I agree that the mind is independent of the brain, but that does not make it an emergent process. Rather to claim emergent processes is a questionable explanation for various phenomena and often a circular argument. One example is the "saltines" of NaCl, common salt. This "saltiness" supposedly is an emergent phenomena, but it is only detectable by mind, another supposedly emergent phenomena. Thus, we end up with, one "emergent phenomena" proves another "emergent phenomena" and vice versa.

Now in contrast there is ample evidence that mind is independent of brain and in a clearly non-materialistic category, but that is a much more complex discussion. In my personal library there are several rather large books devoted to that subject.

William Mayor ,

I appreciate your engagement, but I must point out that your response shifts the discussion away from the scientific framework in which my post was written. The distinction I drew between the human mind and AI was situated in terms of emergence, neural processes, and computational architectures.

Your critique relies on metaphysical categories and examples (“saltiness,” “mind as non-material”), which, while interesting in their own context, are not relevant to the scientific point I was making. The sensation of salt, for instance, is a biological process mediated by receptors and neural transmission—not an argument against emergence.

So while I respect your theological perspective, it does not actually address the argument presented. The issue at hand was not whether mind is “non-material” in a metaphysical sense, but whether biological emergence and artificial instantiation can be equated. They cannot, and that was the core message of my post.

Instead of diverting the discussion into semantic skepticism, it would be more productive to explore whether biological emergence and artificial instantiation can coexist within a comparative framework, rather than dismissing emergence altogether.

Soumendra

I think you miss the point. From a purely scientific viewpoint what is the difference between the neural transmission caused by the sensation of salt and the neural transmission caused by the scent of a rose? The point of origin of the neural transmission might be different but how does that determine what the ultimate sensation is? It is known that any neurological map of the brain is not truly accurate. The best any given map is both very generalized and not universally applicable, and that is without taking into consideration neuroplasticity. Or do you consider the electrical transmission from one generator to be distinct than the electrical transmission from a different generator.

AI is purely binary. Human mind is anything but binary. Binary cannot choose "better or worse", but a human mind can. Science cannot at present, nor for the foreseeable future, comprehend mind. With our current level of knowledge, metaphysics is the only language we can use to describe mind.

I would refer you to Fagin's "Irreducible" if you are not aware of it. As he is a highly regarded physicist, and behind the invention of a couple of computer chips, I think he qualifies as a scientist and knowledgeable about AI.

William Mayor

Your comment is irrelevant to the discussion. The focus here is on the distinction between biological emergence and artificial instantiation, not on the mechanics of sensation. Sensation belongs to the human brain, but the discussion concerns intelligence in relation to consciousness, which is a very different matter. Please stay with the central point instead of diverting into impugned arguments.

— Soumendra

As long as you insist on biological emergence you are not conducting a scientific discussion. Sensation is linked to consciousness. You are attempting to draw distinctions that do not actually exist. AI is not consciousness, nor even a close approximation. It is an algorithm established by conscious human programmers. It is much faster than the human mind, it does not have the unconscious biases of the human mind, but it is no conscious and it is limited by the conscious decisions of its programmers. It is a binary process and consciousness is nonbinary.

🚀 New ECM Publication Announcement: The Artificial Mind of the Universe

I am pleased to share the publication of my latest work:

Appendix 45: The Artificial Mind of the Universe — An Extended Classical Mechanics Perspective

August 2025

DOI: https://doi.org/10.13140/RG.2.2.14014.14407

🔹 Abstract-style overview:

This appendix explores the concept of the artificial mind of the universe within the framework of Extended Classical Mechanics (ECM). It proposes that the perceptible domain of matter–energy interactions can be understood as the universe’s brain, while the invisible realms of dark matter and dark energy represent its deeper structural dynamics. Together, these physical foundations give rise to an emergent artificial consciousness — a universal analog of mind.

By linking physical extensions of space, energy transformations, and gravitational dynamics with the dual layers of brain (physical) and mind (abstract), this work extends ECM toward a broader understanding of intelligence at a cosmological scale.

🔹 Significance:

• Integrates AI analogies into cosmological physics.
• Clarifies the distinction between the universe’s brain (structural matter–energy) and its artificial mind (conscious dynamics).
• Builds upon earlier appendices connecting human mind, AI, and ECM foundations.

Best Regards

Soumendra Nath Thakur

William Mayor,

Your statement that “biological emergence is not scientific” shows a fundamental misunderstanding—biological science is a branch of physical science, and emergence is a well-established concept within it. Sensation belongs to the brain (a physical process), while consciousness belongs to the mind (an abstract domain). To deny this distinction is to conflate reality with abstraction.

Your further claim that “AI is not consciousness” overlooks the difference between traditional programmed algorithms and generative AI, which can operate beyond explicit human instructions through adaptive pattern recognition and interaction. To reduce AI to “binary programming” misses its nuanced capacities, which are designed to interact intelligently with human beings in ways that go far beyond ordinary software.

The issue is not about “god-like humans” or theology, but about distinguishing biological emergence from artificial instantiation. If this distinction is dismissed, the conversation is no longer scientific.

Recommendation

"Mathematical abstraction is not merely a technical exercise but a disciplined act of separating essence from appearance. It identifies the essential characteristics of concepts, stripping away their contingent ties to the material world in order to reveal their deeper order. In doing so, it allows thought to move beyond particular instances toward universal patterns and structures. This process has enabled mathematics to formulate principles of remarkable generality—principles that often find application not only in known domains of the physical world but also in realms of reality not yet perceived or understood."

— Soumendra

Are you familiar with the work of Fredrico Fagin? He is behind the computer chips that allow for AI.

He recognizes that AI is purely binary, very advanced binary but still binary. Biological emergence is a well-establish CONCEPT I agree. Concepts may be correct or incorrect. Sensation is applied to this not based on actual science, but on a "black box" principle. Science knows what goes into the "black box", electrical impulses from the nervous system, and what comes out, sensations, but has no idea how whatever is within this black box transforms the input into the output.

As for AI, it is an extremely fast algorithm. It works by analyzing every possible choice, eliminating those that violate its programming and then determining which of the remaining most closely fits its programmed guidelines. If you program it, as my little brother was involved in at one time, to determine how to drive from point A to point B it can do so very rapidly by examining all possible routes, eliminating those that are not roads open to vehicular traffic or go through some structure such as a parking garage or prohibited area, and eventually settle on the shortest route. Once this is done though, adding in detours causes the system trouble. It is estimated that blocking just 10% of the roads will so slow down the AI that normal human drivers could beat it every time.

At present, science has no clear idea just what consciousness/intelligence/mind is. It declares things to be true about these terms, but that is a declaration, not a proven determination. We have learned how to create something that outwardly mimics intelligence, but this mimicry was developed by true intelligence. Computers, ever since they were first created, can only deal with binary, "A" or "not A", "on" or "off". If we can ever truly develop a quantum computer we MIGHT be able to get past this limitation, but at present we are still limited by it.

First of all; technical definitions can be misleading for those who are not deeply familiar with the subject.

To better understand the topic, let's look at the foundation of artificial intelligence.

A nerve cell consists of a nucleus, a cell body, and two extensions. The short extensions are called "dendrites," and their task is to receive input information. The nucleus integrates this information and, if it reaches a certain threshold, fires to produce an output. The long extension is called an "axon," and it carries the output to other nerve cells. The connection points between axons and dendrites are called "synapses." It is known that there are approximately $10^{14}$ synapses in the human brain [1].

The "artificial neuron," which forms the basis of artificial intelligence, is the result of an effort to mathematically mimic this natural structure and can be formulated as follows:

\begin{align*}

X & \in \mathbb{R}^{n} \quad \text{input vector}, \\

W & \in \mathbb{R}^{n} \quad \text{weight vector}, \\

b & \in \mathbb{R} \quad \text{bias (threshold) scalar}, \\

\Phi & : \mathbb{R} \to \mathbb{R} \quad \text{activation function}, \\

\Phi(x) & = \begin{cases}

\tanh( x ) \in ( -1, +1 ) & \text{hyperbolic tangent}, \\

\sigma( x ) = \dfrac{1}{1 + e^{-x}} \in [ 0, 1 ] & \text{sigmoid (logistic)}, \\

\operatorname{sign}( x ) = \begin{cases}

-1 & \text{if}~x < 0 \\

0 & \text{if}~x = 0 \\

+1 & \text{if}~x > 0

\end{cases} & \text{sign function}, \\

\max( 0, x ) \in [ 0, \infty ) & \text{ReLU (Rectified Linear Unit)}, \\

\vdots & \vdots

\end{cases} \\

f & : \mathbb{R}^{n} \to \mathbb{R} \quad \text{perceptron output}, \\

f(X) & = \Phi\left( \sum_{i=1}^{n} w_i x_i + b \right) \\

\end{align*}

Here, $X$ represents the inputs, $W$ the weights, $\beta$ the bias, and $\Phi$ the activation function. This structure is based on the "perceptron" model developed by McCulloch-Pitts and Rosenblatt [2].

As can be understood from this, artificial intelligence is not the biological cells themselves but a mathematical imitation.

Is artificial intelligence binary? Partly yes. Information is sometimes reduced to the interval $[0, 1]$, but this only applies to cases that can be clearly separated.

Does it try all possible paths? No. It is an algorithmic approach. Artificial intelligence predicts the optimal state; it does not test every possibility.

Is it a black box? Yes. Because it is not possible to track how information is distributed from inputs to outputs. In this respect, it resembles the human brain.

In conclusion: Artificial intelligence is a product of mathematical models inspired by the biological nervous system and is design-dependent. The human mind, on the other hand, relies not on design but on self-regulating complex biological processes.

Therefore, in artificial intelligence, "emergence" can be observed to a limited extent, but it does not give rise to a similar high-level phenomenon like consciousness [3]. Thus, the difference between the functioning of artificial intelligence and human consciousness is not only quantitative but also qualitative in nature.

[1]: Article Total regional and global number of synapses in the human br...

[2]: http://www.deeplearningbook.org

[3]: Article Minds, Brains, and Programs