My father, near the end of his life, considered himself the last Gestalt Psychologist. When I was very young I was fearful of kelp seaweed: my father showed me that it couldn’t hurt me, so I shouldn’t be afraid of it. I learned from him. If you understand something, you can reason about it. If you only have a correlation, you can’t be sure of the factors. He was never afraid to question conventional wisdom or the current fashionable and entrenched ideas (however old or fast those ideas were).
As a clinical school psychologist he was on the front line against invasion of chemical psychiatry into K-12 schools, and he saw how they used “their pseudo-scientific expertise [and argot]” to fool and trap kids and parents into approving the use of brain disabling drugs, within the “educational system” and with the implicit pressure and blessing (and relieving of responsibility) of the teachers and administrators. He also didn’t buy into the dominant paradigms of the first half of 20th century of Freudian psychology and the correlational “blank slate” behaviorism of Watson and Skinner.
“If you don’t understand something said, don’t assume you are at fault.” — David West Keirsey
Throughout my discussions and debates with him in my lifetime, he talked about ideas. We talked about philosophy, science, mathematics, computers, people, and life.
I don’t remember exactly how it happened, but I was in his office. I remember it to this day. Think it was Sue Lapin who directed me to his room, but that’s another story.
He was a classic example of a gray haired, balding, absent-minded professor, his office shelves stuffed to the ceiling with books, papers, and other flotsam and jetsam of an academia life. There we were: two different generations — he, my father’s generation, and me, a 50’s nerd baby boomer. The commonality was we were both computer nerds, interested in ideas and the nascent computer science field. At the time I was just trying to get a job to support my education: a Masters degree at University of Wisconsin, Madison, far from my home in sunny SoCal. I had driven the two thousand miles or so across the US for the first time in my life to get there.
We talked for about four hours non-stop about all kinds of things, the Chinese language is the only subject I remember: he was a fountain of knowledge, and both us could have gone on many Moore hours. I probably didn’t know the significance of it at the time, except he did point me to a job which I got to support myself in that strange land. A year and half later, I got a Masters in Computer Science, and left Madison to wander towards Enlightenment for the next 46 years, and hopefully beyond.
But what I didn’t know at the time how important Ed Moore’s idea was: Moore machines would become important to me for understanding the world. I needed to learn More about Moore and many other things — Slowly.
It took me awhile (about 40 years) to come back to his concepts and the basics of information and computer science: armed with many knowledge domains that I initially failed and succeeded at, and revisited, as I did with Ed’s fast and slow ideas.
I had personally encountered previous many individuals involved with the emerging computer field as an undergraduate, like Richard Hamming and John Seely-Brown, and later in graduate school, Paul Mockapetris, and in Artificial Intelligence and robotics research work (HRL) Carver Mead, Lynn Conway, and Steve Crocker and their work would be important in seeing the underlying patterns of computing, the Internet, and reality.
But it was the work and ideas of Arvind and Kim Gostelow on PetriNets and Dataflow, while I was in graduate school, that I didn’t appreciate until recently. They concentrated on theoretical computation.
‘Invert, always invert’
(‘man muss immer umkehren’)
— Carl Gustav Jacob Jacobi
Combining the three finite cellular automata architectures: Mealy machines, Moore machines, and Petri nets in a Gestalt Science methodology is the next step along the way of this wandering enlightenment. And then there is even More Moore to be understood.
New scientific ideas never spring from a communal body, however organized,
but rather from the head of an individually inspired researcher
who struggles with his problems in lonely thought and unites all his thought
on one single point which is his whole world for the moment.
— Max Planck
When I was young, my father would introduce and discuss, around the dinner table, the ideas of philosophers, scientists, and historians: like Adam Smith, Charles Darwin, Herbert Spencer, John Stuart Mill, Georg Hegel, William James, Arthur Schopenhauer, Bertrand Russell, Oswald Spengler, Will Durant, Ayn Rand, Milton Erickson, and Jay Haley, to name a few.
I had a question early on “How and Why does the World Work?” He had a more difficult question: “What are the long-term patterns of an ‘Individual’s Human Action?” He was clinical school psychologist, who was identifying deviant habits of children, parents, and teachers. He was developing techniques aimed at enabling them to abandon such habits. His methods of research and reasoning enabled him to evolve his ideas into a coherent system. His model of Human Temperament has helped many people to better understand themselves and others.
He was good at qualitative reasoning, wholistic thought: the Gestalt (despite [and because] of having lots of training in statistics). I became good at quantitative reasoning: conventional science and mathematics. Between the two of us, as we debated, I realized that there was a middle way, much more powerful than ad hoc wholistic reasoning or ad hoc atomistic reasoning, when they are used separately. The new middle way, The Slow Idea, is using Comparative Science and Relational Complexity in conjunction as fields of scientific endeavor using systematic qualitative and quantitative reasoning together. To some extent: (hard and soft) science, mathematics, and computer science are towers of Babel, not able to understand each other’s argot and considered irrelevant to other.
The idea of: Slow Ideas <=> Fast Ideas
The root of this idea appeared just recently, thanks to Atul Gawande. He and Matt Ridley noted that ideas operate very much in an evolutionary manner.
FAST IDEAS WORK
eventually, SLOW IDEAS WORK BETTER, and longer
Atul Gawande introduced the idea of slow and fast ideas with an example from the 19th century. The fast idea was anesthesia and the slow idea was antiseptics. To quote him:
“Why do some innovations [ideas] spread so swiftly and others so slowly? Consider the very different trajectories of surgical anesthesia and antiseptics, both of which were discovered in the nineteenth century.”
“The first public demonstration of anesthesia was in 1846…”
“The idea [anesthesia] spread like a contagion, travelling through letters, meetings, and periodicals. By mid-December, surgeons were administering ether to patients in Paris and London. By February, anesthesia had been used in almost all the capitals of Europe, and by June in most regions of the world.”
Antiseptics, on the other hand, was a slow idea. It took decades for antiseptics to accepted by doctors, who had no incentives to change their practices that didn’t help them immediately. Blood stained clothes was a sign of a experienced surgeon; and washing hands, sterilizing instruments, and keeping hospitals clean seemed unnecessary. Germ theory was dismissed by doctors because the “germs” were not readily observed. Miasma Theory still was used as an excuse to not change.
Hey buddy, can you spare a Para-digm?
“Science advances one funeral at a time.” — Max Planck
“The trouble with specialists is that they tend to think in grooves” — Elaine Morgan
Establishment science needs to protect themselves from quacks, but it also resists slow ideas that are not easily incorporated into the current fashionable (often fast) ideas. This is natural, this is the way evolution works. However, Kuhnian revolutions (as in Margulian-Darwinian evolution) are necessary in science to progress and leap across the Quantum Gap.
I was surprised, kinda. But it made sense, why he didn’t think much of my suggestion. In fact, in his seminar at UCIrvine Information and Computer Science department (as tactic to get MIT to give him a better offer as a tenured faculty member), he dismissed my “idea”, quickly, even though he had asked (obviously rhetorically, in hindsight) for suggestions as a kind of Socratic presentation tactic in his talk.
My mentioning of Kirchoff’s law as a parallel in regards into information flow, he thought irrelevant, and was rather dismissive. But who was I, just a graduate student from a west coast Podunk U [which eventually was a key university in the development of the World Wide Web]. He was an assistant Professor from MIT,angling for tenure.
This time I understood. Although I didn’t have a name for it at the time. I just shut up.
Now, I call it eucaryotic hubris. We all have it, in the area of our expertise and our vast areas of ignorance.
This time, I had had enough encounters with these kind of guys to not be in awe of them. I didn’t assume I was at fault in not understanding, and not smart enough it “get what they are promoting”. They were just as ignorant as I was.
And, Stupid, as me. So when I was watching one of Geoffrey Hinton’s youtube talks…
I had interacted this “professor” before, in that seminar. And I had listened to some of his other conference talks, he is very very very smart and accomplished. So smart, these days, he is a distinguished emeritus faculty member, at the institution he got his BS and PhD at. He has never had to move out of Massachusetts, or MIT. No, this guy wasn’t Marvin Minsky, but his student. So when Hinton told his offhand story, about Professor Carl Hewitt, I had to laugh. Deja vu, all over again.
“Indeed, in their later years (after finding out that most others are faking an understanding of the laws of nature), INTPs [Architect Rationals] are likely to think of themselves as the master organizers who must pit themselves against nature and society in an unending effort to create organization out of the raw materials of nature.” – Please Understand Me II, Keirsey, David. Please Understand Me II (Kindle Locations 4099-4107). Prometheus Nemesis Book Company. Kindle Edition.
As scientists, we all are struggling with understanding:
Formatics: Precise Qualitative and Quantitative Comparison. Precise Analogy and Precise Metaphor: how does one do that, and what does one mean by these two phrases? This is an essay, in the form of an ebook, on the nature of reality, measure, modeling, reference, and reasoning in an effort to move towards the development of Comparative Science and Relational Complexity. In some sense, this ebook explores the involution and envolution of ideas, particularly focusing on mathematics and reality as two “opposing” and “fixed points” in that “very” abstract space. As Robert Rosen has implied there has been (and still is going on) a war in Science. Essentially you can view that war as a battle between the “formalists” and the “informalists” — but make no mistake the participants of this war are united against “nature” — both are interested in understanding the world and sometimes predicting what can and will happen, whether that be real or imagined. So… I will ask the questions, for example, of “what could one mean” precisely by the words: “in,” “out,” “large,” and “small.” The problem is both Science and Mathematics are imprecise — but this sentence contains fighting words and is impredicative, to say the least. In my father‘s terms, it is important to distinguish between order and organization, and understand the difference. Lastly, for now, the concepts and their relations, in the circle of ideas of “dimensions of time” and dimensions of energy along with the dimensions of space and dimensions of mass will be explicated, as I evolve (involute and envolute) this ebook. SO WHAT IS HE TALKING ABOUT? Let me try to explain.
… there is something strange going on with Primes
— Paul Erdös
Never mind the mock theta, Ramanujan’s gap, Namagiri dreams.
When Srinivasa Ramanujan wrote to G. H. Hardy in the 16th of January 1913, he had some remarkableformulas in that letter. So remarkable are some of his formulas that mathematicians have been studying Ramanujan’s notebooks of formulas for new mathematical insights to this day, more than a hundred years later.
I beg to introduce myself to you as a clerk in the Accounts Department of the Port Trust Office at Madras… I have no University education but I have undergone the ordinary school course. After leaving school I have been employing the spare time at my disposal to work at Mathematics. I have not trodden through the conventional regular course which is followed in a University course, but I am striking out a new path for myself. I have made a special investigation of divergent series in general and the results I get are termed by the local mathematicians as “startling”.
Hardy invited him to England because some of the formulas “had to be true, because no one could have the imagination to make them up”. But there were no proofs. However, when this poor vegetarian Indian Hindu came to England, eventually Hardy showed Ramanujan (thru Littlewood) that his formula on Primes was not EXACTLY correct. So Ramanujan had to bend to Hardy and work on his proofs of some of his formulas, so when they tackled the function of Partitions P(n), Ramanujan with the help of Hardy got to point where they “cracked” Partitions (and could prove it). They developed a direct formula that computed the number of partitions pretty accurately, and at the limit (infinity) it was “perfect” — and, could by truncating the number for high partition number to an integer could guarantee to be exact: since the number of partitions of integers is an whole number (i.e., the real number series “formula” converges with an deceasing error rate). Together they “cracked” the problem where neither man could do it alone. Ramanujan supplied the “intuition” (the finding of the hidden pattern) and Hardy provided the rigor to explain why the pattern is true. The method they created, in this instance, was called the “circle method” — and it has been used ever since by numerous mathematicians for various other results.
Seasons change with the scenery Weaving time in a tapestry
I was surprised.
I was just eating lunch by myself in the cafeteria. I am attentive, not expressive, kind of guy. Besides this was the first time I was visiting MIT, as a part of Artificial Intelligence (AI) conference. No, my SATs were not good enough to get into CalTech (or MIT), and I am a west coast guy, anyway.
But, lo and behold. He sat down next to me. Obviously, to strike up a conversation.
Ok, now I wasn’t a kid anymore. I was industry-based AI researcher (Hughes Research Labs, HRL) working at the time on Autonomous Vehicle research. Minsky didn’t know me, but, I knew a fair amount about him.
Marvin Minsky, full professor at the Massachusetts Institute of Technology, and “one of fathers of Artificial Intelligence”, came to my table clearly because he was curious. Minsky, a Fieldmarshal Rational, had been very successful in promoting his graduate students to getting academic professorships across the lands. The list of his PhD students is more than impressive. He had government and university funding. MIT is a technological power house. Money, People, and Companies have been flocking to MIT well before I was born.
I tried to make our conversation as interesting as I could. Hey, Marvin was a legend in my field: Artificial Intelligence.
After about 5-10 minutes of conversation, me doing most of the talking about the autonomous vehicle project that I had been involved with, Marvin excuse himself, and wandered over to another table with a couple of people and joined in that conversation.
He didn’t get any useful out of me, in his mind, no doubt. Next. He moved on.
I did get something useful out of the encounter. A slow idea. But not a fast idea. A hint on a part of an idea on how the world works.
It was a Kuhnian moment for me, I knew some things that Marvin couldn’t imagine.
Quan-tum: qua – “in the capacity of”, quan -“shortening”, quant-ity – “amount“
Form-atics: form – “shape“, atics – ending for making adjectives or nouns, reification
Quantum Formatics: the study of discrete form processes within context: a wholistic physical in-formation and ex-formation theory.
How and Why the World Works.
General Relativity(GR) and Quantum Mechanics(QM) have been the most successful science enterprises ever. Discovering phenomena like black holes, the tau particle, gravity waves, and predicting precisely the orbit of Mercury, bending of light, the Teller-Jahn effect, the electron neutrino, and countless other effects.
On the other hand,
“We can’t solve problems by using the same kind of thinking we used when we created them.” — attributed to Albert Einstein.
Intriguely, Erik Verlinde has proposed emergent gravity. However, at this moment there seems to be no test that can include, preclude, or exclude his idea. The concept of Gravity, whether emergent gravity, hoped for quantum gravity, implicit string theory gravity, or Einsteinian statistical gravity [in the form of General Relativity] essentially assumes some form of mathematical continuity, unspecified and under-defined. Because there are at least six forms of continuity, for example, the following four: Continuously differentiable ⊆ Lipschitz continuous ⊆ α-Hölder continuous ⊆ uniformly continuous = continuous ; The real question becomes: which kinds of “continuity” is physically at the “quantum foam” levels?– and what are the relations between concepts (qualities) of various “spins”, “charges”, “spaces”, “energies”, “masses”, “distances”, and “forces”, with different kinds of “times”.
It seems clear that the present quantum mechanics is not in its final form. — Paul Dirac
Moreover, Quantum Mechanics (QM), using the crutch of Born-Schrödinger probabilities in the guise of Fermi-Dirac and Bose-Einstein statistics, is a very very very precise, but incomplete. Although probabilistic unitary quadratic forms (a “real” scalar product or action of a linear functional on a vector in a complex vector space) can help in calculating measures, there is no “definite qualities”. At the quantum levels, one does not have separable “qualities” — just postulated mixed measures denoted by “quantum numbers” and “probabilitic measures” in the form of “real” and/or “complex numbers”.
Adding the two statistical conceptions: GR and QM has not and will not work. A non-statistical methodology is needed to Relate phenomena at the scales of large (GR) and the phenomena at the scales of small (QM). That methodology needs Relational Forms Frameworks.
Information Momentum and Latent Exformation: On the Involution and Envolution of the Universe.