When initially proposed string theory was thought to be preposterous, apart from the mathematical beauty there was nothing so beautiful about being associated with it. Getting associated with it was at that time a career suicide. String theory was not only suggesting some radically different picture of reality, for it to work it suggested that there are far more than 4 dimensions (3 spetial and temporal). Their prediction was varying so much (from 26 at one time to 11 at another) that the theorists were regularly made fun off. John Henry Schwarz who is considered to be the father of string theory was said to be often ridiculed by Richard Feynman. Feynman playfully used to ask him - “Hey Schwarz, how many dimensions are you in today?". Though today string theory has evolved to be one of the possible theories that may give a unified picture of physics and is taken quite seriously by physicists.

As a researcher my involvement with dimensions is quite different. Working in the field of machine learning I often work on very high dimensional data; sometimes as high as million dimensional spaces. When working on such high dimensions one of the problem that affects us the most - is the curse of dimensionality. Simply stated with the increase of number of dimensions the volume of the space explodes exponentially. So when one wants to learn pattern from data in high dimensions no matter how much data you have it always seems less! A high dimensional space is always almost empty...

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