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Indexes of
Indexes of Indexes:
Algorithms create lists, indexes or databases.
They sort and parse.
The net result for you and me – you will soon tell
an algorithm,
"Get me a list of my best business prospects within 50
miles."
Of course, you will have defined your product well and/or
you
will have a very good demographic profile of your classic customer.
Those who
know algorithms willl always have leads for new sales.
Those who understand
algorithms will also sort their customer database
to know when and how to
get repeat business.
Google has
been a great teacher.
Everybody does a search on their own name and most of
us will get long lists of references.
Many people discover hundreds of
people with the same first and/or last name.
When you put
you name in quotes and you get a much smaller list of people with your first
and last name. You may even find a few references to you that you did not know
existed.
The science
of algorithmic matchmaking is in its infancy.
We opened the discussion on
this site with our episode of the show about
eHarmony.
That has quickly become a
billion dollar business
(yet, it can be tricky business – they almost
went broke).
Every
computer-based and/or internet-based business use algorithms.
The best
businesses use them very well.
They have discovered that patterns and
similarities matter.
This is the
part of a drive inward to a deeper level of interiority.
436
Questions. What is a
question? Is it a probe inside? What is it describing inside?
Where do
those "insides" reside? In the mind? And. where is the mind? ...in the brain?
Hmmmm... Maybe? ...human will? Yes. No. Maybe. What can a
"Yes or No" question tell you? What do ranges describe? What are opposites?
...antonyms? What is inbetween?
With eHarmony
within every one of their 436 questions, there is a scale, a value range,
between Yes and No, between 0 and 10.
Matchmaking
requires a range, then degrees of tolerance outside a range. So, how do you
find a possible match? What do you compare? Are certain dimension more
important dimensions than others to weigh? Then, how is each set of answers
weighed against the others? And, how and which do you compare across literally
millions of people?
We are the
front edge of this inquiry. The very nature of complexity is up for
re-examination. Algorithms de-complexify complexity. Certainly prior to the
indexing capabilities of a computer, such tasks would be impossible. There is
no way a human being could do such calculations on such large numbers of
people.
Algorithms: So, we need to learn about indexes,
sorting, parsing, databasing, systems, relationality, and patterns. To see into
the future, it is good to look at the past, especially its most formative
history.
History. The first documented "algorithmic" discussions
were in ancient Greece¹. Pythagoras (circa 450 BC) examined relations
between laws in nature and the harmony within the sounds of music. Pythagoras
could see that music and numbers were inseparable and he believed that these
were the keys to unlock the pathways that bridge the spiritual and physical
universe.
Harmony and
algorithms were also used much later by Mozart when he created an algorithmic
indexing system for his musical piece, Reunion. And, of course,
Ray Kurzweil used algorithms to have a
computer create the music piece he played on I've Got a Secret
(1965).
Of course,
Turing and von Neumann had begun algorithmic explorations in the 1930's such
that by the early 1950s, algorithms had become almost the exclusive domain of
the computer science departments; our philosophers and artists now have some
catch up to do if we are to come full circle from those very early points of
inquiry.
You can feel
the energy within the web pages of US National Institute of Standards &
Technology (NIST), MIT, Stony Brook and others. It seems as though they all
understand that we, as a scientitifc and intellectual community, are on the
edge of very basic discoveries about the nature and structure of the universe
by seeing new patterns, a different kind of supersymmetry, deeply within the
structure of information.
Here is a
little more formal definition,
a dictionary of algorithms (NIST). Also,
there are other great resources to begin to understand the computing
sciences:
First principles. If you are a regular
viewer of the show, you know that we struggle to understand the first
principles of business -- what separates the good, the bad, and the ugly.
We believe
that any business, to be a business, must obey a very simple, first principle
of business: order / continuity. Simply, people need to know that the business
is in business and something can be bought or sold.
Yet, it is
only the good businesses that obey the second principle: relation/symmetry.
These businesses create something of value that others want, and when they get
paid for the product or service, there is a symmetry or balance.
Fast-growing
and truly excellent businesses obey the third principle: dynamics/harmony.
Here, "dynamics" are relations extended through time and "harmony" is at least
two symmetries interacting and extending through time. Algorithms are the keys
that keep some semblance of order within the complexities of these interacting
symmetries and we believe that the people of eHarmony, through their own unique
use of algorithms, are attempting to satisfy this condition.
And, we
believe all fast-growing, good businesses are attempting to satisfy this third
principle.
Today, with
the advent of inexpensive computing, an explosion of ideas and new insights has
begun. In 1955-56 Lejaren Hiller and Leonard Isaacson¹ created the first
algorithmically generated muscial composition at the University of Illinois
using computers. The kids that grew up with technology in their cribs are now
young adults and their insight revolution is just beginning.
Those of us
who grew up in the Newtonian world of space and time failed to interpret the
web correctly and many of us dot-bombed. With the elimination of space-time
borders, businesses like eHarmony are poised for a multi-billion dollar
expansion. Every business and every organization that needs to look at the
interiority of their people will be their next big market.
Today
eHarmony is about finding the love of your life; we predict that it will soon
be about opening the paths for love within our businesses and then throughout
our world. Perhaps it will, as well, be about helping each of us to find out
where there are blocks, walls and conceptual misunderstandings that hold us
back.
For more,
please review two episodes of the show: Information-Knowledge-Insight
and
One
Workplace for all starting with each of their homepages.
REFERENCES:
1. eharmony:
Galen Buckwalter is leading the work on
algorithms. For more about the
29 dimensions, please continue with the
eHarmony discussions about their research.
2. Wolfram:
Mathematica and
A New Kind of Science, by Stephen
Wolfram
3. Alan Turing:
The Turing Machine
4. Ray Kurzweil:
The Edge of Singularity and
Kurzweil Companies
5. Gregory Chaitin:
The Limits of Mathematics
(Springer, 1998)
How to Run Algorithmic
Information Theory on a Computer
See the first chapter of
The Unknowable (Springer, Singapore, 1999)
Also:
A Brief History
of Algorithmic Composition, by John A. Maurer IV (Stanford)
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