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Automating Invention is Robert Plotkin's blog on the impact of computer-automated inventing on the future of invention and patent law.
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July 19, 2005
Shift seen from human coding to machine learning in the face of uncertainty
ComputerWeekly.com reports on the use of machine learning, instead of human-written algorithms, by Microsoft Research Cambridge (MRC) to solve problems in domains such as handwriting recognition. The reason, according to Christopher Bishop, MRC's Assistant Director, is that:
It is impossible to write an algorithm for recognising handwriting; many have tried but all have failed. There are too many differences even in the writing of one person to be able to write a set of rules or algorithm.
. . .
With handwriting recognition, for example, we do not try to program a solution; we give the computer lots of examples of handwriting, along with the text, and the machine learns to match the electronic image to the text.
The preceding quotes are taken from Bishop's British Computer Society Lovelace Lecture. A report of and slides from the lecture may be found here.
Much of the legal scholarship on intellectual property protection for software has focused on protection for "algorithms." In fact, many scholarly treatments have used the terms "software" and "algorithms" interchangeably. Developments such as those described by Bishop make clear that the subject matter of computer science is not limited to algorithms. The legal profession needs to wake up to this difference between the law's conception of computer science and the way that computer science works in the real world.
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