Does anyone really like searching for stuff? It conjures up images of looking through old boxes in the attic to find that one thing you can never seem to lay your hands on. Recently, I went looking for my junior high school yearbook when someone “friended” me on FaceBook and I couldn’t remember them. The experience was exasperating. I looked through at least 20 boxes of stuff, started sneezing from the dust, and never found the darn yearbook. As a result, I am still not sure I was actually in the same science class as this person. The experience reminded me of today’s enterprise search limitations. I blogged about this recently as part of my Top 10 Pet Peeves for 2010.
If you think about it … no one actually likes the searching part. It’s no fun nor is it intuitive. You have figure out a “query” or “search string” and hope for the best. Maybe you’ll get lucky and maybe not. It’s what I call the “search and hope” model and it can be even more frustrating then my attic experience (I feel a sneeze coming on).
In an AIIM Industry Watch Survey earlier this year, one of the key findings was 72% of the people surveyed say it’s harder, or much harder, to find information and documents held on their own internal systems compared to the Web. That makes you scratch your head for sure.
In the end, no one “wants” to search anyway … it’s the thing we seek that we care about, and not the searching process. All I wanted was an answer to my question, which was to see if I could remember this former classmate.
IBM has been working at systems to find answers since the 1950s when the first steps were taken with research on machine based learning. Over 50+ years (and many millions later), we have history being made. An IBM computing system (Watson) will play Jeopardy! live on television against Ken Jennings and Brad Rutter, the two all-time most successful contestants, in a series of battles to be aired February 14-16. The series will feature two matches to see if a machine can compete by interpreting real-language questions, in the Jeopardy! format, by using text analysis (natural language processing), automated classification and other technologies to find the correct answers. Here is a brief overview to Watson.
Watson must find the answers in the same timeframe as the two former champs by processing and understanding the question, researching the possible answers, determining the response and answering quicker than the two former champs … plus it has to be right. WOW!
Jeopardy! is the No. 1-rated quiz show in syndication, with more than 9 million daily viewers. Watson has already passed the test that Jeopardy! contestants take to make it on the show and been has warming up by competing against other former Jeopardy! players. The top prize for the contest is $1 million, $300,000 for second and $200,000 for third. Jennings and Rutter plan to donate half their winnings to charity. IBM will donate all winnings to charity.
I can’t wait to see this. I suspect my fascination has to do with my being involved with content analytics as part of my job at IBM. Or maybe it’s just about the coolest thing ever.
Either way, finding answers sure beats searching and hoping … and this ought to be very very interesting.
Here is a deeper explanation of the DeepQA techology behind Watson for those who are as fascinated by this as I am.