Must See TV: IBM Watson Heads for Jeopardy Showdown

By Michael Feldman

February 9, 2011

Next week the IBM supercomputer known as “Watson” will take on two of the most accomplished Jeopardy players of all time, Ken Jennings and Brad Rutter, in a three-game match starting on February 14. If Watson manages to best the humans, it will represent the most important advance in machine intelligence since IBM’s “Deep Blue” beat chess grandmaster Garry Kasparov in 1997. But this time around, the company also plans to make a business case for the technology. Trivial pursuit this is not.

And impressive technology it is. On the hardware side, Watson is comprised of 90 Power 750 servers, 16 TB of memory and 4 TB of disk storage, all housed in a relatively compact ten racks. The 750 is IBM’s elite Power7-based server targeted for high-end enterprise analytics. (The Power 755 is geared toward high performance technical computing and differs only marginally in CPU speed, memory capacity, and storage options.) Although the enterprise version can be ordered with 1 to 4 sockets of 6-core or 8-core Power7 chips, Watson is maxed out with the 4-socket, 8-core configuration using the top bin 3.55 GHz processors.

The 360 Power7 chips that make up Watson’s brain represent IBM’s best and brightest processor technology. Each Power7 is capable of over 500 GB/second of aggregate bandwidth, making it particularly adept at manipulating data at high speeds. FLOPS-wise, a 3.55 GHz Power7 delivers 218 Linpack gigaflops. For comparison, the POWER2 SC processor, which was the chip that powered cyber-chessmaster Deep Blue, managed a paltry 0.48 gigaflops, with the whole machine delivering a mere 11.4 Linpack gigaflops.

But FLOPS are not the real story here. Watson’s question-answering software presumably makes little use of floating-point number crunching. To deal with the game scenario, the system had to be endowed with a rather advanced version of natural language processing. But according to David Ferrucci, principal investigator for the project, it goes far beyond language smarts. The software system, called DeepQA, also incorporates machine learning, knowledge representation, and deep analytics.

Even so, the whole application rests on first understanding the Jeopardy clues, which, because they employ colloquialisms and often obscure references, can be challenging even for humans. That’s why this is such a good test case for natural language processing. Ferrucci says the ability to understand language is destined to become a very important aspect of computers. “It has to be that way,” he says. “We just cant imagine a future without it.”

But it’s the analysis component that we associate with real “intelligence.” The approach here reflects the open domain nature of the problem. According to Ferrucci, it wouldn’t have made sense to simply construct a database corresponding to possible Jeopardy clues. Such a model would have supported only a small fraction of the possible topics available to Jeopardy. Rather their approach was to use “as is” information sources — encyclopedias, dictionaries, thesauri, plays, books, etc. — and make the correlations dynamically.

The trick of course is to do all the processing in real-time. Contestants, at least the successful ones, need to provide an answer in just a few seconds. When the software was run on a lone 2.6 GHz CPU, it took around 2 hours to process a typical Jeopardy clue — not a very practical implementation. But when they parallelized the algorithms across the 2,880-core Watson, they were able to cut the processing time from a couple of hours to between 2 and 6 seconds.

Even at that, Watson doesn’t just spit out the answers. It forms hypotheses based on the evidence it finds and scores them at various confidence levels. Watson is programmed not to buzz in until it reaches a confidence of at least 50 percent, although this parameter can be self-adjusted depending on the game situation.

To accomplish all this, DeepQA employs an ensemble of algorithms — about a million lines of code — to gather and score the evidence. These include temporal reasoning algorithms to correlate times with events, statistical paraphrasing algorithms to evaluate semantic context, and geospatial reasoning to correlate locations.

It can also dynamically form associations, both in training and at game time, to connect disparate ideas. For example it can learn that inventors can patent information or that officials can submit resignations. Watson also shifts the weight it assigns to different algorithms based on which ones are delivering the more accurate correlations. This aspect of machine learning allows Watson to get “smarter” the more it plays the game.

The DeepQA programmers have also been refining the algorithms themselves over the past several years. In 2007, Watson could only answer a small fraction of Jeopardy clues with reasonable confidence and even at that, was only correct 47 percent of the time. When forced to answer the majority of the clues, like a grand champion would, it could only answer 15 percent correctly. By IBM’s own admission, Watson was playing “terrible.” The highest performing Jeopardy grand champions, like Jennings and Rutter, typically buzz in on 70 to 80 percent of the entries and give the correct answer 85 to 95 percent of time.

By 2010 Watson started playing at that level. Ferrucci says that while the system can’t buzz in on every question, it can now answer the vast majority of them in competitive time. “We can compete with grand champions in terms of precision, in terms of confidence, and in terms of speed,” he says.

In dozens of practice rounds against former Jeopardy champs, the computer was beating the humans with a 65 percent win rate. Watson also prevailed in a 15-question round against Jennings and Rutter in early January of this year. See the performance below.

None of this is a guarantee that Watson will prevail next week. But even if the machine just makes a decent showing, IBM will have pulled off quite possibly the best product placement in television history. Open domain question answering is not only one of the Holy Grails of artificial intelligence but has enormous potential for commercial applications. In areas as disparate as healthcare, tech support, business intelligence, security and finance, this type of platform could change those businesses irrevocably. John Kelly, senior vice president and director of IBM Research, boasts, “We’re going to revolutionize industries at a level that has never been done before.”

In the case of healthcare, it’s not a huge leap to imagine “expert” question answering systems helping doctors with medical diagnosis. A differential diagnosis is not much different from what Watson does when it analyzes a Jeopardy clue. Before it replaces Dr. House, though, the machine will have to prove itself in the game show arena.

If Jennings and Rutter defeat the supercomputer this time around, IBM will almost certainly ask for a rematch, as it did when Deep Blue initially lost its first chess match with Kasparov in 1996. The engineers will keep stroking the code and retraining the computer until Watson is truly unbeatable. Eventually the machine will prevail.

—–

For a broader discussion on this topic between the author and InterSect360 Research CEO Addison Snell, download this week’s HPCwire Soundbite podcast.

Subscribe to HPCwire's Weekly Update!

Be the most informed person in the room! Stay ahead of the tech trends with industy updates delivered to you every week!

Takeaways from the Milwaukee HPC User Forum

September 19, 2017

Milwaukee’s elegant Pfister Hotel hosted approximately 100 attendees for the 66th HPC User Forum (September 5-7, 2017). In the original home city of Pabst Blue Ribbon and Harley Davidson motorcycles the agenda addresse Read more…

By Merle Giles

NSF Awards $10M to Extend Chameleon Cloud Testbed Project

September 19, 2017

The National Science Foundation has awarded a second phase, $10 million grant to the Chameleon cloud computing testbed project led by University of Chicago with partners at the Texas Advanced Computing Center (TACC), Ren Read more…

By John Russell

NERSC Simulations Shed Light on Fusion Reaction Turbulence

September 19, 2017

Understanding fusion reactions in detail – particularly plasma turbulence – is critical to the effort to bring fusion power to reality. Recent work including roughly 70 million hours of compute time at the National E Read more…

HPE Extreme Performance Solutions

HPE Prepares Customers for Success with the HPC Software Portfolio

High performance computing (HPC) software is key to harnessing the full power of HPC environments. Development and management tools enable IT departments to streamline installation and maintenance of their systems as well as create, optimize, and run their HPC applications. Read more…

Kathy Yelick Charts the Promise and Progress of Exascale Science

September 15, 2017

On Friday, Sept. 8, Kathy Yelick of Lawrence Berkeley National Laboratory and the University of California, Berkeley, delivered the keynote address on “Breakthrough Science at the Exascale” at the ACM Europe Conferen Read more…

By Tiffany Trader

Takeaways from the Milwaukee HPC User Forum

September 19, 2017

Milwaukee’s elegant Pfister Hotel hosted approximately 100 attendees for the 66th HPC User Forum (September 5-7, 2017). In the original home city of Pabst Blu Read more…

By Merle Giles

Kathy Yelick Charts the Promise and Progress of Exascale Science

September 15, 2017

On Friday, Sept. 8, Kathy Yelick of Lawrence Berkeley National Laboratory and the University of California, Berkeley, delivered the keynote address on “Breakt Read more…

By Tiffany Trader

DARPA Pledges Another $300 Million for Post-Moore’s Readiness

September 14, 2017

The Defense Advanced Research Projects Agency (DARPA) launched a giant funding effort to ensure the United States can sustain the pace of electronic innovation vital to both a flourishing economy and a secure military. Under the banner of the Electronics Resurgence Initiative (ERI), some $500-$800 million will be invested in post-Moore’s Law technologies. Read more…

By Tiffany Trader

IBM Breaks Ground for Complex Quantum Chemistry

September 14, 2017

IBM has reported the use of a novel algorithm to simulate BeH2 (beryllium-hydride) on a quantum computer. This is the largest molecule so far simulated on a quantum computer. The technique, which used six qubits of a seven-qubit system, is an important step forward and may suggest an approach to simulating ever larger molecules. Read more…

By John Russell

Cubes, Culture, and a New Challenge: Trish Damkroger Talks about Life at Intel—and Why HPC Matters More Than Ever

September 13, 2017

Trish Damkroger wasn’t looking to change jobs when she attended SC15 in Austin, Texas. Capping a 15-year career within Department of Energy (DOE) laboratories, she was acting Associate Director for Computation at Lawrence Livermore National Laboratory (LLNL). Her mission was to equip the lab’s scientists and research partners with resources that would advance their cutting-edge work... Read more…

By Jan Rowell

EU Funds 20 Million Euro ARM+FPGA Exascale Project

September 7, 2017

At the Barcelona Supercomputer Centre on Wednesday (Sept. 6), 16 partners gathered to launch the EuroEXA project, which invests €20 million over three-and-a-half years into exascale-focused research and development. Led by the Horizon 2020 program, EuroEXA picks up the banner of a triad of partner projects — ExaNeSt, EcoScale and ExaNoDe — building on their work... Read more…

By Tiffany Trader

MIT-IBM Watson AI Lab Targets Algorithms, AI Physics

September 7, 2017

Investment continues to flow into artificial intelligence research, especially in key areas such as AI algorithms that promise to move the technology from speci Read more…

By George Leopold

Need Data Science CyberInfrastructure? Check with RENCI’s xDCI Concierge

September 6, 2017

For about a year the Renaissance Computing Institute (RENCI) has been assembling best practices and open source components around data-driven scientific researc Read more…

By John Russell

How ‘Knights Mill’ Gets Its Deep Learning Flops

June 22, 2017

Intel, the subject of much speculation regarding the delayed, rewritten or potentially canceled “Aurora” contract (the Argonne Lab part of the CORAL “ Read more…

By Tiffany Trader

Reinders: “AVX-512 May Be a Hidden Gem” in Intel Xeon Scalable Processors

June 29, 2017

Imagine if we could use vector processing on something other than just floating point problems.  Today, GPUs and CPUs work tirelessly to accelerate algorithms Read more…

By James Reinders

NERSC Scales Scientific Deep Learning to 15 Petaflops

August 28, 2017

A collaborative effort between Intel, NERSC and Stanford has delivered the first 15-petaflops deep learning software running on HPC platforms and is, according Read more…

By Rob Farber

Russian Researchers Claim First Quantum-Safe Blockchain

May 25, 2017

The Russian Quantum Center today announced it has overcome the threat of quantum cryptography by creating the first quantum-safe blockchain, securing cryptocurrencies like Bitcoin, along with classified government communications and other sensitive digital transfers. Read more…

By Doug Black

Oracle Layoffs Reportedly Hit SPARC and Solaris Hard

September 7, 2017

Oracle’s latest layoffs have many wondering if this is the end of the line for the SPARC processor and Solaris OS development. As reported by multiple sources Read more…

By John Russell

Google Debuts TPU v2 and will Add to Google Cloud

May 25, 2017

Not long after stirring attention in the deep learning/AI community by revealing the details of its Tensor Processing Unit (TPU), Google last week announced the Read more…

By John Russell

Six Exascale PathForward Vendors Selected; DoE Providing $258M

June 15, 2017

The much-anticipated PathForward awards for hardware R&D in support of the Exascale Computing Project were announced today with six vendors selected – AMD Read more…

By John Russell

Top500 Results: Latest List Trends and What’s in Store

June 19, 2017

Greetings from Frankfurt and the 2017 International Supercomputing Conference where the latest Top500 list has just been revealed. Although there were no major Read more…

By Tiffany Trader

Leading Solution Providers

IBM Clears Path to 5nm with Silicon Nanosheets

June 5, 2017

Two years since announcing the industry’s first 7nm node test chip, IBM and its research alliance partners GlobalFoundries and Samsung have developed a proces Read more…

By Tiffany Trader

Nvidia Responds to Google TPU Benchmarking

April 10, 2017

Nvidia highlights strengths of its newest GPU silicon in response to Google's report on the performance and energy advantages of its custom tensor processor. Read more…

By Tiffany Trader

Graphcore Readies Launch of 16nm Colossus-IPU Chip

July 20, 2017

A second $30 million funding round for U.K. AI chip developer Graphcore sets up the company to go to market with its “intelligent processing unit” (IPU) in Read more…

By Tiffany Trader

Google Releases Deeplearn.js to Further Democratize Machine Learning

August 17, 2017

Spreading the use of machine learning tools is one of the goals of Google’s PAIR (People + AI Research) initiative, which was introduced in early July. Last w Read more…

By John Russell

EU Funds 20 Million Euro ARM+FPGA Exascale Project

September 7, 2017

At the Barcelona Supercomputer Centre on Wednesday (Sept. 6), 16 partners gathered to launch the EuroEXA project, which invests €20 million over three-and-a-half years into exascale-focused research and development. Led by the Horizon 2020 program, EuroEXA picks up the banner of a triad of partner projects — ExaNeSt, EcoScale and ExaNoDe — building on their work... Read more…

By Tiffany Trader

Cray Moves to Acquire the Seagate ClusterStor Line

July 28, 2017

This week Cray announced that it is picking up Seagate's ClusterStor HPC storage array business for an undisclosed sum. "In short we're effectively transitioning the bulk of the ClusterStor product line to Cray," said CEO Peter Ungaro. Read more…

By Tiffany Trader

Amazon Debuts New AMD-based GPU Instances for Graphics Acceleration

September 12, 2017

Last week Amazon Web Services (AWS) streaming service, AppStream 2.0, introduced a new GPU instance called Graphics Design intended to accelerate graphics. The Read more…

By John Russell

GlobalFoundries: 7nm Chips Coming in 2018, EUV in 2019

June 13, 2017

GlobalFoundries has formally announced that its 7nm technology is ready for customer engagement with product tape outs expected for the first half of 2018. The Read more…

By Tiffany Trader

  • arrow
  • Click Here for More Headlines
  • arrow
Share This