It might be more immediately accelerating to take a somewhat
different tack. In many fields there is research in the labs that is
missing some number of key components, sometimes breakthroughs, in
the same field or others before it can go to next level or be turned
into more broadly accessible technology. For actually turning it to
technology many other factors are also relevant such as availability
of capital, existing and/or likely demand or appeal of the
technology, manufacturability and so on. It seems to me that the
right sort of software could enable researches and technologist to
note these critical missing pieces and factors. Software agents, in
part guided by humans, could scour the world's news and literature
for the missing bits that might enable the next breakthrough or new
technology. On the face of this seems like a more tractable task.
I heard some time back about software research assistants for
scanning the literature of a field for possibly relevant
developments. If anyone has links to such I would love to look into
them.
- samantha
On May 22, 2007, at 7:49 AM, Bruce Bautista wrote:
Hello Mark,
I too have contemplated the idea you are interested in. I believe
it is a sound approach to accelerating the knowledge in many
fields. I do not know of any programs that have been done or are in
progress along these lines. The power of having such a 'knowledge
base' at anyone's disposal would ultimately reduce the global work
force in half to say the least. I will do some research on this
idea and get back to you.
Bruce Bautista
On 5/18/07, Mark H. Herman <[EMAIL PROTECTED]> wrote:
I imagine the following may have already been considered,
nevertheless: It would seem constructive to undertake an
analysis of breakthroughs in various fields (e.g. engineering,
art, chemistry) to search for patterns that might be
replicable. A general example of what I mean by a "pattern"
would be, "thesis, antithesis, synthesis." Examples of
patterns that such an analysis might uncover could include
patterns of formal logic, the novel application in one field of
a structure established in another field, the retrieval of
insights from historical theories or practices that were once
competitive, but were found inadequate and long forgotten,
etc. An analysis of such patterns and the identification of
meta-patterns would seem to require broad familiarity with the
various disciplines in which the breakthroughs occurred;
however, the work of identifying the patterns of specific
breakthroughs, which might require extensive and deep knowledge
in the respective fields, could be divided amongst various
experts of various fields. Perhaps something like this would
be worth adding to the agenda of the AI Impact Initiative or
some similar interdisciplinary body.
-Mark
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