Dr. James Hendler, Professor and Computer Science Department Head, Rensselaer Polytechnic Institute

By Dr. James Hendler

Every single student in the Department of Computer Science here at Rensselaer Polytechnic Institute has the potential to revolutionize computing. But with the arrival of Watson at Rensselaer, they’re even better positioned to do so.

Watson has caused the researchers in my field of artificial intelligence (AI) to rethink some of our basic assumptions. Watson’s cognitive computing is a breakthrough technology, and it’s really amazing to be here at Rensselaer, where we will be the first university to get our hands on this amazing system.

With 90 percent of the world’s data generated in the past two years, the ability for people and even traditional computing systems to make sense of this data has grown complex. The addition of Watson to our campus is very timely considering the growth of what some have termed “Big Data.” 

In 1976, Joseph Weizenbaum, a leading computer scientist, wrote a book called Computer Power and Human Reason: From Judgement to Calculation, in which he criticized the field of AI for trying to replace human creativity and thought with the power of computers.  He suggested that humans and computers were inherently different, and that trying to get computers to think like humans was an insurmountable task, if it was possible at all.

Virginia M. Rometty, the chief executive and newly appointed chairman of I.B.M., answered a mysterious and pressing question on Tuesday: Where is Watson?

Watson is the room-size computer that defeated its human rivals to become a “Jeopardy!” champion. The answer, Ms. Rometty said at Fortune’s Most Powerful Women summit, is that Watson is in medical school.

The computer is working with many health care organizations to learn medical data so it can diagnose cancer, and that is just the beginning. It has so far ingested 80 percent of the world’s medical data.

“Watch it work, and it’s almost as if he’s talking to a colleague,” Ms. Rometty said. “The beauty of it is it tells you what’s right or wrong,” and explains with confidence why it believes what it says.

Watson’s skills – from “Jeopardy!” to oncology to working with banks and call centers – are part of I.B.M.’s bigger aim. It is called cognitive computing, which she described as machines that can learn.

“In this world of huge and big data, you won’t be able to program machines for everything they should know,” said Ms. Rometty. “These machines will have to learn what is right, what is wrong, what is a pattern.”

It is the third wave of computing, she said. At first, computers could count. Today, they are programmed to follow “if this, then that.” Next they will need to discover and learn on their own, she said, not just as a search engine, but proactively. The next era, for all jobs, not just those in computing, will be to help businesses sift big data, she said.

“It’s going to be a whole era to help you get through this, and everyone’s job, from chief marketing officer to chief of police, their jobs are going to be redefined by that,” she said.

nextbigfuture.com

To test the system, Watson was first tasked with answering questions taken from Doctor’s Dilemma, a competition for trainee doctors that takes place at the annual meeting of the American College of Physicians. Watson was given 188 questions that i…

IBM reports that the company is putting Watson to work: “Watson’s cognitive capabilities were designed to take on the real-world challenges of Big Data across a range of industries. From the outset, the aim was to put Watson to work first in healthcare and finance. Both industries confront deluges of unstructured data every day, and both industries have a compelling need to act on information quickly… While the Jeopardy! challenge demonstrated Watson’s ability to provide a single correct answer with confidence, IBM envisions the underlying technology moving toward a broader range of applications and industries to provide evidence-based decision support over large volumes of variable content.”

It continues, “Watson’s goal is to consider not simply queries but entire problem scenarios, to engage interactively to improve the accuracy of its answers and to present explanations that support its output. While healthcare is the first industry Watson has been put to use in, the technology will be adapted and made scalable for other domains such as tech support and contact centers. Watson’s architecture will be advanced to handle real-world challenges found in several business domains, where it will undergo training and a continuous learning process, enabling it to bring value to the enterprise while continuing to get smarter over time.”

(N.B.  IBM Research is also well along on various aspects of AI, such as Watson, and a new generation of cognitive computing chips and other frontiers of neuroscience, supercomputing and nanotechnology)



John Markoff of the New York Times reports, “Inside Google’s secretive X laboratory, known for inventing self-driving cars and augmented reality glasses, a small group of researchers began working several years ago on a simulation of the human brain. There Google scientists created one of the largest neural networks for machine learning by connecting 16,000 computer processors, which they turned loose on the Internet to learn on its own. Presented with 10 million digital images found in YouTube videos, what did Google’s brain do? What millions of humans do with YouTube: looked for cats.”

He continues, “The neural network taught itself to recognize cats, which is actually no frivolous activity. This week the researchers will present the results of their work at a conference in Edinburgh, Scotland. The Google scientists and programmers will note that while it is hardly news that the Internet is full of cat videos, the simulation nevertheless surprised them. It performed far better than any previous effort by roughly doubling its accuracy in recognizing objects in a challenging list of 20,000 distinct items. The research is representative of a new generation of computer science that is exploiting the falling cost of computing and the availability of huge clusters of computers in giant data centers. It is leading to significant advances in areas as diverse as machine vision and perception, speech recognition and language translation.”

IBM hopes its Watson will become doctor’s sidekick

by Elizabeth Stawicki, Minnesota Public Radio

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ST. PAUL, Minn. — Remember Watson, the IBM supercomputer which made headlines last year by trouncing the top two contestants on the TV game show, Jeopardy?

Watson’s million-dollar prize went to charity and now Big Blue is seeking gainful employment for Watson other than as a professional game show contestant.

Today, IBM’s chief medical scientist visited a Minneapolis hospital to talk about how Watson’s artificial intelligence could help doctors wade through loads of research data and apply that knowledge to treating patients.

Ivan Herman recently offered some insight into how Watson actually works. Herman reports, “I was at Chris Welty’s keynote yesterday at the WWW2012 Conference. His talk was on Jeopardy/Watson and, although this is not the first time I heard/saw something on Watson, some things really became clear only at his keynote. Namely: what is really the central paradigm that made the question answering mechanism so successful in the case of Watson? Well… query answering in Watson is not some sort of a deterministic algorithm that turns a natural language question into a query into a huge set of data. This approach does not work.”

He continues, “Instead, a question is analyzed and, based on search in various set of data, a large set of possible answers is extracted. These ‘candidate’ answers are analyzed separately along a whole series of different dimensions (geographical or temporal dimensions, or, which I found the most interesting, putting back candidate answers into the original question and search that again against various sources of information to rank them again). The result is a vector of numerical values representing the results of the analysis along those different dimensions. That ‘vector’ is summed up into one final value using a weight values for each dimension. The weights themselves are obtained through a prior training process (in this case using a number of stored Jeopardy question/answers). Finally, the answer with the highest value (I presume over a certain threshold value) is returned.”

Read more here.