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For the longest time, people thought that humans could not run a mile in less than four minutes. Then, in 1954, [Sir Roger Bannister] beat that perception, and shortly thereafter, once he showed it was possible, many other runners were able to achieve this also. The same is being said now about the IBM Watson computer which appeared this week against two human contestants on Jeopardy!
(2014 Update: A lot has happened since I originally wrote this blog post! I intended this as a fun project for college students to work on during their summer break. However, IBM is concerned that some businesses might be led to believe they could simply stand up their own systems based entirely on open source and internally developed code for business use. IBM recommends instead the [IBM InfoSphere BigInsights] which packages much of the software described below. IBM has also launched a new "Watson Group" that has [Wat
Often, when a company demonstrates new techology, these are prototypes not yet ready for commercial deployment until several years later. IBM Watson, however, was made mostly from commercially available hardware, software and information resources. As several have noted, the 1TB of data used to search for answers could fit on a single USB drive that you buy at your local computer store.
But could you fit an entire Watson in your basement? The IBM Power 750 servers used in IBM Watson earned the [EPA Energy Star] rating, and is substantially [more energy-efficient than comparable 4-socket x86, Itanium, or SPARC servers]. However, having ninety of them in your basement would drive up your energy bill.
That got me thinking, would it be possible to build your own question-answering system, something less fancy, less sophisticated, scaled-down for personal use? John Pultorak explained [how to build your own Apollo Guidance Computer (AGC) in your basement]. Jay Shafer explains [how to build your own house for $20K]. And a 17-year-old George Hotz figured out a [hack to unlock your Apple iPhone] over the summer in his basement.
It turns out that much of the inner workings of IBM Watson were written in a series of articles in [IBM Systems Journal, Vol. 43, No. 3]. You can also read the [Wikipedia article]. Eric Brown from IBM Research will be presenting "Jeopardy: Under the Hood of IBM Watson Supercomputer" at next month's [The Linux Foundation End User Summit].
Take a look at the [IBM Research Team] to determine how the project was organized. Let's decide what we need, and what we don't in our version for personal use:
(Disclaimer: As with any Do-It-Yourself (DIY) project, I am not responsible if you are not happy with your version for personal use I am basing the approach on what I read from publicly available sources, and my work in Linux, supercomputers, XIV, and SONAS. For our purposes, this version for personal use is based entirely on commodity hardware, open source software, and publicly available sources of information. Your implementation will certainly not be as fast or as clever as the IBM Watson you saw on television.)
There you have it. By the time you get your implementation fully operational, you will have learned a lot of useful skills, including Linux administration, Ethernet networking, NFS file system configuration, Java programming, UIMA text mining analysis, and MapReduce parallel processing. Hopefully, you will also gain an appreciation for how difficult it was for the IBM Research team to accomplish what they had for the Grand Challenge on Jeopardy! Not surprisingly, IBM Watson is making IBM [as sexy to work for as Apple, Google or Facebook], all of which started their business in a garage or a basement with a system as small as this version for personal use.
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Tonight PBS plans to air Season 38, Episode 6 of NOVA, titled [Smartest Machine On Earth]. Here is an excerpt from the station listing:
"What's so special about human intelligence and will scientists ever build a computer that rivals the flexibility and power of a human brain? In "Artificial Intelligence," NOVA takes viewers inside an IBM lab where a crack team has been working for nearly three years to perfect a machine that can answer any question. The scientists hope their machine will be able to beat expert contestants in one of the USA's most challenging TV quiz shows -- Jeopardy, which has entertained viewers for over four decades. "Artificial Intelligence" presents the exclusive inside story of how the IBM team developed the world's smartest computer from scratch. Now they're racing to finish it for a special Jeopardy airdate in February 2011. They've built an exact replica of the studio at its research lab near New York and invited past champions to compete against the machine, a big black box code -- named Watson after IBM's founder, Thomas J. Watson. But will Watson be able to beat out its human competition?"
Craig Rhinehart offers [10 Things You Need to Know About the Technology Behind Watson].
An artist has come up with this clever [unofficial poster].
Like most supercomputers, Watson runs the Linux operating system. The system runs 2,880 cores (90 IBM Power 750 servers, four sockets each, eight cores per socket) to achieve 80 [TeraFlops]. TeraFlops is the unit of measure for supercomputers, representing a trillion floating point operations. By comparison, Hans Morvec, principal research scientist at the Robotics Institute of Carnegie Mellon University (CMU) estimates that the [human brain is about 100 TeraFlops]. So, in the three seconds that Watson gets to calculate its response, it would have processed 240 trillion operations.
Several readers of my blog have asked for details on the storage aspects of Watson. Basically, it is a modified version of IBM Scale-Out NAS [SONAS] that IBM offers commercially, but running Linux on POWER instead of Linux-x86. System p expansion drawers of SAS 15K RPM 450GB drives, 12 drives each, are dual-connected to two storage nodes, for a total of 21.6TB of raw disk capacity. The storage nodes use IBM's General Parallel File System (GPFS) to provide clustered NFS access to the rest of the system. Each Power 750 has minimal internal storage mostly to hold the Linux operating system and programs.
When Watson is booted up, the 15TB of total RAM are loaded up, and thereafter the DeepQA processing is all done from memory. According to IBM Research, "The actual size of the data (analyzed and indexed text, knowledge bases, etc.) used for candidate answer generation and evidence evaluation is under 1TB." For performance reasons, various subsets of the data are replicated in RAM on different functional groups of cluster nodes. The entire system is self-contained, Watson is NOT going to the internet searching for answers.
On ZDnet, Steven J. Vaughan-Nichols welcomes our new [Linux Penguin Jeopardy overlords]. I have to say I share his enthusiasm!
This week I am in Moscow, Russia for today's "Edge Comes to You" event. Although we had over 20 countries represented at the Edge2012 conference in Orlando, Florida earlier this month, IBM realizes that not everyone can travel to the United States. So, IBM has created the "Edge Comes to You" events where a condensed subset of the agenda is presented. Over the next four months, these events are planned in about two dozen other countries.
This is my first time in Russia, and the weather was very nice. With over 11 million people, Moscow is the 6th largest city in the world, and boasts having the largest community of billionaires. With this trip, I have now been to all five of the so-called BRICK countries (Brazil, Russia, India, China and Korea) in the past five years!
The venue was the [Info Space Transtvo Conference Center] not far from the Kremlin. While Barack Obama was making friends with Vladimir Putin this week at the G2012 Summit in Mexico, I was making friends with the lovely ladies at the check-in counter.
If it looks like some of the letters are backwards, that is not an illusion. The Russian language uses the [Cyrillic alphabet]. The backwards N ("И"), backwards R ("Я"), the number 3 ("З), and what looks like the big blue staple logo from Netapp ("П"), are actually all characters in this alphabet.
Having spent eight years in a fraternity during college, I found these not much different from the Greek alphabet. Once you learn how to pronounce each of the 33 characters, you can get by quite nicely in Moscow. I successfully navigated my way through Moscow's famous subway system, and ordered food on restaurant menus.
The conference coordinators were Tatiana Eltekova (left) and Natalia Grebenshchikova (right). Business is booming in Russia, and IBM just opened ten new branch offices throughout the country this month. So these two ladies in the marketing department have been quite busy lately.
I especially liked all the attention to detail. For example, the signage was crisp and clean, and the graphics all matched the Powerpoint charts of each presentation.
Moscow is close to the North pole, similar in latitude as Juneau, Alaska; Edinburgh, Scottland; Copenhagen, Denmark; and Stockholm, Sweden.
As a result, it is daylight for nearly 18 hours a day. The first part of the day, from 8:00am to 4:30pm, was "Technical Edge", a condensed version of the 4.5 day event in Orlando, Florida. I gave three of the five keynote presentations:
(Note: I do not speak Russian fluently enough to give a technical presentation, so I did then entire presentation in English, and had real-time translators convert to Russian for me. The audience wore headphones. However, I was able to sprinkly a few Russian phrases, such as "доброе утро", "Я не понимаю по-русский" and "спасибо".)
After the keynote sessions, I was interviewed by a journalist for [Storage News] magazine. The questions covered a variety of topics, from the implications of [Big Data analytics] to the future of storage devices that employ [Phase Change Memory]. I look forward to reading the article when it gets published!
The afternoon had break-out sessions in three separate rooms. Each room hosted seven topics, giving the attendees plenty to choose from for each time slot. I presented one of these break-out sessions, Big Data Cloud Storage Technology Comparison. The title was already printed in all the agendas, so we went with it, but I would have rather called it "Big Data Storage Options". In this session, I explained Hadoop, InfoSphere BigInsights, internal and external storage options.
I spent some time comparing Hadoop File System (HDFS) with IBM's own General Parallel File System (GPFS) which now offers Hadoop interfaces in a Shared-Nothing Cluster (SNC) configuration. IBM GPFS is about twice as fast as HDFS for typical workloads.
At the end of the Technical Edge event, there was a prize draw. Business cards were drawn at random, and three lucky attendees won a complete four-volume set of my book series "Inside System Storage"! Sadly, these got held up in customs, so we provided a "certificate" to redeem them for the books when they arrive to the IBM office.
The second part of the day, from 5:00pm to 8pm, was "Executive Edge", a condensed version of the 2 day event in Orlando, designed for CIOs and IT leaders. Having this event in the evening allowed busy executives to come over after they spend the day in the office. I presented IBM Storage Strategy in the Smarter Computing Era, similar to my presentation in Orlando.
Both events were well-attended. Despite fighting jet lag across 11 time zones, I managed to hang in there for the entire day. I got great feedback and comments from the attendees. I look forward to hearing how the other "Edge Comes to You" events fare in the other countries. I would like to thank Tatiana and Natalia for their excellent work organizing and running this event!
technorati tags: IBM, Moscow, Russia, Edge, ECTY, Cyrillic, Tatiana Eltekova, Natalia Grebenshchikova, Smarter Storage, Smarter Computing, Smarter Planet, Big Data, Cloud, IBM Watson, Jeopardy, Hadoop, HDFS, InfoSphere, BigInsights, GPFS, GPFS-SNC
Last February, IBM introduced Watson on the Jeopardy! game show. These three shows were re-aired this week in the United States. I wrote a series of blog posts back then:
This last one on how to build your own Watson, Jr. has gotten over 69,000 hits! While several people told me they plan to build their own, I have not heard back from anyone yet, so perhaps it is taking longer than expected.
IBM and Wellpoint announced this week that it will be [putting Watson to work] in healthcare. [Wellpoint] is one of the largest health benefits company in the United States, with over 70 million people served through its affiliate plans and its various subsidiaries. I am one of the development lab advocates for Wellpoint, and have been proud to work with the account team to help Wellpoint achieve their goals.
This marks the first commercial deployment of IBM Watson. This is a joint effort. IBM will develop the base IBM Watson for healthcare platform, and Wellpoint will then develop healthcare-specific solutions to run on this platform. Watson's ability to analyze the meaning and context of human language, and quickly process vast amounts of information to suggest options targeted to a patient's circumstances, can assist decision makers, such as physicians and nurses, in identifying the most likely diagnosis and treatment options for their patients.
Is this going to put doctors out of business? No. Physicians find it challenging to read and understand hundreds or thousands of pages of text, and put this into their practice. IBM Watson, on the other hand, can scan through hundred of millions of pages in just a few seconds to help answer a question or provide recommendations. Together, doctors armed with access to IBM Watson will be able to improve the quality and effectiveness of medical care.
From an insurance point of view, improving the quality of care will help reduce medical mistakes and malpractice lawsuits. This is a win-win for everyone except ambulance-chasing lawyers!
The IBM Challenge was a big success. One of the contestants, Ken Jennings, [welcomes our new computer overlords]. Congratulations are in order to the IBM Research team who pulled off this Herculean effort!
Some folks have poked fun at some of the odd responses and wager amounts from the IBM Watson computer during the three-day tournament. Others were surprised as I was that the impressive feat was done with less than 1TB of stored data. Here is what John Webster wrote in CNET yesterday, in hist article [What IBM's Watson says to storage systems developers]:
"All well and good. But here's what I find most interesting as a result of what IBM has done in response to the Grand Challenge that motivated Watson's creators. We know, from Tony Pearson's blog, that the foundation of Watson's data storage system is a modified IBM SONAS cluster with a total of 21.6TB of raw capacity. But Pearson also reveals another very significant, and to me, surprising data point: "When Watson is booted up, the 15TB of total RAM are loaded up, and thereafter the DeepQA processing is all done from memory. According to IBM Research, the actual size of the data (analyzed and indexed text, knowledge bases, etc.) used for candidate answer generation and evidence evaluation is under 1 Terabyte."
To better appreciate how difficult the challenge was, and how a small amount of data can answer a billion different questions, I thought I would cover Business Intelligence, Data Retrieval and Text Mining concepts.
"In this paper, business is a collection of activities carried on for whatever purpose, be it science, technology, commerce, industry, law, government, defense, et cetera. The communication facility serving the conduct of a business (in the broad sense) may be referred to as an intelligence system. The notion of intelligence is also defined here, in a more general sense, as the ability to apprehend the interrelationships of presented facts in such a way as to guide action towards a desired goal."
Ideally, when you need "Business Intelligence" to help you make a better decision, you perform data retrieval from a structured database for the specific information you are looking for. In other cases, you might be looking for insight, patterns or trends. In that case, you go "data mining" against your structured databases.
And that's not including more ethereal questions, such as:
This is just for a small set, two market segments (by gender) and two products (apples and oranges). However, if you have many market segments (perhaps by age group, zip code, etc.) and many products, the number of queries that can be supported is huge. For small sets of data, you can easily do this with a spreadsheet program like IBM Lotus Symphony or Microsoft Excel.
Second, you had to be skilled at SQL to phrase your queries correctly to retrieve the data you are after. What ended up happening was that skilled SQL programmers would develop "canned reports" with fixed SQL parameters, so that less-skilled business decision makers could base their decisions from these reports.
IBM has fully integrated stacks to help process structured data, combining servers, storage, and advanced analytics software into a complete appliance. IBM offers the [Smart Analytics System] for robust, customized deployments, and recently acquired [Netezza] for pre-configured, and more rapid deployments.
However, the bigger problem is that more than 80 percent of information is not structured! Semi-structured data like email provides some searchable fields like From and Subject. The rest of the information is unstructured, such as text files, photographs, video and audio. To look for specific information in unstructured sources can be like looking for a needle in a haystack, and trying to get insight, patterns or trends involves text mining.
IBM is a leader in Business Analytics and has made great progress in dealing with unstructured data. This includes [IBM OmniFind Enterprise Edition], [IBM e-Discovery Manager] and [IBM Cognos Business Intelligence].
This, in effect, is what IBM Watson was able to perform so well this week. Finding the needle in the haystacks of unstructured data from 200 million pages of text stored in its system, combined with the ability to apprehend the interrelationships of meaning and subtle nuance, resulted in an impressive technology demonstration. Certainly, this new technology will be powerful for a variety of use cases across a broad set of industries!
To learn more, read the Arizona Daily Star's article [After 'Jeopardy!' win, IBM program steps out].