The machine is "learning the way a child learns", he says -- by reading and by asking and answering questions of human experts -- in restricted fields of medical and financial knowledge. The field chosen initially in medicine is breast and colon cancer.

Watson represents an attempt to imitate patterns of human thought and learning in hardware, software and stored information; something Saxena sees as a significant third thread of computer development.

First we had mechanical comptometers that performed only a restricted range of operations built into them, he says.

These were succeeded by programmable computers. The emerging generation of computers, Saxena says, will function like Watson does. However he acknowledges the emerging generation will not replace present-day computers as these replaced the comptometers; there will always be a role for computers programmed to perform particular tasks, he says.

There is little programming in the conventional sense involved in Watson, he says; beyond basic skeletons for the representation and interlinking of data and metadata, its ability to arrive at answers in human domains depends on a lot of reading -- 7 million pages on cancer alone, plus much more on general knowledge and general medical terminology -- and exchange of questions and answers with domain experts - in the medical case from the Memorial Sloan Kettering Cancer Center (www.mskcc.org) in New York.