group at IBM, the company that created these “neuromorphic” chips. For the first time, he and his team are sharing their unusual creations with the outside world, running a three-week “boot camp” for academics and government researchers at an IBM R&D lab on the far side of Silicon Valley. Plugging their laptops into the digital rodent brain at the front of the room, this eclectic group of computer scientists is exploring the particulars of IBM’s architecture and beginning to build software for the chip dubbed TrueNorth.

    Some researchers who got their hands on the chip at an engineering workshop in Colorado the previous month have already fashioned software that can identify images, recognize spoken words, and understand natural language. Basically, they’re using the chip to run “deep learning” algorithms, the same algorithms that drive the internet’s latest AI services, including the face recognition on Facebook and the instant language translation on Microsoft’s Skype. But the promise is that IBM’s chip can run these algorithms in smaller spaces with considerably less electrical power, letting us shoehorn more AI onto phones and other tiny devices, including hearing aids and, well, wristwatches.

    “What does a neuro-synaptic architecture give us? It lets us do things like image classification at a very, very low power consumption,” says Brian Van Essen, a computer scientist at the Lawrence Livermore National Laboratory who’s exploring how deep learning could be applied to national security. “It lets us tackle new problems in new environments.”

    The TrueNorth is part of a widespread movement to refine the hardware that drives deep learning and other AI services. Companies like Google and Facebook and Microsoft are now running their algorithms on machines backed with GPUs (chips originally built to render computer graphics), and they’re moving towards FPGAs (chips you can program for particular tasks). For Peter Diehl, a PhD student in the cortical computation group at ETH Zurich and University Zurich, TrueNorth outperforms GPUs and FPGAs in certain situations because it consumes so little power.

    The main difference, says Jason Mars, a professor of a computer science at the University of Michigan, is that the TrueNorth dovetails so well with deep-learning algorithms. These algorithms mimic neural networks in much the same way IBM’s chips do, recreating the neurons and synapses in the brain. One maps well onto the other. “The chip gives you a highly efficient way of executing neural networks,” says Mars, who declined an invitation to this month’s boot camp but has closely followed the progress of the chip.

    That said, the TrueNorth suits only part of the deep learning process—at least as the chip exists today—and some question how big an impact it will have. Though IBM is now sharing the chips with outside researchers, it’s years away from the market. For Modha, however, this is as it should be. As he puts it: “We’re trying to lay the foundation for significant change.”
    The Brain on a Phone

    Peter Diehl recently took a trip to China, where his smartphone didn’t have access to the `net, an experience that cast the limitations of today’s AI in sharp relief. Without the internet, he couldn’t use a service like Google Now, which applies deep learning to speech recognition and natural language processing, because most the computing takes place not on the phone but on Google’s distant servers. “The whole system breaks down,” he says.

    Deep learning, you see, requires enormous amounts of processing power—processing power that’s typically provided by the massive data centers that your phone connects to over the `net rather than locally on an individual device. The idea behind TrueNorth is that it can help move at least some of this processing power onto the phone and other personal devices, something that can significantly expand the AI available to everyday people.

    To understand this, you have to understand how deep learning works. It operates in two stages. First, companies like Google and Facebook must train a neural network to perform a particular task. If they want to automatically identify cat photos, for instance, they must feed the neural net lots and lots of cat photos. Then, once the model is trained, another neural network must actually execute the task. You provide a photo and the system tells you whether it includes a cat. The TrueNorth, as it exists today, aims to facilitate that second stage.

    Once a model is trained in a massive computer data center, the chip helps you execute the model. And because it’s small and uses so little power, it can fit onto a handheld device. This lets you do more at a faster speed, since you don’t have to send data over a network. If it becomes widely used, it could take much of the burden off data centers. “This is the future,” Mars says. “We’re going to see more of the processing on the devices.”

    Neurons, Axons, Synapses, Spikes

    Google recently discussed its efforts to run neural networks on phones, but for Diehl, the TrueNorth could take this concept several steps further. The difference, he explains, is that the chip dovetails so well with deep learning algorithms. Each chip mimics about a million neurons, and these can communicate with each other via something similar to a synapse, the connections between neurons in the brain.

    The setup is quite different than what you find in chips on the market today, including GPUs and FPGAs. Whereas these chips are wired to execute particular “instructions,” the TrueNorth juggles “spikes,” much simpler pieces of information analogous to the pulses of electricity in the brain. Spikes, for instance, can show the changes in someone’s voice as they speak—or changes in color from pixel to pixel in a photo. “You can think of it as a one-bit message sent from one neuron to another.” says Rodrigo Alvarez-Icaza, one of the chip’s chief designers.

    The upshot is a much simpler architecture that consumes less power. Though the chip contains 5.4 billion transistors, it draws about 70 milliwatts of power. A standard Intel computer processor, by comparison, includes 1.4 billion transistors and consumes about 35 to 140 watts. Even the ARM chips that drive smartphones consume several times more power than the TrueNorth.

    Of course, using such a chip also requires a new breed of software. That’s what researchers like Diehl are exploring at the TrueNorth boot camp, which began in early August and runs for another week at IBM’s research lab in San Jose, California. In some cases, researchers are translating existing code into the “spikes” that the chip can read (and back again). But they’re also working to build native code for the chip.

    Parting Gift

    Like these researchers, Modha discusses the TrueNorth mainly in biological terms. Neurons. Axons. Synapses. Spikes. And certainly, the chip mirrors such wetware in some ways. But the analogy has its limits. “That kind of talk always puts up warning flags,” says Chris Nicholson, the co-founder of deep learning startup Skymind. “Silicon operates in a very different way than the stuff our brains are made of.”

    Modha admits as much. When he started the project in 2008, backed by $53.5M in funding from Darpa, the research arm for the Department of Defense, the aim was to mimic the brain in a more complete way using an entirely different breed of chip material. But at one point, he realized this wasn’t going to happen anytime soon. “Ambitions must be balanced with reality,” he says.

    In 2010, while laid up in bed with the swine flu, he realized that the best way forward was a chip architecture that loosely mimicked the brain—an architecture that could eventually recreate the brain in more complete ways as new hardware materials were developed. “You don’t need to model the fundamental physics and chemistry and biology of the neurons to elicit useful computation,” he says. “We want to get as close to the brain as possible while maintaining flexibility.”

    This is TrueNorth. It’s not a digital brain. But it is a step toward a digital brain. And with IBM’s boot camp, the project is accelerating. The machine at the front of the room is really 48 separate machines, each built around its own TrueNorth processors. Next week, as the boot camp comes to a close, Modha and his team will separate them and let all those academics and researchers carry them back to their own labs, which span over 30 institutions on five continents. “Humans use technology to transform society,” Modha says, pointing to the room of researchers. “These are the humans.”

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  • richardmitnick 6:54 am on July 28, 2015 Permalink | Reply
    Tags: , , IBM Corporation   

    From Ars Technica: “Inside the world’s quietest room” 

    Ars Technica logo

    ars technica

    Jul 28, 2015
    Sebastian Anthony

    In a hole, on some bedrock a few miles outside central Zurich, there lived a spin-polarised scanning electron microscope. Not a nasty, dirty, wet hole: it was a nanotech hole, and that means quiet. And electromagnetically shielded. And vibration-free. And cool.

    When you want to carry out experiments at the atomic scale—when you want to pick up a single atom and move it to the other end of a molecule—it requires incredibly exacting equipment. That equipment, though, is worthless without an equally exacting laboratory to put it in. If you’re peering down the (figurative) barrel of a microscope at a single atom, you need to make sure there are absolutely no physical vibrations at all, or you’ll just get a blurry image. Similarly, atoms really don’t like to sit still: you don’t want to spend a few hours setting up a transmission electron microscope (TEM), only to have a temperature fluctuation or EM field imbue the atoms with enough energy to start jumping around on their own accord.

    One solution, as you have probably gathered from the introduction to this story, is to build a bunker deep underground, completely from scratch, with every facet of the project simulated, designed, and built with a singular purpose in mind: to block out the outside world entirely. That’s exactly what IBM Research did back in 2011, when it opened the Binnig and Rohrer Nanotechnology Center.


    The Center, which is located just outside Zurich in Rüschlikon, cost about €80 million (£60 million, $90 million) to build, which includes equipment costs of around €27 million (£20 million, $30 million). IBM constructed and owns the building, but IBM Research and ETH Zurich have shared use of the building and equipment. ETH and IBM collaborate on a lot of research, especially on nanoscale stuff.

    The entrance hall to the Binnig and Rohrer Nanotechnology Center.


    Deep below the Center there are six quiet rooms—or, to put it another way, rooms that are almost completely devoid of any kind of noise, from acoustic waves to physical vibrations to electromagnetic radiation. Each room is dedicated to a different nanometre-scale experiment: in one room, I was shown a Raman microscope, which is used for “fingerprinting” molecules; in another, a giant TEM, which is like an optical microscope, but it uses a beam of electrons instead of light to resolve details as small as 0.09nm. Every room is eerily deadened and quiet, which is juxtapositionally belied by the hulking silhouette of a multi-million-pound apparatus sitting in the middle of it. After investigating a few rooms, I notice that my phone is uncharacteristically lifeless. “That’s the nickel-iron box that encases every room,” my guide informs me.

    It’s impossible to go into every design feature of the noise-free rooms, but I’ll run through the most important and the most interesting. For a start, the rooms are built directly on the bedrock, significantly reducing vibrations from a nearby road and an underground train. Then, the walls of each room are clad with the aforementioned nickel-iron alloy, screening against most external electromagnetic fields, including those produced by experiments in nearby rooms. There are dozens of external sources of EM radiation, but the strongest are generated by mobile phone masts, overhead power lines, and the (electric) underground train, all of which would play havoc with IBM’s nanoscale experiments.

    Internally, most rooms are divided in two: there’s a small ante chamber, which is where the human controller sits, and then the main space with the actual experiment/equipment. Humans generate around 100 watts of heat, and not inconsiderable amounts of noise and vibration, so it’s best to keep them away from experiments while they’re running.

    To provide even more isolation, there are two separate floors in each room: one suspended floor for the scientists to walk on, and another separate floor that only the equipment sits on. The latter isn’t actually a floor: it’s a giant (up-to-68-ton) concrete block that rests on active air suspension. Any vibrations that make it through the bedrock, or that come from large trucks rumbling by, are damped in real time by the air suspension.

    We’re not done yet! To minimise acoustic noise (i.e. sound), the rooms are lined with acoustically absorbent material. Furthermore, if an experiment has noisy ancillary components (a vacuum pump, electrical transformer, etc.), they are placed in another room away from the main apparatus, so that they’re physically and audibly isolated.

    And finally, there’s some very clever air conditioning that’s quiet, generates minimal air flux, and is capable of keeping the temperature in the rooms very stable. In every room, the suspended floor (the human-designated bit) is perforated with holes. Cold air slowly ekes out of these holes, rises to the ceiling, and is then sucked out. The air flow was hardly noticeable, except for on my ankles: in a moment of unwarranted hipness earlier that morning, I had decided to wear boat shoes without socks.

    That’s about it for the major, physical features of IBM Research’s quiet rooms, but there are two other bits that are pretty neat. First, the whole place is lit with LEDs, driven by a DC power supply that is far enough away that its EM emissions don’t interfere. Second, each room is equipped with three pairs of Helmholtz coils, oriented so that they cover the X, Y, and Z axes. These coils are tuned to cancel out any residual magnetic fields that haven’t already been damped by various other shields, such as the Earth’s magnetic field.

    Labelled images of IBM’s noise-free labs, showing various important features

    Just how quiet are the rooms?

    So, after all that effort—each of the six rooms cost about €1.4 million to build, before equipment—just how quiet are the rooms below the Binnig and Rohrer Nanotechnology Center? Let’s break it down by the type of noise.

    The temperature at waist height in the rooms is set to 21 degrees Celsius, with a stability of 0.1°C per hour (i.e. it would take an hour for the temperature to rise to 21.1°C).

    Electromagnetic fields produced by AC sources are damped to less than 3 nT (nanotesla)—or about 1,500 times weaker than the magnetic field produced by a fridge magnet. From DC sources, it’s damped to 20 nT.

    The vibration damping is probably the most impressive: for the equipment on the concrete pedestals, movement is reduced to less than 300nm/s at 1Hz, and less than 10nm/s above 100Hz. These are well below the specs of NIST’s Advanced Measurement Laboratory in Maryland, USA.

    Somewhat ironically for the world’s quietest rooms, the weakest link is acoustic noise. Even though the rooms themselves are shielded from outside noises, and the acoustically absorbent material does a good job of stopping internal sound waves dead, there’s no avoiding the quiet hum of some of the machines or the slight susurration of the ventilation system.

    The acoustic noise level in the rooms is always below 30 dB, dipping down as low as 21 dB if there isn’t a noisy experiment running. In human terms, the rooms were definitely quiet, but not so quiet that I could feel my sanity slipping away, or anything crazy like that. I was a little bit disappointed that I couldn’t hear my various internal organs shifting around, truth be told.

    Why did IBM build six of these rooms?

    “You’re only as good as your tools.” It’s a trite, overused statement, but in this case it perfectly describes why IBM and ETH Zurich spent so many millions of euros on the quiet rooms.

    Big machines like the TEM or spin-SEM need to be kept very still, with as little outside interference as possible: if you can’t stay within the machine’s nominal operational parameters, you’re not going to get much scientifically useful data out of it.

    On the flip side, however, if you surpass the machine’s optimal parameters—if you reduce the amount of vibration, noise, etc. beyond the “recommended specs”—then you can produce images and graphs with more resolution than even the manufacturer thought possible.

    IBM Research’s spin-SEM, for example, used to be located in the basement of the main building, on a normal concrete floor. After being relocated to the quiet rooms, the lead scientist who uses the the spin-SEM said its resolution is 2-3 times better (an utterly huge gain, in case you were wondering).

    For much the same reason, my guide said that “several tooling manufacturers” have contacted IBM Research to ask if they can test their equipment in the noise-free labs: they want to see just how well it will perform under near-perfect conditions.

    The best story, though, I saved for last. Back in the ’80s and ’90s, before the Center was built, the IBM researchers didn’t have a specialised nanotechnology facility: they just worked in their labs, which were usually located down in the basement. When Gerd Binnig and Heinrich Rohrer invented the scanning tunnelling microscope (STM)—an achievement that would later net them a Nobel prize—they worked in the dead of night to minimise vibrations from the nearby road and other outside interference.

    After the new building was finished—which, incidentally, is named after Binnig and Rohrer—my guide spoke to some IBM retirees who had just finished inspecting the noise-free rooms. “We wish we’d had these rooms back in the ’80s and 90s, so that we didn’t have to work at 3am,” they said.

    See the full article here.

    Please help promote STEM in your local schools.

    STEM Icon

    Stem Education Coalition

  • richardmitnick 9:24 pm on June 30, 2012 Permalink | Reply
    Tags: , , , IBM Corporation, , Smarter Planet,   

    From the WCG Clean Energy Project at Harvard: The IBM Contribution 

    The Clean Energy Project (CEP2) at Harvard University gives us the look into IBM’s contribution to the betterment of Society via World community Grid (WCG).

    Watch this short video.

    You can visit the WCG web site (link is above), download the BOINC software agent, and attach to the Clean Energy Project. We would love to have you.

    From the project:

    The mission of The Clean Energy Project is to find new materials for the next generation of solar cells and later, energy storage devices. By harnessing the immense power of World Community Grid, researchers can calculate the electronic properties of hundreds of thousands of organic materials – thousands of times more than could ever be tested in a lab – and determine which candidates are most promising for developing affordable solar energy technology.

  • richardmitnick 11:36 am on March 27, 2012 Permalink | Reply
    Tags: IBM Corporation, ,   

    From the Wall Street Journal: “Rutgers University, IBM Open Supercomputer Center” 

    As a proud alumnus of Rutgers University, I could not let this go by.

    This is copyright protected material, so just a highlight or two.

    March 27, 2012

    “Rutgers University and International Business Machines Corp. IBM -0.02% will cut the ribbon Tuesday on a technology center in New Jersey that houses a $3.3 million supercomputer—stacks of processors that can digest massive quantities of data in a fraction of the time that a desktop unit would take.



    Named “IBM Blue Gene/P,” the machine, about the size of two refrigerators, will be one of the most powerful computers in the Northeast, with thousands of central processing units, or CPUs. IBM hopes in the coming year it will make the prestigious “TOP 500” list of the world’s most powerful computers, determined by a group of academic and government researchers.

    The supercomputer has similar analytical capabilities to “Watson,” the IBM computer that competed on the TV game show “Jeopardy.”

    A genome analysis that would take a year on a desktop, for example, could wrap up in a day on this computer, said Michael Pazzani, vice president for research and economic development at Rutgers in Piscataway, N.J., where the technology center is located.

    ‘This is the first step in a multiyear plan that involves IBM and Rutgers. We hope to become one of the top 10 academic computing centers in the world,’ Mr. Pazzani said.”

    See the full article here.

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