From: Eliezer S. Yudkowsky (sentience@pobox.com)
Date: Sat May 11 2002 - 10:07:32 MDT
Ben Goertzel wrote:
>
> A relatively simple pattern in a yeast gene expression dataset, with a
> fairly clear human meaning, is then:
>
> ----
> C = ( LOW(SIC1) OR MOD_LOW(SIC1) ) AND ( LOW(PCL2) ) AND (LOW(CLN3)) OR
> (MOD_LOW(CLN3) )
>
> D = "involved in transcriptional regulation of CUP1"
>
> C AND EXTR_HIGH( SWI5) -->
> DECREASE(SWI5) AND INCREASE(D)
>
> C AND (MOD_HIGH(SWI5) OR HIGH(SWI5)) -->
> INCREASE(SWI5) AND INCREASE(D)
> ----
>
> This is classic "data mining" -- the system is thrown a bunch of data and
> looks for interesting patterns. It happens to be a datamining problem that
> has proved unsolvable for traditional datamining methods however, in spite
> of several years' effort. (Only several years because gene expression data
> only recently became available due to the recent invention of gene chips &
> spotted microarrays.)
Okay, thanks; that does help. Next question: What is it about Novamente
that makes this problem space more tractable for Novamente than for
traditional applications? Is there any way you can describe this in human
terms?
Does Novamente learn which variables are worth paying attention to, then
perform correlation on those variables instead of all variables in the
problem space? Does Novamente try to notice certain classes of correlations
that data-mining algorithms don't notice because they're not directly
useful, then use these useless correlations to spread attention and thereby
find a dataset among which there are likely to be useful correlations? Has
Novamente learned heuristics that enable it to connect locally visible
properties of a variable to its probability of distant entanglement? Or
does Novamente notice correlations in such a way that the intermediate steps
not only have no humanly comprehensible semantics on a case-by-case basis,
but also in such a way that there is no known explanation for what the
intermediate steps are, in general, doing?
-- -- -- -- --
Eliezer S. Yudkowsky http://intelligence.org/
Research Fellow, Singularity Institute for Artificial Intelligence
This archive was generated by hypermail 2.1.5 : Wed Jul 17 2013 - 04:00:38 MDT