From: "Hal E. Fulton" <hal9000@...>
Date: 2002-09-08T07:59:33+09:00
Subject: Re: Larry Wall's comments on Ruby

----- Original Message -----
From: "Christian Szegedy" <szegedy@t-online.de>
Newsgroups: comp.lang.ruby
To: "ruby-talk ML" <ruby-talk@ruby-lang.org>
Sent: Saturday, September 07, 2002 2:31 PM
Subject: Re: Larry Wall's comments on Ruby


> Albert Wagner wrote:
>
> > precludes the principles from applying to a complex program.  I suppose
that
> > there is either another "complexity theory" or the one that you pointed
me to
> > has been bastardized in the pop science community.
>
> I am a (discrete) mathematician. My brother happens to be a
> professor of complexity theory at the Rutgers University.
> The complexity theory, I pointed to, has its origin in the 1970-s.
> It started with the recognition of the clear distinction between the NP
> and exponential complexity classes. It is a very serious and highly
> fruitful branch of computer science. One could say that this is
> where the main focus of computer science lies. There is nothing
> "bastardized" about it.

You have misunderstood Albert. He meant that perhaps the
widespread conception of complexity theory was a
bastardization of the real one.

My perceptions were the same as Albert's. Assuming what
you say is true, perhaps you are so close to the reality
that you do not ever see the pseudo-realities that other
people are propounding.

For a related example, people blather a lot about chaos
theory nowadays -- people who have never seen a differential
equation. Many of these people learned about chaos theory
by watching _Jurassic Park_ and they always go around
babbling about butterflies and hurricanes.

In much the same way, I have seen relativity and quantum
mechanics brought up in literature courses. In every case,
the professor did not really understand what he was saying.

> > Somewhat related:  I saw a graph some years ago that impacted on me.
The y
> > axis was randomicity and x was complexity.  It was to illustrate that
(a) if
> > randomicity was sufficiently high then statistical methods were useful
and
> > (b) if randomicity was very low and complexity was low then standard
> > mechanical methods were useful.  What I found startling was the large
area in
> > the middle and to the right that were not random enough for statistics
to be
> > reliable and too complex for mechanical methods.  Yet, it was just in
this
> > area, where no reliable tools currently existed that most of the
interesting
> > and important problems of our time existed.
>
> Sound like pseudoscience to me...

Could be pseudoscience, or just someone painting
with a very broad brush.

Hal