Re: [ontolog-forum] Grand Unified Theories

[Jack Park <jackpark@xxxxxxxxx>]

John,

Thanks for this thread. If it doesn't wander too far off topic, it could be a profound conversation.

I just finished reading a copy of One Magisterium: How Nature Knows Through Us by Sean O. Nuallain while flying to and from Tokyo over the last week. It made my head hurt, but reminded me of these points:

Nicholas Rashevsky (father of reaction-diffusion equations) wrote a paper titled, in part: "Topology and Life" in 1954, in which he pointed out that we can tease open a living cell and count all its parts, but we cannot put it back together. He launched what he called Relational Biology, where he began to advocate for the primacy of relations not only among parts but between parts and their environment. His student Robert Rosen wrapped that concept into a commutating diagram he called the M-R System, Metabolism and repair, when in a diagram with the environment, commute to give reproduction, a model of a canonical organism which Rashevsky sought, starting with graph theory, then migrating to what Rashevsky called Organismic Set Theory. Rosen brought in category theory.

O Nuallain said in a passage in his book, in part: worrying about the relations between parts and their environment is wrong.

His book first gave me the impression that he is an extremely literate, but mean spirited scholar. In the end, I decided that he believes he needs to appear mean spirited to get people to think about what he is saying.  The book is dense. Really dense, but I'm glad I read it. Still, my head hurts.

Cheers,

Jack

On Tue, Mar 3, 2015 at 5:11 AM, John F Sowa <sowa@xxxxxxxxxxx> wrote:

Physicists are the closest to finding a Grand Unified Theory (GUT)
of everything.  But every time they find one, it opens up far more
mysteries than it solves.

Meanwhile, the very many practical applications use old theories that
are known to be be inadequate in the details.  Good old-fashioned
Newtonian mechanics is a prime example.  For big things moving at
normal speeds, GONM is the first choice.

Two professors at NYU -- the psycholinguist Gary Marcus and the
AI expert Earnest Davis -- wrote a review of attempts to find
a GUT about intelligence, human or machine:
http://www.newyorker.com/tech/elements/a-grand-unified-theory-of-everything

Opening paragraph:
> Here’s a way to make a lot of money. Publish a speculative scientific
> article with equations nobody understands, put out a press release,
> throw in a few credentials (say, a degree from Harvard or MIT), and
> get a few bloggers to spread the word. In the meantime, quietly
> start  a company based on the idea—the grander, the better.

Marcus also wrote an article "Steamrolled by Big Data", which
discusses a GUT by Jeff Hawkins, which is supposed to do everything:
http://www.newyorker.com/tech/elements/steamrolled-by-big-data

Quotation:
> As one skeptical industry insider, Anthony Nyström, of the Web
> software company Intridea, put it to me, selling Big Data is
> a great gig for charlatans, because they never have to admit to
> being wrong. “If their system fails to provide predictive insight,
> it’s not their models, it’s an issue with your data.” You didn’t
> have enough data, there was too much noise, you measured the wrong
> things. The list of excuses can be long.

I went to the web site for Hawkins' company, Numenta, where I found
the following whitepaper about their Hierarchical Temporal Memory:
http://numenta.com/assets/pdf/whitepapers/hierarchical-temporal-memory-cortical-learning-algorithm-0.2.1-en.pdf

This draft is version 0.2.1 from Sept. 2011.  All the newer things
are videos, mostly by Jeff H., who talks very fast.  I also found
an MS thesis from 2011 by Ryan Price.

If anybody can find anything newer and better, please let me know.

John

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