When I was young, I dreamt of becoming a physicist, but I very quickly discovered that I did not have the mathematical literacy required for that particular career choice.
(In retrospect, perhaps I should have just dug my heels in and persisted with it)
Well, if I cannot do the mathematics myself, I thought, perhaps I can program a computer to help me? This thought lead, eventually, to my doing an undergraduate degree in Artificial Intelligence.
It was during this course that I began to think of reasoning as a process driven predominantly by knowledge, and about the problem of acquiring the vast amounts of knowledge that would so obviously be required to do any sort of useful reasoning in the real world.
I was particularly taken by the potential for machine vision systems to help build knowledge bases such as these, and so I developed an enduring interest in machine vision (and statistical pattern recognition more generally).
In my early career, I was fortunate enough to work with scientists studying human perception, which built up my nascent interest in perceptual processes; a filter through which I still percieve many technical problems.
It has become clear, however, that the main barrier standing in the way of developing sophisticated software systems that can reason about the world and help us to understand our universe is the paucity and limited capability of the software development tools that we have at our disposal.
The latter half of my career has therefore largely turned towards improving the software tools available to the academics, scientists and engineers that I have been priviledged to work with over the years.
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