IBM Research

How can visualization help citizens use open data?

2012-02-02T12:52:00.000-05:00

Open data refers to the free access and reuse of government data — excluding private information such as personal medical data. The concept of establishing a portal for open data is fairly new.

Visualization of city activity, such as traffic, in Helsinki

IBM’s Smarter Cities Challenge sent a team of six experts – including two researchers from the Haifa lab in Israel — to Helsinki. Their mission was to provide recommendations on how visualization could be used to make the city’s open data more accessible to the citizens. The idea was to boost citizen engagement and improve democracy.

After three weeks of work, the team produced a final report with specific recommendations on how to turn data into visual information that would encourage action and drive citizen engagement. Just a few examples that the team suggested include using symbols like a tree to explain how the budget is divided up, projecting the city’s consumption of electricity onto a building, or using touch screens to get feedback in places where people congregate.

"We started off with boring looking data," explained Avi Yaeli, IBM Researcher from Haifa. "But when you can take the data and transform it into a visual story that helps people discover and understand new ideas, it's an exciting way to get citizens involved."

You can read more about the team’s experience here.

Q&A with Giovanni Cherubini, IBM storage scientist

2012-01-23T09:41:00.005-05:00

Scientist at the IBM Research - Zurich Lab celebrates 25 years of service

Giovanni Cherubini celebrates his 25th anniversary of service this month. He is a member of the Storage Technologies department, has been an IBM Master Inventor since 2009 and an IEEE Fellow since 2006. Hailing originally from Padua, Italy, Giovanni now has dual Italian and Swiss citizenship. He has over 80 publications in conference proceedings and peer-reviewed journals, in addition to 40 granted patents and some 20 pending patent applications.

Q. Giovanni, congratulations on your 25th service anniversary. What brought you to the Zurich Lab?

Oh, thank you. I was recruited by Gottfried Ungerboeck, whom I met while I was doing my PhD at UC San Diego. I liked the kind of work Gottfried was doing, so I jumped at the chance.

Q. Were you keen to return to Europe after your PhD?

Well, my interview in Zurich was in July, and I arrived the following January. Coming from San Diego, that meant a temperature drop of about 30 degrees, which was quite a shock. But overall, yes, I was happy to return to Europe to be closer to my family.

Q. You joined the Zurich Lab in 1987. Could you describe a couple of ways in which the Lab has changed since then?

At the time, my group was at an off-site location, and it was a little challenging for newcomers to integrate and feel like part of the Lab. Fortunately, our group of young (at the time!) researchers had just enough critical mass to be able to create our own atmosphere of intellectual stimulation. So that helped not to feel too cut off from the main Lab.

Several years later, the entire department moved to another off-site location, and that was a much bigger group, which meant more interaction.

Then in 2000, we finally moved to the main Lab, which I really appreciated.

Q. Your location wasn’t the only thing that changed. How has your field of research changed over the years?

When I started, my group was working on communications systems. However, this wasn’t IBM’s core business and the support was declining. We brought that work to completion by transferring many of our ideas into industry standards. One of them also became an Accomplishment in 2002.

Back in the 90s, IBM was going through drastic changes, and we as RSMs also had to change. We were increasingly being asked to contribute to the needs and success of the company.

After the communications systems work was wrapped up, I joined the Millipede probe storage project. That was very exciting because it opened up a completely new landscape and gave me the opportunity to learn new skills. Today, I continue to work on control-system-related issues, now within the Tape Storage group.

Q. Was that quite a challenge?

I think it was a valuable experience to realize that we as researchers have to be open to change and willing to adapt our skills, to expand our interests.

Of course those original data communications skills still serve me well even today, although my main focus has changed considerably. It was an interesting evolution to go through, and I learned that essentially everybody has to be able to reinvent and innovate himself and see the opportunities that change can offer.

Q. What do you enjoy most about the working environment at the Zurich Lab?

It’s definitely the stimulating intellectual environment and the flexibility we enjoy. The opportunities to try new things. Of course it’s important to consider the company’s goals and technical priorities. This creates a kind of playground where scientists can find new ways to approach interesting issues and find solutions to significant problems. I also find it gratifying to contribute to successful IBM products.

Q. You’ve worked with the same core group of colleagues throughout your career at the Zurich Lab. What effect does this have on your work?

It’s so important that there’s an element of trust within a group of colleagues, an atmosphere where people can be open and exchange ideas. We’ve achieved a group culture that’s conducive to new ideas and achieving results that are important to the company as well as for our reputation, both as a research lab and as individuals.

Q. Now just a few rapid-fire questions: Beach or mountains?

Mountains.

Q. Beer or wine?

Wine.

Q. PC or Mac?

PC.

Q. Paris or New York?

New York.

Q. Summer or winter?

Summer.

Q. Federer or Nadal?

Federer!

IBM scientists meet Guinness

2012-01-18T04:12:00.000-05:00

An achievement made last year by IBM scientists can’t really compare with the largest collection of Charlie’s Angels memorabilia (5,569 items), the most body piercings in one session (3,900) or the longest cucumber on record (47 inches), all Guinness World Records, but IBM’s nanotech experts have attained a Guinness record of their own. Their feat: creating the smallest 3D map of the Earth.

The map, produced on a tiny sliver of polymer, measures just 22 by 11 micrometers. To put that into perspective, 1000 copies of the map could fit within a single grain of salt.

The Guinness World Record organization recognized the handiwork of IBM scientists in Zurich, Switzerland, and Almaden, Calif., in its new book, Guinness World Records 2012. (Officially they are no longer called the Guinness Book of World Records.)

Unlike many other Guinness participants, the scientists weren’t motivated by a desire for 15 minutes of pop-culture fame. Rather, they created their tiny map to demonstrate a breakthrough in the miniaturization of complex structures. They expect their techniques to open new prospects for developing nanoscale objects in a variety of fields including electronics, medicine, life sciences and opto-electronics.

How did the IBMers do it? They used a tiny silicon tip with a sharp point — 100,000 times smaller than a sharpened pencil — to create the miniature patterns. The etching technique is very similar to how the ancient Egyptian’s used chisels on stone to create drawings and hieroglyphics.

Since some members of the IBM team are avid mountaineers, they also created a 25-nanometer-high 3D replica of the Matterhorn.

True, neither the tiny Matterhorn nor the tiny Earth map compare for sheer weirdness with the record for the greatest distance travelled with a pool cue balanced on the chin (5,472 ft 9 in), but, heck, they’re pretty darn cool.

Inventors' Corner: #8,005,773 - System and method for cortical simulation

2012-01-17T19:06:00.000-05:00

U.S. Patent #8,005,773 is for a "system and method for cortical simulation." The invention describes a method for developing a computerized brain simulation system that can mimic the cognitive systems and function of the cortex of the brain.

IBM Researcher Dr. Dharmendra Modha talks to FastCompany about this Cognitive Computing work.

“Personalized medicine will be key in the future”

2012-01-13T08:08:00.006-05:00

Q&A with Govind Kaigala

Govind Kaigala, scientist at IBM Research – Zurich since May of 2010, is a member of the team working on the microfluidic probe. Govind joined IBM after completing a post-doc at Stanford University and a PhD from the University of Alberta in Canada.

Blog moderator: Congratulations on today’s publication in Lab on a Chip of your innovative proof-of-concept technology called the microfluidic probe.

GK: Thanks, my co-authors and I are glad this paper has been accepted in Lab on a Chip.

Q: This novel silicon probe could possibly become a very useful tool in disease diagnostics and drug design. The scientific article describes the microfluidic probe to quite an accessible extent even for non-specialists, but what we’d like to know from you personally is: What inspired you to work on this?

GK: The idea of a microfluidic probe [MFP] had been evolving within our group for a couple of years before I joined IBM, but no one was assigned to work on this topic exclusively. I was hired to focus on this project, and that gave it a little more momentum. Using the probe with tissue sections too has been around in this group for some time. However, it was not until a Master’s student, Marios Georgiadis, from ETH Zurich joined our team that we decided this may be the opportunity to take on this project.

Q: What was the “Aha!” moment?

GK: Oh, that’s difficult to pinpoint. But, when we were first able to visualize liquid at the apex of the MFP head through a tissue section, we were very excited. There were other moments, like when we overstained a tissue section using the MFP quickly—much faster than conventional times—implying there also existed a time advantage in using this approach.

Q: What precisely makes this new technology so interesting for pathology?

GK: The essential aspect of this technology is that it allows a tiny biopsy tissue sample to be used more efficiently. For example, our publication refers to the need to determine optimal conditions to perform staining.

It’s like the traditional film-development process: if you underexpose or overexpose the film, you don’t get optimal results. There is a strong parallel in the case of pathology. A pathologist draws on years and years of experience to find the optimal conditions for performing tests. The present approach limits pathologists to using a single or a few markers on a tissue section, which restricts “how many questions” they can ask—and therefore how many answers they can get!

With this technology, once the optimal conditions are determined for a given marker and tissue, the pathologist may be able to apply this to a range of chemicals and yet use a limited amount of tissue.

Performing multiple tests rapidly with varying conditions on limited tissue would aid pathologists in making a decision on specific tissue sections in a more quantitative manner. Our device may therefore contribute to personalized medicine, which will be key in the future.

Q: Do you have any other fields in mind where your tool could have a significant impact?

GK: (Laughs) Oh, we have many more ideas. In drug discovery, for example, cells have to be exposed to a range of concentrations of different candidate molecules—this could easily be done with our technology.

Q: Where to you see this technology in 3-5 years?

GK: There are distinct paths we believe this technology may evolve along.

In the longer term, we hope this technology will be licensed and adopted by a pathology-based company to develop a user-friendly “closed” system, which would lend itself to the diagnostic process.

In the short term, we hope this would be widely used as a high-end tool much like a microscope within research laboratories—this would be an “open” system with full access to tubing, connectors and heads.

Q: What did pathologists say when you shared the probe with them?

GK: They love the idea. They think it could be very useful because they are incredibly keen to get more and better information from the tissue samples they work with.

Also, what interests them is that our probe doesn’t change the conventional pathology workflow. If you make drastic changes, it’s not easy to have something percolate rapidly down to the practical level!

Q: So you’re hoping this could be the next big advance in the field of diagnostics?

GK: It’s not “the” solution. It’s but one possible solution that we think is technically pretty cool and may have implications in diagnostic pathology. Of course, we have to remain realistic—this kind of thing takes years to develop and has to go though regulatory authorities before entering the market. It’s not around the corner—but we will likely see such technology used in pathology within our lifetime. We hope to see its impact sooner from its use in research laboratories.

Inventors' Corner: Patent #8,078,492 - Providing consumers with incentives for healthy eating habits

2012-01-11T21:17:00.001-05:00

In this video, IBM Senior Technical Staff Member Michael Paolini describes this invention as a method, system and program that uses data analytics to provide electronic incentives for healthy eating.

The Payoff from the IBM-Google University Research Cloud

2011-12-22T18:20:00.002-05:00

Scientists love it when their work has a direct impact on society, so Naphtali Rishe, director of Florida International University’s High Performance Database Research Center, is thrilled that much of his lab’s data is used by real estate professionals and urban planners. Check out one of his Web sites, which shows detailed maps of Miami-Dade County real estate sales data. Anybody who wants to can dive into the data in search of valuable pieces of information within a sea of geographic sales trends.

One particularly interesting project that Rishe and his colleagues themselves undertook was analysis of the impact of the Gulf oil spill on real estate values on Florida’s west coast. . At a time when a lousy economy had depressed housing values, the Gulf spill drove them down even further.

Rishe is just one of dozens of university researchers who have taken advantage of computing resources made available through the IBM/Google Cloud Computing University Initiative since the program was launched four years ago. “This is bread and butter for researchers like me,” says Rishe.

Google and IBM are in the process of completing the program now that high-performance cloud computing clusters are so widely available to researchers at reasonable costs.

With funding help from the U.S. National Science Foundation, the cloud computing initiative provided assistance to hundreds of university scientists working on research projects that could help us better understand our planet, our bodies, and pursue the limits of the World Wide Web. Overall, more than 1,328 researchers performed more than 126 million computing tasks on the IBM/Google Cloud. Researchers using the cluster have produced 49 scientific publications, educated thousands of students on parallel computing and helped support numerous post-doctoral candidates. Researchers have used the program for such diverse fields as astronomy, oceanography and linguistics.

For instance, researchers at the University of Maryland used the cloud to greatly reduce the processing time for sequencing an organism’s genome, and scientists at Kyushu University in Japan used it to produce a 3D map and satellite navigation system.

Rishe and his colleagues at FIU used the technology frequently to help them develop one of their primary initiatives, TerraFly, a tool for visualizing and querying geospatial data. The TerraFly data collection includes 7cm to 1-meter aerial photography of almost the entire United States, street vectors, parcel polygons, U.S. Census demographic and socioeconomic datasets, daily feeds from NASA and hundreds of other datasets.

IBM 5 in 5: Mind Reading is no longer science fiction

2011-12-19T08:00:00.005-05:00

Brown wearing the EPOC headset.

Editor's note: This post about IBM's 5 in 5 prediction of mind reading technology is by Kevin Brown of IBM Software Group's Emerging Technologies.

One of the many great things about working with the Emerging Technology Services team is that I am always focused on “what’s next.” For a long time speech recognition fitted into this category as the computing industry looked to make technology more pervasive to free our finger tips from typing and to help us become more productive.

We are benefitting from this today with voice recognition for our cars, smartphones and even automated phone services for banks and travel reservations.

Now that speech recognition is becoming mainstream, and many other forms of human computer interaction have come along, like touch, gesture recognition, etc., we are thinking about what’s next - or in the case of the IBM 5 in 5 - what's next by 2017. In my view there will be huge leaps made in bioinformatics - this is a large topic, so I am more specifically referring to the use of sensors to understand our thoughts.

No longer just wishful thinking

While much of the brain remains a mystery, progress has been made in understanding and reading electrical brain activity were we can use computers to see how the brain responds to facial expressions, excitement and concentration levels, and the thoughts of a person without them physically taking any actions.

So the idea is to use these electrical synapses to also do everyday activities such as placing a phone call, turning on the lights or even in the healthcare space for rehabilitation. In fact, that is what initially inspired me to look at this field more closely.

In March 2009, Shah, an IBM colleague, had a stroke which left him completely paralyzed, unable to use his muscles, and without the ability to speak. His brain however was working fine - a condition called Locked-In Syndrome, which means he can only communicate with his eyes - looking up for yes, and down for no.

Coincidentally, my wife happened to be his occupational therapist and I demonstrated to her a device that I had recently been investigating called the EPOC from Emotiv. The device has several sensors sitting on your head, that actually read electrical brain impulses. You can train the device so that by thinking a particular thought, an action can take place on your computer. So for example, using Emotiv's software, you can see a cube on your computer screen and think about moving it to the left, and it will. While I was initially interested in connecting it to email systems and smartphones for business users, it immediately became clear to us how this could help Shah.

Shah being a techie himself was open to testing it out. Amazingly, after only 8 seconds of training, he could move the cube at will on the computer screen. We then connected the device to software which could eventually allow control of the environment. The concentration needed whilst operating the headset is quite a lot, however, so more development of the technology and more training in using the headset may be needed to make it entirely effective. I'm sure this will continue developing within the next 5 years.

This isn’t the only example of progress in this area. Scientists at UC Berkeley have designed and developed a special MRI scan that can model our visual thoughts both while we are awake, but even more intriguingly, while we are dreaming.

All in the Applications

This is a case where the technology has now become cheap enough and mobile enough to become a consumer device but it will take the development of some compelling applications and innovative, imaginative uses over the next few years to really make people eager to use it.

By 2017, like all technology, the EPOC or other similar technologies will probably get smaller. So I can imagine it will have completely dry sensors, and I'd be wearing it all the time, perhaps embedded into a baseball cap, and with a finer range of thought patterns detected and connected directly to my mobile phone - allowing me to interact with the world just by thinking particular thoughts. In doing this I could wonder what the traffic will be like on the way home and this information would pop up in front of me.

If you also think about smarter cities, if everyone is wearing the device and open to sharing their thoughts, city heat maps could be created to see how people are feeling to create a picture of the mental health of a city. Or musicians could create elaborate pieces based on what they are thinking about.

The applications are endless, we just have to build them.
Think this topic is the most-likely prediction, or maybe just the most innovative, among the Next 5 in 5? Vote for it by clicking "like" on IBM's smarter planet.

IBM 5 in 5: Biometric data will be the key to personal security

2011-12-19T08:00:00.004-05:00

Editor's note: This IBM 5 in 5 prediction about biometrics is by IBM Fellow and Speech CTO David Nahamoo.

Everything we do online, or via a computer, requires authenticating who we are – user IDs and passwords are our safeguard. But the security isn’t foolproof. Our IDs and passwords can be stolen and our mobile devices can be lost or stolen.

Over the next five years, your unique biological identity and biometric data – facial definitions, iris scans, voice files, even your DNA – will become the key to safeguarding your personal identity and information and replace the current user ID and password system.

It’s not all about what you know

We know that security improves by combining different biometrics with different methodologies. So, we typically use three ways to authenticate each other:

•   What you have: a badge or ID card
•   What you are: how you look, speak, walk
•   What you know: a secure piece of information or password

Think about what we have to do to authenticate our access for something online: create user IDs and passwords; set up hint questions and site keys for dozens of accounts. Personally, I have a very difficult time remembering more than 50 account log-ins and passwords that I have.

Smart device, smart security

We have been moving from devices like desktops and laptops to smart devices such as mobile phones and tablets – all property that is easily lost, stolen or misplaced. These devices are not yet outfitted with operating systems and security elements that are as strong as immobile devices of the past. Biometric security can strengthen those weaknesses.

Biometric data will allow you to walk up to an ATM and access your bank account by simply speaking your name and looking into the camera. Yes, we’ve all seen the thriller sci-fi movies where a person is forced by the villain to scan their eye or finger to unlock a door. But that’s fiction. In reality, ATM cameras using facial and iris recognition may be able to detect stress, pupil dilation, and changes in heart rate and breathing patterns to establish a confidence level that the user is not in danger.

We can take advantage of the advanced technology being used in the smart devices, such as microphones, touch screens and high definition cameras to fully employ biometric security options. While there is already some adoption of facial and voice recognition, combining these and other biometric data points in the near future can eliminate the hassle of memorizing, storing and securing account IDs and passwords and at the same time give users a greater security confidence.
Think this topic is the most-likely prediction, or maybe just the most innovative, among the Next 5 in 5? Vote for it by clicking "like" on IBM's smarter planet.

IBM 5 in 5: Mobile is closing the Digital Divide

2011-12-19T08:00:00.003-05:00

Editor's note: This post about IBM's Next 5 in 5 prediction about the future of mobile computing is by Paul Bloom, IBM's Chief Technology Officer for Telco Research.

Think about what you can already do with your mobile smartphone – check your bank account, tweet, watch television, and oh yeah, make a call. But all of this access still depends on where you are, and you have to initiate the communication.Over the next five years, mobile devices will assist you in your daily life by initiating the communication with you and providing helpful information based on your context. For example, when you order your lunch from your cell phone, you might get a message recommending a healthier selection, based on the restaurant and your personal profile.

Since your phone will also be your wallet, bank and record keeper, your cell phone will let you know what the impact of this lunch will be on your budget and may modify the recommendation based on predicted cash flow. This is only one example of how your mobile device will have access to the results of predictive analytics based on your location, context and personal information, aiding you in every facet of your life.

Freeing up today’s networks

As more people use mobile phones, the network will take on more workload. Today, wireless data networks are already overloaded because of what we’re sending over them – high definition videos, for example. To meet the demand of all these mobile centric services, we have to optimize and extend the network.

For example, when you download a video, the request goes to a server and all that data gets shipped from the server, down to your device.

How it could change: if the network knows that you, and your neighbors, are watching that HD video, it could be stored in another location (off the server), so that it’s closer to where the videos are being watched.

Or, peer-to-peer access – which harkens back to the early days of computing when companies and universities shared unused compute capability for a task – could turn our mobile devices into a point in the network. If you have bandwidth that you’re not using, someone else who needs additional bandwidth communicates with you to get that additional access.

Communicating at any time from any where

In five years we will see the massive introduction of machine-to-machine based services. So people won’t initiate communication for information; rather, systems will initiate communication and data to the mobile users. For example, your mobile will have access to your electronic healthcare records while also monitoring your vitals, such as blood pressure, in real time. Now, a system could notify and connect you to a doctor if your blood pressure is out of a normal range.

And paper currency will also become obsolete as transactions will go from mobile to mobile. As security issues and banks’ roles are worked out, we will be able to buy and sell goods, lend money to a friend, and more. Countries that don’t have to battle legacy telco infrastructure are leading the way. Kenya, for example, does not have a traditional banking infrastructure. So, you’re seeing telcos offering mobile banking to provide micro-transactions.

Industry regulations, security controls, and improved bandwidth and speed (in the case of countries with legacy infrastructure) will determine how quickly these capabilities and services become available.

Think about this: your mobile device knows where you’re going, where you’ve gone, what you’ve bought, where other people have gone and bought, and other data that could change the way people start thinking about their daily routines (commuting, shopping, investing, etc.). With this whole new set of data that we can apply predictive analytics to, I could predict how a behavior – say, eating fast food – would affect my current health.

Some industrial nations such as South Korea are fast approaching these capabilities. Others you may not suspect, such as Africa are poised to become a “have” in the mobile industry, too. Countries not keeping up (including a “have” like the U.S.) could mean not just weak signal strength in a rural area, or a slowly downloading video – it could prevent the penetration of entire services.

Think this topic is the most-likely prediction, or maybe just the most innovative, among the Next 5 in 5? Vote for it by clicking "like" on IBM's smarter planet.

IBM 5 in 5: Generating energy from unexpected sources

2011-12-19T08:00:00.002-05:00

Editor's note: This post about IBM's Next 5 in 5 prediction about future energy sources is by IBMDistinguished Engineer Harry Kolar.

It happens all the time; you forget your cell phone charger at home, and your smartphone battery runs out after hours of email and Angry Birds. But what if you could recharge your cell phone using power you’ve generated simply by walking?

Anything that moves has the potential to create energy. In the next five years, advances in renewable energy technology could make it possible for us to draw on power generated by everything from our running shoes to the ocean’s waves.

Your body will become an energy-generating machine

Walking involves a variety of dynamic forces. The strike of your heel on the ground and the bend of your sole release a lot of dissipated energy.

These simple movements can become a power source, enough to charge your cell phone, with the help of small device with an antenna inserted into the sole of your shoe.

This science -- parasitic power collection -- pulls and transmits energy created by the slightest movement.

Think about the possibilities. A device on the spokes of your bicycle could measure and collect energy that’s then transmitted to power your kitchen appliances. The water running through your pipes could power on the lights in your house.

Now think bigger: what could you do if you could harness the energy of the ocean?

You can harness the power of the ocean

Wave energy and tidal energy are developing forms of clean energy that are virtually limitless. They’re clean, renewable, and will lessen the strain on our traditional power grids.

Wave energy and tidal energy are collected from the ocean in different ways. Most wave energy converters float on the surface of the water and use various designs to generate electricity. The tidal energy converters typically sit on the sea floor and are completely submerged. They look like large turbines or propellers that spin with the incoming and outgoing tides. Tidal energy is quite predictable due to the periodic nature of the tides, while wave energy requires more complicated modeling to predict characteristics over time.

Before we can make use of these energies, however, we need to understand and minimize their environmental impact. For example, the devices that collect and convert wave and tidal energy generate noise underwater that can affect marine life.

My team is working with The Sustainable Energy Authority Ireland to use real-time streaming analytics that monitor the underwater noise and track its potential impact on the marine environment. That data will be shared across the wave energy industry to help build a clearer picture of how this type of technology can be safely, sustainably used and controlled.

Beyond the obvious benefits like cleaner power, using the ocean’s energy could have significant economic benefits.

High-wave energy conditions exist in many areas around the world and could have real value for coastal countries like Ireland, which has one of the largest concentrations of wave energy in the world, yet had to import about 86 percent of its energy (mostly fossil fuels) in 2010.

The economic ecosystem that will surround wave energy generation sites will involve many parties and bring considerable investment. Power companies will become involved to provide grid connections. Specialty disciplines in marine engineering will be involved in ways like care and maintenance for the sites.

Information Technology will be a key participant in this process too. The integration of leading-edge technologies like advanced analytics and smart grid components will help connect and manage new renewable resources and ensure operational efficiencies as well as consistent and predictable performance.

IT will be needed for monitoring, analysis, simulation and modeling. IT will also help monitor and capture the economic performance of the technology and further support the application of these new renewable energy sources.

Making it easy to make smarter energy choices

Now more than ever, we’re starting to understand the need to conserve energy. With populations growing and electricity demand expected to grow at 2.2 percent per year to 2035 (according to the World Energy Outlook 2010), our current energy infrastructure is just not enough.

But our consumer decisions are motivated by factors like convenience, comfort, cost and the opportunity for digital connection. We need access to the right tools and information to make smarter energy consumption decisions, and those tools are getting closer to reality thanks to technology like parasitic power collection and wave and tidal energy.

Think this topic is the most-likely prediction, or maybe just the most innovative, among the Next 5 in 5? Vote for it by clicking "like" on IBM's smarter planet.

IBM 5 in 5: Big Data & sensemaking engines start feeling like best friends

2011-12-19T08:00:00.001-05:00

Edior's note: This IBM 5 in 5 post about Big Data and analytics is by Jeff Jonas, IBM Distinguished Engineer and Software Group's Chief Scientist of Entity Analytics. He blogs here, www.jeffjonas.typepad.com and can be found on Twitter @jeffjonas.

Click through rates for unsolicited advertisements range from near zero to roughly five percent. From the recipients’ point of view, just about every such communication is more time wasting spam.

Imagine a future where some sources of unsolicited advertisement produce such useful and perfectly timed ads, that you would signup. A world where virtually ever text message or email pushed at you is so relevant that this “service” starts feeling like a best friend.

Here at IBM we are working on sensemaking technologies where the data finds the data, and relevance finds you. Drawing on data points you approve (your calendar, routes you drive, etc.), predictions from such technology will seem ingenious.

Imagine this: You actually sign up for such an unsolicited advertisement service. Three days later, it has suggested nothing. Why? Because there wasn’t anything worth your attention. But on day four, 10 minutes before you hop in the car to drive to a meeting over coffee, you get this text: “Don’t take the 405, take the 110, then exit 10b, and 3 blocks up there’s a Starbucks.”

You think: Well that is nuts; my coffee shop meeting with my buddy Kenny is at least 15 miles from there. So you text “?” as a reply.

The answer: “Big accident on the 405, will affect Kenny too; already cleared this with him, and this Starbucks is the proposed compromise when considering all the factors.”

Now you could text another “?” to see what these other factors are, but you know it’s pointless. As you pull out of your driveway you are thinking “I love you” as you think about this new best friend in your phone.

This new era of Big Data is going to materially change what is possible in terms of prediction. Much like the difference between a big pile of puzzle pieces versus, the pieces already in some state of assembly – the latter required to reveal pictures. This is information in context, and while some pieces may be missing; some may be duplicates; others have errors; and a few are professionally fabricated lies – nonetheless, what can be known only emerges as the pieces come together (data finding data).

Big Data in context is one of the most significant trends in the information technology field.

This type of technology is going to be real time. Today, smart insight being produced at the end of every week, after a customer left a web site or after a bank already approved a loan only leaves organizations wondering why the answers are so late. Sensemaking systems will deliver sub-200ms insight, fast enough to do something about a transaction, while the transaction is still happening (aka perfect timing).

We at IBM are well down this road towards massively scalable sensemaking analytics. And whether you will benefit by ingenious advertising services (versus spam) or better health care outcomes, the future will bring higher quality predictions, faster.

Think this topic is the most-likely prediction, or maybe just the most innovative, among the Next 5 in 5? Vote for it by clicking "like" on IBM's smarter planet.

Dr. Lawrence Lippitt, author of "Preferred Futuring", Visits IBM Research - Zurich

2011-12-12T04:19:00.005-05:00

5 questions with Dr. Larry Lippitt

Q. What is "Preferred Futuring"?

Larry Lippitt. Preferred Futuring is a way to engage everyone in the system to be able to communicate with each other. Communication is so important and so basic to operating as an organization effectively and, nowadays, it happens so very quickly, too.

Preferred Futuring helps people come together and discuss “How on earth did we get to where we are?” and “Where are we, actually?”

Once we’ve agreed on these issues, we can discuss “Do we have any values or beliefs that have participated in getting us there?” because our basic values and beliefs affect the way we behave.

And finally, “What are some of the trends and developments on the horizon?”. As we hope and plan to arrive at the future we want, we need to ask, “Which trends might impact us?” So we need to be smart in our strategic thinking.

Then, collectively, we all participate in determining “Where to we want to be?” Not, “Where should we be?” or “Where ought we to be?” but “Where do we want to be?” It’s about listening to the passion in my heart that says “This is exciting, and I want us to get there together.”

We need to talk with each other in order for us all to work together towards getting there. This is then followed by planning and implementation. That’s basically the process.

Q. The event today is about inspiration transformation. Can you explain?

LL: I have to smile at this because sometimes the process generates so much energy that you just have to get out of people’s way. Inspiration transformation comes from the sudden understanding that we’re all on the same page, or when you recognize what our whole system looks like and think, “Wow, I never knew.”

So the idea is to exprience this sensation together, suddenly, as part of an integral system, not just you over there and me over here. When we begin to see that and experience that, the energy grows. Then we can talk about some of the hard questions, such as “What are we doing right?” as well as “What are we doing wrong?” because everything we’re doing isn’t wrong, of course.

We begin to get a complete picture, a balanced view of where we really are, not just of all the problems we have. Then when we share the vision with each other, it’s like splitting the human energy atom! There’s so much motivation and the ability to innovate, to think outside of the box I was in just a little while ago.

The process gives us the inspiration to continue together, and it gives us the motivation from that energy.

Q. Based on your 30 years of experience, are there any tricks that you can share?

LL: You know, being an effective leader is really not that complicated. It seems that way because there’s so much to do and so much to take into account. But it is really about connecting with the other person. Not letting the fact that you’re the leader or I’m the leader and you are to be led, whatever—not letting that intervene with the fact that we are people and we need to work together to get a job done.

As a leader you need to know that we don’t get anything done unless we can work together as colleagues, as equals, although there may be an unequal status because someone is the designated leader. But it’s important to let that not get in the way.

The other thing is respect and courtesy. These are basic things we should have learned in kindergarten. Respect means that, well, maybe I’m not quite sure about your ideas, but because they’re your window on truth, it is important that I as the leader listen to you.

Because when you listen to that truth, suddenly things change. You have to try to understand the other person through their own eyes. Something magical happens when you’re able to work together and communicate with each other and this enhances the leader’s ability to have empathy.

Q. As we honor 100 years of IBM, any personal anecdotes?

LL: (Laughs) Well, this goes way back in history—because I also go way back. There was the stereotype that, at IBM, everyone was all buttoned-down, we all wore dark suits and ties. One time I was at a facility outside of Boulder, Colorado. I was coming to work one morning and had this little pop! of inspiration about leadership. I was one of these buttoned-down guys, and just had this surge of inspiration.

I don’t think many people at IBM wear dark suits anymore, certainly not in the techie part of the organization—so that’s one memory that makes me laugh.

Q. Any advice for future leaders?

LL: You know, it may not seem a fashionable approach right now because leaders are supposed to direct others and so on. But I think it’s essential to learn the skills that help people do their job, to listen and do those very human things that support the people you work with to do their job better. To develop the skills that let you be helpful and facilitate the processes relating to the work.

Many thanks, Dr. Lippitt, for these very interesting insights.

LL: It was my pleasure, thank you.

The Future of Healthcare

2011-12-06T09:17:00.010-05:00

The introduction of so much new digital medical information is transforming the decision-making process in the healthcare ecosystem. Patients often seek out information before they speak to a doctor, and clinicians are using computers to help with diagnosis or with the selection of treatment options. In short, what used to be an intimate doctor-patient twosome has now become a threesome: the doctor-patient-computer triangle. But do all three entities in this new relationship have an equal say in what decisions are made?

IBM Research – Haifa hosted a healthcare colloquium in honor of IBM's centennial, convening thought leaders from the healthcare community to discuss this new transformation and its implications for the future.

Perspective on the past and vision for the future

IBM researchers in Israel pioneered some of the first IBM projects in the areas of information-based medicine, standards for medical data, interoperability for medical imaging, and clinical genomic analytics. Today, the lab specializes in research related to the integration of vast amounts of medical information and gaining insight from this data by enabling access and sharing.

The researchers have developed an online system that provides clinicians with a prediction of which drug or drug cocktail will be the best for treating a given patient infected with a specific HIV virus. In another project, they created a secure web-based system that allows public health institutions and centers for disease control to electronically share public health data—even across geographical and political borders in the Middle East.

Another project reinvents the patient portal, enabling patients to integrate and manage their healthcare data for all medical needs, receive personalized recommendations or alerts for safer medical treatment, and immediately access data from a vast range of sources.

Yet even with the support of the most sophisticated technology, noted Prof. Jonathan Halevy, of the Shaaeri Zedek Medical Center, the foundation of the doctor-patient relationship remains unchanged. "There is still no substitute for face-to-face encounters between physicians and their patients. The doctor will never be optional."

Watch all of the event's presentations

Keynote Address
Dan Pelino, General Manager of Healthcare and Life Sciences, IBM

The Doctor-Patient Relationship in the Internet Era
Prof. Jonathan Halevy, Director General of Shaare Zedek Medical Center

The Digital Transformation of American Radiology
Dieter Enzmann MD, Chair of UCLA Radiology

Panel: The New Doctor-Patient-Computer Triangle
Participants: Dan Pelino, Shmuel Reis, Kobi Vortman PhD, and Prof. Eddy Karnieli; Moderated by Yardena Peres

Advanced Decision Support Technology – IBM Watson for Healthcare
Dafna Sheinwald PhD, IBM Research – Haifa

From Biological Discovery and Personalized Medicine: The Role of Computation in Human Genetics
Itsik Pe’er PhD, Columbia University

Clinical-Genomics Decision Support at the Point of Care
Boaz Carmeli, IBM Research - Haifa

Closing Remarks
Aya Soffer, Director of Information Management Analytics, IBM Research – Haifa

Poster Session

How to build computers of the future

2011-12-05T12:37:00.002-05:00

Researchers at IBM are building computing devices of the future - but you're less likely to find them focusing on the slimmer, smaller, lighter, sleeker, sexier holiday gift-giving gift ideas. IBM's top computer scientists, physicists and chemists can instead be found improving compute power based on advanced physics discoveries; decreasing the size of transistors while improving performance; and even developing circuit architecture that'll give you better cell phone reception and protect devices against radiation.

And IBM's $6B annual investment in R&D doesn't just mean playtime in the lab. Today, 10 of IBM's research papers were recognized at the IEEE International Electron Devices Meeting. The conference, in its 60th year, is hosted by the world’s largest professional association dedicated to advancing technological innovation and excellence for the benefit of humanity.

Here's a look at what IBMers are contributing to the future of computing:

Racetrack Memory

Photo Caption: IBM Research - Almaden's Stuart Parkin is a pioneer in racetrack memory. Lightning-fast boot times anyone?

Combines the benefits of magnetic hard drives and solid-state memory to outsmart Moore's Law (increased power demands, shrinking devices)
For the first time, IBM researchers are marrying Racetrack memory with CMOS technology (on which virtually all electronic equipment is built)
Improves density, potentially allowing massive amounts of info to be accessed in less than 1 billionth of a second

Graphene

Photo Caption: Earlier this summer, IBM Research unveiled its first wafer-scale graphene integrated circuit smaller than a pinhead

The first ever CMOS-compatible graphene device can advance wireless communications and enable new high-frequency devices operable under adverse temperature and radiation conditions
Resesarchers have developed a new technique to improve the structure of graphene transistors, proving stability at far higher temperatures than previously achieved

Carbon Nanotubes

Photo Caption: Carbon nanotubes have been used to develop improved solar cell technology, and IBMers have discovered excellent off-state behavior in extremely scaled devices - an energy-saving technique

IBM researchers demonstrated the first carbon nanotube transistor rated at less than 10 nanometers, which easily outperforms the best competing silicon-based devices
Nanotechnology discoveries like this point to improved solar cell technology

To read the technical details of IBM's three breakthroughs, check out the IBM press release. The Wall Street Journal's Don Clark interviewed IBM Fellow and VP of Innovation Bernie Meyerson in this story.

Dave Ferrucci at Computer History Museum: How it all began and what's next

2011-12-01T14:37:00.000-05:00

CHM President John Hollar

In front of what Computer History Museum president John Hollar called "the largest crowd for a Revolutionaries lecture" that he's ever seen, IBM Watson principle investigator Dave Ferrucci sat with Financial Times' Richard Waters on November 15th for a conversation about "A Computer Called Watson." To the audience of about 450 Silicon Valley techies, influencers, teenagers and inspired engineers, Dave kicked off the conversation by explaining how Watson came about; and it began with the notion of natural language processing, namely, contextual aspects of language.

"At our house, I'd always call the kids down to see something 'interesting' that I'd done - some type of experiment or science-related thing," Dave said. "After enough of these demonstrations, my daughter started to associate the word 'interesting' with 'boring' - so there's a little about language context."

IBM Watson principle investigator David Ferrucci (left)
with Financial Times' Richard Waters

It turns out Dave was headed toward a career in medicine and was pursuing an M.D. rather than a Ph.D. But the biology major quickly developed a fascination with artificial intelligence, and a passion for programming. "I thought it was incredible that you could tell the computer what to do - and that it would do it," he said.

After obtaining his BS in biology from Manhattan College, he pursued computer science with an emphasis in knowledge representation and reasoning at Renesslaer Polytechnic Institute, completing his Ph.D. in 1994.

Since joining IBM in 1995, Dave has contributed largely to the Research function as a computer scientist. But in 2007, when IBM executive Charles Lickel challenged Dave and his team to revolutionize Deep QA and put an IBM computer against Jeopardy!'s human champions, he was off to the races.

"I had to get funding," Dave explains. "I told the executives I could do this in 3-5 years. I kind of just guessed."

The executives bought it, and Dave had a huge task ahead. By assembling a team of eventually 28 researchers in the areas of natural language processing, software architecture, information retrieval, machine learning and knowledge representation and reasoning, Dave created Watson - a computer system, that, using a combination of sophisticated hardware and software, could understand natural language and deliver a single, precise answer with confidence and evidence for its decision.

At the end of the conversation, Dave told the crowd about Watson's new job in the medical field: "We want Watson to enable better judgement by humans in decision-making, whether it be in medicine, law, finance or services," Dave said. "While the human is the ultimate decision-maker, Watson will provide evidence and confidence by scouring millions of sources of related information in a short amount of time."

GigaOm's Stacey Higginbotham takes on IBM's Watson
and Sierra Ventures' Robert Walker in an exhibition match

In an exhibition Jeopardy! game following the talk, IBM's Eric Brown was the ultimate Alex Trebek, hosting players GigaOm's Stacey Higginbotham, Sierra Ventures' Robert Walker, and "oh yeah, our third contestant, Watson, from Yorktown Heights, New York, built by a couple of computer scientists," an introduction met with laughter that would continue throughout the game.

The humans playfully 'teamed' up against the computer,
high-fiving and fist bumping on each correct answer

The animated human contestants instantly won over the crowd after trailing Watson through the first part of the game. In fact, when Stacey buzzed in with the first correct question for the humans, the crowd went wild.

The night continued in that way, and the human contestants even found themselves getting answers from the crowd, to which host Eric Brown responded: "Watson can't hear you, so humans have an advantage!" As it turned out, the trick was buzzing in before Watson - hard to do unless you're a seasoned Jeopardy! vet like Ken Jennings or Brad Rutter.

As the exciting match wound down, and all three contestants answered the Final Jeopardy! question correctly, Watson came away with the win, but left the auditorium with tremendous enthusiasm for this computer and its impact on the future of technology.

You can watch the entire presentation on YouTube:

More from the event:

Pre-game (post-practice game) thoughts from contestants*:

*apologies for the incorrect orientation

This post originally appeared at ibmresearchalmaden.blogspot.com on Friday, November 18, 2011.

Modeling the planet's future

2011-11-29T11:10:00.005-05:00

5 Minutes with Dr. Robert Bishop, President, International Center for Earth Simulation (ICES)

Q. What is ICES?
Robert Bishop: The acronym “ICES” stands for the International Center for Earth Simulation. We see this as a long-term issue. It’s a very ambitious mission to bring together all the sciences which are currently siloed separately. They don’t talk to each other enough.

As a consequence I don’t think the destiny and the future of the planet is well understood because, until we integrate these sciences horizontally, and have them talk to each other, we really don’t know the best model to simulate the future of the planet.

Q. How does this compare to Google Earth?
RB: Google Earth is a beautiful fly-through of a static database. We want to put dynamics on top of that database so that we could see the weather and the climate, for example, and the environment and biodiversity and even the interaction of the earth with the sun through space weather and all the layers of the ocean and the layers of the atmosphere: We’d like to see it dynamically in a model.

It’s a very complex model, of course. It takes a lot of computing power to create that model and that visual output. But Google Earth is a very good first step. The public is very happy with it as a way of displaying static data. We want to create simulated model dynamic data.

Q. What is the biggest challenge?
RB: Today we have petaflop computing. The top ten computers of the world are all above one petaflop. The next level up in computing has a thousand times more power, called an exaflop. That’s where we’re heading right now in the industry as a whole.

I believe it will take an exaflop to solve the problem that ICES is presented with, which is the integration of all the sciences. There’s too much complexity to compute with today’s level of computing. We can’t get enough compute power to do the job.

We are expecting a thousand times more power in the next ten years and maybe a million times more power in the next 20 years. We are expecting that and we will need it to solve the problems of ICES.

Q. If this all works out, will we then have the power to predict natural disasters?
RB: Well, I think in the case of the natural sciences, beginning with the ocean, the weather and the climate, those things are becoming more and more predictable. If you take the history of the past thirty years, we have improved numerical weather prediction dramatically. I would say today it’s 90% predictable out to five days. Out to ten days its maybe 80% predictable.

The question is, as we go to out a month, a season, a year, interannual, and then ten years or more: what level of predictability can be get if we have more compute power and more data to assimilate.

I think the answer to every one of those questions is that we will be improving predictability but there will never be 100% predictability.

So, in talking to the public, the question is how we talk about uncertainty. How we engage the public in a broader discussion about the future of the planet on the one hand, but on the other hand we have the caveat of how much uncertainty is there in that discussion.

Q. What about citizen science tools, such as World Community Grid?
RB: The citizen science movement is very powerful. I like it, and I think it’s getting more powerful, especially as smart cellphones become available to perhaps the entire population of the world.

The idea of having 7 billion smartphones available for computation is pretty good. It requires a lot of software to bring it together, but I’m thinking more about the data that can be provided on those phones.

For example, over the next 10 years I think it is possible that these phones contain a single-chip automatic weather station. Together with GPS, that data would be very handy for a global simulator to simulate the weather in the future. I look upon it as a data entry point.

Today, if you take some of the developing countries, which have not had many computing resources of their own, the smartphone is actually penetrating those countries very quickly. They could benefit from having output from a global simulator, which would tell them what’s going to happen in their local weather.

It would be a regional downscaling from a global model, which would be helpful for running their own economies.

Q. What can 425,000 IBMers do to help?
RB: First of all, it’s a fantastic group of people, a fantastic company. They’re very professional. I’ve known this company for 45 years of my professional career.

I would love to see a partnership develop with IBM and I think IBM’s concept of standing for a smarter planet—using more intelligence. The ICES’ mission fits exactly within that scope.

The employees of IBM are very powerful and highly respected around the world. So having them contribute their ideas, their engagement with ICES would be wonderful. I would suggest they take a look at our website and let me know how you’d like to connect and participate. I’m quite open.

This is a not-for-profit mission. It’s Swiss-based, a neutral country with a lot of scientific intelligence and integrity. From that point of view I think it could be a good focal point for such a global project. I would very much open up to any inputs or suggested methods of collaboration with IBM and its employees.

Thank you for your time this evening.
RB: It’s been a great pleasure to be here.

Portuguese IBM Scientific Prize Awarded

2011-11-24T05:40:00.001-05:00

The IBM Scientific Prize 2010 was recently presented to Alexandra Silva, for her PhD research at the Centrum Wiskunde & Informatica (CWI) in Amsterdam. Her paper is titled Quantitative Kleene coalgebras.

Silva received the prize during a ceremony in Braga, Portugal, with Education and Science Minister Nuno Crato and IBM Portugal President Jose Joaquim de Oliveira. The award consists of a charter and 15,000 EURO prize.

A copy of her presentation can be downloaded here.

Silva is currently working as an assistant professor at Radboud University Nijmegen and as a research visitor at CWI in Amsterdam, the Netherlands.

Established in 1990 the IBM Scientific Prize is the most important Portuguese award for high scientific merits in computer science and is meant for researchers younger than 36 years. This year also marks the first time a woman has been recognized.

Alexandra Silva finished a degree in Mathematics and Computer Science at the University of Minho (UMinho). Being a PhD student at the Centrum Wiskunde & Informatica (CWI) in the Foundations of Software Engineering (SEN3) research group, she defended her thesis ‘Kleene Cooalgebra’ at the Radboud University Nijmegen (RUN) in 2010, passing ‘cum laude’. She was awarded a postdoctoral fellowship in the HASLab group at UMinho and also won a contest to become Assistant Professor in Nijmegen. In the past, she was also research visitor at Cornell University, and post-doctoral researcher at CWI.

Source: UMinho Portugal and CWI

Linking genes over generations

2011-11-21T08:14:00.022-05:00

Editor’s note: This is a guest post by Dr. Ajay Royyuru, the senior manager of IBM’s Computational Biology Center.

We started the Genographic Project with National Geographic six years ago, and the first thing we worried about was how the general public would respond to our request for their DNA. There’s nothing more personal than that.

Well, we ran out of our initial supply of 30,000 kits – and reached 100,000 DNA samples – in the first year! (I personally didn’t think we would hand out the 30,000 kits over the five years of the project.)

Genetic Privacy
The ethical insight used on the Genographic Project helped IBM form its Genetic Privacy Policy. The policy was one of the testimonies IBM provided in a US Congressional hearing that led to the passage of the Genetic Information Non-discrimination Act in 2008.

Read the IBM testimony to the House Education and Labor Subcommittee on Health, Employment, Labor and Pensions.

What did we do right?

Having a thorough and well-communicated ethics policy led to why we succeeded in collecting the 470,000 samples. We assured the public that though we’re taking their DNA, participation would be anonymous; the DNA would be used only for determining the migratory history of humankind; and that their DNA would not be analyzed for clinically informative markers (such as a family history of hypertension).

Tracking paternal and maternal ancestry

At the outset, we analyzed two pieces of genetic evidence in the Genographic Project. First, looking at the entire human genome, certain fragments pass from one parent to a child that does not mix with the genetic information from the other parent. In males, this is the Y chromosome.

The Y chromosome goes from father to son with almost no modification. But the transition is a bit like copying a book by reading and re-writing – occasionally there’s a typo. That typo is what we call a mutation, or a marker of descent.

A mutation may only appear in one copy of one instance of DNA that could be passed from father to son. For example, only one of two brothers may get the mutation. Now, they are marked by this difference and the brother with the mutation (and his descendants) will carry that marker. We can see that mutation and track the male descendants for generations, back to the first male who showed that marker.

The other piece of genetic evidence we tracked also comes from genetic fragments that can only pass from one parent to a child. DNA contained in mitochondria, structures in the body of every human cell, is passed from a mother to all of her children and provides a means of tracing a maternal line of ancestry.

Genome recombination

Y chromosome and mitochondrial DNA constitute less than 1 percent of the human genome. The rest of the genome is not directly inherited from a single parent. Rather, it undergoes a process of recombination, effectively shuffling fragments of DNA from each parent to create the unique genome of each child.

Tracing the ancestral history on genomic regions besides Y and mitochondrial is a daunting task, confounded by the active recombination that occurs every generation.

Crunching the genetic data

IBM in Genetics

IBM has invested in genomics and computational biology, for more than 15 years. These are disciplines that inform the life science, pharmaceutical and biotechnology industries. IT plays a vital role in enabling new science and discovery in biology, transforming the field into an information science.

We worked with population geneticists in various regional centers across the world to analyze this genetic data in populations of Sub-Saharan Africa, North Africa, the Middle East – and other regions are being concluded. Results published so far about the migratory history of the earliest humans in Africa include genetic evidence of relatively recent migratory events, such as the arrival of Crusaders in the Middle East, and the spread of the Phoenicians into the Mediterranean.

But the computational task of analyzing the data of our 470,000 samples is not a brute force exercise. A supercomputer is not required. Laxmi Parida, a member of the IBM team led a three-year effort in collaboration with Jaume Bertranpetit at the University of Pompeu Fabra in Spain, to develop an elegant algorithm that reconstructs recombinant history of the genome – using only workstations. They analyzed markers on the X chromosome of 1,240 male participants, from 30 different ethnicities across Africa, Middle East, Europe, and Asia.

On the point of migration, our findings showed that Eurasian groups were more similar to populations from southern India, than they were to those in Africa. This supports a southern route of migration from Africa via the Bab-el-Mandeb Strait in Arabia, before any movement heading north. It suggests a special role for South Asia in the “out of Africa” expansion of modern humans.

Keep in mind, exactly which direction or route humans took in migrating out of Africa is still not settled. This new genetic evidence suggests that other fields of research such as archaeology and anthropology should look for additional evidence on the migration route of early humans to further explore this theory.

How to participate

Visit the Genographic Project website to order a DNA kit. IBM employees can order a kit, internally, here.

"It’s exciting when an experiment finally works"

2011-11-21T07:31:00.002-05:00

IBM scientist Werner Escher received the 2011 HILTI Award for innovative research for his outstanding PhD thesis on new liquid cooling technologies for microprocessors. The renowned technical university ETH Zurich issues this award every year in recognition of a thesis or other research paper in the fields of physics or engineering that excels in combining extraordinary scientific research with practical use.

Photo Credit: ETH Zurich/ Oliver Bartenschlager

Werner, currently a research staff member at IBM Research – Zurich, studied mechanical engineering and wrote his PhD thesis entitled "Ultra Thin High Efficiency Heat Sinks with Water or Nanofluid for Electronics" at ETH Zurich and IBM Research – Zurich between 2006 and 2009.

His thesis describes the development of a high-performance liquid-cooled microchannel heat sink to mitigate the daunting issue of efficiently cooling today’s microprocessors as well as those of future generations.

Werner is a member of the research team that pioneered Aquasar, a hot-water-cooled supercomputer. Installed at ETH Zurich, Aquasar uses microchannel liquid coolers to cool the chips with 60°C hot water, which is then redirected to heat the campus buildings. This reduces energy consumption for cooling by 40% and lowers the supercomputer’s carbon footprint by 85% compared to traditional air-cooled systems.

We interviewed Werner about his research, his experience as a graduate student at an industrial research lab and why he chose a career in science and technology.

Can you explain the major issues that you address in your research?

Microprocessors dissipate large amounts of energy with high heat flux densities that are several times higher than those of a hotplate. The goal of this work was to develop new means to remove these very high heat fluxes efficiently while minimizing the volume occupied by the cooler itself. This was achieved by implementing microchannels into the heat-dissipating chip and introducing a hierarchical network that distributes the liquid efficiently to the individual microchannels and minimizes the power required to pump the liquid through the microchannels.

What makes this work so fascinating?

It’s great to see how it all comes together in the end. At the beginning you generate some initial ideas, then you refine them based on calculations and numerical simulations to identify the most promising solutions. It’s exciting when an experiment finally works and confirms your initial predictions.

Have you always known you would pursue a career in research?

I was always interested in new ideas and technologies in general and how they can contribute to fulfilling a given functionality. This was also what motivated me to study mechanical engineering because it nicely combines basic research with the final application.

Any advice to students on how to achieve outstanding results? What’s your secret?

That’s difficult to say. In the end you need to find your own path. I think it’s important in general to be curious, patient and a good team player.

What made you decide to conduct your PhD work at IBM Research – Zurich, an industrial research lab?

Well, as I said, I’ve always been very interested in seeing the practical impact of research. That’s why I preferred to conduct my PhD work at an industrial research lab. It gives you clear feedback on what the market requires and where the bottlenecks of the current solutions are.

Would you recommend it to other students?

For me it was the right decision to conduct my PhD work here at the IBM Research – Zurich Lab. I had the opportunity to work in a team of scientists with years of experience and who are top experts in the field. Discussions within the team were especially constructive, and the help and support I received enabled me ultimately to achieve the results of this project.

What do you want to achieve in the next 5 years?

(Laughs) Oh no, I didn’t know this was going to be a job interview. But seriously, I hope to continue to generate strong results together with my team members and to transfer more of these technologies into products.

What do you consider the most important factors for successful research?

An open-minded environment, stimulating discussions within a creative team, an outstanding infrastructure and sufficient resources.

As a mechanical engineer you are part of a very diverse and multi-disciplinary science project. Can you describe your experience?

I highly appreciate working in interdisciplinary teams where the individual members have different vantage points towards the challenges we face. I think this opens up new perspectives and gives you the opportunity for personal development. And ultimately, it leads to more complete and better solutions.

What has been the most surprising or decisive moment in your research career so far?

Definitely: Receiving the Hilti award.

What does the award mean to you?

It is an honor for me to receive this prestigious award and I would like to take this opportunity to thank my supervisors at ETH and IBM, Prof. Dimos Poulikakos and Dr. Bruno Michel for their continuous support and advice.

What do you do when you are not in your lab?

I enjoy spending time with my family and friends, doing sports or just relaxing and reading a good book.

The Next Grand Challenge in Computing

2011-11-18T11:10:00.006-05:00

At the recent Frontiers of IT colloquium, IBM Aacdemy of Technology Chairman Emeritus Dr. Irving Wladawsky-Berger hosted a panel of industry and academic leaders who discussed what they consider today's grand challenges in computing.

The Panelists:

Jim Schatz, Department Head, Johns Hopkins Applied Information Sciences
David Aronoff, Flybridge Venture Capital
Erik Kruse, Marketing Strategist, Ericsson
Dr. Ashifi Gogo, CEO, Sproxil

The Future of Computing: Reuniting Bits and Atoms

2011-11-16T11:23:00.002-05:00

Dr. Neil Gershenfeld, the director of The Center for Bits and Atoms at MIT, spoke about "how bits meets atoms" at the recent "Frontiers of IT" colloquium at IBM's Thomas J. Watson Research Center.

"Projecting to exascale, we're heading toward 10-to-the-20 [operations per second]. The universe does 10-to-the-120 ops! There isn't a word for that. There's 10-to-the-100 head room we haven't reached. Why not?"

Transforming Health Care Through Data

2011-11-14T12:48:00.002-05:00

Lori Beer, the executive vice president of Enterprise Business Services at WellPoint, spoke about how data -- and analyzing that data with systems such as IBM's Watson -- is transforming health care.

"If you look at [the health care industry], it's not that there's a lack of data. But if you look across the silos of the industry, whether it's pharmaceuticals, or medical devices, or medical providers and patients, it's a bunch of independent pools of information. So how do we bring it together ... and determine what's relevant?

We believe that [IBM Watson] can help bring all involved into the conversation, and help WellPoint share the data."

Advanced Computing Systems for Energy

2011-11-11T11:52:00.003-05:00

Dr. Steven E. Koonin, the undersecretary for Science at the US Department of Energy, spoke about how computing systems are becoming more energy efficient.

“There are three challenges associated with energy. First is energy security … [in part because] the fact that most of the world’s conventional oil reserves are not accessible to the big independent oil companies, but are rather in the hands of the national oil companies.

“Second is the U.S.'s competitiveness. Even with technologies invented and refined in the U.S., it is not manufacturing the new energy technologies.

“And third is environmental impact … most-famously carbon dioxide and its effects on climate. But equally important are water issues. Half of the water withdrawals in the U.S. are due to generating electrical power – more than in agriculture.”

Bio-Inspired Nanoelectronics and Systems

2011-11-09T11:06:00.003-05:00

Dr. Matthew Tirrell, founding director of the Institute for Molecular Engineering at the University of Chicago, spoke about nanotechnology at the recent IBM Research Centennial Colloquium at the Thomas J Watson Research Center. Dr. Tirrell’s work explores new materials based on self-assembly synthetic, and bio-inspired, materials.

“What we’re talking about is the modern age of genetic engineering, where we can imagine living foundries – that is, synthetic biology for synthetic chemistry, making a wide range of products that are perhaps known in nature, but not necessarily made by the organisms that we would like to make them in the most-efficient way [such as pharmaceuticals and fuels].”

Japan Braille Library digitizing books for the blind

2011-11-07T01:49:00.013-05:00

The Japan Braille Library is creating digital versions of international standards-based Braille books, and audio books to improve accessibility for the visually impaired who may not have access to printed materials. Each year, more than 9,000 accessible books are added to the Sapie Library collection, a nationwide online library managed by the Japan Braille Library and the National Association of Institutions of Information Service for Visually Impaired Persons of Japan.

As part of IBM’s Celebration of Service during the company's Centennial year, IBM Research – Tokyo employees are helping the Japan Braille Library with this project. The research team is also developing an electronic book improvement system for the Japan Braille Library. It allows volunteers to collaboratively correct Optical Character Recognition (OCR)-scanned characters via a web browser.

Making Braille books

In Japan, volunteers are the driving force in making accessible books. The process to create Braille books largely relies on manual input, using a standard computer keyboard -- or creating voice recordings for audio books. It can take several months to make an accessible book.

The Japan Braille Library receives requests from library users about which new books to make available. From the wish list, they scan some of the books for the project. The collaborative character correction interface displays a group of OCR-scanned characters recognized as the same character – allowing IBM volunteers to make a batch correction.

Volunteers also use the collaborative ruby correction interface (a small Japanese syllabary character reading aid printed right next to a kanji character). After corrections are made, the digitized books are converted into the international standard-based format and added to the Sapie Library collection.

"Since the kanji characters with ruby tend to be difficult, I enjoyed it because it was like challenging the kanji kentei (Japanese kanji aptitude test)," said an IBM Research volunteer.

IBM Research and Braille technology

In 1986, IBM researchers in Tokyo developed Braille word processing software that significantly sped up Braille translation work. Two years later, IBM collaborated with Braille libraries and volunteer groups across Japan to create an inter-library Braille network. It allowed visually impaired persons to access Braille books from home. The Braille network was migrated to the Internet by the Ministry of Health, Labor and Welfare in 2000. Today, it is Japan's largest bibliographic database, used by visually impaired citizens nationwide.

Artificial Intelligence: The Promise Revisited

2011-11-04T16:24:00.006-04:00

David Ferrucci, IBM Fellow and principal investigator on the IBM Watson Project, discussed what is on the horizon for the fields of artificial intelligence, natural language processing and machine learning at the recent “Frontiers of IT” IBM Research Colloquium.

“I think the impact from robotics on a new age of information science, and even on programming the genome, are all areas that are going to have a big impact in the near future,” Dr. Ferrucci said.

Seeing and feeling shapes described by a stream of sound

2011-11-01T20:08:00.006-04:00

Researchers at IBM’s lab in Tokyo have developed a new method to convert visual shapes on the web into a real-time stream of sound to help visually impaired better understand the shape of an object shown on a web site.

Still an early prototype, the technology converts the shape of an object, such as an image shown on a webpage, into a stream of sound. By listening to the sounds, the visually impaired can mentally feel the shape or better-understand turn-by-turn directions. The technology may also be useful as a real-time guide for online maps which shows route to destination via a mobile phone.

According to a preliminary experiment conducted by the IBM researchers, both blind and sighted people quickly adapted to following directional sound, and recognizing shapes such as randomly drawn paths, letters in the alphabet, and numbers. People with musical training tended to adopt the technology at a faster rate. And some of the participants felt as if they could mentally “see” and “feel” the shapes described by the sounds.

The prototype has the potential to not only help the visually impaired, but to also benefit any user of a mobile device. In situations where a person could use the assistance of a mobile device, but cannot easily look at a screen; or in instances when not all visual information is present (such as in online gaming), the system can provide　real-time guidance in the real world or a virtual world.

IBM researchers in Tokyo are advancing the prototype technology with the goal of helping empower the visually impaired to better-navigate the ever increasing non-textual, visual information on the web.

Fixing the Grid, One Atom at a Time

2011-11-01T15:03:00.000-04:00

IBM scientists and ABB, the world’s largest builder of electric grids, are using computer simulations to potentially develop a new type of insulator that will protect the grid from material deterioration caused by the environment, including pollution, humidity and high winds. This new high-voltage insulator can help reduce the energy loss during transmission, which in turn, can ease the strain on the grid.

"It's like going to the market and buying a full container of milk and then arriving at home to see a glassful has disappeared," explains Dr. Philip Shemella at IBM Research - Zurich. "Using supercomputers we can simulate at the molecular level how the insulators are damaged by the environment and design them to be more efficient and reliable."

A Collaboration of Skills

Started more than two years ago, IBM and ABB scientists in Switzerland formed a joint project to simulate the molecular dynamics of the insulators, which are made of silicon rubber, scientifically known as Polymethylhydrosiloxane or PDMS. The goal of the project was to better understand the physical processes and potential for improved design methods of high-voltage insulation materials.

"IBM brings its extensive expertise in complex computer simulation and we bring over 125 years of experience with electricity," said Dr. Oliver Fritz, ABB researcher, based in Baden-Dattwil, Switzerland.

Using an IBM Blue Gene/P supercomputer and massively parallel algorithms, the scientists were able to simulate and study the individual molecules used in the silicon rubber to better understand how it reacts to damage caused by the environment.

With advanced simulations and the computing power available, the scientists were able to simulate realistic models of the material comprising approximately one million atoms. These simulations will lead to testing new materials in the silicon rubber composition to improve their resiliency to damage.

The findings, published today in The Journal of Physical Chemistry B, DOI: 10.1021/jp207589p in a paper titled "Surface Dynamics of Amorphous Polymers Used for High-Voltage Insulators" helps to unravel the mechanism of water repulsion on the insulator surface.

"Currently, we are running simulations to study how a drop of water affects the reliability of the insulating material. Surprisingly, this is very significant, particularly when it is extrapolated across the entire power grid," adds Shemella.

Four technologies that will change the world

2011-10-31T11:51:00.011-04:00

On October 21 at the Thomas J. Watson Research Center in Yorktown Heights, NY, Dr. John E. Kelly III, IBM Senior Vice President and Director of Research, hosted a colloquium on “Frontiers of IT,” that focused on four key technologies that will change the world: nanotechnology, exascale processing, big data and analytics, and learning systems.

Here are his opening remarks about these technologies:

Healthcare Modeling: What Is or What If?

2011-10-27T06:30:00.000-04:00

Editor's note: Guest author Prof. William B. Rouse is Georgia Institute of Technology's Tennenbaum Institute Executive Director, co-chair of the National Academies Healthy America Initiative and member of the National Academy of Engineering.

Much of contemporary analytics focuses on tabulating and portraying characteristics of existing systems, whether they are for energy supply, health delivery or a wide range of other complex systems. This type of analytics addresses "what is" or in many cases "what was." This approach is backward looking, which makes a lot of sense if there are important lessons to learn from the past and carry forward.

There are some situations, however, where the current system is not one to be emulated. Health delivery is one of these cases. While medical science has steadily advanced, the delivery of health has not. The delivery system is a federation of millions of entrepreneurs with no one in charge. Information systems are highly fragmented and rife with incompatibilities. The incentive system rewards delivery of procedures rather than health outcomes.

We need a very different system in terms of how health delivery is organized, operated, and financed. This requires that we move from "what is" to "what if" in the sense that we need to explore delivery models that do not yet exist. We cannot rely on empirical data from systems that have not been designed and deployed. Further, as these will be very expensive systems, we need some way to drive the future before we write the check.

Computational approaches can provide the means to this end. What we need is interactive organizational simulations that enable key stakeholders to explore alternatives, eliminate bad ideas, and refine good ideas. As stakeholders come from a wide range of disciplines, these simulations have to include compelling interactive visualizations that allow extensive "what if" explorations. When stakeholders move the sliders for key model parameters and choose their own assumptions, they become increasingly committed to the shared models they are developing.

Creation of these types of capabilities requires several ingredients. First, several types of computational models must be linked, e.g., agent-based for patients, discrete-event for delivery processes, microeconomic for providers and payers, rule-based for policy, and system dynamics for exogenous phenomena. Linking such a disparate range of models can be a substantial challenge.

Second, the parameters for component models must be gleaned from large data sets including clinical data, financial data, and claims data. Using such data to parameterize process models, for example, can be quite difficult, as most providers and payers have not structured their data sets in terms of processes. Instead, data are organized by codes for diagnoses, procedures, and locations. This requires that processes be inferred from data sets never intended to support such inferences, which often involves filtering out special cases as well as mistakes.

Third, interactive visualizations are needed for decision makers to understand and be comfortable with computational approaches. They need to view the computational models as a means for exploring a range of possibilities rather than as a "magic box" that produces optimal but, unfortunately, often opaque answers. This requires core competencies in interactive computing and decision support systems.

The three competencies outlined above -- computational modeling, statistical estimation, and interactive visualization -- are rarely found in one individual or even one discipline. Multiple disciplines are needed, working as a team to tackle large-scale "what if" problems. The Georgia Tech - IBM team is well endowed with these competencies. Further, the computational environment being developed by IBM, namely the Smarter Planet Platform for Analysis and Simulation of Health, will enable the team to scale up from initial smaller problems to realistically complex health delivery enterprises.

Smart health is not just about doing what we now do better. Indeed, Peter Drucker has cautioned us to never invest in improving something that you should not be doing at all. For health, being smart means being able explore whole new ways of doing things to eliminate bad ideas and refine good ideas, so that we then invest in improving and deploying these good ideas to create quality, affordable health for everyone.

IBM announced a new research initiative with Georgia Tech, Emory University, Children’s Healthcare of Atlanta, Georgia Cancer Coalition and the Georgia Department of Community Health to bring together the disparate factors that affect health in children, like education, socioeconomic status, access to public transportation, food resources, and more. Called One Million Healthy Children, the program is designed in a way that can be replicated in cities around the world. Atlanta is the first and the project will initially focus on the factors that affect diabetes, autism and asthma. By applying advanced modeling and analytics technology to this disparate data, scientists may be able to give healthcare practitioners a never-before-understood view of a child's health.

We won an Emmy!

2011-10-21T17:13:00.002-04:00

Editor's Note: This post originally appeared on the IBM Research - Almaden Quicksilver Minds blog on Friday, October 21, 2011.

Earlier today it was announced that IBM was presented a unique award. Together with FOX, an IBM Research project born out of Almaden won an Engineering Emmy award for Innovation from the Academy of Television Arts and Sciences. According to the Academy, by improving the ability of media companies to capture, manage and exploit content in digital form, IBM and Fox have fundamentally changed the way that audio and video content is managed and stored.

The Linear Tape File System (LTFS), invented by IBM's lauded Research Division, enabled major improvements in digital workflow and dramatic reductions in the costs associated with capturing, storing and repurposing media content while providing dramatic improvements in transfer rates, storage density, automated workflow, meta-data capture and content availability. Combining digital broadcast and IT standards in a broadcast environment, the LTFS has enabled real-time content recording and high-speed recovery of content to be a broadly-supported, multi-industry solution.

Michael Richmond, Brian Biskeborn, David Pease, Arnon Amir (Almaden Research), and Shinobu Fujihara (Yamato) at the 2010 NAB show where LTFS was announced and released.

In a blog post earlier this year, IBMer Tony Pearson, Master Inventor and Senior Managing Consultant for the IBM System Storage product line, wrote:

"With the capabilities of LTFS, IBM has introduced an entirely new role for tape, as an attractive high capacity, easy to use, low cost and shareable storage media. LTFS can make tape usable in a fashion like removable external disk, a giant alternative to floppy diskettes, DVD-RW and USB memory sticks with directory tree access and file-level drag-and-drop capability. LTFS can allow the for passing of information around from one system or employee to another. And as for high video storage capacity, a 1.5TB LTO-5 cartridge can hold about 50 hours of XDCAM HD video!"

Lead researcher on the project David Pease is a long time storage research expert at the Almaden lab in San Jose, CA. Pioneering many of the tape and disk storage technologies out of IBM Research over the last decade, David recalls a significant factor in deciding to pursue this project the way he did. "We really needed to make the first version open source," David said. "The idea of a file system that was cross-platform and interoperable was key; we wanted people to have an interface they were familiar with, similar to disk with file folders, drag and drop and double-click, but we also wanted to make sure it wasn't tied to only Windows or only Unix. The real future for acceptance for just about any kind of storage technology is interoperability and that people aren't tied to a platform."

David and his team developed LTFS from concept to fruition in just less than 3 years. An impressive feat in the research world, he shares some thoughts about winning an Emmy for his work:

First, I am truly stunned. This recognition is more than we ever expected so early in the project, and hopefully it reflects the importance of what we've done. When we started this work, we said that our goal was to change the tape industry and the Media and Entertainment business; it seems that we are well on the way to realizing these goals.

I have to point out that an idea and project like this are never the work of an individual. From Ed Childers and the other tape experts in Tucson, to the folks at Almaden who encouraged me to get involved with tape (again), to the team of great researchers and developers who worked on this in my group, to the tape specialists in the Yamato Lab who joined my team or worked to support it, I have to say that we couldn't have gotten here without the efforts of each of you. Thank you all for making this possible!

Fun fact: This past February, David Pease completed a 41-day motorcyle ride from San Jose, CA to Panama City, Panama with 3 companions on different stages of the trip. You can read about his travels through California, Northern, Central and Southeast Mexico, Guatemala, Honduras, Nicaragua, Costa Rica and finally Panama at his blog here.

The Frontiers of IT

2011-10-19T10:42:00.003-04:00

IBM Research envisions a future in which advances in technology will create a new class of systems that will go beyond capacity, speed, and complex analytics, and begin to augment human intelligence, with people as an integral and central part of the system.

On October 21, industry experts will gather at IBM's Thomas J. Watson Research Center to explain, debate, and discuss nanotechnology, exascale processing, big data and analytics, and learning systems – or simply put, the “Frontiers of IT.”

Dario Gil, the program director of Energy Technology and Strategy at IBM Research, talks about these frontiers, and what he’s looking forward to at the event.

Smart Grids from Bornholm to Zurich

2011-10-13T05:48:00.003-04:00

There is no doubt that electric vehicles are coming, but questions remain if the electric grid can sustain the extra load.

Here come the EVs, but are we ready?

On the low end, the Electric Power Research Institute estimates their will be 3.1 million electric vehicles on the road by 2020, but without a sound distribution planning system and broader use of renewable resources, like wind and solar, the grid will struggle to meet demand.

Staying ahead of this challenge, IBM Research in Zurich is working with Swiss electric utility provider, EKZ on a pilot project using a smartphone app. The web-based app, which also runs on tablets and computers, enables consumers to conveniently charge their electric vehicles using renewable resources, while also monitoring their energy costs.

The app, which connects to a cloud provided by IBM, analyzes the amount of energy on the grid, current prices and demand forecasts -- it knows on a hot day that their will be a spike in demand. Using this data, the app can offer price points to consumers who can choose, based on price and need, when to charge their vehicle. The app also offers a smart charging feature whereby the user can schedule charges based on the availability of renewable resources, such as sun and wind, allowing the utility to improve load balancing and prevent outages.

IBM scientist Dieter Gantenbein who is involved in the project comments, “This service will make electric vehicles more attractive to consumers by taking into consideration their preferences, while still factoring in cost and overall convenience. In this pilot, the real-time analysis of supply and demand together with a control algorithm will create a dynamic incentive for a sustainable way to charge an electric vehicle’s battery, putting us another step closer to establishing a cleaner transport system.”

Back to Bornholm

Since 2009 the the Danish Island of Bornholm has been testing concepts to better balance wind energy with demand on the grid. The first project was called EDISON, in which 50 electric vehicles were installed on the island as storage batteries for excess wind energy on the grid. When the wind blew the cars charged, when the wind died down, the cars provided extra capacity to the grid.

Two years later the teams learned a lot and they are have recently received further funding to extend the project into the home in a new project called EcoGrid EU. Unlike EDISON, instead of just using car batteries to balance the load the consortium is using dishwashers, heat pumps and electric water heaters to also store excess energy in 2,000 homes on the island. To participate, Danes living on the picturesque island will use smart meters and have access to a Web-based portal, similar to an online auction, where they can schedule when to purchase electricity and at what price.

Lykke Friis, the former Minister for Climate and Energy in Denmark, is a strong advocate of the intelligent electricity system.

She comments, “EcoGrid EU is an incredibly promising pilot project, in which Bornholm will become a test island in the future intelligent electricity system. The results will not only be usable in Denmark and Europe, but all over the world. We need an intelligent electricity system which can integrate more wind power and other renewable energy sources. In order to make the set-up work in the future, it is necessary to turn all resources in regional grids into active players, exactly as it will happen in Bornholm.”

Well known as a birthplace of nanotechnology, Switzerland could easily become the next hub of knowledge about smart grids.

“You get to see the impact of your research”

2011-09-20T08:22:00.001-04:00

As part of IBM Research’s newly extended global Summer intern program, eight undergraduate students from Rensselaer Polytechnic Institute (RPI), Union College, and University of Notre Dame, joined IBM Research – Zurich in Switzerland for two months.

Before heading home, we caught up with most of them to hear about their experience.

Jing Fu studies high performance computing at RPI because he likes to see commercial and scientific programs to solve real-world problems fast on supercomputers. At the Zurich Research Lab, Jing was part of the Storage Systems team.

Matthew Manning enjoys studying Electrical Engineering at Union College because it is a rather broad field that plays a role in almost every area of science. He worked in Nanofabrication group of the lab.

Vincent Hargaden studies Industrial and Systems Engineering at RPI because it allows him to research the interaction between systems at a high level and apply his research to some practical business problems faced by both manufacturing and service companies. During his internship at the lab, he joined the Business Optimization group.

Edit Varga is studying electrical engineering toward a PhD degree at University of Notre Dame because she likes new problems to solve as well as to learn new research areas. For the last two months she has worked in the lab’s Physics of Nanoscale Systems group.

Kristof Tahy is studying electrical engineering toward a PhD degree at University of Notre Dame. During his stay he joined the Nanoscale Electronics group.

Nick Lanzin is studying computational physics at RPI because it combines his curiosity for the natural world with computer technology that will play a major role in tomorrow's research environment. During his summer internship he worked in the Computational Sciences group.

Guangle Zhou studies electrical engineering at the University of Notre Dame purely accidental. He worked in the Nanoscale Electronics group.

In short: how did you like your stay here and why?

Kristof: I really enjoyed my stay here. My goal was to experience corporate working environment and it was fulfilled. But the experience was unexpectedly positive, working here is relaxed, but productive. I'm glad to see how the European working morale is different from the US as well. It was a bit difficult in the beginning to do so much work in so little time, but realizing that there is a life outside of work is great. I had a very good project here, which I enjoyed to work on. The group was very helpful, and it was good to see, that my results are an important part of the research efforts.

Matthew: My stay in Zurich at the IBM lab truly proved to be a once in a lifetime experience. Not only did I learn many new things and gain valuable skills that I will bring back to my home university, but I did so while being immersed in a completely different culture. I would call this internship a perfect combination of education and adventure.

What is the most memorable experience(s) you take home?

Jing: The fact that industrial labs explore a research topic similarly, yet differently from in school and other labs.

Matthew: Traveling to various regions of Switzerland on weekends was certainly a highlight of this trip, however just as memorable were the daily coffee breaks with my research team. Whether discussing our projects or the latest news it was a great time to get to know members of my group and team on a more personal level.

Compared to your universities, what are the differences and similarities of how research is being done?

Vincent: I think the biggest difference is the commercial focus taken by the lab to research. Whether it is for external clients or other IBM divisions, the research undertaken here has to be seen to make a difference commercially. Universities are to a certain extent more removed from this. Certainly, to be competitive for external funding and industry sponsorship, faculty have to convince the funding agencies of the impact their research will have - but the bottom line is that unlike IBM, universities or funding agencies are not listed on the stock exchange…yet.

Jing: Similarities would be to explore an interesting, yet not well understood problem in my general research area. A difference is that in school the main motivation is producing good papers, while in here it is much more real-product-oriented and it's interesting to optimize/explore a real product.

Edit: In the group here, there are different people with different skills, which is very useful. It is much easier to work if there are permanent positions as well, not like in a university group, where everybody is a student, and going on to graduate some time.

So what was your impression of IBM Research - Zurich?

Vincent: I think the Lab is an ideal size - not too big so it is easy to get to know people and find out what is going on in other groups, but at the same time it is sufficiently big enough to be considered by universities and other companies as a source of deep expertise. I also liked the daily routine around coffee and lunch in that the people here make a conscious effort to go to the cafeteria together to have a coffee in the morning/afternoon or to have lunch and chat - sometimes about work, but mostly it's social conversation.

Edit: It is a nice, friendly environment to work, an easy place to find people to get to know some research related information or to get some professional help.

Did you know the lab before your internship?

Nick: I had been to the lab for a two-week visit in December of 2010. This is when I was first introduced to a research project that I would continue working on throughout this summer internship.

Jing: Yes, I knew some of the work in my area from this lab before I came.

Kristof: Yes, I met scientists from this lab at conferences, and I read some of the scientific papers, too.

Guangle: Yes, of course.

What was the biggest challenge (technical, cultural, etc.) while you were here?

Matthew: Adapting to life in Zurich both in and out of the lab was quite painless.

Jing: Cultural wise, the language was a problem in the beginning, but in the lab everything is fine. Technical wise, finishing a project in two months is tough, given a typical curve one would have. As I type this, I am still trying to get the project done nice and elegant.

Guangle: I didn't face any real challenges, but got a lot of help from people here (at IBM).

Vincent: I think that not having much German was a challenge. While the standard of English is very high in the lab and also in Switzerland in general, I would have liked to have better conversational German. When I found out that I was coming here I did buy a German language software package, but didn't make much progress unfortunately. It is a complicated language, but then non-native English speakers say that about English too.

What was the biggest surprise(s)?

Matthew: The biggest surprise was the rather relaxed working environment here at the Lab. I was expecting a much more corporate atmosphere, but was quite pleased with the campus-like feel.

Kristof: Relaxed working environment. I packed a lot of formal clothing, which turned out to be absolutely unnecessary.

Jing: The size of the Lab.

Guangle: The "free" working environment, was not expected.

Do you envision pursuing a career in research? At a corporate research lab?

Edit: Yes, I'm open for it.

Kristof: Yes, and Yes.

Jing: I am aiming to be a researcher for sure. I am considering both industry labs and other national research labs.

Matthew: Currently my focus is much more confined to finishing my Bachelor's degree, however this experience has certainly opened the door to a research career as an option in the future. My experience will play a great role in the decisions I make in furthering my education.

Vincent: Prior to the internship in the lab, I was planning on pursuing an academic career in a research focused university, either in an Engineering or Business school, as my area of study (Operations Research) easily transfers between those two types of schools. But having spent the last two months here in the Lab, I would now consider a corporate research lab. I think in a corporate lab you get to see the impact of your research, as well as still being able to publish papers and present at conferences. The downside of a corporate lab is that you don't get to teach courses to students.

Nick: I absolutely plan on pursuing a career in scientific research. However, I am undecided as to whether this will be in an academic or corporate setting. After earning my PhD I will likely apply to academic post-doctoral research positions, but this depends strongly on what types of jobs are available at the time of my graduation.

Guangle: I would like to work on a research lab in the future if I have some chances.

For more photos click here.

Cross-lingual text mining

2011-09-09T10:21:00.005-04:00

Discovering knowledge from large volumes of multilingual text data just got easier with new text mining technology from IBM Research. Using globally distributed databases, this cross-lingual text mining technology developed by the research team in Tokyo allows users to search through – and find value in – data written in a language they don’t understand.

Knowledge Discovery

For example, manufacturers selling products in the U.S., Europe and Asia could quickly identify defects, or complaints based on the data from tens of thousands of customer contact reports stored by call center operators in local customer languages. The cross-lingual text mining technology extracts context from portions of the text that the user wishes to analyze, translated to their preferred language. It analyzes and returns results, highlighting irregularities such as defects or complaints that were previously unnoticed, due to language barriers.

"Finding accurate translation pairs (to match one language to another) was a challenge in developing the technology. Often, notes taken by call center operators are not grammatically correct or truncated." said Tetsuya Nasukawa, a senior technical staff member at IBM Research – Tokyo.

“The terms being analyzed may not be defined in general translation dictionaries. So, this text mining compares how each concept is expressed in the textual database of the source’s native language – and in the textual database of the requested foreign language to determine the translation pairs.”

To go from a search tool, to a technique that extracts valuable information – from any language domain – users can apply toward trend analysis, claim processing, and other fields, the team in Tokyo used TAKMI (text analysis and knowledge mining) to find noteworthy features, trends and important issues without reading all of the data, and additional technology which extracts translation pairs from any language domains.

Last year, IBM's text mining research team received the Field Innovation Award from The Japanese Society for Artificial Intelligence in recognition of its pioneering text mining research and development effort.

Nobel Laureates Don't Rest, Create Art to Inspire Science

2011-09-05T04:37:00.003-04:00

When the entrance to the lobby of the Binnig and Rohrer Nanotechnology Center was in its early design stages an idea was proposed to have some art put on display that would inspire those that passed through the doors.

While initial concepts didn't pan out, one of the planning committee members recalled that IBM's own Nobel Laureate scientists, Georg Bednorz and Gerd Binnig, were actually very good artists in their own right -- who better to inspire scientists then the two of them?

Bednorz was the first of two to deliver. His yet "Untitled" sculpture was designed in bronze and the piece shows a scientist holding a molecular string (left) and graphene (right) and it is meant to inspire scientists to challenge themselves.

Delivered one week ago, "In Touch with Atoms" is a marble sculpture by Gerd Binnig. The title was inspired by a scientific paper, written by Binnig and fellow Nobel Laureate Heinrich Rohrer, of the same name published in Reviews of Modern Physics, Vol. 71, No. 2 in 1999.

The piece shows a hand carved in marble with a finger pointing atoms embossed in copper representing a silicon (111) surface with the 7 X 7 reconstruction, a pivotal system for the early demonstrations of atomic resolution with the scanning tunneling microscope.

Are you inspired?

See more of the photos of both pieces "Untitled" and "In Touch with Atoms".

Dr. Tze-Chiang Chen receives IEEE honor for technology leadership

2011-08-22T14:36:00.044-04:00

“Generation after generation we hit the technology wall. IBMers possess the attitude that we never see the wall as a barrier; we see it as an opportunity for innovation.”

– T.C. Chen

When Dr. Tze-Chiang Chen joined IBM’s Thomas J. Watson Research Center in Yorktown Heights, New York in 1984, the microprocessors ran at 5 MHz with 275,000 transistors per microprocessor. Since that time, Chen has helped lead one of the world’s most advanced silicon chip technology evolutions. Today, thanks to his contributions, microprocessors run at about 4 GHz with 1-2 billion transistors per processor.

On August 20, 2011, the Institute of Electrical and Electronics Engineers (IEEE) honored Chen with the 2011 Ernst Weber Engineering Leadership Recognition award at the IEEE Honors Ceremony in San Francisco, California. The award acknowledges Chen’s exceptional managerial leadership and contributions in the field of silicon chip technologies. These contributions include acting as the senior manager responsible for the announcement of the world’s fastest and smallest 256 megabit DRAM in the IBM/Siemens/Toshiba DRAM Development Alliance.

Chen credits much of his success to IBM executives who gave him “opportunities, one after the other, to conquer technology challenges.” Chen’s drive, enthusiasm, and dedication to his work undoubtedly had a great deal of impact on his success.

“I am very fortunate to be at IBM Research and to have been given technology challenges over all these years,” says Chen, noting that one of the most enjoyable parts of his IBM career has been to work with a number of talented individuals in research and technology.

Chen says he is honored to receive the award and the recognition the award brings to IBM, proving – as he says - that we are a company consistently at the forefront of the technology evolution.

Chen currently manages more than 600 IBM researchers across six global research laboratories. He has driven the research, development and application of silicon microelectronics technology for a variety of IBM products and solutions. This involvement at all levels – from concept to production – has provided him with what he calls “a fortunate opportunity to initiate, participate, and manage.”

IBM's first cognitive computing chips mimic functions of the brain

2011-08-18T00:01:00.016-04:00

Today, IBM announced the very first cognitive computing chips, designed to emulate the brain’s abilities for perception, action and cognition. The technology could yield many orders of magnitude less power consumption and space than used in today’s computers, and give computers a sort of "right brain" capability to match their superior calculating abilities. Following Watson, it is yet another example of IBM's quest to build learning systems.

The Systems of Neuromorphic Adaptive Plastic Scalable Electronics (SyNAPSE) project is driven from funding by the Defense Advanced Research Projects Agency's (DARPA); and entering Phase 2 of the SyNAPSE project (Phases 0 and 1 are complete), IBM has built two state-of-the-art chips unlike anything produced before. These chips defy the traditional von Neumann architecture, which relies on programs or instructions to complete these tasks. IBM will use these chips as the basis for an architecture with no set programming.

A peek inside IBM's brain lab in San Jose, CA:

SyNAPSE technical project manager Bill Risk next to the "brain wall." Each of the yellow boxes represents one of the cognitive computing chips (256 neurons), and close up you'll see them blinking - these are neurons firing.

IBM researchers Paul Merolla (left) and John Arthur having fun firing up a SyNAPSE demo.

10 things to know about SyNAPSE

1. The brain uses less energy than a 25 watt light bulb and occupies less volume than a 2-liter bottle of soda -- capable of completing complex tasks, while autonomously computing what it needs to, and when, and knowing what information to save and for how long. The brain is the ultimate computer.

A cognitive computing system monitoring the world's oceans could contain a network of sensors and actuators that constantly record and report metrics such as temperature, pressure, wave height, acoustics and ocean tide, and issue tsunami warnings based on its decision making. Similarly, a grocer stocking store shelves could use an instrumented glove that monitors sights, smells, texture and temperature to flag bad or contaminated produce.

2. Today's computers use an architecture that was designed 40 years ago. Without using more power and taking up more space, we simply can't program today's computers to do the tasks that are required to handle the growing mountains of data we are faced with.

3. Cognitive computers emulate the brain’s abilities for sensation, perception, action, interaction and cognition, while integrating and analyzing vast amounts of data from many sources at once: in essence the "right brain" to today's "left brain" computers.

4. These systems won’t be programmed like traditional computers are today. Rather, cognitive computers will learn dynamically through experiences, find correlations, create hypotheses and remember – and learn from – the outcomes, emulating the human brain’s synaptic and structural plasticity (or the brain's ability to re-wire itself over time as it learns and responds to experiences and interactions with its environment.)

5. To accomplish this new kind of system, IBM is combining neuroscience, nanoscience and supercomputing together to rival the function, power and space of the brain.

6. Supercomputing: In November 2009, scientists used an IBM Blue Gene supercomputer to achieve significant advances in large-scale cortical simulation of a cat brain, substantiating the feasibility of a cognitive computing chip.

7. Neuroscience: Last year, scientists here at Almaden uncovered and successfully mapped the largest long-distance network of the monkey brain, which is essential for understanding the brain’s behavior, complexity, dynamics and computation. This discovery gives scientists unprecedented insight into how information travels and is stored across the brain.

8. Nanoscience: The revolutionary new chip that we've unveiled is a building block towards the long-term goal of SyNAPSE; to build a chip system with ten billion neurons and hundred trillion synapses, while consuming merely one kilowatt of power and occupying less than two liters of volume.

9. Computers like this could have a significant impact on virtually every sector of the economy. The application and service possibilities will range from preventing fraud and providing better security, to helping scientists better understand intricate climate changes happening to our planet (see callout text).

10. IBM has assembled a world-class team including collaborators from Cornell University, Columbia University, University of California - Merced and University of Wisconsin - Madison, to work with their scientists from IBM Research sites including Austin, TX, Yorktown Heights, NY, India and Zurich.

Building an inclusive society on the web

2011-08-03T09:04:00.003-04:00

In an effort to improve Web accessibility of public services for every Japanese citizen, including the elderly and disabled, the Ministry of Internal Affairs and Communications (MIC) developed Operational Models for Government Agencies and Municipalities: a manual that provides guidance and procedures that ensure accessibility for such tasks as municipality orders for outsourcing Web site development.

To make the manual consistent with the Japan Industrial Standards (JIS) for accessibility (JIS X 8341-3:2010) that was announced in August 2010, the MIC brought together experts across industry, government, and academia to revise the manual, and at the same time, develop a Web accessibility evaluation tool to complement the manual.

miChecker

The free tool, called miChecker, offers user-friendly features for government agencies and municipalities to comply with JIS X 8341-3:2010. It is based on aDesigner, a Web accessibility assessment tool developed by IBM Research – Tokyo. In addition to checking compliance, aDesigner offers features to allow Web page owners, designers and developers to identify and simulate Web site barriers experienced by the visually impaired.

IBM contributed aDesigner to the Eclipse Foundation as part of the Accessibility Tools Framework (ACTF) – a collection of tools and building blocks developed by IBM.

As part of the MIC's initiative, IBM researchers made modifications to this open source evaluation tool to take into consideration new accessibility guidelines, such as Web Content Accessibility Guidelines 2.0 (WCAG 2.0) and JIS X 8341-3:2010.

In June this year, the MIC made the miChecker available on its Japanese home page to help drive social inclusion and active social participation of Japan's citizens.

To find out more about other accessibility technology developed by IBM Research, click here.

How IBM is digitizing the world's text

2011-08-01T11:00:00.003-04:00

The idea of digitizing all books and making them available on electronic libraries can be traced back to 1945, when Dr. Vannevar Bush wrote "As we may think" in the July issue of The Atlantic. His visionary description of an information centric application called "memex" influenced the development of the hypertext concept and the Internet. And projects in the 1970s – such as Michael Hart's Project Gutenberg, and futurist Ray Kurzweil's Optical Character Recognition (OCR) technology – continued the effort toward the digitization of textual information. But while billions of people access the Internet today, full digitization and availability of past textual information is still a work in progress.

Among many current efforts underway, IBM is working with the European Union on project IMPACT (IMProving ACcess to Text) to efficiently produce digital replicas of historically significant texts and making them widely available, editable and searchable online. As part of the project, IBM researchers in Haifa, Israel developed CONCERT (COoperative eNgine for Correction of ExtRacted Text). It automates simple, repetitious operations using an adaptive OCR engine that automatically learns from its text recognition errors.

Digitizing Japanese literature

The diverse nature of the Japanese language poses a serious challenge to digitizing the country's literature. Japanese script is expressed beyond a few dozen standard characters, typical of most other languages. In addition to Japanese syllabary characters – hiragana and katakana – Japanese includes about 10,000 kanji characters (including old characters, variants and 2,136 commonly used characters), and ruby, a small Japanese syllabary character reading aid printed next to a kanji. Not to mention mixed vertical and horizontal texts.

The National Diet of Japan is Japan's bicameral legislature. It is composed of a lower house, called the House of Representatives, and an upper house, called the House of Councilors. Both houses of the Diet are directly elected under a parallel voting system. In addition to passing laws, the Diet is formally responsible for selecting the Prime Minister.

-- wikipedia.com

Last year, IBM researchers in Tokyo combined their Social Accessibility tool with CONCERT to create a full-text digitization system prototype for the National Diet Library (NDL) of Japan. Dr. Makoto Nagao, the director of the National Diet Library, wrote the book "Digital Library" in 1994, in which he analyzed that the digitization of books is the first step towards realizing an ideal electronic library. The next step is to create a system which allows users take full advantage of digitized information.

"The system needs to have capabilities that are close to how we hold and utilize knowledge in our brain," said Dr. Nagao.

In addition to helping Japanese Diet members to perform their duties, the NDL preserves all materials published in Japan as the national cultural heritage, and make them available to the government institutions and the general public. (As part of this effort, NDL also launched the International Library of Children’s Literature in 2000.)

NDL is making recorded academic literature available online to the public, including making them accessible for the visually impaired, and lending the recordings to libraries throughout Japan.

The IBM Research – Tokyo team also developed a full-text digitization system prototype that improves the digitization of Japanese literature printed during and after the Meiji Period (1868 - 1912); improve accessibility for people with disabilities in reading printed text; and facilitate effective searching and viewing of full-text data. The prototype is also designed with an eye toward future international collaboration and standardization of libraries, including the digitization of historically significant literature, broad utilization of books for various academic activities and online searching.

In a matter of years, all of our textual information will be fully digitized in a reusable way.

Services Innovation Lab strengthens Research

2011-07-28T08:14:00.005-04:00

Today, IBM announced an initiative designed to link state-of-the-art IBM Research projects directly to the largest part of the company - services.

The Services Innovation Lab (SIL), led by researchers with development and client experience in virtually every field of science and technology, will bring together researchers and services professionals to generate ideas, solve problems, capture opportunities and create new innovations that will transform services. You can learn more about the SIL here.

IBM Research - Almaden senior manager for services research, Stefan Nusser, has been named Almaden Lead for the SIL. Below, he provides some additional thoughts on the motivations, goals and ideal outcomes.

Stefan's team, composed of researchers with varying expertise - nanotechnology, computational biology, user interaction, computer science, data mining, security and compliance, mathematics, business optimization and more - includes Sandeep Gopisetty, IBM Research Distinguished Engineer, who already has a portfolio of projects in place for the launch of the SIL:

Backup and recovery tools to help with the majority of critical situations in the customer environment.
Customer environment insights to check the heal and performance, reducing critical situations as well as helping to manage the customer environment more simply.
Addressing the management of firmware and patches for hardware.
Intelligent performance aware automation for complex storage tasks.
Unified policy-based ILM for enterprise storage.

Stay tuned in to the IBM Research news blog to learn more about projects and developments from the SIL.

A Century of IBM Patents

2011-07-25T08:30:00.003-04:00

One hundred years ago, on July 25, 1911, IBM received its first patent for an invention related to punched card tabulation (U.S. Patent # 998,631). Since then, IBM inventors have been granted more than 150,000 patents globally for technological creations that have made a lasting impact on business and society.

Patents and innovation are essential components of IBM's business growth strategy, and they have enabled the company to evolve and lead for a century, despite dramatic changes in the IT industry. This commitment to inventing stretches back to the company's early days, when IBM's founder, Thomas Watson Sr., fostered an environment that stimulated a competitive and inventive spirit.

In the 1920s, IBM established its first patent department and the company's patent operation has evolved and expanded into a world-class organization that leverages cutting-edge technology to help manage tens of thousands of patents in its global portfolio. Over the past 18 consecutive years (1993-2010), IBM has received more U.S. patents than any other organization, and the company's inventors received a record 5,896 U.S. patents in 2010.

Patents are valuable assets and help IBM generate around $1 billion in income annually from the licensing and sale of intellectual property, while enabling the company to ensure and protect its freedom of action -- the ability to freely design and market its products and services.

From the punched card tabulation patent IBM received 100 years ago to last year's earthquake patent, and inventions that were patented earlier this week—such as U.S. Patent #7,984,479 for a computer security invention—IBMers have consistently pioneered ways to improve and transform the way we work and live.

Ponder This: A Q&A with puzzle master Oded Margalit

2011-07-18T13:39:00.016-04:00

Every month since May 1998, thousands of people match wits with the best minds in IBM Research by trying to solve Ponder This puzzles.

The Ponder This puzzles began as a way for IBM researchers to increase productivity. Some employees found that when they got stuck on a problem, that immersing themselves in solving a completely different type of problem helped get them back on track. Researchers started sharing their most ambitious puzzles, and eventually this evolved into a published monthly challenge — Ponder This.

Oded Margalit, a Machine Learning researcher at the IBM Research — Haifa lab, took on the role of unofficial Ponder This puzzlemaster in February, 2009.

What do you find most interesting about Ponder This?

First and foremost, I love puzzles and have been doing them since I was a little kid. I think Ponder This is a great connection to IBM's "think" motto and a good way to extend IBM to the general public. I also like to imagine all the smart people who work on the puzzles as a potential think tank for future IBM challenges!

Where do you get the puzzles and how do you decide on the level of difficulty?

I generally make them up or use ideas that people submit. Occasionally, we have used puzzles from other sources, but we found that many of our users are already familiar with anything that's been published. The challenge is that our original puzzles haven't been tested.

As far as level, each puzzle is posted for a month before the solution is revealed. Twice, we left a puzzle posted for two months because it was too hard. Other times, the solutions start coming in so quickly that we know it's too easy. But I'm getting the hang of what works.

What is your favorite puzzle?

Every puzzle has a story. The most memorable one for me was a few years ago: one of our regular solvers was hospitalized. When his daughter would visit him, she brought along a Ponder This puzzle. The family used it to help pass the time. He sent in the solution from his bed in the ICU!

Another pair of solvers were inspired by one of our puzzles in their own research. Eventually, their ideas were published in the prestigious Physics Review Letter journal, along with a special citation for Ponder This.

What do you know about your solvers?

The last research I did showed that we have about 2,500 solvers from around the world.

What does the future hold for Ponder This?

We plan to continue, and we welcome new solvers and suggestions. We are also happy to receive suggestions for a significant value — send us a meaningful number and we'll create a puzzle around it.

IBM Centennial puzzles

With a nod to IBM's centennial year, all of the 2011 puzzles are being connected to IBM. The solution to one puzzle, for example, was 77,147 — the number of dollars the computing system Watson won on Jeopardy! May's puzzle was based on bar codes, an IBM Research invention.

Oded adds that he considers the perfect puzzle as being easy to describe yet difficult to solve, and most importantly, that the solution is easy to understand.

"Just look around, anything in the world can be made into a puzzle."

July's puzzle

There are 80 students in a school. Each of them eats fruit for dessert every day, and the available fruits are apples, bananas, and cherries.

Find a possible setting of desserts for 14 days, such that for every set of three students, there exists at least one day in which they all ate different desserts. Please supply your solution as a list of lines, in which each line is 80 characters long and contains the letters A, B, and C.

Check back soon on the Ponder This site for the solution, or sign up for the RSS feed to be notified when it is posted, as well as when new challenges are published.

Inventors' Corner: U.S. Patent #7,877,706 – Controlling a document based on user behavioral signals detected from a 3D captured image stream

2011-07-08T15:02:00.003-04:00

This patent describes a technique that enables an individual to use gestures and movements to search the Web or automatically create or update a document, spreadsheet, e-mail, etc.

Similar to the technology used in gaming systems to capture a player's actions or movement, this invention is capable of seeing or detecting certain gestures or movements of computer users, which can be used to interact with a system, instead of relying upon on a keyboard, mouse clicks, or even speaking commands into a microphone connected to a voice recognition system.

The patented method uses one or more cameras to capture three dimensional (3D) user movements and then applies behavioral and movement controls to trigger related document actions, such as opening, editing or finding a document or Web page.

U.S. Patent #7,877,706 was issued to inventors Jacob Albertson, Kenneth Arnold, Steven Goldman, Michael Paolini, and Anthony Sessa.

IBM100: Remembering 1987 Nobel Prize for physics

2011-06-07T13:58:00.011-04:00

Editor's note: Guest author Paul Grant was manager, Cooperative Phenomena Group and Coordinator of High-Tc Research at IBM Research -- Almaden.

On an October afternoon in 1987, a team of IBM researchers at the Almaden Research Center, received impromptu attention on national television -- for their work in physics.

The Nobel Prize in Physics had been awarded to Georg Bednorz and K. Alex Mueller of IBM’s research laboratory in Zurich for their discovery of high temperature superconductivity in copper oxide perovskites (the year before, their colleagues Gerd Binnig and Heinrich Rohrer earned the Nobel Prize for inventing the scanning tunneling microscope).

A number of Almaden scientists had also been working on these new materials for months when, in March of '87, they discovered the atomic structure of the first material to superconduct above the temperature of liquid nitrogen. Previous to this discovery, liquid nitrogen was used as a cheap cryogenic agent made from air and commonly used by dermatologists to treat skin blemishes.

IBM quickly organized a press conference in the lab. The attending Silicon Valley media outlets watched IBMer -- and my daughter -- Heidi Grant lead a demonstration of levitating a magnet over a pellet of the new superconductors. Reporters even jumped and back-pedaled when excess liquid nitrogen spilled across the floor -- which they asked her to repeat several times for the cameras.

After the spectacle of Heidi spilling the liquid nitrogen over and over again for the press, I remember our PR manager, Kay Keeshan saying in jest "thank goodness there isn't any other news to report!"

Photo caption:

IBM Researcher Heidi Grant demonstrating superconductivity at the US National Science Foundation.

IBM100: Memories of Benoit Mandelbrot, by Michael Frame

2011-05-24T09:13:00.004-04:00

An early cosmology placed the earth on the backs of four elephants,  all standing on a turtle. The question, "On what did the turtle  stand?" always was answered, "It's turtles all the way down." Calculus  and all of 19th century analysis worked because the functions studied  are more closely approximated by their tangent lines the more closely we  look. When we zoom in, the curves appear simpler. By the start of the  20th century, mathematicians knew some examples where this was false,  but these were regarded as monsters. Benoit Mandelbrot recognized the  mathematics of these monsters described much of nature, and expanded  this idea into fractal geometry. Very often, nature does not get simpler  under magnification; Benoit gave us a way to quantify the fact that  it's complicated all the way down.  

Michael Frame, a Yale University professor, worked alongside Benoit Mandelbrot, a world renowned mathematician and IBMer, known for coining the word fractal and developing the Mandelbrot set. Read the rest of Frame's article, here.

Inventors' Corner: U.S. Patent #7,516,142 -- System, Method and Program Product for Optimizing a Research and Grant Portfolio

2011-05-17T22:35:00.007-04:00

This invention describes a method, system, and program that assists academic researchers with tracking available grants, identifying potential collaborators and their skills, and locating available equipment and other materials. The system also matches up the people, projects and resources in an ordered and disciplined process. In addition, the patented technique can help university researchers properly respond to requests for grant proposals and to efficiently submit grant proposals.

Scientists from the University of Rhode Island (URI) and IBM Researchers are currently developing a solution based on Patent #7516142 that will enable researchers in the school's pharmacy school to efficiently find the resources they need to more effectively plan, manage and measure the progress of their research projects. Under the collaboration, IBM and URI are working on a tool that combines IBM's data analytics, social networking, and optimization software with URI's knowledge of the academic research experience to discover and capitalize on academic research opportunities.

The researchers are using IBM technology to scour the Internet and other networks for useful data from research publications, grant awards, term papers, etc. and storing in a data warehouse with the URI's data, such as student transcripts, academic expert details and papers, grant info, etc. Next, IBM's analytics software will analyze the content, identify potential projects and uncover available resources and IBM optimization software will recommend connections between open grants and available resources. Finally, IBM social networking software will provide an interface and forum for interested researchers to find and share information about the available projects, as well as their areas of expertise and interest.

U.S. Patent #7,516,142 was issued to inventors Robert Friedlander, Anwer Khan, and James Kraemer.

Nanotechnology and the future of computing

2011-05-17T05:30:00.008-04:00

IBM Research - Zurich and ETH Zurich, a premier European science and technology university, announced today the opening of a new Nanotechnology Center. Joint research projects promise to combine the skills of industry and academic research in ways that neither party could achieve on their own.

The announcement of the new center being made at the first in a series of IBM Research Colloquia. Throughout IBM's Centennial year, IBM will convene thought leaders at our global labs to discuss technologies of the future and their potential impact on business and society. The goal of the Colloquia is to bring together the IBM ecosystem of business, government and academia to help define the computing age of the future.

The IBM Research - Zurich Colloquium will focus on Nanotechnology and the Future of Computing. View recordings of the events via livestream:

Opening Ceremony with IBM Research Senior Vice President John Kelly III

Colloquium Lecture 1: Computing for the Future

Colloquium Lecture 2: Value of Public-Private Partnerships

Colloquium Lecture 3: The Quantum Computer

Webby recognizes IBM site for simplifying Congress’ many bills

2011-05-03T09:53:00.008-04:00

Editor's note: Bradley Schmidt, IBM Government Proposal program manager also contributed to this article.

How many bills did your member of Congress draft last year? On what topics? And what about provisions within the bills not directly related to the topic? Do you even know who your congressperson is?

Of the nearly 10,000 entries submitted to the 15th Annual Webby Awards, fewer than 10% were distinguished as an Official Honoree. This honor signifies an outstanding caliber of work.
– webbyawards.com

Software researchers at the IBM Research Visual Communications Lab in Cambridge, Massachusetts designed the website Many Bills “to make congressional legislation easier to digest.” For their work in simplifying Congress’ bills, the site was named an Official Webby Honoree.

The inspiration for Many Bills came, in part, during the team’s 2009 Transparent Text symposium. Attendees from the nonprofit MAPLight wanted to visualize seemingly unrelated subjects often written into legislation. Done to help gain votes from colleagues, among many other reasons, MAPLight Used the example of a credit card reform bill (HR 627*, sponsored by Rep. Carolyn Maloney, D-NY) that included a section about firearms in national parks.

“Guns in parks, in the same context as credit card reform, seemed a bit off topic,” said Researcher Irene Ros. “So, we began thinking of ways to visualize these potential inconsistencies.”

Reading and learning from many, many bills

Legislation is public record. Anyone can find “firearm” and “national park” in HR 627 – after 13,761 words, on page 32, in section 512, paragraph (a), sub-paragraph (3). Digital copies are available at the Library of Congress’ website, Thomas, which the site GovTrack.us aggregates to make bills downloadable in bulk.

This is where Many Bills comes in: it takes the data from GovTrack and organizes and color codes the bills by topic, congressperson, co-sponsor, and other ways, using web-standards such as HTML5, CSS, and JavaScript (no proprietary plug-ins required).

Bills are categorized by the Congressional Research Service, an arm of the Library of Congress. Many Bills breaks up the bills into these constituent sections and assigns topics to them. It assigned HR 627’s individual sections to the categories “economics,” “education,” and “natural resources.”

Many Bills “learned” how to decipher and categorize this legislative lingo by digesting 10 years worth of past bills using a machine learning toolkit called MALLET.

Users improve Many Bills

Searching for a topic in Many Bills not only shows which bills contain that term or terms, but also highlights the terms within the bill – making it easy to find the term “firearm” in HR 627, for example.

Many Bills also allows users to identify “misfits,” or the text that goes beyond minor category deviations, and into entirely different topics, within a bill (such as HR 627’s section 512). And because Many Bills may not always classify a bill correctly, the site offers users a crowdsourcing feature to flag topics and the “misfit” labels.

We wanted to create a place for people to go and easily look at legislation that is otherwise arcane, baroque documentation.
– Yannick Assogba
IBM Research
Visual
Communications
Lab

The team also recently added a “Members of Congress” section. Now, users can look up their members of Congress to find out what bills they sponsored and co-sponsored, and which were voted into law.

Everyone from journalists, students, and armchair policy wonks can search, study, comment on, and share legislation that affects subjects they care about. Investigating the legislative record of an incumbent congressperson or senator around election time has never been easier.

Looking Ahead

This visualization technology has broad applicability in analyzing any large set of documents, such as the tax code; lengthy business documents and processes; state legal statutes – any place where the amount of text data is an impediment to its digestion.

For now, IBM hopes that Many Bills will help make a seemingly endless ocean of legislation more useful and accessible to everyone. Many Bills’ technology is another example of how analytics can help us understand and organize large data sets.

For more about Many Bills, the team presented at The ACM CHI Conference on Human Factors in Computing Systems in April. And in July, graduate student intern Elif Aktolga from UMass-Amherst will present how she improved Many Bills’ “misfit” detection algorithm at SIGIR 2011.

*Note: The example of HR 627, which passed into law in the 111th Congress, was used only to demonstrate Many Bills’ technology. No judgment or political statement is intended.

Why SmartCamp: spotlight on CareCloud

2011-04-25T19:44:00.008-04:00

In 2010, IBM started SmartCamp, a global initiative for entrepreneurs and start ups that build solutions to make the planet smarter. Participants work with advisors, investors and business mentors from IBM to gain access to venture capital.

“Our mission is to revolutionize healthcare through better technology, so having the chance to engage with an industry leader like IBM was a great way to spread the word and meet with other innovative companies looking to build a smarter planet,” said Albert Santalo, president and CEO of CareCloud, the 2010 Silicon Valley SmartCamp co-winner.

CareCloud’s SmartCamp experience, with President and CEO Albert Santalo

What did CareCloud learn from participating?

“To be recognized by IBM, right in the heart of Silicon Valley, and to receive all the insights of the brilliant people attending, it was an incredible event. SmartCamp helped illuminate some of the key areas for us to focus on to successfully upend an industry resistant to change.”

Has CareCloud experienced an increase in general recognition and business since participating?

“Winning IBM's SmartCamp gave us access to the resources and connections of a global leader in the technology industry.

“It further validated our goal to change the face of healthcare through better technology, recognized us as an innovator in our industry and boosted awareness for our brand. Winning IBM’s Smart Camp was one of the best things that could happen to CareCloud.”

Where and how to participate

In each location, five companies will be selected to spend one day networking with 25 world-class entrepreneurs, investors and industry experts. Applications for the New York City SmartCamp are open until June 3. Apply here.

New York City – June 28, 29 (deadline: June 3)
Tel Aviv – September
Istanbul – October
London - November
China – November
Rio – November

Follow IBM SmartCamp on their blog and Twitter feed @IBMSmartCamp.

IBM Honors the 25th Anniversary of High Temperature Superconductivity

2011-04-18T15:57:00.007-04:00

Twenty-five years ago IBM scientists, J. Georg Bednorz and K. Alex Muller altered the landscape of physics when they observed superconductivity in an oxide material at a temperature 50 percent higher, (-238 deg C, -397 deg F) than what was previously known. This discovery opened an entirely new chapter in the field of physics and earned them the Nobel Prize for Physics in 1987.

Traffic: Global data problem?

2011-04-13T02:18:00.006-04:00

Even with advances in GPS navigation, real-time traffic alerts and mapping, daily commute times are often unreliable, and relevant updates on how to avoid congestion often reach commuters when they are already stuck in traffic and it is too late to change course.

In recent years, IBM researchers have begun to think of traffic as a global data problem.

According to the IBM Global Pain Commuter study conducted last year, the daily commute in some of the world's most economically important international cities is longer and more grueling than before imagined.

But what if you were able to get an email or text message with personalized information on what the traffic patterns of your typical commute look like before your trip even began?

This is a question IBM is answering as part of a new collaboration with the California Department of Transportation and UC Berkeley. Together, they are developing a solution that uses predictive analytics to help commuters avoid traffic congestion and enable transportation agencies to better understand, predict and manage traffic flow. While initially being tested in the United States, IBM is actively working in cities around the world in the area of Smarter Transportation, using a worldwide team of scientists, industry experts and IT services professionals to research, test and deploy new traffic information management capabilities.

Learn more about this project and hear from the lead researcher on this project here.

Video: Discovering excimer laser surgery

2011-04-11T09:54:00.005-04:00

SPIE, the international society for optics and photonics interviews IBM Researcher James Wynne about "the discovery of surgical applications of the excimer laser."

Open architecture helps Watson understand natural language

2011-04-06T09:45:00.006-04:00

Editor’s note: This is a guest post by IBM Senior Technical Staff Member and Apache UIMA Project Management Committee Chairman Marshall Schor. Meet Mr. Schor and Watson at the 2011 Impact Conference, April 10-14.

Natural language is messy. Slang, puns and the context of when and where something is spoken influences meaning. Watson tackled the problem of understanding the natural language of Jeopardy! with a mess of algorithms – managed by an open source architecture.

The open source Unstructured Information Management Architecture (Apache UIMA™) that IBM Research donated to the Apache Foundation in 2006 is what makes Watson’s hundreds of independent algorithms – written in different languages – work together. Watson combines legacy code written in C and C++, developed before Java became popular, with pattern matching algorithms written using Prolog. The majority of the algorithms are coded in Java because it is currently the most popular, general purpose, high performance object oriented language in use today.

IBM Researchers came up with UIMA about a decade ago to connect colleagues who worked on language processing and unstructured information analytics. UIMA (an OASIS standard) wrapped the independent algorithms in a common architecture so they could work together. When UIMA-AS was added to take advantage of multi-core machines and networks of machines, it was a natural fit for Watson.

Watson runs on POWER7 because of its suitability to highly parallelized applications and its high bandwidth between its memory and the 32 cores of each node. UIMA scales out its components across thousands of these cores so Watson can answer a single Jeopardy! clue in about three seconds.

Algorithms at work: Watson learning across categories

Where else is Watson’s software?

UIMA is embedded in several IBM products, including IBM InfoSphere Warehouse, which performs text analytics for both structured and unstructured content. InfoSphere BigInsights has been used to run UIMA analytics within Apache's Hadoop framework for scalable, distributed computing, to analyze and process a broad set of information including unstructured content.

Semiconductor expertise for nanomedicine breakthrough

2011-04-04T07:58:00.006-04:00

For decades, IBM has been known for its leadership in semiconductors, winning the National Medal of Technology in 2005. This award specifically acknowledged over 40 years of IBM semiconductor leadership across a broad spectrum of technologies, including DRAM, copper, Silicon on Insulator, and Silicon Germanium. These innovations — and the Research leaders that have made them possible — have laid the foundation for IBM's continued success in decades to come.

In recent years, IBM researchers are expanding upon lessons learned in intellectual property in semiconductors, and paving the way for IBM to move into entirely new business areas: developing types of plastic that are more friendly for recycling, membranes for water desalination and reading human DNA more easily and quickly (DNA sequencing), just to name a few.

Fundamental principles of nanotechnology like these are allowing IBM to move into entirely new markets and to partner in brand new ways.

Today, Nature Chemistry published a paper by IBM scientists that essentially describes the application of nanotechnology expertise to healthcare, specifically the treatment of antibiotic-resistant bacteria and infectious diseases like Methicillin-resistant Staphylococcus aureus, known as MRSA.

So how exactly can things like magnetism and electrical conductivity be applied to things like medicine and treating infectious disease?

There are two main issues with conventional antibiotics today – one is that they indiscriminately affect all cells – they have no way to tell which ones are infected and which ones are not. Many times it takes multiple cycles of prescribed antibiotics to kill the bacteria.

The second problem is that they do not penetrate cells – so the antibiotics surround infected cells while damaging nearby healthy cells, ultimately allowing bacteria to get stronger and become immune to the antibiotics. Further, the remaining antibiotics typically stay in the body and accumulate in the organs, causing damaging side effects.

Researchers at IBM have designed special nanostructures that have been proven to tackle these two problems. Once in contact with water, the polymers in these agents self-assemble into new structures that are basically magnetically attracted to bacteria membranes based on their electrostatic interaction. Once they ‘find’ the bacterial-infected cells, they break the membrane walls and destroy the bacteria from within the cell. Since there is no physical attraction to the healthy cells, those remain untouched; they can still transport oxygen throughout the body and combat bacteria on their own. Finally, the nanostructures are biodegradable – once they’ve done their job, they leave the body.

MRSA is just one type of dangerous bacteria commonly found on the skin and contracted in places like gyms, schools and hospitals. In 2005, MRSA was responsible for 95,000 serious infections and associated with almost 19,000 hospital stay–related deaths in the United States. Bacteria like MRSA require high doses of antibiotics, which ultimately end up destroying healthy red blood cells in addition to contaminated ones – and even the bad ones end up largely undamaged. For a disease that kills 20% of people that contract it, a better solution needed to be explored.

The ability to explore these uncovered areas is supported by IBM’s long-term vision and investment in research. As science takes us down to the most fundamental structures of life, techniques like these are becoming useful and necessary tools on the path to create better diagnostics and treatments for patients. We’ve already successfully applied principles like these to healthcare initiatives such as 3-D MRI and a one step point-of-care diagnostic test called Lab on a Chip.

For the near-term, these specific agents are intended to be utilized in treating skin infections through the use of deodorants, soaps, hand sanitizers and the like; IBM scientists are looking at developing treatments for things like tuberculosis, lung infections and healing wounds.

Watson goes to school

2011-03-28T15:46:00.000-04:00

Updated 3/29/2011

Watson, IBM’s Deep Question Answering (DeepQA) computing system, tackled Jeopardy!, Congress and South by Southwest. Now, Principal Investigator Dr. David Ferrucci and members of his team are taking Watson to school for a demonstration with Carnegie Mellon University and University of Pittsburgh faculty and students.

The event on March 30, which will be streamed online (link will be live for event), is an opportunity to discuss the future of DeepQA – Watson’s “next job” – with some of the top academics in the field.

What's next in Question Answering

"I think there are two big areas of future research that need our attention:

One is to learn how to build systems in practical business domains with far fewer resources in terms of time, money and people. We need to build applications with Watson’s level of performance for tasks like financial forecasting and health care, and do it cost effectively.

The second area has to do with making Watson smarter. Watson doesn’t grow up in the real world the way that we do, so it doesn’t have a base of common sense knowledge. That’s one of its weaknesses. An interesting question is going to be how Watson can learn to read and build a knowledge base that’s not just factual knowledge, but knowledge about how the world really works.

Teaching a computer to understand a new domain by reading about it is part of our ongoing research with IBM.

Watson has already vitalized research in question answering. People are starting to realize that question answering can be fast enough and good enough to do real world tasks. That’s going to help us as we apply the Watson technology to other areas."

-- Dr. Eric Nyberg, professor with CMU's Language Technologies Institute who consulted with IBM on the Watson project.

The Symposium's agenda

Deep Dive into Deep QA Natural Language Technology with Dr. David Ferrucci and CMU’s Dr. Eric Nyberg

Watson Has a New Job – Keynote Dave Ferrucci, Chief Scientist IBM Watson with Dr. David Ferrucci

Q&A Panel with experts from IBM, CMU and Pitt, moderated by Bernie Meyerson, vice president of Innovation and University Programs, IBM

The panel members include:

Dr. David Ferrucci, principal investigator, IBM Watson
Dr. Eric Nyberg, professor, Language Technologies Institute, CMU
Dr. Scott Fahlman, professor, Language Technologies Institute, CMU
Dr. Jan Wiebe, Professor, Department of Computer Science, director, Intelligent Systems Program, Pitt
Dr. Diane Litman, faculty director, Intelligent Systems Program, Pitt

Check the complete schedule for times and topics.

IBM's Academic Initiative

More than 6,000 universities and 30,000 faculty members worldwide have joined IBM’s Academic Initiative over the past five years. Since 2003, through its University Relations and Academic Initiative, more than 2.5 million students have been trained on IBM and open source technologies.

Remotely manage servers with a mobile app

2011-03-24T22:32:00.000-04:00

Editor’s note: This is a guest post by IBM Senior Technical Staff Member Patrick Bohrer, a research scientist working in mobile systems management.

You can start a car and read a book with a smartphone. But manage a server?

A systems administrator can now monitor an IBM BladeCenter or System x server with the IBM Mobile Remote Systems application – for free.

Walk down an aisle of servers and it’s a myriad of buttons and system indicator lights. Checking on or making changes to a system can be confusing. The IBM Research team in Austin, Texas put the entire interface into a mobile app. Now an administrator can manage and monitor multiple servers from anywhere.

Currently only available for iOS devices (iPhone, iPod Touch, iPad), the app can check systems’ health in a single view, then drill down to examine an individual system’s state, and even perform tasks such as restarting blades, and changing ownership of the media tray or keyboard-video-mouse (KVM) on BladeCenter servers.

Securing access

In a datacenter, an administrator logs in to a system via a power-on password or maybe a screensaver password. On a mobile device, this credential check may mean unlocking a phone through a simple power-on password.

Once unlocked, the user – and when an administrator is away from work, the “user” may be friends and family – has access to every application on the device.

To avoid this potential breach, the Mobile Systems Remote app requires its own application password. The password is required again when the user wants to make a system change. And the app will erase all of its data after too many incorrect password attempts.

User feedback: expanding devices and systems

Administrators can currently access BladeCenter management modules and System x racks that have RSA2 cards (a PCI card service). The app will soon expand to System x boxes with the latest System x Integrated Management Modules (IMM).

The app is only supported for the iPhone right now, but based on customer and user feedback, look for Android and Blackberry options, soon. Have feedback for the team? Add comments to the user forum.

2011 Nico Habermann Award

2011-03-10T10:15:00.000-05:00

Congratulations to Charles Lickel, IBM’s recently retired executive vice president of Global Research Software Strategy, for earning the Computing Research Association’s (CRA) 2011 Nico Habermann Award.

From the CRA:

The Nico Habermann award is given for outstanding contributions aimed at increasing the numbers and/or successes of underrepresented groups in the computing research community.
Charles' accomplishments have had an impact at the national, local, and individual levels for underrepresented groups, and particularly for researchers in the GLBT (gay, lesbian, bisexual, and transgendered) computing community. Within IBM Research, he developed a series of leadership conferences for the GLBT employees. These conferences led to his appointment by the UCLA Anderson School of Business to create a leadership institute in which employees of companies, such as Microsoft and Pepsi, worked with top professors and business leaders to learn to become effective leaders. His leadership and efforts to develop GLBT leaders and act as their role model resulted in his being honored as one of the Gay Financial Network 25 in 2001.
Outside IBM, in addition to his work at the UCLA Anderson School of Business, Charles also has had an impact on computer science programs within academia – such as Arizona State University, New Jersey Institute of Technology, SUNY Albany, and Pace University – through his work on their advisory councils. In 2009, he was awarded the Harvey Milk Alumni Award from SUNY Albany for his outstanding contributions. He has had a significant impact on the universities, their programs, and the students at these universities. In addition to working for the GLBT community, Charles also has been committed to other underrepresented groups in computing and is highly regarded for his leadership within other organizations.

Watson making Information Management (even more) cool

2011-02-17T10:21:00.000-05:00

Editor's note: This is a guest post by IBM's Director of Strategy and Marketing for Database Software and Systems Bernie Spang.

Like many of my colleagues in the IT business, I am often disappointed by the lack of interest I am able to generate among my family and friends when discussing my work. But thanks to Watson, the computing system that can play quiz show Jeopardy! at a champion level, I have experienced a few precious moments where both my kids and parents showed interest in my work

My 15 year old son and 76 year old father both had the same reaction after watching the Watson-Jeopardy! Challenge commercial during the NFL playoffs: “that's cool, but why did IBM build a computer to play games?”

Surprisingly, they both gave me five minutes of their attention – just long enough to sneak in an explanation of how Watson is connected to the IBM Information Management software portfolio.

What is Information Management?

Watson incorporates open technology such as UIMA (Unstructured Information Management Architecture), Eclipse, and Apache Hadoop. The first two of which IBM contributed to the open source community. To build on the medical reference IBM Research Senior Vice President Dr. John Kelly made at the Watson-Jeopardy! press conference in January, a healthcare provider can use this software to analyze patient and treatment information – including doctors’ notes and clinical reports – to pinpoint illness trends and successful treatments.

More about what’s inside Watson

Craig Rhinehart connects Watson and Content Analytics in his blog: 10 Things You Need to Know About the Technology Behind Watson.

These capabilities Watson uses Apache Hadoop to analyze massive amounts of information is also used in IBM’s InfoSphere BigInsights software. And IBM InfoSphere Warehouse uses the UIMA technology for text analytics – just as Watson does.

A new addition to the InfoSphere portfolio, called Streams, analyzes information flowing through systems that may never be stored. Streams can analyze thousands of pieces of vital sign telemetry per second to help save the lives of premature babies (another compelling example that kept my son and father intrigued). While Watson does not use a form of Streams, the two have shared heritage as IBM Research projects.

If you are anything like my dad and son, you are about at your limit of examples to absorb. But hopefully you, too, already get the point. While Watson is an amazing feat of Question Answer technology, my son and dad think the future possibilities for Watson are pretty cool, too.

Watson’s wagering strategies

2011-02-13T11:12:00.000-05:00

Editor’s note: This guest post from IBM Researcher Dr. Gerald Tesauro is the third article in a three-part series about how Watson plays America’s favorite quiz show®.

Daily Doubles and Final Jeopardy! are often the most critical junctures of a Jeopardy! game; the amount wagered can make a big difference in a player’s overall chances to win. How does Watson decide on the amount?

Daily Double wagering

In principle, to compute the best Daily Double (DD) bet, a player must answer two basic questions:

(1) How likely am I to answer the DD clue correctly?

(2) How much will a given bet increase or decrease my winning chances when I get the DD right or wrong?

Match Play

The Watson-Jeopardy Challenge is spread over two games, with combined totals determining the winner. This style of play requires different strategies than a typical game. Final Jeopardy! of game one is analogous to “half time,” so requires different strategies by all competitors, compared to when game two is the last chance to win.

Humans are at best only able to make crude estimates of these quantities. By contrast, Watson uses advanced mathematical models that can answer both questions with far greater precision than humans can achieve.

To address the first question, Watson uses an “in-category DD confidence” model. Based on thousands of tests on historical Jeopardy! categories containing DDs, the model estimates Watson’s DD accuracy, given the number of previously seen clues in the category that Watson got right and wrong.

Watson tackles the second question by using a Game State Evaluator (GSE), a complex regression model that estimates Watson’s winning chances at any stage of the game, given the information set that describes the current game state (for example, the scores of the three players, the number of remaining clues, the value of remaining clues, and the number of remaining DDs).

The GSE was trained over the course of millions of simulated Jeopardy! contests pitting Watson vs. two simulated human opponents. The human opponent models in these simulations capture important statistical profiles of human contestants, such as how often contestants attempt to buzz in; how often they are right when they win the buzz; their accuracy on DDs and Final Jeopardy!.

Optimal wagering

By combining the GSE with the in-category DD confidence, Watson can compute an overall expected chance to win the game for any given DD bet. This analysis runs for every legal betting amount – from the $5 DD minimum, to its entire bankroll for a True Daily Double – to come up with an optimal amount. The calculation also uses risk analytics to trade off expected winning chances against the risk of a particular bet.

Watson’s resulting bet might seem unusual, in that it frequently may be far more aggressive, or far more conservative, than typical human bets. The amount may also take on non-round values (i.e., not an exact multiple of $100). Such values may make the arithmetic a little more challenging for the humans when computing their bets.

Final Jeopardy! wagering

In calculating a Final Jeopardy! (FJ) wager, Watson first needs to know if it is playing a single game or a two-game match [see Call out box: Match Play]. In the latter case, Watson will use very different strategies for game one and game two. The analysis for game one is similar to Daily Double analysis: Watson uses a statistical model of likely human bets, human FJ accuracy, and Watson’s FJ accuracy to calculate its expected winning chances for every legal bet. It then selects the bet giving the best risk-adjusted chance to win the match.

While there are no previously revealed clues in the FJ round, Watson does obtain evidence of its likely FJ accuracy from the category title. Given the title, Watson first computes several salient features via Natural Language Processing analysis. It then consults a “FJ prior accuracy” regression model, based on Watson’s performance on thousands of historical FJ categories, to predict Watson’s accuracy given the category features.

Wagering in game two of a match is similar to FJ in ordinary games. The predominant consideration is score positioning (first, second or third place). In some cases, the contestants may need to use strategic reasoning as in games like Rock-Paper-Scissors – predict the opponents’ bets, while taking into account the fact that the opponents are also trying to predict their bets.

Watson has been programmed with a library of known FJ strategy rules, such as Two-Thirds Betting and Shore’s Conjecture. The research team also added novel rules for some special situations which we discovered.[1]

Depending on the situation, Watson will either bet according to a suitable strategy rule, or it will run a real-time simulation to calculate the best bet, among all legal bets. For the match with Ken and Brad, Watson will also take into account the prize values for second place ($300,000) and third place ($200,000), leading to a different objective than simply trying to win the match.

[1] One such rule in ordinary FJ applies when the leader’s score exactly equals the sum of the other two players’ scores, for example, if Watson has $20,000 and the two humans have $13,000 and $7,000. Watson would normally bet $6,001, to win by $1 when the second place player doubles her score. However, in this case Watson will bet $6,000 to tie for first place. The reason is that if Watson bets $6,001 and is wrong, it gives the third place player a chance to win by $1 ($14,000 to $13,999) if the second place player is wrong.

Knowing what it knows: selected nuances of Watson's strategy

2011-02-03T13:22:00.000-05:00

Editor’s note: This guest post from IBM Researcher Dr. Jon Lenchner is the second article in a three-part series about how Watson plays America’s favorite quiz show®

Watson learns by gathering information, but instead of neural connections, it uses algorithms to understand the natural language that information is written in. These algorithms give it a confidence in a Jeopardy! category and clue, that maps to a probabilistic estimate that the response is correct.

Watson honed this self-assessment of what it does and does not know by training on thousands of historical questions (Watson’s equivalent of taking a few hundred “practice tests”).

The algorithms dealing with natural language are not perfect, so there’s always some degree of uncertainty. Watson calculates its uncertainty and learns which algorithms to trust under which circumstances, such as different Jeopardy! categories.

IBM Researcher Dr. David Gondek, who developed machine learning algorithms and infrastructure that Watson uses to rank and estimate confidence in possible answers, uses an example of how “introducing” and “manufacturing” show how language has many ways to refer to the same relation and can be highly contextual:

“The clue was: It was introduced by the Coca-Cola Company in 1963. Watson can find a passage stating that ‘Coca-Cola first manufactured Tab (the correct response) in 1963’, so in order to answer the question, Watson needed to understand that introducing and manufacturing can be equivalent – if a company is introducing a product. But that is highly dependent on context: if you introduce your uncle, it doesn't mean you manufactured him.”

Watson also exhibits dynamic learning within categories. Watson observes the correct answers to clues to verify it is interpreting the category correctly. The sparring matches offer good examples of Watson making these in-game adjustments. Not only does Watson get better at answering as clues in a category are revealed, but its understanding of its own in-category ability is also refined.

Note, because Watson cannot hear, it does not know how Jennings or Rutter answer a clue. So, Watson cannot use their responses in its accuracy assessment or to change a response it may be considering.

The Confidence to buzz in

Those who watched the practice round could see a graphic of Watson’s confidence level in its top three possible responses, and a line that established a threshold it must reach to buzz in.

Watson’s default threshold is typically 50 percent. In other words, if its confidence estimation determines a 50 percent or higher chance of correctly responding to a clue, it will try to buzz in.

What is a Daily Double?

When a contestant selects a Daily Double, he or she can wager between $5 and either his or her current score (a True Daily Double), if higher than the highest value on the board, or if not, up to the highest value on the board ($1,000 for Single Jeopardy! and $2,000 for Double Jeopardy!)
The first round of Jeopardy! has one Daily Double; the second round has two.

But the buzz threshold is game-state dependent.

The threshold can change substantially towards the end of a game. For example, Watson will lower the threshold if it gives a higher chance to win or, for example, to avoid a statistical lockout. Analogously, if Watson is leading and its only chance of losing a game is to buzz in and respond incorrectly, it will not buzz in, no matter how confident.

Clue selection

If Watson gets to choose a category and clue, its first priority is finding any remaining of the three Daily Doubles in a game. These clues allow a contestant to wager a specific dollar amount on the clue without worry of the other two contestants buzzing in. Jennings, Rutter and Watson have a high chance to answer these correctly, so Daily Doubles provide three opportunities for a critical score boost.

The Watson Research team studied the historical distribution of Daily Doubles and found they appear most-frequently in the three bottom rows, with the fourth being the most common. Daily Doubles also most frequently appear in the first column. Watson also makes use of even more statistics to dynamically predict their location based on what has been exposed so far in a game.

Once the Daily Doubles are off the board, Watson looks for the lowest clue value in a category, for which there are still a significant number of high value clues. Lower value clues help it get the gist of a category with less risk, so that it has a better shot at the high value clues to come.

IBM Research Fourth Quarter 2010 External Honors

2011-01-19T13:14:00.000-05:00

External recognition demonstrates IBM Research's continuing contribution to the company and to the scientific community. Several researchers, past and present, were recognized during the quarter:

Major Award/Medal/Prize

Chieko Asakawa: Achievement Award, Society of Women Engineers, 11/2010
Jan Camenisch: SIGSAC Outstanding Innovation Award, ACM, 10/2010
David Ferrucci: Fred Arditti Innovation Award, Chicago Mercantile Exchange, 10/2010
Alan Gara: Seymour Cray Computer Engineering Award, IEEE: Computer Society, 11/2010
John E. Kelly III: Frederik Philips Award, IEEE, 12/2010

Fellow - Science/Technology Societies

Daniel Dias: IEEE, 11/2010
Brenda Dietrich: INFORMS, 11/2010
Arun Hampapur: IEEE, 11/2010
Arun Iyengar: IEEE, 11/2010
Dharmendra Modha: IEEE, 11/2010
James Stathis: IEEE, 11/2010
Tanveer Syeda-Mahmood: IEEE, 11/2010
David Ugar: ACM, 11/2010
Shumin Zhai: ACM, 11/2010

Award

Matthew Arnold, Stephen Fink, David Grove, Michael Hind, Peter Sweeney: Most Influential OOPSLA Paper Award, ACM, 10/2010
David Bacon: First Decade High Impact Papers, CASCON, 11/2010
Peter Bak: VAST Challenge Award, IEEE Visual Analytics in Science and Technology, 10/2010
Josephine Cheng: Alumnus of the Year, UCLA, 11/2010
Brenda Dietrich: WORMS Award for the Advancement of Women, INFORMS, 11/2010
Kyu-hyoun Kim: JEDEC, 11/2010
Prabhakar Kudva: Region 1 Award, IEEE, 9/2010
Tessa Lau: New Media IT Leadership Award, Women of Color, 10/2010
Brian Lynch: President's Volunteer Service Award, Golden's Bridge Fire Department, 11/2010
Prasenjit Sarkar, Karan Gupta, Reshu Jain, Himabindu Pucha, Dinesh Subhraveti: Supercomputing Storage Winner, IEEE/ACM, 11/2010
Mayank Sharma, Aleksandra Mojsilovic, Yingdong Lu, Mark Squillante, Jianying Hu, Ta-Hsin Li, Heng Cao, Chen Jiang, Tarun Kumar, Yang Liu, Shilpa Mahatma, Yichong Yu: Daniel H. Wagner Prize, INFORMS, 11/2010

How Watson “sees,” “hears,” and “speaks” to play Jeopardy!

2011-01-10T09:32:00.000-05:00

Editor’s note: This guest post from IBM Researcher Dr. David Gondek is the first article in a three-part series about how Watson plays America’s favorite quiz show®

The buzzer sounds.

Jeopardy! host Alex Trebek: “Watson?”

IBM Watson: “What is …”

This scenario will play out on February’s airing of the Jeopardy! quiz show when IBM’s Question Answering system, Watson, will challenge two of the game’s greatest champions, Ken Jennings and Brad Rutter.

Watson, however, cannot “see” or “hear” anything – so how can he play a Jeopardy! game?

Chips, not retinas

When host Alex Trebek finishes stating a clue, a human operator (who works for Jeopardy!) turns on a “Buzzer Enable” light on stage to indicate that contestants can “buzz in” and answer. At exactly the moment the “Buzzer Enable” light is activated, Watson’s system receives a signal that the buzzer is open.

Watson’s avatar, which viewers will see behind a standard Jeopardy! podium, is designer Joshua Davis’ artistic representation of the machine. It does not provide eyes or ears for Watson. Instead, Watson depends on text messaging, sent over TCP/IP, in order to receive the clue. At exactly the moment that the clue is revealed on the game board, a text is sent electronically to Watson’s POWER7 chips. So, Watson receives the clue text at the same time it hits Brad Rutter’s and Ken Jennings’ retinas.

Watson uses IBM’s DeepQA technology (over optimized IBM POWER7 servers) to analyze and produce a Jeopardy! clue response. Those responses come with an associated confidence, or estimated probability that the answer is correct. If his confidence is high enough, Watson may decide to buzz in. To do this, Watson sends a signal to a mechanical thumb, which is mounted on exactly the same type of Jeopardy! buzzer used by human contestants. Just like Ken and Brad, Watson must physically depress a button to buzz in.

Watson’s buzzing is not instantaneous. For some clues he may not complete the question answering computation in time to make the decision to buzz in. For all clues, even if he does have an answer and confidence ready in time, he still has to respond to the signal and physically depress the button.

The best human contestants don’t wait for, but instead anticipate when Trebek will finish reading a clue. They time their “buzz” for the instant when the last word leaves Trebek’s mouth and the “Buzzer Enable” light turns on. Watson cannot anticipate. He can only react to the enable signal. While Watson reacts at an impressive speed, humans can and do buzz in faster than his best possible reaction time.

Speaking when signaled

When answering a clue, Watson must convert his answer from text into speech to verbally respond like any other contestant. An operator prompts Watson to speak his answer. The operator has no control over what Watson might say. The operator just ensures that Watson will speak at the right moment and not interrupt the host or others.

The sound of Watson’s voice is synthesized, based on a human’s voice. Since it’s not possible to record someone speaking every possible word and phrase imaginable – all the more so given the vast range of topics and knowledge that even a single game of Jeopardy! demands – an IBM text-to-speech engine (TTS) “speaks” Watson’s answer. And Watson’s speech must be highly accurate, as mispronunciations of an ambiguous response may be judged incorrect.

Categories and clues

Watson autonomously selects categories and clues, based on algorithms that – just as his human opponents will do – take into consideration available clues; score and game position; knowledge of clues previously revealed, as well as other factors. In the next article of the series, we will take a closer look at how Watson chooses a Jeopardy! category and clue.

Note: As Watson cannot see or hear, he cannot respond to video or audio clues. Jeopardy! has agreed to omit them, just as they have with contestants who are visually or hearing impaired. Watson did take and pass the same Jeopardy! contestant test that humans take to qualify for the show. Find out more about Watson at ibmwatson.com.

An inside look at the Power behind IBM Watson

2010-12-27T09:35:00.000-05:00

Editor's note: This is a guest post from Tilak Agerwala, Vice President, Systems, IBM Research.

The IBM POWER7 processor behind Watson is specifically designed to meet the demands of workloads, like IBM’s DeepQA natural language processing technology. POWER7 is an ideal system for running thousands of analytical tasks at once, which is what the Watson Deep QA software requires. In order to answer a Jeopardy question in under 3 seconds, the system run thousands of breakthrough analytical tasks at once.

Watson uses POWER7 to deliver massive parallelism of multiple complex tasks that execute simultaneously on individual processor threads. Watson relies on multiple IBM Power 750 servers clustered together, each with four processor sockets with eight POWER7 cores per socket, and four threads per core. Combined, they make a workload optimized system that can answer questions posed in natural language in seconds. No other system in the world can do this.

While the Power 750 server provides excellent capabilities to support the IBM Watson Deep QA software, the Power 750 server was not specially designed for Watson. In fact, the same Power 750 servers are ideal for running many types of analytical tasks and available today to help answer practical business challenges across many industries, such as healthcare, financial services, and call center environments.

Power Systems Driving Progress for a Smarter Planet

Rice University in Houston uses IBM Power 755 systems for their cancer research. The challenge for Rice was to accelerate the understanding of the molecular basis of cancer through the application of genome analysis technologies. The researchers used POWER7 systems to provide more flexibility and efficiency in how they analyzed a range of problems.

“The POWER7 architecture has enabled us to pursue a broader range of research problems on a single system than was possible before.” – Dr. B. Kim Andrews, manager of Research Computing.

At GHY International, a customs brokerage firm in Canada, they needed to be better prepared for clients increasing engagement in international trading. GHY needed to quickly deploy new services – and the infrastructure to support those services. So they migrated to a new Power 750 running Power AIX, Power i and Power Linux. And with PowerVM virtualization, they were able to deploy new capabilities in as little as five minutes to support their new-found growth.

Nigel Fortlage, vice president of IT, said that with PowerVM they went from spending 95 percent of their time managing or reacting to their environment, to now only 5 percent.

Today, Power Systems based on POWER7 processors are already helping thousands of businesses deliver services faster, with higher quality, and superior economics. By harnessing the processing prowess of POWER7, Watson and IBM DeepQA give businesses a new dimension in how to solve their most-complex challenges.

IBM computer system a scientific achievement in natural language processing

2010-12-14T08:21:00.000-05:00

Editor's note: This is a guest post from Charles Lickel, Vice President, Software, IBM Research.

The IBM Watson computer system, named after company founder Thomas J. Watson, Sr. catapults data analysis by understanding the nuances of "natural language" that humans use every day.

A breakthrough in the scientific field of DeepQA – a field aimed at furthering computing intelligence – when we began this project more than four years ago, others in the scientific community believed this task to be impossible and we were uncertain about what we would be able to achieve. In fact, it took our research team two years to get the system to be able to analyze a Jeopardy! clue and provide an accurate response in less than three seconds. That was the moment we knew we had a chance of achieving a breakthrough in artificial intelligence and natural language processing, as well as a chance to compete against Jeopardy! champions.

Watson uses Unstructured Information Management Architecture (UIMA), IBM’s open-source framework for analysis of unstructured content, to understand natural language text, speech, images and video. The complex algorithms for the analytics engine behind Watson are tuned specifically for “open-domain” QA – covering a wide domain of knowledge including history, geography, arts, science, sports, and popular culture. It helps Watson handle the broad range of information that language can express and evaluate the “evidence” it collects to determine a confidence level to answer a question.

This fall, the Watson system and the Research team achieved remarkable results, when Watson played more than 55 “sparring games” against former Jeopardy Tournament of Champions contestants.

Watson's ability to understand the meaning and context of human language, and rapidly process information to find precise answers to complex questions, holds enormous potential to transform how computers help people accomplish tasks in business and their personal lives. Watson will enable people to rapidly find specific answers to complex questions. The technology could be applied in areas such as healthcare, for accurately diagnosing patients, to improve online self-service help desks, to provide tourists and citizens with specific information regarding cities, prompt customer support via phone, and much more.

Like Deep Blue, the IBM supercomputer that defeated the reigning world chess champion in 1997, Watson represents a major leap in the capacity of information technology systems to identify patterns, gain critical insight and enhance decision-making despite daunting complexity. But while Deep Blue was an amazing achievement in the application of compute power to a computationally well-defined and well-bounded game, Watson faces a challenge that is open-ended and defies the well-bounded mathematical formulation of a game like chess. Watson has to operate in the near limitless, ambiguous and highly contextual domain of human language and knowledge.

Win or lose, Watson will open eyes to what kinds of questions a computer can answer, and open doors to what kind of problems a computer can solve. For more about the technology behind Watson, visit ibmwatson.com.

Congratulations to IBM's newly appointed ACM Fellows

2010-12-13T19:01:00.001-05:00

Each year, around 40 world leaders in science and technology are part of an elite group that are selected to be named ACM Fellows. The distinction of ACM Fellow comes to those achieving accomplishments that are driving the innovations necessary to sustain competitiveness in the digital age. ACM Fellows are born out of the world's leading universities, corporations and research labs and serve as distinguished colleagues to whom the ACM and its members look for guidance and leadership as the world of information technology evolves.

IBM has held steady in ACM Fellow appointments and this year is no exception. Of the 41 ACM Fellows named for 2010, two IBM researchers achieved this distinction: David Ungar and Shumin Zhai.

David Ungar, selected for his contributions to the design and implementation of object-oriented programming languages, reports in to the Programming Models and Tools Research group at IBM Research - T.J. Watson in NY. David is credited for work on "Tuning Fork," a performance analysis and visualization tool and "Renaissance" - in pursuit of a breakthrough in productivity and performance for massively parallel, tightly-coupled systems such as manycore CPUs. Adding to his list of achievements, David led a group that invented technology that made Java practical and co-designed a programming language that demonstrated how to simplify object-orientation while increasing expressive power. Think JavaScript; it was at the very least the inspiration for the person who designed it.

Having come a long way from repairing stereos and TVs and maintaining and analog computer, David is an expert recognized by peers far beyond IBM.

Shumin Zhai, an IBM Research - Almaden dynamo, was honored for his contributions to human-computer interface research and innovation. Side note: Zhai was a university professor at age 23.

Zhai explains, "I grew up during China's culture revolution, so no one had a job in today's sense. In 1977 - at age 16 - I was among the one percent lucky national university entrance examinees, the first such group after the 10 year culture revolution, to enter universities." He goes on, "By the time I finished my master's degree and started teaching, I was still not much older than the university students I taught. So when I walked into my first lecture I was visibly startled by the students who all customarily raised then burst into laughter. But by the end of the semester, they elected me "the best lecturer" among a teaching staff of well over 100."

Now, as an IBMer, Zhai has several accolades under his belt. We have Zhai to thank for helping invent the ScrollPoint mouse and other input devices of IBM PCs and Thinkpads. He pioneered the touch screen gesture keyboard input method (smartphone, anybody?) with the ShapeWriter project. He's now advancing that research by discovering and refining models and empirical laws of user action on computer screens which quantitatively predict users' performance in pointing, crossing, steering, and stroke gesturing.

Ungar and Zhai join a list of several accomplished IBMers named ACM Fellow over the last 15+ years.

IBM scientist becomes a Humboldtian

2010-12-08T04:19:00.000-05:00

Dr. David DiVincenzo, a quantum physicist from the IBM Thomas J. Watson Research Center in New York, has been awarded the Alexander von Humboldt International Award for Research in Germany. Named for the German naturalist and explorer, winners of the award, also know as Humboldtian's, will have access to a grant worth up to five million Euros to conduct cutting-edge research at German universities.

Dr. DiVincenzo, who researches quantum information theory and quantum computing, was nominated by RWTH Aachen University and Forschungszentrum Jülich, the later being home to the 9th most powerful supercomputer in the world, an IBM Blue Gene.

Dr. DiVincenzo said, " I am pleased that Aachen and Juelich have recognized the future of information technology as one of the centerpieces of their research agenda. I expect to have a productive contribution in this area, as well as in the broader area of theoretical nanoelectronics."

The other winners include:

Psycholinguist Harald Clahsen, currently researching at the University of Essex, Colchester, UK, is to work at the University of Potsdam.
Vahid Sandoghdar is a physicist at the Swiss Federal Institute of Technology Zurich and is to conduct research for the University of Erlangen-Nürnberg and the Max Planck Institute for the Science of Light in Erlangen.

Commenting in the latest winners, Helmut Schwarz, the Foundation's President said, “The nominations from the successful universities of Aachen, Erlangen-Nürnberg and Potsdam show how the Alexander von Humboldt Professorship may be used as a strategic instrument: The award winners will help to expand existing areas of excellence and intensify co-operation with non-university research institutions. The award winners’ knowledge and international repute will contribute to the fulfilment of these strategies.”

Every year, the Alexander von Humboldt Foundation enables more than 2,000 researchers from all over the world to spend time researching in Germany. The Foundation maintains a network of well over 24,000 Humboldtians.

The award ceremony is scheduled for 12 May 2011 in Berlin.

Inventors' Corner: CMOS Integrated Silicon Nanophotonics patents

2010-11-29T09:56:00.000-05:00

IBM has achieved a significant advancement in chip technology that will produce smaller, faster and more power-efficient chips than is feasible with current chip-making techniques. The new technology is called CMOS Integrated Silicon Nanophotonics and is the result of a 10-year research effort across IBM's global research labs.

IBM researchers have generated dozens of pending and issued patents associated with the technology, which integrates electrical and optical devices on the same piece of silicon, and enables computer chips to communicate using pulses of light (instead of electrical signals).

Some of the CMOS Integrated Silicon Nanophotonics patents that IBM inventors hold, include:

U.S. Patent #7,790,495 - Optoelectronic device with germanium photodetector

U.S. Patent #7,738,753 - CMOS compatible integrated dielectric optical waveguide coupler and fabrication

U.S. Patent #7,711,212 - Junction field effect transistor geometry for optical modulators

U.S. Patent #7,684,666 - Method and apparatus for tuning an optical delay line

CMOS Integrated Silicon Nanophotonics is expected to facilitate terabyte-per-second class of single-chip transceivers that will further IBM's Exascale computing program, which is aimed at producing a supercomputer capable of performing one million trillion calculations—or an Exaflop—in a single second.

IBM researchers Yurii Vlasov, William Green, Solomon Assefa, Alexander Rylyakov, Clint Schow and Folkert Horst contributed to the development effort that led to the Nanophotonics technology achievement.

IBM scientist wins major research prize of the German Physical Society

2010-11-22T03:24:00.000-05:00

The German Physical Society (DPG), today awarded the Robert-Wichard-Pohl Prize 2011 to Dr. Gerhard Meyer of the IBM Research lab in Zurich, Switzerland for "his pioneering research in the field of scanning probe microscopy and spectroscopy."

The last IBMers to receive the Prize are none other than Nobel Laureates J. Georg Bednorz and K. Alex Müller in 1987.

In recognizing Gerhard the DPG comments, "His impressive results are a further step to make the world of atoms comprehensible."

In a prepared statement the DPG adds, "Meyer's work has inspired physicists, chemists and biologists alike. The results of his research have generated fascinating images of atoms and molecules that are now included in the textbooks and that illustrate the nano world for all to see."

About Gerhard

Gerhard studied physics in Hanover and achieved his doctorate in 1987. In addition to his first experiments with the scanning tunneling microscope, as a postdoctoral fellow at the IBM Thomas J. Watson Research Center in Yorktown Heights, he also developed an optical readout technology, which has led to breakthroughs in scanning force microscopy.

Then he developed at the Free University of Berlin a low temperature scanning tunneling microscope, which is now used worldwide. After a two-year stay at the Paul Drude Institute in Berlin, he moved to Switzerland where he conducts research since 2002 at IBM Research in Rüschlikon.

Below is a video featuring some of Gerhard's recent work: