Tony Pearson is a Master Inventor and Senior IT Architect for the IBM Storage product line at the
IBM Executive Briefing Center in Tucson Arizona, and featured contributor
to IBM's developerWorks. In 2016, Tony celebrates his 30th year anniversary with IBM Storage. He is
author of the Inside System Storage series of books. This blog is for the open exchange of ideas relating to storage and storage networking hardware, software and services.
(Short URL for this blog: ibm.co/Pearson )
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We are only days away from the big IBM Challenge of Watson computer against two human contestants on the show Jeopardy!
I watched two episodes of Jeopardy! on my Tivo, pausing it to follow the [homework assignment] I suggested in my last post. Here are my own results and observations.
Episode  involved a web programmer, a customer service representative, and a bank teller.
Of the first six categories in Round 1, I guessed four of the six themes for each category. For the category "Diamonds are Forever", I wrote down "All answers are some kind of gem or mineral", but the reality was that all the answers were some physical characteristic of diamonds specifically. For the category "...Fame is not", I wrote down "All answers are TV or Movie celebrities". I was close, but actually it was famous celebrities, rock bands and pop culture of the 1980s. (The movie "Fame" came out in 1980).
In the round, there were 27 of the 30 answers given before they ran out of time. Of these, I was able to get 24 of 27 correct by searching the Internet. That is 88 percent correct. Here were the ones that eluded me:
Answer related to a "multi-chambered mollusk". I could not find anything on the Internet definitively on this, so abstained from wager. The correct question was "What is Nautilus?".
Answer was the Irish variant of "Kathryne". I found Kathleen as a variant, but did not investigate if it had Irish origins. The correct question was "What is Caitlin?"
Answer was this Norse name for "ruler" whether you had red hair or not. I found "Roy" and "Rory" so guessed "What is Rory?" The correct question was "What is Eric?"
The second round, I guesed three of the six themese for the categories. For category "Musical Titles Letter Drop" I wrote down "All the answers are titles of musical songs" but it was actually "Musicals" as in the Broadway shows. For category "Place called Carson", I wrote down "All the answers are places" and was way off on that one, with answers that were people, places and names of corporations. And for "State University Alums", I wrote down "All the answers are college graduates", but instead they were all "State Universities" such as the University of Arizona.
In this second round, only 26 answers were posed. I got 80 percent correct with Internet searching. I missed three on the "Musical Titles", one in "Pope-pourri" and one State University (sorry SMU). The "Musical Titles Letter Drop category" was especially difficult, as for each title of a Musical, you had to remove a single letter out of it to form the correct response.
For the answer "Good luck when you ask the singers "What I Did For Love"; they never tell the truth", you would need to take "Chorus Line" the musical, where the song "What I did for Love" appears, and ask "What is Chorus Lie?" Note that "line" changed to "lie" and the letter "n" was dropped out.
For the answer "Embrace the atoms as Simba and company lose and gain electrons en masse in this production", you would need to recognize that Simba was the main character of "The Lion King" and change it to "What is The Ion King".
I think these play-on-words are the questions that would stump the IBM Watson computer.
In the final round, the category was "Ancient Quotes". I thought the answer would be a famous adage or quotation, but it was instead famous people who uttered those phrases. The answer was "He said, to leave this stream uncrossed will breed manifold distress for me; to cross it, for all mankind". I was able to determine the correct response readily from searching the Internet: The river was the Rubicon, the border of the Gaul region governed by an ambitious general. The correct response "Who was Julius Caesar?"
Total time for the entire exercise: 87 minutes.
The following night, episode  brought back Paul Wampler, the returning champion web programmer, against two new contestants: an actor, and high school principal.
Of the first six categories in Round 1, I guessed five of the six themes for each category. For the category "Nonce Words", I wrote all the answers would be nonsense words. I was close, the clues had words invented for a particular occasion, but the correct responses did not.
I was able to get 29 of 30 correct by searching the Internet. That is 96 percent correct. The one I missed was in the category "Nonce Words" and the answer was "In an arithmocracy, this portion of the population rules, not trigonometry teachers.." My response was "What is Math?" but the correct answer was "What are the majority?" It did not occur for me to even look up [Arithmocracy] as a legitimate word, but it is real.
The second round, I guesed five of the six themese for the categories. For category "Hawk" eyes, the "Hawk" was in quotation marks, so I wrote "All answers would start with the word Hawk or end with the word "eyes". I was close, the correct theme was that the word "hawk" would appear in the front, middle or end of the correct response.
In this second round, I got 28 of 30 correct. I got 93 percent correct with Internet searching. Ironically, it was the category "German Foods" that caught me off guard.
For, the answer was "Pichelsteiner Fleisch, a favorite of Otto von Bismarck, is this one-pot concoction, made with beef & pork". I know that "fleisch" is a German word for meat, so I guessed "What is sausage?" but the correct response was "What is stew?" I should have paid more attention to the "one-pot concoction" part of the answer.
For the answer was "Mimi Sheraton says German stuffed hard-boiled eggs are always made with a great deal of this creamy product". I didn't realize that "stuffed eggs" was German for "deviled eggs". Instead, I found Mimi Sheraton's "The German Cookbook" on Google Books, and jumped to the page for "Stuffed Eggs" The ingredients I read included whippedc cream, cognac, and worcestershire sauce. Taking the "creamiest" ingredient of these, I wrote down "What is whipped cream?" However, it turned out I was actually reading the ingredients for "Crabmeat Cocktail" that was coninuing from the previous page. I thought it was gross to put whipped cream with eggs, and should have known better. The correct response was "What is mayonnaise?"
In the final round, the category was "Political Parties". This could either be political organizations like Republicans and Democrats, or festivities like the Whitehouse Correspondents Dinner. The answer was "Only one U.S. president represented this party, and he said, I dread...a division of the republic into two great parties." So, we can figure out the answer refers to political organizations, but both Democrat and Republican are ruled out because each has had multiple presidents. So, looking at a [List of Political Parties of each US President], I found that there were four presidents in the Whig party, four in the Democrat-Republic party, but only one president in the Federalist party (John Adams), and one in the War Union party (Andrew Johnson). Looking at [famous quotes from John Adams] first, I found the quote, it matched, and so I wrote down "What is the Federalist party?". I got it right, as did two of the three contestants. Ironically, the one contestant who got it wrong, the returning champion web programmer, wagered a small amount, so he still had more money after the round and won the game overall.
Total time for the entire exercise: 75 minutes. I was able to do this faster as I skipped searching the internet for the responses I was confident on.
To find out when Jeopardy is playing in your town, consult the [Interactive Map].
With all the excitement of the [IBM Challenge], where the [IBM Watson computer] will compete against humans on [Jeopardy!], I thought it would be good to provide the following homework exercise to help you appreciate how challenging the game is and the strategies required.
Overview of the game of Jeopardy!
If you are familiar with the show, you can safely skip this section.
Known as "America's Favorite Quiz Show", the Jeopardy pits three contestants against each other. The board is divided into six columns and five rows of answers. Each column indicates the category for that column of answers. The rows are ranked from easiest to most difficult, with more difficult answers being worth more money to wager.
The contestants take turns. The returning champion gets to select a spot on the board, by indicating the category (column) and wager (row), such as "I will take Animals for 800 dollars!" Contestants must then press a button to "buzz in", be recognized by the host, and respond correctly. If the contestant responds incorrectly, the other two contestants have the opportunity to respond. The contestant with the correct response gets to chose the next answer.
For each turn, the host, Alex Trebek, shows the answer on the board, and spends three seconds reading it aloud to give everyone a chance to come up with a corresponding question. This is perhaps what Jeopardy is most famous for. In a traditional "Quiz Show", the host asks questions, and the contestants answer that question. On Jeopardy, however, the host poses "answers", and the contestants provide their response in the form of a "questions" that best fit the category and answer clues. For example, if the categories were "Large Corporations" and the answer was "Sam Palmisano", the contestant would answer "Who is the CEO of IBM Corporation?" Both the categories, and the answers are filled with puns, slang and humor to make it more challenging. Often, the answer itself is not sufficient clue, you have to factor in the category as well to have a complete set of information.
The game is played in three rounds:
In the first round, there are six categories, and the rows are worth $200, $400, $600, $800 and $1000 dollars. If you respond correctly on all five answers in a category column, you would win $3000. If you respond to all thirty answers correctly, you would earn $18,000.
In the second round, there are six different categories, and the rows are worth twice as much.
The final round has a single category and a single question. Each player can decide to wager up to the full amount of their score in this game. This wager is done after they see the category, but before they see the answer.
After the host finishes reading the answer aloud, the buzzers are lighted so that the contestants can buzz in. If a contestant gets the question correctly, he earns the corresponding money for the row it was in. If the contestant guesses incorrectly, the money is subtracted from his score. If the first contestant fails, the buzzers are re-lit so the other two contestants can then buzz in with their answers, learning from previous failed attempts.
To provide added challenge, some of the answers are surprise "Daily Double". Instead of the dollar amount for the row, the contestant can wager any amount, up to their total score they have won so far in that game, or the largest dollar amount for that round, whichever is higher, based on his confidence in that category. There is one "Daily Double" surprise in the first round, and two in the second round.
In the final round, each contestant wagers an amount up to their total score, based on their confidence on the final category. A common strategy for the leading contestant with the highest score is to wager a low amount, so that if he fails to guess the response correctly, he will still have a large dollar amount. For example, if the leader has $2000 and the second place is $900, the leader can wager only $100 dollars, and the second place might wager his full $900. If the leader loses the round, he still has $1900, beating the second place regardless of how well he does.
Whomever has the most money at the end of all three rounds wins that amount of cash, and gets to return to the show for another game the next day to continue his winning streak. The other two contestants are given consolation prizes and a nominal appearance fee for being on the show, and are never seen from again.
The show is only 30 minutes long, so the folks at Sony Pictures who produce the show can film a full weeks' worth of television shows in just two days of real-life, Tuesday and Wednesday, allowing the host Alex Trebek and his "Clue Crew" time to research new categories and answers.
So, here is your homework assignment. Record a full episode of Jeopardy on your VCR or Digital Video Recorder (DVR) and have your thumb ready to press the pause button. For each round, listen to each category, pause, and try to guess what all the answers in that column will have in common. For each category, write down a statement like "All the responses in this category are ...".
The answers could be people, places or things. Suppose the category "Chicks Dig Me". In English, "chicks" can be slang for women, or refer to young chickens. The term "dig" can be slang for admires or adores, so this could be "Male Celebrities" that women find attractive, it could be objects of desire that women fancy (diamonds, puppies, etc.), or it could be places that women like to go to. As it turns out, the "dig" referred to archaeology, and the responses were all famous female archaeologists.
Once you have those all your statements written down, press play button again.
Next, as each answer is shown, you have three seconds to hit the pause again, so that you have the question on the screen, but before any contestants have responded. Go on your favorite search engine like Google or Bing and try to determine the correct response based on the category and answer. Consider these [tips for being an Internet Search ninja]. Once you think you have figured out your response, write it down, and the dollar amount you wager, or decide you will not respond for that answer, if you are not sure about your findings.
Even if you think you already know the correct response, you may decide to gain more confidence of your response by finding confirming or supporting evidence on the Internet.
Press play. Either one of the contestants will get it right, or the host will provide the question that was expected as the correct response.
How well did you do? Were you able to find on the the correct response online, or at least confirm that what you knew was correct. If you got it correct, add in your dollar amount to your score. If you got it wrong, subtract the amount.
At the end of each round, look back at your statements for each category. Did you guess correctly the common theme for each category column of answers? Did you misinterpret the slang, pun or humor intended?
At the end of the game, you might have done better than the contestant that won the game. However, check how much added time you took to do those Internet searches. The average winner only questions half of the answers and only gets 80 percent of them correctly.
If you are really brave, take the [Jeopardy Online Test]. If you do this homework assignment, feel free to post your insights in the comments below.
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!
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:
Game Change on a Smarter Planet: A New Era in IT, discussing Smarter Computing and Expert-Integrated systems, based on what Rod Adkins presented in Orlando.
A New Approach to Storage, explaining IBM Smarter Storage for Smarter Computing, IBM's new approach to the way storage is designed and deployed for our clients
IBM Watson: How it Works and What it Means for Society Beyond Winning Jeopardy! explaining how IBM Watson technologies are being used in Healthcare and Financial Services, based on what I presented in Orlando.
(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!
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."
What Pearson just said is that the data set Watson actually uses to reach his push-the-button decision would fit on a 1TB drive. So much for big data?"
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.
Here's a simple example. John runs a fruit stand. One day, he kept track of how many apples and oranges were bought by men and women. How many questions can we ask against this small set of data? Let's count them:
How many apples were sold to men?
How many apples were sold to women?
How many oranges were sold to men?
How many oranges were sold to women?
But wait! For each row and column, we can combine them into totals.
How many apples were sold in total?
How many oranges were sold in total?
How many fruit in total were sold to men?
How many fruit in total were sold to women?
How many fruit in total were sold?
But wait, there's more! Each row and column can be evaluated for relative percentages, as well as percentages of each cell compared to the total. You could make five relevant pie-charts from this data. This results in 16 more questions, such as:
Of the fruit purchased by men, what percentage for apples?
Of all the apples purchased, what percentage by women?
And that's not including more ethereal questions, such as:
Are there gender-specific preferences for different types of fruit?
What type of fruit do men prefer?
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.
But why limit yourself to two dimensions? The above example was just for one day's worth of activity, if John captures this data for every day for historical and seasonal trending, it can be represented as a three-dimensional cube. The number of queries becomes astronomical. This is the basis for Online Analytical Processing (OLAP), and three-dimensional tables are often referred to as [OLAP cubes].
Back in 1970, IBM invented the Structured Query Language [SQL], and today, nearly all modern relational databases support this, including IBM DB2, Informix, Microsoft SQL Server, and Oracle DB. SQL poses two challenges. First, you had to structure the data in advance to the way you expect to perform your ad-hoc queries. Deciding the groups and categories in advance can limit the way information is recorded and captured.
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.
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!