One Step Closer to Star Trek Reality

My wife is a computer user, but not a scientist and certainly not a Star Trek fan. She and Noam Chomsky do share a common opinion about IBM’s Watson winning against two expert Jeopardy players on February 16th, 2011.

She was not impressed. “What’s the big deal? A computer retrieving facts faster than a human?  That’s not impressive.”

“It’s a bigger steamroller,” says Noam Chomsky.

But I can’t help but be impressed. I think this historical event marks the next step in mankind’s march toward the realization of Star Trek tech. We have achieved the Star Trek communicator, and now we are one step closer to having the Star Trek computer.

Even if you can’t get excited about a computer playing Jeopardy, you have to be impressed with the machine: 90 IBM Power 750 servers using 15 terabytes of RAM, 2,880 processor cores, 500 GB per second on-chip bandwidth, a 10 GB Ethernet network, and 20 TBs of clustered disk storage. Watson evaluated the equivalent of 200 million pages of content – or about 1 million books – written in natural human language to find correct responses to the complex Jeopardy clues. While this is impressive, the real story is about software. To fully understand, we must go back a few years.

The man machine faceoff began in 1959, when Dr. Arthur Samuel, needing a platform for his machine learning research chose the game of checkers. Programs for playing games often fill the role in artificial intelligence research that the fruit fly Drosophila plays in genetics. Drosophilae are convenient for genetics because they breed fast and are cheap to keep, and games are convenient for artificial intelligence because it is easy to compare computer performance with that of people. (Arthur Samuel: Pioneer in Machine Learning)

Dr. Samuel incorporated into this program data from the many volumes of annotated games with the good moves distinguished from the bad ones and in 1961, challenged the Connecticut state checker champion, the number four ranked player in the nation. Dr. Samuel’s program won. Note that this program was run on IBM hardware.

Interestingly, the checker-playing program was one of the earliest examples of non-numerical computation. Dr. Samuel went to work for IBM and greatly influenced the instruction set of early IBM computers. The logical instructions of these computers were put in at his instigation and were quickly adopted by all computer designers, because they are useful for most non-numerical computation (Arthur Samuel: Pioneer in Machine Learning).

In 1997 an IBM supercomputer named Deep Blue defeated Chess Master Gary Kasparov. One of the criticisms of Deep Blue hardware and the software was that it was purpose built. It only played chess. To overcome this objection, IBM assembled commercially available computer hardware to build Watson. It also created software that could be repurposed.

Watson’s software uses IBM’s DeepQA technology that has been under development for many years, IBM says the code software represents a leap forward in the maturity of intelligent systems and language processing in general. It builds on the machine learning research done by Dr. Samuel in those early years to evince an ability to learn from correct and incorrect answers. Katherine Frase, vice president of IBM Research, said, “It’s not about the game.” Frase noted that the Jeopardy game was just a way for IBM to showcase some of the advances it has made in computer science (IBM’s Watson: ‘Jeopardy!’ Win Just the Beginning).

A complaint about Watson that we have discussed around the office was that Watson didn’t have to listen and understand the read clues. The clues were submitted as ASCII text to the computer. The addition of speech recognition would make the system even more anthropomorphic than it already seemed. Well, stay tuned. IBM plans to use this technology to enhance human decision-making in real world applications like health care, law, and call centers. IBM’s next research and technology initiative will combine IBM’s Deep Question Answering (QA), Natural Language Processing, and Machine Learning capabilities with Nuance’s speech recognition and Clinical Language Understanding (CLU) solutions for the diagnosis and treatment of patients that provide hospitals, physicians and payers access to critical and timely information. The two companies expect the first commercial offerings from the collaboration to be available in 18 to 24 months (IBM to Collaborate with Nuance to Apply IBM’s “Watson” Technology to Healthcare).  If you have an iPhone, you probably already have seen the Dragon Dictation app from Nuance.

Additionally, Columbia University Medical Center and the University of Maryland School of Medicine are contributing their medical expertise and research to the project, IBM said. For example, physicians at Columbia University are helping identify critical issues in the practice of medicine where the Watson technology may be able to contribute, and physicians at the University of Maryland are working to identify the best way that a technology like Watson could interact with medical practitioners to provide the maximum assistance (IBM’s Watson: ‘Jeopardy!’ Win Just the Beginning).

Star Trek tech continues to become reality.  “Engage”.

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