Kurzweilai is a site about accelerating intelligence. It
aims to attain the so-called technological singularity, which will enable
mankind to transcend its nature, via an "intelligence explosion". In
other words the last invention man needs to make is an artificial intelligence
that can improve itself limitlessly.
As a patent examiner I have had ideas about producing this
ultimate invention with a slightly different accent. I call this ultimate invention
the meta-invention. It is an invention which generates inventions.
Patent examiners evaluate claims (drafted by patent
attorneys), which are basically abstracted ontological descriptions delimiting
the scope of the invention.
This evaluation process first of all entails assessing
novelty by establishing if similar inventions have any differences. If so, the
next step is the assessment of inventive step, obviousness, which (in Europe) is done via a set of rules called the
problem-solution-approach.
I have had the idea to modify this analysis protocol and
turn it into an active invention generator. This requires some (dry) explanation:
Usually the difference over the closest state of the art is
analysed and it is evaluated if this difference entails a technical effect. If
so the problem to be solved is in the most general sense formulated as
"how to modify invention X in such a way as to obtain effect Y".
If there are documents Z from the same or neighbouring technical
fields where this effect has been obtained with a similar yet more different
invention(s) Z and if there is a pointer encouraging to use this solution
whenever the associated type of problem to obtain effect Y is present, then it
is concluded that it was obvious to incorporate this solution in invention X.
If you put an important part of this in algorithm form for
an AIbot that searches to improve inventions, you create an invention generator
(as well as a semantics generator).
The AIbot starts with a given invention X. It searches for
problems arising in this type of invention in terms of suboptimal effects,
results. Then it starts looking for improved versions of this effect in the
same or neighbouring technical fields, in different inventions aiming for a
similar purpose.
It evaluates the differences between the documents Z found
and Y. The most promising document will be the one which is structurally the
most similar. If the effect in Z is attributable to certain elements Q missing
from X, it will try to modify X so as to incorporate Q.
...
More of this chapter in my next book, which I have submitted for publication.
More of this chapter in my next book, which I have submitted for publication.
Guess what, they actually start to implement something like my idea above: https://www.newscientist.com/article/2084755-computer-generates-all-possible-ideas-to-beat-patent-trolls/
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