The interview with CNBC of @chamath is a much watch because there is so much insight hidden underneath.

There are many things that caught my attention. The one thing was the abstraction that hedge fund strategies are all 'momentum' plays. What it seems to imply is that the marshaling of resources at an opportune time drives the future behavior of a stock.

From basic physics, we know that momentum is mass times velocity. So any 'momentum' tactic employs the variation of mass, velocity or both. Wrt stocks, mass is money and velocity is speed of trade.

We cannot argue that there are benefits of scale associated with having more money. Also, high-frequency trading has shown the value of high-speed trading. So in an abstract sense, market manipulation can involve a kind of momentum play.

The objective of stock trading is to buy a financial instrument at a low price and sell it at a higher price. The purpose of a momentum play is to front-run the decision process of other traders such that one acquires the assets before a decision is made.

Interesting to realize that the living things that lay the foundation of the biosphere are extremely robust as compared to the humans that are destroying the biosphere.

Seed can remain dry and dormant for ages only to reborn when provided the proper nutrients. In contrast, most animals require a continual living vessel to reconstruct itself from its DNA.

Evolution appears to constantly perform tradeoffs between robust organisms and organisms that are adaptable. Co-evolution makes possible the development of complex species as a consequence of robust organisms.

We exist as a consequence of the multitude of less complex individuals that make up our biosphere. We are in fact symbionts that are in constant cooperation with our microbiome. Absent our individual ecologies leads to death.

We are inseparable from our microbiome, we are inseparable from our societies, and we are inseparable from our biosphere. The biggest lie we are told is that as individuals, we are independent of our world.

Star Wars has a simple dichotomy between good and evil. But as the stories have evolved, the nuances between these distinct poles also has acquired a richness that is hard to dismiss.

In the latest trilogy, we discover a dysfunctional civilization even after the defeat of the empire. The argument that the remnants of the empire make is that the galaxy stills seeks a need for order. Order and chaos are at seperate poles where evil is aligned with order.

We know however from D&D alignment charts that good and evil, order and chaos can exist in many combinations:

It is also interesting that the Sith (the Evil sorcerers) only come in pairs as opposed to the Jedi that can be entire communities. Apparently, to sustain evil one has to restrict agency and individuality to just a few. A community of evil-doers very quickly turns on itself.

So at one extreme we have evil, order, individuality and at the other we have good, chaos, collective. Which brings up the question, what is the definition of evil and good? Something that we took for granted ever since the first Star Wars movie.

It is astonishing that most of cognitive science ignores an obvious reality. That there are two kinds of humans.

Tomasello has a very credible hypothesis that what distinguishes humans from the great apes is the inclination towards shared intentional behavior. What is innate is the disposition and like personalities, it is what defines our cognition as we grow.

If cognitive preference is so critical in cognitive development then why is it that we seem to have completely ignored the difference in cognitive preferences between men and women?

Humans are that species of primates that wandered out into the savannah. The savannah is different enough from a dense jungle to exert the evolutionary pressures that encourage the development of planning and forecasting skills.

Furthermore, human infants required a disproportional amount of effort to rear. This meant the specialization of roles between women who were responsible for rearing offspring and men who were responsible for bringing home the bacon. Failure in either implied death.

The Nature versus Nurture is a debate about scientific doctrine. It is a debate about the correct way of explanation for cognition.

The Representation versus Non-Representation shares the same debate. It is also about the correct way of explanation for cognition.

It is also the difference between thinking in nouns versus thinking in verbs. Nature and Representation have deep roots in Western thinking. It is a functionalist and reductionist way of thinking that meets its limits when analyzing complex adaptive systems.

It is perhaps due to this Western bias that concepts from the study of complex systems have had little traction in modern society. It is of course, more than a Western bias, but a human bias to seek out simple causal explanations of this world.

But the world is complex and messy. Spiral dynamics which is an evolutionary model of individuals and society explains how models of the world shape ourselves and our civilization.

Damasio in his book 'The Strange Order of Things' argues that the core of condition lies in homeostasis. I agree with this generalization. But let me work out in a tweet storm how consciousness relates to homeostasis.

Human consciousness is related to awareness of surprising or threatening observations. It's an error-correcting mechanism that lends attention to discrepancies of our expectations of the world.

The mind is composed of many layers of cognition. Also, its massive parallelism implies reducing the conditional checks required for error correction.

To do this, consciousness is engaged only in a time-sliced manner in a periodic manner. The majority of time spent is in unconscious activity with only periodic activation of the conscious error-correcting process.

The system 1 unconscious intuitive mechanism minimizes the effort of performing error correction. It is automated and driven by habit. It is like a river flowing without obstructions.

In physics, energy is that which is causally invariant or symmetric with respect to time. Said differently, energy is never created or destroyed, it is conserved in the universe.

Now there is a question about information. Is information causally invariant? Does information remain the same with respect to time? To understand this, let's first understand what energy is, then attempt to understand what information is.

The strange thing about energy is that it is this universal currency that seems to be interchangeable between the different forces in nature (i.e. electromagnetic, strong, weak and gravity). It is that thing that makes change possible.

Now let's assume that the universe is computational in nature. That is, anything we see in nature is a consequence of computation. That is, there is computation underneath the physics that is driving the universe to change.

What does it mean then that information is conserved in this computational universe? Also, how is energy conservation related to information conservation?

Genes are to Evolution, Memes are to Culture, Dicenes are to General Intelligences.

Open-ended generative processes like evolution and human culture have a thing that is replicated and propagated by the process. For evolution, these are known as genes. For culture, these are known as memes.

It became obvious to me that there isn't an equivalent for individual brains. Is there something that is equivalent to this in general intelligent systems or biological brains?

I have come up with a term that describes these. The word I've invented is 'dicene'. This word is inspired by C.S. Peirce's dicent sign or dicisign. It is the combination then of dicent and gene, and thus dicene.

But why dicene over so many other possibilities like schemes, themes, intuitions, patterns, schemas, embeddings, attention, habits, explanations, ideas, meanings, representations, concepts, analogies, and lekta?

AGI Significance Paradox: As progress accelerates towards AGI, the number of people who realize the significance of each new breakthrough decreases.

Why is it that you can boil a frog in water without it jumping out if you gradually increase the temperature?

The problem for the frog is that it does not have the internal models to realize that there is a change in the water temperature. A cold-blooded creature like the frog has its temperature regulated by the external environment.

To recognize change, an agent must have an internal model of reality that is able to recognize this change. Unfortunately, a majority of the population do not have good models of human general intelligence.

In fact, even the simplistic dual-process model of system 1 and system 2 is not very well known.

My attempt to map the research *doctrines* of various groups working on Artificial General Intelligence.

Although one might see names of individuals here as well as organizations, take it just as identification of the organization behind the person and a very narrow slice of their overall research portfolio.

Here is a @swardley map that captures the relationship of doctrine with other individual and organizational processes.

We can capture a party's doctrine by either an explicitly stated agenda or an aggregation of the kind of approach that is pursued. A doctrine is an invariant property of the overall behavior of a party.

In this map one can see the conflict between different parties (compare @garymarcus with the deep learning folks).

All Biological life on earth is possible because of a discrete digital mechanism of preservation and replication.

The mechanism of signaling between the superorganism we know of as bacteria and its ongoing war against viruses is through a digital mechanism.

The source of innovation in biology is in this milieu of microbiome and viromes that are ubiquitous in every complex multicellular organism on earth. Humans are walking ecologies and cannot survive stripped of these ecologies.

We can picture this as a cloud of digital interaction that surrounds all of us.

The cells of multicellular creatures however do not communicate in the same way as bacteria. The DNA of mammals are sequestered from daily activity so as to prevent wear and tear.

"Three modes of evolution have thus been brought before us: evolution by fortuitous variation, evolution by mechanical necessity, and evolution by creative love." - C.S. Peirce 1893

These words were spoken prior to the discovery of quantum mechanics and computation. What if Peirce knew of these discoveries? If so, how would he have conceptualized these evolutionary modes differently?

I believe there is an extreme benefit in revisiting the writings of great minds in the past and refining them based on scientific discoveries that occurred only in their futures.

wrote the book "A New Kind of Science" that speculated how science would be different if computers existed prior to calculus.

In the same way, let me explore C.S.Peirce ideas of evolutionary philosophy from the vantage point of knowing of the discoveries of quantum physics and universal computation.

Does artificial anthropocentric intelligence lead to superintelligence?

When I use the term Artificial General Intelligence, my meaning of 'General' comes from the psychology definition of the G-factor that is tested in general intelligence tests.

It is an anthropocentric measure. The question that hasn't been explored in depth is whether a "human-complete" synthetic intelligence leads to a superintelligence. The prevailing assumption is that this expected.

I am going to argue that this assumption may not be true.

The assumption that goes into AGI automatically exploding into a superintelligence is driven by the bias that human intelligence is perceived at the pinnacle of all intelligence.

Chess may be a good analogy for explaining the difference between a descriptive model of reality and a generative model of reality.

A descriptive model of chess will describe the rules (i.e. initial setup, allowed moves, points per piece, objectives). This tells you how a chessboard might evolve and also narrows the combinations of realistic chess positions.

In contrast, a generative model involves the actual gameplay between competing players that follow the rules. It generates new styles and patterns. It establishes new strategies and tactics. It generates new openings, middle gameplay, and end game tactics.

A generative model is an evolutionary model that leads to emergent behavior. As a consequence, a master of chess is able to recall the layout of chess positions in a real game in an instant, yet is unable to remember pieces placed in random positions.

That is because causality is present in the movements of pieces in a chessboard. An intuitive system like the human mind is able to capture that causality as a means to understanding and recall.

Abduction is that thought process where we renew our past, question our present, and reimagine our future.

It was C.S. Peirce, a century ago, that coined the use of this term to describe a thought process that would convey hypothesis making.

A little over 50 years ago, proponents of Artificial Intelligence, proposed that deduction would be the core feature of human intelligence. This idea was driven by the bias towards formal logical systems and the emergence of computers.

This approach was in stark contrast to cybernetics (introduced a decade early) that proposed that dynamical systems were a model for intelligence. The descendant of this approach was coined as artificial neural networks.

This dynamical systems approach was later understood as being similar to an induction based thought process. Deep Learning leads to what can be characterized as Artificial Intuition.

A children's book written in 1954 inspired by Wiener's Cybernetics that explains some common day analog systems:

Analog computation originally meant the construction of a simulation of another system by means of a mechanical or electrical system that represented the same dynamics as the physical system. That is an analog of what's being simulated.

Nobert Wiener generalized this idea in Cybernetics to describe control systems that through negative feedback promoted stability.

W.Ross Ashby argued that negative feedback was insufficient for maintaining the stability (homeostasis) of complex system. Ashby proposed the Law of Requisite Variety.

These machines that 'seem to think' are examples of what was known as analog computation. Cybernetics, control theory, biology are examples of analog computation. But what does this mean other than being the opposite of discrete/digital computation?

A good theory of consciousness is one that predicts behavior that is unexplained by other current theories of consciousness. Einstein's General Theory was given credence because it predicted the bending of light.

What do current theories of consciousness predict that is outside common intuition about the nature of consciousness?

Many theories of consciousness are elegant, but do they predict anything out of the ordinary?

A theory of consciousness must be expressed in a formulation, consists of interpretations that are valid and predict something unexpected.

A bad theory of consciousness has ambiguous interpretations and predicts nothing out of the ordinary.

We wake up each day with the same attention budget as everyone else. This is the one thing all humans equally share.

Spending that attention budget by doing this is what gives meaning to our lives.

It's is only through doing that we learn. It is only through learning that we find meaning.

Yet many of us waste attention budget exclusively on consumption. Seeking the random dopamine hits that tickle our curiosity. Yet we seek only the convenient things to do.

Activities that are convenient, that takes little effort don't consume a lot of attention. But enough of these small distractions will. But unfortunately, there's little learning taking place.

Constructivism is perhaps the most important idea that will shape the future of humanity. The ills of society are a consequence of the willful ignorance of constructivism.

There are two important definitions of constructivism, one comes from mathematics and the other from psychology. The mathematical definition leads rejects the law of excluded middle. It's relevant in understanding causation.

The psychological definition: "Humans actively construct their own knowledge, and that reality is determined by our experiences as a learner."

The models of causality that our brains invent to navigate the world is a consequence of our progressive development in the world we live in. Robert Kegan calls his theory constructive developmental theory to emphasize two important aspects of cognitive growth.

Cognitive growth is constructive as explained above. It is also developmental in the sense that our mental models of the world make abrupt changes as we grow in maturity. The symmetries in our models break and lead to new symmetries.