IBM’s Watson Goes Where No Machine Has Gone Before

By Nicole Hemsoth

January 13, 2011

This is just a personal reflection, but if there are two things on television that never get boring, even if I have seen the same episode multiple times, it’s Star Trek: Next Generation and Jeopardy.

To my utter delight, in February, elements of two of my favorite programs are going to meld thematically as IBM’s Watson supercomputer battles it out with history’s most revered trivia champions, Ken Jennings and Brad Rutter.

The IBM researchers behind Watson are confident that they’ve achieved their goal to build a system that can rival mortal abilities to answer questions asked in normal speech–and to do so quickly. As IBM noted of the tournament, which will be held over three days beginning February 14th, this provides the “ultimate challenge because the game’s clues involve analyzing subtle meaning, irony, riddles, and other complexities in which humans excel and computers traditionally do not.”

IBM’s champion has already sparred, with mixed success, against some of the brightest Jeopardy minds during a series of 50 sparring games in advance of the primetime debut, which can be viewed here (along with some neat history behind the machine and its capabilities). Upstairs, in a room filled with servers humming away, Watson was processing quietly…and giving human contenders a run for their money.

Following the airing of the trivia battle, there are very likely going to be fresh rounds of mainstream media comments on the man versus machine debate. News outlets will doubtlessly feature background images of Skynet and other Hollywood versions of “good machines gone bad” because, well, if Watson proves itself on national television, it’s bound to be a little unnerving.

Instead of calling to mind deadly scenes from War Games and countless other sci-fi flicks that feature feral machines with minds of their own hell-bent on destroying their human makers, I think of a kinder, softer version of artificial intelligence (AI) — Lieutenant Commander Data. After all, if there is any Hollywood counterpart to Watson (minus the emotion chip, thank goodness) it’s pop culture’s most-loved Android.

Watson is, in some ways, like a 21st-century prototype of Star Trek’s Data. Both have the equivalent of millions of books built into a natural language processing-based algorithm, both are able to pick up on wordplay subtleties, making them, well, in some ways, “people-smart” and they both have the ability to kick some serious human tail in a head-to-head mental match.

What ordinary viewers might overlook is the power of this context awareness. Watson is not simply answering questions posed simply — “he” is processing vast amounts of context-dependent information presented in natural human speech to arrive at an answer that is based on any number of factors. This is, in a word, absolutely groundbreaking. On a speech and context recognition front, in particular — turning questions that require multifaceted layers of knowledge into answers that rely on a number of variables from any number of sources. The analytics involved are mind-boggling.

And isn’t that what makes Data so fascinating?

The only real difference between Data and Watson, outside of hundreds of years of extra R&D for Data’s wiring, is the human-like veneer — both in terms of appearance and speaking ability. If there’s one thing Watson lacks, it’s the ability to sound like anyone (or anything) but HAL.

This type of artificial intelligence goes far beyond what most of us would consider the great question-answer machine — the search engine. Research and development has been conducted for years to arrive at creating machines that can field simple verbal questions, but these have lacked the algorithmic complexity necessary to arrive at answers based on context.

Just as was at the heart of any number of scenarios involving Data, however, was the inherent question of whether or not, with any amount or development in AI there would be certain core levels of knowledge that even the sophisticated question-answer machines couldn’t get to the heart of. Are there ways to trick to such a context-aware computer — to “stump the chump?”

It will be interesting to see what questions Watson misses and look for patterns that might indicate why a machine might be less proficient at producing an answer with so much of the world’s information storehoused.

But on another note, watching the humans lose to IBM’s marvel of computer engineering would be almost as uncomfortable as watching Worf attempt yoga in a spandex Starfleet uniform. In all fairness to the mortal team, however, it did take IBM multiple tries to a beat a certain chess legend…

As a side issue, IBM’s goal with Watson as a research proof of concept is staggering, but there is clear business value behind the move to take their act to television audiences. If IBM can position itself as a leader in the arena of context-aware machines, the sky is the limit. We already talk to and command our phones, cars, and anything else with a chip, using simple verbal prompts. The company that delivers the power of real speech recognition and processing to any array of consumer and business devices is set to grow.

At a recent conference on cybernetics, the president of the American Association for Artificial Intelligence, when asked what the ultimate goal was for the organization, replied “creating Star Trek’s Mr. Data would be a historic feat of cybernetics, and right now it’s very controversial in computer science whether it can be done. Maybe a self-aware computer can be put into a human-sized body and convinced to live sociable with us and our limitations… that’s a long way head of our technology, but maybe not impossible.”

While indeed, on the sociability, size, and cybernetics front Data is still just science fiction, the advancements that IBM is getting ready to put on display for the world in February seem like a positive sign when it comes to our ability to start interacting personably with our machines.

I’ll be gearing up for the great battle on February 14th. And just to put this out there, if IBM engineers are able to hire Brent Spiner for a little extra context-aware voice-over work, if only for Watson’s primetime television debut, there’s a good chance my head will explode.

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!

Musk’s Latest Startup Eyes Brain-Computer Links

April 21, 2017

Elon Musk, the auto and space entrepreneur and severe critic of artificial intelligence, is forming a new venture that reportedly will seek to develop an interface between the human brain and computers. Read more…

By George Leopold

MIT Mathematician Spins Up 220,000-Core Google Compute Cluster

April 21, 2017

On Thursday, Google announced that MIT math professor and computational number theorist Andrew V. Sutherland had set a record for the largest Google Compute Engine (GCE) job. Sutherland ran the massive mathematics workload on 220,000 GCE cores using preemptible virtual machine instances. Read more…

By Tiffany Trader

NERSC Cori Shows the World How Many-Cores for the Masses Works

April 21, 2017

As its mission, the high performance computing center for the U.S. Department of Energy Office of Science, NERSC (the National Energy Research Supercomputer Center), supports a broad spectrum of forefront scientific research across diverse areas that includes climate, material science, chemistry, fusion energy, high-energy physics and many others. Read more…

By Rob Farber

Nvidia P100 Shows 1.3-2.3x Speedup Over K80 GPU on Financial Apps

April 20, 2017

When it comes to the true performance of the latest silicon, every end user knows that the best processor is the one that works best for their application. Read more…

By Tiffany Trader

HPE Extreme Performance Solutions

Remote Visualization Optimizing Life Sciences Operations and Care Delivery

As patients continually demand a better quality of care and increasingly complex workloads challenge healthcare organizations to innovate, investing in the right technologies is key to ensuring growth and success. Read more…

Quantum Adds Global Smarts to StorNext File System

April 20, 2017

Companies that use Quantum’s StorNext platform to store massive amounts of data this week got a glimpse of new storage capabilities that should make it easier to access their data horde from anywhere in the world. Read more…

By Alex Woodie

Scaling an HPC Career in Nepal Can Be a Steep Climb

April 20, 2017

Umesh Upadhyaya works as an IT Associate at the International Centre for Integrated Mountain Development (ICIMOD) in Nepal, which supports the country’s one and only HPC facility. He is directly involved in an initiative that focuses on climate change and atmosphere modeling Read more…

By Nages Sieslack

Hyperion (IDC) Paints a Bullish Picture of HPC Future

April 20, 2017

Hyperion Research – formerly IDC’s HPC group – yesterday painted a fascinating and complicated portrait of the HPC community’s health and prospects at the HPC User Forum held in Albuquerque, NM. HPC sales are up and growing ($22 billion, all HPC segments, 2016). Read more…

By John Russell

Intel Open Sources All Lustre Work, Brent Gorda Exits

April 19, 2017

In a letter to the Lustre community posted on the Intel website, Vice President of Intel's Data Center Group Trish Damkroger writes that effective immediately the company will be contributing all Lustre development to the open source community. Damkroger also announced that Brent Gorda, General Manager, High Performance Data Division at Intel is leaving the company. Read more…

By Tiffany Trader

NERSC Cori Shows the World How Many-Cores for the Masses Works

April 21, 2017

As its mission, the high performance computing center for the U.S. Department of Energy Office of Science, NERSC (the National Energy Research Supercomputer Center), supports a broad spectrum of forefront scientific research across diverse areas that includes climate, material science, chemistry, fusion energy, high-energy physics and many others. Read more…

By Rob Farber

Hyperion (IDC) Paints a Bullish Picture of HPC Future

April 20, 2017

Hyperion Research – formerly IDC’s HPC group – yesterday painted a fascinating and complicated portrait of the HPC community’s health and prospects at the HPC User Forum held in Albuquerque, NM. HPC sales are up and growing ($22 billion, all HPC segments, 2016). Read more…

By John Russell

Knights Landing Processor with Omni-Path Makes Cloud Debut

April 18, 2017

HPC cloud specialist Rescale is partnering with Intel and HPC resource provider R Systems to offer first-ever cloud access to Xeon Phi "Knights Landing" processors. The infrastructure is based on the 68-core Intel Knights Landing processor with integrated Omni-Path fabric (the 7250F Xeon Phi). Read more…

By Tiffany Trader

CERN openlab Explores New CPU/FPGA Processing Solutions

April 14, 2017

Through a CERN openlab project known as the ‘High-Throughput Computing Collaboration,’ researchers are investigating the use of various Intel technologies in data filtering and data acquisition systems. Read more…

By Linda Barney

DOE Supercomputer Achieves Record 45-Qubit Quantum Simulation

April 13, 2017

In order to simulate larger and larger quantum systems and usher in an age of “quantum supremacy,” researchers are stretching the limits of today’s most advanced supercomputers. Read more…

By Tiffany Trader

Penguin Takes a Run at the Big Cloud Providers

April 12, 2017

HPC specialist Penguin Computing recently re-ran benchmarks from a study of its larger brethren and says the results show its ‘public cloud’ – Penguin on Demand (POD) – is among the leaders in cost and performance. Read more…

By John Russell

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

HPC and the Colocation Datacenter – a Bridge Too Far?

April 7, 2017

A more standardised HPC platform approach is making the running of HPC projects within increasing financial reach. Read more…

By Clive Longbottom, Quocirca

Google Pulls Back the Covers on Its First Machine Learning Chip

April 6, 2017

This week Google released a report detailing the design and performance characteristics of the Tensor Processing Unit (TPU), its custom ASIC for the inference phase of neural networks (NN). Read more…

By Tiffany Trader

Quantum Bits: D-Wave and VW; Google Quantum Lab; IBM Expands Access

March 21, 2017

For a technology that’s usually characterized as far off and in a distant galaxy, quantum computing has been steadily picking up steam. Read more…

By John Russell

Trump Budget Targets NIH, DOE, and EPA; No Mention of NSF

March 16, 2017

President Trump’s proposed U.S. fiscal 2018 budget issued today sharply cuts science spending while bolstering military spending as he promised during the campaign. Read more…

By John Russell

HPC Compiler Company PathScale Seeks Life Raft

March 23, 2017

HPCwire has learned that HPC compiler company PathScale has fallen on difficult times and is asking the community for help or actively seeking a buyer for its assets. 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

For IBM/OpenPOWER: Success in 2017 = (Volume) Sales

January 11, 2017

To a large degree IBM and the OpenPOWER Foundation have done what they said they would – assembling a substantial and growing ecosystem and bringing Power-based products to market, all in about three years. Read more…

By John Russell

CPU-based Visualization Positions for Exascale Supercomputing

March 16, 2017

In this contributed perspective piece, Intel’s Jim Jeffers makes the case that CPU-based visualization is now widely adopted and as such is no longer a contrarian view, but is rather an exascale requirement. Read more…

By Jim Jeffers, Principal Engineer and Engineering Leader, Intel

TSUBAME3.0 Points to Future HPE Pascal-NVLink-OPA Server

February 17, 2017

Since our initial coverage of the TSUBAME3.0 supercomputer yesterday, more details have come to light on this innovative project. Of particular interest is a new board design for NVLink-equipped Pascal P100 GPUs that will create another entrant to the space currently occupied by Nvidia's DGX-1 system, IBM's "Minsky" platform and the Supermicro SuperServer (1028GQ-TXR). Read more…

By Tiffany Trader

Leading Solution Providers

Tokyo Tech’s TSUBAME3.0 Will Be First HPE-SGI Super

February 16, 2017

In a press event Friday afternoon local time in Japan, Tokyo Institute of Technology (Tokyo Tech) announced its plans for the TSUBAME3.0 supercomputer, which will be Japan’s “fastest AI supercomputer,” Read more…

By Tiffany Trader

IBM Wants to be “Red Hat” of Deep Learning

January 26, 2017

IBM today announced the addition of TensorFlow and Chainer deep learning frameworks to its PowerAI suite of deep learning tools, which already includes popular offerings such as Caffe, Theano, and Torch. Read more…

By John Russell

Is Liquid Cooling Ready to Go Mainstream?

February 13, 2017

Lost in the frenzy of SC16 was a substantial rise in the number of vendors showing server oriented liquid cooling technologies. Three decades ago liquid cooling was pretty much the exclusive realm of the Cray-2 and IBM mainframe class products. That’s changing. We are now seeing an emergence of x86 class server products with exotic plumbing technology ranging from Direct-to-Chip to servers and storage completely immersed in a dielectric fluid. Read more…

By Steve Campbell

BioTeam’s Berman Charts 2017 HPC Trends in Life Sciences

January 4, 2017

Twenty years ago high performance computing was nearly absent from life sciences. Today it’s used throughout life sciences and biomedical research. Genomics and the data deluge from modern lab instruments are the main drivers, but so is the longer-term desire to perform predictive simulation in support of Precision Medicine (PM). There’s even a specialized life sciences supercomputer, ‘Anton’ from D.E. Shaw Research, and the Pittsburgh Supercomputing Center is standing up its second Anton 2 and actively soliciting project proposals. There’s a lot going on. Read more…

By John Russell

HPC Startup Advances Auto-Parallelization’s Promise

January 23, 2017

The shift from single core to multicore hardware has made finding parallelism in codes more important than ever, but that hasn’t made the task of parallel programming any easier. Read more…

By Tiffany Trader

HPC Technique Propels Deep Learning at Scale

February 21, 2017

Researchers from Baidu’s Silicon Valley AI Lab (SVAIL) have adapted a well-known HPC communication technique to boost the speed and scale of their neural network training and now they are sharing their implementation with the larger deep learning community. Read more…

By Tiffany Trader

US Supercomputing Leaders Tackle the China Question

March 15, 2017

Joint DOE-NSA report responds to the increased global pressures impacting the competitiveness of U.S. supercomputing. Read more…

By Tiffany Trader

IDG to Be Bought by Chinese Investors; IDC to Spin Out HPC Group

January 19, 2017

US-based publishing and investment firm International Data Group, Inc. (IDG) will be acquired by a pair of Chinese investors, China Oceanwide Holdings Group Co., Ltd. Read more…

By Tiffany Trader

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