IBM’s Watson, a supercomputer designed for artificial intelligence, isn’t just good at answering Jeopardy questions — it’s also smart at diagnostic medicine and creating new recipes.

A new report from the New York Times today shows that IBM is looking to bring Watson’s powerful abilities to more industries in order to give the company an edge in the “big data” field. Watson has already had some success as a diagnostic assistant at a few medical centers around the country, including the Cleveland Clinic. Now IBM is looking to use its powerhouse elsewhere.

New Watson projects will include helping people come up with recipes, assisting in the development of new pharmaceutical drugs, and predicting when industrial machines will need maintenance.

Watson could be helpful to so many industries because it is able to sift through crazy amounts of data and make intelligent decisions about what to do with that information. Watson can look through Web pages, social networks, medical images, patent filings, and more to find what it needs.

IBM’s footprint in big data will only grow larger if it succeeds with placing Watson in commercial spaces. The company claims it is already doing data and analytics work for more than 10,000 customers. It employs 400 mathematicians and 9,000 analytics experts to do its bidding.

If IBM continues its investments it big data, it predicts that revenue generated in the area will hit $16 billion by 2015. Watson specifically isn’t making the company big money yet, but IBM believes they will pay off down the road.

Check out the video below to see Watson diagnose a patient and suggest treatment options.

July 9-10, 2013
San Francisco, CA

Early Bird Tickets on Sale

IBM’s Watson supercomputer has already proven that it can trounce puny humans in Jeopardy. Now the company is positioning Watson as a smarter successor to Siri, Apple’s popular (but often ditzy) iPhone virtual assistant.

But first, IBM has to make Watson less of a power hog for mobile devices and give it additional “senses” (such as voice and image recognition), the company told Bloomberg’s Sarah Frier.

When Watson was first announced in January 2011, IBM termed it as “an analytical computing system that specializes in natural human language and provides specific answers to complex questions at rapid speeds.” Jeopardy was a fantastic way to show off Watson’s rapid-fire manner of thinking, as well as its capability to understand the way humans normally speak.

Even though much of Watson’s brain sits in IBM Research’s Yorktown Heights, New York headquarters, the company says that Watson’s current software would still be too overwhelming for mobile devices. IBM is working on an upgraded “Watson 2.0″ that will be more energy efficient for tablets and smartphones. The addition of “senses” would also make Watson more aware of its environment, which would be an important part of bringing the service to mobile.

Don’t expect to see Watson releasing a standalone Watson app anytime soon though. The company says it’s focusing on corporate customers for now.

Focusing on mobile devices seems like a logical direction for Watson, especially as mobile devices get faster and 4G LTE networks make it easier to transmit huge amounts of data. It’s also one of the many ways IBM expects to increase its business analytics revenue to $16 billion by 2015, the company told Bloomberg.

Much like how Wolfram Alpha adds all sorts of interesting reference and computational capabilities to Siri, Watson could tap into a wealth of information online, along with sensor data from your smartphone, to help you make complex decisions.

In the example Bloomberg gives, a farmer could ask Watson for the best spot in his field to plant corn. Watson could then tap into historical records, location data, and recent scientific research to give an informed response. (And yes, this all sounds a bit like a proto-Skynet.)

Since the beginning, IBM also mentioned that Watson could be a useful tool for the healthcare industry, especially when it comes to making diagnoses. (The company also formed a research partnership with Nuance last year to help prepare Watson for health care purposes.) Going mobile would further Watson’s usefulness for doctors and patients alike.

IBM is testing a program that would allow patients to detail symptoms to Watson, and the A.I. would then offer up potential diagnoses. The company says Watson will eventually be well versed enough in oncology to help with diagnosis and prescriptions. For now IBM is developing this capability for doctors, but eventually it sounds like patients may be able to tap into Watson’s medical smarts on their own.

That means a patient could walk into a hospital and tell the computer about what is bothering them — whether it’s leg pain or a cough or a sore throat — and Watson can quickly process that information and spit out a diagnosis that has the highest probability of being correct. For most cases, that would save hospitals a lot of time because the computer could plow through the large number of cases hospitals regularly contend with that require simple treatments.

Watson was able to diagnose an eye problem with a fictional victim that had a 73 percent chance of being correct, according to a report by the Associated Press. Watson was able to improve the chance that its diagnosis was correct as it was given more symptoms and more clues about the patient’s condition and eventually arrived at a diagnosis of Lyme disease. Watson can also pull information from blogs and other media sources to create a more accurate diagnosis.

Watson is best known for crushing the puny likes of Jeopardy! champions Ken Jennings and Brad Rutter in a series of games. It’s an advanced supercomputer that does a very good job of understanding human language and searching for correct answers. But the supercomputer was no match for former physicist and New Jersey congressman Rush Holt, who beat the computer by edging it out in a few areas that required clever use of language and rhymes like “Hoover’s Maneuvers.”

At its core, Watson is a computer that uses a series of complex search algorithms and some heavy-duty processing firepower to determine an answer that has the highest probability of being correct. But while it has a good bit of “buzzer mojo” that contributed to its wins over Jeopardy! champions Jennings and Rutter, it still hasn’t cracked the code for perfect natural language processing — something that comes easily to humans but can be incredibly difficult for computers.

IBM said it would be at least two years before the supercomputer made it to hospitals as an official product and said it didn’t have any kind of price tags for hospitals just yet.

I had a chance to interview Ferrucci at a press event last night, where he told me that his team is still trying to improve Watson’s underlying technology, but it’s also looking at ways to turn that technology into a commercial product. We’ve already written about IBM’s plans to bring Watson into health care, and Ferrucci told me the company is also examining how Watson could also be used in the finance industry.

Watson wasn’t designed with any commercial purpose in mind, Ferrucci said — he and his team just wanted to develop the natural language technology that allows Watson to understand and answer questions, and then Jeopardy seemed like the natural place to showcase those capabilities. (For more details about how Watson works, check out this interview with one of Ferrucci’s team members.)

But as he continued working, Ferrucci realized that Watson’s process of coming up with different possible answers and verifying them against a large corpus of data mirrors the medical diagnosis process. So doctors and patients could have conversations with Watson where they discuss the symptoms and double-check diagnoses.

More broadly, the Watson team wants to improve the computer’s conversational and analytical capabilities. “I would love to be able to converse at an intellectual level,” Ferrucci said — for example, he’d like to be able to talk to Watson about Joseph Conrad’s novel Heart of Darkness. Watson will never be able to form an independent judgment about the book, Ferrucci said, but in addition to answering basic factual questions, it could eventually develop an understanding about whether or not you would enjoy it.

Of course, Watson’s victory raises some provocative questions about human and machine intelligence — after all, that’s why its participation in Jeopardy was so fascinating. I’ve been thinking about this since reading Adam Gopnik’s New Yorker article on the subject. Gopnik argued that in order to avoid admitting that computers have become smarter than humans, we have started to define intelligence more and more narrowly.

Not surprisingly, Ferrucci took a more optimistic view. He acknowledged that there’s a “John Henry” perspective on these advancements, referring to the mythical American railroad worker who died trying to compete with a steam-powered engine, but Ferrucci said that’s a very “limiting view.” Rather than worrying about whether machines can perform certain tasks better than we can, he said, “I can’t wait until computers can do more and more things.” By making information more accessible, computers enable more human creativity, which is something they’ll never be able to replicate. “The computer doesn’t have human experience,” Ferrucci said.

Surprisingly, the win had nothing to do with Holt’s physics background — just a little bit of scrappy play in categories where the human brain has a slight edge over a supercomputer. Holt, an assistant director of the plasma physics laboratory at Princeton University until he was elected in 1998, managed to outmaneuver Watson in some key categories that showcased the computer’s weaknesses. That included the likes of “presidential rhymes,” which required certain responses like “Hoover’s Maneuvers.”

Watson has shown just how far computing has come today after handily crushing the likes of Jennings and Rutter. But, at its core, it is still a computer that uses a series of complex search algorithms and some heavy-duty processing firepower to determine an answer that has the highest probability of being correct. That’s because using a series of algorithms to understand natural language — something that comes to humans with relative ease — can be incredibly difficult for computers.

Jennings said it was Watson’s “buzzer mojo” — how quickly the computer was able to hit the buzzer to indicate that it would answer the question — that led the computer to victory over he and Rutter. He made the comments on an ask-me-anything thread — which lets users ask the original poster questions through comments and get responses within the thread — on news-aggregation site Reddit. (The thread is also worth checking out because some of Jennings’ comments are pure gold.)

“Every night, all three contestants passed a very hard test to be there. Ergo, nearly all the contestants know nearly all the answers nearly all the time,” Jennings said. “So it just comes down to buzzer mojo. Which is why Watson won so handily … pretty hard to have better response time than a circuit board.”

Holt finished the first round of Jeopardy! last week with 8,600 points to Watson’s 6,200. It wasn’t the first time humanity handed Watson a loss — the computer only won 71 percent of its warm-up matches. But it was the first time since IBM’s highly-publicized campaign that featured the supercomputer’s nationally-televised appearance when it went toe-to-toe and soundly defeated Jeopardy! champions Jennings and Rutter. It was also only a single round — not a full Jeopardy! match.

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Now the team responsible for the humanity’s downfall in Jeopardy is ready to answer questions as to how — and why — they built and programmed Watson on news aggregator Reddit. The team posted a question-and-answer thread, called an “ask-me-anything,” that lets Reddit users comment with questions.

IBM is the latest of a series of companies that has appealed to the Reddit community to generate some positive buzz for their technology. Condé Nast-owned Reddit is populated by tech-savvy individuals that are typically more critical of entrenched services that are plagued with bugs. Maybe the idea is that if you can handle Reddit, you can handle just about anything.

Microsoft regularly throws its teams into the pool with Reddit sharks — the company sent in its Hotmail team (which wasn’t quite that successful) and its Internet Explorer 9 team (which was quite successful.) It seems like it’s a pretty hit-or-miss strategy, but it at least makes the team appear more human to the hyper-critical tech community that populates news aggregator sites like Reddit and Y Combinator’s Hacker News.

Watson competed against Jeopardy champions Ken Jennings and Brad Rutter over three days of intense trivia, and won by making a $17,000-plus Final Jeopardy bet on the answer “William Wilkinson’s ‘An account of the principalities of Wallachia and Modavia’ inspired this author’s most famous novel.” Watson answered, “Who is Bram Stoker?” Watson ended the three-day run with $77,147, while Jennings had $24,000 and Rutter had $21,600. Jennings even quipped on his response that he, for one, “welcomes our new computer overlords.”

So far the team has only jumped in to ask that each curious Redditor stick to a single question per comment. But the answers are probably on the way, given how much interest there was in bringing the IBM team to the site. Earlier today, there was a request to bring the engineers onto the site for an “ask-me-anything” thread that hit the front page — and the official question-and-answer thread hit the front page just a few minutes ago.

In the mean time, IBM’s researcher showed VentureBeat’s Dean Takahashi and others how Watson works at an event in San Francisco last night.

But watching the supercomputer answer questions during the three nights of the Jeopardy shows was puzzling to a lot of viewers, who could see how awesome Watson could be at some questions and how terrible it was at others. John Prager, one of the 25 researchers who worked on Watson’s programming, was at IBM’s event last night during the airing of the final Jeopardy match and he explained both how Watson worked. The explanations give us insight into the nature of human intelligence compared to machine intelligence, one of the oldest technological problems known to computer scientists.

Prager said it’s instructive to compare DeepBlue, IBM’s supercomputer that beat chess champion Garry Kasparov in 1997, to Watson, which played Jeopardy. Chess is the “iconic representation of human intelligence,” Prager said, while Jeopardy is more like the “iconic representation of what it means to be human.” There is very little crossover between the algorithms used to play chess and those used for Jeopardy. That’s because Jeopardy represents a big “natural language understanding” problem.

For humans, understanding language is easy. But that’s the tough part for Watson. Questions like “where was Einstein born?” are easy for Watson if there is a precise answer in its database. If there isn’t an exact match, the computer would have to infer from various snippets of data that suggest the answer. For instance, if the database says that “Jack Welch ran GE like an artist,” the computer might think that Welch was an artist, rather than the former chief executive of General Electric.

Jeopardy has a broad range of topics, opening up the whole of human knowledge for the computer to try to understand. That also makes the artificial intelligence problem tough. Watson needs precision and it has to supply the top answer, in contrast to Google’s search engine which can supply a range of answers. In Jeopardy, if you get a wrong answer, you’re penalized points.

Watson also needs speed, since it’s playing against fast human players. The 2,880 IBM Power750 cores (or computing brains) helps, as does the 15 terabytes of memory it has. The IBM researchers started four years ago and they found that their computers was extremely poor at getting Jeopardy questions right. The programming is in Java and C++. IBM also tapped a fan site that had typed in all of the previous Jeopardy questions and answers over the history of the game show.

“We had a long way to go,” Prager said.

There are a lot of components to what it came up with, including a “question analysis” system that starts working just as a question comes in. That part is like a search engine.  It comes up with a couple of hundred possible answers that it wants to process further. Then it runs 100 to 200 algorithms to look for different features among the answers. A machine language algorithm then sorts which are the most important solutions. Then it calculates a confidence level for the rankings and only gives a ranking if it is above a certain threshold.

In the category of U.S. Cities on Tuesday night, Watson gave the lousy answer “Toronto” in response to a question. That was because it didn’t put much weight on the category in terms of putting boundaries around its possible answers. There are actual cities named Toronto in the U.S., and the Toronto Blue Jays baseball team plays in the American League. These facts may have thrown Watson off, to comic effect. Watson put a lot of question marks after its answer, which means its confidence level was low and was only answering because it was forced to answer.

It also said “1920s” in response to a question about when Oreo cookies were introduced. That was just after human opponent Ken Jennnings was told he was wrong when he said “20s” on the same question. That was because IBM’s researchers chose to simplify Watson’s programming by making the computer “deaf” to the responses of other players. In many sparring games, the likelihood of that circumstance was very low, Prager said.

“It was sheer bad luck that happened,” Prager said.

Host Alex Trebek noted last night that Watson made random bets for dollar amounts when it had Final Jeopardy or Daily Double gambles to make. Prager said Watson determined it didn’t need to bet everything on Tuesday night in order to win. And by statistical analysis of the category, it predicted it wouldn’t do well on short categories or certain topics. So then it knew it had to bet small amounts sometimes. The researcher who programmed that part thought that betting “zero” would be boring and that a random amount would by funny.

Watson wasn’t connected to the Internet, but IBM took a lot of library-like sources and fed them into Watson’s database. That was all done ahead of time. When a program runs live, the code and data is fed into Watson’s memory. Then processors kick in and fetch the best answers. A lot of the data is duplicated and most of the data was updated to within a few weeks of the show’s filming.

IBM trained Watson in 55 sparring games against former Jeopardy winners. Watson won 71 percent of the time. That was the more scientific result compared to the championship matches. Prager said the experience of watching Watson was like a parent watching a child perform in a school play, where you hope the child doesn’t flub his or her lines.

“The trained eye can predict whether Watson will get the answer right when the question comes up,” Prager said. “Watson struggles what they’re really asking for, and if the language is really clear. Jeopardy is an entertainment show and the question is often worded to inform or entertain.”

Burn Lewis, another IBM researcher, said that Watson actually had to press a buzzer to answer questions in the show. The questions are visible to the human players so it “hits their retinas about the same time it hits Watson’s chips,” Prager said. It could do so within six milliseconds, faster than most humans can react. Lewis said that the humans who beat Watson on the buzzer were really gambling, or predicting they could answer a question upon hearing the last word.

Watson generally jumped around a lot on categories because it was looking for Daily Doubles, which offer the chance to get the most points from a question, and there is usually a pattern to where contestants can find those Daily Doubles, Prager said.

IBM thinks that Watson’s innovations can be used in things such as automated customer support.

IBM has put up a blog post that delves into Watson’s Final Jeopardy trouble. There’s also a lot more on the subject of Watson in Stephen Baker’s new book, Final Jeopardy: Man vs Machine and the Quest to Know Everything.

You can check out a preview match between Watson, Jennings and Rutter (where the humans were also destroyed). Also, check out the video of Prager’s talk below. The video is dark because it was shot in a dark comedy club without much lighting, so I apologize for that. But you can hear Prager’s explanations fine.

Best known for its Dragon Natural Speaking speech recognition software, Nuance also focuses heavily on the health care industry. Its Clinical Language Understand technology provides doctors with speech recognition technology that can understand complex medical jargon. That technology will be combined with Watson’s deep question answering, natural language processing and machine learning capabilities, as part of the research agreement.

It’s not difficult to imagine what the combination of Nuance’s technology and Watson’s analytical computing system can provide. It could help doctors diagnose patients instantly, just as it can sift through its massive database to answer obscure Jeopardy questions. And it will continually get better, since Watson can learn from its mistakes. The combined Watson and Nuance project won’t replace actual doctors, instead it will augment their ability to treat patients and help to erase human error that can cost lives.

Products resulting from the IBM and Nuance partnership are expected to hit the market within two years. Researchers from the Columbia University Medical Center and the University of Maryland School of Medicine will also be participating.

IBM mentioned that health care diagnosis was one of the potential uses of Watson’s capabilities when we first covered it last month. Now that it looks like Watson is well on its way to helping doctors, we may also see the technology licensed for other uses, like tech support or enterprise knowledge management. IBM wouldn’t say at the time if it was talking to government agencies, but it’s not difficult to see how Watson could be used to help analysts at agencies like the CIA sift through vast amounts of data.

The computer defeated Jeopardy champions Ken Jennings and Brad Rutter, after a three-night tournament that drew lots of chatter about the progress of artificial intelligence. It’s a testament to the talented human engineers at IBM who figured out how to make a machine that could beat a human at the popular TV game show.

The final show aired tonight, first on the East Coast where IBM threw a party in New York at a place called spin NYC. On the West Coast, I watched the show at a comedy club in San Francisco where a group of IBMers and press are gathered. They cheered when Watson came back with the correct answer on the final question.

John Prager, an IBM researcher, explained how Watson decides what to bet and how to answer. It basically tries to come up with a precise answer, by matching the text in a question to the text in its memory. If there is no match, it takes a guess based on a confidence level, after doing a series of calculations on the probabilities of a right answer. It does so in real time.

At the opening of the show, Alex Trebek talked about how fast Watson was and its tendency to make random bets on the Daily Double and Final Jeopardy wagers. Watson took off on an early lead, but Jennings and Rutter made a comeback. During the competition, Watson correctly answered questions about Sin City (“What is Las Vegas?”) and Bison City (“What is Buffalo?”) and even a question about a Simpsons episode.

Watson won by making a $17,000-plus Final Jeopardy bet on the answer “William Wilkinson’s ‘An account of the principalities of Wallachia and Modavia’ inspired this author’s most famous novel.” Watson answered, “Who is Bram Stoker?” Watson ended the three-day run with $77,147, while Jennings had $24,000 and Rutter had $21,600.

Watson, named after IBM founder Thomas J. Watson, was developed by 25 researchers over four years. The software runs on a supercomputer with 2,880 IBM Power750 cores, or computing brains, and 15 terabytes of memory. One of Watson’s advantages is that it can hit the buzzer to answer a question faster than any human possibly can — six to 10 milliseconds. Watson won $1 million and all of its winnings will be donated to charity.

IBM describes Watson as “an analytical computing system that specializes in natural human language and provides specific answers to complex questions at rapid speeds.” That Watson can tackle a game as complex as Jeopardy shows just how much IBM has progressed since it developed Deep Blue, the supercomputer that defeated chess grandmaster Garry Kasparov in 1997, as VentureBeat’s Devindra Hardawar remarked after last night’s show. Deep Blue relied heavily on mathematical calculations, while Watson has to interpret human language, a far more difficult task.

According to Stephen Baker, author of Final Jeopardy, a book about the Watson Jeopardy challenge, the supercomputer has difficulty with the Final Jeopardy portion of the game because it can’t refuse to answer if it has a bad guess. With a normal question, Watson can just choose not to answer and look smarter in the process.

Watson cannot respond to video or audio clues and the producers of the show agreed to omit them, just as they do for the visually or hearing impaired. Jeopardy is considered an ideal show for testing artificial intelligence because it covers such a broad range of topics and requires a mastery of natural language.

Baker spoke to All Things Digital about Watson’s mistake on Tuesday night, where he elaborated on how it can appear both smart and stupid at the same time. IBM has also put up a blog post that delves into Watson’s Final Jeopardy trouble.

Video of the match isn’t available online yet, but you can check out a preview match between Watson, Jennings and Rutter (where the humans were also destroyed).

At the end of the San Francisco event, I asked Prager, “How do you get from Watson to Skynet?” That’s a reference to the computer network in the Terminator movies that comes alive and tries to extinguish the human race. Prager said, “I don’t see a path to get to Skynet and I don’t know anyone who is working on that. I don’t see a path to HAL either.” HAL is the computer that goes berserk in 2001: A Space Odyssey. And, of course, HAL’s initials are one letter off from the next letters of the alphabet: IBM.

Watson ended the night with $35,754, while former human Jeopardy champs Brad Rutter and Ken Jennings scored $10,000 and $4,800 respectively.

That’s a huge divide, and it goes to show just how much IBM has progressed since its supercomputer Deep Blue defeated chess grandmaster Gary Kasparov in 1997. It’s difficult to imagine what the next generation of supercomputers will defeat humans in given another decade.

IBM describes Watson as “an analytical computing system that specializes in natural human language and provides specific answers to complex questions at rapid speeds.” That Watson can tackle a game as complex as Jeopardy shows just how much IBM has progressed since Deep Blue, which relied heavily on mathematical calculations. Watson instead has to interpret human language, a far more difficult task.

Watson ruled the game for most of the night, winning most question buzzes and giving its competitors little time to score. In an early Daily Double question, Watson wagered an oddly precise $6,435, which drew laughs from the crowd. Jeopardy host Alex Trebek previously noted that Watson had a habit of odd Daily Double wagers, which has befuddled its IBM researchers.

Watson also showed the limits of its cyberbrain in Final Jeopardy. In the category of U.S. Cities, the competitors were given a clue about a city whose largest airport is named for a World War II hero, and its second largest is named for a World War II battle. Watson ended up guessing Toronto, but wisely it bet less than $947, so it didn’t take away from its lead too much.

According to Stephen Baker, author of Final Jeopardy, a book about the Watson Jeopardy challenge, the supercomputer has difficulty with the Final Jeopardy portion of the game because it can’t refuse to answer if it has a bad guess. With a normal question, Watson can just choose not to answer and look smarter in the process. Baker spoke to All Things Digital about Watson’s mistake, where he elaborated on how it can appear both smart and stupid at the same time. IBM has also put up a blog post that delves into Watson’s Final Jeopardy trouble.

Video of the match isn’t available online yet, but you can check out a preview match between Watson, Jennings and Rutter (where the humans were also destroyed).

Human competitor Brad Ruttner tied with Watson, a supercomputer created by IBM. Another human rival, Ken Jennings, isn’t far behind in the first of a two-game tournament. The match showed that IBM’s artificial intelligence technology is a force to be reckoned with, and in the future, it’s only going to get better.

At first, Watson was running away with the show. But at the close of the game, Watson and Rutter were tied with $5,000 in winnings, and Jennings had $2,000. Some 25 IBM Research scientists across the world toiled for four years on Watson, which is IBM’s spiritual successor to Deep Blue, the supercomputer that defeated chess grandmaster Gary Kasparov in 1997. IBM describes Watson as “an analytical computing system that specializes in natural human language and provides specific answers to complex questions at rapid speeds.”

Rutter made the first category choice and beat Watson to the buzzer, allowing Rutter to answer the question. Then Watson took the next questions by storm. It answered 11 of the next 15 questions correctly in the first half of the show. At the start of the second half, Watson had $5,200, Rutter had $1,000, and Jennings only had $200. Then, the humans made their comeback, beating Watson to the buzzer a few times. And Watson got some answers wrong in the second half. Watson can’t adjust its answers to what the other players say, so it simply answers with whatever comes up as its top answer.

Jennings said “20s” when prompted to say the decade when Oreo cookies were introduced. Watson then said “1920s” and got the answer wrong again. IBM focused on Jeopardy for its artificial intelligence research because requires a huge swatch of knowledge in order to play it well. Watson did great with Beatles questions, but pretty poorly in the “decades” historical category.

Our own Devindra Hardawar got to watch Watson play Jennings and Rutter in a practice match in January.

Earlier today we gave you the run down on IBM’s Watson AI supercomputer, and now we have video of our would-be conqueror’s test match with two top Jeopardy players.

IBM only demonstrated a few minutes of the test match, but what was most impressive was just how natural Watson seemed at the game. Sure it sounds robotic, but Watson is choosing questions and formulating answers on par with top Jeopardy contestants Ken Jennings and Brad Rutter. In three minutes of questioning, Watson ended up defeating both humans with $4,400 won, compared to Jennings’ $3,400 and Rutter’s $1,200.

What does this mean for the actual Jeopardy match between Watson and the two champs? I have a feeling both humans will be surprised at just how handily they’re defeated. The actual match is being recording over the next few days, but we won’t see it on television, or learn the results, until the Jeopardy episodes air on February 14 to February 16.

And if it does win, I’ll leave you with this one great quote from an IBM researcher who worked on the supercomputer, “Watson doesn’t have emotions, but Watson knows humans have emotions.”

Today, for the first time ever, IBM demonstrated its Watson artificial intelligence supercomputer at a press conference at IBM Research’s Worldwide Headquarters in Yorktown Heights, New York.

IBM brought in top Jeopardy contestants Ken Jennings and Brad Rutter for a short demonstration match with Watson, in which it trounced both of the humans (we’ll have video of the match soon). Watson will make its television debut on Jeopardy in two matches across three nights, from February 14 to 16, competing against Jennings and Rutter for a $1 million prize. It’s the first time a machine has competed on Jeopardy, and I get the feeling it won’t be the last.

25 IBM Research scientists across the world toiled for four years on Watson, which is IBM’s spiritual successor to Deep Blue, the supercomputer that defeated chess grandmaster Gary Kasparov in 1997. IBM describes Watson as “an analytical computing system that specializes in natural human language and provides specific answers to complex questions at rapid speeds.”

Unlike Deep Blue, Watson needs to do more than just decide the next chess move, something that relies heavily on mathematical calculations. Watson instead has to interpret human language. When it comes to Jeopardy, the system has to understand the question being asked and then search its database of 200 million pages of content to determine the answer. It needs to decide when to take risks, which questions to bet on and how much to bet. IBM says the toughest part for the computer is finding and justifying the correct answer, or in other words computing a confidence that it’s right — something that comes naturally to the top Jeopardy players.

IBM says that the real world applications of Watson are far-reaching: Such a powerful and fast analytical system could save lives when it comes to health diagnosis, IBM’s primary focus at the moment, and it could also help with things like tech support and enterprise knowledge management.

When asked if the US government has shown any interest in the system, IBM would only say it’s been speaking with many interested parties. But it’s not that difficult to see how Watson could be used to help analysts at agencies like the CIA sift through vast amounts of data.

Watson is powered by 10 racks of IBM Power 750 Linux servers with 2,880 processor cores running at 80 teraflops and 15 terabytes of RAM. Deep Blue, on the other hand, ran at around 1 teraflop.

Watson is still dealing with some issues. Jeopardy host Alex Trebek pointed out that Watson confused actor Jamie Foxx with Beethoven in a question regarding his film The Soloist. IBM also remains coy about how Watson bets funds for Jeopardy’s Daily Double question — Trebek remarked that Watson made a peculiar Daily Double wager earlier in the day.

We’re waiting for IBM to put video of the test match online, which will give you the best sense of Watson’s capabilities. Watch for a post on that later today.