I came across this article about Manjul Bhargava, a Princeton professor who was recently awarded the Fields Medal, considered the Nobel Prize of mathematics. What sets him apart from most mathematicians is not just the fact the he improved on Gauss (!) in an old branch of mathematics, number theory, but his passion for explaining his work clearly to the not-so-mathematically minded. It was this paragraph, though, that caught my eye as a patent practitioner:
Elegance and simplicity are two of the highest goals of all mathematical expression. “A not-so-elegant proof would be like a corn maze, where you can’t see where you’re going,” explains Wood. “An elegant proof is like a road where you can see where you’re going.” Ng says: “When he explains his work to you, it seems like it’s obvious. And you think, ‘Oh well, there can’t be much to it because it’s so obvious.’ Then you realize that it’s actually very profound. There are problems that people have been working on for hundreds of years and have made no progress. Manjul somehow managed to see something no one else could.”
One the things that has bothered me almost since my first day in this profession is the unwillingness of many examiners to recognize the failure of others as evidence of non-obviousness. I routinely have to tell clients (with a sigh) that the fact that no one before them solved the particular problem they've solved, let alone in the particular way they've solved it, is often insufficient to overcome an obviousness rejection. Sure, examiners (and judges) aren't supposed to use hindsight in view of the invention itself, but when you present an elegant solution to a problem, you're sometimes inviting the assertion by lesser lights that your solution was obvious.
And according to recent US court decisions, if you're working in the area of algorithms, then you must be working with an abstract area or preempting someone else's research or something like that, so your invention shouldn't even be eligible for patenting. Because, you know, you're just a Fields Medal winner, whose work has broad application to many number theory problems.