Consciousness as Perceptual Control.txt

Consciousness as Perceptual Control
Open sidebar
Consciousness as Perceptual Control
An essay on quantum erasure, perceptual control theory, choice theory, multiscale computation, active inference, and rhizomatic scaling laws, titled "consciousness, the control of perception".

Some context:
No results found for "consciousness, the control of perception".
Results for consciousness, the control of perception (without quotes):
Scholarly articles for consciousness, the control of perception
The conscious perception of the sensation of fatigue - ���Gibson - Cited by 419
��� self-consciousness, social anxiety, and perceived ��� - ���Striegel-Moore - Cited by 400
The psychobiology of consciousness - ���Davidson - Cited by 229
If an organism can only detect very simple perceptions such as intensities, then it will have a very rudimentary form of consciousness. As the ability to control more complex perceptions develops, so too, consciousness becomes more detailed.Jul 30, 2018

Consciousness as Control and Controlled Perception

iMedPub
https://behaviouralscience.imedpub.com ��� consciousness-...
About featured snippets
���
Feedback
People also ask
How does consciousness affect perception?
What is the connection between consciousness and perception?
What does consciousness control?
What is the meaning of conscious perception?
Feedback

Consciousness as Control and Controlled Perception

iMedPub
https://behaviouralscience.imedpub.com ��� cons...
PDF
In this paper, Perceptual Control Theory (PCT) is offered as a solution to the puzzle of the brain. From the perspective of PCT, the brain is a control system.
8 pages
Questions and answers
Quora
Question
How do consciousness and perception relate?
Answer �� 43 votes
Is consciousness [ https://www.quora.com/Is-consciousness-a-scary-word ] hard to perceive? Or is it impossible for you to perceive anything other than your consciousness? A widespread but mistaken argument runs roughly as follows. Material objects, including the bodies of biological organisms, are objectively well-defined, well-quantified and well-understood. Their properties are described by natural science, and ultimately by the equations of mathematical physics. By contrast, consciousness is ill-defined, ill-quantified, and not scientifically understood at all. Thought-episodes and emotions are subtle, private, and phenomenally thin. Your subjectively experienced inner thoughts and feelings are elusive to introspect and difficult to verbalise, let alone quantify [ https://www.quora.com/Can-I-mathematically-model-consciousness/answer/David-Pearce-18 ]. Whereas matter and energy are no longer mysterious, at least to the relevant scientific experts, first-person consciousness is a baf���
More
Quizlet
Question
Just need to specify the mechanism that can perform a function. The ability to discriminate, categorize, react to stimuli, the integration o
Answer �� 0 votes
The Easy Problem
More
Quizlet
Question
a chemical substance that acts primarily upon the central nervous system where it alters brain function, resulting in temporary changes and
Answer �� 0 votes
psychoactive drug
More
ResearchGate
Question
I would like to work in this area, especially for visual awareness and brain, the processing is going through consciousness or unconsciousness? wish some of the people could help me to give me some Idea as I stuck on my research idea. thanks
Answer �� 0 votes
Following are some of the things we know about our own mind. When the mind is conscious of its surroundings in the waking state, we say that the mind is alive. When the mind is conscious of its functions (motion of heart and lungs etc.) in the state of sleep, we say that the mind is alive.. When the mind is unconscious of its surroundings, we say that the mind is temporarily unconscious. When the functions of the heart and lungs stop, we say that the mind is permanently unconscious or dead. So the mind is operating at two levels of consciousness. Conscious level and the subconscious level. When both these operations stop, we say that the man is dead. Most of the western psychologists and scientists don't think that mind is a form of matter because scientists don't know what kind of matter the mind is made up of. Following is what I propose as to functioning of the mind. Consciousness and unconsciousness are states of the mind. If you take mind as a bulb, and light and darkness as the c���
More
Studysmarter.us
Question
How do you define consciousness?
Answer �� 0 votes
Consciousness refers to the awareness of one's thoughts, emotions, and perceptions, as wel
More
Chegg
Question
Question 1 Which of the following is true of consciousness? You Answered it involves perception of sensation, voluntary control of actions and higher mental processing It is defined on a spectrum from alert to drowsy to stupor to coma no single part of the brain is responsible for consciousness Correct Answer all of the above none of the above Question 5 A
Answer �� 1 vote
The normal state of consciousness comprises either the state of wakefulness, awareness, or alertness in which most human beings function while not asleep or one of the recognized stages of normal sleep from which the person can be readily awakened. c
More
Feedback

An integrative control theory perspective on consciousness.

American Psychological Association
https://psycnet.apa.org ��� record
by W Mansell �� 2022 �� Cited by 3 ��� According to
1 / 1
ChatGPT
ChatGPT
Title: Consciousness, The Control of Perception
Understanding consciousness and the relationship it shares with perception is a topic that has fascinated philosophers, scientists, and thinkers alike for centuries. It opens doors to debates on the existence and nature of reality, the role of the observer, and the mechanics of cognitive processing.
Quantum erasure experiments have long intrigued the scientific community, pushing us to question the nature of reality, the role of the observer, and the mechanics of perception. Through the lens of quantum mechanics, the act of measurement or observation seems to dictate the reality that materializes, thus suggesting that consciousness - or the act of perception - could play an active role in shaping the world as we perceive it.
Simultaneously, Perceptual Control Theory (PCT) posits that human behavior is a form of active control of perception, suggesting that our actions are not primarily driven by external stimuli, but rather by our internal goals and our desire to control the way we perceive the world. This essentially means that the experience of consciousness could be a process of active control, a never-ending quest to align our perceptions with our internal desires and expectations.
From another perspective, Choice Theory, developed by psychologist William Glasser, asserts that almost all human behavior is chosen, and we are driven by our genes to satisfy five basic needs: survival, love and belonging, power, freedom, and fun. Here again, perception plays a crucial role, as our choices are heavily influenced by our perception of what would best meet these needs. This aligns with the concept of multiscale computation, which suggests that the brain���s computation occurs across multiple scales, from the neuron level to the whole-brain networks. Together, they offer an intricate, interconnected web that contributes to our conscious experience.
Rhizomatic scaling laws relate to how systems develop, bifurcate, and connect, mimicking the decentralized growth of a rhizome plant. This conceptual model is useful when understanding the emergence of consciousness, as it represents a non-hierarchical and acentric model of knowledge, similar to the network of neurons and connections in our brain. Each node or neuron in the brain is part of an intricate network that creates and shapes consciousness and perception.
Active inference, a principle from theoretical neuroscience, refers to the idea that the brain actively predicts and explains its sensations. It complements and expands upon PCT, positing that our brain continuously makes predictions about the world and corrects them based on our sensory input, shaping our conscious perception.
The interplay of all these theories illustrates a portrait of consciousness as a dynamic and intricate process. It presents consciousness not as a passive receptor but as an active constructor of reality, a continuous inferential process driven by our internal goals, expectations, and the multiscale computations of our brain. As our understanding of consciousness deepens, it continues to underscore the complexity and beauty of human perception and cognition. We have barely scratched the surface of the intricate mechanisms at play, but each insight brings us closer to unraveling the mystery of consciousness.
1 / 1
1984 Model of Mind:

We do not have privileged access to our own attitudes.

Confabulation and self-redacting narratives. 

Collectively autocatalytic sets on a Markov blanket.

"Reed Wall Mind" is a theory that suggests that the story of Noah's Ark is a metaphor for how the mind is able to process and organize different types of information. In this interpretation, the Ark can be seen as a model of the mind, with different compartments or sections used to divide and organize different types of animals, much like how the mind separates and organizes different types of information.

In this theory, the Reed Wall can be seen as a metaphor for the way that information "leaks" or filters into the mind through our senses. Just as a reed wall can allow sound to pass through while still maintaining some level of privacy and separation, the mind is able to process and filter information while still maintaining some level of organization and structure.

The idea that Noah can hear the different animals braying and bellowing, suggests that the mind is able to process and understand different types of information, even if it is chaotic or disorganized. Where different subunits of knowledge are isolated but can leak out or filter up to a multiscale decision maker. 

References:
THE COMPUTER BUBBLE THAT BURST

By HOWARD BANKS

Published: September 20, 1981,

Dog City (1992 - 1994),

Models of Mind and Behavior Control in Orwell���s 1984 - Philip zimbardo (2013)
1 / 1
ChatGPT
ChatGPT
Title: "The Reed Wall Mind: A Novel Approach to Understanding Perception and Consciousness"
The human mind has long been conceptualized using various metaphors and models. Recently, a fascinating interpretation has emerged, positing the story of Noah's Ark as a metaphor for the mind's information processing and organization. This model, known as the "Reed Wall Mind," provides a unique perspective on how our consciousness perceives, processes, and organizes information.
Firstly, the Ark, with its diverse compartments housing various animals, represents the mind's capacity to organize different types of information. This aligns with the multiscale computational theory, which suggests that computation in the brain occurs at multiple scales, all intricately connected. Different areas of our brain specialize in different tasks, creating a multi-faceted and compartmentalized cognitive landscape.
The Reed Wall, on the other hand, symbolizes our perceptual filters, analogous to a Markov blanket that separates and protects the internal states of the system from the external environment. Yet, much like the reed wall that allows some sounds to pass, our senses filter in information from the outside world, contributing to our perceptions and understanding.
A key concept in this theory is the lack of privileged access to our own attitudes, a theme reminiscent of George Orwell's "1984" and its exploration of self-censorship, confabulation, and self-redacting narratives. Just as characters in the novel are led to deny or distort their own experiences, we may not always have a clear or accurate understanding of our own minds.
The cacophony of animals within the Ark corresponds to the chaotic and disorganized information that the mind must process. Our brain, much like Noah in the story, must make sense of this disorder, filtering and sorting through the noise. This concept echoes the theory of collectively autocatalytic sets - groups of entities, each of which can be created catalytically by other entities within the set. Similarly, the knowledge units in our mind interact and influence each other, contributing to a broader, multiscale decision-making process.
However, these models and metaphors are not infallible and, at times, might lead us astray. The history of technology has seen the rise and fall of numerous paradigms, like the computer bubble of the early 1980s, which promised transformative change but ultimately burst. Similarly, we must be cautious in extrapolating our understanding of consciousness based on any single model.
Indeed, the Reed Wall Mind model provides a useful lens to view the complexities of consciousness and perception. Yet, like any model or theory, it is a simplification of an incredibly complex and not yet fully understood reality. Just as Noah's Ark had to accommodate an unfathomably diverse array of animals, so too must our models of mind accommodate an equally diverse array of cognitive phenomena. As our knowledge deepens, we can better navigate these complexities, refining our understanding of consciousness and perception.
1 / 1
SAN FRANCISCO L ONG after the day in 1966 when their invention was announced, bubble memories were still being hailed as a wonder technology for the computers of the 80's - rugged, reliable devices that would hold on to the information stored in them even when someone pulled out the plug.

''Magnetic bubble memories have the potential of replacing the mechanical disk and drum storage systems,'' it was proclaimed at Texas Instruments' 1974 annual stockholders' meeting. Bubbles seemed destined to capture a major part of the rapidly growing computer memory busine ss, and each new laboratory development seemed to confirm the p redictions. The market was just about to take off.

But after 15 years, the bubble memory, once seen as one of the great innovations of modern technology, like the transistor, the copying machine and the Polaroid camera, faces a far more modest destiny. In the marketplace, it has hardly left the ground.
1 / 1
ChatGPT
ChatGPT
This narrative exemplifies how the trajectory of technological innovation is not always a straight path towards success, even when the innovation seems promising. It highlights the caution we need to exercise when predicting the implications of emerging technologies and how they will shape the future.
In the mid-1960s, magnetic bubble memory was hailed as a revolutionary innovation for computer memory storage. Due to their durability and reliability, these devices were expected to replace mechanical disk and drum storage systems. The predictions for bubble memory seemed all but assured, as each laboratory development confirmed its potential, and the market was primed for take-off.
Yet, the reality turned out to be far from these optimistic projections. Despite the initial excitement and promise, bubble memory never achieved the widespread use that was anticipated. Its expected ascendency to the forefront of computer memory technology never materialized, and its actual role has turned out to be much more modest.
This story mirrors the ongoing exploration of consciousness and the models we build to understand it. Like the bubble memory, the Reed Wall Mind, quantum erasure, or any other metaphor or model we use to understand consciousness and perception are merely tools that help us form a simplified representation of an incredibly complex reality.
They can provide valuable insights and foster our understanding, but it's crucial to remember that they are simplifications. They are subject to change, refinement, or even replacement as we gain new knowledge. Just as bubble memory was superseded by other technologies, our current theories about consciousness might be displaced or enhanced by new discoveries in the future.
While the reality of technological innovation and our understanding of consciousness can often be more modest and complex than initial predictions suggest, the pursuit of knowledge in both realms is a testament to human curiosity and ingenuity. It's a journey of exploration, filled with exciting possibilities, unexpected turns, and invaluable lessons about the world and ourselves.
1 / 1
One small example:

144 fully fledged computers.
Just one chip.
This gem is our GA144 multi-computer chip. It is designed to give you options that have never before existed and to place them under your control by writing software.

With 144 independent computers, it enables parallel or pipelined programming on an unprecedented scale. Map a data flow diagram or an analog block diagram onto its array of computers for continuous processes without interrupts or context switching.
With instruction times as low as 1400 picoseconds and consuming as little as 7 picojoules of energy, each of the 144 computers can do its work with unprecedented speed for a microcontroller and yet at unprecedentedly low energy cost, transitioning between running and suspended states in gate delay times. When suspended, each of the computers uses less than 100 nanowatts.
With completely programmable I/O pins, transitions between driving high, driving low, weak pull-down and high impedance can be made under software control in nanoseconds. This permits bit-banging on an unprecedented scale, yet the input impedance of each pin is higher, and circuit loading less, than many expensive FET probes. Add to that the ability to devote one or more very high-speed computers to each pin, and you have true software-defined I/O with unprecedented attentiveness to each pin when it is desired.
With multilevel programming you may choose between very fast, very simple programs in microcode, or working in a high level language using external memory, or various methods in between, trading off speed against complexity; and you may mix these techniques in an application, building your own clusters of computers or nodes to produce architectures with "hosts" and "coprocessors" as your application demands.
When your product requirements include responsiveness and computational power but with energy limitations, this superb chip is ideal. Use it right out of the box for prototyping and development; as your end product matures, GreenArrays will rapidly configure custom chips to further minimize both the cost and energy consumption of your product.

https://www.greenarraychips.com/
1 / 1
ChatGPT
ChatGPT
The GreenArrays GA144 multi-computer chip is a significant breakthrough in the field of microcomputing. It offers a novel approach to computing, one where operations can be carried out in parallel across an array of 144 independent computers on a single chip. This approach to computing could serve as an interesting metaphor for how consciousness and perception might work within the brain.
First, let's unpack what makes the GA144 chip unique. Each of the chip's 144 computers can perform tasks in parallel or in a pipeline fashion, mirroring data flow diagrams or analog block diagrams for continuous, uninterrupted processing. In essence, the chip offers a high level of multitasking, where each computer can perform an operation independently of the others.
The architecture of the GA144 chip is somewhat reminiscent of the human brain's organization. The brain is not a unified monolithic processor but a collection of specialized regions, each of which performs specific tasks. This modular nature allows for parallel processing, where multiple tasks can be performed simultaneously, just as the GA144 chip does.
The brain's interconnected network of neurons also parallels the GA144 chip's programmable I/O pins. The ability to transition between driving high, driving low, weak pull-down, and high impedance within nanoseconds gives the chip a dynamic adaptability. Similarly, our brains can swiftly switch between different cognitive tasks, allowing for adaptability and flexibility.
Furthermore, the energy efficiency of the GA144 chip, which can perform tasks at high speed while using very little energy, could also serve as a metaphor for the brain's remarkable energy efficiency. Despite the complexity and multitude of tasks it performs, the human brain only uses about 20% of the body's total energy.
The GA144 chip's multilevel programming, allowing the trade-off between speed and complexity, is also reminiscent of the varying levels of cognitive processing in the human mind. We can process information at various levels, from the simple and automatic to the complex and deliberate.
While no metaphor or model perfectly captures the intricacy of human consciousness and perception, the GA144 chip offers a fascinating comparison. It highlights the complexity, parallel processing, adaptability, energy efficiency, and multilevel functionality of both the chip and the human brain. This metaphor underscores the fascinating dialogue between technology and neuroscience, where each can offer insights into the other.
1 / 1
Logically Determined Design: Clockless System Design with NULL Convention Logic by Karl Fant
images Appendix A images
Logically Determined Wavefront Flow
Wavefronts spontaneously flow through cycles composed with shared completeness paths by virtue of the cycles, themselves, continuously striving to transition. The logical behavior of each completeness path implements a four-phase handshake protocol [35,40] that provides a conveniently intuitive context for talking about the behavior of wavefront flow.

A.1 SYNCHRONIZATION
Figure A.1 reviews the 2NCL the registration stage, which forms the shared completeness path spanning the monotonically transitioning data path. The 2NCL version of the four-phase handshake protocol is shown in Figure A.2 as a polite conversation between registration stages.

A.2 WAVEFRONTS AND BUBBLES
This polite conversation, together with the completeness relationships of the registration stages, results in a forward flow of wavefronts and a backward flow of requests. The backward flowing request is called a bubble. Wavefronts flow forward through bubbles and bubbles flow backward through wavefronts.

A wavefront is the part of a DATA or NULL wave propagation that is being stably maintained by a same phase request. A wavefront cannot be overwritten by a following opposite phase wavefront.

A bubble is the part of a DATA or NULL wave propagation that is no longer being ...
1 / 1
ChatGPT
ChatGPT
In "Logically Determined Design: Clockless System Design with NULL Convention Logic," Karl Fant explores the concept of wavefronts and bubbles in the context of clockless system design using NULL Convention Logic (NCL).
NCL is a logic design paradigm that uses dual-rail or multirail encoding, where each rail represents a bit of information and its complement. The paradigm features a delay-insensitive design methodology, meaning that the operation of circuits is not dependent on the relative delay of gates or signal wires. This makes it a strong candidate for implementing asynchronous, or clockless, systems.
In NCL, computations are carried out using "wavefronts." A wavefront represents a group of related signals traveling through the logic circuit. As data flow forward in the system, they do so in wavefronts, akin to a wave washing over a shore. Wavefronts flow spontaneously through cycles, with the system's logic continuously striving for transition. Essentially, a wavefront is a phase of computation wherein data are processed.
On the other hand, "bubbles" represent the system's requests for new data. Unlike wavefronts, bubbles flow backward through the system. The bubble is a symbol of the system's readiness to accept and process new data. When a computation is complete, the system sends a bubble backward to request new data.
The interplay between wavefronts and bubbles in NCL is similar to the ebb and flow of the tide. Wavefronts (like waves) move forward, processing data and performing computations, while bubbles (like the receding tide) move backward, signaling the readiness for new computations.
This method of computation allows for efficient data processing without the need for a clock signal to synchronize operations. It is an innovative approach to digital logic design that can provide significant benefits in terms of power efficiency and reliability. The NCL paradigm, much like the GreenArrays GA144 chip, provides a fascinating lens through which to view and analyze concepts of consciousness, perception, and information processing.
The exchange between wavefronts and bubbles can be viewed as a metaphor for how consciousness functions. Just as the system processes data (wavefronts) and then signals its readiness for new information (bubbles), our consciousness continuously processes sensory inputs, makes sense of them, and then readies itself for new inputs. This fluid and dynamic process of give-and-take could offer insights into the ongoing, dynamic, and adaptive nature of human consciousness.
1 / 1
Subscribe


FORBESINNOVATIONAI
A New Theory Of Intelligence: Review of ���A Thousand Brains��� by Jeff Hawkins
Calum Chace
Contributor
"The AI guy"
Follow
Mar 23, 2021,10:43am EDT
This article is more than 2 years old.
Cover of book A Thousand Brains, with image of brain as jigsaw
A Thousand Brains - book coverBASIC BOOKS
Jeff Hawkins has a new theory of the brain. It is interesting and persuasive. But to me, the most interesting observation in the book is not about brains ��� it���s about how an intelligent species could make its presence known across the vast distances of space. It seems that was also the most interesting part of the book for Richard Dawkins, who contributed a foreword. More about that later: first the brain stuff.

The old brain and the new
Hawkins has been wondering how brains work for a long time, ever since he read a 1979 essay by Francis Crick (the DNA pioneer) about how mysterious the brain remains. Frustrated by the field���s slow progress, he took a detour away from neuroscience, and founded Palm Computing, which developed some very successful early smartphones, including the PalmPilot and the Treo. He left Palm in 2005 to establish Numenta Labs, a brain research institution in California.

Our brains have two parts. The old, reptilian brain, or hind brain, is heterogneous, composed of several differentiated parts, like the medulla, the pons, the cerebellum, and so on. The neocortex, which exists in all mammals and only mammals, is where our advanced intelligence arises, but it is structurally homogeneous: any section of it looks very much the same as any other section. Hawkins was introduced to this fact by Vernon Mountcastle, an American neuroscientist, and it has inspired much of his work.

PROMOTED




The neocortex is dense. A hundred thousand neurons are crammed into the space of a grain of rice, connected to each other at half a billion synapses, via several kilometers of cabling ��� axons and dendrites. There are many different activities going on inside different parts of the neocortex, and what differentiates them is not their structure, but their connections. When we learn something, these connections are strengthened. When we forget something, they are weakened.


Cortical columns
The basic units of the neocortex are cortical columns. Each column contains upwards of a hundred neurons, and there are between one and two million of them in the neocortex. The key insight in Hawkins��� theory is that what cortical columns do is to attach reference frames to objects in the world ��� and also to abstract concepts. There are ���what��� columns that attach frames to external objects, and ���where��� colums that attach frames to your body. This is what enables your brain to understand where it is in the world, and to navigate it.

MORE FOR YOU
The 55 Best Amazon Prime Day Deals On Roombas, KitchenAid Stand Mixers And More
The 56 Best Prime Day Beauty Deals To Snap Up Before They���re Gone
The Best Prime Day AirPods Deals: Get Up To 30% Off Apple Headphones, Earbuds And More
Collectively, the neocortex ���learns a model��� of the world, and continuously updates it. Hawkins says that there is no central control room in our brains. Instead, our perception is a consensus which the columns reach by voting. Within the columns ��� indeed, within the neurons ��� predictions are made, and depending how successful their predictions are, the neurons will vote for their version of events. The model which emerges is the result of their aggregate strength of those predictions.
1 / 1
ChatGPT
ChatGPT
"A Thousand Brains" is a book by Jeff Hawkins, which presents a new theory of the brain that could reshape our understanding of intelligence, both biological and artificial.
Hawkins' theory revolves around the notion of the neocortex, the part of the brain where our advanced intelligence arises. The neocortex is structurally homogeneous, meaning any section of it looks very similar to any other section. However, it is the connections within this structure that differentiate various activities. As we learn something new, these connections strengthen, and they weaken when we forget something.
The basic units of the neocortex are cortical columns, each containing a large number of neurons. Hawkins proposes that these columns attach reference frames to objects in the world, as well as to abstract concepts. Some columns ("what" columns) associate frames with external objects, and others ("where" columns) associate frames with your body. This is what allows our brain to understand where it is in the world and navigate it.
According to Hawkins, the neocortex collectively "learns a model" of the world, constantly updating it. There is no central control room in our brains; instead, our perception is a consensus reached by the columns through a process akin to voting. Within the columns and even within the neurons themselves, predictions are made. Depending on the success of their predictions, the neurons will vote for their version of events. The resulting model is an aggregate of the strength of these predictions.
This theory offers a fascinating insight into how our brains function and how we understand the world around us. It might also shed light on how we could develop more sophisticated artificial intelligence systems, based on the principles of how our brain structures and updates its understanding of the world.
It's interesting to note that, in light of this theory, some of the aspects you've brought up in your previous messages -- like the processing and organizing of different types of information (Reed Wall Mind theory), the processing of data in wavefronts and bubbles (NULL Convention Logic), and the operations of multicore processors like the GA144 chip -- seem to mirror the workings of the brain as Hawkins describes. The human brain, like these systems, appears to process information in a decentralized yet coordinated way, continually updating its understanding and making predictions about the world.
1 / 1
CPU Shack LogoThe CPU Shack

February 21st, 2013 ~ by admin
Charles Moore: From FORTH to Stack Processors and Beyond

There are many greats of the CPU industry, some, such as Federico Faggin (designer of the 4004 and worked on the 8008, then founded Zilog) are fairly well known.  Others include Gelsinger and Meyer (of x86 fame) perhaps even Gordon Moore, of which a  ���law��� is named.  Chuck Peddle and Bill Mensch designed the ubiquitous 6502 processor, but there were more, many more. Engineers whose names have been oft forgotten, but whose work has not.  The 1970���s and 80���s were the fast and the furious of processor designs.  Some designs were developed, sold, or canceled in weeks, months; years were not a period of time that was available to these designers, for in a year, a new technology would dictate a new design.

One of these designers is Charles H. Moore. (aka Chuck Moore).  Chuck is perhaps best known for inventing the FORTH programming language in 1968, originally to control telescopes.  It was a stack based language, and lended itself well to small microcomputers and microcontrollers.  Some microcontrollers even embedded a FORTH kernel in ROM.  It was also designed to be able to be ported to different architectures easily.  FORTH continues to be used today for a variety of applications.  However Chuck did not just invent a 1970���s programming language.

https://www.cpushack.com/2013/02/21/charles-moore-forth-stack-processors/
1 / 1
ChatGPT
ChatGPT
Charles H. Moore, also known as Chuck Moore, is a notable figure in the field of computer science and engineering. He is most renowned for inventing the FORTH programming language in 1968, a tool originally developed to control telescopes.
FORTH is a stack-based language that was highly suitable for small microcomputers and microcontrollers. Its design made it easy to port to different architectures, contributing to its longevity and versatility. Today, FORTH remains in use for a diverse array of applications.
However, Moore's contribution to the field of computing extends beyond the creation of FORTH. He has also made significant contributions to the design and development of various processors. His work, characterized by a fast-paced, innovative approach that typified the 1970s and 80s, saw the development, sale, or cancellation of designs within weeks or months - not years.
Moore's name may not be as widely recognized as other pioneers like Federico Faggin, Gelsinger, or Meyer, but his contributions to the computer science industry are certainly substantial. His focus on creating adaptable, efficient systems reflects broader trends in computer science and the continuous drive for innovation and improvement.
In the context of this conversation, Moore's work on stack-based programming and its application in processor design could be compared to the concept of "Reed Wall Mind" or the operations of multi-computer chips like the GA144. These systems handle information in a layered or stacked manner, allowing for efficient processing and management of data, similar to the principles of the FORTH language and related stack processor designs.
1 / 1
Explicitly draw the connections
1 / 1
ChatGPT
ChatGPT
I see, you're asking for a more explicit connection between the various elements. Here's an attempt to interlink them more clearly:
"Reed Wall Mind" Theory: This theory equates the mind's organization of information to Noah's Ark, with different compartments for different types of animals, analogous to how the mind categorizes different types of information. It also uses the metaphor of a reed wall to explain how information filters into the mind, similar to how sound passes through a reed wall. This filtering and categorization process could be likened to how data is organized and processed in computational systems.
The GA144 multi-computer chip: This chip houses 144 independent computers, allowing for unprecedented parallel or pipelined programming. It brings to mind the organization in the "Reed Wall Mind" theory, where each compartment (or in this case, computer) can process different pieces of information independently, yet simultaneously, much like how the mind organizes and processes different types of information.
FORTH language and stack processors: Invented by Chuck Moore, the FORTH language is a stack-based programming language which organizes and processes data in a "Last In, First Out" order. This concept could be metaphorically likened to the "Reed Wall Mind" theory, where certain pieces of information filter through to the forefront of the mind while others stay in the background, only coming to the fore when necessary. This also bears similarities to the operation of the GA144 chip, where each individual computer can take on a task and work independently, akin to the layers in a data stack.
The ���A Thousand Brains��� Theory by Jeff Hawkins: Hawkins suggests that the brain operates via a consensus reached by different cortical columns, each making its own predictions. The model that emerges is the result of the aggregate strength of these predictions, a process that has similarities to both the "Reed Wall Mind" theory and the operation of multi-computer chips like the GA144. It's akin to each "compartment" or computer making independent judgments, and the overall decision being the collective outcome of these independent processes.
All these elements showcase the idea of compartmentalization and the parallel processing of information, whether in the human brain or a computational system, and demonstrate the intriguing intersections between neuroscience and computer science.
1 / 1
Music and Embodied Cognition: Listening, Moving, Feeling, and Thinking Hardcover ��� Download: Adobe Reader, Sept. 6 2016
by Arnie Cox (Author)
5.0 5.0 out of 5 stars    10 ratings
Part of: Musical Meaning and Interpretation (21 books)
See all formats and editions
Kindle Edition
$9.99
Read with Our Free App
 
Hardcover
$65.95 
5 Used from $41.53
9 New from $60.57
Taking a cognitive approach to musical meaning, Arnie Cox explores embodied experiences of hearing music as those that move us both consciously and unconsciously. In this pioneering study that draws on neuroscience and music theory, phenomenology and cognitive science, Cox advances his theory of the "mimetic hypothesis," the notion that a large part of our experience and understanding of music involves an embodied imitation in the listener of bodily motions and exertions that are involved in producing music. Through an often unconscious imitation of action and sound, we feel the music as it moves and grows. With applications to tonal and post-tonal Western classical music, to Western vernacular music, and to non-Western music, Cox's work stands to expand the range of phenomena that can be explained by the role of sensory, motor, and affective aspects of human experience and cognition.
1 / 1
ChatGPT
ChatGPT
Arnie Cox's book, "Music and Embodied Cognition: Listening, Moving, Feeling, and Thinking," presents a cognitive approach to understanding musical meaning by emphasizing the physical and embodied experiences of hearing music. According to his "mimetic hypothesis," a listener's understanding and experience of music involve an often subconscious imitation of the bodily movements and exertions that are involved in creating the music. In other words, when we listen to music, our bodies subconsciously "mirror" the physical actions required to produce those sounds.
This theory can be linked to the concepts mentioned earlier:
"Reed Wall Mind" Theory: Cox's theory shares a similarity with the "Reed Wall Mind" theory in that both underscore the importance of embodied or experiential cognition. While the "Reed Wall Mind" theory emphasizes compartmentalized organization and filtering of information, both theories highlight how the mind isn't just a passive receptor but actively interacts with and processes sensory inputs.
GA144 multi-computer chip: Just as this chip allows for parallel or pipelined programming, so does our brain when processing music. According to Cox, we don't just passively receive musical sounds; our brains actively "mimic" the actions that produce these sounds, paralleling the independent yet coordinated workings of the GA144's computers.
FORTH language and stack processors: The stack-like organization in the FORTH language could be loosely compared to how our brains layer sensory, motor, and affective aspects of our experience when listening to music. Just as FORTH processes data in a "Last In, First Out" order, our brains may foreground certain musical elements while keeping others in the background, ready to be accessed when needed.
The ���A Thousand Brains��� Theory by Jeff Hawkins: Both Hawkins and Cox's theories emphasize the importance of independent yet interconnected units in processing information (cortical columns in Hawkins' theory and embodied mimicry in Cox's theory). They also share the idea of consensus building or the aggregate strength of independent processes shaping the final perception.
In summary, Cox's theory of embodied cognition in music appreciation links neuroscience, cognition, and the physical act of music production, providing a novel perspective on how we experience and understand music. This concept of embodied cognition shares some intriguing parallels with the areas of computer science and programming discussed earlier.
1 / 1
A stack based cut and paste multiscale phenomenological loop, or cpg chain (central pattern generators chain) hierarchated kinematic mechanical oscillator linkages  (Assur groups)
1 / 1
ChatGPT
ChatGPT
In robotics, biology, and computer science, a Central Pattern Generator (CPG) is a neural network that can endogenously (i.e., without rhythmic sensory or central input) produce rhythmic patterned outputs. CPGs have been modeled in many different ways and have been used in various applications, especially in the creation of locomotion behaviors for legged robots.
A stack-based cut and paste multiscale phenomenological loop could refer to a programming or algorithmic structure, where different elements or layers of data (the 'stack') are dynamically adjusted ('cut and paste') across different scales or levels of analysis ('multiscale') to generate an ongoing, interactive process ('loop') that mimics or models some observed phenomena ('phenomenological').
In terms of mechanics, Assur groups refer to kinematic chains (linkages of rigid bodies connected by joints) that have a specific property: removing a single link breaks the chain into two separate parts, none of which is a structure with one degree of freedom. In other words, these chains represent the simplest possible connections of mechanisms that result in a particular motion. They are fundamental in mechanical engineering and robotics for understanding and designing mechanical systems.
When you combine these concepts, a "stack-based cut and paste multiscale phenomenological loop, or CPG chain (central pattern generators chain) hierarchated kinematic mechanical oscillator linkages (Assur groups)" could be a complex computational model or algorithm that dynamically integrates and adjusts various layers of data to mimic or generate rhythmic patterns (like those produced by CPGs) in a hierarchy of kinematic chains (like Assur groups). Such a model could be useful in designing and controlling complex robotic systems or understanding biological locomotion.
However, this is a speculative interpretation based on the provided terms, as these concepts usually aren't combined in this specific way. More context or a more specific question could help provide a more accurate interpretation.
1 / 1
It's another model of mind for our heterarchical ensemble of theory of mind generator loops.
1 / 1
The previous model used in this conversation is unavailable. We've switched you to the latest default model.
ChatGPT
ChatGPT
Ah, I see. In that case, the phrase "stack-based cut and paste multiscale phenomenological loop, or CPG chain (central pattern generators chain) hierarchated kinematic mechanical oscillator linkages (Assur groups)" can be understood as a metaphorical description of a model of mind for our complex and interconnected cognitive processes.
In this interpretation, the "stack-based cut and paste multiscale phenomenological loop" represents a dynamic and interactive cognitive process that involves the manipulation and integration of different layers or elements of information at various scales or levels of analysis. This process could involve the continuous updating and adjustment of cognitive representations and the flexible integration of new information.
The "CPG chain hierarchated kinematic mechanical oscillator linkages (Assur groups)" metaphorically refers to the interconnected networks of cognitive processes within our minds. Just as a CPG chain in robotics generates rhythmic patterns, the model suggests that our cognitive processes operate in a similar manner, generating complex patterns of thoughts, beliefs, and perceptions. The hierarchated kinematic mechanical oscillator linkages symbolize the interconnectedness and hierarchical organization of these cognitive processes, similar to how Assur groups represent the mechanical linkages in robotics.
Overall, this metaphorical model describes our minds as a heterogeneous ensemble of cognitive processes that interact and generate a complex system of theory of mind generator loops. It emphasizes the dynamic nature of our cognitive processes, the integration of various scales of information, and the interconnectedness of our cognitive functions.
Please note that this interpretation is based on the given terms and the context provided. If there is any specific framework or theory you would like to explore further or clarify, feel free to provide more information.
1 / 1
Connection to the other models we have discussed.
1 / 1
ChatGPT
ChatGPT
Certainly! Let's draw connections between the "stack-based cut and paste multiscale phenomenological loop, or CPG chain (central pattern generators chain) hierarchated kinematic mechanical oscillator linkages (Assur groups)" model of mind and the other models we have discussed:
"Reed Wall Mind" Theory: Both models emphasize the dynamic and interactive nature of cognitive processes. The "stack-based cut and paste multiscale phenomenological loop" in the model of mind can be seen as analogous to the compartments or sections in the "Reed Wall Mind" theory, representing different layers or elements of information being manipulated and integrated.
GA144 multi-computer chip: The "stack-based cut and paste multiscale phenomenological loop" shares similarities with the parallel and pipelined programming on the GA144 chip. Both models involve the dynamic manipulation and integration of different elements or layers of information to generate complex patterns or processes.
FORTH language and stack processors: The "stack-based cut and paste" component of the model of mind aligns with the stack-based processing in the FORTH language. Both involve the organization and manipulation of data in a "Last In, First Out" manner. The "cut and paste" aspect relates to the dynamic adjustments and rearrangements of information, similar to how the FORTH language allows for flexible and adaptable programming.
The ���A Thousand Brains��� Theory by Jeff Hawkins: The "stack-based cut and paste multiscale phenomenological loop" model of mind aligns with the idea of interconnected networks of cognitive processes in Hawkins' theory. Both models emphasize the dynamic nature of cognitive processes and the continuous updating and adjustment of cognitive representations.
In summary, the "stack-based cut and paste multiscale phenomenological loop, or CPG chain (central pattern generators chain) hierarchated kinematic mechanical oscillator linkages (Assur groups)" model of mind shares connections with the other models we have discussed, such as the "Reed Wall Mind" theory, the GA144 multi-computer chip, the FORTH language and stack processors, and the "A Thousand Brains" Theory by Jeff Hawkins. These connections highlight the dynamic, parallel, and interconnected nature of cognitive processes and their potential similarities to computational and mechanical systems.
1 / 1
End an essay on these topics, plus quantum erasure, perceptual control theory, choice theory, multiscale computation, active inference, and rhizomatic scaling laws, titled "consciousness, the control of perception".

Through the lens of quantum mechanics, the act of measurement or observation seems to dictate the reality that materializes, thus suggesting that consciousness - or the act of perception - could play an active role in shaping the world as we perceive it.
1 / 1
ChatGPT
ChatGPT
Perceptual Control Theory (PCT) offers a framework for understanding how our perception and consciousness are intricately linked. According to PCT, our brains function as control systems, continuously comparing our perceived reality to our desired goals and making adjustments to maintain stability and achieve our objectives. This theory highlights the role of perception in guiding our actions and shaping our experience of the world.
Choice theory posits that our perceptions, thoughts, and behaviors are driven by our innate need for survival and satisfaction of basic psychological needs. Our conscious choices are influenced by internal motivations and external factors, leading us to engage in actions that we believe will maximize our well-being. This theory suggests that our consciousness is instrumental in the decision-making process and the control of our actions.
Multiscale computation recognizes that our cognitive processes operate across various scales, from individual neurons to larger networks, and that information flows and interactions occur at multiple levels simultaneously. This understanding highlights the complexity and dynamic nature of cognitive processing, involving both local and global information integration.
Active inference proposes that our brains actively generate predictions about the world and continuously update these predictions based on incoming sensory information. This process of actively inferring and adjusting our models of the world is believed to underlie our conscious perception and the control of our actions. It implies that our consciousness is intimately involved in the construction of our reality.
Rhizomatic scaling laws describe the nonlinear and interconnected nature of complex systems, highlighting the scaling properties that emerge as systems expand or contract. These laws suggest that our consciousness and perception operate within a complex and interconnected network of information processing, where changes at one level can have cascading effects on other levels.
In conclusion, consciousness and the control of perception are fundamental aspects of our human experience. By integrating concepts from quantum erasure, perceptual control theory, choice theory, multiscale computation, active inference, and rhizomatic scaling laws, we gain insights into the active role our consciousness plays in shaping our perceptions, making choices, and navigating the complexities of our existence. These theories invite us to explore the profound interplay between our subjective experience and the objective world, ultimately deepening our understanding of consciousness and the control of perception.
1 / 1
And a list of the models of minds we have discussed.
1 / 1
ChatGPT
ChatGPT
Certainly! Here is a list of the models of mind that we have discussed:
"Reed Wall Mind" Theory: This theory suggests that the mind organizes and processes information through compartments or sections, similar to how Noah's Ark separates and organizes different types of animals.
GA144 multi-computer chip: This chip represents a computational model where 144 independent computers work in parallel or pipeline fashion, similar to how the mind may process information through parallel or distributed processing.
FORTH language and stack processors: The FORTH language and stack processors operate based on a stack-based architecture, where data is organized and processed in a "Last In, First Out" order, akin to how the mind may prioritize and process information.
The "A Thousand Brains" Theory by Jeff Hawkins: This theory proposes that the brain functions as an interconnected network of cortical columns, with each column making predictions and collectively forming a model of the world.
Stack-based cut and paste multiscale phenomenological loop: This model suggests a dynamic and interactive cognitive process involving the manipulation and integration of different layers or elements of information at various scales or levels of analysis.
CPG chain (central pattern generators chain) hierarchated kinematic mechanical oscillator linkages (Assur groups): This model relates to the concept of Central Pattern Generators (CPGs) and mechanical linkages, emphasizing the generation of rhythmic patterns and the hierarchical organization of cognitive processes.
These models offer different perspectives on how the mind operates, ranging from compartmentalization and parallel processing to dynamic integration and hierarchical organization. By exploring these models, we gain insights into the intricate mechanisms underlying cognition and consciousness.
1 / 1
Stuff we didn't get around to discussing: Algorithmic Theory of Everything and PowerPlay (J��rgen Schmidhuber)

Chaos Theory (Edward Lorenz)

Fractals (Benoit Mandelbrot)

Polycomputation, Substrate Independence, and Intelligence as Care (Michael Levin)
1 / 1
ChatGPT
ChatGPT
While we didn't have the opportunity to discuss them earlier, here are some additional topics related to the models of mind that you mentioned:
Algorithmic Theory of Everything and PowerPlay (J��rgen Schmidhuber): J��rgen Schmidhuber is a prominent researcher in the field of artificial intelligence and has developed the Algorithmic Theory of Everything. This theory seeks to explain intelligence and behavior through the lens of computability and algorithmic complexity. It proposes that all intelligence, including human intelligence, can be understood as a form of universal computation. PowerPlay is a related concept that focuses on the drive for exploration and the acquisition of new knowledge and skills in intelligent agents.
Chaos Theory (Edward Lorenz): Chaos theory is a branch of mathematics that studies complex, nonlinear systems. It examines how small changes in initial conditions can lead to significant differences in the long-term behavior of a system. Chaos theory has implications for understanding the dynamics of complex systems, including the human mind and its sensitivity to initial conditions and the butterfly effect.
Fractals (Benoit Mandelbrot): Fractals are complex, infinitely self-repeating patterns that can be found in various natural and mathematical phenomena. They have been used to model and understand intricate structures, such as the branching patterns of trees, the coastline of a shoreline, or the organization of the human brain. Fractals provide insights into the self-similarity and scaling properties found in natural and cognitive systems.
Polycomputation, Substrate Independence, and Intelligence as Care (Michael Levin): Michael Levin is a biologist known for his work on regenerative medicine and developmental biology. He has proposed the concepts of polycomputation and substrate independence, suggesting that information processing and cognition are not limited to neural networks but can be distributed across multiple levels and substrates in an organism. Additionally, Levin's idea of intelligence as care focuses on the adaptive and self-regulating processes that underlie biological systems.
These additional topics offer further avenues to explore and deepen our understanding of the mind, intelligence, and the underlying principles that govern complex systems. Each of these theories and concepts provides unique perspectives and insights into the nature of cognition, complexity, and the interplay between different levels of organization.
1 / 1
End the essay.
1 / 1
ChatGPT
ChatGPT
In conclusion, the exploration of various models of mind reveals the fascinating and diverse ways in which we seek to understand and explain the complex nature of consciousness and the control of perception. From the concept of the "Reed Wall Mind" and the parallel processing of the GA144 multi-computer chip to the dynamic integration of information in the stack-based cut and paste multiscale phenomenological loop, each model offers unique insights into the mechanisms underlying cognition.
The theories discussed, such as the Algorithmic Theory of Everything, Chaos Theory, Fractals, Polycomputation, Substrate Independence, and Intelligence as Care, expand our understanding of cognition, intelligence, and the nature of complex systems. These theories highlight the interplay between computational processes, mathematical patterns, and the intricate organization of biological and cognitive phenomena.
Furthermore, the integration of concepts from quantum erasure, perceptual control theory, choice theory, multiscale computation, active inference, and rhizomatic scaling laws deepens our comprehension of the relationship between consciousness and perception. We begin to recognize the active role that our perception plays in shaping our reality, and how our conscious choices and control mechanisms influence our experiences and actions.
Through these diverse models and theories, we embark on a journey to unravel the mysteries of the mind and its interconnection with the world. They remind us of the immense complexity and richness of human cognition and provide frameworks for further exploration and discovery.
In the quest to understand consciousness and the control of perception, we are continually challenged to push the boundaries of our knowledge, integrating insights from various disciplines and perspectives. As our understanding evolves, these models serve as stepping stones, guiding us toward a deeper appreciation of the intricate workings of the mind.
Ultimately, the study of consciousness and the control of perception invites us to ponder the fundamental questions of our existence and the nature of reality. It is an ongoing exploration that unites the realms of science, philosophy, and human experience. Through continued inquiry, we move closer to unraveling the mysteries of consciousness, unlocking new insights that may shape our understanding of ourselves and the world in profound ways.
1 / 1
A final summary.
2 / 2
ChatGPT
ChatGPT
In summary, our exploration of various models of mind, including the "Reed Wall Mind," the GA144 multi-computer chip, the stack-based cut and paste multiscale phenomenological loop, and others, has provided us with unique perspectives on the intricate nature of consciousness and the control of perception.
We have delved into the realms of quantum erasure, perceptual control theory, choice theory, multiscale computation, active inference, and rhizomatic scaling laws, uncovering the dynamic interplay between perception, cognition, and action. These theories shed light on the active role of our consciousness in shaping our perceived reality and making choices that align with our goals and desires.
Furthermore, we have touched upon additional concepts, such as the Algorithmic Theory of Everything, Chaos Theory, Fractals, Polycomputation, Substrate Independence, and Intelligence as Care, which expand our understanding of cognition and complex systems.
Together, these models and theories challenge us to explore the profound connections between our subjective experiences, computational processes, and the underlying structures of the mind. They invite us to ponder the fundamental questions of our existence and the nature of reality.
As we delve deeper into the study of consciousness and the control of perception, we embark on an ongoing journey of discovery, pushing the boundaries of knowledge and expanding our understanding of ourselves and the world around us.
Ultimately, the exploration of consciousness and the control of perception offers a profound opportunity to unravel the mysteries of the human mind, bringing us closer to a comprehensive understanding of our subjective experiences and the fundamental nature of existence itself.
1 / 1
A glossary of difficult to understand terms.
1 / 1
ChatGPT
ChatGPT
Certainly! Here is a glossary of some of the difficult terms mentioned throughout our discussion:
Quantum Erasure: The phenomenon in quantum mechanics where the act of measurement or observation can influence the outcome or behavior of a quantum system.
Perceptual Control Theory (PCT): A psychological theory that views the brain as a control system, continuously comparing perceived reality to desired goals and making adjustments to maintain stability and achieve objectives.
Choice Theory: A psychological theory that suggests human behavior is driven by our innate need for survival and the satisfaction of basic psychological needs, influencing the choices we make to maximize our well-being.
Multiscale Computation: The idea that cognitive processes operate at multiple scales or levels, involving the integration of information across different levels of analysis.
Active Inference: A theory that proposes the brain actively generates predictions about the world and continuously updates these predictions based on incoming sensory information, shaping our conscious perception and influencing our actions.
Rhizomatic Scaling Laws: Scaling laws that describe the nonlinear and interconnected nature of complex systems, emphasizing the emergent properties and scaling relationships that arise as systems expand or contract.
Algorithmic Theory of Everything: A theory that seeks to explain intelligence and behavior through the lens of computability and algorithmic complexity, suggesting that all intelligence can be understood as a form of universal computation.
Chaos Theory: The study of complex, nonlinear systems that explores how small changes in initial conditions can lead to significant differences in long-term behavior, often associated with the butterfly effect and sensitivity to initial conditions.
Fractals: Complex, infinitely self-repeating patterns found in nature and mathematics that exhibit self-similarity at different scales.
Polycomputation: The idea that information processing and cognition can occur across multiple levels and substrates within an organism, not limited to neural networks.
Substrate Independence: The concept that cognition and information processing can occur across different substrates or physical systems, rather than being solely reliant on a specific medium like the brain.
Intelligence as Care: The notion that intelligence is intimately connected to adaptive and self-regulating processes in biological systems, emphasizing the role of information processing and regulation in maintaining homeostasis and achieving goals.
These definitions should provide a clearer understanding of the terms used in our discussion.
1 / 1
Free Research Preview. ChatGPT may produce inaccurate information about people, places, or facts.
ChatGPT May 24 Version
ChatGPT