Campus is still abuzz from last week’s announcement that IBM will give a version of its Watson system to Rensselaer. The computer rose to fame in early 2011 after if defeated the two all-time human champions of the quiz show Jeopardy!. The Internet is also abuzz with the news, and our own Jim Hendler is at the very center of the media merriment.

Professor Hendler, who is the head of our Department of Computer Science and one of the lead researchers on the Watson project at Rensselaer, recently did a Q&A with the Washington Post about the future of Watson at Rensselaer. A snippet is below, and you can read the entire story here.

WashPo: What will be the first steps in introducing Watson to the RPI team?

Hendler: Programming Watson requires understanding its particular flow of control in Question-Answering. For those people on campus who have not already been involved in the project, we will have several faculty, staff and students take a 2-day training course led by the IBM team, and then those people, in turn, will be able to teach others as well as jump-starting our work.

What “classes” will Watson be taking? Additionally, will this be, perhaps, the opportunity to create a “curriculum,” if you will, for other systems when it comes to processing the large volume of unstructured data out there?

We will be looking at a number of different projects that explore what Watson can do. One thing we want to explore is how Watson can interact with social media, especially things such as “tweets” where the language is not as carefully constructed as it is in the documents Watson has used in the Jeopardy game. Another thing we will be exploring is adding various kinds of numerical reasoning to Watson. There’s lots more.

So to do all this, we’re taking a two-pronged attack. One approach, utilizing our graduate students, will be exploring how to add new capabilities to Watson and how to use its current capabilities in many of our ongoing research projects. For example, I run a group that does a lot of work with Open Government Data systems (like the US data.gov) and we’re excited about the possibility of using Watson to help researchers around the world find relevant government data and documents for their work.

At the end of the three-year project, what is the ultimate goal for Watson?

Imagine having been the first university to get a telescope a few centuries back. Everywhere you pointed it was something new and exciting, and it would be impossible to predict everything you would see. Having Watson is like that for us — our goal for the next few years is to gain an understanding of what having the new ways of bringing unstructured data and documents into our computational lives will be.

At Rensselaer, it’s a different story.

Student members of the Entrepreneurship Club are getting ready to host the preliminary round of the University Hacker Olympics. The event will make its official debut tomorrow, from 2 to 6 p.m, in the Center of Industrial Innovation (CII) room 4034.

In a span of only four hours, students from Rensselaer and several universities will work to write a piece of code to solve a puzzle. If it works, then the students will continue to tweak the algorithm. Students creep up the leader board (we are not talking about the reality television show Dancing With the Stars) by refining the code to make it run faster and more efficiently.

So, how did all of this get started?

The Entrepreneurship Club was approached by several tech startup companies in California to compete in the event. Business and Management major, Kevin Petrikas, who also serves as the club’s president says that the club has been looking to expand its membership and include tenacity minded people:

The Hacker Olympics will help promote entrepreneurship on campus by linking the best and brightest RPI students to the top startups in California hopefully producing relationships and job offers. I think that students will get excited about entrepreneurship and an event like this encourage students to think about starting their own companies, or at least that’s the goal.

In addition to Rensselaer, some participating colleges and universities include: Berkeley, Brown, Carnegie Mellon, Champaign, Columbia, Harvard, Johns Hopkins, MIT, Ohio, Penn State, Purdue, Rice, RIT, Stanford, University of Michigan, University of California, and many more.

The overall event is sponsored by SignalFire, a California-based company that was created to “engage the world’s most audacious dreamers and builders through events and initiatives designed to bring together today’s technology leaders with tomorrow’s breakout stars.”

The goal of the preliminary round is to construct a team of over 100 top developers from participating schools. Winners will get an all expense paid trip to Silicon Valley to compete in a weekend long hackathon, and get a chance to code alongside CTO’s and top engineers from the hottest tech startups like AirBNB, Square, Stripe, and 30 others. The national finals will be held Jan 11-13, 2013.

What do the winning hackers get out of this? Beyond the chance of competing for over $150,000 in travel and related prizes, winners get to party with awesome people. Meet other awesome students from across the country. And maybe even land a job at a top Silicon Valley company.

Sounds golden to me.

Click here for more information about the national competition.

Jim Myers, director of the Rensselaer supercomputing center, CCNI, was recently named to the High Performance Computing (HPC) Advisory Committee of the U.S. Council on Competitiveness.

We ask Jim about his work:

Q: So, why is CCNI so super?

A: Every hour, CCNI does more calculations than everyone on the planet working together could do in a lifetime. And more importantly, the researchers and companies who use CCNI know how to harness that power to make cutting-edge discoveries and design advanced new products. CCNI is super because it amplifies our human ability to innovate.

What is parallel processing all about?

We all parallel process whenever we work as a team – each person works on a small piece of a larger problem the team is trying to solve. CCNI works the same way – with thousands of processors working on smaller parts of one big problem at the same time. Just as coordinating a team can be harder than working alone, “parallel programming” can be harder than programming for your home computer. But in both cases, the ability to solve problems faster and to solve larger problems is worth the effort.

Tell me briefly about your Medici@RPI project.

Medici brings a lot of the ease-of-use we expect from web applications to the management of scientific data sets. It actually looks a bit like Flickr and lets you tag data, but it can also track data “provenance” – where data comes from – to support reproducible research. Being able to dig back from results to understand how they were derived becomes increasingly important as we use supercomputers to do scientific experiments, design new products, and inform decision making. I should note that Medici was developed by my former colleagues at the National Center for Supercomputing Applications (where Mosaic, the first web browser, came from) and we’re hoping that it will be a part of an ongoing collaboration between several universities.

Your undergraduate degree is in physics, and your doctorate is in chemistry. How did you end up in computer science?

I realized, as did the people who created CCNI, that one of the best ways to accelerate innovation is to harness computer science research and computational resources. In my case, I kept finding situations where some relatively simple programming enabled my research, and that of my colleagues, to go a lot faster – more science was getting done than if I stayed in the lab 24 hours a day. That just snow-balled and eventually landed me here.

Here’s a short list of totally unrealistic movies about scary computers gone bad: Tron, War Games, The Matrix, Westworld, Terminator 2, I Robot. Which one is tops, in your book?

First – let me just say that I sleep fine at night, and the CCNI computers have shown no signs of wanting to take over the world. While all of these movies have interesting ideas in them, I’d have to pick Westworld just because it raised things like the idea of using computers for entertainment and computer viruses so early.

You’ve been in the Troy area for almost a year. What’s your favorite restaurant so far?

Wait a minute – it’s actually been less than six months – snowy ones at that! We’ve got a lot more exploring to do, but we like Ala Shanghai in Latham. They have a very broad menu and the atmosphere reminds my wife and I of places we went in graduate school.

Read more about Jim here. And be sure to check out our other 3° Interviews on The Approach.

There’s quite a buzz this morning about the third and final installment of Jeopardy! The IBM Challenge. And with good reason: Our new favorite friend Watson handily defeated his carbon-based opponents, the two most-celebrated Jeopardy! champions of all time, Ken Jennings and Brad Rutter.

Of course, given that Rensselaer graduates at IBM led and worked on the Watson project for four years, there was little doubt here in Troy that the now-famous supercomputer would prevail.

If Tuesday evening was the challenge’s Empire Strikes Back, filled with pitfalls and peril, then last night’s game was undoubtedly Return of the Jedi. Determining the heroes and villains, however, was a matter of perspective. Underneath his Final Jeopardy answer, Jennings wrote “I, for one, welcome our new computer overlords.” In his mind, he was co-piloting the Falcon with Rutter but they epically failed to destroy the Death Star.

While I was sitting in EMPAC last night with 800+ students, faculty, staff, and alumni, it was clear the audience had a different idea. To us, Watson was the hero of the story, our Luke Skywalker. The newsclip above ran last evening on Channel 13, which gives a nice overview of the viewing party. Below is a great observation by Times Union blogger Kevin Marshall, who was also at EMPAC last night:

“Aspiring scientists and engineers in the crowd treated the contraption with an eagerness and endearment that, though sometimes masked through attempts at ironic humor, was clearly affection for the machine. It was all in fun and a good sign for those of us who recognize our country’s quiet crisis in the maths and sciences, but I still felt slightly disheartened that people were rooting for the inorganic to triumph over the human underdogs.”

Jennings, who played well on Wednesday and at one point posed a very real threat to Watson, later came around to our way of thinking. “I wasn’t the hero at all. I was the villain,” he wrote last night in an essay at Slate titled “My Puny Human Brain.” He goes on to pay the IBM Watson team a sincere compliment rife with geek cred. “Watson has lots in common with a top-ranked human Jeopardy! player: It’s very smart, very fast, speaks in an uneven monotone, and has never known the touch of a woman,” he wrote.

It was a treat to watch the panel discussion leading up to and following the Jeopardy! broadcast. You can watch the whole thing here. Rensselaer graduates and IBM Team Watson researchers Chris Welty and Adam Lally shared great insight and really connected with the audience. My favorite anecdote was about Watson’s betting strategy. On Daily Doubles and Final Jeopardy, the computer wagers highly particular numbers that initially seem (but are not) somewhat random. This caught the attention of many people in the early testing days of the system, prompting the researchers to tweak algorithms so Watson always rounded its bet to the nearest 100. After instituting this change, people said they missed the quirkiness of the odd bets, so the Watson team ditched the round number command.

Another favorite part of the discussion, which was moderated by Rensselaer Vice President for Research Fran Berman, was hearing Rensselaer professors Deborah McGuinness, Sanmay Das, and Selmer Bringsjord connect their own research streams to the technology behind Watson.

The panel remarked that Watson doesn’t truly understand the significance or meaning of Jeopardy! answers or questions, it’s more about making connections and probability. Well, McGuinness is a world leader in using ontologies to empower computers to semantically “understand” language. She mentioned her wine app, now available for download on iDevices, that uses personal preferences, info from the cloud, and other factors to help users pair a wine with their meal in real time. Looking forward, we should expect to incorporate more kinds of Watson-like assistance in everything from making medical decisions to choosing a good pinot, she said.

Financial modeling expert Das spoke about our natural inclination to mistrust computers, simply because they’re computers, but how Watson can help peel back those biases. This is a good thing, he said, as in a few years we’ll all be best buds with our cell phone, which will be able to speak with us and convey truly useful information.

Welty went one step further, and noted he expects our cars to be self-driven and operated in the near future, which will reduce the total number of accidents and make our roadways considerably more efficient.

Bringsjord, who was Welty’s faculty advisor at Rensselaer, is a global thought leader in the field of artificial intelligence. He agreed about the vast potential of Watson technology as a way to augment, but not replace, the human mind. Bringsjord said he’s doubtful that Watson or other computers will be able to become self-aware or pass the Ada Lovelace Test and sincerely surprise their programmers with original, creative thought. However, he said we should take every precaution to make sure AI and cognitive systems – particularly those used in defense applications – have stringent and robust failsafes to counter any possibility of computers acting in an evil or immoral fashion. This harkens to his well-established research thrust that calls for vigilance today to hedge against potential AI hazards in the future. Overall, Bringsjord was bullish on Watson and decidedly proud of his former students:

“It’s an amazing thing to ponder how fast [IBM], with its brilliant minds, has taken us from Deep Blue – at a time when people said, ‘Meh, [chess] is a solvable game on an 8×8 grid, where’s the language?’ And here we sit. Personally, it’s amazing to me, as I knew these three guys here, and I knew they were brilliant. But what they’ve done here, with their colleagues, is amazing.

All in all, if Ken Jennings were in the audience last night, I’m confident the panelists’ discussion would have quelled all of his concerns about “computer overlords.”

Below is some grist for the mill:

The Associated Press quoted Rensselaer Professor Jim Hendler in a story that appeared online and in newspapers across the globe this morning:

“A human working with Watson can get a better answer,” said James Hendler, a professor of computer and cognitive science at Rensselaer Polytechnic Institute. “Using what humans are good at and what Watson is good at, together we can build systems that solve problems that neither of us can solve alone.”

Additionally, Rensselaer graduate and Watson team leader David Ferrucci was quoted in the New York Times this morning:

Nevertheless, Watson, which took 25 IBM scientists four years to create, is more than just a trivia whiz, some experts say.

“I see human intelligence consuming machine intelligence, not the other way around,” David Ferrucci, IBM’s lead researcher on Watson, said in an interview Wednesday. “Humans are a different sort of intelligence. Our intelligence is so interconnected. The brain is so incredibly interconnected with itself, so interconnected with all the cells in our body, and has co-evolved with language and society and everything around it.”

“Humans are learning machines that live and experience the world and take in an enormous amount of information — what they see, what they taste, what they feel, and they’re taking that in from the day they’re born until the day they die,” he said. “And they’re learning from all the input all the time. We’ve never even created something that attempts to do that.”

The stature of Rensselaer as a national locus and leader in the emerging field of Web science research is quickly crystallizing. We’ve known it to be the case for a while, and the rest of the country is finally catching on.

Faculty and students from the Institute’s Tetherless World Constellation have been hard at work backing up this reputation. Over the past eight months, the group has created more than 40 “mash-ups” of U.S. government data. These mash-ups connect previously unconnected data sets, taken from the year-old www.data.gov site, and combine them into something new and interesting.

The video sbove, created by doctoral student Dominic DiFranzo, is an excellent example. Dominic mashed up raw data on ozone and visibility readings in the United States with separate geographical data on where the readings were taken. This had not been done before, as the two data sets were released on separate Web sites using differing technologies. The result is a mash-up that plots this combined information in a way that’s interactive (i.e. clickable, zoomable, scrollable), user-friendly (it leverages the ubiquitous Google Maps platform), and intuitive. Check out this demo of the mash-up.

Another mash-up demo uses different data sets on Supreme Court decisions to visualize the how different justices veered more conservative or progressive on different issues (e.g. gun control, crime) over the years. Other demos include mashing up the White House visitor list with information from Wikipedia and Google, mashing up U.S. and British information on aid to foreign nations, and a mashed-up timeline of government agency budgets and New York Times reports on those agencies.

The full list of mash-up demos is at http://data-gov.tw.rpi.edu/wiki/Demos

Dominic actually gave a demo of his mash-up last Friday at the event in Washington D.C. commemorating the one-year anniversary of Data.gov. At the event, U.S. Chief Information Officer Vivek Kundra applauded RPI’s leadership role in using the Web to promote government transparency. At the same event, Kundra named RPI Professor James Hendler an “Internet Web Expert” who will advise Data.gov. To boot, RPI last month launched the nation’s first undergraduate degree program in Web Science. This is a place where things are happening.

The best part of the story, in my mind, is that Hendler and the RPI team are doing all of this with an open-source mind set. While the mash-up demos are very interesting, the Tetherless team’s ultimate goal is to create a platform for anyone to quickly and easily pull data sets together and create their own mash-ups. They’re endeavoring to design a simple, powerful interface for anyone to pull data sets from Data.gov and weave them together in a meaningful way.

Grist for the mill: check out this Wired story on the one-year anniversary of Data.gov; a good overview of the Tetherless World Constellation; and a nice Alumni Magazine story on Web science and the work of the Tetherless folks.

Web scientists at Rensselaer believe that a revolution in the age-old scientific process is at our fingertips.

Interdisciplinary research has become a prerequisite to even be considered for most major research funding. But, despite the increased collaboration across disciplines, data remains highly specialized and inaccessible. This keeps the scientific process moving at a crawl. To build on the data of another scientist, the original results often need to be painstakingly recreated before the work of answering any new questions can even begin. This process also prevents anyone without a Ph.D. from getting involved in the real scientific process.

Our triad of web gurus in the Tetherless World Research Constellation are looking to move the discoveries in the laboratory to the World Wide Web. This triad includes data scientist Peter Fox, semantic ontology expert Deborah McGuiness, and Semantic Web creator James Hendler.

To quickly advance the processes of science, the scientists are creating platforms for massive scientific collaboration on the Web. Their technologies would be based in the Semantic Web, tagging data in thousands of ways and making each piece of data a million times more useful to a computer than the static numbers-on-the-screen of today’s scientific datasets. This would allow the computer to interpret data like never before, allowing the computer to compile millions of datasets from scientists around the world.

Their research could significantly increase access to scientific data and the scientific process by opening the opportunity for discovery up to scientists, policy makers, teachers, and even the general public. This could speed the rate of discovery on topics that consistently cross disciplines such as climate change and the causes of cancer. If you click on the graphic above, you can see all the different types of data and disciplines that intersect during a search for information on the Earth’s atmosphere.

More information can be found in a story that I wrote on the research here.

Here is a quick quiz for our keen-eyed, celestial-minded readers:

Which of the above images of a lunar eclipse is an actual photo taken with a digital camera, and which is computer simulation rendered from scratch by Rensselaer researchers?

Answer is after the fold …

If you guessed that the image on the right is the photograph, then you’re correct. But as the images are nearly identical and probably indistinguishable to the untrained eye, it must have been a lucky guess.

And that’s exactly the point. Computer graphics experts and computer scientists strive to create visualizations and simulations that are so close to reality, the human mind can’t tell the difference. It’s a technique most of us are exposed to on any given day via television and film. In the realm of science and research, these types of simulations can be used to test data, proof models, or create renderings.

In this case, the lunar eclipse simulations created by professor Barbara Cutler and doctoral student Ted Yapo are affording researchers a novel chance to look back in time at historical eclipses, and even peek forward in time at future eclipses. Reach more about it at the project page and in our recent news story.

Also, be sure to follow this link and watch a cool video of the simulations in action: Lunar Eclipse Modeling