IBM via AFP - Getty Images

IBM's Watson computer is made up of a cluster of 90 computer servers with a total of 2,880 processor cores.

It was nice of Watson to donate its $1 million in "Jeopardy!" winnings to charity this week, but don't think for a second that the human-thumping, question-answering machine is purely philanthropic. There are high hopes Watson will make plenty of companies and people piles of money.

To get things started, on Thursday IBM and Nuance Communications announced a collaboration "to explore, develop and commercialize the Watson computing system's advanced analytics capabilities in the healthcare industry."

The collaboration, which also involves Columbia University and the University of Maryland, could lead, for example, to a know-it-all medical assistant. Instead of explaining symptoms to a flesh-and-bone doctor, you'll tell them to Doc Watson. After mulling the information for a split second, the machine will identify what you likely have and prescribe a treatment.

The first commercial offerings could be available in 18 months. Hospitals and clinics may gobble up the technology. What's more, the existence of Doc Watson would likely change what students in medical school study, Herbert Chase, who is working on the project at Columbia University, told the New York Times.

"I have been in medical education for 40 years and we're still a very memory-based curriculum," he said. "The power of Watson-like tools will cause us to reconsider what it is we want students to do."

Consumer interaction
IBM executives also told the newspaper they are in discussions with a major consumer electronics retailer to develop a version of Watson that can interact with consumers to help them with buying decisions and technical support.

Specifics on the project are thin, but experts speaking about Watson in a series of videos on IBM's website note that the technology is almost certain to find a home in tech-support call centers. Instead of yelling at a human for not being able to understand why your gadget doesn't work, Watson will coolly and accurately explain what's wrong so you can fix it and be on your way.

The videos also make clear that the financial services industry is keen to put Watson to use. Just as the machine was able to search through a massive database to come up with the right answer to trivia questions on "Jeopardy!," researchers imagine Watson being able to sift through piles of financial data to spot the next big thing, potentially more efficiently than highly paid Wall Street analysts.

"If you simultaneously see all the research, and financial news, market news, economic information, you could start to ask questions such as which companies are most likely to be acquisition targets over the next three months," said Jay Dweck, who the video identifies as a financial services executive.

Dweck left a position this January as head of a quantitative software and modeling group in Morgan Stanley's sales and trading division, Bloomberg reported. While there, he built and managed software programs that handle trading. Watson, it appears, is envisioned as the next evolution in so-called quant funds, where sophisticated computer models are used to make investment decisions.

A lawyer and consultant?
Other potential applications for Watson's technology may be found in helping legal professionals comb through law cases and civic planners study and resolve traffic issues, according to Investor's Business Daily.

Watson might also have a future as a consultant to the Department of Homeland Security, Darren Hayes, a computer information systems program chairman at New York's Pace University, told the financial news service.

"The focus (on homeland security) has been on information gathering — license plates, credit card transactions, Internet activity, flight manifests, telephone records, bank transactions, and so on — for millions of people. Synthesizing those terabytes of information is tremendously challenging," he said.

Essentially, any task that currently employs intelligent humans to sift through piles of data to find an answer may soon be replaced by Watson. That could free up some professionals such as doctors from rote memorization, but it could also put thousands of people out of work, from call center staffers to legal assistants and financial analysts in a bid to boost the corporate bottom line.

More stories about Watson:

• Beyond 'Jeopardy': Watson wins
• Supercomputer crushes competition on 'Jeopardy'
• Computer beats 'Jeopardy' champs in test round
• IBM's Watson may help with future trips to the doctor

John Roach is a contributing writer for msnbc.com. Connect with the Cosmic Log community by hitting the "like" button on the Cosmic Log Facebook page or following msnbc.com's science editor, Alan Boyle, on Twitter (@b0yle).

IBM via AFP - Getty Images

IBM's Watson computer is made up of a cluster of 90 servers with a total of 2,880 processor cores.

IBM's Watson supercomputer looks like the clear favorite to win this week's man-vs.-machine match on the "Jeopardy" TV game show in the wake of today's action. Right now, the score totals are $35,734 for Watson, vs. $10,400 and $4,800 for the game's two human champions. But even if by some miracle Watson doesn't take the million-dollar top prize, computer scientists say its performance will be judged a triumph for artificial intelligence.

"Watson is clearly playing at a championship level," inventor/futurist Ray Kurzweil, who predicts that A.I. will match human intelligence by the year 2029, told me today in an e-mail. "Note that it's only going to keep getting better. We cannot say that for unaided human intelligence."

Kurzweil said Watson merits the high praise he bestowed upon the machine after seeing its performance in last month's public practice round. In his essay on KurzweilAI.net, he said computers had "not shown an ability to deal with the subtlety and complexity of language" ... until Watson came onto the scene.

"Watson is a stunning example of the growing ability of computers to successfully invade this supposedly unique attribute of human intelligence," Kurzweil wrote. He said that level of language understanding, combined with a well-programmed aptitude for pattern recognition, would make Watson's descendants "far superior to a human."

Alien intelligence
Boris Katz, a computer scientist at the Massachusetts Institute of Technology who pioneered the development of natural-language question-answering systems, agrees that Watson is a wonder. "IBM did a fantastic job," he told me. But he said Watson's foibles also show that a computer's brand of intelligence is still alien to us.

When Watson is good, it's very, very good. But when it is bad, it's horrid. For example, one of the clues dropped during a practice round was: "This trusted friend is the first non-dairy powdered creamer." The correct answer was "Coffee-mate," but Watson gave a nonsensical non-non-dairy reply: "What is milk?"

Another example: On Monday, "Jeopardy" rival Ken Jennings gave a wrong answer for the decade when Oreo cookies were introduced (the '20s), and Watson followed up with what was basically the same answer. ("What is 1920s?") It was left to the third contestant, Brad Rutter, to come up with the right answer (the 1910s). Expert observers assume that Watson flubbed the answer because it didn't catch the fact that the '20s and the 1920s were just two different ways to refer to the same decade.

"When you look at the blunders, you realize that they did not build a machine that thinks like us," Katz said. "The success of Watson does not bring us closer to the understanding of human intelligence. When we observe it making these mistakes, that should remind all of us that this problem is still with us, and it's waiting to be solved."

Overconfident computer?
Watson draws upon 15 trillion bytes of information in its memory banks, the equivalent of 200 million pages of text, and ranks the  potential answers for a given clue using 2,880 parallel processor cores in its 90 computer servers. If the highest-scoring answer exceeds its built-in "confidence threshold," it'll buzz in. If no answer scores high enough to reach the threshold, Watson will keep mum. At least theoretically.

"We're seeing already that there are times when Watson really doesn't have enough information to have a good answer, but has the 'confidence' to give an answer anyway," said Eric Nyberg, a computer scientist at Carnegie Mellon University who helped program the supercomputer.

Despite Watson's occasional missteps, Nyberg is proud of the computer's overall prowess, as well as the speed with which it's answering the "Jeopardy" questions. "I was pleasantly surprised that Watson was able to buzz in against Ken [Jennings], because in all of 'Jeopardy,' he's the guy with the fastest trigger finger," he told me.

Today, during an interview on MSNBC, Jennings acknowledged that Watson has "an edge on that buzzer that human reflexes have a hard time keeping up with." He also acknowledged that the pressure was on, big time, going into the final round. (Jennings actually knows who won, since the three shows were taped last month under tight security.)

 "The computer can't get stage fright, it can't get discouraged or frustrated. It's like 'Terminator,' it's just going to keep coming," Jennings said. "And so the human race is going to have to play probably aggressively here — big bets where necessary, play recklessly to win." 

On Wednesday, TV viewers will find out how this particular man-vs.-machine match ends. But the computer scientists emphasized that this is just the beginning for Watson and its successors. "The fact that it's this fast, and this accurate, and its abilities allow it to do this well at 'Jeopardy' means that question-answering technology is really ready for prime time," Nyberg said.

Watson was built to serve up quiz-show knowledge, but those question-answering capabilities would probably be most valuable in specialized fields such as medicine and law. Watson's kin could help us puny humans sift through millions of possibilities and come up with the five or six best medical diagnoses, or legal precedents, or chemical configurations, or ... well, you name it.

"We're not thinking about applications where there isn't a human in the loop," Nyberg said. "We're definitely talking about an intelligent information agent that's working with a human."

What do you think? Will Watson win this week's showdown? Will question-answering machines become our most reliable advisers? Or will this turn into a replay of "Terminator 3: Rise of the Machines"? Feel free to weigh in with your comments below.

Correction for 12:20 a.m. ET Feb. 16: Error! Error! I've fixed the humans' totals at the end of the first game, and have corrected The Associated Press' figures in the referenced story as well.

More human-vs.-machine matches:

• Chess computer beats world's best player
• Checkers computer becomes invincible
• Poker-playing robot beats human pros
• New Scientist: Computer beats human at Japanese chess

Join the Cosmic Log community by hitting the "like" button on the blog's Facebook page or following b0yle on Twitter.

US Military

The Pentagon is drowning a "data deluge" from drones such as the one pictured here and other intelligence gathering activities. It has put out a call for a mathematical language to make sense of it all.

The Pentagon's Defense Advanced Research Projects Agency has sharpened its focus on a future where machines do most of the dirty work — and a good deal of the thinking, too.

Last week, the military think tank kicked off a program called Mind's Eye, which is aimed at developing "a visual intelligence capability for unmanned systems." This week, it sent out an announcement that hints at the agency's plans for a mathematical language that would give data-collecting sensors the ability to speak to each other, think for themselves, and take action with scant human interference.

The Mind's Eye program essentially ups the ante for camera-equipped unmanned vehicles by giving them not just a processor for collecting visual information, but a "visual intelligence, enabling these platforms to detect operationally significant activity and report on that activity so warfighters can focus on important events in a timely manner." That would take boots off the ground and free data analysts from their chairs.

DARPA watchers have also pointed out an announcement calling for proposals to participate in the Mathematics of Sensing, Exploitation, and Execution program, or MSEE. The announcement says MSEE's mission is to find new ways to handle a "data deluge."

"The amount of data collected by Department of Defense sensor systems far outstrips the ability of both human analysts and current automated decision systems to extract actionable information," it reads. In other words, all the data coming in from drones and satellites taking pictures and making videos, plus tapped phone lines and who knows what else, is simply too much. Instead of being helpful in stopping the bad guys, it's a hindrance.

MSEE seeks a unified mathematical language that can teach sensors what data to collect as well as how to interpret and act on it. The agency's call for proposals says the goal of the program is "to capture the economy and efficiency that derives from an intrinsic, objective-driven unification of sensing and exploitation." To get there, "all proposed research must describe a unifying mathematical formalism that incorporates stochasticity fundamentally."

Wired.com's Spencer Ackerman notes that in about three and a half years, the agency wants prototypes to "furnish sensor output products" from imagery and video, communications intercepts and the tracking of a moving target.

"If your algorithm can train those very distinct sensors how to determine for themselves what relevant data is, you'll have gone a long way to draining oceans of data into a customizable kiddie pool for military analysts," he writes.

Skynet, anyone? Feel free to weigh in with your comments below.

John Roach is a contributing writer for msnbc.com. Connect with the Cosmic Log community by hitting the "like" button on the Cosmic Log Facebook page or following msnbc.com's science editor, Alan Boyle, on Twitter (@b0yle).