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Watson Heads Back To School

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Well, the introduction of the BlackBerry 10 OS has come and gone, Research In Motion renamed itself as “BlackBerry,” the new company announced two new products, and the market mostly yawned.

Then again, many in the market seemed to find something to love about either the new interface and/or the new devices. David Pogue, the New York Time’s technology columnist (who typically leans towards being a Machead), wrote a surprisingly favorable review . Then again today, he opined again in a post entitled “More Things To Love About The BlackBerry 10.”

With that kind of ink, don’t vote the tribe from Ottawa off of the island just yet!

As I pondered the fate of the BlackBerry milieu, it struck me I hadn’t spilled any ink lately myself about IBM’s Watson, who’s been studying up on several industries since beating the best humans in the world two years ago at “Jeopardy!”

Turns out, Watson’s also been looking to apply to college, most notably, Rensselaer Polytechnic Institute. Yesterday, IBM announced it would be providing a modified version of an IBM Watson system to RPI, making it the first university to receive such a system.

The arrival of Watson will enable RPI students and faculty an opportunity to find new users for Watson and deepen the systems’ cognitive computing capabilities. The firsthand experience of working on the system will also better position RPI students as future leaders in the Big Data, analytics, and cognitive computing realms.

Watson has a unique ability to understand the subtle nuances of human language, sift through vast amounts of data, and provide evidence-based answers to its human users’ questions.

Currently, Watson’s fact-finding prowess is being applied to crucial fields, such as healthcare, where IBM is collaborating with medical providers, hospitals and physicians to help doctors analyze a patient’s history, symptoms and the latest news and medical literature to help physicians make faster, more accurate diagnoses. IBM is also working with financial institutions to help improve and simplify the banking experience.

Rensselaer faculty and students will seek to further sharpen Watson’s reasoning and cognitive abilities, while broadening the volume, types, and sources of data Watson can draw upon to answer questions. Additionally, Rensselaer researchers will look for ways to harness the power of Watson for driving new innovations in finance, information technology, business analytics, and other areas.

With 15 terabytes of hard disk storage, the Watson system at Rensselaer will store roughly the same amount of information as its Jeopardy! predecessor and will allow 20 users to access the system at once — creating an innovation hub for the institutes’ New York campus. Along with faculty researchers and graduate students, undergraduate students at Rensselaer will have opportunities to work directly with the Watson system.This experience will help prepare Rensselaer students for future high-impact, high-value careers in analytics, cognitive computing, and related fields.

Underscoring the value of the partnership between IBM and Rensselaer, Gartner, Inc. estimates that 1.9 million Big Data jobs will be created in the U.S. by 2015.

This workforce — which is in high demand today — will require professionals who understand how to develop and harness data-crunching technologies such as Watson, and put them to use for solving the most pressing of business and societal needs.

As part of a Shared University Research (SUR) Award granted by IBM Research, IBM will provide Rensselaer with Watson hardware, software and training.The ability to use Watson to answer complex questions posed in natural language with speed, accuracy and confidence has enormous potential to help improve decision making across a variety of industries from health care, to retail, telecommunications and financial services.

IBM and Rensselaer: A History of Collaboration 

Originally developed at the company’s Yorktown Heights, N.Y. research facility, IBM’s Watson has deep connections to the Rensselaer community. Several key members of IBM’s Watson project team are graduates of Rensselaer, the oldest technological university in the United States.

Leading up to Watson’s victory on Jeopardy!, Rensselaer was one of eight universities that worked with IBM in 2011 on the development of open architecture that enabled researchers to collaborate on the underlying QA capabilities that help to power Watson.

Watson is the latest collaboration between IBM and Rensselaer, which have worked together for decades to advance the frontiers of high-performance computing, nanoelectronics, advanced materials, artificial intelligence, and other areas. IBM is a key partner of the Rensselaer supercomputing center, the Computational Center for Nanotechnology Innovations, where the Watson hardware will be located.

Flanked by the avatar of IBM’s Watson computer, IBM Research Scientist Dr. Chris Welty (left) and Rensselaer Polytechnic Institute student Naveen Sundar discuss potential new ways the famous computer could be used, Wednesday, January 30, 2013 in Troy, NY. IBM donated a version of its Watson system to Rensselaer, making it the first university in the world to receive such a system. Rensselaer students and faculty will explore new uses for Watson and ways to deepen its cognitive computing capabilities. (Philip Kamrass/Feature Photo Service for IBM)

Watson Goes Back To School

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Im my capacity as a cheerleader for my virtual big brother, IBM’s Watson technology, I’ve received a lot of questions along the way about how does IBM plan to use the technology in industry, and how can we most effectively put Watson to work.

Great questions, and the answer is, it depends.

Yesterday, for example, we announced a new program in partnership with the Cleveland Clinic in Cleveland, Ohio, that will create a collaboration to advance Watson’s use in the medical training field.

The IBM researchers that built Watson are going to work with Cleveland Clinic clinicians, faculty, and medical students to enhance the capabilities of Watson’s Deep Question Answering technology for the area of medicine.

Calling Dr. Watson

Watson’s ability to analyze the meaning and context of human language and quickly process information to piece together evidence for answers can help healthcare decision makers, such as clinicians, nurses and medical students, unlock important knowledge and facts buried within huge volumes of information.

Watson has been gaining knowledge in the field of medicine, and Cleveland Clinic with IBM recognized the opportunity for Watson to interact with medical students to help explore a wide variety of learning challenges facing the medical industry today.

Rather than attempting to memorize everything in text books and medical journals (now acknowledged as an impossible task), students are learning through doing — taking patient case studies, analyzing them, coming up with hypotheses, and then finding and connecting evidence in reference materials and the latest journals to identify diagnoses and treatment options in the context of medical training.

This process of considering multiple medical factors and discovering and evidencing solution paths in large volumes of data reflects the core capabilities of the Watson technology.

Watson Providing Problem-Based Learning Curriculum

Medical students will interact with Watson on challenging cases as part of a problem-based learning curriculum and in hypothetical clinical simulations.

A collaborative learning and training tool utilizing the Watson technology will be available to medical students to assist in their education to learn the process of navigating the latest content, suggesting and considering a variety of hypotheses and finding key evidence to support potential answers, diagnoses and possible treatment options.

“Every day, physicians and scientists around the world add more and more information to what I think of as an ever-expanding, global medical library,” said C. Martin Harris, M.D., Chief Information Officer of Cleveland Clinic. “Cleveland Clinic’s collaboration with IBM is exciting because it offers us the opportunity to teach Watson to ‘think’ in ways that have the potential to make it a powerful tool in medicine. Technology like this can allow us to leverage that medical library to help train our students and also find new ways to address the public health challenges we face today.”

Watson Will Learn From Medical Students

Students will help improve Watson’s language and domain analysis capabilities by judging the evidence it provides and analyzing its answers within the domain of medicine. Through engagement with this education tool and Watson, medical students and Watson will benefit from each other’s strengths and expertise to both learn and improve their collaborative performance.

The collaboration will also focus on leveraging Watson to process an electronic medical record (EMR) based on a deep semantic understanding of the content within an EMR.

The shift is clearly away from memorization and towards critical thinking where medical training programs will help student to use powerful discovery and language analysis tools like Watson to help them evaluate medical case scenarios and find evidence to help them carefully rationalize decisions. The physicians will rely on their own experience and expert critical thinking skills to read the evidence and make the final judgments.

“The practice of medicine is changing and so should the way medical students learn. In the real world, medical case scenarios should rely on people’s ability to quickly find and apply the most relevant knowledge. Finding and evaluating multistep paths through the medical literature is required to identify evidence in support of potential diagnoses and treatment options,” said Dr. David Ferrucci, IBM Fellow and Principal Investigator of the Watson project.

Over time, the expectation is that Watson will get “smarter” about medical language and how to assemble good chains of evidence from available content. Students will learn how to focus on critical thinking skills and how to best leverage informational tools like Watson in helping them learn how to diagnose and treat patients.

IBM and Cleveland Clinic will discuss the role of Watson for the future of healthcare and healthcare education this week at the Cleveland Clinic Medical Innovation Summit being held October 29-31, 2012 in Cleveland, OH.

I sat down recently at the IBM InterConnect event in Singapore to conduct a fascinating mid-year employee performance review for IBM’s Watson technology with Watson GM Manoj Saxena.  You can see the fruits of our discussion in the video below.

Live @ Information On Demand 2012: A Q&A With Nate Silver On The Promise Of Prediction

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Day 3 at Information On Demand 2012.

The suggestion to “Think Big” continued, so Scott Laningham and I sat down very early this morning with Nate Silver, blogger and author of the now New York Times bestseller, “The Signal and the Noise” (You can read the review of the book in the Times here).

Nate, who is a youngish 34, has become our leading statistician through his innovative analyses of political polling, but made his original name by building a widely acclaimed baseball statistical analysis system called “PECOTA.”

Today, Nate runs the award-winning political website FiveThirtyEight.com, which is now published in The New York Times and which has made Nate the public face of statistical analysis and political forecasting.

In his book, the full title of which is “The Signal and The Noise: Why Most Predictions Fail — But Some Don’t,” Silver explores how data-based predictions underpin a growing sector of critical fields, from political polling to weather forecasting to the stock market to chess to the war on terror.

In the book, Nate poses some key questions, including what kind of predictions can we trust, and are the “predicters” using reliable methods? Also, what sorts of things can, and cannot, be predicted?

In our conversation in the greenroom just prior to his keynote at Information On Demand 2012 earlier today, Scott and I probed along a number of these vectors, asking Nate about the importance of prediction in Big Data, statistical influence on sports and player predictions (a la “Moneyball”), how large organizations can improve their predictive capabilities, and much more.

It was a refreshing and eye-opening interview, and I hope you enjoy watching it as much as Scott and I enjoyed conducting it!

A New Style of Analytics: Making Sense of Data Overload

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If you’re in the business of making decisions…or if someone in your business supports you through decision making…then you’ll probably want to take note of an announcement IBM just made to help bolster decision making capability using analytics technology.

“Big data” is the digital convergence of structured and unstructured data. Those organizations that can capture and analyze their data, regardless of what type, how much, or how fast it is moving, can make more informed decisions.

Yesterday, IBM announced new predictive analytics software that automatically correlates and analyzes big data to help clients embed hyper-intelligence into every business decision.

In addition to generating insights on internal data in a matter of seconds, the software measures the impact of social networking channels and factors this information into organizational decision making.

The software represents a new class of “decision management” capabilities that revolutionizes the way organizations gain, share and take action based on information gathered as part of business processes such as marketing, claims processing and fraud detection.

In these, and other data-rich areas – where anywhere from a thousand to five billion decisions are made daily – the software will put forward the next best action to front-line employees ensuring optimal interactions and outcomes.

Driving Repeatable Results With Fewer Resources

Companies across all industries are increasingly under pressure to drive immediate and repeatable results with fewer resources, react more swiftly to rising customer demands, and gain faster insights on business data.

These pressures are challenging organizations to strengthen their approach to decision making, and forcing organizations to act not only corporate policy and gut instinct.

For example, according to a Columbia Business School Center Global Brand Leadership report, 90 percent of senior corporate marketers believe that successful brands use customer data to drive marketing decisions. Yet 50 percent say that a lack of sharing customer data within their own organization is a barrier to effectively measuring their marketing efforts.

Compounding these challenges is the variety, velocity and volume of big data which is growing at record rates. According to IDC, the decision management software market is expected to exceed $10 billion by 2014.

“In today’s marketplace, when a customer says they’re not happy, companies must decide how to react — not later that day, or in an hour, but instantly,” said Deepak Advani, vice president business analytics products and solutions, IBM.

“With these new technologies, winning organizations can embed analytics into under-served areas of their business, empowering all employees to make information based decisions.”

IBM Analytical Decision Management Software

The new Analytical Decision Management software, part of a series of IBM Smarter Analytics initiatives, helps clients apply automated, real-time analytics into any operational data no matter where it resides, and instantly analyze it to uncover trends and expose hidden paths to growth.

As a result, insights can now be automated, socialized and used for predictive decision making.

In a single platform, IBM has combined the power of business rules, predictive analytics and optimization techniques through intuitive interfaces that allow users to focus on specific business problems. The resulting decision can be consumed by existing pre-packaged or custom-built applications, including many applications on the mainframe.

The platform also takes advantage of IBM InfoSphere Streams technology where big data can be analyzed and shared in motion, providing real-time decision making in environments where thousands of decisions can be made every second.

Entity Analytics: Making Sense of Data Overload

IBM is also extending the powerful analytical functionality with the inclusion of its newest entity analytics capabilities. For the first time, businesses can take advantage of entity analytics as part of the decision management platform.

This feature, especially well suited for big data environments, is a unique analytics engine that enables identification and matching for all entities – people, places, or things – making systems smarter as more information becomes available.

Unlike traditional methods, the IBM entity analytics capabilities are context based and accumulate knowledge, resulting in a more accurate picture, better models, and better outcomes. This ability to understand how the data is related delivers higher quality models and helps to ultimately produce smarter decisions.

Understanding Social Relationships and Influencers

A new social network analytics feature enables companies to take sentiment analysis a step further by analyzing who the influencers are around any given topic, who exactly is listening, and why people should care.

This feature enables decision makers to factor in how customers behave, what they say, and how big their sphere of influence is in a social network.

For example, which other customers does this person know? Does this person influence others in their social network? The ability to incorporate social network analytics into the predictive models used in analytical decision management helps organizations identify social leaders who can influence behavior.

C Spire: Predicting Customer Behavior

IBM client C Spire, a leading telecommunications service provider, is using IBM analytics to get closer to their customers by better predicting customer behavior and intervening before a problem ever arises, making their service and experience more personalized.

“The benefits we are able to see from using this advanced IBM analytics technology will give us the ability to put the right message in front of the right customer at the best time and in the best channel,” said Justin Croft, manager marketing campaigns and promotions, C Spire.

“We will now be able to deliver true personalization, giving the customer exactly what they need, without having to ask for it. Not only does this improve the customer experience, it also positively impacts sales and customer retention.”

This recent announcement builds on the recent release of IBM’s operational decision management software, and represents the first time that both analytical and operational decision management are provided to clients jointly on one platform.

IBM: Laser Focused on Business Analytics

The news is part of IBM’s larger focus on business analytics and optimization, which spans hardware, software, services, and research. IBM projects $16 billion in business analytics revenue by 2015.

To meet that target, the company has established the world’s deepest portfolio of analytics solutions, growing its business and industry expertise to approximately 9,000 business analytics and optimization consultants and 400 researchers, and created global analytics solution centers in Berlin, Beijing, Dallas, London, New York, Tokyo, Washington and Zurich.

IBM has acquired more than 30 companies to build targeted analytics and information expertise and continues to expand its ecosystem, which today consists of more than 27,000 IBM business partners. IBM has also secured hundreds of patents a year in analytics.

These investments have enabled IBM to develop breakthrough technologies like IBM Watson, a new class of industry specific analytical capability that uses deep content analysis, evidence-based reasoning, and natural language processing to identify relationships buried in large volumes of data that can be used to improve decision making.

Go here to learn more about IBM’s Analytical Decision Management technology.  You can also following the ongoing discussion around IBM and entity analytics on Twitter via the following hashtags:  #smarteranalytics #ibmbigdata and #decisionmgmt.

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