Time: Be Ruthless With It

Time: Be Ruthless With It

One thing I have seen over the past few years is time… that one great resource you cannot really get more of can be split on many diversions.  I see that in business daily. In volunteer work etc. As you grow older and wiser one sees that you must protect and guard your time on the same level you do your resources and your freedom.  Time… it is finite, don’t waste it!

Judy Blue Eyes

What a sweet song… walking into Central Bier Haus with my daughter as it played yesterday… truly timeless.

The Sixties – 1968



If you look at the whole year as theater,
as the real acts of tragedy, there’s an
almost poetic feeling to it. 1968 was
one Goddamn thing after another.

Synchronicity – LSSL

Well then…

Synchronicity I
With one breath, with one flow
You will know
A sleep trance, a dream dance
A shaped romance
SynchronicityA connecting principle
Linked to the invisible
Almost imperceptible
Something inexpressible
Science insusceptible
Logic so inflexible
Causally connectable
Yet nothing is invincible

If we share this nightmare
We can dream
Spiritus mundi

If you act as you think
The missing link

We know you, they know me

A star fall, a phone call
It joins all

It’s so deep, it’s so wide
You’re inside

Effect without cause
Sub-atomic laws, scientific pause

Friday Selfie!

Friday Selfie

Seeing how I never post my mug to my own blog and it’s Princess Beatrice’s birthday today I said to myself… ‘Self’, how else can I celebrate her special day than with a selfie! #nogaslightzone

Occam’s Razor

Occam's Razor

The principle states that one should not make more assumptions than the minimum needed. This principle is often called the principle of parsimony.

It underlies all scientific modelling and theory building. It admonishes us to choose from a set of otherwise equivalent models of a given phenomenon the simplest one.

In any given model, Occam’s razor helps us to “shave off” those concepts, variables or constructs that are not really needed to explain the phenomenon. By doing that, developing the model will become much easier, and there is less chance of introducing inconsistencies, ambiguities and redundancies.