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.

Cognitive systems: A new era of computing

Over the past few decades, Moore’s Law, processor speed and hardware scalability have been the driving factors enabling IT innovation and improved systems performance. But the von Nuemann architecture—which established the basic structure for the way components of a computing system interact—has remained largely unchanged since the 1940s. Furthermore, to derive value, people still have to engage with computing systems in the manner that the machines work, rather than computers adapting to interact with people the way they work.

With the continuous rise of big data, that’s no longer good enough.

We now are entering the Cognitive Systems Era, in which a new generation of computing systems is emerging with embedded data analytics, automated management and data-centric architectures in which the storage, memory, switching and processing are moving ever closer to the data.

Whereas in today’s programmable era, computers essentially process a series of “if then what” equations, cognitive systems learn, adapt, and ultimately hypothesize and suggest answers. Delivering these capabilities will require a fundamental shift in the way computing progress has been achieved for decades.

The four characteristics of cognitive systems

(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.”

Companies like NeuroSky Inc., and Emotiv Systems are developing consumer-grade headsets that read the brain’s electrical signals to control onscreen action

A new head-mounted controller allows users to control the video games they play with their brainwaves — and only at a cost of $130. Photo: neurosky.comSEE ALL 52 PHOTOS

The gaming controller of the future won’t have joysticks or buttons; it’ll wrap around your head. A number of companies like San Jose-based NeuroSky are developing affordable, consumer-ready controllers that takes cues from the electrical signals in a wearer’s brain to dictate onscreen action. Here, a concise guide to the new smart technology:

How does it work?
The head-mounted controller reads the brain’s electrical activity much in the same way that an electroencephalograph, or EEG, works. It then beams that information via BlueTooth to a connected smartphone. NeuroSky, Inc., which has made news with aStar Wars-based children’s toy called Force Trainer that let children suspend a ping pong ball in the air using a fan and their brainwaves, sells a mind-control headset called MindWave Mobile.