LifeOS: exploring the system that executes DNA

September 19, 2011

Probability, Uncertainty and Quantum Waves of Consciousness

The terms uncertainty and probability are mathematical concepts that do not refer to anything physical. Uncertainty is a condition of the mind. Whether the cat is alive or dead is only an uncertainty to the mind of an observer outside the box. To the cat and its fleas, there is no uncertainty. Probability is statistical, inferring the comparison of many events over time. Time is another mental concept involving a memory and something like an imagination that can plot a path into the future.

If it is true that Quantum Mechanics, “is the mathematical description of the motion and interaction of subatomic particles,” and involves these same nonphysical, but decidedly mental concepts, how can we deny that QM is the very essence of intelligence? When we say, “That’s probably true,” or “I think so,” we are exercising our ability to imagine the future.

How is it that subatomic particles are engaged in the same kind of behavior? If subatomic particles are somehow connected to future events, it must be through some nonphysical process that remembers, evaluates and acts, very much like our own consciousness. The process is most certainly nonlinear, non-local, fully coherent and interconnected.

The model becomes clear when we view the Universe, not as an explosion, but a computation. The Big Bang becomes the Big Bootup, with no need to suspend classical physics for it to happen.

There is no paradox between quantum mechanics and classical physics if you consider one is the process and the other is the output. In the information processing model, the output of the quantum process is the physical Universe. The physical Universe is the expression of the current state of the process. The overlapping, nested and holistically interconnected quantum coherent fields represented by wavefunction, are the process in action. In this model it makes perfect sense that subatomic particles represent non-local variables, and could be collapsed by local interference.


February 10, 2009

Networks in Complex Systems

Biological systems process matter, energy and information. Every bit that moves in the process follows a path. Those pathways form a map of the interactions between the various elements of the system. These maps describe networks.

Computers have given us the reason, as well as the tools, to understand, build and maintain networks. They have given us the memory necessary to track their evolution. They have given us the power to analyze all kinds of information and discover the universal patterns of network functionality and growth. This is an extra bonus of the information age. Besides, the explosion of information technologies and the increased efficiency they have brought to all human endeavors, besides the exponential increase in the availability of information to all, besides the awesome power we have acquired to input the global system, the most important aspect may be our realization that information processing is fundamental to living systems. The study of networks in complex systems may be a Rosetta stone that will help us decipher the code of life.

It is becoming a truism that we’re living in the era of networks. Just about anywhere we turn, we encounter one. We have the World Wide Web and the internet; we have social networks, genetic networks, and biochemical networks. These things – web pages, genes, chemicals in our cells – are nothing new. What is new is that everybody’s waking up to the fact that there is a network behind all of these systems, and we need to think about networks as a common feature of all complex systems.
–Albert-László Barabási
Interview at:

Throughout this discussion we have been shifting our focus from objects to process. LifeOS is a process of motion rather than a static structure. The study of networks gives us another method for understanding what a system does.

Household Networks

A house is a basic system that provides benefits for its inhabitants. The structure and its subsystems protect the inhabitants from the elements while networks provide the energy, materials and information necessary for it to function as a household.

The walls are subsystems that support a roof that consists of subsystems that channel rain water around the structure, keeping the interior dry. Pipes and wires bring incoming essential elements like water, gas, electricity and carry away the waste.

The pipes and wires are easy to see as networks, as their blueprints clearly show their web of relationships, but there are other functions that fit the pattern, as well. Windows and doors are openings that regulate and filter incoming light and air, while allowing or preventing access by insects and such. Groceries follow channels that are not as constrained as pipes and wires, but can be diagramed, as well. First there is the network that supplies the groceries to the market place and then the pathways the goods follow once in the house. A map of these pathways is complex and dynamic. These networks interact to provide the needs for each functional element to carry out its task.

Informational Networks

Besides the material and energy, we have purely informational networks that participate in the household dynamic. Phone calls make changes in other networks, like “Pick up some blueberries on the way home from work”, or calling a plumber. Radio, TV and of course, the internet, provide information that has real effects in the household.

Essentially we are looking at this household as if it were a giant cell. There are openings in the membrane that regulate and filter intake and output from the local environment. Internal networks route elements to their respective processing stations, etc. Purely informational networks influence and control process behavior at every turn. The way that a cell’s internal networks and systems function over time, determines its success.

Network View

This is just some of the magic of using the network view to analyze a system. The flow of energy, material and information throughout the system, is directly related to its state. Blockages and congestion in this flow are fundamental to system failure. Network view can expose potential bottlenecks and disturbances before failure becomes an issue. Like when you notice the sluggish drain, and call the plumber before the toilet overflows.

Besides being an excellent way to analyze a specific process, networks are a common denominator in all complex systems. Network view offers a way to understand the life process at all levels.


Networks grow in very specific patterns. Growth is accomplished by adding nodes to existing networks, one node at a time. The nodes, their connections and carrying capacity, adapt to demands; that is, they grow to accommodate use. This pattern is observable in such diverse systems as cells, organs, social groups, memory/learning, the internet, prairie dog trails and our household example. The rules that govern network evolution in complex systems are like the rules that govern information processing in general, in that the rules apply across the board, regardless of the platform, language or medium employed.

Network Types

Basically networks come in types that are characterized by the number of links per node, degree of separation(how many hops to connect any two nodes) and their shape.
Random Networks have nodes with nearly the same number of links. Older nodes will have more links than newer ones, but variation will be small. The number of hops necessary to connect any two nodes will be proportional to the size of the network. So, large scale random networks will get slower as they grow. They also tend to be unstable when stressed by heavy loads.

If steeped in neodarwinism, one might expect biological networks to be random in their construction. However, random networks rarely appear in living systems. When a node is added, decisions are made as to how it will be connected, based on a combination of network design criteria(preferential attachment) and usage. In fact, this network design criteria, employed at the cellular level, is well ahead of our current understanding. We are still learning.

Biological systems and most manmade networks fall into two categories: scale-free and hierarchical.

Scale-free Networks are characterized by a very low number of hops to connect any two nodes, regardless of network size. The structure that results has a wide variation in the number of links per node. Some nodes collect considerably more links, becoming hubs, while others have only a few connections. Scale-free networks are much more robust than random networks. Many more nodes can be disabled without disrupting traffic. They excel in the efficient distribution of information.

Hierarchical Networks form clusters that have many internal links, and limited external links. This is the basis for modules, organs and agents. These networks are best at processing information. Hierarchical networks are characteristic of entities.

These two types of networks are analogous to conventional and relational databases, or parallel and series circuits in electronics. If you can see the yin and yang of the two, or the split brain model, you’ve got it. These two fundamental modes of operation interact to weave our reality at all levels.

Invisible Criteria

It is obvious that the formation of networks is guided by some invisible criteria. At the critical stage where a node is added to a network, called preferential attachment, decisions are made that affect the future efficiency and stability of the system. Just as in dopamine neurons, where future expectations play a role in their behavior, the growth of biological networks exhibit the same ability to plan ahead, like something “knows” what it is doing.

In human networks we know where the “intelligence” is applied. It is at this same crucial step in the process. When a node is added, humans choose how it is connected. Yet, until we learned about networks, we were powerless to predict how they would function. Biological systems have known how to manage networks all along. They have a way to apply knowledge to the growth of networks. Seems to me that is a job for our coherent fields.

Holographic Fields are similar to networks in that every node is connected to every other node, in one hop. However, the nodes aren’t connected by “lines”, as in the others. No matter nor energy is exchanged, only information. There are no pathways, rather a field that contains the potential for all pathways. It becomes a medium that information traverses in waves. Any disturbance within the field traces patterns between affected nodes. These trails are the beginnings of physical network linkages to come. From these patterns grow combinations of hierarchical modules linked seamlessly into scale-free networks that process to a targeted outcome.

January 14, 2009

Team Subconscious

Captain Self runs a tight ship, passing out orders left and right, but we know who does the work. Sure, we can see that there are organs that perform specific functions, but in practice, the whole organism is involved to varying degrees, in every activity. It is a team effort.

Team Management

Environmental stimulation results in the formation of ad hoc teams of organs, glands, neural pathways and muscle groups that respond with adaptive action. That is, the teams that react to environmental input, are made up of cells, the crew of your ship. There are trillions of them, functioning together as a unit. Their numbers are way too many, and they are engaged in relationships far too complex, for the conscious mind to manage. Just like in your computer, you don’t need to know what is going on inside to get results. It is Team Subconscious that manages our background processes.

Team Tradition

So, Captain Self is spared the details, leaving him free to focus on his main responsibility, relating to the big picture, the external environment. However, these teams have a tradition dating back millions, sometimes billions, of years. Their functionality has not changed significantly in many, many generations. Until fairly recently, their input had also been stable. In the last few hundred years, cultural changes, especially to diet and the levels of chemical pollutants, have placed unprecedented stress on all of the ship and crew.

This stress causes general agitation to the system. The system doesn’t like change, especially the unprecedented kind. The agitation stimulates the system to search for an adaptive response. Although the captain might be consulted from time to time, response comes from Team Subconscious. Within the team, there are well established command units that govern critical behavior.

Team Behavior

What we affectionately refer to as the “reptilian” brain, for example, gets the name from its resemblance in function to the brains of snakes, lizards and other reptiles. The main concern of this command unit is the very basics of survival of the individual, followed closely by survival of the species through reproduction. There isn’t any consideration for social relationships going on here. The so called, mammalian brain, was added later, onto the reptilian portion. This command unit features improved social interactions, like nurturing of the offspring and sharing food.

Each of these command units was developed to cope with a specific set of environmental conditions. As conditions changed, new command capabilities were added to the existing set. This was accomplished by adding new tissue, just like any other learning process.

These teams were assembled to give added functionality during earlier stages of development. However, the more primitive portions remain in the information stream and have the power to override commands arriving from later(less proven) teams.

The new departments gain control through successful performance, but the slightest hint that these newer departments might not be performing as expected and the system reverts to more tried and proven(primitive) behaviors. This is the same bias towards established routines that we see in diverse social and conceptual endeavors, like addictive behavior, paradigm shift and software development.

Disabled Ships

A good captain needs to know how his teams interact. Take that reptilian bunch already mentioned; this outfit is all sex and survival. Back in the days when they were in charge, life was simple. Life is several stages more complex these days, but in a pinch, that rowdy bunch will take over and revert to “primitive” behavior, whether appropriate, or not. Our jails are full of disabled ships, whose captains were rendered ineffective by rebellious crews, especially that reptilian team at the base of the skull.

The marshal arts, for example, are disciplines that seek to put the captain in touch with these elements and forge a positive relationship with them. It is training, practice and living with intent, that builds self-trust, self-respect and self-confidence. Once a level of trust is established, the captain can assign specific tasks and expect consistent results from the ship and crew. That’s how you build a reliable interface.

It is important to remember that both the captain and crew are part of the system. They use the same neurotransmitters, sensory processes and DNA language as the rest of the Life. Neither are in any way separate from the system.

Lonely at the Top

In spite of the obvious physical unity, the captain often feels separate and somewhat alienated from the ship and crew. A certain feeling of separation is important to the functioning of an individual agent. This perspective enhances an agent’s ability to act freely in the environment, making it better at seeking out adaptive behavior. However, when not balanced by a sense of belonging to the team, the feeling of separation can lead to trouble.

Captain Eternity

The idea, supported by some captains, that they live on forever, while the ship and crew are just temporary, is at the heart of the problem. Not only does this attitude indicate a perceived separation from the physical body, and an overinflated ego, but this is just about as separate as a captain can get from reality. Even if they were to be immortal, captains are of little use to the system without a ship and crew.

As i said before, the crew has been doing their jobs for billions of years, while it is the captain who is temporary. If there were anything worth saving about a human existence, it certainly would be more than just the captains log. It would have to include the much larger body of information gathered by the rest of the team. Only then would environmental changes be registered by the system. The captain seems blind to the nature of these environmental changes and the long range effects of current actions. It is as if the captain is operating from a different set of values than the crew. And the gulf widens.

Out of Touch

The wider the gulf, the more contentious the relationship becomes, the more the crew acts on their own, leaving the captain to rationalize increasingly irrational behavior. What the captain sees as mutiny is really that Team Subconscious has lost confidence in the captain’s ability to insure survival of the ship in particular and the species in general. Although the team takes commands from the captain, their allegiance is really to the ship.

Make Peace with the Crew

So, take a look at your own relationship with your crew. Are you a good leader? Are you and your crew working together for common goals? Do you feel good about the Team? If not, it is up to you, the captain, to improve this working relationship.

December 23, 2008

Captain Self

Viewing Reality

At first glance it seems that you and i are dealing directly with the environment. We can see it, touch it, smell it, hear it and otherwise interact just as if we were really observing reality directly. However, we interact with the environment through an interface. Why is it important to know this? Because it gives us the power to choose hidden options or even update its features.

I can remember the picture that became my view of the self for many years. It was from an old Flash Gordon comic strip. Back when i was a kid, we used to spread out the Sunday Comics on the floor, and listen to the radio. There was a guy who would go through the funnies and read with us. One episode of Flash Gordon was a mechanical football game. The players were thirty feet tall human replicas that played a brutal brand of train wreck football. Each machine had a pilot and copilot that sat inside the helmet, right behind the “eyes”. It was like the cockpit of an airplane, with gauges and dials everywhere. From there they worked control levers and switches to play the game.

Captain Self

Captain Self

That’s the way i had it pictured in my head, Captain Self, at the controls of this biological machine. Since then, control systems for aircraft have advanced, and over the years, i tended to add the same new capabilities to the Captains control room. Then there was Captain Kirk’s control room to borrow from. However, there were some problems with my model.

Learning about how the senses work and then following their information channels into the brain, it becomes obvious that there is nobody sitting behind the eyes. The senses each provide information to different parts of the brain. These different sections somehow work together to display a seamless virtual reality to the user. This is truly an amazing feat of biological information processing.

The captain of this ship is isolated somewhere in a back room, without windows and certainly no real view of the outside world. The Captain is led to believe that the view presented by the eyes is reality, but we now know better. It is all done with smoke and mirrors. The user/conscious mind is being presented with a virtual reality, that has been filtered, cropped, censored and otherwise altered by subsystems beyond conscious control. Who’s in charge, here?

Subconscious Deception

This virtual reality display has some very interesting attributes. One is the fact that this internal display is so well linked to external reality. The virtual image of my hands at the keyboard is so well linked to the external world that i am sure i am seeing the real thing. The sounds of the keys and the movements of my fingers, all in perfect sync. However, this complex display takes some time to conjure up in the brain; it is fast, but not instantaneous. There is another time lag in the decision making process. By the time i see something, some tenths of a second have elapsed. Deciding what to do takes a little time, then getting that decision out to the body uses up some more. That might not seem like a lot of time, but airbags can deploy faster. If the user were left to deal with such erratic transmissions, precise navigation would be difficult to impossible.

The subconscious clears that troublesome mismatch up by using a subtle deception. The subconscious goes ahead and makes the decision when it needs to be made to compensate for the time lag, and then delays informing the conscious mind until it matches the scenario. Clever stuff.

Virtual Persona

Then one night i was watching a TV show about virtual reality gaming and saw a guy in a suit wired up to input body movements into a computer. He was wearing a helmet that projected his virtual reality onto a screen in front of his eyes. He moved his body and his virtual persona moved in sync. That was my new Captain Self.

Gone were those primitive control levers and switches. The Captain moves and the ship moves. That’s what’s going on in the brain. It is creating a virtual reality with neurons and waves of sensory information, that matches the environment. The user interacts as if it were a direct connection to reality.

My Captain Self model also demonstrates how intelligence relates. The Captain has an intellect inside the helmet that is the user, and then there is the intelligence that manages the virtual displays and their complex interactions. This is the same intelligence that manages other, less sensual, but no less complex, internal affairs.

Captain and Crew

Captain Self is in charge and responsible for the behavior of the ship and crew. However, the good Captain is a relative newcomer, only being in charge for this lifetime. The crew has a long history of operating these ships and really doesn’t consult the Captain, except in emergencies. The crew is so good at doing their jobs that the Captain is seldom aware that there even is a crew. All the Captain has to do is think of an action and the ship responds. That makes a good interface: seamless, intuitive and invisible to the user.

November 29, 2008

Fields of Coherence

The core concept that holds the LifeOS model together is that of the coherent electromagnetic field, aka a hologram, hereafter referred to as, CEF. After reading several papers on the coherence of magnetic fields and the origins of the universe, it seems to me that there is great deal of evidence for our universe being fully coherent. If our current universe ever experienced a Big Bang type of singularity, where all matter was compressed to the max, it could be defined as complete coherence. Seems to me that the compressed universe would have to be vibrating as one, like a super crystal. As the universe expanded, coherence would have remained a fundamental property.

Waves of Feedback

The Computational Mind isn’t based on arbitrary numbers or a digital interpretation of the environment, but direct interaction with it through the holographic aspect of matter. We are not separate observers of phenomena, rather participants in multiple, dynamic feedback loops. When we think of a feedback loop, we generally envision a linear information channel, like the wire and thermostat. Actually, feedback involves continuous waves of information, from every connected source, regarding our interaction with the environment. Every movement of matter and/or energy within the system is participating in feedback. These waves are repeating patterns that are constantly being compared to the waves that have come before, in every CEF at every level. Their deviations produce interference when laid down over the past patterns. The interference causes ripples throughout the system, that identify its location, amplitude and other information about the deviation.

CEF as a Database

This CEF is like a faraday cage, in that it protects the field contents from outside electromagnetic interference. Input and output react at the boundary layer as if reacting to the entire field. However, the interaction at the boundary layer involves some sort of information management. Interactions don’t involve all of the information available within the field, but only a small portion. It is like the boundary layer responds to the input as a query and only selected information is transferred. This makes the field an electromagnetic entity.

A CEF as Pure Mathematics

Each CEF is a model for the Whole. The dynamic hologram that each CEF generates is a map to all of the possible relationships within the hyperspace it occupies. This in turn is a micro model of all of the possible relationships in the Universe. A formula could be written to describe any specific interference event in the hologram, but what the hologram does is describe the entire hyperspace it occupies in terms of the wavelength of its synchronized light. Essentially, the laser light bathes the CEF’s hyperspace in pure math. Any relationship that could be represented by a formula is intrinsic to each itineration of every CEF. These fields are nested, overlapped and interconnected by their membership the holoverse, as well as countless other feedback loops that carry specific information between discreet individual CEFs. It is all information flowing in all directions. The Whole is thus apprised of all relationships, from all points of view, all of the time.

A CEF as a Pattern For Growth

The growing tips of plants project an electromagnetic field in the direction they intend to grow.

Plants have to have a memory to grow. During the day they collect light energy and at night they turn that stored energy into new growth. If the plant is going to grow towards the sun, which they all do, it has to have a memory. The plant has to have a way to remember the path of the sun, and from that, predict where the arc of the sun will be in the future. It does so by extending the electromagnetic field of its current state, from its growing tip, towards the projected arc of the sun, as a template. You could say that the plant “imagines” how it needs to grow to get maximum sunlight the next day.

It also exhibits the very basics of awareness, to be aware of the environment, set goals and build towards achieving them.

Intelligent Action

You and i are subsystems that use thought to analyze a situation, set a goal meant to rectify it, then plan and implement action in order to accomplish that goal. All around us we see countless other subsystems that are doing the action thing, but we fail to acknowledge that they are also analyzing the situation, setting goals, planning and accomplishing, and in many cases, doing it more efficiently than human beings.

Goal oriented behavior is fundamental at all levels of Life. Even the smallest of creatures must identify food and devour it in order to survive. The same sequence of behavior must take place in the simplest of machines and animals in order to achieve goals.

The most efficient way to solve problems is at the point of action, where the individual interfaces with its environment. The farther away from the action that important decisions are made, the greater the chance for error. We find that to be true in human organizations of all kinds. Other subsystems are organized the same way.

That’s free will: the ability of the individual agent to make the final choice. Biological systems benefit from both good and bad choices by individuals, by keeping track and learning from all their experience.

A CEF as Operating System

Where is the operating system on your computer? On the hard drive? Nope, that’s just a static copy. The active version of the OS is in RAM, random access memory. You can’t look at it, only the results of its activity. The code that is active is invisible. In RAM we have a dynamic array of information stored in a matrix of binary switches. It is a very simple version of our CEF, in that it reacts to input with specific output. Just like our CEFs, it has internal instructions that control its output. Those internal instructions are compatible with the internal instructions that operate every other agent in the network.

It is the same with LifeOS: the active operating system is invisible, but we can see the results of its activity. This operating system is not in code that has to be read before it acts, but present in the structure and properties of living CEFs.

The kernel of this operating system is in every atom, a fractal arrangement of energy vortices that contain direction, intent and unlimited potential(uncertainty), guided along the pathways of highest probability by memory, continually plotting expectations into the future. Waves of expectation are projected on incoming sensory data, in a dynamic flow of imagination becoming real. This process functions at all levels of biological systems.


Consciousness is what goes on inside a CEF. It is the interface between the CEF and the outside environment. Its complexity is mirrored by the information it contains. The “consciousness” of a cell is only interested in its own internal affairs, therefore it would seem far too simple(primitive) a process for us to call by that name. We expect a great deal more from anything we would call truly conscious. However, in terms of systemic functions, manipulation of information towards specific goals, in harmony with overall goals and procedures, is being accomplished at the cellular level. This kind of intelligent action was going on long before there were any multicellular beings, let alone “intelligent” primates. Let it also be noted that biological systems have used these techniques(manipulation of information towards specific goals) successfully for billions of years, before mankind came along and screwed things up by forgetting the part about, “harmony with overall goals and procedures”.

November 25, 2008

Abstract Intelligence

Abstract Computational Device

When we talk about biocomputers, the first example that usually comes to mind is the human brain. The computational model of the brain mind interaction has gained some popularity, but the biological model has a couple of major differences that we need to be aware of.

First is that the computer was designed as an abstract computational device. We design computers as general purpose tools that can be used in any number of ways.

When we want to use it for something specific, we need a program designed to process specific information in very specific ways to obtain the desired output. We have to input the values we are going to use for our computation. These values are the only thing that gives our computations meaning. The computer itself, was designed without any specific meaning for its code or output. In biological systems, the situation is very different. Information processing evolved around meaning to begin with. The values it processes are raw data, with meaningfulness integrated. It is sort of an inside out version of the process that designed computers.

Decentralized Processing

The same kind of reorganization of system components is exemplified by fact that the central processing unit(cpu) is anything, but central. Every cell does its own processing. In computers, the RAM, cpu, data storage and devices are all separate units that accomplish the various computational functions. In biological systems, cells adapt to perform all functions.

From basic stem cells, all other cells form according the information activated in the DNA. Therefore it must be assumed that all of the functionality of consciousness is contained within every cell, at least the coded instructions that make a cell able to participate in consciousness. Whether one believes that consciousness is a purely internal affair of the brain or that it is connected to a universal source, all of the functionality that makes it possible, must be contained in each and every cell.

This “inside out” version of our computer model appears more like a network than a single machine. However, while these cells all have their own onboard processor, they are all processing in synch, acting very much like a single supercomputer. Instead of processing digital strings in parallel, the biocomputer is processing waves of information in a nonlinear fashion, comparing incoming waves with the record of past waves.

Every component within our biological network contains its own network of nested networks of parallel wave processors. Even the “wires” that connect components act like a router in that they have their own processor.

Field State

All of these processors working in synch generate a coherent electromagnetic field that is a dynamic reflection of the “state” of the organism. Each cell within the system is recording its own state, as well as, the state of the overall organism in holographic interference patterns. Organs, connecting subsystems and muscle groups form their own coherent fields, that monitor and record their own state.

The basic process goes like this:
Input as interference patterns, generated by dynamic state of the organism. Past patterns build up to indicate the shape of future patterns. These past patterns are projected into the future as expectations. In this way, input is compared with expectations. Deviation from expectations produces ripples in the interference patterns that define the inconsistency from every possible angle.

We can think of this as a linear process, it is more like our model of a computer, so it makes the concept easier to grasp, but in reality these interference patterns contain all of the information available for memory for the entire organism. That is a lot of information, more than a linear description can accommodate. Trillions of cells participating in a dynamic field of their combined states. So, when we say, “compare input with expectations”, we are talking about comparing oncoming waves of information, rather than a digital string.

Waves of Meaning

It would be like standing on the seashore and noticing the changing patterns of waves pounding at your feet. The position of every water molecule is affected by the changing forces of wind, tide, temperature, salinity, shape of the sea bed, earthly vibrations and all. It is as if you could look at each wave and predict its motion, according to past memory. Then being able to see the deviation from expectations and surmise the change that brought it about, and make corrections to restore predictability. A tough assignment, right? If every molecule in your ocean was a sensor that reported its position and “state”, in one dynamic readout, the task would be much easier.

Computers are essential to the functioning of an information processing system, but when those basic concepts are expanded to incorporate distribution of targeted information in waves, across a network, with feedback from the information itself controlling distribution, we just begin to reach the level of sophistication demonstrated by biological systems. These are systems that monitor themselves and propose adaptive strategies to attain goals, as do intelligent human beings.

All Intelligent

In recent years, science has discovered things like entangled particles, wave functions, feedback loops and holographic principles. It was thought that these phenomena had little to do with natural systems, but were concepts confined to the lab and theoretical exercise. In reality these concepts are fundamental to systems at all levels. It is not that there are sometimes feedback loops, nor that wave functions sometimes mirror reality’s uncertainties, nor that particles sometimes become entangled, nor that holographic principles sometimes appear, but that these principles work together to produce the most sophisticated information processing system imaginable. The system is all feedback, all entangled, all holographic, all memory, all processing, with intent, with targeted goals achieved by employing strategies. This system exhibits capability that gives a new depth to the meaning of the term, intelligence.

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