Logic of Yoga

[Bhadraiah Mallampalli]

Correction:
>an organism has to spend all its life only to decide how to life a >tea
>cup.

Please read as "to lift a tea cup."

I said Prof Goddard's work gives the look of yoga. It also gives the feel of
yoga because (IMO) it is yoga. It is Prof Goddard's privilege to explain
this item, but it is just too tempting not to continue. This note is going
to be a bit longer than I want it to be, because I have to explain the
underlying terminology also. It will be the last one.

When I see an object "A" moving one way relative to another object it is
half the truth. When I also see the object "B" moving back relative to
object "A" it is the other part of the truth. When I see both at the same
time I feel a little dizzy sensation, which is no other than vyAna. I am not
good at physiological psychology but they explain this dizziness as relaetd
to some kind of sense of balance in optical nervous system which helps in
navigation. Basically vyAna has a physical equivalent in all parts of the
body and sense organs, because it "vyApt" - spread out.

Well, if one goes with a preconceived intention of looking for vyAna, one
may not always find it because the preconceived intention itself is the
"known" somatic stimulus called agni. And this "known" is only a part of the
truth, and one has to look for the other part to get to vyAna. Looking for
the other part is nowhere but oneself and this leads to "not this, not this"
etc.

Now the "short cut" that I mentioned earlier is just another name for the
"path of least resistance". The path of most resistance is agni, because
being the known material object it resists any attempts to destroy it.

As of today we have two ways to arriving at the path of least resistance.
Tensor analysis approach of relativity, and fuzzy logic approach.

Tensor analysis: The foundations laid by Prof Goddard's in this field help
us to define similar mechanism of finding absolute truth for limited and
unlimited (details to be worked out). Once we have limited and unlimited,
known and unknown are a piece of cake. Remember known, unknown etc are
multi-dimensional data structures which include not only space and time, but
also neuro-fuzzy linguistic values of nearby or faraway space-time
structures (to be explained in next paragraph). Whatever is within the
limited space is known, and whatever is outside of it is unknown. The next
step will be to define indra, bRhaspati as tensors. If bRhaspati is the
"known" controlled by the "unknown", it is a covariant tensor
differentiation (a change in known divided by a change in unknown). But
change in one variable divided by change in another itself presupposes a
cause-effect relationship! Basically Einstein had replaced the cause-effect
relationship of "action at a distance" to an infinitesimal chain at tensor
level. There is a cause-effect chain as long as you see duality. Now the
path of least resistance is derived by interaction of the tensors (indra
etc) as these tensors attempt to find the absolute truth.

Another way of looking at the picture is using neuro-fuzzy technology. The
relativity approach is only good for space-time continuums, but when "hard"
objects interact or collide we have a different situation. I speak to a
person, I don't speak to a space-time continuum. I eat a piece of bread,
again not a space-time. Then I also give names to these objects using
whatever language I know. I can not give a "perfect" name to any object
because there is not always enough time for me to find a perfect name. If I
have to cross a road I judge the distance as "near" or "far" and take a
quick decision instead of attempting to measure in yards, feet and inches.
This is called fuzzy linguistics, which is another name for a set of "hard"
objects, but the object also "know" some "rules" that help them in
interacting in such a way as to arrive at a path of least resistance. There
are also times when we do not perceive any "hard objects", and that is when
the system is taking care of itself (driving involuntarily on a well known
route), and this is the neuro part of it.

References in a subsequent mail if any one is interested.

Thanks for the attention
Bhadraiah



















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