Just look at the scorecard: First, Watson schools humanity at the TV game show “Jeopardy.” Granted, that was a publicity stunt, but a fun and interesting one, about which at least one really smart person decided to write a book. (See my coverage of Watson’s three-day campaign of human domination on “Jeopardy” from last year: Day one | Day two | Day three.)

And what does it do for an encore? It plays “Jeopardy” with a U.S. senator and, well, you know, sorta lets him win. Then it gets a real job, working for health-insurance giant WellPoint.

So, if hearing from Watson is beginning to feel a little like that annual Christmas card from the annoying family whose kids are a little too highly accomplished, you can add this to the pile: Watson is now a doctor, too. Well, he’s been to medical school, at least, and even has a specialty: Oncology. And now he has a job at a very high-profile cancer-treatment center: New York’s Memorial Sloan-Kettering Cancer Center.

Attentive AllThingsD readers will remember January’s extensive Seven Questions session with Manoj Saxena about going to medical school. And while Watson isn’t really a doctor — more like an extremely well-read physician’s assistant — it sure is interesting to learn what it can do: Watson can consult both the very latest medical literature and look back through the history of previous cancer cases to help doctors figure out the best way to treat a particular cancer.

We’re still pretty far away from computers actually making medical decisions. Watson isn’t that good, so there will always be a human doctor as a backstop to its suggestions of possible treatment options. But as you’ll hear Dr. Larry Norton say in the IBM video below, computers like Watson are helping us shift away from an era in which doctors make decisions based on their own experience and opinions, to one where they can readily consult the evidence and determine with a firm “yes” or “no” if something is likely to work. No one likes to think about cancer, but if you or someone you care about gets it, it’s an encouraging thought.

And yes, while IBM keeps banging the publicity drum for Watson, it looks like the machine is going to be doing its part for IBM’s bottom line, too. Big Blue has a target of $16 billion in revenue derived from its data-analytics business by 2015. Bloomberg News quotes Ed Maguire, an analyst with CLSA in New York, as estimating that Watson could bring in about $2.5 billion in sales and contribute as much as 52 cents in per-share earnings by that time. Yeah, I’m kinda jealous of Watson, too.

And while it was something of a publicity stunt to put a sophisticated and specialized IBM computer in people’s living rooms, the fact remains that Watson is, well, a pretty sophisticated and specialized computer.

Since schooling humanity at “Jeopardy” — which was the subject of a book — Watson went on to get a real job working for the health insurance company Wellpoint.

Now IBM has decided it is ready to tackle something a little more involved. Watson is about to go to medical school, and will even study a specialty: Oncology. Sometime this year, after studying and even taking exams to prove what it has learned, Watson will be assigned to assist human physicians in the treatment of breast, lung and colon cancer.

If this seems like kind of a big deal, it is. Watson won’t be the first computer to serve as a reference tool, helping doctors do their jobs. But then there has never been a computer quite like Watson, which can learn so readily from natural language — and play TV game shows and win.

Last week, I talked with Manoj Saxena, general manager of the Watson program at IBM, to talk about what Watson will — and won’t — be doing in helping doctors treat humans with cancer, and what that might mean for the future of medicine.

My first question was about what Watson has been doing since its big win:

AllThingsD: So, Manoj, last I knew, Watson had been working for Wellpoint, which is a large health insurer. What exactly has it been doing?

Saxena: Let me bring you up to speed. In August, we announced the first commercial relationship of Watson with Wellpoint, one of the nation’s largest health insurers. They have 35 million customers in 14 different states. One out of nine Americans are covered by them. The first area was around utilization or approval. Let’s say you or I call up a clinic or hospital saying we have flu-like symptoms. Where Watson would come in is on the approval process, saying we’re covered. Then Watson looks at the history that the hospital has in its records. It might say that it’s early December, and I come in at this time every year saying the same thing; and the last two times it was a ragweed allergy, not the flu. And the medical journals say there’s a connection between ragweed and fever that looks like the flu. And by the way, the newspaper says there was an outbreak of ragweed in Central Texas. And then, in addition to treating for flu, also look for allergies. So Watson is considering the medical record; the patient history that the insurance company has; and third, the medical journal and news information about what may be causing a certain thing. So that’s what it’s doing with Wellpoint so far.

How then do you make the pivot to working with cancer?

We’ve installed another adviser — these solutions are called Watson Advisers. This one is called Watson Oncology Adviser, and this is a big one. As you may remember, medical information is doubling every five years. Doctors tell us that they are spending only five hours per month going through new information in medical literature. On one hand, you have all this medical information coming out. We’ve decided to focus first on breast, lung and colon cancers as the three to apply Watson to. And Cedars-Sinai has partnered with Wellpoint to help come up with the right cancer solutions. And the point is to build the expertise within Watson to help treat cancer.

So Watson won’t be directly involved with the treatment, but rather to build up its own knowledge base?

Watson doesn’t make the decisions. It’s a physician’s assistant. But before it becomes that, it has a lot to learn. Out of the box, Watson has the knowledge of a first-year medical resident. That is where it’s at today. With Cedars-Sinai and Wellpoint, we’re going to teach it all about cancer during the next six months. We’re going to show it actual cases that were solved in the past. And over time, we’ll tweak and teach it, using things we already know.

Is there a human analog to this process?

A good human analog is how we learn. As children, our teachers and parents sit with us and ask questions to understand how well we learned from what we read. And then, later, we learn by doing. This will address the first two phases. Watson will read on its own, and then oncologists are going to ask questions of Watson to understand how well he has learned and then understood. And then once we feel comfortable that it has learned enough, then we will let it begin working as a physician’s assistant, and then it will go from there.

Since, in the end, there are humans being treated, do you have to get any kind of regulatory approval to do this?

No. It’s very similar to how doctors refer to medical journals. Doctors might turn to Google or something like that to look up info from their medical journals. That doesn’t require any approvals. Someone else asked me what happens if Watson suggests a particular treatment, the doctor accepts it, and the patient dies. Or what happens when Watson suggests something and the doctor doesn’t take his advice. Our view is that it’s the same as looking up textbooks and information. The physician is the one who makes the final decision.

And that will always be the case?

That will always be the case, yes. We are far, far away from computers doing medical treatments. I don’t even see it in the forseeable future.

How do you actually go about feeding information to Watson? How does it learn?

It’s a good question. There are four different types of information that’s fed into Watson. At the base of the pyramid, it’s general information like Wikipedia and Google and general information like that. And a lot of that is general knowledge; and a lot of that is already in place, because we needed that to play Jeopardy! Then the second layer is the medical textbooks and medical journals and vocabularies, and those are fed in as natural-language information. It can be any scanned information or text information because Watson understands natural language. So that information is the second part. It can process text and tables, but it can’t process pictures and videos, but we’re working on that. And then there’s the actual test cases, the information on people with 30 years of cancer treatment history. We feed that into what are called “answer keys.” The fourth layer are new domain-specific information models that are specific protocols and procedures that the health insurance companies will want to feed into Watson.

Where do you draw the line? There is an accepted mainstream body of knowledge and accepted treatments for different cancers, and then there are newer things that may be controversial for some reason.

The way we approach it is in two parts. One is the body of knowledge that is already known. But it does not get applied and in context, and often doctors don’t have access to it in context. There are things like cancer treatment guidelines and well-understood things about radiation and effects on different cancers. Call them the known treatment pathways. The second are the emerging treatment pathways, particularly in the area of genomics. That is the one that can get added on. It’s the one our partners are looking at. In about a decade, most cancer treatments are going to shift to genomics-based treatments, rather than chemotherapy-based treatments. There’s a deluge of information about converting the knowledge about DNA into biological knowledge, and then converting that into treatment knowledge. That is the second part of what we’ll be doing.

Do you have other diseases that you think Watson can help treat in the future?

Yes. Diabetes and cardiology, heart problems are next on the horizon. We’ll also be applying Watson in financial services.

If you’re a regular AllThingsD reader, you’ve already been introduced to the world’s most power supercomputer: It is the Fujitsu K Computer, which the Japanese computing concern disclosed earlier this month, and it runs in Japan’s quasi-public research institution RIKEN. That’s it in the picture above.

It’s capable of performance as high as 10.51 petaflops, or 10.51 quadrillion floating point operations per second. The same machine had been rated in the top spot on the list before, but was less powerful then, because it was still being assembled, and then capable of only 8.16 petaflops.

The machine is based on SPARC chips — the chips for which Sun Microsystems, now part of Oracle, gained such renown. Fujitsu has been building SPARC chips under license and using them in its own servers and supercomputers for years. In this case, there are 705,024 SPARC64 processing cores in action. And if my memory is correct, the chips in question each have four cores on board, meaning there are 176,256 individual processing chips in the machine.

It’s the first machine on the Top 500 list to venture past the 10-petaflop milestone; however, work is underway in the U.S. on a machine known as Titan, which will supposedly break the 20-petaflop mark sometime next year.

In the meantime, the second most powerful machine in the world is in China. The Tianhe-1A system took the top spot on the list a year ago — and in the process, caused President Obama such consternation about the state of American leadership in innovation that he mentioned it in his State of the Union address to Congress. Its performance reaches 2.57 petaflops and it’s powered by a combination of Intel-made Xeon processors and Nvidia graphical processing units.

In fact, the supercomputers in the top 10 spots on the list are otherwise unchanged from the list released in June.

At No. 3 is Jaguar, the system at the Oak Ridge National Laboratory that is being rebuilt into the machine called Titan, which I mentioned before. It’s a system built by Cray primarily around Nvidia GPUs and Opteron processors from Advanced Micro Devices. Its current performance is just shy of 1.8 petaflops.

The No. 4 system is in China. It’s called Nebulae and is at the National Supercomputing Centre in Shenzen. Its performance is just short of the 1.3-petaflop mark. No. 5 is called Tsubame 2.0, and is at the Tokyo Institute of Technology in Japan.

Chip companies in particular like to crow about the use of their products in the systems that wind up on the list. That makes this a banner day for Intel. Of the 500 systems on the list, 384 of them — 77 percent — use Intel chips. Chips from AMD, Intel’s main rival, are in 63 systems.

It’s a banner day for Nvidia, too. Its GPU chips can be found in 35 systems, more than double the number from the previous list. GPUs were invented to make the graphics in computer games more stunning and realistic; as such, it meant they were, from the beginning, pretty good at performing a certain type of math problem known as a floating point operation. It turns out that the people who run supercomputers do a lot of floating point operations — or FLOPs — too. So as GPUs have gotten more powerful, they’re finding their way into an ever-larger number of the world’s top supercomputers. Two supercomputers on the list use GPU chips from AMD’s graphics chip unit, ATI. Two more use IBM’s PowerCell architecture, which is a sibling of the Cell processor chip found in the Sony PlayStation 3.

President Obama shouldn’t feel so bad about the U.S. not being in the top spot. For one thing, practically all of the systems on the list are built on American-made technology. And among the systems that can reach 1 petaflop in performance or more, the U.S. has five, more than any other country. China and Japan have two each, and France has one. And the U.S. has more supercomputers on the list than any other country: 263. European countries have a combined 127; China has 75 and Japan has 30.

Intel may furnish more chips to the Top 500 list than anyone, but the king of the systems vendors on the list is unquestionably IBM, followed by Hewlett-Packard. IBM built 223, or more than 44 percent, of the machines on the list; HP built 140 of them. IBM also led the performance pack: Its machines are responsible for more than 27 percent of the total. Fujitsu, which made the list-topping K Computer, was in second place, with 14.7 percent. Cray and HP were in a statistical dead heat, with about 14 percent each.

Here’s a link to the full list, and a bunch of other things related to supercomputing.

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As ZDNet reports, Watson won the round with $4,400, while Ken Jennings had $3,400 and Brad Rutter brought in $1,200.

The game has been in the planning stages for years, and has been written about several times. The New York Times covered IBM’s work in a big story in 2009.

The whole point of teaching a computer to play “Jeopardy” lies in the complex computing work that’s required to make a machine understand natural human language and detect the same subtle cues of human speech that humans learn to understand over the years. “Jeopardy” questions can involve clever turns of phrases, riddles and other tricks of speech that can confuse a computer in ways that a game of chess won’t. Computers have already defeated humans at chess, you’ll recall, and it was an IBM computer that did it.

After the “Jeopardy” match, the human players said Watson had one distinct advantage: It doesn’t get psyched out. If another player wins a string of questions, it doesn’t suffer from the emotional response of losing confidence.

I don’t usually watch “Jeopardy,” or any game show for that matter. But I’m looking forward to seeing how the real game turns out.

Below is a rough video by ZDNet’s Larry Dignan, who attended the round.

Participants hope to outrace Chinese engineers in bringing a thousand-fold acceleration of today’s most powerful machines–replaying a crusade in the past decade that leapfrogged a supercomputer in Japan that briefly held the world speed crown.

This time, the challenges could be much tougher. Achieving the next major leap in computing performance could require systems with as many as a billion electronic brains, as well as programming breakthroughs to exploit them. And Republicans in Congress bent on reducing deficits may be hard to persuade to subsidize such developments.

It’s not going to be easy,” concedes Horst Simon, deputy laboratory director at Lawrence Berkeley National Laboratory in California, a major supercomputer user. But he says a case can be made that important scientific problems won’t be solved without a new generation of systems. “It is really an economic-competitiveness issue and a national-security issue,” he says.

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The system was designed by China’s National University of Defense Technology and is housed at the National Supercomputing Center in the city of Tianjin. It is part of a new breed that exploits graphics chips more commonly used in playing videogames–supplied by Nvidia Corp.–as well as standard microprocessors from Intel Corp.

Supercomputers are massive machines that help tackle the toughest scientific problems, including simulating commercial products like new drugs as well as defense-related applications such as weapons design and breaking codes. The field has long been led by U.S. technology companies and national laboratories, which operate systems that have consistently topped lists of the fastest machines in the world.

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Built on more than 100 patents or patents-pending, OnLive plans to deliver games either to the browser via plug-ins or to the TV through a micro set-top box.

Liveblog

Cloud game service OnLive take the stage to demo its pre-release game-delivery system.

10:16 am: Walt joins Kara onstage to talk about the power of cloud computing and to introduce OnLive.

10:17 am: Steve Perlman, CEO and founder of OnLive, comes on and says in two weeks, users will be able to log on and start cloud gaming.

Perlman says gaming is the first offering from OnLive, and that this is the hardest thing to do in the cloud.

Walt reminds the audience that Perlman worked on QuickTime at the young Apple Computer (AAPL) and the early Microsoft (MSFT), among others.

10:19 am: Perlman shows the Web interface for playing and watching games.

He shows that the games play on the computer, even though the full games would not run on the hardware he’s using if it were local.

10:20 am: Perlman says that as long as you are within 1,000 miles of OnLive’s data center, there is no perceptible latency thanks to new, proprietary compression technology.

10:21 am: Perlman shows how OnLive can create and serve huge volumes of 3-D video “brag clips” just as fast as the games.

The whole interface is a movable wall of individual videos.

10:23 am: Now Perlman brings out his “micro-console” to demo on a TV.

He says it’s very inexpensive and that depending on the business model OnLive adopts, he could even offer it for free to users who sign up for the service. According to Perlman, “The electronics inside cost less than the case and connectors.”

10:25 am: Perlman restarts the little black box, which is the size of a large deck of cards.

The interface on the TV micro-console is the same as the Web version.

Walt asks how many users can be online. Perlman says it is scalable to millions of users.

10:27 am: Walt asks what the price is.

Perlman says it will be less than $15 a month, but also hints that access to individual games will add additional costs.

10:28 am: Now Perlman starts an “unauthorized” demo of OnLive on the iPad. No Flash here.

He says the interface OnLive designed is also great for the iPad.

He sends a message to his “friend” who is playing another game, then begins playing a game called Borderlands on the iPad itself.

10:31 am: Perlman says that the game he’s playing wouldn’t play on any hardware in the room (only very high-end gaming consoles and computers).

10:32 am: Now Perlman opens the version for the iPhone–this one doesn’t work quite right, but Perlman says it’s prototype software and should work because to the iPhone, it’s just streaming media.

Walt asks for examples of what else he can deliver besides games.

Perlman answers by saying that the data center OnLive will be using may be the largest supercomputer in the world when it turns on in two weeks.

He says delivering video would be easy. He says OnLive’s microbox can run software that is too complex to run on any computer currently using Microsoft software.

Now he plays a Harry Potter movie on the iPad: No lag in play.

Now Perlman shows something new: A photo-realistic face generated with the same technology that was used to alter Brad Pitt’s face in “Benjamin Button.”

10:37 am: Perlman could keep going, but Walt and Kara bring the demo to a close.

D8 is on a short coffee break–back in a few with Tim Armstrong of AOL (AOL)

A note about our coverage: This liveblog is not an official transcript of the conversation that occurred onstage. Rather, it is a compilation of quotes, paraphrased statements and ad-lib observations written and posted to the Web as quickly as possible. It is not intended as a transcript and should not be interpreted as one.

National labs and other research institutions buy these supercomputers to handle huge number-crunching tasks, like modeling weather patterns, nuclear explosions and aircraft designs. They rely heavily on advances from the semiconductor industry, since each system uses thousands of microprocessor chips–typically supplied by Intel, Advanced Micro Devices (AMD) and IBM (IBM).

Rankings on the so-called Top500 list are determined by performing a set of mathematical calculations known as Linpack that indicate how fast a system is.

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The first computer ever to pass the petaflop milestone, Roadrunner is more than twice as fast as the top-ranked computer in the previous Top500 ranking. It’s also one of the most energy efficient systems on the Top500. But you wouldn’t know from looking at it. It’s housed in the Los Alamos National Laboratory and will be used principally for nuclear weapons simulations.

How did the Iranian computing center get its hands on 216 Opterons when the chips are embargoed from export to Iran? Well, it didn’t get them from AMD. “AMD fully complies with all United States export control laws, and all authorized distributors of AMD products have contractually committed to AMD that they will do the same with respect to their sales and shipments of AMD products,” the company said in a hastily released statement. “Any shipment of AMD products to Iran by any authorized distributor of AMD would be a breach of the specific provisions of their contracts with AMD.”

So, again, how did 216 Opterons find their way into Iran? Via the United Arab Emirates, perhaps? AMD did, after all, receive $622 million in funding from Mubadala Development Co., the investment arm of the Abu Dhabi government.

The so-called Mach-Zehnder electro-optic modulator transmits data between between multiple cores on a chip using pulses of light through silicon, instead of electrical signals on wires. It’s 100 to 1,000 times smaller than previously demonstrated modulators, and it transmits data 100 times faster than traditional copper wires while using 10 times less power.

If IBM’s able to replicate it commercially–and the company insists it can–it could inspire a vast array of new highly portable supercomputers that expend as little energy as a lightbulb. “Just like fiber-optic networks have enabled the rapid expansion of the Internet by enabling users to exchange huge amounts of data from anywhere in the world, IBM’s technology is bringing similar capabilities to the computer chip,” Will Green, IBM’s lead scientist on the project, told Reuters. “You immediately can envision the mobile applications that that would allow you to do. Remote laboratory instruments for medical applications, screening for diseases or even complicated DNA analysis.”

The so-called Mach-Zehnder electro-optic modulator transmits data between between multiple cores on a chip using pulses of light through silicon, instead of electrical signals on wires. It’s 100 to 1,000 times smaller than previously demonstrated modulators, and it transmits data 100 times faster than traditional copper wires while using 10 times less power.

If IBM’s able to replicate it commercially–and the company insists it can–it could inspire a vast array of new highly portable supercomputers that expend as little energy as a lightbulb. “Just like fiber-optic networks have enabled the rapid expansion of the Internet by enabling users to exchange huge amounts of data from anywhere in the world, IBM’s technology is bringing similar capabilities to the computer chip,” Will Green, IBM’s lead scientist on the project, told Reuters. “You immediately can envision the mobile applications that that would allow you to do. Remote laboratory instruments for medical applications, screening for diseases or even complicated DNA analysis.”