The news that IBM’s Watson had beaten the humans on Jeopardy didn’t really come as a really big surprise for me. It’d been coming since Kasparov left the room in tears after losing to Deep Blue.
The argument then was that chess is about finite number of possible moves. The use of intensive mathematics, brutal processing logic and speed make chess a well defined challenge – computers were appropriately designed for such a challenge. However, natural language is very different. Modeling natural language mathematically is very challenging, and at the time (of deep blue vs. Kasparov), even natural language processing researchers admitted we were many years yet before computers would understand queries and respond to them in human language. I’ve banged on about intelligent personal learning agents based on semantic technologies in the past, and Watson – a ‘natural language processing’ ‘pattern recognizing’ ‘world aware’ engine – is a huge step towards making that happen.
Just before I went on holiday recently I was asked how human learning has changed with the advent, penetration and increasing ubiquity of computing technology.
