Great website link, Thanks. (01)
Ps: I really enjoy your mailing list. (02)
Matt M. Kaufman
Sent from my iPhone (04)
On Oct 7, 2011, at 7:21 AM, "John F. Sowa" <sowa@xxxxxxxxxxx> wrote: (05)
> On 10/7/2011 12:52 AM, Rob Freeman wrote:
>> On the subject of foundational issues. Here's a website I found just
>> this week (via a random search for "vector language models" on Google+
>> of all things):
>> I submit it for the broader information of the Ontolog community, as
>> a separate development along similar themes to my own (without the
>> "intuition" label please, but hey, labels have their place.)
> Actually, what I like most about that web site is the word 'intuition'.
> Another word I like even better is 'imagination' -- because it clearly
> emphasizes the word 'image'. As I said in the ontofound.pdf slides,
> images and mental models are the foundation for human language.
> I certainly agree that something like intuition or imagination is
> essential for truly human-like intelligence. And my quotations from
> Paul Halmos and Albert Einstein emphasize the importance of intuition
> for *discovery* and *innovation* in mathematics, science, and *life*.
> I hadn't heard of Monica Anderson before, but her CV shows that she has
> a solid programming background with a lot of experience in using and
> developing AI software (including writing an interface to Cyc):
> I agree with the following points:
>> Several disciplines such as Chaos Theory, Complexity Theory, and the new
>> discipline of Systems Biology concern themselves with complex systems
>> of all kinds. No matter which direction you approach from, you will soon
>> discover a set of underlying problem types that make these fields resist
>> analysis and modeling efforts using the established methods of conventional
>> Intuition is Theory-free. It does not require a high-level logical model.
>> This neatly solves a bootstrapping problem of Artificial Intelligence.
>> You cannot create high-level models until you already have Intelligence.
>> Intuition based skills improve with practice, whereas Logic based
>> skills do not...
>> Intuition also has severe limitations; some of these mirror the
>> advantages of Logic based systems...
> I also appreciate her candor about the results:
>> I am currently exploring Artificial Intuition based methods. The performance
>> I can achieve with the hardware and the algorithms I have is unspectacular.
>> All my results to date can be rather easily duplicated using conventional
>> programming methods. I like to say I have results but no demonstration,
>> and the difference is that a result is impressive to someone who understands
>> how it was achieved, whereas a demo is impressive to anyone whether or not
>> they understand the technology.
> This quotation is from http://artificial-intuition.com/possible.html
> That same page has various diagrams, which I don't disagree with. But
> I prefer Minsky's, which shows similar kinds of tradeoffs *and* relates
> them to the kinds of software methods. See slide 25 of
> Note that Minsky shows all the currently popular methods, and he shows
> their strengths and limitations. I believe that *all* of the methods
> in his diagram are valuable for many purposes. But I also agree that
> none of them, by itself, can support everything. And I agree that
> "we must find a better representation!"
> I have been saying that in many different ways in many different talks,
> publications, and emails.
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