Big Data. Big Decisions
InformationWeek
Special Coverage Series


IBM's Watson Finds Home At Rensselaer Poly Tech

IBM's cognitive computer will let university do advanced computing research and expose students to big data analytics disciplines.

20 Top Masters Degrees For Big Data Analytics Professionals
20 Top Masters Degrees For Big Data Analytics Professionals
(click image for larger view and for slideshow)

Rensselaer Polytechnic Institute has secured a complete installation of the IBM Watson system through an IBM grant program.

More Insights

Webcasts

More >>

White Papers

More >>

Reports

More >>

RPI faculty, researchers, and students will get an opportunity to work hands-on with the latest iteration of the cognitive computing system that famously bested human champions at Jeopardy! in 2011.

"The notion here is that we want to take the Watson system and get it into the university academic world," said Michael Henesey, a VP of Business Development who works with IBM Research. "We think this is going to produce great things."

[ Ready to polish your crystal ball? Read To Avoid Nasty Surprises, Higher Ed Turns To Prediction.]

RPI was chosen partly because of its strength in cognitive computing research and because computer scientists there were involved in some of the original research projects that led to the creation of Watson. In addition, RPI has long provided talent to IBM, which is headquartered in New York State and has one of its principle research centers there. This is the latest in a series of IBM partnerships with universities aimed at training data scientists.

"We'll hopefully generate strong new professionals out of it," Henesey said. That's the focus of IBM's broader efforts involving more than 200 educational institutions globally in big data and analytics research and education, he said. "We want skills to flow and become available to us. Our customers are also telling us this is a top concern of theirs because of the vast amount of information they're coming into contact with from social media and sensor data. We're seeing that 90% of the world's data was created in the last two years -- that's a fun statistic -- so we know it's growing, but the trick is how do we work with it."

15 terabytes of hard disk storage, the Watson system at Rensselaer will store more information than its Jeopardy! predecessor and will allow 20 users to access the system at once. Cognitive computing systems like Watson attempt to mimic the human brain, absorbing vast amounts of natural language data such as news articles, decoding its nuances and seeking to derive inferences and make optimal decisions.

IBM has been exploring practical applications of Watson technology in healthcare with WellPoint and Memorial Sloan-Kettering Cancer Center and in financial services with Citigroup. However, it's still far from being a neatly bundled product, and these organizations are partnering with IBM in a spirit of experimentation and exploration, Henesey said.

IBM's work with Rensselaer is "a collaboration to evolve the technology, so it's a little different," Henesey said. However, in addition to providing computer science researchers with a test bed, RPI will be encouraged to find applications of the analytic engine for use in other branches of science or economics. "They're very good at going cross-domain within the university," he said.

The grant of the Watson system was made under IBM's Shared University Research awards program, which connects the research and researchers at universities with IBM Research, IBM Global Services and IBM's development and industries labs. Among other things, the program aims to increase access and use of IBM technologies for research and in curriculum.

Henesey wouldn't say whether other universities should be lining up with requests for a similar grant of a Watson system. "What we're announcing now is the relationship with RPI. We're going to try to get that right and see where it takes us."



Related Reading




Currently we allow the following HTML tags in comments:

Single tags

These tags can be used alone and don't need an ending tag.

<br> Defines a single line break

<hr> Defines a horizontal line

Matching tags

These require an ending tag - e.g. <i>italic text</i>

<a> Defines an anchor

<b> Defines bold text

<big> Defines big text

<blockquote> Defines a long quotation

<caption> Defines a table caption

<cite> Defines a citation

<code> Defines computer code text

<em> Defines emphasized text

<fieldset> Defines a border around elements in a form

<h1> This is heading 1

<h2> This is heading 2

<h3> This is heading 3

<h4> This is heading 4

<h5> This is heading 5

<h6> This is heading 6

<i> Defines italic text

<p> Defines a paragraph

<pre> Defines preformatted text

<q> Defines a short quotation

<samp> Defines sample computer code text

<small> Defines small text

<span> Defines a section in a document

<s> Defines strikethrough text

<strike> Defines strikethrough text

<strong> Defines strong text

<sub> Defines subscripted text

<sup> Defines superscripted text

<u> Defines underlined text

BYTE encourages readers to engage in spirited, healthy debate, including taking us to task. However, BYTE moderates all comments posted to our site, and reserves the right to modify or remove any content that it determines to be derogatory, offensive, inflammatory, vulgar, irrelevant/off-topic, racist or obvious marketing/SPAM. BYTE further reserves the right to disable the profile of any commenter participating in said activities.

Disqus Tips To upload an avatar photo, first complete your Disqus profile. | View the list of supported HTML tags you can use to style comments. | Please read our commenting policy.

Follow InformationWeek

By The Numbers

What Are Your Primary Concerns About Using Big Data Software?

Base: 417 respondents at organizations using or planning to deploy data analytics, BI or statistical analysis software
Data: InformationWeek 2013 Analytics, Business Intelligence and Information Management Survey of 541 business technology professionals, October 2012

What Do You Think?

What's your attitude about SQL analysis on top of Hadoop?
We want fast, standard SQL analysis capabilities on Hadoop ASAP
Hadoop is for unstructured data; SQL is for relational databases
We'll give SQL on Hadoop a try, but relational DBs will remain the mainstay
Given strong SQL support on Hadoop, we'd nix the data warehouse
We're not interested in Hadoop
No opinion



Related Content

From Our Sponsor

Five Big Data Challenges and How to Overcome Them with Visual Analytics

Five Big Data Challenges and How to Overcome Them with Visual Analytics

Business leaders often need a visual snapshot of data to quickly grasp and use it. This paper identifies five challenges in presenting data and how visual analytics can resolve them. Solutions are suggested to overcome the challenges of: speed, data clarity, data quality, displaying meaningful results, and dealing with outliers.

Game-Changing Analytics: How IT Executives Can Use Analytics to Create Innovation and Business Success

Game-Changing Analytics: How IT Executives Can Use Analytics to Create Innovation and Business Success

Today's competitive advantage requires a deeper understanding of your business, your market and your customers. As an IT executive, you can drive that knowledge transformation. In this white paper, learn how to make decisions as a strategic business leader and three steps to begin an analytics initiative within your enterprise.

Data Visualization Techniques: From Basics to Big Data with SAS Visual Analytics

Data Visualization Techniques: From Basics to Big Data with SAS Visual Analytics

High-performance data visualization turns sophisticated analyses into meaningful graphics, leading to faster and smarter decision making. In this white paper, learn how visual analytics can transform big data, with additional features such as real-time functionality, mobile compatibility, robust applications for technical groups and accessibility for nontechnical users.

Big Data: Lessons from the Leaders

Big Data: Lessons from the Leaders

Financial performance, competitive advantage, operational efficiency, strategic decision making - every business goal can extract value from big data, and the time for doubt or inaction has long passed. In this Economist Intelligence Unit report, in-depth interviews with data pioneers reveal the link between the effective use of big data and the bottom line among other results.

Decision-Driven Data Management: A Strategy for Better Decisions with Better Data

Decision-Driven Data Management: A Strategy for Better Decisions with Better Data

Which came first, the data or the decision? This white paper makes the case for having a decision in mind, then tailoring big data's volume, variety and velocity to achieve business results such as overcoming customer dissatisfaction or creating well-informed strategies in real time.

Informationweek Reports

Research: The Big Data Management Challenge

Research: The Big Data Management Challenge

The challenge of big data is real, but most organizations don't differentiate 'big data' from traditional data, and nearly 90% of respondents to our survey use conventional databases as the primary means of handling data. We'll help you understand what constitutes big data (it's not just size) and the numerous management challenges it poses.